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Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort | Drug delivery schedules are key factors in the efficacy of cancer therapies, and mathematical modeling of population dynamics and treatment responses can be applied to identify better drug administration regimes as well as provide mechanistic insights. To capitalize on the promise of this approach, the cancer field must meet the challenges of moving this type of work into clinics. |
Diode-clamped multilevel converters: a practicable way to balance DC-link voltages | The converter topologies identified as diode-clamped multilevel (DCM) or, equivalently, as multipoint clamped (MPC), are rarely used in industrial applications, owing to some serious drawbacks involving mainly the stacked bank of capacitors that constitutes their multilevel dc link. The balance of the capacitor voltages is not possible in all operating conditions when the MPC converter possesses a passive front end. On the other hand, in ac/dc/ac power conversion, the back-to-back connection of a multilevel rectifier with a multilevel inverter allows the balance of the dc-link capacitor voltages and, at the same time, it offers the power-factor-correction capability at the mains ac input. An effective balancing strategy suitable for MPC conversion systems with any number of dc-link capacitors is presented here. The strategy has been carefully studied to optimize the converter efficiency. The simulation results related to a high-power conversion system (up to 10 MW) characterized by four intermediate dc-link capacitors are shown. |
The pet connection: pets as a conduit for social capital? | There is growing interest across a range of disciplines in the relationship between pets and health, with a range of therapeutic, physiological, psychological and psychosocial benefits now documented. While much of the literature has focused on the individual benefits of pet ownership, this study considered the potential health benefits that might accrue to the broader community, as encapsulated in the construct of social capital. A random survey of 339 adult residents from Perth, Western Australia were selected from three suburbs and interviewed by telephone. Pet ownership was found to be positively associated with some forms of social contact and interaction, and with perceptions of neighbourhood friendliness. After adjustment for demographic variables, pet owners scored higher on social capital and civic engagement scales. The results suggest that pet ownership provides potential opportunities for interactions between neighbours and that further research in this area is warranted. Social capital is another potential mechanism by which pets exert an influence on human health. |
Fully integrated wideband high-current rectifiers for inductively powered devices | This paper describes the design and implementation of fully integrated rectifiers in BiCMOS and standard CMOS technologies for rectifying an externally generated RF carrier signal in inductively powered wireless devices, such as biomedical implants, radio-frequency identification (RFID) tags, and smartcards to generate an on-chip dc supply. Various full-wave rectifier topologies and low-power circuit design techniques are employed to decrease substrate leakage current and parasitic components, reduce the possibility of latch-up, and improve power transmission efficiency and high-frequency performance of the rectifier block. These circuits are used in wireless neural stimulating microsystems, fabricated in two processes: the University of Michigan's 3-/spl mu/m 1M/2P N-epi BiCMOS, and the AMI 1.5-/spl mu/m 2M/2P N-well standard CMOS. The rectifier areas are 0.12-0.48 mm/sup 2/ in the above processes and they are capable of delivering >25mW from a receiver coil to the implant circuitry. The performance of these integrated rectifiers has been tested and compared, using carrier signals in 0.1-10-MHz range. |
Exploiting deep neural networks for detection-based speech recognition | In recent years deep neural networks (DNNs) – multilayer perceptrons (MLPs) with many hidden layers – have been successfully applied to several speech tasks, i.e., phoneme recognition, out of vocabulary word detection, confidence measure, etc. In this paper, we show that DNNs can be used to boost the classification accuracy of basic speech units, such as phonetic attributes (phonological features) and phonemes. This boosting leads to higher flexibility and has the potential to integrate both top-down and bottom-up knowledge into the Automatic Speech Attribute Transcription (ASAT) framework. ASAT is a new family of lattice-based speech recognition systems grounded on accurate detection of speech attributes. In this paper we compare DNNs and shallow MLPs within the ASAT framework to classify phonetic attributes and phonemes. Several DNN architectures ranging from five to seven hidden layers and up to 2048 hidden units per hidden layer will be presented and evaluated. Experimental evidence on the speaker-independent Wall Street Journal corpus clearly demonstrates that DNNs can achieve significant improvements over the shallow MLPs with a single hidden layer, producing greater than 90% frame-level attribute estimation accuracies for all 21 phonetic features tested. Similar improvement is also observed on the phoneme classification task with excellent frame-level accuracy of 86.6% by using DNNs. This improved phoneme prediction accuracy, when integrated into a standard large vocabulary continuous speech recognition (LVCSR) system through a word lattice rescoring framework, results in improved word recognition accuracy, which is better than previously reported word lattice rescoring |
Use of two-stage anaerobic treatment for distillery waste | |
An Open Virtual Environment for Autonomous Agents Using VRML and Java | We describe a VRML/Java-based virtual environment that is populated with heterogeneous articulated agents. In this simulated environment, agents compete for collecting certain objects while avoiding obstacles and other agents. Environment simulation, agent control, and visualization are distributed using a client/server approach. An important feature of the framework is its openness for novel kinds of agents: user defined agents can be integrated into the environment by supplying VRML models of the agents’ visual appearance and agent control clients that follow a predefined communication protocol. The environment serves as testbed for exploring principles for the design of autonomous, yet instructable agents. Instructability is necessary because agents represent human users. Autonomy is required so as to relieve the human from too much technical detail when directing the agent to approach and to pick up target objects with their manipulators. Autonomy is also necessary to enable the agents to explore the virtual environment in the absence of continuous instructions by the user. CR |
Learning to Grade Short Answer Questions using Semantic Similarity Measures and Dependency Graph Alignments | In this work we address the task of computerassisted assessment of short student answers. We combine several graph alignment features with lexical semantic similarity measures using machine learning techniques and show that the student answers can be more accurately graded than if the semantic measures were used in isolation. We also present a first attempt to align the dependency graphs of the student and the instructor answers in order to make use of a structural component in the automatic grading of student answers. |
Validation of the Kirundi versions of brief self-rating scales for common mental disorders among children in Burundi | BACKGROUND
In Sub Saharan Africa, there has been limited research on instruments to identify specific mental disorders in children in conflict-affected settings. This study evaluates the psychometric properties of three self-report scales for child mental disorder in order to inform an emerging child mental health programme in post-conflict Burundi.
METHODS
Trained lay interviewers administered local language versions of three self-report scales, the Depression Self-Rating Scale (DSRS), the Child PSTD Symptom Scale (CPSS) and the Screen for Child Anxiety Related Emotional Disorders (SCARED-41), to a sample of 65 primary school children in Burundi. The test scores were compared with an external 'gold standard' criterion: the outcomes of a comprehensive semistructured clinical psychiatric interview for children according the DSM-IV criteria (the Schedule for Affective Disorders and Schizophrenia for School-Age Children - K-SADS-PL).
RESULTS
The DSRS has an area under the curve (AUC) of 0.85 with a confidence interval (c.i.) of 0.73-0.97. With a cut-off point of 19, the sensitivity was 0.64, and the specificity was 0.88. For the CPSS, with a cut-off point of 26, the AUC was 0.78 (c.i.: 0.62-0.95) with a sensitivity of 0.71 and a specificity of 0.83. The AUC for the SCARED-41, with a cut-off point of 44, was 0.69 (c.i.: 0.54-0.84) with a sensitivity of 0.55 and a specificity of 0.90.
CONCLUSIONS
The DSRS and CPSS showed good utility in detecting depressive disorder and posttraumatic stress disorder in Burundian children, but cut-off points had to be put considerably higher than in western norm populations. The psychometric properties of the SCARED-41 to identify anxiety disorders were less strong. The DSRS and CPSS have acceptable properties, and they could be used in clinical practice as part of a two-stage screening procedure in public mental health programmes in Burundi and in similar cultural and linguistic settings in the African Great Lakes region. |
Conditional image generation using feature-matching GAN | Generative Adversarial Net is a frontier method of generative models for images, audios and videos. In this paper, we focus on conditional image generation and introduce conditional Feature-Matching Generative Adversarial Net to generate images from category labels. By visualizing state-of-art discriminative conditional generative models, we find these networks do not gain clear semantic concepts. Thus we design the loss function in the light of metric learning to measure semantic distance. The proposed model is evaluated on several well-known datasets. It is shown to be of higher perceptual quality and better diversity then existing generative models. |
A deep learning approach to detection of splicing and copy-move forgeries in images | In this paper, we present a new image forgery detection method based on deep learning technique, which utilizes a convolutional neural network (CNN) to automatically learn hierarchical representations from the input RGB color images. The proposed CNN is specifically designed for image splicing and copy-move detection applications. Rather than a random strategy, the weights at the first layer of our network are initialized with the basic high-pass filter set used in calculation of residual maps in spatial rich model (SRM), which serves as a regularizer to efficiently suppress the effect of image contents and capture the subtle artifacts introduced by the tampering operations. The pre-trained CNN is used as patch descriptor to extract dense features from the test images, and a feature fusion technique is then explored to obtain the final discriminative features for SVM classification. The experimental results on several public datasets show that the proposed CNN based model outperforms some state-of-the-art methods. |
Effect of treatment duration on plasma levels of clozapine andN-desmethylclozapine in men and women | Plasma levels of clozapine and its major metabolites,N-desmethylclozapine and clozapine-N-oxide, were measured in 18 schizophrenic patients at different times (4, 6 and 24 weeks) during the course of treatment with multiple doses of the drug, by using high performance liquid chromatography (HPLC) with UV detection. Plasma levels of clozapine andN-desmethylclozapine were significantly higher in females than in males after 4 and 6 weeks, but not after 24 weeks, of treatment. No sex difference was found at any time with respect to plasma levels of clozapine-N-oxide. |
Management challenges to implementing agile processes in traditional development organizations | Discussions with traditional developers and managers concerning agile software development practices nearly always contain two somewhat contradictory ideas. They find that on small, stand-alone projects, agile practices are less burdensome and more in tune with the software industry's increasing needs for rapid development and coping with continuous change. Managers face several barriers, real and perceived, when they try to bring agile approaches into traditional organizations. They categorized the barriers either as problems only in terms of scope or scale, or as significant general issues needing resolution. From these two categories, we've identified three areas - development process conflicts, business process conflicts, and people conflicts - that we believe are the critical challenges to software managers of large organizations in bringing agile approaches to bear in their projects. |
Towards Computer Assisted International Sign Language Recognition System: A Systematic Survey | There is a number of automated sign language recognition systems proposed in the computer vision literature. The biggest drawback of all these systems is that every nation has their own culture oriented sign language. In other words, everyone needs to develop a specific sign language recognition system for their nation. Although the main building blocks of all signs are gestures and facial expressions in all sign languages, the nation specific requirements make it difficult to design a multinational recognition framework. In this paper, we focus on the advancements in computer assisted sign language recognition systems. More specifically, we discuss if the ongoing research may trigger the start of an international sign language design. We categorize and present a summary of the current sign language recognition systems. In addition, we present a list of publicly available databases that can be used for designing sign language recognition systems. |
Assessing semantic annotation activities with formal concept analysis | This paper describes an approach to assessing semantic annotation activities based on formal concept analysis (FCA). In this approach, annotators use taxonomical ontologies created by domain experts to annotate digital resources. Then, using FCA, domain experts are provided with concept lattices that graphically display how their ontologies were used during the semantic annotation process. In consequence, they can advise annotators on how to better use the ontologies, as well as how to refine these ontologies to better suit the needs of the semantic annotators. To illustrate the approach, we describe its implementation in @note, a Rich Internet Application (RIA) for the collaborative annotation of digitized literary texts, we exemplify its use with a case study, and we provide some evaluation results using the method. The enormous efforts to digitize physical resources (documents, books, museum exhibits, etc.), along with recent advances in information and communication technologies, have democratized access to a cultural, scientific and academic heritage previously available to only a few. Likewise, the current trend is to produce new resources in a digital format (e.g., in the context of social networks), which entails an in-depth paradigm shift in almost all the humanistic, social, scientific and technological fields. In particular, the field of the humanities is one which is going through a significant transformation as a result of these digitalization efforts and the paradigm shift associated with the digital age. Indeed, we are witnessing the emergence of a whole host of disciplines, those of Digital Humanities (Berry, 2012), which are closely dependent on the production and proper organization of digital collections. As a result of the undoubted importance of digital collections in modern society, the search for effective and efficient methods to carry out the production, preservation and enhancement of such digital collections has become a key challenge in modern society (Calhoun, 2013). In particular, the annotation of resources with metadata that enables their proper cataloging, search, retrieval and use in different application scenarios is one of the key elements to ensuring the profitability of these collections of digital objects. While the cataloging and retrieval of resources (whether digital or non-digital) have been the object of study in library sciences for decades (Calhoun, 2013), modern applications require annotating resources in semantically richer and more flexible ways, in many cases allowing multiple alternative annotations in the same collection. In consequence, the tendency is to introduce the use of ontology-based semantic technologies, in … |
On the feasibility of hybrid Battery/Ultracapacitor Energy Storage Systems for next generation shipboard power systems | This paper explores a Battery/Ultracapacitor Energy Storage System (BUCESS) for navy application. A new configuration of the battery and ultracapacitor combined system is introduced for propulsion system and pulse power loads. A dual active bridge (DAB) topology is selected to control the bidirectional power flow through phase shifting for charging and discharging batteries and ultracapacitors. High-frequency switching devices are selected to achieve dc-dc conversion at high voltage and high power levels. A 500V–1kV BUCESS is designed and analyzed to investigate 100kW transmission for batteries and 1MW for ultracapacitors both in charging and discharging modes. |
Is diabetes treated as an acute or chronic illness in community family practice? | OBJECTIVE
Poor quality of diabetes care has been ascribed to the acute care focus of primary care practice. A better understanding of how time is spent during outpatient visits for diabetes compared with visits for acute conditions and other chronic diseases may facilitate the design of programs to enhance diabetes care.
RESEARCH DESIGN AND METHODS
Research nurses directly observed consecutive outpatient visits during two separate days in 138 community family physician offices. Time use was categorized into 20 different behaviors using the Davis Observation Code (DOC). Time use was compared for visits for diabetes, other chronic conditions, and acute illnesses during 1,867 visits by patients > or =40 years of age.
RESULTS
Of 20 DOC behavioral categories, 10 exhibited differences among the three groups. Discriminant analysis identified two distinct factors that distinguished visits for chronic disease from visits for acute illness and visits for diabetes from those for other chronic diseases. Compared with visits for other chronic diseases, visits for diabetes devoted a greater proportion of time to nutrition counseling, health education, and feedback on results and less time to chatting. Compared with visits for acute illness, visits for diabetes were longer and involved a higher proportion of dietary advice, negotiation, and assessment of compliance.
CONCLUSIONS
Visits for diabetes are distinct from visits for other chronic diseases and acute illnesses in ways that may facilitate patient self-management. Novel quality-improvement interventions could support and expand existing differences between family physicians' current approaches to care of diabetes and other chronic and acute illnesses. |
The Cosmic-Ray Contribution to Galactic Abundances of the Light Elements : Interpretation of GCR LiBeB Abundance Measurements from ACE / CRIS | Inelastic collisions between the galactic cosmic rays (GCRs) and the interstellar medium (ISM) are responsible for producing essentially all of the light elements Li, Be, and B (LiBeB) observed in the cosmic rays. Previous calculations (e.g., [1]) have shown that GCR fragmentation can explain the bulk of the existing LiBeB abundance in the present day Galaxy. However, elemental abundances of LiBeB in old halo stars indicate inconsistencies with this explanation. We have used a simple leaky-box model to predict the cosmic-ray elemental and isotopic abundances of LiBeB in the present epoch. We conducted a survey of recent scientific literature on fragmentation cross sections and have calculated the amount of uncertainty they introduce into our model. The predicted particle intensities of this model were compared with high energy (EisM=200-500 MeV/nucleon) cosmic-ray data from the Cosmic Ray Isotope Spectrometer (CRIS), which indicates fairly good agreement with absolute fluxes for Z?:. 5 and relative isotopic abundances for all LiBeB species. |
Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index | This paper proposes genetic algorithms (GAs) approach to feature discretization and the determination of connection weights for artificial neural networks (ANNs) to predict the stock price index. Previous research proposed many hybrid models of ANN and GA for the method of training the network, feature subset selection, and topology optimization. In most of these studies, however, GA is only used to improve the learning algorithm itself. In this study, GA is employed not only to improve the learning algorithm, but also to reduce the complexity in feature space. GA optimizes simultaneously the connection weights between layers and the thresholds for feature discretization. The genetically evolved weights mitigate the well-known limitations of the gradient descent algorithm. In addition, globally searched feature discretization reduces the dimensionality of the feature space and eliminates irrelevant factors. Experimental results show that GA approach to the feature discretization model outperforms the other two conventional models. q 2000 Published by Elsevier Science Ltd. |
The Mesozoic Rimrock Lake inlier, southern Washington Cascades: Implications for the basement to the Columbia Embayment | The Mesozoic Rimrock Lake inlier lies between the North Cascades, Blue, and Klamath Mountains, and thus has significant implications for the basement to the Columbia Embayment. The inlier consists of the Late Jurassic Indian Creek complex and the voluminous Late Jurassic-Early Cretaceous Russell Ranch complex. The Indian Creek complex consists of trondhjemitic to gabbroic rocks, some of which underwent dynamo-thermal medium-grade metamorphism that was probably broadly synchronous with plutonism. Lithologies and geochemical data indicate that the complex represents the roots of an arc. The Russell Ranch complex is a tectonic melange, consisting mainly of arkose and mudstone, with subordinate chert, conglomerate, and pillowed greenstone, and minor green tuff. Deposition may have occurred on an inner fan or the inner part of a mid-fan. Sandstones were derived from a plutonic terrane, presumably a dissected are. The geochemistry of greenstones apparently is most compatible with eruption as within-plate tholeiites or MORB. The complex displays a block-in-matrix mesoscopic fabric; greenstone and the foliated Twin Sisters Lakes silicic metavolcanic unit occur as kilometer-scale blocks. Predominantly steep faults riddle the complex. Overlapping time relations between normal and thrust faults, several generations of folds, and cleavages record protracted deformation. Steep faults separate the units and are bracketed between Early Cretaceous and earliest Eocene, as is deformation of the Russell Ranch complex. These are mostly brittle structures, but one mylonite zone has a gentle stretching lineation suggestive of strike slip. Large displacements probably occurred between the Indian Creek and Russell Ranch complexes, but an original basement and cover relationship cannot be precluded. The complexes are broadly correlative with rocks to the north. The Late Jurassic are, represented by the Indian Creek complex, may include rocks in other inliers in central Washington, the melange belts of north-western Washington, and the San Juan Islands. The Russell Ranch complex most closely resembles parts of the western melange belt and the Constitution Formation. Late Jurassic arc-type rocks also occur in the Klamath and Blue Mountains, and the Russell Ranch complex may correlate with the Yolla Bolly terrane of the Franciscan Complex. These correlations suggest that lithological belts are more continuous between Washington and California than implied by models which propose major tectonic dispersal. The Mesozoic arc-type crust and continentally derived clastic rocks in the inlier demonstrate that the basement to the Columbia Embayment includes a variety of tectonic slices or terranes and that the embayment is not simply underlain by Tertiary or Mesozoic oceanic crust as is commonly proposed. |
Deep-plane face-lift vs superficial musculoaponeurotic system plication face-lift: a comparative study. | OBJECTIVE
To evaluate deep-plane face-lift vs superficial musculoaponeurotic system (SMAS) plication face-lift in correcting the melolabial fold, jowl, and cheek areas of the face in short-term follow-up.
DESIGN
Masked, randomized review by 4 board-certified facial plastic surgeons experienced in rhytidectomy of full-face (frontal, oblique, and lateral views) before-and-after photographs of 20 patients who underwent deep-plane face-lift and 20 who underwent SMAS plication face-lift. Participants rated the melolabial fold, jowl, and cheek areas for overall correction of the deformities pertaining to the aesthetic results for deep-plane vs SMAS plication face-lift. Categories were excellent, good, average, acceptable, and poor.
RESULTS
Three categories of results were determined: best, average, and poorest. Overall, SMAS plication face-lifts scored higher than deep-plane face-lifts. In the best category, there were more SMAS plication face-lifts. In the average category, there were more deep-plane face-lifts. In the poorest category, there were equal numbers of deep-plane and SMAS face-lifts. Patients were divided into the following age groups: 50 to 59, 60 to 69, and 70 to 80 years. In the 2 younger groups, SMAS face-lifts scored higher than deep-plane face-lifts. In the oldest group, deep-plane face-lifts scored slightly higher than SMAS face-lifts.
CONCLUSION
Deep-plane face-lift does not seem to offer superior results over SMAS plication face-lift in patients younger than 70 years. |
The Origins of Democracy: A Model with Application to Ancient Greece | A method is disclosed for preparing a coated rotor housing useful in a rotary internal combustion engine. A first mandrel is defined from conductive material such as a chrome-bearing steel. The outer surface of the first mandrel is shaped to be the mirror image of the resultant internal surface of the rotor housing; the first mandrel material is passivated preferably by the use of boiling water to form a chrome oxide material on the outer surface to prevent adhesion of surrounding coated materials. A thin, composite-particle wear-resistant coating is electrolytically deposited on to the first mandrel to form an assembly. The wear-resistant coating is preferably comprised of nickel carrying embedded silicon carbide particles. The first mandrel is stripped from the deposited thin coating leaving a self-supporting liner or sleeve, the liner may be used in its unitary form or may be sliced into smaller liner bands for separate processing. The liner is placed about a brother mandrel (identical in shape to the first mandrel, but previously preheated by use in the die-cast machine) and together they are inserted into a die-cast machine. Molten aluminum is supplied to the machine for casting about said liner to define a complete housing construction, the liner offering high wear-resistance. |
Wordbank: an open repository for developmental vocabulary data. | The MacArthur-Bates Communicative Development Inventories (CDIs) are a widely used family of parent-report instruments for easy and inexpensive data-gathering about early language acquisition. CDI data have been used to explore a variety of theoretically important topics, but, with few exceptions, researchers have had to rely on data collected in their own lab. In this paper, we remedy this issue by presenting Wordbank, a structured database of CDI data combined with a browsable web interface. Wordbank archives CDI data across languages and labs, providing a resource for researchers interested in early language, as well as a platform for novel analyses. The site allows interactive exploration of patterns of vocabulary growth at the level of both individual children and particular words. We also introduce wordbankr, a software package for connecting to the database directly. Together, these tools extend the abilities of students and researchers to explore quantitative trends in vocabulary development. |
A Sentence Interaction Network for Modeling Dependence between Sentences | Modeling interactions between two sentences is crucial for a number of natural language processing tasks including Answer Selection, Dialogue Act Analysis, etc. While deep learning methods like Recurrent Neural Network or Convolutional Neural Network have been proved to be powerful for sentence modeling, prior studies paid less attention on interactions between sentences. In this work, we propose a Sentence Interaction Network (SIN) for modeling the complex interactions between two sentences. By introducing “interaction states” for word and phrase pairs, SIN is powerful and flexible in capturing sentence interactions for different tasks. We obtain significant improvements on Answer Selection and Dialogue Act Analysis without any feature engineering. |
A randomized, open-label trial of iron isomaltoside 1000 (Monofer®) compared with iron sucrose (Venofer®) as maintenance therapy in haemodialysis patients | BACKGROUND
Iron deficiency anaemia is common in patients with chronic kidney disease, and intravenous iron is the preferred treatment for those on haemodialysis. The aim of this trial was to compare the efficacy and safety of iron isomaltoside 1000 (Monofer®) with iron sucrose (Venofer®) in haemodialysis patients.
METHODS
This was an open-label, randomized, multicentre, non-inferiority trial conducted in 351 haemodialysis subjects randomized 2:1 to either iron isomaltoside 1000 (Group A) or iron sucrose (Group B). Subjects in Group A were equally divided into A1 (500 mg single bolus injection) and A2 (500 mg split dose). Group B were also treated with 500 mg split dose. The primary end point was the proportion of subjects with haemoglobin (Hb) in the target range 9.5-12.5 g/dL at 6 weeks. Secondary outcome measures included haematology parameters and safety parameters.
RESULTS
A total of 351 subjects were enrolled. Both treatments showed similar efficacy with >82% of subjects with Hb in the target range (non-inferiority, P = 0.01). Similar results were found when comparing subgroups A1 and A2 with Group B. No statistical significant change in Hb concentration was found between any of the groups. There was a significant increase in ferritin from baseline to Weeks 1, 2 and 4 in Group A compared with Group B (Weeks 1 and 2: P < 0.001; Week 4: P = 0.002). There was a significant higher increase in reticulocyte count in Group A compared with Group B at Week 1 (P < 0.001). The frequency, type and severity of adverse events were similar.
CONCLUSIONS
Iron isomaltoside 1000 and iron sucrose have comparative efficacy in maintaining Hb concentrations in haemodialysis subjects and both preparations were well tolerated with a similar short-term safety profile. |
Reuleaux: Robot Base Placement by Reachability Analysis | Before beginning any robot task, users must position the robot's base, a task that now depends entirely on user intuition. While slight perturbation is tolerable for robots with moveable bases, correcting the problem is imperative for fixed- base robots if some essential task sections are out of reach. For mobile manipulation robots, it is necessary to decide on a specific base position before beginning manipulation tasks. This paper presents Reuleaux, an open source library for robot reachability analyses and base placement. It reduces the amount of extra repositioning and removes the manual work of identifying potential base locations. Based on the reachability map, base placement locations of a whole robot or only the arm can be efficiently determined. This can be applied to both statically mounted robots, where the position of the robot and workpiece ensure the maximum amount of work performed, and to mobile robots, where the maximum amount of workable area can be reached. The methods were tested on different robots of different specifications and evaluated for tasks in simulation and real world environment. Evaluation results indicate that Reuleaux had significantly improved performance than prior existing methods in terms of time-efficiency and range of applicability. |
Socially-Relevant Capstone Design Projects in Power Engineering | Senior design projects can be a way to bring the university closer to societal needs. This paper describes how the senior capstone design courses in power engineering developed at the University of Puerto Rico-Mayagiiez (UPRM) strive to provide a service to society. These projects deal with societal needs, and are part of design courses that culminate the major design experience as specified by ABET. Teams of students identify a society-based problem, propose a design solution, perform measurements/simulations and present the final analysis and design to an industry or community partner. An important aspect of the projects is the inclusion of both technical and social constraints such as safety and environmental issues. These design experiences are an ideal way to understanding the new challenges in power systems planning, policy, analysis and design |
On finding multi-constrained paths | New emerging distributed multimedia applications provide guaranteed end-to-end quality of service (QoS) and have stringent constraints on delay, delay-jitter, cost, etc. The task of QoS routing is to find a route in the network which has sufficient resources to satisfy the constraints. The delaycost-constrained routing problem is NP-complete. We propose a heuristic algorithm for this problem. The idea is to first reduce the NP-complete problem to a simpler one which can be solved in polynomial time, and then solve the new problem by either an extended Dijkstra’s algorithm or an extended Bellman-Ford algorithm. We prove the correctness of our algorithm by showing that a solution for the simpler problem must also be a solution for the original problem. The performance of the algorithm is studied by both theoretical analysis and simulation. |
Automated and Portable Native Code Isolation | The coexistence of programs written in a safe language with user-supplied unsafe (native) code is convenient (it enables direct access to hardware and operating system resources and can improve application performance), but at the same time it is problematic (it leads to undesirable interference with the language runtime, decreases overall reliability, and lowers debuggability). This work aims at retaining most of the benefits of interfacing a safe language with native code while addressing its problems. It is carried out in the context of the JavaTM Native Interface (JNI). Our approach is to execute the native code in an operating system process different from that of the safe language application. A technique presented in this paper accomplishes this transparently, automatically, and without sacrificing any of the JNI functionality. No changes to the Java virtual machine (JVMTM) or its runtime are necessary. The resulting prototype does not depend on a particular implementation of the JVM, and is highly portable across hardware architectures and operating systems. This approach can readily be used to improve reliability of applications consisting of a mix of safe and native code; to enable the execution of user-supplied native code in multitasking systems based on safe languages and in embedded virtual machines; and to facilitate mixed-mode debugging, without the need to re-implement any of the components of the language runtime. The design and implementation of a prototype system, performance implications, and the potential of this architecture are discussed in the paper. |
Bloch, Marc Léopold Benjamin (1886–1944) | The French historian Marc Bloch (1886–1944) is one of the authors most frequently cited by those working in contemporary historical disciplines around the world. This immense influence is founded on both scholarly and biographical grounds. As one of the founders, together with Lucien Febvre, of the journal ‘ Annales d'histoire economique et sociale ’ in 1929, and as a pioneer in the field of the history of society and mentality, a historical theoretician, and a critical intellectual who was executed by the Gestapo in 1944, Bloch has become an inspiration and model for generations of researchers working in a diverse range of scientific fields and from a variety of different political perspectives. |
Adult N orills for the Box and Block Test of Manual Dexterity ( hand evaluation , hand , motor skills , occupational therapy , tests ) | The Box and Block Test, a test of manual dexterity, has been used by occupational therapists and others to evaluate physically handicapped individuals. Because the test lacked normative data for adults, the results of the test have been interpreted subjectively. The purpose of this study was to develop normative data for adults. Test subjects were 628 Normal adults (310 males and 318 females)from the seven-county Milwaukee area. Data on males and females 20 to 94 years old were divided into 12 age groups. Means, standard deviations, standard error, and low and high scores are reported for each five-year age group. These data will enable clinicians to objectively compare a patient's score to a normal population parameter. Occupational therapists are frequently involved with increasing the manual dexterity of their patients. Often, these patients are unable to perform tests offine manual or finger dexterity, such as the Purdue Pegboard Test or the Crawford Small Parts Dexterity Test. Tests of manual dexterity, such as the Minnesota Rate of Manipulation Test, have limited clinical application because a) they require lengthy administration time, b) a standardized standing position must be used for testing, and c) the tests use normative samples that poorly represent the wide range of clinical patients. Because of the limitations of such standardized tests, therapists often evaluate dexterity subjectively. The Box and Block Test has been suggested as a measure of gross manual dexterity (1) and as a prevocational test for handicapped people (2). Norms have been collected on adults with neuromuscular involvement (2) and on normal children (7, 8, and 9 years old) (3). Standardized instructions along with reliability and validity data, are reported in the literature (2,3), but there are no norms for the normal adult population. Therefore, the purpose of this study was to collect normative data for adults. Methods |
The rediscovery of the Villa Gamberaia in images and projects of the early 1900s | Abstract The garden of Villa Gamberaia occupies a prominent place in the early twentieth-century historiography of Italian gardens, such that it even challenges the primacy of what Sir George Sitwell called the sacred triad of Villa d'Este, Villa Lante and the Giardino Giusti at Verona.1 As Charles Latham wrote: From the moment that you pass the gate, with its sentinel cypresses, the impression is one of such perfect loveliness that at last, by force of contrast, the mind goes back to strong Caprarola or tragic Este, only to turn once more to bathe in the perfection of the Tuscan villa.2 In this paper, I shall try to capture the secrets of this fatal attraction by drawing upon the reflections of some of the most important writers and scholars in the field in the first part of the century. |
OF HOTEL TAJ IN THE CONTEXT OF CRM AND CUSTOMER RETENTION | To enhance profitability and guest satisfaction and loyalty, the organizations (hotels) should focus on implementing Customer Relationship Management (CRM) strategies that aim to seek, gather and store the right information, validate and share it throughout the organization . Hotel industry is a highly flourishing, lucrative and competitive market. To compete in such a market, the hotels should focus on maintaining good relations with the customers and satisfying the customers. Increasingly, the organizations are using Customer Relationship Management (CRM) to help boost sales and revenues by focusing on customer retention and customer loyalty. The present research was undertaken to study the Customer Relationship Management (CRM) practices in hotel industry. The purpose of this study was to determine the impact of Customer Relationship Management (CRM) on customer loyalty in the hotel industry. The study was conducted at the Hotel Taj Hotel, New Delhi. The objectives of the study were to determine if (CRM) has an impact on customer retention, to determine if the practice of effective CRM in organizations leads to a long or short term financial impact, to find out the extent or degree to which effective CRM leads to customer satisfaction and to assess if the services provided by the hotel meets the needs and wants of customers. It was found that most of the employees had a positive attitude towards CRM practices and the most common activities undertaken were studying the existing database of the customers and personal counseling. The benefits of CRM are increased customer satisfaction and increased customer retention. |
MECHANICAL DESIGN OF A LEGGED-WHEEL HYBRID QUADRUPED ROBOT FOR MULTI-TERRAIN NAVIGATION | The two most common modes of locomotion used by humans are legged mode and wheeled mode, the former an inherent gift while the latter being an ingenious invention on their part. While both have their advantages, they may fall short in some aspects for instance, legs may fail in terms of high speeds and wheels might prove not so handy in the more demanding and uneven terrains Thus, a leg-wheel hybrid platform promises to ensure both high speeds and good stability on a variety of terrains . |
Effects of age of second-language learning on the production of English consonants | This study examined the production of English consonants by native speakers of Italian. The 240 adult native Italian speakers of English who participated had begun learning English when they emigrated to Canada between the ages of 2 and 23 years. Wordinitial, word-medial and word-final tokens of English stops and fricatives were assessed through forced-choice judgments made by native English-speaking listeners, and acoustically. The native Italian subjects' ages of learning (AOL) English exerted a systematic effect on their production of English consonants even though they had lived in Canada for an average of 32 years, and reported speaking English more than Italian. In all but two instances, one or more native Italian subgroup defined on the basis of AOL differed significantly from subjects in a native English (NE) control group. The AOL of the first native Italian subgroup to differ from the NE subjects varied across consonant and syllable position. The results are discussed in terms of hypotheses proposed in the a b Purchase Export literature concerning the basis of segmental errors in L2 speech production. |
Student under stress | Stress is a natural phenomenon, sooner or later experienced by the most Rapid increase in the number of students with health problems, seeking health and advisory services, causes deep concern to parents, schools and wider community. This, in turn, arouses the interest in the research of the negative effects of poor physical and mental health on academic success. Considering the fact that school age population was rarely the subject of research, this paper deals with psycho-social and developmental aspects of stress, namely, with causes, consequences and the strategies for overcoming stressful events in the education of children and adolescents. Life events in which children most often participate and which are also potential sources of stress (stressors) can be classified into familial, interpersonal, personal and academic. Out of numerous identified sources of stress, we have focused our attention on several less researched ones in the field of school life starting school, transition from primary school to secondary and from secondary school to university, peer rejection and problems concerning financing school education. Anxiety, depression and anger were analyzed as the most frequent consequences of unfavorable life events. The following strategies for overcoming stress are most often used by children and adolescents: seeking social support, problem-solving orientation, reduction and avoidance of tension as well as sport and recreation. |
Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction | Two new, cost-effective thresholding algorithms for use in extracting binary images of characters from machineor hand-printed documents are described. The creation of a binary representation from an analog image requires such algorithms to determine whether a point is converted into a binary one because it falls within a character stroke or a binary zero because it does not. This thresholding is a critical step in Optical Character Recognition (OCR). I t is also essential for other Character Image Extraction (CIEJ applications, such as the processing of machine-printed or handwritten characters from carbon copy forms or bank checks, where smudges and scenic backgrounds, for example, may have to be suppressed. The first algorithm, a nonlinear, adaptive procedure, is implemented with a minimum of hardware and is intended for many CIE applications. The second is a more aggressive approach directed toward specialized, high-volume applications which justify extra complexity. |
Feature Importance Measure for Non-linear Learning Algorithms | Complex problems may require sophisticated, non-linear learning methods such as kernel machines or deep neural networks to achieve state of the art prediction accuracies. However, high prediction accuracies are not the only objective to consider when solving problems using machine learning. Instead, particular scientific applications require some explanation of the learned prediction function. Unfortunately, most methods do not come with out of the box straight forward interpretation. Even linear prediction functions s(x) = ∑ j βjxj are not straight forward to explain if features β exhibit complex correlation structure. |
Privacy-preserving data publishing for cluster analysis | Releasing person-specific data could potentially reveal sensitive information about individuals. k-anonymization is a promising privacy protection mechanism in data publishing. Although substantial research has been conducted on k-anonymization and its extensions in recent years, only a few prior works have considered releasing data for some specific purpose of data analysis. This paper presents a practical data publishing framework for generating a masked version of data that preserves both individual privacy and information usefulness for cluster analysis. Experiments on real-life data suggest that by focusing on preserving cluster structure in the masking process, the cluster quality is significantly better than the cluster quality of the masked data without such focus. The major challenge of masking data for cluster analysis is the lack of class labels that could be used to guide the masking process. Our approach converts the problem into the counterpart problem for classification analysis, wherein class labels encode the cluster structure in the data, and presents a framework to evaluate the cluster quality on the masked data. 2008 Elsevier B.V. All rights reserved. |
Dual-Band Microstrip Bandpass Filter Using Stepped-Impedance Resonators With New Coupling Schemes | A microstrip bandpass filter using stepped-impedance resonators is designed in low-temperature co-fired ceramic technology for dual-band applications at 2.4 and 5.2 GHz. New coupling schemes are proposed to replace the normal counterparts. It is found that the new coupling scheme for the interstages can enhance the layout compactness of the bandpass filter; while the new coupling scheme at the input and output can improve the performance of the bandpass filter. To validate the design and analysis, a prototype of the bandpass filter was fabricated and measured. It is shown that the measured and simulated performances are in good agreement. The prototype of the bandpass filter achieved insertion loss of 1.25 and 1.87 dB, S11 of -29 and -40 dB, and bandwidth of 21% and 12.7% at 2.4 and 5.2 GHz, respectively. The bandpass filter is further studied for a single-package solution of dual-band radio transceivers. The bandpass filter is, therefore, integrated into a ceramic ball grid array package. The integration is analyzed with an emphasis on the connection of the bandpass filter to the antenna and to the transceiver die |
A 56.4-to-63.4 GHz Multi-Rate All-Digital Fractional-N PLL for FMCW Radar Applications in 65 nm CMOS | A mm-wave digital transmitter based on a 60 GHz all-digital phase-locked loop (ADPLL) with wideband frequency modulation (FM) for FMCW radar applications is proposed. The fractional-N ADPLL employs a high-resolution 60 GHz digitally-controlled oscillator (DCO) and is capable of multi-rate two-point FM. It achieves a measured rms jitter of 590.2 fs, while the loop settles within 3 μs. The measured reference spur is only -74 dBc, the fractional spurs are below -62 dBc, with no other significant spurs. A closed-loop DCO gain linearization scheme realizes a GHz-level triangular chirp across multiple DCO tuning banks with a measured frequency error (i.e., nonlinearity) in the FMCW ramp of only 117 kHz rms for a 62 GHz carrier with 1.22 GHz bandwidth. The synthesizer is transformer-coupled to a 3-stage neutralized power amplifier (PA) that delivers +5 dBm to a 50 Ω load. Implemented in 65 nm CMOS, the transmitter prototype (including PA) consumes 89 mW from a 1.2 V supply. |
Incorporating Discrete Translation Lexicons into Neural Machine Translation | Neural machine translation (NMT) often makes mistakes in translating low-frequency content words that are essential to understanding the meaning of the sentence. We propose a method to alleviate this problem by augmenting NMT systems with discrete translation lexicons that efficiently encode translations of these low-frequency words. We describe a method to calculate the lexicon probability of the next word in the translation candidate by using the attention vector of the NMT model to select which source word lexical probabilities the model should focus on. We test two methods to combine this probability with the standard NMT probability: (1) using it as a bias, and (2) linear interpolation. Experiments on two corpora show an improvement of 2.0-2.3 BLEU and 0.13-0.44 NIST score, and faster convergence time. 1 |
Passive Investment Strategies and Efficient Markets | This paper presents the case for and the evidence in favour of passive investment strategies and examines the major criticisms of the technique. I conclude that the evidence strongly supports passive investment management in all markets—smallcapitalisation stocks as well as large-capitalisation equities, US markets as well as international markets, and bonds as well as stocks. Recent attacks on the efficient market hypothesis do not weaken the case for indexing. |
A Traceability Attack against e-Passports | Since 2004, many nations have started issuing “e-passports” containing an RFID tag that, when powered, broadcast information. It is claimed that these passports are more secure and that our data will be protected from any possible unauthorised attempts to read it. In this paper we show that there is a flaw in one of the passport’s protocols that makes it possible to trace the movements of a particular passport, without having to break the passport’s cryptographic key. All an attacker has to do is to record one session between the passport and a legitimate reader, then by replaying a particular message, the attacker can distinguish that passport from any other. We have implemented our attack and tested it successfully against passports issued by a range of nations. |
Probabilistic Neural Programs | We present probabilistic neural programs, a framework for program induction that permits flexible specification of both a computational model and inference algorithm while simultaneously enabling the use of deep neural networks. Probabilistic neural programs combine a computation graph for specifying a neural network with an operator for weighted nondeterministic choice. Thus, a program describes both a collection of decisions as well as the neural network architecture used to make each one. We evaluate our approach on a challenging diagram question answering task where probabilistic neural programs correctly execute nearly twice as many programs as a baseline model. |
Pouch of Douglas pelvic hernia: a rare entity managed laparoscopically | Pouch of Douglas hernias are uncommon forms of pelvic hernia. They are most commonly seen in multiparous, elderly women and those having undergone previous pelvic surgery (Stamatiou et al. in Am Surg 76(5):474–479, 2010). Herein, we present a case of a 77-year-old female presenting with groin pain due to a Pouch of Douglas hernia. She had no previous abdominal or pelvic surgery. This was repaired via a trans-abdominal pre-peritoneal approach and the patient’s symptoms resolved. To our knowledge, this is the first case report in the literature of an idiopathic Pouch of Douglas hernia managed laparoscopically. |
Sequential characterization of atrial tachyarrhythmias based on ECG time-frequency analysis | A new method for characterization of atrial arrhythmias is presented which is based on the time-frequency distribution of an atrial electrocardiographic signal. A set of parameters are derived which describe fundamental frequency, amplitude, shape, and signal-to-noise ratio. The method uses frequency-shifting of an adaptively updated spectral profile, representing the shape of the atrial waveforms, in order to match each new spectrum of the distribution. The method tracks how well the spectral profile fits each spectrum as well as if a valid atrial signal is present. The results are based on the analysis of a learning database with signals from 40 subjects, of which 24 have atrial arrhythmias, and an evaluation database with 211 patients diagnosed with atrial fibrillation. It is shown that the method robustly estimates fibrillation frequency and amplitude and produces spectral profiles with narrower peaks and more discernible harmonics when compared to the conventional power spectrum. The results suggest that a rather strong correlation exist between atrial fibrillation frequency and f wave shape. The developed set of parameters may be used as a basis for automated classification of different atrial rhythms. |
Zara The Supergirl: An Empathetic Personality Recognition System | Zara the Supergirl is an interactive system that, while having a conversation with a user, uses its built in sentiment analysis, emotion recognition, facial and speech recognition modules, to exhibit the human-like response of sharing emotions. In addition, at the end of a 5-10 minute conversation with the user, it can give a comprehensive personality analysis based on the user’s interaction with Zara. This is a first prototype that has incorporated a full empathy module, the recognition and response of human emotions, into a spoken language interactive system that enhances human-robot understanding. Zara was shown at the World Economic Forum in Dalian in September 2015. |
Predicting driver drowsiness using vehicle measures: recent insights and future challenges. | INTRODUCTION
Driver drowsiness is a significant contributing factor to road crashes. One approach to tackling this issue is to develop technological countermeasures for detecting driver drowsiness, so that a driver can be warned before a crash occurs.
METHOD
The goal of this review is to assess, given the current state of knowledge, whether vehicle measures can be used to reliably predict drowsiness in real time.
RESULTS
Several behavioral experiments have shown that drowsiness can have a serious impact on driving performance in controlled, experimental settings. However, most of those studies have investigated simple functions of performance (such as standard deviation of lane position) and results are often reported as averages across drivers, and across time.
CONCLUSIONS
Further research is necessary to examine more complex functions, as well as individual differences between drivers.
IMPACT ON INDUSTRY
A successful countermeasure for predicting driver drowsiness will probably require the setting of multiple criteria, and the use of multiple measures. |
Agile Project Management: A Case Study of a Virtual Research Environment Development Project | In this paper we use a case study of a project to create a Web 2.0-based, Virtual Research Environment (VRE) for researchers to share digital resources in order to reflect on the principles and practices for embedding eResearch applications within user communities. In particular, we focus on the software development methodologies and project management techniques adopted by the project team in order to ensure that the project remained responsive to changing user requirements without compromising their capacity to keep the project ‘on track’, i.e. meeting the goals declared in the project proposal within budget and on time. Drawing on ethnographic fieldwork, we describe how the project team, whose members are distributed across multiple sites (and often mobile), exploit a repertoire of coordination mechanisms, communication modes and tools, artefacts and structuring devices as they seek to establish the orderly running of the project while following an agile, user-centred development approach. |
A Survey of Memristive Threshold Logic Circuits | In this paper, we review different memristive threshold logic (MTL) circuits that are inspired from the synaptic action of the flow of neurotransmitters in the biological brain. The brainlike generalization ability and the area minimization of these threshold logic circuits aim toward crossing Moore’s law boundaries at device, circuits, and systems levels. Fast switching memory, signal processing, control systems, programmable logic, image processing, reconfigurable computing, and pattern recognition are identified as some of the potential applications of MTL systems. The physical realization of nanoscale devices with memristive behavior from materials, such as TiO2, ferroelectrics, silicon, and polymers, has accelerated research effort in these application areas, inspiring the scientific community to pursue the design of high-speed, low-cost, low-power, and high-density neuromorphic architectures. |
Online anomaly detection with concept drift adaptation using recurrent neural networks | Anomaly detection in time series is an important task with several practical applications. The common approach of training one model in an offline manner using historical data is likely to fail under dynamically changing and non-stationary environments where the definition of normal behavior changes over time making the model irrelevant and ineffective. In this paper, we describe a temporal model based on Recurrent Neural Networks (RNNs) for time series anomaly detection to address challenges posed by sudden or regular changes in normal behavior. The model is trained incrementally as new data becomes available, and is capable of adapting to the changes in the data distribution. RNN is used to make multi-step predictions of the time series, and the prediction errors are used to update the RNN model as well as detect anomalies and change points. Large prediction error is used to indicate anomalous behavior or a change (drift) in normal behavior. Further, the prediction errors are also used to update the RNN model in such a way that short term anomalies or outliers do not lead to a drastic change in the model parameters whereas high prediction errors over a period of time lead to significant updates in the model parameters such that the model rapidly adapts to the new norm. We demonstrate the efficacy of the proposed approach on a diverse set of synthetic, publicly available and proprietary real-world datasets. |
Understanding packet delivery performance in dense wireless sensor networks | Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal characteristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks.In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments: an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks. |
A fractional order fuzzy PID controller for binary distillation column control | Expert and intelligent control schemes have recently emerged out as a promising solution with robustness which can efficiently deal with the nonlinearities, along with various types of modelling uncertainties, present in different real world systems e.g. binary distillation column. This paper is an attempt to propose an intelligent control system which takes the form of a Fractional Order Fuzzy Proportional – Integral – Derivative (FOFPID) controller which is investigated as a solution to deal with the complex dynamic nature of the distillation column. The FOFPID controller is an extension of an existing formula based self tuning fuzzy Proportional Integral controller structure, which varies its gains at run time in accordance with the instantaneous error and rate of change of error. The FOFPID controller is a Takagi-Sugeno (TS) model based fuzzy adaptive controller comprising of non-integer order of integration and differentiation operators used in the controller. It has been observed that inclusion of non-integer order of the integration and differentiation operators made the controller scheme more robust. For the performance evaluation of the proposed scheme, the performance of FOFPID controller is compared with that of its integer order counterpart, a Fuzzy Proportional – Integral – Derivative (FPID) controller. The parameters of both the controllers were optimized for minimum integral of absolute error (IAE) using a bio-inspired global optimization algorithm, Genetic Algorithm (GA). Intensive LabVIEW TM simulation studies were performed which included setpoint tracking with and without uncertainties, disturbance rejection, and noise suppression investigations. For testing the parameter uncertainty handling capability of the proposed controller, uncertain and time varying relative volatility and uncertain tray hydraulic constant were applied. Also, for the disturbance rejection studies, intensive simulations were conducted, which included two most common causes of disturbance i.e. variation in feed composition and variation in feed flow rate. All the simulation investigations clearly suggested that FOFPID controller provided superior performance over FPID controller for each case study i.e. setpoint tracking, disturbance rejection, noise suppression and parameter uncertainties. |
Exploiting deep residual networks for human action recognition from skeletal data | The computer vision community is currently focusing on solving action recognition problems in real videos, which contain thousands of samples with many challenges. In this process, Deep Convolutional Neural Networks (D-CNNs) have played a significant role in advancing the state-of-the-art in various vision-based action recognition systems. Recently, the introduction of residual connections in conjunction with a more traditional CNN model in a single architecture called Residual Network (ResNet) has shown impressive performance and great potential for image recognition tasks. In this paper, we investigate and apply deep ResNets for human action recognition using skeletal data provided by depth sensors. Firstly, the 3D coordinates of the human body joints carried in skeleton sequences are transformed into image-based representations and stored as RGB images. These color images are able to capture the spatial-temporal evolutions of 3D motions from skeleton sequences and can be efficiently learned by D-CNNs. We then propose a novel deep learning architecture based on ResNets to learn features from obtained color-based representations and classify them into action classes. The proposed method is evaluated on three challenging benchmark datasets including MSR Action 3D, KARD, and NTU-RGB+D datasets. Experimental results demonstrate that our method achieves state-of-the-art performance for all these benchmarks whilst requiring less computation resource. In particular, the proposed method surpasses previous approaches by a significant margin of 3.4% on MSR Action 3D dataset, 0.67% on KARD dataset, and 2.5% on NTURGB+D dataset. |
Lumpectomy margins, reexcision, and local recurrence of breast cancer. | BACKGROUND
The diagnosis of breast cancer is often made by excisional biopsy without margin assessment for mammographic findings or palpable masses. Many patients treated with breast conservation undergo reexcision to obtain clear margins although the relationship between clear margins and local recurrence remains controversial.
METHODS
Patients undergoing breast conservation and adjuvant radiation therapy with complete follow-up over 5 years were studied. Factors associated with obtaining clear histopathologic margins and undergoing reexcision to obtain clear margins were studied in relation to the risk of local recurrence.
RESULTS
Clear biopsy margins were associated with diagnosis by fine-needle aspiration cytology (fine-needle aspiration 42%, spot localization 11%, excisional biopsy 10%; P <0.001). Reexcision was significantly related to diagnostic method (spot localization 63%, excisional biopsy 36%, fine-needle aspiration 10%; P <0.001), first margin status (clear 0%, close 11%, positive 46%, unknown 48%; P <0.001), patient age (54 years for reexcised patients and 58 for non-reexcised patients; P <0.001), and tumor size (mean tumor size 1. 4 cm for reexcised patients and 1.7 cm for non-reexcised patients; P = 0.003). Patients undergoing reexcision were significantly more likely to be diagnosed by spot localization, have nonnegative excisional biopsy margins, be younger, and have smaller tumors than patients not undergoing reexcision. Local recurrence was not significantly related to margin status (8% with clear margins, 7% with positive margins, 19% with close margins, and 11% with unknown margins) or reexcision (10% local recurrence rate for patients with negative final margins after reexcision and 12% with positive, close or unknown first margin without reexcision). Estrogen receptor status was the only variable related to local recurrence in Cox proportional hazards model (P = 0.009). Estrogen receptor negative patients with nonnegative margins experienced a 20% rate of local recurrence compared with 10% for estrogen receptor negative patients with negative margins and 7% for estrogen receptor positive patients regardless of margin status (P = 0.021).
CONCLUSIONS
Clear excision margins are facilitated by preoperative diagnosis by fine-needle cytology. For patients with nonnegative margins, reexcision was more commonly performed in young patients with small tumors diagnosed by spot localization biopsy. The relationship of local recurrence to margins and reexcision was not statistically significant. Estrogen receptor negative tumors with nonnegative margins had a significantly higher rate of local recurrence than estrogen receptor negative tumors with clear margins and estrogen receptor positive tumors regardless of margin status. |
Functional and evolutionary aspects of chemoreceptors | The perception and processing of chemical signals from the environment is essential for any living systems and is most probably the first sense developed in life. This perspective discusses the physical limits of chemoreception and gives an overview on the receptor types developed during evolution to detect chemical signals from the outside world of an organism. It discusses the interaction of chemoreceptors with downstream signaling elements, especially the interaction between electrical and chemical signaling. It is further considered how the primary chemosignal is appropriately amplified. Three examples of chemosensory systems illustrate different strategies of such amplification. |
Fast PixelCNN: Based on network acceleration cache and partial generation network | Single image super resolution is one of the most important topic in computer vision and image processing research, many convolutional neural networks (CNN) based super resolution algorithms were proposed and achieved advanced performance, especially in recovering image details, in which PixelCNN is the most representative one. However, due to the intensive computation requirement of PixelCNN model, running time remains a major challenge, which limited its wider application. In this paper, several modifications are proposed to improve PixelCNN based recursive super resolution model. First, a discrete logistic mixture likelihood is adopted, then a cache structure for generating process is proposed, with these modifications, numerous redundant computations are removed without loss of accuracy. Finally, a partial generating network is proposed for higher resolution generation. Experiments on CelebA dataset demonstrate the effectiveness the superiority of the proposed method. |
Order patterns recurrence plots in the analysis of ERP data | Recurrence quantification analysis (RQA) is an established tool for data analysis in various behavioural sciences. In this article we present a refined notion of RQA based on order patterns. The use of order patterns is commonplace in time series analysis. Exploiting this concept in combination with recurrence plots (RP) and their quantification (RQA) allows for advances in contemporary EEG research, specifically in the analysis of event related potentials (ERP), as the method is known to be robust against non-stationary data. The use of order patterns recurrence plots (OPRPs) on EEG data recorded during a language processing experiment exemplifies the potentials of the method. We could show that the application of RQA to ERP data allows for a considerable reduction of the number of trials required in ERP research while still maintaining statistical validity. |
Scholarly publishing and linked data: describing roles, statuses, temporal and contextual extents | Recently, several ontologies have been introduced for semantic publishing. However, scholarly publishing, like other real-world domains, needs to be described also in terms of precise temporal durations and the particular contexts in which the relevant processes take place. For instance, a document changes status during its publication process, e.g., from "draft" to "submitted" to "under review" to "accepted for publication", and so on. Similarly, one's roles may change with time: one's affiliation with an academic institution or one's role as a journal editor are likely to change over time. Existing well-known ontologies used to describe individuals and bibliographic entities in the Linked Data are currently not able to model situations of temporary or context-dependent possession (e.g., the holding of a status or of a role). In this paper, we address this issue by introducing two ontologies for semantic publishing, the Publishing Roles Ontology and the Publishing Status Ontology, that define the roles of people and the statuses of documents in the scholarly publishing domain. |
A 12-bit 20 MS/s 56.3 mW Pipelined ADC With Interpolation-Based Nonlinear Calibration | The linearity of a high-resolution pipelined analog- to-digital converter (ADC) is mainly limited by the capacitor mismatch and the finite operational amplifier (OPAMP) gain in the multiplying-digital-to-analog converter (MDAC). Therefore, high resolution pipelined ADCs usually require high-gain OPAMP and large capacitors, which causes large ADC power. In recent years, various nonlinear calibration techniques have been developed to compensate both linear and nonlinear error from MDCAs so that low-power MDACs with small capacitors and low-gain OPAMP can be used. Hence, the ADC power can be greatly reduced. This paper introduces a novel interpolation- based digital self-calibration architecture for pipelined ADC. Compared to previous techniques, the new architecture is free of adaptation. Hence, long convergence is not needed. The complexity of the digital processor is also considerably lower. The new architecture does not use backend ADC to measure MDACs. Hence, it is free of the accumulation of measurement error, which leads to more accurate calibration. A prototype ADC with the calibration architecture is fabricated in a 0.35 3.3 V CMOS process. The ADC samples at 20 MS/s. The calibration improves the ADC DNL and INL from 1.47 LSB and 7.85 LSB to 0.2 LSB and 0.27 LSB. For a 590 kHz sinusoidal signal, the calibration improves the ADC signal-to-noise-distortion ratio(SNDR) and spurious-free dynamic range (SFDR) from 41.3 dB and 52.1 dB to 72.5 dB and 84.4 dB respectively. The 11.8-ENOB 20 MS/s ADC consumes 56.3 mW power with 3.3 V supply. The 0.78 pJ/step figure-of-merit (FOM) is low for designs in 0.35 CMOS processes. At the Nyquist frequency, SNDR of the calibrated ADC drops 8 dB due to the slow settling of the first pipeline stage. |
Linear-time computability of combinatorial problems on series-parallel graphs | A series-parallel graph can be constructed from a certain graph by recurslvely applying "series" and "parallel" connections The class of such graphs, which Is a well-known model of series-parallel electrical networks, is a subclass of planar graphs It is shown in a umfied manner that there exist hnearume algorithms for many combinatorial problems ff an input graph is restricted to the class of series-parallel graphs. These include 0) the decision problem with respect to a property characterized by a finite number of forbidden graphs, (u) the mlmmum edge (vertex) deletion problem with respect to the same property as above, and (Ul) the generalized matching problem Consequently, the following problems, among others, prove to be hnear-tlme computable for the class of series-parallel graphs. (I) the minimum vertex cover problem, (2) the maximum outerplanar (reduced) subgraph problem, (3) the minimum feedback vertex set problem, (4) the maximum (induced) hne-subgraph problem, (5) the maximum matching problem, and (6) the maximum disjoint triangle problem. |
Novel class of medications, orexin receptor antagonists, in the treatment of insomnia – critical appraisal of suvorexant | Insomnia, a highly prevalent disorder, can be detrimental to patients' overall health and worsen existing comorbidities. Patients may have acute episodes of insomnia related to a traumatic event, but more commonly insomnia occurs chronically. While proper sleep hygiene and behavioral therapy play important roles in the nonpharmacologic management of short-term and chronic insomnia, medications may also be required. Historically, insomnia has been treated with agents such as benzodiazepines, nonbenzodiazepine receptor agonists, and melatonin agonists. Dual orexin receptor antagonists represent a new class of medications for the treatment of insomnia, which block the binding of wakefulness-promoting neuropeptides orexin A and orexin B to their respective receptor sites. Suvorexant (Belsomra) is the first dual orexin receptor antagonist to be approved in the US and Japan and has demonstrated efficacy in decreasing time to sleep onset and increasing total sleep time. Its unique mechanism of action, data to support efficacy and safety over 12 months of use, and relative lack of withdrawal effects when discontinued may represent an alternative for patients with chronic insomnia who cannot tolerate or do not receive benefit from more traditional sleep agents. Suvorexant is effective and well tolerated, but precautions exist for certain patient populations, including females, obese patients, and those with respiratory disease. Suvorexant has only been studied vs placebo, and hence it is unknown how it directly compares with other medications approved by the US Food and Drug Administration for insomnia. Suvorexant is not likely to replace benzodiazepines or nonbenzodiazepine receptor antagonists as a first-line sleep agent but does represent a novel option for the treatment of patients with chronic insomnia. |
Occupational hearing loss in teachers: a probable diagnosis. | UNLABELLED
Teachers frequently report auditory symptoms and excessive noise in classrooms, but noise level measurements are not done routinely. Study model - a prospective clinical trial.
AIM
To study auditory symptoms and audiometric exams of teachers and classroom noise levels.
MATERIAL AND METHOD
Data from two groups, GI (40 teachers) and GII (40 voluntaries) were studied as follows: age, gender, working conditions, audiometric exams, and classroom noise levels.
RESULTS
In GI there were more females (86%), working in basic teaching (75%), in classes with 21-40 students (70%), with workloads between 26 and 40 hours per week (47%), and variable professional teaching time. Most teachers in GI reported excessive classroom noise (93.5%) and auditory symptoms (65%). In GI, 25% of teachers presented audiometric alterations (versus 10% of controls), with an acoustic notch predominating (11.25%; p<0.05). Noise levels close to 87dBA were recorded in classes at all teaching levels.
CONCLUSIONS
occupational hearing loss may occur in teachers. Further studies are needed to confirm this proposition. |
Democrats, republicans and starbucks afficionados: user classification in twitter | More and more technologies are taking advantage of the explosion of social media (Web search, content recommendation services, marketing, ad targeting, etc.). This paper focuses on the problem of automatically constructing user profiles, which can significantly benefit such technologies. We describe a general and robust machine learning framework for large-scale classification of social media users according to dimensions of interest. We report encouraging experimental results on 3 tasks with different characteristics: political affiliation detection, ethnicity identification and detecting affinity for a particular business. |
Spin Transfer Torques | This tutorial article introduces the physics of spin transfer torques in magnetic devices. We provide an elementary discussion of the mechanism of spin transfer torque, and review the theoretical and experimental progress in this field. Our intention is to be accessible to beginning graduate students. This is the introductory paper for a cluster of “Current Perspectives” articles on spin transfer torques published in volume 320 of the Journal of Magnetism and Magnetic Materials. This article is meant to set the stage for the others which follow it in this cluster; they focus in more depth on particularly interesting aspects of spin-torque physics and highlight unanswered questions that might be productive topics for future research. |
Antisolvent membrane crystallization of pharmaceutical compounds. | This article describes a modification of the conventional membrane crystallization technique in which a membrane is used to dose the solvent/antisolvent composition to generate supersaturation and induce crystallization in a drug solution. Two operative configurations are proposed: (a) solvent/antisolvent demixing crystallization, where the solvent is removed in at higher flow rate than the antisolvent so that phase inversion promotes supersaturation and (b) antisolvent addition, in which the antisolvent is dosed into the crystallizing drug solution. In both cases, solvent/antisolvent migration occurs in vapor phase and it is controlled by the porous membrane structure, acting on the operative process parameters. This mechanism is different than that observed when forcing the liquid phases through the pores and the more finely controllable supersaturated environment would generate crystals with the desired characteristics. Two organic molecules of relevant industrial implication, like paracetamol and glycine, were used to test the new systems. Experiments demonstrated that, by using antisolvent membrane crystallization in both configurations, accurate control of solution composition at the crystallization point has been achieved with effects on crystals morphology. |
Identification of embedded mathematical formulas in PDF documents using SVM | With the tremendous popularity of PDF format, recognizing mathematical formulas in PDF documents becomes a new and important problem in document analysis field. In this paper, we present a method of embedded mathematical formula identification in PDF documents, based on Support Vector Machine (SVM). The method first segments text lines into words, and then classifies each word into two classes, namely formula or ordinary text. Various features of embedded formulas, including geometric layout, character and context content, are utilized to build a robust and adaptable SVM classifier. Embedded formulas are then extracted through merging the words labeled as formulas. Experimental results show good performance of the proposed method. Furthermore, the method has been successfully incorporated into a commercial software package for large-scale e-Book production. |
Heart failure biomarkers in patients with dilated cardiomyopathy. | BACKGROUND
We set out to evaluate the utility of selected heart failure (HF) biomarkers in patients with dilated cardiomyopathy (DCM).
METHODS
In a prospective, randomized study, 68 DCM patients with left ventricular ejection fraction (LVEF) ≤ 40% treated optimally were included. They were observed for 5 years. Initial and control tests included full clinical examination, measurement of tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6) and IL-10, syndecan-4, cystatin C (CysC) and N-terminal pro-brain natriuretic peptide (NT-proBNP), echocardiographic examination, and the assessment of exercise capacity in 6-minute walk test (6MWT).
RESULTS
Finally, after 5-year follow-up we analyzed the data of 45 DCM patients. Concentration of syndecan-4 correlated negatively with LVEF (R=-0.36, p=0.02) and positively with LV systolic (R=0.57, p<0.001) and diastolic diameters (R=0.64, p<0.001). A positive correlation between CysC and right ventricular diastolic diameter (R=0.38, p=0.01), and negative correlations between CysC and glomerular filtration rate (R=-0.49, p<0.001), LVEF (R=-0.4, p=0.02), and 6 MWT (R=-0.46, p<0.001) were noted. Patients who had an increase in LVEF during 5 years were characterized by lower levels of CysC (p=0.01) and NT-proBNP (p<0.001). CysC≤95mg/l and NT-proBNP≤32pg/ml were the best predictors of LVEF increase in DCM patients. Multivariate regression analysis showed that 6 MWT was the only independent predictor of HF re-hospitalization (OR 0.989; p<0.001), and NT-proBNP and LV diastolic diameter were the only risk factors of increased mortality (OR 1.001; p=0.007 and OR 2.960; p=0.025, respectively) in DCM patients.
CONCLUSIONS
CysC correlates negatively with both kidney function and exercise capacity. Syndecan-4 may be a useful biomarker for predicting adverse LV remodeling in DCM patients. |
Conceptual Modeling through Linguistic Analysis Using LIDA | Despite the advantages that object technology can provide to the software development community and its customers, the fundamental problems associated with identifying objects, their attributes, and methods remain: it is a largely manual process driven by heuristics that analysts acquire through experience. While a number of methods exist for requirements development and specification, very few tools exist to assist analysts in making the transition from textual descriptions to other notations for object-oriented analysis and other conceptual models. In this paper we describe a methodology and a prototype tool, Linguistic assistant for Domain Analysis (LIDA), which provide linguistic assistance in the model development process. We first present our methodology to conceptual modeling through linguistic analysis. We give an overview of LIDA's functionality and present its technical design and the functionality of its components. We also provide a comparison of LIDA's functionality with that of other research prototypes. Finally, we present an example of how LIDA is used in a conceptual modeling task. |
Design and Development of the Cable Actuated Finger Exoskeleton for Hand Rehabilitation Following Stroke | Finger impairment following stroke results in significant deficits in hand manipulation and the performance of everyday tasks. While recent advances in rehabilitation robotics have shown promise for facilitating functional improvement, it remains unclear how best to employ these devices to maximize benefits. Current devices for the hand, however, lack the capacity to fully explore the space of possible training paradigms. Particularly, they cannot provide the independent joint control and levels of velocity and torque required. To fill this need, we have developed a prototype for one digit, the cable actuated finger exoskeleton (CAFE), a three-degree-of-freedom robotic exoskeleton for the index finger. This paper presents the design and development of the CAFE, with performance testing results. |
The diagnosis and management of Piriformis Syndrome: myths and facts. | Piriformis Syndrome (PS) is an uncommon, controversial neuromuscular disorder that is presumed to be a compression neuropathy of the sciatic nerve at the level of the piriformis muscle (PM). The diagnosis is hampered by a lack of agreed upon clinical criteria and a lack of definitive investigations such as imaging or electrodiagnostic testing. Treatment has focused on stretching, physical therapies, local injections, including botulinum toxin, and surgical management. This article explores the various sources of controversy surrounding piriformis syndrome including diagnosis, investigation and management. We conclude with a proposal for diagnostic criteria which include signs and symptoms, imaging, and response to therapeutic injections. |
New VF-power system architecture and evaluation for future aircraft | Conventional aircraft power system is a constant-frequency (CF) supply based on mechanical-regulated constant-speed mechanism that has relatively low efficiency. Replacing the CF system with variable-frequency (VF) power improves overall efficiency, and reduce the system's weight and volume. However, this creates a new tier of requirements and design challenges. Novel VF-power architecture is developed with minimization of the power losses throughout the stages of power conversions. Optimal partitioning and grouping of onboard AC loads has been discussed with specific system data. New VF-input multi-functional power converters are also briefly discussed. |
Academic abilities in children and adolescents with a history of autism spectrum disorders who have achieved optimal outcomes. | This study examines the academic abilities of children and adolescents who were once diagnosed with an autism spectrum disorder, but who no longer meet diagnostic criteria for this disorder. These individuals have achieved social and language skills within the average range for their ages, receive little or no school support, and are referred to as having achieved "optimal outcomes." Performance of 32 individuals who achieved optimal outcomes, 41 high-functioning individuals with a current autism spectrum disorder diagnosis (high-functioning autism), and 34 typically developing peers was compared on measures of decoding, reading comprehension, mathematical problem solving, and written expression. Groups were matched on age, sex, and nonverbal IQ; however, the high-functioning autism group scored significantly lower than the optimal outcome and typically developing groups on verbal IQ. All three groups performed in the average range on all subtests measured, and no significant differences were found in performance of the optimal outcome and typically developing groups. The high-functioning autism group scored significantly lower on subtests of reading comprehension and mathematical problem solving than the optimal outcome group. These findings suggest that the academic abilities of individuals who achieved optimal outcomes are similar to those of their typically developing peers, even in areas where individuals who have retained their autism spectrum disorder diagnoses exhibit some ongoing difficulty. |
Graph-based anomaly detection | Anomaly detection is an area that has received much attention in recent years. It has a wide variety of applications, including fraud detection and network intrusion detection. A good deal of research has been performed in this area, often using strings or attribute-value data as the medium from which anomalies are to be extracted. Little work, however, has focused on anomaly detection in graph-based data. In this paper, we introduce two techniques for graph-based anomaly detection. In addition, we introduce a new method for calculating the regularity of a graph, with applications to anomaly detection. We hypothesize that these methods will prove useful both for finding anomalies, and for determining the likelihood of successful anomaly detection within graph-based data. We provide experimental results using both real-world network intrusion data and artificially-created data. |
Are ICT, Workplace Organization and Human Capital Relevant for Innovation? A Comparative Study Based on Swiss and Greek Micro Data | This paper investigates the relationship between indicators for the intensity of use of ICT (examining three different types of ICT widely used in firms: internal, e-sales, e-procurement IS), several forms of workplace organization, and human capital on one hand, and several measures of innovation performance at firm level on the other hand, in an innovation equation framework, in which was also controlled for standard innovation determinants such as demand, competition and firm size. The empirical part is based on data of Swiss and Greek firms. This paper contributes to literature in three ways: first, it analyzes three important factors, i.e. information technology, workplace organization and human capital, which are considered to be drivers of innovation performance particularly in the last fifteen to twenty years, in the same setting, it uses several innovation indicators that cover both the input and the output side of the innovation process and, third, it does the analysis in a comparative setting for two countries, Greece and Switzerland, with quite different levels of technological and economic development. |
Path Integral Networks: End-to-End Differentiable Optimal Control | In this paper, we introduce Path Integral Networks (PI-Net), a recurrent network representation of the Path Integral optimal control algorithm. The network includes both system dynamics and cost models, used for optimal control based planning. PI-Net is fully differentiable, learning both dynamics and cost models end-to-end by back-propagation and stochastic gradient descent. Because of this, PI-Net can learn to plan. PI-Net has several advantages: it can generalize to unseen states thanks to planning, it can be applied to continuous control tasks, and it allows for a wide variety learning schemes, including imitation and reinforcement learning. Preliminary experiment results show that PI-Net, trained by imitation learning, can mimic control demonstrations for two simulated problems; a linear system and a pendulum swing-up problem. We also show that PI-Net is able to learn dynamics and cost models latent in the demonstrations. |
Smart manufacturing, manufacturing intelligence and demand-dynamic performance | Smart Manufacturing is the dramatically intensified and pervasive application of networked information-based technologies throughout the manufacturing and supply chain enterprise. It responds and leads to a dramatic and fundamental business transformation to demand-dynamic economics keyed on customers, partners and the public; enterprise performance; demand-driven supply chain services; and broad-based workforce involvement. ITenabled Smart factories and supply networks can better respond to national interests and strategic imperatives and can revitalize the industrial sector by facilitating global competitiveness and exports, providing sustainable jobs, radically improving performance, and facilitating manufacturing innovation. |
Importance of early insulin secretion: comparison of nateglinide and glyburide in previously diet-treated patients with type 2 diabetes. | OBJECTIVE
This study compared the effects of nateglinide, glyburide, and placebo on postmeal glucose excursions and insulin secretion in previously diet-treated patients with type 2 diabetes.
RESEARCH DESIGN AND METHODS
This randomized, double-blind, placebo-controlled multicenter study was conducted in 152 patients who received either nateglinide (120 mg before three meals daily, n = 51), glyburide (5 mg q.d. titrated to 10 mg q.d. after 2 weeks, n = 50), or placebo (n = 51) for 8 weeks. Glucose, insulin, and C-peptide profiles during liquid meal challenges were measured at weeks 0 and 8. At weeks -1 and 7, 19-point daytime glucose and insulin profiles, comprising three solid meals, were measured.
RESULTS
During the liquid-meal challenge, nateglinide reduced the incremental glucose area under the curve (AUC) more effectively than glyburide ( = -4.94 vs. -2.71 mmol. h/l, P < 0.05), whereas glyburide reduced fasting plasma glucose more effectively than nateglinide ( = -2.9 vs. -1.0 mmol/l, respectively, P < 0.001). In contrast, C-peptide induced by glyburide was greater than that induced by nateglinide ( = +1.83 vs. +0.95 nmol. h/l, P < 0.01), and only glyburide increased fasting insulin levels. During the solid meal challenges, nateglinide and glyburide elicited similar overall glucose control ( 12-h incremental AUC = -13.2 vs. -15.3 mmol. h/l), but the insulin AUC induced by nateglinide was significantly less than that induced by glyburide ( 12-h AUC = +866 vs. +1,702 pmol. h/l, P = 0.01).
CONCLUSIONS
This study demonstrated that nateglinide selectively enhanced early insulin release and provided better mealtime glucose control with less total insulin exposure than glyburide. |
Performance evaluation in obstacle avoidance | No quantitative procedure currently exists to evaluate the obstacle avoidance capabilities of robotic systems. Such an evaluation method is not only needed to compare different avoidance methods, but also to determine the operational limits of autonomous systems. This work proposes an evaluation framework which can find such limits. The framework comprises two types of tests: detection tests and avoidance tests. For each type, both environment and performance metrics need to be defined. For detection tests such metrics are well known, but for avoidance tests such metrics are not readily available. Therefore a new set of metrics is proposed. The framework is applied to a UAV that uses stereo vision to detect obstacles. Three different avoidance methods are compared in environments of varying difficulty. |
Dynamic Coattention Networks For Question Answering | Several deep learning models have been proposed for question answering. However, due to their single-pass nature, they have no way to recover from local maxima corresponding to incorrect answers. To address this problem, we introduce the Dynamic Coattention Network (DCN) for question answering. The DCN first fuses co-dependent representations of the question and the document in order to focus on relevant parts of both. Then a dynamic pointing decoder iterates over potential answer spans. This iterative procedure enables the model to recover from initial local maxima corresponding to incorrect answers. On the Stanford question answering dataset, a single DCN model improves the previous state of the art from 71.0% F1 to 75.9%, while a DCN ensemble obtains 80.4% F1. |
Vehicle control system for automatic valet parking with infrastructure sensors | This paper presents vehicle control system for automatic valet parking with infrastructure sensors. First, we describe the automatic valet parking service system. In the service, vehicle moves autonomously based on sensing data generated by infrastructure sensors. Second, we implement vehicle control system for automatic valet parking. We design hardware and software components focusing on minimizing the add-on devices and maximizing data integration. Finally, we do a feasibility test for verification of the system. |
Low-dose versus high-dose methotrexate during remission induction in childhood acute lymphoblastic leukemia (Protocol 81-01 update). | We evaluated event-free survival (EFS) and leukemia-free interval (LFI) of children treated for acute lymphoblastic leukemia (ALL). Patients were randomized to receive either a low dose or high dose of methotrexate (MTX) as a single agent at the time of diagnosis. Five days later, multidrug therapy was begun. We assessed the early antileukemic efficacy of the two doses of MTX, as well as toxicity and long-term efficacy. An increase in cell kill, as indicated by a larger decrease in the percentage of viable cells in the bone marrow between days 0 and 5, was observed for the high-dose MTX group when compared with the low-dose MTX group (P = .04). At 7.1 years of median follow-up, the 38 children randomized to receive high-dose MTX had a better EFS and LFI compared with the 39 patients randomized to receive low-dose MTX. The 7-year percentages (+/- SE) for EFS were 82% +/- 6% for high-dose MTX and 69% +/- 7% for low-dose MTX (P = .13). The 7-year percentages for LFI were 91% +/- 5% and 69% +/- 7%, respectively (P = .01). We recommend that high-dose MTX be considered as an effective addition to induction therapy in childhood ALL. |
Seasonal variability in clinical care of COPD outpatients: results from the Andalusian COPD audit | OBJECTIVES
Clinical practice in chronic obstructive pulmonary disease (COPD) can be influenced by weather variability throughout the year. To explore the hypothesis of seasonal variability in clinical practice, the present study analyzes the results of the 2013-2014 Andalusian COPD audit with regard to changes in clinical practice according to the different seasons.
METHODS
The Andalusian COPD audit was a pilot clinical project conducted from October 2013 to September 2014 in outpatient respiratory clinics of hospitals in Andalusia, Spain (8 provinces with more than 8 million inhabitants) with retrospective data gathering. For the present analysis, astronomical seasons in the Northern Hemisphere were used as reference. Bivariate associations between the different COPD guidelines and the clinical practice changes over the seasons were explored by using binomial multivariate logistic regression analysis with age, sex, Charlson comorbidity index, type of hospital, and COPD severity by forced expiratory volume in 1 second as covariates, and were expressed as odds ratio (OR) with 95% confidence intervals (CIs).
RESULTS
The Andalusian COPD audit included 621 clinical records from 9 hospitals. After adjusting for covariates, only inhaler device satisfaction evaluation was found to significantly differ according to the seasons with an increase in winter (OR, 3.460; 95% CI, 1.469-8.151), spring (OR, 4.215; 95% CI, 1.814-9.793), and summer (OR, 3.371; 95% CI, 1.391-8.169) compared to that in autumn. The rest of the observed differences were not significant after adjusting for covariates. However, compliance with evaluating inhaler satisfaction was low.
CONCLUSION
The various aspects of clinical practice for COPD care were found to be quite homogeneous throughout the year for the variables evaluated. Inhaler satisfaction evaluation, however, presented some significant variation during the year. Inhaler device satisfaction should be evaluated during all clinical visits throughout the year for improved COPD management. |
Normalisation by evaluation in the compilation of typed functional programming languages | This thesis presents a critical analysis of n rmalisation by evaluation as a technique for speeding up compilation of typed functional programming languages. Our investigation focuses on the SML.NET compiler and its typed intermediate language MIL. We implement and measure the performance of normalisation by evaluation for MIL across a range of benchmarks. Taking a di fferent approach, we also implement and measure the performance of a graph-based shrinking reductionsalgorithm for SML.NET. MIL is based on Moggi’s computational metalanguage. As a stepping stone to normalisation by evaluation, we investigate strong normalisation of the computational metalanguage by introducing an extension of Girard-Tait reducibility. Inspired by previous work on local state and parametric polymorphism, we define reducibility for continuationsand more generally reducibility for f ame stacks . First we prove strong normalistion for the computational metalanguage. Then we extend that proof to include features of MIL such as sums and exceptions. Taking an incremental approach, we construct a collection of increasingly sophisticated normalisation by evaluation algorithms, culminating in a range of normalisation algorithms for MIL. Congruence rules and α-rules are captured by a compositional parameterised semantics. Defunctionalisationis used to eliminateη-rules. Normalisation by evaluation for the computational metalanguage is introduced using a monadic semantics. Variants in which the monadic e ffects are made explicit, using either state or control operators, are also considered. Previous implementations of normalisation by evaluation with sums have relied on continuation-passing-syle or control operators. We present a new algorithm which instead uses a single reference cell and a zipper structure. This suggests a possible alternative way of implementing Filinski’s monadic reflectionoperations. In order to obtain benchmark results without having to take into account all of the features of MIL, we implement two di fferent techniques for eliding language constructs. The first is not semantics-preserving, but is e ffective for assessing the e fficiency of normalisation by evaluation algorithms. The second is semantics-preserving, but less flexible. In common with many intermediate languages, but unlike the computational metalanguage, MIL requires all non-atomic values to be named. We use either control operators or state to ensure each non-atomic value is named. We assess our normalisation by evaluation algorithms by comparing them with a spectrum of progressively more optimised, rewriting-based normalisation algorithms. The SML.NET front-end is used to generate MIL code from ML programs, including the SML.NET compiler itself. Each algorithm is then applied to the generated MIL code. Normalisation by evaluation always performs faster than the most na ı̈ve algorithms — often by orders of magnitude. Some of the algorithms are slightly faster than normalisation by evaluation. Closer inspection reveals that these algorithms are in fact defunctionalised versions of normalisation by evaluation algorithms. Our normalisation by evaluation algorithms perform unrestricted inlining of functions. Unrestricted inlining can lead to a super-exponential blow-up in the size of target code with respect to the source. Furthermore, the worst-case complexity of compilation with unrestricted inlining is non-elementary in the size of the source code. SML.NET alleviates both problems by using a restricted form of normalisation based on Appel and Jim’sshrinking reductions . The original algorithm is quadratic in the worst case. Using a graph-based representation for terms we implement a compositional linear algorithm. This speeds up the time taken to perform shrinking reductions by up to a factor of fourteen, which leads to an improvement of up to forty percent in total compile time. |
Social skills group training in high-functioning autism: A qualitative responder study. | Systematic reviews show some evidence for the efficacy of group-based social skills group training in children and adolescents with autism spectrum disorder, but more rigorous research is needed to endorse generalizability. In addition, little is known about the perspectives of autistic individuals participating in social skills group training. Using a qualitative approach, the objective of this study was to examine experiences and opinions about social skills group training of children and adolescents with higher functioning autism spectrum disorder and their parents following participation in a manualized social skills group training ("KONTAKT"). Within an ongoing randomized controlled clinical trial (NCT01854346) and based on outcome data from the Social Responsiveness Scale, six high responders and five low-to-non-responders to social skills group training and one parent of each child (N = 22) were deep interviewed. Interestingly, both high responders and low-to-non-responders (and their parents) reported improvements in social communication and related skills (e.g. awareness of own difficulties, self-confidence, independence in everyday life) and overall treatment satisfaction, although more positive intervention experiences were expressed by responders. These findings highlight the added value of collecting verbal data in addition to quantitative data in a comprehensive evaluation of social skills group training. |
Factors associated with prospective long-term treatment adherence among individuals with bipolar disorder. | OBJECTIVE
Clinical characteristics, adverse effects of medication, and treatment attitudes have been associated with adherence in bipolar populations in cross-sectional studies. The aim of this secondary analysis from a larger study was to identify the association between baseline variables and average treatment adherence over a subsequent three-year period.
METHODS
Veterans with bipolar disorder were evaluated on self-reported adherence status at baseline and every six months over a three-year period. The sample was dichotomized into two clinically relevant categories: those who were primarily adherent and those who were primarily nonadherent. Demographic and clinical variables were examined for the two groups of patients in relation to their average adherence over the three-year period.
RESULTS
The study recruited a sample of 306 persons with severe bipolar disorder. The sample was predominantly male (278 men, or 91%), with a mean+/-SD age of 46.6+/-10.1 years. A total of 240 individuals (78%) were largely adherent to treatment, and 37 individuals (12%) were largely nonadherent to treatment. Nonadherent individuals were less likely to be on intensive somatotherapy regimens (p=.001); experienced more barriers to care, including lack of telephone access (p<.05) and life obligations and commitments (p<.05); and had more prior suicide attempts (p=.003).
CONCLUSIONS
Nonadherent individuals with bipolar disorder received less intensive pharmacologic treatments, had more suicide attempts, and experienced more barriers to care than adherent individuals. Nonadherence may have system as well as patient components. Consideration of nonadherence as a function of both patient factors and system factors will enhance our ability to understand nonadherence and intervene more effectively. |
Complications of circumcision | Circumcision remains the most common operation performed on males. Although, not technically difficult, it is accompanied by a rate of morbidity and can result in complications ranging from trivial to tragic. The reported incidence of complications varies from 0.1% to 35% the most common being infection, bleeding and failure to remove the appropriate amount of foreskin. Forty patients suffering from different degrees of circumcision complications and their treatment are presented. In all patients satisfactory functional and cosmetic results were achieved. Whether it is done for ritualistic, religious or medical reasons circumcision should be performed by a fully trained surgeon using a proper technique as follows 1) adequate use of antiseptic agents; 2) complete separation of inner preputial epithelium from the glans; 3) marking the skin to be removed at the beginning of operation; 4) careful attention to the baby’s voiding within the first 6 to 8 h after circumcision; 5) removal or replacement of the dressings on the day following circumcision. |
Epigenome-wide Association Studies and the Interpretation of Disease -Omics | Epigenome-wide association studies represent one means of applying genome-wide assays to identify molecular events that could be associated with human phenotypes. The epigenome is especially intriguing as a target for study, as epigenetic regulatory processes are, by definition, heritable from parent to daughter cells and are found to have transcriptional regulatory properties. As such, the epigenome is an attractive candidate for mediating long-term responses to cellular stimuli, such as environmental effects modifying disease risk. Such epigenomic studies represent a broader category of disease -omics, which suffer from multiple problems in design and execution that severely limit their interpretability. Here we define many of the problems with current epigenomic studies and propose solutions that can be applied to allow this and other disease -omics studies to achieve their potential for generating valuable insights. |
Planetary Rover Developments Supporting Mars Exploration, Sample Return and Future Human-Robotic Colonization | We overview our recent research on planetary mobility. Products of this effort include the Field Integrated Design & Operations rover (FIDO), Sample Return Rover (SRR), reconfigurable rover units that function as an All Terrain Explorer (ATE), and a multi-Robot Work Crew of closely cooperating rovers (RWC). FIDO rover is an advanced technology prototype; its design and field testing support NASA’s development of long range, in situ Mars surface science missions. Complementing this, SRR implements autonomous visual recognition, navigation, rendezvous, and manipulation functions enabling small object pick-up, handling, and precision terminal docking to a Mars ascent vehicle for future Mars Sample Return. ATE implements on-board reconfiguration of rover geometry and control for adaptive response to adverse and changing terrain, e.g., traversal of steep, sandy slopes. RWC implements coordinated control of two rovers under closed loop kinematics and force constraints, e.g., transport of large payloads, as would occur in robotic colonies at future Mars outposts. RWC is based in a new extensible architecture for decentralized control of, and collective state estimation by multiple heterogeneous robotic platforms—CAMPOUT; we overview the key architectural features. We have conducted experiments with all these new rover system concepts over variable natural terrain. For each of the above developments, we summarize our approach, some of our key experimental results to date, and our future directions of planned development. |
Discriminatively boosted image clustering with fully convolutional auto-encoders | Traditional image clustering methods take a two-step approach, feature learning and clustering, sequentially. However, recent research results demonstrated that combining the separated phases in a unified framework and training them jointly can achieve a better performance. In this paper, we first introduce fully convolutional auto-encoders for image feature learning and then propose a unified clustering framework to learn image representations and cluster centers jointly based on a fully convolutional auto-encoder and soft k-means scores. At initial stages of the learning procedure, the representations extracted from the auto-encoder may not be very discriminative for latter clustering. We address this issue by adopting a boosted discriminative distribution, where high score assignments are highlighted and low score ones are de-emphasized. With the gradually boosted discrimination, clustering assignment scores are discriminated and cluster purities are enlarged. Experiments on several vision benchmark datasets show that our methods can achieve a state-of-the-art performance. |
Seismodeformations in Late Holocene estuary deposits in the central part of St. Petersburg | Deformations in a section of layered Late Holocene estuary-flood-plain deposits, found for the first time in the central part of St. Petersburg, are discussed. The discussed reason why this section could have been deformed inside the undeformed stratum is a horizontally directed dynamical shock. The probable causes of deformation are considered, with the most real one being a relatively distant earthquake. An attempt is made to estimate the intensity of this quake for the territory of the city. |
Effects of low-intensity laser therapy on the orthodontic movement velocity of human teeth: a preliminary study. | BACKGROUND AND OBJECTIVES
Low-intensity laser therapy (LILT) has been studied in many fields of dentistry, but to our knowledge, this is the first time that its effects on orthodontic movement velocity in humans are investigated.
STUDY DESIGN/PATIENTS AND METHODS
Eleven patients were recruited for this 2-month study. One half of the upper arcade was considered control group (CG) and received mechanical activation of the canine teeth every 30 days. The opposite half received the same mechanical activation and was also irradiated with a diode laser emitting light at 780 nm, during 10 seconds at 20 mW, 5 J/cm2, on 4 days of each month. Data of the biometrical progress of both groups were statistically compared.
RESULTS
All patients showed significant higher acceleration of the retraction of canines on the side treated with LILT when compared to the control.
CONCLUSIONS
Our findings suggest that LILT does accelerate human teeth movement and could therefore considerably shorten the whole treatment duration. |
An effective voting method for circle detection | The drawbacks of the standard Hough transform (SHT) are the computational time spending and the large storage requirement. Moreover, the voting method of SHT affects accuracy of detection. In this paper, a new voting method is proposed to reduce the computation and storage requirements of SHT for circle detection. This method improves the efficiency of circle detection by letting each pixel only belong to one candidate of circle parameters. Synthetic images are used to show the capability of the proposed method. |
Adapting Grammatical Error Correction Based on the Native Language of Writers with Neural Network Joint Models | An important aspect for the task of grammatical error correction (GEC) that has not yet been adequately explored is adaptation based on the native language (L1) of writers, despite the marked influences of L1 on second language (L2) writing. In this paper, we adapt a neural network joint model (NNJM) using L1-specific learner text and integrate it into a statistical machine translation (SMT) based GEC system. Specifically, we train an NNJM on general learner text (not L1-specific) and subsequently train on L1-specific data using a Kullback-Leibler divergence regularized objective function in order to preserve generalization of the model. We incorporate this adapted NNJM as a feature in an SMT-based English GEC system and show that adaptation achieves significant F0.5 score gains on English texts written by L1 Chinese, Russian, and Spanish writers. |
Tunneling nanotube (TNT)-like structures facilitate a constitutive, actomyosin-dependent exchange of endocytic organelles between normal rat kidney cells. | Tunneling nanotube (TNT)-like structures are intercellular membranous bridges that mediate the transfer of various cellular components including endocytic organelles. To gain further insight into the magnitude and mechanism of organelle transfer, we performed quantitative studies on the exchange of fluorescently labeled endocytic structures between normal rat kidney (NRK) cells. This revealed a linear increase in both the number of cells receiving organelles and the amount of transferred organelles per cell over time. The intercellular transfer of organelles was unidirectional, independent of extracellular diffusion, and sensitive to shearing force. In addition, during a block of endocytosis, a significant amount of transfer sustained. Fluorescence microscopy revealed TNT-like bridges between NRK cells containing F-actin but no microtubules. Depolymerization of F-actin led to the disappearance of TNT and a strong inhibition of organelle exchange. Partial ATP depletion did not affect the number of TNT but strongly reduced organelle transfer. Interestingly, the myosin II specific inhibitor S-(-)-blebbistatin strongly induced both organelle transfer and the number of TNT, while the general myosin inhibitor 2,3-butanedione monoxime induced the number of TNT but significantly inhibited transfer. Taken together, our data indicate a frequent and continuous exchange of endocytic organelles between cells via TNT by an actomyosin-dependent mechanism. |
Falling asleep with Angry Birds, Facebook and Kindle: a large scale study on mobile application usage | While applications for mobile devices have become extremely important in the last few years, little public information exists on mobile application usage behavior. We describe a large-scale deployment-based research study that logged detailed application usage information from over 4,100 users of Android-powered mobile devices. We present two types of results from analyzing this data: basic descriptive statistics and contextual descriptive statistics. In the case of the former, we find that the average session with an application lasts less than a minute, even though users spend almost an hour a day using their phones. Our contextual findings include those related to time of day and location. For instance, we show that news applications are most popular in the morning and games are at night, but communication applications dominate through most of the day. We also find that despite the variety of apps available, communication applications are almost always the first used upon a device's waking from sleep. In addition, we discuss the notion of a virtual application sensor, which we used to collect the data. |
Arabic Named Entity Recognition: A Feature-Driven Study | The named entity recognition task aims at identifying and classifying named entities within an open-domain text. This task has been garnering significant attention recently as it has been shown to help improve the performance of many natural language processing applications. In this paper, we investigate the impact of using different sets of features in three discriminative machine learning frameworks, namely, support vector machines, maximum entropy and conditional random fields for the task of named entity recognition. Our language of interest is Arabic. We explore lexical, contextual and morphological features and nine data-sets of different genres and annotations. We measure the impact of the different features in isolation and incrementally combine them in order to evaluate the robustness to noise of each approach. We achieve the highest performance using a combination of 15 features in conditional random fields using broadcast news data (Fbeta = 1=83.34). |
How does climate change influence Arctic mercury? | Recent studies have shown that climate change is already having significant impacts on many aspects of transport pathways, speciation and cycling of mercury within Arctic ecosystems. For example, the extensive loss of sea-ice in the Arctic Ocean and the concurrent shift from greater proportions of perennial to annual types have been shown to promote changes in primary productivity, shift foodweb structures, alter mercury methylation and demethylation rates, and influence mercury distribution and transport across the ocean-sea-ice-atmosphere interface (bottom-up processes). In addition, changes in animal social behavior associated with changing sea-ice regimes can affect dietary exposure to mercury (top-down processes). In this review, we address these and other possible ramifications of climate variability on mercury cycling, processes and exposure by applying recent literature to the following nine questions; 1) What impact has climate change had on Arctic physical characteristics and processes? 2) How do rising temperatures affect atmospheric mercury chemistry? 3) Will a decrease in sea-ice coverage have an impact on the amount of atmospheric mercury deposited to or emitted from the Arctic Ocean, and if so, how? 4) Does climate affect air-surface mercury flux, and riverine mercury fluxes, in Arctic freshwater and terrestrial systems, and if so, how? 5) How does climate change affect mercury methylation/demethylation in different compartments in the Arctic Ocean and freshwater systems? 6) How will climate change alter the structure and dynamics of freshwater food webs, and thereby affect the bioaccumulation of mercury? 7) How will climate change alter the structure and dynamics of marine food webs, and thereby affect the bioaccumulation of marine mercury? 8) What are the likely mercury emissions from melting glaciers and thawing permafrost under climate change scenarios? and 9) What can be learned from current mass balance inventories of mercury in the Arctic? The review finishes with several conclusions and recommendations. |
Dysfunction of ventral striatal reward prediction in schizophrenia | BACKGROUND
Negative symptoms may be associated with dysfunction of the brain reward system in schizophrenia. We used functional magnetic resonance imaging (fMRI) to assess the BOLD response in the ventral striatum of unmedicated schizophrenics during presentation of reward-indicating and loss-indicating stimuli.
METHODS
A total of 10 schizophrenic men (7 never medicated, 3 unmedicated for at least 2 years) and 10 age-matched healthy male volunteers participated in an incentive monetary delay task, in which visual cues predicted that a rapid response to a subsequent target stimulus would result either in monetary gain or loss or would have no consequence.
RESULTS
Compared to healthy controls, unmedicated schizophrenics showed reduced ventral striatal activation during the presentation of reward-indicating cues. Decreased activation of the left ventral striatum was inversely correlated with the severity of negative (and trendwise positive) symptoms.
DISCUSSION
Reduced activation in one of the central areas of the brain reward system, the ventral striatum, was correlated with the severity of negative symptoms in medication-free schizophrenics. In unmedicated schizophrenic patients, a high striatal dopamine turnover may increase the "noise" in the reward system, thus interfering with the neuronal processing of reward-predicting cues by phasic dopamine release. This, in turn, may contribute to negative symptoms as such as anhedonia, apathy, and loss of drive and motivation. |
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