The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper, we survey the 20-year history of this idea and discuss its relation to kernelization in parameterized complexity. With these methods, initiatives such as the 1000 Genomes Project and the 100,000 Genomes Project are now feasible. Advances in sequencing have far outstripped advances in computer processors and random-access memory, however, so it is increasingly challenging to make use of the data available. For example, while modern aligners can easily hold in memory the index for approximate pattern matching on a single human genome, they cannot handle thousands of human genomes. Schneeberger et al.  proposedWhen we are not given an upper bound on the pattern length, we can use one of the competing indexes that does not require such a bound or we can scan, with an online pattern-matching algorithm, the reference genome, and the parts of the other genomes near phrase boundaries. Wandelt and Leser  and Rahn2S is a string with S[n] = $, which is an end-of-file symbol that does not occur elsewhere in S. LZ77 works by parsing S into phrases such that, for each phrase S, S occurs in S but S does not occur in S; that phrase is stored as a triple consisting of a pointer to S’s first occurrence in S , j − i, and S[j]. The LZ77 encoding of S takes 𝒪 (z log n) bits, where z is the number of phrases in the parse. For example, in the following verses vertical lines indicate phrase boundaries:9|9-|b|o|t|tl|e|s|-o|f|-be|er|-on|-t|h|e-|w|a|ll|-9|9-bottles-of-beer-I|f-o|n|e-o|f-t|ho|se|-bottles-s|hou|ld|-h|ap|pe|n-to|-f|all-98|-bottles-of-beer-on-the-wall-98|-bottles-of-beer-on-the-wall-98-bottles-of-beer-I|f-one-of-those-bottles-should-happen-to-fall-97|-bottles-of-beer-on-the-wall …In general, the best compression of highly repetitive datasets is achieved with the LZ77 algorithm by Ziv and Lempel . Suppose Although these verses may be annoyingly similar by the standards of natural language, they are far less similar than human genomes. Indeed, most repetitive biological datasets are much too similar (as well as much too large) for us to use them as informative examples.S with 𝒪 (z log n) rules. An SLP for S is a context-free grammar in Chomsky normal form that generates S and only S; it is balanced if the height of each subtree in the parse tree is logarithmic in that subtree’s size. It follows from Rytter’s and Charikar et al.’s results that we can store S in 𝒪 (z log2n) bits and support random-access reading of any substring of S with length l in 𝒪 (log n + l) time. Verbin and Yu  bits and support random-access reading in 𝒪 (log n + l) time. Rytter’s, Charikar et al.’s, and Bille et al.’s constructions are not practical, but there are practical grammar-based compressors, such as those by Larsson and Moffat (S can easily be augmented to support random-access reading in 𝒪 (log log n + l) time. LZ78 also works by parsing S into phrases but then each phrase must extend a previous phrase plus one character. Because of this property, the LZ78 encoding of S has Ω (S = na.One drawback of LZ77 compression is that reading a character in a compressed string can be very slow. Rytter  and Charn and Yu  showed tn and Yu  showed hd Moffat  and Marud Moffat . As far d Moffat  and Gagid Moffat  are the d Moffat  does notS = na) and there are several implementations of this approach, such as those by Deorowicz and Grabowski  has length at most m + k, and any such substring that does not cross or end at an LZ78 phrase boundary must be an exact copy of an earlier one that does. They gave an algorithm for approximate pattern matching in LZ78 strings that works by extracting the m + k and m + k − 1 characters before and after each LZ78 phrase boundary, respectively, using a technique similar to those discussed in Section Farach and Thorup  observed Ukkonen  showed hP’s approximate matches in S from an SLP for S. Recently, Gagie et al. (S in 𝒪 (z log n) time such that later, given P and k, we can find all P’s occ approximate matches in 𝒪  + occ) time. Their algorithm works by extracting the m + k and m + k − 1 characters before and after each LZ77 phrase boundary, respectively, and then continuing as with the algorithm by Bille et al.  bits and returns the locations of all P’s occ occurrences in S in 𝒪 (m log m + occ log log n) time. These indexes require no assumptions about the pattern.Kärkkäinen and Ukkonen  gave the Navarro  modifiedo et al.  and Do eo et al.  gave indo et al.  and Takao et al.  gave indo et al. . Gagie eo et al.  recentlyq − 1 characters, where q is a parameter. If P has length exactly q, then their index returns the locations of all P’s occurrences in S in optimal 𝒪 (m + occ) time. If we are given an upper bound M on the pattern length at construction time, then even with Kärkkäinen and Ukkonen’s original version, we need keep only a kernel of the text and can use 𝒪 (z log n + zM log σ) bits in total, where σ is the size of the alphabet. We suspect this escaped investigation for so long because it seemed too obvious and inelegant to be theoretically interesting, and the need to index massive, highly repetitive datasets in practice has become pressing only since the development of next-generation sequencing methods.Kärkkäinen and Sutinen  gave an q-grams or seeds. Danek et al.’s index for the database for the 1000 Genomes Project is the first one to fit in the memory of a commodity personal computer. Ferrada et al. (The use of kernelization for indexing was eventually investigated by Schneeberger et al. , althouga et al.  emphasizThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Co-occurrence of aggression and anxiety might change during adolescence, or stay stable. We studied change and stability of four types of co-occurrence regarding direct aggression and anxiety in adolescence: an anxious and non-aggressive type, an aggressive and non-anxious type, a comorbid aggressive-anxious type and a no problems type. We applied a person-centered approach to assess increases and decreases of these types, and tested various models of intra-individual change of the types: the stability, acting out and failure models. We used data from a five-wave study of 923 early-to-middle and 390 middle-to-late adolescents , thereby covering the ages of 12–20. We observed accelerated development in the older cohort: adolescents tended to grow faster out of the aggressive types in middle-to-late adolescence than in early-to-middle adolescence. We observed one other group-dependent pattern of heterogeneity in development, namely “gender differentiation”: gender differences in aggression and generalized anxiety became stronger over time. We found support for two perspectives on intra-individual change of the four types, namely the stability and the acting out perspective. The no problems—and to a lesser extent the anxious—type proved to be stable across time. Acting out was found in early-to-middle adolescents, males, and adolescents with poorer-quality friendships. In all three groups, there were substantial transitions from the anxious type to the aggressive type during 4 years (between 20 and 41 %). Remarkably, acting out was most prevalent in subgroups that, generally speaking, are more vulnerable for aggressive behavior, namely early-to-middle adolescents and males. We interpret acting out as the attempt of adolescents to switch from anxiety to instrumental aggression, in order to become more visible and obtain an autonomous position in the adolescent world. Acting out contributed to the explanation of accelerated development and gender differentiation. We also observed an increase of adolescents with no problems. These findings highlight that the co-occurrence of aggression and anxiety changes considerably during adolescence, but also that the anxious and no problems types are quite stable in this period. Aggression and anxiety co-occur in childhood and adolescence. According to a recent review Granic , rates oWe will focus on direct aggression  and generalized anxiety disorder . For a number of reasons, we decided to use specific conceptualizations of aggression and anxiety. For instance, many studies have shown that direct aggression differs from other forms of aggression. It is conceptually different from indirect and relational aggression  and explored a number research questions when it was not possible to formulate hypotheses.First, we addressed age, gender, and friendship differences in development of direct aggression and generalized anxiety disorder. Our first hypothesis (H1) originates from the review of research into normative development of direct aggression and generalized anxiety disorder in adolescence, and predicts a regular decrease of the aggressive type over time in adolescence, along with an increase of the anxious type in middle-to-late adolescence. We tested H1 for two cohorts: early-to-middle and middle-to-late adolescents. We explored increases and decreases of the strong co-occurrence type, the comorbid aggressive type. The second hypothesis (H2) addressed gender differences. In general, the studies of our literature review reported higher levels of direct aggression  with an average age of 12.4 years (SD = .59) at baseline, and a middle-to-late adolescent cohort  with an average age of 16.7 years (SD = .80) at baseline. Because both age groups were assessed during five measurement waves, a total age range from 12 to 20 years was available. The early-to-middle adolescent cohort consisted of 468 boys (50.7 %) and 455 girls (49.3 %), and the middle-to-late adolescent cohort consisted of 169 boys (43.3 %) and 221 girls (56.7 %). A more detailed description of the sample can be found in Meeus et al. Data for this study were collected as part of an ongoing Dutch research project on COnflict And Management Of RElationships (CONAMORE), with a 1-year interval between each of the five available waves. The longitudinal sample consisted of 1313 participants, divided into an early-to-middle adolescent cohort (2 (χ2/df) of 1.14, p > .05, which, according to Bollen  procedure. Little’s Missing Completely At Random (MCAR) test produced a normed χo Bollen , indicatParticipants and their parents received an invitation letter describing the research project and goals and inviting them to participate. More than 99 % of the families who were approached signed the informed consent form. During regular annual assessments, participating adolescents completed questionnaires at school or at home. Confidentiality of responses was guaranteed. Adolescents received €10 (approximately US $13) for each wave in which they provided data.The 9-item Generalized Anxiety Disorder symptoms scale (from now on GAD) of the original 38-item SCARED  was employed in this study. This scale has been regularly used in developmental psychopathology studies of adolescents from the general population   to 5 (more is not possible). Examples of items are “Does your best friend like or approve of the things you do?” (support), “Do you and your best friend get on each other’s nerves?”(negative interaction), and “How often does your best friend tell you what to do?”(power). Internal consistencies were high, with alphas ranging across waves from .82 to .93 for support, negative interaction and power. Since we aimed to study the moderating role of best friendship quality in the development of aggression/anxiety, we used Latent class growth analysis (LCGA) to distinguish between higher- and poorer-quality friendships across the five waves. We estimated levels and linear and curvilinear changes of the three dimensions. We found a two-class solution to be superior to the one-class solution according to the bootstrapped VLMR-LMT test (p < .001). Entropy (E) of this solution was good, at .91. To avoid a large number of transitions with very low or zero cell frequencies in the latent transition (LTA) models, we decided to continue with the two-class solution and not to test for additional three or more class models. A majority of the 1045 respondents (79.4 %) was classified in the higher-quality friendship class, and 268 (20.6 %) in the poorer-quality friendship class. The higher-quality friendship class showed greater levels of support, lower levels of negative interaction, and lower levels of power, as compared to the poorer-friendship quality class.The Network of Relationships Inventory (NRI)  and latent transition analysis (LTA). LCA is a group-based, person-centered analytic strategy that is a confirmatory version of cluster analysis. LTA represents a longitudinal extension of LCA. LTA calculates increases and decreases in class size across time, as well as patterns of stability and change over time in the form of movement or transitions between classes . LTA offers two types of structural parameters: (a) varying numbers of participants in a class across waves, indicating increase or decrease in class size over time, and (b) transitions of individuals between classes that explain these changes in class size. Note that the transitions indicate patterns of intra-individual change in aggression/anxiety types. LTA is therefore appropriate for evaluating stability or change of the aggression/anxiety types over time, and the aggression/anxiety types transitions that explain stability and change over time.We analyzed our data in three steps. First, we applied cross-sectional LCA to explore the number of classes (aggression/anxiety types) within each of the five waves. We found four classes in each of the waves. BIC of four-class solutions was at least 257.22 lower than that of one-, two-, and three-class solutions. Second, we select the best-fitting, five-wave LTA model in a number of successive steps. We found that a stationary, three-covariate LTA model provided the best fit to the data. BIC’s for the three-covariate model, and the no-covariate model were 10,541.02, and 10,677.21, respectively. This model suggests that adolescents regularly made transitions between aggression/anxiety types across waves, and with the same probability. Additionally, the regular pattern varied by age groups, gender, and best friendship groups. In sum, age groups, gender, and best friendship groups were moderators of these developmental processes. Entropy of the final model was very good (.87). Third, we applied Bayesian evaluations of the contingency tables generated by the final LTA model. LTA results can be converted into contingency tables that summarize the prevalence of classes (co-occurrence types) across waves. We use Bayesian Model Selection with (in)equality constraints between the parameters of interest .Transition probabilities of stability of the aggression/anxiety types across 4-year intervals, as found in the final stationary model, are presented in Table early-to-middle [.05] < GAD → DAearly-to-middle [.20]), whereas both failure and acting out were not apparent in middle-to-late adolescence (DA → GADmiddle-to-late = GAD → DAmiddle-to-late [≤.05]). We applied Bayesian Model Selection to test three alternative models of age group differences of failure and acting out in waves 1 and 5. Model 1 assumed no cohort differences in failure and acting out. Model 2 assumed probabilities of failure to be lower than probabilities of acting out in the younger age group, as compared to no differences in probabilities in failure and acting out in the older age group. Model 3, the unconstrained model, did not specify any constraints of failure and acting out across age groups. Model comparisons showed that Model 2, the “acting out in early-to-middle adolescence model”, was by far the best-fitting model (see Table early-to-middle [.20] > GAD → DAmiddle-to-late [.01]). A follow-up set of Bayesian models confirmed this to be the case , whereas both failure and acting out were not apparent in females  . A follow-up set of Bayesian models confirmed this to be the case , whereas both failure and acting out were not apparent in higher-quality friendships (hqf) (DA → GADhqf = GAD → DAhqf [≤.06]) (see Table pqf = .25) than higher-quality friendships (GAD → DAhqf = .06). A follow-up set of Bayesian models confirmed this to be the case  (DA → GAD DApqf .2), wherea DApqf .2), whereaThe present longitudinal research set out to examine the development of co-occurring direct aggression and generalized anxiety disorder during adolescence. To what extent are adolescents aggressive, anxious, or show a combination of both high aggression and anxiety? We studied whether these co-occurrence patterns remain stable or change during adolescence. Do anxious adolescents “act out” and become aggressive over time, as the acting out model would suggest . Remarkably, acting out was most prevalent in subgroups that, generally speaking, are more vulnerable for aggressive behavior, namely early-to-middle adolescents and males.Acting out can be seen as a mechanism that contributes to the explanation of the two observed processes of developmental heterogeneity in aggression and generalized anxiety: accelerated development in middle-to-late adolescence and gender differentiation. Accelerated differential development was visible in accelerated decrease of aggression in middle-to-late adolescence and not in early-to-middle adolescence. Acting out indexes growing from the anxious type into the aggressive type, and therefore partly prevents a decrease of the aggressive type in early-to-middle adolescence. This prevention effect of acting out is no longer active in middle-to-late adolescence. Thus, acting out partly explains an accelerated decrease of the aggressive type in middle-to-late adolescence. Additionally, acting out was a building block of gender differentiation. Acting out was present in males and not in females. Acting out implies growing into the aggressive type, and therefore partly explains the increase of the aggressive type in males and not in females. Thus, acting out partly explains gender differences in aggression that grow during adolescence.The percentages of acting out  in early-to-middle adolescents, males, and adolescents with poorer friendships were rather substantial, and ranged between 20 and 41 %, respectively . Therefore, the aggression/anxiety types were not the outcome of overlapping and biased self-reports.A third limitation has to do with our quite specific conceptualization of aggression and anxiety behaviors. This calls for replication of the present study with various other measures of internalizing and externalizing problems.A fourth limitation is that we are unable to compare our findings on stability of the types with those of the earlier studies. This is simply due to the fact that the earlier studies did not present percentages of stability in these co-occurrence types.Clinical implications of the present study are twofold. First, generalized anxiety seems to be a more persistent risk factor for adolescents’ future than aggression. We found intra-individual stability of the anxious type to already be substantial in early-to-middle adolescence (.58 across 4 years). Both findings underscore the need and possibility for early identification of generalized anxiety. This is especially because we also know that early intervention for generalized anxiety can be successful and more cost-effective than clinical treatment , whereas the anxious type increases regularly during the entire adolescent period. We found substantial support for the acting out perspective. We interpreted acting out as the attempt of adolescents to switch from anxiety to instrumental aggression (Kunimatsu and Marsee


Nucleic Acids Res. (2014) 42 (16): 10832–10844. doi: 10.1093/nar/gku764The authors wish to apologize for errors in the last paragraph of the DISCUSSION section in this paper. The “RNA DQ” should read as “intramolecular RNA G-quadruplex (RQ)” at its first appearance and as “RQ” at the followings. The “DNA DQ” should all read as “DQ”.With these corrections, the correct version appears below (starting from “Alternatively…”).3 loop and bulge, the RQ might also be unstable as was the DQ. With the participation of G3 tracts from the DNA and RNA, the HQ of three G-quartets was much more stable and should be more competitive to form and to play a role in transcription termination.Alternatively, the RNA could also form an equivalent intramolecular RNA G-quadruplex (RQ) of three G-quartet layers by using the 13G-15G as the non-template DNA strand did in this work. However, the mutation in the 13G-15G in our work is expected to disrupt (M14/16) or promote (M3G) the formation of RQ, respectively, as to the DQ. But these showed little effect on the termination . This suggested that the RQ was largely irrelevant to the termination. On the other hand, because of the bulky T


Since high-intensity aerobic exercise depends on such physiological factors, it has been hypothesized that IPC can also improve exercise performance. Although some studies confirmed this hypothesis (Salvador et al. 2 and muscle deoxygenation during square-wave transitions from low- to moderate-intensity and from moderate- to severe-intensity cycling exercise. Besides, authors assessed the effect of IPC on the time to exhaustion in the severe-intensity workload. Authors found that IPC increased the time to exhaustion, which supports an increase in exercise performance. Furthermore, IPC did not change the pulmonary V̇O2 kinetics, but changed the kinetics of muscle deoxygenation. These findings are original and advance the knowledge about the effect of IPC on exercise physiology. However, some aspects of the experimental protocol and data analysis deserve attention to interpret these findings.In this context, a recent study by Kido et al.  examined2 kinetics. Nevertheless, repetitions of exercise transitions are crucial to increase the signal-to-noise ratio. This was proposed by Lamarra et al. (L is a constant that depends on the value of the underlying time constant; SD is the standard deviation of the breath-by-breath fluctuation in V̇O2; ΔV̇O2 is the V̇O2 amplitude above the baseline level; and n is the number of exercise transitions. Based on this equation, typically, four to eight exercise bouts are used for moderate-intensity transitions and two to four exercise bouts are used for severe-intensity transitions (Poole and Jones 2 kinetics.Authors used just one exercise transition to calculate the pulmonary V̇Oa et al. , who des2, the kinetics of muscle deoxygenation was changed by IPC. Muscle deoxygenation, as measured by near-infrared spectroscopy, is a proxy of muscle oxygen extraction. Thus, a change in this variable should influence the pulmonary V̇O2 kinetics, which was not observed, maybe due to the aforementioned limitation on the V̇O2 kinetics analysis. Noteworthy, authors investigated the effect of IPC on work-to-work transitions, and it is known that the phase II of pulmonary V̇O2 kinetics is slowed when high-intensity exercise is initiated from a moderate-intensity work rate in comparison with a rest-to-work transition (Dimenna et al. Despite the fact that authors did not find an effect of IPC on the kinetics of pulmonary V̇OSpecifically regarding the muscle deoxygenation, authors concluded that IPC accelerated its kinetics in the transition from low- to moderate-intensity exercise, but did not change the kinetics in moderate- to severe-intensity exercise. Moreover, the amplitude of the deoxy-Hb/Mb response in the low- to moderate-intensity exercise was reduced by IPC, whereas IPC did not change the amplitude in the moderate- to severe-intensity exercise. However, as the amplitude of the deoxy-Hb/Mb was reduced in the low- to moderate-intensity exercise, the baseline value for the moderate- to severe-intensity exercise was consequently reduced, which may have compromised the interpretation about the kinetics of deoxy-Hb/Mb in the moderate- to severe-intensity transition. In addition, the amplitude of deoxy-Hb/Mb response during exercise was analyzed relative to the plateau value during a 10-min arterial occlusion. But, authors did not report the values obtained during this maneuver. Were these values affected by the IPC? If these values were affect, does it explain the difference in amplitude during exercise? Alternatively, if data were normalized by the resting baseline value, would the interpretation be similar? At last, the time delay, time constant, and mean response time were calculated from data normalized by the end exercise amplitude. Would the interpretation be similar if the analysis was done from data normalized by the resting baseline value or by the plateau during the 10-min arterial occlusion?2 utilization and delivery in the microcirculation via near-infrared spectroscopy. First, Barbosa et al. (Besides Kido et al. , two stua et al.  studied a et al.  then repa et al.  and Patta et al.  (i.e., la et al.  (i.e., ha et al. . Thus, fa et al. .


Electronic cigarettes (e-cigarettes) have risen in popularity in the U.S. While recent studies have described the prevalence and demographics of e-cigarette users, few studies have evaluated the impact of advertising on perceptions and interest in trial. This pilot study was conducted to assess whether exposure to ads for e-cigarettes or a comparison product (snus), elicited differences in interest to try e-cigarettes between smokers and non-smokers.A web-based survey was completed by 600 respondents, aged 18–65, recruited from an internet panel in the U.S. Respondents answered questions assessing tobacco use, and then viewed nine magazine ads for Blu e-cigarettes or Camel snus, a low-nitrosamine smokeless tobacco product, in random order. After viewing each ad, respondents were asked a series of questions about their perceptions, beliefs, attitudes, and interest in trial. At the end, respondents were asked to choose a free sample product from the following options: an e-cigarette, smokeless tobacco (SLT), pack of cigarettes, or no product.p-value < 0.001). Six percent of non-smokers exposed to e-cigarette ads reported interest in trying e-cigarettes. E-cigarettes were the most popular product selected to sample (34 %), followed by cigarettes (8 %) and SLT (3 %); 331 respondents (55 %) chose no product. Participants randomized to the e-cigarette ad group were significantly more likely to choose an e-cigarette at product selection . Within the e-cigarette condition, 71 % of smokers selected an e-cigarette at product selection, compared to 25 % of non-smokers; smoking status was significantly associated with sample product selection .Ad receptivity scores did not appear to be influenced by ad theme; differences existed between smokers and non-smokers. Participants exposed to e-cigarette ads more frequently reported favorable product attitudes compared to participants exposed to snus ads. Cigarette smokers in the e-cigarette condition were more likely to report interest in trying e-cigarettes compared to non-smokers in that condition  contains supplementary material, which is available to authorized users. E-cigarettes are a novel phenomenon. These devices provide nicotine to users in the form of an aerosol vapor, which is promoted as a reduced risk form of delivery. Awareness of e-cigarettes and other electronic nicotine delivery devices is increasing. Recent nationally representative studies conducted among the U.S. adult general population have shown that awareness of e-cigarettes has risen from approximately 40 % in 2010, to nearly 60 % in 2011 .The increased awareness of e-cigarettes may be linked to a corresponding increase in media presence; including ads in magazines, television, and strategic product placement of e-cigarettes in Hollywood productions. For example, e-cigarettes have been used by celebrities in commercials, print ads, movies, and television shows . AvailabWhile e-cigarettes may be beneficial for individual smokers as a harm reduction device, it is yet unclear if these devices yield a positive or negative public health impact. The use of e-cigarettes as a complete replacement for conventional cigarettes or as a quit aid could result in a net public health gain , 14. HowEvidence from multiple U.S. Surgeon General’s reports support the notion that tobacco advertising and promotion can influence risk perception, trial, and use of tobacco products in both adults and youth –18. SuchWhile an increasing number of recently published studies have described awareness and use of e-cigarettes –3, very This pilot study aimed to explore issues related to e-cigarette advertising and the potential impact such advertisements may have on the public’s willingness to try e-cigarettes among current smokers and non-smokers. Namely, we sought to assess whether exposure to ads for e-cigarettes or a comparison product (snus), showed differences in interest to try e-cigarettes among both cigarette smokers and non-smokers.http://www.lightspeedgmi.com/). Eligible participants answered a series of preliminary questions to confirm that they were between ages 18 and 65, current United States residents, and able to read and write in English. After determining eligibility, participants were directed to an informed consent screen, clicking a button indicating consent. Respondents completed a core series of questions adapted from a similar study assessing tobacco use, past quit attempts, use of nicotine replacement therapies, and knowledge, attitudes, and beliefs about nicotine-containing products , even once?” and currently reported using the tobacco product every day or some days. “Ever users” for a tobacco product were defined as those individuals who responded “Yes” to the question, “Have you ever used [tobacco product], even once?”, and currently reported not using the product at all. “Never users” for a tobacco product were defined as those individuals who responded “No” to the question, “Have you ever used [tobacco product], even once?” In analyses examining differences between current cigarette smokers versus current non-smokers, “ever” and “never” smokers were combined into one category.For each individual ad, we asked the series of statements shown in Table We employed two different measures to assess interest in trying e-cigarettes within our sample. The first measure, “intention to try”, was based on the statement: “Based on what I just saw, I think this product is something I want to try.” . To keep our analysis succinct, we opted to recode this Likert measure into a binary variable. The answer options “strongly agree” and “agree” were combined to indicate “intention to try”, while the remaining options were combined to indicate “does not intend to try”.The second measure, labeled “willingness to receive a free product”, was derived from the question administered for product selection by respondents, which stated, “If we had the opportunity to send you a free sample of one of the products listed below, which of the products would you choose?” .d is reported for effect sizes related to independent samples t-tests. Results are reported for four groups of interest: Smokers who viewed ads for e-cigarettes, non-smokers who viewed ads for e-cigarettes, smokers who viewed ads for snus, and non-smokers who viewed ads for snus.Descriptive analyses were performed on these pilot data. Pearson chi-square tests were conducted to assess associations between demographic variables, smoking status and main outcome measures . Demographic measures included age group , gender , level of education , and racial self-identification . Independent samples t-tests  were used in comparing mean ad receptivity scores, grouped according to cigarette smoking status (current smoker versus current non-smoker) Cramer’s V is reported for effect sizes related to Pearson chi-square tests, while Cohen’s χ2 = 144.692, p-value < 0.001; Cramer’s V = .491). Current smokeless tobacco use among current cigarette smokers was 17 %, while 4 % of current non-smokers reported use of smokeless tobacco . Ten percent of the total sample reported using more than one tobacco product, while nearly 20 % of our sample consisted of individuals who have at least tried an e-cigarette one time .A total of 46,561 e-mail invitations were sent to GMI panelists, inviting them to take part in the survey. 875 individuals began the survey, of which 600 completed the survey in full Table . Most paχ2 = 46.237, p-value < 0.001, Cramer’s V = .278). Table χ2 = 31.117, p-value < 0.001, Cramer’s V = .322). Similar trends were observed among smokers and non-smokers within the snus comparison condition. Among all non-smokers in either condition, more favorable perceptions were observed for e-cigarettes compared to snus.Participants were asked to respond to a set of questions assessing attitudes about the product shown in their exposure condition (e-cigarette or snus) displayed in Table p-value < 0.001, Cohen’s d = 0.872). In the snus comparison condition, the combined mean ad receptivity score for smokers was 113.41 (SD = 45.10), compared to 98.92 (SD = 45.25) for non-smokers. We observed a positive, weak relationship between snus ad receptivity and smoking status (t(298) = 2.561, p-value = .011, Cohen’s d = 0.297). Mean ad receptivity scores among smokers in the snus condition ranged from 37.51-38.30, while mean ad receptivity scores among smokers exposed to e-cigarette ads ranged from 45.68-47.09.Figure χ2 = 91.95, p-value < 0.001, Cramer’s V = .554). Among all participants in the snus comparison condition, 10 % reported that they intended to try snus and a weaker, yet statistically significant association was observed between smoking status and intention to use snus .In the combined sample, 94 respondents (16 %) reported that the product shown in their exposure grouping (snus or e-cigarettes) was “something I want to try” Fig.  Among alχ2 = 10.59, p-value = 0.014, Cramer’s V = .133). Within the e-cigarette condition, smokers more frequently selected an e-cigarette at product selection, compared to non-smokers . Within the snus condition, e-cigarettes remained the most frequently selected tobacco product among responders, with smokers more frequently reporting this choice than non-smokers. Product choice in the snus condition was significantly associated with smoking status .In the product selection task, over half of the sample (55 %) elected to not be sent a free sample product. E-cigarettes were the most frequently selected tobacco product among all participants, with 34 % reporting this choice. Selection of smokeless tobacco and cigarettes among sample members was low . Participants exposed to e-cigarettes ads were more likely to select an e-cigarette as their hypothetical free product (39 %) compared to participants who saw ads for snus (28 %). In comparing ad exposure conditions, we observed a statistically significant association between ad exposure grouping and product choice . One-quarter of non-smokers in the e-cigarette condition selected the e-cigarette as their sample product; 3 % of which previously reported intention to try the product after being shown ads for e-cigarettes. These findings among non-smokers in the e-cigarette condition were not statistically significant. In the snus comparison condition, we did not observe any significant associations between product selection and intention to try e-cigarettes among smokers. Among non-smokers in the snus condition, 5 % of non-smokers previously reported intention to try snus, while 4 % selected smokeless tobacco during product selection. Nearly 16 % of non-smokers in the snus condition chose an e-cigarette during product selection. We observed a statistically significant association between product choice and intention to try snus among non-smokers in the snus condition .In total, 16 % of respondents reported that they intended to try the product shown in their exposure condition. Forty-five percent of respondents elected to receive a sample product . Among smokers in the e-cigarette condition who reported intending to try an e-cigarette, 90 % selected the e-cigarette as their sample product, while 10 % selected another option. Among smokers in the e-cigarette condition who did not report intending to try an e-cigarette, 46 % selected the e-cigarette as their sample product, while 53 % selected another option  that may enhance appeal as a product that may reduce harm to health. Such aspects are not currently addressed by the data presented in this report, and should be studied in greater detail.These data suggest that more favorable perceptions toward e-cigarettes existed among all participants, but particularly among current cigarette smokers, who rated e-cigarette ads, interest in trial, and attitudinal measures on e-cigarettes more favorably when compared to snus, a similarly marketed harm reduction product. Smokers exposed to either form of advertising overwhelmingly chose the e-cigarette in the product selection task, yet this was much more frequently observed among smokers in the e-cigarette condition. This product selection occurred over other options, one of which was a pack of cigarettes. Such findings may suggest that e-cigarettes, often proposed as a product that may reduce harm to health, appear to be more favorable to smokers than snus, another frequently proposed harm reduction product. These pilot data do not measure specifically why this may be the case. Snus is a smokeless tobacco product, possessing a different mode of administration for nicotine than e-cigarettes, and smokeless products currently carry health warning labels as mandated by law. Our findings also support the notion of snus posing relatively low appeal to smokers for harm reduction, as demonstrated through previous studies , 35. FacWhile we observed more favorable ad receptivity scores for e-cigarette ads compared to snus among smokers, ad receptivity for either tobacco product was relatively similar among non-smokers in both conditions. Additionally, non-smokers in our study generally did not report intention to use either of the products they were exposed to, with 6 % of non-smokers in each group reporting intention to try the product after viewing ads. In the product selection task, non-smokers were more likely to reject the offer of a free sample tobacco product, compared to smokers. Interestingly, a small proportion of non-smokers who did not previously report intention to try e-cigarettes prior to the offer of a free e-cigarette opted to select a free sample e-cigarette. The broader implications of these findings among non-smokers are unclear. With the limited offering of products during product selection, coupled with the absence of measures to indicate reasons for selection of a particular product or participant follow-up over time, we cannot be sure whether non-smokers in our sample chose a free tobacco product for personal use or for some other reason. Future studies should examine such reasons in greater detail.Our data did not allude to particular advertisement themes  having a strong association with either use intention to use or willingness to receive a free product. It could be that other elements of advertisements not addressed in this study could play a determining factor in influencing interest in these products, a few of which have been demonstrated in other studies. For example, Pepper et al.  conducteThere are potential negative and positive public health impacts of widespread promotion and advertising of e-cigarettes. If e-cigarettes are deemed by the FDA as a potentially reduced exposure product or a smoking-cessation aid, then advertising targeted to smokers to switch to these products completely for harm reduction or cessation could be beneficial for overall public health. The data for this study showed that smokers were interested in receiving a free sample e-cigarette, regardless of advertising condition; the data also showed that 3 % of non-smokers in the e-cigarette condition displayed interest in trying e-cigarettes. Yet, when offered a free sample tobacco product, 25 % of non-smokers in the e-cigarette condition selected an e-cigarette. The current marketing environment for e-cigarettes is saturated with promotions and price discounts for these products. Such an environment could result in a greater proportion of non-tobacco users to consider trying e-cigarettes. While our data do not directly speak to increased uptake among non-tobacco users, our findings suggest low interest, and more extensive research is needed to determine the appeal of e-cigarettes to nonusers of tobacco.The findings from our pilot study are subject to limitations. Primarily, this study was conducted among a fairly small sample recruited from an opt-in panel of internet users. When compared to the U.S. general population, our sample members more frequently reported having a college degree , were more likely to identify as being White, non-Hispanic , and had higher rates of cigarette  and smokeless tobacco use  . This afContinued promotion and advertising may peak public interest in e-cigarettes compared to snus, and may have an impact on willingness to receive promotional products or intention to try e-cigarettes. Our study found that e-cigarette advertising may influence intention to try these products, particularly among current smokers. In addition to the absence of an established safety profile and regulation on the quality of e-cigarettes, additional considerations about product advertising should be considered in developing future regulatory actions.


In the linear regime, a spiral interference pattern containing phase defects is visible. In the nonlinear (superfluid) regime, the interference disappears and eight vortices appear, minimizing the energy while conserving the quantized angular momentum. The radial position of the vortices evolves in the region between the two pumps as a function of the density. Hydrodynamic instabilities resulting in the spontaneous nucleation of vortex-antivortex pairs when the system size is sufficiently large confirm that the vortices are not constrained by interference when nonlinearities dominate the system.Exciton-polaritons are light-matter mixed states interacting via their exciton fraction. They can be excited, manipulated, and detected using all the versatile techniques of modern optics. An exciton-polariton gas is therefore a unique platform to study out-of-equilibrium interacting quantum fluids. In this work, we report the formation of a ring-shaped array of same sign vortices after injection of angular momentum in a polariton superfluid. The angular momentum is injected by a  Quantized vortices have been extensively investigated in different fields of physics, such as superconductivity4581011121315et alet alSeveral schemes to produce vortices and vortex lattices have been proposed and implemented. Liew ℓ. Note that self-ordered, same-sign vortex lattices have been theoretically predicted in Ref. In this work, as a first step towards the physics of rotating polariton quantum fluids, we theoretically propose and experimentally implement a scheme that generates stable chains of same-sign vortices in a coherently driven polariton superfluid. The global angular momentum is injected by mean of a Laguerre-Gauss (LG) laser beam with orbital angular momentum These characteristics are close to those of cold atom condensates29303126ωlaser − ωpol, where ωlaser and ωpol are respectively the pump and bare polariton energies at normal incidence k = 0 μm−1. A single-mode, polarization-preserving fiber selects the TEM00 mode. The polarization is linear  after the fiber and the remaining polarization fluctuations are cut by a polarizing beam splitter (PBS). As visible in We consider a planar semiconductor microcavity in the strong coupling regime, where exciton-photon coupled states (i.e. polaritons) are created by a laser excitation. We make use of a CW single mode, frequency-locked Ti:Sa laser to resonantly excite the cavity. Resonant pumping creates a low-density exciton gas, which allows us to neglect interactions between polaritons and the exciton reservoir, in contrast with experiments performed under non-resonant pumpingℓ = 8 and a Gaussian (G) beam of zero orbital momentum at the center. Both the spot size and the intensity of the laser beams are fully determined by the hologram. The LG-beam diameter is chosen to be larger than the waist of the G-beam. As a result, their spatial overlap is small, allowing for the interference to be very weak. To avoid spin-dependent phenomena, the  beam of orbital momentum λ-GaAs planar microcavity containing three GaAs-InGaAs quantum wells, with a polariton Rabi splitting of 5.1 meV. The cavity finesse is F = 3000, which results in a polariton linewidth of about 0.1 meV. The cavity is wedged in one direction, providing a large choice of cavity-exciton detunings by pumping at different positions in the sample. In order to enhance the polariton-polariton interactions, we use a cavity-exciton detuning of δ = Cω − Xω = 1 meV (XωC)( is the excitonic (cavity) energy at normal incidence, k = 0 μm−1), thus increasing the exciton fraction of polaritons and, consequently, the nonlinear effects. The microcavity is cooled down to 5 K in a cryostat and the measurements are taken in transmission. Above a critical value of Δ, a bistable behavior appearspI = 300 mW, we modify Δ. We consider three different cases: low density  in 2 = 0.4 meV, point (ii) in 3 = 0.7 meV, point (iii) in The sample is a 2The detection is simultaneously made in energy and in real- and momentum space. An objective collects the sample emission. CCD cameras are used for direct imaging of the real- and the momentum space, while the energy (wavelength) is measured with a spectrometer. We only collect circularly-polarized light, therefore filtering out any residual spin-flip effect. The polariton phase is measured with an off-axis interferometry setup: a beam splitter divides the real-space image into two parts, one of which is expanded to generate a phase reference beam. The selection of the Gaussian part at the center of the image ensures a flat phase reference, which is used to make an off-axis interference pattern. With this method, the vortex position in the image is independent of the phase of the reference beamP(r) = LGP(r) + GP(r) with A1 and A2 are the amplitudes of the pumping lasers, with σ1 = 5.0 μm and σ2 = 3.0 μm. Direct comparison with the experiments is then performed by extracting the steady-state density |ψ|2 and phase arg(ψ).In order to describe the configuration under study, we numerically solve the driven-dissipative Gross-Pitaevskii equation, which in the parabolic approximation reads1 ≈ 0 meV), we observe - both experimentally (2 = 0.4 meV (point (ii) in 20ℓ single-charged vortices from a pump with angular momentum ℓ is a manifestation of the quantum nature of the polariton fluid, in analogy to the formation of the Abrikosov lattice from a single highly-charged vortex.In the linear regime  = ρ1/2[P1(r)/A1 + P2(r)/A2] is the Thomas-Fermi density profile induced by the pump, ri = R is the position of each vortex in the chain, and R that minimizes the energy, R0, can then be extracted by minimizing the total energy E[R] = Ekin + Eint and taking the physically relevant solution of the condition δE/δR = 0, whereE as a function of R for different values of ξ ~ ρ−1/2. We observe that R0, the value of R that minimizes the energy, increases as the value of ξ (ρ) is decreased. Since ρ increases with Δ, ξ decreases with Δ; it follows that R0 increases with Δ. R0 as a function of ρ calculated by this method and the comparison with experimental data. As expected, the higher the density, the further from the center the vortices migrate. This behavior and the agreement between the variational method and experiment are a clear indication of the phase freedom obtained when interactions dominate, a feature that is independent from the optical interference.It is important to remark that the spatial freedom of the vortices provides a quantitative test of the model given below. As predicted by our model, we observe that the vortices in the nonlinear case exhibit a radial phase freedom, while their azimuthal position is locked by the pump phase. Their radial position is modified as the density 3 = 0.7 meV (point (iii) in ξ, we observe the spontaneous nucleation of vortex-antivortex pairs. Four pairs are experimentally visible in ℓ = 0 caseIn the upper bistability branch, the polariton energy is renormalized through self-interaction to the pump energy, so that the pumping is resonant and yields high polariton densities. This is not the case in the lower bistability branch, where the pumping is not resonant and thus inefficient. For large Δ, the low pump intensity regions in the lower bistability branch are off-resonant, as can be seen in In the present work, we resonantly inject polaritons with a given total angular momentum and observe the formation of a ring of quantized single-charged vortices. For the first time, a regular ring pattern of elementary vortices of the same sign is reported in a polariton superfluid. In the superfluid regime, the radial position of each vortex is not determined by the pump but rather depends on the polariton density. Experimental and theoretical indications of this behavior, due to strong nonlinear interactions, are provided through the system hydrodynamical characteristics. The mechanism leading to the creation of vortex chains results from the combination of the saturation of the radial counterflow instability with the injection of angular momentum in a limited region of space. Let us note that this general behavior was experimentally and theoretically verified to be the same if the number of injected vortices is changed, whether odd or even. We expect that the present scheme will pave the stage to study a series of new vortex collective phenomena that have been observed in cold atom BEC3435φLG = ℓφ [2π], where  are the polar coordinates in the SLM plane. However, imposing this phase on the SLM produces a superposition of φLG + G = ℓφH(r − r0) + π(1 − H(r − r0)), where H(r) is the Heaviside distribution and r0 is a constant determining the LG/G intensity ratio. The resulting hologram is presented in Collimated Laguerre-Gauss beams are a class of modes possessing a simple phase profile with radial invariance. The phase profile of a π). This vertically deviates the first order reflection forming the pump, allowing us to block the zero-order reflection. The final hologram is presented in A small fraction of the light is not modified by the SLM, for which it acts like a mirror. To separate this from the desired mode a grating hologram (T.B. performed the experiment, analyzed the data and wrote the manuscript. H.T. and D.S. performed the simulations and wrote the manuscript. Q.G. and E.G. participated to the manuscript. A.B. supervised the experiment. G.M. developed the theoretical model. All authors reviewed the manuscript.


All-optical switching is the foundation of emerging all-optical (terabit-per-second) networks and processors. All-optical switching has attracted considerable attention, but it must ultimately support operation with femtojoule switching energies and femtosecond switching times to be effective. Here we introduce an all-optical switch architecture in the form of a dielectric sphere that focuses a high-intensity photonic nanojet into a peripheral coating of semiconductor nanoparticles. Milli-scale spheres coated with Si and SiC nanoparticles yield switching energies of 200 and 100 fJ with switching times of 10 ps and 350 fs, respectively. Micro-scale spheres coated with Si and SiC nanoparticles yield switching energies of 1 pJ and 20 fJ with switching times of 2 ps and 270 fs, respectively. We show that femtojoule switching energies are enabled by localized photoinjection from the photonic nanojets and that femtosecond switching times are enabled by localized recombination within the semiconductor nanoparticles. The terabit-per-second rates of optical fibres exceed the capability of electronics, but all-optical switches are needed to alleviate the bottleneck in these networks. Here, Born et al. describe such a switch using dielectric spheres, yielding femtojoule switching energy and femtosecond switching times. Logic operations are at the core of data processing, and switching is the key mechanism for logic operations. Switching is typically realized via electronics, with transistors relaying the flow of data, but there is pressure to introduce switches that can operate at optical fibre transmission rates13The AOS is a photonic analogue to the electronic transistor, as it enables nonlinear mixing of optical beams, but all-optical switching must be implemented with consideration to demands for low switching energies and ultrafast switching times5678910et al.et al.Early AOS studies focused on the development of semiconductor materials for ultrafast switching times—ideally on a femtosecond level. Charge-carrier photoinjection and recombination were applied in semiconductors having simple planar topologies, that is, bulk wafers, so the all-optical switching times were limited by bulk recombination lifetimes. It was later found that semiconductors with ultrashort lifetimes could establish ultrafast switching between coincident control (pump) and signal (probe) beams. For example, Ganikhanov et al.et al.et al.More recent AOS studies have focused the development of device geometries for low switching energies—ideally on a femtojoule level. Increased beam intensities, and enhanced mixing of beams, have been introduced through many  devices. Almeida In this study, the demands of all-optical switching, being AOS activation with femtojoule switching energies and AOS recovery with femtosecond switching times, are addressed through the development of a non-resonant AOS architecture. A nanojet focal geometry is introduced, in the form of a dielectric sphere, to focus high-intensity photonic nanojets into a semiconductor nanoparticle material system that coats the sphere. It is found that the localized photoinjection of charge carriers by the nanojet supports AOS activation with femtojoule switching energies, and the localized recombination of charge carriers in the semiconductor nanoparticles supports AOS recovery with femtosecond switching times. A milli-scale AOS architecture is demonstrated—in support of emerging optical fibre front-end systems, such as optical time-division multiplexingT, is a result of perturbations to the surface transmission, Ts, and bulk transmission, Tb. The result is seen as a transient on the total differential transmission, ΔT(t)/T≈ΔTs(t)/Ts+ΔTb(t)/Tb, with opposing polarities for the surface and bulk contributions. According to Drude theory, the pump-induced generation of the charge-carrier density, N, increases the differential surface transmission, ΔTs(t)/Ts, and decreases the differential bulk transmission, ΔTb(t)/Tb. This occurs because N decreases the refractive index near the surface, Δns(t), and increases the absorption coefficient in the bulk, Δαb(t), which modulates the total differential transmission according to18Semiconductor charge carriers that are photoinjected by a pump beam can be used to modulate a coincident probe beam. The pump-induced modulation to the probe beam's total transmission, ns is the refractive index near the surface, and δz is the photoinjection depth of charge carriers into the bulk.where ns(t) and Δαb(t) evolve in proportion to the charge-carrier density, N, which varies through time, t, along the normal dimension to the semiconductor surface, z, according toBoth Δδ(t). The initial distribution for N is an exponential decay into the semiconductor, with an initial charge-carrier density of N0 at the surface and a 1/e photoinjection depth of δz into the bulk. The photoinjection depth, δz, is defined here as a general parameter that can be less than or equal to the semiconductor's penetration depth. Given a suitable focal geometry, with tight focusing and a short depth of focus penetrating into the semiconductor, δz can be made to be less than the semiconductor's penetration depth. The boundary condition for N at the semiconductor surface adheres to D∂N/∂z=SvN, for a diffusion coefficient, D, and surface recombination velocity, Sv. Given a suitable material system, with a high density of surface states, this boundary condition can reduce the overall charge-carrier lifetime, τ, to a value below the bulk charge-carrier lifetime, τb.where the three terms on the right-hand side characterize the respective processes of photoinjection, recombination, and diffusion. Photoinjection from an ultrashort laser pulse is applied by way of the time-varying delta function, Ep, that is needed to establish the initial charge-carrier density, N0=Epη/(ħωpV), in the first term of ħ is the reduced Planck's constant, ωp is the angular frequency of the pump beam, and V≈Aφδz is the photoinjection volume set by the pump beam's cross-sectional photoinjection area, Aφ, and photoinjection depth, δz. In this study, localized photoinjection is applied by way of a nanojet focal geometry, to yield a reduced focal spot size, that is, photoinjection area, and reduced depth of focus, that is, photoinjection depth. This leads to reduced photoinjection volumes and high initial charge-carrier densities.Localized photoinjection can enable AOS activation with femtojoule switching energies, by minimizing the pump pulse energy, τ, as a result of τ=1/τb+SvR. An increase in the surface recombination velocity, Sv, or the specific surface area, that is, surface-to-volume ratio, R, has τ decrease below the bulk charge-carrier lifetime, τb. Our prior work has shown that nanoscale cylindricalR, increases the surface state density and decreases the charge-carrier lifetime. In this study, localized recombination is applied by way of a nanoparticle material system. It is typically advantageous to apply both a material system with an increased surface state density and a focal geometry that localizes photoinjection in the region of high surface state density—and this two-fold approach is taken here.Localized recombination can enable AOS recovery with femtosecond switching times, by promoting surface recombination and thus minimizing the overall charge-carrier lifetime, The all-optical switching results of this study are defined with respect to nominal tests using a standard focal geometry with a microscope objective and targets comprised of the well-established semiconductors, semi-insulating GaAs, float-zone Si and 6H-SiC, with respective wafer thicknesses of 350, 280 and 330 μm. These semiconductors are particularly advantageous for this study, given their wide range of bulk lifetimes and surface recombination velocities.T/T, for the three semiconductor targets. The negative signal polarities indicate that pump-induced modulation to the probe beam is dominated by absorption in the bulk for all three semiconductor targets, which agrees with the observed long bulk lifetimes. GaAs exhibits a picosecond-scale bulk lifetime of τb=280 ps, Si exhibits a nanosecond-scale bulk lifetimeτb=20 ns and SiC exhibits a microsecond-scale bulk lifetimeτb=20 μs. The fast transient at the onset of the SiC response is due to charge-carrier scattering. Details on the SiC charge-carrier dynamics are given in the Methods section. All three materials exhibit unacceptably slow recovery times for AOS operation, as minimal contributions are seen from surface recombination in the GaAs, Si and SiC targets, despite their wide range of surface recombination velocities, Sv=1.2 × 104 m s–1, Sv=500 m s–1 and Sv=4,000 m s–1, respectively20Aφ, and depth, δz, of the pump beam in the semiconductor establish a reduced photoinjection volume, V≈Aφδz. This leads to a large initial charge-carrier density, N0, and a small charge-carrier lifetime, τ, if the photoinjection is preferentially applied at a semiconductor surface. The nanojet focal geometry must be implemented with careful consideration to the properties of the sphere, however, as there is an inherent relationship between the photonic nanojet's intensity and the sphere's diameter, d, and refractive index, n. With this in mind, the properties of the sphere that yield the optimal nanojet are studied by way of theoretical analyses across two regimes of scale.Localized photoinjection is considered in this section, for enhanced AOS activation, by way of a nanojet focal geometry. A high-intensity photonic nanojet25n<2 for diameters d>100 μm. The curve shows that high-intensity focusing at the exit interface of the sphere is brought about the refractive index of n≈2. An intensity colourmap for this milli-scale regime is generated from the Ray theory curve and is shown at the top of the figure. The peak intensity for n≈2 is shown in white. These findings agree with limiting case of a ball lens in the thick-lens formulan≈2.In the milli-scale regime, with sphere diameters that are much larger than the wavelength, focusing is well-described by Ray theory. et al. Mie theory simulations are carried out to identify the maximum intensities at the exit interface of the sphere, intersecting with the optical axis, as a function of the sphere refractive index, n, and diameter, d. The full distribution of intensities from Mie theory is shown for the micro-scale regime as an intensity colourmap map in d<30 μm and 1.5<n<2. The trendline for maximum intensities is shown as a solid blue curve. The curve rises from a low refractive index at small diameters, n≈1.75, toward the Ray theory result at large diameters, n≈2. The highest intensities are seen as a broad band of intensities that peak at n≈1.75 for small d then rise toward n≈2 for sufficiently large d, where the Mie theory and Ray theory results merge.In the micro-scale regime, with sphere diameters that are comparable to the wavelength, it is necessary to implement a rigorous three-dimensional electromagnetic analysis. This can be done efficiently for a spherical geometry using Mie theory. Given the optical responses of Resonance manifests itself as two patterns of interferometric fringes in the intensity colourmap map for the micro-scale regime in n≈2, has a 42% reduction in the (transverse) spherical aberration, compared with that of a sphere with a refractive index of n≈1.5.Spherical aberration manifests itself as imperfect focusing at the exit interface of the sphere. This leads to an increased demand on the switching energy, as the incident beam power must be increased to compensate for the reduced intensity. Note that spherical aberration can be compensated, to some degree, in that a sphere, being approximated as a plane-parallel plate between two plano-convex lenses, will have spherical aberration be over-corrected by the plane-parallel plate and under-corrected by the lensesT/T, is shown in n=1.51, (b) n=1.76, (c) n=1.83 and (d) n=1.98. The experimental curves are shown with corresponding theoretical curves, having been generated by a Drude/charge-carrier dynamical model. The model couples the Drude theory characteristics for probe beam transmission from The measured differential transmission, Δn=1.51 sphere exhibits decreased probe transmission from pump-induced changes primarily to the absorption coefficient in the bulk—like that seen for the nominal semiconductor tests with a microscope objective. In contrast, the increasingly positive curves of the n=1.76, 1.83 and 1.98 spheres exhibit increased probe transmission from pump-induced changes primarily to the refractive index near the surface. For increasing sphere refractive indices, the preferential deposition of charge carriers near the semiconductor surface is also seen by way of reducing charge-carrier lifetimes. Charge-carrier lifetimes of τ=210, 120, 60 and 10 ps are measured for the sphere refractive indices of n=1.51, 1.76, 1.83 and 1.98, respectively. The decreasing charge-carrier lifetimes come about from a diminishing depth of focus and the corresponding preferential deposition of charge carriers at the semiconductor surface—where there exists a high surface state density and appreciable surface recombination velocity, Sv=1.2 × 104 m s–1. Curve-fitting of the Drude/charge-carrier dynamical model results to the experimental results confirms that the increasing sphere refractive indices reduce both the pump beam's photoinjection area, Aφ, and photoinjection depth, δz. For sphere refractive indices of n=1.51, 1.76, 1.83 and 1.98, the respective photoinjection depths into the semiconductor decrease, according to δz=480, 300, 180 and 70 nm, and this leads to an increase in the initial charge-carrier densities.It is apparent from the experimental and theoretical results of d=2.0 mm and refractive index of n=1.98, can support all-optical switching with femtojoule switching energies and picosecond switching times. The implementation tested here, with a GaAs target beyond the sphere, yields an ∼10-fJ switching energy  and a 10-ps switching time. It is worth noting, however, that further reductions in the switching time can be met by enhancing surface recombination, and such enhancements are explored in the following section.Given these experimental findings, it is apparent that a nanojet focal geometry, with a sphere diameter of R=12/d for a sphere. This maximization of surface-to-volume hastens the charge-carrier recombination rate, according to 1/τ=1/τb+SvR. The charge-carrier lifetime, τ, can ideally be reduced to a value well below the bulk semiconductor lifetime, τb.Localized recombination is considered in this section, for enhanced AOS recovery, by introducing a semiconductor nanoparticle material system. The introduction of semiconductor nanoparticles increases the specific surface area to its highest theoretical limit, being π steradians solid angle of the sphere.The nanoparticle material system is integrated with the nanojet focal geometry, by coating nanoparticles over the entire surface of the dielectric sphere, to form the complete AOS architecture. An AOS architecture such as this enables ease of alignment, in that the geometry inherently overlaps the coincident pump and probe foci within the nanoparticles at the exit interface of the sphere, and it also enables omni-directionality, in that the coincident pump and probe beams can be incident over the full 4The Si and SiC nanoparticles that are used have approximate diameters of 20 and 50 nm, respectively.  Spheres in the micro-scale regime, with diameters ranging from 1 to 30 μm, will require the sphere to have a refractive index along the blue curve of n≈1.75 and n≈1.83. The spheres used in the AOS architecture must be selected with careful consideration to their refractive index, Given the considerations above for nanoparticles and dielectric spheres, the AOS architecture is tested with spheres in both the milli- and micro-scale regimes using nanoparticle coatings of both Si and SiC.d=2.0 mm, being at the upper limit of the milli-scale regime, and are comprised of S-LAH79 glass, with a refractive index of n=1.98±0.02 The figure insets show a Mie theory simulation and scanning electron microscope (SEM) image of the nanoparticles.Experimental results for the milli-scale AOS architecture are shown in T/T, for all-optical switching between pump and probe beams, with Si nanoparticles. The applied Si nanoparticles have a relatively low surface recombination velocity, Sv=500 m s–1, but a noteworthy decrease in AOS recovery time is still observed—being approximately two thousand times faster than that of bulk Si. This rapid recovery is due to the promotion of surface recombination from the increased specific surface area of the nanoparticles. Ultimately, the milli-scale AOS architecture with the d=2.0-mm sphere and Si nanoparticles yields a switching time of 10 ps and switching energy estimated to be 200 fJ.T/T, for all-optical switching between pump and probe beams, with SiC nanoparticles. The applied SiC nanoparticles have a relatively high surface recombination velocity, Sv=4,000 m s–1, so a dramatic decrease in recovery time is observed—being approximately sixty million times faster than that of bulk SiC.  Ultimately, the milli-scale AOS architecture with the d=2.0-mm sphere and SiC nanoparticles meets the demands for all-optical switching, as it yields a switching time of 350 fs and switching energy estimated to be 100 fJ.d=30–40 μm, being at the upper limit of the micro-scale regime, and are comprised of N-LASF9 glass, with a refractive index of n=1.83±0.02 The figure insets show a Mie theory simulation and an SEM image of the nanoparticles.Experimental results for the micro-scale AOS architecture are shown in T/T, for all-optical switching between pump and probe beams, with Si nanoparticles. The applied Si nanoparticles again produce a noteworthy decrease in the AOS recovery time—being even faster than that of the d=2.0-mm sphere in + nm, particles that are seen to be interspersed among the 20-nm nanoparticles in SEM images. The milli-scale AOS architecture, with its larger focal spot area is unable to avoid the aggregates of larger particles, which have a smaller specific area and longer charge-carrier lifetime, and this leads to its longer recovery time. Ultimately, the micro-scale AOS architecture with the d=30–40-μm sphere and Si nanoparticles yields a switching time of 2 ps and switching energy estimated to be 1 pJ.T/T, for all-optical switching between pump and probe beams, with SiC nanoparticles. The applied SiC nanoparticles produce a dramatic decrease in AOS recovery time—being even faster than that of the d=2.0-mm sphere in d=30–40-μm sphere and SiC nanoparticles meets the demands for all-optical switching, as it yields a switching time of 270 fs and switching energy estimated to be 20 fJ.An AOS architecture was introduced in this work. A guiding principle of localization was used in the design and analysis to facilitate AOS activation with femtojoule switching energies and AOS recovery with femtosecond switching times. The AOS architecture applied a nanojet focal geometry, in the form of a dielectric sphere, to focus high-intensity beams into a nanoparticle material system, in the form of a coating of semiconductor nanoparticles. The AOS architecture was implemented on milli-scale dimensions, with Si and SiC semiconductor nanoparticles, to yield respective switching energies of 200 and 100 fJ, with respective switching times of 10 ps and 350 fs. The AOS architecture was then implemented on micro-scale dimensions, with Si and SiC semiconductor nanoparticles, to yield respective switching energies of 1 pJ and 20 fJ, with respective switching times of 2 ps and 270 fs.It was found that the AOS architecture could establish localized photoinjection of charge carriers, to enable femtojoule switching energies, and it could establish localized recombination of charge carriers, to enable femtosecond switching times. The AOS architecture met practical considerations for coupling, including beam alignment, directionality and capture cross-section, as well as practical considerations for stability, including physical and temperature sensitivity. Future applications of the AOS architecture may be implemented with consideration to coupling of the spheres to waveguides and/or fibres. Optical micro-electro-mechanical systems packaging can facilitate this integration, by way of on-chip spherical mounts based on V-grooves33353738T/T, of the probe beam is measured by time-resolved sampling as a function of the time delay between pump and probe pulses. The data are acquired with a lock-in amplifier (SR830) using a 100-ms time constant. The GaAs and Si targets use pump and probe pulses with respective wavelengths of 780 and 1,550 nm . The SiC target uses pump and probe pulses with respective wavelengths of 390 and 1,550 nm . The 780–1,550-nm pump–probe experiments with d=2.0-mm spheres use a pump–probe power ratio of 1:2. The 390–1,550-nm pump–probe experiments with d=2.0-mm spheres use a pump–probe power ratio of 1:20. The 780–1,550-nm pump–probe experiments with d=30–40-μm spheres use a pump–probe power ratio of 3:1. The 390–1,550-nm pump–probe experiments with d=30–40-μm spheres use a pump–probe power ratio of 1:1. For these pump–probe conditions, the pump photon energy is above-bandgap and the probe photon energy is below-bandgap. This leads to probe-power-independence for all reported results, that is, multi-photon contributions from the probe beam are not observed.The pump–probe experimental configuration, seen in A tabletop pump–probe experimental set-up such as this characterizes the impulse response of the AOS architecture. For future applications, seeking compact device profiles and ultrashort laser pulses, the AOS architecture can be integrated with a sub-millimetre ultrashort pulsed laser, such as a mode-locked laser diodeExperimental results are collected for focusing through spheres into a GaAs target and into nanoparticle coatings.d=2.0 mm. They are mounted in the pump–probe experimental set-up by bonding the spheres to a 22-gauge needle tip with ultraviolet-curable polymer. The GaAs target is positioned in the focal plane of the spheres by collimating the back-reflected beams, as collimated back-reflected beams indicate that the reflective GaAs target is positioned in the focal plane of the sphere. Ultimately, the spheres with refractive indices of n=1.51, 1.76, 1.83 and 1.98 will be separated from the GaAs target by 480, 160, 100 and <1 μm, respectively. The respective sensitivities for these positions, being 1.1, 0.7, 0.6 and <0.5 μm, are dictated by each sphere's depth of focus.For the experiments that focus into a GaAs target, the spheres have a diameter of d=2.0 mm and d=30–40 μm. The d=2.0-mm spheres are mounted as stated above. The d=30–40-μm spheres are mounted on a planar glass substrate. The nanoparticles are applied to the surface of the sphere with a dry-coating processFor the experiments that focus into (Si or SiC) nanoparticle coatings, the spheres have diameters of N, and it is these time constants that witness pronounced effects from the increased specific surface area of the nanoparticles. Short-recovery time constants are observed at ∼3 ps for the bulk and at 350 and 270 fs for the SiC nanoparticles on the micro- and mill-scale architectures, respectively. The short-recovery time constants are attributed to ultrafast charge-carrier dynamics in the SiC bandstructureM-sidevalley and then undergo intervalley and intravalley scattering. The scattering yields femtosecond and picosecond transients for the effective mass and mobility. The effective mass and mobility transients form ultrafast transients on the refractive index near the surface, Δns(t), and absorption coefficient in the bulk, Δαb(t), respectively, and this is ultimately seen as an ultrafast modulation on the differential transmission of the probe beam, according to 3948The bulk SiC results of How to cite this article: Born, B. et al. Integration of photonic nanojets and semiconductor nanoparticles for enhanced all-optical switching. Nat. Commun. 6:8097 doi: 10.1038/ncomms9097 (2015).


Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases. Face recognition has been an active topic in machine learning, computer vision and pattern recognition research due to its potential value for applications and theoretical challenges. Face recognition is widely applied in real life, such as online image search, law enforcement, access control for secure facilities , security surveillance, and etc. Many face recognition approaches have been proposed, such as, Eigenfaces , Fisherfet al.  8] [8]et al [8]et alet al.  12]  ∈ Rm×in consists of training images belonging to the ith subject and X =  ∈ Rm×n denotes the training images matrix by concatenating all training samples. Given the training samples in X, the aim of face recognition is to classify a query image y ∈ Rm.Firstly, let us present a typical face recognition problem. Assume there are Recent research has proved that linear regression based algorithms, e.g. Nearest Feature Subspace (NFS) , Linear y ∈ Rm belonging to class i, if given sufficient training samples of class i, we haveiβ =  ∈ Rni is the coefficient vector corresponding to Xi. Of course, this class-specific subspace is embedded in the linear space spanned by all the training images. Hence, y can be cast as the linear combination of all training samples, i.e.β ∈ Rn is a coefficient vector. Actually, we don’t know which class the query image y comes from. Hence, the goal of sparse representation is to represent y using as few training images as possible, which is computed by solving the following minimization problem:ϵ is a pre-specified small constant and ∥⋅∥0 means ℓ0-norm. The above problem is NP-hard and it can be solved by approximating the ℓ0-norm with ℓ1-norm based convex relaxation. Hence, problem ℓ1-norm regularizer, i.e.λ is a scalar constant. In the ideal case, the entries of X from the ith class. In practice, this is not real, the recovered coefficient vector y is assigned to the class which has the minimum reconstruction residual.Sparse representation has attracted broad interest in various domains due to its great success in image processing. The basic idea of sparse representation is to represent a given test sample correctly with as few training samples as possible. SRC assumes that training samples from each subject lie on a linear subspace spanned by the training images from the given subject. Therefore, for a test sample et al.  [11 [11et alet al.  13]. Ho. Hoet ali.e., occlusions, lighting variations, facial expressions) violate the linear subspace assumption. Furthermore, due to insufficient number of training images, the query images of the ith class may be not lie on the subspace spanned by training images Xi. Therefore, the performance of SRC will deteriorate in these two situations. In order to handle the small sample size problem, leave-one-class-out subspace model is proposed  and E = . Di contains the structured patterns and discriminative feature of the ith subject. Therefore, Di has a better representative ability than the original data Xi in describing the face images of the ith subject  ∈ Rm×n for c subjects and the query image y, parameters λ1, λ2.Output: Class label of the query image y.Step 1: Learning class-specific dictionary and intra-class variant dictionary by low-rank matrix recovery. fori = 1: cdo Di,Ei ∥Di∥* + λ1∥Ei∥1 s.t.Xi = Di + Ei  minend for Step 2: Building supervised dictionary and Within-individual variant dictionary. D =  is make up of the class-specific sub-dictionaries Di. The within-individual variant dictionary E =  is builded by integrate all the sparse error matrix of each subject. However, for each column of E, if the norm is less than a threshold η (e.g. η = 10−3), it is removed from E. The supervised dictionary Step 3: Finding sparse representation of the query image y in term of new dictionary [D E]. ℓ1-norm minimization problem Solving the  Step 4: Classification fori = 1: cdo   end for Identity(y) = argminie(i) ith subject as Si. Thus, we havey, we assume that it comes from the ith class. If we have observed a sufficient number of training images per subject, then the query image can be well reconstructed by the training images belonging to the ground-truth class of it. Therefore, y ∈ Si. Obviously, SRC has achieved very promising results in this situation.In this section, the justification of our method and the difference with SRC will be discussed. Linear regression based algorithms assume that the images from a single subject lie on a linear subspace. We denote the subspace spanned by the training images from the ith class to cover the variations of the test image y, i.e., y ∉ Si. However, for large scale face recognition problems where the training sets contain large number of subjects, some training images from other subjects can be used to describe the test image y. Therefore, in this paper, we suppose that the test sample lies on the subspace spanned by all training samples, i.e., y ∈ S = span{X1, …, Xc} and y ∉ Si. For SRC, the training samples, which are the most similar with the query image y, are selected to represent y. Since y ∉ Si, there exist training samples y. Certainly, y can’t be modeled accurately by training images just from others because there must be some unique patterns owned by the ith class. So, we haveXi− represents all training samples except for the ith subject. According to y can be written as:αij and βj are the coefficients. Obviously, α =  ≠ 0 and β =  ≠ 0. Without loss of generality, assume that kth (k ≠ i) subject. If the contribution of training data belonging to the ith class is small, it is possible that y as the kth class. For example, the query image in y which might be caused by illuminations, expressions, or occlusions. However, SRC can’t separate these components  from the original training samples, hence, SRC treats them as discriminative feature of each subject.In practice, facial images might suffer from expression, illumination variations and even occlusions, there isn’t adequate number of training images for the Si, i.e., the subspace of Subject i, can be modeled asi and it is the discriminative component of this subject, while ei1, ei2, …, eini are basis vectors for the within-individual subspace and explain why training images of Subject i do not look identical. Hence, the basis vectors of subspace Si can be divided into two categories: The first one is the discriminative vector for each class; the other one is within-individual variant vector. However, in practical scenarios, facial images are affected by many factors, it’s not appropriate to describe the class-specific information of Subject i by just one basis Di as representation basis matrix of Subject i and Si is the subset of space spanned by Di and Ei, i.e.,dij and eij represent the jth  column of Di and Ei, respectively. We denote span{ei1, ei2, …, eini} represents the noise or within-individual variance of Xi. We combine the sparse error matrices of all subjects into a within-individual variant dictionary E = , which can be used to model the intra-class variations lighting conditions, expressions or occlusions. Therefore, W = span{e11, …, en11, …, ecnc} is a within-individual subspace. From ith subject, it lies in the linear subspace y in i, but it may be lie in y belongs to Subject 84. However, y ∉ S84 due to the occluded regions. By taking advantage of low rank matrix recovery, we obtain the within-individual subspace W. The query image y can be represented by the class-specific subspace W. Hence, LRSE+SC can alleviate the small sample size problem and the problem of the corrupted data.According to the theories of linear subspace and λ1 tends to infinity, all the atoms of within-individual dictionary E are zeros. In this situation, our method LRSE+SC is equivalent to SRC.From ℓ1-regularized least squares problem. The feature-sign search algorithm is very fast and achieves high performance .There are two parameters, tions in , the corλ1, λ2 over recognition accuracy, we perform two experiments on AR database. λ1, λ2. These two examples demonstrate that the optimal values of λ1, λ2 are correlated with training samples and test samples. However, when λ2 = 0.001, 0.0005, LRSE+SC achieves good performance. It is easy to see that LRSE+SC can achieve good performance when the value of λ1 in the neighborhood of 0.023.In order to study the influences of parameters In this paper, we have introduced a novel face recognition framework by utilizing low rank matrix recovery. In this mechanism, we try to decompose the original images into the class-specific feature and within-class variant feature. We have demonstrated theoretically and experimentally that the within-class variant feature which is separated from the original images is very important to deal with small sample size problem.Our method leverages low-rank and sparse error matrix decomposition technique and sparse representation scheme. Firstly, we recover the low-rank matrix of each subject by removing the sparse error in the training images. Then the low-rank matrix can be used as supervised dictionary to coding the test samples. Our algorithm regards the sparse error matrix of all subjects as sparse within-class variant dictionary to represent the variants of the test image and training images from the same class, which may be caused by illuminations, expressions and disguises. Experiments confirm that LRSE+SC approach outperforms SRC and ESRC for small sample size problem.