Miracle-dz/UniFAR-FTUs huggingface dataset:
Extrema‐weighted feature extraction for functional data

Motivation: Although there is a rich literature on methods for assessing the impact of functional predictors, the focus has been on approaches for dimension reduction that do not suit certain applications. Examples of standard approaches include functional linear models, functional principal components regression and cluster‐based approaches, such as latent trajectory analysis. This article is motivated by applications in which the dynamics in a predictor, across times when the value is relatively extreme, are particularly informative about the response. For example, physicians are interested in relating the dynamics of blood pressure changes during surgery to post‐surgery adverse outcomes, and it is thought that the dynamics are more important when blood pressure is significantly elevated or lowered. Results: We propose a novel class of extrema‐weighted feature (XWF) extraction models. Key components in defining XWFs include the marginal density of the predictor, a function up‐weighting values at extreme quantiles of this marginal, and functionals characterizing local dynamics. Algorithms are proposed for fitting of XWF‐based regression and classification models, and are compared with current methods for functional predictors in simulations and a blood pressure during surgery application. XWFs find features of intraoperative blood pressure trajectories that are predictive of postoperative mortality. By their nature, most of these features cannot be found by previous methods. Availability and implementation: The R package ‘xwf’ is available at the CRAN repository: https://cran.r‐project.org/package=xwf. Supplementary information: Supplementary data are available at Bioinformatics online.
Study on the Application of Inverse Heat Conduction Problem on the Temperature Field of Motor

A two-dimensional inverse heat conduction model has been built based on the flat linear motor by the heat transfer theory and the Levenberg-Marquardt method.The thermal field of test piece has been calculated according to the model,and the intensity of inner heat source,thermal conductance and position of cable have been studied by the model.The results show that the inverse heat conduction model is more suitable to the single variable than the multivariable.The effects of measurement errors have been studied,and the result show that measurement errors have little effect on the calculated results of intensity of inner heat source,but large influence on the thermal conductance.
Prevalence of anti-DFS 70 antibodies in patients with and without systemic autoimmune rheumatic diseases

Objective Autoantibodies to the dense fine speckled 70 (DFS70) antigen are common among antinuclear antibodies (ANA) positive healthy individuals (HI). We assessed the prevalence of anti-DFS70 antibodies in patients with and without ANA-associated rheumatic diseases (AARDs) by two methods: chemiluminescent immunoassay (CIA) and an indirect immunofluorescence (IIF) assay based on immunoadsorption for DFS70.
Robust object detection by cuboid matching with local plane optimization in indoor RGB-D images

We propose a new cuboid matching algorithm for robust object detection in RGB-D images from an indoor scene. Unlike traditional bounding boxes, a cuboid is more flexible and accurate to represent the object's orientation and basic geometry that can serve as an informative mid-level representation for scene understanding. However, over-detection and miss-detection are common problems when the scene is too cluttered and has many irrelevant planar surfaces. We approach these problems from two perspectives. First, we apply a few planar features to improve initial plane generation and to select dominant plane candidates for cuboid initialization. Second, cuboid candidates are optimized to their local fitness involving both color and depth features. The experimental results show significant improvements over the state-of-art method both quantitatively and qualitatively.
Occurence of Internet Addiction in a General Population Sample: A Latent Class Analysis

Background: Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence. Aims: This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence. Methods: A telephone survey was conducted based on a random digit dialling procedure including landline telephone (n = 14,022) and cell phone numbers (n = 1,001) in participants aged 14-64. The Compulsive Internet Use Scale (CIUS) served as the basis for a LCA used to look for subgroups representing participants with Internet addiction or at-risk use. CIUS was given to participants reporting to use the Internet for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend (n = 8,130). Results: A 6-class model showed best model fit and included two groups likely to represent Internet addiction and at-risk Internet use. Both groups showed less social participation and the Internet addiction group less general trust in other people. Proportions of probable Internet addiction were 1.0% (CI 0.9-1.2) among the entire sample, 2.4% (CI 1.9-3.1) in the age group 14-24, and 4.0% (CI 2.7-5.7) in the age group 14-16. No difference in estimated proportions between males and females was found. Unemployment (OR 3.13; CI 1.74-5.65) and migration background (OR 3.04; CI 2.12-4.36) were related to Internet addiction. Conclusions: This LCA-based study differentiated groups likely to have Internet addiction and at-risk use in the general population and provides characteristics to further define this rather new disorder.
Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication II: associations with persistence of DSM-IV disorders.

CONTEXT Although significant associations of childhood adversities (CAs) with adult mental disorders have been widely documented, associations of CAs with onset and persistence of disorders have not been distinguished. This distinction is important for conceptual and practical purposes. OBJECTIVE To examine the multivariate associations of 12 retrospectively reported CAs with persistence of adult DSM-IV disorders in the National Comorbidity Survey Replication. DESIGN Cross-sectional community survey. SETTING Household population in the United States. PARTICIPANTS Nationally representative sample of 5692 adults. MAIN OUTCOME MEASURES Recency of episodes was assessed separately for each of 20 lifetime DSM-IV mood, anxiety, disruptive behavior, and substance use disorders in respondents with a lifetime history of these disorders using the Composite International Diagnostic Interview. Predictors of persistence were examined using backward recurrence survival models to predict time since most recent episode controlling for age at onset and time since onset. RESULTS The CAs involving maladaptive family functioning (parental mental illness, substance use disorder, criminality, family violence, physical and sexual abuse, and neglect) but not other CAs were significantly but modestly related to persistence of mood, substance abuse, and anxiety disorders. Number of maladaptive family functioning CAs had statistically significant, but again substantively modest, subadditive associations with the same outcomes. Exposure to multiple other CAs was significantly associated with persistence of mood and anxiety disorders. Associations remained statistically significant throughout the life course, although the substantive size of associations indicated by simulations showing time to most recent episode would increase by only 1.6% (from a mean of 8.3 years to a mean of 8.4 years) in the absence of CAs. CONCLUSIONS The overall statistically significant associations of CAs with adult DSM-IV/Composite International Diagnostic Interview disorders are due largely to component associations with onsets rather than with persistence, indirectly suggesting that the greatest focus of public health attention on CAs should be aimed at primary rather than secondary prevention.
Gesture-based Mobile Communication System Providing Side-by-side Shopping Feeling

This demo is a gesture-based communication framework designed for an immersive joint shopping scenario. It focuses on enhancing the mobile human-to-human interaction between two geographically separated users: an in-house user and an in-store user. By exploring the uses of depth-based tracking techniques and the integration of head-mounted displays and the spherical camera, we (1) construct an immersive virtual shopping environment for the in-house user remaining in a house and (2) offer a novel way for the users to achieve a real-time gestural communication in the physical shopping environment which the in-store user stays in, while (3) the latter gets an augmented reality experience. Through this demo, both users could share a feeling that they go for shopping side by side in the same place.
Generic finite approximations for practical Bayesian nonparametrics

Many data analysis problems can be seen as discovering a latent set of traits in a population. For instance, we might recover topics or themes from scientific papers, ancestral populations from genetic data, interest groups from social network data, or unique speakers across audio recordings of many meetings [3, 11, 29]. In all of these cases, we might reasonably expect the number of latent traits present in a data set to grow with the size of the data. One modeling option is to choose a different prior for different data set sizes, but constructing a new prior separately for every size of data set is unwieldy. A simpler option is to choose a single prior that naturally yields different expected numbers of traits for different numbers of data points. In theory, Bayesian nonparametrics (BNP) provides a rich set of priors with exactly this desirable property. BNP accomplishes this property by imagining a latent countable infinity of traits, so that there are always more traits to reveal in the data at larger data set sizes. This latent, infinite-dimensional parameter presents a major practical challenge, though. In what follows, we propose a simple approximation across a wide range of BNP models that is amenable to modern, efficient inference schemes and black-box code; fits easily within complex, potentially deep generative models; and admits straightforward parallelization.
Performance evaluation of frequent pattern mining algorithms using web log data for web usage mining

In today's information era, the Internet is a powerful platform as the data repository that plays a great role in storing, sharing, and retrieve information for knowledge discovery. However, as there are countless, dynamic, and significant growth of data, web users face big problems in terms of the relevant information required. Consequently, poor information precision and retrieval are part of the hottest recent research areas in today's world. Despite the voluminous of information resided on the web, valuable informative knowledge could possibly be discovered with the application of advanced data mining techniques. Association rule mining, as a technique in data mining, is one way to discover frequent patterns from various data sources. In this paper, three of the foremost association rule mining algorithms used for frequent pattern discovering namely, Eclat, Apriori, and FP-Growth examined on three sets of transactional databases devised from server access log file. The comparison is made both in execution time and memory usage aspects. Unlike most previous research works, findings, in this paper, reveal that each of the algorithms has their own appropriateness and specificities that can best fit depending on the data size and support parameter thresholds.
More on the Best Evolutionary Rate for Phylogenetic Analysis

&NA; The accumulation of genome‐scale molecular data sets for nonmodel taxa brings us ever closer to resolving the tree of life of all living organisms. However, despite the depth of data available, a number of studies that each used thousands of genes have reported conflicting results. The focus of phylogenomic projects must thus shift to more careful experimental design. Even though we still have a limited understanding of what are the best predictors of the phylogenetic informativeness of a gene, there is wide agreement that one key factor is its evolutionary rate; but there is no consensus as to whether the rates derived as optimal in various analytical, empirical, and simulation approaches have any general applicability. We here use simulations to infer optimal rates in a set of realistic phylogenetic scenarios with varying tree sizes, numbers of terminals, and tree shapes. Furthermore, we study the relationship between the optimal rate and rate variation among sites and among lineages. Finally, we examine how well the predictions made by a range of experimental design methods correlate with the observed performance in our simulations. We find that the optimal level of divergence is surprisingly robust to differences in taxon sampling and even to among‐site and among‐lineage rate variation as often encountered in empirical data sets. This finding encourages the use of methods that rely on a single optimal rate to predict a gene's utility. Focusing on correct recovery either of the most basal node in the phylogeny or of the entire topology, the optimal rate is about 0.45 substitutions from root to tip in average Yule trees and about 0.2 in difficult trees with short basal and long‐apical branches, but all rates leading to divergence levels between about 0.1 and 0.5 perform reasonably well. Testing the performance of six methods that can be used to predict a gene's utility against our simulation results, we find that the probability of resolution, signal‐noise analysis, and Fisher information are good predictors of phylogenetic informativeness, but they require specification of at least part of a model tree. Likelihood quartet mapping also shows very good performance but only requires sequence alignments and is thus applicable without making assumptions about the phylogeny. Despite them being the most commonly used methods for experimental design, geometric quartet mapping and the integration of phylogenetic informativeness curves perform rather poorly in our comparison. Instead of derived predictors of phylogenetic informativeness, we suggest that the number of sites in a gene that evolve at near‐optimal rates (as inferred here) could be used directly to prioritize genes for phylogenetic inference. In combination with measures of model fit, especially with respect to compositional biases and among‐site and among‐lineage rate variation, such an approach has the potential to greatly improve marker choice and should be tested on empirical data.
High Power Integrated Photonic W-Band Emitter

High power W-band integrated photonic emitters were successfully demonstrated by the integration of modified unitraveling-carrier photodiodes (PDs) with high directional gain Vivaldi antennas. An impedance matching network was designed to achieve conjugate matching between the PD and the antenna for better power delivery. An effective isotropic radiation power as high as 5 dBm at 110 GHz was measured for the emitter with a 5-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>-diameter PD. The impedance matching was shown to significantly affect the effective isotropic radiation power.
Early onset of type 2 diabetes among visible minority and immigrant populations in Canada

ABSTRACT Objectives: Type 2 diabetes is a chronic condition that affects nearly over three million Canadians, including immigrants. The timing of the first onset of diabetes has been linked to several other severe diseases. Yet, there is a dearth of empirical studies that examine the timing of the first onset of diabetes among Canadians, in general, and among immigrants and ethnic minority populations within Canada, in particular. Design: Applying event history techniques to the 2013 Canadian Community and Health Survey, we address this research void by examining factors that contribute to the first onset of diabetes among immigrant and visible minority populations in Canada (N = 8905). Given the gendered patterns in the epidemiology of diseases and the differences in risk factors for men and women, gender-specific models were estimated. Results: Results showed that South Asian, Black and Filipino women developed diabetes earlier, compared to women from the UK. Similarly, South Asian, Chinese, Filipino, Black, South East Asian and Arab men developed diabetes earlier than men from the UK. A significant and important finding of this analysis was that the risks of developing diabetes vanished completely for Black and Filipino women, after accounting for lifestyle factors. For South Asian women, however, there was significant attenuation in their risks after accounting for lifestyle factors. The findings were strikingly different for immigrant men. Specifically, their risks of developing diabetes increased after accounting for lifestyle factors. Conclusions: These results suggest the development of gender-specific and lifestyle interventions, targeted at specific immigrant groups with increased risks of developing diabetes earlier in the life course.
Pharmacological Treatment of ADHD in Addicted Patients: What Does the Literature Tell Us?

Learning objectives After participating in this activity, learners should be better able to:• Evaluate pharmacologic treatment of attention deficit/hyperactivity disorder (ADHD) in patients with substance use disorder (SUD) • Assess the causes of the diminished efficacy of ADHD medication in patients with comorbid SUD Objective Substance use disorder (SUD) and attention-deficit/hyperactivity disorder (ADHD) frequently co-occur, and the presence of ADHD complicates the treatment of the addiction. Pharmacotherapy is a potent intervention in childhood and adult ADHD, but findings have been mixed in adolescent and adult ADHD patients with SUDs. This review focuses on several contributing factors and possible explanations, with implications both for future research and for clinical practice. Method This systematic review examined all randomized, placebo-controlled trials of pharmacotherapy for ADHD in adult and adolescent SUD patients. Results The number of studies is limited, and several studies are hampered by qualitative flaws. The results, in general, are inconclusive for most medications studied, but more recent trials using psychostimulants in robust dosing have demonstrated significantly positive results. Conclusion In reviewing these trials, possible explanations relating to the particular characteristics and problems of this complex patient group are discussed. Several factors, including ADHD symptom severity, psychiatric comorbidity, persistent drug use, choice of medication, and concomitant psychosocial intervention, influence study results. Taking these factors into account may improve the likelihood of detecting significant effects in future research, as the recent positive trials have indicated, and may help in the appropriate selection of pharmacotherapy in clinical practice.
Development and Implementation of an Innovative Burn Nursing Handbook for Quality Improvement

Evidence-based burn nursing literature is extremely limited and often nonexistent. As a result, there is a lack of standardization in burn nursing care. Our objective was to evaluate burn nursing knowledge at an academic medical center and to implement innovative educational tools to enhance staff competency and improve the quality of care. A collaboration of practicing clinical nurses developed a 24-question knowledge assessment survey (presurvey) to evaluate fundamental burn nursing knowledge (fluid management, burn pathophysiology, burn-related procedures, wound care, and infection control). Pre-education knowledge surveys were administered to 59 burn nurses electronically. A writing team of new and experienced nurses was established and a 51-page handbook focusing on areas of need identified in the survey developed. This book was disseminated to staff as required for reading. Post-educational surveys were sent to the same nurses who completed the initial survey. Forty-six nurses (46/59, 78.0%) completed the survey, with a mean (SD) of 55.9 (11.0)% of questions being answered correctly. Postsurveys sent to the same 46 nurses who completed the presurvey had a response rate of 78.3% (36/46). We observed a significant increase in correctly answered questions (mean [SD]: 69.6 [8.7]%, P < .001) in the postsurvey intervention. The handbook improved education and significantly improved overall fundamental burn knowledge of practicing nursing staff. The use of electronic surveys to drive development of targeted educational interventions provides evidence-based tools for establishing burn nursing standards and developing quality improvement metrics.
Role of the nifB1 and nifB2 Promoters in Cell-Type-Specific Expression of Two Mo Nitrogenases in the Cyanobacterium Anabaena variabilis ATCC 29413

ABSTRACT Anabaena variabilis ATCC 29413 has one Mo nitrogenase that is made under oxic growth conditions in specialized cells called heterocysts and a second Mo nitrogenase that is made only under anoxic conditions in vegetative cells. The two large nif gene clusters responsible for these two nitrogenases are under the control of the promoter of the first gene in the operon, nifB1 or nifB2. Despite differences in the expression patterns of nifB1 and nifB2, related to oxygen and cell type, the regions upstream of their transcription start sites (tss) show striking homology, including three highly conserved sequences (CS). CS1, CS2, and the region just upstream from the tss were required for optimal expression from the nifB1 promoter, but CS3 and the 5′ untranslated region (UTR) were not. Hybrid fusions of the nifB1 and nifB2 upstream regions revealed that the region including CS1, CS2, and CS3 of nifB2 could substitute for the similar region of nifB1; however, the converse was not true. Expression from the nifB2 promoter region required the CS1, CS2, and CS3 regions of nifB2 and also required the nifB2 5′ UTR. A hybrid promoter that was mostly nifB2 but that had the region from about position −40 to the tss of nifB1 was expressed in heterocysts and in anoxic vegetative cells. Thus, addition of the nifB1 promoter region (from about position −40 to the tss of nifB1) in the nifB hybrid promoter supported expression in heterocysts but did not prevent the mostly nifB2 promoter from also functioning in anoxic vegetative cells. IMPORTANCE In the filamentous cyanobacterium Anabaena variabilis, two Mo nitrogenase gene clusters, nif1 and nif2, function under different environmental conditions in different cell types. Little is known about the regulation of transcription from the promoter upstream of the first gene of the cluster, which drives transcription of each of these two large operons. The similarity in the sequences upstream of the primary promoters for the two nif gene clusters belies the differences in their expression patterns. Analysis of these nif promoters in strains with mutations in the conserved sequences and in strains with hybrid promoters, comprising parts from nif1 and nif2, provides strong evidence that each promoter has key elements required for cell-type-specific expression of the nif1 and nif2 gene clusters.