Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Online Multi-Object Tracking (MOT) from videos is a challenging computer vision task which has been extensively studied for decades. Most of the existing MOT algorithms are based on the Tracking-by-Detection (TBD) paradigm combined with popular machine learning approaches which largely reduce the human effort to tune algorithm parameters. However, the commonly used supervised learning approaches require the labeled data (e.g., bounding boxes), which is expensive for videos. Also, the TBD framework is usually suboptimal since it is not end-to-end, i.e., it considers the task as detection and tracking, but not jointly. To achieve both label-free and end-to-end learning of MOT, we propose a Tracking-by-Animation framework, where a differentiable neural model first tracks objects from input frames and then animates these objects into reconstructed frames. Learning is then driven by the reconstruction error through backpropagation. We further propose a Reprioritized Attentive Tracking to improve the robustness of data association. Experiments conducted on both synthetic and real video datasets show the potential of the proposed model. Our project page is publicly available at: https://github.com/zhen-he/tracking-by-animation
Supporting Action Planning for Sedentary Behavior Change by Visualizing Personal Mobility Patterns on Smartphone

Scientific evidence has shown that long-term sedentary behaviour is detrimental to human health. Therefore, a trend appears in the field of healthy lifestyle promotion that more attention is drawn to sedentary behaviour rather than only physical activity. However, technology-based mobile health intervention tools targeting reducing sedentary behaviour are still lacking. This paper aims to explore a solution for sedentary behaviour change through supporting action planning. Action planning can not only bridge the intention-behavior gap in controlled motivation processes, but also enforce the cue-behavior association in unconscious processes. We present a smartphone-based personal mobility pattern visualization, with which we expect the users can make better action plans. The interactive visualization integrates temporal and spatial patterns of personal sedentary and walking behaviour, to provide explicit hints on when, where, and how to reduce sedentary behaviour and increase daily steps. We also present our experimental design to evaluate the visualization- based intervention tool.
Paralogs of the Calcium-Dependent Activator Protein for Secretion Differentially Regulate Synaptic Transmission and Peptide Secretion in Sensory Neurons

The two paralogs of the calcium-dependent activator protein for secretion (CAPS) are priming factors for synaptic vesicles (SVs) and neuropeptide containing large dense-core vesicles (LDCVs). Yet, it is unclear whether CAPS1 and CAPS2 regulate exocytosis of these two vesicle types differentially in dorsal root ganglion (DRG) neurons, wherein synaptic transmission and neuropeptide release are of equal importance. These sensory neurons transfer information from the periphery to the spinal cord (SC), releasing glutamate as the primary neurotransmitter, with co-transmission via neuropeptides in a subset of so called peptidergic neurons. Neuropeptides are key components of the information-processing machinery of pain perception and neuropathic pain generation. Here, we compared the ability of CAPS1 and CAPS2 to support priming of both vesicle types in single and double knock-out mouse (DRG) neurons using a variety of high-resolution live cell imaging methods. While CAPS1 was localized to synapses of all DRG neurons and promoted synaptic transmission, CAPS2 was found exclusively in peptidergic neurons and mediated LDCV exocytosis. Intriguingly, ectopic expression of CAPS2 empowered non-peptidergic neurons to drive LDCV fusion, thereby identifying CAPS2 as an essential molecular determinant for peptidergic signaling. Our results reveal that these distinct functions of both CAPS paralogs are based on their differential subcellular localization in DRG neurons. Our data suggest a major role for CAPS2 in neuropathic pain via control of neuropeptide release.
Insular‐limbic dissociation to intra‐epidermal electrical Aδ activation: A comparative study with thermo‐nociceptive laser stimulation

Intra‐epidermal electrical stimulation (IEES) has been shown to activate selectively Aδ fibers subserving spinothalamic‐mediated sensations. Owing to electrically induced highly synchronous afferent volleys, IEES induces Aδ‐mediated evoked potentials at nonpainful intensities, contrasting with thermo‐nociceptive laser pulses which entail painful pricking sensations. Here, we recorded intracortical responses from sensory and limbic‐cognitive regions of human subjects in response to IEE and laser stimuli, in order to test the hypothesis that IEES could dissociate the sensory from nonsensory networks of nociceptive processing. Intracortical evoked potentials were obtained in 11 epileptic patients with stereotactically implanted electrodes in sensory regions receiving spinothalamic afferents (posterior insula), limbic regions receiving spino‐parabrachial input (amygdalar nucleus), and high‐order affective‐cognitive regions (anteromedial frontal cortex, including perigenual anterior cingulate and rostromedial prefrontal areas). Responses in the sensory posterior insula were of similar amplitude and latency to IEE and laser stimuli (after accounting for heat‐transduction time of laser), and consistent in both cases with spinothalamic activation. However, responses to IEES in the amygdala and the anteromedial frontal regions were inconsistent and significantly smaller compared to those evoked to the laser stimulation. Thus, IEES can effectively activate the spinothalamic‐sensory system with little recruitment of affective‐motivational networks, including those triggered by spino‐parabrachio‐amygdalar projections. The fact that identical sensory responses were associated to either painful or nonpainful percepts underscores that subjective pain perception is not solely dependent on the sensory recruitment, but rather on the combined activation of sensory, limbic and cognitive areas with precise spatiotemporal relations.
Multiple objective test set selection for software product line testing: evaluating different preference-based algorithms

The selection of optimal test sets for Software Product Lines (SPLs) is a complex task impacted by many factors and that needs to consider the tester's preferences. To help in this task, Preference-based Evolutionary Multi-objective Algorithms (PEMOAs) have been explored. They use a Reference Point (RP), which represents the user preference and guides the search, resulting in a greater number of solutions in the ROI (Region of Interest). This region contains solutions that are more interesting from the tester's point of view. However, the explored PEMOAs have not been compared yet and the results reported in the literature do not consider many-objective formulations. Such an evaluation is important because in the presence of more than three objectives the performance of the algorithms may change and the number of solutions increases. Considering this fact, this work presents evaluation results of four PEMOAs for selection of products in the SPL testing considering cost, testing criteria coverage, products similarity, and the number of revealed faults, given by the mutation score. The PEMOAs present better performance than traditional algorithms, avoiding uninteresting solutions. We introduce a hyper-heuristic version of the PEMOA R-NSGA-II that presents the best results in a general case.
Managing Problem Drinking: Screening Tools and Brief Interventions for Primary Care Physicians

A high percentage of patients seen in primary care clinics partake in excessive alcohol consumption. It leads to numerous health problems and remains one of the leading risk factors for chronic disease. Despite the health concerns, screening for and intervening in patients’ alcohol misuse has yet to become standard practice in many primary care settings. There is well-established empirical evidence that brief doctor-patient interactions reduce alcohol consumption among excessive drinkers in primary care settings. This article draws on randomized controlled trials and literature on screening techniques, motivational interviewing, the transtheoretical model of behavior change, and medication-assisted treatments to enhance brief intervention methodology. Through this review, evidence-based practical strategies are presented to primary care doctors that reduce alcohol consumption in patients screened as problem drinkers. Referral information for those individuals with severe drinking problems is included. We propose that short, multicomponent interventions are most effective when they include interventions that utilize the lifestyle medicine philosophy, a nonjudgmental therapeutic alliance, and account for patient concerns more directly.
Acetylation of SUMO2 at lysine 11 favors the formation of non‐canonical SUMO chains

Post‐translational modifications by ubiquitin‐related SUMO modifiers regulate cellular signaling networks and protein homeostasis. While SUMO1 is mainly conjugated to proteins as a monomer, SUMO2/3 can form polymeric chains. Poly‐SUMOylation is best understood in the SUMO‐targeted ubiquitin ligase (StUbL) pathway, where chains prime proteins for subsequent ubiquitylation by StUbLs. SUMO chains typically form in response to genotoxic or proteotoxic stress and are preferentially linked via lysine 11 of SUMO2/3. Here, we report that K11 of SUMO2/3 undergoes reversible acetylation with SIRT1 being the K11 deacetylase. In a purified in vitro system, acetylation of SUMO2/3 impairs chain formation and restricts chain length. In a cellular context, however, K11 acetyl‐mimicking SUMO2 does not affect the StUbL pathway, indicating that in cells non‐canonical chains are more prevalent. MS‐based SUMO proteomics indeed identified non‐canonical chain types under basal and stress conditions. Importantly, mimicking K11 acetylation alters chain architecture by favoring K5‐ and K35‐linked chains, while inhibiting K7 and K21 linkages. These data provide insight into SUMO chain signaling and point to a role of K11 acetylation as a modulator of SUMO2/3 chains.
An Omnistereoscopic Video Pipeline for Capture and Display of Real-World VR

In this article, we describe a complete pipeline for the capture and display of real-world Virtual Reality video content, based on the concept of omnistereoscopic panoramas. We address important practical and theoretical issues that have remained undiscussed in previous works. On the capture side, we show how high-quality omnistereo video can be generated from a sparse set of cameras (16 in our prototype array) instead of the hundreds of input views previously required. Despite the sparse number of input views, our approach allows for high quality, real-time virtual head motion, thereby providing an important additional cue for immersive depth perception compared to static stereoscopic video. We also provide an in-depth analysis of the required camera array geometry in order to meet specific stereoscopic output constraints, which is fundamental for achieving a plausible and fully controlled VR viewing experience. Finally, we describe additional insights on how to integrate omnistereo video panoramas with rendered CG content. We provide qualitative comparisons to alternative solutions, including depth-based view synthesis and the Facebook Surround 360 system. In summary, this article provides a first complete guide and analysis for reimplementing a system for capturing and displaying real-world VR, which we demonstrate on several real-world examples captured with our prototype.
A comparative system‐level analysis of the neurodegenerative diseases

Neurodegenerative diseases are disorders in the central nervous system with consequent progressive neurological symptoms including behavioral and cognitive disabilities. Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, Parkinson’s disease, multiple sclerosis, and schizophrenia are the most important and abundant neurodegenerative diseases that affect different parts of the brain. Detailed studies unveiled the molecular mechanisms and pathways affected in each of these disorders. The role of many genes has been documented in the onset and progression of each disease. Although many system‐level approaches have been used to understand the exact cause of these diseases, there is no comparative analysis in this regard. Despite all differences in the molecular basis of these diseases, overlapping symptoms might indicate the involvement of the similar pathways and processes. Here, we have applied a system biology approach to uncover many aspects of main neurodegenerative diseases using microarray data obtained from 118 cases of postmortem brain samples. Our analysis has identified key genes that might contribute to the status of diseases. We have also compared the involved biological process and pathway between different disease to find possible similar mechanisms that exist in all of them. We also predicted potentially important transcription factors in each disease and predicted the core gene regulatory networks. We have provided a list of possible new key regulators that could be further explored and also discussed the role of these hub genes. The results of this study would be useful to develop new diagnostic strategies and also to find new drug targets.
Risk of adverse outcomes following urinary tract infection in older people with renal impairment: Retrospective cohort study using linked health record data

Background Few studies have investigated the risk of adverse outcomes in older people with renal impairment presenting to primary care with a urinary tract infection (UTI). The aim of this study was to determine the risk of adverse outcomes in patients aged ≥65 years presenting to primary care with a UTI, by estimated glomerular filtration rate (eGFR) and empirical prescription of nitrofurantoin versus trimethoprim. Methods and findings This was a retrospective cohort study using linked health record data from 795,484 patients from 393 general practices in England, who were aged ≥65 years between 2010 and 2016. Patients were entered into the cohort if they presented with a UTI and had a creatinine measurement in the 24 months prior to presentation. We calculated an eGFR to estimate risk of adverse outcomes by renal function, and propensity-score matched patients with eGFRs <60 mL/minute/1.73 m2 to estimate risk of adverse outcomes between those prescribed trimethoprim and nitrofurantoin. Outcomes were 14-day risk of reconsultation for urinary symptoms and same-day antibiotic prescription (proxy for treatment nonresponse), hospitalisation for UTI, sepsis, or acute kidney injury (AKI), and 28-day risk of death. Of 123,607 eligible patients with a UTI, we calculated an eGFR for 116,945 (95%). Median age was 76 (IQR, 70–83) years and 32,428 (28%) were male. Compared to an eGFR of >60 mL/minute/1.73 m2, patients with an eGFR of <60 mL/minute/1.73 m2 had greater odds of hospitalisation for UTI (adjusted odds ratios [ORs] ranged from 1.14 [95% confidence interval (CI) 1.01–1.28, p = 0.028], for eGFRs of 45–59, to 1.68 [95% CI 1.01–2.82, p < 0.001] for eGFRs <15) and AKI (adjusted ORs ranged from 1.57 [95% CI 1.29–1.91, p < 0.001], for eGFRs of 45–59, to 4.53 [95% CI 2.52–8.17, p < 0.001] for eGFRs <15). Compared to an eGFR of >60 mL/minute/1.73 m2, patients with an eGFR <45 had significantly greater odds of hospitalisation for sepsis, and those with an eGFR <30 had significantly greater odds of death. Compared to trimethoprim, nitrofurantoin prescribing was associated with lower odds of hospitalisation for AKI (ORs ranged from 0.62 [95% CI 0.40–0.94, p = 0.025], for eGFRs of 45–59, to 0.45 [95% CI 0.25–0.81, p = 0.008] for eGFRs <30). Nitrofurantoin was not associated with greater odds of any adverse outcome. Our study lacked data on urine microbiology and antibiotic-related adverse events. Despite our design, residual confounding may still have affected some of our findings. Conclusions Older patients with renal impairment presenting to primary care with a UTI had an increased risk of UTI-related hospitalisation and death, suggesting a need for interventions that reduce the risk of these adverse outcomes. Nitrofurantoin prescribing was not associated with an increased risk of adverse outcomes in patients with an eGFR <60 mL/minute/1.73 m2 and could be used more widely in this population.
Mandarin-English Code-switching Speech Recognition

This work presents the development of a Mandarin-English code-switching speech recognition system. We demonstrate three key novelties in our system. First, we increase our lexicon coverage to 360K words, where phone sets of different languages are maintained separately. Secondly, we used over 1000 hours of training data combining both mono-lingual and code-switch corpus to develop the acoustic model. Finally, for language modelling, we applied context-aware text normalization and word-class language model. When testing on our internal code-switch close talk microphone recording, the system achieves recognition performance that can support real applications.
Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks

This paper describes our submission to CoNLL UD Shared Task 2018. We have extended an LSTM-based neural network designed for sequence tagging to additionally generate character-level sequences. The network was jointly trained to produce lemmas, part-of-speech tags and morphological features. Sentence segmentation, tokenization and dependency parsing were handled by UDPipe 1.2 baseline. The results demonstrate the viability of the proposed multitask architecture, although its performance still remains far from state-of-the-art.
Obstructive Sleep Apnea in Elective Spine Surgery: National Prevalence and Inpatient Outcomes

Study Design: Retrospective cohort study. Objectives: Epidemiologic studies suggest that the prevalence of moderate to severe obstructive sleep apnea (OSA) is increasing. OSA has been linked to increased rates of postoperative complications following surgery. Large studies, however, regarding surgical outcomes in this patient population, particularly in the spine literature, are limited. Consequently, the purpose of this study was to assess the prevalence of and postoperative risks conferred by OSA in the elective spine population. Methods: Using data from the National Inpatient Sample from 2008 to 2012, an estimated 56 372 (5.1%) patients with OSA undergoing elective cervical and thoracolumbar spine surgery were selected and compared to 1 052 837 patients without OSA undergoing the same procedures. Our primary outcome measures included postoperative complication rates, inpatient mortality, length of stay, and total hospital charges. Results: Patients with OSA were, on average 2.6 years older than those without OSA (P < .001) and had a higher comorbidity burden. The prevalence of OSA increased between 2008 and 2012 from 3.5% to 6.8%; P < . 001. OSA was associated with a 3-fold increase in major complications (P < .001) and was confirmed as an independent risk factor for major complications based on multivariate analysis (odds ratio [OR] = 2.82; 95% CI = 2.59-2.79; P < .001). Rates of deep venous thrombosis were doubled in patients with OSA. OSA was determined to be an independent predictor of pulmonary complications (OR = 2.69; 95% CI = 2.59-2.79; P < .001). OSA did not increase the risk of postoperative mortality. Conclusions: Patients with OSA often have multiple concomitant comorbidities and consequently are at increased risk of experiencing a more difficult postoperative course following elective spine surgery. Specifically, increased risks of pulmonary complications and deep venous thrombosis should be anticipated.
RNA Interference as a Prospective Tool for the Control of Human Viral Infections

RNA interference (RNAi), which is mediated by small interfering RNAs (siRNAs) derived from viral genome or its replicative intermediates, is a natural antiviral defense in plants, fungi, and invertebrates. Whether RNAi naturally protects humans from viral invasion is still a matter of debate. Nevertheless, exogenous siRNAs are able to halt viral infection in mammals. The current review critically evaluates the production of antiviral siRNAs, delivery techniques to the infection sites, as well as provides an overview of antiviral siRNAs in clinical trials.
Coupled Clustering Ensemble by Exploring Data Interdependence

Clustering ensembles combine multiple partitions of data into a single clustering solution. It is an effective technique for improving the quality of clustering results. Current clustering ensemble algorithms are usually built on the pairwise agreements between clusterings that focus on the similarity via consensus functions, between data objects that induce similarity measures from partitions and re-cluster objects, and between clusters that collapse groups of clusters into meta-clusters. In most of those models, there is a strong assumption on IIDness (i.e., independent and identical distribution), which states that base clusterings perform independently of one another and all objects are also independent. In the real world, however, objects are generally likely related to each other through features that are either explicit or even implicit. There is also latent but definite relationship among intermediate base clusterings because they are derived from the same set of data. All these demand a further investigation of clustering ensembles that explores the interdependence characteristics of data. To solve this problem, a new coupled clustering ensemble (CCE) framework that works on the interdependence nature of objects and intermediate base clusterings is proposed in this article. The main idea is to model the coupling relationship between objects by aggregating the similarity of base clusterings, and the interactive relationship among objects by addressing their neighborhood domains. Once these interdependence relationships are discovered, they will act as critical supplements to clustering ensembles. We verified our proposed framework by using three types of consensus function: clustering-based, object-based, and cluster-based. Substantial experiments on multiple synthetic and real-life benchmark datasets indicate that CCE can effectively capture the implicit interdependence relationships among base clusterings and among objects with higher clustering accuracy, stability, and robustness compared to 14 state-of-the-art techniques, supported by statistical analysis. In addition, we show that the final clustering quality is dependent on the data characteristics (e.g., quality and consistency) of base clusterings in terms of sensitivity analysis. Finally, the applications in document clustering, as well as on the datasets with much larger size and dimensionality, further demonstrate the effectiveness, efficiency, and scalability of our proposed models.
Efficient Counterfactual Learning from Bandit Feedback

What is the most statistically efficient way to do off-policy optimization with batch data from bandit feedback? For log data generated by contextual bandit algorithms, we consider offline estimators for the expected reward from a counterfactual policy. Our estimators are shown to have lowest variance in a wide class of estimators, achieving variance reduction relative to standard estimators. We then apply our estimators to improve advertisement design by a major advertisement company. Consistent with the theoretical result, our estimators allow us to improve on the existing bandit algorithm with more statistical confidence compared to a state-of-theart benchmark.