Miracle-dz/UniFAR-FTUs huggingface dataset:
Static Analysis Tools X Code Coverage Improvement Module Modified Android Runtime Collected Files Target Application Revealed Application Just-inTime Collecting Offline Reassembling

The scale of Android applications in the market is growing rapidly. To efficiently detect the malicious behavior in these applications, an array of static analysis tools are proposed. However, static analysis tools suffer from code hiding techniques like packing, dynamic loading, self modifying, and reflection. In this paper, we thus present DEXLEGO, a novel system that performs a reassembleable bytecode extraction for aiding static analysis tools to reveal the malicious behavior of Android applications. DEXLEGO leverages just-in-time collection to extract data and bytecode from an application at runtime, and reassembles them to a new Dalvik Executable (DEX) file offline. The experiments on DroidBench and real-world applications show that DEXLEGO correctly reconstructs the behavior of an application in the reassembled DEX file, and significantly improves analysis result of the existing static analysis systems.
MapRDD: Finer Grained Resilient Distributed Dataset for Machine Learning

The Resilient Distributed Dataset (RDD) is the core memory abstraction behind the popular data-analytic framework Apache Spark. We present an extension to the Resilient Distributed Dataset for map transformations, that we call MapRDD, which takes advantage of the underlying relations between records in the parent and child datasets, in order to achieve random-access of individual records in a partition. The design is complemented by a new MemoryStore, which manages data sampling and data transfers asynchronously. We use the ImageNet dataset to demonstrate that: (I) The initial data loading phase is redundant and can be completely avoided; (II) Sampling on the CPU can be entirely overlapped with training on the GPU to achieve near full occupancy; (III) CPU processing cycles and memory usage can be reduced by more than 90%, allowing other applications to be run simultaneously; (IV) Constant training step time can be achieved, regardless of the size of the partition, for up to 1.3 million records in our experiments. We expect to obtain the same improvements in other RDD transformations via further research on finer-grained implicit & explicit dataset relations.
Learning Sampling Policies for Domain Adaptation

We address the problem of semi-supervised domain adaptation of classification algorithms through deep Q-learning. The core idea is to consider the predictions of a source domain network on target domain data as noisy labels, and learn a policy to sample from this data so as to maximize classification accuracy on a small annotated reward partition of the target domain. Our experiments show that learned sampling policies construct labeled sets that improve accuracies of visual classifiers over baselines.
Emotional Distress in Patients Newly Diagnosed with Late Stage Cancers

A new diagnosis of cancer and a recurrence after a disease free interval are recognized as times of high emotional distress for patients. These crisis periods are known as the existential plight occurring within the first 100 days. This time of emotional distress may be extended beyond 100 days for those patients who have late stage and progressive disease at diagnosis. *Corresponding author: Elizabeth Ercolano, Associate Research Scientist, Yale School of Nursing 100 Church Street South New Haven, Ct, USA, Tel: 203-7372193; Fax: 203-785-4874; E-mail: elizabeth.ercolano@yale.edu Received March 01, 2013; Accepted March 17, 2013; Published March 20, 2013 Citation: Ercolano E, Bai M, Lazenby M, Ma T, McCorkle R (2013) Emotional Distress in Patients Newly Diagnosed with Late Stage Cancers. J Palliative Care Med S3: 002. doi:10.4172/2165-7386.S3-002 Copyright: © 2013 Ercolano E, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Individual and Network Factors Associated With HIV Care Continuum Outcomes Among Nigerian MSM Accessing Health Care Services

Background and Setting: Because data on the determinants of the HIV care continuum from key populations such as men who have sex with men (MSM) in resource-limited settings are limited, the study aimed to characterize HIV care continuum outcomes and assess individual and network barriers to progression through the HIV care continuum among MSM in Abuja and Lagos, Nigeria. Methods: TRUST/RV368 study used respondent-driven sampling to accrue MSM into community-based clinics in Nigeria. Participants received HIV testing at enrollment. HIV-infected participants were offered antiretroviral therapy (ART) with HIV RNA testing every 3 months (Abuja) or 6 months (Lagos). Multiple logistic regression models were used to calculate adjusted odds ratios for factors associated with each point in the HIV care continuum, including HIV testing, ART initiation, and 6-month viral suppression. Results: A total of 1506 MSM were recruited, 1178 (78.2%) tested for HIV and 369 (31.3%) were HIV positive newly diagnosed. Of these, 188 (50.1%) initiated ART, 136 (72.3%) completed 6 months, and 96 (70.6%) were virally suppressed. Larger network size and stronger social network support were each positively associated with HIV testing uptake. Factors associated with ART initiation were higher education and stronger social network support. Having stronger social network support was associated with increased odds of viral suppression at 6 months. Conclusions: Social determinants of health potentiated increased HIV care continuum outcomes. Integration of HIV prevention, HIV counseling and testing services, and universal coverage of ART into a community-based clinic is critical in achieving better HIV care continuum outcomes.
Projection-Free Bandit Convex Optimization

In this paper, we propose the first computationally efficient projection-free algorithm for bandit convex optimization (BCO). We show that our algorithm achieves a sublinear regret of $O(nT^{4/5})$ (where $T$ is the horizon and $n$ is the dimension) for any bounded convex functions with uniformly bounded gradients. We also evaluate the performance of our algorithm against baselines on both synthetic and real data sets for quadratic programming, portfolio selection and matrix completion problems.
Height restriction barriers detection from traffic scenarios using stereo-vision

Height restriction barriers detection is important usually for trucks' driving assistance systems. In this paper we propose a novel approach that uses stereo-vision and combines intensity and depth information for height barriers detection and tracking. High quality stereo-reconstruction is carried out by the SORT-SGM algorithm. Canny edges are extracted from 2D intensity image and filtered out by the 3D information. Horizontal lines are determined using the Hough transformation on the filtered edges and then validated by an intensity correlation approach taking into consideration that usually height restriction barriers have a repetitive textural pattern. Neighboring lines are clustered together in order to form the barrier region of interest. The height of the barrier is also approximated from the 3D points that belong to the barrier's region of interest. SURF features are extracted for the detected barriers from the intensity image and used for tracking them across frames. The whole height restriction barriers detection system performs real time with high accuracy results.
Joint Path Selection and Rate Allocation Framework for 5G Self-Backhauled mm-wave Networks

Owing to severe path loss and unreliable transmission over a long distance at higher frequency bands, this paper investigates the problem of path selection and rate allocation for multi-hop self-backhaul millimeter-wave (mm-wave) networks. Enabling multi-hop mm-wave transmissions raises a potential issue of increased latency, and thus, this paper aims at addressing the fundamental questions: how to select the best multi-hop paths and how to allocate rates over these paths subject to latency constraints? In this regard, a new system design, which exploits multiple antenna diversity, mm-wave bandwidth, and traffic splitting techniques, is proposed to improve the downlink transmission. The studied problem is cast to as a network utility maximization, subject to the upper delay bound constraint, network stability, and network dynamics. By leveraging stochastic optimization, the problem is decoupled into: 1) path selection and 2) rate allocation sub-problems, whereby a framework which selects the best paths is proposed using reinforcement learning techniques. Moreover, the rate allocation is a non-convex program, which is converted into a convex one by using the successive convex approximation method. Via mathematical analysis, the comprehensive performance analysis and convergence proof are provided for the proposed solution. The numerical results show that the proposed approach ensures reliable communication with a guaranteed probability of up to 99.9999% and reduces latency by 50.64% and 92.9% as compared to baseline models. Furthermore, the results showcase the key tradeoff between latency and network arrival rate.
A Course-Embedded Comparison of Instructor-Generated Videos of Either an Instructor Alone or an Instructor and a Student

Instructor-generated videos have become a popular way to engage students with material before a class, yet this is a relatively unexplored area of research. There is support for the use of videos in which instructors tutor students, but few studies have been conducted within the context of a classroom. In this study, conducted in a large-enrollment college physiology course, we used a randomized crossover design to compare the impact of two types of instructor-generated videos that students watched as part of their preclass assignments. We compared videos featuring only an instructor (instructor-only videos) with videos featuring an instructor tutoring a student (instructor–tutee videos). We analyzed student survey responses and weekly physiology quiz scores and found that students preferred, enjoyed, and valued the instructor-only videos significantly more than the instructor–tutee videos. In contrast to prior literature, students with a grade point average (GPA) below the median (3.49) performed significantly better on physiology quizzes after watching instructor-only videos compared with instructor–tutee videos. Students with a GPA at or above the median performed equivalently on physiology quizzes after watching instructor-only or instructor–tutee videos. We present this study as an example of bringing cognitive science studies into the context of a real physiology classroom.
An examination of physiological mechanisms underlying the frequency-doubling illusion.

PURPOSE The frequency-doubling illusion is an apparent doubling of spatial frequency when a sinusoidal grating is modulated rapidly in temporal counterphase. It has been proposed that the illusion arises from a spatially nonlinear ganglion cell class. The current study reexamines this possibility and investigates other mechanisms that may underlie the illusion. METHODS Responses of macaque magnocellular (MC) retinal ganglion cells were recorded to counterphase-modulated sinusoidal gratings of various spatial frequencies, and linearity of spatial summation was assessed. Human psychophysical thresholds were measured for a variety of phase discrimination and matching tasks. RESULTS Consistent with lateral geniculate recordings reported by other authors, no evidence was found of a separate nonlinear (M(y)) MC cell class. The small, spatially nonlinear responses found were least at the low spatial frequencies used in clinical testing. Further analysis showed that no spatially modulated signal can be expected from the nonlinear response of a ganglion cell; the nonlinearity of spatial summation gives a doubled response in time but not across space. Psychophysical performance was consistent with an inability to distinguish the temporal phase of counterphase-modulated gratings when the illusion occurs. From 4 to 40 Hz, the zero-crossings of the modulated sinusoidal grating provided a spatial cue and were matched to comparison patterns at twice the stimulus spatial frequency. CONCLUSIONS These results are inconsistent with the hypothesis that spatially nonlinear (M(y)) retinal ganglion cells are the physiological substrate of the frequency-doubling illusion. A cortical loss of temporal phase discrimination may be the principle cause of the illusion.
Teste de memória de trabalho em crianças de 3 a 6 anos de idade

Pre-escolares constituem uma faixa populacional que merece atencao devido as caracteristicas da maturacao biologica, bem como pelo impacto deste periodo nas fases posteriores do desenvolvimento. Nesta fase, muitas habilidades cognitivas se desenvolvem de maneira acelerada, entre elas, a memoria, sendo esta importante para o desenvolvimento. A avaliacao da memoria e importante para identificar possiveis dificuldades nessa habilidade, desta forma poderemos propor atividades de intervencao que, se formadas durante o desenvolvimento podem ser reforcadas ou enfraquecidas, assim, tanto o aprendizado quanto o desenvolvimento podem envolver alteracoes que ira resultar em mudancas nas funcoes cognitivas. Neste sentido, a avaliacao da memoria de trabalho durante a fase pre-escolar e relevante, pois tem sido considerada como um bom preditor do sucesso escolar, auxilia na compreensao, organizacao e reorganizacao das informacoes recebidas. O objetivo deste estudo foi avaliar a memoria de trabalho entre criancas com desenvolvimento tipico de 3 a 6 anos de idade. Para tanto foram avaliadas individualmente 235 criancas de ambos os sexos, de escolas publicas e privadas, com idade entre 3 a 6 anos (M = 4,5; DP= 1,12). Analises mostram que nao houve diferencas significativas em relacao a genero. Analises por comparacao de grupo escola Particular e escola Publica mostrou que as criancas de escola Particular obtem melhor desempenho nas provas do TMT, no entanto analise de Box Plot apontou que independentemente do tipo de escola a memoria de trabalho tem uma progressao. Analises dos resultados indicam correlacoes significativas entre todos os subtestes do TMT, bem como de cada um dos subtestes com a pontuacao total. A fim de verificar a fidedignidade do instrumento, foram conduzidas analises de consistencia interna atraves do coeficiente Alfa, o resultado foi de 0,84 revelando boa adequacao do instrumento. Evidencias de validade por mudanca desenvolvimental foram constatadas, revelando uma tendencia ao aumento do desempenho TMT com o aumento da idade das criancas. Portanto, obtem-se indicios de que a habilidade avaliada pelo TMT aumenta com a progressao das faixas etarias. Analises apontaram que as criancas com 3 anos de idade acertaram menos do que todas as demais. Alem disso, criancas de 6 anos acertaram mais do que todas as demais. Este trabalho pode contribuir para disponibilizacao de instrumento para avaliar a memoria de trabalho em criancas pre-escolares.
Design of an Automatic Facial Expression Detector

Facial expression recognition (FER) has attracted signiﬁcant attention in computer vision. It has many applications in real-life, such as human-computer interactions, surveillance, visual reality, video conferencing, customer satisfaction studies. Due to its fast-growing need in the market, many researchers have proposed diﬀerent methods to improve both accuracy and processing speed. So far, many FER systems can achieve real-time recognition. Facial expression classiﬁcation has three steps: facial detection, facial alignment, and feature extraction combined with classiﬁcation. Traditional computer vision ﬁnds features and then applies classiﬁers on top of the feature. However, due to the recent rapid development of deep neural networks, both academic and industrial research are sometimes more likely to combine feature extraction and classiﬁcation into one network structure. In this paper, we will discuss some eﬀective meth-ods that can be used for each step and will design our own automatic facial expression detector.
Early or late cranioplasty following decompressive craniotomy for traumatic brain injury: A systematic review and meta-analysis

Objective To evaluate the effectiveness of early (<3 months) cranioplasty (CP) and late CP (>3 months) on post-operative complications in patients receiving decompressive craniotomy (DC) for traumatic brain injury (TBI). Methods The Cochrane Library, PubMed and EMBASE databases were systematically searched for studies published prior to May 21, 2017. A meta-analysis examined post-operative overall complication rates, infection rates, subdural fluid collection and operating times according to early and late CP. Results Of the initial 1675 references, five studies, all cohort, involving a total of 413 patients, were selected for the review. There was no difference between early and late CP in post-operative overall complication rate (RR=0.68, 95%CI [0.36, 1.29]) and the post-operative infection rate (RR=0.50, 95%CI [0.20, 1.24]) in patients receiving DC for TBI. However, there was a significant difference in post-operative subdural effusion (RR=0.24, 95%CI [0.07, 0.78]) and mean operative time (mean difference = −33.02 min, 95%CI [−48.19, −17.84]) both in favour of early CP. Conclusions No differences were found between early and late CP in post-operative overall complications and procedural related infections in patients receiving DC for TBI, but early CP reduced the complication of subdural effusion and the mean operating time. These findings need to be confirmed by large, randomised controlled trials.
Slow-releasing tranilast in polytetrafluoroethylene/polylactide-co-glycolide laminate delays adjustment after strabismus surgery in rabbit model.

PURPOSE To determine the usefulness of slow-releasing tranilast in polytetrafluoroethylene/polylactide-co-glycolide (PTFE/PLGA) laminate for delayed adjustable strabismus surgery. METHODS A prospective, masked-observer, controlled study was performed in 25 rabbits. Fifty rabbit eyes were divided randomly into three groups. After a recession of the superior rectus muscle (SRM), a PTFE/PLGA laminate containing tranilast, PTFE alone, or balanced salt solution was applied beneath and over the SRM in the PTFE/PLGA-tranilast group (group P-T), the PTFE group (group P), and the control group, respectively. Delayed adjustment was performed by a masked observer once on each SRM 3 or 5 weeks after surgery. Adjustability, adjustment lengths, forces required, and adhesion degrees were evaluated. RESULTS In the control group, adjustment was impossible in any eye 3 or 5 weeks after surgery. In group P, adjustment was possible in 5 of 8 eyes 3 weeks after surgery and in 5 of 10 eyes 5 weeks after surgery. In group P-T, adjustment was possible in 8 of 10 eyes 3 and 5 weeks after surgery. On comparing adjustability, a significant difference was observed between group P-T and the control group 3 and 5 weeks after surgery (P = 0.006, P = 0.006, respectively). A significant difference was observed between group P-T and the control group (P = 0.016) in terms of adhesion between SRMs and conjunctivae 5 weeks after surgery. CONCLUSIONS Slow-releasing tranilast in PTFE/PLGA was found to reduce adhesion and allowed delayed adjustment in most eyes for up to 5 weeks after surgery.
Extracting Urban Microclimates from Electricity Bills

Sustainable energy policies are of growing importance in all urban centers.Climate — and climate change — will play increasingly important roles in these policies.Climate zones defined by the California Energy Commissionhave long been influential in energy management.For example, recently a two-zone division of Los Angeles(defined by historical temperature averages) was introduced for electricity rate restructuring.The importance of climate zones has been enormous,and climate change could make them still more important. AI can provide improvements on the ways climate zones are derived and managed.This paper reports on analysis of aggregate household electricity consumption (EC) data from local utilities in Los Angeles,seeking possible improvements in energy management. In this analysis we noticed that EC data permits identificationof interesting geographical zones — regions having EC patterns that are characteristically different from surrounding regions.We believe these zones could be useful in a variety of urban models.
Direct Detection of T- and B-Memory Lymphocytes by ImmunoSpot® Assays Reveals HCMV Exposure that Serum Antibodies Fail to Identify

It is essential to identify donors who have not been infected with human cytomegalovirus (HCMV) in order to avoid transmission of HCMV to recipients of blood transfusions or organ transplants. In the present study, we tested the reliability of seronegativity as an indicator for the lack of HCMV exposure in healthy human blood donors. Eighty-two HCMV seronegative individuals were identified, and their peripheral blood mononuclear cells (PBMC) were tested in ImmunoSpot® assays for the presence of HCMV-specific T- and B-memory lymphocytes. Eighty-two percent (67 of 82) of these HCMV seronegative individuals featured at least one memory cell that was lineage specific for HCMV, with the majority of these subjects possessing CD4+ and CD8+ T cells, as well as B cells, providing three independent lines of evidence for having developed immunity to HCMV. Only 15 of these 82 donors (18%) showed neither T- nor B-cell memory to HCMV, consistent with immunological naïveté to the virus. The data suggest that measurements of serum antibodies frequently fail to reveal HCMV exposure in humans, which may be better identified by direct detection of HCMV-specific memory lymphocytes.
Action Acquisition with Memory Reinforcement Learning using Prior Knowledge Anonymous submission

It is difficult for humans to obtain new knowledge, but we can acquire new knowledge by imitating others behaviors. Inspired by such human characteristics, we propose a deep reinforcement learning method called memory reinforcement learning. Our approach leverages the technique of experience replay and a replay buffer architecture. We manually create stable action transition sequences (prior knowledge) and store these transitions in the replay buffer at the beginning of training. These hand-crafted transition sequences enable us to avoid random action selections and a local optimal policy. Consequently, our method can acquire stable control efficiently. Experimental results on a lane-changing task of autonomous driving indicate that the proposed method can efficiently acquire stable control.
Binding of Helicobacter pylori to Human Gastric Mucins Correlates with Binding of TFF1

Helicobacter pylori binds to the gastric mucin, MUC5AC, and to trefoil factor, TFF1, which has been shown to interact with gastric mucin. We examined the interactions of TFF1 and H. pylori with purified gastrointestinal mucins from different animal species and from humans printed on a microarray platform to investigate whether TFF1 may play a role in locating H. pylori in gastric mucus. TFF1 bound almost exclusively to human gastric mucins and did not interact with human colonic mucins. There was a strong correlation between binding of TFF1 and H. pylori to human gastric mucins, and between binding of both TFF1 and H. pylori to gastric mucins with that of Griffonia simplicifolia lectin-II, which is specific for terminal non-reducing α- or β-linked N-acetyl-d-glucosamine. These results suggest that TFF1 may help to locate H. pylori in a discrete layer of gastric mucus and hence restrain their interactions with epithelial cells.