Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic topic classification of test cases using text mining at an Android smartphone vendor

Background: An Android smartphone is an ecosystem of applications, drivers, operating system components, and assets. The volume of the software is large and the number of test cases needed to cover the functionality of an Android system is substantial. Enormous effort has been already taken to properly quantify "what features and apps were tested and verified? ". This insight is provided by dashboards that summarize test coverage and results per feature. One method to achieve this is to manually tag or label test cases with the topic or function they cover, much like function points. At the studied Android smartphone vendor, tests are labelled with manually defined tags, so-called "feature labels (FLs)", and the FLs serve to categorize 100s to 1000s test cases into 10 to 50 groups. Aim: Unfortunately for developers, manual assignment of FLs to 1000s of test cases is a time consuming task, leading to inaccurately labeled test cases, which will render the dashboard useless. We created an automated system that suggests tags/labels to the developers for their test cases rather than manual labeling. Method: We use machine learning models to predict and label the functionality tested by 10,000 test cases developed at the company. Results: Through the quantitative experiments, our models achieved acceptable F-1 performance of 0.3 to 0.88. Also through the qualitative studies with expert teams, we showed that the hierarchy and path of tests was a good predictor of a feature's label. Conclusions: We find that this method can reduce tedious manual effort that software developers spent classifying test cases, while providing more accurate classification results.
An empirical study of WIP in kanban teams

Background: Limiting the amount of Work-In-Progress (WIP) is considered a fundamental principle in Kanban software development. However, no published studies from real cases exist that indicate what an optimal WIP limit should be. Aims: The primary aim is to study the effect of WIP on the performance of a Kanban team. The secondary aim is to illustrate methodological challenges when attempting to identify an optimal or appropriate WIP limit. Method: A quantitative case study was conducted in a software company that provided information about more than 8,000 work items developed over four years by five teams. Relationships between WIP, lead time and productivity were analyzed. Results: WIP correlates with lead time; that is, lower WIP indicates shorter lead times, which is consistent with claims in the literature. However, WIP also correlates with productivity, which is inconsistent with the claim in the literature that a low WIP (still above a certain threshold) will improve productivity. The collected data set did not include sufficient information to measure aspects of quality. There are several threats to the way productivity was measured. Conclusions: Indicating an optimal WIP limit is difficult in the studied company because a changing WIP gives contrasting results on different team performance variables. Because the effect of WIP has not been quantitatively examined before, this study clearly needs to be replicated in other contexts. In addition, studies that include other team performance variables, such as various aspects of quality, are requested. The methodological challenges illustrated in this paper need to be addressed.
Immune cells in the tumour: new routes of retinoids for chemoprevention and chemotherapeutics

Retinoids, vitamin A and its natural and synthetic analogues have various functions, including being involved in cell proliferation and differentiation and participating in the formation of vertebrate morphology. In addition, they may activate certain tumour suppressor genes that then act as tumour inhibitors. In the past decades, retinoids have been regarded as promising chemotherapeutic and chemopreventive agents; however, their mechanisms are still not fully understood. Immune cells that participate in or are associated with the immune response play vital roles in the initiation and development of many cancers. Interestingly, recent studies have demonstrated that retinoids can also exert various effects on immune cells including macrophages, T cells and dendritic cells in tumour tissues to execute anti‐tumour actions, providing new insights into chemoprevention and chemotherapeutics. In this review, we focus on the effects of retinoids on immune cells in the tumour, which may provide new approaches for antineoplastic strategies.
Opposite Regulation of CHOP and GRP78 and Synergistic Apoptosis Induction by Selenium Yeast and Fish Oil via AMPK Activation in Lung Adenocarcinoma Cells

Selenium has been intensively studied for the use of cancer prevention and treatment. However, the clinical effects are still plausible. To enhance its efficacy, a combinational study of selenium yeast (SY) and fish oil (FO) was performed in A549, CL1-0, H1299, HCC827 lung adenocarcinoma (LADC) cells to investigate the enhancement in apoptosis induction and underlying mechanism. By sulforhodamine B staining, Western blot and flow cytometric assays, we found a synergism between SY and FO in growth inhibition and apoptosis induction of LADC cells. In contrast, the fetal lung fibroblast cells (MRC-5) were unsusceptible to this combination effect. FO synergized SY-induced apoptosis of A549 cells, accompanied with synergistic activation of AMP-activated protein kinase (AMPK) and reduction of Cyclooxygenase (COX)-2 and β-catenin. Particularly, combining with FO not only enhanced the SY-elevated proapoptotic endoplasmic reticulum (ER) stress marker CCAAT/enhancer-binding protein homologous protein (CHOP), but also reduced the cytoprotective glucose regulated protein of molecular weight 78 kDa (GRP78). Consequently, the CHOP downstream targets such as phospho-JNK and death receptor 5 were also elevated, along with the cleavage of caspase-8, -3, and the ER stress-related caspase-4. Accordingly, inhibition of AMPK by compound C diminished the synergistic apoptosis induction, and elevated CHOP/GRP78 ratio by SY combined with FO. The AMPK-dependent synergism suggests the combination of SY and FO for chemoprevention and integrative treatment of LADC.
Phrase-Based Attentions

Most state-of-the-art neural machine translation systems, despite being different in architectural skeletons (e.g. recurrence, convolutional), share an indispensable feature: the Attention. However, most existing attention methods are token-based and ignore the importance of phrasal alignments, the key ingredient for the success of phrase-based statistical machine translation. In this paper, we propose novel phrase-based attention methods to model n-grams of tokens as attention entities. We incorporate our phrase-based attentions into the recently proposed Transformer network, and demonstrate that our approach yields improvements of 1.3 BLEU for English-to-German and 0.5 BLEU for German-to-English translation tasks on WMT newstest2014 using WMT'16 training data.
Two Regulators, PA3898 and PA2100, Modulate the Pseudomonas aeruginosa Multidrug Resistance MexAB-OprM and EmrAB Efflux Pumps and Biofilm Formation

It is generally believed that the Pseudomonas aeruginosa biofilm matrix itself acts as a molecular sieve or sink that contributes to significant levels of drug resistance, but it is becoming more apparent that multidrug efflux pumps induced during biofilm growth significantly enhance resistance levels. We present here a novel transcriptional regulator, PA3898, which controls biofilm formation and multidrug efflux pumps in P. aeruginosa. ABSTRACT It is generally believed that the Pseudomonas aeruginosa biofilm matrix itself acts as a molecular sieve or sink that contributes to significant levels of drug resistance, but it is becoming more apparent that multidrug efflux pumps induced during biofilm growth significantly enhance resistance levels. We present here a novel transcriptional regulator, PA3898, which controls biofilm formation and multidrug efflux pumps in P. aeruginosa. A mutant of this regulator significantly reduced the ability of P. aeruginosa to produce biofilm in vitro and affected its in vivo fitness and pathogenesis in Drosophila melanogaster and BALB/c mouse lung infection models. Transcriptome analysis revealed that PA3898 modulates essential virulence genes/pathways, including multidrug efflux pumps and phenazine biosynthesis. Chromatin immunoprecipitation sequencing (ChIP-seq) identified its DNA binding sequences and confirmed that PA3898 directly interacts with promoter regions of four genes/operons, two of which are mexAB-oprM and phz2. Coimmunoprecipitation revealed a regulatory partner of PA3898 as PA2100, and both are required for binding to DNA in electrophoretic mobility shift assays. PA3898 and PA2100 were given the names MdrR1 and MdrR2, respectively, as novel repressors of the mexAB-oprM multidrug efflux operon and activators for another multidrug efflux pump, EmrAB. The interaction between MdrR1 and MdrR2 at the promoter regions of their regulons was further characterized via localized surface plasmon resonance and DNA footprinting. These regulators directly repress the mexAB-oprM operon, independent of its well-established MexR regulator. Mutants of mdrR1 and mdrR2 caused increased resistance to multiple antibiotics in P. aeruginosa, validating the significance of these newly discovered regulators.
Changes of ruminal pH, rumination activity and feeding behaviour during early lactation as affected by different energy and fibre concentrations of roughage in pluriparous dairy cows

ABSTRACT The aim of this study was to assess differences of ruminal pH and rumination activity between the prepartal and postpartal period of cows and to investigate changes of feeding behaviour and ruminal fermentation depending on postpartal rations with slight differences in roughage energy and fibre concentration. Therefore, 11 rumen-cannulated German Holstein cows were used from 3 weeks antepartum until 16 weeks postpartum. During the dry period, all cows received the same diet. After calving cows were assigned to two groups receiving partial mixed rations with different energy concentrations (6.1 MJ NEL/kg DM [moderate], with 18% straw on dry matter [DM] basis, group MR) or 6.5 MJ NEL/kg DM [high], with 6% straw on DM basis, group HR). In both groups, concentrates were supplied on average at 45% of total DM intake. Circadian measurements of ruminal pH, ruminal temperature and rumination activity were conducted weekly during the transition period and bi-weekly after week 4 postpartum. Throughout the postpartal period, feed intake behaviour was measured, and twice during the experiment, rumen fluid composition and net-acid-base excretion in urine were determined. Mean ruminal pH, feeding behaviour, rumination activity and rumen fluid composition did not differ between the groups, whereas group HR exhibited higher diurnal variations of pH and had a lower rumen temperature than group MR postpartum. However, these differences also occurred during the prepartal period when groups received equal rations. It was observed that ruminal pH values and the risk for subacute ruminal acidosis (SARA) were increased during postpartal period, whereby the circadian pH values showed high cow-individual variations. Overall, differences of energy and fibre concentrations in roughage did not affect the observed variables, whereby it should be noted that the number of cows was quite low in this study. Our results suggest that the ruminal pH characteristics are rather cow individual, indicating that cows presumably differ in their susceptibility to develop SARA.
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

There is an increasing need to bring machine learning to a wide diversity of hardware devices. Current frameworks rely on vendor-specific operator libraries and optimize for a narrow range of server-class GPUs. Deploying workloads to new platforms -- such as mobile phones, embedded devices, and accelerators (e.g., FPGAs, ASICs) -- requires significant manual effort. We propose TVM, a compiler that exposes graph-level and operator-level optimizations to provide performance portability to deep learning workloads across diverse hardware back-ends. TVM solves optimization challenges specific to deep learning, such as high-level operator fusion, mapping to arbitrary hardware primitives, and memory latency hiding. It also automates optimization of low-level programs to hardware characteristics by employing a novel, learning-based cost modeling method for rapid exploration of code optimizations. Experimental results show that TVM delivers performance across hardware back-ends that are competitive with state-of-the-art, hand-tuned libraries for low-power CPU, mobile GPU, and server-class GPUs. We also demonstrate TVM's ability to target new accelerator back-ends, such as the FPGA-based generic deep learning accelerator. The system is open sourced and in production use inside several major companies.
High subsequent and recurrent sexually transmitted infection prevalence among newly diagnosed HIV-positive Thai men who have sex with men and transgender women in the Test and Treat cohort

We determined subsequent and recurrent sexually transmitted infections (STIs) among men who have sex with men (MSM) and transgender women (TGW) in the Test and Treat cohort. Thai MSM and TGW adults with previously unknown HIV status were enrolled and tested for HIV. Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and syphilis were tested at baseline, month 12, and month 24 to identify subsequent STIs (any STIs diagnosed after baseline) and recurrent STIs (any subsequent STIs diagnosed among those with positive baseline STIs). Among 448 participants, 17.8% were HIV-positive, the prevalence of subsequent STIs and recurrent STIs was 42% (HIV-positive versus HIV-negative: 66.3% versus 36.7%, p < 0.001) and 62.3% (81% versus 52.5%, p < 0.001), respectively. Common subsequent STIs by anatomical site were rectal CT infection (21.7%), rectal NG infection (13.8%), pharyngeal NG infection (13.1%), and syphilis (11.9%). HIV-positive status was associated with both subsequent STIs (adjusted hazard ratio [aHR] 2.38; 95%CI 1.64–3.45, p < 0.001) and recurrent STIs (aHR 1.83; 95%CI 1.16–2.87, p = 0.01). The results show that newly diagnosed HIV-positive MSM and TGW were at increased risk of STIs despite being in the healthcare system. STI educational counseling is necessary to improve STI outcomes among MSM and TGW in both HIV prevention and treatment programs.
Xenobiotic and endobiotic handling by the mucosal immune system.

PURPOSE OF REVIEW Mucosal immune cells in the intestinal tract are continuously exposed to a barrage of both foreign and endogenously generated metabolites, termed xenobiotics, and endobiotics, respectively. This review summarizes recent insights into the mechanisms by which xenobiotics and endobiotics regulate intestinal immunity and inflammation. RECENT FINDINGS The community of enteric microbes (i.e., microbiota) has profound impacts on the development and function of the mucosal immune system. The composition and function of gut microbiota is dynamically regulated by diet, and this interplay dictates which and how many immunomodulatory xenobiotics are present in the intestine. Microbiota also regulate the concentration and composition of circulating bile acids, an abundant class of liver-derived endobiotics with pleotropic immunoregulatory activities. A growing body of literature is emerging that sheds new light on the mechanisms by which xenobiotics and endobiotics interact with germline-encoded receptors and transporters to shape mucosal immune function. SUMMARY The complex and dynamic interplay among xenobiotics, endobiotics, and the mucosal immune system is a new frontier in mucosal immunology that is proving fruitful for the discovery of novel and pharmacologically accessible mechanisms with relevance to human inflammatory diseases.
Cognitive decline in Parkinson’s disease: the impact of the motor phenotype on cognition

Objectives Parkinson’s disease (PD) is the second most common neurodegenerative disorder and is further associated with progressive cognitive decline. In respect to motor phenotype, there is some evidence that akinetic-rigid PD is associated with a faster rate of cognitive decline in general and a greater risk of developing dementia. The objective of this study was to examine cognitive profiles among patients with PD by motor phenotypes and its relation to cognitive function. Methods Demographic, clinical and neuropsychological cross-sectional baseline data of the DEMPARK/LANDSCAPE study, a multicentre longitudinal cohort study of 538 patients with PD were analysed, stratified by motor phenotype and cognitive syndrome. Analyses were performed for all patients and for each diagnostic group separately, controlling for age, gender, education and disease duration. Results Compared with the tremor-dominant phenotype, akinetic-rigid patients performed worse in executive functions such as working memory (Wechsler Memory Scale-Revised backward; p=0.012), formal-lexical word fluency (p=0.043), card sorting (p=0.006), attention (Trail Making Test version A; p=0.024) and visuospatial abilities (Leistungsprüfungssystem test 9; p=0.006). Akinetic-rigid neuropsychological test scores for the executive and attentive domain correlated negatively with non-tremor motor scores. Covariate-adjusted binary logistic regression analyses showed significant odds for PD-mild cognitive impairment for not-determined as compared with tremor-dominant (OR=3.198) and akinetic-rigid PD (OR=2.059). The odds for PD-dementia were significant for akinetic-rigid as compared with tremor-dominant phenotype (OR=8.314). Conclusion The three motor phenotypes of PD differ in cognitive performance, showing that cognitive deficits seem to be less severe in tremor-dominant PD. While these data are cross-sectional, longitudinal data are needed to shed more light on these differential findings.
Prediction of relatedness in stack overflow: deep learning vs. SVM: a reproducibility study

Background Xu et al. used a deep neural network (DNN) technique to classify the degree of relatedness between two knowledge units (question-answer threads) on Stack Overflow. More recently, extending Xu et al.'s work, Fu and Menzies proposed a simpler classification technique based on a fine-tuned support vector machine (SVM) that achieves similar performance but in a much shorter time. Thus, they suggested that researchers need to compare their sophisticated methods against simpler alternatives. Aim The aim of this work is to replicate the previous studies and further investigate the validity of Fu and Menzies' claim by evaluating the DNN- and SVM-based approaches on a larger dataset. We also compare the effectiveness of these two approaches against SimBow, a lightweight SVM-based method that was previously used for general community question-answering. Method We (1) collect a large dataset containing knowledge units from Stack Overflow, (2) show the value of the new dataset addressing shortcomings of the original one, (3) re-evaluate both the DNN-and SVM-based approaches on the new dataset, and (4) compare the performance of the two approaches against that of SimBow. Results We find that: (1) there are several limitations in the original dataset used in the previous studies, (2) effectiveness of both Xu et al.'s and Fu and Menzies' approaches (as measured using F1-score) drop sharply on the new dataset, (3) similar to the previous finding, performance of SVM-based approaches (Fu and Menzies' approach and SimBow) are slightly better than the DNN-based approach, (4) contrary to the previous findings, Fu and Menzies' approach runs much slower than DNN-based approach on the larger dataset - its runtime grows sharply with increase in dataset size, and (5) SimBow outperforms both Xu et al. and Fu and Menzies' approaches in terms of runtime. Conclusion We conclude that, for this task, simpler approaches based on SVM performs adequately well. We also illustrate the challenges brought by the increased size of the dataset and show the benefit of a lightweight SVM-based approach for this task.
Neural Correlate of Transition Violation and Deviance Detection in the Songbird Auditory Forebrain

Deviants are stimuli that violate one's prediction about the incoming stimuli. Studying deviance detection helps us understand how nervous system learns temporal patterns between stimuli and forms prediction about the future. Detecting deviant stimuli is also critical for animals' survival in the natural environment filled with complex sounds and patterns. Using natural songbird vocalizations as stimuli, we recorded multi-unit and single-unit activity from the zebra finch auditory forebrain while presenting rare repeated stimuli after regular alternating stimuli (alternating oddball experiment) or rare deviant among multiple different common stimuli (context oddball experiment). The alternating oddball experiment showed that neurons were sensitive to rare repetitions in regular alternations. In the absence of expectation, repetition suppresses neural responses to the 2nd stimulus in the repetition. When repetition violates expectation, neural responses to the 2nd stimulus in the repetition were stronger than expected. The context oddball experiment showed that a stimulus elicits stronger neural responses when it is presented infrequently as a deviant among multiple common stimuli. As the acoustic differences between deviant and common stimuli increase, the response enhancement also increases. These results together showed that neural encoding of a stimulus depends not only on the acoustic features of the stimulus but also on the preceding stimuli and the transition patterns between them. These results also imply that the classical oddball effect may result from a combination of repetition suppression and deviance enhancement. Classification analyses showed that the difficulties in decoding the stimulus responsible for the neural responses differed for deviants in different experimental conditions. These findings suggest that learning transition patterns and detecting deviants in natural sequences may depend on a hierarchy of neural mechanisms, which may be involved in more complex forms of auditory processing that depend on the transition patterns between stimuli, such as speech processing.
Task-Specificity of Muscular Responses During Motor Imagery: Peripheral Physiological Effects and the Legacy of Edmund Jacobson

Motor imagery has become a key issue in cognitive neuroscience and particularly in fMRI research. However, peripheral physiological effects of motor imagery were already being studied a century ago with some research hypotheses even tracing back to Washburn (1916). This review focuses on research by Edmund Jacobson in the early 1930s. Jacobsen demonstrated that peripheral physiological effects rely on task-specific instructions: Bending the right arm elicits muscular responses in the right biceps, but not in the muscles of other limbs. This review discusses how Jacobsen examined this issue in a series of studies. This scientific spadework is worth recalling here because of its methodological innovations and its forward-looking discussion that even today, continues to be relevant for prospective research on this topic.