Miracle-dz/UniFAR-FTUs huggingface dataset:
Code Review Practices for Refactoring Changes: An Empirical Study on OpenStack

Modern code review is a widely used technique employed in both industrial and open-source projects to improve software quality, share knowledge, and ensure adherence to coding standards and guidelines. During code review, developers may discuss refactoring activities before merging code changes in the code base. To date, code review has been extensively studied to explore its general challenges, best practices and outcomes, and socio-technical aspects. However, little is known about how refactoring is being reviewed and what developers care about when they review refactored code. Hence, in this work, we present a quantitative and qualitative study to understand what are the main criteria developers rely on to develop a decision about accepting or rejecting a submitted refactored code, and what makes this process challenging. Through a case study of 11,010 refactoring and non-refactoring reviews spread across OpenStack open-source projects, we find that refactoring-related code reviews take significantly longer to be resolved in terms of code review efforts. Moreover, upon performing a thematic analysis on a significant sample of the refactoring code review discussions, we built a comprehensive taxonomy consisting of 28 refactoring review criteria. We envision our findings reaffirming the necessity of developing accurate and efficient tools and techniques that can assist developers in the review process in the presence of refactorings.
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection*

Despite most existing anomaly detection studies assume the availability of normal training samples only, a few labeled anomaly examples are often available in many real-world applications, such as defect samples identified during random quality inspection, lesion images confirmed by radiologists in daily medical screening, etc. These anomaly examples provide valuable knowledge about the application-specific abnormality, enabling significantly improved detection of similar anomalies in some recent models. However, those anomalies seen during training often do not illustrate every possible class of anomaly, rendering these models ineffective in generalizing to unseen anomaly classes. This paper tackles open-set supervised anomaly detection, in which we learn detection models using the anomaly examples with the objective to detect both seen anomalies (‘gray swans’) and unseen anomalies (‘black swans’). We propose a novel approach that learns disentangled representations of abnormalities illustrated by seen anomalies, pseudo anomalies, and latent residual anomalies (i.e., samples that have unusual residuals compared to the normal data in a latent space), with the last two abnormalities designed to detect unseen anomalies. Extensive experiments on nine real-world anomaly detection datasets show superior performance of our model in detecting seen and unseen anomalies under diverse settings. Code and data are available at: https://github.com/choubo/DRA
iPLAN: Interactive and Procedural Layout Planning

Layout design is ubiquitous in many applications, e.g. architecture/urban planning, etc, which involves a lengthy iterative design process. Recently, deep learning has been leveraged to automatically generate layouts via image generation, showing a huge potential to free designers from laborious routines. While automatic generation can greatly boost productivity, designer input is undoubtedly crucial. An ideal AI-aided design tool should automate repetitive routines, and meanwhile accept human guidance and provide smart/proactive suggestions. However, the capability of involving humans into the loop has been largely ignored in existing methods which are mostly end-to-end approaches. To this end, we propose a new human-in-the-loop generative model, iPLAN, which is capable of automatically generating layouts, but also interacting with designers throughout the whole procedure, enabling humans and AI to co-evolve a sketchy idea gradually into the final design. iPLAN is evaluated on diverse datasets and compared with existing methods. The results show that iPLAN has high fidelity in producing similar layouts to those from human designers, great flexibility in accepting designer inputs and providing design suggestions accordingly, and strong generalizability when facing unseen design tasks and limited training data.
Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point

We propose cooperative edge-assisted dynamic federated learning (CE-FL). CE-FL introduces a distributed machine learning (ML) architecture, where data collection is carried out at the end devices, while the model training is conducted cooperatively at the end devices and the edge servers, enabled via data offloading from the end devices to the edge servers through base stations. CE-FL also introduces floating aggregation point, where the local models generated at the devices and the servers are aggregated at an edge server, which varies from one model training round to another to cope with the network evolution in terms of data distribution and users’ mobility. CE-FL considers the heterogeneity of network elements in terms of communication/computation models and the proximity to one another. CE-FL further presumes a dynamic environment with online variation of data at the network devices which causes a drift at the ML model performance. We model the processes taken during CE-FL, and conduct analytical convergence analysis of its ML model training. We then formulate network-aware CE-FL which aims to adaptively optimize all the network elements via tuning their contribution to the learning process, which turns out to be a non-convex mixed integer problem. Motivated by the large scale of the system, we propose a distributed optimization solver to break down the computation of the solution across the network elements. We finally demonstrate the effectiveness of our framework with the data collected from a real-world testbed.
Are High-Resolution Event Cameras Really Needed?

Due to their outstanding properties in challenging conditions, event cameras have become indispensable in a wide range of applications, ranging from automotive, computational photography, and SLAM. However, as further improvements are made to the sensor design, modern event cameras are trending toward higher and higher sensor resolutions, which result in higher bandwidth and computational requirements on downstream tasks. Despite this trend, the benefits of using high-resolution event cameras to solve standard computer vision tasks are still not clear. In this work, we report the surprising discovery that, in low-illumination conditions and at high speeds, low-resolution cameras can outperform high-resolution ones, while requiring a significantly lower bandwidth. We provide both empirical and theoretical evidence for this claim, which indicates that high-resolution event cameras exhibit higher per-pixel event rates, leading to higher temporal noise in low-illumination conditions and at high speeds. As a result, in most cases, high-resolution event cameras show a lower task performance, compared to lower resolution sensors in these conditions. We empirically validate our findings across several tasks, namely image reconstruction, optical flow estimation, and camera pose tracking, both on synthetic and real data. We believe that these findings will provide important guidelines for future trends in event camera development.
A Conservative Q-Learning approach for handling distribution shift in sepsis treatment strategies

Sepsis is a leading cause of mortality and its treatment is very expensive. Sepsis treatment is also very challenging because there is no consensus on what interventions work best and different patients respond very differently to the same treatment. Deep Reinforcement Learning methods can be used to come up with optimal policies for treatment strategies mirroring physician actions. In the healthcare scenario, the available data is mostly collected offline with no interaction with the environment, which necessitates the use of offline RL techniques. The Offline RL paradigm suffers from action distribution shifts which in turn negatively affects learning an optimal policy for the treatment. In this work, a Conservative-Q Learning (CQL) algorithm is used to mitigate this shift and its corresponding policy reaches closer to the physicians policy than conventional deep Q Learning. The policy learned could help clinicians in Intensive Care Units to make better decisions while treating septic patients and improve survival rate.
Association of Central Retinal Arteriolar and Venular Equivalents with Brain-aging and Macular Ganglion Cell-inner Plexiform Layer Thickness

ABSTRACT Introduction Neurodegeneration and cognitive decline in aging are growing public health concerns. This study investigates associations between central retinal arteriolar and venular equivalents (CRAE, CRVE) and brain-aging, a sensory and cognitive test composite measure, and macular ganglion cell-inner plexiform layer (mGCIPL) thickness, a biomarker of neurodegeneration. Methods Beaver Dam Offspring Study (BOSS) participants are adult children (baseline (2005–2008) age 21–84 years) of the population-based Epidemiology of Hearing Loss Study participants. Follow-up occurred every 5 years. In 2010–2013, fundus photographs were used to measure retinal vessels. A brain-aging score was constructed by principal component analysis using sensorineural and cognitive data. Associations between incident brain-aging and vessel measures were investigated using logistic regression. Associations between CRAE and CRVE and mGCIPL thickness, measured in 2015–2017, were also investigated. Results Participants (N = 2381; mean age: 53.9 years (SD = 9.8); 54% women) had a mean CRAE and CRVE of 148.8 µm (SD = 14.5) and 221.7 µm (SD = 20.7), respectively. Among those without ocular conditions, wider CRAE was associated with decreased 5-year brain-aging risk (33% per SD CRAE increase). Both vessel measures were independently associated with mGCIPL thickness. The mGCIPL thickness increased by approximately 1.7 µm and 2.0 µm per SD increase in CRAE and CRVE, respectively. Discussion The association of CRAE with incident brain-aging indicates its potential use as a screening tool among those without eye disease. The associations between CRAE and CRVE and mGCIPL thickness indicate narrower vasculature could affect neuronal health. These associations point to potential usefulness of retinal vessel measurements to identify people at higher risk of sensorineural declines and neurodegeneration.
Animals in multidimensional space: Interpreting coordinates throughout lexical-semantic features in mild cognitive impairment and control subjects

ABSTRACT Introduction Semantic verbal fluency is a useful neuropsychological tool since it involves language and executive abilities that can be impaired in patients with neurodegenerative diseases in comparison to healthy controls. The present study explores retrieve and executive control processes using traditional quantitative and qualitative raw scores and examines the utility of multidimensional scaling combined with linear regression to provide new insights about the underlying semantic network in mild cognitive impairment and in healthy older adults. Method A total of 165 Spanish older adults, 81 patients and 84 controls, were assessed in different cognitive domains and evoked animal names in one minute. Group differences on fluency raw scores were first explored. Regressions using tests to predict groups’ fluency scores were also performed. The 12 animals that had been produced more frequently were selected to perform a multidimensional scaling analysis for each group. Four features related to animal names were extracted from normative studies and then were used as predictors in linear regression to provide an interpretation of the resulting dimensions’ coordinates. Results Patients performed worse on memory and naming and produced a shorter list of animals than controls. In controls, naming and visual memory explained a small part of variance related to the total of animals produced and to the number of switches. Both groups exhibited similar semantic maps. Conclusions Results suggest that patients’ map is influenced by words with a dense associative neighborhood that were acquired at an early age, whereas in controls none of the predictors explained dimensions.
Amniotic membrane attenuates heterotopic ossification following high‐dose bone morphogenetic protein‐2 treatment of segmental bone defects

Treatment of large bone defects with supraphysiological doses of bone morphogenetic protein‐2 (BMP‐2) has been associated with complications including heterotopic ossification (HO), inflammation, and pain, presumably due to poor spatiotemporal control of BMP‐2. We have previously recapitulated extensive HO in our rat femoral segmental defect model by treatment with high‐dose BMP‐2 (30 μg). Using this model and BMP‐2 dose, our objective was to evaluate the utility of a clinically available human amniotic membrane (AM) around the defect space for guided bone regeneration and reduction of HO. We hypothesized that AM surrounding collagen sponge would attenuate heterotopic ossification compared with collagen sponge alone. In vitro, AM retained more BMP‐2 than a synthetic poly(ε‐caprolactone) membrane through 21 days. In vivo, as hypothesized, the collagen + AM resulted in significantly less heterotopic ossification and correspondingly, lower total bone volume (BV), compared with collagen sponge alone. Although bone formation within the defect was delayed with AM around the defect, by 12 weeks, defect BVs were equivalent. Torsional stiffness was significantly reduced with AM but was equivalent to that of intact bone. Collagen + AM resulted in the formation of dense fibrous tissue and mineralized tissue, while the collagen group contained primarily mineralized tissue surrounded by marrow‐like structures. Especially in conjunction with high doses of growth factor delivered via collagen sponge, these findings suggest AM may be effective as an overlay adjacent to bone healing sites to spatially direct bone regeneration and minimize heterotopic ossification.
An optimized agonist peptide of protease-activated receptor 4 and its use in a validated platelet-aggregation assay

Abstract Protease-activated receptor 4 (PAR4) is a promising drug target to improve the efficacy/safety window of antiplatelet agents. The native peptide GYPGQV, and the more-potent peptide AYPGKF, are PAR4-specific activators. However, these PAR4 agonist peptides (APs) elicit an agonist response, for example, platelet aggregation, at concentrations of 50 to 1000 µM in platelet-function assays, thereby limiting their utility to monitor the pharmacodynamic effects of PAR4 antagonists over a wide concentration range. Improved pharmacodynamic assays are needed for clinical development of PAR4 antagonists. We attempted to identify potent PAR4 APs to aid development of robust assays for optimization of PAR4 antagonists. Using an AYPG-based biased phage-display peptide library approach followed by chemical peptide optimization, A-Phe(4-F)-PGWLVKNG was identified. This peptide demonstrated an EC50 value of 3.4 µM in a platelet-aggregation assay, which is 16-fold more potent than AYPGKF. Using this new PAR4 AP, a platelet-rich plasma-aggregation assay using light-transmission aggregometry was developed and validated in a series of precision and reproducibility tests. PAR4 antagonist responses to PAR4 AP A-Phe(4-F)-PGWLVKNG (12.5 µM to 100 µM) were subsequently evaluated in this assay in vitro and ex vivo in a human study using BMS-986120, a PAR4 antagonist that entered clinical studies.
The SQ HDM SLIT‐Tablet is safe and well tolerated in patients with House Dust Mite allergic rhinitis with or without asthma: A “real‐life” French study

Abstract Background The SQ House Dust Mite (HDM) SubLingual ImmunoTherapy (SLIT)‐Tablet (Acarizax) is the only allergen immunotherapy authorized by European regulatory authorities to treat HDM‐induced allergic asthma (AA) that is not well‐controlled by inhaled corticosteroids and associated with mild‐to‐severe HDM allergic rhinitis (AR). The aim of this study was to add evidence on the safety of the SQ HDM SLIT‐Tablet in patients with AR, alone or with AA, under real‐life conditions. Methods This was a French “real‐life”, multicenter, non‐comparative, longitudinal, prospective study. It included patients initiating the SQ HDM SLIT‐Tablet for either persistent moderate‐to‐severe HDM AR or AA not well‐controlled by inhaled corticosteroids and associated with mild‐to‐severe HDM AR. Adverse Events (AEs) were collected at the first intake and throughout the study. Logistic regression was used to compare safety according to asthma control before treatment initiation. Results Between May 09, 2018 and May 29, 2019, 1526 patients were enrolled at 185 sites and 1483 were included in the safety population (SAF). Of them, 33.6% had suspected clinical manifestations of AA. Asthma was uncontrolled for 18.2% of the patients, partially controlled for 27.9% and well‐controlled for 53.8%. Overall, 31.9% of the SAF patients experienced at least one AE. The percentage of patients with AEs was 29.9% among patients with AR alone and 35.9% among those with AA (p = 0.0193). No significant difference was observed in the rate of AE or SAE depending on asthma control at inclusion (2.2% of SAEs reported for patients with uncontrolled asthma, 1.4% for partly controlled and 1.1% for well‐controlled). Conclusions The overall results indicate a good SQ HDM SLIT‐Tablet safety profile consistent with that reported in previous studies, regardless of asthma control.
Circ_0041732 regulates tumor properties of triple-negative breast cancer cells by the miR-149-5p/FGF5 pathway

Background Triple-negative breast cancer (TNBC) is a subtype of breast cancers with a high recurrence and mortality. The important factors promoting the TNBC process have not been fully identified. In this research, the role of a TNBC-related circular RNA (circRNA), circ_0041732, was revealed in TNBC cell tumor properties. Methods The expression levels of circ_0041732, microRNA-149-5p (miR-149-5p) and fibroblast growth factor 5 (FGF5) were detected by quantitative real-time polymerase chain reaction. The protein expression was determined by Western blot analysis or immunohistochemistry assay. Cell proliferation was detected by cell counting kit-8 and cell colony formation assays. Cell apoptosis was analyzed by flow cytometry and caspase-3 activity assays. Cell migration and invasion were evaluated by wound-healing and transwell invasion assays. Cell angiogenic capacity was investigated by a tube formation assay. The targeting relationship between miR-149-5p and circ_0041732 or FGF5 was identified by dual-luciferase reporter and RNA immunoprecipitation assays. The impacts of circ_0041732 knockdown on tumor formation were determined by an in vivo assay. Results Circ_0041732 and FGF5 expression were significantly upregulated, whereas miR-149-5p was downregulated in TNBC tissues and cells compared with normal breast tissues and cells, respectively. Circ_0041732 silencing inhibited TNBC cell proliferation, migration, invasion, and tube formation, but induced apoptosis. Additionally, circ_0041732 regulated TNBC cell tumor properties by binding to miR-149-5p. MiR-149-5p also modulated TNBC cell tumor properties by targeting FGF5. Furthermore, circ_0041732 knockdown hindered tumor formation in vivo. Conclusion Circ_0041732 silencing suppressed TNBC cell tumor properties by decreasing FGF5 expression through miR-149-5p. This finding demonstrated that circ_0041732 had the potential as a therapeutic target for TNBC.
A Systematic Review Exploring Variables Related to Bystander Intervention in Sexual Violence Contexts

This article presents a systematic review of the available literature which has investigated the role of key variables in facilitating or inhibiting bystander intervention (including direct intervention, tertiary and secondary prevention) in sexual violence (SV) contexts. Studies exploring the role of individual, situational and contextual variables were grouped to provide a narrative overview of bystanders’ personal characteristics as well as the immediate and wider contexts which may be influencing their bystander behaviour. A systematic search of published literature from four electronic databases identified 2526 articles that were screened, of which 85 studies met the inclusion criteria. Most studies focused upon the role of individual variables, in particular gender of bystander. This body of work finds females are more likely to intervene than males; however, not all studies report these differences and in some cases, this is influenced by the type of intervention behaviour being considered. Regarding situational variables, the most commonly researched variable was the presence of other bystanders, although the role of this variable as inhibiting or facilitating was not clear. Finally, the most commonly researched contextual variable was social norms towards intervention, which has consistently shown greater bystander intervention when there is a belief that peers support such behaviour. Very few studies considered the interaction between these variables. Therefore, it is important for future research to consider this gap in the literature so that we can obtain a more well-rounded understanding of variables that can inhibit and facilitate bystander intervention in SV contexts.
Intranasal Administration of Extracellular Vesicles Mitigates Apoptosis in a Mouse Model of Neonatal Hypoxic-Ischemic Brain Injury

Introduction: Neonatal hypoxic-ischemic brain injury (HIBI) results in significant morbidity and mortality despite current available therapies. Seeking a potential supplemental therapy for HIBI, we investigated the neuroprotective effects of extracellular vesicles derived from neural stem cells (NSC-EVs) and hypoxia-preconditioned brain cells (brain-EVs). Methods: HIBI was induced in postnatal day 9 mice by carotid ligation followed by hypoxia. Following injury, NSC-EVs, brain-EVs, or saline were administered intranasally. Brains were assessed for infarct size, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining, and caspase-3 expression. Additionally, brain-EV microRNA (miRNA) contents were analyzed by miRNA sequencing. Results: Both EV treated groups showed decreased infarct size (brain-EVs p = 0.004 and NSC-EVs p = 0.052), and although NSC-EV administration resulted in significantly fewer TUNEL+ cells (p = 0.0098), there was no change in caspase-3 expression after NSC-EV administration, suggesting a caspase-3-independent mechanism. Brain-EVs resulted in a nonsignificant decrease in TUNEL+ cells (p = 0.167) but significant decreases in caspase expression (cleaved p = 0.015 and intact p = 0.026). Brain-EVs consistently expressed several miRNAs, including two which have been shown to be downregulated after HIBI: miR-342-3p and miR-330-3p. Conclusion: Understanding the regenerative effects and contents of NSC-EVs and brain-EVs could allow for the development of targeted EV-based therapies that could reduce morbidity and mortality for neonates affected by HIBI.