Miracle-dz/UniFAR-FTUs huggingface dataset:
Poster: Guiding Developers to Make Informative Commenting Decisions in Source Code

Code commenting is a common programming practice of practical importance to help developers review and comprehend source code. However, there is a lack of thorough specifications to help developers make their commenting decisions in current practice. To reduce the effort of making commenting decisions, we propose a novel method, CommentSuggester, to guide developers regarding appropriate commenting locations in the source code. We extract context information of source code and employ machine learning techniques to identify possible commenting locations in the source code. The encouraging experimental results demonstrated the feasibility and effectiveness of our commenting suggestion method.
Formal Micro-Architectural Analysis of On-Chip Ring Networks

In the realm of Multi-Processors System-on-Chip (MPSoC’s), the Network-on-Chip (NoC) connecting all system components plays a crucial role in the overall correctness and performance of the system. Recent papers have proposed several ring based NoC solutions. The description and analysis of these micro-architectures are informal in nature. Text is used to argue about, e.g., deadlock freedom. For the first time, this paper proposes an environment for the formal modelling and analysis of such ring architectures with an emphasis on liveness properties. Our contribution includes a language to model ring micro-architectures, invariant generation techniques, deadlock freedom verification, and the application of our approach on a realistic case-study. The analysis reveals a possible deadlock not mentioned in the original paper.
Effector CD4 T cells with progenitor potential mediate chronic intestinal inflammation

Dysregulated CD4 T cell responses are causally linked to autoimmune and chronic inflammatory disorders, yet the cellular attributes responsible for maintaining the disease remain poorly understood. Herein, we identify a discrete population of effector CD4 T cells that is able to both sustain and confer intestinal inflammation. This subset of pathogenic CD4 T cells possesses a unique gene signature consistent with self-renewing T cells and hematopoietic progenitor cells, exhibits enhanced survival, and continually seeds the terminally differentiated IFN&ggr;-producing cells in the inflamed intestine. Mechanistically, this population selectively expresses the glycosyltransferase ST6Gal-I, which is required for optimal expression of the stemness-associated molecule TCF1 by effector CD4 T cells. Our findings indicate that the chronicity of T cell–mediated inflammation is perpetuated by specific effector CD4 T cells with stem-like properties.
Long-term changes in the water quality and fish community of a large boreal lake affected by rising water temperatures and nutrient-rich sewage discharges – with special emphasis on the European perch

In this study, we report the changes in the water quality and fish community of a large boreal lake (Lake Pyhaselka, Finland) in 1975–2005, when the lake was affected first by industrial and municipal sewage discharge and then by rising water temperatures. In the 1980s, the lake’s trophic state proceeded from oligotrophic to mesotrophic, which favoured cyprinids. The increased cyprinid density strengthened the competition pressure on perch (Perca fluviatilis ) reducing the growth rates of young perch. The lake’s trophic state shifted from mesotrophic back to oligotrophic in the 1990s as a result of effective treatment of sewage waters. The water temperature in Lake Pyhaselka rose from the beginning to the end of the monitoring period. The higher temperature favoured perch. In future, the warming may benefit pikeperch (Sander lucioperca ) even more than perch. This will probably affect the perch population, as pikeperch prey effectively on perch.
Brook Auto: High-Level Certification-Friendly Programming for GPU-powered Automotive Systems

Modern automotive systems require increased performance to implement Advanced Driving Assistance Systems (ADAS). GPU-powered platforms are promising candidates for such computational tasks, however current low-level programming models challenge the accelerator software certification process, while they limit the hardware selection to a fraction of the available platforms. In this paper we present Brook Auto, a high-level programming language for automotive GPU systems which removes these limitations. We describe the challenges and solutions we faced in its implementation, as well as a complete evaluation in terms of performance and productivity, which shows the effectiveness of our method.
YouTree: A Visualization Paradigm of Statistically and Textually Similar Videos

The rise of social media usage in the form of multimedia is on an exponential increase owing to the increased internet bandwidths in the recent past. As a result, people communicate in the form of videos and images a lot more than ever. One such video sharing and content developer platform is YouTube. YouTube has many features on video analytics in the form of recommendation systems, monetisation etc. It also offers many features for developers to evaluate their content and offers insights on the performance of their videos. Though these features are available, there is not even a single feature for developers to evaluate their content based on the performance of other's videos, which share the same nature of the content - the similarity between any two videos. Here, the similarity between two videos has a statistical measure apart from the content, which includes description and comments of a video. Thus, we propose an analysis of a query video and a range of videos to determine the most similar videos using statistical and textual similarity. The statistical similarity is evident from the number of derived features extracted from a video and the textual similarity is found by analysing the text data from the description and comments of a video. Experimental results show that the resultant similar videos are highly representative of both the statistical and textual similarity and can be used as a measure to compare two videos.
ROS is the major player in regulating altered autophagy and lifespan in sin-3 mutants of C. elegans

ABSTRACT SIN3, a transcriptional corepressor has been implicated in varied functions both as transcription activator and repressor. Recent studies associated Sin3 with the macroautophagic/autophagic process as a negative regulator of Atg8 and Atg32. Though the role of SIN3 in autophagy is being explored, little is known about the overall effect of SIN3 deletion on the survival of an organism. In this study using a Caenorhabditis elegans sin-3(tm1279);him-5(e1490) strain, we demonstrate that under in vivo conditions SIN-3 differentially modulates autophagy and lifespan. We provide evidence that the enhanced autophagy and decreased lifespan observed in sin-3 deletion mutants is dependent on ROS and intracellular oxidative stress. Inability of the mutant worms to maintain redox balance along with dysregulation of enzymatic antioxidants, depletion of GSH and NADP reserves and elevation of ROS markers compromises the longevity of the worms. It is possible that the enhanced autophagic process observed in sin-3(tm1279);him-5(e1490) worms is required to compensate for oxidative stress generated in these worms. Abbreviations: cat: catalase; DCFDA: 2ʹ,7ʹ-dichlorodihydrofluoroscein diacetate; GSH: reduced glutathione; GSSG: oxidized glutathione; H2O2: hydrogen peroxide; HDAC: Histone deacetylase; HID: HDAC interacting domain; him-5: high incidence of males; HLH-30: Helix Loop Helix-30; HNE: 4-hydroxyl-2-noneal; LIPL: LIPase Like; MDA: malondialdehyde; NGM: nematode growth medium; PAH: paired amphipathic α-helix; PE: phosphatidylethanolamine; RFU: relative fluorescence unit; ROS: reactive oxygen species; sin-3/SIN3: yeast Switch Independent; SOD: superoxide dismutase; NADP: nicotinamide adenine dinucleotide phosphate; SQST-1: SeQueSTosome related-1; ATG: AuTophaGy related
Mitigating Botnet Attack Using Encapsulated Detection Mechanism (EDM)

Botnet as it is popularly called became fashionable in recent times owing to it embedded force on network servers. Botnet has an exponential growth of about 170, 000 within network server and client infrastructures per day. The networking environment on monthly basis battle over 5 million bots. Nigeria as a country loses above one hundred and twenty five (N125) billion naira to network fraud annually, end users such as Banks and other financial institutions battle daily the botnet threats. The most worrisome part of the botmaster’s botnet is it propagation as an entity even when it is known to be large pool of malicious threats. The attacks leave end users (clients) to the risk of losing valuable credentials when connected to the affected infrastructure. It is on the above premise that this paper sort to expose the botnet method of propagation through proactive mechanism called Encapsulated Detection Mechanism (EDM) for botnet on Server Systems with further operations on conceptual framework, structural modules, usability and application of botnet. The mechanism uses one dimensional data stream evolutionary window approach of Distance Base Model (DBM) as an Outlier Analysis (OA). The Captcha, Username password and EDM Analyzer act as the front end of the data stream checker using Bot-Stream OutlieR Miner (B-STORM) algorithm and B-Exact Algorithm. The research work showed high level of data entering compliance efficiency on the server end network by neutralizing and mitigating botnet attack that falls short of the predefined data order within the networking signature.
Comparative expression analysis of genes encoding metallothioneins in response to heavy metals and abiotic stresses in rice (Oryza sativa) and Arabidopsis thaliana

ABSTRACT To get insights into the functions of metallothionein (MT) in plant response to multiple stresses, expressions of 10 rice MT genes (OsMTs) and 7 Arabidopsis MT genes (AtMTs) were comprehensively analyzed under combined heavy metal and salt stress. OsMT1a, OsMT1b, OsMT1c, OsMT1g, and OsMT2a were increased by different heavy metals. Notably, ABA remarkably increased OsMT4 up to 80-fold. Combined salt and heavy metals (Cd, Pb, Cu) synergistically increased OsMT1a, OsMT1c, and OsMT1g, whereas combined salt and H2O2 or ABA synergistically increased OsMT1a and OsMT4. Heavy metals decreased AtMT1c, AtMT2b, and AtMT3 but cold or ABA increased AtMT1a, AtMT1c, and AtMT2a. AtMT4a was markedly increased by salt stress. Combined salt and other stresses (Pb, Cd, H2O2) synergistically increased AtMT4a. Taken together, these findings suggest that MTs in monocot and dicot respond differently to combined stresses, which provides a valuable basis to further determine the roles of MTs in broad stress tolerance. Graphical Abstract MTs in monocot and dicot respond differently to single stress or combined salt and heavy metal, which provides information to generate plants with broad stress tolerance.
Poster: Improving Bug Localization with Report Quality Dynamics and Query Reformulation

Recent findings from a user study suggest that IR-based bug localization techniques do not perform well if the bug report lacks rich structured information such as relevant program entity names. On the contrary, excessive structured information such as stack traces in the bug report might always not be helpful for the automated bug localization. In this paper, we conduct a large empirical study using 5,500 bug reports from eight subject systems and replicating three existing studies from the literature. Our findings (1) empirically demonstrate how quality dynamics of bug reports affect the performances of IR-based bug localization, and (2) suggest potential ways (e.g., query reformulations) to overcome such limitations.
A Core Regulatory Pathway Controlling Rice Tiller Angle Mediated by the LAZY1-Dependent Asymmetric Distribution of Auxin[OPEN]

Transcriptome dynamics upon gravistimulation of rice shoot reveal a core regulatory pathway controlling rice tiller angle mediated by the LAZY1-dependent asymmetric distribution of auxin. Tiller angle in cereals is a key shoot architecture trait that strongly influences grain yield. Studies in rice (Oryza sativa) have implicated shoot gravitropism in the regulation of tiller angle. However, the functional link between shoot gravitropism and tiller angle is unknown. Here, we conducted a large-scale transcriptome analysis of rice shoots in response to gravistimulation and identified two new nodes of a shoot gravitropism regulatory gene network that also controls rice tiller angle. We demonstrate that HEAT STRESS TRANSCRIPTION FACTOR 2D (HSFA2D) is an upstream positive regulator of the LAZY1-mediated asymmetric auxin distribution pathway. We also show that two functionally redundant transcription factor genes, WUSCHEL RELATED HOMEOBOX6 (WOX6) and WOX11, are expressed asymmetrically in response to auxin to connect gravitropism responses with the control of rice tiller angle. These findings define upstream and downstream genetic components that link shoot gravitropism, asymmetric auxin distribution, and rice tiller angle. The results highlight the power of the high-temporal-resolution RNA-seq data set and its use to explore further genetic components controlling tiller angle. Collectively, these approaches will identify genes to improve grain yields by facilitating the optimization of plant architecture.
Tight Bound of Incremental Cover Trees for Dynamic Diversification

Dynamic diversification---finding a set of data points with maximum diversity from a time-dependent sample pool---is an important task in recommender systems, web search, database search, and notification services, to avoid showing users duplicate or very similar items. The incremental cover tree (ICT) with high computational efficiency and flexibility has been applied to this task, and shown good performance. Specifically, it was empirically observed that ICT typically provides a set with its diversity only marginally ($\sim 1/ 1.2$ times) worse than the greedy max-min (GMM) algorithm, the state-of-the-art method for static diversification with its performance bound optimal for any polynomial time algorithm. Nevertheless, the known performance bound for ICT is 4 times worse than this optimal bound. With this paper, we aim to fill this very gap between theory and empirical observations. For achieving this, we first analyze variants of ICT methods, and derive tighter performance bounds. We then investigate the gap between the obtained bound and empirical observations by using specially designed artificial data for which the optimal diversity is known. Finally, we analyze the tightness of the bound, and show that the bound cannot be further improved, i.e., this paper provides the tightest possible bound for ICT methods. In addition, we demonstrate a new use of dynamic diversification for generative image samplers, where prototypes are incrementally collected from a stream of artificial images generated by an image sampler.
Impact of smartphone-assisted prenatal home visits on women’s use of facility delivery: Results from a cluster-randomized trial in rural Tanzania

Background About half of births in rural Tanzania are assisted by skilled providers. Point-of-care mobile phone applications hold promise in boosting job support for community health workers aiming to ensure safe motherhood through increased facility delivery awareness, access and uptake. We conducted a controlled comparison to evaluate a smartphone-based application designed to assist community health workers with data collection, education delivery, gestational danger sign identification, and referrals. Methods Community health workers in 32 randomly selected villages were cluster-randomized to training on either smartphone (intervention) or paper-based (control) protocols for use during household visits with pregnant women. The primary outcome measure was postnatal report of delivery location by 572 women randomly selected to participate in a survey conducted by home visit. A mixed-effects model was used to account for clustering of subjects and other measured factors influencing facility delivery. Findings The smartphone intervention was associated with significantly higher facility delivery: 74% of mothers in intervention areas delivered at or in transit to a health facility, versus 63% in control areas. The odds of facility delivery among women counseled by smartphone-assisted health workers were double the odds among women living in control villages (OR, 1.96; CI, 1.21–3.19; adjusted analyses). Women in intervention areas were more likely to receive two or more visits from a community health worker during pregnancy than women in the control group (72% vs. 60%; chi-square = 6.9; p < 0.01). Previous facility delivery, uptake of antenatal care, and distance to the nearest facility were also strong independent predictors of facility delivery. Interpretation Community health worker use of smartphones increased facility delivery, likely through increased frequency of prenatal home visits. Smartphone-based job aids may enhance community health worker support and effectiveness as one component of intervention packages targeting safe motherhood. Trial registration NCT03161184.
A Novel Indoor Localization Algorithm for Efficient Mobility Management in Wireless Networks

Along with the penetration of smart devices and mobile applications in our daily life, how to effectively manage the mobility issues in wireless networks becomes a challenging task. The ability to continuously and accurately track the target object’s position plays a vital role in mobility management. In this paper, we propose a novel indoor localization algorithm that fuses multiple signal features as the location fingerprints. The rationale that motivates our algorithm design stems from the following observation: although using one special signal feature (e.g., channel state information (CSI)) might achieve statistically higher accuracy than using another signal feature (e.g., received signal strength (RSS)), the accuracy for individual position estimations is usually diversified when only one signal feature is used in localization. For example, using RSS can obtain more accurate location estimation than using CSI for some individual positions. Thus, we propose a novel indoor localization algorithm that fuses multiple types of signal features as fingerprint of positions, which can effectively improve localization accuracy. We designed several fusion schemes and evaluated their performance. Experiments show that our algorithm achieves localization error below 0.5m and 1.1m in two typical indoor environments, about 30% lower than the accuracy of algorithms by fusing multiple signal features.
A user-satisfaction-based clustering method

Clustering is a common method for data analysis where a good clustering helps users to better understand the data. As for clustering quality measurement, the mainly used are some objective measures, while some researchers also paid attention to users' goals and they proposed methods to get users involved in clustering. However, a good clustering must meet the satisfaction of the users. Apart from these objective measures and users' goals, whether the clustering is easy to understand is also important for clustering quality measurement, especially in high-dimensional data clustering, if the data points in the final clusters are with high dimensions, it will hinder users' understanding of the clustering results. With all these concerns considered, we proposed an index of users' satisfaction with high-dimensional data clustering. According to this index, we further put forward a user-satisfaction-based clustering method to better serve users' satisfaction. We first developed an optimization model about users' satisfaction, then we used genetic algorithm to solve this model and obtained some high-quality clusterings, after reclustering of the clusterings obtained in previous steps, a few representative high-quality clusterings are provided for users to select. The experiment results suggest that our method is effective to provide some representative clusterings with the clustering quality, users' goals and the interpretability of clustering results being well considered.
Epigenetic regulators Rbbp4 and Hdac1 are overexpressed in a zebrafish model of RB1 embryonal brain tumor, and are required for neural progenitor survival and proliferation

ABSTRACT In this study, we used comparative genomics and developmental genetics to identify epigenetic regulators driving oncogenesis in a zebrafish retinoblastoma 1 (rb1) somatic-targeting model of RB1 mutant embryonal brain tumors. Zebrafish rb1 brain tumors caused by TALEN or CRISPR targeting are histologically similar to human central nervous system primitive neuroectodermal tumors (CNS-PNETs). Like the human oligoneural OLIG2+/SOX10+ CNS-PNET subtype, zebrafish rb1 tumors show elevated expression of neural progenitor transcription factors olig2, sox10, sox8b and the receptor tyrosine kinase erbb3a oncogene. Comparison of rb1 tumor and rb1/rb1 germline mutant larval transcriptomes shows that the altered oligoneural precursor signature is specific to tumor tissue. More than 170 chromatin regulators were differentially expressed in rb1 tumors, including overexpression of chromatin remodeler components histone deacetylase 1 (hdac1) and retinoblastoma binding protein 4 (rbbp4). Germline mutant analysis confirms that zebrafish rb1, rbbp4 and hdac1 are required during brain development. rb1 is necessary for neural precursor cell cycle exit and terminal differentiation, rbbp4 is required for survival of postmitotic precursors, and hdac1 maintains proliferation of the neural stem cell/progenitor pool. We present an in vivo assay using somatic CRISPR targeting plus live imaging of histone-H2A.F/Z-GFP fusion protein in developing larval brain to rapidly test the role of chromatin remodelers in neural stem and progenitor cells. Our somatic assay recapitulates germline mutant phenotypes and reveals a dynamic view of their roles in neural cell populations. Our study provides new insight into the epigenetic processes that might drive pathogenesis in RB1 brain tumors, and identifies Rbbp4 and its associated chromatin remodeling complexes as potential target pathways to induce apoptosis in RB1 mutant brain cancer cells. This article has an associated First Person interview with the first author of the paper. Summary: This study shows that chromatin remodelers that are overexpressed in a zebrafish model of RB1 mutant brain cancer are required for neural progenitor proliferation and survival, providing insight into potential mechanisms that drive tumor growth.
RAMP: Resource-Aware Mapping for CGRAs

Coarse-grained reconfigurable array (CGRA) is a promising solution that can accelerate even non-parallel loops. Acceleration achieved through CGRAs critically depends on the goodness of mapping (of loop operations onto the PEs of CGRA), and in particular, the compiler’s ability to route the dependencies among operations. Previous works have explored several mechanisms to route data dependencies, including, routing through other PEs, registers, memory, and even re-computation. All these routing options change the graph to be mapped onto PEs (often by adding new operations), and without re-scheduling, it may be impossible to map the new graph. However, existing techniques explore these routing options inside the Place and Route (P&R) phase of the compilation process, which is performed after the scheduling step. As a result, they either may not achieve the mapping or obtain poor results. Our method RAMP, explicitly and intelligently explores the various routing options, before the scheduling step, and makes improve the mapping-ability and mapping quality. Evaluating top performance-critical loops of MiBench benchmarks over 12 architectural configurations, we find that RAMP is able to accelerate loops by 23× over sequential execution, achieving a geomean speedup of 2.13× over state-of-the-art.