Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel approach to automatic query reformulation for IR-based bug localization

Automatic query reformulation techniques for Information Retrieval based Bug Localization (IRBL) have been proposed to improve the quality of queries and IRBL performance. Recently proposed techniques determine the quality of queries via the bugs' description and reformulate them using important terms in the top-N source files retrieved by the initial query. However, the bugs' description may not contain enough information about the bugs, and the retrieved top-N files may not always provide important terms. In this paper, we propose a novel automatic query reformulation approach to improve IRBL performance beyond that of a recent technique. Our method expands bug reports using attachments and expands queries by reducing the noisy terms in them. We experimented with 1,546 bug reports. According to our results, we found that the quality of 70 reports was wrongly determined, and our method improved IRBL performance by up to 118% for these reports. Moreover, compared with a state-of-the-art technique, our method resulted in improvements of approximately 17% in Top-1, 11% in MRR@10, and 10% in MAP@10.
Cybercriminal Minds: An investigative study of cryptocurrency abuses in the Dark Web

The Dark Web is notorious for being a major distribution channel of harmful content as well as unlawful goods. Perpetrators have also used cryptocurrencies to conduct illicit financial transactions while hiding their identities. The limited coverage and outdated data of the Dark Web in previous studies motivated us to conduct an in-depth investigative study to understand how perpetrators abuse cryptocurrencies in the Dark Web. We designed and implemented MFScope, a new framework which collects Dark Web data, extracts cryptocurrency information, and analyzes their usage characteristics on the Dark Web. Specifically, MFScope collected more than 27 million dark webpages and extracted around 10 million unique cryptocurrency addresses for Bitcoin, Ethereum, and Monero. It then classified their usages to identify trades of illicit goods and traced cryptocurrency money flows, to reveal black money operations on the Dark Web. In total, using MFScope we discovered that more than 80% of Bitcoin addresses on the Dark Web were used with malicious intent; their monetary volume was around 180 million USD, and they sent a large sum of their money to several popular cryptocurrency services (e.g., exchange services). Furthermore, we present two real-world unlawful services and demonstrate their Bitcoin transaction traces, which helps in understanding their marketing strategy as well as black money operations.
Machine learning for improving mobile user satisfaction

Optimizing energy consumption in modern mobile handheld devices plays a crucial role as lowering power consumption impacts system's autonomy and system reliability. Recent mobile platforms have an increasing number of sensors and processing components. Added to the increasing popularity of power-hungry applications, battery life in mobile devices is an important issue. However, we think that the utilization of the large amount of data from the various sensors can be beneficial to detect the changing device context, the user needs or the running application requirements in terms of resources. When these information are used properly, an efficient control of power knobs can be implemented thus reducing the energy consumption. This paper presents URBOC, for User Request Based Optimization Component. This component is an extension of our previous framework [7] ENOrMOUS. This framework was able to identify and classify the user contexts in order to understand user habits, preferences and needs which allow to improve the operating system power scheme. In this paper, we extend the use of ENOrMOUS by allowing the user to send requests in order to extend the battery life up to a specific time. Machine Learning (ML) and data mining algorithms have been used to obtain an efficient trade-off between power consumption reduction opportunities and user requests satisfaction. The proposed solution increases battery life by up to seven hours depending on user requests vs. the out-of-the-box operating system power manager with a negligible overhead.
Populating the knowledge base of a conversational agent: human vs. machine

In this paper we study the task of creating questions to populate the knowledge base of a domain-oriented conversational agent, constituted of question-answer pairs. Considering the growing interest in Question Generation, a question arises: how good are current systems in the task of automatically populating an agent's knowledge base? In this study, three systems are evaluated in several dimensions specifically tailored for the task in hand. We evaluate not only the capacity of these systems to create questions close to the ones suggested by humans, but also the human effort in editing the set of generated questions to be ready to be added to the agent's knowledge base. This experiment leads us to a second question: does the set of automatically generated question complement/extend the questions generated by humans? Results show that these state-of-the-art Question Generation systems, even as a whole, are far from being able to generate the majority of the questions proposed by humans (up to 20% of coverage), and that, on average, several edits are needed (around 3) to correct the generated questions. However, on the other hand, these systems also contribute with questions that humans have not thought about, thus contributing to extend the pool of questions generated by humans.
Potassium Dependent Regulation of Astrocyte Water Permeability Is Mediated by cAMP Signaling

Astrocytes express potassium and water channels to support dynamic regulation of potassium homeostasis. Potassium kinetics can be modulated by aquaporin-4 (AQP4), the essential water channel for astrocyte water permeability regulation. We investigated whether extracellular potassium ([K+]o) can regulate astrocyte water permeability and the mechanisms of such an effect. Studies were performed on rat primary astrocytes and a rat astrocyte cell line transfected with AQP4. We found that 10mM [K+]o caused an immediate, more than 40%, increase in astrocyte water permeability which was sustained in 5min. The water channel AQP4 was a target for this regulation. Potassium induced a significant increase in intracellular cAMP as measured with a FRET based method and with enzyme immunoassay. We found that protein kinase A (PKA) could phosphorylate AQP4 in vitro. Further elevation of [K+]o to 35mM induced a global intracellular calcium response and a transient water permeability increase that was abolished in 5min. When inwardly rectifying potassium (Kir)-channels were blocked, 10mM [K+]o also induced a calcium increase and the water permeability increase no longer persisted. In conclusion, we find that elevation of extracellular potassium regulates AQP4 and astrocyte water permeability via intracellular signaling involving cAMP. A prolonged increase of astrocyte water permeability is Kir-channel dependent and this response can be impeded by intracellular calcium signaling. Our results support the concept of coupling between AQP4 and potassium handling in astrocytes.
Output-Optimal Massively Parallel Algorithms for Similarity Joins

Parallel join algorithms have received much attention in recent years due to the rapid development of massively parallel systems such as MapReduce and Spark. In the database theory community, most efforts have been focused on studying worst-case optimal algorithms. However, the worst-case optimality of these join algorithms relies on the hard instances having very large output sizes. In the case of a two-relation join, the hard instance is just a Cartesian product, with an output size that is quadratic in the input size. In practice, however, the output size is usually much smaller. One recent parallel join algorithm by Beame et al. has achieved output-optimality (i.e., its cost is optimal in terms of both the input size and the output size), but their algorithm only works for a 2-relation equi-join and has some imperfections. In this article, we first improve their algorithm to true optimality. Then we design output-optimal algorithms for a large class of similarity joins. Finally, we present a lower bound, which essentially eliminates the possibility of having output-optimal algorithms for any join on more than two relations.
Modelling multi level consistency in erasure code based storage systems

In the internet era, cloud storage services are in high demand. Due to huge volumes of the present day big data, cloud service providers look for alternatives for data replication, which has been traditionally used for providing fault tolerance and availability. If three copies of data are maintained for ensuring availability, then there is 200% storage overhead in replication based storage systems. Erasure code based storage is proving itself the most suitable alternative to replication schemes. Hardware assisted encoding, decoding process and research outcomes on data updates from various research communities, indicate a promising future for erasure code based storage systems for hot data storage. In this paper, a new protocol is proposed which shows how to provide different types of consistency in erasure code based storage systems in concurrent data access scenarios where failures of components are anticipated. We have developed protocols and data structures for implementing the strong, eventual and monotonic types of consistencies. The proposed consistency model has been tested successfully and the results are promising.
Statically analyzing information flows: an abstract interpretation-based hyperanalysis for non-interference

In the context of systems security, information flows play a central role. Unhandled information flows potentially leave the door open to very dangerous types of attacks, such as code injection or sensitive information leakage. Information flows verification is based on the definition of Non-Interference [8], which is known to be an hyperproperty [7], i.e., a property of sets of executions. The sound verification of hyperproperties is not trivial [3, 16]: It is not easy to adapt classic verification methods, used for trace properties, in order to deal with hyperproperties. In the present work, we design an abstract interpretation-based static analyzer soundly checking Non-Interference. In particular, we define an hyper abstract domain, able to approximate the information flows occurring in the analyzed programs.
An Inflammation Loop Orchestrated by S100A9 and Calprotectin Is Critical for Development of Arthritis

Objective The S100A9 and S100A8 proteins are highly expressed by neutrophils and monocytes and are part of a group of damage-associated molecular pattern molecules that trigger inflammatory responses. Sera and synovial fluids of patients with rheumatoid arthritis (RA) contain high concentrations of S100A8/A9 that correlate with disease activity. Methods In this study, we investigated the importance of S100A9 in RA by using neutralizing antibodies in a murine lipopolysaccharide-synchronized collagen-induced arthritis model. We also used an in vitro model of stimulation of human immune cells to decipher the role played by S100A9 in leukocyte migration and pro-inflammatory cytokine secretion. Results Treatment with anti-S100A9 antibodies improved the clinical score by 50%, diminished immune cell infiltration, reduced inflammatory cytokines, both in serum and in the joints, and preserved bone/collagen integrity. Stimulation of neutrophils with S100A9 protein led to the enhancement of neutrophil transendothelial migration. S100A9 protein also induced the secretion by monocytes of proinflammatory cytokines like TNFα, IL-1β and IL-6, and of chemokines like MIP-1α and MCP-1. Conclusion The effects of anti-S100A9 treatment are likely direct consequences of inhibiting the S100A9-mediated promotion of neutrophil transmigration and secretion of pro-inflammatory cytokines from monocytes. Collectively, our results show that treatment with anti-S100A9 may inhibit amplification of the immune response and help preserve tissue integrity. Therefore, S100A9 is a promising potential therapeutic target for inflammatory diseases like rheumatoid arthritis for which alternative therapeutic strategies are needed.
Two new species and a new combination of Allacta (Blattodea, Ectobiidae, Pseudophyllodromiinae) from China, with notes on their behavior in nature

Abstract Two new species, Allactabrunasp. n. and Allactaalbasp. n. , from China are described and illustrated. Allactahainanensis (Liu et al., 2017), comb. n. is proposed and re-described; figures including genitalia are provided. A key is provided to all species from China based on males. Notes on the bionomics of this genus in China are provided.
Family-based activity settings of children in a low-income African context

Background There has been an overwhelming call to improve the understanding of how children develop within an African context as Euro-American definitions of competence have been uncritically adopted as the norm for children in Africa. The activities that children engage in within the family setting are seen as important to understand how children develop within context. The use of activity settings is closely aligned with a strengths-based perspective of family-centred practice and contributes to improved sustainability of intervention. Objectives This study that was conducted in Soweto, South Africa, aims to describe activity settings that typically developing young children in low-income African contexts participate in. Method A descriptive design using structured interviews was utilised to obtain information about activity settings that children aged 3–5 years and 11 months engaged in. Structured interviews with 90 caregivers were conducted. Results Findings show that children participate in a variety of activities with varied participation levels. The types of activities are dependent on the context and perceptions of caregivers. Conclusion These findings draw attention to understanding activities that children engage in within the family context.
Motor Control System for Adaptation of Healthy Individuals and Recovery of Poststroke Patients: A Case Study on Muscle Synergies

Understanding the complex neuromuscular strategies underlying behavioral adaptation in healthy individuals and motor recovery after brain damage is essential for gaining fundamental knowledge on the motor control system. Relying on the concept of muscle synergy, which indicates the number of coordinated muscles needed to accomplish specific movements, we investigated behavioral adaptation in nine healthy participants who were introduced to a familiar environment and unfamiliar environment. We then compared the resulting computed muscle synergies with those observed in 10 moderate-stroke survivors throughout an 11-week motor recovery period. Our results revealed that computed muscle synergy characteristics changed after healthy participants were introduced to the unfamiliar environment, compared with those initially observed in the familiar environment, and exhibited an increased neural response to unpredictable inputs. The altered neural activities dramatically adjusted through behavior training to suit the unfamiliar environment requirements. Interestingly, we observed similar neuromuscular behaviors in patients with moderate stroke during the follow-up period of their motor recovery. This similarity suggests that the underlying neuromuscular strategies for adapting to an unfamiliar environment are comparable to those used for the recovery of motor function after stroke. Both mechanisms can be considered as a recall of neural pathways derived from preexisting muscle synergies, already encoded by the brain's internal model. Our results provide further insight on the fundamental principles of motor control and thus can guide the future development of poststroke therapies.
Climate adaptation in the public health sector in Africa: Evidence from United Nations Framework Convention on Climate Change National Communications

Climate change has potential to affect human health in various ways. Extreme temperatures and cold both result in deaths, while the changing habitats favouring the breeding of vectors could result in the spread of diseases such as malaria, cholera and typhus. This article reviews climate change adaptation measures in the African public health sector. The evidence is drawn from National Communications of 21 countries as submitted to the United Nations Framework Convention on Climate Change (UNFCCC). This article combines the literature review and grounded theory approaches with data obtained from the UNFCCC National Communications. Among key adaptation measures emerging from the work are weather-based forecasting and early warning systems, public education and awareness, putting in place appropriate policies, surveillance, research and monitoring as well as improving public health infrastructure and technology. The study recommends that African nations should commit to address health impacts of climate change through the implementation of appropriate adaptation measures.
Impact of climate change on primary agriculture, water sources and food security in Western Cape, South Africa

Climate change is undoubtedly one of the biggest crises that humanity is facing today. There is a robust scientific consensus that human-induced climate change is occurring not only in the Western Cape but around the world. The objective of this research was to assess the impact of climate change on primary agriculture and food security. The paper is based on a literature review. A variety of literature reviews, for example, 11 government reports and 21 journal articles including experience outside Western Cape, were consulted to enrich the local experience regarding the impact of climate change on agriculture. The results indicated that many dams had low water levels (40%) during 2016/2017, which reduced crop yields including grapes. Droughts, which affected both smallholder and commercial farmers, are now a common phenomenon. Livestock production has declined over time, with small stock, the beef and dairy industry being the most affected. The paper concludes by highlighting climate adaptation and mitigation interventions and strategies for both crops and livestock production in the Western Cape. The major recommendations included scaling up on the use of organic matter to avoid burning and creating gas emissions to the atmosphere, the effective use of livestock manure and the use of appropriate and adaptable seed varieties, managing the manure of the livestock to assist in mulching to reduce water loss through evaporation and using adaptable seeds. Keywords: climate change; impact; mitigation; primary agriculture; adaptation; drought.
Enhanced precipitation variability decreases grass- and increases shrub-productivity

Significance Although increased climatic variability resulting from climate change has been accepted by the scientific community and forms part of the public narrative, studies of the effect of climatic variability on ecosystems have received much less attention than effects of changes in the mean state of climate. Here, we report on a field experiment where we experimentally increased interannual variability of precipitation while maintaining average precipitation constant. Our results indicated that total productivity and that of grasses declined in response to increased precipitation variability, although shrubs benefited, suggesting a potential shift from grassland to shrubland in the future, with large consequences for the supply of ecosystem services. In addition, the effect of variability increased through time. Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society.
Effect of Er,Cr:YSGG on Remineralization Using CPP - ACPF (MI - Paste Plus) after Enamel Erosion Caused by Carbonated Soft Drink in Primary Teeth: In-Vitro Study

BACKGROUND: Erosion is a widespread phenomenon with higher predilection in primary dentition. AIM: The aim of the present study is to assess the remineralising effect of Er,Cr:YSGG laser application combined with CPP-ACPF after erosive demineralisation by Coca-Cola in primary teeth. METHODS: Fifty teeth (n = 10) were divided into; Group I: Artificial saliva, (Saliva natural, Medac, UK), Group II: CPP-ACPF (MI Paste Plus, GC Corp, USA), Group III: Er,Cr:YSGG (Waterlase iPlus, USA), Group IV: CPP-ACPF + Er,Cr:YSGG, Group V: Er,Cr:YSGG + CPP-ACPF. Teeth were immersed in Coca-Cola for 10 min, 5 times/day for 5 days. DIAGNOdent (DD) measurements were taken before and after the experiment. RESULTS: There was a significant increase in DD readings after erosive-treatment cycles in all test groups. The highest reading was in samples immersed in artificial saliva, and the lowest was in those subjected to combined CPP-ACPF and Er,Cr:YSGG laser application, regardless of the sequence used. There was no significant difference between samples immersed in artificial saliva, and after CPP-ACPF application. Similarly, there was no significant difference between samples treated by combined treatment of CPP-ACPF and Er,Cr:YSGG application. However, there was a significant difference between samples immersed in artificial saliva or treated with CPP-ACPF application and those subjected to combined treatment CPP-ACPF along with Er,Cr:YSGG. CONCLUSION: Combining Er,Cr:YSGG laser and CPP-ACPF paste significantly increased enamel remineralisation, regardless of the sequence implemented. Saliva naturally and CPP-ACPF application had a comparable effect on remineralisation.