Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality microbiological diagnostics and antimicrobial susceptibility testing, an essential component of antimicrobial resistance surveillance and control efforts in Pacific island nations

Problem Emerging bacterial antimicrobial (antibiotic) resistance (AMR) is a global threat to human health. However, most lower income countries do not have microbiological diagnostic testing for prompt, reliable confirmation of bloodstream infection and identification of AMR. Context Clinicians in Pacific island nations are increasingly challenged by patients who have infection due to antimicrobial-resistant bacteria. Treatment of infection remains empirical because of a lack of diagnostic testing capacity and may follow guidelines that were formulated without reference to local measures of AMR prevalence. There is limited understanding among clinicians of microbiology testing and test interpretation. Action Examine the lessons learnt from pilot laboratory development programmes in two Pacific island nations that focused on establishing standard procedures for micrological diagnostics and antimicrobial susceptibility testing (AST) and on improving the training of clinicians to increase their use of laboratory services. Outcome The pilot programmes addressed a range of logistical difficulties and evaluated two blood culture systems. They also examined and improved internal QC implementation and evaluated the prevalence of AMR. Discussion Continued development of microbiological diagnostic capability in the Pacific region is paramount. Pacific Island nations need to develop the capability of at least one central laboratory to culture AMR pathogens and subject them to quality-controlled AST or arrange for suitable referral to a nearby country. Discussion This study demonstrated a persistently high prevalence of three major bacterial STIs across four countries in WHO’s Western Pacific Region during nearly two decades. Further strengthening of strategies to control and prevent STIs is warranted.
Data-parallel query processing on non-uniform data

Graphics processing units (GPUs) promise spectacular performance advantages when used as database coprocessors. Their massive compute capacity, however, is often hampered by control flow divergence caused by non-uniform data distributions. When data-parallel work items demand for different amounts or types of processing, instructions execute with lowered efficiency. Query compilation techniques---a recent advance in GPU-accelerated database processing---suffer from the problem even more, because divergence effects are amplified during the execution of fused pipeline operators. In this work, we identify two types of control flow divergence---filter divergence and expansion divergence---that frequently occur in real world workloads. We quantify the problem for two poster cases and propose techniques to balance these divergence effects. By balancing divergence effects, our approach is able to restore processing efficiency even when pipelines contain heavily skewed operations. Our query compiler DogQC has a wider range of functionality than other query coprocessors and achieves performance improvements. We observe shorter execution times for TPC-H benchmark queries by factors up to 4.51x compared with existing GPU query compilers and by factors up to 4.54x compared with CPU-based systems.
Automated Cross-Platform Reverse Engineering of CAN Bus Commands From Mobile Apps

In modern automobiles, CAN bus commands are necessary for a wide range of applications such as diagnosis, security monitoring, and recently autonomous driving. However, only a small portion of CAN bus commands is standardized, and a vast majority of them is developed privately by car manufacturers. Today, the most effective way of revealing the proprietary CAN bus commands is to reverse engineer with real cars, which unfortunately is time-consuming and costly. In this paper, we propose a cost-effective (no real car needed) and automatic (no human intervention required) system, CANHUNTER, for reverse engineering of CAN bus commands using just car companion mobile apps. To achieve high effectiveness, we design an efficient technique to uncover the syntactics of CAN bus commands with backward slicing and dynamic forced execution, and a novel algorithm to uncover the semantics of CAN bus commands by leveraging code-level semantic clues. We have implemented a prototype of CANHUNTER for both Android and iOS platforms, and tested it with all free car companion apps (236 in total) from both Google Play and Apple App Store. Among these apps, CANHUNTER discovered 182, 619 unique CAN bus commands with 86.1% of them revealed with semantics, covering 360 car models from 21 car manufactures. We have also evaluated their correctness (both syntactics and semantics) using public resources, cross-platform and cross-app validation, and also realcar testing, with which over 70% of all the uncovered commands are validated. We observe no inconsistency in cross-platform and cross-app validation. While there are 3 semantic inconsistency among 241 manually validated CAN bus commands from public resources and real-car testing, we find that these three cases are actually caused by mistakes from app developers.
IFTE 2018 4 th International Forum on Teacher Education REFLECTIVE BASES OF STUDENTS ’ COGNITIVE STATES

The article shows the necessity of studying the reflective bases of cognitive states, shows the significant role of reflection in the regulation of cognitive mental states of students in the course of educational activity. The aim of the study is to identify the role of reflective processes in the mental regulation of students’ cognitive states. The study involved 98 people; all of them are students of the Kazan University of different areas of study. The average age of students is 21. In the article used both domestic and foreign techniques, as well as the original author's methodology for diagnosing reflective processes. Among them, the list of 24 cognitive mental states was used. Students had to choose cognitive states that they most often experience in the process of learning activity. Correlation and frequency analysis, as well as analysis of variances method were used. The authors found that most often in the course of educational activity students experience states of interest, concentration, curiosity and inspiration. The development of reflective processes of recognition, awareness and identification, as well as self-reflection, improves the cognitive components of states and contributes to the increase of adequacy, controllability and purposefulness of behaviour in the course of students' learning activities. © 2018 Published by Future Academy www.FutureAcademy. org.UK
Adversarial Classification Under Differential Privacy

—The last decade has seen a growing interest in adversarial classiﬁcation , where an attacker tries to mislead a classiﬁer meant to detect anomalies. We study this problem in a setting where anomaly detection is being used in conjunction with differential privacy to protect personal information. We show that a strategic attacker can leverage the additional noise (introduced to ensure differential privacy) to mislead the classiﬁer beyond what the attacker could do otherwise; we also propose countermeasures against such attacks. We then evaluate the impact of our attacks and defenses in road trafﬁc congestion and smart metering examples
The causal structure of lenition

Studies of variable lenition patterns converged on two phonetic properties as characteristic of lenition: reduced duration and increased intensity. However, the causal precedence of the two factors remains unclear. We focus on the causal structure of variable lenition. Study 1 examines the relationship between three correlates of lenition: speech rate, stress, and low information content, and their effect on reduced duration and increased intensity. We find that though increased intensity is more prototypically viewed as the core aspect of lenition, the effect of the three correlates on intensity is mediated by duration. Study 2 shows that all frequent lenition processes in the Buckeye corpus involve durational reduction. The contribution of this paper is a proposal with a fairly simple principle, with few auxiliary assumptions: Reduced duration precedes increased intensity in variable lenition. *
Exploring Deep Learning Models for Vulnerabilities Detection in Smart Contracts

Solidity is a Domain Specific Language (DSL) that has emerged from the invention of distributed ledger and that has been designed for Ethereum. Due to its specific structure, DSLs are threatened by unique bugs and vulnerabilities that could induce millions of dollars losses. In this project, a Deep Learning (DL) model used with a novel source code input representation was created for the line-level vulnerability detection task. The input’s structure in combination with a specific DL model can capture intricate data and control dependencies between various program variables. Using controlled settings and well-defined experiments, an exploration of the proposed approach was achieved to perfectly understand the model and to improve the performances. The developed method has successfully classified line-level vulnerabilities using a corpus of Solidity contracts as input. Our proposed pipeline is able to capture intricate dependencies between the program’s elements and to understand the overall structure of the code. Characteristics defining the optimal type of input are described to define the cases in which the proposed pipeline should be used.
Façade Fire Incidents in Tall Buildings Fire and Safety

Following recent tall building façade fire incidents, Research Seed Funding provided by CTBUH has supported exploratory research into identifying existing reviews of façade fires on tall buildings, creating a database of relevant façade fire incidents and examining where the emerging field of machine learning might be applied to the analysis of the incident database. The database included the general characteristics of the buildings, the regulatory environment in which the buildings were constructed, the types of materials used to create the façade, and the associated test standards with which the materials complied. This database will be used to identify areas of new work that should be advanced in conjunction with funding bodies and research partners. This paper provides a summary of the research work undertaken to generate the database.
Propriétés de Safety et de co-safety dans un contexte temporisé

Runtime enforcement is a powerful technique to ensure that a running system respects some desired properties. Using an enforcement monitor, an (un-trustworthy) input execution (in the form of a sequence of events) is modiﬁed into an output sequence that complies to a property. Runtime enforcement has been extensively studied over the last decade in the context of untimed properties. This paper introduces runtime enforcement of timed properties. We revisit the foundations of runtime enforcement when time between events matters. We show how runtime enforcers can be synthesized for any safety or co-safety timed property. Proposed runtime enforcers are time retardant: to produce an output sequence, additional delays are introduced between the events of the input sequence to correct it. Runtime enforcers have been prototyped and our simulation experiments validate their effectiveness.
EVIDENCE BASED PRACTICE SYMPOSIUM OCCUPATIONAL THERAPY CLASS OF 2017

Partnering for Change (P4C), a collaborative and tiered model for delivering rehabilitation services, was piloted with Occupational Therapy (OT) services in child care centres. A program evaluation was conducted using a qualitative approach to explore the experiences of the child care centres. Outcomes were compared to previous P4C literature to identify unique considerations for implementing P4C in child care settings. Recommendations for future practice and research have been outlined.
Evaluation of tendering effect from date seed extract (P. dactalytera) in knuckle part meat

Phoenic dactylifera (date) is a species of flowering plants in the family of Arecaceae. Date seeds are considered as a waste from many processing that produced plants pitted date, confectionery date syrup and date itself. Currently, the seeds are used mainly for animal feed in the cattle and chicken industry. In 2004, about 863,000 tonnes of date seeds are produced out of 6.9 million tonnes date. Tenderness is the major concern that affecting consumer acceptance of beef in meat industry. This study was carried out in order to investigate the effects of the bioactive compound extracted from date seed as a tenderizing agent in meat. Extraction of date seeds used a different method of extraction (Soxhlet and Maceration). The application of extracted on knuckle part of beef were performed and papain was used as a positive control and followed by the sensory evaluation. The analysis of cooked meat was performed in order to analyze the physico-chemical properties of date seeds extract. The result from the study revealed that the aqueous extract (maceration techniques) gave the best percentage of the total yield recovery with 28.44%. The physico-chemical properties of cooked meat showed the reducing of pH value after cooking. Meanwhile for the cooking yield, result showed that almost 86% of water losses during cooking for aqueous extract and positive control and 96% for negative control. According to the sensory evaluation of the cooked meat, scoring test and hedonic test were performed using One Way Anova. The result for texture is 6.10±2.1, juiceness is 5.87±1.76 and taste is 6.80±1.34. All attributes have no significant different at p <0.05 between aqueos extract, and positive control. A general acceptance shows that no significant different between aqueos extract (6.50±2.0) and positive control (7.13±1.98). The result suggested that the tenderization effect of date seed improved the textural properties of knuckle part meat and have potential for tenderization purpose in food industry.
Exploiting Search Space Structure in Classical Planning: Analyses and Algorithms

The author has completed 2 years of research in Masters degree and is in the first year of the PhD, which is not so close to the dissertation. As a result, this dissertation abstract contains several speculative materials. This is because the author’s current publications lack the coherent story, primarily due to the lack of good understanding of macro operators and search algorithms in the planning community. I address this issue in the future work sections and make up the coherent story that is necessary to form a viable thesis. At the time of writing this, I expect from the Consortium the advice how to form a viable, coherent dissertation thesis, which is completely different from writing an individual research paper. I also wish to connect with mentors and students in the Consortium for future collaboration, because some of future work may not make way into the thesis. In the following sections, I first present my past work, then I propose some future ideas.
Co-creativity in Videogame Puzzle Creation

This work proposes a solution to improve the cooperation be-tween humans and computer Artiﬁcial Intelligence (AI), as a colleague , in the creation of puzzles for video game levels. With this interaction we hope to give the designer a source of creative stimulus, in order to achieve overall more creative results than those obtained if said designer was working alone. The proposed solution consists of a co-creative puzzle creation tool, focused on improving creativity by allowing human and computer to work together in producing content using the Legend of Grimrock 2 Level Editor, exploring the digital “peer” paradigm. Its interface can be used by the designer to preview generated suggestions and orient its behavior. Suggestions are generated and iteratively evolved by three genetic algorithms and can be guided by the designer on different domains: objective , innovation , user map ; all then combined in a fourth one that re-evaluates the best suggestions of each previous algorithm, again on the three domains, with different weights based on the users conﬁguration, to choose the best suggestion overall. Results showed a positive inﬂuence on the puzzle creation because our approach takes into account the smaller nuances of the co-creative interaction. Outlined improvements such as a better way to support designer-speciﬁc interaction patterns, improved algo-rithm behaviour and integration with past tools set the direction for future work. We concluded that through an intuitive interface, ﬂexible and adjustable behavior, we were able to provide some positive contributions to the quality of the co-creative puzzle creation process.
Towards Explaining Deep Learning Networks to Distinguish Facial Expressions of Pain and Emotions

Deep learning networks are successfully used for object and face recognition in images and videos. In order to be able to apply such networks in practice, for example in hospitals as a pain recognition tool, the current procedures are only suitable to a limited extent. The advantage of deep learning meth-ods is that they can learn complex non-linear relationships be-tween raw data and target classes without limiting themselves to a set of hand-crafted features provided by humans. However, the disadvantage is that due to the complexity of these networks, it is not possible to interpret the knowledge that is stored inside the network. It is a black-box learning procedure. Explainable Artiﬁcial Intelligence (AI) approaches mitigate this problem by extracting explanations for decisions and representing them in a human-interpretable form. The aim of this paper is to investigate the explainable AI method Layer-wise Relevance Propagation (LRP) and apply it to explain how a deep learning network distinguishes facial expressions of pain from facial expressions of emotions such as happiness and disgust.
FATIGUE AND SHEAR PROPERTIES OF HIGH RELIABLE SOLDER JOINTS FOR HARSH APPLICATIONS

The reliability of an electronic product in harsh applications is typically limited by the fatigue failure of one of the interconnected solder joints. Mechanical properties of common lead-free solder joints have been studied for large bulk solder samples. However, the microstructure of solder joints in a realistic application has been proved completely different than that of bulk solder samples, which can lead to different mechanical properties. SnAgCu (SAC) based solder alloys are widely used in the lead -free applications, however, solder alloys with only Sn, Ag and Cu demonstrate low reliability in harsh environments. In this study, individual highreliability SnAgCu based solder joints (Innolot, MaxRel, Ecolloy) were tested to investigate their shear and fatigue properties. The experiment includes shear of individual solder joints under 4 strain rates: 1, 0.1, 0.01, 0.001 sec, and fatigue of individual solder joints under various stress amplitudes. For the shear testing, shear strengths of solder joints for each strain rate were systematically recorded and compared. For the fatigue testing, the effect of stress amplitude on the fatigue life and work dissipation was studied as well. Moreover, the effect of surface finish (OSP, ImAg, and ENIG) on the solder joints reliability was also investigated. The experiment results showed that shear strength tends to increase with the increase of shear strain rate. Solder joints with high Bi and Ag contents demonstrate superior shear and fatigue properties. However, excessive Bi may lead to the embrittlement of solder joints and change of failure modes during mechanical testing.
Satellite products for precipitation estimation in mountain regions: A case study in Nepal

Precipitation in mountain regions is often highly variable and poorly observed , limiting abilities to manage water resource challenges. Here, we evaluate the TRMM 3B-43 monthly precipitation product over Nepal against weather station data. We find that the TR MM precipitation product exhibits little mean bias and reasonable skill in giving precipitation ove r Nepal. Skill 5 can be increased substantially by adjusting for spatial and seasonal bias es using the gridded station precipitation product APHRODITE and by incorporating information f r m the finer resolution satellite product PERSIANN, with the overall Nash-Sutcliffe efficien y i creasing from 0.71 (unadjusted TRMM) to 0.88 (adjusted TRMM). The adjusted TRMM prod uct is promising for use in water resources applications. 10
Spatiotemporal dynamics of eucaryotic gradient sensing

Cell migration plays a crucial role in our birth, survival and death. We are conceived as amorphous fertilized eggs. It is cell migration, among other processes, that sculpts a richly structured embryo from a fertilized egg. While we live, cell migration heals our wounds (Martin, 1997) and protects us from surrounding pathogens (Jones, 2000). But when we age, cell migration can accelerate death. Cancer metastasis is caused by directed migration of tumor cells from their primary site to their preferential sites of metastasis (Moore, 2001). A better understanding of the mechanism of cell migration will have profound biomedical consequences.
Viruses of Microorganisms

Algae are photosynthetic organisms that drive aquatic ecosystems, e.g. fuelling food webs or forming harmful blooms. The discovery of viruses that infect eukaryotic algae has raised many questions about their influence on aquatic primary production and their role in algal ecology and evolution. Although the full extent of algal virus diversity is still being discovered, this review summarizes current knowledge of this topic. Where possible, formal taxonomic classifications are referenced from the International Committee on Taxonomy of Viruses (ICTV); since the pace of virus discovery has far surpassed the rate of formal classification, however, numerous unclassified viruses are discussed along with their classified relatives. In total, we recognized 61 distinct algal virus taxa with highly variable morphologies that include dsDNA, ssDNA, dsRNA, and ssRNA genomes ranging from approximately 4.4 to 560 kb, with virion sizes from approximately 20 to 210 nm in diameter. These viruses infect a broad range of algae and, although there are a few exceptions, they are generally lytic and highly species or strain specific. Dedicated research efforts have led to the appreciation of algal viruses as diverse, dynamic, and ecologically important members of the biosphere, and future investigations will continue to reveal the full extent of their diversity and impact. Introduction Algae are the engines of aquatic ecosystems that convert inorganic matter into organic matter and fuel aquatic food webs. Their growth influences the productivity of aquatic environments, and also environmental quality by either supporting or impeding beneficial human use, e.g. by sustaining fisheries, or forming nuisance blooms. A few decades ago, scientists discovered that viruses infecting eukaryotic algae are present in nearly all aquatic environments, and that most of these pathogens are both speciesspecific and cause the lysis, or death, of their hosts. As an aside, throughout this review we will use the term ‘algae’ specifically to refer to eukaryotic algae; in some discussions of aquatic primary production cyanobacteria are also included under the umbrella term algae, such as in the first two sentences of this paragraph, but here we are focusing only on eukaryotes. Discovery of ubiquitous algal viruses in aquatic environments raised many questions about the influence of viruses on aquatic primary production and their role in algal ecology and evolution, and spurred the development of algal virus ecology as a research field unto itself. Work on this topic has taught us much about the importance of algal viruses, and over the years numerous reviews have summarized this work (Brussaard, 2004; Brussaard and Martínez Martínez, 2008; Dunigan et al., 2006; Kang et al., 2005; Nagasaki, 2008; Short, 2012; Suttle, 2000; Van Etten et al., 2002; Van Etten and Meints, 1999; Wilson et al., 2009; Yamada et al.,