Miracle-dz/UniFAR-FTUs huggingface dataset:
Seroprevalence and Molecular Detection of Bovine Anaplasmosis in Egypt

Bovine anaplasmosis is a tick-borne disease with zoonotic potential, caused by the obligate intracellular bacterium Anaplasma marginale. The disease is distributed worldwide in tropical and subtropical regions. The economic losses from anaplasmosis in animals is of significant importance because it causes severe morbidity and mortality in cattle. Recovered animals may become persistent carriers. Epidemiological information on the actual status of bovine anaplasmosis in Egypt is scarce. Thus, this study aimed to determine anti-Anaplasma antibody and DNA in serum samples using ELISA and PCR, respectively. In total, 758 bovine sera were collected from cattle farms located in 24 Egyptian governorates in 2015 to 2016. Sera were analyzed with the commercially available ‘Anaplasma antibody competitive ELISA v2’ kit and ‘AmpliTest Anaplasma/Ehrlichia spp. real time TaqMan TM PCR. Anaplasma spp. antibodies were detected in 140 (18.5%) (CI: 15.8–21.4%) of the investigated sera by ELISA, and Anaplasma/Ehrlichia-DNA was detected in 40 (5.3%) (CI: 3.8–7.1%) of the positive sera by real time PCR. Co-detection of both Anaplasma spp. and Coxiella burnetii-specific antibodies was proven in 30 (4%) of the investigated sera. The results of this work confirm the significant prevalence of bovine anaplasmosis in Egypt. Raising awareness in decision makers of the public health, veterinarians and animal owners is required to reduce the spread of infection.
INTERNALLY SELF ORGANISING NEURAL NETWORK FOR ONLINE LEARNING OF PERCEPTION TO ACTION MAPPINGS IN SENSOR NETWORKS

This paper presents a neural approach for learning relationships between perceptual classifications and real world actions in sensor networks. The mapping is constructed online using short-term non-specific feedback from the environment. The presented architecture combines an online adaptable classifier with a novel neural mapping function. Simulations demonstrate learning to be fast and stable, and the network to be topologically and synaptically adaptable in response to changing feedback. Results obtained from our experiments demonstrate the possibility of effective online learning using non-specific indicators.
Supplementary material: Multimodal Style Transfer via Graph Cuts

We visualize multimodal style representation in Fig. 1. For each style image, we extract its VGG feature (at layer Conv 4 1 in VGG-19) and cluster it into K = 3 clusters. Then, we conduct t-SNE [7] visualization with the cluster labels. As shown in Fig. 1, clustering results match the multimodal style distribution well. Features in the similar group would tend to have similar cluster number. These observation not only shows the multimodal style distribution, but also demonstrates that clustering is a proper way to model such a multimodal distribution.
Mise au point sur les conséquences hémodynamiques de l’acidose lactique dans les états de choc Hemodynamic Consequences of Severe Lactic Acidosis in Shock States

High lactate concentration with low pH is systematically considered as a marker of severity in critically ill patients and is also a biological marker of tissue oxygen debt irrespective of the initial hypoxic or dysoxic trigger. Lactic acidosis is not only the cause and consequence of reduced cardiac contractility and vascular hyporesponsiveness that arise due to the administration of vasopressors during shock state, but it also displays protective effects against shockinduced cytokine storm. In view of these antagonist effects, the most recent septic shock guideline recommends against the prescription of symptomatic treatment for pH above 7.15 while issuing no recommendation for pH levels < 7.15. This work, based on a critical and personal appraisal of the literature, will describe how lactic acidosis increases during shock, its deleterious effects on the cardiovascular system including its counterintuitive protective effects, and finally the literature on which the various therapeutic options are based.
Exploiting Graph Convolutional Networks for Representation Learning of Mobile App Usage

We propose to apply graph convolutional networks to a novel domain, mobile app usage. User state estimation from smartphone usage has attracted attention thanks to the prevalence of smartphones. Basic statistics such as the sum of the number of used apps and usage duration have been used for estimating the user state. However, the accuracy of user state estimation can be improved by considering the sequence of apps used and the relationship between each app based on graph convolutional networks. In this paper, we proposed a representation learning method for mobile app usage using graph convolutional networks. We evaluate the proposed method through comparison to another deep learning approach, i. e. , long short-term memory, for a classification problem.
High-Frequency Trading, Endogenous Capital Commitment and Market Quality

I study market quality implications of the competition between traditional market making and high-frequency trading. A long-run market maker responds to the competition from high-frequency traders by reducing both the spread and the amount of capital committed in market making. While a lower spread level is beneficial, less capital commitment deteriorates market quality. Specifically, the market's capacity to satisfy large demand is impaired. My model provides a more comprehensive illustration of high-frequency trading's implications on market quality by integrating both price and quantity effects. I further use this framework to analyze implications of different high-frequency trading regulatory measures.
Deploying Efficiently MapReduce Applications in Heterogeneous Computing Environments using Novel Scheduling Algorithms

Cloud computing has become increasingly popular model for delivering applications hosted in large data centers as subscription oriented services. Hadoop is a popular system supporting the Map Reduce function, which plays a crucial role in cloud computing. The resources required for executing jobs in a large data center vary according to the job type. In Hadoop, jobs are scheduled by default on a first-come-first-served basis, which may unbalance resource utilization. This paper proposes a job scheduler called the job allocation scheduler (JAS), designed to balance resource utilization. For various job workloads, the JAS categorizes jobs and then assigns tasks to a CPUbound queue or an I/O-bound queue. However, the JAS exhibited a locality problem, which was addressed by developing a modified JAS called the job allocation scheduler with locality (JASL). The JASL improved the use of nodes and the performance of Hadoop in heterogeneous computing environments. Finally, two parameters were added to the JASL to detect inaccurate slot settings and create a dynamic job allocation scheduler with locality (DJASL). The DJASL exhibited superior performance than did the JAS, and data locality similar to that of the JASL
Accurate 3D Reconstruction by Stereo and ToF Data Fusion

3D video applications require the acquisition of high quality depth information in real time. This issue can be solved using stereo vision systems or time-of-flight (ToF) cameras. Both solutions present critical issues, that can be overcome by their combined use. A heterogeneous acquisition system is considered in this paper, made of two high resolution standard cameras (stereo pair) and one ToF camera. The ToF range camera technology is quite new, therefore a brief description of how a ToF range cameras works is firstly given, presenting also an equivalent AM communication system model. A probabilistic ad hoc fusion algorithm is then derived in order to obtain high quality depth information from the information of both the ToF camera and the stereo-pair. Finally experimental results show the effectiveness of the fusion algorithm in order to extract precise depth information. Part of this work is based on the paper “A Probabilistic Approach to ToF and Stereo Data Fusion” presented at the 3DPVT10 conference.
A Comprehensive Framework for a Risk and Role Based Enterprise Security Awareness, Training and Educati on Program for ISO/IEC 27002 Compliance

Organizations are faced with a variety of ever changing information security risks. This study examines the state of information security, user groups and user roles responsible for and ISO/IEC domains required for risk mitigation in a large public organization in Canada. The objective is to develop a comprehensive risk and ro le based framework for an enterprise security awareness, training and education (SATE) program for ISO/IEC 27002 compliance with the intent to improve an existing SATE program in a large public organization. This paper discusses th e results of an information security survey conducted in 2010 an d describes the framework and its components and inte ractions. Significant findings of this study include: (1) a new and more comprehensive set of user roles within a user group for a SATE program not previously identified by the SANS Institute, (2) a significant number of new threats and vulnerabilities not previously identified in global and national information security surveys, (3) the use of a risk factor to prioritize what information security risks should be addressed in a SATE program, (4) the rationalization for the subject content in an enterprise SATE program and (5) a framework for a risk and role based enterprise SATE program f or ISO/IEC 27002 compliance. Keywords-component; user role; role based; risk based; ISO/IEC 27002 compliance; security awareness; security training; security education; threats; vulnerabilities
Risk Evaluation of Pyrolyzed Biochar from Multiple Wastes

This paper aims at demonstrating the significance of biochar risk evaluation and reviewing risk evaluation from the aspects of pyrolysis process, feedstock, and sources of hazards in biochar and their potential effects and the methods used in risk evaluation. Feedstock properties and the resultant biochar produced at different pyrolysis process influence their chemical, physical, and structural properties, which are vital in understanding the functionality of biochar. Biochar use has been linked to some risks in soil application such as biochar being toxic, facilitating GHGs emission, suppression of the effectiveness of pesticides, and effects on soil microbes. These potential risks originate from feedstock, contaminated feedstock, and pyrolysis conditions that favor the creation of characteristics and functional groups of this nature. These toxic compounds formed pose a threat to human health through the food chain. Determination of toxicity levels is a first step in the risk management of toxic biochar. Various sorption methods of biochar utilized low-cost adsorbents, engineered surface functional groups, and nZVI modified biochars. The mechanisms of organic compound removal was through sorption, enhanced sorption, modified biochar, postpyrolysis thermal air oxidation and that of PFRs degradation was through activation, photoactive functional groups, magnetization, and hydrothermal synthesis. Emissions of GHGs in soils amended with biochar emanated through physical and biotic mediated mechanisms. BCNs have a significance in reducing the health quotient indices for PTEs risk contamination by suppressing cancer risk arising from consumption of contaminated food. The degree of environmental risk assessment of HM pollution in biomass and biochars has been determined by using potential ecological risk index and RAC while organic contaminant degradation by EPFRs was considered when assessing the environmental roles of biochar in regulating the fate of contaminants removal. The magnitude of technologies’ net benefit must be considered in relation to the associated risks.
Perceived threats of vision impairment and its effect on consumption pattern of dietary supplement of lutein and zeaxanthin

Purpose: To explore perceived threats of vision impairment as well as the perceived benefits and barriers of lutein-containing supplements using a health belief model (HBM), and also to assess how these may affect dietary supplement consumption behaviours. Methods: A structured questionnaire was developed on HBM through a focus group interview to gather information from 1,075 drugstore customers in Taiwan. Respondents were 55.16 % female, 64.47 % married, 53.12 % aged between 31 and 50 years, and 91 % with at least a high school education. Results: Perceived severity was much higher that perceived susceptibility. Susceptibility was the most stable construct. Occupation, residence area, and workplace were the top three factors differentiating the variance in HBM constructs. Perceived benefits appeared as the most powerful predictor, followed by perceived barriers. HBM predictors jointly explained 21.9 % of the variance in luteinand zeaxanthintaking behaviour. Moderating effects of health-related information were not significant. Conclusion: HBM is useful to understand this behaviour. Consumer behaviour is mainly affected by perceived benefits, and not the threat of vision impairment. Since people ignore the possibility of suffering severe vision impairment, more health education is required.
Encrypted and Unencrypted Computation for Abstract Machine

Security is a major issue nowadays. Many cryptographic algorithms are used for maintaining data security. For performance as well as for physical security reasons, it is often advantageous to realize cryptographic algorithms in hardware. This proposed system based on heterogeneous abstract machine for encrypted and unencrypted compute program. In this abstract machine encryption and decryption of data is done in same memory location. The following situations are considered: several users upload data encrypted with a public-key FHE, a server carries out computations on the encrypted data and then sends them to an agency who has a decryption key for the FHE. In this situation, one approach to reduce the storage requirement is to use AES encryption to encrypt data, and then perform homomorphism computations on cipher texts after converting to FHE-cipher texts.
Quality assurance of qualitative research: a suggested approach for assessing and strengthening qualitative research within global health trials

The concept of quality assurance of clinical trials is well established, as are the mechanisms and processes for enacting it, informed largely by the Good Clinical Practice (GCP) guidelines (European Medicines Agency 2002). The GCP guidelines are designed to assure the protection of research participants, and the credibility and quality of trial data and results. Questions have been raised about the suitability of GCP beyond drug registration trials, and the burden that adherence to the guidelines poses for researchers, particularly in low income countries (Lang, White et al. 2010). However, GCP remains the universal standard for quality assurance of trials and has become a legal requirement for conducting clinical trials in a number of countries, leading to a culture of structured, standardised processes for maintaining and demonstrating quality in clinical research.
Early Attentional Modulation by Working Memory Training in Young Adult ADHD Patients during a Risky Decision-Making Task

Background: Working memory (WM) deficits and impaired decision making are among the characteristic symptoms of patients affected by attention deficit/hyperactivity disorder (ADHD). The inattention associated with the disorder is likely to be due to functional deficits of the neural networks inhibiting irrelevant sensory input. In the presence of unnecessary information, a good decisional process is impaired and ADHD patients tend to take risky decisions. This study is aimed to test the hypothesis that the level of difficulty of a WM training (WMT) is affecting the top-down modulation of the attentional processes in a probabilistic gambling task. Methods: Event-related potentials (ERP) triggered by the choice of the amount wagered in the gambling task were recorded, before and after WMT with a the dual n-back task, in young ADHD adults and matched controls. For each group of participants, randomly assigned individuals were requested to perform WMT with a fixed baseline level of difficulty. The remaining participants were trained with a performance-dependent adaptive n-level of difficulty. Results: We compared the ERP recordings before and after 20 days of WMT in each subgroup. The analysis was focused on the time windows with at least three recording sites showing differences before and after training, after Bonferroni correction (p<0.05). In ADHD, the P1 wave component was selectively affected at frontal sites and its shape was recovered close to controls’ only after adaptive training. In controls, the strongest contrast was observed at parietal level with a left hemispheric dominance at latencies near 900 ms, more after baseline than after adaptive training. Conclusion: Partial restoration of early selective attentional processes in ADHD patients might occur after WMT with a high cognitive load. Modified frontal sites’ activities might constitute a neural marker of this effect in a gambling task. In controls, conversely, an increase in late parietal negativity might rather be a marker of an increase in transfer effects to fluid intelligence.
The Impact of Binocular Vision and Tracking Intervention on Academic Performance: An In-School Vision Therapy Pilot Program

Background: Convergence insufficiency (CI) and saccadic deficiency (SD) are common visual conditions that can cause negative effects on a child’s learning. It is postulated that with early vision therapy (VT) intervention to treat these visual conditions, associated learning difficulties and frustrations could be avoided as a child progresses through school. Methods: Twenty-nine second grade students were evaluated for a binocular vision or oculomotor disorder. Subjects diagnosed with a disorder were enrolled in an in-school VT program, grouped based on their diagnosis. Seventeen subjects completed the VT program. At the end of VT, those who completed therapy were evaluated to monitor their progress and academic performance. Results: Subjects diagnosed with CI showed a statistically significant improvement in their near point of convergence (NPC) break value (p=0.042). Subjects diagnosed with SD showed a statistically significant improvement in their Developmental Eye Movement (DEM) test adjusted horizontal score (p=0.008), DEM ratio (p=0.037), Northeastern State University College of Optometry (NSUCO) saccade testing accuracy (p=0.043), head movement (p=0.003), and body movement (p = 0.010) scores, as well as mathematics standardized testing (p=0.034) scores. Subjects who were not enrolled in VT showed a statistically significant improvement in their math standardized test scores (p=0.018). When comparing all subjects who were enrolled in VT to all subjects who were not, there was a statistically significant difference in the pre-therapy math (p=0.036) and reading (p=0.003) standardized test scores, in the post-therapy math standardized test scores (p=0.012), and in the difference between preand post-standardized math scores (p=0.047). Conclusion: In-school VT has the potential to create improvements in visual performance for children, especially those with SD. This type of program also has the potential to improve standardized test scores in math (especially in those with SD) and reading. Further research is needed to determine whether a longer course of VT or a program structured differently may improve results in children with CI.
Procalcitonin levels among patients with fever secondary to intracerebral hemorrhage and severe infection. A cross-sectional study

INTRODUCTION In intensive care units (ICUs), delay in diagnosis and treatment increases mortality rates. Serious infections among ICU patients most commonly consist of respiratory tract infections, followed by urinary system infections, wound site infections and primary bacteremia.1,2 Fever in patients hospitalized in ICUs is an important indicator of infection. Despite new treatment alternatives, the infection-related mortality rate remains high. Likewise, clinical findings of fever remain frequent. Moreover, routine laboratory tests are not specific and sometimes may mislead clinicians. Lack of early-phase and specific markers for diagnosing infection cause delays in treatment and unnecessary use of antibiotics.3 Early diagnosis and appropriate antibiotherapy decrease infection-related morbidity and mortality.4 Assessment of clinical and laboratory findings constitutes an ideal method for diagnosing infection. Growth of an infectious agent through culturing provides the most important laboratory evidence. However, this method is time-consuming. While awaiting the results from culturing, other diagnostic laboratory parameters such as the levels of procalcitonin (PCT), C-reactive protein (CRP), leukocytes, neutrophils and erythrocyte sedimentation rate (ESR) have been used. Over recent years, serum PCT has been found to be an important and promising biomarker for making the initial diagnosis of infection.5 The incidence of fever in ICUs is 23%. 6 Nearly 50% of these cases relate to noninfectious etiologies. The noninfectious causes of fever include bleeding, atelectasis, drug effects, venous thromboembolism and blood transfusion reactions.7 Another noninfectious type of fever seen in ICUs is central fever in patients diagnosed with intracerebral hemorrhage.6 Central fever has been defined as emergence of fever in patients with intracerebral IMD. Attending Physician, Department of Infectious Diseases and Clinical Microbiology, Fırat Üniversitesi Tıp Fakültesi, Elazig, Turkey. orcid.org/0000-0002-0863-8530 IIMD. Professor, Department of Infectious Diseases and Clinical Microbiology, Fırat Üniversitesi Tıp Fakültesi, Elazig, Turkey. orcid.org/0000-0003-2560-3265 IIIMD. Associate Professor, Department of Infectious Diseases and Clinical Microbiology, Fırat Üniversitesi Tıp Fakültesi, Elazig, Turkey. orcid.org/0000-0002-9052-7986 IVMD. Professor, Department of Immunology, Fırat Üniversitesi Tıp Fakültesi, Elazig, Turkey. orcid.org/0000-0003-0463-3422 VMD. Professor, Department of Infectious Diseases and Clinical Microbiology, Fırat Üniversitesi Tıp Fakültesi, Elazig, Turkey. orcid.org/0000-0002-6515-011X VIMD. Professor, Department of Anesthesia and Reanimation, Fırat Üniversitesi Tıp Fakültesi, Elazig, Turkey. orcid.org/0000-0002-0072-8582
Silver Nanoparticles against Foodborne Bacteria. Effects at Intestinal Level and Health Limitations

Foodborne diseases are one of the factors that endanger the health of consumers, especially in people at risk of exclusion and in developing countries. The continuing search for effective antimicrobials to be used in the food industry has resulted in the emergence of nanotechnology in this area. Silver nanoparticles (Ag-NPs) are the nanomaterial with the best antimicrobial activity and therefore, with great potential of application in food processing and packing. However, possible health effects must be properly addressed to ensure food safety. This review presents a detailed description on the main applications of Ag-NPs as antimicrobial agents for food control, as well as the current legislation concerning these materials. Current knowledge about the impact of the dietary exposure to Ag-NPs in human health with special emphasis on the changes that nanoparticles undergo after passing through the gastrointestinal tract and how they alter the oral and gut microbiota, is also summarized. It is concluded that given their potential and wide properties against foodborne pathogens, research in Ag-NPs is of great interest but is not exempt from difficulties that must be resolved in order to certify the safety of their use.