Miracle-dz/UniFAR-FTUs huggingface dataset:
Isolation and Identification of Methicillin Resistance Staphylococcus aureus and Detection their Ability to the Production of Virulence Factors

* Objectives: Isolation and Identification of S.aureus and study their susceptibility to the production of virulence factors. * Methods: A total of 50 clinical specimens of Staphylococcus aureus isolates were collected in AL- Najaf AL-Asharaf governorate during the period of (10/10/2013-20/1/2014) by the cultural characteristic colonies, microscopic for cells, biochemical tests, antibiotics susceptibility test to Staphylococcus aureus using an antibiotic diffusion disc assay, in addition to studying the virulence factors produced from S.aureus . * Results: The results show that the Staphylococcus aureus resistant to methicillin formed 70% and 30% of isolates were sensitive to the same antibiotics. Tested 10 isolates to methicillin-resistant for their efficiency in forming the highest inhibitory areas for testing their sensitivity to other antibiotics used, the results show S.aureus resistant to penicillin about 100%, while there is no resistance to CO-Trimethoprim because it was sensitive completely 100%. The susceptibility investigated of Staphylococcus aureus resistance methicillin isolates to the production of biofilm and slime layer with using both tube method and growth on Congo red agar respectively. Ten isolates of S.aureus were tested based on resistance to methicillin and their high susceptibility to the production of the biofilm and the slime layer. * Conclusion: So we conclude, they have Staphylococcus aureus is highly resistant to β- Lactam antibiotics and the CO-trimethoprim is the most effective in the inhibiting growth of this bacteria. In addition to its ability to produce virulence factors. The increase cause bacterial resistance to our local isolates may be due to the frequent use of antibiotics, which allowed for increased bacterial resistance to various antibiotics.
Threshold Effect of Institutional Quality and the Validity of Environmental Kuznets Curve

Using a threshold estimation technique, this study examines the validity of environmental Kuznets curve (EKC) under different institutional quality regimes. A combined set of 99 developed and developing countries over the period from 2008 to 2016 has been chosen to confirm the issue in hand. Adopting panel threshold regression technique by Hansen (1999), the paper finds evidence substantiating the presence of single threshold effect. In general, we find that EKC hypothesis does not hold in the full sample analysis, in which high income fails to bring environmental degradation down. Only in the case of a segregated sample of developed countries, we find that the impact of high income (or income square) on environmental degradation is negative and significant after a certain level of ‘high’ institutional quality has been attained. On the contrary, EKC is found to be invalid, and high income fails to be converted fully to environment-protecting activities in developing countries. Therefore, the effectiveness of income in mitigating environmental issues seems to be dampened by the poor institutional quality in developing countries.
One dimensional fractional frequency Sumudu transform by inverse α−difference operator

In this paper, we define fractional frequency Sumudu transform by inverse α−difference operator. Here we present certain new results on Sumudu transform of polynomial factorial, trigonometric and geometric functions using shift value. Finally, we provide the relation between convolution product and fractional Sumudu transform of polynomial and exponential function. Numerical results are verified and analysed the outcomes by graphs.
Profil Penggunaan Antibiotik Pada Pasien Pediatri Rujukan Berdasarkan Sistem Defined Daily Dose (DDD)

Tujuan dari penelitian ini adalah untuk mengetahui profil penggunaan antibiotik pada pasien pediatri yang dirujuk ke RSPAL Dr. Ramelan selama bulan April hingga Juli 2019. Penelitian ini merupakan penelitian observasional deskriptif yang dilakukan secara prospektif. Variabel yang terlibat adalah besar penggunaan antibiotik yang dinyatakan dalam satuan Defined Daily Dose (DDD)/100 hari rawat inap dan standar yang digunakan berdasarkan ketentuan dari WHO. Terdapat 30 subyek yang dirujuk ke RSPAL Dr. Ramelan. Sebagian besar subyek telah tinggal lebih dari 48 jam di rumah sakit sebelumnya, mereka menerima antibiotik sejak hari pertama di RSPAL Dr. Ramelan. Sebanyak 13 subyek (43%) menerima antibiotik yang serupa dengan rumah sakit sebelumnya dan 17 subyek lainnya (57%) tidak. Hasil penelitian menunjukkan bahwa penghitungan total konsumsi antibiotik sebesar 10,50 DDD/100 hari-rawat dari 8 jenis antibiotik yang digunakan yaitu ampisilin-sulbaktam, kloksasilin, seftriakson, amikasin, gentamisin, meropenem, levofloksasin, dan metronidazol. Konsumsi antibiotik tertinggi adalah meropenem yang memiliki 3,49 DDD/100 hari-rawat, konsumsi antibiotik terendah adalah kloksasilin yang memiliki 0,05 DDD/100 hari-rawat. Diharapkan penelitian ini dapat menjadi salah satu indikator evaluasi penggunaan antibiotik yang dilakukan di rumah sakit agar dapat meningkatkan rasionalitas penggunaan antibiotik sehingga menurunkan resiko penyebaran resistensi antibiotik khususnya melalui pasien rujukan.
Scalable molecular dynamics with NAMD on the Summit system

NAMD (NAnoscale Molecular Dynamics) is a parallel molecular dynamics application that has been used to make breakthroughs in understanding the structure and dynamics of large biomolecular complexes, such as viruses like HIV and various types of influenza. State-of-the-art biomolecular simulations often require integration of billions of timesteps, computing all interatomic forces for each femtosecond timestep. Molecular dynamics simulation of large biomolecular systems and long-timescale biological phenomena requires tremendous computing power. NAMD harnesses the power of thousands of heterogeneous processors to meet this demand. In this paper, we present algorithm improvements and performance optimizations that enable NAMD to achieve high performance on the IBM Newell platform (with POWER9 processors and NVIDIA Volta V100 GPUs) which underpins the Oak Ridge National Laboratory's Summit and Lawrence Livermore National Laboratory's Sierra supercomputers. The Top-500 supercomputers June 2018 list shows Summit at the number one spot with 187 Petaflop/s peak performance and Sierra third with 119 Petaflop/s. Optimizations for NAMD on Summit include: data layout changes for GPU acceleration and CPU vectorization, improving GPU offload efficiency, increasing performance with PAMI support in Charm++, improving efficiency of FFT calculations, improving load balancing, enabling better CPU vectorization and cache performance, and providing an alternative thermostat through stochastic velocity rescaling. We also present performance scaling results on early Newell systems.
Internet Addiction Among KNUST School of Medical Sciences and Dentistry (KSMD) Students - A Preliminary Study in Ghana.

The rising rate of internet accessibility has brought with it an attendant challenge of Internet Addiction (IA). This study assessed the level of IA and its relationships to loneliness, self-esteem, and satisfaction with life focusing on students of the Kwame Nkrumah University of Science and Technology School of Medical Sciences (KSMD) Kumasi, Ghana. The cross-sectional survey method was used with 122 students conveniently sampled from KSMD. From the findings, no severe internet addiction was found, however, 9.84 % and 41.80 % scored in the moderate and mild internet addiction ranges respectively. The results also indicated a weak positive correlation between internet addiction and loneliness, self-esteem and a weak negative but highly significant association with satisfaction with life. While severe IA is not yet a serious problem, 9.83 and 41.3% of the study population suffered from moderate and mild IA respectively and stood the risk of progressing to the severe end of the IA continuum. Counseling was therefore recommended for students to master control over their internet usage. Keywords: Internet addiction, Loneliness, Self-Esteem, Satisfaction with Life.
Sentiment Analysis: A Case Study among the selected Government Agencies in the Philippines

This paper describes a sentiment analysis method to analyze comments polarity and to facilitate selected government agencies such as DepEd, DPWH, DILG, DND, DSWD, and DOH to describe quantitatively the opinions and comments of active users and citizens on social networks such as YouTube. The method used was from the latest comments from the first 100 were selected from each video to form the final datasets used in the study. The comments were extracted from 1450 videos and contain a total number of 14,506 posts. The objectives of the study were (1) to analyze the citizen’s attitude among the six government agencies in the category of positive and negative polarity. (2) to utilized the results in developing a decision support system.
A Crowdsourced Mobile App Architecture for Plotting User Rated Free WiFi Hotspots

Free WiFi hotspots are gaining popularity in public spaces and private businesses alike. Governmental bodies are installing hotspots across frequently visited places to connect their citizens to information and other online services, while businesses are attracting and retaining customers with value-added free WiFi services on their premises. As more hotspots come into activity, keeping track of all the free WiFi locations can soon become a challenging task for a common user. To add to the dilemma, free hotspots services are often discontinued without prior notice. In this paper, the architecture and implementation of a crowdsourced mobile app system to keep track of active WiFi hotspots on a map is presented. The mechanism to allow users to add new hotspots to the map and provide a rating for the quality of a free hotspot is also described.
Vitamin D3 levels in allergic rhinitis: a case control study from South Karnataka

Allergic rhinitis (AR) is a commonest type of noninfective rhinitis encountered in day to day otolaryngology practice. There is significant disease burden worldwide due to this condition. Most common symptoms of this condition include sneezing, rhinorrhea, nasal obstruction, itching and sometimes anosmia. AR negatively effects quality of life of the patient. It can impact school attendance, workplace performance and social life. Allergic rhinitis is an IgE mediated immune response which occurs when nasal mucosa is exposed to the allergen. Etiology of allergy is still an area of active research and there are ongoing trials which are trying to identify exact etiology of various types of allergy. Recently vitamin D3 is being studied extensively and found be one of the causes for food allergy, asthma and eczema. Role of vitamin D3 in AR seems to be as a disease modifying factor rather than disease causing factor. 5 It is already known that vitamin D3 influences activity of B cells, T cells, macrophages and monocytes. Vitamin D3 seems to be having profound impact on innate and adaptive immunity. It also modulates immunity by influencing the activity of various cytokines ABSTRACT
Linking fish assemblages to hydro‐morphological units in a large regulated river

Flow‐related changes of physical habitat represent a potentially significant environmental filter determining the presence and composition of fish assemblages in rivers. The mesoscale (100–103 m) of river habitat has been identified as an appropriate resolution to model linkages between fish and their abiotic environment that are relevant yet logistically feasible for management of large rivers with complex habitats and diverse fish assemblages. This study identified well‐defined mesohabitat types (i.e. hydro‐morphological units) that influence the fish community of the lower Saint John River, New Brunswick, downstream of a large hydropower generating station (the Mactaquac Generating Station). Four hydro‐morphological units or habitats (i.e. pool, riffle, run and slack water) were identified and linked to three distinct fish assemblages. Eurytopic species represent habitat generalists that were common among all habitats throughout the study area. Rheophilic species preferred fast‐flowing run habitat, whereas limnophilic species were mainly associated with slack water habitat. Riffle habitats that frequently run dry during low flows were mostly vacant of fish species, suggesting that fish assemblages that would naturally occur in these environments could be affected by fluctuations in flow (i.e. hydropeaking) due to dam operation. Our improved understanding of the relationship between fish assemblages and hydro‐morphological units is a fundamental first step to develop meaningful habitat models that can facilitate the effective evaluation of flow management options regarding hydropower and other flow manipulation activities in large rivers with diverse fish fauna.
Comparison of Optimization of Exergy Efficiency of a Crude Distillation Unit Using Artificial Neural Network (ANN) and Response Surface Methods (RSM)

The study carried out simulation of the Crude Distillation Unit (CDU) of the New Port Harcourt Refinery (NPHR) and performed exergy analysis of the Refinery. The Crude Distillation Unit (CDU) of the New Port Harcourt refinery was simulated using HYSYS (2006.5). The Atmospheric Distillation Unit (ADU) which is the most inefficient unit and where major separation of the crude occurs was focused on. The simulation result was exported to Microsoft Excel Spreadsheet for exergy analysis. The ADU was optimized using statistical method and Artificial Neural Network. Box-Behnken model was applied to the sensitive operating variables that were identified. The statistical analysis of the RSM was carried out using Design Expert (6.0). Matlab software was used for the Artificial Neural Network. All the operating variables were combined to give the best optimum operating conditions. Exergy efficiency of the ADU was 51.9% and 52.4% when chemical exergy was included and excluded respectively. The optimum operating conditions from statistical optimization (RSM) are 586.1 K for liquid inlet temperature, 595.5 kPa for liquid inlet pressure and condenser pressure of 124 kPa with exergy efficiency of 69.6% which is 33.0% increment as compared to the base case. Original Research Article Braimah; JERR, 14(3): 1-14, 2020; Article no.JERR. 58522 2 For the ANN optimization, the exergy efficiency of the ADU was estimated to be 70.6%. This gave an increase of 34.9% as compared to the base case. This study concluded that enormous improvement can be achieved both in design feasibility and improved efficiency if the feed operating parameters and other sensitive parameters are carefully chosen. Furthermore, ANN optimization gave better exergy efficiency of 70.6% than RSM optimization of 69.6%.
Noise analysis using Tucker decomposition and PCA on spectral images

Given the improvement of Remote Sensing (RS) sensors, it has been possible to increase spatial and spectral resolution on many of them. Nevertheless, the amount of data to represent and post-process has become highly prohibitive. Therefore, the need to be able to process such huge data sets, and one of the possible ways to deal with problems is the use of compression methods, however, data loss happen if the need of data size reduction is a must. RS spectral imagery contain high quantities of redundant information along the spectral domain, thus, making possible to use compression methods effectively as for example, tensor decomposition algorithms. In Tucker decomposition (TKD), an interesting and strange phenomenon happens when spatial domain is maintained and spectral domain is reduced, as a preprocessing step of a semantic segmentation task. Under these conditions, it is possible to observe an improvement on Pixel Accuracy (PA) metric when it is compared with the same uncompressed spectral image. Therefore, this work presents a study on how noise affects the Tucker Decomposition compared with Principal Component Analysis (PCA) and its impact in semantic segmentation.
Unified approaches on talent development in football? Differences and similarities among representatives from a football association and two professional football clubs

Abstract Talent development is a major task for most coaches, both in professional and non-professional clubs. This study provides a qualitative analysis of how coaches and administrators from both the national football association and two professional clubs express their beliefs on coaching/skill acquisition perspective on how talent development should be done. This article consists of 14 semi-structured interviews with three administrators and two coaches at the Norwegian football federation and two administrators and seven coaches from two professional clubs. The results suggest shared views on the necessity of joining a professional club to become an elite player, although the perceived importance of the professional clubs differs among the respondents. Concerning early recruitment, some of the association and elite coaches believe present practice is able to identify and recruit the most talented players. The professional clubs are also aware of the risk of missing out on talented players, but justify their practice of early recruitment of talented players on increased competition. These different perspectives on talent development comparing representatives from the association and professional clubs could potentially effect the future talent development process and results.
A China Railway Express-Based Model for Designing a Cross-Border Logistics Information Cloud Platform Scheme

This paper describes the development and plans for the implementation of a cloud-based logistics platform to enable and optimize cross-border shipping, using the China Railway Express (CR Express) in the context of China’s recent One Belt and One Road (OBOR) initiative as an example of an extremely complex system that is running at suboptimal efficiency. We design a cross-border logistics information cloud platform (CLICP) and its architecture. The proposed CLICP comprises a hybrid cloud model with three layers of cloud services. We also examine the CLICP’s operation and the design of the platform’s functions, including core business and value-added service functions, such as real-time bidding, freight information push, and carrier one-stop service management functions. Finally, we propose a model for deploying our CLICP. Our study makes a significant contribution to the literature because of its hybrid cloud model architecture and for the completeness of its functionality. The study also has a good application prospect for the operation of CR Express and will play a better supporting role in cross-border logistics.
OneCommunity Reads: A Model for Latino Parent-Community Engagement and Its Effect on Grade-Level Reading Proficiency

The importance of establishing effective literacy/reading skills at an early age, preschool to early elementary, is well known and accepted among educators. For students whose heritage language is not English, the influential factors of cultural relevance and parent/family involvement for the acquisition of these fundamental skills are underscored. OneCommunity (OC) Reads is a literacy program focused on enhancing Latino children’s reading proficiency in a culturally sensitive manner utilizing the funds of knowledge of parents/families and community. Using a community-based, participatory evaluation/research paradigm, the impact of OC Reads was examined using both quantitative and qualitative data. Findings indicated parents/families were affected positively, resulting in increased empowerment and involvement in the schools and the community. Themes derived from the qualitative data included (a) broad empowerment, (b) increased mutual understanding and respect, (c) shared responsibility, and (d) academic and reading improvement. Strengths were noted in the areas of culturally sensitive and helpful processes, and additional activities and enhancements. OC Reads’ success in enhancing literacy/reading proficiency with its nontraditional approach of empowering parents and building on the cultural realities of the students gives further credence to the literature regarding the success of such approaches.
Ensuring safety for vehicle parking tasks using Hamilton-Jacobi reachability analysis

In this paper, we propose an approach for ensuring the safety of a vehicle throughout a parking task, even when the vehicle is being operated at varying levels of automation. We start by specifying a vehicle parking task using linear temporal logic formulae that can be model checked for feasibility. The model-checking is facilitated by the construction of a temporal logic tree via Hamilton-Jacobi reachability analysis. Once we know the parking task is feasible for our vehicle model, we utilize the constructed temporal logic tree to directly synthesize control sets. Our approach synthesizes control sets that are least-restrictive in the context of the specification, since they permit any control inputs that are guaranteed not to violate the specification. This least-restrictive characteristic allows for the application of our approach to vehicles under different modes of operation (e.g., human-in-the-loop shared autonomy or fully-automated schemes). Implementing in both simulation and on hardware, we demonstrate the approach’s potential for ensuring the safety of vehicles throughout parking tasks, whether they are operated by humans or automated driving systems.
Enabling accurate indoor localization for different platforms for smart cities using a transfer learning algorithm

Indoor localization algorithms in smart cities often use Wi‐Fi fingerprints as a database of Received Signal Strength (RSS) and its corresponding position coordinate for position estimation. However, the issue of fingerprinting is the use of different platform‐devices. To this end, we propose a Long Short‐Term Memory (LSTM)‐based novel indoor positioning mechanism in smart city environment. We used LSTM, a type of recurrent neural network to process sequential data of users trajectory in indoor buildings. The proposed approach first utilizes a database of normalizing fingerprint landmarks to calculate WiFi Access Points (WAPs) RSS values to mitigate the fluctuation issue and then apply the normalization parameters on the RSS values during the online phase. Afterwards, we constructed a transfer model to adapt the RSS values during the offline phase and then applying it on the RSS values from the different smartphones during the online phase. Thorough simulation results confirm that the proposed approach can obtain 1.5 to 2 meters positioning accuracy for indoor environments, which is 60% higher than traditional approaches.
A Representation Method for Cellular Lines based on SVM and Text Mining

One important problem in Bioinformatics is the discovery of new interactions between cellular lines and chemical compounds. In silico methods for cell-line screening are fundamental to optimize cost and time in the drug discovery processes. In order to build these methods, we need to computationally represent cell lines. Current methods for modeling cell line interactions rely on comparing genetic expression profiles. However, these profiles are usually unknown.In this work, we present a method to characterize and represent cell lines by text processing the related scientific literature. We collect abstracts of scientific papers about cellular lines from Cellosaurus and PubMed. These documents are then represented as TF-IDF vectors. We build a data set for classification with the document vectors having the cell line identifier as the target class. We then apply a multiclass SVM classification method. We use Support Vector Domain Description to describe and characterize each cell line with its corresponding hyperplane obtained with a one-vs-rest training. We evaluated several configurations of classifiers, using micro-averaged precision as metric to choose the best classifier, and were able to differentiate cellular lines from a set of 200+.