Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Style Preferences among Pre-clinical Medical Students in a Public University in Pahang

Educational experts affirm that students prefer various type of learning preference. It is known that the learning style preferences vary among medical students worldwide. Knowing the types will help medical educators to improve their way of conveying lectures and teaching in a more effective learning environment. This study aims to describe the learning style preferences of pre-clinical medical students and the association with their socio-demography. This is a cross sectional study done among Year 1 and Year 2 pre-clinical year medical students in a public university in Kuantan Pahang. Medical students who fulfilled the inclusion and exclusion criteria were recruited using systematic random sampling. A validated learning style questionnaire (VARK) was used to assess their learning style. Descriptive statistics and bivariable analysis was used using SPSS version 23. A total of 166 pre-clinical year medical students participated in this study. The mean age was 21.3 (0.84). Majority of them were Malays (98.2%) and females (69.9%). Most of the students preferred unimodal learning style (80.0%) with the most preferred learning style preferences being kinaesthetic (39.1%). Bivariable analysis showed female students preferred kinesthetic learning style compared to male students (p=0.03). In this study, majority of the pre-clinical year medical students preferred ‘life-like’ learning experience in their study. Hence, we recommend that medical educators to be more aware of the varieties of learning style preferences in order to improve the quality of teaching and learning experiences.
Chinese attitudes towards global financial regulatory cooperation: revisionist or status quo?

International financial regulatory cooperation since its beginnings in the early 1970s has been dominated by a handful of advanced countries. Until very recently, almost all developing countries played no significant role in the formulation of global regulatory norms and standards. After the global financial crisis of 2008-9, the G 20, which had itself displaced the G-7 as the key grouping in global economic governance, directed all of the major global institutions involved in standard-setting to undertake reforms to their governance structure so as to reflect the changed political environment. Accordingly, a number of emerging market countries have been brought into the inner of global regulatory standard setting, including organizations such as the Basel Committee (BCBS), IOSCO, IASB, and the FSB. Most of these institutions remain, along with the G20 itself, dominated by advanced countries from Europe and North America. Nevertheless, the crisis has brought some major emerging market countries into the inner circles of global regulatory standard-setting for the first time (see table 1 in Chapter 1). As the introductory chapter in this volume notes, the expanded role of major developing countries in the process of international standard setting raises crucial questions about the significance of the crisis and the future of global economic governance. But how do the major emerging countries approach global standard-setting and how (if at all) has the recent crisis affected their attitudes towards it?
The Arg753Gln polymorphism of the human Toll-like receptor 2 gene in tuberculosis disease

Toll-like receptor 2 (TLR2), a member of the Toll-like receptor family, plays an important role in recognition of, and subsequent immune response activation against, mycobacteria. The genetic polymorphism of TLR2 (arginine to glutamine substitution at residue 753 (Arg753Gln)) has been associated with a negative influence on TLR2 function, which may, in turn, determine the innate host response to mycobacteria. The aim of the present study was to investigate the Arg753Gln single nucleotide polymorphism of the TLR2 gene in tuberculosis (TB) patients compared to healthy controls. A retrospective case/control study was carried out. The Arg753Gln polymorphism of the TLR2 gene was studied in 151 TB patients compared to 116 ethnically and age-matched healthy control subjects. The TLR2 polymorphism (adenine (A) allele) was observed in 17.9 and 7.7% of TB patients and controls, respectively. When the ratios of the three genotypes were compared between the two groups, the AA genotype was found to be more significantly associated with TB. Allele frequencies for guanine (G) and A were found to be 0.95 and 0.05 in the control group and 0.86 and 0.14 in the TB patient group, respectively. The risk of developing TB disease was increased 6.04‐ and 1.60‐fold for carriers of the AA and GA genotypes, respectively. In conclusion, the present data suggest that the arginine to glutamine substitution at residue 753 polymorphism of the Toll-like receptor 2 gene influences the risk of developing tuberculosis.
Activity classification using realistic data from wearable sensors

Automatic classification of everyday activities can be used for promotion of health-enhancing physical activities and a healthier lifestyle. In this paper, methods used for classification of everyday activities like walking, running, and cycling are described. The aim of the study was to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required. A large and realistic data library of sensor data was collected. Sixteen test persons took part in the data collection, resulting in approximately 31 h of annotated, 35-channel data recorded in an everyday environment. The test persons carried a set of wearable sensors while performing several activities during the 2-h measurement session. Classification results of three classifiers are shown: custom decision tree, automatically generated decision tree, and artificial neural network. The classification accuracies using leave-one-subject-out cross validation range from 58 to 97% for custom decision tree classifier, from 56 to 97% for automatically generated decision tree, and from 22 to 96% for artificial neural network. Total classification accuracy is 82% for custom decision tree classifier, 86% for automatically generated decision tree, and 82% for artificial neural network
Supporting adaptable applications in grid resource management systems

Grid computing promises to bring the resources to satisfy the increasing requirements of scientific applications. As grids result from several organizations that pool their computational resources, resource availability varies frequently inside grids. Relying on autonomous dynamic adaptability and managing dynamic collections of resources, technologies have been proposed in order to handle those variations at the level of applications. However, despite applications have evolved in order to fit better dynamic grid environments, grid resource managers still restrict to rigid jobs, thus inhibiting application adaptability and malleability. This paper discusses 3 options to overcome that restriction. Malleable job management can be built on top of existing unmodified infrastructures. It can also be implemented as a modification of the infrastructure. At last, we propose an intermediate approach that fosters the cooperation between the infrastructure and its users. Requiring an initial modification of the infrastructure, the latter design combines cost efficiency with possibility to further extend the job model without any additional modification of the infrastructure. In the discussion, qualitative arguments arc supported by some experimental results.
Speaker tracking with spherical microphone arrays

In prior work, we investigated the application of a spherical microphone array to a distant speech recognition task. In that work, the relative positions of a fixed loud speaker and the spherical array required for beamforming were measured with an optical tracking device. In the present work, we investigate how these relative positions can be determined automatically for real, human speakers based solely on acoustic evidence. We first derive an expression for the complex pressure field of a plane wave scattering from a rigid sphere. We then use this theoretical field as the predicted observation in an extended Kalman filter whose state is the speaker's current position, the direction of arrival of the plane wave. By minimizing the squared-error between the predicted pressure field and that actually recorded, we are able to infer the position of the speaker.
Integrating Equity and Efficiency Considerations in the Evaluation of public decision

One of the main criticisms to Cost-Benefit Analysis (CBA) has been that it takes no explicit account of income differences among affected individuals. In trying to overcome this shortcoming, efforts have been devoted to capture differences on the marginal utility of income, whereas the utility derived from changes in the distribution of income itself has been more neglected. This paper proposes a new approach –the Efficiency and Distributional Cost-Benefit Analysis (EDCBA)– that explicitly incorporates the perception of changes in income distribution into Cost-Benefit Analysis.
2016 Fifth International Conference on Recent Trends in Information Technology Surveillance and Steering of Irrigation System in Cloud Using Wireless Sensor Network and Wi-fi Module

— Internet of Things (IoT) has become very popular in the field of communication. IoT will become a reality over the next few years, with rapid and widespread smart devices will be able to execute independently according to the change in their surroundings. The use IoT techniques to identify and channelize the irrigation methods are discussed in this work. In order to develop an automated technique to analyze the water required by the plants at a particular time, a database is created. The database contains training samples related to the soil type, moisture content, temperature, plant leaf condition and the humidity level and the amount of water flow required for subsequent set of features. Different type of soils and plants differ in water content required. The database is build using the features extracted from the images of the soil and the plants. The color of the plants and the soil images can be retrieved using Fisher's linear discriminant analysis (LDA), The Fisher's LDA approach is used to project the plant and soil RGB images into the database to retrieve the color indicating the moisture level. The RGB images are needed to be analyzed accurately to determine the water requirement. However, color processing has great advantages for its simplicity, robustness, power and efficiency. The graph cut based segmentation can be implemented to segment the regions accurately and using this technique the water content in the leaf and the soil covering the plants can be differentiated. The processing of the images should be performed by differentiating the plant and soil segments. A novel classification algorithm called transductive support vector machine (TSVM) is used for classification and quantification. Thus, the required irrigation level of the plants can be determined and the process could be carried out in an efficient manner.
Na+,K+-pump stimulation improves contractility in isolated muscles of mice with hyperkalemic periodic paralysis

In patients with hyperkalemic periodic paralysis (HyperKPP), attacks of muscle weakness or paralysis are triggered by K+ ingestion or rest after exercise. Force can be restored by muscle work or treatment with β2-adrenoceptor agonists. A missense substitution corresponding to a mutation in the skeletal muscle voltage-gated Na+ channel (Nav1.4, Met1592Val) causing human HyperKPP was targeted into the mouse SCN4A gene (mutants). In soleus muscles prepared from these mutant mice, twitch, tetanic force, and endurance were markedly reduced compared with soleus from wild type (WT), reflecting impaired excitability. In mutant soleus, contractility was considerably more sensitive than WT soleus to inhibition by elevated [K+]o. In resting mutant soleus, tetrodotoxin (TTX)-suppressible 22Na uptake and [Na+]i were increased by 470 and 58%, respectively, and membrane potential was depolarized (by 16 mV, P < 0.0001) and repolarized by TTX. Na+,K+ pump–mediated 86Rb uptake was 83% larger than in WT. Salbutamol stimulated 86Rb uptake and reduced [Na+]i both in mutant and WT soleus. Stimulating Na+,K+ pumps with salbutamol restored force in mutant soleus and extensor digitorum longus (EDL). Increasing [Na+]i with monensin also restored force in soleus. In soleus, EDL, and tibialis anterior muscles of mutant mice, the content of Na+,K+ pumps was 28, 62, and 33% higher than in WT, respectively, possibly reflecting the stimulating effect of elevated [Na+]i on the synthesis of Na+,K+ pumps. The results confirm that the functional disorders of skeletal muscles in HyperKPP are secondary to increased Na+ influx and show that contractility can be restored by acute stimulation of the Na+,K+ pumps. Calcitonin gene-related peptide (CGRP) restored force in mutant soleus but caused no detectable increase in 86Rb uptake. Repeated excitation and capsaicin also restored contractility, possibly because of the release of endogenous CGRP from nerve endings in the isolated muscles. These observations may explain how mild exercise helps locally to prevent severe weakness during an attack of HyperKPP.
Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia.
Topography-Based Detection of the Iris Centre Using Multiple-Resolution Images

Low cost iris tracking is one of the most challenging research topics for the eye-tracking community. To this end, accurate detection of the iris centre in images captured by a web cam is a major goal. We propose a novel method for iris detection that is based on image topography using multi-resolution to detect the most stable "valley" over different resolutions, which is assumed to be the iris centre. Our algorithm was tested using the BioID database obtaining the best average behavior. Our algorithm functions in real time and does not require complex post processing stages.
Zinc as an agent for the prevention of biofilm formation by pathogenic bacteria

Biofilm formation is important for the persistence of bacteria in hostile environments. Bacteria in a biofilm are usually more resistant to antibiotics and disinfectants than planktonic bacteria. Our laboratory previously reported that low concentrations of zinc inhibit biofilm formation of Actinobacillus pleuropneumoniae. The aim of this study is to evaluate the effect of zinc on growth and biofilm formation of other bacterial swine pathogens.
Performance evaluation of N-process Stop and Wait in MIMO systems with transmit antenna selection

In this paper we investigate the performance of multiple input multiple output (MIMO) systems with transmit antenna selection when N-process Stop and Wait (N-SAW) is applied at the data link layer. Two antenna selection schemes, throughput and capacity based transmit antenna selection, are considered. In throughput based transmit antenna selection, cross layer information is used to select antennas that maximise system throughput while capacity based transmit antenna selection utilises information from the physical layer to select antennas that maximise system capacity. The performance evaluation will be carried out in the presence of stalling of packets which occurs in the receiver reordering buffer when N-SAW is implemented. The results show that implementing throughput based antenna selection results in enhanced system performance when compared to capacity based transmit antenna selection.
Ethnic media in the digital age

different countries. A group of authors, including Augustine Pang, Jeremiah Icanh Lim Limsico, Lishan Phong, Bernadette Joy Lopez Lareza, and Sim Yee Low, seek to explore the factors and dynamics of Twitter hashtag hijackings. The findings reveal that there are four factors which make Twitter hashtag campaign possible to be hijacked, such as an ill-timed launch and ill-conceived hashtags selection. The significance of this study lies in the fact that the authors offer practical guidance to organizations in dealing with hijacked Twitter hashtag campaigns. This book provides a valuable resource for a deeper understanding of media hypes. Through an international lens, it not only establishes a theoretical framework for readers, but also provides readers with examples of media hypes and online storms by numerous case studies. The media hype theory generated by Vasterman is employed by international researchers in the analysis of traditional and social media, crises, and specific issues. Furthermore, the self-reinforcing news dynamics are reassured and further verified by a number of authors in the book. Even though the case studies, contexts, and circumstances may differ, the theoretical framework remains the same. This book also reveals that different methodologies can be applied to analyze similar issues by adopting similar theories and concepts, which provides guidance for future research to examine media hype-related issues.
University Graduates with Learning Disabilities Define Success and the Factors that Promote It

ABSTRACT The concept of success has been investigated before, primarily with an emphasis on explanatory factors among highly successful individuals. Voices of individuals with any form of disability are generally missing from this discourse. This qualitative study examined definitions of success as well as the factors that promote it amongst graduates with learning disabilities from a university faculty of education, thereby inviting an inclusive dialog around a heretofore socially and educationally exclusive topic. A participatory action framework was chosen allowing the participants to take an active role in the enquiry. This approach was a natural offshoot of the community of learners that the graduates had participated in during their studies. While success was defined as a multifaceted concept accounted for by multiple factors, many of the findings aligned with those reported in previous studies. However, several unique themes emerged; success as a relative concept, ‘paying it forward,’ and the disability as a driving force. Instances of overlap between definitions and factors emphasised inherent connections between beliefs and actions. Practical implications for support services for students with special needs, in higher education, are considered in light of the findings.
Viral Isolates with Length Polymorphisms Immunodeficiency Virus Type 1 Clades and Drug Resistance Genotyping of Human HIV PRT 440 Platform for Antiretroviral Performance of the Affymetrix GeneChip

1999, 37(8):2533. J. Clin. Microbiol. A. Wegner Stuart Bloor, Brendan Larder, Nelson L. Michael and Scott Cooley, Robert Sawyer, Alex A. Sleeker, Peter Vickerman, Maryanne Vahey, Martin E. Nau, Sandra Barrick, John D. Viral Isolates with Length Polymorphisms Immunodeficiency Virus Type 1 Clades and Drug Resistance Genotyping of Human HIV PRT 440 Platform for Antiretroviral Performance of the Affymetrix GeneChip
Distributed KNN-graph approximation via hashing

Efficiently constructing the K-Nearest Neighbor Graph (K-NNG) of large and high dimensional datasets is crucial for many applications with feature-rich objects, such as images or other multimedia content. In this paper we investigate the use of high dimensional hashing methods for efficiently approximating the K-NNG, notably in distributed environments. We first discuss the importance of balancing issues on the performance of such approaches and show why the baseline approach using Locality Sensitive Hashing does not perform well. Our new KNN-join method is based on RMMH, a recently introduced hash function family based on randomly trained classifiers. We show that the resulting hash tables are much more balanced and that the number of resulting collisions can be greatly reduced without degrading quality. We further improve the load balancing of our distributed approach by designing a parallelized local join algorithm, implemented within the MapReduce framework.
Aix MapTask: A new French resource for prosodic and discourse studies

This paper introduces the Aix MapTask corpus. This corpus was modelled after the original HCRC Maptask. Lexical material selection has been carefully crafted for speech and prosodic analysis [1]. We present the design of the lexical material, the protocol and basic quantitative facts about the existing corpus. We also describe an additional face-to-face condition now being collected. Finally, we explain how the material has been transcribed and processed.
Polygenic scores mediate the Jewish phenotypic advantage in educational attainment and cognitive ability compared with Catholics and Lutherans.

A newly released multivariate polygenic score for educational attainment, cognitive ability, and self-rated mathematical ability in the Wisconsin Longitudinal Study was examined as a mediator of the group difference between Jews (n = 53) and 2 Christian denominations, Catholics (n = 2,603) and Luthe
Defining metrics to automate the quantitative analysis of textual information within a web page

The aim of this paper is to define a system of metrics and experimental ways to valuate them to quantitatively analyze the textual information contained by a web page and to determine the differences between the displayed textual information, shown to the human visitor, and the one extracted by the search engines robots. These metrics are the foundation to specify, design and realize an autonomous intelligent robot to find, signal, and interpret the textual information within a web page, hidden or not. For each of that defined metric is specified a computation formula and, if necessary, a procedure to be followed to obtain the involved elements. For each metric is given an interpretation and usefulness depending on the range of the valuation. The metrics are independent on the search engine type, commercial or semantic.