Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene Expression Correlates with the Number of Herpes Viral Genomes Initiating Infection in Single Cells

Viral gene expression varies significantly among genetically identical cells. The sources of these variations are not well understood and have been suggested to involve both deterministic host differences and stochastic viral host interactions. For herpesviruses, only a limited number of incoming viral genomes initiate expression and replication in each infected cell. To elucidate the effect of this limited number of productively infecting genomes on viral gene expression in single cells, we constructed a set of fluorescence-expressing genetically tagged herpes recombinants. The number of different barcodes originating from a single cell is a good representative of the number of incoming viral genomes replicating (NOIVGR) in that cell. We identified a positive correlation between the NOIVGR and viral gene expression, as measured by the fluorescent protein expressed from the viral genome. This correlation was identified in three distinct cell-types, although the average NOIVGR per cell differed among these cell-types. Among clonal single cells, high housekeeping gene expression levels are not supportive of high viral gene expression, suggesting specific host determinants effecting viral infection. We developed a model to predict NOIVGR from cellular parameters, which supports the notion that viral gene expression is tightly linked to the NOIVGR in single-cells. Our results support the hypothesis that the stochastic nature of viral infection and host cell determinants contribute together to the variability observed among infected cells.
Assessment of the quality of information literacy (IL) training among teacher trainees enrolled in selected Northern Malaysian Teacher Education Institutes

Our case study examined and assessed the quality and effectiveness of information literacy training employed by teacher trainees in their follow-on research process. A sample of teacher trainees enrolled in selected Malaysian Teacher Education Institutes located in the northern region of Malaysia was surveyed. These Institutes’ mission is to produce trained teachers who will possess a comprehensive and accurate understanding of information literacy core principles and skills, and be able to apply those core principles and skills in their various follow-on research processes. Many recent observers have reported that many, perhaps even most, future Malaysian teachers, enter teaching practice without having adequately learned the necessary core information literacy principles and skills which can then be implicitly employed in their follow-on research processes. The study recommends various reforms which are needed in official Malaysian teacher training policies, programs and curricula, based on the case study’s findings, conclusions and recommendations. An Information Literacy Research Process Model was developed and employed by the authors in this case study, and then used to describe and explain trainee behaviors in searching for, retrieving, organizing, evaluating and applying the obtained information wisely and ethically, using learned information literacy core principles and skills. The researchers studied these behaviors in the context of the Malaysian teacher training curricula which is used by all Malaysian training institutes. A sample of teacher trainees was selected from several of these Institutes located in the northern region of the country. A “mixed methods” design was used for this purpose, consisting of (1) face-to-face interviews and (2) document analysis, in order to perform a sampling of the examined teacher trainees. The case study was strengthened by using two separate phases of data gathering. The study’s findings, conclusions and recommendations will hopefully provide insights to the various Education Ministry stakeholder groups (government policy makers, teachers, parents, school administrators, etc.) so as to enable them to better move forward in terms of defining sharpened, modernized and strengthened teacher training reforms, then applying them, and finally realizing upgraded expected positive outcomes – all within the framework of the overall Malaysian National Information Literacy Agenda.
Lumbar spine finite element model for healthy subjects: development and validation

Abstract Finite element (FE) method is a proven powerful and efficient tool to study the biomechanics of the human lumbar spine. However, due to the large inter-subject variability of geometries and material properties in human lumbar spines, concerns existed on the accuracy and predictive power of one single deterministic FE model with one set of spinal geometry and material properties. It was confirmed that the combined predictions (median or mean value) of several distinct FE models can be used as an improved prediction of behavior of human lumbar spine under identical loading and boundary conditions. In light of this improved prediction, five FE models (L1-L5 spinal levels) of the human lumbar spine were developed based on five healthy living subjects with identical modeling method. The five models were extensively validated through experimental and computational results in the literature. Mesh convergence and material sensitivity analysis were also conducted. We have shown that the results from the five FE models developed in this paper were consistent with the experimental data and simulation results from the existing literature. The validated modeling method introduced in this study can be used in modeling dysfunctional lumber spines such as disc degeneration and scoliosis in future work.
Crowd Behaviors Analysis and Abnormal Detection in Structured Scene

Recently, crowd behavior analysis and abnormal trajectory detection have emerged as a significant research field in the visual surveillance. In this paper, we propose a framework for analyzing the crowd behavior and detecting abnormal trajectories in a structured scene. We employ Fast LDA (latent Dirichlet allocation) algorithm to clustering the trajectories. Our framework is based on this method, and it achieves a faster and more accurate clustering result. In order to obtain the crowd motion pattern, we propose two categories of regions of interest, optimal path and critical regions respectively. We use LOF (local outlier factor) algorithm to detect whether the sample points corresponding to the trajectories are abnormal or not, our framework overcomes the problem whose trajectory length is not uniform. Experimental results illustrate that the proposed framework is effective in motion pattern learning and abnormal trajectory detection. Keywords-component; Crowd Behavior Analysis; Trajectory clustering; Abnormal Detection; Fast LDA; LOF
Musculoskeletal extremity injuries in a cohort of schoolchildren aged 6–12: A 2.5‐year prospective study

The objectives of this prospective school cohort study were to describe the epidemiology of diagnosed musculoskeletal extremity injuries and to estimate the injury incidence rates in relation to different settings, different body regions and injury types. In all, 1259 schoolchildren, aged 6–12, were surveyed weekly during 2.5 years using a new method of automated mobile phone text messaging asking questions on the presence of any musculoskeletal problems. All injuries were clinically diagnosed. Physical activity was measured from text messaging and accelerometers. A total number of 1229 injuries were diagnosed; 180 injuries in the upper extremity and 1049 in the lower extremity, with an overall rate of 1.59 injuries per 1000 physical activity units [95% confidence interval (CI) 1.50–1.68]. Upper extremities accounted for a rate of 0.23 (95% CI 0.20–0.27) and lower extremities accounted for 1.36 (95% CI 1.27–1.44). This study has added a wide overall perspective to the area concerning incidence and incidence rates of musculoskeletal extremity injuries in schoolchildren aged 6–12 years, including severe and less severe, traumatic, and overuse injuries. The understanding of injury epidemiology in children is fundamental to the acknowledgement and insurance of the appropriate prevention and treatment.
Explorer Automatic annotation of coral reefs using deep learning

Healthy coral reefs play a vital role in maintaining biodiversity in tropical marine ecosystems. Deep sea exploration and imaging have provided us with a great opportunity to look into the vast and complex marine ecosystems. Data acquisition from the coral reefs has facilitated the scientific investigation of these intricate ecosystems. Millions of digital images of the sea floor have been collected with the help of Remotely Operated Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs). Automated technology to monitor the health of the oceans allows for transformational ecological outcomes by standardizing methods for detecting and identifying species. Manual annotation is a tediously repetitive and a time consuming task for marine experts. It takes 10-30 minutes for a marine expert to meticulously annotate a single image. This paper aims to automate the analysis of large available AUV imagery by developing advanced deep learning tools for rapid and large-scale automatic annotation of marine coral species. Such an automated technology would greatly benefit marine ecological studies in terms of cost, speed, accuracy and thus in better quantifying the level of environmental change marine ecosystems can tolerate. We propose a deep learning based classification method for coral reefs. We also report the application of the proposed technique towards the automatic annotation of unlabelled mosaics of the coral reef in the Abrolhos Islands, Western Australia. Our proposed method automatically quantifies the coral coverage in this region and detects a decreasing trend in coral population which is in line with conclusions by marine ecologists.
Viewpoint invariant gender recognition

In this paper, we address a problem of gender classification of faces taken from arbitrary viewpoints. We use a face model for accurate face localisation based on a combination of appearance and geometry. A probabilistic matching of particular traits on face allows to classify the gender of face even when pose changes. We deal with the local invariant features whose performances have already been proved. Each facial feature retained in the detection step will be weighted by a probability to be male or female. Such feature contributes to determine the gender associated to a given face. We evaluate the model by testing it simultaneously in face localisation and gender classification experiments on PIE, FERET and CMU-profiles databases. The experimental results show that the probabilistic invariant model performs well to detect face and gives a rate of 92.1% of accurate gender classification in the presence of viewpoint changes and large appearance variability of faces.
Council playgrounds in New South Wales: compliance with safety guidelines

Abstract: Despite initiatives to improve the safety of play environments, playground–related injuries continue to be a major public health problem. Efforts to address playground safety in New South Wales were consolidated during 1994 through the Kidsafe Playground Safety Project. In stage 1 of the project (described here), 240 council playgrounds were assessed to determine the extent to which playground equipment complied with safety guidelines. On–site inspection of the selected playgrounds provided data on 862 separate pieces of playground equipment. Of the 723 pieces requiring under–surfacing, less than half (45.4 per cent) had the recommended type of undersurfacing while only 42 of those pieces had undersurfacing to the recommended depth. However, when the fall height of equipment was considered in addition to the undersurfacing guidelines, only 13 (1.8 per cent) of the 723 pieces of equipment simultaneously satisfied all of the safety guidelines. Regrettably, none of the 240 council playgrounds assessed complied fully with the key safety guidelines. The results underscore the need for a collaborative effort on the part of local government, Kidsafe and health promotion and regional public health units to ensure that council playgrounds in New South Wales comply with recommended safety guidelines. (Aust N Z J Public Health 1997; 21: 577–80)
Activation of mitogen-activated protein kinases (p38-MAPKs, SAPKs/JNKs and ERKs) by the G-protein-coupled receptor agonist phenylephrine in the perfused rat heart.

We investigated the ability of phenylephrine (PE), an alpha-adrenergic agonist and promoter of hypertrophic growth in the ventricular myocyte, to activate the three best-characterized mitogen-activated protein kinase (MAPK) subfamilies, namely p38-MAPKs, SAPKs/JNKs (i.e. stress-activated protein kinases/c-Jun N-terminal kinases) and ERKs (extracellularly responsive kinases), in perfused contracting rat hearts. Perfusion of hearts with 100 microM PE caused a rapid (maximal at 10 min) 12-fold activation of two p38-MAPK isoforms, as measured by subsequent phosphorylation of a p38-MAPK substrate, recombinant MAPK-activated protein kinase 2 (MAPKAPK2). This activation coincided with phosphorylation of p38-MAPK. Endogenous MAPKAPK2 was activated 4-5-fold in these perfusions and this was inhibited completely by the p38-MAPK inhibitor, SB203580 (10 microM). Activation of p38-MAPK and MAPKAPK2 was also detected in non-contracting hearts perfused with PE, indicating that the effects were not dependent on the positive inotropic/chronotropic properties of the agonist. Although SAPKs/JNKs were also rapidly activated, the activation (2-3-fold) was less than that of p38-MAPK. The ERKs were activated by perfusion with PE and the activation was at least 50% of that seen with 1 microM PMA, the most powerful activator of the ERKs yet identified in cardiac myocytes. These results indicate that, in addition to the ERKs, two MAPK subfamilies, whose activation is more usually associated with cellular stresses, are activated by the Gq/11-protein-coupled receptor (Gq/11PCR) agonist, PE, in whole hearts. These data indicate that Gq/11PCR agonists activate multiple MAPK signalling pathways in the heart, all of which may contribute to the overall response (e.g. the development of the hypertrophic phenotype).
Use of polymerase chain reaction for detection of Chlamydia trachomatis

A polymerase chain reaction (PCR) assay was developed for detection of Chlamydia trachomatis DNA. From the published sequence of the common C. trachomatis plasmid, two primer sets were selected. Detection of amplified sequences was done by agarose gel electrophoresis of cleaved or uncleaved amplified sequences, Southern hybridization, or dot blot analysis. The PCR assay was optimized and, after 40 cycles of amplification with primer set II, demonstrated a sensitivity of 10(-17) g of DNA, which corresponds to the detection of one copy of the plasmid. Because of the high sensitivity, we developed a closed system in which airborne contamination was minimized. Analysis of 228 clinical samples tested by cell culture, IDEIA enzyme immunosorbent assay (Medico-Nobel, Boots-Celltech Ltd., Berkshire, United Kingdom), and PCR showed a sensitivity of 100%, a specificity of 93% when PCR was compared with cell culture, and a corrected specificity of 99% when PCR was compared with cell culture or IDEIA.
Cyclic‐diGMP signal transduction systems in Vibrio cholerae: modulation of rugosity and biofilm formation

Cyclic di‐guanylic acid (c‐diGMP) is a second messenger that modulates the cell surface properties of several microorganisms. Concentrations of c‐diGMP in the cell are controlled by the opposing activities of diguanylate cyclases and phosphodiesterases, which are carried out by proteins harbouring GGDEF and EAL domains respectively. In this study, we report that the cellular levels of c‐diGMP are higher in the Vibrio cholerae rugose variant compared with the smooth variant. Modulation of cellular c‐diGMP levels by overexpressing proteins with GGDEF or EAL domains increased or decreased colony rugosity respectively. Several genes encoding proteins with either GGDEF or EAL domains are differentially expressed between the two V. cholerae variants. The generation and characterization of null mutants of these genes (cdgA–E, rocS and mbaA) revealed that rugose colony formation, exopolysaccharide production, motility and biofilm formation are controlled by their action. Furthermore, epistasis analysis suggested that cdgC, rocS and mbaA act in convergent pathways to regulate the phenotypic properties of the rugose and smooth variants, and are part of the VpsR, VpsT and HapR signal transduction pathway.
A Systematic Review on Author Identification Methods

Author Identification is a technique for identifying author of anonymous text. It has near about 130 year’s long history, started with the work by Mendenhall 1987. Applications of Author identification include plagiarism detection, detecting anonymous author, in forensics and so on. In this paper the authors outline features used for Author identification like vocabulary, syntactic and others. Researchers worked on various methods for Author identification they also outline this paper on types of Author Identification methods that include 1. Profile-based Approaches which includes Probabilistic Models, Compression Models, Common n-Grams (CNG) approach, 2. Instance-based Approaches which includes Vector Space Models, Similarity-based Models, Meta-learning Models and 3. Hybrid Approaches. At the end the authors conclude this paper with observations and future scope. KeywoRDS Attribution Method, Author Identification, Feature Set, Text Features, Text Mining
Arrayed cellular environments for stem cells and regenerative medicine

The behavior and composition of both multipotent and pluripotent stem cell populations are exquisitely controlled by a complex, spatiotemporally variable interplay of physico‐chemical, extracellular matrix, cell‐cell interaction, and soluble factor cues that collectively define the stem cell niche. The push for stem cell‐based regenerative medicine models and therapies has fuelled demands for increasingly accurate cellular environmental control and enhanced experimental throughput, driving an evolution of cell culture platforms away from conventional culture formats toward integrated systems. Arrayed cellular environments typically provide a set of discrete experimental elements with variation of one or several classes of stimuli across elements of the array. These are based on high‐content/high‐throughput detection, small sample volumes, and multiplexing of environments to increase experimental parameter space, and can be used to address a range of biological processes at the cell population, single‐cell, or subcellular level. Arrayed cellular environments have the capability to provide an unprecedented understanding of the molecular and cellular events that underlie expansion and specification of stem cell and therapeutic cell populations, and thus generate successful regenerative medicine outcomes. This review focuses on recent key developments of arrayed cellular environments and their contribution and potential in stem cells and regenerative medicine.
Why do users intend to use near field communication services?

Near field communication NFC is a short-range wireless connectivity technology that enables ubiquitous wireless communications. Services based on NFC technology can facilitate daily activities and transaction processes for consumers, as well as generate sizable revenues for businesses. Understanding the predictors for users' behavioural intention to adopt NFC services is thus critical to mobile network operators, handset manufactures, trusted third parties, and application developers. Considering the features of NFC services and drawing on relevant theories on individual characteristics, this study proposed a research model for predicting users' behavioural intention to adopt NFC services. Analytical results from this study show that perceived convenience and perceived sociability both correlate positively with behavioural intention. Furthermore, personal innovativeness strengthens the positive relationship between perceived sociability and behavioural intention, and self-efficacy attenuates the positive relationship between perceived convenience and behavioural intention.
Logistic regression when covariates are random effects from a non‐linear mixed model

In many studies, the association of longitudinal measurements of a continuous response and a binary outcome are often of interest. A convenient framework for this type of problems is the joint model, which is formulated to investigate the association between a binary outcome and features of longitudinal measurements through a common set of latent random effects. The joint model, which is the focus of this article, is a logistic regression model with covariates defined as the individual‐specific random effects in a non‐linear mixed‐effects model (NLMEM) for the longitudinal measurements. We discuss different estimation procedures, which include two‐stage, best linear unbiased predictors, and various numerical integration techniques. The proposed methods are illustrated using a real data set where the objective is to study the association between longitudinal hormone levels and the pregnancy outcome in a group of young women. The numerical performance of the estimating methods is also evaluated by means of simulation.
Hepatitis C Virus Infection Activates the Immunologic (Type II) Isoform of Nitric Oxide Synthase and Thereby Enhances DNA Damage and Mutations of Cellular Genes

ABSTRACT Hepatitis C virus (HCV) infection causes hepatitis, hepatocellular carcinoma, and B-cell lymphomas in a significant number of patients. Previously we have shown that HCV infection causes double-stranded DNA breaks and enhances the mutation frequency of cellular genes, including proto-oncogenes and immunoglobulin genes. To determine the mechanisms, we studied in vitro HCV infection of cell culture. Here we report that HCV infection activated the immunologic (type II) isoform of nitric oxide (NO) synthase (NOS), i.e., inducible NOS (iNOS), thereby inducing NO, which in turn induced DNA breaks and enhanced the mutation frequencies of cellular genes. Treatment of HCV-infected cells with NOS inhibitors or small interfering RNA specific for iNOS abolished most of these effects. Expression of the core protein or nonstructural protein 3 (NS3), but not the other viral proteins, in B cells or hepatocytes induced iNOS and DNA breaks, which could be blocked by NOS inhibitors. The core protein also enhanced the mutation frequency of cellular genes in hepatocytes derived from HCV core transgenic mice compared with that in control mice. The iNOS promoter was activated more than fivefold in HCV-infected cells, as revealed by a luciferase reporter assay driven by the iNOS promoter. Similarly, the core and NS3 proteins also induced the same effects. Therefore, we conclude that HCV infection can stimulate the production of NO through activation of the gene for iNOS by the viral core and NS3 proteins. NO causes DNA breaks and enhances DNA mutation. This sequence of events provides a mechanism for HCV pathogenesis and oncogenesis.
Capacity of Wireless Networks With Social Characteristics

This paper studies the throughput capacity of wireless networks with social characteristics. We propose a simple model to reflect both the social relations between nodes and power-law node degree distribution, and then examine their impact on capacity. We show the fact that two features above lead to traffic locality and improve capacity. Moreover, multicasting may be employed to further enhance performance when information is desired to be published from the source to all its contacts, of which the number follows power-law distribution. In addition, we propose the corresponding capacity-achieving communication schemes, which optimally exploit the underlying structure. Our study is an attempt to understand how social relations may impact on network capacity from a theoretical perspective, and provides fundamental insight on the design and analysis of real wireless networks.