Miracle-dz/UniFAR-FTUs huggingface dataset:
Entry Mode Strategy and Firm Performance in Emerging Economy: Moderating Role of Organisational Structure and Environmental Turbulence

Research question: This study assessed the combined moderating effect of organizational structure and environmental turbulence on entry mode strategy - performance link focusing on baby care industry in Lagos State, Nigeria. Motivation: The manufacturers of baby care products in Nigeria have struggled to understand the complexities of entry mode strategy and how to use firm-specific capabilities to contain the threats from new entrants given the idiosyncrasies of the business environment in Nigeria. Also, considering the fast changing business environment and the need for firms to align internal organisational structure to manage the external environmental challenges, this study via the supposition of Hage (1965) axiomatic theory of organisations examined the joint moderating effect of organisational structure and environmental turbulence on entry mode strategy - performance linkage focusing on the baby care industry in Lagos State, Nigeria. Idea: Empirical submissions on the combined moderating effect of organizational structure and environmental turbulence on the interactions of entry mode strategy and organizational performance are sparse. Hence, this study addressed this gap in literature. Data: The survey research design and a sample of 518 employees engaged in FMCG manufacturers in Lagos State, Nigeria were adopted for this study. Tools: A validated structured questionnaire was the instrument of data collection for this study and the hierarchical regression analysis was adopted to test the hypotheses formulated. Findings: The results showed that the interaction between entry mode strategy and firm performance was positive and significant. Further analysis revealed that the interaction term of organizational structure and environmental turbulence accounted for the rise in firm performance to suggest that organizational structure and environmental turbulence are joint significant moderators. This suggests that entry mode strategy appropriateness is key to firm performance and that the fit between organisational structure and the macro-environment is a precondition to higher performance. Contribution: This study adds to recent empirical literature on the link between entry mode strategy, organizational structure, environmental turbulence, and firm performance within emerging economy context, and it provides additional support for the assumptions of the eclectic theory and Hage’s axiomatic theory of organization.
UM SISTEMA AUTONÔMICO MULTIAGENTE BASEADO EM ONTOLOGIAS PARA SEGURANÇA EM AMBIENTES COMPUTACIONAIS

Computational security has become a worry among corporations. Indeed, the use of specifics tools, procedures and policies that cover requirements to keep computational and IT infrastructure protected of malicious agents has been proved necessary. In order to address the problem of protecting computational resources, in this work we propose an autonomic model called AutoCore, constituted by a Muilt-Agent system, an Intelligent Interface (CoreEditor) and a formal ontologies (CoreSec). This proposal has been implemented, tested and validated in real scenarios to assist the safety activities and to minimize the administrator complexity.
Deep Features Based Multiview Gait Recognition

Pattern recognition is one of the computing intensive application. As information technology has evolved to such an extend, it is easier to identify various patterns in images or videos. As an example consider fingerprint identification, which is image pattern identification application widely used in smartphones to authenticate a person. Similarly Gait recognition, which is a video pattern identification application, is used for surveillance purpose. A lot of research is going on gait recognition. In our purposed deep Convolutional Neural Network (CNN) architecture, Gait Energy image is used as the input and simple several layers are used in matrix analytics. The softmax classifier is used to measure the similarity between Gallery gaits and Probe gaits. This paper uses CASIA Dataset B for performance evaluation of Gait recognition using different angle view variation, normal walking, wearing clothing and carrying bags conditions. The experimental results show that the proposed deep CNN architecture’s accuracy is better than Bag-of-Words (BoW), Histogram of Image Gradient (HOG) and 3D-Histogram of Merged Orientations (3D-HOMO)
Brugada syndrome: current concepts and genetic background

Brugada syndrome (BrS) is a hereditary clinical-electrocardiographic arrhythmic entity with low worldwide prevalence. The syndrome is caused by changes in the structure and function of certain cardiac ion channels and reduced expression of Connexin 43 (Cx43) in the Right Ventricle (RV), predominantly in the Right Ventricular Outflow Tract (VSVD), causing electromechanical abnormalities. The diagnosis is based on the presence of spontaneous or medicated ST elevation, characterized by boost of the J point and the ST segment ≥2 mm, of superior convexity "hollow type" (subtype 1A) or descending rectilinear model (subtype 1B). BrS is associated with an increased risk of syncope, palpitations, chest pain, convulsions, difficulty in breathing (nocturnal agonal breathing) and/or Sudden Cardiac Death (SCD) secondary to PVT/VF, unexplained cardiac arrest or documented PVT/VF or Paroxysmal atrial fibrillation (AF) in the absence of apparent macroscopic or structural heart disease, electrolyte disturbance, use of certain medications or coronary heart disease and fever. In less than three decades since the discovery of Brugada syndrome, the concept of Mendelian heredity has come undone. The enormous variants and mutations found mean that we are still far from being able to concretely clarify a genotype-phenotype relationship. There is no doubt that the entity is oligogenetic, associated with environmental factors, and that there are variants of uncertain significance, especially the rare variants of the SCN5A mutation, with European or Japanese ancestors, as well as a spontaneous type 1 or induced pattern, thanks to gnomAD (coalition) researchers who seek to aggregate and harmonize exome and genome sequencing data from a variety of large scale sequencing projects and make summary data available to the scientific community at large). Thus, we believe that this in depth analytical study of the countless mutations attributed to BrS may constitute a real cornerstone that will help to better understand this intriguing syndrome.
The Use of Technology to Promote Learner Autonomy in Teaching English

This study aimed at investigating EFL teachers’ perceptions of the use of technology to promote learner autonomy in teaching English. A focus group research was used as its design with qualitative analysis for data interpretation. The participants of the study were five English teachers who teach English as a foreign language in Indonesia. The data were collected from an online discussion forum and analysed through data reduction, data display for categorization, and conclusion. The study reveals that EFL teachers had positive perceptions of the use of technology in promoting learner autonomy in teaching English. Dealing with the use of technology in the teaching language classroom, the majority of teachers have already used technology such as the Internet, and some applications (Quizlet, Grammarly, English Central, Padlet, Mentimenter) with the potential for promoting learner autonomy. Moreover, the interviewed teachers reported that using technology in teaching and learning English in the classroom is not without constraints. The main problem is the limited internet connection. These results indicate that EFL teachers understand and are aware of technology to promote learning autonomy in teaching English.
Management of Depression and Anxiety in Primary Care - An Update

Depression and anxiety are the most common mental health diagnoses in primary care. In this article, we discuss changes in Diagnostic and Statistical Manual of Mental Disorders (DSM) with respect to depressive and anxiety disorders. We also provide a brief overview of assessment of these disorders and associated safety concerns, while maintaining focus on the pharmacologic and non-pharmacologic interventions for the management of depression and anxiety in primary care.
PDBcle – An online tool for extracting chain structure and sequence of macromolecule and small molecule structure from the Protein Data Bank

Background: Protein Data Bank (PDB) is the most popular structure database that contains experimentally determined three-dimensional (3D) structures of biological macromolecules and small molecules. The rich features of PDB are keyword assisted advanced text search, structure search by sequence alignment, sequence motif search, ligand to target-ligand complex search through SMILES substructure search, JSON API query search, structure alignment, structure quality assessment, genome viewer, and 3D structure viewer. It is widely used in molecular modelling and computer-aided drug design. PDBcle is a simple tool to extract chain sequence of protein/nucleotide and 3D structure of protein/ nucleotide/ ligand from the PDB. Objectives: To construct an online tool for separating molecule-wise chain sequence and structure of polymers and non-polymer structures in a macromolecule. Moreover, the separated sequences and structures are produced to moleculespecific standard file format. Methods: The graphical web-interface of PDBcle tool has been designed using PHP, CSS, and pure JavaScript. Parsing the atomic coordinate records and sequence records from the PDBML/XML file and/or PDBx/mmJSON file through the API of PDB was done through PHP server script. Findings: The PDBcle tool retrieves and generates separate structure/sequence files for each amino acid/RNA chain, and pair of chains for DNA base pairs with/without ligand complex from the PDB. The ligand molecules are separated and sorted from the chains and produced to an SDF file. Applications: PDBcle tool is publicly accessible at https://www.biogem. org/tool/pdbcle/. Keywords: PDBcle; PDB; PDB Chain and Ligand Extractor; PDB Sequence Extractor; PDBML
Bayesian On-line Change-point Detection

This thesis details an approach known as change-point detection (CPD) that aims to detect changes in the mean, variance and covariance of a time series. The scope of CPD is limited to an on-line (real-time) Bayesian spatio-temporal setting. In this setting, the goal of CPD is to provide step-ahead predictions and partition the time series into disjoint segments every time a new datum is received using Bayesian inference. This is achieved by modelling each datum as a sample from a data-generating process which we are imitating using a probability distribution as a model. At each time step the most likely model is chosen among a universe of potential models. This leads to the development of the Bayesian on-line change-point detection and model selection (BOCDMS) algorithm which has a linear computational and storage complexity in the number of observations. Model selection is narrowed by employing two conjugate point process models: the Poisson Gamma (PG) and Multinomial Dirichlet (MD) models. We study the properties of these models and assess their sensitivity and performance on four synthetic and three real-world datasets, the latter of which are related to crime in Chicago, property transactions in the UK and cryptocurrency transactions.
INVESTIGATION OF BIAS IN MACHINE LEARNING THROUGH FACIAL RECOGNITION AND SKIN LESION CLASSIFICATION

Machine learning is a discipline of artificial intelligence concerned with the design, creation, and implementation of computer software that can learn autonomously. The purpose of this project was to evaluate both the versatility of artificial neural networks (ANNs) and their vulnerability to biases across multiple datasets. Three algorithms were constructed: a Convolutional Neural Network (CNN) using Keras and TensorFlow, a Multilayer Perceptron (MLP) classifier using neural net Scikit-Learn, and a Simplistic Nearest Centroid classifier for comparison. These algorithms were subsequently tested on three datasets: a homemade facial recognition dataset with images from NJGSS scholars, the UTKFace dataset of facial images, and the University of Edinburgh’s Dermofit skin lesion image dataset. Each dataset was tested with at least one of the neural networks, as well as the nearest centroid classifier. We used these algorithms and datasets to develop systems to recognize NJGSS scholars’ faces, classify UTKFace images according to gender and race, and classify Dermofit skin lesion images according to lesion type. These recognition and classification systems were subsequently used to investigate ethical issues in machine learning, in particular the bias created by the use of unbalanced datasets.
Investigation of the Effects of Methylphenidate and Endurance Exercise on Structural Changes in Brain Tissue of Male Rats with Hyperactivity

Material and Methods: In this study, 33 rats were divided into a control group (5 rats) and 4 experimental groups (28 rats) and 10 mg/kg of L-NAME (L-Arginine Methyl Ester) was injected peritoneally for 8 weeks for 6 days a week. Rats that tested positive for open test were used. Balance and motor coordination tests were taken after 8 weeks of training using Beam Walking or Balance Test. The drug group was given 1 mg per kg of Methylphenidate orally. The rats in the exercise group trained 30 minutes a day and 7 days a week for 4 weeks. Open Field Test was used to diagnose hyperactivity. 5-band treadmill was used for doing endurance exercise.
Assessment of Microvascular Changes using Optical Coherence Tomography Angiography after Phacoemulsification Surgery in an Indian Population

Purpose: To identify changes in superficial retinal capillary microvasculature before and after cataract surgery using optical coherence tomography angiography (OCTA). Setting: Rajan eye care, Tertiary care center in Chennai, India. Design: Prospective observational study. Methods: Patients above 40 years who underwent uncomplicated cataract surgery had 6 × 6 mm OCTA foveacentered scans using Zeiss Angioplex 5000 OCTA before and 4 weeks postoperatively. Signal strength and automated values obtained for perfusion density (PD) and vascular density (VD) were recorded. Results: Fifty-eight eyes of 33 patients aged 67 ± 5 years were enrolled. Signal strength (3.9 ± 2.3 vs. 5.7 ± 2.1, p<0.001), PD (16.4 ± 10.4 vs. 26.6 ± 10.3, p<0.001) and VD (7.4 ± 4.5 vs. 11.4 ± 4.0, p<0.001) increased significantly after surgery. Strong positive correlation was seen between signal strength and PD (r=0.86, p<0.001) and VD (r=0.79, p<0.001). Linear mixed model analysis with eye as grouping factor, time (i.e. pre and post-surgery) and signal strength as covariates showed, surgery independently caused an increase in PD (ß=3.63 increment in PD after surgery, p<0.001) and VD (ß=1.61 increment in VD after surgery, p=0.003). After adjusting for signal strength, a 20% increment in macular PD and VD was observed in central 1 mm area around fovea. Foveal avascular zone (FAZ) area, perimeter and circularity, did not change after surgery. Conclusion: Macular perfusion and vascularity indices increase immediately after cataract surgery independent of improvement in signal strength, though FAZ is not influenced.
Vogt-Koyanagi-Harada syndrome: a discussion about resistance to corticotherapy

ABSTRACT Vogt-Koyanagi-Harada (VKH) syndrome is an inflammatory condition of unknown etiology that can affect the eye. The most common ocular manifestation related to VKH is bilateral diffuse uveitis associated to exudative retinal detachment. Although these patients respond well to steroid pulse therapy, we report a case of a 44-year-old female patient presenting bilateral exudative retinal detachment and clinical diagnosis of VKH, who did not respond to the first cycle of 3-day pulse therapy with methylprednisolone. The exudation was reabsorbed only after a second cycle of steroid therapy.
Ju l 2 02 1 Reconstruction from the Fourier transform on the ball via prolate spheroidal wave functions ∗

We give new formulas for finding a compactly supported function v on Rd, d > 1, from its Fourier transform Fv given within the ball Br. For the one-dimensional case, these formulas are based on the theory of prolate spheroidal wave functions (PSWF’s). In multidimensions, well-known results of the Radon transform theory reduce the problem to the one-dimensional case. Related results on stability and convergence rates are also given.
Cascade Tank Water Quality Management: A Case Study in Thirappane Tank Cascade System, Sri Lanka

Tank cascade system (TCS) is a series of tanks located in a mesocatchment and has been accepted as a Globally Important AgriculturalHeritage System found in Sri Lanka. Ecosystem components of theTCS play a major role in purifying water within the system. Thisstudy attempted to investigate the water quality status and the farmers’willingness to rehabilitate the ecosystem components of the ThirappaneTCS. Drinking and irrigation water quality parameters were tested in34 locations and drinking and irrigation water quality indexes werecalculated. Participatory rural appraisal and a questioner survey wereconducted to gather social data. Water of TCS was observed to beappropriate for irrigation but not for drinking during the Maha croppingseason. Based on the results of the Nitrate (as NO3- ) and Total Phosphate(as PO4 3-), water of TCS can be categorized as eutrophic. Presenceof ecosystem features of tank cascade system, annual income of therespondents, satisfaction on the quality of water for drinking, and theawareness about the tank cascade system significantly influenced theparticipatory decisions of the community on the rehabilitation of TCS.This study shall be an example and an eye opener to formulate sustainabletank cascade management plan.
Direct Selling to Heterogenous Consumers with Value-Added Service

This study is based on a unique direct selling method in the health food and cosmetics market. We build a supply chain consisted of one supplier and one retailer and utilize a game theory model to study it. The supplier owns superior power and can set the price and commission rate, whereas the retailer can determine the quality of value-added service. To maintain social welfare, the government may limit the commission rate set by the supplier. We find that the government’s regulation might make the supply chain’s social and economic performance better off or worse off, depending on a consumer’s preference to value-added services. Additionally, we provide a cost-sharing contract between supplier and salespeople to achieve supply chain coordination. Our study provides applicable insights for each supply chain player and political guidance for the government.
Aux-AIRL: End-to-End Self-Supervised Reward Learning for Extrapolating beyond Suboptimal Demonstrations

Real-world human demonstrations are often sub-optimal. How to extrapolate beyond suboptimal demonstration is an important open research question. In this ongoing work, we analyze the success of a previous state-of-the-art self-supervised reward learning method that requires four sequential optimization steps, and propose a simple end-to-end imitation learning method Aux-ARIL that ex-trapolates from suboptimal demonstrations without requiring multiple optimization steps.
Self-Reported Depressive Symptoms and Suicidality in Adolescents with Attention-Deficit/Hyperactivity Disorder: Roles of Bullying Involvement, Frustration Intolerance, and Hostility

This study examined the relationships of cyberbullying and traditional bullying victimization and perpetration, perceived family function, frustration discomfort, and hostility with self-reported depressive symptoms and suicidality in adolescents diagnosed as having attention-deficit/hyperactivity disorder (ADHD). Both the self-reported severity of depressive symptoms on the Center for Epidemiological Studies Depression Scale and the occurrence of suicidal ideation or a suicide attempt on the suicidality module of the Kiddie Schedule for Affective Disorders and Schizophrenia were assessed in 195 adolescents with ADHD. The adolescents completed the Cyberbullying Experiences Questionnaire, Chinese version of the School Bullying Experience Questionnaire, Frustration–Discomfort Scale, Buss–Durkee Hostility Inventory, and Family APGAR Index. Caregivers completed the ADHD problems component of the Child Behavior Checklist for Ages 6–18. Multiple regression analyses were used to examine the correlates for each of self-reported depressive symptoms and suicidality. The results showed that after the effects of gender, age, ADHD symptoms, and family function were controlled, greater frustration discomfort and bullying perpetration significantly predicted self-reported depressive symptoms. Being cyberbullying victims and displaying hostility significantly predicted the risk of suicidality. Various types of bullying involvement, frustration intolerance, and hostility significantly predicted self-reported depressive symptoms and suicidality in adolescents with ADHD. By monitoring and intervening in these factors, we can reduce the risk of depression-related problems and suicidality in adolescents with ADHD.
Real-time measurements of tonal audibility by using multifunctional measuring system

Akiko Sugahara , Kohei Okubo, Miki Yonemura, Hyojin Lee, Shinichi Sakamoto, Yuichi Yonemoto and Toshiya Ohshima Faculty of Architecture, Kindai University, 3–4–1 Higashiosaka, 577–8502 Japan Department of Architecture, Graduate School of Engineering, The University of Tokyo, 4–6–1 Komaba, Meguro-ku, Tokyo, 153–8505 Japan Institute of Industrial Science, The University of Tokyo, 4–6–1 Komaba, Meguro-ku, Tokyo, 153–8505 Japan RION Co., Ltd., 3–20–41 Higashimotomachi, Kokubunji, 185–8533 Japan Aviation Environment Research Center, Organization of Airport Facilitation, 1–3–1 Shibakoen, Minato-ku, Tokyo, 105–0011 Japan
The Impact of Employment Protection on the Quality of Job Match : Evidence from Job Duration Data in South Korea

This study analyzes how firms and workers respond to regulations limiting the use of temporary employment. In 2007, the Korean government introduced a labor market reform that required employers to convert a worker’s contract from a temporary to permanent one in order to continue to employ a worker for more than two years. From the perspective of employers, the new regulation can be thought of as a potential increase in firing costs for temporary workers after two years. Thus, employers have an incentive to improve the screening process to establish better matches and weed out bad matches prior to the increase in firing costs. From the perspective of workers, temporary workers have an incentive to provide greater effort after the policy change because the reform offers a potential path to permanent employment. My result shows economically and statistically significant decreases in the probability of job separation in the first five months of tenure after the policy change, which implies that firms respond to the increased protection for temporary workers by improving their recruitment practices. However, based on observed overtime, I find no evidence supporting the view that temporary employees provide greater effort after the reform. JEL classification: J68; J63; J24; C41; C24; C25
Optical cavity integrated surface ion trap for enhanced light collection

This work was supported by Sandia’s Laboratory Directed Research and Development (LDRD) and the Intelligence Advanced Research Projects Activity (IARPA). Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.