Miracle-dz/UniFAR-FTUs huggingface dataset:
Ghanaian SMEs’ perspective on the interrelationship between market and entrepreneurial orientations

PurposeThis research examines the interrelationships between market orientation (MO) and entrepreneurial orientation (EO) in the small- and medium-sized enterprise (SME) sector. Due to the conflicting results associated with each orientation's influence on firm performance, some researchers advanced that scholars should resort to concurrent observation of the constructs. To the researchers, concurrent deployment of the constructs by businesses is likely to result in an enhanced performance. However, what is lacking in their proposition is how the deployment of these resources should be, thereby leading to a knowledge gap in the literature. The aforementioned gap is what this paper seeks to address.Design/methodology/approachThe study employed deductive research approach, and data were collected from 366 SMEs' owners or owner-managers of SMEs in two metropoles in Ghana. For this study, the hand delivery and collection of questionnaire technique was deployed. The reason is that most respondents may be reluctant to respond to the questionnaires through the post or Internet. Partial least square-structural equation modelling (PLS-SEM) was employed for the data analysis due to its importance in allowing the testing of relationships among constructs. Furthermore, seven-point Likert scale was used to generate responses from the respondents.FindingsThe result indicates that MO and EO have a positive and significant influence on each other. However, the influence of EO on MO is greater. Therefore, when owners of SMEs are embracing the two constructs in their businesses, EO should precede MO. The finding is a novelty of this study. Through this result, the owners of SMEs would have knowledge of embracing EO before MO during the employment of the two constructs in their firms. The study further revealed that not all the components of MO have positive and significant influence on EO, and the reverse is true. Without this study, the owners of SMEs would have placed equal attention on each construct and their components. The study also indicates that deployment of MO in its composite form rather than components is the best way for improving EO.Practical implicationsThe more SMEs engage in MO activities, the likelihood of an increase in their entrepreneurial spirit and the opposite is true. However, engaging in more EO activities would result in higher MO than the reverse.Originality/valueThe findings add to the empirical literature by revealing the interrelationships between MO and EO, which serve as a guide to owners of SMEs and practitioners in their concurrent deployment of the two constructs. The findings would also open replication doors for future researchers in different settings.
The Relevance of Islamic Economics and Finance Fundamentals to the Contemporary Economy: Islamic Economist Perceptions

There have been some studies related to the fundamental values of Islamic economics and finance. However, not many studies directly examine the relevance of the fundamental values of Islamic economics and finance to the modern contemporary economy. This study intends to examine the perception of Islamic economists on the relevance of the fundamental values of Islamic economics and finance to the contemporary economy. This research was conducted with a qualitative design by conducting a structured survey and in-depth interviews with 61 participants. Data analysis used in this research is collected from surveys and interviews from several sources and analyzed by qualitative descriptive method. The findings show that the Islamic economists perceived that the Islamic economics and finance fundamental values are relevant to contemporary modern economic conditions. The values are also considered better in overcoming economic and financial problems, thus achieving Islamic goals of public prosperity. The results also reveal the need for more vigorous efforts in promoting Islamic economics and finance fundamental values. ==========================================================================================================ABSTRAK – Relevansi Fondasi Ekonomi dan Keuangan Islam dengan Ekonomi Kontemporer: Persepsi Ekonom Islam. Kajian-kajian terkait dengan nilai-nilai dasar ekonomi dan keuangan Islam telah banyak dijumpai dalam literatur. Namun, tidak banyak penelitian yang secara langsung mengkaji relevansi nilai-nilai fundamental ekonomi dan keuangan Islam dalam tataran ekonomi kontemporer. Oleh karena itu, penelitian ini bertujuan untuk mengkaji persepsi ekonom Islam terhadap relevansi aspek fundamental ekonomi dan keuangan Islam dalam terhadap ekonomi kontemporer. Penelitian ini dilakukan dengan pendekatan kualitatif dimana data-data didapat dengan cara survei terstruktur dan wawancara mendalam dengan 61 peserta. Analisis data dilakukan dengan metode deskriptif kualitatif. Hasil kajian menunjukkan bahwa para ekonom Islam menganggap bahwa nilai-nilai fundamental ekonomi dan keuangan Islam relevan dengan kondisi ekonomi kontemporer. Nilai-nilai tersebut juga dianggap lebih baik dalam mengatasi masalah ekonomi dan keuangan kontemporer, sehingga mencapai tujuan syariah untuk kesejahteraan umat. Hasil kajian juga mengungkapkan tentang pentingnya upaya yang lebih gencar dalam mempromosikan nilai-nilai fundamental ekonomi dan keuangan Islam.
Microbiome Diversity in Vaginal Fluid and Sensitivity Patterns in Preterm Premature Rupture of Membrane Cases

Introduction: Preterm premature rupture of membranes (PPROM) is spontaneous rupture of the fetal membranes before 37 completed weeks and before the onset of labor. PPROM occurs in 3% of all pregnancies and is responsible for approximately one-third of all preterm deliveries. It leads to increase in perinatal morbidity and mortality. Aim: The present study aimed to characterize the microbiome of vaginal fluid, which will be helpful in the selection of empiric antimicrobial therapy. Materials and Method: A prospective observational study was conducted in the Department of Obstetrics and Gynaecology, Pradyumna Bal Memorial Hospital, Kalinga Institute of Medical Sciences (KIMS), Bhubaneswar during the period of October 2019 to June 2021 to characterize the microorganisms in the vaginal fluid and their antimicrobial sensitivity patterns found in antenatal women presenting with PPROM. A total of 160 antenatal women diagnosed with PPROM, gestational age between 28 weeks to 36 weeks and 6 days were included in the study. High vaginal swabs were collected for microbial culture and sensitivity. Results: Out of 160 samples, the growth of organisms was observed in 134 (85.09%) samples. Out of them, 133 were monomicrobial, one was polymicrobial. Common isolated infections included Enterococcus faecalis (17.39%), followed by Staphylococcus aureus (14.29%), Escherichia coli (11.18%), and Staphylococcus haemolyticus (6.21%). Most of them were sensitive to ampicillin followed by linezolid and vancomycin. S. aureus was most sensitive to linezolid followed by gentamicin and vancomycin. Most isolates were multidrug-resistant. Conclusion: The empirical antimicrobial treatment started for PPROM management should be based on the established changing microbiological pattern and sensitivities with due consideration of geographical and demographic variations.
Analyses of Vibration Signals Generated in W. Nr. 1.0038 Steel during Abrasive Water Jet Cutting Aimed to Process Control

The presented research was aimed at finding a suitable tool and procedure for monitoring undercuts or other problems such as cutting without abrasive or inappropriate parameters of the jet during the abrasive water jet (AWJ) cutting of hard-machined materials. Plates of structural steel RSt 37-2 of different thickness were cut through by AWJ with such traverse speeds that cuts of various qualities were obtained. Vibrations of the workpiece were monitored by three accelerometers mounted on the workpiece by a special block that was designed for this purpose. After detecting and recording vibration signals through the National Instruments (NI) program Signal Express, we processed this data by means of the LabVIEW Sound and Vibration Toolkit. Statistical evaluation of data was performed, and RMS was identified as the parameter most suitable for online vibration monitoring. We focus on the analysis of the relationship between the RMS and traverse speed.
Cap analysis of gene expression reveals alternative promoter usage in a rat model of hypertension

Cap analysis of gene expression (CAGE) tag sequencing from left ventricles of a rat model of hypertension identifies genes that use alternative promoters in a disease condition. The role of alternative promoter usage in tissue-specific gene expression has been well established; however, its role in complex diseases is poorly understood. We performed cap analysis of gene expression (CAGE) sequencing from the left ventricle of a rat model of hypertension, the spontaneously hypertensive rat (SHR), and a normotensive strain, Brown Norway to understand the role of alternative promoter usage in complex disease. We identified 26,560 CAGE-defined transcription start sites in the rat left ventricle, including 1,970 novel cardiac transcription start sites. We identified 28 genes with alternative promoter usage between SHR and Brown Norway, which could lead to protein isoforms differing at the amino terminus between two strains and 475 promoter switching events altering the length of the 5′ UTR. We found that the shift in Insr promoter usage was significantly associated with insulin levels and blood pressure within a panel of HXB/BXH recombinant inbred rat strains, suggesting that hyperinsulinemia due to insulin resistance might lead to hypertension in SHR. Our study provides a preliminary evidence of alternative promoter usage in complex diseases.
Downregulation of Methionine Cycle Genes MAT1A and GNMT Enriches Protein-Associated Translation Process and Worsens Hepatocellular Carcinoma Prognosis

The major biological methyl donor, S-adenosylmethionine (adoMet) synthesis occurs mainly in the liver. Methionine adenosyltransferase 1A (MAT1A) and glycine N-methyltransferase (GNMT) are two key enzymes involved in the functional implications of that variation. We collected 42 RNA-seq data from paired hepatocellular carcinoma (HCC) and its adjacent normal liver tissue from the Cancer Genome Atlas (TCGA). There was no mutation found in MAT1A or GNMT RNA in the 42 HCC patients. The 11,799 genes were annotated in the RNA-Seq data, and their expression levels were used to investigate the phenotypes of low MAT1A and low GNMT by Gene Set Enrichment Analysis (GSEA). The REACTOME_TRANSLATION gene set was enriched and visualized in a heatmap along with corresponding differences in gene expression between low MAT1A versus high MAT1A and low GNMT versus high GNMT. We identified 43 genes of the REACTOME_TRANSLATION gene set that are powerful prognosis factors in HCC. The significantly predicted genes were referred into eukaryotic translation initiation (EIF3B, EIF3K), eukaryotic translation elongation (EEF1D), and ribosomal proteins (RPs). Cell models expressing various MAT1A and GNMT proved that simultaneous restoring the expression of MAT1A and GNMT decreased cell proliferation, invasion, as well as the REACTOME_TRANSLATION gene EEF1D, consistent with a better prognosis in human HCC. We demonstrated new findings that downregulation or defect in MAT1A and GNMT genes can enrich the protein-associated translation process that may account for poor HCC prognosis. This is the first study demonstrated that MAT1A and GNMT, the 2 key enzymes involved in methionine cycle, could attenuate the function of ribosome translation. We propose a potential novel mechanism by which the diminished GNMT and MAT1A expression may confer poor prognosis for HCC.
Does the use of mobile applications or mobile health technology improve diet quality in adults? A protocol for a systematic literature review

Background: Mobile technology has grown at an exceptional rate and is now a huge part of our daily living. This use of mobile technology has opened up new possibilities in treating health, with almost half of the current applications linked to the mHealth sector. In particular, dietary measurement, applications have become very accessible and very popular. As dietary issues have become more prevalent, more mobile and mHealth applications offer various solutions. This systematic review aims to address if the use of such mobile applications or mobile health technology can improve diet quality in adults that interact with them. Methods: A systematic review of randomised controlled trials (RCTs) and non-randomised controlled trials (NRCTs) will be conducted. The Cumulative Index to Nursing and Allied Health Literature (Cinahl), The American Psychological Association’s (APA Psycinfo), and PubMed will be searched from January 2010 to November 2021. Primary outcomes will include identifying if adults who use mobile applications and health technology improve their diet quality compared to adults who do not use this technology. Study selection will follow the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) guidelines. The methodological appraisal of the studies will be assessed independently by two different reviewers (AS and JR) using the Cochrane Risk-of-Bias Tool for RCTs and the Risk-of Bias In Non-Randomised Studies Tool for NRCTs. Ethics and dissemination: Ethical approval is not essential for this systematic review. Only data from studies that are publically available from previously published studies will be used. The findings of this systematic review will be submitted for publication in a peer-reviewed journal and presented at relevant conferences. PROSPERO registration: CRD42021240224 (01/03/2021).
A practical implementation of mask detection for COVID-19 using face detection and histogram of oriented gradients

ABSTRACT Wearing a face mask is one of the effective barriers against the coronavirus COVID-19 pandemic. It offers protection according to the World Health Organization and many medical papers. This paper proposes a method for masked face recognition in order to force the population to put on masks and reduce the COVID-19 pandemic in the world. The Viola-Jones algorithm is used to detect the face, and the Histogram of Oriented Gradients (HOG) technique was used to extract the relevant features from face images. The performance of the proposed algorithm is analysed for different data using two common image classification methods, including support vector machines and K Nearest Neighbor (KNN) algorithm for machine learning, which are used to classify the feature vectors. Their performance was compared and evaluated using accuracy. In this case, the experimental result shows that the support vector machine classifier achieved the highest accuracy and surpasses the KNN method in mask detection with an accuracy of 99.43%.
Analysis of amino acids content in the plant components of the antidiabetic herbal mixture by GC-MS

Medicinal plants and their combinations due to the wide range of biologically active substances can influence on various links of the pathogenetic mechanism of development of DM type 2 and its complications. One of such combinations is an antidiabetic herbal mixture (Urticae folia, Rosae fructus, Myrtilli folia, Menthae folia and Taraxaci radices) with established hypoglycaemic, hypolipidemic, antioxidant, hepatoprotective, pancreatoprotective activity in previous pharmacological studies in vivo and in vitro and defined phytochemical composition. Thus, the aim of this study was to identify and establish the content of amino acids in the plant components of antidiabetic herbal mixture. The amino acids were separated by GC-MS method with pre-column derivatization. The calibration curves of twenty CRS of amino acids were linear (R2 > 0.98) over the range of 1–100 µg/mL, the LODs and the LOQs were in the range of 0.01–0.07 µg/mL and 0.02–0.20 µg/mL, respectively. The results of analysis showed that the predominant essential amino acid was L-proline in Taraxaci radices, Urticae folia, Rosae fructus and Menthae folia, its total content was 101.46 mg/g, 25.31 mg/g, 23.04 mg/g and 19.30 mg/g, respectively. In addition, it was established total content of essential amino acid – L-leucine that can stimulate insulin secretion in β-cells of the pancreas. Its total content was 58.51 mg/g in Taraxaci radices, 9.58 mg/g in Myrtilli folia, 4.68 mg/g in Rosae fructus, 2.99 mg/g in Urticae folia and 0.79 mg/g in Menthae folia. Chromatographic examination also revealed L-phenylalanine, an essential amino acid important for antidiabetic therapy that can increase insulin secretion, stimulate proliferation and neogenesis of β-cells of the pancreas and reduce insulin resistance. Its total content was 13.42 mg/g in Myrtilli folia, 2.23 mg/g in Rosae fructus, 1.478 mg/g in Urticae folia, 1.46 mg/g in Taraxaci radices and 0.52 mg/g in Menthae folia. This phytochemical study shows, which plant material forms the amino acid composition and content in the finished herbal mixture and due to which biologically active substances the antidiabetic activity of this phytocomposition is manifested.
Seismic Response of a 5-MW Wind Turbine: The ShakeOut Scenario

In November 2008, the National Science Foundation (NSF) and the U.S. Geological Survey (USGS) sponsored “The Great Southern California ShakeOut” to raise awareness about the possible ramifications of a 7.8-magnitude earthquake along the San Andreas Fault. Such an earthquake would directly affect Palm Springs, California, a prime location for wind power. California’s Assembly Bill (AB) 32 (2006), legislation requiring reduction in emissions to 1990 levels by 2020, reinforces the importance of investigating the influence that seismic events might have on design loads for new large wind turbines. Anticipating that turbines will grow larger than the current 3-MW models with a hub height of 80 m, we examined the ramifications of a motion derived for The Great Southern California ShakeOut on the National Renewable Energy Laboratory’s (NREL) 5-MW baseline wind turbine model with a hub height of 90 m. The resulting structural demand is compared for scenarios where the turbine is idling, continues operation, and initiates an emergency shutdown.
Performance Prediction of Quantization Based Automatic Target Recognition Algorithms

Horvath, Matthew S. , Ph.D., Engineering Ph.D. Program, Department of Electrical Engineering, Wright State University, 2015. Performance of Quantization Based Automatic Target Recognition Algorithms. The investment in and subsequent development of sensor technology has led to a glut of sensor data burdening the typically human-centric analysis and exploitation process. It is now more important than ever to have robust and well-studied automatic target recognition (ATR) algorithms to alleviate some of the burden on the human operators. The difficulty of designing these systems is that there are many sources of potential variation in the data, often referred to as operating conditions (OCs) and designing algorithms robust to these OCs is difficult. Additionally, analytically determining algorithm performance, often referred to as performance prediction, as a function of these OCs is important as it provides insight into when the algorithms will fail. Quantization based ATR algorithms have shown to be robust to certain OCs. These quantization based algorithms first discretize the pseudo-continuous data into Nq discrete bins. This discretization step is important as it hypothetically reduces the variation due to certain nuisance parameters in the data and errors resulting from approximated signatures. This research focused on three algorithms: multinomial pattern matching (MPM), quantized grayscale matching (QGM), and a quantized mean-squared error approach (QMSE). The first two are known as model-based ATR algorithms and assume that in-class images are the result of realizations of a statistical model with class-conditional parametrizations. The last is a template-based algorithm which assumes a deterministic “mean” image is available with which to compare candidate targets. The goal of this research is to develop analytic solutions, or approximations, to the performance of these algorithms in a process known as performance prediction. This analysis shows the expected performance of these algorithms as a function of the parameters used to model the OCs, which is difficult to do with empirical simulations on even a large truthed iii dataset. We focus on performance prediction approaches to a baseline AWGN noise case applicable to both SAR and EO/IR imagery, an degradation case again applicable to both SAR and EO/IR imagery, and an ideal point response case applicable to SAR imagery only, and assume that these variations are conditionally independent from other sources of variation in the data.
An Analytics Approach to Hypertension Treatment

Hypertension is a major public health issue worldwide, affecting more than a third of the adult population and increasing the risk of myocardial infarction, heart failure, stroke, and kidney disease. Current clinical guidelines have yet to achieve consensus and continue to rely on expert opinion for recommendations lacking a sufficient evidence base. In practice, trial and error is typically required to discover a medication combination and dosage that works to control blood pressure for a given patient. We propose an analytics approach to hypertension treatment: applying visualization, predictive analytics methods, and optimization to existing electronic health record data to (1) find conjectures parallel and potentially orthogonal to guidelines, (2) hasten response time to therapy, and/or (3) optimize therapy selection. This thesis presents work toward these goals including data preprocessing and exploration, feature creation, the discovery of clinically-relevant clusters based on select blood pressure features, and three development spirals of predictive models and results.
Experimental Diagnostics of the Emotional State of Individuals Using External Stimuli and a Model of Neurocognitive Brain Activity

In this paper, we study ways and methods to diagnose the emotional state of individuals using external audiovisual stimuli and heart telemetry tools. We apply a mathematical model of neurocognitive brain activity developed specifically for this study to interpret the experimental scheme and its results. This experimental technique is based on monitoring and analyzing the dynamics of heart rate variability (HRV), taking into account the particular context and events occurring around the subject of the study. In addition, we provide a brief description of the theory of information images/representations used for the paradigm and interpretation of the experiment. For this study, we viewed the human mind as a one-dimensional potential hole with finite walls of different sizes and an internal potential barrier modeling the border between consciousness and subconsciousness. We also provided the foundations of the mathematical apparatus for this particular view. This experiment allowed us to identify the characteristic markers of influencing external stimuli, which form a foundation for diagnosing the emotional state of an individual.