Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear and nonlinear combined aerodynamic reduced order model based on residual network framework

Residual convolutional neural network (ResNet) is a rising technology in the field of artificial intelligence due to its advantages of easy optimization, high accuracy, information fidelity and no gradient disappearance. Based on the powerful ability of machine learning to learn from big data features, a residual network aerodynamic reduced order model (ROM) framework based on CFD sample data was proposed. In this letter, a binary airfoil is taken as the research object, and the displacement information representing the movement characteristics of the flow field can be transmitted by two ways: one is that the input information is continuously captured and extracted by the deep convolution layer; the other is that the input information is directly transmitted around the convolutional layer. Then the characteristic information of the two approaches is integrated and activated through the output layer to complete the regression prediction of the wing aerodynamic characteristics. Finally, the ROM frame is used to predict the strongly nonlinear hysteresis loops of airfoil under pitching motion, and the results show that the ROM frame is effective. In addition, the framework can be applied to qualitative interpretation of complex flow phenomena and aeroelastic analysis.
Integrating information practices into everyday teaching

This paper reports on the information practices and information literacy (IL) skills of South Korean elementary school students from the perspectives of working teachers. Key to this investigation was the notion of information practice, and how this is shaped by the practice architecture found in an educational setting. A sequential mixed design was undertaken to investigate these ideas which consisted of exploratory interviews with 4 elementary school teachers and was followed by a questionnaire which analysed the responses of 314 elementary school teachers. Findings indicate that in this setting, teachers, students and pre-set curricular content serve as the most frequently used information sources for students during their everyday classes. We pay specific attention to the ongoing centrality of the textbook, in its traditional paper format, to the ways in which teachers design learning activities, and suggest that this limits the diversity of informational approaches to which young South Korean learners are exposed. While these learners are engaged, they are limited in terms of informational genre since teachers and textbooks were found to be dominant information proxies. Activities in which students engage in active seeking or scanning are rarer. Contexts with such a configuration may be hindering the development of critical information literacy skills that are vital in dealing with the abundance of information faced by individuals today.
Negative reflections of nepotism on employees and obstacles in the process of institutionalization of family businesses

One of the most prominent problems faced by family businesses is the presence of nepotism. This study was conducted to find out if nepotism is present in local family businesses operating in Kosovo. It also aims to identify the negative reflections of nepotism on employees and the effects of nepotism on obstructing the institutionalization of family businesses. In this study, direct interviews were conducted with the managers of 10 family businesses who have no family ties with the founders of the business. The study was conducted with qualitative methods with the model of the case study, where the program MAXQDA 2020 was used for data analysis, which created codes and categories from the results of interviews. From the results of this study, it is understood that nepotism as a phenomenon is widespread in these enterprises. On the other hand, some of the negative reflections of nepotism on the managers and other employees of these family businesses have been identified as a result of the existence of nepotism. It is also understood that the existence of nepotism is an obstacle to the institutionalization of family businesses
Fibrosis Predictive Score in Caucasian Patients with Metabolic Syndrome

Introduction Many of the patients presenting with metabolic syndrome (MetS) also have liver steatosis (NAFLD) and some of them could develop liver fibrosis. Purpose To develop a simple score that could rule out fibrosis, especially significant fibrosis (F≥2) and could be used in daily practice in patients with MetS, in order to identify patients at risk. Patients and Methods A total of 204 patients with MetS were prospectively enrolled. Evaluation of liver fibrosis was made using Vibration Controlled Transient Elastography while evaluation of steatosis was achieved using ultrasound (US). Results Out of 204 patients with MetS, 179 patients (87.7%) had reliable liver stiffness measurements and 22.9% (41/179) had F ≥2. To formulate the fibrosis predicting score, all clinical variables associated with F ≥2 in the univariate analysis were considered in a multivariate regression model. According to the power of correlation, by consensus, we attributed 1 point for BMI >31.4 kg/m2, 1 point for female gender, 1 point for HDLc <47mg/dL, 1 point for mild steatosis at US, 1.5 point for moderate and 2 points for severe steatosis. Conclusion At an optimal cut-off value of <3.5, our score could be used to rule-out the risk for developing at least significant fibrosis with a high negative predictive value (NPV 89.2%) in patients with MetS.
First order universal filters employing single DV-EXCCCII

ABSTRACT This paper reports two filter circuits based on Differential Voltage Extra-X Current Controlled Current Conveyor (DV-EXCCCII). The first proposed circuit is a voltage-mode first-order universal filter that employs one DV-EXCCCII, one resistor, and one grounded capacitor. This circuit can realise all standard first-order filters, that is, low-pass, high-pass and all-pass filter. The second proposed circuit is a first-order multimode universal filter that employs a single DV-EXCCCII. This circuit can realise filter in current-mode, voltage-mode and trans-admittance mode with a single capacitor. However, a trans-impedance mode universal filter is realised with an additional resistor. Furthermore, the filter is electronically tunable with the bias current of DV-EXCCCII. The proposed filter circuits are verified using the SPECTRE simulator of CADENCE VIRTUOSO tool in 0.18 µm UMC CMOS technology parameters.
Automation Stages & Levels, 20 Years After

In this article I describe the origins of the stages and levels of the automation concept and present the taxonomy, model, and theories underlying this concept. I then show how both simplifications and elaborations of the resulting tradeoff model of degree of automation can address some of Kaber’s concerns about its utility in design.
Prediction of G-protein Coupled Receptors using Deep Learning: A Review

The biggest super classes of the membrane proteins are G-protein coupled receptors as well as GPCRs are very significant for drug design goals. GPCRs are sometimes known as heptahelical receptor as well as seven-transmembrane receptor. GPCRs are accountable for several physicochemical and biological activities like cellular growth, neurotransmission, smell as well as vision. This paper presents a review related to current approaches to predict GPCRs. Extensive research on GPCRs have progressed to novel discoveries that open undiscovered and promising drug design opportunities and efficient drug-targeting Gprotein coupled receptors therapies. This paper concentrates primarily on the process of deep learning to
Composite Analysis of Mobile Banking Usage: Dimension and Construct Effect

This study explores the dimension and construct effect of mobile banking usage on customer satisfaction and loyalty. The research done in previous studies only considered a dimensional or constructive effect. But the construct model cannot be expressed as a dimensional effect. Furthermore, the dimension connection cannot be defined as a construct effect. As a result, both levels should be subjected to hypothesis testing. Mobile banking usage model is measured using a composite model and a formative-formative type for second-order constructs, while customer satisfaction and loyalty are measured using a consistent partial least squares method (PLSc). The data were obtained from 400 students at Valaya Alongkorn Rajabhat University. The consequence of the dimensional effect shows that the influence of promotions, perceived usefulness, and perceived security has a substantial impact on customer satisfaction and loyalty. For the construct effect, the 7Ps organize the mobile banking usage model well, which significantly impacts customer satisfaction and loyalty.
Hybrid Grey Wolf and Finite Element Method (GWO-FEM) Algorithm for Enhancing High Voltage Insulator String Performance in Wet Pollution Conditions

The presence of wet pollution on the upper surface of a string insulator increases the electric field on the insulator surface, especially at the triple junction (pin-cement, cement-porcelain) as well as at the surrounding air of the insulator. The rise of the electric field leads to the ionization of the air surrounding the insulator. This phenomenon, called corona discharge, is accompanied by several consequences that are harmful to the electricity transmission network, such as electromagnetic interferences, energy losses, visible light, audible noise, and the destruction of materials by erosion. If favorable conditions are gathered, it may even cause the flashover of the insulator. Designing an optimal insulator shape that reduces this electric field value at the triple junction will be an important achievement in enhancing the performance of electrical grids. The objective of this paper is to evolve a hybrid algorithm based on the GWO-FEM for optimizing the shape and the electrical performance of a string insulator. To achieve this purpose, this work is structured in four parts. First, modeling of the insulator string geometry is conducted in Comsol-multiphysics, then FEM computation of the electric field on the polluted surface of the string insulator is completed, and the maximum electric field value at the triple junction is saved as the fitness function that will be sent to the GWO algorithm to be optimized (minimized). The third part of the work is devoted to the coding of the constrained (electrical and geometrical constraints) GWO algorithm in a Matlab interface, and finally, coupling the GWO code with the FEM code. This study is achieved in wet polluted conditions. The results are given in both 2D and 3D representations. From the obtained results we can confirm that the developed GWO-FEM hybrid algorithm for optimizing insulator strings is a very promising tool for designing and enhancing the shape and the electrical performance of insulators.
Navitoclax Enhances the Therapeutic Effects of PLK1 Targeting on Lung Cancer Cells in 2D and 3D Culture Systems

The efficacy of antimitotics is limited by slippage, whereby treated cells arrested in mitosis exit mitosis without cell division and, eventually, escape apoptosis, constituting a serious resistance mechanism to antimitotics. Strategies to overcome slippage should potentiate the cancer cell killing activity of these antimitotics. Such strategies should accelerate cell death in mitosis before slippage. Here, we undertook a mechanistic analysis to test whether the apoptosis activator Navitoclax potentiates apoptosis triggered by the antimitotic BI2536, a potent inhibitor of Polo-like kinase 1 (PLK1) with the goal of overcoming slippage. We found that cancer cells in 2D cultures treated with BI2536 alone accumulate in mitosis, but a significant fraction of arrested cells undergo slippage and survive. Remarkably, combining BI2536 with Navitoclax dramatically reduces slippage, shifting the cell fate to accelerated death in mitosis. The results are confirmed in 3D spheroids, a preclinical system that mimics in vivo tumor drug responses. Importantly, in 3D spheroids, the effect of the BI2536/Navitoclax combination requires a lower therapeutic dosage of each drug, underlying its potential to improve the therapeutic index. Our results highlight the relevance of apoptosis potentiators to circumvent slippage associated with antimitotics. The combination of BI2536 with Navitoclax shows in vitro synergy/additive effect, which warrants further clinical research.
Os stakeholders e seu grau de influência no setor ferroviário: um estudo na Ferrovia Tereza Cristina – FTC

O tema estratégia organizacional destaca a importância do conhecimento acerca dos stakeholders para as empresas e do atendimento de suas expectativas. Neste contexto apresenta-se este estudo com o objetivo geral identificar os stakeholders da empresa Ferrovia Tereza Cristina (FTC) e as influências que eles exercem sobre ela. A pesquisa realizada foi de campo, com predomínio do enfoque quantitativo, apontou como resultado 23 stakeholders do ambiente externo e 3 do ambiente interno, o que demonstra que a empresa está voltada para o ambiente externo do que interno. Quanto ao grau de influência que estes stakeholders exercem sobre a empresa, destacam-se no ambiente interno os acionistas (stakeholder interno) e, no ambiente externo os clientes (transporte de carga) e as mineradoras (stakeholders externos). Quanto à dependência estratégica da empresa sobre os stakeholders, os resultados evidenciaram que a FTC possui uma forte relação de interdependência com seus stakeholders, ou seja, entre os atores envolvidos neste cenário (FTC e stakeholders) existe uma dependência mútua onde a empresa não sobrevive sem os stakeholders e, estes não sobrevivem sem a empresa. Por outro lado, a FTC se mostrou dependente dos órgãos governamentais e dos órgãos reguladores, Agência Nacional de Energia Elétrica e Agência Nacional de Transporte Terrestre.
Android malware detection using network traffic based on sequential deep learning models

The increasing trend of smartphone capabilities has caught the attention of many users. This has led to the emergence of malware that threatening the users' privacy and security. Many malware detection methods have been proposed to deal with emerging threats. One of the most effective ones is to use network traffic analysis. This article proposed a method based on LSTM (Long Short‐term Memory) for malware detection which is capable of not only distinguishing malware and benign samples, but also detecting and identify the new and unseen families of malware. As far as we know, this is the first time that traffic data has been modeled as a sequence of flows and a sequential based deep learning model is employed. In this article, we have performed several case studies to exhibit the capabilities of the proposed method including malware detection, malware family identification, new (not seen before) malware family detection, as well as evaluating the minimum time required to detect malware. The case studies show that the model is even capable of detecting new families of malware with more than 90% accuracy, although these results can only be verified on existing families in this dataset and such a claim cannot be generalized to other examples of malware. Moreover, it is shown the model is able to detect the malware through capturing 50 connection flows (about 1600 packets in average) with the AUC of more than 99.9%.
Resilience in Nursing Students: The Effect of Academic Stress and Social Support

Objective: This study was conducted to evaluate the levels of psychological resilience, academic stress and social support available to nursing students and the relationship between these factors. Methods: The population of the study, which had a descriptive and correlational research design, was made up of 1202 students, while the sample consisted of 322 students selected using the sample size formula for a known population. Data were collected using a Structured Questionnaire, the Psychological Resilience Scale for Adults, the Nursing Education Stress Scale and the Multidimensional Scale of Perceived Social Support. Results: 76.7% of students were female and 23.3% were male. A statistically significant correlation was found between scores for psychological resilience and perceived social support (p<0.05). It was found that the individual characteristics of students affected their psychological resilience. Levels of psychological resilience, academic stress, and social support among nursing students are at a moderate level. Conclusion: The significance of resilience is clear, a better understanding is needed of what factors affect a student’s level of resilience and how this resilience can best be improved.
After the merger

Open any newspaper and you'll find a story on the latest merger or acquisition. A recent global survey conducted by A.T. Kearney has yielded results comparable with many other studies on the subject. High percentages of all mergers worldwide fail to create value. In some cases they even destroy it.A record number of mergers are making headlines and prompting questions about which businesses will ultimately succeed and which will fail. Although integration is not without stress for an organization and its employees, mergers can succeed if companies develop and adhere to a highly disciplined strategy of value-adding on day one while implementing a blueprint for future growth.After the Merger overcomes the vagueness of general, well-intended advice and illustrates case by case, rule by rule, how to be successful when embarking on a merger.
Design of Main Circuit Parameters for Modular Multilevel Matrix Converter in LFAC System

The low-frequency AC (LFAC) transmission is a competitive scheme for offshore wind power integration, in which the modular multilevel matrix converter (M3C) is the key equipment. In this paper, the selection methods of the M3C main circuit parameters are proposed. First, the maximum arm voltage is derived and the selection method of the sub-module (SM) number is established. Then, according to the switching function approach, the analytical expressions of the average SM capacitor current and the average SM capacitor voltage are derived. On this basis, the selection method of the SM capacitance is proposed. Additionally, the design principle of the arm inductance is proposed. Finally, a case is elaborated to illustrate the proposed M3C main circuit parameter selection methods and provide a reference for practical projects.
Optimized Deconvolutional Algorithm-based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction

To apply deconvolution algorithm in computer tomography (CT) perfusion imaging of acute cerebral infarction (ACI), a convolutional neural network (CNN) algorithm was optimized first. RIU-Net was applied to segment CT image, and then equipped with SE module to enhance the feature extraction ability. Next, the BM3D algorithm, Dn CNN, and Cascaded CNN were compared for denoising effects. 80 patients with ACI were recruited and grouped for a retrospective analysis. The control group utilized the ordinary method, and the observation group utilized the algorithm proposed. The optimized model was utilized to extract the feature information of the patient's CT images. The results showed that after the SE module pooling was added to the RIU-Net network, the utilization rate of the key features was raised. The specificity of patients in observation group was 98.7%, the accuracy was 93.7%, and the detected number was (1.6 ± 0.2). The specificity of patients in the control group was 93.2%, the accuracy was 87.6%, and the detected number was (1.3 ± 0.4). Obviously, the observation group was superior to the control group in all respects (P < 0.05). In conclusion, the optimized model demonstrates superb capabilities in image denoising and image segmentation. It can accurately extract the information to diagnose ACI, which is suggested clinically.
Climate and human exploitation have regulated Atlantic salmon populations in the River Spey, Scotland, over the last 2000 years

Historical salmon catch records suggest that climatic variability, and more recently human exploitation, control patterns of abundance in Atlantic salmon populations. We present the first long-term (2000-year) reconstruction of Atlantic Salmon population variations based on a Marine Derived Nutrient (MDN) lake sediment record. Our record is constructed from nitrogen isotopes (δ15N) measured from a lake sediment core, which we compare with an escapement index (EI) derived from historic net catch data on major Scottish salmon rivers. We used an isotope mixing model to demonstrate that the N isotope values are likely enriched with MDN and demonstrate that Loch Insh sediments are enriched compared with a control site (Loch Vaa) that has never had exposure to salmon. We demonstrate that current adult spawner returns are around half that of historic values prior to major human exploitation. Before the onset of widespread human exploitation and habitat degradation, large fluctuations in salmon abundance are attributed to variations in North Atlantic sea surface temperature. While our data support published reconstructions of declining Atlantic salmon stocks in Northwest European rivers over the last 1000 years, rather than point to a solely human cause, the human impact appears to be overprinted on larger-scale changes in marine habitat occurring at the transition from the warmer Medieval Climatic Anomaly (MCA) to the cooler Little Ice Age (LIA).
UNDERSTANDING TRIPLE NEGATIVE BREAST CANCER: A REVIEW ON MOLECULAR SIGNALING PATHWAYS

Triple Negative Breast Cancer (TNBC) is a divergent disease which lacks receptor for estrogen (ER), progesterone (PR) and human epidermal growth factor receptor 2 (HER2). It constitutes about 15-20% of total breast cancer cases globally which mainly strikes younger women. Due to its aggressive nature, the standard choice of treatment for TNBC is chemotherapy, but the same has very poor prognosis due to risk of tumor recurrence, metastasis and death. To direct the line of research to get pathological Complete Response (pCR) and increase the Quality of Life (QOL) years of cancer patients, it is necessary to understand the molecular pathways and their down signalling pathways which can be targeted. Triple negative breast cancer involves several signaling pathways leading to tumor initiation, proliferation and metastasis such as Ras/Raf/MEK pathway, PI3/AKT/mTOR pathway, DNA repair pathway, Wnt/β-catenin Pathway, Hedgehog pathway, Notch signalling pathway and immune pathway. Currently available treatment for triple negative breast cancer comprises chemotherapy in combination which includes anthracyclines, platinum compounds, folate antagonist, taxanes, cyclophosphamide and others. The present review focuses on the molecular aspect of TNBC subtypes and targets. Also the ongoing clinical trials along with the completed clinical trials targeting different pathways for the treatment of TNBC patients are discussed.
Percepción de los estudiantes universitarios sobre el uso de la Inteligencia Artificial en los procesos de reclutamiento y selección de personal

Los adolescentes son el grupo más influenciable al impacto de las nuevas tecnologías, especialmente si estas pueden simplificarles las cosas. Muchos de estos jóvenes son universitarios y encuentran en la tecnología a un importante aliado. En ese sentido, la presente investigación busca demostrar como los estudiantes universitarios peruanos perciben la importancia que tiene la tecnología, particularmente a la Inteligencia Artificial como un eje de influencia a la hora en que las empresas reclutan y seleccionan a su personal. Se trabajó mediante un muestreo por conveniencia en donde se analizaron las opiniones de 120 estudiantes de los últimos semestres de dos universidades de la ciudad de Lima. Los resultados indican que los estudiantes universitarios perciben una moderada influencia de la Inteligencia Artificial sobre los procesos de Reclutamiento y Selección. La presente investigación puede servir como referencia para el análisis de nuevas tecnologías y su impacto en distintos grupos demográficos.