Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis, Characterization, ADMET Prediction and Molecular Docking Studies Against COVID-19 Proteins of Novel 2-(3-(4-substitutedaryl)guanidine-1-yl)-4-phenyl-6-(thiophene-2-yl)pyrimidines

Novel 2-(3-(4-substituted aryl)guanidine-1-yl)-4-phenyl-6-(thiophene-2-yl)pyrimidines (7) were synthesized by simple condensation between chalcones with therapeutic biguanide derivatives The novel guanidinopyrimidine derivatives (7) were characterized by different spectral studies Furthermore, subject to ADMET prediction using pkSCM software and molecular docking studies against different kinds of novel RNA proteins such as, spike (PDB ID: 6XC3), main protease (3CLpro - PDB ID: 6LU7), RNA-dependent RNA polymerase (RdRp - PDB ID: 6W9Q) and host protein ACE2 (PDB ID:1R42) spike protein and also the activities are compared with FDA-approved few human trial drugs such as hydroxychloroquine (HQC), favipiravir and lopinavir © 2020 Ubiquity Press All rights reserved
Modeling and identification of rotational joint driven by polymer fiber actuator

Coiled polymer actuators have the characteristic to generate power by contracting when heated under strain. This work presents a project of a rotational joint driven by such actuators. Furthermore, the thermomechanical model of the CPAs is identified by means of the least squares method. In addition, a model of the joint considering a viscous friction is suggested. Finally, the joint model is identified by means of a non linear optimization algorithm.
Rastreamento do ponto de máxima potência em sistemas fotovoltaicos sob condições de sombreamento usando rede neural artificial

This paper proposes a method of maximum power point tracking for photovoltaic systems combining an Artifical Neural Network (ANN) with the Incremental Conductance (InC) method. Although it’s been largely applied, the InC method generally fails to track the Maximum Power Point (MPP) in a partial shading condition. For this reason, an ANN was trained for the purpose of providing an initial reference voltage that will guarantee the InC method to track the MPP in these conditions. Different levels of partial shading conditions are analyzed for an array of varied numbers of solar panels, comparing the InC method with and without the RNA. Results show the system with the ANN converged to the MPP in all considered cases. Resumo: Este trabalho propõe um método de rastreamento do ponto de máxima potência em sistemas fotovoltaicos combinando uma Rede Neural Artificial (RNA) com a técnica da Condutância Incremental (CIn). Apesar de bastante aplicada, a técnica CIn geralmente falha em rastrear o Ponto de Máxima Potência (PMP) sob condições de sombreamento parcial. Por essa razão, uma RNA foi treinada com objetivo de fornecer uma tensão de referência inicial que garante que o rastreamento pela CIn busque o PMP nessas condições. São analisadas diferentes condições de sombreamento para um arranjo de quantidade variável de painéis, comparando a técnica CIn com e sem a utilização da RNA. Os resultados apresentados mostram que o sistema com a RNA convergiu para o PMP em todas as situações consideradas.
Dynamic matrix control with input saturation constrained

It is proposed, in this paper a dynamic matrix control (DMC) with an anti-windup (AW) based on linear matrix inequalities (LMI). The DMC-AW control is applied in the ballbeam system, in which the main purpose is to control the ball position on a rotating beam. System modeling was performed, which presented two degrees of freedom. For the mechanical system implementation a microcontroller, an ultrasonic sensor, and a servo motor were used. The proposed control was implemented both numerically with the software MATLAB and with the microcontroller ATmega328Pu. The simulation results validated the efficiency of the proposed DMC-AW and showed that the approach improves the response of the system under input saturation.
Participation in global value chains and the US–China technology gap: an application of the generalized propensity score

ABSTRACT In this study, using the generalized propensity score on a sample of 172,336 firms, we examine the technology gap between the US and China when Chinese enterprises participate in global value chains (GVC) at different potential continuous levels. We find an N-shaped relationship between the two key variables. To narrow the technology gap with the US, our empirical result also shows that it is suggested for Chinese firms to engage in GVC during the moderate interval (0.23 ~ 0.77).
Antioxidant and Antimicrobial Activities of Korean Mistletoe (Viscum album var. coloratum) Extracts against Food Poisoning Bacteria

This study was conducted to investigate the antimicrobial activities and antioxidant activities of the Korean mistletoe extract and its solvent fractions (e.g. n-hexane, ethyl ether, ethyl acetate, butanol). Ethyl ether fraction against Bacillus cereus showed stronger activities than benzoic acid (2.5 mg/mL). The MIC of korean mistletoe extract and slovent fractions were in the range of 6.25-25 mg/mL. The MIC (6.25 mg/mL) of ethyl acetate fraction onto Staphylocossus aureus was the lowest among them. Ethyl ether fraction which showed the strongest antioxidant activities by DPPH (1,1-diphenyl-2-picryl-hydrazyl) and FRAP (ferric ion reducing antioxidant power) methods had the highest total phenolic contents. It is suggested that Korean mistletoe could be utilized as natural preservative material through the study of the active compounds from ethyl ether fraction.
Sharia Board of Islamic Banks and the Attitude of Fatwa Shopping

Fatwa shopping attitude is a process of searching Sharia opinions from different Sharia scholars for suitable and convenient Fatwa to suit the need of bank managers (BMs) even at the minimum level of Sharia compliance. This research was conducted to identify the Sharia Board Members (SBMs) and the new attitude of Fatwa shopping within the supervisory and advisory mandate. The objectives of this study are to identify the mandate of SBMs of IBs and to review the attitude of Fatwa shopping within the advisory and supervisory mandate. Data was collected by way of documentary review method of existing literatures, narrative analysis as well as conceptual approach of analysis. The study gathered that both SBMs and BMs have different objectives when assessing new products which create disagreement of objectives at the strategic level. The study concluded that the leniency in issuing Fatwa ruling might lead SBMs to exercise the attitude of Fatwa shopping or easily compromise toward BMs objectives. A situation of this kind has resulted many challenges toward Sharia complaint, then the products approved by SBMs which have been alleged as non-compliant to Sharia. The finding s of this paper can be recommended for regulators, policy makers of Islamic banks and the body of knowledge of researchers for positive use of conceptualizing the current system to suit core component of Islamic Fatwa framework (IFF) in which the attitude of Fatwa shopping would be matter of history in near future.
Fully end-to-end deep-learning-based diagnosis of pancreatic tumors

Artificial intelligence can facilitate clinical decision making by considering massive amounts of medical imaging data. Various algorithms have been implemented for different clinical applications. Accurate diagnosis and treatment require reliable and interpretable data. For pancreatic tumor diagnosis, only 58.5% of images from the First Affiliated Hospital and the Second Affiliated Hospital, Zhejiang University School of Medicine are used, increasing labor and time costs to manually filter out images not directly used by the diagnostic model. Methods: This study used a training dataset of 143,945 dynamic contrast-enhanced CT images of the abdomen from 319 patients. The proposed model contained four stages: image screening, pancreas location, pancreas segmentation, and pancreatic tumor diagnosis. Results: We established a fully end-to-end deep-learning model for diagnosing pancreatic tumors and proposing treatment. The model considers original abdominal CT images without any manual preprocessing. Our artificial-intelligence-based system achieved an area under the curve of 0.871 and a F1 score of 88.5% using an independent testing dataset containing 107,036 clinical CT images from 347 patients. The average accuracy for all tumor types was 82.7%, and the independent accuracies of identifying intraductal papillary mucinous neoplasm and pancreatic ductal adenocarcinoma were 100% and 87.6%, respectively. The average test time per patient was 18.6 s, compared with at least 8 min for manual reviewing. Furthermore, the model provided a transparent and interpretable diagnosis by producing saliency maps highlighting the regions relevant to its decision. Conclusions: The proposed model can potentially deliver efficient and accurate preoperative diagnoses that could aid the surgical management of pancreatic tumor.
Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

E-commerce has become an integral part of businesses for decades in the modern world, and this has been exceptionally speeded up during the coronavirus era. To help businesses understand their current and future performance, which can help them survive and thrive in the world of e-commerce, this paper proposes a hybrid approach that conducts performance prediction and evaluation of the e-commerce industry by combining the Grey model, i.e., GM (1, 1) and data envelopment analysis, i.e., the Malmquist-I-C model. For each e-commerce company, GM (1, 1) is applied to predict future values for the period 2020–2022 and Malmquist-I-C is applied to calculate the efficiency score based on output variables such as revenue and gross profit and input variables such as assets, liabilities, and equity. The top 10 e-commerce companies in the US market are used to demonstrate model effectiveness. For the entire research period of 2016–2022, the most productive e-commerce marketplace on average was eBay, followed by Best Buy and Lowe’s; meanwhile, Groupon was the worst-performing e-commerce business during the studied period. Moreover, as most e-commerce companies have progressed in technological development, the results show that the determinants for productivity growth are the technical efficiency change indexes. That means, although focusing on technology development is the key to e-commerce success, companies should make better efforts to maximize their resources such as labor, material and equipment supplies, and capital. This paper offers decision-makers significant material for evaluating and improving their business performance.
On the Inapplicability of Supervised Machine Learning to Evolutionary Studies

Supervised machine learning (SML) is a powerful method for predicting a small number of well-defined output groups (e.g., potential buyers of a certain product) by taking as input a large number of known well-defined measurements (e.g., past purchases, income, ethnicity, gender, credit record, age, favorite color, favorite chewing gum). SML is predicated upon the existence of a training dataset in which the correspondence between the input and output is known to be true. SML has had enormous success in the world of commerce, and this success has prompted a few scientists to employ it in the study of molecular and genome evolution. Here, we list the properties of SML that make it an unsuitable tool in evolutionary studies. In particular, we argue that SML cannot be used in an evolutionary exploratory context for the simple reason that training datasets that are known to be a priori true do not exist. As a case study, we use an SML study in which it was concluded that most human genomes evolve by positive selection through soft selective sweeps (Schrider and Kern 2017). We show that in the absence of legitimate training datasets, Schrider and Kern (2017) used (1) simulations that employ many manipulatable variables and (2) a system of cherry-picking data that would put to shame most modern evangelical exegeses of the Bible. These two factors, in addition to the lack of methodological detail and the lack of either negative controls or corrections for multiple comparisons, lead us to conclude that all evolutionary inferences derived from so-called SML algorithms (e.g., discoal) should be taken with a huge shovel of salt.
VYGOTSKY SOCIOCULTURAL APPROACH IN EARLY CHILDHOOD EDUCATION

This systematic review article focuses on Vygotsky’s Sociocultural approach in the context of early childhood education which focuses on the teaching of learning and development that can be achieved through the sociocultural environment of students. This article is built by conducting previous studies or literature highlights to obtain information related to Vygotsky's sociocultural approach which refers to aspects of teaching-learning and student development. Meanwhile, this article reporting method uses optional reporting items for systematic study and Meta-Analysis (PRISMA) or Systematic Literature Review (SLR) article adapted for current research review while using two main databases namely Scopus and Web of Science. Thus, this search effort has resulted in a total of 26 articles that have been systematically censored and analyzed and then the survey successfully formulated the six main themes contained in Vygotsky's sociocultural approach namely, Social theme, Language theme, Process theme, Meaningful learning theme, Constructor theme- knowledge, and Artifacts. In total, further analysis of the six themes has resulted in five sub-themes. The findings of this study have delved deeper into sociocultural from Vygotsky’s perspective as a basis for child development.
Analysis and Design of a Diplexer for Satellite Communication System

─ This paper presents the design and analysis of a diplexer for satellite communication system based on hybrid spoof surface plasmon polariton (SSPP) and substrate integrated waveguide (SIW) transmission lines. The proposed diplexer consists of a SSPP printed line composed of H-shaped periodical grooved strips to operate as a low pass filter and a SIW to operate as a high pass filter. The operating frequency bands of the proposed diplexer are from 11.7 to 12.75 GHz for the downlink (DL) band, and from 17.3 to 18.35 GHz for the uplink (UL) band. These frequency bands correspond to the operating frequencies in Nile Sat 201 system. The frequencies of the DL and UL bands are adjusted independently by tuning the structure parameters of SSPP and SIW sections, respectively. The proposed hybrid SSPP-SIW diplexer is fabricated and measured. Simulated and measured results show good channel isolation, low return loss and low insertion loss in the required frequency bands. Index Terms ─ High-pass filter, Low-pass filter, Spoof Surface Plasmon Polaritons (SSPPs), Substrate Integrated Waveguide (SIW).
COMPARISON OF SERUM FERRITIN LEVELS IN NAFLD PATIENTS AND HEALTHY CONTROLS

Objective: To determine and compare serum ferritin levels in non-alcoholic fatty liver disease (NAFLD) patients of our ethnicity. Study Design: Cross sectional comparative study. Place and Duration of Study: The study was conducted at Radiology department of Shalamar Hospital, Medical OPD of Combined Military Hospital, Lahore and Medical OPD of Omer Hospital, Lahore, from Jul 2015 to Sep 2015. Methodology: A total number of 43 non-alcoholic fatty liver disease patients diagnosed after ultrasonography were included in the study. An equal number of age, gender and body mass index (BMI) matched healthy controls were selected by non-probability purposive sampling. Fasting serum ferritin levels, body mass index and waist circumference were measured in both the cases and controls. Data were entered and analyzed on SPSS 21.For quantitative data median IQR was calculated. Mann Whitney U-test was used for group comparison. To find an association, Spearman‟s Ranked correlation was applied. A p-value of ≤0.05 was taken as significant. Results: The non-alcoholic fatty liver disease cases had significantly higher serum ferritin (p<0.001) compared to the controls and a significant correlation between ferritin with body mass index and waist circumference in the non-alcoholic fatty liver disease subjects was recorded (p=0.04 and p=0.03 respectively). Conclusion: The non-alcoholic fatty liver disease patients have higher levels of serum ferritin as compared to the healthy controls in our ethnicity but within normal range.
QoS Priority-Based Mobile Personal Cell Deployment with Load Balancing for Interference Reduction between Users on Coexisting Public Safety and Railway LTE Networks

The Republic of Korea has played a leading role in the development of next-generation long-term evolution (LTE) public safety networks. The LTE-based public safety (PS-LTE) network, the LTE-based high-speed railway (LTE-R) network, and the LTE-based maritime (LTE-M) network use the same 700 MHz frequency band. That results in severe co-channel interference (CCI), so there is a dire need for practical research into resolving the CCI issue. Moreover, unplanned deployment of the mobile personal cell (mPC) generates serious user-association issues owing to its movement, which leads to severe co-channel interference in coexisting PS-LTE and LTE-R networks. Indeed, it is important to satisfy users’ quality of service (QoS) requirements during resource allocation in specific public safety situations. Therefore, we address the CCI issues through wise deployment of the mPC for user association and load balancing in overlapping PS-LTE and LTE-R networks. In this paper, we propose a QoS mPC deployment (QoS_mPCD) scheme for priority-based load balancing and interference reduction in coexisting PS-LTE and LTE-R networks. The proposed scheme efficiently manages the user-association and load-balancing problems, and allocates the best resources to high-priority users based on defined service priority levels. Moreover, we employ an enhanced inter-cell interference coordination (eICIC) scheme that further reduces the interference with the users offloaded onto an mPC. System-level simulations are performed to evaluate the proposed QoS_mPCD scheme by considering important performance matrices such as user equipment (UE) throughput, UE received interference, and UE outage probabilities.
Corrosion of steel in carbonated concrete: mechanisms, practical experience, and research priorities – a critical review by RILEM TC 281-CCC

Carbonation of concrete is generally assumed to lead to reinforcing steel corrosion. This mindset has long dictated the research priorities surrounding the developments towards new, low-emission binders. Here, by reviewing documented practical experience and scientific literature, we show that this widely held view is too simplistic. In fact, there are many cases from engineering practice where carbonation of the cementitious matrix surrounding the steel did not lead to noticeable corrosion or to corrosion-related damage at the level of a structure. The influencing factors that can, however, lead to considerable corrosion damage are identified as the moisture state, the microstructure of the carbonated concrete, various species that may be present – even in minor amounts – in the concrete pore solution, and the cover depth. The circumstance that a reduced pH alone is not sufficient to lead to significant steel corrosion in concrete seriously challenges the established approach of assessing the durability performance based on carbonation testing and modeling. At the same time, this circumstance offers great opportunities for reducing the environmental impact of concrete structures with low-emission binders. To realize these opportunities, the focus in research and engineering should shift from studying carbonation to studying corrosion of steel in carbonated concrete.
Rhizosphere chemistry in an ammonium sulfate and water manipulated Norway spruce [Picea abies (L.) Karst.] forest

The purpose of this study was to examine how the treatments ammonium sulfate, drought and irrigation changed chemical characteristics of three soil fractions (bulk soil, rhizosphere and soil root interface (SRI)) from E, Bh and Bs horizons of Podzol in a Norway spruce stand in southwestern Sweden. Regardless of the treatment, the properties of the rhizosphere and SRI nearly always differed from the bulk soil due to the high quantity of organic and root material. Irrigation and ammonium sulfate raised water soluble cations and base saturation in the bulk soil. This was possibly due to leaching from the humus and exchange reactions. In the rhizosphere and SRI, irrigation and ammonium sulfate lowered soluble base cations (BC) and base saturation when compared with control; this is attributed to a combination of leaching and high nutrient demand by trees creating a zone of relative depletion. Drought accumulated more organic matter (OM), acidity and cations in the soil fractions suggesting that the lack of wa.
Data‐driven power system linear model identification for selective modal analysis by frequency interpolations

This paper proposes a new approach to identify a data-based power system linear model by means of frequency interpolations, aiming to obtain a suitable system representation for selective-modal analysis purposes. The key idea behind the identiﬁcation process is the Loewner-based frequency interpolation carried out by the Loewner matrices. The proposed approach demonstrates that the Loewner-based frequency interpolation is able to ﬁt a linear model that can be used for small-signal analysis studies, since it provides the state-space representation, the frequency response, and modal information (frequency, damping, and mode-shape). Then, a selective modal analysis is accomplished over two test cases (Kundur and New England–New York power grids) by employing the identiﬁed linear model provided by the Loewner-based frequency interpolation method. The attained results conﬁrm the outstanding performance of the proposal which is validated against the small-signal analysis and compared with the eigensystem realisation algorithm, overcom-ing the absolute error of the model identiﬁed with the traditional eigensystem realisation algorithm approach by at least 37 times, and properly capturing the modal information in a frequency band of concern.
Isolation of mutagenic aromatic amines from a coal conversion oil by cation exchange chromatography

A procedure has been devised whereby one- to five-ring primary aromatic amines and azaarenes, as well as their alkylated derivatives, may be separated according to their relative basicities. The cation exchange high-performance liquid chromatographic procedure separates analogous members of these two classes of bases, as well as closely related bases within each class. The two classes are readily resolved except for unusual cases in which structural properties are responsible for similar basicities. The procedure was effective in isolation of mutagenic components from a complex mixture of bases derived from a process stream of a coal gasification pilot plant. Fractions containing much of the mutagenic activity contained fewer than 20 two- and three-ring primary aromatic amines but no azaarenes.