Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining patterns in the generation of magnetic fields when using different arc welding techniques

This paper reports a study into the levels of magnetic fields induced by arc welding equipment in various ways in order to assess their impact on the body of welders. It is known that welders are exposed to a magnetic field of high intensity. Depending on the welding technique and the type of welding equipment, it may exceed the maximum permissible levels (MPL). Note that new Ukrainian sanitary standards for magnetic fields have been introduced, which regulate their levels depending on the frequency range. Therefore, it became necessary to carry out their hygienic assessment according to the new standards in order to devise appropriate methods for protecting welders. To this end, it was required to choose a new generation of devices to determine the intensity of magnetic fields induced by welding equipment. Based on the analysis of the constructed oscillograms and spectrograms of magnetic fields, it was found that semi-automatic welding with a metal electrode in carbon dioxide is characterized by an increased level of magnetic field in the frequency range of 50‒1000 Hz. With automatic arc welding under the flux, there are no excess of the maximum permissible levels of individual harmonics of the magnetic field but there is an excess of the total value of all harmonic components of the magnetic field. Manual arc welding with direct current involving a non-melting electrode in argon is characterized by a moderate level of magnetic field in workplace. During manual arc welding with coated electrodes, the exceeded level of the magnetic field is observed only on the electrode cable itself. It is shown that the spectral composition of the magnetic field signal is determined mainly by the welding technique itself, the peculiarities of arc combustion, and the nature of the transfer of electrode metal in the arc gap, as well as the initial parameters of the power supplies of the welding arc
A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG

Objective. Electrocardiogram (ECG) is an important diagnostic tool that has been the subject of much research in recent years. Owing to a lack of well-labeled ECG record databases, most of this work has focused on heartbeat arrhythmia detection based on ECG signal quality. Approach. A record quality filter was designed to judge ECG signal quality, and a random forest method, a multilayer perceptron, and a residual neural network (RESNET)-based convolutional neural network were implemented to provide baselines for ECG record classification according to three different principles. A new multimodel method was constructed by fusing the random forest and RESNET approaches. Main Results. Owing to its ability to combine discriminative human-crafted features with RESNET deep features, the proposed new method showed over 88% classification accuracy and yielded the best results in comparison with alternative methods. Significance. A new multimodel fusion method was presented for abnormal cardiovascular detection based on ECG data. The experimental results show that separable convolution and multiscale convolution are vital for ECG record classification and are effective for use with one-dimensional ECG sequences.
Functional Analysis of Two Terpene Synthase Genes Isolated from the Flowers of Hosta ‘So Sweet’

The Hosta hybrid cultivar ‘So Sweet’, an important ornamental and widely used horticultural plant, is noted for its rich, fragrant white flowers. The main aroma components of Hosta flowers are terpenoids, mainly monoterpenes. Until now, the terpene synthases responsible for terpene production in Hosta were not described. In this study, two terpene synthase (TPS) genes (HsTPS1 and HsTPS2) were cloned and characterized to further study their function. Furthermore, the volatile terpenes of Hosta ’So Sweet’ in two flower development stages from two in vitro enzyme tests were analyzed by gas chromatography–mass spectrometry (GC–MS). We analyzed the expression levels of two genes at four different developmental stages using quantitative real-time PCR, while localization was analyzed using Nicotina benthamiana leaves. In vitro, the two proteins were identified to mainly produce linalool and nerol. In addition, the active products of the two recombinant proteins were (E,E)-farnesol and (E,E)-farnesal, respectively, using farnesyl pyrophosphate as a substrate. The high expression of HsTPS1 and HsTPS2 was correlated with the release of components of Hosta flowers. To our knowledge, this is the first time that the terpene synthase genes of Hosta species have been isolated and identified, providing an opportunity to study the terpene metabolic pathways in Hosta species.
Overview: Polycarbonates via Ring-Opening Polymerization, Differences between Six- and Five-Membered Cyclic Carbonates: Inspiration for Green Alternatives

This review aims to cover the topic of polycarbonate synthesis via ring-opening polymerization (ROP) of cyclic carbonates. We report a wide variety of ROP-initiating systems along with their detailed mechanisms. We focus on the challenges of preparing the polymers; the precise control of the properties of the materials, including molecular weight; the compositions of the copolymers and their structural characteristics. There is no one approach that works for all scales in cyclic carbonates ROP. A green process to produce polycarbonates is a luring challenge in terms of CO2 utilization and the targeted domains for application. The main resolution seems to be the use of controlled incorporation of functional/reactive groups into polymer chains that can tailor the physicochemical and biological properties of the polymer matrices, producing what appears to be an unlimited field of applications. Glycerol carbonate (GC) is prepared from renewable glycerol and considered as a CO2 fixation agent resulting in GC compound. This family of five-membered cyclic carbonates has attracted the attention of researchers as potential monomers for the synthesis of polycarbonates (PCs). This cyclic carbonate group presents a strong alternative to Bisphenol A (BPA), which is used mainly as a monomer for the production of polycarbonate and a precursor of epoxy resins. As of December 2016, BPA is listed as a substance of very high concern (SVHC) under the REACH regulation. In 2006, Mouloungui et al. reported the synthesis and oligomerization of GCs. The importance of GCs goes beyond their carbonate ring and their physical properties (high boiling point, high flash point, low volatility, high electrical conductivity) because they also contain a hydroxyl group. The latter offers the possibility of producing oligo and/or polycarbonate compounds that have hydroxyl groups that can potentially lead to different reaction mechanisms and the production of new classes of polycarbonates with a wide range of applications.
Surface drainage features identification using LiDAR DEM smoothing in agriculture area: a study case of Kebumen Regency, Indonesia

ABSTRACT Digital Elevation Model (DEM) is the most vital data to generate drainage networks and to provide critical terrain factors and hydrologic derivatives, such as slope, aspect, and streamflow. The accuracy of generated drainage features is extensively dependent on the quality and resolution of DEM, such as LiDAR-derived DEM. Contrary, it has a high level of roughness and complexity. Thus, smoothing methods are sometimes employed to conquer the roughness. This paper presents feature-preserving DEM smoothing (FPDEM-S) and edge-preserving DEM smoothing (EPDEM-S) approaches to smooth surface complexity in kind of preserving small drainage features using the 0.5 m – resolution LiDAR DEM of the Kedungbener River area in Kebumen Regency, Indonesia. Entangling linear morphometric factors, those smoothing approaches delivered a slight difference of stream number, with the FPDEM-S stream length ratio performing 7% better tendencies. The FPDEM-S method perormed better than EPDEM-S in this study area to provide an optimal smoothed LiDAR DEM at certain parameter values. Summarising that two smoothing methods approaches performed similar characteristics of watershed as an oval structure close to the circular shape. Also, it can be revealed that the watershed did not reach maturity phase.
A Big Data Integration Platform for Ideological and Political Education for Smart Campuses

The advent of large data and the era of large data has brought significant impact and changes to human production and life. Through the acquisition, analysis, processing, prediction, and dissemination of big data in scientific research, large data has emerged as the source of advanced technological to generate global quantitative data. It not only reveals the gaps and deficiencies of traditional approaches to ideological and mechanical studies methods in obtaining ideological behavior but also information about academic subjects providing support for optimizing and innovative technology and ideological transformation and then conducting intellectual and practical research in colleges and universities. In the age of large digital data, the ideology and politics of education are facing modern domestic and foreign situations, as well as new characteristics and new needs for ideology and politics study. This makes ideology and politics research methods even more important, which is seen as an opportunity for continuous creation and innovation and also adapts to the requirements of the times and reality. Smart campus refers to an intelligent integrated environment for campus work, study, and life based on the Internet of Things. This integrated environment takes various application service systems as the carrier and fully integrates teaching, scientific research, management, and campus life. From the large-scale data era, the educational theory of whether colleges and universities’ ideological and political research is rich or not supports more scientific theories to carry out psychological and mechanical research. It is evident that in the age of large data, the ideological and political research in colleges and institutes is not only a theoretical issue but also an important practical issue. Therefore, conducting ideological and political research in colleges and institutes in the age of large data has profound theoretical significance and great practical significance.
Factors Associated with Screening Mammogram Uptake among Women Attending an Urban University Primary Care Clinic in Malaysia

Screening mammograms have resulted in a reduction in breast cancer mortality, yet the uptake in Malaysia was low. This study aimed to determine the prevalence and factors associated with screening mammogram uptake among women attending a Malaysian primary care clinic. A cross-sectional study was conducted among 200 women aged 40 to 74 attending the clinic. The data was collected using questionnaires assessing sociodemographic, clinical characteristics, knowledge and health beliefs. Multiple logistic regression was used to identify factors associated with mammogram uptake. The prevalence of screening mammograms was 46.0%. About 45.5% of women with high breast cancer risk had never undergone a mammogram. Older participants, aged 50 to 74 (OR = 2.57, 95% CI: 1.05, 6.29, p-value = 0.039) and those who received a physician’s recommendation (OR = 7.61, 95% CI: 3.81, 15.20, p-value < 0.001) were more likely to undergo screening mammography. Significant health beliefs associated with mammogram uptake were perceived barriers (OR = 0.81, 95% CI: 0.67, 0.97, p-value = 0.019) and cues to action (OR = 1.30, 95% CI: 1.06, 1.59, p-value = 0.012). Approximately half of the participants and those in the high-risk group had never undergone a mammogram. Older age, physician recommendation, perceived barriers and cues to action were significantly associated with mammogram uptake. Physicians need to play an active role in promoting breast cancer screening and addressing the barriers.
Bibliometric Analysis of the Green Deal Policies in the Food Chain

2022. Bibliometric Analysis of Policies 2022 Abstract Nutrition concerns and food waste are a priority for the European Union, and the implementation of Green Pact policies is of major interest to all those involved in the food chain sector. The main purpose of this paper is to conduct an in-depth analysis of scientific production using bibliometrics, to understand the current structure of studies and future research directions on Green Deal policies in the food chain. 672 documents published between 2000 and 2021 were identified in the Web of Science database. Their scientific content was analysed using VOSviewer software on several levels: descriptive analysis, performance analysis, and scientific mapping from a conceptual, intellectual, and social perspective. In addition, to determine research gaps, the 10 most relevant and influential papers are analysed and synthesized. The most productive countries in terms of scientific output are Italy, India, and the USA, the peak being reached in 2021, and the main field approached is environmental sciences. Most of the articles analysed are reviews, highlighting gaps in primary research on Green Deal policies in the food industry. In this regard, several future research directions in the field are
Radio Machine Learning Dataset Generation with GNU Radio

This paper surveys emerging applications of Machine Learning (ML) to the Radio Signal Processing domain. Provides some brief background on enabling methods and discusses some of the potential advancements for the field. It discusses the critical importance of good datasets for model learning, testing, and evaluation and introduces several public open source synthetic datasets for various radio machine learning tasks. These are intended to provide a robust common baselines for those working in the field and to provide a benchmark measure against which many techniques can be rapidly evaluated and compared.
Sargassum detection and path estimation using neural networks

Sargassum has affected the Mexican Caribbean coasts since 2015 in atypical amounts, causing economic and ecological problems. Removal once it reaches the coast is complex since it is not easily separated from the sand, damaging dune vegetation, heavy transport compacts the sand and further deteriorates the coastline. Therefore, it is important to detect and estimate the sargassum mats path to optimize the collection efforts in the water. There have been some improvements in systems that rely on satellite images to determine areas and possible paths of sargassum, but these methods do not solve the problems near the coastline where the big mats observed in deep sea end up segregating in little mats which often do not show up in the satellite images. Besides, the temporal scales of nearshore sargassum dynamics are characterized by finer temporal resolution. This paper focuses on cameras located near the coast of Puerto Morelos reef lagoon where images are recorded of both beach and near-coastal sea. First, we apply preprocessing techniques based on time that allows us to discriminate the moving sargassum mats from the static sea bottom, then, using classic image processing techniques and neural networks we detect, trace, and estimate the path of the mat towards the place of arrival on the beach. We compared classic algorithms with neural networks. Some of the algorithms we tested are k-means and random forest for segmentation and dense optical flow to follow and estimate the path. This new methodology allows to supervise in real time the demeanor of sargassum close to shore without complex technical support.
Spectrophotometric methods for quantitative determination of sotalol in tablets

The aim of the work. To develop a method for spectrophotometric determination of sotalol with diazonium salts. Establish optimal conditions for the quantitative determination of sotalol in drugs. Validate the developed methodology. Materials and methods. Reagents and solvents used in the study were: diazole red 2J (obtained from NVF “Sinbias”), tablets “Sotalol Sandoz” 40 mg (Salyutas Pharma GmbH, series JZ1188), “Sotalol Sandoz” 80 mg (Salyutas Pharma GmbH, series KA0464) and “Sotalol Sandoz” 160 mg (Salyutas Pharma GmbH, series JY3504), methanol (LAB-SCAN, Ireland, batch № 5120/13), sodium carbonate (Sinbias) and purified water were also used. Analytical equipment: spectrophotometer “SPECORD-200” (Analytic Jena AG, Germany), scales laboratory electronic RADWAG XA 210.4Y, bath ultrasonic Sonorex Digitec DT100H, laboratory glassware of class A. All studies were conducted in the experimental pharmaceutical research department of the scientific medical laboratory center (SMLC) of the Zaporizhzhia State Medical University. Results and discussion. The technique of spectrophotometric determination of the quantitative content of sotalol based on its reaction with red diazole in water-methanol medium has been developed. The stoichiometric ratios of the reactive components as 1:1 were obtained by the methods of continuous changes and the saturation method. Validation of the developed on such indicators as linearity, precision, correctness and robustness is carried out. Based on these data, the developed method is correct and could be used in the quality control departments of chemical and pharmaceutical companies. Conclusions. A method of quantitative spectrophotometric determination of sotalol in the tablet dosage form “Sotalol Sandoz” 40 mg, “Sotalol Sandoz” 80 mg and “Sotalol Sandoz” 160 mg of industrial production was developed, validation characteristics were investigated: linearity, precision, correctness, range of application and robustness
Structure-Based Development of SARS-CoV-2 Spike Interactors

Coronaviruses, including SARS-CoV-2 (the etiological agent of the current COVID-19 pandemic), rely on the surface spike glycoprotein to access the host cells, mainly through the interaction of their receptor-binding domain (RBD) with the human angiotensin-converting enzyme 2 (ACE2). Therefore, molecular entities able to interfere with the binding of the SARS-CoV-2 spike protein to ACE2 have great potential to inhibit viral entry. Starting from the available structural data on the interaction between SARS-CoV-2 spike protein and the host ACE2 receptor, we engineered a set of soluble and stable spike interactors, here denoted as S-plugs. Starting from the prototype S-plug, we adopted a computational approach by combining stability prediction, associated to single-point mutations, with molecular dynamics to enhance both S-plug thermostability and binding affinity to the spike protein. The best developed molecule, S-plug3, possesses a highly stable α-helical con-formation (with melting temperature Tm of 54 °C) and can interact with the spike RBD and S1 domains with similar low nanomolar affinities. Importantly, S-plug3 exposes the spike RBD to almost the same interface as the human ACE2 receptor, aimed at the recognition of all ACE2-accessing coronaviruses. Consistently, S-plug3 preserves a low nanomolar dissociation constant with the delta B.1. 617.2 variant of SARS-CoV-2 spike protein (KD = 29.2 ± 0.6 nM). Taken together, we provide valid starting data for the development of therapeutical and diagnostic tools against coronaviruses accessing through ACE2.
Cardiac Autonomic Function Following Bilateral and Unilateral Upper Body Acute Resistance Exercise

The purpose of this study was to compare cardiac autonomic responses following bilateral and unilateral upper-body (UB) acute resistance exercise (ARE). In total, 14 individuals were assessed for markers of cardiac autonomic responses via heart rate variability (HRV) and baroreflex sensitivity (BRS) at rest and at 10- and 30-min following ARE. Logarithmically transformed (ln) HRV measures included: total power (ln TP), high-frequency power (ln HF power), low-frequency power (ln LF power), sympathovagal balance (ln LF: HF), and the square root of the mean squared differences of successive R-R intervals (ln RMSSD). BRS was assessed using the sequence method. Two-way repeated measures ANOVAs were used to analyze effects of UB ARE (bilateral, unilateral) across time (Rest, 10, and 30 min). There were no significant (p > 0.05) interactions. However, there were significant (p ≤ 0.05) main effects of time such that ln TP, ln HF power, ln RMSSD, and BRS decreased and did not recover within 30 min compared to Rest for both conditions. Collectively, this study suggests that bilateral and unilateral UB ARE yielded similar reductions, for at least 30 min, in respect to vagal measures of HRV and BRS.
THE EFFECT OF OCB MEDIATION ON THE RELATIONSHIP BETWEEN WORK ATTITUDE AND KNOWLEDGE SHARING ON THE PERFORMANCE OF SATPOL PP AND WH ACEH

This study examines the effect of OCB mediation on the work attitudes and knowledge sharing influences on the performance of Satpol PP and WH Aceh. The population was all employees/members of the Satpol PP and WH Aceh, totaling 907 people. Sample was determined using the probability sampling technique with the help of the Slovin formula so that the sample obtained is 278 people. The analytical equipment used was SEM-AMOS. The results explain several conclusions, namely work attitude, knowledge sharing, OCB and member performance are good, work attitude does not affect OCB, knowledge sharing affects OCB, work attitude does not affect member performance, knowledge sharing does not affect member performance, OCB affects member performance, work attitude does not affect member performance through OCB, and Knowledge sharing affects member performance through OCB. These results show that OCB only mediates the effect of knowledge sharing on member performance, and as a full mediator in this model. So overall, it is answered that the model for improving the performance of Satpol PP and WH Aceh members is a function of increasing Knowledge sharing and OCB.
THE EFFECT OF CAREER DEVELOPMENT ON EMPLOYEE ENGAGEMENT WITH ORGANIZATIONAL COMMITMENT AS AN INTERVENING VARIABLE AT PT. BANK ACEH SYARIAH HEAD OFFICE

This study aims to examine how career development can affect employee engagement mediated by organizational commitment to employees of PT. Bank Aceh Syariah Head Office (Bank Aceh KPO). The survey was conducted to collect data by distributing questionnaires to a sample of 195 respondents who are employees of Bank Aceh KPO. The analysis method used Structural Equation Modeling (SEM). The result proves that career development affects organizational commitment, organizational commitment affects employee engagement, career development affects employee engagement, and career development affects employee engagement through organizational commitment. The model test also proves that organizational commitment is a variable that functions as a partial mediator. It becomes clear that the model of increasing employee engagement at Bank Aceh KPO is a function of better career development, and stronger organizational commitment.
A methodology for modeling the effects of icing on rotary wing aerodynamics

A computational methodology has been developed for modeling the effects of ice accretion on a helicopter rotor in forward flight. The mythology is modular to allow for independent update of the individual modules as improvements to the underlying methodologies are made. This process requires software specialized for ice accretion, computational aerodynamics, grid generation, and rotor aeroelasticity. This methodology is exercised on three flights of the UH60A BLACK HAWK in icing conditions. The computed torque rise compares favorably to the measured torque rise. Additional experimental data on blade ice shapes and sectional loads is needed to fully evaluate the methodology.