bluuebunny/crossref_metadata_2025 huggingface dataset:
CD36 and Its Role in Regulating the Tumor Microenvironment
Authors: Liao Xinzhi , Yan Sheng , Li Jialin , Jiang Chengming , Huang Sigen , Liu Shengyin , Zou Xiaofeng , Zhang Guoxi , Zou Junrong , Liu Quanliang
Published: October 2022

CD36 is a transmembrane glycoprotein that binds to a wide range of ligands, including fatty acids (FAs), cholesterol, thrombospondin-1 (TSP-1) and thrombospondin-2 (TSP-2), and plays an important role in lipid metabolism, immune response, and angiogenesis. Recent studies have highlighted the role of CD36 in mediating lipid uptake by tumor-associated immune cells and in promoting tumor cell progression. In cancer-associated fibroblasts (CAFs), CD36 regulates lipid uptake and matrix protein production to promote tumor proliferation. In addition, CD36 can promote tumor cell adhesion to the extracellular matrix (ECM) and induce epithelial mesenchymal transition (EMT). In terms of tumor angiogenesis, CD36 binding to TSP-1 and TSP-2 can both inhibit tumor angiogenesis and promote tumor migration and invasion. CD36 can promote tumor angiogenesis through vascular mimicry (VM). Overall, we found that CD36 exhibits diverse functions in tumors. Here, we summarize the recent research findings highlighting the novel roles of CD36 in the context of tumors.
Phenotypic Diversity Analysis of the Progeny Variation of a ‘Mosaic Leaf’ Loropetalum chinense var. rubrum Based on Flower Organ Characteristics
Authors: Zhang Li , Yu Xiaoying , Zhang Xia , Zhang Damao , Li Weidong , Xiang Lili , Yang Yujie , Li Yanlin , Xu Lu
Published: October 2022

Loropetalum chinense var. rubrum is a common landscape plant. Because of the preference for the ‘red leaf’ trait, the ‘flower color’ trait was ignored in breeding, and the genetic diversity of L. chinense var. rubrum was replaced by a few genotypes. Therefore, the potential value of flower color traits was affected, and the genetic diversity was not fully exploited. In this study, we utilized a cultivar with mosaic-colored flowers and leaves and observed 15 phenotypic traits in its flower organs and its progeny, as well as a total of 60 different flower color materials. We analyzed the variation characteristics and diversity of flower colors, and qualitatively described and preliminarily classified flower colors using the ISCC-NBS and CIELab systems to explore the correlation with the flower color phenotype from the distribution and content of anthocyanins. The phenotypic diversity of the flower organs was enriched, and genetic differences in flower color were significant for the L.chinense var. rubrum, with most of the 15 phenotypic traits showing significant positive correlations, and the most critical phenotypes are sepal, petal and nectary color, as well as petal length. According to the CIELab color system and anthocyanin content and distribution characteristics, it is considered more accurate and convenient to classify the color phenotypes of L. chinense var. rubrum flowers into five categories. In this study, for the first time, the flower organ phenotype of L. chinense var. rubrum has been systematically analyzed, and it is explored as a reference method for breeding new cultivars of a diverse range of colors in L. chinense var. rubrum.
Introduced, Mixed, and Peripheral: Conservation of Mitochondrial-DNA Lineages in the Wild Boar (Sus scrofa L.) Population in the Urals
Authors: Markov Nikolay I. , Ranyuk Maryana N. , Babaev Elmar A. , Seryodkin Ivan V. , Senchik Alexander V. , Bykova Elena A. , Esipov Alexander V. , Nurtazin Sabir T. , Pavlova Olga S. , Matrosova Vera A.
Published: October 2022

Translocations and introductions are important events that allow organisms to overcome natural barriers. The genetic background of colonization success and genetic consequences of the establishment of populations in new environments are of great interest for predicting species’ colonization success. The wild boar has been introduced into many parts of the world. We analyzed sequences of the mitochondrial-DNA control region in the wild boars introduced into the Ural region and compared them with sequences from founder populations (from Europe, the Caucasus, Central Asia, and the Far East). We found that the introduced population has high genetic diversity. Haplotypes from all the major phylogenetic clades were detected in the analyzed group of the animals from the Urals. In this group, no haplotypes identical to Far Eastern sequences were detectable despite a large number of founders from that region. The contribution of lineages originating from Eastern Europe was greater than expected from the proportions (%) of European and Asian animals in the founder populations. This is the first study on the genetic diversity and structure of a wild boar population of mixed origin at the northern periphery of this species’ geographical range.
The Impact of the Honeybee Apis mellifera on the Organization of Pollination Networks Is Positively Related with Its Interactive Role throughout Its Geographic Range
Authors: Dáttilo Wesley , Cruz Carlos Pinilla , Luna Pedro , Ratoni Brenda , Hinojosa-Díaz Ismael A. , Neves Frederico S. , Leponce Maurice , Villalobos Fabricio , Guevara Roger
Published: October 2022

Studies at local spatial scales have shown that the generalist honeybee Apis mellifera L. can strongly affect the structural organization and properties of pollination networks. However, there is still little knowledge on how the connectivity of the honeybee within networks (i.e., interactive role) could affect pollination networks at a global scale. To fill this gap, we evaluated how the interactive role of A. mellifera could affect niche overlap, specialization, and robustness of pollination networks. We used 109 weighted pollination networks spread across about 94 degrees of latitude and 227 degrees of longitude. We developed a new standardized framework based on species removal to assess the impact of the honeybee on plant-pollinator networks. We found that when the honeybee was removed from the networks, plant species had less niche overlap (i.e., shared fewer interactions via their pollinators) and the networks became more specialized and more robust to species extinctions. Our findings indicate that A. mellifera’s effects on pollination networks vary geographically and could influence several ecological and evolutionary factors acting at local scales, including pollination services. We hope this contribution will stimulate new macroecological studies involving abundant and generalist species and their functional roles within ecological communities.
Technical Data of In Silico Analysis of the Interaction of Dietary Flavonoid Compounds against Spike-Glycoprotein and Proteases of SARS-CoV-2
Authors: Altu Nurbella Sofiana , Budiman Cahyo , Razali Rafida , Mokhtar Ruzaidi Azli Mohd , Kamaruzaman Khairul Azfar
Published: October 2022

The spike glycoprotein (S protein), 3-chymotrypsin-like protease (3CL-Pro), and papain-like protease (PL-Pro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus are widely targeted for the discovery of therapeutic compounds against this virus. Dietary flavonoid compounds were proposed as a candidate for safe therapy for COVID-19 patients. Nevertheless, wet lab experiments for high-throughput screening of the compounds are undoubtedly time and cost consuming. This study aims to screen dietary flavonoid compounds that bind to S protein, 3CL-Pro, and PL-Pro of SARS-CoV-2. For this purpose, protein structures of the receptor-binding domain (RBD) of S protein (6M0J), 3CL-Pro (6LU7), and PL-Pro (6W9C) were retrieved from the RCSB Protein Data Bank (PDB). Twelve dietary flavonoid compounds were selected for the studies on their binding affinity to the targeted proteins by global and local docking. The docking and molecular dynamic (MD) simulations were performed using YASARA software. Out of 12 compounds, the highest binding score was observed between hesperidin against RBD S protein (−9.98 kcal/mol), 3CL-Pro (−9.43 kcal/mol), and PL-Pro (−8.89 kcal/mol) in global docking. Interestingly, MD simulation revealed that the complex between 3CL-Pro and RBD S protein has better stability than PL-Pro. This study suggests that hesperidin might have versatile inhibitory properties against several essential proteins of SARS-CoV-2. This study, nevertheless, remains to be confirmed through in vitro and in vivo assays.
Influence of Color on Loudness Perception of Household Appliances: Case of a Coffee Maker
Authors: Papadakis Nikolaos M. , Zantzas Andreas , Lafazanis Konstantinos , Stavroulakis Georgios E.
Published: October 2022

Previous studies have investigated the effect of color on the assessment of loudness in various cases, such as cars, trains, and concert halls. This study sets out to explore the influence of color on the loudness perception of household appliances, in particular in the case of coffee makers. To this end, images of a coffee maker colored in black, red, dark green, light blue, light green, and white were displayed to participants during a magnitude estimation task. In a repeated measures design, the sound of a coffee maker was used synchronously as a stimulus presented in different sound levels (74, 78, 82, and 86 dB LAeq). The sample of participants was selected to be gender balanced and unfamiliar with similar experiments. Statistical analysis suggested that the color of the visual stimulus had no influence on loudness judgments. However, a gender-based statistically significant influence regarding the color of the coffee maker on loudness evaluation was found for females. An interpretation of the results is attempted in the discussion. The results of this study suggest that since there is the possibility of gender differences in the assessment of loudness for household appliances, special care should be taken in similar studies to account for these effects. Finally, these gender differences could possibly be utilized for product sound design and product marketing where the appropriate use of color has been found to be effective.
When a Rapid Accurate Diagnosis Changes Therapeutic Approach: Recognizing Acute Abdominal Pain with Ascites as a Possible Presentation of Systemic Lupus Erythematosus
Authors: Huang Szu-Cheng , Chan Yi-Ling , Cheng Hao-Tsai , Goh Zhong Ning Leonard , Wong Yon-Cheong , Seak Chen-Ken , Seak Joanna Chen-Yeen , Li Chih-Huang , Chen Hsien-Yi , Seak Chen-June
Published: October 2022

Systemic lupus erythematosus (SLE) is a chronic, multi-organ autoimmune disease which rarely presents with peritoneal involvement. As such, its diagnosis in the emergency department (ED) based on a clinical presentation of gastrointestinal symptoms is extremely challenging. Yet, reaching such a diagnosis in the ED is crucial for avoiding unnecessary surgical intervention and initiating early glucocorticoid therapy to maximise patient outcomes. Here, we report a case of newly diagnosed SLE in a 28-year-old lady who presented atypically and unusually with abdominal pain and ascites. She required extensive but methodical investigations, and was eventually diagnosed with lupus mesenteric vasculitis with underlying newly diagnosed SLE in the ED. The patient was promptly treated with methylprednisolone resulting in marked clinical improvement. Emergency physicians should be mindful of abdominal pain with ascites as an extremely rare but important clinical presentation of SLE. Early diagnosis and commencement of glucocorticoid therapy in these patients are crucial in halting disease progression and averting the need for surgical intervention.
Commercially Available Molecular Approaches to Evaluate Endometrial Receptivity: A Systematic Review and Critical Analysis of the Literature
Authors: Maziotis Evangelos , Kalampokas Theodoros , Giannelou Polina , Grigoriadis Sokratis , Rapani Anna , Anifantakis Marios , Kotsifaki Amalia , Pantou Agni , Triantafyllidou Olga , Tzanakaki Despoina , Neofytou Spyridoula , Vogiatzi Paraskevi , Bakas Panagiotis , Simopoulou Mara , Vlahos Nikolaos
Published: October 2022

Despite the advances in the field of reproductive medicine, implantation failure represents a challenging condition affecting 10–30% of patients subjected to in vitro fertilization (IVF). Research has focused on the identification of molecules playing crucial roles in endometrial receptivity, with the aim of designing predictive tools for efficient detection of the implantation window. To that end, novel molecular genomic and transcriptomic approaches have been introduced as promising tools to enable personalized approaches with the aim of optimizing embryo transfer dating. However, the clinical value of these approaches remains unclear. The aim of this study is to provide a systematic review and critical analysis of the existing evidence regarding the employment of commercially available novel approaches to evaluate endometrial receptivity. An Embase and PubMed/Medline search was performed on 1 February 2022. From the 475 articles yielded, only 27 were included and analyzed. The considerable heterogeneity of the included articles indicates the uniqueness of the implantation window, showcasing that the optimal time for embryo transfer varies significantly between women. Moreover, this study provides information regarding the technical aspects of these advanced molecular tools, as well as an analysis of novel possible biomarkers for endometrial receptivity, providing a basis for future research in the field.
Radiomics-Based Detection of COVID-19 from Chest X-ray Using Interpretable Soft Label-Driven TSK Fuzzy Classifier
Authors: Zhang Yuanpeng , Yang Dongrong , Lam Saikit , Li Bing , Teng Xinzhi , Zhang Jiang , Zhou Ta , Ma Zongrui , Ying Tin-Cheung (Michael) , Cai Jing
Published: October 2022

The COVID-19 pandemic has posed a significant global public health threat with an escalating number of new cases and death toll daily. The early detection of COVID-related CXR abnormality potentially allows the early isolation of suspected cases. Chest X-Ray (CXR) is a fast and highly accessible imaging modality. Recently, a number of CXR-based AI models have been developed for the automated detection of COVID-19. However, most existing models are difficult to interpret due to the use of incomprehensible deep features in their models. Confronted with this, we developed an interpretable TSK fuzzy system in this study for COVID-19 detection using radiomics features extracted from CXR images. There are two main contributions. (1) When TSK fuzzy systems are applied to classification tasks, the commonly used binary label matrix of training samples is transformed into a soft one in order to learn a more discriminant transformation matrix and hence improve classification accuracy. (2) Based on the assumption that the samples in the same class should be kept as close as possible when they are transformed into the label space, the compactness class graph is introduced to avoid overfitting caused by label matrix relaxation. Our proposed model for a multi-categorical classification task (COVID-19 vs. No-Findings vs. Pneumonia) was evaluated using 600 CXR images from publicly available datasets and compared against five state-of-the-art AI models in aspects of classification accuracy. Experimental findings showed that our model achieved classification accuracy of over 83%, which is better than the state-of-the-art models, while maintaining high interpretability.
Copper Accumulation in the Lips of Brass Players: Case Report of a Rare Phenomenon
Authors: Baráth Zoltán , Heltai Nóra , Kereszty Éva , Kiss Ildikó , Gajdács Márió , Práger Nándor Tamás , Kárpáti Krisztina , Matusovits Danica
Published: October 2022

Work-related exposures affecting oral health are important factors of morbidity and decreased quality of life, which may emerge from numerous physical, chemical, or mental occupational exposures. Copper (Cu) is an important trace element, however, it may also cause allergies, depose and accumulate in the body, leading to acute and chronic toxicity. In the present report, we describe a rare phenomenon found during the examination of two professional brass players, after incidentally noting an artefact during magnetic resonance imaging (MRI) scans, which were performed to monitor bone healing after bone augmentation procedures in an unrelated clinical study. During a detailed workup of patient characteristics, data on medical history, lifestyle, professional habits related to playing the instrument, and oral health status were collected. Overall, both patients presented with similar histories, and the differences from the context of this study were not relevant; however, both brass players were using an uncoated Cu mouthpiece for over 15 years. Based on the imaging findings (a shadow in the area of the lips on the MRI images) and the organoleptic evaluation of the lips and mucosa of the individuals (temporary faint green discoloration), it is most likely that the brass players were affected by oxidized Cu accumulation in the lip. In contrast to several professions, musicians are usually not required by law to attend obligatory occupational health check-ups, which may facilitate the occurrence of such exposures in musicians. Clinicians should be on the lookout for brass players involved in the profession for a long time, who may have used the mouthpieces for an extended period of time, in addition to musicians affected by Wilson’s disease. In patients affected by this phenomenon, diagnostics of oral cancer and prosthodontic procedures may be cumbersome, due to the detrimental impact on the utility of MRI imaging from artefact-formation and scattering.
Performance Modulation of S-CO2 Brayton Cycle for Marine Low-Speed Diesel Engine Flue Gas Waste Heat Recovery Based on MOGA
Authors: Xie Liangtao , Yang Jianguo
Published: October 2022

(1) Background: the shipping industry forced ships to adopt new energy-saving technologies to improve energy efficiency. With the timing modulation for the marine low-speed diesel engine S-CO2 Brayton cycle, the waste heat recovery system is optimized to improve fuel economy. (2) Methods: with the 6EX340EF marine low-speed diesel engine established in AVL Cruise M and verified by the bench test data, the model of the S-CO2 Recompression Brayton Cycle (SCRBC) system for the low-speed engine flue gas waste heat recovery was developed in EBSILON, and verified by SANDIA experimental data. On this basis, the effects of injection timing and valve timing parameters on the comprehensive performance of the main engine and the waste heat recovery system were investigated. By optimizing the timing modulation parameters through multi-objective genetic algorithm (MOGA) and evaluating the flue gas waste heat recovery from the perspective of thermodynamic performance and emission reduction, the research on the performance modulation method of the S-CO2 Brayton Cycle for flue gas waste heat in marine low-speed engines has been completed. (3) Results: the SCRBC with waste heat modulation will further increase the total power and efficiency, which in turn brings about a reduction in the fuel consumption rate. The efficiency of the SCRBC system with the addition of waste heat modulation increases by 2.28%, 1.04% and 2.07% at 50%, 75% and 100%, respectively. After adding the residual heat modulation, the maximum annual CO2 emission reduction of 748.51 × 103 kg·a−1 occurred at 50% load; with the exergy analysis, the cooler has the largest system exergy loss of 165 kW, with the exergy loss efficiency of 2.06% under 100% load. (4) Conclusions: the research on the performance modulation method of S-CO2 Brayton cycle for flue gas waste heat in the marine low-speed engine has been completed, which further improves the efficiency of the system and can be extended to other engines.
The Use of Augmented Reality to Strengthen Competence in Data Analysis and Problem Solving in Engineering Students at the Universidad del Valle de México
Authors: Zamora-Antuñano Marco Antonio , Barros-Baertl Rossana , Tovar-Luna Belzabeth , González-Gutiérrez Carlos Alberto , Mendez-Lozano Nestor Efren , Cruz-Perez Miguel Ángel
Published: October 2022

The objective of this research was to analyze the improvement in the data analysis and problem-solving competence of students of industrial and systems engineering (IIS) and mechatronics engineering (IMEC) through the use of this technology and its impact on the results of the undergraduate general examination (EGEL). A training course was held for teachers and students for the design of learning objects (LO), and a questionnaire on the use of AR and the improvement in learning was administered. AR is a technology that has begun to be introduced in different contexts and at different educational levels. The results obtained through the Wilcoxon test and the multiple correspondence analysis (MCA) showed that there were improvements in academic performance with the use of AR and an interest in this tool being used during the academic training process.
Deletion-Based Tangle Architecture for Edge Computing
Authors: Tulkinbekov Khikmatullo , Kim Deok-Hwan
Published: October 2022

IOTA Tangle offers a promising approach for distributed ledger technology with the capability to compete with the traditional blockchain. To enable microtransactions the Internet of things (IoT) environment, IOTA employs a direct acrylic graph that ensures the integrity and immutability of the transactions. However, IoT data exhibit time sensitivity, wherein the value is lost after a period. Storing these temporary data for immutable storage would not be affordable in the distributed ledger. This study proposes a novel approach—referred to as D-Tangle—that enables data deletions in the Tangle architecture. To achieve this goal, D-Tangle divides transactions into three categories based on their expiration features and employs the climb-up writing technique. Extensive evaluations prove that D-Tangle enables instant deletions in finite lifetime data. Moreover, immutability and deletion upon request are guaranteed for unknown lifetime data.
A Digital Bang-Bang Clock and Data Recovery Circuit Combined with ADC-Based Wireline Receiver
Authors: Gu Youzhi , Feng Xinjie , Chi Runze , Wu Jiangfeng , Chen Yongzhen
Published: October 2022

With the great increases in data transmission rate requirements, analog-to-digital converter (ADC)-based wireline receivers have received more and more attention due to their flexible and powerful equalization capabilities. Considering power consumption, baud-rate Mueller–Muller clock and data recovery (MM-CDR) circuits are widely used in ADC-based wireline receivers since MM-CDR circuits only need one sample signal per unit interval (UI). However, MM-CDR circuits need to set an additional Vref voltage to match the size of the main tap of the channel. If the Vref matching is not appropriate or the signal quality is good as a square wave, MM-CDR circuits cannot accurately lock on to a certain phase and instead drift within a phase range. Therefore, MM-CDR circuits are not as robust and stable as oversampled CDR circuits. In this study, a digital bang-bang clock and data recovery (DBB-CDR) circuit combined with an ADC-based wireline receiver was proposed. The DBB-CDR circuit could eliminate various unstable factors of MM-CDR circuits and achieve fast and robust phase locking without excessively increasing power consumption. A model of the DBB-CDR circuit was combined with an actual 32 Gb/s ADC-based wireline receiver, which was implemented in 28 nm CMOS technology to analyze the performance of the DBB-CDR circuit. The simulation results showed that the DBB-CDR circuit could achieve 0.42 UIpp JTOL@10MHz, and that the minimum JTOL value was 0.362 UIpp under a 0.04 UI variance of Gaussian jitter. The area and power consumption of the DBB-CDR circuit were only 64 μm2 and 0.02 mW, respectively; and the DBB-CDR circuit could also obtain very stable phase locking and demonstrated a fast frequency offset tracking ability when there was a frequency offset.
Performance Evaluation of an On-Body Wireless Body Network Based on an Ultra-Wideband Physical Layer under a Dynamic Channel Model
Authors: Takabayashi Kento , Tanaka Hirokazu , Sakakibara Katsumi
Published: October 2022

Wireless body area networks (WBANs) are attracting attention as an important technology for realizing the Internet of Medical Things (IoMT). In addition, ultra-wideband (UWB) is one of the wireless communication technologies suitable for the IoMT and WBANs. Our previous study investigated the feasibility of WBANs utilizing UWB under ideal and static wearable WBAN channel models. The present research applies a dynamic on-body UWB channel model to a WBAN as a more realistic channel model. The feasibility of a high-reliability UWB-WBAN is demonstrated by evaluating the physical layer performance. Numerical results reveal the maximum number of retransmissions needed to achieve the desired transmission failure ratio for each link type and the corresponding energy efficiency and average number of retransmissions. These findings contribute to the realization of a highly reliable IoMT utilizing UWB-WBANs in a practical environment.
Stability Analysis for Linear Systems with a Differentiable Time-Varying Delay via Auxiliary Equation-Based Method
Authors: Yin Zongming , Jiang Xiefu , Zhang Ning , Zhang Weihua
Published: October 2022

This paper concentrates on the stability problem for linear systems with a differentiable time-varying delay via an auxiliary equation-based method. By supposing that the second-order derivative of the system state is available, an auxiliary equation is obtained. On the basis of the system equation and the auxiliary equation, we define a suitable delay-product-type augmented Lyapunov-Krasovskii functional (LKF), under which more delay and system state information can be exploited. Based on the LKF, by utilizing some vital lemmas, adding zero terms, and the convex analysis method, we propose a new stability condition that is less conservative. Finally, to illustrate the merit of the obtained stability condition, two typical numerical examples are given.
Long-Term Electricity Demand Forecasting in the Steel Complex Micro-Grid Electricity Supply Chain—A Coupled Approach
Authors: Moalem Sepehr , Ahari Roya M. , Shahgholian Ghazanfar , Moazzami Majid , Kazemi Seyed Mohammad
Published: October 2022

Demand forecasting produces valuable information for optimal supply chain management. The basic metals industry is the most energy-intensive industries in the electricity supply chain. There are some differences between this chain and other supply chains including the impossibility of large-scale energy storage, reservation constraints, high costs, limitations on electricity transmission lines capacity, real-time response to high-priority strategic demand, and a variety of energy rates at different hours and seasons. A coupled demand forecasting approach is presented in this paper to forecast the demand time series of the metal industries microgrid with minimum available input data (only demand time series). The proposed method consists of wavelet decomposition in the first step. The training subsets and the validation subsets are used in the training and fine-tuning of the LSTM model using the ELATLBO method. The ESC dataset used in this study for electrical demand forecasting includes 24-h daily over 40 months from 21 March 2017, to 21 June 2020. The obtained results have been compared with the results of Support Vector Machine (SVM), Decision Tree, Boosted Tree, and Random Forest forecasting models optimized using the Bayesian Optimization (BO) method. The results show that performance of the proposed method is well in demand forecasting of the metal industries.
Machine Learning Approach for Smart Distribution Transformers Load Monitoring and Management System
Authors: Ramesh Jayroop , Shahriar Sakib , Al-Ali A. R. , Osman Ahmed , Shaaban Mostafa F.
Published: October 2022

Distribution transformers are an integral part of the power distribution system network and emerging smart grids. With the increasing dynamic service requirements of consumers, there is a higher likelihood of transformer failures due to overloading, feeder line faults, and ineffective cooling. As a consequence, their general longevity has been diminished, and the maintenance efforts of utility providers prove inadequate in efficiently monitoring and detecting transformer conditions. Existing Supervisory Control and Data Acquisition (SCADA) metering points are sparsely allocated in the network, making fault detection in feeder lines limited. To address these issues, this work proposes an IoT system for real-time distribution transformer load monitoring and anomaly detection. The monitoring system consists of a low-cost IoT gateway and sensor module which collects a three-phase load current profile, and oil levels/temperature from a distributed transformer network, specifically at the feeder side. The data are communicated through the publish/subscribe paradigm to a cloud IoT pipeline and stored in a cloud database after processing. An anomaly detection algorithm in the form of Isolation Forest is implemented to intelligently detect likely faults within a time window of 24 h prior. A mobile application was implemented to interact with the cloud database, visualize the real-time conditions of the transformers, and track them geographically. The proposed work can therefore reduce transformer maintenance costs with real-time monitoring and facilitate predictive fault analysis.
The Release and Reduction of Mercury from Solid Fuels through Thermal Treatment Prior to Combustion
Authors: Misztal Edyta , Chmielniak Tomasz , Mazur Izabela , Sajdak Marcin
Published: October 2022

The main source of mercury (Hg) anthropogenic emissions is the combustion of hard and lignite coal in power plants. Reduction of Hg emissions from coal-based power production systems involves Hg removal from the fuel before combustion/gasification by thermal treatment (i.e., low-temperature pyrolysis). Herein, we present the results of laboratory and bench-scale studies on Hg removal from coal via thermal fuel treatment. The influence of the process temperature and coal residence time in the reaction zone on Hg removal efficiency and fuel parameters is studied. The properties of the process products are analyzed as follows: proximate and ultimate analysis for solids as well as H2, N2, CO, CO2, CH4, organic compounds C2–C5, density, and HHV for gaseous. The results show a substantial reduction of Hg in the fuel using a low-temperature pyrolysis process. At moderate pyrolysis temperature provided Hg removal efficiencies of up to 50% for hard coal and over 90% for lignite, with a moderate decrease in the chemical enthalpy of the fuel.
Comparison of “Zero Emission” Vehicles with Petrol and Hybrid Cars in Terms of Total CO2 Release—A Case Study for Romania, Poland, Norway and Germany
Authors: Lieutenant Klaus , Borissova Ana Vassileva , Mustafa Mohamad , McCarthy Nick , Iordache Ioan
Published: October 2022

The authors compare the energy consumption and CO2 emissions from vehicles using internal combustion engines (ICE), battery electric vehicles (BEV), fuel cell electric vehicles (FCEV), and two types of hybrid vehicles, BEV-ICE hybrid and BEV-FCEV hybrid. This paper considers several scenarios for four countries’ electricity production from primary energy sources to estimate total CO2 release. Energy consumption of the vehicle per 100 km, emissions during manufacturing, battery production, and lifecycle of the vehicle are considered in the total amount evaluation of CO2 released. The results show that with current technologies for battery manufacturing, and a significant proportion of national grid electricity delivered by fossil fuels, BEV is the best choice to reduce carbon emissions for shorter driving ranges. In the case of electricity generation mainly by low-carbon sources, FCEV and BEV-FCEV hybrid vehicles end up with lower carbon dioxide emissions. In contrast, with electricity mainly generated from fossil fuels, electric vehicles do not reduce CO2 emissions compared to combustion cars.
A Paradox over Electric Vehicles, Mining of Lithium for Car Batteries
Authors: Luong John H. T. , Tran Cang , Ton-That Di
Published: October 2022

Lithium, a silver-white alkali metal, with significantly high energy density, has been exploited for making rechargeable lithium-ion batteries (LiBs). They have become one of the main energy storage solutions in modern electric cars (EVs). Cobalt, nickel, and manganese are three other key components of LiBs that power electric vehicles (EVs). Neodymium and dysprosium, two rare earth metals, are used in the permanent magnet-based motors of EVs. The operation of EVs also requires a high amount of electricity for recharging their LiBs. Thus, the CO2 emission is reduced during the operation of an EV if the recharged electricity is generated from non-carbon sources such as hydroelectricity, solar energy, and nuclear energy. LiBs in EVs have been pushed to the limit because of their limited storage capacity and charge/discharge cycles. Batteries account for a substantial portion of the size and weight of an EV and occupy the entire chassis. Thus, future LiBs must be smaller and more powerful with extended driving ranges and short charging times. The extended range and longevity of LiBs are feasible with advances in solid-state electrolytes and robust electrode materials. Attention must also be focused on the high-cost, energy, and time-demand steps of LiB manufacturing to reduce cost and turnover time. Solid strategies are required to promote the deployment of spent LiBs for power storage, solar energy, power grids, and other stationary usages. Recycling spent LiBs will alleviate the demand for virgin lithium and 2.6 × 1011 tons of lithium in seawater is a definite asset. Nonetheless, it remains unknown whether advances in battery production technology and recycling will substantially reduce the demand for lithium and other metals beyond 2050. Technical challenges in LiB manufacturing and lithium recycling must be overcome to sustain the deployment of EVs for reducing CO2 emissions. However, potential environmental problems associated with the production and operation of EVs deserve further studies while promoting their global deployment. Moreover, the combined repurposing and remanufacturing of spent LiBs also increases the environmental benefits of EVs. EVs will be equipped with more powerful computers and reliable software to monitor and optimize the operation of LiBs.
Windmill Global Sourcing in an Initiative Using a Spherical Fuzzy Multiple-Criteria Decision Prototype
Authors: Raizah Zehba , Kodipalya Nanjappa Udaya , Ajjipura Shankar Harshitha , Khan Umair , Eldin Sayed , Kumar Rajesh , Galal Ahmed
Published: October 2022

The government of Karnataka has resolved to promote and employ an increasing number of alternative fuels, particularly, wind energy. Selecting a windmill supplier is a key decision when developing a wind energy project, and investors must evaluate various qualitative and quantitative variables that interact symmetrically to discover the best source. As a result, a multi-criteria decision-making procedure is applied to choose a wind turbine provider for wind power projects. A variety of approaches have been used to address this judgment process, some of which were predicated on the use of multi-criteria judgment techniques alone or in conjunction with some different multiple-criteria decision approaches. In this study, the researchers advocated selecting windmill producers for geothermal power generation using a judgment method based on a spherical fuzzy system. After the analyses of the last stage of this research, turbine manufacturers for installations could be suggested. The purpose of this research was to develop a fuzzy multi-criteria foundation for choosing appropriate rotor makers for electricity production. Specialists can utilize the conclusions of this study to choose an appropriate windmill operator in other states, including for green initiatives of a similar nature.
Influence of the Shielding Winding on the Bearing Voltage in a Permanent Magnet Synchronous Machine
Authors: Berhausen Sebastian , Jarek Tomasz , Orság Petr
Published: October 2022

This article presents selected methods of limiting the bearing voltages of synchronous machines with permanent magnets supplied from power electronic converters. The authors analyzed methods based on the use of various shielding windings placed in slot wedges and mounted in the stator end-winding region. The values of the parasitic capacitances of the machine, on which the levels of bearing voltages depend, were determined using the finite element method. Three-dimensional simulation models were used for the calculations. The analysis of the influence of the shielding windings on the bearing voltage waveforms was conducted on the basis of circuit models with two- and three-level converters. The obtained calculation results indicate a high potential in limiting bearing voltages.
State of Charge Estimation for Electric Vehicle Battery Management Systems Using the Hybrid Recurrent Learning Approach with Explainable Artificial Intelligence
Authors: Shahriar Saleh Mohammed , Bhuiyan Erphan A. , Nahiduzzaman Md. , Ahsan Mominul , Haider Julfikar
Published: October 2022

Enhancing the accuracy of the battery state of charge (SOC) estimation is essential in developing more effective, dependable, and convenient electric vehicles. In this paper, a hybrid CNN and gated recurrent unit-long short-term memory (CNN-GRU-LSTM) approach, which is a recurrent neural network (RNN) based model with an explainable artificial intelligence (EAI) was used for the battery SOC estimation, where the cell parameters were explicitly synchronized to the SOC. The complexed link between the monitoring signals related to current, voltage, and temperature, and the battery SOC, was established using the deep learning (DL) technique. A LG 18650HG2 li-ion battery dataset was used for training the model so that the battery was subjected to a dynamic process. Moreover, the data recorded at ambient temperatures of −10 °C, 0 °C, 10 °C, and 25 °C are fed into the method during training. The trained model was subsequently used to estimate the SOC instantaneously on the testing datasets. At first, the training process was carried out with all temperature data to estimate the SOC by the trained model at various ambient temperatures. The proposed approach was capable to encapsulate the relationships on time into the network weights and, as a result, it produced more stable, accurate, and reliable estimations of the SOC, compared to that by some other existing networks. The hybrid model achieved a mean absolute error (MAE) of 0.41% to 1.13% for the −10 °C to 25 °C operating temperatures. The EAI was also utilized to explain the battery SOC model making certain decisions and to find out the significant features responsible for the estimation process.
Application of High-Performance Liquid Chromatography with Fluorescence Detection for Non-Polar Heterocyclic Aromatic Amines and Acridine Derivatives Determination in Pork Loin Roasted in a Roasting Bag
Authors: Śnieżek Ewa , Szumska Magdalena , Nowak Agnieszka , Muzyka Roksana , Janoszka Beata
Published: October 2022

Heat treatment of meat can lead to the formation of carcinogenic organic compounds. The influence of dried fruits on the formation of non-polar heterocyclic aromatic amines (carbolines) and nitrogen derivatives of polycyclic aromatic hydrocarbons (azaarenes) in roasted pork loin was elucidated. Two hundred grams of fruit per 1 kg of meat were used as stuffing. Carbolines, derivatives of pyridoimidazole and pyridoindole, and azaarenes (benzoacridines and dibenzoacridines) were determined by means of high-performance liquid chromatography with fluorescence detection. The total concentration of six δ-, γ- and α-carbolines in roasted pork loin was 1.3 ng/g. This content decreased by 64%, 58%, and 54% in pork loin stuffed with prunes, apricots, and cranberries, respectively. Concentrations of β-carbolines (harmane and norharmane) increased under the influence of added fruits. The norharmane content increased the most, from 2.2 ng/g in the control sample to 12.3 ng/g in meat prepared with cranberries. The harmane content increased from 1.0 ng/g to 3.6 ng/g in meat with prunes. The total concentration of azaarenes (two benzoacridines and dibenzo[a,c]acridine), which was close to 0.1 ng/g, decreased in dishes with prunes and apricots by 54% and 12%, respectively. Azaarenes were not found in samples of meat stuffed with cranberries.
Application of Cheese Whey Containing Postbiotics of Lactobacillus acidophilus LA5 and Bifidobacterium animalis BB12 as a Preserving Liquid in High-Moisture Mozzarella
Authors: Sharafi Houshmand , Moradi Mehran , Amiri Saber
Published: October 2022

High-moisture mozzarella cheese (HMMC) is a highly perishable cheese with a short shelf life. In this study, the effects of UF cheese whey containing postbiotics from Lactobacillus acidophilus LA-5 (P-LA-5), Bifidobacterium animalis BB-12 (P-BB-12), and their combination on the microbial (i.e., psychrophiles, mesophiles, lactic acid bacteria, and mold-yeast population) and sensory properties of HMMC were investigated. Postbiotics were prepared in a cheese whey model medium as a novel growth media and used as a preserving liquid in HMMC. The results demonstrate that postbiotics reduced the growth of all microorganisms (1.5–2 log CFU/g reduction) and P-LA5 and P-BB12 had the highest antibacterial performance on mesophiles and psychrophiles, respectively. Mold and yeast had the highest susceptibility to the postbiotics. Postbiotics showed a significant effect on maintaining the microbial quality of HMMC during storage, proposing postbiotics as a new preserving liquid for HMMC.
Effects of Fertilizer on the Quality and Traceability of Tibet highland Barley (Hordeum vulgare L.): A Diagnosis Using Nutrients and Mineral Elements
Authors: Zhao Shanshan , Qiu Cheng , Zhang Tangwei , Hu Xiangyu , Zhao Yan , Cheng Xiyu , Ma Yuxuan , Qie Mengjie , Chen Chang
Published: October 2022

Production areas influence the quality of highland barley (Hordeum vulgare L.), and fertilization levels may be associated with the origin traceability of highland barley. As the main object of the study, a collection of highland barley was planted in different areas in Tibet, China, to explore the effect of fertilizer on the quality and traceability of highland barley. We carried out field experiments with and without fertilizer treatment (using urea and diamine phosphate). Highland barley was distinguished by nutrient and mineral element contents in combination with chemometric methods. The results indicated that fertilizer treatment significantly affected some mineral element contents in highland barley and improved the accuracy of highland barley traceability. The combination of nutrients and mineral elements could distinguish highland barley from those raised in other areas due to influence of growing environment. P, K, Fe, and Cu provided a great contribution to the classification of highland barley. Thus, the combination of nutrients and mineral elements can be used as a powerful tool to track highland barley, indicating that fertilization treatment should be considered when tracing highland barley.
The Impact of COVID-19 on Physical Activity Patterns of Dental Students: A Multinational Survey
Authors: AL-Mhanna Sameer Badri , Wan Ghazali Wan Syaheedah , Mohamed Mahaneem , Mohamed Roshan Noor , Mirza Mubashir Baig , Basheer Syed Nahid , Arora Suraj , Afolabi Hafeez Abiola , Mutalub Yahkub Babatunde , Goni Mohammed Dauda , Sheikh Abdulrahman M.
Published: October 2022

Background: The authorities of the world had to take extraordinary containment measures due to the coronavirus (COVID-19) pandemic spreading across the globe. The only way to stay active during the pandemic was at-home physical activity (PA). The current study evaluates how these preventative measures impacted the PA and well-being of students. Methods: This study is multicentral and was conducted in Malaysia, India, Cambodia, and Saudi Arabia; participants were recruited from four different regions to answer the online questionnaire provided via a link shared using their personal WhatsApp, Facebook Messenger, and Twitter social media. Results: The means of vigorous, moderate, and light PA (min/day) between the active and inactive groups were significantly different (p = 0.001, 0.007, and 0.001), respectively. In comparison with pre-COVID-19, the participants reported that it became more challenging to engage in regular exercise since the onset of social distance, associated with a lack of motivation followed by “less confidence”, “less enjoyment”, “less support, and fewer opportunities to engage in exercise”; moreover, it was “difficult to maintain close relationships” and “hard to voice their options on contentious matters” (p = 0.001). Public health measures affected the PA and well-being of active and inactive students; this demonstrates that health promotion strategies aimed at enhancing levels of PA in inactive students may be necessary to improve students’ well-being.
Microclimate and Weathering in Cultural Heritage: Design of a Monitoring Apparatus for Field Exposure Tests
Authors: Germinario Luigi , Coletti Chiara , Girardi Giampaolo , Maritan Lara , Praticelli Nicola , Sassi Raffaele , Solstad Jørgen , Mazzoli Claudio
Published: October 2022

An innovative experimental method for the long-term monitoring of outdoor microclimate and material decay at cultural heritage sites was developed to aid the formulation of new damage functions and models for climate-change risk assessment. To that end, an apparatus for field exposure tests was designed to monitor a variety of historical building materials in different environmental settings. The data series acquired, i.e., surface temperature and moisture, are compared with the corresponding meteorological datasets on a local and regional scale. The apparatus is designed for supporting also the monitoring of the physical and chemical changes caused by weathering. This novel method is expected to provide insights into the interaction between historical materials and the environment, which can be exploited for the protection and conservation of cultural heritage.
Ferrous Industrial Wastes—Valuable Resources for Water and Wastewater Decontamination
Authors: Matei Ecaterina , Predescu Andra Mihaela , Șăulean Anca Andreea , Râpă Maria , Sohaciu Mirela Gabriela , Coman George , Berbecaru Andrei-Constantin , Predescu Cristian , Vâju Dumitru , Vlad Grigore
Published: October 2022

Ferrous waste by-products from the metallurgical industry have a high potential for valorization in the context of the circular economy, and can be converted to value-added products used in environmental remediation. This research reviews the latest data available in the literature with a focus on: (i) sources from which these types of iron-based wastes originate; (ii) the types of ferrous compounds that result from different industries; (iii) the different methods (with respect to the circular economy) used to convert them into products applied in water and wastewater decontamination; (iv) the harmful effects ferrous wastes can have on the environment and human health; and (v) the future perspectives for these types of waste.