bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inflammation Meets Metabolism Roles: for the Receptor for Advanced Glycation End Products Axis in Cardiovascular Disease
Authors: Senatus Laura , MacLean Michael , Arivazhagan Lakshmi , Egana-Gorrono Lander , Lopez-Diez Raquel , Manigrasso Michaele B. , Ruiz Henry H. , Vasquez Carolina , Wilson Robin , Shekhtman Alexander , Gugger Paul F. , Ramasamy Ravichandran , Schmidt Ann Marie 
Published: June 2021

Abstract
Fundamental modulation of energy metabolism in immune cells is increasingly being recognized for the ability to impart important changes in cellular properties. In homeostasis, cells of the innate immune system, such as monocytes, macrophages and dendritic cells (DCs), are enabled to respond rapidly to various forms of acute cellular and environmental stress, such as pathogens. In chronic stress milieus, these cells may undergo a re-programming, thereby triggering processes that may instigate tissue damage and failure of resolution. In settings of metabolic dysfunction, moieties such as excess sugars (glucose, fructose and sucrose) accumulate in the tissues and may form advanced glycation end products (AGEs), which are signaling ligands for the receptor for advanced glycation end products (RAGE). In addition, cellular accumulation of cholesterol species such as that occurring upon macrophage engulfment of dead/dying cells, presents these cells with a major challenge to metabolize/efflux excess cholesterol. RAGE contributes to reduced expression and activities of molecules mediating cholesterol efflux. This Review chronicles examples of the roles that sugars and cholesterol, via RAGE, play in immune cells in instigation of maladaptive cellular signaling and the mediation of chronic cellular stress. At this time, emerging roles for the ligand-RAGE axis in metabolism-mediated modulation of inflammatory signaling in immune cells are being unearthed and add to the growing body of factors underlying pathological immunometabolism.
Numerical Study of Stress-Strain State of Workpiece in Contact Problem of Surface Mandrel Drilling
Authors: Sivtsev N. S. , Tarasov V. V. 
Published: June 2021

In recent years, the economic factor has played an increasingly important role in the selection of technologies for manufacturing machine parts with specified values of normalized parameters of geometric accuracy and quality of working surfaces. As applied to surface plastic deformation processes, this is noticeably manifested in the search for effective friction control methods in the “tool – workpiece” pair, which ultimately determines the distribution pattern and the magnitude of stresses and strains in the workpiece and the tool. It is not possible to obtain a rigorous analytical solution to the problem of establishing a connection between surface conditions, friction, and the stress-strain state of the contacted bodies. In this regard, the construction of mathematical models comes to the fore, the solution of which is possible by numerical methods. The paper presents the results of a numerical study (computational experiment) of a finite-element model of workpiece deformation under various conditions of contact interaction and friction by one of the methods of surface plastic deformation – surface mandrel drilling. The friction coefficient has been chosen as the criterion for assessing the conditions of contact interaction and friction. It is shown that a change in the friction coefficient in the process of surface mandrel has no noticeable effect on the formation of a stress field in the deformable workpiece both in the axial, and in the radial and circumferential directions. At the same time, with an increase in the value of the friction coefficient in the “tool – workpiece” pair and with the associated increase in the force of mechanical resistance to deformation of the workpiece, their growth is observed. A computational experiment has confirmed the presence of non-contact deformations of the workpiece and tool during surface mandrel drilling, as well as as a decrease in the value of residual deformations in the workpiece with a decrease in the coefficient of friction. Balance assessment of contact surface displacements in the workpiece (the inner surface of the hole to be machined) and the tool (mandrel) has shown that the deformations of the tool in the elastic region can lead to a significant decrease in the real tightness of surface mandrel drilling.
Effect of insect feces (Hermetia illucens) on rice growth and heavy metal migration from polluted soil to rice plant
Authors: Wang Xiaobo , Wu Nan , Wu Xiang , Geng Weina , Xu Xiaoyan 
Published: June 2021

Abstract
Insect feces are a new kind of biological organic fertilizer. Little is known about the influences of insect feces on rice growth and heavy metal migration from soil to rice plant. In this study, the effects of different amounts (CK (0%), T1 (2%), T2 (4%), T3 (6%), and T4 (8%) ) of black soldier fly larvae (BSFL) feces on the rice growth and the migration/accumulation of heavy metals (Cd and Pb) were investigated by pot experiments within two years. The application of insect feces remarkably increased the contents of soil pH, organic matter, ammonium nitrogen, available phosphorus and potassium. Meanwhile, the insect feces application reduced the weak acid soluble contents of soil Cd and Pb by 8.3–56.8%, but increased those in the oxidizable (by 22.4–165.7%) and residual (by 1.8–225.6%) states. Except for the T4 treatment in the first year, all fertilization treatments increased the rice yield (up to 43.7% and 195.5% higher than those of CK within two years). Moreover, the insect feces application reduced the contents of Cd (8.3%-66.7%) and Pb (6.4%-61.8%) in different parts of rice. Under the same treatment, the metal contents in each part of rice in the second year were lower than those in the first year. The insect feces application decreased the absorption coefficients (24.4%-57.5%) and secondary transport coefficients (3.6%-44.1%) of Cd and Pb by rice plant.
Successful Experimental Infant Baboon Model for Childhood Cryptosporidiosis Studies
Authors: Jillani Ngalla Edward , Nyachieo Atunga , Chai Chivatsi Daniel , Nyariki Nyabuga James 
Published: June 2021

Abstract
Background: Cryptosporidiosis causes high morbidity and fatality to children under two years globally. The lack of an appropriate animal model that mimics the pathogenesis of disease in humans has hampered the development and testing of potential therapeutic options. This study aimed to develop and validate an infant baboon infection model of cryptosporidiosis.Methods: Eighteen immunocompetent weaned infant baboons aged 12 to 16 months were used. The animals were: n=3 controls and three experimental groups of n=5 animals each inoculated with Cryptosporidium parvum oocysts as follows: Group 1: 2x104, Group 2: 2x105, Group 3: 2x106 followed by daily fecal sampling for oocysts evaluation. Blood sampling for immunological assay was done on infection day and thereafter weekly until the end of the experiment followed by necropsy and histopathology. Statistical analysis was done using R, statistical package for the social sciences (SPSS) and Graph Pad Prism software. Analysis of variance (ANOVA) and Bonferroni post-hoc tests were used for comparison of the means, with p<0.05 considered as a significant difference. Correlation coefficient and Probit analysis were also performed.Results: In all experimental animals but not controls, the onset of oocysts shedding occurred between days 2 and 4, with the highest oocyst shedding occurring between days 6 and 28. Histological analysis revealed parasites establishment only in infected animals. Levels of cytokines (TNF-α, IFN-γ, and IL-10) significantly increased in experimental groups compared to controls. Conclusion: 2x104 oocysts were an effective minimum quantifiable experimental infection dose for developing a reproducible infant baboon model.
Theoretical Modeling for Predicting Material Removal Rate through Interelectrode Gap
Authors: Kumar Deepak , Bajpai Vivek , Singh Nirmal Kumar 
Published: June 2021

Abstract
In EDM, the thermal energy of the discharge causing material erosion which is supplied by the power source unit as electrical input. The discharge energy may be recognized by the current and voltage pulses on time transient discharge characteristic curve (V-I curve) during machining. However, the plasma resistance is very short for a smaller interelectrode gap in micro-EDM compared to the impedance of the circuit. Hence, direct probe-based measurement of current and voltage pulses may include the voltage drop across the stray impedance which causes variation in its exact value. Here, a modeling-based approach may help to analyze the energy interaction with the interelectrode gap. This article presents a theoretical modeling approach to predict the interelectrode gap based on gap voltage, gap current, and plasma characteristics. Initially, a simplified two-dimensional heat conduction equation (cylindrical form) was studied to understand the asymmetry of heat flow in Gaussian distribution. A numerical analysis of a single discharge pulse was considered by applying some basic assumptions. A numerical model has been developed to predict gap distance and MRR considering gap voltage, gap current, and plasma properties. The predicted model was validated against previously reported data from the literature. Later on, the impact of gap voltage on gap distance, plasma resistance, and material erosion rate was analyzed and discussed briefly.
Ball and Player Detection &amp; Tracking in Soccer Videos Using Improved YOLOV3 Model
Authors: Naik Banoth Thulasya , Hashmi Mohammad Farukh 
Published: June 2021

Abstract
Over the past few years, there has been a tremendous increase in the interest and enthusiasm for sports among people. This has led to an increase in the importance given to video recording of various sports that capture even the minutest detail using high-end equipment. Recording and analysis have thereby become extremely crucial in sports like soccer that involve several complex and fast events. Ball detection and tracking along with player analysis have emerged as an area of interest among a lot of analysts and researchers. This is because it helps coaches in performance assessment of the team and in decision making to obtain optimized results. Video analysis can additionally be used by coaches and recruiters to look for new, talented players based on their previously played games. Ball detection also plays a pivotal role in assisting the referees in making decisions at game-changing moments. However, as the ball is almost always moving, its shape-appearance keeps changing over time and it is frequently occluded by players, it makes it difficult to track it throughout the game. We propose a deep learning-based YOLOv3 model for the ball and player detection in broadcast soccer videos. Initially, the videos are processed and unnecessary parts like zoom-ins, replays, etc., are removed to obtain only the relevant frames from each game. Tracking is achieved using the SORT algorithm which employs a Kalman filtering and bounding box overlap.
Probabilistic Assessment of Monthly River Flow Discharge Using Copula And OSVR Approaches
Authors: Tahroudi Mohammad Nazeri , Mirabbasi Rasoul , Ramezani Yousef , Ahmadi Farshad 
Published: June 2021

Abstract
Simulation of flow discharge based on monthly precipitation values as inputs is one of the important issues in hydrology and water resources studies, especially in areas where data with the shorter time scales are not available. In this study, the applicability of support vector regression (SVR) model optimized by Ant colony and Copula-GARCH algorithms was investigated and compared to simulate the flow discharge based on total monthly rainfall in Talezang Basin, Iran. Entropy theory was used to select a suitable meteorological station corresponding to a hydrometric station. The vector autoregressive model was also used as the base model in Copula-GARCH simulations. The correlation results of the studied paired variable confirmed the possibility of using copula-based models. The simulation results were evaluated using R2, Nash-Sutcliffe Efficiency (NSE) and root mean square error (RMSE) statistics. According to the 99% confidence intervals of the simulations, the accuracy of both models was confirmed. The simulation results showed that the Copula-GARCH model was more accurate than the optimized SVR (OSVR) model. Considering the 90% efficiency (NSE = 0.90) of Copula-GARCH approach, the results show a 36% improvement of RMSE statistics by Copula-GARCH model compared to OSVR model in simulating the flow discharge on a monthly scale. The results also showed that by combining nonlinear ARCH models with the copula-based simulations, the reliability of the simulation results increases, which was also confirmed using the violin plot. The results also showed an increase in the accuracy of the Copula-GARCH model at the minimum and maximum values of the data.
Challenges of online education /distance learning for university students during the COVID-19 pandemic: An observation from Bangladesh
Authors: Hossain Md. Tanvir , Nishu Nishana Afrin , Sultana Afsana , Jahan Nusrat , Snigdha Shayla Sharmin , Bashitialshaaer Raed 
Published: June 2021

Abstract
Following the spread of COVID-19, online education/distance learning (OE/DL) was opted by the governments across the world. However, many challenges remained unexplored as OE/DL was quite an unfamiliar teaching approach, particularly in Bangladesh. This study was aimed at identifying the major challenges of OE/DL in Bangladesh from the perspectives of students. Data for this web-based cross-sectional study were collected using an e-questionnaire based on Google Form. Out of 451 initial responses, 419 were retained based on some specifications. The univariate analyses identified the financial, technical, and pedagogical issues as major problems. Exploratory factor analysis and confirmatory factor analysis suggest a two-factor solution – ‘financial-technical obstacles’ and ‘pedagogical obstacles’ – with overall good reliability (Cronbach’s α = 0.881; McDonald’s ω = 0.880). The two-factors, with strong intercorrelation (r = 0.552), meet the criteria of discriminant validity. To overcome the shortfalls of OE/DL in Bangladesh, inclusiveness with sustainable educational and infrastructural approaches was recommended.
Highly Reliable Routing In Healthcare Systems Based on Internet of Things
Authors: Javid Saeed , Mirzaei Abbas 
Published: June 2021

Abstract
Healthcare is an important application of Internet of things (IoT) and body sensor networks (BSNs). Known as a method of measuring and collecting data in healthcare applications, a BSN must provide more reliable routing. Therefore, it is necessary to develop a method for reducing communication rates and improving reliability in healthcare systems. This paper proposes a novel method for routing data packets to enhance reliability in IoT-based healthcare systems. Given the nature of healthcare systems and importance of energy consumption, the proposed method employs different criteria (residual energy and variance of distance from neighbours) to perform the routing process. The results of implementing the proposed method indicated its acceptable performance in comparison with LSR, OLSR, and MAEB protocols. The method also managed to achieve the goals of retaining the quality of packets received by the sink and reducing energy consumption in healthcare systems.
Automatic Sleep Stage Classification Based on Two-channel EOG and One-channel EMG
Authors: LI Yanjun , Yang Xianglin , Xu Zhi , Zhang Yu , Cao Zhongping 
Published: June 2021

Abstract
The sleep monitoring with PSG severely degrades the sleep quality. In order to simplify the hygienic processing and reduce the load of sleep monitoring, an approach to automatic sleep stage classification without electroencephalogram (EEG) was explored. Totally 108 features from two-channel electrooculogram (EOG) and 6 features from one-channel electromyogram (EMG) were extracted. After feature normalization, the random forest (RF) was used to classify five stages, including wakefulness, REM sleep, N1 sleep, N2 sleep and N3 sleep. Using 114 normalized features from the combination of EOG (108 features) and EMG (6 features), the Cohen’s kappa coefficient was 0.749 and the accuracy was 80.8% by leave-one -out cross-validation (LOOCV) for 124 records from ISRUC-Sleep. As a reference for AASM standard, the Cohen’s kappa coefficient was 0.801 and the accuracy was 84.7% for the same dataset based on 438 normalized features from the combination of EEG (324 features), EOG (108 features) and EMG (6 features). In conclusion, the approach by EOG+EMG with the normalization can reduce the load of sleep monitoring, and achieves comparable performances with the "gold standard" EEG+EOG+EMG on sleep classification.
Internet of Vehicles and Connected Smart Vehicles Communication System Towards Autonomous Driving
Authors: Hbaieb Amal , AYED Samiha , CHAARI Lamia 
Published: June 2021

Abstract
Internet of Vehicles (IoV) is one of the attractive solutions that revolutionized automotive services. IoV is the key concept toward smart and autonomous cars. Providing different wireless connectivity’s for vehicles permits the communication inside and outside the vehicle. These connectivities allow the vehicle to interact with other vehicles and with its environment. Autonomous driving is an innovative automotive service that will be enabled by the technology advancement related to IoV and connected cars. Big data technology has a significant impact on the development of autonomous driving and IOV concept as it refers to a huge interactive networks of information. In this paper, we focus on wireless technologies and the communication system to provide Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) or Vehicle- to-Road (V2R), Vehicle-to-Sensor (V2S), Vehicle-to-Human (V2H), Vehicle-to-Cellular (V2C), Vehicle-to-Grid (V2G), and Vehicle-to-Internet (V2I) connectivities. Accordingly, this paper proposes a novel planning scheme for internet connected and autonomous driving vehicles. Particularly, we present the principal components and how they should be distributed across this kind of architecture; i.e., identifying information flows, required exchanged data and basic functionalities required to build autonomous driving service as well as the holistic hardware and software architecture involving the in-car gateway.
Encryption and Decryption Based on Bit Scrambling Using LFSR and Chaos Masking to Combat the Security Attacks in Optical Communication
Authors: marudhai valarmathi , prince Shanthi 
Published: June 2021

Abstract
With the latest technological advancements and attractive features of all optical networks such as bandwidth, performance, reliability, cost efficiency, redundancy these networks have been considered as most viable solution to satisfy promptly growing bandwidth demands. With the increased demand for an optical network, there arises the need for security as well. Vulnerabilities in all optical network made to concentrate more on security issues, as an unimaginable amount of data is being transmitted across these communication links. The proposed methodology to provide the security to these links involve the design of optical linear feedback shift register (LFSR) which gives the scrambled bits also known as randomization. By this process the information signal will be in unreadable form it is highly difficult to predict for the intruder to hack the information signal. In addition to this, the chaos masking and de masking technique is preferred to secure the information. The generated chaotic signal is non- periodic and non- binary so it is not possible to predict the form of the signal. Further this work gives the performance analysis for with and without chaos masking and demasking technique for the acceptable BER of 10e-12 and Q-factor of 7. It also gives the design and study for in-band jamming and out-band jamming attacks for all-optical networks. Simulation of proposed design is done using OptiSystem version 16.0 software tool and the performance are analyzed at different data rate and for different fiber length.
Community Pharmacies, Drug Stores, and Antibiotic Dispensing in Indonesia: A Qualitative Study
Authors: Ferdiana Astri , Liverani Marco , Khan Mishal , Wulandari Luh Putu Lila , Mashuri Yusuf Ari , Batura Neha , Wibawa Tri , Yeung Shunmay , Day Richard , Jan Stephen , Wiseman Virginia , Probandari Ari 
Published: June 2021

Abstract
Background

Inappropriate dispensing of antibiotics at community pharmacies is an important driver of antimicrobial resistance (AMR), particularly in low- and middle-income countries. Thus, a better understanding of dispensing practices is crucial to inform national, regional, and global responses to AMR. This requires careful examination of the interactions between vendors and clients, sensitive to the context in which these interactions take place.
Methods

In 2019, we conducted a qualitative study to examine antibiotic dispensing practices and associated drivers in Indonesia, where self-medication with antibiotics purchased at community pharmacies and drug stores is widespread. Data collection involved 60 in-depth interviews with staff at pharmacies and drug stores (n = 31) and their clients (n = 29), conducted in an urban (Bekasi) and a semi-rural location (Tabalong) to capture different markets and different contexts of access to medicines. Interview transcripts were analysed using thematic content analysis.
Results

A common dispensing pattern was the direct request of antibiotics by clients, who walked into pharmacies or drug stores and asked for antibiotics without prescription, either by their generic/brand name or by showing an empty package or sample. A less common pattern was recommendation to use antibiotics by the vendor after the patient presented with symptoms. Drivers of inappropriate antibiotic dispensing included poor knowledge of antibiotics and AMR driving patient demand, financial incentives to maximise medicine sales in an increasingly competitive market, the unintended effects of health policy reforms, and weak regulatory enforcement.
Conclusions

Inappropriate dispensing of antibiotics in community pharmacies is the outcome of complex interactions between vendors and clients, shaped by wider and changing socio-economic processes. Concerted action should be taken to address this complexity and involve such providers in the development and implementation of AMR national action plans.
Clarifying the Relationship Among Green Investment, Clean Energy Consumption, Carbon Emissions, and Economic Growth: A Provincial Panel Analysis of China
Authors: Wan Yuanyuan , Sheng Ni 
Published: June 2021

Abstract
Green investment considers energy conservation and environmental protection as its main goals. Few studies based on simultaneous equation models have evaluated the relationships between green investment, clean energy consumption, carbon emissions, and economic growth. We use panel data from 30 provinces and cities in China from 2003 to 2017 to establish a simultaneous equation model that can evaluate these crucial relationships. At the national level, green investment has a significantly positive impact on clean energy consumption and economic growth; however, it has no significant effect on carbon dioxide emissions. Moreover, there is a U-shaped relationship between economic growth and clean energy consumption, as well as economic growth and CO2 emissions. When the per capita GDP is greater than 105735.92 (RMB), the use of clean energy will increase and CO2 emissions will decrease, thereby benefitting the environment and economy. Additionally, the impacts of green investment on clean energy differ in China’s eastern, central, and western regions, and the non-linear relationships between economic growth and clean energy consumption in these regions also differ. Based on these findings, countermeasures and suggestions are proposed to spur development within different regions.