bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Model of Factors Affecting Work-Family Conflict and Its Indicators: A Fuzzy Total Interpretive Structural Modeling Approach
Authors: arghavan mohammad reza , Alimohammadlou Moslem , amini alireza 
Published: January 2024

Abstract
Objective
The imbalance between work and family life, otherwise called work-family conflict, represents one of the major challenges that individuals encounter in the twenty-first century. Given this issue, the present study seeks to identify the factors affecting work-family conflict and its indicators and to interpret the relationships between them.
Method
The study used qualitative and quantitative approaches and involved three stages. At stage 1, the meta-synthesis method was employed to screen 3204 publications, as a result of which 391 ones were selected. The contents of these publications were analyzed to identify work-family conflict indicators. At stage 2, all of the employees working for the branches of such banks as Melli, Mellat, Pasargad, Sepah, Shahr, Tejarat, and Iran Zamin, and Refah Kargaran in Lar city, Iran, were included as samples based on the census method. Next, the impacts of the factors identified on the employees’ work-family conflict were measured and examined. At stage 3, the opinions of 22 experts in the banking industry of Lar city were analyzed based on paired comparisons through the fuzzy total interpretive structural modeling (FISM) method.
Findings
: The study revealed that the effective factors fell under four dimensions, namely “occupational”, “familial”, “individual”, and “environmental.” Furthermore, the work-family conflict indicators were “doubt, hesitation, and caution”, “anxiety and distress”, “a sense of emptiness”, “physical health issues”, “occupational problems”, and “family problems.” There was a cause-effect relationship between the factors affecting work-family conflict and its indicators. The factors and indicators were divided into eight level partitions as described below: (a) the first level (receiving the highest impact): “quality of family life”, “psychological growth”, “adaptive behavior”, “a sense of emptiness”, and “family problems”; (b) the second level: “inability to self-organize” and “physical health issues”; (c) the third level: “locus of control” and “spiritual intelligence”; (d) the fourth level: “passion for work and the organization”, “time pressure imposed by family”, “pressure of family expectations”, “doubt, hesitation, and caution”, “anxiety and distress”, and “occupational problems”; (e) the fifth level: “occupational welfare and support schemes”, “a supportive leadership style”, “caregiving and nursing courses”, and “cultural conditions; (f) the sixth level: “time pressure at work” and “occupational risks and conflicts”; (g) the seventh level: “background characteristics”, “the importance of occupational roles”, “dynamic inter-role demands”, “social conditions”, and “economic insecurity”; and (h) the eighth level (most effective level): “the pressure of job demands” and “a human-centered organizational architecture”
IL-37 ameliorates myocardial fibrosis by regulating mtDNA-enriched vesicle release in diabetic cardiomyopathy mice
Authors: Wu Bang wei , Huang Qingyu , Chen Tongqing , Li Jian , Wang Yiming , Shi Huairui , Yu Yifei , Ji Qingwei , Shen Xiaoyan Xiaoyan , Sun Tao Tao , Shi Haiming , Luo Xinping , Jin Bo , You Yan 
Published: January 2024

Abstract
Background
Diabetic cardiomyopathy (DCM), a serious complication of diabetes, leads to structural and functional abnormalities of the heart and ultimately evolves to heart failure. Currently, treatment options for DCM remain limited. IL-37 exerts a substantial influence on the regulation of inflammation and metabolism. Whether IL-37 is involved in DCM is unknown.
Methods
The plasma samples were collected from healthy controls, diabetic patients and DCM patients, and the level of IL-37 and its relationship with heart function were observed. The changes in cardiac function, myocardial fibrosis and mitochondrial injury in DCM mice with or without IL-37 intervention were investigated in vivo. By an in vitro co-culture approach involving HG challenge of cardiomyocytes and fibroblasts, the interaction carried out by cardiomyocytes on fibroblast profibrotic activation was studied. Finally, the possible interactive mediator between cardiomyocytes and fibroblasts was explored, and the intervention role of IL-37 and its relevant molecular mechanisms.
Results
We showed that the level of plasma IL-37 in DCM patients was upregulated compared to that in healthy controls and diabetic patients. Both recombinant IL-37 administration or inducing IL-37 expression alleviated cardiac dysfunction and myocardial fibrosis in DCM mice. Mechanically, hyperglycemia impaired mitochondria through SIRT1/AMPK/PGC1α signaling, resulting in significant cardiomyocyte apoptosis and the release of extracellular vesicles containing mtDNA. Fibroblasts then engulfed these mtDNA-enriched vesicles, thereby activating TLR9 signaling and the cGAS-STING pathway to initiate pro-fibrotic process and adverse remodeling. However, the presence of IL-37 ameliorated mitochondrial injury by preserving the activity of SIRT1-AMPK-PGC1α axis, resulting in a reduction in release of mtDNA-enriched vesicle and ultimately attenuating the progression of DCM.
Conclusions
Collectively, our study demonstrates a protective role of IL-37 in DCM, offering a promising therapeutic agent for this disease.
CH4 transport in wetland plants under controlled environmental conditions – untangling the impacts of phenology
Authors: Ge Mengyu , Korrensalo Aino , Putkinen Anuliina , Laiho Raija , Kohl Lukas , Pihlatie Mari , Lohila Annalea , Makiranta Päivi , Siljanen Henri , Tuittila Eeva-Stiina , Wang Jinsong , Koskinen Markku 
Published: January 2024

Abstract
Background and Aims
Methane (CH4) fluxes at peatland plant surfaces are the net result of transport of soil-produced CH4 and within-plant CH4 production and consumption, yet factors and processes controlling these fluxes remain unclear. We aimed to assess the effects of environmental variables, seasonality and CH4 cycling microbes in CH4 fluxes from shoots of characteristic fen species.
Methods
We conducted high-frequency automated CH4 flux measurements from shoots of a sedge (Carex rostrata), a forb (Menyanthes trifoliata) and two shrubs (Betula nana, Salix lapponum) in a climate-controlled environment. Measurements were conducted from intact plant-soil samples collected throughout growing seasons 2020 and 2021 from Lompolojänkkä fen, northern Finland.
Results
All studied species showed seasonal variability in CH4 fluxes. The CH4 fluxes were not impacted by light level, while higher porewater CH4 concentration increased fluxes from C. rostrata and M. trifoliata, decreased fluxes from S. lapponum, and did not affect fluxes from B. nana. Air temperature only and negatively affected CH4 flux from C. rostrata. Both methanogens and methanotrophs were detected in aboveground parts of S. lapponum and M. trifoliata, methanotrophs in B. nana, while neither were detected in C. rostrata.
Conclusion
Our study demonstrates that the seasonal phase of the plants regulates CH4 fluxes they mediate across species, which was not observed in the field. The detection of methanogens and methanotrophs in herbs and shrubs suggests that microbial processes may contribute to their CH4 fluxes.
Insights and Applications: Evaluating Edge Effects in Planar Capacitors with Advanced Modeling
Authors: JEBRI Zaineb , ALI Mahfoudh TALEB 
Published: January 2024

Abstract
An analysis of edge effects in planar capacitors with parallel electrodes is presented in this article. Many electronic applications utilize capacitors, and understanding the phenomena around their edges is crucial to their design and optimization. Our research explores in detail the distribution of electric fields and electric potential near electrodes using models and methods based on Maxwell's principles and Gauss's theorem. Divergent electric fields can create edge effects, which affect capacitor performance by creating edge effects. A circular electrode shape is one of the strategies we present to mitigate these effects. The implications of these findings in the field of electronics and related technologies are discussed in the final section.
Time Series Analysis of Air Quality of an Industrial District of India Using Remote Sensing and GIS: Impact of Covid-19 Lockdown
Authors: SAHU NAMRATA , SARKAR ADITI 
Published: January 2024

Abstract
In the wake of Covid-19, most countries in the world had lockdowns, shutting down most of the human activities, leading to a never before seen condition of minimum anthropogenic intervention. This caused a unique situation where the earth healed, so as the air quality. This study provides a comparative time series analysis of the ground level and the remotely sensed technique of air quality measurement, showing the results in the best available resolution to date and also the daily variation of the pollutants and air quality index (AQI) in various plots. The plan of the study also included the derivation of particle matter 2.5 (PM2.5) from aerosol optical depth (AOD) to get the remote sensing-based PM 2.5 variation for the study area Howrah using a Geographically Weighted Regression (GWR) model to get an adequate spatiotemporal variation of the pollutant. The study shows an overall improvement of the air quality for the lockdown periods, but again an increase in pollutants level as the restrictions were eased down again. The maximum level of AQI decreased by 53.264% for the year 2020 and 5.183% for the year 2021 as compared to the not-lockdown period in 2019. The overall comparison between the graphs of AQI, SO2, NO2, PM10, and PM2.5 suggests better quality of air in the year 2020 as compared to 2019 and 2021, the latter being better than the middle one. The O3 showed an increasing trend for the year 2020 when there was a noticeable decrease in all other criteria pollutant levels.
Study on the water retention curve of shreddedmunicipal solid waste considering the compressibility of specimens based on the centrifuge method
Authors: Dang Meirong , Chai Junrui , Xu Zengguang , Lu Xiaochun , An Zhongqiu 
Published: January 2024

Abstract
The water retention curve (WRC) of municipal solid waste (MSW) is the important hydraulic parameter for the study of unsaturated seepage analysis in landfills. Due to the compressibility and degradability of the waste, the search for a method to quickly and accurately test its water retention curve (WRC) is a current problem that needs to be solved. In this paper, considering the volume change of the waste specimens in test, the test principle of centrifuge testing of WRC is corrected to make it applicable to the testing of waste WRC. In addition, the WRCs of 20 MSW specimens with typical landfill compositions and porosities are measured using the corrected centrifuge test. The effects of compositions and porosities of waste specimens on WRC parameters were analyzed. The results are summarized as follows. Disregarding the height reduction of specimens resulted in overestimated matric suction values and underestimating volume water content values. By comparing uncorrected and corrected values, the maximum difference of the matric suction and volumetric water content reach 233 kPa and 11%, respectively. This study can provide a reference for accurately measuring the WRC of MSW using a centrifuge. For the waste specimen without kitchen and yard waste, composition had less of an effect on the WRC of waste compared to porosity. The effect of the content of the non-absorbable fraction on the residual volumetric water content θr and the parameter nv in the van Genuchten model was significant. The initial porosity n had a great effect on the parameter α.
Effects of herbaceous morphology changes on the hydrodynamic characteristics of rocky desertification sloping farmland based on flume experiments
Authors: Wang Chenyang , Yan Youjin , Dai Quanhou , Xu Xiaojin , Gan Xianmin , Zhou Hong 
Published: January 2024

Abstract
The process of herbaceous vegetation decay can impact the hydraulic characteristics of slope runoff, thereby affecting soil erosion. However, there have been limited studies quantifying the influence of this decay process on the runoff hydraulic characteristics within soil patches on rocky desertification slopes. In this study, we conducted indoor erosion experiments using simulated fragmented soil patches of rocky desertification slopes in a flume. The experiments involved three different surface cover morphologies during the herbaceous decay process (overall morphology, root morphology, and bare ground), three slope gradients (5°, 15°, and 25°), and three flow discharges (0.03, 0.10, and 0.16 L·s− 1). Our findings indicate that the hydraulic parameters of slope runoff respond differently to changes in slope gradient and flow discharge. The mean flow velocity is the most responsive to variations in slope vegetation morphology. On bare ground slopes, the mean flow velocity was 12% and 22% higher compared to root and overall slopes, respectively. The Froude number and runoff shear stress are the main factors that alter the hydraulic characteristics of slope runoff under the combined effects of slope gradients, flow discharge, and morphology changes. The Froude number increased by 917%, and the runoff shear stress increased by 836% due to the combined effects of slope, flow discharge, and morphology changes. These research findings provide substantial evidence for enhancing the comprehension of the mechanisms through which the decay of herbaceous vegetation impacts slope hydraulic processes. Moreover, they offer a scientific foundation for enhancing the predictive accuracy of soil erosion process models.
WeldNet: a lightweight deep learning model for welding defect recognition
Authors: Wang Rongdi , Wang Hao , He Zhenhao , Zhu Jianchao , Zuo Haiqiang 
Published: January 2024

Abstract
Weld defect detection is an important task in the welding process. Although there are many excellent weld defect detection models, there is still much room for improvement in stability and accuracy. In this study, a lightweight deep learning model called WeldNet is proposed to improve the existing weld defect recognition network for its poor generalization performance, overfitting and large memory occupation, using a design with a small number of parameters but with better performance. We also proposed ensemble-distillation strategy in the training process, which effectively improved the accuracy rate and proposed an improved model ensemble scheme. The experimental results show that the final designed WeldNet model performs well in detecting weld defects and achieves state-of-the-art performance. Its number of parameters is only 26.8\% of that of ResNet18, but the accuracy is 8.9\% higher, while achieving 41 FPS on cpu to meet the demand of real-time operation. The study is of guiding significance for solving practical problems in weld defect detection, and provides new ideas for the application of deep learning in industry. The code used in this article is available at:
https://github.com/Wanglaoban3/WeldNet.git
Round robin MQTT-based routing algorithm for agricultural IoT network: communication optimization between sensors, actuators and brokers
Authors: Hamini Nardjes , Yagoubi Mohamed Bachir 
Published: January 2024

Abstract
This paper proposes a new protocol based on MQTT for IoT networks in the agricultural domain named FNMB. The latter constitutes a good means of communication between publishers, subscribers and brokers and improves the transfer of agricultural data and allows a good balance of the load between brokers using the principle of the round-robin technique. By alternating between brokers the roles of central broker and bridge broker, our approach allows the network to operate smoothly and reliably. This article also explores the advantages of our approach compared to traditional IoT systems with a single broker, or with a fixed central broker in the case of multiple brokers, based on criteria such as energy consumption and load balancing, and shows the promising results obtained with our approach.
High AST and the Presence of Liver Metastases May Guide for the Need for FDG PET in Advanced Prostate Cancer Patients
Authors: Telli Tugce , Tuncel Murat , Karabulut Erdem , Aksoy Sercan , Erman Mustafa , Akdogan Bulent , Caglar Meltem 
Published: January 2024

Abstract
Objective
2-[18F]fluoro-D-glucose (FDG) Positron Emission Tomograpy/Computed Tomography (PET/CT) may help to evaluate the tumor heterogeneity in patients with metastatic castration-resistant prostate cancer (mCRPC) and determine treatment eligibility for Prostate Specific Membrane Antigen (PSMA) targeted radioligand therapy (PSMA-RLT). The aim of the study is to evaluate the biochemical and clinical parameters which can predict the presence of FDG-PSMA discordant disease.
Material and Methods
A total of 70 advanced mCRPC patients who underwent [68Ga]Ga-PSMA-11 PET and FDG PET/CT between August 2016 and June 2021 were retrospectively analyzed. Inter-tumoral heterogeneity was both visually and semi-quantitatively evaluated. Baseline clinical, laboratory and PSMA PET/CT related semi-quantitative parameters were analyzed to predict FDG discordant disease with logistic regression analysis. A receiver operating characteristic (ROC) analysis was performed to determine the threshold values for the statistically significant parameters.
Results
29/70 (41.4%) of the patients had FDG-PSMA discordant disease based on visual assessment. Overall 427 mismatch lesions (FDG > PSMA) were detected: the majority of these lesions were in the bones (n = 236, 55.2%), lymph nodes (n = 95, 22.2%), and visceral organs (n = 88, 20.6%). Most significant parameters to predict FDG-PSMA discordant disease were serum AST (Youden Index derived cut-off value ≥ 24.5 IU/l, sensitivity 75.8%, specificity 73.2%, AUC = 0.79) and the presence of liver metastases.
Conclusion
The presence of liver metastases, elevated AST may be easily used in clinical practice to predict FDG-PSMA discordant disease.
Research on Dynamic Tensile Characteristics and Surface Crack Evolution Law of coal under Impact Loading
Authors: Wang Ziping , Li Shengwei , Zhang Yi , Qi Peiwen , Zhang Youyou , Chen Yuanjing , Li Yexue , Zeng Gang 
Published: January 2024

Abstract

To investigate the dynamic tensile failure process of coal subjected to impact loading, this study used high-speed camera photography and digital image correlation technology to capture the dynamic tensile failure of coal under impact loading. The dynamic tensile evolution from initial stress to failure was quantitatively analyzed. The captured coal fracture images were processed, and the fractal dimension was used to quantitatively describe the surface crack evolution of coal under impact loading. The following conclusions were drawn from the experimental results: (1) An empirical formula was established to describe the dynamic tensile strength characteristics of coal under different loading rates. (2) During the loading process of Brazilian disc coal samples under impact loading, the maximum strain first appeared at the contact end between the sample and the incident rod. (3) Under impact loading, the Brazilian disc coal sample cracked from the center of the sample and the crack subsequently extended toward both ends. The fractal dimension of the crack exhibited a power exponential relationship with time, and the variation range of the fractal dimension of the crack was in the range of 1.05–1.39.
Impact of COVID-19 on Physical Activity Level and Mental Health of Adolescents: An Investigation during a Major Disaster
Authors: Dong Ru-bao , Dou Kai-yun , HUANG Jiaben , WANG Ronghua 
Published: January 2024

Abstract
During COVID-19, did physical activity levels (PAL) play a role in protecting adolescent mental health?
Objective: This study aims to further understand the changes in PAL and mental health among adolescents before and after the outbreak of COVID-19 and explore the protective role of physical activity (PA) on the mental health of adolescents during major disasters.
Methods: A convenient sampling method was used to conduct a cross-sectional survey using the Physical Activity Questionnaire for Children (PAQ-C) and the Minnesota Multiphasic Personality Inventory-60 (MMPI-60). Correlations between PAL and mental health scores of adolescents were tested using Pearson correlation, independent samples t-test, and cross-tabulation analysis in SPSS.
Results: Before and after the outbreak of COVID-19, the PAL of adolescents was 2.36±0.74 and 2.50±0.66, respectively, with a significant difference (p<0.01, 95% CI: 0.09, 0.19). The mental health scores were 1.71±0.60 and 1.86±0.73, respectively, with a significant difference (p<0.01, 95% CI: -0.20, -0.10). The detection rates of mental health problems were 27.50% and 35.50%, respectively. The rates of achieving PAL standards were 30.20% and 18.00% among adolescents, while the rates of not achieving PAL standards were 39.60% and 18.00%.
Conclusion: PA is a protective factor for the mental health of adolescents during major disasters.
Resolving Dual Active Galactic Nuclei with ∼100 pc
separation in MCG-03-34-64
Authors: Falcao Anna Trindade , Turner Tracey , Kraemer Steve , Braito Valentina , Reeves James , Schmitt Henrique 
Published: January 2024

Abstract
Galaxy mergers are expected to play a key role in the evolution of galaxies and their central supermassive black holes (SMBHs) (Springel+2005, Colpi+2011). An observational signature of this phenomenon is the detection of dual active galactic nuclei (AGNs) amongst merging systems, as predicted by cosmological models of structure formation (Colpi+2014, Blumenthal+2018). Dual AGNs at sub-kiloparsec-scale separation are the precursors of merging black hole binaries, an important source of gravitational waves (e.g., Izquierdo-villalba+2021), but a paucity of such systems have been confirmed to date by direct imaging, while other similar claims have been strongly disputed (Koss+2015, Veres+2021). Here we report the serendipitous multiwavelength discovery of a dual black hole system with a separation of ~100 pc, in the gas-rich luminous infrared galaxy MCG-03-34-64 (z=0.016). Chandra/ACIS imaging shows two spatially-resolved peaks of equal intensity in the neutral Fe Kα emission line, consistent with a dual SMBH, which is supported by Hubble Space Telescope (HST), and Very Large Array (VLA) observations. The separation of ~100 pc is the closest dual AGN separation reported to date with spatially-resolved, multiwavelength observations.
Based on the relationship between Hounsfield units and bone mineral density: a tool for preoperative planning of rotator cuff tears
Authors: Liu Guihu , Wang Xiaolong , Ma Yinguang , Zhang Yaxuan , Zhou Haibin , Shen Guangsi 
Published: January 2024

Abstract
Purpose
To quantify the abnormal bone mass of the proximal humerus using the Hounsfield unit (HU) to assist in preparing preoperative surgical plan and improve the curative effect.
Methods
We identified patients who underwent computed tomography and dual-energy X-ray absorptiometry (DXA). The proximal humerus HU values and DXA results were recorded, the correlation of HU and BMD was calculated, and the diagnostic effect was evaluated.
Results
A total of 600 proximal humeri (389 patients) were included in the study. There was no significant difference in the HU values between shoulders (t = 0.62, p = 0.536). The HU values of the humeral head and the greater and lesser tuberosity were negatively correlated with age, but positively correlated with BMD (p < 0.001). We have obtained the exact cut-off value of HU values. All the cut-off values had good diagnostic values, and the area under the curve (AUC) was more significant than 0.70. The linear regression equations of HU values and T score were obtained.
Conclusion
The HU value of CT is an excellent method to evaluate the bone mass of the proximal humerus. We obtained threshold values of abnormal BMD of the humerus head, greater tuberosity, and lesser tuberosity, which can be used to assist in selecting anchors during ARCR and improve the curative effect.