bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seroprevalence and risk factors of hepatitis B and C virus infections among street barbers and beauticians: a community-based study in the Eastern hemisphere of Ghana
Authors: Korang Felix Kwame , Adjei-Gyamfi Silas , Danso-Appiah Anthony , Kamiya Yasuhiko 
Published: August 2024

Abstract

Background: Hepatitis B virus (HBV) and hepatitis C virus (HCV) infections remain a major public health concern across the globe. There is paucity of data on the seroprevalence of viral hepatitis among some high-risk and less-recognized populations in most developing countries like Ghana. This study was conducted to determine the seroprevalence and risk factors associated with HBV and HCV infections among street barbers and beauticians in the Eastern hemisphere of Ghana.Methods: A community-based cross-sectional study was conducted between April and June 2021 at five randomly selected district capitals in the Volta Region. Multistage sampling was employed to select 340 street barbers and beauticians. A structured questionnaire was used to elicit information from participants before collecting blood samples for the assessment of hepatitis B surface antigen and anti-hepatitis C virus. At a 95% significance level, bivariate and multivariate analyses were computed to identify associated factors of HBV and HCV using STATA version 17.0.Results: The overall seroprevalence of HBV and HCV among street barbers and beauticians was 9.7% (95% CI = 6.7–13.3%) and 4.7% (95% CI = 2.7–7.5%), respectively. Participants who had never been vaccinated against HBV (AOR = 9.65; 95% CI = 1.20–77.4; p = 0.033) or never married (AOR = 15.0; 95% CI = 3.34–67.4; p < 0.001) were more likely to be infected with HBV. Street barbers and beauticians who had no history of exposure to customers’ blood while performing their work were 93% less likely to contract HBV (AOR = 0.07; 95% CI = 0.02–0.33; p = 0.011). Participants who had a history of an injury via cut while attending to customers (AOR = 13.0; 95% CI = 2.84–59.6; p = 0.001) and those who were not married (AOR = 8.37; 95% CI = 1.05–66.9; p = 0.045) were also more likely to test positive for HCV.Conclusion: HBV and HCV infections are common among street barbers and beauticians in the Eastern hemisphere of Ghana. While the high prevalence of HBV was predicted by marital status and history of HBV vaccination and blood exposures, that of HCV was also determined by marital status and history of cut injury. Explicit guidelines on the health practices of study participants through the creation of awareness on the modes of transmission and prevention of occupation-related viral infections as well as HBV vaccination programs should be provided for these high-risk workers.
Effects of urban green space habitats and tree species on ectomycorrhizal fungal diversity
Authors: Lin Qian-Cai , Cen Ying-Qing , Xu Ming , Jiang Dan-Dan , Zhang Jian 
Published: August 2024

Abstract

Ectomycorrhizal fungi (EMF) are key symbiotic microbial components for the growth and health of trees in urban greenspace habitats (UGSHs). However, the current understanding of EMF diversity in UGSHs remains poor. Therefore, in this study, using morphological classification and molecular identification, we aimed to investigate EMF diversity in three EMF host plants: Cedrus deodara in the road green belt, and C. deodara, Pinus massoniana, and Salix babylonica in the park road green belt, in Guiyang, China. A total of 62 EMF operational taxonomic units (OTUs) were identified, including 13 EMF OTUs in the C. deodara road green belt, and 23, 31, and 9 EMF OTUs in the park green belts. C. deodara, P. massoniana, and S. babylonica were respectively identified in park green belts. Ascomycota and Basidiomycota were the dominant phyla in the EMF communities in road and park green habitat, respectively. The Shannon and Simpson indices of the C. deodara EMF community in the park green belt were higher than those in the road green belt. EMF diversity of the tree species in the park green belt was P. massoniana > C. deodara > S. babylonica. Differences in EMF community diversity was observed among the different greening tree species in the UGSHs. UGSHs with different disturbance gradients had a significant impact on the EMF diversity of the same greening tree species. These results can be used as a scientific reference for optimizing the design and scientific management of UGSHs.
Demographic and Lifestyle Factors Affecting BMI and Weight Satisfaction of physicians in Babylon province: Cross-Sectional Study
Authors: Kadhem Qais Ismaeel , ABBAS IHAB ABDULAMEER , Hussain Nibras Alaa 
Published: August 2024

Abstract

Background
Rising worldwide health issue obesity is typified by an excessive body fat buildup endangering health. Over the past few decades, the incidence of obesity has sharply risen, which has resulted in an increase in related health issues like type 2 diabetes, heart illnesses, and certain malignancies.
Objective
examines demographic, socioeconomic, and lifestyle factors affecting obesity among medical professionals, analyses medical field data to identify obesity reasons and provide realistic weight control and obesity prevention strategies.
Method
January–June 2024 cross sectional survey of 200 Babylon physicians. Stratified random selection ensured a balanced mix of demographic and socioeconomic traits throughout data collection.
Results
Of the physician replies, most were female (53%), urbanites (96%), aged 36–45 (43%), and 46–55 (32%), With 78% inactivity, most responders—medical (59.5%)—had private clinics (72%) and Age, private employment, and weight satisfaction were linked to BMI; 74% of respondents were overweight or obese. Though they tried to lose weight, 56.5% of them were dissatisfied with it.
Conclusion
Doctors are becoming overweight and obese, and BMI is closely connected with age, private work, and weight satisfaction. Doctors are often unhappy with their weight, suggesting weight control concerns. Low physical activity may be linked to work overload. Exercise and lifestyle improvements for doctors are desperately needed. Patient care providers' health will improve by addressing these challenges.
Electric vehicle path optimization research based on charging and switching methods under V2G
Authors: Liu Haoran , Zhang Aobei 
Published: August 2024

Abstract

This paper presents a novel approach to advancing sustainable urban logistics and distribution, focusing on fast charging and power exchange modes as the core research objects. Our key contribution lies in the development of an electric vehicle path optimization model, wherein the primary objective is total cost minimization. Additionally, we leverage V2G technology to enable slow charging and discharging management of electric vehicles upon their return to the distribution center. Furthermore, we introduce a robust calculation method for estimating battery loss costs, taking into account ambient temperature and discharge depth. The logistics distribution model is effectively solved using a genetic algorithm, incorporating both charging modes under the V2G framework. The simulation results demonstrate that our V2G model significantly enhances the operational flexibility of electric vehicle logistics distribution, leading to a substantial reduction in distribution costs. Moreover, it effectively balances peak and valley loads within the distribution system. In this study, we conduct an in-depth analysis of the charging and swapping mode model through experimental comparisons, offering valuable insights to aid decision-making in the logistics sector regarding charging and swapping strategies. Additionally, we investigate the impact of slow charging and discharging management on the distribution system. Furthermore, we perform a comprehensive sensitivity analysis to explore factors influencing battery loss in electric vehicles. Notably, we find a direct correlation between higher temperatures and deeper discharge depths with increased battery loss. Our research introduces a cutting-edge solution to optimize urban logistics, significantly contributing to sustainable development. The proposed model provides critical implications for the logistics industry, driving efficient and eco-friendly practices in electric vehicle distribution.
Crystal growth, structural phase transitions and optical gap evolution of FAPb(Br1-xClx)3 hybrid perovskites (FA: formamidinium ion, CH(NH2)2+)
Authors: López Carlos A. , Fabelo Oscar , Abia Carmen , Fernández-Diaz María T. , Alonso José Antonio 
Published: August 2024

Abstract

Chemically tuned organic-inorganic hybrid halide perovskites based on bromide and chloride anions CH(NH2)2Pb(Br1 − xClx)3 (CH(NH2)2+: formamidinium ion, FA) have been crystallized and investigated by neutron powder diffraction (NPD), single crystal X-ray diffraction (SCXRD), scanning electron microscopy (SEM) and UV-vis spectroscopy. CH(NH2)2PbBr3 and CH(NH2)2PbCl3 experience successive phase transitions upon cooling, lowering the symmetry from cubic to orthorhombic phases; however, these transitions are suppressed for the mixed halide phases, probably due to compositional disorder. The band-gap engineering brought about by the chemical doping of CH(NH2)2Pb(Br1 − xClx)3 perovskites (x = 0.0, 0.33, 0.5, 0.66 and 1.0) can be controllably tuned: the gap progressively increases with the concentration of Cl− ions from 2.17 to 2.91 eV at room temperature, presenting a nonlinear behavior. This study provides an improved understanding of the structural and optical properties of these appealing hybrid perovskites.
Landslide susceptibility assessment using hybrid integration of best-first decision tree and machine learning ensembles
Authors: Wang Jianguo , Li Weipeng , Li Linhai , Fan Yuchao 
Published: August 2024

Abstract

During the study, we investigate and compare spatial prediction result of landslide hazards with a relative less-used model BFT (Best-first Decision Tree) and its three integrated models RSBFT (RandomSubspace ensemble based BFTree), MBBFT (MultiBoost ensemble based BFT), BABFT (Bagging ensemble based BFT) in Meixian County, Baoji city, Shaanxi province, China. BFTree is a machine learning technique by optimizing split nodes of standard decision tree. Integrated learning is an excellent method by combining several weakly supervised models into a strong supervised model. For data preparation, 87 historical landslide events as landslide inven-tory map and 16 landslide conditioning factors as spatial database have been collected and organized in the study area. At last, the FR (frequency ratio) method was applied for the correlation analysis and CAE (correla-tion attribute evaluation) method was applied for analyzing contribution value of each factor. For the model studies, landslide susceptibility indexes would be possible to measure using BFT, BABFT, MBBFT, RSBFT models and prepared data. Then, four landslide susceptibility maps are generated. At last, randomly assigned 61 (70%) landslides locations has been used to build the landslide models. The other 26 (30%) landslide loca-tions were used to validate. The result of verification shows that three ensemble models have boosted the pre-dictive ability of the base model; MBBFT have better prediction ability than others; RSBFT model has no overfitting problems.
An Investigation of the Fair Play Understanding of the Leading Personnel Participating in Physical Education and Sports Activities in the Military System
Authors: GÜNEŞ Ejder 
Published: August 2024

Abstract

Background: This study aims to investigate the fair play understanding of the leading personnel participating in physical education and sports activities in the military system. There is no detailed examination in the literature on the fair play understanding of military leaders within the Turkish Armed Forces and their contribution to sports activities. The study was conducted on 257 officers, non-commissioned officers, and specialist sergeants in the Presidential Guard Regiment Command. The "Multidimensional Sportspersonship Orientation Scale" was used to measure the sportspersonship understanding of the personnel and to evaluate it in a correlational way with demographic data.
Methods: In this study, which aims to investigate and interpret the fair play understanding of the leading personnel participating in physical education and sports activities in the military system, the "Correlational Research" model from the quantitative research model was used. The population of the study consists of officers, non-commissioned officers, and specialist sergeants who are in charge of the military personnel within the Presidential Guard Regiment Command. The sample of the study consists of 257 leading military personnel randomly selected from the study population. The data were collected through online forms on 08.02.2024. The scale used consists of 5 sub-dimensions and 20 items in total, known as the "Multidimensional Sportspersonship Orientation Scale."
Results: The study results revealed that the fair play and sportspersonship understandings of military personnel are lower than those of civilians. In the military system, factors such as stress and the struggle for survival, especially on battlefields, may conflict with the concept of sportspersonship. Leading personnel, who are usually raised with a warrior mentality, often prioritize sportspersonship values as secondary. These low sportspersonship values call into question the importance of fair play and sportspersonship behaviors within the military system.
Conclusion: This study is an important step to understanding the ability of military leaders to balance between ethical and sporting values. The findings highlight the necessity of developing fair play understanding within the military system. This study contributes empirical data to the literature on the understanding of fair play in the military system and helps fill the gap in this field. Future studies in other military branches should be considered to generalize these findings.
Predicting NGL Recovery from Flared Gas Using Nonlinear Multiple Regression and Artificial Neural Network Model
Authors: Asal M. Abdelraof , Gomaa Sayed , Aboul-Fetouh Mostafa E. , Aboul‑Fotouh Tarek M. 
Published: August 2024

Abstract

Recovery of natural gas liquid (NGL) from flared gas is considered one of the techniques of emissions reduction, the recovered quantity depends on several factors including the natural gas composition, operating pressure, and temperature. Process simulation is required to measure the recovery of NGL from the flared gas, and process simulation cases are required to predict the NGL productivity, these cases should be generated at several operating conditions for optimization purposes. In this paper, 12873 data sets are generated using Aspen HYSYS for different natural gas compositions collected from 11 natural gas fields. These huge data sets are used to develop an artificial neural network (ANN) model for predicting the NGL recovery. The developed model was trained based on 70% of the data sets, validated based on 15%, and tested using 15 % of all the data sets. The results show that the developed NN model can accurately the NGL recovery based on the natural gas composition, and the operating pressure and temperature with a coefficient of determination of 0.9999 and an absolute average error of 4%.
The proposed model for estimating NGL production rates is a feasible environmental issue. The availability of changing the operating pressure and temperature could help in selecting the proper equipment such as recovery compressors and refrigeration unit size. This approach also could allow production companies to join the project quickly, eliminate carbon dioxide emissions, and start to gain money in a short time.
COVID-19 Vaccination Outreach to Vulnerable and Remote Communities in Bihar, India: Lessons from an Assessment of an Innovative Program
Authors: Thakur Putul , Akhauri Santosh , Pradhan Narottam , Jha Rakesh Kumar , Singh Sanjay Kumar , Sinha Narendra Kumar , Kumar Mani , Singh Anubhuti , Swati Swati , Mondal Sudipta 
Published: August 2024

Abstract

Background and objectives
During the peak of the COVID-19 pandemic, equitable delivery of COVID-19 vaccines was one of the major challenges in policymaking. In search of innovative solutions, Project Concern International (PCI), with support from the Packard Foundation and the Government of Bihar developed and tested a human centric design to vaccinate the populations in disadvantaged geographies and from vulnerable subgroups. This study aims to examine the association of the intervention on improving vaccination coverage in the project area as well as across various population subgroups.
Data and Methods
The study is based on a quasi-experimental design with intervention and comparison arms comprising of 100 villages each. Data on COVID-19 vaccination coverage and other socioeconomic correlates was collected through cross-sectional household survey in July 2022. The survey covered five randomly selected intervention districts (Arwal, Kaimur, Katihar, Madhepura and Jamai). Descriptive statistical analysis, logistic regression, and propensity score matching (PSM) techniques with diagnostic checks are applied to discern the association of the project intervention on COVID-19 vaccination coverage.
Results
There was a significant improvement in vaccine uptake of two or more doses of vaccine in the intervention arm (intervention-83%, comparison-74%). 56% of pregnant women, 82% of the people suffering from critical illness and 82% of the differently abled people received two or more doses in the intervention arm. Women, educated individuals, and those with access to mobile had higher likelihood of vaccine coverage. The PSM analysis confirms that the intervention area had about 10%-point higher coverage of COVID-19 vaccination then the comparison area.
Conclusion
The RECOVER Bihar intervention was significantly associated with increased uptake of the COVID-19 vaccine among all categories of beneficiaries, including vulnerable categories. The learnings from the program design can be adopted in other programs to reach hard-to-reach and vulnerable populations. This will help to increase access to vaccination among vulnerable communities in various low-income and resource-poor settings.
Effects of Porphyromonas gingivalis lipopolysaccharide on the behavior of human dental pulp stem cells in vitro and their inflammation-related transcriptomics profile
Authors: He Fei , Zhu Jingya , Zeng Xiangni , Huang Rihong 
Published: August 2024

Abstract

Objective: This study aims to investigate the effects of Porphyromonas gingivalis lipopolysaccharide (P. g LPS) on the migration, proliferation, and odontoblast differentiation of human dental pulp stem cells (DPSCs) in vitro, and to explore the transcriptomics related to LPS-induced inflammation.
Methods: Human DPSCs were cultured and treated with 0.5-2 µg/mL of LPS for 24, 48, and 72 h, respectively. The expression of Arg-1, IL-1β, and TNF-α in DPSCs and cell viability was assessed. The time and concentration of LPS with the least influence on cell growth were selected to establish an in vitro pulpitis model. The CCK8 assay and Transwell method were used to detect the influence of LPS on cell proliferation and migration. LPS-stimulated DPSCs were induced to differentiate into odontoblasts, and the effect of LPS on cell differentiation was analyzed. RNA-Seq analysis was performed to investigate the transcriptomics profile related to LPS inflammation
Results: Based on the results of cell viability and expression of inflammatory factors, DPSCs pre-treated with 1µg/mL of LPS for 24 hours were utilized as the in vitropulpitis model in this study. Under these conditions, the migration and cell proliferation rate of DPSCs were significantly suppressed (P<0.01). Following induction by odontoblast differentiation medium for 21 days, the expression of odontoblast marker genes (DSPP, DMP1, and RUNX2) and alkaline phosphatase in LPS-stimulated cells was significantly inhibited (P<0.01), and the number of calcium staining-positive cell nodules reduced significantly compared to that in the control group. Transcriptomic analysis revealed enrichment of the TLR4/NF-κB signaling pathway and NOD-like receptor signaling pathway under LPS stimulation; KEGG analysis showed enrichment of PI3K-Akt signaling pathway, chemokine action pathway, TNF, NF-kappaB signaling pathway in DPSCs under inflammatory conditions.
Conclusions: DPSCs have the capacity to secrete inflammatory cytokines and contribute to tissue inflammatory reactions. Under inflammatory conditions in this study, their migration, proliferation, and differentiation abilities are inhibited. LPS participates in the regulation of cell signaling networks through multiple mechanisms.
Clinical significance: This study suggests that DPSCs may still maintain their proliferation and differentiation capabilities under severe inflammation in clinical practice. Therefore, controlling inflammation and enhancing the biological properties of stem cells are important strategies for promoting the healing of dental pulp.
Potential role of multiwalled carbon nanotube priming in boosting nitrogen metabolism and nutritional value during the sprouting process
Authors: Khaled Yasmen , Hegab Momtaz M. , Okla Mohammad K. , AlGarawi Amal Mohamed , Tawfik Wael Z. , AbdElgayed Gehad , Sayed Mona 
Published: August 2024

Abstract

Sprouts are well known for having a remarkable nutritional profile. Enhancing the tissue chemical composition and quality of sprouts is essential since these metabolites offer numerous health advantages. To this end, this study aimed to investigate the effects of priming with multiwalled carbon nanotubes (MWCNT) on the growth and nitrogen metabolism of four horticultural plants, namely T. foenum graecum, L. grandifloruum, L. sativum, and A. gravelones. The properties of our synthesized MWCNTs included three characteristic peaks 3434, 1539, and 1068 cm− 1 attributable to the stretching vibration of O–H, bending vibration, and C − O, respectively. MWCNT priming increased the sprouting process by inducing biomass and protein accumulation. MWCNT priming improved nitrogen metabolism, including amino acid and polyamine metabolism. At the amino acids level, there was an increase in amino acids levels (e.g., glycine, lysine, asparagine, and glutamic acid) as well as their metabolic enzyme activity including glutamine synthetase (GS), threonine synthase (TS), and glutamate synthase (GOGAT). Increased polyamine levels like spermine, putrescine, and spermidine were also associated with boosting their related biosynthetic enzyme activities i.e., arginine decarboxylase (ADC), ornithine decarboxylase (ODC), spermidine synthase, and spermine synthase. This improvement of nitrogen metabolic pathways highlights the potential of MWCNT to boost the tissue chemical composition of horticultural plants.