bluuebunny/crossref_metadata_2025_split huggingface dataset:
ANALISIS FAKTOR UNTUK PEMBENTUKAN INDEKS KESEHATAN IBU DI PROVINSI KALIMANTAN SELATAN
Authors: Noorsa'adah Noorsa'adah , Salam Nur , Anggraini Dewi 
Published: August 2024

Maternal health is an important health problem because mothers are the printers of the next generation. Maternal health can describe the quality of the child to be born, so maternal health is very important to pay attention to. In Indonesia, the government has made various efforts to improve maternal health, which is still far from being expected. In this improvement effort, it is necessary to have a measure that can be used to monitor and evaluate the health development carried out, especially in the Province of South Kalimantan. Therefore, this study aims to establish a measure that can be used to describe maternal health through a composite index approach. The formation of the composite index is carried out using a technique offered by the Organization for Economic Co-Operation and Development (OECD), namely using factor analysis. Factor analysis was conducted to reduce indicators that were not significant in describing maternal health. Furthermore, the composite index formed is used to group districts/cities to make it easier to set priorities for maternal health development in South Kalimantan Province. Based on factor analysis results, the final indicators used to form the maternal health index amounted to 24 of the 30 initial indicators. After that, from the formation of the maternal health index using the composite index, it was found that the best maternal health was dominated by the cities of Banjarbaru and Banjarmasin. Meanwhile, the worst maternal health index is in Hulu Sungai Selatan District. Keywords: Maternal Health , Composite Index, Factor Analysis.
ANALISIS REGRESI ROBUST M ESTIMATOR UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI LAMA STUDI MAHASISWA S1 STATISTIKA FMIPA UNIVERSITAS LAMBUNG MANGKURAT
Authors: Putri Widawati Annisa 
Published: August 2024

Robust regression is a statistical technique commonly used to model relationships between variables by minimizing the impact of outlier data. The use of robust regression M Estimator works well when there are outliers in the data. In this study, robust regression M estimator analysis will be applied to student study period data. The aim of this research is to determine the significant factors influencing the study period of Statistics undergraduate students at the Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. The results of the research show that the residual data characteristics are not normal and there are outliers in the data. Using the Robust Regression M Estimator, the F test results show that F calculated 6.2492 > F table 2.173112, which means rejecting H0, indicating that the independent variables collectively have a significant effect on the dependent variable. From the t-test, it is known that the Guidance Process for students while working on their final project, the Employment Status of students, and the GPA of students significantly affect the Study Period of students. Keywords: Robust Regression M Estimator, Study Period of Students, ULM
PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) MENGGUNAKAN PEMBOBOT KERNEL PADA KASUS TINGKAT PENGANGGURAN TERBUKA DI KALIMANTAN
Authors: Oktafiani Viona 
Published: August 2024

AbstractUnemployment is one of the serious problems in Indonesia's economic development. This unemployment describes human resources that have not been utilized optimally, as a result of which people's productivity and income have not been maximized, this can also be one of the causes of poverty and other social problems. This study aims to find out the general picture of the open unemployment rate in the Kalimantan region, get the best model and factors that influence the open unemployment rate and illustrate it through thematic maps. The study began with testing assumptions and spatial effects then continued with testing global regression modeling and Geographically Weighted Regression. The weighting function used in this study is adaptive gaussian kernel. The variable that has a positive effect on the open unemployment rate in the Kalimantan region is population density. While the variable that negatively affects the open unemployment rate is the Labor Force Participation Rate. Keywords: Open Unemployment Rate, Kalimantan Island, Spatial, GWR
Study on the Influencing Factors of Land Desertification Degree in Xilingol Grassland
Authors: Liang Shuning , Diao Mingguang , Zhang Chuyan , Liu Tianze 
Published: August 2024

Abstract

The study focuses on the Xilingol grassland in Inner Mongolia, collecting climate, surface, and human-related data for various banners and counties in Xilingol League. Initially, the correlation coefficient method was used to select the nine indicator factors most closely related to the degree of land desertification. Then, the Analytic Hierarchy Process (AHP) was utilized to rank the weights of these factors, constructing a system for evaluating the degree of land desertification, and an evaluation model was established using the comprehensive index method. This model introduced the land desertification evaluation index, dividing the degree of desertification into four levels, with highly and moderately desertified areas mainly distributed in the western part of Xilingol League, while moderately and mildly desertified areas mainly distributed in the eastern and southern regions. The study indicated that climatic factors are the primary factors affecting land desertification, followed by Humanistic and surface factors. Additionally, measures for preventing and controlling land desertification in different regions of the Xilingol Grassland were proposed, offering a scientific basis for formulating desertification prevention and control policies in the Xilingol League.
Estimation of Battery Life Cycle &amp; Remaining using Machine Learning
Authors: Khurana Ashish , Singh O P 
Published: August 2024

Abstract

Accurately estimating the remaining useful life (RUL) and capacity of lithium-ion batteries essential for optimizing the performance, safety, and efficiency of various applications, including electric vehicles, portable electronics, and renewable energy systems. Traditional methods for predicting battery health often fall short due to the nonlinear and intricate degradation patterns of lithium-ion batteries. This research paper introduces an innovative machine learning-based approach to enhance the prediction accuracy of RUL and capacity for lithium-ion batteries. By leveraging comprehensive datasets from a custom-built battery prognostics testbed at the NASA Ames Prognostics Center of Excellence (PCoE), which includes real-time measurements of charge, discharge, and electrochemical impedance spectroscopy across different temperatures. This study aims to significantly improve battery health monitoring and prognostics
Effect of the balcony configuration on the pollution concentration entered to the buildings
Authors: Heidari Ali Akbar , Eskandari Hamid , Peyvastehgar Yaghub , Mansourian Elham 
Published: August 2024

Abstract

Various factors affect the pollutant entering the buildings. One of which is the buildings form and its various components configuration. In this regards, balconies are one of the external components of the buildings, which play a significant role in pollutant entry to the buildings. Until now, various researches have been investigated the role of balconies on the pollutant exposure in the street canyons. While, this issue has not been investigated in relation to indoor spaces so far. Based on, this research investigates the role of balcony configuration on the pollutant concentration inside the buildings. For this, 16 balcony forms in terms of geometry, depth, length, and parapet were simulated in CFD. The building is located near an urban highway (as a source of pollution). Introducing the best balcony configuration in which increases the inside ventilation and prevent the pollutant entering the building is one of this research goal. For this the TOPSIS method is used. In this research, NO₂ emissions have been investigated as one of the pollutant particles generated by vehicle traffic. The results show that the balcony with less spatial confinement significantly prevent the pollution entering the building and increase the indoor air quality (IAQ). This article can lead to a deeper understanding of the impact of buildings configuration specially balcony forms on the indoor air quality in the middle rise urban buildings.
Cellular Network Traffic Prediction with Hybrid Graph Convolutional Recurrent Network
Authors: Zhang Miaoru , Zhou Hao , Yu Ke , Wu Xiaofei 
Published: August 2024

Abstract

This paper addresses the challenges of exponentially growing traffic in cellular networks by proposing a novel predictive model, HGCRN, which combines static graph convolutional recurrent neural network and meta-graph learning. The model is designed to effectively capture the complex spatio-temporal dependencies in network traffic, enhancing prediction accuracy and operational efficiency. By constructing graph adjacency matrices that go beyond mere geographical proximity, HGCRN offers a deeper understanding of the dynamic interactions within the network. Tested on real-world datasets from Telecom Italia and China Mobile, the model demonstrates significant improvements over traditional and state-of-the-art methods in terms of predictive accuracy and reliability.
β'-COP Mediated Loading of PPARγ into Trophoblast-Derived Extracellular Vesicles
Authors: Luo Xiaofang , Yin Biyang , Huang Biao , Cao Jinfeng , Wang Hao , Qi Hongbo 
Published: August 2024

Abstract

Fetal growth restriction is characterized by impaired fetal growth and dysregulated lipid metabolism. Extracellular vesicles have been proved playing a crucial role in transporting biomolecules from mother to fetus. However, the mechanisms underlying cargo sorting and loading into trophoblastic extracellular vesicles remain elusive. The focus of our study is to examine how the essential fatty acid regulator, peroxisome proliferator-activated receptor gamma (PPARγ), is sorted and loaded into extracellular vesicles originating from trophoblasts. In this study, proteomic analysis was performed on placenta derived extracellular vesicles from normal and fetal growth restriction pregnancies. Interactions between PPARγ and COPI subunit were evaluated using co-immunoprecipitation and bioinformatics simulation. Molecular dynamics simulations were conducted to identify critical binding sites between β'-COP, a subunit of COPI, and PPARγ. lentivirus-mediated knockout and overexpression were employed to elucidate the role of β'-COP in PPARγ loading into extracellular vesicles. We have demonstrated that PPARγ protein levels were significantly decreased in fetal growth restriction placental extracellular vesicles. β'-COP subunit directly interacted with PPARγ in trophoblasts, mediating its sorting into early endosomes and multivesicular bodies for extracellular vesicle incorporation. Knockout of β'-COP impaired PPARγ loading into extracellular vesicles. Molecular dynamics simulations identified critical binding sites for β'-COP and PPARγ. Mutation of these sites significantly weakened the β'-COP-PPARγ interaction and reduced PPARγ levels in trophoblastic extracellular vesicles. In conclusion, β'-COP mediates sorting and loading of PPARγ into trophoblastic extracellular vesicles. This study provide insights into regulating extracellular vesicles cargo loading and potential strategies for targeted cargo delivery from maternal to fetus.
The Effect of Variable Humidity on Corrosion Fatigue of AA7085-T7451 with Surface Salt Deposits
Authors: Montiel Gabriella , Free Brandon , Marino Gabriella , Schindelholz Eric , Dorman Sarah Galyon , Locke Jenifer 
Published: August 2024

Abstract

Corrosion fatigue (CF) crack growth is quantified as a function of relative humidity (RH) using AA7085-T7451 samples with NaCl deposited to understand the effect of deliquesced surface electrolyte droplets on CF performance when humidity varies. Fracture mechanics testing holding mechanical driving forces for cracking constant and incrementally increasing humidity show that crack growth rate (da/dN) more than doubles once RH moves above 78–80% RH. When decreasing RH, some amount of drying below the efflorescence RH (ERH) and/or a sufficient time is needed to pass in order for da/dN to return to that expected for a dry crack tip. All in all, this study establishes time of crack tip wetness as an important parameter for predicting fatigue lifetimes in atmospheric conditions, a parameter that cannot be solely predicted by RH, as accelerated cracking can continue for a limited amount of time even when RH is brought below the ERH.
Decoding Perinatal Mental Health: Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health through Explainable Machine Learning
Authors: Wang Guanjin , Bennamoun Hachem , Kwok Wai Hang , Quimbayo Jenny Paola Ortega , Kelly Bridgette , Ratajczak Trish , Marriott Rhonda , Walker Roz , Kotz Jayne 
Published: August 2024

Abstract

Background
Perinatal mental health significantly affects mothers, infants, and families. Despite their resilience and strengths, Aboriginal mothers experience disproportionate physical and mental health disparities. These result from historical and ongoing impacts of colonization and the resultant complex trauma. Conventional approaches to perinatal care present many barriers for Aboriginal mothers who frequently feel disengaged, apprehensive and unsafe. Current score-based risk-screening practices that algorithmically drive referrals, further ingrain fears including culturally biased judgments and child removal. The Baby Coming You Ready (BCYR) model of care centred around a digitised, holistic, strengths-based assessment, was co-designed to address these barriers. The recent successful pilot demonstrated BCYR effectively replaced all current risk-based screens. However, many professionals disproportionately rely on psychological risk scores, overlooking the contextual circumstances of Aboriginal mothers, their cultural strengths and mitigating protective factors.
Methods
To address this singular reliance screening psychometrics whilst supporting strengthened culturally considered clinical assessment, we propose a culturally sensitive eXplainable AI (XAI) solution. It combines XAI with Aboriginal lived experience, knowledge and wisdom to generate a clinical prediction model to support professionals and Aboriginal mothers being screened. The XAI solution can identify, prioritise, and weigh both maternal protective strengths and risk factors, quantify their relative impacts on perinatal mental-health and well-being at both group and individual levels.
Results
Different machine learning algorithms, including Random Forest, K-nearest neighbour, and support vector machine, alongside glassbox Explainable Boosting Machine (EBM) models, were trained on the real life de-identified data generated during the BCYR pilot. Additionally, XAI techniques like SHAP and LIME are utilised for interpretability on black box models. Results show the EBM model demonstrates superior performance in prediction, with an accuracy of 0.849, F1 score of 0.771 and AUC of 0.821. Global explanations across the entire dataset and local explanations for individual cases, achieved through different methods, were compared and showed similar and stable results.
Conclusions
This study demonstrated the potential for this XAI solution to enhance professionals' capability in culturally responsive clinical reasoning in perinatal mental-health screening to improve experience and strengthen outcomes for Aboriginal women.
Prevalence of Salmonella and E. coli and associated risk factors in Camel and Bovine Meat slaughtered at Jigjiga Municipal Abattoir, Somali Regional State, Ethiopia.
Authors: Ahmed Mustafe , Abdilahi Mahamed , Bashir Bashir 
Published: August 2024

Abstract

A cross-sectional study involving microbiological analysis was conducted from March 2021 to August 2021 on 384 healthy slaughtered camels and bovines at the municipal abattoir of Jigjiga. Since there is no report on the status of Salmonella and E. coli, the study was conducted with the objectives, of isolating and identifying Salmonella and E. coli from raw meats of camels and bovines slaughtered at Jigjiga municipal abattoir and assessing possible related risk factors towards the pathogens. A total of 384 carcass meat and swab samples were collected, isolated, and examined for the presence of Salmonella and E. coli. From the total samples examined, 64 were found E. coli positive (16.7%) and 44 were found Salmonella positive with an overall prevalence of 11.5%. Out of the total 185 meat samples of camels, 31 were found positive for Salmonella and 32 were found positive for E. coli. From the total 199 meat samples of bovines, 13 were found positive for Salmonella and 32 were found positive for E. coli. In the univariable logistic regression analysis result, Salmonella revealed a statistically significant difference among different ages (OR (CI) = 2.36 (1.195–4.679); p-value = 0.013). The multivariable regression analysis showed there was no statistically significance difference between the two sex groups (OR (CI) = 2.01 (0.892–4.544); p = 0.092). In an univariable logistic regression analysis result, the odds of meat contamination in young aged animals, with E. coli were three times higher than in adult animals, showing a statistically significant difference (OR = 2.83 (1.567–5.095; p = 0.001). The prevalence of E. coli was higher in animals with poor body condition (31.9%), followed by medium (15.5%) and good body conditioned animals (1.8%). In the multivariable logistic regression analysis, the odds of contamination of samples with E. coli from poor body condition animals showed 22 times higher than samples taken from good condition (OR (CI) = 21.8 (5.022–95.059); p = 0.000). The present study showed the presence of a considerable proportion of Salmonella and E. coli in camel and bovine meat samples. Thus, intervention programs such as awareness creation are essential to minimize the risk associated with the consumption of camel and bovine raw meat with the possibility of contamination with Salmonella and E. coli. Furthermore, we recommended the use of standardized procedures in slaughtering and handling camel and bovine meat, the provision of training on best practices of handling meat for handlers and raising the level of awareness of people.
Metabolic activities of bioactive compounds on cellular models of hepatosteatosis and adipose tissue: the role of peroxisome proliferator-activated receptors (PPARs)
Authors: DIAB Farah , ZBEED Hawraa , ZEAITER Lama , BALDINI Francesca , PAGANO Aldo , MINICOZZI Velia , VERGANI Laura 
Published: August 2024

Abstract

Obesity is associated with fatty liver disease. Available therapies show modest efficacy, and nutraceuticals with good effectiveness and safety are largely investigated. We focused on five natural compounds, three plant phenolic compounds (carvacrol, rosmarinic acid, silybin), and two thyroid hormones to compare their beneficial effects on two cellular models of hepatosteatosis and adipogenesis. All compounds ameliorated the lipid accumulation and oxidative stress in both models, but with different potencies. The peroxisome proliferator-activated receptors (PPARs) are pivotal controllers of adipogenesis and lipid metabolism. For the main isoforms, PPARγ and PPARa, we assessed their possible binding to the compounds by molecular docking calculations, and their expression pattern by real-time PCR. All compounds bind both PPARs with different affinity, while not all compounds affect their expression. The results may clarify the distinctive molecular mechanisms underlying the action of the five compounds in the different cell models with possible applications to treat obesity.
Does Social Participation Help Reduce Health Inequalities Among the Elderly? Evidence from CHARLS Data
Authors: Li Jie , Wang Hongxi , Huang Qianling , Lin Xin , Huang Yaoyao , Zeng Zhi 
Published: August 2024

Abstract

Background: In the context of active aging, social participation of older adults has received widespread attention. Previous research has demonstrated the health-promoting effects of social participation. However, health inequalities in older adults related to social participation require further research. This study examined whether social participation helps to reduce health inequalities in older adults and explored how best to improve health inequalities in older adults in terms of the multiple factors that influence their social participation.
Methods:This study used the data of the elderly over the age of 60 from the China Health and Retirement Longitudinal Study (CHARLS) in 2013,2015, and2018 to explore health inequalities related to social participation among older adults. By measuring health inequalities among older adults with concentration index and decomposing the concentration index we explored the impact of socio-demographic characteristics, socio-economic status, intergenerational support from children and disability on health inequalities related to social participation.
Results: We found that social participation not only promotes the health level of older adults, but also effectively reduces the level of health inequalities among older adults. At present, there are health inequalities in Chinese older population that favor those with higher levels of social participation. Health inequalities related to work status had little change over time, while those related to social interaction levels are gradually improving. The role of work status and level of socialization on health inequalities is influenced by socio-demographic characteristics, socio-economic status, intergenerational support, initial health status and other factors.
Conclusion: By analyzing the results of the study, we concluded that social participation helps to reduce health inequalities. Older adults should be encouraged to be more involved in social work at a younger age and more involved in social activities at an older age. Male older adults should be more involved in social activities, and society should pay more attention to the labor and employment security of women and elderly people with low education. contributing to the reduction of health inequalities. Policies should tend to promote higher level of socialization among the older adults in the central and western parts of the China. Families should be more encouraged to adopt older adults’ participation in intergenerational care.