bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychological Status of Mothers with Firstborns Diagnosed of Cerebral Palsy
Authors: Assibey Dennis , Quayson Leticia , Banini Sandra , Agyenkwa Seth Kwame , Mensa-Bonsu Ellen A. , Yarfi Cosmos , Ashigbi Evans Yayra 
Published: November 2024

Abstract

Background:Cerebral palsy (CP) is a non-progressive neurological disorder affecting motor functions, caused by permanent brain damage during the prenatal, perinatal, or early postnatal stages. Although research highlights heightened stress, anxiety, and depression among mothers of children with CP, little is known about these psychological challenges faced by mothers of firstborns diagnosed with the condition. Therefore, the study seeks to evaluate the psychological status of mothers whose firstborns have been diagnosed with Cerebral Palsy in Ghana.
Methodology: A cross-sectional study with proportion sampling technique was used to collect data on the psychological status of 75 mothers whose first child had been diagnosed with CP. The study was conducted at four physiotherapy units in Ghana, namely Korle Bu Teaching Hospital, 37 Military Hospital, Greater Accra Regional Hospital, and Princess Marie Louise Children's Hospital. The data was collected using Depression, Anxiety, and Stress Scale (DASS-42) tool.
Results: The mean age of the participants was 29.61(SD=6.35), with majority 42.7%(n=32) having one child and almost half of the participants 49.3%(n=37) having primary education and 13.3%(n=10) having no education. The study found significant psychological burdens among mothers, with severe levels of depression (mean=22.51 ± 8.648) and stress (mean=26.53 ± 7.987). Notably, 46.7%(n=35) of mothers experienced moderate depression, while 33.3%(n=25) faced severe stress. Anxiety levels were generally normal (mean=5.85 ± 2.481), with 82.7% (n=52) of mothers in the normal range. The results showed strong significant positive correlations between depression and anxiety (r =0.721, p < 0.001), depression and stress (r = 0.930, p < 0.001) and anxiety and stress (r = 0.738, p < 0.001). Significant variations in stress were observed across age groups (χ2 = 19.783, p = 0.028), and a notable correlation was found between the number of children and depression levels (χ2 = 21.77, p = 0.030).
Conclusion: The study emphasizes the importance of supportive psychological interventions that are crucial to address the unique burdens faced by these mothers in the Ghanaian context and also highlights the need for Health Professionals (Physiotherapists) to identify mothers who need psychological interventions and make appropriate referrals.
Clinical Trial Number: Not Applicable.
A widespread porin-cytochrome complex Om(abc)B kickstarts microbial respiration and nanowire formation
Authors: Erwin Joseph , Shen Cong , Saldivar Vanessa , Morales Aldo Salazar , Pentalic Vasilije , Samatey Fadel , Dahl Peter , Gu Yangqi , Yalcin Sibel Ebru , Malvankar Nikhil 
Published: November 2024

Abstract

Microbial respiration via extracellular electron transfer (EET) drives several globally-important environmental processes and has applications in bioenergy, bioremediation, and bioelectronics. Geobacter sulfurreducens produce micrometer-long cytochrome nanowires for long-range (>10 µm) EET, but also require transmembrane porin-cytochrome complexes (PCCs), which can only perform EET on the cell surface. It was unknown why cells performing long-range EET need both PCCs and nanowires. Using Om(abc)B and OmcS as a model PCC and nanowire, respectively, for EET to Fe(III), we show that PCCs and nanowires form sequential, independent EET pathways where PCCs first kickstart EET and provide energy crucial for nanowire synthesis, and then nanowires perform long-range EET. Our model explains why both PCCs and nanowires are necessary. To understand the underlying EET mechanism, we purified native Om(ab)B and OmcB and found high excitonic coupling among hemes. Their midpoint reduction potentials (-182, -167 mV, respectively) are tuned for efficient electron transport. Additionally, OmcB transfers electrons to Fe(III) ~5 times more efficiently than OmcS. Our work suggests that the metabolic trade-off between PCCs and nanowires results from efficient proteome allocation. Notably, PCCs are widespread in environmentally-important bacteria and co-evolved with OmcS nanowires. This previously-undescribed nanowire synthesis strategy could accelerate EET in diverse microbes and environments.
Co-Infection of Human Papillomavirus Genotypes Exacerbates Symptomatic Risks and Transmission Dynamics
Authors: Tang Yue , Abudurusuli Guzainuer , Xu Jingwen , Tu Ruiqin , Hong Shishi , Ye Huiming , Chen Tianmu , Zhou Yulin , Lu Weihong 
Published: November 2024

Abstract

Background
The World Health Organization noted a significant rise in global human papillomavirus (HPV) prevalence among women, from 14\% (2019) to 24\% (2024), highlighting the need to understand the transmission dynamics and public health impact. Existing research focuses on single genotype infections and statistical methods, overlooking the effects of co-infection and multi-genotype interactions.
Methods
Data from HPV nucleic acid tests at two Xiamen hospitals were analyzed using cumulative link models to study symptom severity related to multi-genotype infections. An ordinary differential equation model estimated the reproduction numbers for different infection types.
Results
Increased risk of HPV-related diseases correlates with age (odds ratio, OR for ages 41–60: 37.07; over 60: 115.7). Multi-genotype infections correlate with greater disease severity (OR for two genotypes: 1.11; three genotypes: 1.21). Co-infections, especially involving high-risk genotypes, show higher transmissibility (median R0 for two high-risk genotypes: 6.82).
Conclusions
The findings urge a revision of HPV prevention strategies, focusing on the varying risks across age groups and the enhanced severity and transmissibility of multi-genotype infections. Enhanced surveillance and revised vaccination programs may be crucial to address these challenges.
Integrated Concept Engagement (ICE): An Intervention to Mitigate Neurophobia - A Pilot Study
Authors: Ismail Fatima Y. , Ljubisavljevic Milos R. 
Published: November 2024

Abstract

Background: The inherent complex nature of neuroscience teaching presents a unique challenge in medical education. Novel educational approaches are needed to address neurophobia in both undergraduate and postgraduate medical education. This pilot study investigated the feasibility of a novel educational approach, coined Integrated Concept Engagement (ICE), which merges the framework of the flipped classroom and blended learning to enhance learners' understanding of neuroscience and neurology.
Methods: The ICE model is a learner-centered intervention that utilizes important educational concepts, including the integration of subject-based knowledge via real-world clinical scenarios to foster critical thinking and problem-solving skills, spaced repetition, microlearning, anonymity and real-time feedback via an online interactive platform, within a safe learning environment.
Results: Our preliminary data suggest that the implementation of the ICE model is feasible and has enriched the learning experience by promoting self-identification of knowledge gaps, fostering collaborative learning, and improving the understanding of various neurological topics.
Conclusion: ICE has the potential to be a valuable teaching strategy in medical education. However, further research is needed to explore its scalability and applicability across different educational settings to assess its effectiveness in terms of knowledge retention and clinical reasoning skillsfully.
Fundamentals of occupational health and safety practices outside the workplace among health professionals in Ghana: An assessment of determinants of crash helmet use in the Tamale Teaching Hospital
Authors: Hussein Aziza , Opoku-Mensah Foster Abrampa , Amoafo Isaac Quansah , Saifu Kasim 
Published: November 2024

Abstract

Objectives
This study investigates the determinants of crash helmet use among healthcare professionals at Tamale Teaching Hospital (TTH) in Ghana. Grounded in the Health Belief Model, the Theory of Planned Behavior, and Social Cognitive Theory, the study emphasizes the roles of personal attitudes, perceived risks, and social influences in promoting safety behavior. By integrating these theoretical frameworks, the study highlights how individual beliefs and societal factors can impact the adoption of safety measures.
Methods
Employing a cross-sectional quantitative design, the study aimed to assess helmet usage among healthcare professionals. The target population consisted of approximately 4,000 staff members at TTH. Using the Krejcie and Morgan table, a sample size of 351 participants was determined. Stratified random sampling was implemented to ensure adequate representation across various job roles, including doctors, nurses, and paramedics. The dependent variable in this study was helmet usage, categorized as binary (uses/does not use), while the independent variables included job role, safety training (received/not received), years of experience, and attitudes towards safety. A structured questionnaire, incorporating closed and Likert-scale questions, was utilized to capture demographic data, helmet use habits, and safety attitudes. Statistical analyses were conducted using SPSS version 27, applying logistic regression, chi-square tests, and correlation analysis to assess the relationships between the variables.
Results
The findings indicated that safety training (β = 0.80, p < 0.001) and positive attitudes towards safety (β = 0.005, p = 0.005) significantly influenced helmet use. Medical doctors emerged as the most compliant group, demonstrating a higher likelihood of helmet usage (β = 0.43, p < 0.001). Years of experience exhibited varying effects on helmet compliance, with professionals at different career stages showing distinct usage patterns.
Conclusions
The study underscores the need for targeted interventions aimed at enhancing safety training and cultivating positive safety attitudes to improve helmet compliance among healthcare professionals. The study emphasizes that, to bolster helmet usage, healthcare institutions should expand safety training programs, promote a culture of safety, and develop tailored strategies to address the unique needs of various job roles within the healthcare setting.
Gamma-irradiation Induced Nonconventional Fluorescence Enhancement in Silicone Foams
Authors: Huang Zhendong , Liu Qiang , Jiang Binlian , Dou Ruiyang , Dai Bowen , Huang Wei , Chen Hongbing 
Published: November 2024

Abstract

An unexpected fluorescence enhancement phenomenon in silicone foams induced by gamma-irradiation is reported. These materials contain no traditional luminophores. The fluorescence intensity increases with the absorbed dose (within 1000 Gy). Time-dependent density functional theory (TDDFT) calculations suggest that the mechanism is a crosslinking-enabled emission process, which is enhanced by gamma-irradiation. The fluorescence changes are visible and can even applied to distinguish irradiated silicone foam samples with absorbed doses less than 25 Gy, achieving sensitive visualization of gamma-irradiation damage. The potential applications for radiation damage self-reporting and information encryption are demonstrated. The fluorescence intensity shows similar trends with radiolysis gas products (typical aging parameter) in early-stage irradiation, which can represent radiation-induced crosslinking and radiolysis respectively to reveal the changes of materials after low dose irradiation from two aspects. This work could broaden the application of nonconventional fluorescent materials and help understand the effects of low-dose radiation on silicone materials.
Analysis of the determinants of agricultural income of rural households in a context of climate variability : the case of the community of Toulom in the Far North of Cameroon
Authors: Douswe Benoit , NYORE NYORE 
Published: November 2024

Abstract

Agriculture remains a major source of livelihood in most developing economies and Cameroon in particular, therefore improving agricultural income is one of the most effective means of welfare improvement in these economies. This study focuses on the analysis of the determinants of agricultural income of rural households in a context of climate variability in the locality of Touloum in the Far North of Cameroon. To do this, we used secondary data from the Care International database (2021), with a sample size of 100 households. Multiple regression and statistical analysis shows that 46.6% of household heads have access to inputs. However, 39.6% had a background in agriculture. The study revealss that the agricultural income of households in the locality is between 4000 and 160,000 FCFA, and a majority are those with an agricultural income above 160,000 FCFA. This indicates that a greater proporttion of households in the study area have a high level of agricultural income. However, through the empirical analysis, individuals between the age range of 30 to 55 years, have low levels of education, limited area of cultivation and poor access to agricultural inputs which positively influences the agricultural income of the households in the locality of Toulom. These determinants of income must be integrated into rural agricultural development policies in order to improve the purchasing power of households and their well-being.
Resilient and Secure Control Frameworks for Cyber-Physical Systems in Smart Grids using Anomaly-Graph Fusion Isolation Framework (AG-FIF)
Authors: Alkhorem Azan Hamad , Alghamdi Tami Abdulrahman , Almalki Sultan Ahmed 
Published: November 2024

Abstract

In the realm of addressing the primary unfeasible issue in the cybersecurity in smart grids to ensures protection of critical infrastructure, a novel “Anomaly-Graph Fusion Isolation Framework (AG-FIF)” was introduced. In the existing, unauthorized access to smart meter data due to weak encryption and poor authentication in smart grid systems, while scalability challenges hinder real-time processing. Hence a novel, Integrated Anomaly Detection Ensemble (IADE) was introduced in this approach, offers strong defence against manipulation of scalability problems in smart grid settings with Support Vector Machine (SVM) for classification purpose, Random Forest for integration purpose and Autoencoders for reconstruction purpose. Moreover, the smart grid information networks are being swamp with DDoS attacks due to bad management of resources, while standard methods have a difficulty in detection and relief in dynamic distributed environment. Thus, a novel Graph-Enhanced Isolation Tree Framework (GEITF) was invented, which controlling network resources and lessening the effects of dispersed and dynamic DDoS attacks with Graph Convolutional Networks (GCNs) for modelling purpose, Isolation Forest for detection purpose and Decision trees for classification purpose. The AG-FIF framework delivers 98.55% accuracy, 97.35% F1-Score, low FNR (1.01%), FPR (1.03%), and excels in resource management, robustness, and scalability.
Effect of shell layer thickness on low temperature SCR performance of FeMnOx@TiO2 core-shell catalysts
Authors: Ge Jiachen , Zhang Xinfeng , Miao Jianping , Ge jiaqi , Chen Hongping 
Published: November 2024

Abstract

FeMnOx@TiO2 core-shell catalysts with different shell layer thicknesses were prepared by co-precipitation method to investigate the effect of shell layer thickness on the activity and stability of the catalyst for low-temperature denitrification. It was found that the NOx removal efficiency of FeMnOx@TiO2 with 60% (FM@T60) shell layer content was above 98% between 160 and 320 °C. The physicochemical properties of the catalysts were investigated and analyzed by characterization means such as XRD, BET XPS, H2-TPR. The TiO2 shell layer in FM@T60 effectively mitigated the toxic effect of SO2, provided a large specific surface and a concentrated pore size distribution facilitated the adsorption-desorption reaction of the catalyst. The large number of acidic sites in FM@T60 improved the NH3 adsorption performance. The abundant active components Mn3+, Fe3+ and a high proportion of chemisorbed oxygen of FM@T60 promoted the electron migration and conversion between the core-shell interface, which enhanced the redox capacity of the catalyst. The synergistic interaction between the core and shell of FM@T60 catalyst improved its low-temperature NH3-SCR reaction efficiency and sulfur resistance.
Face Image-based Emotion Recognition using Fractal Dimension and Deep Convolutional Neural Network
Authors: Karnati Mohan , Seal Ayan , Krejcar Ondrej 
Published: November 2024

Abstract

Face images are the primary non-verbal, face-to-face communication method used in criminal detection, depression analysis, mental disease identication, health forecasting, and other applications. As a result, there has been a lot of study on emotion recognition using face images in recent years. However, it remains a big challenge, especially when intra-class variations are high. A novel deep convolutional neural network (DCNN) on textured images is suggested in this work for solving the emotion recognition task. Firstly, the texture of original face images is measured by dierential box-counting-based fractal dimension to obtain low-level features. Secondly, the novel proposed DCNN framework explores facial landmarks as a form of a curve that produces distinct local facets to distinguish two expressions. The suggested DCNN combines features from many scales. This fusion of multi-scale features allows the proposed DCNN to gather more reliable and noise-resistant characteristics from an image's multiple portions. Furthermore, the proposed framework can preserve spatial and structural information and focus on describing details in local regions of the textured face images. Five publicly accessible benchmark databases, namely Extended Cohn-Kanade, Japanese Female Facial Expressions, Real-World Aective Faces, Karolinska Directed Emotional Faces, and Facial Expression Recognition 2013, are considered in this work to compare the proposed method with some state-of-the-art (SOTA) approaches based on four classication evaluation metrics: f1-score, recall, accuracy, and precision. Practical results exemplify that the proposed method defeats some SOTA approaches, proving its eectiveness for vision-based industrial systems such as autonomous driving, virtual reality, medical rehabilitation, etc.
Socio-Demographic and Health Risk Factors Associated with Cardiovascular Health Among Urban Joggers in Dhaka: A Cross- Sectional Study
Authors: Rahman Md. Habibur , Ahmed Mohsin , Shiblee SA , Hassan Mir Khalid , Mozomder Md Iftekhar Mahmud 
Published: November 2024

Abstract

Background: Ischemic heart disease (IHD) poses a significant threat to sustainable growth in the 21st century. Regular exercise does, in fact, reduce the risk of ischemic heart disease.
Objective: The goal of this study is to identify and analyse the differences in Socio-Demographic and Health Risk Factors Associated with Cardiovascular Health Among Urban Joggers in Dhaka.
Methods: A cross-sectional study was conducted with 322 participants who participate in walking activities in the parks of Dhaka on a regular basis. We used a convenience sampling approach to gather data on demographic variables, health risk factors, and a history of ischemic heart disease.
Results: The study population had an average age of 51.13 years, with 82.6% males and 17.4% females. Significant differences were found between genders in terms of education, occupation, economic status, BMI, and health factors. Males had higher rates of smoking and stroke, while females had higher rates of dyslipidemia. Age-wise, seniors had a higher prevalence of hypertension, diabetes, and IHD compared to younger groups. Overall, 15.2% of participants had IHD, with significant associations found between IHD prevalence and age, education, occupation, and BMI.
Conclusion: This study highlights the importance of demographic and health risk factors in understanding the heart health of urban joggers in Dhaka.
CDOM Absorption Characteristics and DOC Concentrations in Remote Sensing Inversion Studies of Karst Plateau Reservoirs
Authors: Kong Jie , Zhou Zhongfa , Xie Rukai , Wang Yanbi , Ding Caixia , Li Rui 
Published: November 2024

Abstract

Colored dissolved organic matter (CDOM), which is a type of dissolved organic matter (DOM) in water bodies with color-carrying optical properties and is also the main component of dissolved organic carbon (DOC), is an important component of optically active substances in water bodies. Remote sensing monitoring of its concentration is scientifically important for understanding the carbon cycle of water bodies and understanding the distribution of organic matter. In this study, two field sampling and experimental analyses were conducted in April and July 2024 in the Pingzhai Reservoir, a karst reservoir in Southwest China, to study the CDOM concentration and absorption spectral characteristics. The inverse model of the CDOM concentration was established on the basis of Sentinel-2B/MSI remote sensing data and the machine learning random forest method, and the inverse model of the DOC concentration was developed by combining the strong correlations between the CDOM and DOC concentrations, after which the water body DOC concentration was estimated. The effects of water quality parameters and meteorological factors on CDOM and DOC concentrations were subsequently explored. The results revealed that (1) the CDOM of the Pingzhai Reservoir could be well inverted on the basis of measured data, Sentinel-2B/MSI remote sensing data and a random forest model; (2) the CDOM of the Pingzhai Reservoir had a good correlation with the DOC, and the accuracy of the inversion model of the DOC was high (R2 = 0.72, MAE = 0.33, RMSE = 0.44); (3) the Pingzhai Reservoir SUVA254 (ratio of the absorption coefficient of the CDOM at a wavelength of 254 nm to the DOC concentration) values were relatively high, and the M values (ratio of the absorption coefficient of the CDOM at wavelengths of 250 nm and 365 nm) were relatively small, which indicated that the CDOM of the Pingzhai Reservoir tended to be input from land-based sources and had a relatively high content of humus; and (4) the results of the redundancy analyses indicated that water quality parameters such as the chlorophyll a (Chl-a), total suspended matter (TSM), turbidity (Tur), and dissolved oxygen (DO) had important effects on the CDOM concentration. This study contributes to the understanding of the changes in CDOM and DOC concentrations in the Pingzhai Reservoir and provides a reference basis for water ecological environmental protection and water resource management.
Benzene-Hexane Separation by Room Temperature Ionic Liquid: A Molecular Dynamics Simulation Study
Authors: Kumar Praveen 
Published: November 2024

Abstract

In this study, benzene extraction from benzene-hexane mixture in room temperature [Emim][NTf2] ionic liquid (IL) has been studied by employing molecular dynamics simulation. We observed that [Emim][NTf2] IL can extract benzene from benzene-hexane mixture efficiently and effectively even if it is present at < 10 wt%. The extraction of benzene from the benzene-hexane mixture is characterized from calculation of distribution coefficient (β) and selectivity (S). An important rational behind the benzene extraction by IL is observed that benzene-cation interactions are stronger than benzene-anion interactions, which is also supported by the DFT calculations.