bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contribution of community health workers to covid-19 screening: pilot experiment through community health care sites in the Democratic Republic of Congo, 2023.
Authors: Mungala Pomie Mutombo , Nkodila Aliocha Natuhoyila , Makindu Goethe Mukoko , Luntadila Papy Diazola , Basikila Paul , Bile Pitchou Lokoli , Bukasa Patrick Katuala , Nsio Justus , Kuzeye Jules Nakafwako , Tukadila Hervé Alex Kabangi , N’siala Adrien Kumbi , Kintaudi Léon Ngoma Miezi , Kalonji Albert Ntumba , Lukanu Philippe Ngwala , Likwela Joris Losimba 
Published: November 2024

Abstract

Background
The establishment of Community Health Care Sites (CHCS) is an opportunity for the use of SARS-COV-2 antigenic rapid diagnostic test (Ag RDTs) at the community level to contribute to the control of the circulation of SARS-CoV-2. The objective of this study was to evaluate the contribution of CHCS to the detection of Covid-19 cases in the Democratic Republic of Congo.
Methods
descriptive cross-sectional study using two approaches: a quantitative approach and a qualitative approach in 112 CHCS. Data on COVID-19 screening during 4 months of implementation of the FIND project from March to June 2023 as well as the opinions of providers and patients with covid-19 were collected.
Results
in total, 5733 patients presented for COVID-19 screening in the CHCS including 1590 (27.7%) in Kinshasa and 4143 (72.3%) in Kongo Central. 89.2% of them showed suspicious signs of Covid-19. Among them, 1430 and 3260 accepted the screening test in Kinshasa and Kongo Central respectively, i.e. an adherence rate of (89.9%) in Kinshasa and (78.7%) in Kongo Central. Among these cases tested, 4.9% were positive for Ag RDT. CHCS contributed 23% of the country's total cases in case detection. Among the factors listed by the CHW-CHCSs as determining the search for care for COVID-19 by the community, we noted the free COVID-19 Ag RDT, the awareness of the community by the Community health workers (CHWs) delivering care in CHCSs (CHW-CHCS), the friendly welcome for patients by CHW-CHCS and the geographical proximity of COVID-19 diagnosis through the CHCS established within the community. The Health zone management team, registered nurse, community leaders, CHW-CHCSs and Patients had expressed the wish to maintain the COVID-19 screening approach in the CHCS for reasons of free testing, bringing the diagnosis closer to the community and the earliness of the test.
Conclusion
the use of Ag-RDTs in the CHCS could contribute to a rapid improvement in access to screening tests for emerging infectious diseases, particularly for hard-to-reach populations, and accelerate efforts to interrupt the circulation of infectious agents, especially those with epidemic potential.
Real-World Outcomes with Sacituzumab Govitecan among Breast Cancer patients with Central Nervous System metastases
Authors: Grinda Thomas , Morganti Stefania , Hsu Liangge , Yoo Tae-Kyung , Kusmick Ross J. , Aizer Ayal A. , Giordano Antonio , Leone Jose P. , Hughes Melissa , Tolaney Sara M. , Lin Nancy U. , Sammons Sarah L. 
Published: November 2024

Abstract

Central nervous system (CNS) metastases are associated with poor prognosis in patients with metastatic breast cancer (MBC). In this retrospective study, we investigated the activity of sacituzumab govitecan (SG) in 33 patients with HER2-negative MBC and CNS metastases, including active, stable/treated, and leptomeningeal disease (LMD). SG demonstrated a modest CNS objective response rate of 4/30 (13%) and median CNS-progression-free survival of 2.9 months (95%CI:2.0-4.3) in a heavily pretreated population.
Elevated Frontal QRS-T Angle as a Predictor of Cardiovascular Risk in Graves’ Disease: A Comparative Study
Authors: Wang Zhen , Xu Jia , Fan Ting-ting , Gong A-juan , Li Meng-li , Zhu Nin-jun , Wang Xiao-chen 
Published: November 2024

Abstract

Purpose
Graves' disease (GD) is linked to cardiovascular complications, but reliable non-invasive predictors are limited. This study aimed to assess whether the frontal QRS-T (fQRS-T) angle could predict mortality and cardiovascular outcomes in GD patients.
Methods
Initially, we conducted a retrospective analysis of electrocardiogram (ECG) parameters from 291 GD patients compared with 96 healthy controls. GD patients were then categorized based on the presence of hyperthyroid heart disease. Using logistic regression, we identified predictors of cardiovascular outcomes. Subsequently, a retrospective cohort study followed 41 patients with an fQRS-T angle ≥90° and 82 matched controls over five years, assessing all-cause mortality and ventricular fibrillation (VF) using Kaplan-Meier analysis.
Results
Initial analysis showed that a significantly higher proportion of GD patients had an fQRS-T angle ≥90° compared to healthy controls (p< 0.001). Among GD patients, those with hyperthyroid heart disease were more likely to have an fQRS-T angle ≥90° (p < 0.001). Multivariate logistic regression analysis revealed that age, fQRS-T angle, thyroxine (T4), and platelet were independent predictors of hyperthyroid heart disease. In the cohort study, 41 GD patients with an fQRS-T angle ≥90° were selected as the exposure group, and 82 patients without a widened angle were selected as controls. Kaplan-Meier analysis demonstrated a significant difference in event-free survival between the groups, as assessed by log-rank test(P=0.001).
Conclusion
An increased fQRS-T angle is significantly associated with higher mortality and cardiovascular risk in GD patients. Measuring the fQRS-T angle could enhance risk stratification and guide clinical management in this population
Deep Learning-Based Prediction of Seawater Intrusion Using recurrent architectures: application on Kalymnos Island
Authors: Kopsiaftis George , Protopapadakis Eftychios , Kaselimi Maria , Voulodimos Athanasios , Mansour Majdi , Rallis Ioannis , Doulamis Anastasios , Doulamis Nikolaos , Mantoglou Aristotelis 
Published: November 2024

Abstract

This study explores the application of deep learning models (DL) for the prediction of seawater intrusion in coastal aquifers, under time-varying recharge and pumping conditions, for Kalymnos Island, Greece. The models, based on recurrent architectures, i.e. RNN, LSTM, and GRU, are trained to simulate the temporal dynamics of the seawater intrusion front. For the creation of the dataset, a detailed 3D variable density model was developed, capturing transient behavior over a 50-year period, using monthly recharge and pumping variations. The results demonstrate that bidirectional models exhibit superior performance in capturing complex dependencies, achieving lower prediction errors compared to unidirectional models. The study underscores the utility of DL models as efficient surrogates for computationally intensive hydrodynamic simulations, presenting a viable approach to sustainable coastal aquifer management.
A study on the configuration and spatial distribution of medical communities:Evidence from 832 poverty-stricken counties in East, Central, and West China
Authors: Wang Jie , Xia Dong , Lyu Zhiyu , Chen Mengdi , Chen Jiapeng , Zhang Lulu 
Published: November 2024

Abstract

Background
Although China has taken significant steps to alleviate poverty, supporting the current post-poverty rural revitalization is critical to avoid the phenomenon of a “return to poverty due to illness.” This means that widespread access to healthcare services is crucial. To that end, this study analyzes the regional differences and spatial distribution of the configuration of medical communities in 832 poverty-stricken labeled counties in East, Central, and West China in 2023. The results can provide a reference for optimizing the resource allocation of medical and health institutions in these counties.
Methods
A county-level 2023 vector map was created as a base map. ArcGIS 10.8 software was used to match health resource information with administrative divisions on the map, establishing corresponding spatial and attribute databases. Numbers of county hospitals, township hospitals, village clinics, and other community medical institutions in the 832 counties were captured from published statistics. Data on related medical communities were from China’s national dynamic monitoring system, established in January 2024. The allocation of medical communities was measured using Health Resource Density Index values, and regional differences and spatial distribution were analyzed through spatial autocorrelation and hotspot analysis.
Results
The spatial distribution of medical communities in the poverty-stricken counties in East, Central, and West China was imbalanced, with the HRDI values showing a global positive spatial autocorrelation with different types of medical and health institutions in different “hot spot” and “cold spot” areas. Among them, the resources in poverty-stricken counties in Hebei in the East were relatively good, whereas resources in the poverty-stricken counties in Qinghai and Ningxia in the West were relatively poor. Overall, the number of medical communities was higher in the East than in the West, where health resources in the East are relatively richer, and the population in the West relatively smaller.
Conclusion
There are inequities in the allocation of medical communities in the 832 poverty-stricken counties in East, Central, and West China. Recommendations include rationally optimizing the distribution of medical and health institutions, government investment in and coordination of their development, and the promotion of more integrated medical communities in these areas.
Interprofessional homebased reablement intervention for older adults in Sweden: A randomized controlled trial
Authors: Gustafsson Lena-Karin , Söderman mirkka , Johansson Carl , Elfström Magnus 
Published: November 2024

Abstract

Background
Reablement has a health promotive perspective. The goal is to enhance or maintain health and functional ability and, thereby, the ability of older adults to live in their own homes. The intervention described in this study was introduced so the older person would remain at home and be given the opportunity to regain or maintain functional ability physically, mentally, and socially to live independently and have optimal health and well-being. This paper aims to report the measured effects of reablement among the older adults in terms of bio-psycho-social health that emerged in the randomized controlled trial (RCT).
Methods
A sample of older adults (65+) was studied, consisting of those who applied for homecare in the municipal home service (n = 237), those who received intensive home reablement (IHR) carried out by an interprofessional team, and a control group who received home-based care as usual. Data were collected at three different occasions with validated instruments: at inclusion, after completion of IHR, and 3 months after completed intervention.
Results
Both groups improved significantly at the post-measurement, and this improvement was maintained at the 3-month follow-up regarding: global quality of life (HACT); general health (EQ-5D-5L); the self-estimates for mobility, hygiene, daily activities, pain/discomfort, anxiety/depression (EQ-5D-5L); psychological well-being (GP-CORE); self-assessed capacity to perform physical activities as well as satisfaction with performance (COPM); measures of physical activity capacity regarding lower extremities (SPPB); upper extremities (hand dynamometer test). No between group differences were statistically significant. At the 3-month follow-up, the average number of homecare hours was slightly lower in the group that underwent IHR than in the group receiving usual homecare and rehabilitation interventions, but the difference was not statistically certain.
Conclusions
In this RCT with a relatively short follow-up period, IHR was equivalent to traditional homecare regarding older people’s self-reported health, physical activity ability and number of homecare hours.
Trial registration:
ClinicalTrials.gov (https://clinicaltrials.gov/study/NCT03565614?intr=Reablement&rank=4) Registration number: NCT03565614. Registered on 1 January 2016.
Diagnostic Challenges of Dermatomyositis in a Resource-Limited Setting: Case report
Authors: Alemu Getachew Sahile , Ambaye Mekdes Tarekegn 
Published: November 2024

Abstract

Background: Dermatomyositis (DM) is a rare idiopathic inflammatory myopathy characterized by distinct cutaneous manifestations and progressive proximal muscle weakness. However, in areas with limited diagnostic tools without high index of suspicions, early identification is often challenging, increasing the risk of complications
Case presentation: We report the case of a 50-year-old Ethiopian woman who presented with progressive difficulty swallowing, proximal muscles weakness, and characteristic dermatologic manifestations Despite multiple emergency visits and extensive workups like chest CT and barium swallow, the diagnosis was delayed. Key findings included elevated muscle enzymes and low serum albumin, and a muscle biopsy revealed muscle fiber atrophy the diagnosis of dermatomyositis was confirmed by the ACR-EULAR classification criteria.
Management: we treated the patient with high-dose prednisolone and methotrexate as a steroid-sparing agent, along with nutritional support. Her muscle strength and dysphagia significantly improved within weeks of therapy initiation.
Conclusion: Our goal is to emphasizes the importance of early recognition of dermatomyositis, especially in resource-limited settings, to avoid unnecessary financially debilitating workup and prevent complications like malnutrition that is completely avoidable with early detection
Causal relations existed between age at menarche and the adverse pregnancy and perinatal outcomes: A Mendelian randomization study
Authors: Hou Wenhui , Wen Tianrui , Wang Ziyi , Ma Yuanlin , Li Zequan , Meng Yanlei , Bu Bei , Lu Manman 
Published: November 2024

Abstract

Background: To investigate whether age at menarche (AAM) is related to the pregnancy and perinatal outcomes. The purpose of this study was to investigate potential causal connections between AAM and adverse pregnancy and perinatal outcomes.
Methods: We performed a two-sample mendelian randomization (MR)study to investigate the causal effect of AAM on the pregnancy and perinatal outcomes. MR was carried out using summary data from genome-wide association studies (GWAS). The inverse variance weighted (IVW) method of MR was employed as the primary analysis to explore the causal relationship between AAM and adverse pregnancy and perinatal outcomes. The reliability of the results was validated by sensitivity analysis, encompassing Cochran's Q test, residual one analysis, MR-egger intercept regression analysis, and funnel plot. Independent queues were also employed to confirm the reliability of the results.
Result(s): Two-sample MR analysis with the IVW method suggested that AAM exerted causal effects on the risk of GDM (OR 0.902, 95% CI 0.854-0.954, P<0.001) and hypertensive disorders of pregnancy (OR 0.906, 95% CI 0.857-0.959, P=0.001) However, no causal effect was observed for other pregnancy and perinataldiseases (gestational oedema and proteinuria without hypertension, polyhydramnios, intrahepatic cholestasis of pregnancy, placenta disorder, placental abruption, placenta previa, premature rupture of membranes, postpartum haemorrhage, preterm labour, poor fetal growth and respiratory distress of newborn) (all P > 0.05). Further analyses of hypertensive disorder subtypes revealed causal effect of AAM ongestational hypertension (OR 0.907, 95% CI 0.845-0.974, P=0.007), pre-eclampsia or eclampsia (OR 0.871, 95% CI 0.810-0.937, P<0.001), and chronic hypertension (OR 0.859, 95% CI 0.766-0.964, P=0.010), but not chronic hypertension with superimposed pre-eclampsia (OR 0.753, 95% CI 0.508-1.116, P=0.158), but not chronic hypertension with superimposed pre-eclampsia (P> 0.05).
Conclusion(s): We confirmed a causal relationship between AAMand GDM, gestational hypertension, pre-eclampsia or eclampsia, chronic hypertension, but not chronic hypertension with superimposed pre-eclampsia. Further research is necessary to understand the underlying mechanisms.
Monocular Depth Estimation for Vehicles with
mounted camera in Mixed Traffic conditions
Authors: Taviti Jeevana Jyothi , Mekala Deepika , Chilukuri Bhargava Rama 
Published: November 2024

Abstract

Depth estimation is crucial for computer vision applications like autonomous driving. While traditional methods such as LiDAR and radar are expensive, making monocular depth estimation a more cost-efficient alternative. However, deriving accurate depth from a single image is challenging due to its under-constrained nature. Monocular cues like perspective, scaling, and occlusion aid human depth perception, which deep learning-based models leverage to map image features to depth values. This research addresses the complexities of monocular depth estimation in mixed traffic conditions commonly found on Indian roads, with diverse vehicle classes, road surfaces, and unpredictable obstacles. Traditional methods often struggle in these scenarios. To overcome this, our study integrates object detection with deep learning models to estimate vehicle distances from frontal camera views. Validated using dashcam and drone footage, the proposed approach achieves an RMSE below 4 meters for both training and testing datasets. Moreover, the ensemble models reduced RMSE by up to 60% and improved the \(\textnormal{R}^\textnormal{2}\) value by 40%. This solution significantly enhances the spatial awareness of autonomous vehicles, providing a robust means of navigating heterogeneous traffic environments.
Socially responsible leadership as perceived by nursing students and non-nursing students in Taiwan
Authors: Liu Hsing-Yuan , Han Hui-Mei , Hsu Ding-Yang , Han Chin-Yen , Huang Ding-Hau , Chen Hsiu-Fang , Li Yu-Chi , Lin Chin-Yen , Chao Chun-Yen 
Published: November 2024

Abstract

Background: Socially responsible (SR) leadership offers college students a comprehensive view of leadership, leading to a more holistic approach to achievement in leadership development. However, little is known about students’ leadership ability in Taiwanese higher education compared to those of Europe and the U.S.A., particularly in Taiwanese nursing education. The aims of this study were to 1) examine Taiwanese college students’ self-perceived competence in SR leadership; and 2) compare nursing and non-nursing students’ competence on eight core values of SR leadership in Taiwan.
Methods: This was a cross-sectional study. Data on SR leadership competence were collected from 96 Taiwanese college students (63 nursing students and 33 non-nursing students) enrolled in a leadership course incorporating design thinking contents. Cluster analysis and multiple regressions were applied to examine individual differences in students’ self-perceived SR leadership competence indexed by eight core values consisting of consciousness of self, congruence, commitment, collaboration, common purpose, controversy with civility, citizenship, and change.
Results: Students perceived their SR leadership at the medium-highlevels. Nursing students perceived greater overall mean SR leadership than the non-nursing students. Among eight core values, nursing students’ lowest mean score was consciousness of self. Taiwanese nursing students demonstrated significantly higher competence in controversy with civility of SR leadership competence than their non-nursing counterparts who had higher SR leadership capacity.
Conclusions: Nursing educators could target students’ controversy with civility of SR leadership competence may be the key to enhance students’ SR leader capacity.
Ring of capillary actuators as trap, tweezers, and ratchet for floating particles
Authors: Metzmacher Jean , Delens Megan , Vandewalle Nicolas 
Published: November 2024

Abstract

The manipulation of small floating objects represents a crucial step in mesoscale and microfabrication, or the self-aggregation of particles into functional devices. These tiny objects placed at a liquid-air interface interact due to the local liquid slopes created by their menisci. In this study, we present Dipolar Capillary Actuators (DCA), which can modify the local slope of the interface on demand thanks to the magnetic and capillary torque balance. We experimentally characterize these systems and provide a model to describe their ability to alter liquid slopes. These tiny DCA devices can attract or repel floating particles regardless of size, shape, and wettability. We present a proof-of-concept system comprising six DCAs arranged in a ring that serves as a capillary trap, tweezers, and ratchet.
Using Acoustic Emission Signal Analysis and Machine Learning Algorithms for Predicting Mechanical Hardness in Laser Directed Energy Deposition Parts
Authors: Xu Ke , Mahmoud Youmna , Manoochehri Souran , Vallabh Chaitanya Krishna Prasad 
Published: November 2024

Abstract

Despite recent advancements in Laser Directed Energy Deposition (LDED) Additive Manufacturing (AM) process, LDED fabricated parts frequently suffer from predictable and optimized mechanical performance and print quality. To address this, efforts are focused on predicting mechanical properties of fabricated parts using real-time monitoring data. This study aims to develop a non-destructive method coupled with machine learning (ML) models for predicting the mechanical hardness of samples printed by LDED process using acoustic emission (AE). The influence of key printing parameters, namely overlap ratio, dwell time, and number of layers, on the relationship between AE signal characteristics and the resulting mechanical hardness are investigated. AE features are extracted through signal processing from the raw signals acquired during the printing process. The mechanical hardness of the fabricated samples are then evaluated using Rockwell Hardness (HRB) measurements. For establishing a predictive relationship between the obtained AE features and the mechanical hardness, we develop and test three ML models, namely, Support Vector Regression (SVR), Gradient Boosting Regression (GBR), and Gaussian Process Regression (GPR). The performance of these models is assessed using two key metrics: Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Among the tested models, GBR demonstrated the highest accuracy, achieving an MAE of 1.41 and a MAPE of 1.88% in predicting the hardness of fabricated samples. These results highlight the potential of integrating AE sensors with advanced machine learning algorithms for real-time, non-destructive prediction of mechanical properties in LDED AM process.