bluuebunny/crossref_metadata_2025_split huggingface dataset:
Availability and readiness of healthcare facilities and their effects on antenatal care services uptake in Bangladesh: analysis of linked data
Authors: Khan Md. Nuruzzaman , Alam Md. Badsha , Chowdhury Atika Rahman , Kabir Md. Awal , Khan Md. Mostaured Ali 
Published: March 2023

Abstract
Background: Sustainable Development Goals 3.7 targets to ensure universal access to sexual and reproductive healthcare services, where antenatal care (ANC) is a core component. This study aimed at examining the influence of health facility availability and readiness on uptake of four or more ANC in Bangladesh.
Methods: The 2017/18 Bangladesh Demographic and Health Survey data were linked with the 2017 Health Facility Survey and analysed in this study. The associations of health facility level factors with recommended number of ANC uptake were determined. Multilevel mixed-effect poison regression model was used to determine the association adjusting for potential confounders.
Results: Nearly 44% of mothers reported four or more ANC uptake with significant variations across several areas in Bangladesh. The average distance of mothers' homes from the nearest health facilities was 6.12 km, which was higher in Sylhet division (7.90 km) and lower in Dhaka division (4.01 km). The overall uptake of the recommended number of ANC visits was positively associated with higher scores for the management (adjusted prevalence ratio (APR) 1.85; 95% CI, 1.16-2.82) and infrastructure (APR, 1.59; 95% CI, 1.09-1.82) of health facilities closest to mothers' homes. The APRs for mothers reporting using the recommended number of ANC were increased to 3.02 (95% CI, 2.01-4.19) and 2.36 (95% CI, 2.09-4.16) times for each unit increase in the availability and readiness scores to provide ANC services at the closest health facilities, respectively. Every kilometre increase in the average regional-level distance between mothers' homes and the nearest health facilities reduced the likelihood of receiving the recommended number of ANC visits by nearly 42%.
Conclusion: The availability of healthcare facilities closes to residence as well as their improved management, infrastructure, and readiness to provide ANC play crucial role to increase ANC services uptake. Policies and programmes should prioritise to increase availability, accessibility, and readiness of health facilities to provide ANC services.
The effect of perceived professional benefits on health professionals’ job engagement: The role of psychological availability and future perceived professional benefits
Authors: Wan Jin , Zhou Wenjun , Qin Mingyue , Zhou Haiming 
Published: March 2023

Abstract
Objective
To investigate the impact of perceived professional benefits on the job engagement of health professionals.
Methods
Correlation analysis, hierarchical regression analysis and bootstrap tests were used to analyze the influence of perceived professional benefits on the job engagement of health professionals and to examine the mediating effect of psychological availability and the moderating effect of future perceived professional benefits.
Result
Health professionals’ perceived professional benefits have a positive impact on their job engagement; psychological availability plays a mediating role between perceived professional benefits and job engagement. Future perceived professional benefits not only positively regulate the impact of perceived professional benefits on health professionals’ psychological availability but also positively regulate the mediating role of psychological availability between perceived professional benefits and job engagement.
Conclusion
Perceived professional benefits can improve the job engagement of health professionals by improving their psychological availability. However, for health professionals with low future perceived professional benefits, perceived professional benefits do not have a significant impact on their job engagement through psychological availability. Therefore, while improving health professionals’ perceived professional benefits, we should also improve their future perceived professional benefits.
Prediction of severe haemolysis during extracorporeal membrane oxygenation (ECMO) using multiple machine learning
Authors: liu kepeng , Wang Qi , Liang Yan , Zhang Yan , Gu Chen , Zheng Qiuyue , Liao Xiaozu , Li Binfei 
Published: March 2023

Abstract
Objective
We examine whether machine learning can be used to predict severe haemolysis in patients during extracorporeal membrane oxygenation.
Methods
The present study is a reanalysis of public data from 1063 ECMO patients. We trained the corresponding model using 5 machine learning and built a machine learning prediction model in Python.
Results
The top 5 factors found to influence haemolysis by data analysis were Sequential Organ Failure Assessment(SOFA), pump head thrombosis(PHT), platelet concentrate(PC)/ days, lactate dehydrogenase(LDH) pre, and fresh frozen plasma(FFP)/days, respectively. In the training group, among the algorithms, the highest AUC values rate was that of GradientBoosting (0.886). Our validation in the test group by different machine learning algorithms found that the three algorithms with the highest AUC values were 0.806, 0.781, and 0.759 for XGB, GradientBoosting, and Randomforest, respectively. In addition, among the algorithms, XGB had the highest accuracy with a value of 0.913.
Conclusions
According to our results, XGB performed best overall, with an AUC >0.8, an accuracy >90%. Besides, the top 5 factors found to influence haemolysis by data analysis were SOFA, PHT, PC/days, LDH pre, and FFP/days. Therefore, machine learning studies have better predictive value for whether patients develop severe haemolysis during ECMO.
Fingerprinting Hyperglycemia using Predictive Modelling Approach based on Low-Cost Routine CBC and CRP Diagnostics
Authors: Tahir Amna , Asghar Kashif , Shafiq Waqas , Batool Hijab , Khan Dilawar , Chughtai Omar , Chaudhary Safee Ullah 
Published: March 2023

Abstract
Hyperglycemia is an outcome of dysregulated glucose homeostasis in the human body and may induce chronic elevation of blood glucose levels. Lifestyle factors such as overnutrition, physical inactivity, and psychosocials coupled with systemic low-grade inflammation have a strong negative impact on glucose homeostasis, in particular, insulin sensitivity. Together, these factors contribute to the pathophysiology of diabetes (DM) and expanding landscape of its prevalence regionally and globally. The rapid rise in the prevalence of type 2 diabetes, therefore underscores the need for its early diagnosis and treatment. In this work, we have evaluated the discriminatory capacity of different diagnostic markers including inflammatory biomolecules and RBC (Red Blood Cell) indices in predicting the risk of hyperglycemia and borderline hyperglycemia. For that, 208,137 clinical diagnostic entries obtained over five years from Chugtai Labs, Pakistan, were retrospectively evaluated. The dataset included HbA1c (n = 142,011), complete blood count (CBC, n = 84,263), fasting blood glucose (FBG, n = 35,363), and C-reactive protein (CRP, n = 9,035) tests. Our results provide four glycemic predictive models for two cohorts HbA1c and FBG) each having an overall predictive accuracy of more than 80% (p-value < 0.0001). Next, multivariate analysis (MANOVA) followed by univariate analysis (ANOVA) was employed to identify predictors with the highest discriminatory capacity for different levels of glycemia. We show that the interplay between inflammation, hyperglycemic-induced derangements in RBC indices, and altered glucose homeostasis could be employed efficaciously for prognosticating hyperglycemic outcomes. Our results then conclude a highly sensitive and specific glycemic predictor that employs inflammatory markers coupled with RBC indices to predict glycemic outcomes (ROC p-value < 0.0001). Taken together, this study outlines a predictor of glycemic outcomes which could assist as a prophylactic intervention in predicting the early onset of hyperglycemia and borderline hyperglycemia.
Automated and Intelligent Synthesis of Oxygen-Producing Catalysts from Martian Meteorites by Robotic AI-Chemist
Authors: Jiang Jun , Zhu Qing , Huang Yan , Zhou Donglai , Zhao Luyuan , Guo Lulu , Yang Ruyu , Sun Zixu , Luo Man , Zhang Fei , Xiao Hengyu , Tang Xinsheng , Zhang Xuchun , Song Tao , Li Xiang , Chong Baochen , Zhou Junyi , Zhang Yihan , Zhang Baicheng , Cao Jiaqi , Zhang Guozhen , Wang Song , Ye Guilin , Zhang Wanjun , Zhao Haitao , Cong Shuang , Li Huirong , Shang Weiwei , Luo Yi 
Published: March 2023

Abstract
Living on Mars requires ability to synthesize living products locally using Martian resources. The synthesis of necessary chemicals from local materials, especially oxygen, which is essential for survival, is a challenging task. Here, we demonstrate a robotic AI-Chemist that automatically synthesizes and intelligently optimizes usable oxygen evolution reaction catalysts from Martian meteorites. The entire process including Martian ore pre-treatment, catalyst synthesis, characterization, and testing, and most importantly, the search of optimal formula, was performed without human intervention. Using a machine learning model derived from both first-principles data and experimental measurements, this methodology automatically and rapidly identified a globally optimal synthetic formula from more than 3 million possible compositions. The synthesized catalyst offers state-of-the-art performance with a current density of 10 mA/cm2 at an overpotential of 445.1 mV for more than 550,000 s, convincingly demonstrating the feasibility of the robotic AI-Chemist in the automatic synthesis of chemicals/materials for Mars exploration.
Flexible Phase Change Materials for Overheating Protection of Electronics
Authors: Feng Chang-Ping , Guan Xiao , Shi Meng , Wei Fang , Lan Hong-Bo , Yang Wei 
Published: March 2023

Abstract
With the increase of power density of electronics, adequate overheating protection of electronics is quite urgent, especially for wearable electronics integrated with biological tissues. Herein, flexible leakage-proof phase change materials (PCMs) with state-of-the-art overheating protection capability were fabricated by a novel static polymer swelling method. The resultant flexible PCMs exhibited a high latent heat energy storage density of 136.5 J/g and pronounced shape stability even with a temperature resistance of 120 °C. The demonstration of wearable electronics with our fabricated flexible PCMs as the overheating protection substrate illustrated that the generated heat of wearable electronics could be absorbed by flexible PCMs-based overheating protection substrate without causing a significant rise of skin and electronics temperature. The present study represents an important route to solve the overheating problem of wearable electronics integrated with biological tissues.
Trends and Geospatial Distribution of Stillbirths in Uganda, 2014 - 2020
Authors: Nakamya Petranilla , Komakech Allan , Migamba Stella M. , Biribawa Claire , Kwesiga Benon , Bulage Lilian , Ario Alex R. , Ocom Felix 
Published: March 2023

Abstract
Introduction

Uganda with 17.8 stillbirths per 1,000 deliveries in 2021, is among the countries with a high burden of stillbirths globally. In 2014, Uganda adopted the World Health Organization Every New-born Action Plan (ENAP), which targets < 10 stillbirths per 1,000 deliveries by 2035. Little is known about the trends of stillbirth burden since ENAP was introduced. We assessed the temporal, and spatial distribution of stillbirths, in Uganda, 2014–2020, to inform programming for safe pregnancies and deliveries.

Methods

We obtained and analysed stillbirth surveillance data from the District Health Information System, 2014–2020. A stillbirth was defined as the death of a foetus > 28 weeks of pregnancy or weighing > 1000g before or during birth and reported to a health facility. We calculated annual incidence rates of stillbirths per 1,000 deliveries at district, regional, and national levels. We used logistic regression to determine the significance of trends.

Results

The overall national annual incidence of stillbirths decreased from 24/1,000 deliveries in 2014 to 17/1,000 deliveries in 2020. During the same period, reporting rates declined from 71% in 2014 to 46% in 2020. The central region continuously had the highest incidence rate for the past 5 years despite the largest decline (OR = 0.79; CI = 0.77–0.83, P < 0.001) while the eastern region had the smallest decline (OR = 0.59; CI = 0.57–0.61, P < 0.001). Districts with persistently high annual incidence rates of stillbirths (> 30/1000) included Mubende, Kalangala, Hoima, and Nebbi. There was no difference in the reporting rates of the most- vs least-affected districts.

Conclusion

Even with suboptimal reporting, the incidence of stillbirths remained above the national target. Specific areas in the country appear to have particularly high stillbirth rates. We recommend continuous capacity building in managing pregnant women with an emphasis on the most affected districts, and investigation into the reasons for low reporting.
Electromyography Signal Based Hand Gesture Classification System Using Hilbert Huang Transform and Deep Neural Networks
Authors: S Mary Vasanthi , T Jayasree , A HAITER LENIN 
Published: March 2023

Abstract

In this paper, classification of hand gestures for the smart control of prosthetic hands is proposed. The surface Electromyography (sEMG) signals are used for classifying the hand gestures. The important attributes of the signal are extracted by finding Hilbert Huang Transform (HHT). These features are given as input to the Deep Neural Network (DNN) classifier for further classification. The experimental results show that high classification accuracy can be achieved for the proposed method compared to the other techniques.
Body mass index-based inflammation index is a promising prognostic predictor in older adult cancer patients
Authors: Huang Jiaxin , Zhang Xi , Tang Meng , Zhang Qi , Deng Li , Song Chunhua , Li Wei , Shi Han-Ping , Cong Ming-Hua 
Published: March 2023

Abstract

Background: Older patients with cancer often have a worse prognosis than the general cancer patient population due to decreased immune responses, chronic inflammation status, and malnutrition. The present study aimed to develop a novel body mass index (BMI)-based inflammation index and investigate its prognostic significance in older patients with cancer.
Methods: A total of 2376 patients were enrolled in this study. Concordance index (C-index) and receiver operating characteristic (ROC) curves were applied to compare the prognostic value of BMI-based inflammation indices. The overall survival (OS) was calculated and compared using the Kaplan–Meier method generated by the log-rank test. A Cox proportional hazard regression model was performed to identify independent predictors associated with OS.
Results: We recorded 1112 death cases during a median follow-up of 17.43 months. Both the area under ROC curves and the C-index of the BMI to C-reactive protein/lymphocyte ratio (BCLR) were higher than other inflammation indices. There was a significant L-shaped association between BCLR and all-cause mortality in older patients with cancer (P<0.001). A low BCLR was significantly associated with shortened OS and served as an independent risk factor for survival in older patients with cancer (hazard ratio=1.51, 95% confidence interval=1.32–1.73, P<0.001). In the subgroup analysis, a low BCLR was an independent risk factor for prognosis inpatients with lung cancer, upper gastrointestinal cancer, hepatobiliary and pancreatic cancer and colorectal cancer. In addition, the prognostic value of low BCLR was also confirmed in underweight, normal as well as overweight and obesity populations. Multivariate logistic regression models showed that a low BCLR was an independent risk factor associated with short-term mortality, malnutrition and cancer cachexia in older patients with cancer.
Conclusion: The BCLR is a promising indicator to assess nutritional-inflammatory status in older patients with cancer and can be used to identify patients with worse prognoses.
Blood proteins self-assembly, staphylococcal enterotoxins-interaction, antibacterial synergistic activities of biogenic carbon/FeSO 4 /Cu/CuO nanocomposites modified with three antibiotics
Authors: Alavi Mehran , Karimi Nasser 
Published: March 2023

Abstract
Nanocomposites based on copper, iron, and carbon materials are novel nanomaterials with both antibacterial and biocompatibility properties considerable to fight against multidrug-resistant bacteria. In this study, phytogenic carbon/FeSO4/Cu/CuO nanocomposites modified by three antibiotics including tetracycline, amoxicillin, and penicillin were employed to hinder antibiotic resistant bacteria of Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. Interaction of albumin and hemoglobin as major blood proteins with these nanocomposites were evaluated by SEM, FTIR, and AFM techniques. As in silico study, molecular docking properties of staphylococcal enterotoxin toxin A and B with (Z)-α-Bisabolene epoxide, (E)-Nerolidol, α-Cyperone, daphnauranol C, nootkatin, and nootkatone as major secondary metabolites of Daphne mucronata were obtained by AutoDock Vina program. Results of both in vitro and in silico surveys disclosed significant antibacterial activity of antibiotic functionalized carbon/FeSO4/Cu/CuO nanocomposites compared to antibiotics alone towards Gram-negative and Gram-positive bacteria. Synergistic activity of bio-fabricated carbon/FeSO4/Cu/CuO nanocomposites with antibiotics may be affected by main parameters of concentration and ratio of antibacterial agents, physicochemical properties of nanocomposites, bacterial type (Gram-negative or Gram-positive), antibacterial mechanisms, and chemical structure of antibiotics.
Enhancing spatiotemporal reconstructions of hydroclimate variability across the Mediterranean during the last millennium
Authors: Anchukaitis Kevin , Touchan Ramzi , Meko David , Kherchouche Dalila , Slimani Said , Sivrikaya Fatih , Ilmen Rachid , Mitsopoulos Ioannis , Stephan Jean , Attieh Jihad , Hasnaoui Foued , Camarero J. Julio , Sánchez-Salguero Raúl , Guibal Frederic , Piermattei Alma , Christou Andreas , Krcmaric Jordan , Cook Benjamin 
Published: March 2023

Abstract
The Mediterranean region is projected to experience severe drying trends and more extreme hydroclimate events as a consequence of anthropogenic climate change over the next century. In some places this signal may have already emerged from natural variability. Here we provide context for recent and future changes with a new high-resolution (0.5$^o$) spatial reconstruction of the Palmer Drought Severity Index (PDSI) using a tree-ring network that spans much of the last millennium. This network provides new information that extends and enhances the existing Old World Drought Atlas (OWDA), and we identify and attribute the differences between the OWDA and our reconstruction. We also reexamine previous conclusions about the severity of recent drought in the context of earlier centuries. We find that, in both the western Mediterranean and the Levant, recent dry periods are indeed the worst in at least the last 500 years, but our assessment of the significance and uncertainty of this finding is affected by differences in the tree-ring networks used for the reconstructions. Long millennium-length hydroclimate reconstructions in the Mediterranean provide the opportunity to understand variability and trends in the hydroclimate of the region, while extant uncertainties arising from the existing tree-ring chronology network and methodological choices call attention to locations that require further proxy collection and statistical scrutiny.
Effects of reversible SERCA inhibition on catecholamine exocytosis and intracellular [Ca2+] signaling in chromaffin cells from normotensive Wistar Kyoto rats and Spontaneously Hypertensive rats
Authors: Parada-Parra Oscar Javier , Hernandez-Cruz Arturo 
Published: March 2023

Abstract
Intracellular [Ca2+]c signaling and catecholamine (CA) exocytosis from adrenal chromaffin cells (CCs) differ between mammalian species. These differences partly result from the different contributions of Ca2+-induced Ca2+-release (CICR) from internal stores, which boosts intracellular Ca2+ signals. Transient inhibition of the smooth endoplasmic reticulum (SERCA) Ca2+ pump with cyclopiazonic acid (CPA) reduces CICR. Martínez-Ramírez et al. authors found that CPA had opposite effects on catecholamine secretion and intracellular Ca2+ signals in mouse and bovine CCs, where it enhanced and inhibited exocytosis, respectively. After CPA withdrawal, exocytosis diminished in mouse CCs and increased in bovine CCs. These differences can be explained if mouse CCs have weak CICR and strong Ca2+ uptake, and the reverse is true for bovine CCs. Counterintuitively, CPA reduced the amplitude of Ca2+ signals in both mouse and bovine CCs.
Here we examined the effects of CPA on stimulated CA exocytosis and Ca2+ signaling in rat CCs and investigated if it alters differently the responses of CCs from normotensive (WKY) or hypertensive (SHR) rats, which differ in the strength of their CICR. Our results demonstrate that CPA application inhibits the voltage-gated exocytosis and Ca2+ transients in rat CCs, regardless of strain (SHR or WKY). CPA inhibited Ca2+ signals significantly more in SHR CCs than in WKY CCs. Despite the greater phylogenetic distance from the most recent common ancestors, CPA alters the CA secretion in rat CCs more similarly to bovine CCs than mouse CCs. Rat CCs display Ca2+ signals with one or two components. In CCs with two Ca2+ components, simultaneous amperometry also shows two bursts of exocytosis. The late component is abolished with CPA and Ryanodine, suggesting that it is due to CICR. Agents such as CPA that inhibit the SERCA pump and suppress catecholamine secretion indiscriminately from WKY and SHR in CCs are not likely helpful as therapeutic agents for hypertension.
(EERO) Energy-Efficient Fog Resource Optimization Model for Scientific Workflow Applications
Authors: Rahul Satyakam , Bhardwaj Vinay 
Published: March 2023

Abstract
Network congestion and increased latency may result from the speedy development of intelligent services and Internet of Things devices contacting cloud data centers. Fog computing meets the latency and privacy needs of operations running at the network edge by focusing on widely linked heterogeneous devices. The intricate and stringent Quality of Service limitations makes allocating resources in this paradigm challenging. We investigate workflow scheduling in fog-cloud systems to give an energy-efficient task plan within tolerable application completion times. The Energy Efficient optimization mode is presented. This paper investigated the outcomes of algorithms created by the community to address issues with energy management. The objective is to provide energy-efficient algorithms for a particular problem that minimize service compromise while reducing energy usage. The algorithms must attain a provably good performance, a crucial requirement. The goal is to find an efficient Pareto front by employing a Bayesian method with a maximum likelihood procedure for processing the fog node tasks while improving task scheduling by integrating heuristic methodologies such as PEFT and the Multi-objective genetic algorithm.