bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating unintended pregnancy and induced abortion in Liberia: A nationally representative cross-sectional survey
Authors: Ushie Boniface Ayanbekongshie , Giorgio Margaret , Juma Kenneth , Donzo Vekeh , Philbin Jesse , Lu Lily , Bankole Akinrinola , Massaquoi Moses , Ouedraogo Ramatou , Dunbar Nelson 
Published: July 2024

Abstract

Background: More than 60% of unintended pregnancies end in induced abortions globally. In Liberia, limited access to contraceptives caused by health system challenges and sociocultural barriers leads to many unintended pregnancies. Nevertheless, very little is known about the incidence of induced abortion and unintended pregnancy in the country. This study aimed to estimate the incidence of induced abortion and unintended pregnancy in Liberia in 2021.
Methods: The study utilized the Abortion Incidence Complications Method. First, we estimated the total number of induced abortions that resulted in women seeking facility-based post-abortion care in 2021 using data from a nationally representative sample of health facilities (n=128). Next, we used data from a survey of experts on abortion in Liberia (n=89) to estimate the proportion of induced abortions that resulted in complications treated in health facilities in 2021. The inverse of this proportion is a multiplier, which was applied to the estimate of the total number of induced abortion-related complications treated in health facilities to obtain the total number of induced abortions in 2021. We complemented this estimate of induced abortion with the Demographic Health Survey data to estimate the incidence of unintended pregnancies in Liberia in 2021.
Results: We estimated that 14,555 patients received post-abortion (PAC) treatment in Liberia in 2021. Approximately 58% of these post-abortion care cases (n=8,461) were due to induced abortions. Accounting for induced abortions that had complications that did not require facility-based treatment and those without complications, we estimated that 38,779 induced abortions occurred in Liberia in 2021, corresponding to a national induced abortion incidence rate of 30.7 per 1,000 women of reproductive age (15–49). The unintended pregnancy rate among women of reproductive age was 86.54 per 1,000, and approximately 35% of all pregnancies ended in an abortion.
Conclusions: Despite the legal restrictions on abortions, study findings show that unintended pregnancy and induced abortion are common in Liberia. There is a need for strengthened efforts to increase access to contraceptives, safe abortion care under legal indications, and quality PAC to improve socioeconomic and health outcomes for women and girls in Liberia.
Super-resolution 3D Tomography of Vector Near-fields in Dielectric Optical Nano-resonators
Authors: Tao zhensheng , Zhu Bingbing , Cai Qingnan , Liu Yaxin , Zhang Sheng , Liu Weifeng , he qiong , Zhou Lei 
Published: July 2024

Abstract

All-dielectric optical nano-resonators, exhibiting exotic near-field distributions upon excitations, have emerged as low-loss, versatile and highly adaptable components in nanophotonic structures for manipulating electromagnetic waves and enhancing light-matter interactions. However, achieving experimental full three-dimensional characterization of near-fields within dielectric nano-resonators poses significant challenges. Here, we develop a novel technique using high-order sideband generation to image near-field wave patterns inside dielectric optical nano-resonators. By exploiting the phase-sensitivity of various harmonic orders that enables the detection of near-field distributions at distinct depths, we achieve three-dimensional tomographic and near-field imaging with nanometer resolution inside a micrometer-thick silicon anapole resonator. Furthermore, our method offers high-contrast polarization sensitivity and phase-resolving capability, providing comprehensive vectorial near-field information. Our approach can potentially be applied to diverse dielectric metamaterials, and becomes a valuable tool for comprehensive characterization of near-field wave phenomena within dielectric materials.
Suprachiasmatic nucleus dysfunction induces anxiety- and depression-like behaviors via activating the BDNF-TrkB pathway of the striatum
Authors: Xie Wei , L Xiaotao , Ding Yuewen , Zhu Xiaoyu , Qiu Jing , Shen Xiaoqin , Xiong Yifan , Zhou Jieli , Liang Xiaoshan 
Published: July 2024

Abstract

The circadian rhythm system consists of a master clock located in the suprachiasmatic nucleus (SCN) of the hypothalamus and peripheral clocks dispersed throughout other brain areas (including striatum, Str) as well as various tissues and organs. Circadian rhythm disturbance is a major risk factor and common comorbidity for mood disorders, especially anxiety and depression. Bmal1 is one of the fundamental clock protein genes that is required to maintain circadian rhythm. Recent research has revealed a link between suprachiasmatic nucleus dysfunction and anxiety and depression, but the underlying mechanisms remain to be fully elucidated. This study aimed to investigate how circadian rhythm disturbance may lead to anxiety and depression-like behaviors. Through behavioral tests, virus tracing, molecular biology and other techniques, we found neural connection from the suprachiasmatic nucleus to the striatum. SCN lesions and Bmal1flox/flox+pAAV-hSyn-Cre-GFP (conditional knockout, cKO) mice exhibited disruptions in core body temperature rhythm, as well as anxiety- and depression-like behaviors. Importantly, these mice displayed altered expression patterns of clock protein genes and an upregulation of the Brain-Derived Neurotrophic Factor (BDNF) - Tyrosine Kinase receptor B (TrkB) signaling pathway within the striatum. Microinjection of the TrkB inhibitor ANA-12 can effectively reverse anxiety and depression-like behaviors. These findings indicate that suprachiasmatic nucleus dysfunction may contribute to the pathogenesis of anxiety and depression through upregulation of the BDNF-TrkB pathway in the striatum, potentially mediated by neural projections from the SCN. Bmal1 gene within SCN may represent a novel therapeutic target for mood disorders.
Energy-aware Real-time Task Partitioning on Multi-core Processors with Shared Resources
Authors: Konswa Amina , El-Henawy Ibrahim , Abdelatif Amr Mohamed 
Published: July 2024

Abstract

Nowadays, multi-core processors are increasingly adopted in embedded systems. These processors can achieve energy consumption minimization by employing dynamic voltage/frequency scaling techniques (DVFS). Several energy-aware real-time task partitioning algorithms have been suggested for multicore processors. While many of these algorithms focus on independent real-time tasks, there has been relatively limited research dedicated to task synchronization. This paper focuses on optimizing energy consumption by assigning dependent real-time tasks to a multi-core processor. When multiple tasks on different cores access shared resources simultaneously, it can result in longer blocking times, consequently increasing the execution time of tasks. This situation can result in missing hard deadlines, potentially causing system failure. The Highest Task-Based Partitioning (HTBP) algorithm is structured to decrease overall energy consumption while ensuring deadlines are met. It allocates tasks with high similarity (accessing the same set of resources) to the same core, effectively minimizing the occurrence of remote blockings. In the evaluation of the HTBP algorithm, we compared it with similarity-based partitioning (SBP), worst-fit decreasing (WFD) and best-fit decreasing (BFD). Our results indicate that our proposed (HTBP) algorithm outperforms SBP, WFD, and BFD algorithms (bin-packing algorithms), minimizes the overall energy dissipation, and improves schedulability.
Effect of Rounded Trailing Edges on Unsteady Airfoil Loading at Low Reynolds Numbers
Authors: Lee Yi Tsung , Ramesh Kiran , Gopalarathnam Ashok 
Published: July 2024

Abstract

The steady potential flow past a traditional airfoil with a round leading edge and a sharp trailing edge can usually be simulated using the assumption of Kutta condition at the trailing edge. However, for the airfoil undergoing unsteady motion, especially at high reduced frequencies, numerical and experimental studies have shown that the flow can curve around the trailing edge, resulting in the stagnation point moving away from the trailing edge. This phenomenon becomes increasingly apparent when the airfoil has a round trailing edge instead of the usual sharp one. In this work, the effect of trailing edge roundness on the unsteady airfoil flow is studied by generating airfoil shapes with various amounts of roundness. Computational fluid dynamics (CFD) studies of unsteady flow past airfoils with different rounded trailing edges are performed to study the effects of the trailing-edge suction force on the flowfield. A composite pressure difference model universally valid on the entire airfoil is derived in this work to take into account the edge radii and the corresponding edge suction effect. We show that, in scenarios where the stagnation point moves away from the trailing edge, a trailing edge suction force associated with the flow curving around the trailing edge is necessary to better estimate the airfoil unsteady load distribution.
QxEAI: Quantum-like evolutionary algorithm for automated probabilistic forecasting
Authors: Xin Kevin , Xin Lizhi 
Published: July 2024

Abstract

Forecasting, to estimate future events, is crucial for business and decision-making. This paper proposes QxEAI, a methodology that produces a probabilistic forecast that utilizes a quantum-like evolutionary algorithm based on training a quantum-like logic decision tree and a classical value tree on a small number of related time series. We demonstrate how the application of our quantum-like evolutionary algorithm to forecasting can overcome the challenges faced by classical and other machine learning approaches. By using three real-world datasets (Dow Jones Index, retail sales, gas consumption), we show how our methodology produces accurate forecasts while requiring little to none manual work.
Automatic 12 Volts Battery Charge Controller for Telecommunication Applications
Authors: Tirones Sylvester , Kumar Raj 
Published: July 2024

Abstract

Everyday electronic applications involve the use of electric energy to do work. The increase in the supply of electric appliances has put enormous pressure on the electricity demand. In most remote locations with equipped electronic applications, DC power is required for their functionality, and thus batteries also play a vital role in terms of energy storage. Rechargeable batteries are extensively used as backup power in applications that require constant use, but these batteries can become quite worthless without a battery charger. Telecommunication applications provide an essential role in transmitting and receiving information in a variety of places, and as such, to enable constant use of power supply to those instruments, a battery charger with correct battery specification for charging and discharging becomes very handy. Therefore, the proposed design of an automatic 12-volt battery charge controller for telecommunication applications is paramount during the disruption of the main power source and enables the further run-time for these telecommunication appliances to operate smoothly. It details the experimental aspect of the design to the component level, and software-based simulation to test the working of the prototype to be within a specific control limit for charging and discharging of the 12-volt Lead-acid battery.
Healthcare Seeking Behavior of Mothers of Under-five Children With Febrile Illness and Associated Factors in Uyo Metropolis
Authors: OKPOKOWURUK FRANCES SAM 
Published: July 2024

Abstract

Background
The under-five mortality rate which is an index of population health continues to be high in sub Saharan Africa, Nigeria and Akwa Ibom state of Nigeria which is the setting for this study. The healthcare seeking behaviour of mothers is an important determinant of illness outcome in children. Thus, the objective of this study was to assess the percentage of mothers of febrile under five children exhibiting appropriate healthcare seeking behaviour and the factors that predict this behaviour.
Methods
This quantitative study was carried out using a self-administered/online structured questionnaire which elicited sociodemographic information from mothers aged 18–49 years with under-five children who had had a fever in the four weeks prior to the study. The variables were subjected to statistical analysis to test for association between appropriate healthcare seeking behaviour and various sociodemographic variables and to identify significant predictors of appropriate healthcare seeking behaviour.
Results
Three hundred and twenty mothers/caregivers were recruited into this study. Only 12.5% of the mothers exhibited appropriate healthcare seeking behaviour. Multivariate analysis identified increasing levels of educational attainment (aOR = 0.18, p = 0.002), increased family size ≥ 7(aOR = 7.03, p = 0.02), increasing average monthly family income (aOR = 3.44, p = 0.027) and the reason proffered for going to the health facility which was to prevent worsening of the condition (aOR = 11.72, p = 0.021) as significant predictors of appropriate healthcare seeking behaviour.
Conclusion
The level of appropriate healthcare seeking behaviour in mothers/caregivers in this study was abysmally low. Social determinants of health amongst other factors were found to be significant predictors of healthcare seeking behaviour.
Impact of Primary Health Care data quality on their use for infectious disease surveillance
Authors: Florentino Pilar T. V. , Bertoldo-Junior Juracy , Barbosa George C. G. , Cerqueira-Silva Thiago , Oliveira Vinicius A. , Souza Kate T. , Garcia Márcio H. O. , Penna Gerson O , Boaventura Viviane , Ramos Pablo Ivan P. , Barral-Netto Manoel , Marcilio Izabel 
Published: July 2024

Abstract

Background
The surge of emerging and re-emerging infectious disease outbreaks underscores the need for robust Early Warning Systems (EWS) to inform mitigation and response measures. Administrative healthcare databases offer valuable epidemiological insights without imposing additional burdens on health services. However, administrative data are primarily collected for operational use, making data quality assessment crucial to ensure accurate interpretation of epidemiological analysis results. This study focuses on the development and implementation of a Data Quality Index for surveillance integrated into an EWS for influenza-like illness outbreaks based on a nationwide Primary Health Care (PHC) dataset.
Methods
We established a composite indicator measuring completeness and timeliness of PHC data from the Brazilian National Information System on Primary Health Care. Completeness was defined as the proportion of weeks within an 8-week rolling window with any register of encounters. Timeliness was assessed by calculating the interval between the date of encounter and its corresponding registry in the information system. Using the backfilled PHC dataset as a gold standard, we evaluated the impact of data quality in the EWS for influenza-like illness outbreaks using different levels of data quality of the weekly updated real-time PHC dataset across all 5,570 Brazilian municipalities from October 10, 2023, to March 10, 2024.
Results
In the study period, the backfilled PHC dataset registered 198,335,762 encounters due to influenza-like illness, averaging 8,623,294 encounters per week. Analysis of concordant warnings between the backfilled and the real-time dataset showed that 100% completeness and at least 80% timeliness were optimal for the highest concordance. Municipalities with at least 60% of weeks featuring a suitable Data Quality Index showed the highest concordance of warnings between the backfilled and real-time datasets.
Conclusion
Our study highlights the critical role of data quality in enhancing the performance of early warning systems based on PHC data. In addition, we provide a practical approach for monitoring data quality in real time. Our findings demonstrate that optimal completeness and timeliness of data significantly impact the EWS's ability to detect ILI outbreaks. Continuous monitoring and improvement of data quality should be prioritized to ensure the reliability and effectiveness of surveillance systems.
Grocery store workers knowledge, attitudes, and barriers influencing uptake of COVID-19 vaccine: A qualitative study
Authors: Kaur Harpriya , Esqu Nikie Sarris , Payne Julianne , Durocher Becky , Strazza Karen , Sivén Jacqueline , Flynn Michael A. , Viator Catherine , Menéndez Cammie Chaumont 
Published: July 2024

Abstract

Objective
The objective of the study was to gain insight into the knowledge, behavior, attitudes and beliefs related to COVID-19 vaccines, and communication preferences of U.S. grocery store workers.
Methods
In-depth interviews were conducted from May 2021 through June 2022 with 75 grocery store workers across the United States (US) who identified themselves as Asian, Black, Hispanic, or White persons. Researchers used maximum variation sampling to recruit a diverse sample by race and ethnicity, age, gender, union status, and geographic location. Rapid Turn-Around (RTA) techniques were utilized to conduct qualitative data analysis.
Results
Of the 75 total participants, 39 were female and 36 were male. Participants identified as Asian (n = 16), Black or African American (n = 19), Hispanic or Latino (n = 16) and White (n = 22) persons and ranged in age: 18–34 years (n = 28), 35–49 years (n = 20) and ≥ 50 years (n = 27). Most (79%) participants reported that they were vaccinated against COVID-19 and considered various factors when deciding to get vaccinated such as protecting oneself and loved ones, vaccine safety and potential side effects, others’ experiences with vaccination, the vaccine development process, beliefs regarding their immune systems, vaccine effectiveness, and similarities between the COVID-19 and influenza vaccines. Most unvaccinated women expressed concerns about side effects, compared to about half of the unvaccinated men. Specifically, most unvaccinated female workers had concerns related to fertility issues. Participants’ attitudes regarding employer vaccine incentives and mandates and sources used to learn about the vaccine varied by vaccination status. Although participants’ employers had provided them information regarding the COVID-19 vaccine, these communications were not in participants’ preferred formats.
Conclusion
Unvaccinated participants’ attitudes and beliefs suggest there is a critical need to address misinformation related to COVID-19 vaccines and potential side effects among grocery store workers. To promote fair and equitable access to health information, culturally and linguistically appropriate health communication efforts aligned to grocery workers’ health communication preferences are needed.
Investigating Flow-Induced Changes in Coaxial Cylindrical Dielectric Barrier Discharge Using Equivalent Circuit Modelling and Chemical Workbench Simulations
Authors: Pathak Ram Mohan , Jayanarasimhan Ananthanarasimhan , Nandi Sounak , Rao Lakshminarayana 
Published: July 2024

Abstract

This study presents the development of an equivalent electrical circuit model using MATLAB/Simulink to simulate the discharge behaviour of a coaxial cylindrical dielectric barrier discharge (DBD) and explores the influence of the flow regime on its electrical characteristics. Validation of the experimental findings was performed using Chemical Workbench (CWB). The simulations provided valuable insights into the DBD behaviour, facilitating its performance optimization. The equivalent circuit model demonstrated accurate predictions of peak current amplitude\({ (I}_{peak})\), root mean square of total current \(\left({ I}_{rms }\right)\), and microfilament discharge resistance \(\left({ R}_{f }\right)\). The study unveiled a significant impact of the flow regime on the electrical properties of the DBD. As the flow rate (Q) transitioned from the laminar flow regime (Reynolds number, Re = 300) to the turbulent flow regime (Re = 4500), the peak current \({ (I}_{peak})\) exhibited an increase from 60 mA to 80 mA for Argon (Ar) and 90 mA to 140 mA for Nitrogen (N2) gas. Simultaneously, the \({ R}_{f }\) decreased from 3.0 mΩ to 0.6 mΩ for Ar and 2.0 mΩ to 0.1 mΩ for N2. The impact of the flow regime on \({ R}_{f }\) was analyzed using the Peclet number (Pe) to gain a better understanding of heat/mass transport from the discharge to the surroundings. The MATLAB/Simulink and CWB models corroborated these findings, demonstrating excellent agreement with the experimental results. This validation underscores the reliability of the models in effectively characterizing the discharge parameters of the DBD.
Modal analysis reveals imprint of snowflake shape on wake flow structures
Authors: Tagliavini Giorgia , Holzner Markus , Corso Pascal 
Published: July 2024

Abstract

This study investigates the complex interplay of wake flow structures, particle shape, and falling behavior of snowflakes through advanced flow analysis. We employ Proper Orthogonal Decomposition and Dynamic Mode Decomposition to analyze the wake flow patterns of three distinct snowflake geometries at Reynolds number of 1500: a dendrite crystal, a columnar crystal, and a rosette-like particle. Proper Orthogonal Decomposition reveals that spatial resolution significantly impacts the capture of flow structures, particularly for particles with with more intricate wake flow structure, corresponding to unstable falling motion. Dynamic Mode Decomposition demonstrates high sensitivity to temporal resolution, with data of the forces exerted on the snowflake incorporated in the matrix prior to the decomposition mitigating information loss at lower sampling rates. We establish a linear relationship between snowflake shape porosity and minimum and maximum Dynamic Mode Decomposition eigenfrequencies, absolute decay or growth rates, and wavenumbers of the most energetic mode, linking particle geometry to wake flow characteristics. Higher porosity corresponds to more stable, small-scale flow structures and steady falling motion, while lower porosity promotes larger, unstable structures and falling trajectories with random particle orientations. These findings reveal the interdependence of snowflake geometry, wake flow configuration, and falling behavior and highlight the importance of considering both spatial and temporal resolutions when dealing with modal analysis. This research contributes to improved predictions of snowflake falling behavior, with potential applications in meteorology and climate science.