bluuebunny/crossref_metadata_2025_split huggingface dataset:
An analytical approach towards attaining Leave No One Behind using patterns and distributions of inequalities in antenatal and facility delivery coverage in Uttar Pradesh, India
Authors: Namasivayam Vasanthakumar , Prakash Ravi , Dehury Bidyadhar , Isac Shajy , Wehrmeister Fernando C. , Becker Marissa , Blanchard James , Boerma Ties 
Published: August 2024

Abstract

Background:
Leave No One Behind (LNOB) is a central, transformative promise of the 2030 Agenda for Sustainable Development Goals. To attain LNOB, systematic analysis of patterns and distributions of inequalities in coverage of health outcomes on a continuous basis at different program delivery layers is required, to design tailored health interventions. We analysed the patterns of change and geographic distribution of inequalities in coverage of antenatal care and facility-based delivery in Uttar Pradesh(UP), India and developed a framework to guide health programmers understand inequalities better, to accelerate progress by reaching those left behind.
Methods:
Data from five-rounds of National Family Health Survey (1992–2021) and two-rounds of Community Behaviour Tracking Survey (2014–2018) is used. Education and wealth have been used as stratifiers. Three measures of inequality- mean difference from mean, slope index of inequality, and inequality pattern index are used to depict the state, district and sub-district level inequalities.
Results:
UP observed a substantial reduction in the education-related inequality in both ANC and facility-delivery during 1992–2021. The slope index of inequality declined from 65.3 [95%CI:60.0-70.6] to 9.3 [95%CI:7.8–10.8] for ANC and from 44.7 [95%CI:38.5–50.9] to 29.9 [95%CI:27.8–32.0] for facility-delivery during 1992–2021. The inequality pattern index showed that, with improved reach of interventions, many districts moved towards bottom inequality from top inequality for any ANC while a fewer districts for facility-delivery. Even in districts with high coverage and low inequality, sub-district level(blocks) inequality persisted. Similarly, in blocks with high coverage and low inequality, Accredited Social Health Activist (ASHA) level inequality persisted. Interestingly, for the same ASHA area, the patterns of inequality differed for any ANC and facility delivery, in some districts inequalities direction changed based on the stratifier chosen.
Conclusions:
The proposed health equity framework suggest that to achieve LNOB status, understanding inequality with the coverage status is important. If coverage is high and inequality persists, identify the program layer at which maximum inequality persists to identify the left behinds. Whereas, if coverage is poor, programs are required to improve coverage first. Findings also call for systematic way of collecting and organizing granular data to understand inequality and identify the left-behinds.
Pixel_DiffusionSeg:Instance segmentation basedon multi-level deformable self-attention anddiffusion models
Authors: Chen Hongqian , Yang Rui , Li Hui , Gao Yu , Ge Yuting 
Published: August 2024

Abstract

Addressing the issues of incomplete detection of instance targets, the challengesin detecting occluded objects, and incomplete segmentation in complex scenesusing diffusion models for multi-target instance segmentation, this paper introduces Pixel DiffusionSeg, an instance segmentation approach based on multi-leveldeformable attention and diffusion models. This method leverages the benefitsof deformable self-attention, which adaptively adjusts the receptive field size,incorporating it into the proposed framework. Additionally, it aggregates multi-scale features and introduces a pixel decoder to achieve pixel-level predictionresults, thereby preserving the image’s detailed information and enhancing segmentation accuracy. The method treats instance segmentation as a process ofdenoising and remodeling masks using diffusion models, capable of reversingnoisy ground truth masks without being biased by noisy candidate boundingboxes. Comparative experiments on the COCO val2017 dataset demonstrate thatthe enhanced model exhibits significant improvements in terms of the number1of detected objects, object scores, segmentation completeness, and generalization performance. Utilizing a ResNet-50 backbone, the model achieves an AP of37.45% , surpassing the 37.3% AP of DiffusionInst. Our code will be graduallymade available at https://github.com/chenhongqian/Pixel DiffusionSeg.
The Effectiveness of Virtual Reality in Managing Labor Pain: A Systematic Review and Meta-Analysis
Authors: Najjariasl Parisa , Dalvandi Kamran , Shabani Fateme , Zamanian Hadi , Ramezani Amirreza 
Published: August 2024

Abstract

This systematic review and meta-analysis aimed to evaluate the effectiveness of virtual reality (VR) in managing labor pain. A comprehensive search of databases including Embase, Scopus, PubMed, and Web of Science identified clinical trials exploring the efficacy of VR in reducing labor pain. The inclusion criteria focused on low-risk, full-term pregnant women receiving VR interventions through head-mounted displays or glasses during any stage of labor. Ten randomized controlled trials (RCTs) were included in the analysis. The meta-analysis revealed a significant reduction in labor pain associated with VR interventions, with a pooled effect size of -0.7012 (95% CI: -0.8380 to -0.5644). Subgroup analyses indicated consistent pain reduction across different parity groups, though heterogeneity was noted among the primiparous and mixed parity groups. Meta-regression analysis identified cervical dilation stage, pain assessment tools, and blinding status as significant moderators of VR's effectiveness. The findings support VR as a promising non-pharmacological intervention for labor pain management, offering significant analgesic effects without the adverse outcomes associated with pharmacological options. Future research should focus on standardizing VR protocols, exploring the optimal timing and duration of interventions, and understanding the long-term effects of VR during labor. This review underscores the potential of VR to enhance labor pain management strategies, improving outcomes for women in labor.
Changes in mercury content in oysters in relation to sediment and seston content in the Colombian Caribbean lagoons
Authors: Vélez-Mendoza Anubis , Mora Jeimmy Paola Rico , Campos-Campos Néstor Hernando , Almario-García Margui Lorena , Sanjuan-Muñoz Adolfo 
Published: August 2024

Abstract

Total mercury was evaluated in the mangrove oyster Crassostrea rhizophorae, in sediments and seston from the Ciénaga Grande de Santa Marta (CGSM) and Cispatá Bay (BhC) in two climatic seasons (rainy and dry). Composite samples of sediments, seston and oysters in juvenile and adult sizes were collected at six stations (three in each ecosystem) and Hg was quantified by atomic absorption spectrophotometry (EPA method 7473 PLTX-017). BhC had the highest Hg concentrations in sediment, seston and oysters compared to CGSM, with values close to the tolerable threshold for the ecosystem and associated biota (TEL) of 0.13 µg/g Hg and with a low risk of Hg contamination in the mangrove oyster. Although at CGSM Hg was below the TEL in sediment and was considered safe in the oyster, significant bioaccumulation was evident with the metal content in the seston, indicating a potential risk to the ecosystem and humans. The variables organic matter and temperature influenced metal availability in the sediment and seston, respectively; in contrast, they had no significant relationship in the oyster. In CGSM, higher [Hg] was recorded in adult sizes, while in BhC the highest accumulation occurred in juveniles, especially during the dry season. These results emphasize the need for continuous monitoring of Hg contamination in both ecosystems. In addition, they highlight the importance of considering the size of oysters when assessing Hg contamination, as they may vary according to specific ecosystem and climatic conditions.
Evaluation of Aeroacoustic Optimisation Strategies for a Generic Flight Mission of a Tilt-Propeller Aircraft
Authors: Bergmann Ole , Möhren Felix , Frey David , Janser Frank , Braun Carsten 
Published: August 2024

Abstract

Balancing propeller performance between cruise and hover conditions is a critical challenge in eco-friendly aircraft design. This paper presents a novel serial multidisciplinary propeller optimization approach, integrating blade element momentum theory for performance assessment and Farassat’s formulation 1A for noise emission prediction. Combined with a genetic algorithm, three different propeller design strategies are systematically evaluated for their suitability in a multidisciplinary propeller optimization routine. The novel serial optimization approach reduces the parameter space in a stepwise manner. The assessment shows that, in the initial step, linear chord and parabolic twist distributions are sufficient for determining the optimal blade number and diameter, significantly accelerating the optimization process. In contrast, detailed blade shape optimization requires a parametric blade description. The assessment shows that considering the system mass is crucial for holistic optimization, while motor efficiency mapping is less critical. This paper provides an innovative optimization scheme that can be utilized in the propulsion system design for new aircraft, enhancing performance and reducing noise emissions.
Determinants of Sustainability Performance of Manufacturing Companies Using Two-stage Data Envelopment Analysis
Authors: Sutiene Kristina , Vaz Clara B. , Vaitiekuniene Raminta 
Published: August 2024

Abstract

The investigation of business performance through the lens of sustainability has become an increasingly attractive topic among scholars. This study contributes to the field by proposing a two-stage methodology. First, to assess companies' efficiency in terms of sustainability, the scores of the Environmental, Social and Governance (ESG) pillars are combined into the single weighted sustainability performance indicator using the 'Benefit of Doubt' (BoD) model, which is maximized for each company by comparing it against the best performers in terms of ESG scores based on Data Envelopment Analysis (DEA). Then, in the second stage, the significant determinants are identified after the efficiency estimates are regressed on the company performance indicators using Tobit panel regression. To demonstrate this approach, we selected 559 companies from the manufacturing sector, as this industry continues to face challenges in reducing environmental impact, improving resource efficiency, and fostering social responsibility. The main findings include the examination of top performers and underperforming companies in terms of sustainability, alongside key financial indicators identified in the study.
Stability of the Gut Microbiome in Honey Bees During Harsh Winters and Overwintering Storage
Authors: Brar Gagandeep , Ngor Lyna , McFrederick Quinn S. , Torson Alex , Rajamohan Arun , Rinehart Joesph , Singh Preetpal , Bowsher Julia 
Published: August 2024

Abstract

Honey bee gut microbiota play a number of specific roles in promoting host growth and physiology. While the gut microbiota of honey bee queens, workers, and larvae has been extensively studied, less is known about the role and composition of gut microbiota in the winter worker bees. This study investigates the dynamics of the gut microbiota in overwintering adult worker bees, focusing on two commercial bee strains: Bolton™ bees and Mann Lake™ bees. The strains were investigated under different storage conditions (indoor storage at 6°C and outdoor storage in natural conditions) during the winter months (October, November, and December). Utilizing 16S rRNA gene amplicon sequencing, we characterized the microbial composition of the whole gut. We observed a stable microbiota with slight variations in host-associated bacterial communities with Lactobacillus genus dominating in all the overwintering honey bee guts. Bolton bees exhibited higher abundance levels of Bartonella, Bifidobacterium, and Wolbachia, while Mann Lake bees showed increased abundance of Commensalibacter. Our results suggest that alpha diversity is influenced by the month rather than by the bee strain or storage conditions. We also found significant differences in beta diversity by month. Overall, in this study a stable gut microbiota was observed in both indoor and outdoor environmental conditions across different months with slight differences in abundance between bee strains. Considering all potential benefits of the honey bee gut microbiome to health and nutrition, this study suggests that beekeepers need not be concerned about whether overwintering storage conditions affect the gut microbiome.
Bioenergetic trade-offs can reveal the path to superior microbial CO2 fixation pathways
Authors: Rodríguez Jorge , Taha Ahmed , Patón Mauricio 
Published: August 2024

Abstract

Biotechnology can lead to cost-effective processes for capturing CO2 using the natural or genetically engineered metabolic capabilities of microorganisms. However, introducing desirable genetic modifications into microbial strains without compromising their fitness (growth yield and rate) during industrial-scale cultivation remains a challenge. Recently, a computational methodology was developed that considers the trade-offs between energy efficiency (yield) and growth rate, allowing us to evaluate candidate metabolic modifications in silico for microbial conversions. A comprehensive optimisation of known prokaryotic autotrophic CO2 fixation pathways was conducted, considering all possible variants under different environmental conditions. The results revealed the superior configurations in terms of both yield (efficiency) and rate (driving force). This approach and results can guide optimal pathway configurations for enhanced prokaryotic carbon fixation through metabolic engineering. By aligning strain modifications with these theoretically revealed near-optimal pathway configurations, we can optimally engineer strains of good fitness under open culture industrial scale conditions.
Towards Human-Centered AI in Speech Therapy: Perspectives from a Low-Resource Setting
Authors: Deka Chinmoy , Shrivastava Abhishek , Kumar Rishav 
Published: August 2024

Abstract

Background: While Speech-Language Pathologists (SLPs) are crucial in addressing Speech Sound Disorder (SSD), a global shortage of SLPs poses significant challenges in providing speech therapy services, particularly in impoverished and rural areas. Despite the potential of AI-based automated speech therapy tools, concerns such as job displacement, algorithmic bias, and privacy issues persist.
Purpose: This study adopted a Human-Centered AI (HCAI) approach to understand the needs and perspectives of SLPs, aiming to inform the development of a Human-Centered AI-based Speech Therapy Tool (HCAI-STT) for children with SSD.
Methods: A qualitative study using deductive reflexive thematic analysis with MAXQDA software was conducted to explore the needs and perspectives of SLPs.
Results: The domain understanding theme highlighted the complexity of functional SSD, emphasizing unknown etiology, parental concerns, and the developmental nature of speech acquisition. Current practices involve using digital tools under supervision and adhering to therapy guidelines. Key challenges included accessibility issues, socio-economic constraints, and the absence of a standardized Assamese Photo Articulation Test (PAT). Future directions highlighted the need for technology-based interventions, culturally relevant audio-visual stimuli, mobile-based solutions, and affordable tools.
Conclusion: The findings emphasize the necessity for a culturally tailored, technologically advanced approach to speech therapy. Recommendations include integrating Assamese PAT, culturally relevant audio-visual stimuli, AI-based diagnostic and feedback tools, and home-based therapy with supervision. These insights will guide the development of the HCAI-STT, enhancing AI integration in speech therapy and improving quality and accessibility. Future research will engage additional stakeholders and develop and evaluate the tool’s usability, efficacy, and effectiveness.
The simplest 4-D autonomous hyperchaotic system coined: Theoretical analysis and analog circuit design
Authors: Xiong Yongyong , Zhang Xiao , Chedjou Jean Chamberlain , Wu Yesen , Shukhratovich Makhkamov Bakhtiyor , Jiang Donghua , Kengne Jacques 
Published: August 2024

Abstract

In this paper, a new fourth-order autonomous hyperjerk system capable of producing hyperchaotic signals (FHHO hereafter) is proposed. The proposed model features a single nonlinear term represented by the hyperbolic sine of the weighted sum of two state variables (i.e., the fundamental variable and the jerk). The FHHO system is dissipative and symmetric and has a single unstable equilibrium point located at the origin of the state space. To describe the mechanisms leading to chaos and subsequent hyperchaos, a systematic study is carried out using appropriate analysis tools, such as Lyapunov exponent graphs, phase portraits, Poincaré maps, and bifurcation diagrams. We highlight rich and varied dynamics marked by periodic, tori, chaotic or hyperchaotic attractors and, even more interestingly, offset control and symmetry control properties. The electronic simulator of the proposed FHHO model is built using only five operational amplifiers (i.e., four integrators and a summing amplifier) and a pair of diodes mounted head to tail. The experimental results confirm the presence of hyperchaotic signals as well as the bifurcation modes predicted by the theoretical study. To the best of our knowledge, the hyperchaotic model studied combines the two forms of simplicity rarely encountered, namely, the simplicity of the evolution equations and the simplicity of electronic realization.
Prevalence of Gastrointestinal Nematodes of Dogs and Associated Hematological Changes in Gombe State, Nigeria
Authors: Audu Y. 
Published: August 2024

Abstract

Gastrointestinal (GI) nematodes are a common parasitic problem in dogs, causing significant health issues. These parasites live in the digestive tract and can lead to a variety of symptoms, depending on the type and severity of infection. A cross sectional study was conducted from August 2023 to December 2023 to determine the prevalence of gastrointestinal nematodes of dogs and their effect on haematological parameters in Gombe State, Nigeria. A total of 200 faecal samples from dogs were collected using systematic random sampling technique from six (two from each Senatorial zone) randomly selected Local Government Areas (LGAs) out of the eleven LGAs in the State. Formalin-ether centrifugation-floatation technique was used to detect nematode parasites using microscopy. Haematological evaluations were performed according to standard procedures. The overall prevalence of gastrointestinal nematodes of dogs in the study area was 36.5%. The parasites identified were Ancylostoma caninum, Toxocara canis and Trichuris vulpis with 58.9%, 28.7% and 12.3% prevalences respectively. The haematological parameters revealed reduction of the Mean Corpuscular Volume (MCV) of both the infected and non-infected dogs below the reference values while only the infected group has Mean Corpuscular Hemoglobin Concentration (MCHC) below the reference values. There were eosinophilia, monocytosis and leukocytosis in the infected group whereas neutrophilia occurred in both the infected and non-infected groups. All other haematological values are within the reference ranges. This study establishes the prevalence of gastrointestinal nematodes of dogs and associated risk factors in Gombe State, Nigeria.
Anaerobic co-digestion of fish waste and other organic materials
Authors: kumar Holigi siva 
Published: August 2024

Abstract

This study explores the anaerobic co-digestion of fish waste with various organic substrates to enhance biogas production, addressing the environmental challenges posed by fish waste disposal. With 185 million tons of fish produced annually, a significant portion becomes waste during processing, leading to health hazards and ecological impacts. Anaerobic digestion (AD) is presented as an effective solution for converting this waste into biogas, a renewable energy source. The research investigates the effects of different substrate combinations, including cow dung, vegetable waste, and water hyacinth, on biogas yield and methane content. Batch tests were conducted over 40 days, maintaining optimal waste-to-inoculum ratios. Results indicated that co-digestion significantly improved biogas production, with the highest yield (68.15%) observed from the mixture of fish waste and water hyacinth, compared to 50.2% from fish waste alone. The study highlights the importance of maintaining a balanced carbon-to-nitrogen ratio and optimizing operational parameters, such as temperature, to maximize methane output. Overall, this research underscores the potential of anaerobic co-digestion as a sustainable approach to waste management and renewable energy generation from fish waste.
Incidence of Depression, Anxiety and Stress among Final-Year Medical Students versus Internship Graduates of the Faculty of Medicine, Sana'a University 2023
Authors: Al-Haddad KM , Raja'a YA , Al-Nuzaili AF , Al-Hakimi AA , Zayed AA , Al-Yosefi MA , Al-Madhfari RH , Khaled AR , Raja'a AY , Al-Garbani GA , Al-Yazidi NA , Al-Selmi SF 
Published: August 2024

Abstract

ABSTRACT
Background: Depression, anxiety, and stress among medical students are significant health issues because of their impact on the challenging journey in medicine.
Objective: To assess the degree of relief in depression, anxiety, and stress attributed to the graduation of final-year medical students from the Faculty of Medicine and Health Science, Sana'a University, Yemen, in 2023.
Methodology: A cohort design was employed. There were 408 volunteers, with a response rate of 99.8%. They were contacted electronically through faculty registries. There were 212 final-year respondents and 197 interns. The data were collected via questionnaires that included sociodemographic characteristics and a validated self-administered DASS-21 questionnaire to assess depression, anxiety and stress. The collected data were analysed via SPSS version 26. Ethical Clearance Certificate, according to Helsinki Declaration, was obtained from the Faculty of Medicine, Sana'a University.
Results: Final-year medical students had incidence rates of 74.1% depression, 66% anxiety and 62.7% stress. However, 63.96% of internship graduates were depressed, 56.9% were anxious, and 45% were stressed. Relief was significantly associated with depression (p=0.032) and stress (p<0.0001), whereas anxiety was not significantly associated (p=0.067).
Conclusion: The rates of depression, anxiety and stress were high in both cohorts. The relief attributed to graduation was significant for depression and stress.