bluuebunny/crossref_metadata_2025_split huggingface dataset:
Practice and Attitudes of Nursing Staff to Bereavement Care for Pregnancy Loss: A Cross-Sectional Survey
Authors: Liu Siyu , Han Hongmei , Athurupana Rukmali , Qian Ying , Yang Titi , Nakatsuka Mikiya 
Published: October 2024

Abstract

Background
Despite its recognized significance, numerous obstacles hinder the implementation of bereavement care for pregnancy loss by nursing staff (including midwives and nurses). The availability and barriers to bereavement care in Japan are unclear. To assess the practices and attitudes of caregivers toward bereavement care for pregnancy loss, examine organizational support, and evaluate the burden on caregivers in delivering this care.
Methods
A cross-sectional survey conducted from January to April 2022 with 370 nursing staff from 43 Japanese maternity facilities assessed bereavement care necessity, implementation, staff support, and burden.
Results
Over 50% of nurses acknowledged bereavement care's importance, but a gap exists between its perceived necessity and execution, especially in post-discharge referrals (89.2% needed, 33.2% done), manuals provisions (74.6%, 25.7%), peer group introductions (73%, 17.8%), couple counselling (89.5%, 28.6%), husband support (91.4%, 40%), ongoing care (90.8%, 41.4%), and wish-based care planning (94.5%, 50.5%). Only 41.8% reported teamwork in bereavement care, with organizational support below 30%. Approximately 63.5% of nursing staff viewed bereavement care as a burden, with mental (80.4%) and time burdens (60%) being significant.
Conclusions
Despite bereavement care's necessity, there's a significant gap in joint couple counselling, targeted husband support, personalized and continuous care, and informative material provision. Organizational support deficiency and emotional burden pose major challenges for nursing staff in delivering bereavement care. Developing supportive policies, allocating necessary resources, and engaging with interdisciplinary support networks, all while ensuring staff well-being and continuous service improvement are crucial.
Characterization and Retrieval of Snow Grain Size in the Upper Himalayan Region Using Hyperspectral Prisma Data
Authors: Rawat Manish , Pandey Ashish , Das Dhananjay Paswan , Gupta Praveen Kumar 
Published: October 2024

Abstract

Rapid urbanization have significantly increased freshwater consumption, leading researchers to focus on accurately predicting snowmelt-derived streamflow using hydrological models. The glacierized basins of the Himalayan region are significantly vulnerable to climate change. The understanding of physical characterization of snow such as snow cover and snow grain size, remains challenging due to inaccessible terrains which creates hindrance for in-situ data collection. The hyperspectral remote sensing datasets are most promising for monitoring and retrieving the snow properties at the micro and macro levels. In this study, the PRISMA hyperspectral dataset was used for the retrieval of different snow grain sizes in the Bhilangana basin of the upper Himalayan region using the Spectral Angle Mapper (SAM) classification method and the Snow Grain Index (SGI) method. The spectral reflectance of different types of glacier features was generated using the SAM classification technique on PRISMA hyperspectral imagery and validated from the USGS spectral library for mapping. The results demonstrated that there is good qualitative agreement observed between the class-wise grain size classes using the grain index and SAM method. Additionally, the overall accuracy of the SAM and the grain size index classification methods for retrieving the grain size of different classes was approximately 88% .The outcomes of the study discloses the competency of PRISMA data for snow grain size mapping over the Mountainous region. The estimated parameters could be applied to climatology, hydrology, and mountain hazard mapping over the Himalayan region. Detailed snow grain size mapping can enhance mountain hazard assessments, including the prediction and management of snow avalanches, thereby contributing to the safety and sustainability of mountainous areas in the Himalayan region.
Local Feature Enhancement for Robust 2D Multi-Person Pose Estimation via Posture Refinement Network
Authors: Tian Weili , Zhan Jin , Guan Zhaokang , Yi Chensheng , Lei Fangyuan , Liu Xiaoyong , Li Huihui , Zeng Yufeng 
Published: October 2024

Abstract

Accurate 2D multi-person pose estimation remains challenging due to issues such as occlusion, missing body parts, and low resolution, particularly in complex backgrounds. This paper proposes a novel posture refinement network that leverages local feature enhancement and fusion to address these limitations. The network employs HRNet as the backbone to extract multi-scale feature maps, introducing a Dilated Convolution Module (DCM) with cascaded dilated convolutions to enrich pose keypoints representations. Additionally, a Hybrid Self-Attention Module (HSM) integrates contextual information to further refine pose estimates. Extensive experiments on the MSCOCO and CrowdPose datasets demonstrate that our method outperforms comparable methods, particularly in estimating human end joint positions with greater accuracy and robustness. Our findings highlight the effectiveness of local feature enhancement in robust multi-person pose estimation. The code and models are available at https://github.com/Twl-GZ/Human-pose.
Wear Prediction and Chaos Identification of Rigid Flexible Coupling Multi-link Mechanisms with Clearance
Authors: Li Feng , Meng Kai , Jiang Shuai , Han Hu 
Published: October 2024

Abstract

Traditional revolute clearance joint assumes that the shape of contact surface of joint is regular and ignores the effect of wear, which reduces prediction accuracy of dynamics model. To accurately describe collision behavior of motion pair, Archard formula was applied to construct a wear clearance model. Based on absolute node coordinate method, multi-body dynamics modeling, wear prediction, and chaotic identification analysis methods for a flexible multi-link mechanism with clearance considering wear effect were proposed. The research results indicate that wear intensifies the irregularity of clearance surface contour, leading to an increase in instability of the dynamic response and a decrease in motion accuracy of mechanism. The existence of smaller clearance values and slower driving speeds can effectively reduce dynamic deviation of mechanisms, improve motion accuracy and stability of mechanism, and alleviate chaotic phenomenon of mechanism. The variation laws of wear depth with driving speed and clearance value, as well as wear prediction of the motion pair were analyzed and obtained.
Programmable bacteria act as live biotherapeutics to remodel tumor stroma and potentiate immunotherapy
Authors: Stylianopoulos Triantafyllos , Panagi Myrofora , Mpekris Fotios , Ramos Marcos Burger , Voutouri Chrysovalantis , Michael Christina , Pearce Oliver , de Sampaio Pedro Correa , Soulier Annelise 
Published: October 2024

Abstract

Immunotherapy has transformed cancer treatment but its efficacy is limited in many solid tumors in large part due to the immunosuppressive tumor microenvironment (TME). TME might be composed of a dense/stiff extracellular matrix (ECM) that impedes infiltration of immune cells. To address this abnormality, Neobe Therapeutics developed an engineered live biotherapeutic in the form of programmable bacteria that offer advantages for delivering enzymes to remodel the ECM. Using engineered Escherichia coli to express and release hyaluronidase under a hypoxia-inducible promoter, the bacteria target hyaluronan within the TME. Our study demonstrates that hyaluronan degradation reduces tumor stiffness and restores vascular functionality in murine models of breast cancer. This potentiates immune checkpoint inhibitor efficacy by facilitating immune cell infiltration and immunostimulation. Additionally, our findings suggest that the potency of antitumor responses depends on baseline stiffness levels and ECM composition, highlighting the potential of programmable bacteria to improve immunotherapy outcomes in drug resistant, solid tumors.
Annotated Bangla Natural Language Processing (BNLP) by using python or machine learning.
Authors: Biswas Maneesha Rani , Rabbi Md. Fajle 
Published: October 2024

Abstract

This paper offers a thorough method for creating and assessing Python-based Natural Language Processing (NLP) tools for Bengali language. The study and practice of natural language processing focuses on how computers may be programmed to recognize, comprehend, and manipulate natural language speech or text for practical purposes. The study entails a thorough process for developing and testing NLP tools for the Bangla language that are based on Python and Machine Learning. It centers on the ways in which computers may be taught to perform tasks like Named Entity Recognition, Tokenization, Part-of-Speech (POS) Tagging, and Sentiment Analysis in order to comprehend Bengali text. The study commences with the introduction of a thoroughly annotated corpus that forms the basis for these activities and is intended to encompass a broad spectrum of language situations and structures. The study hopes to encourage future research and development in Bangla NLP by making these tools and resources open-source, encouraging cooperation and creativity. This project aims to aid the larger NLP community by offering a strong basis for applications like machine translation and sentiment analysis on Bangla Language.
Oxygen vacancy-induced strengthening and toughening in (K,Na)NbO3-based piezoceramics revealed via nanoindentation
Authors: Guo Jinming , Zhang Zhidong , Yang Bin , Chen Longyu , Zhang Zaoli 
Published: October 2024

Abstract

Dislocations are emerging as a pivotal factor for tailoring the functional and mechanical properties of ceramics. The introduction of point defects, notably oxygen vacancies, is unavoidable during the conventional sintering process in polycrystalline ceramics. Understanding the interplay between dislocations and oxygen vacancies is necessary for its profound implications. In this work, an innovative approach is implemented to regulate the dislocation-based incipient plasticity and creep behavior in (K0.5Na0.5)NbO3 (KNN)-based ceramics through oxygen vacancy engineering via CuO “hard” doping. Nanoindentation pop-in tests reveal that increasing oxygen vacancy concentrations significantly promotes the nucleation and activation of dislocations. Theoretical calculations based on Density Functional Theory further corroborate that oxygen vacancies contribute to a decrease in Peierls stress and total misfit energy, facilitating dislocation nucleation and activation. Nanoindentation hardness and creep behavior demonstrate oxygen vacancy impedes dislocation mobility due to solute strengthening and pinning effect. The effect of oxygen vacancies is elucidated through diverse mechanisms related to the interaction between dislocations and oxygen vacancies at different stages. This oxygen vacancy-induced strengthening and toughening strategy displays a significant potential to improve the mechanical properties of piezoelectric ceramics while still maintaining high electrical performance.
The greater role of Southern Ocean warming compared to Arctic warming in shifting future tropical rainfall patterns
Authors: Park Hyo-Seok , Jeong Hyein , Kang Sarah , Chung Eui-Seok 
Published: October 2024

Abstract

The recent rapid decline in Antarctic sea ice highlights the growing influence of rising Southern Ocean surface temperatures on global climate. While Arctic warming has been extensively studied, the importance of Southern Ocean warming is emerging only now. Multi-model simulations indicate that over 1.5°C of Southern Ocean surface warming can counteract the projected northward shift in zonal-mean precipitation over the tropics by the mid-21st century. SST nudging experiments suggest that a 1.0°C warming in the Southern Ocean could impact tropical precipitation as significantly as a 1.5°C warming in the Arctic. Regionally, Southern Ocean warming increases rainfall in northeastern Brazil while heightening drought risks in the Sahel. These effects are more pronounced than those from a weakening Atlantic meridional overturning circulation. Thus, Southern Ocean warming may play a more crucial role than Arctic warming in shaping tropical climate patterns in the coming decades.
Predicting IVF live birth probabilities using machine learning, center-specific models: validation results and potential benefits over national registry-based models.
Authors: Yao Mylene , Nguyen Elizabeth , Retzloff Matthew , Gago L. , Nichols John , Payne John , Ripps Barry , Opsahl Michael , Groll Jeremy , Beesley Ronald , Neal Gregory , Adams Jaye , Nowak Lorie , Swanson Trevor , Chen Xiaocong 
Published: October 2024

Abstract

Ongoing improvement of pretreatment live birth prognostication for in vitro fertilization (IVF) is critical for informing fertility patients' treatment decisions, advocating for IVF coverage and supporting value-based IVF care. The US national registry Society for Assisted Reproductive Technology (SART) IVF live birth prediction (LBP) model (SART model) has been widely adopted for its prognostic support without external validation or utilization studies. We conducted a retrospective model validation study to compare the IVF LBP performance of machine learning, center-specific (MLCS) models versus the SART model in 6 unrelated US fertility centers using their respective center-specific test sets comprising an aggregate of 4,635 patients' first-IVF cycle data. Compared to the SART model, MLCS2 showed higher median Precision Recall AUC at 0.75 (IQR 0.73, 0.77) vs. 0.69 (IQR 0.68, 0.71), p<0.05 and higher median F1 Score across LBP thresholds. Further, MLCS1 showed no evidence of data drift when validated using out-of-time test data from a later period. Reclassification analysis showed that MLCS2 models assigned more appropriate and higher IVF LBPs compared to the SART model, which underestimated patient prognoses (continuous net reclassification index: 18.3%, p<0.0001). Overall, MLCS2 and SART models assigned 30% of patients to differential prognostic groups, with MLCS2 assigning 26% of patients to a higher LBP category compared to the SART model. Importantly, MLCS2 models identified 11% of patients to have LBP ≥ 75%, whereas the SART model detected none. This group had a live birth rate of 81%. We recommend testing a larger sample of fertility centers to further evaluate MLCS model benefits and limitations.
Synthesis of Ti4Au3C3 and its derivative trilayer goldene through chemical exfoliation
Authors: Hultman Lars , Shi Yuchen , Kashiwaya Shun , Lu Jun , Dahlqvist Martin , Sangiovanni Davide , Rogoz Vladyslav , Magnuson Martin , Greczynski Grzegorz , Andersson Mike , Rosen Johanna 
Published: October 2024

Abstract

Achieving large two-dimensional (2D) sheets of any metal is challenging due to their tendency to coalescence or cluster into 3D shapes. Recently, single-atom-thick gold sheets, termed goldene, was reported1. Here, we raise the question if goldene can be extended to include multiple layers? The answer is yes, and trilayer goldene is the magic number, for reasons of electronegativity. Experiments are made to synthesize the atomically laminated phase Ti4Au3C3 through substitutional intercalation of Si layers in Ti4SiC3 for Au. Density functional theory calculations suggest that it is energetically favorable to insert three layers of Au into Ti4SiC3, compared to inserting a monolayer, bilayer or more than three layers. Isolated trilayer goldene sheets, ~ 100 nm wide and 6.7 Å thick, were obtained by chemically etching the Ti4C3 layers from Ti4Au3C3 nanolaminate templates. Furthermore, trilayer goldene is found in both hcp and fcc forms, where the hcp is ~ 50 meV/atom more stable at room temperature from ab initio molecular dynamics simulations.
Testing resistance of Daphnia magna in various environments
Authors: Ankous Hadil katrennada , grimes Samir 
Published: October 2024

Abstract

Environmental pollution is a critical threat to aquatic ecosystems, particularly in regions subjected to industrial and urban pressures. This study examines the application of Daphnia magna as a bio-indicator species for detecting pollution in various Algerian water sources, including desalination water, wastewater, oueds, and industrial effluents. The primary objective is to assess water quality at these key locations by analyzing the effects of different effluents on the life history traits of Daphnia magna. This research is essential for advancing environmental monitoring and pollution assessment, especially as anthropogenic impacts on aquatic ecosystems intensify. Addressing existing knowledge gaps, the study focuses on specific pollutants in Algerian waters and their impact on Daphnia magna. The methodology involves chronic and acute toxicity tests, offering a thorough evaluation of water quality through multiple exposure scenarios. Key findings reveal significant adverse effects of effluents, such as reduced size at first reproduction, decreased longevity, and altered reproductive parameters. These results underscore the pronounced sensitivity of Daphnia magna to pollution, reinforcing its effectiveness in environmental monitoring. The implications suggest that water quality at the studied sites is compromised, with potential consequences for broader aquatic ecosystems, emphasizing the necessity for ongoing, systematic monitoring and intervention.
Enhanced Algorithmic Convergence Analysis for Federated Low-Rank Matrix Completion
Authors: Li Chris Junchi 
Published: October 2024

Abstract

In this work, we explore the low-rank matrix completion (LRMC) problem, which is crucial for data science and machine learning applications. We develop and analyze a Gradient Descent-based solution, termed Alternating GD and Minimization (AltGDmin), aimed at efficiently recovering an $n \times q$ rank-$r$ matrix $\Xstar$ from a subset of its entries, particularly when $r \ll \min (n, q)$. Our theoretical guarantees, including iteration and sample complexity bounds, demonstrate that AltGDmin is not only the most communication-efficient solution in a federated setting but also one of the fastest methods available, achieving the second-best sample complexity among all iterative solutions to LRMC. Furthermore, we establish convergence results for noisy LRMC and highlight how our lemmas improve the sample complexity guarantee for AltMin, the fastest centralized solution. Overall, our findings emphasize the importance of leveraging the low-dimensional structure of data to recover missing entries and enhance predictive capabilities in matrix completion.
A Novel Unit Distribution Named As Median Based Unit Rayleigh (MBUR): Properties and Estimations
Authors: Attia Iman Mohammed 
Published: October 2024

Abstract

the importance of continuously emerging new distribution is a mandate to understand the world and environment surrounding us. In this paper, the author will discuss a new distribution defined on the interval (0,1) as regards the methodology of deducing its PDF, some of its properties and related functions. A simulation and real data analysis will be highlighted.
Austerity and Its Effects on Investments, Consumption, and Wages: An Analysis of Germany (2010–2014)
Authors: Houssam BOUGHABI 
Published: October 2024

Abstract

This paper investigates the economic impact of austerity measures in Germany during Angela Merkel's chancellorship from 2010 to 2014, focusing on their effects on public expenditures, investments, and consumption patterns. Austerity policies, implemented in response to fiscal imbalances following the global financial and Eurozone debt crises, aimed to restore economic stability. However, the contractionary effects of these measures on growth and employment have been widely debated. This study addresses a key gap in the literature by examining how austerity affected investment volatility and wage dynamics in Germany. Using an econometric model that incorporates long-memory processes and fractional integration, the paper explores the relationship between public expenditures, shrinking consumption, and wage support, and considers the role of debt financing in maintaining economic balance. The findings offer a detailed understanding of the long-term economic consequences of austerity policies, contributing to the broader discussion on fiscal consolidation and economic recovery.
JEL Classification. E62, H63, H68, C58, G32
Floods and Public Health Concerns in Uyo LGA, Akwa Ibom State, Nigeria
Authors: Umoh Justin Imeh , Brendan Michael Peter 
Published: October 2024

Abstract

Flooding is a recurrent natural hazard with significant environmental and human health consequences (Afangide et al., 2018). Rising global temperatures contribute to increased heavy rainfall events, leading to overflows of rivers and inundation of land (Ekong, 2019). Floods not only damage infrastructure and displace communities but also contaminate water sources and create breeding grounds for disease vectors (Adewale, 2020).
Uyo, the capital city of Akwa Ibom State, Nigeria, experiences frequent flooding due to a combination of factors. Rapid urbanisation with inadequate drainage systems, coupled with poor waste disposal practices, exacerbates the problem (Adewale, 2020). The 2022 flood season in Uyo highlighted the city's vulnerability, with major roads submerged despite government interventions (AKSMH, 2022).
This study investigates the health implications of floods in Uyo LGA. We focus on the most flood-prone areas and assess the likelihood of flood-related diseases among residents. Our objectives are to identify the streets most affected by flooding in Uyo LGA and evaluate the potential for flood-induced illnesses in these streets. analyse the health impacts of flooding on residents and recommend strategies to mitigate the health consequences of floods.
diablo en sus infiernos
Authors: Sánchez Godínez Jesús Antonio 
Published: October 2024

El diablo en sus infiernos es una obra coordinada por María Jesús Zamora Calvo, la cual nos lleva a explorar la evolución del Diablo en la cultura occidental, particularmente en el contexto hispano, a través de representaciones medievales, modernas y contemporáneas. Reúne los ensayos de catorce investigadores que analizan la presencia del demonio en un infierno que se extiende a terrenos legales, artísticos, históricos, antropológicos y fílmicos; convirtiéndose de esta manera, en varios infiernos.