bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proposing new design and retrofitting objectives for seismic design of hospital structures - A case study of Imam Khomeini Hospital in Eslamabad-e Gharb
Authors: Mehrjoo Majid , Aval Seyed Bahram Beheshti 
Published: June 2023

Abstract

This paper compares two methods for retrofitting an existing hospital concrete structure to improve its seismic performance: internal and external retrofitting. Internal retrofitting involves adding chevron braces, reinforcing shear walls with Fibre-reinforced plastic (FRP) coating, and wrapping the walls, columns, and beams using steel jackets. External retrofitting uses two braced exterior steel frames connected to the concrete building using dampers. The paper also proposes a new design objective for hospital structures that ensures immediate occupancy performance level under earthquake hazard level-1 and prevents collapse under higher ground motion intensity. The paper evaluates the base structure, the two retrofitting schemes, and the proposed design method using pushover and nonlinear dynamic analyses under 20 selected earthquake records. The paper then compares the probabilistic seismic risk models using fragility curves. The results show that external retrofitting is more effective and economical than internal retrofitting and that the proposed design objective can significantly reduce the seismic risk of hospital structures.
Prediction and Validation of Mild Cognitive Impairment in Occupational Dust Exposure Population Based on Machine Learning
Authors: Cai Fulin , Zhang Mei , Liu Yafeng , Chen Xiufeng , He Jiale , Xue Sheng 
Published: June 2023

Abstract
Objective: Workers who are exposed to dust for extended periods of time may experience varying degrees of cognitive impairment. However, there is limited research on the associated risk factors. This study aims to identify key variables using machine learning algorithms (ML) and develop a model to predict the occurrence of mild cognitive impairment in miners.
Methods: A total of 1938 miners were included in the study. Univariate analysis and multivariable logistic regression were employed to identify independent risk factors for cognitive impairment among miners. The dataset was randomly divided into a training set and a validation set in an 8:2 ratio, consisting of 1550 and 388 individuals, respectively. An additional group of 351 miners was collected as a test set for cognitive impairment assessment. Seven machine learning algorithms, including XGBoost, Logistic Regression, Random Forest, Complement Naive Bayes, Multi-Layer Perceptron, Support Vector Machine, and K-Nearest Neighbors, were used to establish a predictive model for mild cognitive impairment in the dust-exposed population, based on baseline characteristics of the workers. The predictive performance of the models was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC), and the XGBoost model was further explained using the SHapley Additive exPlanations (SHAP) package. Cognitive function assessments using rank sum tests were conducted to compare differences in cognitive domains between the mild cognitive impairment group and the normal group.
Results: Univariate and multivariable logistic regression analyses revealed that education level, age, years of employment, SSRS (Self-Rating Scale for Stress), and HAMA (Hamilton Anxiety Rating Scale) were independent risk factors for cognitive impairment among dust-exposed workers. Comparative analysis of the performance of the seven machine learning algorithms demonstrated that XGBoost (training set: AUC=0.959, validation set: AUC=0.795) and Logistic Regression (training set: AUC=0.818, validation set: AUC=0.816) models exhibited superior predictive performance. Results from the test set showed that the AUC of the XGBoost model (AUC=0.913) outperformed the Logistic Regression model (AUC=0.778). Miners with mild cognitive impairment exhibited significant impairments (p<0.05) in visual spatial abilities, attention, abstract thinking, and memory areas.
Conclusion: Education level, age, years of employment, SSRS, and HAMA were identified as independent risk factors for cognitive impairment among miners. Machine learning algorithms can be used to predict the risk of cognitive impairment in this population, with XGBoost algorithm showing the best performance. The developed model can guide the implementation of appropriate preventive measures for dust-exposed workers.
Ongoing shuffling of protein fragments diversifies core viral functions to tackle bacterial resistance mechanisms
Authors: Smug Bogna , Szczepaniak Krzysztof , Rocha Eduardo , Dunin-Horkawicz Stanislaw , Mostowy Rafal 
Published: June 2023

Abstract
Phages are known for their genetic modularity. Their genomes are built of independent functional modules that evolve separately and combine in various ways, making them astoundingly diverse. Multiple studies have demonstrated how genome mosaicism emerges in phage populations and facilitates adaptation to their hosts, bacteria. However, less is known about the extent of (within-)protein modularity and its impact on viral evolution. To fill this knowledge gap, here we quantified such modularity by detecting instances of protein mosaicism, defined as a homologous fragment between two otherwise unrelated proteins. We used highly sensitive homology detection to quantify protein mosaicism between pairs of 133,574 representative phage proteins and to understand its relationship with functional diversity in phage genomes. We found that diverse functional classes often shared homologous domains. This phenomenon was often linked to protein modularity, particularly in receptor-binding proteins, endolysins and DNA polymerases. We also identified multiple instances of recent diversification via exchange and gain/loss of domains in receptor-binding proteins, neck passage structures, endolysins and some members of the core replication machinery. We argue that the ongoing diversification via shuffling of protein domains associated with those functions is reflective of co-evolutionary arms race and the resulting diversifying selection to overcome multiple bacterial resistance mechanisms.
Beyond Mothers: The Crucial Role of Family Caregivers' Knowledge on Exclusive Breastfeeding in Rural Western China.
Authors: Nie Jingchun , Ye Jinbiao , Wu Shichong , Wang Nan , Li Yangyuan , Liu Yunjie , Reheman Zulihumaer , Wu Junhao , Yang Jie , Shi Yaojiang 
Published: June 2023

Abstract
Background
The exclusive breastfeeding rate in China remains quite low. Numerous studies have identified the impact of maternal characteristics on exclusive breastfeeding. However, how the family members’ characteristics, for example primary family caregivers’ health and nutrition knowledge, correlated with exclusive breastfeeding is still unclear.
Methods
A cross-sectional study was conducted in two prefecture-level cities from the Qinba Mountains area. Data on exclusive breastfeeding, knowledge of health and nutrition, breastfeeding practices, breastfeeding family support, breastfeeding self-efficacy, and conflict frequency were collected via structured questionnaires from 372 caregivers-infant pairs. The mother was interviewed first, and then the primary family caregiver was given a brief questionnaire. Each interview was conducted alone to avoid interruptions from other family members. Univariate and multivariate regressions were conducted to explore the correlation between knowledge of mothers and primary family caregivers and exclusive breastfeeding.
Results
The exclusive breastfeeding rate among infants aged 6 months in this sample was 15.7%. The average score for the mothers’ health and nutrition knowledge was 4.6 (SD = 1.4), while the average score for the primary family caregivers was 3.6 (SD = 1.4). The health and nutrition knowledge of both the mother (OR = 1.48, P = 0.002) and the primary family caregiver (OR = 1.34, P = 0.017) remained significantly positively associated with exclusive breastfeeding, and the odds ratios were relatively close. There was a significant positively correlation (OR = 1.98, P < 0.001) between the average health and nutrition knowledge of the mother and the primary family caregiver and exclusive breastfeeding. The primary family caregiver’s knowledge of health and nutrition showed a significant positive correlation with the family practical support perceived by the mother (OR = 1.23, P = 0.027), and it also had a significant positive correlation with the breastfeeding self-efficacy of the mother (β = 1.40, P = 0.013).
Conclusions
The characters of family primary caregiver play much role on exclusive breastfeeding. To promote exclusive breastfeeding, interventions should address the needs of the whole family instead of just mothers.
EGFR core fucosylation, induced by enveloped viruses, promotes TRIM40-mediated-RIG-I ubiquitination and suppresses interferon-I antiviral defenses
Authors: Pan Qiu , Xie Yan , Zhang Ying , Guo Xinqi , Liu Min , zhang Xiao-Lian 
Published: June 2023

Abstract
Aberrant N-glycosylation has been implicated in viral diseases. Alpha-(1,6)-fucosyltransferase (FUT8) is the sole enzyme responsible for core fucosylation of N-glycans during glycoprotein biosynthesis. Here we found that multiple viral envelope proteins (including HCV-E2, VSV-G, SARS-COV-2-Spike and HIV-gp120) enhanced FUT8 expression and core fucosylation. HCV-E2 manipulates host transcription factor SNAIL to induce FUT8 expression through EGFR-AKT-SNAIL activation and SNAIL nuclear translocation. These aberrant increased-FUT8 expression promotes TRIM40-mediated RIG-I K48-ubiquitination and suppresses the antiviral interferon (IFN)-I response through core fucosylated EGFR-JAK1-STAT3-RIG-I signaling. FUT8 inhibitor 2FF, N-glycosylation site-specific mutation (Q352AT) of EGFR, and tissue-targeted Fut8 silencing significantly increased antiviral IFN-I responses and suppressed RNA viral replication, suggesting that core fucosylation mediated by FUT8 is critical for antiviral innate immunity. These findings reveal an immune invasion mechanism in which virus-induced FUT8 suppresses endogenous RIG-I-mediated antiviral defenses by enhancing core fucosylated EGFR-mediated activation. FUT8 may be a promising target for RNA viral therapies.
A novel free-gliding ski tribometer for quantification of ski-snow friction with high precision
Authors: Sandberg Joakim , Kalliorinne Kalle , Hindér Gustav , Holmberg Hans-Christer , Almqvist Andreas , Larsson Roland 
Published: June 2023

Abstract
The nature of snow and the ever-changing environment make measurements of friction on snow and ice challenging. In addition, since this friction is low, the equipment utilised must be highly sensitive. Previous investigations of ski–snow friction have ranged from small-scale model experiments performed in the laboratory to experiments with full-sized skis outdoors. However, few have been conducted under conditions similar to those encountered during actual skiing. Here, we developed a novel sled tribometer which provides highly reproducible coefficient of friction (COF) values for full-sized skis gliding at relevant speeds (approximately 20 km/h) in a controlled indoor environment. The relative standard deviation (RSD) of COF is as low as 0.5 % enable differentiation between the structures and preparations of different ski bases. The continuous recording of speed enable novel investigations of COF variations when skis are allowed to free-glide to a full stop in a natural setting. Different methods of analysing the results are presented which shows that the precision is not a single number, but a function of the range of speeds over which the average COF is calculated.
SiC MOSFET Based Dual Active Half-Bridge Converter for Energy Storage Systems : Design and Analysis
Authors: Bhajana Veera Venkata Subrahmanya Kumar , Drabek Pavel , Kakani Vijay , Biswal Pravat , Popuri Madhuchandra 
Published: June 2023

Abstract
This article presents the performance evaluation of isolated Dual Active Half-Bridge (DAHB) converter with discrete SiC MOSFET devices. Novelty of this paper is that a DAHB converter without resonant network provides soft-switching to its SiC MOSFETs. The impact of resonant network on SiC MOSFET DAHB under two different modes is evaluated. The soft-switching characteristics, zero voltage switching and zero current switching operations are achieved by using resonant network. The discrete switching devices, SiC MOSFETs are used to develop the DAHB module. The experimental investigations are performed on DHB converter system with 330V-500V with switching frequency, 100 kHz operated at 700W output power to obtained 96.5% efficiency.
To what extent can the Ozone Valley over the Tibetan Plateau influence the East Asian summer precipitation?
Authors: Zhu Lingaona , Wu Zhiwei 
Published: June 2023

Abstract
The ozone valley over the Tibetan Plateau (OVTP) has experienced significant interannual variations during the past decades. Previous studies have primarily focused on the origins of OVTP, while the climate impact of OVTP is still an open question. This study reveals that OVTP during its peak season (May-July) explains approximately 15% of the summer precipitation variability in East Asia. The results suggest that the surface temperature (Ts) anomaly over the Tibetan Plateau (TP) acts as a link between OVTP and East Asian precipitation. Causality analysis confirms that the intensification of OVTP leads to a significant increase in Ts over northwestern TP. Through a positive land-atmosphere feedback, the Ts anomaly over the TP is amplified. The anomalous Ts pattern persists into summer (June-August) due to the land memory effect and impacts the East Asian precipitation by modulating the local circulation. Numerical experiments show that diabatic heating over the TP induces an anomalous anti-cyclone centered over the Yangtze-Huaihe River Basin, leading to negative precipitation anomalies in the Yangtze River Basin and positive precipitation anomalies in southern China. Our analysis of Coupled Model Intercomparison Project Phase 6 models reveals that more accurate prediction of East Asian precipitation requires improved understanding of the relationship between OVTP and TP Ts.
Feedback attribution to recent Arctic temperature extremes and the role of natural variability
Authors: Blau Manuel Tobias , Chung Eui-Seok , Ha Kyung-Ja 
Published: June 2023

Abstract
The polar regions have been undergoing amplified warming in recent years. However, natural climate variability can further amplify or dampen the ongoing warming trend causing extreme temperature events. Therefore, it is important to determine the role of climate variability on shaping the characteristics of extreme temperature events. By employing a surface radiation budget framework, we examine the main causes for Arctic amplification and extreme summer temperature events over the period 1979-2021, considering feedback attribution analysis and natural climatic modes. The results demonstrate that increases in clear-sky longwave radiation explain most of the temperature trend, with the surface albedo feedback and changes in ocean heat storage playing a supporting role. Regarding recent extreme temperature events on inter-annual time scales, climate variability such as the North Atlantic Oscillation and the Greenland Blocking Index has exerted a significant impact on such extreme events by modulating the feedback strength. Furthermore, we find that extreme temperature events can be explained in large part by anomalous atmospheric circulation related to strengthened blocking anti-cyclones associated with the Greenland Blocking Index.
Pruning DETR: Efficient End-to-End Object Detection With Sparse Structured Pruning
Authors: Sun Huaiyuan , Zhang Shuili , Tian Xve , Zou Yuanyuan 
Published: June 2023

Abstract
Deep learning methods in the field of object detection have made significant progress in terms of performance, but end-to-end implementations still face challenges. Recently, the Transformer-based DETR model successfully introduced the attention mechanism into object detection tasks, achieving end-to-end object detection. However, despite its competitive accuracy, DETR still falls short in terms of inference speed and computational costs. To address this issue, this paper proposes an optimization of the DETR model using structured pruning through sparsity-induced pruning, aiming to improve its inference speed and reduce computational costs. We adjust the importance of module outputs through parameter scaling factors and sparse regularization terms, and optimize the parameter scaling factors using an improved Accelerated Proximal Gradient (APG) method. Experimental results on the COCO dataset demonstrate that our approach achieves a computational cost reduction of over 32% while maintaining an AP value of 42.7%, resulting in an inference speed improvement of over 17% to reach 32.7 FPS. This study provides an effective solution for further enhancing the real-time capability of Transformer-based object detection models.
Maternal satisfaction with shared decision-making among women who underwent caesarean section in Sidama region South Ethiopia: Facility based cross-sectional study
Authors: Wondimu Melkamu Getu , Sisay Binyam Demisse , Aga Meseret Birhanu , Alemu Belete 
Published: June 2023

Abstract
Background:- Maternal satisfaction with shared decision-making is one of the most important aspects of the healthcare delivery system that aims at providing quality services that meet the expectations of the mothers. In Ethiopia have been limited studies to maternal satisfaction with shared decision-making. Therefore, the aim of the study is to explore the maternal satisfaction with involvement in decision-making to identify the key influencing factors.
Methods:- Facility-based cross-sectional study was conducted from June 01/2022-July 01/2022 in Sidama region Public Hospitals, among women who underwent a caesarean section. The total sample size was 416. A simple random sampling technique was used to select the study participant. Bivariate and multivariable binary logistic regression was carried out. The strength of the association of outcome and predictor variables was presented by crude and adjusted odds ratio at a 95% confidence interval. Variables with a p value of < 0.05 were considered statistically significant.
Result:-In this study, among total study participants, 174 (41.8%) respondents were satisfied with shared decision-making during a caesarean section. Urban residence [AOR 1.7 (95% CI: 1.02, 2.7)], explaining the procedure in the mother tongue [AOR 2.4 (95% CI: 1.5, 3.9)], provision adequate information [AOR 3.2 (95% CI: 1.87, 5.3)] and spent sufficient time with care providers [AOR 1.8(95% CI: 1.08, 2.9)]were positively associated with maternal satisfaction.
Conclusion and recommendation:-Maternal satisfaction with shared decision-making is relatively low. Therefore, healthcare providers need to do more to increase mothers' satisfaction with collaborative decision-making during the procedure.
Automatic Detection and Classification of Mango Disease Using Convolutional Neural Network and Histogram Oriented Gradients
Authors: Sema Wasyihun , Yayeh Yirga , Andualem Girmaw 
Published: June 2023

Abstract
This study suggests a Convolutional Neural Network (CNN) and Histogram Oriented Gradients (HOG)-based automatic detection and classification system for mango disease. Early detection is essential for efficient disease management since mango disease can have a major influence on fruit quality and yield. The suggested system makes use of the CNN algorithm for extracting features and the HOG technique for capturing shape and texture data. The extracted features are subsequently used to feed a disease classification model for disease detection. The efficiency of the proposed model is demonstrated by experimental findings, which achieve excellent accuracy in both disease detection and classification tasks. The CNN-HOG hybrid model outperforms CNN or HOG alone in terms of performance, demonstrating the complementary nature of these two methods for the detection and classification of mango disease. The system's performance is evaluated using measures for accuracy, precision, and recall and the accuracy of the proposed model is 98.80%. This research helps establish effective and trustworthy tools for managing mango disease by automating the detection and classification process. This enables prompt intervention and reduces crop losses.
Application of left common carotid-left subclavian artery shunt for reconstruction of left subclavian artery in TEVAR of type B aortic dissection with insufficient proximal anchoring area: 10 years of single-center experience
Authors: Wang Maohua , Song Qingpeng , Wei Yuhua , Zhang Jingyong , Dong Dianning , Wu Xuejun 
Published: June 2023

Abstract
Objectives：In thoracic endovascular aortic repair(TEVAR) of type B aortic dissection (TBAD) , left common carotid-left subclavian artery（LCCA-LSA) shunt is a feasible method to reconstruct left subclavian artery (LSA) in order to provide enough proximal anchoring area. The purpose of this study was to evaluate the safety and early efficacy of LCCA-LSA shunt in the reconstruction of LSA in TEVAR of TBAD with insufficient proximal anchoring area.
Methods：The clinical data of 63 patients (mean age 52.3 ±11.6years, 54 males and 9 females) with TBAD who underwent LCCA-LSA shunt to reconstruct LSA in TEVAR from January 2010 to December 2021 were analyzed retrospectively. The technical success rate, operation time, complications such as leakage, stroke, hemorrhage, spinal cord ischemia, pulmonary infection, perioperative death and readmission were recorded and analyzed retrospectively.
Results：A total of 63 patients were included, 60 cases (95.2%) of LCCA-LSA shunt, 3 cases (4.8%) of LSA-LCCA transposition; 10 cases (15.9%) underwent carotid-carotid bypass surgery at the same time, 9 cases (14.3%) underwent ligating LSA of proximal LVA surgery and 15 cases (23.8%) underwent embolization of LSA root surgery. The average operation time is 323.7±91.6 min. The results of intraoperative angiography showed that all the LSA were reserved, therefore the technical success rate was 100%. Within 1 month after operation, 11 cases (17.5%) had complications occurred, 9 cases(14.3%) were cured and discharged from hospital, 1 case (1.6%) had sequela of cerebral infarction and 1 case (1.6%) died at 18 days after the surgery. During the follow-up period, 6 patients (9.5%) were readmitted to hospital because of new distal rupture or/and internal leakage, all of which were cured and discharged.
Conclusion：For TBAD patients without enough proximal anchoring area, LCCA-LSA shunt for LSA reconstruction has a high technical success rate, low mortality and low incidence of residual complications, which is a good choice and has unique advantages. However, medium and longterm safety and efficacy still need a large number of sample studies.