bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wave‐CAIPI Multiparameter MR Imaging in Neurology
Authors: Liu Congcong , Ye Yongquan , Guo Yifan , Zhou Yihang , Zhu Yanjie , Liu Xin , Xu Jian , Zheng Hairong , Liang Dong , Wang Haifeng 
Published: January 2025

ABSTRACTIn clinical practice, particularly in neurology assessments, imaging multiparametric MR images with a single‐sequence scan is often limited by either insufficient imaging contrast or the constraints of accelerated imaging techniques. A novel single scan 3D imaging method, incorporating Wave‐CAIPI and MULTIPLEX technologies and named WAMP, has been developed for rapid and comprehensive parametric imaging in clinical diagnostic applications. Featuring a hybrid design that includes wave encoding, the CAIPIRINHA sampling pattern, dual time of repetition (TR), dual flip angle (FA), multiecho, and optional flow modulation, the WAMP method captures information on RF B1t fields, proton density (PD), T1, susceptibility, and blood flow. This method facilitates the synthesis of multiple qualitative contrast‐weighted images and relaxometric parametric maps. A single WAMP scan generates multiple contrast‐weighted images and relaxometric parametric maps, including PD‐weighted (PDW), T1‐weighted (T1W), T2*‐weighted (T2W), adjusted T1‐weighted (aT1W), susceptibility‐weighted imaging (SWI), B1t map, T1 map, T2/R2* map, PD map, and quantitative susceptibility mapping (QSM). Both phantom and in vivo experiments have demonstrated that the proposed method can achieve high image quality and quantification accuracy even at high acceleration factors of 4 and 9. The experiments have confirmed that the rapid single scan method can be effectively applied in clinical neurology, serving as a valuable diagnostic tool for conditions such as pediatric tuberous sclerosis complex (TSC)‐related epilepsy, adult Parkinson's disease, and suspected stroke patient. The WAMP method holds substantial potential for advancing multiparametric MR imaging in clinical neurology, promising significant improvements in both diagnostic speed and accuracy.
How to educate patients and caregivers on end‐of‐life nutrition care and support
Authors: Schwartz Denise Baird , Wolfe Citty Sandra , Barrocas Albert , O'Sullivan‐Maillet Julie 
Published: January 2025

AbstractBackgroundThere are numerous articles, book chapters, and published guidelines on the topic of clinical ethics in the use of artificially administered nutrition and hydration, which often incorporates end‐of‐life (EOL) nutrition care and support. Components of clinical ethics involve the importance of ethical principles, patient‐centered care, and shared decision‐making. However, there is sparse information on how to educate patients and caregivers on this subject.MethodsInitially, PubMed and the Cochrane Library were used to find articles on the subject. Articles were reviewed and new concepts were identified to include.ResultsThere is a practice gap with not applying clinical ethics in practice. The application of clinical ethics, which includes the teach‐back method of education, soft skills and behavioral skills training, and potential sacred moments, is not well addressed in the literature. Demonstration of the process of incorporating clinical ethics into practice is beneficial in helping educate clinicians so they can then effectively educate the patient and caregiver on EOL nutrition care and support. Reasons for not applying clinical ethics in actual clinical practice may be because of clinicians not receiving training, the lack of opportunity to observe the technique applied in actual clinical practice, or possibly concern for the presumed additional time required in clinical practice to apply clinical ethics.ConclusionEducating patients and caregivers on EOL nutrition care and support presupposes engaging, educating, and empowering clinicians about clinical ethics by demonstrating the process and encouraging educators to incorporate the information in an interdisciplinary/interprofessional curriculum.
Validity and Reliability of Patient Activation Measure (PAM13‐I) Italian Version Among Patient Undergoing Elective Surgery
Authors: Provenzano Maria , Cillara Nicola , Podda Mauro , Gonzalez Cesar Ivan Aviles , Cicalò Enrico , Fransvea Pietro , Poillucci Gaetano , Deserra Antonello , Ricciardelli Luigi , Jiménez‐Herrera Maria ,   and the DeDiLaCo study collaborative group
Published: January 2025

ABSTRACTThe patient activation measure (PAM), a recognized measure of how active patients are in their care, is one of the most extensively used, widely translated, and tested instruments worldwide in measuring patient activation. This study aimed to assess the psychometric properties and construct validity of the Italian version of the 13‐item Patient Activation Measure (PAM13‐I) among patients undergoing elective laparoscopic cholecystectomy. A multicenter study was conducted across 111 surgical units in Italy. This study involved the preoperative administration of the PAM questionnaire to 4532 patients. The psychometric properties of the PAM were evaluated using Rasch analysis. The PAM13‐I demonstrated good internal consistency (Cronbach's α = 0.95) and reliability indices. While fit statistics were acceptable, ceiling effects were observed. No significant differential item functioning was found. However, issues with targeting and local response dependency were identified. The Italian PAM‐13 showed promising psychometric properties among surgical patients, indicating its potential utility in assessing patient activation. However, concerns regarding ceiling effects and targeting suggest the need for further refinement and validation in surgical populations.
An Exploratory Model of How Ethical Indicators Predict Health Professional Burnout
Authors: Kjos Andrea L. , Gnacinski Stacy L. , Wahl Carly A. 
Published: January 2025

ABSTRACTThe objectives of this study were to characterize burnout in five different health professions (i.e., pharmacists, nurses, occupational therapists, psychologists, and mental health counselors) as well as to determine if moral distress, ethical stress, and/or ethical climate were predictive of burnout and job satisfaction. Cross‐sectional survey data were collected in the USA using validated measures from a sample of 291 in early 2022 (COVID‐19 Omicron wave). The average age of participants was 51 years (s.d. = 12.59) and most identified as female (78%), White/Caucasian (82%), married/in a domestic partnership (72%), without dependents (57%), and had > 20 years of experience (53%). Results demonstrated that two of the three dimensions of burnout (i.e., emotional exhaustion and depersonalization) reached clinically significant levels among nurses, occupational therapists, and pharmacists, but not among psychologists or mental health counselors. In testing an exploratory structural equation model, moral distress, ethics stress, and ethical climate contributed significantly to the burnout and job satisfaction of all professionals (CFI = 0.905; SRMR = 0.056; Gamma hat scaled = 0.931). These findings support a theoretical framework for explaining associations between ethical indicators and burnout and job satisfaction. Future research should explore if professions with less burnout experience differences in the organizational environment, autonomy, and independence of clinical work, and/or professional identity. Exploration into professional socialization, such as strategies learned as part of training and development, may be warranted to identify factors that buffer or mitigate burnout risk.
Medial orbitofrontal cortex structure, function, and cognition associates with weight loss for laparoscopic sleeve gastrectomy
Authors: Li Xin , Zhang Wen , Bi Yan , Duan Yanjie , Sun Xitai , Chen Jiu , Zhang Xin , Zhang Zhou , Zhu Zhengyang , Zhang Bing 
Published: January 2025

AbstractObjectiveThe objective of this study was to investigate underlying mechanisms of long‐term effective weight loss after laparoscopic sleeve gastrectomy (LSG) and effects on the medial orbitofrontal cortex (mOFC) and cognition.MethodsA total of 18 individuals with obesity (BMI ≥ 30 kg/m2) underwent LSG. Clinical data, cognitive scores, and brain magnetic resonance imaging scans were evaluated before LSG and 12 months after LSG. We employed voxel‐based morphometry analysis and seed‐based resting‐state functional connectivity (RSFC) analysis to assess LSG‐induced structural and functional changes in mOFC. Partial correlation analysis and univariate and multivariate linear regression models were used to explore associations among biochemical indexes, neuroimaging, cognition, and weight loss.ResultsNo significant improvement in general cognition was found after LSG. Decreases in gray matter volume of the bilateral mOFC and increases in RSFC of the right mOFC were observed 12 months after LSG. Weight loss was associated with RSFC, general cognitive scores, and triglyceride changes. Multivariate linear regression model revealed gray matter volume of the left mOFC and working memory scores at baseline explained 55.2% of the variation in weight loss.ConclusionsThese findings suggest that mOFC imaging and cognitive scores could serve as biomarkers for predicting persistent weight loss after LSG, which provides a solid foundation for a potential target for neuromodulation research.
Correlation between interfacial bonding behavior and surface treatments in bonded carbon fiber composite joints
Authors: Wang Tingting , Gong Bowen , Hu Weiyuan , Wang Huan , Ouyang Wenting , Peng Hua‐Xin 
Published: January 2025

AbstractSurface treatments play a crucial role in enhancing the bonding strength of composites. The effect of surface treatment has received much attention in the literature but reported effect of combined treatments are less prevalent. Therefore, this work explored the correlation between plasma, sanding, porous release film treatments, its combination and bonding behavior in bonded carbon fiber composite joints. The bonding performance of composites was predominantly affected by three mechanisms: chemical cross‐linking, chemical adsorption and mechanical interlocking. The bonding strength was enhanced after plasma treatment through the increased polar functional groups and surface wettability, resulting in a 7% (28.6 MPa) improvement compared to untreated samples. Sanding and porous release film treated surfaces exhibited increased roughness and mechanical interlocking, with strength up to 29.5 and 38.7 MPa enhancement in shear strength. Furthermore, plasma and sanding treatments removed surface contaminants and enhanced the bonding strength. Plasma treatment on surfaces treated with porous release film led to a slight decrease in bonding strength (35.9 MPa), as the deep valleys were changed into shallow ones by plasma. Spearman correlation analysis was used to establish the relationship between characterization parameters and shear strength. The results revealed a robust correlation between surface roughness and strength, highlighting its potential for predicting bonding performance.Highlights
Comprehensive investigations on the correlation between surface treating techniques and bonding behaviors.
The shear strength increased as the integrity of adhesive film decreased.
Roughness has the most robust correlation with shear strength.
Impact of Antibiotic Shortages on Antibiotic Utilisation in the Community
Authors: Lambert Maarten , Taxis Katja , Pont Lisa 
Published: January 2025

ABSTRACTBackgroundDrug shortages are an increasing and worldwide problem. Oral antibiotics are one of the most used medicines worldwide and have recently been affected by drug shortages. Despite this, little is known about the impact of antibiotic shortages on prescribing practices.AimTo explore the impact of oral antibiotic shortages on national antibiotic utilisation.MethodsA cross‐sectional study of oral antibiotic shortages and antibiotic utilisation was conducted using Australian reimbursement and regulatory data from January 2022 to December 2023. All nationally reimbursed oral antibiotics were included in the study. The number and duration of reported antibiotic shortages per product were determined for each active ingredient. The clinical impact was assessed using national utilisation in Defined Daily Doses per 100 000 inhabitants. Changes in trends were analysed using Joinpoint regression.ResultsShortages were reported for eighteen of the twenty‐one (86%) oral antibiotics reimbursed in Australia. For ten active ingredients, shortages did not coincide with changes in utilisation data. No clear relation between the number and duration of shortages and impact on utilisation was observed. Changes in utilisation coinciding with shortages were observed for eight active ingredients. For cefaclor (−20% decrease in utilisation) and roxithromycin (−26% decrease), the impact of shortages is most clearly reflected by decreases in utilisation. For the other six, minor changes in utilisation were observed coinciding with shortages.ConclusionsAntibiotic shortages were common in Australia during 2022 and 2023. The impact of shortages differs per antibiotic, for some antibiotics there are shortages coinciding with declines in utilisation. For others, shortages occur without apparent changes in utilisation.
Polarization modification of trans‐1,4‐butadiene‐co‐isoprene rubber through homogeneous chlorination and the chlorination mechanism
Authors: Song Xinping , Wang Li , Shao Huafeng , Zhao Jiruo , He Aihua 
Published: January 2025

AbstractPolarization modification can improve performance and increase applications for a material, so polarization of nonpolar rubber materials has always been an important research and development direction for rubber modification. In this work, the preparation and chlorination mechanism of a chlorinated trans‐1,4‐butadiene‐co‐isoprene rubber (CTBIR) was investigated. The chlorination reaction, micro‐structure analysis, and homogeneous chlorination mechanism have been discussed in detail. The chlorination process of TBIR is a free radical reaction and the chlorinated product structure is very complex with a diversified structure caused by the presence of two diolefin monomers, butadiene and isoprene, in TBIR. The free radical chlorination of TBIR includes chlorine substitution and double‐bond addition reactions, resulting in basic chlorinated structures including allyl chlorine, 1,2‐chloro, methyl‐chloride, and small amounts of vinylidene chloride, and ring structures. The structures of double‐bonded and allyl chlorine vary with the modification of the chlorine content, and can be controlled by chlorination reaction conditions, such as reaction time.Highlights
Homogeneous chlorination of high trans‐1,4‐butadiene‐co‐isoprene rubber (TBIR).
Detailed structure characterization and analysis of the CTBIR.
Mechanism of the homogeneous chlorination of TBIR.
Registration of Tx3499–Tx3503 sorghum germplasm resistant to acetyl‐coenzyme A carboxylase‐inhibiting herbicides
Authors: Crozier Daniel , Bagavathiannan Muthukumar , Hodnett George L. , Norsworthy Jason K. , Beechinor Kayla A. , Rooney William L. 
Published: January 2025

AbstractThe sorghum [Sorghum bicolor (L.) Moench ssp. bicolor] germplasm lines Tx3499–Tx3503 (Reg. no. GP‐948–Reg. no. GP‐952, PI 706257–PI 706261) were developed by the Texas A&M AgriLife Research sorghum breeding program in 2024. These lines are resistant to acetyl‐coenzyme A carboxylase (ACCase)‐inhibiting herbicides used for post‐emergence control of common grass weeds. Genetic resistance to aryloxyphenoxypropionate and phenylpyrazoline class herbicides was introgressed into Tx3499–Tx3503 from a donor line that contained a single partially dominant gene. These lines represent diverse pedigrees and an array of combinations of grain color, plant color, maintenance of sterility or restoration of fertility to A1 male‐sterile cytoplasm, as well as other agronomic traits. They provide the sorghum industry with sources of resistance to ACCase‐inhibiting herbicides in elite backgrounds for use as seed and pollinator parent germplasm.
Using Pharmacoepidemiology to Examine the Interplay of Sulfonylureas and Infection Risk in Patients With Diabetes Mellitus
Authors: Wu Yu‐ying , Lin I‐Fan , Chen Kuan‐Hua , Wang Hsi‐Hao , Huang Chun‐Kai 
Published: January 2025

ABSTRACTSulfonylureas (SU) are commonly prescribed as oral hypoglycemic agents for the management of diabetes mellitus (DM). We postulated that SU possess antimicrobial properties due to their structural resemblance to the antimicrobial agent sulfamethoxazole. Using data from Taiwan's National Health Insurance Research Database, we enrolled patients diagnosed with DM between 2000 and 2013 and followed them for a three‐year period. Patients who consistently used SU were categorized into the SU cohort, while those who had never used SU formed the non‐sulfonylurea (non‐SU) cohort. The primary study endpoints were diagnoses of pneumonia and urinary tract infections (UTIs). Within the database, we identified a total of 15,458,554 patients with DM, with 754,601 (4.88%) in the SU cohort and 2,244,436 (14.52%) in the non‐SU cohort. After individual matching based on age, gender, index day, and propensity score of comorbidities, we included 663,056 patients in each cohort. The cumulative incidence of pneumonia and UTI was 29,239 (4.41%) and 60,733 (9.16%) in the SU cohort, respectively, and 24,599 (3.71%) and 56,554 (8.53%) in the non‐SU cohort, respectively. Our findings indicated that the use of SU increased the risk of pneumonia (1.26–1.60 times) and UTI (1.13–1.22 times), while also potentially offsetting the protective effects of metformin. This pharmacoepidemiological study represents a concerted effort to assess latent drug properties that may have a significant impact on the clinical management of patients with DM.
A Universal Visual Detection Method for Camellia oleifera Fruit Picking Robot
Authors: Wang Jinpeng , Yuan Fei , Zhou Jialiang , He Meng , Zhen Qianguang , Fang Chenzhe , Chen Sunan , Zhou Hongping 
Published: January 2025

ABSTRACTIn recent years, the application of robots in the field of fruit picking has steadily increased. Mechanized methods for harvesting oil tea fruits include comb picking, vibratory picking, and gripping picking, among others. Traditional reliance on a single‐picking method is limited by variability in fruit size, shading, and environmental conditions. To develop a universal vision system suitable for picking robots capable of multiple picking methods and achieve intelligent harvesting of oil tea fruits. This paper proposes an enhanced You Only Look Once v7 (YOLOv7)‐based oil tea fruits recognition method specifically designed for subsequent clamp or comb picking. The network's feature extraction capability is enhanced by incorporating an attention mechanism, an optimized small target detection layer, and an improved training loss function, thereby improving its detection of occluded and small target fruits. An innovative Automatic Assignment (AA) method clusters and subclusters the detected oil tea fruits, providing crucial fruit distribution data to optimize the robot's picking strategy. Additionally, for vibration harvesting, this paper introduces a vibration point detection method utilizing the Pyramid Scene Parsing Network (PSPNet) semantic segmentation network combined with connectivity domain analysis to identify vibration points on the trunks and branches of oil tea trees. Experimental results demonstrate that the generalized visual detection method proposed in this study surpasses existing models in identifying oil tea fruit trees, with the enhanced YOLOv7 model achieving mean average precision, recall, and accuracy of 91.7%, 94.0%, and 94.9%, respectively. The AA method achieves clustering and subclustering of oil tea fruits with a processing delay of under 5 ms. For vibration harvesting, PSPNet achieves branch segmentation precision, recall, and intersection ratio of 97.3%, 96.5%, and 94.5%, respectively. The proposed branch vibration point detection method attains a detection accuracy of 93%, effectively pinpointing vibration points on the trunks and branches of oil tea trees. Overall, the proposed visual method can be implemented in robots using various picking techniques to enable automated harvesting.
Toward Universal Embodied Planning in Scalable Heterogeneous Field Robots Collaboration and Control
Authors: Wan Hanwen , Zhang Yuhan , Wang Junjie , Wu Donghao , Li Mengkang , Chen Xilun , Deng Yixuan , Huang Yuxuan , Sun Zhenglong , Zhang Lin , Ji Xiaoqiang 
Published: January 2025

ABSTRACTMulti‐robot systems offer substantial enhancements in efficiency, scalability, robustness, and flexibility for executing complex tasks through collaborative efforts. However, existing methodologies are constrained by their lack of generalizability, the need for extensive modeling, and most importantly, limitations in their applicability in complex scenarios. This paper presents a novel approach to multi‐robot task planning and coordination, introducing a comprehensive pipeline encompassing data generation, supervised fine‐tuning, and rigorous error analysis using the Multi‐Robot collaboration Error Diagnostic (MRED) metrics. Bridging the gap between natural language commands and physical groundings in robot collaboration tasks, we present MultiPlan: the first data set specifically designed for LLM fine‐tuning. The MultiPlan data set encompasses 100 distinct indoor and outdoor scenarios, ranging from office to garden. Experiments underscore the efficacy of the proposed methodology, including comparative analyses against state‐of‐the‐art LLMs and generalization studies on previously unseen tasks. Results reveal that the fine‐tuned model achieves a 24.8% relative improvement over the GPT‐4 model in addressing complex multi‐robot planning scenarios. We also conducted field evaluations in both office and urban settings to demonstrate the deployment performance of the proposed method. These results demonstrate the model's superior capabilities in task decomposition, error management, and adaptation to novel contexts.
QSAR Modeling of Pyridone Derivatives as α‐amylase Inhibitors Using Chemical Descriptors and Machine Learning
Authors: Zhang Ya‐Kun , Tong Jian‐Bo , Chang Ze‐Lei , Yan Jing , Xing Xiao‐Yu , Yang Yu‐Lu , Xue Zhan 
Published: January 2025

AbstractDiabetes is a prevalent chronic metabolic disorder that affects the lives and health of millions of individuals annually. α‐amylase, a key digestive enzyme, plays a critical role in carbohydrate digestion. Inhibition of α‐amylase activity can effectively slow the digestion of carbohydrates, thereby aiding in the maintenance of stable blood glucose levels. Consequently, the identification and development of potent α‐amylase inhibitors have become a significant research focus in diabetes management. This study employed a modeling approach based on chemical descriptors and machine learning techniques to systematically explore the relationship between the chemical structures of 32 pyridone derivatives and their α‐amylase inhibitory activity. A robust and predictive quantitative structure‐activity relationship (QSAR) model was developed through optimization with the Sparrow algorithm, Monte carlo domain applicability evaluation, and Y‐randomization testing. Utilizing this model in conjunction with data from the ZINC15 database, 23 potential compounds exhibiting favorable activity were designed. Further evaluation through SwissADME performance predictions identified three compounds with high inhibitory potential. Molecular docking studies provided insights into the potential binding modes and mechanisms of action of these compounds. The results of this study offer valuable theoretical support for the development of pyridone derivatives as potential therapeutic agents for diabetes and provide novel insights for the discovery of α‐amylase inhibitors.