bluuebunny/crossref_metadata_2025_split huggingface dataset:
Active avoidance recruits the anterior cingulate cortex regardless of social context in male and female rats.
Authors: Ruble Shannon , Kramer Cassandra , West Lexe , Payne Karissa , Ness Halle , Erickson Greg , Scott Alyssa , Diehl Maria 
Published: June 2024

Abstract

Actively avoiding danger is necessary for survival. Most research has focused on the behavioral and neurobiological processes when individuals avoid danger alone, under solitary conditions. Therefore, little is known about how social context affects active avoidance. Using a modified version of the platform-mediated avoidance task in rats, we investigated whether the presence of a social partner attenuates conditioned freezing and enhances avoidance learning compared to avoidance learned under solitary conditions. Rats spent a similar percentage of time avoiding during the tone under both conditions; however, rats trained under social conditions exhibited greater freezing during the tone as well as lower rates of darting and food seeking compared to solitary rats. Under solitary conditions, we observed higher levels of avoidance in females compared to males, which was not present in rats trained under social conditions. To gain greater mechanistic insight, we optogenetically inactivated glutamatergic projection neurons in the anterior cingulate cortex (ACC) following avoidance training. Photoinactivation of ACC neurons reduced expression of avoidance under social conditions both in the presence and absence of the partner. Under solitary conditions, photoinactivation of ACC delayed avoidance in males but blocked avoidance in females. Our findings suggest that avoidance is mediated by the ACC, regardless of social context, and may be dysfunctional in those suffering from trauma-related disorders. Furthermore, sex differences in prefrontal circuits mediating active avoidance warrant further investigation, given that females experience a higher risk of developing anxiety disorders.
Forecasting extremes of football players' performance in matches.
Authors: Nowak Michal , Bok Bartosz , Wilczek Artur , Kamola Mariusz , Oleksy Łukasz 
Published: June 2024

Abstract

Based on training history, accurate predictive modelling of an athlete's performance in competition can be a cornerstone for prior optimal planning of exercise mix and intensity. While universal in many sports, such a goal is challenging in football due to the complexity of factors leading to the final score and the complexity of the preceding training process. We developed and tested a range of models, the best of which were to forecast selected play performance indices with an accuracy of 10-20%. Such score applies to models run on raw player location data and aggregating performance indices developed with expert knowledge in the football training domain. Results show that individual player models perform better than collective ones and that more recent training data are better predictors. While we consider the accuracy of the models still of limited reliability, their transparency and present quality make them useful in the daily planning of training activities that impact player performance in the coming match. Additionally, observations of training parameters generated in short-term intervals are more effective and correlated with extreme match results than long-term dates. Specific training parameters may be key in predicting exceptional football player performance, but they may also vary from person to person.
Impact of digital self-scheduling on operations management and patient experience in hospital outpatient settings: a systematic review and meta-analysis
Authors: Zheng Miao , Li Teng , Wang Hongqian , Zhong Hongling , Zhou Haizhou , Fan Yaojun , Peng Jing , Wang Fang , Lin Li , Wang Lihua 
Published: June 2024

Abstract

Digital self-scheduling (DSS) adopted for outpatient appointment system improves efficiency and quality of services, but how it contributes to improving outpatient care delivery in hospital settings remains unverified. To evaluate the impact of DSS on operations management and patient experience in hospital outpatient services. Studies published in PubMed, Embase, Web of Science, EBSCO, Science Direct, Scopus, and IEEE Xplore were searched up to June 2022. Studies describe DSS intervention for accessing outpatient services in hospital settings, analysing its effectiveness on operations management or patient experience compared with traditional scheduling methods/or not intervention, were included. PRISMA and SWiM guidelines were used to report the study. The ROBINS-I and GRADE criteria were used for rating risk of bias and quality of evidence. Meta-analysis was conducted for combinable results from at least two studies, performed by RevMan 5.4. A total of 18 observational studies were included. Compared with conventional methods, DSS resulted in lower no-show rates (OR = 0.70, 95% confidence interval (CI): 0.57–0.85, p < 0.001), increased scheduling efficiency (OR = 4.94, 95% CI: 4.54–5.38, p < 0.001), and improved patient satisfaction (OR = 2.83, 95% CI: 2.20–3.64, p < 0.001). Younger age (MD -9.07, 95%CI: -14.75 to -3.38, p = 0.002) and higher education (OR = 0.85, 95% CI: 0.80–0.91, p < 0.001) were observed in DSS population. Patient acceptance of DSS increased alongside the advancement of digital technologies and dominated by the ease of use. This study suggested the use of DSS for improving hospital outpatient services, but there is insufficient evidence for waiting time and other outcomes of outpatient operations, so future research is warranted.
Arctic and Antarctic Sea Ice Extent Forecasting using hybrid LSTM Techniques
Authors: Sureja Spandan 
Published: June 2024

Abstract

Recent changes in global climate patterns have triggered the melting of polar sea ice, especially in Arctic regions. A decrease in the extent of sea ice is observed at a much faster rate than previously expected. The Antarctic region, on the other hand, has shown a stable sea ice pattern throughout the last few decades. However, the southern polar region is not completely unaffected. Recent studies of the Bellingshausen and Amundsen Seas have shown a downward trend in sea ice. The extent of sea ice is crucial for regulating global climate patterns, ocean circulation and human activities, including shipping and fishing. Hence, forecasting sea ice extent is vital for global economy planning and climatology studies. In this paper, time-series forecasting of 5 Antarctic and Arctic regions is evaluated using a hybrid convolutional long short-term memory (ConvLSTM) and a bidirectional long short-term memory (LSTM) and compared with a standalone long short-term memory (LSTM). This study uses regional sea ice extent data rather than considering the extent across entire hemispheres. Evaluation metrics such as the root mean squared error (RMSE) and mean absolute error (MAE) are used to compare the performances of the models. With lower RMSE scores across all lead times, the proposed hybrid models show better performance in regional sea ice forecasting than does the standalone LSTM. The study also indicated that the climatic conditions of a particular region play a crucial role in forecasting efficiency, especially at longer lead times.
Development and Application of Concrete-Filled Steel Tubular (CFST) Column Supporting High-stress Roof Strata in Large-span Mine Roadway
Authors: Song Wei , WANG Han-Qiu , Liu Xue-Feng , QIU Heng-Jian , QIU Feng-Qi , SHENG Feng-Tian 
Published: June 2024

Abstract

The stability of large-span roadway junctions is challenging to control solely through simple passive support and conventional combined support. Therefore, this paper incorporates a novel high strength concrete-filled steel tubular (CFST) column considering the steel tube structure and concrete materials designed to offer adequate support for controlling the rock strata in large-span mining roadway. Subsequently, the CFST column model was designed based on a large-span roadway in a certain mine. The results show that circular-section CFST columns are significantly superior to square-section CFST columns. As the steel tube's wall thickness increases, the structure's bearing capacity significantly increases. Considering both performance and cost, a new concrete material was studied that enhances bearing capacity by increasing its strength and the tightness of contact with steel tubes. Circular steel tubes with an outer diameter of 800 mm and a wall thickness of 24 mm were used as columns, filled with a new type of concrete material, for supporting the roof strata of the large-span mining roadway. After calculating the support forces, it was concluded that CFST columns could effectively bear the stress released by the strata, thereby reducing the displacement of the top rocks, with a notable support effect.
Gender affects spine-pelvic-lower limb force line:A cross-sectional imaging study of knee osteoarthritis
Authors: Yin Shilin , Du peiyu , Du Shuangqing , Zhang Yongwang , Liu Lu , Sun Zhipeng , Bai Yicong , Tian Xinyu , Li Xi , Yan Yun tao 
Published: June 2024

Abstract

Objective:The aim of this study was to investigate the relationship between imaging indicators of knee osteoarthritis and the presence of gender orientation and risk factors.
Methods:This study retrospectively included 318 patients with knee osteoarthritis.Based on Kellgren-Lawrence(KL)scoring system,These patients were classified as having limited knee osteoarthritis(LKOA) and severe knee osteoarthritis(SLOA).We measured the lumbar lordosis angle(LL),sacral slope angle(SS),pelvic incidence angle(PI),the mechanical axis deviation(MAD),Joint line convergence angle(JLCA) and lateral proximal femur angle(LPFA) in each patient to explore whether the correlation between these parameters is correlation under different gender conditions.
Results:The study showed that in LKOA group,JLCA in female patients showed significant negative correlation with PI and LL(P<0.01),while SS in male patients showed significant positive correlation with MAD and LPFA(P<0.01).Multiple linear regression analysis revealed that PI was an independent risk factor for JLCA in female patients.In male patients,SS is an independent risk factor for MAD.However, in the SKOA group, there was no significant correlation between JLCA,MAD and LL,SS and PI in either male or female (P>0.05),suggesting that gender had less influence on the relationship between these parameters in the more severe stage of the disease.
Conclusion:There were differences between lumbar vertebrae-pelvic parameters and knee line of force in patients with limited knee osteoarthritis of different genders.The JLCA was associated with Pelvic retroversion and straightening of lumbar curvature in women,while the shift of mechanical axis deviation was associated with Pelvis forward in men.In patients with severe knee osteoarthritis,lumbar-pelvic parameters were not associated with knee line of force,and gender differences disappeared.
Midkine Attenuates Aβ Fibril Assembly and Amyloid Plaque Formation
Authors: Peng Junmin , Zaman Masihuz , Yang Shu , Huang Ya , Yarbro Jay , Wang Zhen , Liu Danting , Soliman Hadeer , Hemphill Alex , Harvey Sarah , Pruett-Miller Shondra , Stewart Valerie , Tanwar Ajay , Kalathur Ravi , Grace Christy , Turk Martin , Chittori Sagar , Jiao Yun , Wu Zhiping , High Anthony , Wang Xusheng , Serrano Geidy , Beach Thomas , Yu Gang , Yang Yang , Chen Ping-Chung 
Published: June 2024

Abstract

Proteomic profiling of Alzheimer's disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with Aβ since the early disease stage, but their roles in disease progression are not fully understood. Here we present that MDK attenuates Aβ assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both Aβ40 and Aβ42 peptides in Thioflavin T fluorescence assay, circular dichroism, negative stain electron microscopy, and NMR analysis. Knockout of Mdkgene in 5xFAD increases amyloid formation and microglial activation. Further comprehensive mass spectrometry-based profiling of whole proteome and aggregated proteome in these mouse models indicates significant accumulation of Aβ and Aβ-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in Alzheimer's disease.
A new kind of colleague for the future? Nurses’ evaluation of a service robot for inpatient care – A technology acceptance study
Authors: Friese Christopher , Klebbe Robert , Heimann-Steinert Anika 
Published: June 2024

Abstract

Background: Nursing is increasingly being enhanced by the use of assistive technologies. These technological advances include assistive robots, which have already shown positive impacts on older adults as well as formal and informal caregivers. However, a lack of end-user acceptance is considered one of the most significant barriers to the implementation and successful long-term use of robots in nursing. Therefore, a user-centered research and development approach is particularly important to ensure the use of robotics is not technology-driven, but oriented towards nursing goals and processes.
Methods: Our study presents the results of the evaluation of a service robot developed for routine tasks in inpatient care in a user-centered design. In three scenarios (information service, delivery of items, and delivery of beverages), 30 nurses tested the robot in a simulated care setting with regard to acceptance-related dimensions and the intention to use the system. In addition, the participants’ general attitudes towards robots and robotics experiences were surveyed.
Results: Generally, the robot was seen as user-friendly and useful. Skepticism towards the system was low and the accessibility was rated as moderate. Overall, a high intention to use was reported. No significant differences were identified in the assessment of the robot between participants with and without robotics experience. However, dependency analyses showed various strongly significant correlations. Usability, perceived usefulness, and accessibility as well as a personal positive attitude towards robots all correlated positively with the intention to use. Skepticism towards the system correlated negatively.
Conclusion: In our study, a high level of acceptance was measured for the developed service robot within the selected application scenarios. In line with the current state of research, our results suggest that the target group-specific communication of robot capabilities and limitations as well as opportunities for personal experience are particularly important aspects for promoting the intention to use and acceptance of robotic systems. Strategies for the transfer of knowledge and skills as well as financing concepts are urgently needed so that the nursing sector can become more widely aware of and benefit from the potential of robotics.
Insights into long-term glass corrosion mechanisms from the Ballidon project: a 50-year-old glass burial experiment in an alkaline near surface environment.
Authors: Thorpe Clare , Fisher Adam , Manifold Garry , Creasey-Gray Stuart , Jackson Caroline , Stone J , Corkhill Claire , Boothman Christopher , Lloyd Jonathan , Hand Russell 
Published: June 2024

Abstract

Results are presented from the Ballidon experiment, one of the longest running glass durability experiments. Nine glasses of varying composition including simulant Roman and medieval glasses, as well as borosilicate, plate glass, soda-lime-silica, E-glass and a lead optical glass were buried in mildly alkaline and under-saturated conditions for 50 years. The relative durability of the nine glasses compared well with that predicted by the stirred reactor coupon analysis (SRCA) short-term durability test with alteration layers present on the least durable glasses and only localised (vermiform) attack observable on the most durable glasses. Alteration layers on the naturally altered Ballidon samples were analysed with particular attention to the influence of elements from the environment on their chemical composition and to evidence of post-formation evolution of the layers. It was evident that Ca (from the limestone sediment) and P (from the local groundwater) were sequestered in alteration layers and contributed to the formation of Ca, Pb and Fe-phosphate rich phases. Separation of the alteration layers into ‘bands’ or lamellae with different chemical environments occurred in poorly durable glasses, with Si and Al rich bands alternating with Ca, Fe and P rich bands. There was evidence that banding in alteration layers moved and evolved over time in response to water ingress, for example from cracks and fissures.
Research on Time-Varying Path Optimization for Multi-Vehicle Type Fresh Food Logistics Distribution Considering Energy Consumption
Authors: Chen Hao , Wang Wenxian , Jia Li , Wang Haiming 
Published: June 2024

Abstract

With the increasing demand for fresh food markets, refrigerated transportation has become an essential component of logistics operations. Currently, fresh food transportation frequently faces issues of high energy consumption and high costs, which are inconsistent with the development needs of the modern logistics industry. This paper addresses the optimization problem of multi-vehicle type fresh food distribution under time-varying conditions. It comprehensively considers the changes in road congestion at different times and the quality degradation characteristics of fresh goods during distribution. The objectives include transportation cost, dual carbon cost, and damage cost, subject to constraints such as delivery time windows and vehicle capacity. A piecewise function is used to depict vehicle speeds, proposing a dynamic urban fresh food logistics vehicle routing optimization method. Given the NP-hard nature of the problem, a hybrid Tabu Search (TS) and Genetic Algorithm (GA) approach is designed to compute a Pareto optimal solution. Comparison with TS and GA algorithm results shows that the TS-GA algorithm provides the best optimization efficiency and effectiveness for solving large-scale distribution problems. The results indicate that using the TS-GA algorithm to optimize a distribution network with one distribution center and 30 delivery points resulted in a total cost of CNY 12,934.02 and a convergence time of 16.3 seconds. For problems involving multiple vehicle types and multiple delivery points, the TS-GA algorithm reduces the overall cost by 2.94–7.68% compared to traditional genetic algorithms, demonstrating superior performance in addressing multi-vehicle, multi-point delivery challenges.
Impacts of aerosol concentration on precipitation pattern of tropical cyclones in South China area
Authors: Shi Xiaoming , Mak Ho Yi Lydia , Zhang Yi 
Published: June 2024

Abstract

Previous studies have discovered that an increase in aerosol concentration could affect the development of precipitation and tropical cyclones. However, with increasing efforts to mitigate climate change, the amount of aerosols in the atmosphere is expected to decrease in the future. This study aims at understanding how such a reduction in aerosol number concentration could affect the precipitation pattern of tropical cyclones through case studies of Typhoon Haikui and Koinu. The Thompson aerosol-aware microphysics scheme in the Weather Research and Forecst(WRF) model is used, and the water-friendly aerosol number concentration is reduced by a factor of 100. For both tropical cyclones, a reduction in aerosol results in consistent expansion of precipitation area due to the enhanced warm rain process. However, the mean precipitation intensity of Koinu decreases while that of Haikui increases, depending on whether warm-rain or ice-phase dominates and whether upper-level convection is altered.
Inhibition of capD gene confers disrupted capsule development and decreased pathogenicity in Elizabethkingia miricola
Authors: Hu Ruixue , Liu Fangyuan , Yu Fang , Hou Jiahao , Chen Dan , Gu Zemao 
Published: June 2024

Abstract

Elizabethkingia miricola is a multidrug-resistant pathogen that can cause life-threatening infections in immunocompromised patients and outbreaks in amphibians. However, the specific virulence factors of this microorganism have not been previously determined. In this study, we identified the polysaccharide biosynthesis protein gene capD, located in the conserved region of the Wzy-dependent capsule synthesis gene cluster in E. miricola strain FL160902, and investigated its role in the pathogenesis of E. miricola. Our results showed that the capD deletion strain (ΔcapD) lost its typical encapsulated structure with a 45% reduction in cell wall thickness. CapD affects Wza expression in the capsule polysaccharide synthesis pathway. Furthermore, the survival rates were significantly reduced in ΔcapD in response to complement-mediated killing, desiccation stress, oxidative stress, and macrophage phagocytosis, while biofilm formation, self-aggregation ability, and adherence to both endothelial and epithelial cells were enhanced. Additionally, the deletion of ΔcapD sharply attenuated the virulence of E. miricola in a frog infection model. Overall, these findings suggest that CapD contributes to polysaccharide synthesis and plays a crucial role in the pathogenesis of E. miricola.
Assessing Artificial Intelligence-Generated Patient Discharge Information for the Emergency Department: A Pilot Study
Authors: De Rouck Ruben , Wille Evy , Gilbert Allison , Vermeersch Nick 
Published: June 2024

Abstract

Background: Effective patient discharge information (PDI) in emergency departments (EDs) is vital and often more crucial than the diagnosis itself. Patients who are well informed at discharge tend to be more satisfied and experience better health outcomes. The combination of written and verbal instructions tends to improve patient recall. However, creating written discharge materials is both time-consuming and costly. With the emergence of generative artificial intelligence (AI) and large language models (LMMs), there is potential for the efficient production of patient discharge documents. This study aimed to investigate several predefined key performance indicators (KPIs) of AI-generated patient discharge information.
Methods: This study focused on three significant patients’ complaints in the ED: nonspecific abdominal pain, nonspecific low back pain, and fever in children. To generate the brochures, we used an English query for ChatGPT-4 (an LLM) and DeepL software to translate the brochures to Dutch. Five KPIs were defined to assess these PDI brochures: quality, accessibility, clarity, correctness and usability. The brochures were evaluated for each KPI by 8 experienced emergency physicians using a rating scale from 1 (very poor) to 10 (excellent). To quantify the readability of the brochures, frequently used indices were employed: the Flesch Reading Ease, Flesch-Kincaid Grade Level, Simple Measure of Gobbledygook, and Coleman-Liau Index on the translated text.
Results: The brochures generated by ChatGPT-4 were well received, scoring an average of 7 to 8 out of 10 across all evaluated aspects. However, the results also indicated a need for some revisions to perfect these documents. Readability analysis indicated that brochures require high school- to college-level comprehension, but this is likely an overestimation due to context-specific reasons as well as features inherent to the Dutch language.
Conclusion: Our findings indicate that AI tools such as LLM could represent a new opportunity to quickly produce patient discharge information brochures. However, human review and editing are essential to ensure accurate and reliable information. A follow-up study with more topics and validation in the intended population is necessary to assess their performance.