bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of Diabetic Ketoacidosis at Onset, Diabetes Technology Uptake, and Clinical Outcomes After 1 and 2 Years of Follow-up: A Collaborative Analysis of Pediatric Registries Involving 9,269 Children With Type 1 Diabetes From Nine Countries
Authors: Dovc Klemen , Neuman Vit , Gita Gemulla , Cherubini Valentino , Alonso G. Todd , Fritsch Maria , Boettcher Claudia , de Beaufort Carine , Holl Reinhard W. , de Bock Martin 
Published: February 2025

OBJECTIVE
This study examined the association between diabetic ketoacidosis (DKA) at type 1 diabetes diagnosis and long-term glycemic outcomes, insulin requirements, BMI SDS, and diabetes technology uptake in youth.

RESEARCH DESIGN AND METHODS
Data were from nine countries (Austria, Czechia, Germany, Italy, Luxembourg, New Zealand, Slovenia, Switzerland, and U.S. [Colorado]), including youth (0.5–15.9 years) diagnosed with type 1 diabetes in 2019–2020 and followed for 2 years thereafter. Participants were divided into three groups: no DKA, nonsevere, and severe DKA at diagnosis. HbA1c, insulin requirements, BMI SDS, and use of technology, including automated insulin delivery (AID), were assessed.

RESULTS
The analysis included 9,269 individuals (54.8% males, mean age 9.0 years). DKA at diagnosis was observed in 34.2% of participants and severe DKA in 12.8%. After 1 year, adjusted mean HbA1c was higher in the severe DKA group (7.41%) compared with nonsevere DKA (7.23%, P = 0.001) and no DKA groups (7.14, P &lt; 0.001), and this difference persisted after 2 years (7.58% vs. 7.38% [P &lt; 0.001] and vs. 7.32% [P &lt; 0.001]). Higher BMI SDS was observed in both DKA groups compared with no DKA. The use of AID was associated with lower HbA1c levels compared with other treatment modalities and moderated differences between DKA groups after 2 years of follow-up (P = 0.072).

CONCLUSIONS
Severe and nonsevere DKA at type 1 diabetes diagnosis were both associated with persistently higher HbA1c and higher BMI SDS. AID use diminishes the association of DKA at diagnosis and higher HbA1c over time.
Aleksej Navalnyj. Å drepe en fremtid
Authors: Lassen Morten 
Published: February 2025

Færseths bog Aleksej Navalnyj. Å drepe en fremtid er en glimrende journalistisk fortælling om Navalnyjs vej til at blive Kremls fjende nummer ét. Nye læsere vil få et fint overblik, men samtidig er det en bog uden referencer, og uden en forståelse for den historiske arv og dens konsekvenser for Ukraine-krigen.
Færseth's book Aleksej Navalnyj. Å drepe en fremtid (Aleksey Navalny. To Kill a Future) is an excellent journalistic account of Navalny's path to becoming the Kremlin's enemy number one, and readers will get a solid overview. Nevertheless, the book lacks references and an understanding of the historical legacy and its consequences for the war in Ukraine.
High doses of buprenorphine hydrochloride are well tolerated and produce a mild and prolonged thermal antinociceptive effect in orange-winged Amazon parrots (Amazona amazonica)
Authors: Douglas Jamie M. , Guzman David Sanchez-Migallon , Beaufrère Hugues , Paul-Murphy Joanne R. 
Published: February 2025

Abstract

Objective
To evaluate the duration of action and antinociceptive and sedative effects of buprenorphine hydrochloride following SC administration to orange-winged Amazon parrots (Amazona amazonica).

Methods
10 adult, healthy Amazon parrots were included. High-concentration buprenorphine formulation (1.8 mg/mL and 0.1, 1, and 2 mg/kg) and saline solution (0.9% NaCl; 0.55 mL/kg) were administered SC to the parrots in a within-subjects, complete, masked crossover study design. Foot withdrawal thermal threshold was determined prior to administration of treatment and 0.5, 1.5, 3, and 6 hours postinjection. Agitation-sedation scores were determined 1 to 2 minutes prior to each thermal challenge.

Results
Buprenorphine at 2 mg/kg significantly increased the thermal foot withdrawal threshold, whereas lower doses evaluated did not have a significant effect. Although no significant interaction effect of treatment*time was observed, the graphical data suggest that the effect could increase over time and still be present at the 6-hour time point. No significant effect of buprenorphine on agitation-sedation score or nausea-like behavior was observed.

Conclusions
SC administration of buprenorphine at 2 mg/kg has a mild thermal antinociceptive effect in orange-winged Amazon parrots, which graphically appears to have a slow onset and last for the duration of the testing times. In addition, buprenorphine did not cause agitation or sedation, nausea-like behavior, or vomiting. Further studies are needed to fully evaluate the effects of buprenorphine in psittacines.

Clinical Relevance
Buprenorphine hydrochloride could be considered for pain management in the orange-winged Amazon parrot and does not cause significant adverse effects following single SC administration.
Mild Transmissible Gastroenteritis in Pigs Suckling Vaccinated Sows
Authors: Larson D. J. , Solorzano R. F. , Morehouse L. G. , Olson L. D. 
Published: February 2025

SUMMARY
A strain of transmissible gastroenteritis (tge) virus of low virulence was isolated from 14-day-old pigs suckling sows vaccinated with an attenuated tge vaccine. Diarrhea developed in suckling pigs approximately 14 days after farrowing in 4 farrowings; however, none of these pigs died from diarrhea. Diarrhea ceased after the 4th farrowing, when vaccination of sows was discontinued. Experimentally, both the field isolate and the vaccine strain were infective and in some instances lethal for 2-day-old pigs exposed orally; however, neither strain was as virulent as the Purdue strain.
Progeny Testing for Bovine Syndactyly
Authors: Johnson J. L. , Leipold H. W. , Snider G. W. , Baker R. D. 
Published: February 2025

SUMMARY
Syndactylous donors, superovulation, embryo transfer, and fetal removal via cesarean section were used to test our Holstein-Friesian bulls suspected of being heterogous for syndactyly. Two bulls produced syndactylous fetuses, and thus were proved heterozygous. The other to bulls each sired eight normal fetuses and were assumed to be homozygous normal.
Clinicopathologic manifestations of progressive renal disease in Lhasa Apso and Shih Tzu dogs
Authors: O'Brien Timothy D. , Osborne Carl A. , Yano Barry L. , Barnes Donald M. 
Published: February 2025

SUMMARY
Chronic generalized renal disease was detected in 21 Lhasa Apso and 14 Shih Tzu dogs. Most were growing pups or young adults at the time of diagnosis. The most commonly reported clinical abnormalities were vomiting, polydipsia, weight loss, and diarrhea. Less frequently reported signs included polyuria, anorexia, dehydration, and depression. Common abnormal laboratory findings included non-regenerative anemia, impaired ability to concentrate urine, and azotemia. Less common abnormal laboratory findings included hyperphosphatemia, hypocalcemia, metabolic acidosis, hypoproteinemia, hyperamylasemia, and mild hyperkalemia. Two dogs were mildly hypercalcemic. Gross morphologic renal changes included bilateral reduction in size and irregular capsular surfaces. Microscopic lesions of varying severity affected various components of nephrons in the cortex and medulla. Cortical lesions were often segmental in distribution; medullary lesions were consistently diffuse and generally more severe than those in the cortex. Lesions in both areas commonly resulted in destruction of nephrons, with subsequent replacement by collagenous connective tissue. Infiltrates of interstitial mononuclear cells were conspicuously absent.
The cause of the renal disorder in Lhasa Apso and Shih Tzu dogs could not be determined on the basis of observations in this study. Current managment is limited to appropriate supportive and symptomatic therapy designed to minimize fluid, electrolyte, acid-base, endocrine, and nutrient imbalances caused by renal dysfunction.
Research on optimisation of transformer manufacturing process and construction of smart factory based on digital twin technology
Authors: Yang Jiexuan , He Xuye , Zhang Jian , Wu Xingwang , Wang Hong 
Published: February 2025

Abstract
As the manufacturing process of a transformer needs to go through many kinds of processes, the good or bad manufacturing process directly affects the performance level of the transformer. In this paper, the green manufacturing process chain of transformers is established by comprehensively considering resource and energy consumption, as well as environmental impact. Based on the existing technical architecture of the manufacturing workshop, a digital twin technology architecture system is proposed for the manufacturing process. Starting from the three dimensions of the key elements of the twin model, entity modelling, digital twin virtual modelling, and virtual-reality mapping association modelling, a unified logical data model is established, and the design of the smart factory of a transformer manufacturing enterprise is completed. Experiments show that in the new working conditions based on digital twin technology, the accuracy error in transformer production is less than 0.02mm, and the production order delay rate has significantly improved. The manufacturing process optimisation module has better processing parameter monitoring and processing process simulation performance and also realises the constant power adaptive control of the processing process, which helps to improve the processing efficiency and processing accuracy of the manufacturing process.
A data-driven high-speed railway service quality optimisation model and its influencing factors for grouping research
Authors: Yuan Fang , Qiu Xiaodong 
Published: February 2025

Abstract
High-speed railway service quality is a kind of experience and the degree of satisfaction of the experience when passengers consume passenger transport services, focusing on the process of service and the perceived satisfaction of passengers. This paper establishes the service quality evaluation index framework and system for high-speed railways by combining the concept of service quality for high-speed railways with the SERVQUAL model. The SERVQUAL evaluation model calculates the SQ score of each service factor to understand the change in service quality and combines the index weights and scores to calculate the recommendation degree of service quality optimisation of high-speed railways. The fsQCA method is introduced to construct the high-speed railway service quality influence model, and the data is obtained through a questionnaire to carry out a group analysis of the influence factors. The mean value of the evaluation score of high-speed railway service quality is -0.46, and the optimisation recommendation degree of the high-speed railway service quality optimisation indicators that need to be optimised is lower than -0.01. The coverage of the solutions in the group analysis is 0.872, which indicates that the five groupings are able to explain more than 87.2% of the high-speed railway service quality related cases in the sample. The data-driven service quality optimisation of high-speed railways needs to pay attention to the optimisation of basic service equipments and tools, and improve the dynamic response ability to better satisfy the needs of passengers in order to enhance their sense of access.
Research on power dynamic data sample generation technology based on brain-like computation and its efficient computation methods
Authors: Zhang Peng , Zhang Guoliang , Zhou Fei , Kong Qingyu , Chu Zongbo , Fan Xiaoyu , Xia Weishang 
Published: February 2025

Abstract
The paper aims to address the issue of insufficient fault samples in UHV converter equipment, which hinders their intelligent operation and inspection. For the operation and inspection of UHV converter equipment, this paper suggests a multimodal brain-like learning sample spatio-temporal correlation generation method. This method grabs typical fault samples from the defect-fault development time sequence process and creates samples using the nearest-neighbor generating segment technique by fusing the time sequence evolution law and the similarity of the adjacent samples. Based on the physical model of the converter and converter valve, we analyze the fault development laws of partial discharge, high temperature overheating, and micro-motion wear. The multimodal fault sample generation model with an embedded fault mechanism is established by integrating the time-sequence fault evolution mechanism and the spatial correlation between multimodal state quantities. The simulation demonstrates that brain-like learning generates samples embedded in the fault evolution laws of converter partial discharge and converter valve IGBT micromotion wear in 539 columns, encompassing 376 converter and 163 converter valve cases. The consistency between the generated samples and the actual samples exceeds 90%, thereby facilitating the training of brain-like models for health assessment of extra-high-voltage converter equipment, fault diagnosis, and trend prediction.
Research on Interactive Content Development of Vocal Music Teaching in College Music Courses in the New Media Era
Authors: Hu Zhanjun 
Published: February 2025

Abstract
With the rapid development and popularity of the Internet, the integration of teaching content and new media is constantly deepening. Modern new media technology is being applied to the teaching of vocal music, and studying the combination of new media and vocal music teaching is crucial for advancing the development of vocal music curricula in colleges and universities. This study concentrates on interactive content, examining the interactive expression methods of new media technologies from a fresh perspective. Combined with the demand for the cultivation of students’ core qualities in vocal music teaching, the study further develops and optimizes the interactive content of vocal music teaching, integrates it with vocal music teaching, and proposes a vocal music teaching mode based on the optimized interactive content of this paper. To further verify the effectiveness of the vocal music teaching mode, this paper employs the hierarchical analysis method and factor analysis to construct an evaluation index system that measures the impact of interactive vocal music teaching. The weights of the five first-level indicators in the evaluation index system of this paper are 0.315, 0.300, 0.198, 0.083, and 0.104, which make the evaluation indicators reasonable and effective. In the teaching experiment, the mean value of each index in the optimized vocal music teaching mode, which is based on the development of new media interactive content, ranges from high to low: the teaching content (4.635), the teaching effect (4.552), the teaching goal (4.430), the teaching average (4.354), and the teaching method (4.123). The overall mean score was 4.339, indicating excellent overall teaching effectiveness and providing new insights into the development of interactive content for vocal music teaching.
Research on the Role of Digital Media Technology in the Cultural Inheritance of Fujian-Taiwan Folk Songs
Authors: Guo Wei , Wang Xiaoning , Tong Weiwei 
Published: February 2025

Abstract
Fujian-Taiwan folk song culture is a typical representative of the excellent traditional culture of the Chinese nation, and it has important cultural and artistic value for the inheritance and protection of Fujian-Taiwan folk song culture. In this paper, an infectious disease model is used to construct a cultural inheritance model of Fujian-Taiwan folk songs. The model parameters are solved using genetic algorithms to explore the influence of digital media technology support on the cultural inheritance development trend of Fujian-Taiwan folk songs. Based on digital media technology, the Hidden Markov Algorithm is used to design an automatic creation model for Fujian-Taiwan folk songs. It improves the quantity and quality of the creation of Min-Taiwan folk songs, increases the dissemination base of Min-Taiwan folk song culture, and thus promotes the inheritance of Min-Taiwan folk song culture. The HMM model used in this paper is significantly better than other models involved in the comparison of both reconstruction performance and objective index evaluation. In the subjective human-ear comparison, the mean scores of the Fujian-Taiwan folk song samples created by the HMM model in terms of naturalness and pleasantness were 8.47 and 8.39, respectively, which were significantly higher than those of the other models, and were closer to the mean scores of the real samples. This paper’s model is effective in creating Fujian-Taiwan folk songs and contributes to the lasting heritage of Fujian-Taiwan folk song culture.
A Study of Using Deep Learning Technology to Improve the Accuracy of Polyphonic Singing in Community Choirs
Authors: Li Yue , Wang Dan 
Published: February 2025

Abstract
Polyphonic choral singing can not only cultivate musical imagination and improve musical literacy but also allow singers to feel the harmonious and beautiful musical rhythm during polyphonic choral singing. To improve the accuracy of polyphonic singing, the study designed a music source separation structure based on recurrent neural networks using deep learning technology. And, combined with ResNet and CBAM, a joint neural network based on Res-CBAM was designed for optimization. After that, the main melody of the human voice was extracted using the polyphonic music melody extraction algorithm that was created in this paper. The listening training was then done in three areas: pitch, rhythmic rhythm, and vocal balance. The trained community choir members showed significant improvements in singing ability, breath control, pitch, rhythm, polyphonic choral ability, and expressiveness (p<0.05). It indicates that the auditory discrimination training based on the polyphonic music melody extraction algorithm has a facilitative effect on the accuracy of polyphonic singing in the choir.
Innovative Research on Digital Talent Cultivation Mode of Higher Vocational Innovation and Entrepreneurship Education Promoted by Industry-Teaching Integration
Authors: Kong Tingting , Feng Lin , Guo Quan 
Published: February 2025

Abstract
As an important concept of modernisation and reform of higher vocational education, the integration of industry and education can make important contributions to economic and social development, and it is also the main mode of higher vocational education. By studying the trend of the development of higher vocational industry-teaching integration, this paper finds that the top three secondary themes of industry-teaching integration are 3,875 articles on industry-teaching integration, 855 articles on talent cultivation and 758 articles on digitisation, and digital talent cultivation is still popular in the research of industry-teaching integration. In order to promote the integration of industry and education in higher vocational innovation and entrepreneurship education and explore the digital talent cultivation mode, this paper constructs a comprehensive evaluation index system for the integration of industry and education through fuzzy hierarchical analysis on the basis of hierarchical analysis and fuzzy comprehensive evaluation, using triangular fuzzy numbers to act as the evaluation language. Then the dilemmas and problems of de-development are analysed using the evaluation system that integrates industry and education. It can be seen through the evaluation results that, in the evaluation index system of integration of industry and education, the effect index of integration of industry and education is the highest at 84.109. However, the score of the index of resource allocation for the integration of industry and education is only 56.754, and there are serious problems with resource allocation in the development of the integration of industry and education. For this reason, this paper constructs a digital talent cultivation model for higher vocational innovation and entrepreneurship education, starting from the talent cultivation mechanism and resource cooperation path for the problems of industry-teaching integration, in order to achieve the deep intermingling of innovation and entrepreneurship education and industry-teaching integration in higher vocational education and to promote the cultivation of digital talents.
An empirical study on the improvement of students’ physical fitness and health in college physical education programmes based on big data
Authors: Chen Jun 
Published: February 2025

Abstract
Improving the quality of college physical education classroom teaching, ensuring that the course can achieve the due exercise load, and at the same time ensuring that the content arrangement of the physical education classroom can promote the development of students’s physical fitness and health, has become an important issue facing the physical education teaching in colleges and universities. This paper constructs a sports teaching IOT platform based on heart rate monitoring, which takes the heart rate belt as the sensor and completes the connection and transmission of the user’s heart rate data through the NFC device and the mobile smart device based on the Android system. It realizes the monitoring of the user’s heart rate data. Based on this heart rate monitoring platform, a decision tree algorithm for college students’ physical fitness data analysis is proposed, which analyzes the physical fitness and health status of the overall students in the school through the uploaded heart rate data, thus providing reasonable suggestions for the arrangement of physical education curriculum content. The heart rate monitoring method in this paper can achieve over 85% monitoring accuracy in a shorter execution time, and the decision tree algorithm for college student fitness optimization can control the students’ heart rate within the optimal heart rate index interval of aerobic exercise. Physical fitness test experiments show that they can provide the basis and guarantee for the core literacy of students’ physical education courses, and provide new ideas for promoting the innovative development of physical education.
Knowledge Graph Technology Helps Intelligent Reform of Innovation and Entrepreneurship Guidance Courses for College Students
Authors: Chen Yeting , Chen Wenchi 
Published: February 2025

Abstract
Constructing personalised learning resources based on a knowledge graph is an innovative work for the intelligent reform of college students’ innovation and entrepreneurship guidance courses. In this paper, we design a personalised recommendation method for resources based on a knowledge graph and finally construct a KG-NCF model to realise intelligent recommendations of learning resources for college students’ innovation and entrepreneurship guidance courses. The study uses the recall evaluation index to validate different recommendation methods. The average recall of this paper’s method is 0.738, which is higher than other algorithms by 0.044 to 0.132. The mean value of students’ evaluation of the innovation and entrepreneurship guidance course applying this paper’s method is 3.37 points, which is 1.37 points higher than the standard score. It shows that the personalised resource recommendation model based on a knowledge graph can provide higher quality innovation and entrepreneurship learning resources for university students.