bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tratamiento de camuflaje en paciente clase II esqueletal con laterognasia mandibular: Reporte de caso clínico
Authors: Montaño-Cisneros Ilse Montserrat , Moreno-Moreno José Javier , Rodríguez-Chávez Jaqueline Adelina , Villanueva-Betancourt Daniel , Meléndez-Ruiz José Luis , Paz-Cristóbal Alejandra Noemí 
Published: February 2025

Introducción: en pacientes clase II que tienen una discrepancia en forma y tamaño de maxilar y mandíbula se genera una desarmonía facial. Los tratamientos para su corrección se realizan de manera ortopédica, ortodóntica, ortoquirúrgica o una combinación de estas. Objetivo: establecer correcta sobremordida horizontal y vertical, eliminar curva de Spee, mantener clase molar I, establecer clase I canina. Presentación del caso: se presenta paciente clase II esqueletal división 1, clase I molar, clase canina no establecida, dentición mixta, línea media inferior desviada 3mm a la derecha (Laterognasia) sobremordida horizontal 1mm, sobremordida vertical 0mm. Se coloco aparatología Roth slot 0.018”, extracciones de primeros premolares superiores e inferiores, uso de elásticos de línea media. Se mantuvo clase I molar, se logró clase I canina, con mejor sobremordida vertical y horizontal. Conclusión: El presente trabajo sugiere el camuflaje ortodóncico como una alternativa de tratamiento cuando el paciente no está dispuesto a someterse a una cirugía ortognática.
Fatores explicativos para o uso de cartão de crédito por alunos do curso de gestão de cooperativas de universidades brasileiras
Authors: Invenção de Jesus Sandra , Bruno de Jesus Silva Thiago , Sousa Allison Manoel de , Juliano Duarte Matias Hugo , Sell Filipy Furtado 
Published: February 2025

O objetivo do estudo foi analisar a relação da educação financeira e do otimismo como fatores explicativos do uso de cartões de crédito por estudantes do curso de Gestão de Cooperativas de Universidades Brasileiras. A abordagem do estudo foi quantitativa e descritiva. A amostra compreende 112 respostas do levantamento aplicado a estudantes de graduação. Os achados da pesquisa demonstram que a maior parcela dos estudantes (77,68%) possui cartão de crédito evidenciando o crescimento acelerado dos níveis de consumo. Quanto à educação financeira, grande parte dos estudantes não tem curso de finanças pessoais (média de 1,9464). A educação financeira tem relação significativa e negativa ao uso dos cartões de créditos. Os respondentes demonstraram-se otimistas apesar do otimismo não possuir relação significativa com o uso do cartão de crédito. Este estudo é relevante ao compreender os fatores que influenciam o uso do cartão de crédito.
Urate nephrolithiasis in ranch mink
Authors: Tomlinson Michael J. , Perman Victor , Westlake Robert L. 
Published: February 2025

SUMMARY
Urate nephrolithiasis with epistaxis and bleeding around foot pads was diagnosed in ranch mink. Investigation of affected, unaffected-related, and unaffected-unrelated mink did not disclose the cause of these problems but did eliminate inherited bleeding disorders as a cause of the bleeding. All affected mink were males, had been sired by related sires, and were affected in the 1st year of life. Elimination of affected mink and their parents from the breeding stock eliminated the condition from the herd. The findings were consistent with an inherited defect in uric acid metabolism or excretion.
Paradoxic hypercalcemia and hypophosphatemia associated with chronic renal failure in horses
Authors: Tennant Bud , Bettleheim P. , Kaneko J. J. 
Published: February 2025

SUMMARY
Chronic renal failure associated with hypercalcemia and hypophosphatemia was diagnosed in 6 horses. The renal lesions in 5 of the horses were classified as chronic glomerulonephritis and in the sixth, as chronic interstitial nephritis/pyelonephritis. There was no evidence of primary hyperparathyroidism or pseudohyperparathyroidism, thus suggesting that hypercalcemia associated with advanced renal failure in horses is related to a unique role of the equine kidney in calcium homeostasis.
Glycosylated hemoglobin in diabetic and nondiabetic dogs
Authors: Mahaffey Edward A. , Cornelius L. M. 
Published: February 2025

SUMMARY
Glycosylated hemoglobin (HbA1) was measured in 40 nondiabetic hospitalized dogs, 16 clinically normal laboratory colony dogs, and 16 diabetic dogs. Mean HbA1 values (% of total Hb) for the 3 groups were 6.43, 5.62, and 9.63, respectively. The mean values for the 2 nondiabetic groups differed significantly (P<0.05), and the mean values for the nondiabetic dogs were significantly lower than the mean value for that of the diabetic dogs (P<0.001). Fifteen of 16 diabetic dogs had HbA1 concentrations greater than 7.5%. These results suggested that HbA1 measurement may be valuable for monitoring effectiveness of therapy in canine diabetes mellitus.
Hypoadrenocorticism following therapy with o,ṕ-DDD for hyperadrenocorticism in four dogs
Authors: Willard M. D. , Schall W. D. , Nachreiner R. F. , Shelton D. G. 
Published: February 2025

SUMMARY
Hypoadrenocorticism developed in 4 of 26 dogs treated with mitotane (o,ṕ-DDD) for hyperadrenocorticism. Evidence of the hypoadrenocorticism was detected from 2-8 weeks after the beginning of weekly or bimonthly maintenance o,ṕ-DDD therapy.
The adversely affected dogs had hyponatremia plus hyperkalemia, and 3 of the 4 had severely diminished plasma cortisol concentrations at rest or after stimulation with ACTH given im. One dog did not have detectable plasma aldosterone concentrations before or after ACTH administration. Clinically, 3 of the 4 dogs responded well to mineralocorticoid replacement. Electrolyte determinations after replacement therapy in 1 dog documented normal serum sodium and potassium concentrations. One dog died despite therapy and was determined to have adrenocortical destruction.
Antimicrobic resistance and susceptibility in five bacterial pathogens: A comparison of susceptibility tests in 1974 and 1978
Authors: Glisan Gary L. , Steele James H. , Whitford Howard , Christensen Bobbe L. , Kapadia Asha 
Published: February 2025

SUMMARY
A study based on a review of records of bacterial cultures in 1974 and 1978 was conducted to ascertain any changes in patterns of antimicrobic resistance or susceptibility to 13 selected antimicrobics. Isolates of Salmonella spp, Escherichia coli (encapsulated), E coli (hemolytic), Pasteurella haemolytica, and Pasteurella multocida were obtained from bovine, equine, porcine, ovine, and caprine animals, or their tissues, submitted to the Texas Veterinary Medical Diagnostic Laboratory from September 1973 through August 1974 and from September 1977 through August 1978. Two groups, bovine and combined species (including bovine), were formed. Information was collated by year and simple proportions, using the number of tests wherein the organism was resistant as the numerator and total sensitivity tests as the denominator, were calculated for each antimicrobic/organism combination. Proportions from year groups 1974 and 1978 were then compared to ascertain any changes in antimicrobic susceptibility. In the bovine group, encapsulated E coli had increased resistance to 3 antimicrobics and decreased resistance to 1 antimicrobic, hemolytic E coli had decreased resistance to 1 antimicrobic, Salmonella spp had decreased resistance to 6 antimicrobics, and P haemolytica had decreased resistance to 5 antimicrobics. In the combined species group, encapsulated E coli had decreased resistance to 2 antimicrobics, hemolytic E coli had decreased resistance to 1 antimicrobic and increased resistance to another antimicrobic, Salmonella spp had decreased resistance to 8 antimicrobics and increased resistance to 1 antimicrobic, P haemolytica had decreased resistance to 5 antimicrobics, and P multocida had decreased resistance to 2 antimicrobics.
The data indicated an overall decrease in the proportion of organisms resistant to antimicrobics in 1978, as compared with 1974.
Design and Application of English Language and Literature Smart Classroom Based on Artificial Intelligence Technology
Authors: Zhang Zhi 
Published: February 2025

Abstract
The development of artificial intelligence (AI) technology has revolutionized the education industry. The study introduces artificial intelligence technology into the teaching of English language and literature, and designs an intelligent classroom teaching model of English language and literature with five aspects: teaching, learning, examining, evaluating and managing. The intelligent classroom model’s intelligent technology design is demonstrated by using the appreciation of English Language and Literature as an example. The scoring rules are used as the model input to construct the automatic scoring model of literary works with improved two-layer LSTM. Through comparison experiments, it is found that the mean value of QWK of the improved two-layer LSTM model has been significantly improved by 3.18%~9.76% compared with the comparison, which reflects a better scoring performance of the English language and literature compositions. In addition, the smart classroom teaching model has an enhancement effect on students’ performance, and the learning performance of practicing students is 5.24% and 7.66% higher than that of the control students and before the experiment, respectively, and the smart classroom of English Language and Literature based on Artificial Intelligence technology is able to promote the enhancement of the students’ learning level, and realize the intelligent and efficient development of English language teaching.
A Study of Online Behavioural Data Analysis and Teaching Intervention Strategies for College English Learners
Authors: Zhang Hui 
Published: February 2025

Abstract
This study aims to understand the characteristics of online learning behaviors among modern online education learners, implement these behaviors, propose strategies for learning support services, and propose reform proposals to enhance the quality of online teaching. This paper collects English learners’ online learning behavior data from relevant learning platforms and quantifies as well as processes the data. Subsequently, a model of behavioral analysis is constructed using social network analysis and the DBSCAN clustering method. The teacher takes the lead in teaching social behavior, ensuring that other English learners do not feel isolated from each other. By extracting the behavioral data of 5163 students for analysis, the English learners’ learning discussion time is mainly several at the beginning of the semester and the end of the semester, and the number of discussions at other times is almost zero. The DBSCAN clustering algorithm was used to classify English learners into three types, and intervention strategies were proposed for each type to improve teaching quality.
A group intelligence optimisation method for privacy protection problems in smart home environments
Authors: Yu Jiaze 
Published: February 2025

Abstract
The protection of user privacy data in the smart home environment has become an important way to maintain and optimise the wisdom of the group in the current information age. In this paper, we propose the key technologies for smart home privacy protection from the three levels of terminal devices, data transmission interfaces and application platforms. Based on API, we propose a privacy leakage detection scheme for the smart home platform, which combines with Hook technology to obtain device privacy information and complete privacy leakage detection. Based on the improved RAPPOR algorithm, the terminal data is grouped and then executed for privacy protection. The interface data security transmission scheme is constructed based on Chaotic Logistic and RC4 stream cipher. Application practice is carried out in a living room using a smart home in District A. The accuracy rate of the privacy leakage detection technology of this paper’s platform is as high as 97.8%, and the success rate of information processing of terminals applying this paper’s terminal privacy data protection technology always maintains the level of more than 97% in different data streams downward. The authentication phase has the lowest computational overhead among all accepted data transmission confidentiality methods, with just 0.068 ms. This paper’s smart home privacy protection technology performs well in terms of effectiveness and reliability.
The Complementary Role of Artificial Intelligence to Traditional Teaching Methods in Music Education and Its Educational Effectiveness
Authors: Zhang Lei 
Published: February 2025

Abstract
In the field of music education, the application of artificial intelligence technology is gradually changing the traditional teaching mode, providing new opportunities and challenges for music education. In this paper, we use artificial intelligence technology to build a smart classroom for music teaching and combine it with a user-based collaborative filtering recommendation algorithm to provide students with personalized music learning materials. Moreover, a treble feature extraction model is integrated into the smart classroom, and the DTW improvement algorithm is used to match the students’ treble features, and the student’s mastery of music skills in the smart classroom is evaluated through the sight-singing scoring technology. Students’ overall satisfaction ratings for the music teaching mode in the smart classroom designed in this paper were 4.35 to 4.60, and only a very few students disliked the teaching mode. The personalised recommendation system built in this paper has a precision rate, recall rate and F-value of 0.50, 0.41 and 0.38, respectively, when the number of recommendations is 50, and it can provide students with personalised music learning materials suitable for them. After the experiment, the average scores of the experimental class on pitch, rhythm, sight-reading ability, music notation, and polyphonic music perception increased by 7.72, 6.37, 7.82, 6.92, and 8.16 points, respectively, compared with the control class. In this paper, the difference between the intelligent scoring system and the teacher’s scores on the “pitch” scores is 0.036~4.903. Artificial intelligence technology provides an effective supplement to traditional music teaching and improves the personalization, efficiency, and quality of teaching.
Practical Research on Virtual Reality and Augmented Reality Technology in Min Cultural Heritage Digital IP Character Design Innovation
Authors: Li Honglin , Weng Jiankai 
Published: February 2025

Abstract
With the development of virtual reality (VR) technology and augmented reality (AR), the communication media and expression of culture have been further expanded. In this paper, VR and AR technologies are applied to the digital IP character design of Min cultural heritage, focusing on the image generation and action recognition processes in the digital IP character design process. The LAFITE model is used to generate the digital IP image of Min cultural heritage, and after the pose representation of the digital IP character, the multi-class support vector mechanism is used to construct the action recognition model. The model tests proved that the FID and IS produced by the LAFITE model are superior to those produced by other traditional models by 30% to 316% and 6% to 48% respectively. The output images of the Min cultural heritage digital IP characters are also of better quality. The MSVM model exhibits a high recognition rate for various actions of the IP characters, with each index value exceeding 93%, thereby facilitating effective interaction and enrichment of digital IP characters. The image output and action recognition model proposed in the study can promote the innovative design of digital IP characters of Min culture and enhance the digital creative expression and interactive forms of Min culture.
3D Occupancy Network Modelling for Multi-view Image Fusion Techniques in Autonomous Driving
Authors: Hu Xingyu , Ma Xipei , Fan Pingqing , Yang Chao 
Published: February 2025

Abstract
The article outlines the principle and mathematical model of multi-view image fusion technology and acquires research data based on multi-view image fusion technology. Combining research data, vehicle structural parameters, and Ackermann’s steering principle, the vehicle kinematics model is constructed to complete the task of 3D occupancy network modeling. The loss function of the selected network is discussed and its training is optimized. The simulation analysis shows that along with the increase in vehicle distance, the vehicle distance detection error increases by 6.59, and the average detection error is 3.72%, which is within the error allowance. In addition, in the path planning simulation analysis, the path planning time of this paper’s method is, which indicates that the 3D occupancy network can quickly and efficiently plan an effective and feasible path according to the change of obstacle position, and it practices the principle of safe and automatic driving well.
Practical Exploration of Data-Driven Strategy Optimisation of E-commerce Platforms to Promote Regional Common Prosperity
Authors: Huang Yijing 
Published: February 2025

Abstract
To achieve common prosperity, rural revitalisation is the way to go, and to promote regional economic development and narrow the gap between urban and rural areas, optimising the data-driven strategy of the e-commerce platform is an inevitable choice. This paper selects the data of 204 prefecture-level cities in China from 2014 to 2023 as the research sample, takes the e-commerce platform data-driven strategy optimisation demonstration area as a quasi-natural experiment, and adopts the multi-period DID model to explore the impact of rural e-commerce development on the urban-rural income disparity and its realisation path. The results show that the data-driven strategy of the e-commerce platform reduces the urban-rural income gap while improving the overall income level of farm households, and has a contributing effect on regional common wealth. In addition, the construction of traditional and new digital infrastructure, as well as the enhancement of the human capital of village cadres, can create a more level playing field and effectively promote regional common wealth. The purpose of this paper is to help drive and stimulate consumption in regional areas by optimizing data-driven strategies of e-commerce platforms, thereby achieving rapid regional economic growth.
A Study on the Optimisation of Personalised English Learning Paths Based on Big Data Analysis and Its Impact on Teaching Efficiency
Authors: Li Nan 
Published: February 2025

Abstract
Personalized learning paths can take into account the individual differences of different learners’ abilities, knowledge backgrounds and knowledge mastery levels based on big data and provide targeted learning sequences for different learners to achieve the purpose of improving teaching efficiency. In this paper, we construct a personalized learning path optimization model that includes a neural network collaborative filtering layer, a cognitive level diagnosis layer, and a learning path generation layer. The nonlinear relationship between learners and knowledge points is represented by obtaining interaction information between learners and knowledge points, so that the model can better extract the vector features of learners and knowledge points. Teaching practice shows that the experimental class under this learning path improves by 25.82 points, which is significantly larger than the control class, and students in all segments make significant progress. There are no students with more than 80 points in the pre-test, while there are as many as 11 students with more than 90 points at the end of the semester, which verifies the effectiveness of the model in improving the efficiency of teaching and meeting the needs of personalized learning. This study provides useful insights for making scientific teaching decisions, objectively evaluating student learning outcomes, and improving teaching efficiency.
Deep Learning Models in Network Intrusion Detection Systems
Authors: Li Jian 
Published: February 2025

Abstract
Network intrusion detection technology is crucial for maintaining a stable network environment and defending against network attacks. This paper first normalizes and solo thermal codes the network intrusion data. Then, it uses the ResNet18 model to pull out the deep features in the data. The CEKL loss function is used to keep the data balance in the ResNet18 training process. Finally, the Softmax function is used to classify and detect the network intrusion data. The detection model is then used as the core technology to design the network intrusion detection system. After testing, the average accuracy of this paper’s model in network intrusion datasets Bot-IoT and ToN-IoT is 99.02% and 99.06%, respectively. In addition, the network intrusion detection system has a high recognition rate (94.41%–97.92%) for known types of attacking network samples, with low false alarms and missed alarms, and the system stress test meets expectations. The research work in this paper aims to optimize the shortcomings common to existing intrusion detection algorithms and proposes a feasible modeling idea for existing network intrusion detection techniques, which has excellent potential for application.
Research on the enhancement mechanism of big data-driven government innovation subsidy policy on the multi-level financing model of science and technology-based enterprises
Authors: Wang Lin 
Published: February 2025

Abstract
The financing activities of enterprises are related to the long-term healthy development of enterprises, and when capital becomes the external bottleneck restricting the innovation activities of enterprises, government subsidies will occupy a more critical position in the financing activities of science and technology-based enterprises. In this paper, government subsidies are used as a mediating variable to look at how financing constraints affect different life cycles of science and technology-based businesses. The businesses are then put into four groups: start-up, growth, maturity, and decline. The main goal is to see how financing constraints change during each life cycle. Construct a research model to analyze the relationship between government subsidies, financing constraints, and technology-based enterprises using the mediating variable testing procedure. Combine the sample data to describe the development of innovation activities and the financing status of science- and technology-based enterprises. Benchmark regression analyses are conducted to test the direct effect of government subsidies on the innovation of science and technology-based enterprises, the mediating role of financing constraints, and the heterogeneous effect of the mediating effect of financing constraints under different life cycles, respectively. The analysis shows that the coefficients of government subsidies in the II, V, and X periods are -0.003, -0.006, and 0.056, which are not significant, while the coefficients of government subsidies in VII, VIII, and IX are 0.125, -0.052, and -0.786, respectively, which are significant at the 1% level. It can be seen that the mediation effect of financing constraints under the perspective of government subsidies mainly arises in the maturity period and is not significant in the start-up period, growth period, and decline period.