bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intestinal full-thickness needle-core biopsy via laparotomy is safe, rapid, and effective and less invasive than standard incisional biopsy in dogs and cats
Authors: Maggiar Adrien , Andréjak-Bénit Juliette , Miclard Julien , Sarran Delphine , Billet Jean-Philippe 
Published: December 2023

Abstract

OBJECTIVE
To describe the intestinal full-thickness needle-core biopsy technique via abdominal laparotomy outcomes and compare the histopathological and immunohistochemical diagnosis with standard incisional intestinal biopsy technique in dogs and cats.

ANIMALS
3 dogs and 17 cats.

METHODS
Client-owned dogs and cats were prospectively enrolled if intestinal full-thickness biopsies were indicated for the diagnosis of diffuse chronic intestinal diseases following ultrasonography. The study period extended from June 2021 to December 2022. All animals underwent intestinal biopsies with both techniques (needle-core biopsy and standard incisional biopsy) via abdominal laparotomy. Data collected included clinical signs, biopsy collection times, complications, and histopathologic and immunohistochemical findings. A minimum follow-up of 14 days was required.

RESULTS
The main clinical sign at presentation was chronic vomiting (65%). Mean needle-core biopsy collection time (262 seconds) was significantly shorter than standard incisional biopsy collection time (599 seconds; P < .000001). The incidence of minor complications was 10% (inflammation of the skin surgical site secondary to licking). One catastrophic complication occurred on a standard incisional biopsy site in 1 cat in a context of bile peritonitis (5% of all cases). There were no complications associated with the needle-core biopsy. All but 1 cat were discharged, with a median of 2 days (range, 1 to 4 days) after surgery. The diagnoses resulting from both techniques were 100% concordant for the distinction between inflammatory bowel disease and intestinal lymphoma via histopathology and immunochemistry.

CLINICAL RELEVANCE
Needle-core biopsy is safe, rapid, and effective and is less invasive than standard incisional biopsy.
Comparative Study Between Sliding Mode Controller and PI Controller for AC/DC Bridgeless Converter Under Uncertain Parameters
Authors: Almobaied Moayed , Musleh Ahmed Mosa 
Published: December 2023

Abstract
In this paper, a comparative study between nonlinear sliding mode controller (SMC) and standard PI controller for stabilizing bridgeless AC/DC converter under uncertain parameters is presented. This type of converters is widely used in harvesting low energy systems as in wind turbine, piezoelectric transducers and heat exchange transducers. Designing robust controllers to enhance the efficiency and accuracy of these converters has become a promising track in control engineering field. The traditional bridge rectifier is widely used in the majority types of AC/DC conventional converters to gain the rectified DC voltage from the low AC input voltage source. However, these traditional converters are not effective for the low output voltage of renewable sources due to the voltage drops across rectifier’s diodes. The proposed SMC-PI controller is used to enhance the stability and the response of these converters under uncertain parameters comparing with the standard PI controller. The proposed approach consists of both Boost and Buck-Boost converters with two controllers in order to maximize the useful output energy from the source. The graphical method has been used to obtain the limitation of the coefficients of the standard PI controller. A parameter space approach is used to find all robust stabilization PI coefficients and the stability regions. A comparative study using simulations in MATLAB is presented to ensure the effectiveness and robustness of the proposed SMC-PI controller under some external disturbances.
3D Mapping with a Drone Equipped with a Depth Camera in Indoor Environment
Authors: Alexovič Stanislav , Lacko Milan , Bačík Ján 
Published: December 2023

Abstract
This paper presents a quadrotor drone designed for the 3D reconstruction of indoor environments using a depth camera and a tracking camera. The drone’s hardware and software components are described, including the Holybro X500V2 kit, the Intel RealSense T265 tracking camera, and the Intel RealSense D435i depth camera. The paper outlines the process of building a complete TF tree, capturing point clouds with RtabMap, and streaming video. The drone’s pose stabilization and successful test flight in an indoor environment are also discussed, including its ability to navigate through indoor spaces and provide accurate data for 3D reconstruction. The paper concludes with recommendations for future development, such as autonomous navigation and exploration of unknown areas. The results demonstrate the feasibility and potential of this drone for creating detailed and comprehensive maps of indoor environments.
The Application of Digital Multimedia Technology in the Innovative Mode of English Teaching in institutions of higher education
Authors: Liu Yun 
Published: December 2023

Abstract
Innovative English teaching resources will inevitably result from the use of media technology in the classroom. This article will examine the new approach to teaching English in college from the standpoint of teaching resources. In order to establish a new mode of English teaching in higher education institutions based on personalized recommendation of teaching resources, this paper proposes two recommendation algorithms: one is content-based, and the other is collaborative filtering. The algorithm is enhanced by combining it with the design of multimedia English teaching resources. The influence of hit rate and MAE values prior to and following the cooperative filtering recommendation method is examined. The distinction between the pre-and post-test results of the experimental and control courses is analyzed and compared to conclude the examination of the impact of the novel model of teaching college English. The analysis indicates that the improved recommendation algorithm has a 4.85% higher hit rate than the traditional collaborative filtering algorithm. The improved recommendation algorithm is more accurate than the traditional recommendation algorithm, as suggested by this.
Exploring Strategies for Promoting Overseas Alumni Giving Activities in Colleges and Universities Based on Coupled Models
Authors: Wang Yongsheng 
Published: December 2023

Abstract
This paper adjusts the coupling model to analyze the variables in order to measure the degree of coupling between overseas alumni donation behavior and university strategies. The entropy weighting method is used for the determination of indicator weights and systematic, comprehensive evaluation function. The replicated dynamic equations of alumni entrepreneurs and colleges and universities are explored separately to verify the relationship between the probability of alumni donations, the probability of colleges and universities willing to accept donations and the probability of entrepreneurs’ willingness to donate. To simulate the impact of three types of university incentive strategies, namely, tax incentives, reputational gains, and networking resources, on the donation decisions of overseas alumni and to explore the ranking of the three types of incentive strategies in a single incentive strategy implementation environment. In order to explore the cooperative evolution process of multi-channel coupling, the group structure, size, degree of interaction and cognition are modeled with appropriate parameterization, and the evolution results of the independent and coupled scenarios are compared. The simulation data show that in the environment of single university incentive strategy implementation, the ranking of incentive effects is, in order, tax benefits > networking resources > reputational gains.
Research on Emotional Improvement of Product Design Based on Emotion Recognition Technology
Authors: Xin Lujuan 
Published: December 2023

Abstract
In this paper, we first extracted the time-domain features, frequency-domain features and spatial-domain features of EEG signals, combined with the three-stage feature selection algorithm applicable to the binary classification problem and the multi-classification problem, and constructed the SEE model for emotion recognition based on EEG signals. Then, based on the three-level design model of emotion, emotion decoding and labeling are carried out on the instinctive layer, behavioral layer and reflective layer of product design, and the constructed model is combined to improve the product design emotionally. Finally, after analyzing the results of product emotion annotation, we explore the performance of the EEG-based emotion recognition model and the improvement effect of product design emotionalization. The results showed that the average accuracy of the EEG signal emotion recognition model for various emotion recognition was about 0.99, and the intensity of emotion intensity in Dahe was 0.32 and 0.25, respectively, accounting for 0.57 of the total sample, and the performance evaluation indicators of the eight emotions were greater than 0.85. Ninety percent of product experiencers had pre- and post-improvement differences between [0.12, 0.22] for happiness and [-0.20, -0.04] for dissatisfaction.
Research on the Comparative Development of Modern Popular Music and Traditional Music Culture in Colleges and Universities in the Age of Artificial Intelligence
Authors: Li Lin 
Published: December 2023

Abstract
In this paper, the forward neural network multi-feature fusion algorithm is used to extract the emotional features of music culture on artificial intelligence technology, considering the diversity and intermittency of the emotional features of the study, which needs to be parameterized. In the forward neural network architecture, the activation value obtained by using the nonlinear activation function is used, and the results obtained are passed to the next layer of data to realize layer-by-layer forward computation, which leads to the back-propagation activation function. The music culture emotion classification model is constructed based on the propagation mode of the forward neural network to determine the emotion recognition process. The research object is selected, the research process is determined, and in order to ensure the true validity of the research, it is necessary to test the reliability and validity of the research design scheme and to develop an empirical analysis of the comparison between popular music and traditional music culture. The results show that on the model, especially in the recognition of sacred, sad, passionate emotion type of music classification accuracy reached more than 88.2%. This paper’s model can improve the classification accuracy of music emotion to a certain extent. In the ontological knowledge analysis of popular music and traditional music culture, all three editions of textbooks show that general knowledge of music is predominant and has a large proportion, appreciation knowledge and extended knowledge are also considerable, and music knowledge is the least and has a small proportion. This study demonstrates the synergistic development of traditional culture and modern popular music, which is of great significance to the development of music education in colleges and universities.
The Impact of the Big Ideology Program on the Construction of Academic Ethos in Colleges and Universities in the Context of Three-Whole Parenting
Authors: Liu Haijun , Tao Bingbing 
Published: December 2023

Abstract
This paper uses multiple linear regression model to study the correlation between the ideological and political courses and the construction of university academic style, explores the calculation process of multiple linear regression, studies the impact analysis of linear regression model and the diagnosis of abnormal points, and analyzes the underfitting and overfitting respectively. The linear regression analysis model was used to study the differences in the academic style level of college students of different grades and genders, the correlation analysis of various dimensions of academic style and ideological and political level was carried out, and the linear fit of ideological and political curriculum education and academic style was analyzed by MATLAB to infer the significance level of ideological and political education and academic style. The results show that the correlation coefficient between ideology and politics and the dimension of learning purpose is 0.053, P=0.003<0.05. The correlation coefficient between ideology and politics and learning attitude was 0.239, P=0.008<0.05. The correlation coefficient between ideology and politics and learning effect dimension was 0.682, P=0.018<0.05. The data presented shows that ideology and politics have a significant impact on the construction of academic style.
Construction of medical aromatherapy experimental teaching resources based on digital three-dimensional technology
Authors: Xu Jing 
Published: December 2023

Abstract
In this paper, on the basis of the Unity3D engine, image feature points are coarsely extracted, and a quadtree-based division algorithm is applied to filter the optimal FAST corner points. The fast 3D reconstruction technique is constructed through the construction method of nonlinear scale space similar to scale-invariant feature transform (SIFT), which is layer incremented according to the scale level logarithmic layer. The reconstructed 3D virtual teaching laboratory tool is obtained by importing the matched feature points into the model after the diffusion is completed. Finally, the teaching process and teacher-student behavioral data analysis were conducted for TCM and acupuncture students using the medical aromatherapy experimental course “Clinical Experiment of Aromatherapy for Primary Dysmenorrhea” as the teaching objective. The results showed that the maximum value of iFIAS of the experimental group was 100, and the mean value was 79.35, while the maximum value of technical iFIAS of the control group was only 51.32, and the mean value was 21.34, which was a significant difference between the two. It shows that the teaching method improves classroom learning interest and effect. The purpose of this paper is to provide relevant opinions and references for the future development direction of the combination of aromatherapy teaching and 3D virtual reality.
Analysis of the Implementation Path of Civic Education Work in institution of higher education under the Background of Internet+
Authors: Zeng Yihua 
Published: December 2023

Abstract
In this work, the ideology and political characteristics are iteratively calculated using Cuckoo Search Algorithms and the Extreme Learning Machine. The ideology and political objective function are then obtained using CS-ELM. A CS-ELM-based index framework for ideology and political education effect in educational institutions is developed, all of the bird’s nest objective function values are calculated, as well as the bird’s nest position with the highest objective function value is retained in order to accurately and effectively evaluate the current state of ideology and political education effect in educational institutions. The experimental data set is an evaluation of the ideology and political education effects of colleges and universities from 2013 to 2022. Research and analysis are conducted on the evaluation of ideology and political education in institution of higher education in order to remove the quantitative definition of the collected raw data, and mixing is used to process the raw data to make it into a dimensionless one. The hierarchy of higher education has an impact on the establishment of high-quality economies. The CS-ELM model is the best way to assess ideology and political teaching effectiveness in higher education institutions, as per the results. This is because, when looking at the evaluation from an overall perspective, the RMSE value is 0.007, and the R-value is 0.995. This study enhances the quality of instruction in the classroom, promotes a positive environment and attitude, and motivates students to be actively involved in their education.
Voltage transformer metering error state prediction method based on GA-BP algorithm
Authors: Gao Shuai , Zhao Lin , Jiang Zhenyu , Zhang Yin , Bai Yicheng 
Published: December 2023

Abstract
The metering accuracy of the voltage transformer is related to the normal operation of the power system, and the metering results can be optimized through the prediction of the error state. In this paper, according to the generation mechanism of the measurement error of the transformer, the maximum information coefficient is used to extract the error characteristic quantity, and the measurement perturbation model is constructed by combining the ambient temperature and the secondary load factor. Due to the specificity of the ambient temperature, a BP neural network is also used to compensate for the temperature of the perturbation model, which prepares for the improved BP neural network based on a genetic algorithm to recognize the error data. Finally, the simulated operation of the three-phase voltage transformer and the measured data of the wiring substation were utilized for validation, respectively. With the help of three-phase CVT simulation, the error change of A-phase simulated CVT amplitude information at the 4001st sampling point is 0.0962%, and the error change of phase information is -4.572′.GA-BP neural network also has high sensitivity to the difficult-to-detect asymptotic error and is able to realize the error calibration of voltage transformer.
Analyzing the Emotional Characteristics of British and American Literature by Combining Semiotics and the Operational Model of Thinking
Authors: Huang Ning 
Published: December 2023

Abstract
This paper first analyzes the emotional features of English and American literary works by combining semiotics of interactivity, language class emotional context and thinking operation model. Then, a B-Feature-BP text emotion feature construction model is constructed on the basis of the BRET model combined with the BP neural network, and the emotion features of English and American literary works are constructed by combining semiotics and the thought operation model. Then, based on the multi-task learning method in deep learning, a multi-task MT-GSU model is proposed to classify and recognize the emotional features of constructed text. Finally, the performance of constructing, classifying and recognizing the emotional features of English and American literary works in this paper is analyzed so as to analyze the emotional features of English and American literary works. The results show that the performance of the constructed emotional features is all greater than 0.8, and the emotional features of the characters, the environment, and the whole of the English and American literary works are above 0.87, and the classification time is between [0.338,0.721]s. The intensity of tendency of the characteristics of the emotions of the works of English and American literature is [0.68,0.78], the intensity of stability is [0.6,0.74], the intensity of profundity is [0.71,0.79], and the intensity of efficacy is [0.72,0.82]. This study has a positive impact on the appreciation and translation of English and American literary works.
Research on the Design of Cultural and Creative Products Based on Lingnan Intangible Cultural Heritage in the Age of Artificial Intelligence
Authors: Qin Qin 
Published: December 2023

Abstract
Lingnan Intangible Cultural Heritage (ICH) has a long history and contains rich and unique regional culture, which can provide new thoughts and ideas for cultural and creative product design. In this paper, firstly, the cVAE-GAN network model is utilized to extract the features of the modeling symbols of Lingnan intangible cultural heritage, which helps to obtain the modeling symbols of Lingnan intangible cultural heritage for cultural and creative product design. Secondly, the HSV color space model realizes the refinement of the color elements of Lingnan intangible cultural heritage, which promotes the application of color diversity in the design of Lingnan cultural and creative products. Then, the two methods are combined with artificial intelligence technology to construct the Lingnan emotional interactive cultural and creative product design framework, which enables the computer to integrate the designer’s design emotion on the basis of learning modeling and color and promotes the enhancement of the emotional value of Lingnan non-heritage cultural and creative products. Finally, to verify the effectiveness of the method described in this paper, a relevant test analysis was conducted. The results show that when the computational order is more than 60 orders, the cVAE-GAN network in this paper extracts the styling symbol features in only about 115ms, the PSNR improvement of the HSV color space model under different color blocks is more than 2dB, and the RSD of H-channel can be found to be in the range of 0.5% to 5.0% after performing color noise removal. Carrying out the cultural and creative product design of Lingnan intangible cultural heritage in the era of artificial intelligence needs to be more clear about the shape and color of the intangible heritage and fully combine with the designer’s emotion in order to make the Lingnan intangible cultural and creative products revitalized with new vitality.
The Integration and Design of Green Concept in Jewelry under the Background of Information Technology
Authors: Zhu Yu , Wang Chao 
Published: December 2023

Abstract
This paper first integrates the green concept into jewelry design from three aspects of jewelry materials, modeling and production process, and demonstrates the jewelry 3D printing technology in line with the green concept in the context of information technology and analyzes its technical process. Then, based on the PCA method and the point cloud data of space lattice, the three-dimensional normal estimation of jewelry is carried out, the three-dimensional reconstruction and cavity repair of jewelry is carried out through the triangular mesh model, and the complete output of the jewelry model in STL format is carried out, and the STL fast slicing is carried out. Finally, the effects of 3D modeling, slicing efficiency, and jewelry design are analyzed through numerical simulation experiments. The results show that the standard deviation of the error in the x-direction σ =0.16um, expectation μ =−0.007um, the standard deviation of the error in the y-direction σ =0.08um, expectation μ =0.003um, and the standard deviation of the error in the z-direction σ =0.28um, expectation μ =−0.001um, with a variation range of (−0.028, 0.028), in the three-dimensional modeling of jewelry. Compared with the traditional slicing algorithm, this paper’s slicing efficiency of jewelry is improved by (0.26, 0.45), when the production quantity is more than 500 pieces, in terms of the cost of the traditional production method is more advantageous.