bluuebunny/crossref_metadata_2025_split huggingface dataset:
ON THE GENERALIZED DUAL FIBONACCI AND LUCAS OCTONIONS
Authors: Köme Sure 
Published: October 2024

Generalized number systems, particularly octonions with their algebraic structure, have drawn much interest in mathematics, physics, and computer technology. Therefore, in this paper, we introduce two new concepts, modified generalized dual Fibonacci and modified generalized dual Lucas octonions, to expand the topic of octonions. Additionally, we explore the well-known Catalan and Cassini identities, shedding light on the characteristics of these new constructs. Also, we give generating functions and the Binet formulas of the modified generalized dual Fibonacci and modified generalized dual Lucas octonions.
Impact of JETA As Measured by an AI Generated Taxonomy: Reaching Beyond Accounting
Authors: Cong Yu , Du Hui 
Published: October 2024

ABSTRACT
We analyze the impact of publications in Journal of Emerging Technologies in Accounting (JETA) at its 20-year anniversary. Using OpenAlex, an aggregated bibliometric database and its concept taxonomy generated by artificial intelligence (AI), as well as its topic classification system supported by large language models (LLMs), we demonstrate that the impact of JETA is reaching beyond accounting to areas in computer science, engineering, social science, and even medicine among many others. The analyses are based on articles in the journals (other than JETA) that have cited JETA publications and the concepts and topics in the articles.
It’s Not Intelligence; It’s Functionality!
Authors: Gu Yu , Huang Qing , Vasarhelyi Miklos A. 
Published: October 2024

ABSTRACT
The press and pundits have extensively discussed the dangers of artificial general intelligence (AGI) and the various ethical and functional effects of current emerging technologies. This paper attempts to focus on AI as applied to accounting and auditing and its realities. It shows studies using machine learning and natural language processing, including generative efforts, and robotic and extended process automation. It concludes that a very promising set of applications is emerging, but there is little immediate danger of being replaced by machines to most in the profession, although the impacts are going to be substantive. These applications primarily utilize individual or combined AI functions, and the realization of true intelligence remains a distant goal.
JEL Classifications: M41; M42; C45.
Increasing Physical Soil Quality by Using Rice Straw Biomass
Authors: Sumiyati Sumiyati , Tika I Wayan , Sulastri Ni Nyoman , Kinasih Mentari 
Published: October 2024

Paddy straw as an agricultural waste can be returned to the soil to increase the organic matter content. This study aims to determine the optimum inoculant treatment of rice paddy straw on soil quality. The straw handling was carried out by spreading the straw on paddy fields and sprayed with four inoculant treatments (0, 3, 6, 9, and 12 L/ha). The incubation process was carried out for 21 days and incorporated in the soil through plowing. Each treatment was repeated three times so that the total treatment was 15 units. The variables observed in each treatment were soil quality. The soil quality parameters observed were particle density, bulk density, porosity, field capacity and pH. ANOVA statistical analysis which was continued by the Tukey HSD Post Hoc Test to determine the effect of treatment on soil quality. The results showed that the inoculant treatments showed a significant difference (p-value=0.05) in soil volume, density, and porosity. P4 gave the optimum results which are statistically not significantly different from P3. P4 shows the physical properties of the soil which consist of the soil bulk density of 0.61 g/cm3; particle density 1.74 g/cm3; porosity was 64.91%, and pH 6.68. The utilization of straw biomass as source of organic material contributes to zero waste rice cultivation. Keywords: Effective microorganisms, Rice straw, Soil density, Soil pH, Soil porosity.
Pendampingan Belajar Matematika Peserta Didik dalam Memahami Materi Persamaan Garis Lurus
Authors: Nur Miftahul Jannah  , Hilmirrahma  , St. Aswiah  , Siti Sulaeha  , Suharti  
Published: October 2024

Persamaan garis lurus merupakan suatu materi pelajaran yang memiliki beberapa materi prasyarat yang harus dipahami sehingga peserta didik mengalami kesulitan dalam memahami materi tersebut. Salah satu penyebab peserta didik mengalami kesulitan dalam memahami materi persamaan garis lurus dikarenakan masih kurangnya pemahaman siswa terkait materi prasyarat yakni diagram kartesius, fungsi, dan aljabar. Pengabdian dilakukan di MTs Madani Alauddin Po-pao kelas VIII C yang bertujuan membantu peserta didik dalam memahami materi persamaan garis lurus dengan melakukan pendampingan kepada peserta didik. Pengabdian dilakukan oleh mahasiswa dan dosen pendidikan matematika yang sedang melaksanakan Praktik Lapangan Persekolahan (PLP) 2 sebanyak 8 kali pertemuan dengan melakukan pendampingan kepada peserta didik pada saat pembelajaran berlangsung maupun pengerjaan tugas pada saat akhir pertemuan baik secara personal dan secara berkelompok dalam mengerjakan lembar kerja peserta didik pada pertemuan ke 3 dan 4. Hasil pendampingan menunjukkan bahwa hasil belajar peserta didik meningkat yakni dilihat dari hasil posttest yang menunjukkan 27 peserta didik yang masuk pada kategori sedang hingga sangat tinggi yang mana dibandingkan dengan hasil pretest sebelumnya hanya 14 peserta didik yang masuk pada kategori sedang hingga sangat tinggi. Selain itu, setelah melakukan wawancara diketahui bahwa peserta didik menyukai pembelajaran yang dilakukan secara collaborative karena suasana kelas yang menarik dan tidak merasa canggung apabila terdapat sesuatu yang ingin dipertanyakan. Sehingga pengabdian yang dilakukan dengan pendampingan belajar memberikan dampak positif bagi peserta didik dalam memahami materi persamaan garis lurus.
Cardiomyopathies – genetic and molecular issues
Authors: Soczynska Julia , Gawelczyk Wiktor , Mozdziak Paul Edward 
Published: October 2024

Abstract
Cardiomyopathy is a condition that may have a genetic basis. It is a serious ailment because it affects almost half of the individuals who die suddenly in childhood, adolescence, or related to heart transplant procedures. The inheritance patterns of this disease can vary. For example, as described in the work on HCM and ARVC, they are inherited in an autosomal dominant manner. De novo mutations may involve genes related to myofilaments, Z-discs, components related to cellular calcium handling, or desmosomes, among others. However, detailed molecular aspects should be correlated with clinical features because changes within a single gene may be associated with diverse abnormalities. Depending on the manifestation of the action of certain allele changes, they may range from microscopic deviations to causing heart failure and impaired blood flow through other organs, thereby disrupting the functionality of the entire body, hindering daily life and lowering its quality. Currently, the analysis of the degree of interaction of genetic determinants in cardiomyopathy is becoming increasingly accessible due to modernization and improvement of tools in the field of diagnosing anomalies in gene sequences and expression. A more precise understanding of causative mutations and associated conditions may contribute to determining strategic points for the future regarding the most beneficial course of action in specific circumstances and evaluating the effectiveness of the steps taken in the long run. In addition to mutations typically causing cardiomyopathy, there are also mutations contributing to their development within the spectrum of other diseases. This includes the PRKAG2-related cardiac syndrome, associated with abnormal metabolism, Danon disease, mitochondrial disorders, ion channelopathies, or conduction disorders.
Recent findings of cardiac dysfunction and anti-cancer therapy
Authors: Papierkowska Julia , Gawelczyk Wiktor , Soczynska Julia 
Published: October 2024

Abstract
Cardiovascular diseases and carcer have a lot of things in common. Both of those conditions are responsible for most deaths in first world countries. Moreover, considerable amount of heart dysfunction complications, result from cancer treatment. For example, common anticancer drugs like anthracyclines are cardiotoxic. Administrations of these compounds may cause cardiotoxicity type I. Trastuzumab is also a compound that is used in cancer treatment, sometimes used concurrently with anthracyclines, and this drug is associated with cardiotoxicity type II. These drugs and many others have side effects ranging from mild to severe like irreversible cardiac damage that may result in heart failure. Cyclophosphamide is a chemotherapy medication used to treat various types of cancer and also can be useful to treat autoimmunological conditions. Radiotherapy, also known as radiation therapy, is a medical treatment that uses high doses of radiation to kill cancer cells and shrink tumors. It is also a stressful treatment on the cardiovascular system to such degree, that the second most fatal complication after utilizing radiotherapy is heart dysfunction. Pre-existing cardiovascular disease can influence the treatment as well as the prognosis of the patient. Patients with former cardiovascular disease are associated with less treatment options, significantly higher likelihood of worse treatment outcomes and complications that often result in death.
Research on the application of wireless energy transmission technology in smart grid
Authors: Sun Mei 
Published: October 2024

Abstract
With the continuous development of wireless energy transmission technology, the role of wireless rechargeable sensor networks (WRSNs) in smart grids has become more and more important. In this paper, after fully investigating the application of wireless energy transmission technology in smart grids, the solution vector of SFLA is discretized, and the IMSFLA model based on the hybrid frog jump algorithm is proposed to solve the wireless energy transmission planning problem in the smart grid. Finally, it is applied to the optimal design of the charging scheme of WRSNs, and the simulation results of the IMSFLA algorithm are compared and analyzed with those of the Taboo Search (TS) algorithm after exploring its wireless transmission performance. In terms of energy utilization, when the number of nodes is increased to 550, the energy utilization of IMSFLA algorithm is improved by 7% compared to TS algorithm, and when the number of nodes is increased to 550-800, the optimized results of TS algorithm deviates significantly more compared to IMSFLA algorithm. This indicates that the IMSFLA algorithm designed in this paper has a better effect on the optimization of the charging scheme of wireless rechargeable sensor networks, which is of great practical significance for improving the stability of the smart grid.
An analytical model of soccer players’ career development incorporating knowledge graphs
Authors: Cao Bo 
Published: October 2024

Abstract
Career planning is of great importance to this special group of athletes, but most athletes do not have a better personal development plan for their professional sports career, so it is necessary to analyze the career development of soccer players. In this paper, firstly, we constructed the knowledge map of soccer players’ career development using the GAT mechanism and RNN model classification to construct the GGNN inference model and then analyzed the group characteristics of soccer players. Finally, the construction of a career development assistance system for soccer players was implemented. The main results are as follows: the cultural characteristics of soccer players from 2000 to 2020 found that the percentage of their university education increased by 13%. While the percentage of education in other stages decreased, especially the percentage of education in junior high school and elementary school decreased significantly by 11% and 33%. In the survey on the influencing factors of soccer players’ future re-selection, it was found that the influence of parents and friends on soccer players’ view of career choice reached 71%, of which 43% believed that their parents had the greatest influence on them, and 28% believed that it was their friends. Obviously, the model of soccer players’ career development that integrates knowledge graphs can better help soccer players implement career planning and improve the security of retired soccer players’ re-choice of career.
Exploration of Energy Meter Data Security and Fast Response Technology in Spot Power Trading
Authors: Chen Fangfang , Jiang Honglang , Jiang Xiaoqiang , Luo Ranran , Liu Bo , Peng Jianzhong 
Published: October 2024

Abstract
With the advancement of smart grid construction, higher requirements have been put forward for energy meter data, which need to realize real-time, accurate, efficient, safe, and economical data transmission. In this paper, an intelligent collection of energy meter data is designed to monitor energy meter data. The PCA algorithm is utilized to downscale the energy meter data, and the LMR algorithm is combined to monitor abnormal data from the meter. Based on the smart contract in blockchain technology, a parallel Pedersen commitment algorithm based on privacy protection is designed, a hybrid signature algorithm is created to ensure the secure transmission of energy meter data and a cluster load balancing model for energy meter data is also designed in combination with Hopfield neural network. The PCA-LMR algorithm identifies 95 anomalies of the data in 12 months and under the encryption of a smart contract. The packet loss rate of energy meter data is maintained at about 2%, and after optimizing the cluster load capacity of energy meter data using the Hopfield neural network, the cluster load variance value is about 1.84 in 20 h. Modern technology can improve the secure transmission of energy meter data and enhance its rapid response ability to ensure the economic benefits of the power system.
Research on the Integration of Artificial Intelligence-driven Industrial Economics and Technology Industry Incubation
Authors: Li Junyi 
Published: October 2024

Abstract
The development mode relying on the traditional factor dividend has become unsustainable, and the integration and application of artificial intelligence technology can promote the high-quality development of science and technology industry incubation, and it brings more space for the development of the science and technology industry economy. This paper firstly discusses how artificial intelligence predicts economic trends, optimizes the production process, and automates decision support systems through machine learning models. By analyzing how AI processes large amounts of economic data, identifying market patterns, and evaluating the value of investment projects in future markets, it is able to assess the value of investment projects in future markets. Aiming at the shortcomings of the original K-Means clustering algorithm, the method of determining the initial clustering center and the method of automatically determining the K-value are investigated so as to realize the automatic clustering of industrial economic development data. From the empirical analysis, it can be seen that the regression coefficients of the interaction term Treatit × Yearit in columns (1) and (2) are all significantly positive at the 1% level. The cluster analysis also visualizes both the types and levels of enterprises in the economic development in a more intuitive way, which shows that the AI model can drive the development of the industrial economy and has an irreplaceable position in the process of technology industry incubation.
Study on Japan’s Cybersecurity Strategy and Regional Cybersecurity Construction in the Face of Global Competition
Authors: Tang Zhijian 
Published: October 2024

Abstract
Cybersecurity has emerged as a crucial security concern for countries worldwide, and Japan has made significant strides in this area, providing other countries with valuable lessons from its experience. In the context of global competition, this paper presents Japan’s cybersecurity situation, examines the top-level design of the Japanese government’s cybersecurity strategy, and outlines a three-pronged approach to building regional cybersecurity. Aiming to address the shortcomings of the existing DAEDALUS cyber attack warning system, this paper proposes an unknown attack detection algorithm based on an open-set classification network, which improves the algorithm’s recognition accuracy in the face of unknown attacks through loss function optimization and classifier replacement on the basis of a convolutional neural network’s open-set classification architecture. The experimental results demonstrate that, under various openness conditions, this algorithm optimizes the average F1 value of the three recognition models to 78.47 and enhances the detection accuracy of OCN in unknown attacks across two datasets to 84.94% and 76.53%, respectively. This paper demonstrates the accuracy of the OCN algorithm in recognizing unknown attacks.
Numerical simulation and analysis of microfracture mechanism of magnesium alloy materials
Authors: Yang Yongxin , Wei Baoli , Liu Huazhou , Yang Shaolong , Li Jiang , Qu Chenming , Feng Yashan 
Published: October 2024

Abstract
This paper takes the typical AZ31B magnesium alloy, which is increasingly widely used in engineering, as the research object and aims to study the fracture properties of magnesium alloys and their damage mechanisms under different loading strain rates and loading modes. EBSD, trace method, and other techniques are applied to study the fracture modes at a low strain amplitude of 0.42% and high strain amplitude of 1.746%, to explore and compare the type and number of microcracks at these two strain amplitudes, and to analyze the reasons for the formation of different types of microcracks. The results show that the experimental 0pass and 4pass start to fracture when they are numerically simulated impact loaded at impact velocities of 225m/s and 260m/s, and the larger the value of impact loading, the more complete the fracture occurs. The fatigue fracture occurred at TBs, GBs, and PSBs with a strain amplitude of 1.746% and 0.42%, respectively. The SF of PSBs was mainly distributed in the range of 0.8-1.0, while that of TBs was most distributed in the interval of 0-0.2 and 0.6-0.9. The larger the SF, the more prone to sprouting of microcracks. The smaller the value of m′, the larger the value of Φ, the more likely to promote microcracks sprouting at the grain boundaries.
An Adaptive Learning Path Optimization Model for Advanced English Learners
Authors: Xiao Hua 
Published: October 2024

Abstract
The advent of the big data era has triggered a major change in teaching methods, and personalized learning based on adaptive learning platforms with big data analysis technology has become a new paradigm of education technology. Firstly, the basic information characteristics of learners are described, and the learner characteristic model is constructed with cognitive level, learning style, learning emotion, and learning ability. At the same time, the framework construction of the learning path method is completed based on the knowledge map. On this basis, the adaptive learning path system improved based on a genetic algorithm was used to characterize the higher-order English learners, and then the clustering algorithm was used to analyze the characteristics of the higher-order English learners by clustering analysis. Eight clustering variables were selected to divide the learners into four categories. The first category of the “excellent learners” scored very high in the eight elements, indicating that the learners had a very high score in the adaptive learning path. The first category, “excellent learners”, scored high on all eight elements, indicating that the learners have strong learning abilities in the adaptive learning path. In order to verify the effect of the learning path on students’ academic performance, a pre-and post-test was conducted, and the difference in the mean values reflected that the learning path system has a significant effect on the improvement of performance. The learners’ perception of the system’s usefulness and ease of use resulted in F-values of 9.539 and 5.856, respectively, and the Sig. The values are 0.005 and 0.016, which are less than 0.05, and there is a significant difference. It indicates that the optimized adaptive learning path is highly recommended for use among higher-order English learners.
Exploration of Physical Education Teaching Reform in Colleges and Universities in the Context of Deep Learning
Authors: Zhang Chao , Yu Kaiyang 
Published: October 2024

Abstract
Deep learning is an important path for the digital reform of college sports teaching. In this context, the study is first conducted to acquire sports data in colleges and universities. Openpose technology is used to collect skeletal point coordinate data and process it to construct a human sports model. Then, based on the similarity comparison of sports poses, the generated sports sequences are filled to simulate the real human sports sequences and data, and the DTW algorithm is used to match the sports sequences and data with the features, eliminate the inconsistency between the length of the poses to be matched and the template pose sequences, and then give the scores of the poses to realize the evaluation of the learners’ sports performance. Combining the principles and functions mentioned above, we construct a system for evaluating sports teaching and analyze its application examples. The distribution of the distance between the quaternion-based swing action and the standard swing action is within the range of 0.18~0.25, and the distance between various types of actions and the standard action is not large. The professional scoring was 5.199 points higher than the DTW-based stance score of 90.183 points. In addition, in the experimental group and the control group, there is a significant difference in the analysis of students’ movement skills assessment, P<0.05, indicating that compared with the traditional teaching mode, the deep learning-based physical education teaching system has a strong relevance as well as the ability to provide real-time movement feedback and movement correction for students’ movement practice.
Research on the optimization of emotion expression movement based on cognitive computing in dance creation
Authors: Sun Chao 
Published: October 2024

Abstract
Cognitive computing technology realizes the processing of complex data and problems by simulating the human cognitive way, which is inspiring for the optimization of emotional expression in dance creation. In this paper, we propose a cognitive computing-based model for optimizing dance action emotions, using the improved 3DCNN model for dance action recognition and then CNN-BLSTM based on deep and shallow feature fusion for dance emotion recognition. The experimental results show that the students in the experimental group improved their movement emotion performance by 117% compared with the control group. Their professional level score was 8.42 points higher than that of the control group, the expert assessment score reached 43.98 points, and 82.5% of the students showed interest in dance learning. It shows that the optimization method for expressing dance emotions in this paper has good effects.