Microbial fermented feed enhances the nutritional and fermentation quality of feed through microbial technology, making it suitable for livestock, poultry, and aquaculture, particularly for young animals and antibiotic-free farming needs.  This study utilized Bacillus to ferment complete pig feed to investigate the effects of Bacillus on the nutritional and fermentation quality of the feed post-fermentation.  The complete feed was mixed with water at a 1:1 ratio, and 5% Bacillus was added, thoroughly mixed, and then bagged (with an exhaust valve) for fermentation at room temperature for 10 days. A control group was set up with the same proportion of sterile water added to unfermented feed.  The nutritional and fermentation quality of the fermented feed were subsequently measured.  The results indicated that compared to unfermented feed, the contents of dry matter, crude fiber, neutral detergent fiber, ADF, ammonia nitrogen, and soluble sugar in fermented feed were significantly lower than those in the control group (P < 0.05), while the contents of crude protein and starch were significantly higher than those in the control group (P < 0.05).  The lactic acid, acetic acid, and propionic acid in experimental group I and experimental group II were significantly higher than those in the control group (P < 0.05), whereas the pH and butyric acid content in the control group were significantly higher than those in experimental group I and experimental group II (P < 0.05).  The acetic acid, propionic acid, and butyric acid contents in experimental group II were significantly higher than those in experimental group I, and the pH was significantly lower than that in experimental group I.  Fermented feed with different Bacillus strains improved the nutritional quality and fermentation quality of the feed.

【Objective】 To investigate the effects of substituting fermented non-conventional feed for the basal diet in fattening Bamei pigs. 【Methods】Seventy-two Bamei pigs during the fatling period were randomly divided into two groups, each containing six replicates with six pigs per replicate. The control group (CK) was fed a corn-soybean meal basal diet, while the experimental group (FK) received the basal diet supplemented with 10% fermented non-conventional feed (dry matter basis) as an equal replacement. After 60 days of feeding, twelve pigs from each group were slaughtered for sample collection and performance evaluation. 【Results】 The results demonstrated that fermented non-conventional feed significantly reduced the cardiac organ index (P < 0.05) and increased the renal organ index (P < 0.05). Regarding immune-related gene expression, the feed markedly elevated the relative mRNA expression levels of IL-1, IL-2, TNF, IgA, and IgM in both lymphoid and hepatic tissues (P < 0.01). 【Conclusion】 In summary, replacing 10% of the basal diet with non-conventional fermented feed improves the health status and immune function of fattening Bamei pigs. Thus, substituting conventional feed with fermented non-conventional feed is not only feasible but also offers an economically efficient nutritional strategy for local pig breeds farming.

This study aimed to investigate the myofiber characteristics of different cuts of Qinghai yak beef and their correlation with meat quality. Six cuts of yak beef, namely tenderloin, knuckle, shank, chuck, striploin, and neck, were analyzed for their myofiber properties using frozen sectioning and ATPase histochemical staining, and the correlation between these characteristics and meat quality attributes including meat color, pH, cooking loss, fat content, shear force, and texture profile analysis (TPA) was assessed. Results indicated that muscle location significantly affected the proportions of type I, IIA, and IIB myofibers (P < 0.05), which were closely related to beef quality. In terms of myofiber diameter, chuck exhibited the lowest type I diameter, whereas neck had a significantly higher type I diameter compared to other cuts (P < 0.05). Analysis of myofiber area also revealed significant differences in the area of the same myofiber type across different cuts (P < 0.05). Furthermore, other meat quality indicators such as fat content, cooking loss, meat color, and chewiness varied significantly among cuts (P < 0.05), while pH values did not differ significantly. These findings demonstrate that muscle location has a significant impact on yak beef quality and that a strong correlation exists between myofiber characteristics and beef quality.

This study systematically analyzes the key factors influencing brand value enhancement for ecological agricultural products, using ecological products from Northwestern Sichuan as a case study. It uncovers the multidimensional components affecting brand value, highlighting the significance of ecological agricultural products in promoting sustainable agricultural development and their distinctive market characteristics and environmental benefits. The research reveals that brand value is significantly shaped by Brand Communication Strategy, Product Differentiation Strategy, and Marketing Innovation. A case study approach explores ecological agricultural brands, and products from Northwestern Sichuan, summarizing the factors contributing to their success. Empirical research substantiates the fundamental nature of these influencing factors. The comprehensive analysis indicates that building a robust brand image and adopting effective marketing strategies are essential for increasing the brand value of ecological agricultural products. Looking forward, industry participants are encouraged to strengthen brand development and optimize consumer experiences to navigate the intensifying market competition, thus achieving dual ecological and economic benefits.

This study focuses on how New Quality Productive Forces (NQPF) empower the circular economy industry in the Beijing-Tianjin-Hebei (BTH) metropolitan region, exploring their synergistic mechanisms in carbon reduction, pollution control, green expansion and economic growth. Through systematic literature review and case studies, the research first reveals the current status of circular economy development in the BTH region, identifying existing challenges in industrial decarbonization/pollution reduction and the urgency of ecological conservation. The study further defines the conceptual framework of NQPF, clarifying its catalytic role in promoting circular economy through resource efficiency enhancement, industrial structure optimization, and technological innovation. By introducing empowerment mechanisms and pathway analysis, the research demonstrates that NQPF not only improves the overall efficiency of circular economy but also fosters cross-sectoral collaboration, forming a new model of green development. Data collection and analysis indicate that the BTH region needs to strengthen policy coordination and social participation to achieve comprehensive green transformation. Based on findings, the study proposes policy recommendations and industrial collaborative development models to enhance public awareness and ensure ecological sustainability alongside economic growth.

The integration of millimeter-wave (mmWave) radar technology with ResNet, a deep convolutional neural network, has emerged as a promising solution for applications such as autonomous driving, healthcare, and industrial automation. This paper reviews recent advancements in integrating millimeter-wave radar technology with Residual Neural Networks (ResNet) and their significance for future innovations. Millimeter-wave radar offers high resolution and robustness in adverse conditions, making it essential for autonomous vehicles, drone operations, and smart cities. ResNet, a major development in deep learning, tackles gradient issues in neural network training through its residual learning framework. The paper also suggests future research directions to enhance the practical applications of millimeter-wave radar and ResNet in areas like autonomous driving, environmental monitoring, and weather forecasting, highlighting their potential and prospected applications.

Telecom fraud is a criminal activity that utilizes phones, the internet, and text messages to deceive victims into transferring funds. With the advancement of technology, telecom fraud methods continue to evolve, making the identification and prevention of these fraudulent activities increasingly important. This paper combines data provided by the organizing committee for data analysis and the establishment of a telecom and bank card fraud prediction model.

In Problem 1, data visualization techniques were used to analyze the environment in which telecom and bank card fraud occurs. Pie charts and bar charts were created to display the frequency of fraud occurrences and the ratio of online to offline fraud. The analysis revealed a higher incidence of telecom fraud in online environments, providing a basis for subsequent preventive strategies.

In Problem 2, we used a logistic regression model to analyze the impact of bank card usage (whether the card was used for transfers on a device and whether a PIN code was used for transactions) on the probability of telecom fraud. The results showed that using a PIN code significantly reduced the likelihood of fraud, suggesting that strengthening the use of PIN codes is an effective strategy in preventing telecom fraud.

In Problem 3, we tested the linearity and normality of variables, using Spearman’s correlation analysis and chi-square tests to reveal the correlation between factors such as the transaction amount ratio, whether transactions were conducted with the same bank, and whether transactions were made online. The in-depth analysis of these indicators aids in more accurately identifying potential fraudulent activities and provides feature importance for the prediction model.

In Problem 4, convolutional neural network (CNN) models, long short-term memory (LSTM) models, and attention mechanisms were introduced. We employed stacking ensemble learning to integrate models, improved the attention mechanism, and added measures to prevent overfitting. Finally, we calculated accuracy, precision, recall, and F1 scores for each model. The results showed that the telecom and bank card fraud prediction model established in this paper achieved an accuracy of 99.99%, effectively predicting fraud. Based on the data analysis throughout this paper, we provide recommendations for public security departments, banks, and citizens to reduce the probability of telecom fraud.

In conclusion, this paper applies modern data analysis and machine learning techniques, with particular innovations in model integration and the application of attention mechanisms. Not only does this improve the prediction ability of the models, but it also validates their applicability and robustness through accuracy and error analysis. The research results are compared with existing technologies in a horizontal comparison and demonstrate the model's potential for future expansion, providing a promising outlook for telecom and bank card fraud detection.

The main purpose of the article in to study the impact of the development of digital economy on the efficiency of healthcare resource allocation in China , and to explore the specific mechanism of action and regional heterogeneity of its efficiency enhancement. Based on the panel data of 30 provinces in China from 2012 to 2022, the article constructs a two-way fixed-effects model, taking the level of digital economy development as the core explanatory variable, the healthcare resource allocation efficiency measured by the Envelopment of Data Approach (EDA) as the explanatory variable, and gradually introduces control variables such as the level of urbanisation, the level of economic development, the level of education, and the fiscal expenditure. In addition, the article adopts three-level indicator substitution of explanatory variables and principal component analysis (PCA) instead of entropy weight method (EWM) accounting, Tobit regression and other methods to carry out the robustness test, and explores the heterogeneous impact of the digital economy in the eastern, central and western regions through group regression. The results of the study show that the digital economy significantly improves the efficiency of healthcare resource allocation, and this effect remains robust after introducing different control variables. The reliability of the model and the robustness of the results are further verified by robustness tests. Heterogeneity analysis shows that the digital economy has the most significant effect on healthcare resource allocation efficiency in the eastern region, while it is relatively weaker in the central and western regions. The findings of the article not only enrich the research on the digital economy and healthcare resource allocation efficiency, but also provide policy references for optimising healthcare resource allocation. It is recommended to strengthen the construction of digital infrastructure in the future and formulate policies according to local conditions to promote the balanced development of regional medical resources.

Modern Lü Opera has achieved a qualitative leap in singing techniques and expressiveness. Performers not only skillfully employ vibrato, making the voice as delicate and flowing as silk, but also enhance breath control, infusing each phrase with power and emotion. At the same time, they ingeniously integrate resonance techniques, rendering the sound fuller, more rounded, and penetrating. The flexible mastery of dynamic shading and the natural variation of timbre further enhance the emotional appeal of the singing, aligning the voice seamlessly with the character's emotions in a nuanced manner. The exquisite application of these techniques not only elevates the realism and immersion of the drama but also allows the audience to experience the unique charm of Lü Opera, injecting new vitality into its inheritance and development.

With the rapid development of technology and the ever-changing global landscape, technologies such as cloud computing, artificial intelligence, big data, and blockchain are being widely adopted. E-commerce is rising rapidly, and in today's era, Alibaba Group's overall development trend has gradually heated up after the "1+6+N" business model reform. For investors, stock trend prediction is an important task, but predicting stock price movements is challenging due to the influence of various factors. The Random Forest model is an important technology in the field of artificial intelligence, with significant effectiveness in simulating the specific characteristics of research objects, handling nonlinear problems, and studying non-stationary data. This paper aims to predict Alibaba Group's future development prospects and stock price fluctuations after a series of reforms by constructing a Random Forest model. A multivariate linear regression model is used for numerical analysis, while the model's predictions are systematically scored under the MAE, MSE, MAPE, and RMSE indicators. The accuracy of the Random Forest model in predicting Alibaba Group's future stock price trends is as high as 82.97%.

Abstract

FinTech is an emerging interdisciplinary major, but several issues remain in talent cultivation, such as unclear professional characteristics, low integration of different disciplinary curricula, and a lack of understanding among instructors regarding the integration of professional development and ideological and political education. This study analyzes these issues and proposes reform suggestions. First, emphasis should be placed on faculty development by enhancing instructors' awareness of integrating ideological and political education with professional development, strengthening their professional capabilities, innovating teaching methods, and establishing an evaluation and feedback mechanism to comprehensively improve their expertise in interdisciplinary education and teaching. Second, curriculum development should be the key focus. Measures such as constructing an integrated teaching system, building a case repository for ideological and political education in FinTech, and improving the evaluation of ideological and political education effectiveness in professional courses can help achieve full integration of ideological and political education with professional development. Additionally, the OBE (Outcome-Based Education) approach should be consistently applied throughout the integration process to ensure that professional development goals are effectively supported.

With the end of the COVID-19, the global economy has entered a period of rapid recovery. China , in particular, has transitioned to a new stage of economic development. The home appliance industry, a trillion dollar sector, has playing a crucial role driving China's domestic demand. Its significant scale has consistently contributed to both economic growth and improvements in quality of life. Increasingly, attention is being paid to the impact of internal control effectiveness in home appliance enterprises on non-financial performance measures , such as intelligent green innovation and ESG (Environmental, Social, and Governance) performance. Many companies aim to strengthen internal controls to enhance operational efficiency, improve economic performance, and boost financing capabilities.

This paper mainly introduces the definition of orthogonal matrix and its nine common properties, as well as some applications of orthogonal matrix in advanced algebra: using orthogonal matrix to solve some specific problems related to orthogonal transformation in Euclidean space, transforming quadratic form into canonical form through orthogonal matrix, simplifying quadratic surface equation with orthogonal matrix, and using orthogonal matrix in matrix decomposition.

The aim of this study is to investigate the influence of each parameter on the mechanical properties of strip steel in the continuous annealing process of cold rolled strip steel. The influence of each parameter on the hardness of strip steel was systematically analysed by collecting the specification data, process parameters and performance index data of the strip steel products, and applying descriptive statistical analysis, Spearman correlation coefficient analysis, random forest regression and factor analysis. The results show that carbon content, quenching furnace temperature, homogenising furnace temperature and fast cooling furnace temperature are the key factors affecting the hardness of strip steel. Among them, carbon content and quenching furnace temperature showed a significant positive correlation with hardness, while the average heating furnace temperature and fast cooling furnace temperature showed a significant negative correlation with hardness. These findings provide an important theoretical basis for optimising the production process of cold rolled strip steel, which helps to improve the product quality and the economic benefits of enterprises.

The implementation of the rural revitalization strategy has brought new opportunities and challenges to the development of agricultural insurance. Based on an analysis of the current status of agricultural insurance in Guangxi, this paper explores the necessity of technological empowerment in agricultural insurance, outlines the practical pathways for technology-driven agricultural insurance in Guangxi, and proposes corresponding countermeasures to address existing issues. The study aims to provide references for the high-quality development of agricultural insurance in Guangxi and contribute to rural revitalization.

This dissertation explores the factors that influence students’ choices to attend English medium of instruction (EMI) international schools in Southern China. I investigate the benefits and drawbacks these students face when studying at an EMI school. The research employed a case study approach, collecting data through mixed methods, i.e. a quantitative questionnaire and a qualitative semi-structured interview from a range of students from one EMI international school in Dongguan city, China. The findings build on previous studies within the field. In the present study, the findings suggested that students’ motivation to study in EMI schools was influenced by their desire to study overseas, the small class sizes, the more active learning environment, greater pastoral care and the increased opportunities to develop their English language proficiency and skills that these schools offer.  

Additionally, the findings identified a number of concerns and disadvantages highlighted in a few studies, including prohibitive tuition costs, unqualified teachers and in some cases, poor management within EMI schools. The findings also suggest that a number of students who had attended an EMI school would not recommend others to attend the same type of school due to the high tuition, inferior quality of teaching and poor management. The results question whether students who have graduated from an EMI school regard their school to have a superior status compared to local high schools. Based on the findings, recommendations are that EMI international schools should aim to enhance the quality of teaching and the organization of schools if they wish to attract more students in the future. The growth of EMI schools has been significant within the Guangdong region of China, however the quality assurance and longevity of these new institutions has yet to be proven. If EMI schools are to contribute greatly to the education and if they are going to be successful, then some of the issues raised in the present study need to be addressed.

This article analyzes various legal aspects related to the sovereignty, self-determination, and international legal processes involving Antilia, Caladon, and Goron, focusing on the principles of territorial integrity and self-determination under international law. Antilia's claim to statehood is evaluated based on the Montevideo Convention, demonstrating that it meets the criteria of a permanent population, defined territory, established government, and international recognition. The article also discusses Caladon’s claim to territorial integrity and its opposition to Antilia’s independence, arguing that Caladon’s rejection of Antilia’s referendum is consistent with the principle of territorial integrity under international law. Furthermore, Goron’s intervention in Antilia is assessed in light of the responsibility to protect principle and the potential violation of Article 2(4) of the UN Charter. The article also explores jurisdictional issues related to international crimes committed by Avi Jostein Sen, with a focus on the principles of universal jurisdiction and sovereign immunity. Finally, the article addresses the enforceability of arbitration clauses in international contracts, using a dispute between companies G and S as a case study, highlighting the application of the New York Convention and the Australian International Arbitration Act.

Tongue recognition plays a pivotal role in traditional Chinese medicine (TCM), and there have been many deep learning studies applied to tongue recognition, but there are fewer studies on lightweight tongue recognition, and the use of a lightweight network to apply tongue recognition to mobile has a pivotal role in the digitalisation and standardisation development of TCM, as well as monitoring and warning of people's health conditions, and a deep learning-based lightweight recognition method is the key to achieve mobile deployment. In this research paper, an efficient hybrid tongue image recognition network (SESAViT), a novel neural network integrating convolutional neural network and VIT, is proposed. We found that in the image recognition task, although VIT shows advantages in extracting global information, it is computationally intensive, so we simplify the computational VIT approach by using the sandwich layout, segmented attention module, making it possible to get rid of the limitation of VIT's multi-head self-attention mechanism, and we call the model SAViT.For the convolutional neural network part, we use the token mixer and channel mixer separation to achieve lightweight improvement. Our experiments on a homemade tongue dataset demonstrate the superiority of our method, with tongue colour, tongue moss features, tongue body features, tongue shape, dentate tongue and cleft tongue classification accuracies of 86.284%, 82.467%, 83.417%, 86.259%, 84.759% and 85.759%, respectively, which is much better than that of lightweight networks based on VIT and MobileNet v3 by about 3%.

With the rapid development of science and technology, the intelligent network automobile industry is an important direction in the future transportation field.It has attracted wide attention.As an important city in western China, Chongqing also has broad prospects for development in the field of intelligent network automobile.With the promotion of the construction of Chongqing's "33618" modern manufacturing cluster system, Chongqing's automobile industry has developed vigorously.However, the development of Chongqing Intelligent Network United Automobile is also facing some difficulties, including insufficient technological innovation and insufficient market demand.Lack of talent and so on. The purpose of this paper is to analyze the current development dilemma of Chongqing intelligent network automobile industry cluster, and put forward the corresponding countermeasures.In order to promote the healthy development of this field.