With the rapid development of modernization and the reform and development of quality education, the main direction and goal of vocational colleges in the new era is to cultivate high-level skilled talents required by the times. With the development of globalization and the refined division of labor in industrial technology, the requirements of various industries for high-level skilled talents with the ability to adapt to market development are gradually increasing. This article focuses on exploring and analyzing the demand for hospital imaging technology talents under the rapid development of the new era industry, and discovering the problems in talent cultivation in vocational colleges. In response to the existing problems, actively utilizing college resources and practical opportunities, innovating the college school cooperation mode and teaching methods for imaging technology majors in vocational colleges, and gradually expanding into a standardized, scientific, and developable college cooperation mode for vocational education, Implement the national strategic plan for cultivating quality talents in vocational colleges, focus on doing a good job in the work of "cultivating morality and talents", adhere to the "three education" reform, and improve the quality of talent cultivation.

In recent years, e-sports, as an emerging form of competition, has been rapidly integrated into the daily life of college students, and with its rich interactivity, instant feedback and teamwork, e-sports provides them with an effective channel for emotional catharsis and psychological regulation. This study takes students from four universities as the survey object and adopts quantitative research method to analyze the relationship between different types of e-sports activities and psychological stress resistance through questionnaire survey method combined with spss. The samples were randomly sampled, and a total of 500 valid questionnaires were collected. The results of the study show that: 1. In terms of participation, the ability of students to withstand academic stress and life stress is significantly improved, and e-sports is an effective way to regulate emotions and relieve stress; 2. the three types of games (First-person Shooter, Multiplayer Online Battle Arena, Real-Time Strategy Game) have different impacts on stress tolerance, of which FPS has the greatest impact on stress tolerance; 3. the frequency of playing e-sports affects your stress tolerance; 4. teamwork and strategy play an important role in e-sports resilience.

Since 2019, Togo has resolutely engaged in the decentralization process marked by communalization and elections of municipal councilors. Financial autonomy constitutes an essential lever for the free administration of municipalities, allowing them to ensure decision-making and the implementation of development projects. However, despite a legal and regulatory framework defining taxation specific to local authorities, Togolese municipalities are often perceived as needing more financial resources. This study aims to map the financing mechanisms for decentralization in Togo and analyze their contribution to municipal budgets. By adopting a quantitative approach combining documentary analysis and interviews with 188 experts and practitioners of local finance from various Togolese structures, four main financing mechanisms were identified: local, national, Community, and international. Among these mechanisms, own resources (in particular from the sale of products and services, fiscal and non-fiscal taxes) and state transfers via the Support Fund for Local Authorities emerge as the primary sources of financing for municipalities. However, the study reveals that several instruments of local mechanisms, although institutionally defined, still need to be updated in many municipalities, thus limiting their effectiveness in resource mobilization. These results highlight the importance of optimizing the management of local mechanisms to strengthen municipalities’ financial autonomy and support territories’ sustainable development.

The study explores improving opportunities of forecasting accuracy from the traditional method through advanced forecasting techniques. This enables companies to optimize inventory management, production planning, and reducing the travelling time thorough vehicle route optimization. The article introduced a holistic framework by deploying advanced demand forecasting techniques i.e., AutoRegressive Integrated Moving Average (ARIMA) and Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) models, and the Vehicle Routing Problem with Time Windows (VRPTW) approach. The actual milk demand data came from the company and two forecasting models, ARIMA and RNN-LSTM, have been deployed using Python Jupyter notebook and compared them in terms of various precision measures. VRPTW established not only the optimal routes for a fleet of six vehicles but also tactical scheduling which contributes to a streamlined and agile raw milk collection process, ensuring a harmonious and resource-efficient operation. The proposed approach succeeded on dropping about 16% of total travel time and capable of making predictions with approximately 2% increased accuracy than before.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

Electrical energy is known as an essential part of our day-to-day lives. Renewable energy resources can be regenerated through the natural method within a reasonably short time and can be used to bridge the gap in extended power outages. Achieving more renewable energy (RE) than the low levels typically found in today’s energy supply network will entail continuous additional integration efforts into the future. This study examined the impacts of integrating renewable energy on the power quality of transmission networks. This work considered majorly two prominent renewable technologies (solar photovoltaic and wind energy). To examine the effects, IEEE 9-bus (a transmission network) was used. The transmission network and renewable sources (solar photovoltaic and wind energy technologies) were modelled with MATLAB/SIMULINK^®. The Newton-Raphson iteration method of solution was employed for the solution of the load flow owing to its fast convergence and simplicity. The effects of its integration on the quality of the power supply, especially the voltage profile and harmonic content, were determined. It was discovered that the optimal location, where the voltage profile is improved and harmonic distortion is minimal, was at Bus 8 for the wind energy and then Bus 5 for the solar photovoltaic source.