Managing business development related to the innovation of intelligent supply chains is an important task for many companies in the modern world. The study of management mechanisms, their content and interrelations of elements contributes to the optimization of business processes and improvement of efficiency. This article examines the experience of China in the context of the implementation of intelligent supply chains. The study uses the methods of thematic search and systematic literature review. The purpose of the article is to analyze current views on intelligent supply chain management and identify effective business management practices in this area. The analysis included publications devoted to various aspects of supply chain management, innovation, and the implementation of digital technologies. The main findings of the article are as follows: Firstly, the key elements of intelligent supply chain management mechanisms are identified, secondly, successful experiences are summarized and the main challenges that companies face in their implementation are identified. In addition, the article focuses on the gaps in research related to the analysis of successful experiences and the reasons for achieving them.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

Nowadays, international exchanges are becoming more and more frequent in the world. As a global language, English can establish a communication bridge between different countries and nationalities, and its importance is obvious. Since 2001, China has gradually added English education to the curriculum plan of primary schools in various regions. Later, with the deepening of the industry’s understanding of English teaching, the education reform has also followed up. It can be said that the level of educators and educates is rising spirally. However, there are still many restrictive factors in the current situation of primary school students’ learning English, among which the more prominent factors are the strength of English teachers and the evaluation mechanism for students’ learning achievements.

The scientific objective of this study is to demonstrate how a hybrid photovoltaic-grid-generator microsystem responds under transient regime to varying loads and grid disconnection/reconnection. The object of the research was realized by acquiring the electrical magnitudes from the three PV systems (25 kW, 40 kW, and 60 kW) connected to the grid and the consumer (on-grid), during the technological process where the load fluctuated uncontrollably. Similar recordings were also made for the transient regime caused by the grid disconnection, diesel generator activation (450 kVA), its synchronization with PV systems, power supply to receivers, and grid voltage restoration after diesel generator shutdown. Analysis of the data focused on power supply continuity, voltage stability, and frequency variations. Findings indicated that on-grid photovoltaic systems had a 7.9% maximum voltage deviation from the standard value (230 V) and a frequency variation within ±1%. In the transient period caused by the grid disconnection and reconnection, a brief period with supply interruption was noted. This study contributes to the understanding of hybrid system behavior during transient regimes.

Village Finance System (SISKEUDES) is a village financial reporting application policy. The application of the SISKEUDES is as a form of accountability to be accessible and known by the community. However, communication problems, resources, knowledge and limited internet networks in many regions still cause problems in reporting process. The research used a qualitative descriptive method by conducting in-depth interviews and document analysis of Mamala Negeri SISKEUDES. The policy implementation model according to George Edward III was used as an analysis tool. This research was designed to be carried out for 5 (five) months to explore various data from various information regarding this research problem. The research findings are that the provision of facilities and infrastructure for Mamala Negeri supporting human resources is still limited, making it difficult to apply the SISKEUDES 2.0 application. Besides, the village also needs more systematic transaction planning, which allows each transaction to be recorded completely both planning and realization.

Urban areas are increasingly vulnerable to fire disasters due to high population density, sprawling infrastructure, and often inadequate safety measures. This study aims to analyze the capacity of the DKI Jakarta government in terms of human resource capabilities, asset readiness, and budget planning capabilities. Furthermore, it measures the government’s success as evidenced by the public response to the achievement of firefighter performance. This study uses qualitative analysis with a content analysis approach. Data sources come from annual performance report documents and the content of the DKI Jakarta Fire Department website containing city disaster information. Performance report and website data are analyzed and used as research data to support qualitative analysis. This research shows that command decisions are essential in the organizational structure of the fire brigade. Both laboratory services are carried out optimally as a concrete effort to map fire potential. The laboratory tests the safety and suitability of firefighting equipment. Available budgetary support provides broad operational powers for the fire service. The government’s strength in minimizing or overcoming fire problems has received a positive response from the public. The operational achievements of firefighting continue to be consistent and increase. Ultimately, this research provides scientific insight into disaster mitigation and reducing the fire risk in cities.