The regulation of compressor extraction and energy storage can improve the performance of gas turbine energy system. In order to make the gas turbine system match the external load more flexibly and efficiently, a gas turbine cogeneration system with solar energy coupling compressor outlet extraction and energy storage is proposed. By establishing the variable condition mathematical model of air turbine, waste heat boiler and solar collector, we use Thermoflex software to establish the variable condition model of gas turbine compressor outlet extraction, and analyze the variable condition of the coupling system to study the changes of thermal parameters of the system in the energy storage, energy release and operation cycle. Taking the hourly load of a hotel in South China as an example, this paper analyzes the case of the cogeneration system of solar energy coupling compressor outlet extraction and energy storage, and compares it with the benchmark cogeneration system. The results show that taking a typical day as a cycle, the primary energy utilization rate of the system designed in this paper is 3.2% higher than that of the traditional cogeneration system, and the efficiency is 2.4% higher.

Introduction: Food well-being of the population is one of the priorities of the Togolese government, which relies on the agricultural investment and food security Programme to increase national food production. In addition, the country relies on food imports to make up the shortfall. At the same time undernourishment and malnutrition remain high among the country’s population. This research analyzes food supply and its implications for household consumption in Grand Lomé, Togo. [Methods] The methodology used documents, a survey of 963 heads of household randomly sampled households and semi-structured interviews with 10 households and with Togolese food safety agency (ANSAT). Quantitative data were processed and analyzed using Excel spreadsheets R and R-Studio, while content analysis was applied to the verbal applied to the verbal statements collected. Results: Firstly, the results show that domestic agricultural production contributed an average of 91% of food supply between 2014–2017. The deficit is made up by food imports, which rose from 13.5% in 2014 to 15.4% in 2017. This translated into an acceptable food energy consumption of 2337 Kcal/head/day in 2017. Secondly, 81% of respondents recognize a strong food presence at consumer markets, except that the chi-square test applied to the data at the 5% threshold shows (p-value < 2.2 × 10⁻¹⁶), indicates that this satisfaction is a function of place of residence. Despite this, persistent shortages affect more staple crops, livestock and dairy products, leading households to deprive themselves and buy food at affordable prices. Finally, we observe non-diversified diets marked by regular consumption of “cereals/legumes”, vegetables and beverages to the detriment of “tubers/roots”, “meat/fish”, “fruit” and “dairy products”. Conclusion: This research shows that food supply, although adequate, is not sufficient to ensure balanced, nutritious and culturally appropriate food consumption by urban households. Recommendations: To meet these challenges, the central government, in collaboration with urban communes and consumer advocates, must mobilize resources to create urban agricultural farms, strengthen food protection systems, distribute staple products directly to households and limit the importation of food that is hazardous to health.

This article delves into the application of blockchain technology in enhancing intellectual property (IP) protection within the e-commerce sector, providing a comprehensive analysis of its future prospects. By examining the core characteristics and working principles of blockchain, the paper reveals the unique advantages it offers in strengthening IP protection for e-commerce. The article elaborates on how blockchain’s features of decentralization, data immutability, and timestamping contribute to a secure, transparent, and efficient IP protection mechanism in the e-commerce field. Furthermore, the paper discusses the practical application of blockchain technology in IP registration, management, transaction, and rights protection, highlighting its significant impact on security traceability, transaction cost reduction, and efficiency improvement. Lastly, the article anticipates the future role of blockchain technology in IP protection in e-commerce and believes that with continued technological advancements and enhanced policy support, blockchain will play an increasingly pivotal role in this domain. The paper also proposes potential challenges and solutions that require attention, aiming to foster the healthy and sustainable development of blockchain technology.

Over the last few decades, demographic growth combined with poorly controlled urbanization has confronted African cities with a variety of environmental protection challenges. As part of a gradual awareness-raising process, African countries have ratified conventions and adopted a series of laws to protect the environment. Since independence (1960), Gabon has adopted legal instruments to provide a better framework for environmental protection. Despite the existence of well-developed legislation, the Libreville conurbation faces difficulties in waste management. This situation contributes to the degradation of the coastal zone. This study aims to analyse stakeholders’ perceptions of environmental protection regulations in solid waste management practices along the coastline of the Libreville metropolitan area in Gabon. The methodology includes documentary research, field observations, and surveys of 300 study area participants. The results show that the degradation of the coastline is due to a lack of awareness and compliance with the laws governing environmental protection and waste management. As a result, waste disposal practices such as dumping in nature, waterways, illegal dumps, and gutters are commonplace among the population. To achieve sustainable coastal zone management, it is essential to apply regulatory texts and involve stakeholders in improving planning and the quality of the coastal environment.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

This paper highlights the complex relationship between entrepreneurship, sustainable development, and economic growth in 41 European countries, using a reliable K-Means cluster analysis. The research thoroughly evaluates three key factors: the SDG Index for sustainable development, GDP per capita for economic well-being, and the New Business Density Rate for entrepreneurial activity. Our methodology reveals three distinct narratives that embody varying degrees of economic vitality and sustainability. Cluster 1 comprises the financially stable and sustainability-oriented countries of Western and Northern Europe. Cluster 2 showcases the variegated economic and sustainability initiatives in Central and Southern Europe. Cluster 3 envelopes the economic titans with noteworthy business expansion but with the potential for better sustainable practices. The analysis reveals a favourable association between economic prosperity and sustainable development within clusters, although with nonlinear intricacies. The research concludes with a series of strategic imperatives specifically crafted for each cluster, promoting economic variation, increased sustainability, invention, and worldwide collaboration. The resulting findings highlight the crucial need for policy-making that considers the specific context and the potential for combined European resilience and sustainability.