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.
Nothofagus pumilio forests constitute the most economically important forest stand in southern Argentina and Chile. Total volume stocking and volumetric yield vary according to site quality, degree of occupation, growth stage and forest history of the stand. The objective of this work was to evaluate the stocking and the productive potential in quantity and quality of products for the sawmilling industry, using three harvesting systems (short logs, long logs and complete shafts) in the protection cut of a N. pumilio forest of site quality III in Tierra del Fuego (Argentina). The trials were conducted in an irregular mature forest with two strata and abundant regeneration (3.0 ha; RDI 93.8–113.4%). Total volumes varied between 726.5 and 850.3 m3∙ha-1, with a volume/basal area ratio of 11.8 to 12.1 m3∙m-2. The harvesting rates obtained were: 45.5% for complete logs, 21.3% for long logs and 22.4% for short logs. A model was used to estimate the timber volume for each system, where full shafts resulted in a significant increase in timber volume. Considering new alternatives in the planning of harvesting in forest management for N. pumilio forests, such as the system of complete shafts, allows obtaining higher harvesting rates, increasing the benefits for the forestry company and minimizing the damage to the forest, due to the shorter distance of the machinery in the forest harvesting.
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 argues for a novel approach to financing infrastructure needs in Arab countries. It first describes the context of rising public debt in the region, contrasting it with the vast infrastructure needs. It then discusses the challenges in meeting these needs with traditional financing. The paper then makes the case for maximizing finance for development by using public-private partnerships and presents a few successful examples in Arab countries. Finally, the paper explores the way forward and concludes on the need for strong state capacity and integrity to promote the “maximizing finance for development” approach.
Recent research efforts have increasingly concentrated on creating innovative biomaterials to improve bone tissue engineering techniques. Among these, hybrid nanomaterials stand out as a promising category of biomaterials. In this study, we present a straightforward, cost-efficient, and optimized hydrothermal synthesis method to produce high-purity Ta-doped potassium titanate nanofibers. Morphological characterizations revealed that Ta-doping maintained the native crystal structure of potassium titanate, highlighting its exciting potential in bone tissue engineering.
The COVID-19 pandemic has instigated global lockdowns, profoundly altering daily life and resulting in widespread closures, except for essential services like healthcare and grocery stores. This scenario has notably intensified mental health challenges, particularly among children and adolescents. Influenced by a myriad of factors including developmental stages, educational backgrounds, existing psychiatric disorders, and socioeconomic status, the pandemic’s impact extends beyond the immediate health crisis. This paper critically examines the multifaceted effects of the pandemic on mental and physical health across various age groups. It highlights the increased incidence of stress, anxiety, and depression, underscoring the pandemic’s deep psychological footprint. Additionally, the paper explores the societal implications, from altered family dynamics and educational disruptions due to the shift to online learning, to workplace transformations. These changes have led to a mix of adaptive responses and adverse effects, including heightened domestic tensions and mental health issues. The paper also delves into the ethical challenges faced by medical professionals during this crisis, balancing urgent patient care with ongoing medical research and mental health considerations. This analysis aims to provide a comprehensive understanding of the COVID-19 pandemic’s extensive impact on health and society, emphasizing the importance of addressing mental health as a crucial component of the response strategy.
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