Broad-spectrum antibiotics, such as tetracyclines, are used to treat and manage a range of infectious disorders. Since the kidneys are the primary organs responsible for excreting tetracyclines, clinicians should refrain from prescribing them to patients who have renal failure. Tetracyclines are one of the clinical waste products of today. One of the biggest problems in the field of pollution of the environment today is the persistence of different pharmaceutical residues, drug residues, pesticides, and metal ion species of the new-generation pollutants in surfaces and groundwater. In the present work, carboxymethyl cellulose (CMC)-CuO nanoparticles (CMC-CuO NPs) were synthesized using CuO NPs within different amounts of CMC (0.5, 1.0, 1.5 and 2.0 g) at 85 °C. The synthesized nanoparticles were characterized by XRD, FT IR, SEM, and TG-DTA analysis. According to XRD and SEM, the crystallize size and morphology influenced the dosage of CMC. FT-IR analysis confines the layer of CMC to the CuO nanoparticle surface. TG-DTA results indicated that the CMC content of CMC-CuO NPs was between the range of 69% and 75% by weight. The effects of some parameters such as initial concentration, pH, adsorbent dosage, and contact time on the adsorption of tetracycline from aqueous model solutions on CMC-CuO NPs were investigated with batch studies. It was found that the removal of tetracycline was obtained about 80% with optimized parameters of 10 mg/L concentration, 180 min contact time, 5 pH, and 0.3 g/25 mL dose. The synthesized CMC-CuO NPs nanocomposite may be a promising material for the removal of tetracycline in environmental pollution and toxicology.

As the most basic cultural venue and an important public space in rural areas, the rural museum is not only an important carrier to realize the national strategy of rural revitalization, but also a key link to open up the "last kilometer" of spiritual prosperity in the common prosperity between urban and rural areas. As one of the three pilot provinces for the construction of rural museums under the State Administration of Cultural Heritage, Zhejiang Province has listed rural museums as one of the top ten practical matters for people's livelihood, and took the lead in issuing the Zhejiang Provincial Rural Museum Construction Guide (Trial) at the national level. The construction of rural museums in Zhejiang province has entered a new stage. The paper extracts and summarizes the common problems, successful experiences and typical cases existing in the actual development process of Zhejiang rural museums, and constructs the "Zhejiang paradigm" for the sustainable development of rural museums with promotion value and demonstration significance, providing Zhejiang experience for the sustainable development of national rural museums.

The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks' performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.

The MENA region, known for its significant oil and gas production, has been widely acknowledged for its reliance on fossil fuels. The dependence on fossil fuels has led to significant environmental pollution. Therefore, the shift towards a more environmentally friendly and enduring future is crucial. Thus, the current study tries to investigate the effect of green technology innovations on green growth in MENA region. Specifically, we examine whether the effect of green technology innovations on green growth depend on the threshold level of income. To this end, a panel threshold model is estimated for a sample of 10 MENA countries over the period 1998–2022. Our main findings show that only countries with income level beyond the threshold can benefit significantly from green technology innovations in term of green growth. Nevertheless, our findings indicate a substantial and adverse impact of green technology innovation on countries where income levels fall below the specified threshold.

This study explores the feminization of poverty and the dynamics of the care economy in rural areas, focusing on the municipality of Génova, Quindío, Colombia. The novelty of this study lies in its analysis of the compounded effects of the COVID-19 pandemic on women’s economic participation and care responsibilities in a rural context, offering insights relevant to Latin America. This study addresses the critical problem of how increased caregiving responsibilities and labor informality during the pandemic have disproportionately impacted economically active women, exacerbating gender inequalities. The objective is to analyze the relationship between the care economy and feminization of poverty, providing policy recommendations for post-pandemic recovery in rural settings. The methodology consisted of a two-stage approach. In the first stage, a probabilistic stratified sampling design was applied using data from the Colombian National Population and Housing Census and the Génova, Quindío, and Colombia Municipal Panel. In the second stage, fieldwork was conducted with a sample of 347 women using the RedCap application for data collection. The results indicate a significant increase in unpaid domestic and caregiving work during the pandemic, particularly for the elderly, disabled, and children. Additionally, labor informality increased, further limiting economic opportunities for women. The key conclusion is that public policies aimed at reducing gender disparities in rural labor markets must prioritize caregiving support and formal employment opportunities for women. These findings suggest that addressing the care economy is crucial for closing gender gaps and fostering equitable economic recovery in rural Latin American areas.

This study’s primary objective is to determine the financial repercussions, including expenses, profits, and losses, that certain stakeholders in the Tuong-mango value chain face at various distribution stages. This was achieved through the utilisation of stakeholders cost-benefit value chain analysis. These individuals collectively contributed 849 sample observations to the dataset including 732 farmers, 10 cooperative, 32 collectors, 25 wholesalers, 30 retailers, 12 exporters and processors, and 08 grocery stores/fruit. The robust financial performance of the Tuong-mango value chain is attributable to its integrated economic efficiency, as evidenced by its over USD 1 billion in revenue and USD 98.2 million in net income. The marketing channels, specifically channels 1, 2, and 3, generate a total of USD 906.1 million in revenue, yielding a net profit of USD 81.9 million. The combined sales from domestic marketing channels 4 and 5 total USD 160 million, yielding a net profit of USD 16.2 million. The findings indicate that due to their limited scope and suboptimal grade 1, farmers are the most vulnerable link in the supply chain. This study proposes three strategies for augmenting quality, fostering technological advancement, and facilitating the spread of benefits. This study’s findings contribute to the existing literature on value chain analysis as it pertains to various tropical fruits and vegetables. The study provides empirical evidence supporting the utility of the value chain method in policy formulation.