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.

According to the United Nations, by 2050, about 68% of the world’s population will live in urban areas. This population increase requires environmental resilience and planning ability to reduce the negative environmental impacts associated with growth. In this scenario, life cycle analysis, whose standards were introduced by ISO 14000 series, is an essential tool. From this perspective, smart cities whose concern about environmental sustainability is paramount corroborating SDG 11. This study aims to provide a holistic view of environmental technologies developed by Brazilian inventors, focused on life cycle analysis, which promotes innovation by helping cities build greener, more efficient, resilient, and sustainable environments. The methodology of this article was an exploratory study and investigated the scenario of patents in the life cycle. 209 patent processes with Brazilian inventors were found in the Espacenet database. Analyzing each of the results individually revealed processes related to air quality, solid waste, and environmental sanitation. The review of patent processes allowed mapping of the technological advances linked to life cycle analysis, finding that the system is still little explored and can present competitive advantages for cities.

This study aims to identify factors related to the impact of social capital on happiness among multicultural families using the 2019 Community Health Survey, which represents the South Korean population. The study utilized data from the 2019 Korea Community Health Survey, and the study participants, aged 20 years or older, included 3524 members of multicultural families from a total of 229,099 adult households. The study found a significant difference in happiness scores across different age groups (t = 57.00, p < 0.01). Based on the median value of happiness, significant relationships were found with the independent variables: Physical Environment of Trust (t = −5.13, p < 0.001), Social Networks (t = −5.51, p < 0.001), and Social Participation (t = −5.47, p < 0.001). Happiness was found to have a positive correlation with the Physical Environment of Trust (r = 0.12, p < .001), Social Participation (r = 0.11, p < 0.001), and Social Network (r = 0.13, p ≤ 0.001). In contrast, Age (r = −0.13, p ≤ 0.001) and Stress (r = −0.14, p ≤ 0.001) showed negative correlations with happiness (r = 0.57, p < 0.001). The analysis identified a positive community physical environment (t = 3.85, p < 0.01), increased social networks (t = 4.27, p < 0.01), and higher social participation (t = 6.88, p < 0.01) as significant predictors of happiness. This model suggests that the explanation power is 15%, which is statistically significant (R² = 0.15, F = 57.72, p < 0.001). This study highlights the influence of social capital on the happiness of multicultural families living in Korea. Given the increasing number of multicultural families in the country, strategic interventions aimed at enhancing social networks and participation are necessary to promote their happiness.

The coupling coordination degree model is used to analyze the change law of the inherent coupling relationship between the forest economy and the ecological environment system in Heilongjiang Province from 2006 to 2018 and its causes. The results show that by combining the coupling relationship with the relative priority of under-forest economic development, the coupling relationship change can be divided into three stages, the coupling coordination degree from 2006 to 2009 is mainly on the verge of imbalance, and the under-forest economic development lags behind the development of the ecological environment. From 2010 to 2012, the coupling coordination degree changed from the reluctant coupling stage to the stage on the verge of imbalance, and the forest economy was ahead of the ecological environment development. From 2013 to 2018, the degree of coupling and coordination was in the reluctant coupling stage, and the under-forest economy and the ecological environment continued to develop in synchronize and in harmony. Therefore, according to the research results, it is proposed to establish the principle of ecological priority, adhere to the development of characteristics, improve the level of science and technology, and rationally develop the under-forest economic industry, so as to promote the coupling and coordinated development of the under-forest economy and ecological environment system in Heilongjiang Province.

Hospital waste containing antibiotics is toxic to the ecosystem. Ciprofloxacin is one of the essential, widely used antibiotics and is often detected in water bodies and soil. It is vital to treat these medical wastes, which urge new research towards waste management practices in hospital environments themselves. Ultimately minimizes its impact in the ecosystem and prevents the spread of antibiotic resistance. The present study highlights the decomposition of ciprofloxacin using nano-catalytic ZnO materials by reactive oxygen species (ROS) process. The most effective process to treat the residual antibiotics by the photocatalytic degradation mechanism is explored in this paper. The traditional co-precipitation method was used to prepare zinc oxide nanomaterials. The characterization methods, X-Ray diffraction analysis (XRD), Fourier Transform infrared spectroscopy (FTIR), Ulraviolet-Visible spectroscopy (UV-Vis), Scanning Electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS) have done to improve the photocatalytic activity of ZnO materials. The mitigation of ciprofloxacin catalyzed by ZnO nano-photocatalyst was described by pseudo-first-order kinetics and chemical oxygen demand (COD) analysis. In addition, ZnO materials help to prevent bacterial species, S. aureus and E. coli, growth in the environment. This work provides some new insights towards ciprofloxacin degradation in efficient ways.

This multiple case study qualitative research examined the impact of adoption and diffusion of innovation on Small and Medium Enterprises (SME’s) growth in the hostile business landscape of Khyber-Pakhtunkhwa, Pakistan. This research is intended to investigate research data and consequent findings based on an interview protocol that was purposefully developed from extant literature, complemented by an initial pilot study of two pharmaceutical SMEs. The researcher conducted 20 interviews, guided by the semi-structured interview protocol offered to the respondents beforehand after sorting their informed consent. The 20 participants represented the different hierarchal levels of the 08 case study of pharmaceutical from the two industrial clusters of Khyber Pakhtunkhwa, Pakistan, located at the Hayatabad Industrial Estate, Peshawar, and the Rashkai Industrial Estate, Nowshera. The analysis of the data presented findings and corroborated the research propositions that those SMEs that are structurally entrepreneurial and adopt innovation amenably, are open to mobility and tourism, yield satisfactory results in terms of their growth as compared to those that are inertial and unentrepreneurial. Similarly, the results offer confirmation that the effectiveness of government agencies that are explicitly formed to address the problems of small businesses is insufficient. They rather create hindrances than assistance due to the excessive delays in approving innovative ideas and conceptions by these related organizations and ministries. Moreover, the proposed framework offers pragmatic recommendations to contextualize entrepreneurial culture and innovative structures in SMEs and their essential factors in critical environmental circumstances.