Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

Rural tourism plays a crucial role in rural development in Indonesia by providing employment opportunities, livelihood, infrastructure, cultural preservation, and environmental preservation. However, it is prone to external shocks such as natural disasters, public health events, and volatility in the national and global economy. This study measures the resilience of rural tourism to external shocks caused by the COVID-19 pandemic in 24 rural tourism destinations in Indonesia covering four years from 2019 to 2022. A synthetic composite index of the Adjusted Mazziotta-Pareto index (AMPI) is used to measure rural tourism resilience followed by clustering analysis to determine the typology of the resilience. The AMPI measure is also compared with the conventional Mazziotta-Pareto index (MPI) method. The resilience index is composed of capacity and performance components related to resilience. The results show that in the first year of COVID-19, most tourism villages in Indonesia were severely affected by the pandemic, yet they were able to recover afterward, as indicated by positive differences in the AMPI index before and after COVID-19. Thus, rural tourism villages in Indonesia have a strong capacity and performance to recover from pandemic shock. Lessons learned from this analysis can be applied to policies related to rural tourism resilience in developing countries.

The technology known as Internet of Things, or IoT, has started to permeate many facets of our lives and offers a plethora of options and empowerment, expanding the potentials of integrating it in education. Considering how new IoT is and how it may affect education, it is now essential to investigate its potential in order to choose where to begin using it in the classroom. Examining the possible applications of IoT in education may be strongly aided by the knowledge and perspectives of professionals and experts. As a result, the present research concentrated on looking at and evaluating the viewpoints that relevant experts shared on platform (X) via a variety of tweets. The present study takes a qualitative approach, analyzing a collection of expert tweets on IoT in education on platform X using qualitative content analysis. The primary themes of the study findings, the software-based and material-based enablers of IoT in education, indicate the key potentials of IoT in education. These consist of data, sensors, interactive devices, e-learning tools, network accessibility and communications, integrating developing technologies, and system administration. The enormous individual enablers of IoT in education also include sustainability, professional growth, planning, preparing the next generation, and upholding the safety of the learning environment. The study suggested that in order to handle the IoT, classrooms and the educational environment needed to be restructured. Additionally, human resources needed to be developed in order to keep up with the educational environment’s progress.

Improving the practical skills of Science, Technology, Engineering and Mathematics (STEM) students at a historically black college and university (HBCU) was done by implementing a transformative teaching model. The model was implemented on undergraduate students of different educational levels in the Electrical Engineering (EE) Department at HBCU. The model was also extended to carefully chosen high and middle schools. These middle and high school students serve as a pipeline to the university, with a particular emphasis on fostering growth within the EE Department. The model aligns well with the core mission of the EE Department, aiming to enhance the theoretical knowledge and practical skills of students, ensuring that they are qualified to work in industry or to pursue graduate studies. The implemented model prepares students for outstanding STEM careers. It also increases enrolment, student retention, and the number of underrepresented minority graduates in a technology-based workforce.

The obtaining of new data on the transformation of parent materials into soil and on soil as a set of essential properties is provided on the basis of previously conducted fundamental studies of soils formed on loess-like loams in Belarus (15,000 numerical indicators). The study objects are autochthonous soils of uniform granulometric texture. The basic properties without which soils cannot exist are comprehensively considered. Interpolation of factual materials is given, highlighting the essential properties of soils. Soil formation is analyzed as a natural phenomenon depending on the life activity of biota and the water regime. Models for differentiation of the chemical profile and bioenergy potential of soils are presented. The results of the represented study interpret the available materials taking into account publications on the biology and water regime of soils over the past 50 years into three issues: the difference between soil and soil-like bodies; the soil formation as a natural phenomenon of the mobilization of soil biota from the energy of the sun, the atmosphere, and the destruction of minerals in the parent materials; and the essence of soil as a solid phase and as an ecosystem. The novelty of the article study is determined by the consideration of the priority of microorganisms and water regime in soil formation, chemical-analytical identification of types of water regime, and determination of the water regime as a marker of soil genesis.

The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity's greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.