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.

Cellulose nanocrystal, known as CNCs, is a form of material that can be produced by synthesizing carbon from naturally occurring substances, such as plants. Due to the unique properties it possesses, including a large surface area, impressive mechanical strength, and the ability to biodegrade, it draws significant attention from researchers nowadays. Several methods are available to prepare CNC, such as acid hydrolysis, enzymatic hydrolysis, and mechanical procedures. The characteristics of CNC include X-ray diffraction, transmission electron microscopy, dynamic light scattering, etc. In this article, the recent development of CNC preparation and its characterizations are thoroughly discussed. Significant breakthroughs are listed accordingly. Furthermore, a variety of CNC applications, such as paper and packaging, biological applications, energy storage, etc., are illustrated. This study demonstrates the insights gained from using CNC as a potential environmentally friendly material with remarkable properties.

In the era of rapid information technology development, artificial intelligence (AI) and virtual reality (VR) technologies have gradually infiltrated the field of university English teaching, brought significant applications and impacted to English language learning in listening, speaking, writing, translation, and personalized learning. AI plays a vital role as an auxiliary teaching method in university English instruction, and the integration of VR technology further enhances teaching efficiency. This research will propose relevant recommendations to provide theoretical references for university English education in the age of AI, while also offering insights and guidance to educators in the education industry during the informatization reform of education.

In this paper, we will provide an extensive analysis of how Generative Artificial Intelligence (GenAI) could be applied when handling Supply Chain Management (SCM). The paper focuses on how GenAI is more relevant in industries, and for instance, SCM where it is employed in tasks such as predicting when machines are due for a check-up, man-robot collaboration, and responsiveness. The study aims to answer two main questions: (1) What prospects can be identified when the tools of GenAI are applied in SCM? Secondly, it aims to examine the following question: (2) what difficulties may be encountered when implementing GenAI in SCM? This paper assesses studies published in academic databases and applies a structured analytical framework to explore GenAI technology in SCM. It looks at how GenAI is deployed within SCM and the challenges that have been encountered, in addition to the ethics. Moreover, this paper also discusses the problems that AI can pose once used in SCM, for instance, the quality of data used, and the ethical concerns that come with, the use of AI in SCM. A grasp of the specifics of how GenAI operates as well as how to implement it successfully in the supply chain is essential in assessing the performance of this relatively new technology as well as prognosticating the future of generation AI in supply chain planning.

Land use or land cover (LU/LC) mapping serves as a kind of basic information for land resource study. Detecting and analyzing the quantitative changes along the earth’s surface has become necessary and advantageous because it can result in proper planning, which would ultimately result in improvement in infrastructure development, economic and industrial growth. The LU/LC pattern in Madurai City, Tamil Nadu, has undergone a significant change over the past two decades due to accelerated urbanization. In this study, LU/LC change dynamics were investigated by the combined use of satellite remote sensing and geographical information system. To understand the LU/LC change in Madurai City, different land use categories and their spatial as well as temporal variability have been studied over a period of seven years (1999-2006), by analyzing Landsat images for the years 1999 and 2006 respectively with the help of ArcGIS 9.3 and ERDAS Imagine 9.1 software. This results show that geospatial technology is able to effectively capture the spatio-temporal trend of the landscape patterns associated with urbanization in this region.

In the teaching of graphic design, students' learning state and learning effect are poor due to the lack of attractiveness of teaching materials. In order to fully display the graphic design knowledge contained in totem patterns, a model based on the pattern elements of totem patterns was constructed. Through Marvelous Designer software, the display of totem visual effects under different pattern element configurations was realized, providing a basis for the comparative explanation of graphic design teaching. When designing the teaching content, based on the totem art culture, it has constructed three parts of teaching methods of plane composition, teaching contents of plane composition and teaching concepts of plane composition, which correspond to the material selection, composition and freehand brushwork skills of totem patterns in modeling creativity and expression techniques, and the range of material selection, composition form and connotation of plane design teaching, the specific application is realized through knowledge transfer.