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.

The direct expansion heat pump with solar energy is an energy conversion system used for water heating applications, air heating for air conditioning buildings, water desalination, solar drying, among others. This paper reviews the main designs and analysis of experiments in order to identify the fundamental objectives of any experiment which may be: to determine the factors that have a significant influence, to obtain a mathematical model and/or to optimize performance. To achieve this task, the basic and advanced configuration of this system is described in detail in order to characterize its thermal performance by means of energy analysis and/or exergy-based analysis. This review identifies possible lines of research in the area of design and analysis of experiments to develop this water heating technology for industrial applications.

Alfalfa is considered the most used forage crop in the world, its main use is for cattle feeding, due to its high nutritional value, specifically in protein and digestible fiber. Currently, the trend in agriculture is to reduce the application of chemicals and among them are fertilizers that pollute soil and water, so the adoption of new technologies and other not so new is becoming a good habit among farmers. Nanotechnology in the plant system allows the development of new fertilizers to improve agricultural productivity and the release of mineral nutrients in nanoforms, which has a wide variety of benefits, including the timing and direct release of nutrients, as well as synchronizing or specifying the environmental response. Biofertilizers are important components of integrated nutrient management and play a key role in soil productivity and sustainability. While protecting the environment, they are a cost-effective, environmentally friendly and renewable source of plant nutrients to supplement chemical fertilizers in the sustainable agricultural system. Nanotechnology and biofertilization allow in a practical way the reduction in the application of chemicals, contributing to the sustainability of agriculture, so this work aims to review the relevant results on biofertilization, the use of nanotechnology and the evaluation of the nutritional composition of alfalfa when grown with the application of biofertilizers.

This paper qualitatively analyzes the connotation of woodland welfare and the changes of woodland welfare that may be caused by the transfer of the right to use, and interprets the welfare improvement caused by the transfer of the right to use of woodland in the ideal state by using the relevant theories and models of microeconomics. Based on the prospect theory and psychological account theory of behavioral economics, this paper analyzes the reasons why the transfer of forestland use right has not been carried out on a large scale in China.

Shore line change is considered as one of the most dynamic processes, which were mapped along the coast of Tiruvallur district by using topographic maps of 1976 and multi-temporal satellite images. The satellite images pertaining to 1988, 1991, 2006, 2010, 2013 and 2016 were used to extract the shorelines. It is important to map and monitor the HTL (High Tide Line) at frequent time intervals as the shoreline was demarcated by using visual interpretation technique from satellite images and topographic maps. Followed by this, an overlay analysis was performed to calculate areas of erosion and accretion in the study area. The results revealed that the coast of Tiruvallur district lost 603 ha and gained 630 ha due to erosion and accretion respectively. It was confirmed after the ground truth survey carried out in the study area. The high accretion of 178 ha was found nearby Pulicat Lake and low accretion of 19 ha was seen between Pulicat Lake and Kattupali Port. The high erosion area was found along the Pulicat Lake, Kattupali and Ennore ports, and Ennore creek mouth and southern Ennore such as Periya Kuppam, Chinna Kuppam, Kasi Koil Kuppam, and Thyagarajapuram. It may be concluded that the coastal erosion and accretion in the study area were mainly caused by anthropogenic and natural factors, which altered the coastal environment.

Flower-visiting insects may be pollinators or, conversely, unrelated to the reproductive process of plants. Interactions between pollinating and non-pollinating flower visitors can negatively influence pollen transfer. Little is known about the effects of bee visits on pollination of squash (Cucurbita spp.) flowers and their interactions with the presence of other floral visitors. The study was conducted at the Facultad de Ciencias Agrarias (Universidad Nacional de Rosario) in the south of Santa Fe (Argentina) and evaluated the effect of the presence of non-pollinating floral visitors on bee foraging in the flowers of two cultivated squash species. Flower sex and squash species C. maxima and C. moschata were included as variables. A total of 937 visitors were recorded in 403 flowers. Bees of the tribes Eucerini and Apini were the most abundant pollinators with an average of 2.3 individuals per flower during 10 minutes of observation. Diptera, flower sex and squash species did not influence the number of bee visits, whereas the prolonged stay of coleoptera and formicids negatively affected the presence of bees on both squash species. The presence of coleoptera reduced bee visits by 38%, while in the presence of ants, bees did not visit the flowers. The theft of nectar and pollen by non-pollinating floral visitors could have a negative effect on the reproductive success of squash.