In this study, ‘Xinli No. 3’, ‘Shengli rootstock’, ‘Shenli rootstock’ and ‘Shengzhen No. 1’ were used as rootstock, and ‘Jinchun No. 39’ cucumber was used as scion to study the effects of different rootstock on the yield and quality of grafted cucumber, and to select high quality rootstock suitable for cucumber grafting. Different rootstock affected the survival rate, phenology, the height of plant, stem diameter, growth potential, yield and quality of cucumber grafting. Among them, the survival rate of ‘Shenli rootstock’ grafted cucumber is the highest, and the growth of ‘Shengzhen No. 1’ grafted cucumber is relatively the strongest. There was no significant difference in fruit tuber, melon edge, thorn color and pulp crispness between self-rooted seedling (CK) and each rootstock grafting combination. The average yield of ‘Xinli No. 3’ grafted cucumber plot was not significantly different from that of self-rooted seedlings (CK). The length of ‘Shenli rootstock’ and ‘Shengli rootstock’ grafted cucumber was significantly higher than that of self-rooted seedlings (CK), and the length of ‘Shengzhen No. 1’ Grafted Cucumber was significantly higher than that of self-rooted seedlings (CK). The contents of vitamin C and soluble protein of ‘Shengli rootstock’, ‘Shenli rootstock’ and ‘Shengzhen No. 1’ grafted cucumber were significantly higher than those of self-rooted seedlings (CK), and the contents of soluble sugar were lower than those of self-rooted seedlings (CK). Therefore, ‘Shengzhen No. 1’ and ‘Jinchun No. 39’ have strong compatibility with cucumber. As rootstocks, the grafted cucumber plants not only have strong growth potential and high yield, but also significantly increase the content of soluble protein and vitamin C.

The detection of urban expansion through digital processing of satellite images provides valuable information for understanding the dynamics of land use change and its spatial relationship with environmental factors. In order to apply or generate effective land-use planning policies, it is essential to have a historical record of the regional distribution of human settlements, an element that is practically non-existent in our country. For this reason, this text aims to determine the urban growth rate during the period 2000–2014 in the state of Hidalgo, Mexico, and to identify potential expansion zones from Landsat images. Six Landsat scenes were used for the spatial analysis of the state urban coverage and their relationship with the road influence area was evaluated. Two maps were obtained as cartographic products: one of urban coverage distribution and another of the municipalities with the greatest expansion, whose areas are located in the Valle del Mezquital region. However, Mineral de la Reforma, Tetepango, Tizayuca and Pachuca de Soto stand out for their growth rates during the study period: 183.44%, 102%, 94% and 68.5%, respectively. In total, the state urban area in-creased 72.3 km² from 2000 to 2014 with an average growth rate of 1.8% per year. Such growth was associated with the areas of influence of important road infrastructure, such as the Libramiento Arco Norte in Hidalgo. Therefore, the Mezquital Valley and the Mexico Basin are considered as potential regions for urban expansion in the state.

The importance of improving industrial transformation processes for more efficient ones is part of the current challenges. Specifically, the development of more efficient processes in the production of biofuels, where the reaction and separation processes can be intensified, is of great interest to reduce the energy consumption associated with the process. In the case of Biodiesel, the process is defined by a chemical reaction and by the components associated to the process, where the thermochemical study seeks to develop calculations for the subsequent understanding of the reaction and purification process. Thus, the analysis of the mixture of the components using the process simulator Aspen Plus V9^® unravels the thermochemical study. The UNIFAC-DMD thermodynamic method was used to estimate the binary equilibrium parameters of the reagents using the simulator. The analyzed aspects present the behavior of the components in different temperature conditions, the azeotropic behavior and the determined thermochemical conditions.

The conversion of the energy supply to renewable sources (wind, photovoltaics) will increase the volatility in electricity generation in the future. In order to ensure a balanced power balance in the power grid, storage is required - not only for a short time, but also seasonally. The bidirectional coupling of existing energy infrastructure with the power grid can help here by using the electricity in electrolysis systems to produce hydrogen. The hydrogen can be mixed with natural gas in the existing infrastructure (gas storage, pipelines) to a limited extent or converted directly to methane in a gas-catalytic reaction, methanation, with carbon dioxide and/or carbon monoxide. By using the natural gas infrastructure, the electricity grids are relieved and renewable energies can also be stored over long periods of time. Another advantage of this technology, known as “Power-to-Gas”, is that the methane produced in this way represents a sink for CO₂ emissions, as it replaces fossil sources and CO₂ is thus fed into a closed cycle.

Research in the field of Power-to-Gas technology is currently addressing technological advances both in the field of electrolysis and for the subsequent methanation, in particular to reduce investment costs. In the field of methanation, load-flexible processes are to be developed that are adapted to the fluctuating supply of hydrogen. The profitability of the Power-to-Gas process chain can be increased through synergistic integration into existing industrial processes. For example, an integrated smelting works offers a promising infrastructural environment, since, on the one hand, process gases containing carbon are produced in large quantities and, on the other hand, the oxygen as a by-product from the water electrolysis can be used directly. Such concepts suggest an economic application of Power-to-Gas technology in the near future.

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.

This study uses dynamic capability theory and a resource-based view to examine whether intellectual capital (human, relational, and structural capital) mediates entrepreneurial leadership and innovation success. Drawing on data from 422 senior-level employees working in Peruvian I.T. companies, the proposed relationships were analyzed using SmartPLS 4. Entrepreneurial leadership was found to foster employees’ innovative performance through the mediating role of human capital, relational capital, and structural capital. Practically, businesses often rely on innovation for survival and growth, so they should consider entrepreneurial leadership to create intellectual capital (human capital, relational capital and structural capital) for innovation performance. Businesses should provide entrepreneurial training that emphasizes role modeling intellectual capital and encourages employees to recognize and pursue entrepreneurial opportunities. With significantly limited research, the study contributes by investigating the interrelationship of entrepreneurial leadership, intellectual capital, and innovation performance. The study contributes to the Resource Based View and Dynamic Capability Theory by demonstrating how entrepreneurial leadership contributes to innovation performance through human capital, relational capital, and structural capital.