Spatial Pattern of Underground Space Development in Major Cities in China: Evaluation and Analysis

Underground space development has gradually become an organic part of China’s urban development and construction. Comprehensively developing underground space scientifically and rationally to give full play to its comprehensive benefits is the main problem faced by China’s underground space development at this stage. This research starts with the measurement of the level of urban underground space (UUS) development. This paper constructs a UUS development level measurement indicator system, which is composed of Construction of UUS (D1), urban economic development indicators (D2), and urban population development indicators (D3), which has 12 secondary indicators, and then we use entropy-TOPSIS method to quantitatively evaluate the development level of underground public space in 39 prefecture-level cities and above in my country and analyze its spatial differentiation. The results show that the urban agglomeration has the characteristics of “high-high” cluster distribution with the development level of underground space. However, the overall level of underground space development in China’s major cities is not high and there are apparent differences in the level of UUS development. In terms of spatial distribution, the sustainable development level of cities in the eastern coastal regions of China is relatively high, with towns in the central and northeastern areas ranking second and western towns and northeastern cities ranking the lowest. At the same time, we found that there is a mismatch between the underground space development index and the economic population development index in the evaluation index. Finally, some suggestions are put forward to realize the balanced development of UUS development in our country.

Identification of Policies Based on Assessment-Optimization Model to Confront Vulnerable Resources System with Large Population Scale in a Big City

The conflict between excessive population development and vulnerable resource (including water, food, and energy resources) capacity influenced by multiple uncertainties can increase the difficulty of decision making in a big city with large population scale. In this study, an adaptive population and water–food–energy (WFE) management framework (APRF) incorporating vulnerability assessment, uncertainty analysis, and systemic optimization methods is developed for optimizing the relationship between population development and WFE management (P-WFE) under combined policies. In the APRF, the vulnerability of WFE was calculated by an entropy-based driver–pressure–state–response (E-DPSR) model to reflect the exposure, sensitivity, and adaptability caused by population growth, economic development, and resource governance. Meanwhile, a scenario-based dynamic fuzzy model with Hurwicz criterion (SDFH) is proposed for not only optimizing the relationship of P-WFE with uncertain information expressed as possibility and probability distributions, but also reflecting the risk preference of policymakers with an elected manner. The developed APRF is applied to a real case study of Beijing city, which has characteristics of a large population scale and resource deficit. The results of WFE shortages and population adjustments were obtained to identify an optimized P-WEF plan under various policies, to support the adjustment of the current policy in Beijing city. Meanwhile, the results associated with resource vulnerability and benefit analysis were analyzed for improving the robustness of policy generation.

VISOKO OBRAZOVANjE I PODSTICAJI POPULACIONOM RAZVOJU REPUBLIKE SRBIJE

This paper discusses the current situation in the service sector in the field of higher education in the context of encouraging population development in Serbia. Depopulation is an endemic problem of Serbian society. It is necessary to start looking for an adequate answer to the question of how to encourage population policy in Serbia as soon as possible. In that sense, it is necessary to subject to critical analysis the current Strategy for Encouraging Birth in Serbia, and particularly its part that is dedicated to population education. In addition, it is necessary to consider potential future measures in the field of education, which would be aimed not only at encouraging reproductive behavior, but also towards a more complete and better understanding of population problems and issues.

BIOPESTICIDE TEST FOR MEALYBUGS IN GREENHOUSE PLANTS OF TROPICAL AND SUBTROPICAL CLIMATE IN THE CONDITIONS OF THE NUR-SULTAN GREENHOUSE COMPLEX

The article considers the results of a biopesticide test for a pest of plants in the greenhouse of the Botanical Park of Nur-Sultan. The article aims to determine the effectiveness of protective measures for the conservation of collectible plants in the greenhouse of the Botanical Garden of Nur-Sultan. In order to fulfill this task, the object of the study was the main pest of the Nur-Sultan greenhouse, the mealybug and the dynamics of its population development. The study revealed the annual and seasonal dynamics of the number of mealybugs and traced the sequence of alternation of ornamental plants with phytophages throughout the year. To assess the pest's resistance to biological control, two biopesticides were taken. These are: "Bona Forte Spray" on a natural pyrethrin basis and " Phytoverm " on the basis of aversectin - C. In accordance with the research results, conclusions were drawn

Population Fluctuation of Disonycha teapensis Blake (Coleoptera: Chrysomelidae) in Crotalaria longirostrata Hook. & Arn. (Fabales: Fabaceae) in Huimanguillo, Tabasco, Mexico

Objective: To establish the population fluctuation of Disonycha teapensis adults and larvae and to determine its relationship with the amount of damaged foliage, temperature, and precipitation. Methodology: The study was carried out in a n=48 Crotalaria longirostrata plant crop. The following data was recorded every week: number of adults and larvae, damaged leaflets percentage, plant phenology, temperature, and precipitation. Based on these data, monthly averages were calculated, and correlation analysis were performed between the population fluctuation of D. teapensis and the fluctuation of the damaged foliage percentage, temperature, and precipitation. Results: All the phenological stages of C. longirostrata were affected by the pest, which showed a constant population growth. The population fluctuation resembled the fluctuation of the damaged foliage percentage, with a significant positive correlation between both variables. Regarding temperature and precipitation, the correlation was negative but not significant; therefore, the relationship between population fluctuation and these climatic factors is not clear. Study Limitations: It was not possible to conduct the study for a full year. Conclusions: The population development of D. teapensis depends on the increase in the amount of foliage of its host plant. This insect attacks plants in all their phenological stages and the amount of damaged foliage is considerable.

Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease

Medicines and agricultural biocides are often discovered using large phenotypic screens across hundreds of compounds, where visible effects of whole organisms are compared to gauge efficacy and possible modes of action. However, such analysis is often limited to human-defined and static features. Here, we introduce a novel framework that can characterize shape changes (morphodynamics) for cell-drug interactions directly from images, and use it to interpret perturbed development of Phakopsora pachyrhizi, the Asian soybean rust crop pathogen. We describe population development over a 2D space of shapes (morphospace) using two models with condition-dependent parameters: a top-down Fokker-Planck model of diffusive development over Waddington-type landscapes, and a bottom-up model of tip growth. We discover a variety of landscapes, describing phenotype transitions during growth, and identify possible perturbations in the tip growth machinery that cause this variation. This demonstrates a widely-applicable integration of unsupervised learning and biophysical modeling.