Enclosure Rather Than Topography Enhances the Soil Ecological Stoichiometry in Typical Steppe on the Loess Plateau, China

Grassland is one of the largest terrestrial ecosystems in the world, a large part of which is distributed in varied topography. And grazing and enclosure are the main ways to use this part. Grazing changes the soil structure through feeding, trampling and excreta return, thus affects the soil nutrients. The aspect mainly affects soil temperature and moisture by affecting solar radiation. The slope affects soil nutrients by affecting surface runoff. Water and temperature are the main factors affecting soil nutrients. We carried out to explore the effect of enclosure years and topography on soil ecological stoichiometry. The results showed that: soil organic carbon density, soil nitrogen density and soil phosphorus density increased with the increasing enclosure years and decreased with the increasing slope. Soil N/P (ratio between soil nitrogen density and soil phosphorus density) increased with increasing the enclosure years and the slope while soil C/N (ratio between soil organic carbon density and soil nitrogen density) decreased. Soil C/P (ratio between soil organic carbon density and soil phosphorus density) increased with the increasing enclosure years, however the trend with slope change was not obvious. The enclosure of sunny slope is more beneficial to soil nutrient accumulation

Evaluating the Determinants of Young Runners' Continuance Intentions toward Wearable Devices

Running has gained popularity as a fitness activity in China, with a growing number of young runners utilizing wearable devices to monitor their running routines and engage in quantified self-practices. The continuous evolution of wearable devices in terms of products and services has expanded the choices available to young runners. Therefore, there is a need to analyze the factors influencing the continuance intention of young runners, providing insights into how to promote the sustained growth of these products or services in the market. This study is grounded in the Technology Acceptance Model and the Theory of Planned Behavior, with an extension incorporating the quantified self to explore the impact of users' continuance intentions to use wearable devices. A survey was conducted among 468 young runners who already used wearable devices, and the data collected were analyzed using PLS-SEM. The results indicate that perceived usefulness and attitudes from the Technology Acceptance Model positively influence intentions for continued use. Additionally, subjective norms according to the Theory of Planned Behavior positively influence continuance use intentions. However, perceived behavioral control does not have a significant effect on continuance use intentions. Conversely, the Quantified-Self positively influences continuance use intentions and partially mediates the relationship between perceived usefulness and continuance use intentions. This research has several theoretical implications for the Theory of Planned Behavior, the Technology Acceptance Model, and the Quantified-Self research construct. Moreover, this study has practical implications for practitioners concerning the adoption and acceptance of wearable devices by young people. This approach enables practitioners to target and implement precise strategies to meet the current demands of the young runner market. Doi: 10.28991/HIJ-2023-04-04-02 Full Text: PD

An artificial bee colony-based hybrid approach for waste collection problem with midway disposal pattern

This paper investigates a waste collection problem with the consideration of midway disposal pattern. An artificial bee colony (ABC)-based hybrid approach is developed to handle this problem, in which the hybrid ABC algorithm is proposed to generate the better optimum-seeking performance while a heuristic procedure is proposed to select the disposal trip dynamically and calculate the carbon emissions in waste collection process. The effectiveness of the proposed approach is validated by numerical experiments. Experimental results show that the proposed hybrid approach can solve the investigated problem effectively. The proposed hybrid ABC algorithm exhibits a better optimum-seeking performance than four popular metaheuristics, namely a genetic algorithm, a particle swarm optimization algorithm, an enhanced ABC algorithm and a hybrid particle swarm optimization algorithm. It is also found that the midway disposal pattern should be used in practice because it reduces the carbon emission at most 7.16% for the investigated instances

Study on Thermal Conductivity Methane Sensor Constant Temperature Detection Method

The thermal conductivity methane sensor can detect methane concentration that measures the thermal conductivity coefficient of the measured methane different from the background gas. This sensor has advantages of detection of a variety of gases, large measuring range, stability, long working life, but also has defects, such as poor detection accuracy, sensitivity affected by ambient temperature and sensor temperature, the defect limits a wide applications of the sensor. This paper analyzes the theory of thermal conductivity methane sensor and method of measurement, proposes thermal conductivity methane sensor constant temperature detection method, and experimentally validates the feasibility of ambient temperature compensation. Experimental results show that the method effectively reduces the effect of ambient temperature on measuring accuracy

On scenario construction for stochastic shortest path problems in real road networks

Stochastic shortest path computations are often performed under very strict time constraints, so computational efficiency is critical. A major determinant for the CPU time is the number of scenarios used. We demonstrate that by carefully picking the right scenario generation method for finding scenarios, the quality of the computations can be improved substantially over random sampling for a given number of scenarios. We study a real case from a California freeway network with 438 road links and 24 5-minute time periods, implying 10,512 random speed variables, correlated in time and space, leading to a total of 55,245,816 distinct correlations. We find that (1) the scenario generation method generates unbiased scenarios and strongly outperforms random sampling in terms of stability (i.e., relative difference and variance) whichever origin-destination pair and objective function is used; (2) to achieve a certain accuracy, the number of scenarios required for scenario generation is much lower than that for random sampling, typically about 6-10 times lower for a stability level of 1\%; and (3) different origin-destination pairs and different objective functions could require different numbers of scenarios to achieve a specified stability.Comment: 34 pages, 8 figure

CDCA2 Inhibits Apoptosis and Promotes Cell Proliferation in Prostate Cancer and Is Directly Regulated by HIF-1α Pathway.

Prostate cancer (PCa) is a major serious malignant tumor and is commonly diagnosed in older men. Identification of novel cancer-related genes in PCa is important for understanding its tumorigenesis mechanism and developing new therapies against PCa. Here, we used RNA sequencing to identify the specific genes, which are upregulated in PCa cell lines and tissues. The cell division cycle associated protein (CDCA) family, which plays a critical role in cell division and proliferation, is upregulated in the PCa cell lines of our RNA-Sequencing data. Moreover, we found that CDCA2 is overexpressed, and its protein level positively correlates with its histological grade, clinical stage, and Gleason Score. CDCA2 was further found to be upregulated and correlated with poor prognosis and patient survival in multiple cancer types in The Cancer Genome Atlas (TCGA) dataset. The functional study suggests that inhibition of CDCA2 will lead to apoptosis and lower proliferation in vitro. Silencing of CDCA2 also repressed tumor growth in vivo. Loss of CDCA2 affects several oncogenic pathways, including MAPK signaling. In addition, we further demonstrated that CDCA2 was induced in hypoxia and directly regulated by the HIF-1α/Smad3 complex. Thus, our data indicate that CDCA2 could act as an oncogene and is regulated by hypoxia and the HIF-1αpathway. CDCA2 may be a useful prognostic biomarker and potential therapeutic target for PCa

Safeguarding China’s long-term sustainability against systemic disruptors

China’s long-term sustainability faces socioeconomic and environmental uncertainties. We identify five key systemic risk drivers, called disruptors, which could push China into a polycrisis: pandemic disease, ageing and shrinking population, deglobalization, climate change, and biodiversity loss. Using an integrated simulation model, we quantify the effects of these disruptors on the country’s long-term sustainability framed by 17 Sustainable Development Goals (SDGs). Here we show that ageing and shrinking population, and climate change would be the two most influential disruptors on China’s long-term sustainability. The compound effects of all disruptors could result in up to 2.1 and 7.0 points decline in the China’s SDG score by 2030 and 2050, compared to the baseline with no disruptors and no additional sustainability policies. However, an integrated policy portfolio involving investment in education, healthcare, energy transition, water-use efficiency, ecological conservation and restoration could promote resilience against the compound effects and significantly improve China’s long-term sustainability

Plant beta-turnover rather than nestedness shapes overall taxonomic and phylogenetic beta-diversity triggered by favorable spatial–environmental conditions in large-scale Chinese grasslands

IntroductionAlthough it is widely acknowledged that biodiversity maintains plant community assembly processes, exploring the patterns and drivers of beta-diversity (β-diversity; species variation among local plant communities) has received much less attention compared to alpha-diversity (α-diversity; species variation within a local plant community). Here, we aim to examine the patterns and spatial–environmental drivers of taxonomic and phylogenetic β-diversity, and their components such as species turnover and nestedness, in large-scale Leymus chinensis grassland communities.MethodsWe collected plant community data from 166 sites across widely distributed L. chinensis communities in northern China, and then calculated the taxonomic and phylogenetic β-diversity indices (overall, turnover and nestedness) using a pairwise dissimilarity approach. To assess the effects and to explain the variation in the patterns of β-diversity, we collected data on geospatial, climate and soil conditions. We applied descriptive statistics, Mental correlations, and multiple linear regression models to assess the patterns and spatial–environmental drivers of β-diversity.ResultsThe β-turnover, as compared to β-nestedness, exhibited a predominant influence, constituting 92.6% of the taxonomic β-diversity and 80.4% of the phylogenetic β-diversity. Most of the spatial–environmental variables were significantly positively correlated with the overall taxonomic and phylogenetic β-diversity and β-turnover, but not with β-nestedness. Climatic factors such as MAP and MAT were the strongest predictors of both taxonomic and phylogenetic β-diversity and β-turnover. The variance partitioning analysis showed that the combined effects of spatial and environmental factors accounted for 19% and 16% of the variation in the taxonomic and phylogenetic β-diversity (overall), 17% and 12% of the variation in the β-turnover, and 7% and 1% of the variation in the β-nestedness, respectively, which were higher than independent effects of either spatial or environmental factors.DiscussionAt larger spatial scales, the turnover component of β-diversity may be associated with the species complementarity effect, but dominant or functionally important species can vary among communities due to the species selection effect. By incorporating β-diversity into grassland management strategies, we can enhance the provision of vital ecosystem services that bolster human welfare, serving as a resilient barrier against the adverse effects of climate change at regional and global scales