Search

ABSTRACTIn the context of global warming and the increasing water shortage in dry areas, it is necessary to find a sustainable pathway for utilization of land resources (ULR) to solve these problems. For this purpose, using socioeconomic and environmental indicators from 2006 to 2018 and taking the Tarim Basin, China as an example, this study employed an integrated approach composed of the indicator evaluation system (IES) and the System Dynamics (SD) model to evaluate the possibility of sustainable ULR in the basin. During the simulation, three scenarios namely traditional development (TD), economic priority (EP) and harmonious development (HD) were designed, and different thresholds were set for each indicator of potential ULR in each sub-region to predict their future development status. The IES was established to derive the sustainable utilization degree (SUD) of ULR. The results show that the SUD in Tarim in 2030 is likely be 0.60 (TD), 0.62 (EP) and 0.68 (HD), indicating that only in HD scenario is it possible to find pathway to solve water scarcity problem and achieve sustainable ULR. This study provides a supportive idea for decision-making on sustainable ULR in Tarim and also an approach for similar sustainability assessment in other dry areas.

Abstract Background Currently, there are many different findings on the relationship between physical activity and depression, and there may be differences between genders. This study therefore focused on gender differences to understand the relationship between physical activity behaviour and the risk of depression in married individuals. Methods 15607 married people in the China Family Panel Studies 2020 (CFPS 2020) were used to understand the relationship between physical activity and depression risk in different populations, and the chi-square test, Mann-Whitney U-test, and binary logistic regression were used to explore the relationship between physical activity and depression risk in the married population. Results 527 (6.64%) women were at high risk of depression and 365 (4.76%) men were at high risk of depression; physical activity was associated with the risk of depression in the married population, but after incorporating demographic and relevant cognitive variables, physical activity was negatively associated with the risk of depression in women (OR = 0.94, P 0.05). Conclusion Physical activity was directly related to the risk of depression in married women, but not in married men.

Point-of-care testing (POCT) is a contemporary diagnostic approach characterized by its user-friendly nature, cost efficiency, environmental compatibility, and lack of reliance on professional experts. Therefore, it is widely used in clinical diagnosis and other analytical testing fields to meet the demand for rapid and convenient testing. The application of POCT technology not only improves testing efficiency, but also brings convenience and benefits to the healthcare industry. The personal glucose meter (PGM) is a highly successful commercial POCT tool that has been widely used not only for glucose analysis, but also for non-glucose target detection. In this review, the recent advances from 2020 to 2024 in non-glucose target analysis for PGMs as POCT devices are summarized. The signal transduction strategies for non-glucose target analysis based on PGMs, including enzymatic transduction, nanocarrier transduction (enzyme or glucose), and glucose consumption transduction are briefly introduced. Meanwhile, the applications of PGMs in non-glucose target analysis are outlined, encompassing biomedical, environmental, and food analysis, along with other diverse applications. Finally, the prospects of and obstacles to employing PGMs as POCT tools for non-glucose target analysis are discussed.

Internet information technology has brought challenges to the integration of college and university Civics in student education and management work, and at the same time, it also provides an opportunity for the integration of information technology. In this paper, on the basis of two kinds of nodes of basic Petri nets, the library and change, we constructed the workflow of identification Petri nets oriented to the education and management of students in the Civic Government of colleges and universities. The workflow engine is designed as the center of gravity of the reference model, consisting of six basic elements of student management. In the information fusion workflow, a multi-source information fusion method based on CNN and LSTM is proposed to further integrate Civics into student education management. The response time of the student management action flow is shorter than the retrieval time based on the original mechanism, and the average response time is reduced by 57.4 ms when the workflow reaches 5000. The fusion of Civic Politics and education management in the context of three-whole-parenting optimizes the management work method.

Currently, in the production of cigarettes in the blade, charging export moisture control means is relatively single and can not effectively guarantee the excellent quality of cigarette filament. In this paper, first of all, the working principle of the tobacco blade charging machine is introduced, and the moisture of the tobacco leaf for the charging machine is dynamically analyzed, and the influence of the return air temperature control of the charging machine on the export moisture of the blade charging process is explored. Secondly, based on the traditional PID controller, an adaptive fuzzy PID controller is established by combining adaptive fuzzy rules, and then the stacked noise-reducing self-encoder in deep learning is combined with the adaptive fuzzy PID control to design the intelligent control structure of export moisture of leaf charging process. Finally, the effectiveness of export moisture intelligence control, process capability index, and the effect before and after application were analyzed in controlled experiments, respectively. The results show that the difference between the predicted value and the real value of blade export moisture in this paper’s method is only 0.5%, and the process capability index of this paper’s method is improved by 1.48 compared with the PID controller, and it can control the temperature of the return air of the charging machine in the range of 56.86℃~57.21℃. The intelligent control method of export moisture introduced by deep learning can accurately control the export moisture of the leaf dosing process, which effectively ensures the quality of tobacco filament making.

Yak milk is a dietary source of high-quality protein in the plateau region of China but as yet uncharacterized oxidative changes occur during heat treatment. Therefore, oxidation of and proteomic changes to milk proteins from plateau pasture-fed yaks after at different temperatures were investigated. Content of carbonyl groups, surface hydrophobicity increased, and total sulfhydryl, disulfide bond content decreased. Endogenous fluorescence intensity decreased after at increasing temperatures, indicating increased particle size, and absolute values of the zeta potential decreased. Analysis by Fourier transform infrared spectroscopy showed changes of the secondary structure, with relative content of α-helices increasing and then decreasing, β-sheet showed a trend of decreasing and then increasing while the relative content of random curl did not change. The close range of the β-turn gradually decreased, breaking the protein microstructure, and folding stacking occurred. Proteomics analyses showed a temperature dependent effect. Sixty-two proteins were suppressed and 49 elevated with 4 pathways up-regulated and 7 down-regulated at 65 °C. Thirty-one proteins were suppressed and 37 elevated with 5 pathways up-regulated and 4 down-regulated at 90 °C. The most extensive changes were observed at 120 °C, when 327 proteins were suppressed and 308 elevated with 11 pathways up-regulated and 33 down-regulated.

Dairy products are susceptible to modifications in protein oxidation during heat processing, which can lead to changes in protein function, subsequently affecting intestinal health. Despite being a unique nutritional source, yak milk has not been thoroughly examined for the effects of its oxidized proteins on intestinal microbiota and metabolism. Hence, this study employed different heat treatment methods (low-temperature pasteurization, high-temperature pasteurization, and high-temperature sterilization) to induce oxidation in yak milk proteins. The study then assessed the degree of oxidation in these proteins and utilized mice as research subjects. Using metagenomics and metabolomics methods, this study examined the structure of intestinal microbial communities and metabolic products in mice consuming oxidized yak milk. The results showed a decrease in carbonyl and total thiol contents of yak milk proteins after different heat treatments, indicating that heat treatment causes oxidation in yak milk proteins. Metagenomic analysis of mouse intestinal microbiota revealed significant changes in 66 genera. In the high-temperature sterilization group (H), key differential genera included Verrucomicrobiales, Verrucomicrobiae, Akkermansiaceae, and 28 others. The high-temperature pasteurization group (M) mainly consisted of Latilactobacillus, Bacillus, and Romboutsia. The low-temperature pasteurization group (L) primarily comprised of Faecalibacterium, Chaetomium, Paenibacillaceae, Eggerthella, Sordariales, and 33 others. Functionally, compared to the control group (C), the H group upregulated translation and energy metabolism functions, the L group the M group significantly upregulated metabolism of other amino acids, translation, and cell replication and repair functions. Based on metabolomic analysis, differential changes in mouse metabolites could affect multiple metabolic pathways in the body. The most significantly affected metabolic pathways were phenylalanine metabolism, vitamin B6 metabolism, steroid hormone biosynthesis, and pantothenate and CoA biosynthesis. The changes were similar to the functional pathway analysis of mouse metagenomics, affecting amino acid and energy metabolism in mice. In summary, moderate oxidation of yak milk proteins exhibits a positive effect on mouse intestinal microbiota and metabolism. In conclusion, yak milk has a positive effect on mouse intestinal microflora and metabolism, and this study provides a scientific basis for optimizing dairy processing technology and further developing and applying yak milk.

Land use/cover change (LUCC) detection and modeling play an important role in global environmental change research, in particular, policy-making to mitigate climate change, support land spatial planning, and achieve sustainable development. For the time being, a couple of hybrid models, such as cellular automata–Markov (CM), logistic–cellular automata-Markov (LCM), multicriteria evaluation (MCE), and multicriteria evaluation–cellular automata–Markov (MCM), are available. However, their disadvantages lie in either dependence on expert knowledge, ignoring the constraining factors, or without consideration of driving factors. For this purpose, we proposed in this paper a new hybrid model, the logistic–multicriteria evaluation–cellular automata–Markov (LMCM) model, that uses the fully standardized logistic regression coefficients as impact weights of the driving factors to represent their importance on each land use type in order to avoid these defects but is able to better predict the future land use pattern with higher accuracy taking Hefei, China as a study area. Based on field investigation, Landsat images dated 2010, 2015, and 2020, together with digital elevation model (DEM) data, were harnessed for land use/cover (LUC) mapping using a supervised classification approach, which was achieved with high overall accuracy (AC) and reliability (AC > 95%). LUC changes in the periods 2010–2015 and 2015–2020 were hence detected using a post-classification differencing approach. Based on the LUC patterns of the study area in 2010 and 2015, the one of 2020 was simulated by the LMCM, CM, LCM, and MCM models under the same conditions and then compared with the classified LUC map of 2020. The results show that the LMCM model performs better than the other three models with a higher simulation accuracy, i.e., 1.72–5.4%, 2.14–6.63%, and 2.78–9.33% higher than the CM, LCM, and MCM models, respectively. For this reason, we used the LMCM model to simulate and predict the LUC pattern of the study area in 2025. It is expected that the results of the simulation may provide scientific support for spatial planning of territory in Hefei, and the LMCM model can be applied to other areas in China and the world for similar purposes.

Background/Aims: Acinetobacter baumannii is an aerobic and Gram-negative bacterial pathogen with high morbidity and mortality. It remains a serious public health problem arising from its multidrug-resistant and extensive antibiotic resistance spectrum. Methods: In the present study, iTRAQ coupled with 2D LC-MS/MS was used to evaluate the proteome in standard Acinetobacter baumannii standard strains and tigecycline-resistant strains. Results: A total of 3639 proteins were identified and 961 proteins were identified to be differentially expressed in tigecycline-resistant Acinetobacter baumannii strains compared to the standard strains. 506 (52.6%) proteins were up-regulated and 455 (47.4%) proteins were down-regulated. Based on the GO enrichment analysis and KEGG pathway analysis, we concluded that most differentially expressed proteins were associated with stress responses, cellular component organization, proteins synthesis, degradation and function. Moreover, β-lactam resistance, the longevity regulating pathway and other related pathways were also involved in the regulation of tigecycline-resistant Acinetobacter baumannii. The differential expression of key proteins were evaluated by transcript analysis using quantitative RT-PCR. Conclusion: These results may provide new insights into the mechanisms of drug resistance in Acinetobacter baumannii.

Up to date, model and parameter uncertainties are generally overlooked by majority of researchers in the field of battery diagnostics and prognostics. As a consequence, accuracy of the battery performance estimation is dominated by the model fidelity and may vary from cell-to-cell. This paper proposes a systematic framework to quantify battery model and parameter uncertainties for more effective battery performance estimation. Such a framework is generally applicable for estimating various battery performances of interest (e.g. state of charge (SOC), capacity, and power capability). Case studies for battery SOC estimation are conducted to demonstrate the effectiveness of the proposed framework.

This study investigates the impacts of industrial intelligence on the total factor energy productivity (TFEP) using extended STIRPAT and spatial moderation models for China's industrial sector. The results show that TFEP and industrial intelligence are both increasing, and industrial intelligence positively affects TFEP, for every 1% increase in industrial intelligence will lead to TFEP growth by 0.121% in the study area and 0.031% in surrounding areas. Environmental regulation, industrial upgrading, and advanced human capital all function as helpful moderators between industrial intelligence and TFEP, that is, for every 1% increase in environmental regulation, industrial upgrading, and advanced human capital, the growth of TFEP caused by industrial intelligence enhanced by 0.003%, 0.009%, and 0.022% in study area and 0.005%, 0.042%, and 0.054% in surrounding areas. [ABSTRACT FROM AUTHOR]

Introduction: As a means of environmental regulation, the low-carbon city pilot policy aims to address climate change and alleviate environmental resource pressures in economic development. The development of low-carbon cities often requires changes to the existing industrial and energy structures, which will have a significant impact on the regional economy. Methods: The study is based on panel data from 273 prefecture level cities in China from 2012 to 2022, and uses the Analytic Hierarchy Process and Entropy Comprehensive Evaluation Method to construct an evaluation index system for urban circular benefits. Finally, the multiple time point differences model and mediation effect model were used to evaluate the impact and influencing factors of policies on urban economy. Results: The results indicate that at the 1% level, the explanatory variable coefficient significantly improves the level of urban circular economy development after adding control variables. The construction of low-carbon pilot cities has improved the performance of circular economy development by about 6.42%. The mediating effect of industrial structure rationalization is significantly positive at the 1% significance level, indicating that the construction of low-carbon pilot cities has greatly promoted the coordinated development of industrial relations within China's low-carbon development regions. Discussion: It can be seen that the low-carbon city pilot policy has a significant promoting effect on China's economic development and the development of urban circular economy. Therefore, it is recommended to further expand the pilot scope of low-carbon cities and fully leverage their promoting role. This article is based on panel data from 273 prefecture level cities from 2012 to 2012, and uses a multi time difference model to analyze the impact of low-carbon city pilot policies on the development of urban circular economy. The research results indicate that the construction of low-carbon pilot cities has significantly promoted the coordinated development of intra regional industrial relationships. [ABSTRACT FROM AUTHOR]