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BackgroundType 2 diabetes mellitus (T2DM) is a commonly observed metabolic anomaly globally, and as of the present time, there's no recognized solution. There is an increasing body of evidence from numerous observational studies indicating a significant correlation between gut flora and metabolic disease progression, particularly in relation to T2DM. Despite this, the direct impact of gut microbiota on T2DM isn't fully understood yet.MethodsThe summary statistical figures for intestinal microbiota were sourced from the MiBioGen consortium, while the summary statistical data for T2DM were gathered from the Genome-Wide Association Studies (GWAS) database. These datasets were used to execute a two-sample Mendelian randomization (MR) investigation. The Inverse Variance Weighted (IVW), Maximum Likelihood, MR-Egger, Weighted Median, and Weighted Models strategies were employed to assess the impact of gut microbiota on T2DM. Findings were primarily obtained using the IVW technique. Techniques like MR-Egger were employed to identify the occurrence of horizontal pleiotropy among instrumental variables. Meanwhile, Cochran's Q statistical measures were utilized to assess the variability or heterogeneity within these instrumental variables.ResultsThe outcomes from the IVW analysis demonstrated that the genus Alistipes (OR = 0.998, 95% confidence interval: 0.996–1.000, and P = 0.038), genus Allisonella (OR = 0.998, 95% confidence interval: 0.997-0.999, P = 0.033), genus Flavonifractor (OR = 0.995, 95% confidence interval: 0.993–0.998, P = 3.78 × 10−3), and genus Haemophilus (OR = 0.995, 95% confidence interval: 0.993–0.998, P = 8.08 × 10−3) all acted as defense elements against type 2 diabetes. Family Clostridiaceae1 (OR = 1.003, 95% confidence interval: 1.001–1.005, P = 0.012), family Coriobacteriaceae (OR = 1.0025, 95% confidence interval: 1.000–1.005, P = 0.043), genus Actinomyces (OR = 1.003,95% confidence interval: 1.001–1.005, P = 4.38 × 10−3), genus Candidatus Soleaferrea (OR = 1.001,95% confidence interval: 1.000–1.002 P = 0.012) were risk factors for type 2 diabetes. False Discovery Rate correction was performed with finding that genus.Allisonella, genus.Alistipes, family Coriobacteriaceaeand T2DM no longer displayed a significant causal association. In addition, no significant heterogeneity or horizontal pleiotropy was found for instrumental variable.ConclusionThis MR study relies on genetic variation tools to confirm the causal effect of genus Flavonifractor, genus Haemophilus, family Clostridiaceae1, genus Actinomyces and genus Candidatus Soleaferrea on T2DM in the gut microbiome, providing new directions and strategies for the treatment and early screening of T2DM, which carries significant clinical relevance. To develop new biomarkers and better understand targeted prevention strategies for T2DM, further comprehensive investigations are required into the protective and detrimental mechanisms exerted by these five genera against T2DM.

Heterogeneous cellular networks (HCNs) are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity. However, the densified multi-tier network architecture introduces excessive intra- and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks. In this article, a dynamic spectrum control (DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity. Specifically, the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families, which represent the transmission decisions, by performing iterative and orthogonal sequence transformations. Based on the sequence families, multiple users can dynamically occupy different frequency slots for data transmission simultaneously. In addition, the collision probability of the data transmission is analyzed, which results in closed-form expressions of the reliable transmission probability and the secrecy probability. Then, the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities. Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance. Finally, the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.

Figuring out household water demand response is of importance to sustainable water pricing policy making and optimalization. The paper estimates price and income elasticities of residential water demand in China by using the unique dataset from Chinese Household Water Use Behavior Survey 2019 in 50 cities. Two instrumental variables of marginal water price and average water price are used to address the endogeneity in the context of increasing-block water pricing policy. Results show that price elasticity ranges from −0.170 to −0.543, meaning that the demand for water is inelastic. Income elasticity ranges from 0.062 to 0.133, indicating that water is a necessary commodity. It unveils that water scarcity cities have more sensitive price response. It verifies the effectiveness of the differential increasing-block water pricing schemes tailor-made to local water resources endowments. Besides, it shows that high water-consuming households have more sensitive price response. It suggests that implementing more stringent IBWP scheme for those households constitutes a promising policy improvement option in the future.

With the advance of the information technologies,the scale of the information services gradually expands,from ground services,to aerial,maritime,and spatial services,with the soaring requirements on multi-dimensional comprehensive information resources.The space-air-ground integrated networks (SAGINs) are envisioned to provide seamless network services to spatial,aerial,maritime,and ground users,satisfying the future network requirements on all-time,all-domain,and all-space communications and interconnected networking.Firstly,we reviewed the current research development of SAGINs,discussing the research trends on the low-earth orbiting (LEO) satellite constellation and space-ground network integration.Then,the reinforcement learning (RL) framework was proposed in SAGINs to address the problems of complex architecture,high dynamics,and resource constraints in SAGINs,which facilitated efficient and fast network design,analysis,optimization,and management.As a case study,the method of applying deep RL (DRL) was showed for the intelligent access network selection in SAGINs.To improve the RL training efficiency,a comprehensive SAGINs simulation platform was established,through which the agent-environments interaction was accelerated and training samples could be obtained more cost-effectively.Finally,some open research directions were presented.

Detecting crop calendar changes is critically important for crop monitoring and management, but the lack of annual, Asia-wide, and long-term rice calendar datasets limits our understanding of rice phenological changes and their climate drivers. In this study, we retrieved key rice phenological dates from the GLASS AVHRR LAI through combining threshold-based and inflection-based detection methods, analyzed the changes during the period 1995–2015, and identified the key climate drivers of the main rice seasons in Asia. The retrieved phenological dates had a high level of agreement with the referenced observations. All R2 were greater than 0.80. The length of the vegetation growing period (VGP) was mostly shortened (by an average of −4 days per decade), while the length of the reproductive growing period was mostly prolonged (by an average of 2 days per decade). Moreover, solar radiation had the most significant impact on the rice calendar changes, followed by the maximum and minimum temperatures. The VGP in tropical areas is the most sensitive to climate change. Our study extends the annual rice phenology dynamics to a higher spatial–temporal resolution and provides new insights into rice calendar changes and their climate drivers, which will assist governments and researchers regarding food security and agricultural sustainability.

Urbanization and economic development pose a challenge to the water ecological environment of cities. “Ecological Civilization” is a term that demonstrates the strategy to achieve the win-win goal of economic development and eco-environment protection. “Water Ecological Civilization” is a vital part of “Ecological Civilization”. This paper introduced a composite index to characterize the Urban Water Ecological Civilization (UWEC) and established an evaluation index system for UWEC based on a multicriteria analytical framework. The evaluation system contains 20 indicators selected from six criterion layers: water resources utilization (A, evaluating the efficiency of industrial, agricultural, domestic and public water use), water security assurance (B, evaluating the flood control, drainage and drinking water safety), water environmental protection (C, evaluating the water environment quality and water pollution prevention), water ecological restoration (D, evaluating the health of regional water ecosystem), water culture system (E, evaluating the inheritance of water culture and the popularization of UWEC awareness) and water management institution (F, evaluating the implementation of management systems). In our research, three major urban agglomerations (UAs) in Yangtze River Economic Belt (YREB) were chosen to be the study area. The results presented that the UWEC level of UAs gradually increased along the Yangtze River from west to east, showing obvious spatial differences. The main criteria restricting the UWEC level of UAs in the Yangtze River Delta were D and E, while E and F were the main restricting criteria for the UWEC level of UAs in the Middle Reaches of the Yangtze River and Cheng-Yu District. The indicator of “drainage compliance rate” got the lowest score among all indicators for three UAs. In addition, targeted measures for improving the UWEC level of UAs in YREB were proposed. Our study is supposed to provide a scientific reference to the improvement of UWEC level for UAs in YREB and trigger further research in the field of water ecological civilization.

Wireless distributed storage systems can potentially relieve the centralized traffic burden of base stations (BSs), and further improve system reliability for content sharing in device-to-device (D2D) communications. Mobile devices [i.e., content requesters (CRs)] can not only download their desired contents from serving BSs, but can also get them from neighboring devices [i.e., content helpers (CHs)] with possession of the contents. However, D2D links between CRs and CHs are not necessarily stable, due to user mobility and the time-varying property of wireless links. This paper focuses on the utilization of socially enabled D2D links to deliver the desired contents based on distributed storage. We evaluate the success rate for downloading and repairing in D2D-assisted networks accordingly, by analyzing statistic social interaction information for potential D2D links. Thus, it is necessary to maintain or assign enough qualified D2D links to afford content downloading and repairing from neighboring devices. To reduce the overall system transmission cost, this paper further proposes a hierarchical bi-partite method to guarantee at least k admissible D2D links according to their statistical channel state information, by considering one type of erasure correcting codes, the maximum distance separable code. Simulation results demonstrate the performance and advantage of our proposed scheme.