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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.

Soybean, an essential food crop, has witnessed a steady rise in demand in recent years. There is a lack of high-resolution annual maps depicting soybean planting areas in China, despite China being the world’s largest consumer and fourth largest producer of soybeans. To address this gap, we developed a novel method called phenological- and pixel-based soybean area mapping (PPS) based on Sentinel-2 remote sensing images from the Google Earth Engine (GEE) platform. We utilized various auxiliary data (e.g., cropland layer, detailed phenology observations) to select the distinct features that differentiate soybeans most effectively from other crops across various regions. These features were then input for an unsupervised classifier (K-means), and the most likely type was determined by a post-classification method based on dynamic time warping (DTW). For the first time, we generated a dataset of soybean planting areas across China, with a high spatial resolution of 10 meters, spanning from 2017 to 2021 (ChinaSoyArea10m). The R² values between the mapping results and the census data at both county- and prefecture-level were consistently around 0.85 in 2017–2020. Moreover, the overall accuracy of mapping results at the field level in 2017, 2018, and 2019 were 77 %, 84 % and 88 %, respectively. Compared with the existing 10-m crop-type maps in Northeast China (Cropland Data Layer, CDL) based on field samples and supervised classification methods, the mapping accuracy is significantly improved by 31 % (R² increases from 0.53 to 0.84) according to their consistency with census data, particularly at the county level. ChinaSoyArea10m is spatially consistent well with the two existing datasets (CDL and GLAD maize-soybean map). ChinaSoyArea10m provides important information for sustainable soybean production and management, as well as agricultural system modeling and optimization. ChinaSoyArea10m can be downloaded from an open-data repository (DOI: https://zenodo.org/doi/10.5281/zenodo.10071426, Mei et al., 2023). [ABSTRACT FROM AUTHOR]

Rice is the most important staple food in Asia. However, high-spatiotemporal-resolution rice yield datasets are very limited over a large region. The lack of such products hugely hinders the studies on accurately assessing the impacts of climate change and simulating agricultural production. Based on dynamic rice maps in Asia, we incorporated four predictor categories into three machine learning (ML) models to generate a high-spatial-resolution (4km) rice yield dataset (AsiaRiceYield4km) 30 for main rice seasons from 1995 to 2015. Four predictor categories considered the most comprehensive rice growing conditions and the optimal ML model was determined for each rice season based on an inverse proportional weight method. The results showed that AsiaRiceYield4km has a good accuracy for seasonal rice yield prediction (single rice: R2 = 0.88, RMSE = 920 kg/ha, double rice: R2 = 0.91, RMSE = 554 kg/ha, and triple rice: R2 = 0.93, RMSE = 588 kg/ha). Compared with Spatial Production Allocation 35 Model (SPAM), R2 of grided rice yields was improved by 0.20 and RMSE was reduced by 618 kg/ha on average for single rice. Particularly, constant environmental conditions including longitude, latitude, elevation, and soil properties contributed the most (-45%) to rice yield prediction. As for different growing periods of rice, we found that the predictors in reproductive period had more impacts on rice yield prediction than those of the vegetative period and the whole growing period. AsiaRiceYield4km is 40 a novel high-spatial-resolution gridded rice yield dataset that can fill the unavailability of seasonal yield products across major rice production areas and promote more relevant studies on agricultural sustainability in the world. AsiaRiceYield4km can be downloaded from an open-data repository [ABSTRACT FROM AUTHOR]

This article reviews studies and the status of clinical research from the past five years. The conclusion is that acupuncture can affect both physiological symptoms and disease pathologies, and that different acupuncture manipulations have different effects on the normal state and pathological condition of the patient. [ABSTRACT FROM AUTHOR]

This paper aims at checking the effectiveness of environmental policy pushed by the Central Government at provincial level since China's entry into the World Trade Organization (WTO). For this purpose, the industrial system of each province is divided into industrial production sub-system and pollution treatment sub-system, and a novel slack-based measure data envelopment analysis (SBM-DEA) model with non-cooperative game is proposed to evaluate the environment efficiency of both industrial production sub-system and pollutant treatment sub-system. The results show that the proposed model can describe the environmental efficiency more precisely than the traditional DEA models. During 2003-2012, the efficiencies of industrial production sub-system and pollution treatment sub-system at the provincial level are both relatively low. Specifically, the efficiency of industrial production is not only lower than pollution treatment efficiency, but is falling generally, especially in the Eastern area. However, in the Central and Western area, the efficiency of industrial production remains relatively stable, and pollution treatment efficiency is rising steadily. The technology gap between the Central/Western area and the Eastern area is narrowing, particularly concerning pollution treatment technology. We thus conclude that though the Central Government's environmental policies fail to solve the inner contradiction between economic and environmental systems, and they indirectly contribute to the expansion of pollutant treatment technology among the Eastern, Central, and Western areas, which is conducive to the coordinated development among different areas. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications has attracted substantial research attention recently owing to its simplicity and its potential to improve spectrum and energy efficiency within the existing cellular infrastructure. This work presents a low complexity method for matching D2D links with cellular user equipments (CUEs) to form partners for spectrum sharing. The overall objective is to maximize well defined performance metrics of all D2D links and CUEs after successful pairing under power and QoS constraints. We begin by identifying a set of D2D link candidates for each CUE uplink for a requisite SINR level to reduce the number of potential pairing searches. More importantly, we present a simple pairing algorithm to reduce the computational cost well below the well known Hungarian (Kuhn-Munkres) algorithm used in the literature for the pairing problem. Our new algorithm exhibits low complexity and is effective in improving the sum rate of all spectrum sharing CUEs and D2D links with modest performance loss. [ABSTRACT FROM PUBLISHER]

As a typical environment-economy linking system, recycling and its efficiency measurement with a triple-bottom-line (TBL) thinking, increasingly play an important role in the development of real economies and environmental protection. Since the classic black-box-based data envelopment analysis DEA model may over-estimate the operation performance of a decision making unit (DMU), this paper describes a novel network based on DEA model to narrow the gap between the DEA theory and practical needs on decision making. The proposed DEA model firstly accesses the overall efficiency of recycling systems and then divides it into efficiencies of two sub-systems. Finally, a case from Chinese provincial economy is applied to verify the novel model and the related results with comparing them with those of traditional black box DEA model so as to indicate a more accurate efficiency measurement with the new DEA model. [ABSTRACT FROM AUTHOR]

Data envelopment analysis (DEA) assumes that the data set is precise when performing efficiency evaluation of peer decision making units (DMUs). The current paper proposes a multiple linear regression analysis (MLRA) approach to estimate missing values if some of the entries in the data set are missing. Its algorithm to derive the estimations is also proposed. In order to verify the credibility of the proposed approach, an example of 30 US commercial banks is applied to case analysis. Using the proposed algorithm, the efficiencies of all DMUs are obtained. A Friedman test and a Kendall's Tau rank correlation analysis statistically examine the results. Moreover, the efficiency interval and efficiency distribution for a DMU are obtained considering random errors of the estimations. After that, an example of public secondary schools serves to illustrate the applications in the end. [ABSTRACT FROM AUTHOR]

Notch signaling controls diverse eukaryotic differentiation processes in multiple cell types, thus demanding versatile tools with which Notch triggers downstream events. Ubiquitin-medicated proteolysis has previously been shown to be one such tool with which Notch regulates the turnover of the basic helix-loop-helix transcription factor, E47. Here, we show that Notch signaling also accelerated the degradation of Tal1/SCL (T cell acute leukemia 1/stem cell leukemia) protein, a basic helix-loop-helix protein involved in the development of hematopoietic, vascular, and neuronal tissues. Notch-induced Tal1/SCL degradation was mediated by ubiquitination and proteasomes. The sequence responsible for Tall degradation was localized to a region in the C terminus of Tal1, which is evolutionarily conserved, thus suggesting a functional significance. Analogous to the situation for E47, Notch-induced Tall/SCL degradation not only required Skp2, a substrate-binding subunit of SCF ubiquitin ligase complexes, but also relied on CHIP, a chaperone-binding protein with a ubiquitin ligase activity. In contrast to the fact that the N-terminal tetratricopeptide region (TPR) domain of CHIP is necessary and sufficient for E47 ubiquitination and degradation, CHIP promoted Tal1 degradation with both chaperone binding and ubiquitin ligase activities, which are mediated by its TPR domain and U box, respectively. Although the TPR domain was not involved in Tal1/SCL binding, it was required for enhancing its degradation. Likewise, the ubiquitin ligase activity of CHIP was dispensable for Tal1/SCL binding but essential for degradation. These findings provide both novel mechanistic insights into the operation of cullin-based ubiquitin ligase complexes and potential means by which Notch and Tal1/SCL regulate eukaryotic development. [ABSTRACT FROM AUTHOR]