Island biogeography theory and the habitat heterogeneity jointly explain global patterns of Rhododendron diversity

Mountain biodiversity is of great importance to biogeography and ecology.However,it is unclear what ecological and evolutionary processes best explain the generation and maintenance of its high levels of species diversity.In this study,we determined which of six common hypotheses(e.g.,climate hypotheses,habitat heterogeneity hypothesis and island biogeography theory)best explain global patterns of species diversity in Rhododendron.We found that Rhododendron diversity patterns were most strongly explained by proxies of island biogeography theory(i.e.,mountain area)and habitat heterogeneity(i.e.,elevation range).When we examined other relationships important to island biogeography theory,we found that the planimetric area and the volume of mountains were positively correlated with the Rhododendron diversity,whereas the‘mountains-to-mainland’distance was negatively correlated with Rhododendron diversity and shared species.Our findings demonstrate that Rhododendron diversity can be explained by island biogeography theory and habitat heterogeneity,and mountains can be regarded as islands which supported island biogeography theory.

Genetic Variations and Nonalcoholic Fatty Liver Disease:Field Synopsis,Systematic Meta-Analysis,and Epidemiological Evidence

Objective To systematically summarize the published literature on the genetic variants associated with nonalcoholic fatty liver disease(NAFLD).Methods Literature from Web of Science,PubMed,and Embase between January 1980 and September 2022 was systematically searched.Meta-analyses of the genetic variants were conducted using at least five data sources.The epidemiologic credibility of the significant associations was graded using the Venice criteria.Results Based on literature screening,399 eligible studies were included,comprising 381 candidate gene association,16 genome-wide association,and 2 whole-exome sequencing studies.We identified 465 genetic variants in 173 genes in candidate gene association studies,and 25 genetic variants in 17 genes were included in the meta-analysis.The meta-analysis identified 11 variants in 10 genes that were significantly associated with NAFLD,with cumulative epidemiological evidence of an association graded as strong for two variants in two genes(HFE,TNF),moderate for four variants in three genes(TM6SF2,GCKR,and ADIPOQ),and weak for five variants in five genes(MBOAT7,PEMT,PNPLA3,LEPR,and MTHFR).Conclusion This study identified six variants in five genes that had moderate to strong evidence of an association with NAFLD,which may help understand the genetic architecture of NAFLD risk.

A phylogenetic approach identifies patterns of beta diversity and floristic subregions of the Qinghai-Tibet Plateau

Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic regions.In this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet Plateau.We also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the QTP.We also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic difference.The environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic instability.Hierarchical dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the QTP.Our results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.

Identification and Expression Analysis of Abscisic Acid Signal Transduction Genes in Hemp Seeds

Abscisic acid(ABA)is involved in regulating diverse biological processes,but its signal transduction genes and roles in hemp seed germination are not well known.Here,the ABA signaling pathway members,PYL,PP2C and SnRK2 gene families,were identified from the hemp reference genome,including 7 CsPYL(pyrab-actin resistance1-like,ABA receptor),8 CsPP2CA(group A protein phosphatase 2c),and 7 CsSnRK2(sucrose nonfermenting1-related protein kinase 2).The content of ABA in hemp seeds in germination stage is lower than that in non-germination stage.Exogenous ABA(1 or 10μM)treatment had a significant regulatory effect on the selected PYL,PP2C,SnRK2 gene families.CsAHG3 and CsHAI1 were most significantly affected by exogenous ABA treatment.Yeast two-hybrid experiments were performed to reveal that CsPYL5,CsSnRK2.2,and CsSnRK2.3 could interact with CsPP2CA7 and demonstrate that this interaction was ABA-independent.Our results indicated that CsPYL5,CsSnRK2.2,CsSnRK2.3 and CsPP2CA7 might involve in the ABA signaling transduction pathway of hemp seeds during the hemp seed germination stages.This study suggested that novel genetic views can be brought into investigation of ABA signaling pathway in hemp seeds and lay the foundation for further exploration of the mechanism of hemp seed germination.

An Image Segmentation Algorithm Based on a Local Region Conditional Random Field Model

To reduce the computation cost of a combined probabilistic graphical model and a deep neural network in semantic segmentation, the local region condition random field (LRCRF) model is investigated which selectively applies the condition random field (CRF) to the most active region in the image. The full convolutional network structure is optimized with the ResNet-18 structure and dilated convolution to expand the receptive field. The tracking networks are also improved based on SiameseFC by considering the frame relations in consecutive-frame traffic scene maps. Moreover, the segmentation results of the greyscale input data sets are more stable and effective than using the RGB images for deep neural network feature extraction. The experimental results show that the proposed method takes advantage of the image features directly and achieves good real-time performance and high segmentation accuracy.

A Stochastic Programming Strategy in Microgrid Cyber Physical Energy System for Energy Optimal Operation

This paper focuses on the energy optimal operation problem of microgrids (MGs) under stochastic environment. The deterministic method of MGs operation is often uneconomical because it fails to consider the high randomness of unconventional energy resources. Therefore, it is necessary to develop a novel operation approach combining the uncertainty in the physical world with modeling strategy in the cyber system. This paper proposes an energy scheduling optimization strategy based on stochastic programming model by considering the uncertainty in MGs. The goal is to minimize the expected operation cost of MGs. The uncertainties are modeled based on autoregressive moving average (ARMA) model to expose the effects of physical world on cyber world. Through the comparison of the simulation results with deterministic method, it is shown that the effectiveness and robustness of proposed stochastic energy scheduling optimization strategy for MGs are valid. © 2014 Chinese Association of Automation.

Industrial Wireless Control Networks:From WIA to the Future

1.Introduction Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each other.Following this trend,industrial wireless control networks(IWCNs)are becoming increasingly attractive to industrial automation since they can help speed up production efficiency,reduce cost,enhance safety,and finally realize intelligent manufacturing[1].

A Priority-aware Frequency Domain Polling MAC Protocol for OFDMA-based Networks in Cyber-physical Systems

Wireless networking in cyber-physical systems (CPSs) is characteristically different from traditional wireless systems due to the harsh radio frequency environment and applications that impose high real-time and reliability constraints. One of the fundamental considerations for enabling CPS networks is the medium access control protocol. To this end, this paper proposes a novel priority-aware frequency domain polling medium access control (MAC) protocol, which takes advantage of an orthogonal frequency-division multiple access (OFDMA) physical layer to achieve instantaneous priority-aware polling. Based on the polling result, the proposed work then optimizes the resource allocation of the OFDMA network to further improve the data reliability. Due to the non-polynomial-complete nature of the OFDMA resource allocation, we propose two heuristic rules, based on which an efficient solution algorithm to the OFDMA resource allocation problem is designed. Simulation results show that the reliability performance of CPS networks is significantly improved because of this work. © 2014 Chinese Association of Automation.

Coordination of multiple mobile robots with limited communication range in pursuit of single mobile target in cluttered environment

This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target,with the aim of reducing the capture time.Compared with the previous algorithms,we assume that the target can be detected by any robot and captured successfully by two or more robots.In this paper,we assume that each robot has a limited communication range.We maintain the robots within a mobile network to guarantee the successful capture.In addition,the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time.A coordination algorithm considering both aspects is proposed.This algorithm can greatly reduce the expected time of capturing the mobile target.Finally,we validate the algorithm by the simulations and experiments.

MAS Based Distributed Automatic Generation Control for Cyber-Physical Microgrid System

The microgrid is a typical cyber-physical microgrid system (CPMS). The physical unconventional distributed generators (DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components, such as the embedded computer and communication network, are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid, the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information (such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system (MAS). Based on the global information from cyber components of CPMS, automatic generation control (AGC) and automatic voltage control (AVC) are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods. © 2014 Chinese Association of Automation.

An Overview of Smart City in China

The year of 2013 is considered the first year of smart city in China. With the development of informationization and urbanization in China, city diseases(traffic jam, medical problem and unbalanced education) are more and more apparent. Smart city is the key to solving these diseases. This paper presents the overall smart city development in China in term of market scale and development stages, the technology standards, and industry layout. The paper claims that the issues and challenges facing smart city development in China and proposes to make polices to support smart city development.

Tradeoff between utility and lifetime in energy-constrained wireless sensor networks

We study the tradeoff between network utility and network lifetime using a cross-layer optimization approach. The tradeoff model in this paper is based on the framework of layering as optimization decomposition. Our tradeoff model is the first one that incorporates time slots allocation into this framework. By using Lagrangian dual decomposition method, we decompose the tradeoff model into two subproblems： routing problem at network layer and resource allocation problem at medium access control （MAC） layer. The interfaces between the layers are precisely the dual variables. A partially distributed algorithm is proposed to solve the nonlinear, convex, and separable tradeoff model. Numerical simulation results are presented to support our algorithm.

Quantitative analysis of the main components in ceramic raw materials based on the desktop LIBS analyzer

The concentrations of SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiO,and loss on ignition(L.O.I.) are the main inorganic components of geological samples.Concentrations of the eight oxides and L.O.I.are also the main indicators of concern in the production of building ceramics.Quantitative analysis of the eight oxides and L.O.I.was performed using fiber-laserbased laser-induced breakdown spectroscopy(LIBS).A combination of continuous background deduction,full width at half maximum(FWHM) intensity integral and spectral sum normalization was proposed for data processing.After the data processing combined the continuous background deduction,FWHM intensity integral and spectral sum normalization,the mean absolute errors(MAEs) of the calibration of L.O.I.,SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiOwas reduced from 2.03%,12.06%,4.84%,1.10%,0.69%,0.31%,0.11%,0.20%and 0.10% to 1.80%,9.48%,2.12%,0.36%,0.58%,0.11%,0.08%,0.19% and 0.05%,respectively.This multivariate method was further introduced and discussed to improve the analysis performance.The MAEs of L.O.I.,SiO,Al2O,KO and NaO were further reduced to1.12%,2.07%,1.38%,0.35% and 0.43%,respectively.The results show that the overall prediction error can meet the requirements for the production of building ceramics.The LIBS desktop analyzer has great potential in detection applications on geological samples.

State feedback control of network-based systems with packet disordering

A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network-based systems with packet disordering, is constructed. Different from the existing models of network-based systems, the number of delay items is time-varying in the model proposed. Further, this model is converted into a parameter-uncertain discrete-time system with time-varying delay item numbers in terms of matrix theory. Moreover, the less conservative stability condition is obtained by avoiding utilisation of Moon et al.’ inequality and bounding inequalities for quadratic functional terms. By solving a minization problem based on linear matrix inequalities, the state feedback controller is presented. A numerical example is given to illustrate the effectiveness of the proposed method.

Efficacy and Safety of Sofosbuvir-based Regimens in Hepatitis C Patients With Decompensated Cirrhosis:A Systematic Review and Meta-analysis

Background and Aims:Decompensated cirrhotic patients with hepatitis C(HCV)are often under-represented in clinical trials.We aimed to evaluate pooled data on the efficacy and safety of sofosbuvir(SOF)-based regimens in these patients.Methods:We conducted a systemic review and meta-analysis by searching multiple databases for studies published from October 2010 to October 2020.Outcomes of interest were sustained virologic response(SVR)and safety of SOFbased regimens in decompensated HCV patients.Two reviewers independently performed the study selection and data extraction.Results:We included 33 studies that enrolled 5,302 HCV patients.The pooled SVR rate in decompensated patients with SOF-based regimens was 85.1%(95%CI:82.8–87.3).Patients on SOF/velpatasvir±ribavirin achieved a significantly higher SVR(91.0%,95%CI:87.7–93.9)than that of SOF/ledipasvir±ribavirin[(86.3%,95%CI:84.6–87.8);p=0.004],or on SOF/daclatasvir±ribavirin(82.4%,95%CI:78.2–86.2%;p<0.001).Adding ribavirin to SOFbased regimens(pooled SVR 84.9%,95%CI:81.7–87.9)did not significantly increase the SVR[83.8%(95%CI:76.8–89.8%;p=0.76)]in decompensated patients,which was also true in subgroup analyses for each regimen within the same treatment duration.However,adding ribavirin significantly increased the frequency of adverse events from 52.9%(95%CI:28.0–77.1)to 89.2%(95%CI:68.1–99.9)and frequency of severe events.The pooled incidence of hepatocellular carcinoma and case-fatality of decompensated patients were 3.1%(95%CI:1.5–5.0)and 4.6%(95%CI:3.1–6.3),respectively.The overall heterogeneity was high.There was no publication bias.Conclusions:The analysis found that 12 weeks of SOF/velpatasvir without ribavirin is the preferred therapy,with a significantly higher SVR compared with other SOF-based regimens in decompensated HCV patients.

Protein O-GlcNAcylation homeostasis regulates facultative heterochromatin to fine-tune sog-Dpp signaling during Drosophila early embryogenesis

Protein O-GlcNAcylation is a monosaccharide post-translational modification maintained by two evolutionarily conserved enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA). Mutations in human OGT have recently been associated with neurodevelopmental disorders, although the mechanisms linking O-GlcNAc homeostasis to neurodevelopment are not understood. Here, we investigate the effects of perturbing protein O-GlcNAcylation using transgenic Drosophila lines that overexpress a highly active OGA. We reveal that temporal reduction of protein O-GlcNAcylation in early embryos leads to reduced brain size and olfactory learning in adult Drosophila. Downregulation of O-GlcNAcylation induced by the exogenous OGA activity promotes nuclear foci formation of Polycomb-group protein Polyhomeotic and the accumulation of excess K27 trimethylation of histone H3 (H3K27me3) at the mid-blastula transition. These changes interfere with the zygotic expression of several neurodevelopmental genes, particularly short gastrulation (sog), a component of an evolutionarily conserved sog-Decapentaplegic (Dpp) signaling system required for neuroectoderm specification. Our findings highlight the importance of early embryonic O-GlcNAcylation homeostasis for the fidelity of facultative heterochromatin redeployment and initial cell fate commitment of neuronal lineages, suggesting a possible mechanism underpinning OGT-associated intellectual disability.

Industrial Internet for intelligent manufacturing:past, present, and future

Industrial Internet, motivated by the deep integration of new-generation information and communication technology(ICT) and advanced manufacturing technology, will open up the production chain, value chain, and industry chain by establishing complete interconnections between humans, machines, and things. This will also help establish novel manufacturing and service modes, where personalized and customized production for differentiated services is a typical paradigm of future intelligent manufacturing. Thus, there is an urgent requirement to break through the existing chimney-like service mode provided by the hierarchical heterogeneous network architecture and establish a transparent channel for manufacturing and services using a flat network architecture. Starting from the basic concepts of process manufacturing and discrete manufacturing, we first analyze the basic requirements of typical manufacturing tasks. Then, with an overview on the developing process of industrial Internet, we systematically compare the current networking technologies and further analyze the problems of the present industrial Internet.On this basis, we propose to establish a novel “thin waist” that integrates sensing, communication, computing, and control for the future industrial Internet. Furthermore, we perform a deep analysis and engage in a discussion on the key challenges and future research issues regarding the multi-dimensional collaborative sensing of task–resource, the end-to-end deterministic communication of heterogeneous networks, and virtual computing and operation control of industrial Internet.

紫茎泽兰在中国的气候生态位稳定且其分布范围仍有进一步扩展的趋势

明确入侵物种气候生态位的时空动态格局,不仅有助于理解入侵物种生态位的变化趋势,还可以使物种分布模型更真实地预测物种的扩散动态。本文使用恶性入侵植物紫茎泽兰(Ageratina adenophora)在原产地及我国的分布点和环境因子数据,结合生态位分析及物种分布模型,分析了紫茎泽兰入侵至我国后其气候生态位的时空变化特征、地理分布格局变化及其限制因子。结果表明:(1)紫茎泽兰入侵至我国后其气候生态位在时间和空间上虽略有扩张,但仍保持较高的稳定性。尤其是入侵的初始阶段(1980年之前)稳定性最高(NS=0.995),此后其气候生态位的稳定性逐渐降低,具体表现为该植物在中国更倾向于分布在潮湿(高最暖季降水量)、寒冷(低最干季平均温)且平均日较差低的生境。(2)过去50年里紫茎泽兰的适宜分布范围显著增加(151.77%–271.14%),且其适宜分布区的重心在2010年之前表现出向东北(贵州西南部、四川南部)扩散的趋势,2010年以后表现出向西南(云南北部、贵州北部)扩散的趋势。在扩散过程中,该物种的气候生态位稳定性也表现出随着纬度的增加而逐渐降低的趋势。(3)未来气候变化情景下,紫茎泽兰的适宜分布范围将进一步增加(111.97%),到2040年该物种基本可以扩散至其整个潜在适宜分布区,仅在藏东南地区有小范围的适宜生境受扩散限制无法达到。

Corrosion Resistance of Graphene-Reinforced Waterborne Epoxy Coatings

Graphene （G） was dispersed uniformly in water and used as an inhibitor in waterborne epoxy coatings. The effect of dispersed G on anticorrosion performance of epoxy coatings was evaluated. The composite coatings displayed outstanding barrier properties against H20 molecule compared to the neat epoxy coating. Open circuit potential （OCP）, Tafel and electrochemical impedance spectroscopy （EIS） analysis confirmed that the corrosion rate exhibited by composite coatings with 0.5 wt% G was an order of magnitude lower than that of neat epoxy coating. Salt spray test results revealed superior corrosion resistance offered by the composite coating.

Multi-agent deep reinforcement learning for end—edge orchestrated resource allocation in industrial wireless networks

Edge artificial intelligence will empower the ever simple industrial wireless networks(IWNs)supporting complex and dynamic tasks by collaboratively exploiting the computation and communication resources of both machine-type devices(MTDs)and edge servers.In this paper,we propose a multi-agent deep reinforcement learning based resource allocation(MADRL-RA)algorithm for end-edge orchestrated IWNs to support computation-intensive and delay-sensitive applications.First,we present the system model of IWNs,wherein each MTD is regarded as a self-learning agent.Then,we apply the Markov decision process to formulate a minimum system overhead problem with joint optimization of delay and energy consumption.Next,we employ MADRL to defeat the explosive state space and learn an effective resource allocation policy with respect to computing decision,computation capacity,and transmission power.To break the time correlation of training data while accelerating the learning process of MADRL-RA,we design a weighted experience replay to store and sample experiences categorically.Furthermore,we propose a step-by-stepε-greedy method to balance exploitation and exploration.Finally,we verify the effectiveness of MADRL-RA by comparing it with some benchmark algorithms in many experiments,showing that MADRL-RA converges quickly and learns an effective resource allocation policy achieving the minimum system overhead.