Smart and fast reinforcement design for anti-dip bedding rock slopes

Rock slopes are usually reinforced by a number of rock bolts due to the high efficiency and low price.However,where should the rock bolts be installed is still a troublesome issue.For anti-dip bedding rock slopes(ABRSs),the installation position of rock bolts is a controlling factor that determines the reinforcement effect.In this work,a theoretical method is firstly proposed for assessing the stability of ABRSs reinforced by rock bolts using a limit equilibrium model.A comparison of theoretical calculations and numerical results was conducted to test the correctness of the theoretical method.Based on the stability assessment of ABRSs,we introduce adaptive moment estimation method(Adam)to optimize the installation location of rock bolts.Using Adam optimizer,the optimal layout of rock bolts with the maximum factor of safety can be determined,and the factor of safety of the slope increases by about 25%using the same amount of rock bolts but with different installation locations.The proposed method enables the fast stability analysis and supporting design for reinforced ABRSs,which paves the way to smart supporting design of slopes.

Interaction of methionine sulfoxide reductase B5 with SlMYC2 stimulates the transcription of MeJA-mediated autophagy-related genes in tomato fruit

Methyl jasmonate(MeJA)has been shown to induce autophagy in various plant stress responses and metabolic pathways.MYC2 is involved in MeJA-mediated postharvest fruit biological metabolism,but it is unclear how it affects MeJA-induced fruit autophagy.In this study,we noticed that silencing SlMYC2 significantly reduced the increase in autophagy-related genes(SlATGs)expression induced by MeJA.SlMYC2 could also bind to the promoters of several SlATGs,including SlATG13a,SlATG13b,SlATG18a,and SlATG18h,and activate their transcript levels.Moreover,SlMsrB5,a methionine sulfoxide reductase,could interact with SlMYC2.Methionine oxidation in SlMYC2 and mimicking sulfoxidation in SlMYC2 by mutation of methionine-542 to glutamine reduced the DNA-binding ability and transcriptional activity of SlMYC2,respectively.SlMsrB5 partially repaired oxidized SlMYC2 and restored its DNA-binding ability.On the other hand,silencing SlMsrB5 inhibited the transcript levels of SlMYC2-targeted genes(SlATG13a,SlATG13b,SlATG18a,and SlATG18h).Similarly,dual-luciferase reporter(DLR)analysis revealed that SlMsrB5–SlMYC2 interaction significantly increased the ability of SlMYC2-mediated transcriptional activation of SlATG13a,SlATG13b,SlATG18a,and SlATG18h.These findings demonstrate that SlMsrB5-mediated cyclic oxidation/reduction of methionine in SlMYC2 inf luences SlATGs expression.Collectively,these findings reveal the mechanism of SlMYC2 in SlATGs transcriptional regulation,providing insight into the mechanism of MeJA-mediated postharvest fruit quality regulation.

MIKC^(C)-type MADS-box genes in Rosa chinensis: the remarkable expansion of ABCDE model genes and their roles in floral organogenesis

MIKC^(C)-type MADS-box(MIKC^(C))genes encode transcription factors that have crucial roles in controlling floral organogenesis and flowering time in plants.Although this gene family has been well characterized in many plant species,its evolutionary and comprehensive functional analysis in rose is lacking.In this study,58 non-redundant MIKC^(C)uni-transcripts were extensively identified from rose transcriptomes.Phylogenetic analysis placed these genes into 12 clades with their Arabidopsis and strawberry counterparts,and revealed that ABCDE model(including AP1/FUL,AP3/PI,AG,and SEP clades),and SOC1 and AGL6 clade genes have remarkably expanded in Rosa chinensis,whereas genes from the FLC and AGL17 clades were undetectable.Sequence alignments suggest that the AP3/PI clade may contribute to more specific functions in rose due to a high variation of amino acid residues within its MADS-box domains.A comparative analysis of gene expression in specific floral organ differentiation stages and floral organs between R.chinensis cv.Old Blush and the closely related mutant genotype R.chinensis cv.Viridiflora(floral organs mutated into leaf-like structures)further revealed the roles of ABCDE model genes during floral organogenesis in rose.Analysis of co-expression networks provided an overview of the regulatory mechanisms of rose MIKC^(C)genes and shed light on both the prominent roles of AP3/PI clade genes in floral organogenesis and the roles of RcAGL19,RcAGL24,and RcSOC1 in regulating floral transition in rose.Our analyses provide an overall insight of MIKC^(C)genes in rose and their potential roles in floral organogenesis.

A TPDP-MPM-based approach to understanding the evolution mechanism of landslide-induced disaster chain

With complex topographic and hydrological characteristics,the landslide-induced surge disaster chain readily develops in mountainous and gorge areas,posing a huge challenge for infrastructure construction.This landslide-induced surge disaster chain involves a complex fluid-solid coupling between the landslide mass and a water body and exhibits complex energy conversion and dissipation characteristics,which is challenging to deal with using traditional finite element analysis.In this study,the energy evolution characteristics in the whole process of the disaster chain were first investigated,and the momentum-conservation equations for different stages were established.Then,the two-phase doublepoint material point method(TPDP-MPM)was used to model the landslide-induced surge disaster chain,and an experiment involving block-induced surge was modeled and simulated to validate this method.Finally,three generalized models were established for the landslide-induced surge process in a U-shaped valley,including subaerial,partly submerged,and submarine scenarios.The interaction mechanism between the landslide mass and the water body in the disaster chain was revealed by defining the system energy conversion ratio and the mechanism of evolution of the disaster chain from the perspective of energy.The results help further evaluate the secondary disasters,given the submerged position of the landslide mass.

A Localized Inter-Actuator Network Topology Repair Scheme for Wireless Sensor and Actuator Networks

Node failure is one of the most severe problems that wireless sensor and actuator networks(WSANs) have to deal with. The failure of actuator nodes, in particular, may result in substantial consequences such as network partitioning, incorrect and incomplete decision execution for WSANs. This paper proposes an efficient localized scheme, called LANTR, to repair the damaged topology of inter-actuator network while single actuator node paralyzes. For the failure of an ordinary actuator node, LANTR can rapidly repair the topology through relocating only one-hop neighbors of the failure node, meanwhile, keep the original topology structure as much as possible. Given the magnitude of cut vertex actuators playing on the connectivity, LANTR designs a novel method for each cut vertex to select out a specific guardian node with the minimum degree or minimum cumulative degree from its neighbors, which can reduce the repair influence on the original topology and effectively reduce the coverage loss rate. The performance of the proposed scheme is evaluated and compared with several existing representative topology repair schemes, and the results indicate that LANTR can more effectively and efficiently repair the topology of inter-actuator networks.

A novel fault-tolerant scheduling approach for collaborative workflows in an edge-IoT environment

As a newly emerging computing paradigm, edge computing shows great capability in supporting and boosting 5G and Internet-of-Things (IoT) oriented applications, e.g., scientific workflows with low-latency, elastic, and on-demand provisioning of computational resources. However, the geographically distributed IoT resources are usually interconnected with each other through unreliable communications and ever-changing contexts, which brings in strong heterogeneity, potential vulnerability, and instability of computing infrastructures at different levels. It thus remains a challenge to enforce high fault-tolerance of edge-IoT scientific computing task flows, especially when the supporting computing infrastructures are deployed in a collaborative, distributed, and dynamic environment that is prone to faults and failures. This work proposes a novel fault-tolerant scheduling approach for edge-IoT collaborative workflows. The proposed approach first conducts a dependency-based task allocation analysis, then leverages a Primary-Backup (PB) strategy for tolerating task failures that occur at edge nodes, and finally designs a deep Q-learning algorithm for identifying the near-optimal workflow task scheduling scheme. We conduct extensive simulative case studies on multiple randomly-generated workflow and real-world edge-IoT server position datasets. Results clearly suggest that our proposed method outperforms the state-of-the-art competitors in terms of task completion ratio, server active time, and resource utilization.

硫酸盐腐蚀下钢纤维混凝土力-化耦合损伤细观模拟

利用有限元软件开展钢纤维混凝土在硫酸盐腐蚀下的细观模拟。首先,在Abaqus中基于MonteCarlo方法构建钢纤维和粗骨料随机分布的二维钢纤维混凝土模型,并进行硫酸根离子扩散模拟,确定不同龄期的硫酸根离子浓度场。然后,通过虚拟温度场法进行化学损伤模拟,得到不同龄期的化学进程。最后,对化学损伤后的试件施加位移荷载得到力–化耦合后的应力–应变曲线。模拟结果表明,随着腐蚀龄期的增加,由腐蚀产物导致的化学损伤不断增加,具体表现为导致的拉伸应变不断增大;但由于混凝土中钢纤维的存在,能量被有效地吸收和分散,明显阻止了贯穿裂缝的产生,从而提高了混凝土的耐久性和可靠性。

A Load Balancing Model Based on Cloud Partitioning for the Public Cloud

Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.

Discovering admissible Web services with uncertain QoS

Open and dynamic environments lead to inher- ent uncertainty of Web service QoS （Quality of Service）, and the QoS-aware service selection problem can be looked upon as a decision problem under uncertainty. We use an empiri- cal distribution function to describe the uncertainty of scores obtained from historical transactions. We then propose an approach to discovering the admissible set of services in- cluding alternative services that are not dominated by any other alternatives according to the expected utility criterion. Stochastic dominance （SD） rules are used to compare two services with uncertain scores regardless of the distribution form of their uncertain scores. By using the properties of SD rules, an algorithm is developed to reduce the number of SD tests, by which the admissible services can be reported pro- gressively. We prove that the proposed algorithm can be run on partitioned or incremental alternative services. Moreover, we achieve some useful theoretical conclusions for correct pruning of unnecessary calculations and comparisons in each SD test, by which the efficiency of the SD tests can be im- proved. We make a comprehensive experimental study using real datasets to evaluate the effectiveness, efficiency, and scal- ability of the proposed algorithm.