Coseismic Coulomb stress changes induced by a 2020-2021 M_(W)>7.0 Alaska earthquake sequence in and around the Shumagin gap and its influence on the Alaska-Aleutian subduction interface

Three M_(W)>7.0 earthquakes in 2020-2021 occurred in the Shumagin seismic gap and its adjacent area of the Alaska-Aleutian subduction zone,including the Mw7.8 Simeonof thrust earthquake on July 22,2020,the M_(W)7.6 Sand Point strike-slip earthquake on October 19,2020,and the M_(W)8.2 Chignik thrust earthquake on July 29,2021.The spatial and temporal proximity of these three earthquakes prompts us to probe stress-triggering effects among them.Here we examine the coseismic Coulomb stress change imparted by the three earthquakes and their influence on the subduction interface.Our results show that:(1)The Simeonof earthquake has strong loading effects on the subsequent Sand Point and Chignik earthquakes,with the Coulomb stress changes of 3.95 bars and 2.89 bars,respectively.The Coulomb stress change caused by the Sand Point earthquake at the hypocenter of the Chignik earthquake is merely around 0.01 bars,suggesting the negligible triggering effect on the latter earthquake;(2)The triggering effects of the Simeonof,Sand Point,and Chignik earthquakes on aftershocks within three months are not well pronounced because of the triggering rates of 38%,14%,and 43%respectively.Other factors may have played an important role in promoting the occurrence of these aftershocks,such as the roughness of the subduction interface,the complicated velocity structure of the lithosphere,and the heterogeneous prestress therein;(3)The three earthquakes caused remarkable coseismic Coulomb stress changes at the subduction interface nearby these mainshocks,with an average Coulomb stress change of 3.2 bars in the shallow region directly inwards the trench.

Time Sequence of Himalayan Endogenetic Mineralization on the East Side of the Qinghai-Tibet Plateau

Among the endogenetic deposits in the Sanjiang area and at the west margin of the Yangtze platform, Himalayan deposits are the most important and contribute a large proportion of the resources of superlarge deposits. Among the controlled resources of this region, 84% of copper resources, 67% of Pb-Zn, 31% of Ag, 77% of gold and 24% of tin come from Himalayan deposits on the east side of the Qinghai-Tibet plateau. Himalayan endogenetic mineralization shows a relatively complete sequence evolution in the Sanjiang area and on the west margin of the Yangtze platform. Mineralization is manifested by gold deposits related to K-rich lamprophyre, REE deposits related to alkalic complexes and Cu-Au-polymetallic deposits related to alkaline porphyry. Six sequences of mineralization evolution since 65 Ma B.P. in the Sanjiang area and on the west side of the Yangtze platform can be recognized. Himalayan endogenetic mineralization on the east side of the Qinghai-Tibet plateau reached its peak before the Oligocene, corresponding to episodes I and II of the intracontinental orogenic cycle. Afterwards, mineralization waned obviously.

Research on the Application of Time Structure Variation Analysis to the Jiashi-Bachu Earthquake Swarm Sequence

In 1997 - 2003, 27 earthquakes with M≥ 5.0 occurred in the Jiashi-Bachu area of Xinjiang. It was a rare strong earthquake swarm activity. The earthquake swarm has three time segments of activity with different magnitudes in the years 1997, 1998 and 2003. In different time segments, the seismic activity showed strengthenin-qguiet changes in various degrees before earthquakes with M ≥ 5.0. In order to delimitate effectively the precursory meaning of the clustering （strengthening） quiet change in sequence and to seek the time criterion for impending prediction, the nonlinear characteristics of seismic activity have been used to analyze the time structure characteristics of the earthquake swarm sequence, and further to forecast the development tendency of earthquake sequences in the future. Using the sequence catalogue recorded by the Kashi Station, and taking the earthquakes with Ms≥ 5.0 in the sequence as the starting point and the next earthquake with Ms = 5.0 as the end, statistical analysis has been performed on the time structure relations of the earthquake sequence in different stages. The main results are as follows： （1） Before the major earthquakes with M ≥ 5.0 in the swarm sequence, the time variation coefficient （δ-value） has abnormal demonstrations to different degrees. （2） Within 10 days after δ= 1, occurrence of earthquakes with M ≥ 5.0 in the swarm is very possible. （3） The time variation coefficient has three types of change. （4） The change process before earthquakes with M5.0 is similar to that before earthquakes with M6.0, with little difference in the threshold value. In the earthquake swarm sequence, it is difficult to delimitate accurately the attribute of the current sequences （foreshock or aftershock sequence） and to judge the magnitude of the follow-up earthquake by δ-value. We can only make the judgment that earthquakes with M5.0 are likely to occur in the sequence. （5） The critical clustering characteristics of the sequence are hierarchical. Only corresponding to a certain magnitude can the sequence have the variation state of critical clustering. （6） The coefficient of the time variation has a clear meaning in physics. After the clustering-quiet state of earthquake activity has appeared, it can describe clearly the randomness of the seismogenic system. Furthermore, it can efficiently clarify whether or not the clustering quiescence variation is of some prognostic meaning. In the case that the earthquake frequency attenuation is essentially normal （h 〉 1 ） and there is no remarkable clustering-quiescence state, it is still possible to discover the abnormal change of the sequence from the time variation coefficient. On the contrary, in the later period of swarm activity, after the appearance of many seismic quiescence phenomena, this coefficient did not appear abnormally, even when h 〈 1, suggesting that the δ-value diagnosis is more universal.

A Hybrid Estimation of Distribution Algorithm for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times

A hybrid estimation of distribution algorithm (EDA) with iterated greedy (IG) search (EDA-IG) is proposed for solving the unrelated parallel machine scheduling problem with sequence-dependent setup times (UPMSP-SDST). For makespan criterion, some properties about neighborhood search operators to avoid invalid search are derived. A probability model based on neighbor relations of jobs is built in the EDA-based exploration phase to generate new solutions by sampling the promising search region. Two types of deconstruction and reconstruction as well as an IG search are designed in the IG-based exploitation phase. Computational complexity of the algorithm is analyzed, and the effect of parameters is investigated by using the Taguchi method of design-of-experiment. Numerical tests on 1640 benchmark instances are carried out. The results and comparisons demonstrate the effectiveness of the EDA-IG. Especially, the bestknown solutions of 531 instances are updated. In addition, the effectiveness of the properties is also demonstrated by numerical comparisons. © 2014 Chinese Association of Automation.

Single Machine Scheduling with Time-Dependent Learning Effect and Non-Linear Past-Sequence-Dependent Setup Times

This paper studies a single machine scheduling problem with time-dependent learning and setup times. Time-dependent learning means that the actual processing time of a job is a function of the sum of the normal processing times of the jobs already scheduled. The setup time of a job is proportional to the length of the already processed jobs, that is, past-sequence-dependent (psd) setup time. We show that the addressed problem remains polynomially solvable for the objectives, i.e., minimization of the total completion time and minimization of the total weighted completion time. We also show that the smallest processing time (SPT) rule provides the optimum sequence for the addressed problem.

Nonlinear Time-Varying Systems Identification Using Basis Sequence Expansions Combined with Neural Networks

A new method for identifying nonlinear time varying systems with unknown structure is presented. The method extends the application area of basis sequence identification. The essential idea is to utilize the learning and nonlinear approximating ability of neural networks to model the non linearity of the system, characterize time varying dynamics of the system by the time varying parametric vector of the network, then the parametric vector of the network is approximated by a weighted sum of known basis sequences. Because of black box modeling ability of neural networks, the presented method can identify nonlinear time varying systems with unknown structure. In order to improve the real time capability of the algorithm, the neural network is trained by a simple fast learning algorithm based on local least squares presented by the authors. The effectiveness and the performance of the method are demonstrated by some simulation results.

Identical Machine Scheduling Problem with Sequence-Dependent Setup Times: MILP Formulations Computational Study

This work aims to give a systematic construction of the two families of mixed-integer-linear-programming (MILP) formulations, which are graph- based and sequence-based, of the well-known scheduling problem. Two upper bounds of job completion times are introduced. A numerical test result analysis is conducted with a two-fold objective 1) testing the performance of each solving methods, and 2) identifying and analyzing the tractability of an instance according to the instance structure in terms of the number of machines, of the jobs setup time lengths and of the jobs release date distribution over the scheduling horizon.

Real-Time Update of Sequence Placement Logic for High Arch Dams Based on Evidence Weight Discount

Sequence placement logic plays a significant role in construction simulation of high arch dams and directly affects the simulation process and results. To establish a sequence logic for dam block placement, the construction scheme, real-time construction process, and random factors of the site all need to be considered in detail. There are few studies available currently that take all these factors into consideration. To address this problem, a real-time update of sequence placement logic for high arch dams based on evidence weight discount is proposed in this study. First, the subjective weight of the dam block sequence priority criteria is built using a consistent matrix method based on the construction scheme. Second, using evidence theory, dynamic objective weight of the priority criteria and basic probability assignment is built. Finally, using a weight self-adaptive adjustment method and comprehensive evidence discounting, the placing probabilities of different dam blocks are obtained. A case study indicates that this method can realize real-time update of sequence placement logic. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.

A Linear Programming Approach for Parallel Cell Scheduling with Sequence-Dependent Setup Times

In this study, we consider the problem of scheduling a set of jobs with sequence-dependent setup times on a set of parallel production cells. The objective of this study is to minimize the total completion time. We note that total customer demands for each type should be satisfied, and total required production time in each cell cannot exceed the capacity of the cell. This problem is formulated as an integer programming model and an interface is designed to provide integrity between data and software. Mathematical model is tested by both randomly generated data set and real-world data set from a factory that produce automotive components. As a result of this study, the solution which gives the best alternative production schedule is obtained.

Time-Hopping Sequence Design for Virtual Full Duplex via Rapid On-Off-Division Duplex

To achieve virtual full-duplex(VFD)communication using half-duplex radios,the rapid on-off-division(RODD)technique has been proposed in recent years.The time-hopping(TH)sequence is critical to controlling self-interference introduced in the paradigm.By constructing the collision model with a symbol level time scale,the periodic collision correlation function properties are introduced as the performance metric for the TH sequence in the RODD system.To achieve the best VFD performance,an optimization-based method for TH sequence design is proposed.In addition,the conventional TH frame structure design for RODD system is improved.Numerical simulations are presented to demonstrate that the proposed approach can significantly increase system performance.Results indicate that the TH sequence design is very effective for the RODD system.

Effect of Sludge Retention Time on Nitrite Accumulation in Real-time Control Biological Nitrogen Removal Sequencing Batch Reactor

In this study,four sequencing batch reactors(SBR),with the sludge retention time(SRT)of 5,10,20 and 40 d,were used to treat domestic wastewater,and the effect of SRT on nitrite accumulation in the biological nitrogen removal SBR was investigated.The real-time control strategy based on online parameters,such as pH,dissolved oxygen(DO)and oxidation reduction potential(ORP),was used to regulate the nitrite accumulation in SBR. The model-based simulation and experimental results showed that with the increase of SRT,longer time was needed to achieve high level of nitritation.In addition,the nitrite accumulation rate(NAR)was higher when the SRT was relatively shorter during a 112-day operation.When the SRT was 5 d,the system was unstable with the mixed liquor suspended solids(MLSS)decreased day after day.When the SRT was 40 d,the nitrification process was significantly inhibited.SRT of 10 to 20 d was more suitable in this study.The real-time control strategy combined with SRT control in SBR is an effective method for biological nitrogen removal via nitrite from wastewater.

一种基于real-time PCR技术的TTV检测方法的建立及应用

目的:本研究旨在开发一种具有更高灵敏度和特异性的TTV检测技术,为揭示TTV在多种疾病过程中的作用提供重要的技术支持。方法:为了更精确、灵敏的检测TTV,本研究分析了目前公布的所有亚型的TTV基因序列,在此基础上建立了一种基于UTR区域的real-time PCR检测方法,并与文献报道应用较为广泛的PCR检测方法进行了对比。结果:本研究建立的方法在1×10^(7)~1×10^(1) copies/μL标准品浓度范围内具有良好的线性关系,相关系数为1.000,斜率为-3.446,检测下限为1×10^(1) copies/μL。重复性试验结果显示,组内变异系数为7.22%,表明本方法重复性、稳定性较强。针对30份临床样本,使用本研究建立的real-time PCR检测方法及目前被多个研究所使用的4套引物进行对比。结果表明,本研究所建立的方法灵敏度显著高于文献中报道的4种方法(P<0.01);Sanger测序结果表明,本方法检测出的30份阳性样本均为TTV,检测特异性为100%。结论:本研究采用基于TaqMan探针的real-time PCR检测方法,检测灵敏性高、覆盖基因型范围广,尤其对于TTV病毒载量较低的情况下能够进行定量检测,对于TTV病毒的致病性及作为免疫标志物的应用提供重要的技术支持。

Research on time structure characteristic of gas concentration sequence in the working face

In the procedure of coal industry production, the losses of the persons and economy caused by the gas explosion accidents are most serious, therefore, prevention and control of the gas explosion accident of the coal mines is an important issue needed to be solved urgently in the safety production work of our coal mines. The characteristic of time structure variation index characteristic was analyzed about gas concentration sequence of three measure points in the NO. 1I 1024 working face. It was found that the value of time variation about three measure points was mostly 1〈δ≤1.5, and gas emission presented consistently strong-clustering state twice, and the value of time variation presented continuous variation state in the active stage of gas concentration. Complex characteristics of the value indicated gas emission was continuously variable in time or space and presented the complex nonlinear characteristics. So the characteristic about gas emission system was correctly depicted and analyzed to gas emission system according to the relation of its state variation and essential of nonlinear system. The result also provided reliable warranty for its continued nonlinear research on gas emission.

A test sequence generation method of zone controller based on timed automata

In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata model is established based on function analysis of the zone controller, and the correctness of the model is verified by UPPAAL. Then by parsing the timed automata model files, state information and transition conditions can be extracted to generate test case sets. Finally, according to the serialization conditions of test cases, the test cases are serialized into test sequences by using the improved depth first search algorithm. A case, the ZC controls the train running within its jurisdiction, shows that the method is correct and can effectively improve the efficiency of test sequence generation.

Real Time Power Monitoring Detection Based on Sequence Time Domain Reflectometry Approach

Sequence Time Domain Reflectometry (STDR) have been demonstrated to be a powerful technique for detecting the length of cable or length of open circuit or short circuit cables. Using this method along with using smart meter on the main electrical panel board to monitor consumption if load at each circuit, enable user to monitor power consumption at each node (power outlet) only by operating a smart digital meter and an STDR circuitry on each circuit at the main electrical panel board. This paper introduces this method and examines it on dead-wire and energized wire with a load connected across it. Experimental results are demonstrated for both types. Test result show the potential application of this approach to provide consumption information and potential cost saving via feedback for users.

Next Generation Transcriptome Sequencing and Quantitative Real-Time PCR Technologies for Characterisation of the Bemisia tabaci Asia 1 mtCOI Phylogenetic Clade

A programme of functional genomics research is underway at the University of Greenwich,UK,to develop and apply genomics technologies to characterise an economically-important but under-researched Bemisia tabaci（Hemiptera：Aleyrodidae）,the Asia 1 mtCOI phylogenetic group.A comparison of this putative species from India with other important B.tabaci populations and insect species may provide targets for the development of more effective whitefly control strategies.As a first step,next-generation sequencing（NGS）has been used to survey the transcriptome of adult female whitefly,with high quality RNA preparations being used to generate cDNA libraries for NGS using the Roche 454 Titanium DNA sequencing platform.Contig assemblies constructed from the resultant sequences（301 094 reads）using the software program CLC Genomics Workbench generated 3 821 core contigs.Comparison of a selection of these contigs with related sequences from other B.tabaci genetic groups has revealed good alignment for some genes（e.g.,HSP90）but misassemblies in other datasets（e.g.,the vitellogenin gene family）,highlighting the need for manual curation as well as collaborative international efforts to obtain accurate assemblies from the existing next generation sequence datasets.Nevertheless,data emerging from the NGS has facilitated the development of accurate and reliable methods for analysing gene expression based on quantitative real-time RT-PCR,illustrating the power of this approach to enable rapid expression analyses in an organism for which a complete genome sequence is currently lacking.

The asymptotic relation between the first crossing point and the last exit time of Gaussian order statistics sequences

In this paper,we study the asymptotic relation between the first crossing point and the last exit time for Gaussian order statistics which are generated by stationary weakly and strongly dependent Gaussian sequences.It is shown that the first crossing point and the last exit time are asymptotically independent and dependent for weakly and strongly dependent cases,respectively.The asymptotic relations between the first crossing point and the last exit time for stationary weakly and strongly dependent Gaussian sequences are also obtained.

A Petri Net Model for Part Sequencing and Robot Moves Sequence in A 2-Machine Robotic Cell

This paper deals with part sequencing and optimal robot moves sequence in 2-machine robotic cells according to Petri net graph. We have assumed that the robotic cell is capable of producing same and different parts. We have considered a new motion cycle for robot moves sequence which is the development of existing motion cycles in 2-machine robotic cells. The main goal of this study is to minimize the cycle time by determining the optimal part sequencing and robot moves sequence in the robotic cell. So, we have proposed a model based on Petri network.

Sequence Analysis and Quantitative Detection of Norwalk-like Viruses in Cultured Oysters of China

We isolated 4 Norwalk-like viruses （NLVs） contaminated oysters from 33 Chinese oysters collected from local commercial sources of Shandong Province. After amplification of the RNA-dependent RNA polymerase （RdRp） region of NLVs genomes with RT-PCR, the open reading frame 1 （ORF 1） of the RdRp was sequenced and subjected to multiple-sequence alignment. The results showed that NLVs in the four isolates belong to genogroup Ⅱ. The sequence comparison showed that the similarity between four Chinese oyster isolates were higher than 99.0%, which indicated that NLVs prevalent in close areas have high homogeneity in genome sequences. In addition, the most conserved sequences between diverse NLVs were used to design primers and TaqMan probes, then the real-time quantitative PCR assay was performed. According to the standard curve of GII NLVs, the original amounts （copies） of NLVs in positive patient＇s fecal isolate, positive Japanese oyster isolate, and the Chinese oyster isolate were 8.9× 10^8, 1.25× 10^8 and 4.7× 10^1 respectively. The detecting limit of NLVs was 1 × 10^1 copies. This study will be helpful for routine diagnosis of NLVs pathogens in foods and thus for avoiding food poisoning in the future.