An Improved Hyperplane Assisted Multiobjective Optimization for Distributed Hybrid Flow Shop Scheduling Problem in Glass Manufacturing Systems

To solve the distributed hybrid flow shop scheduling problem(DHFS)in raw glass manufacturing systems,we investigated an improved hyperplane assisted evolutionary algorithm(IhpaEA).Two objectives are simultaneously considered,namely,the maximum completion time and the total energy consumptions.Firstly,each solution is encoded by a three-dimensional vector,i.e.,factory assignment,scheduling,and machine assignment.Subsequently,an efficient initialization strategy embeds two heuristics are developed,which can increase the diversity of the population.Then,to improve the global search abilities,a Pareto-based crossover operator is designed to take more advantage of non-dominated solutions.Furthermore,a local search heuristic based on three parts encoding is embedded to enhance the searching performance.To enhance the local search abilities,the cooperation of the search operator is designed to obtain better non-dominated solutions.Finally,the experimental results demonstrate that the proposed algorithm is more efficient than the other three state-of-the-art algorithms.The results show that the Pareto optimal solution set obtained by the improved algorithm is superior to that of the traditional multiobjective algorithm in terms of diversity and convergence of the solution.

Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data.Data security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms.In this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market.Moreover,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users.Specifically,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic bidding.The incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading scenario.With temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies.Furthermore,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

A fault warning for inter-turn short circuit of excitation winding of synchronous generator based on GRU-CNN

Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.

动量表象中的氦原子和氢分子

本文推导出动量表象中的基态氦原子和氢分子波函数。对午氦原子,使用了动量变量P_(r),P_(θ),P_(φ),它们分别共轭于球坐标位置变量r,θ,φ。对于氢分子,使用了动量变量P_(ξ),P_(η),P_(φ),它们分别共轭于椭球坐标位置变量ξ,η,φ。

Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm

In this study, we present a Pareto-based chemicalreaction optimization(PCRO) algorithm for solving the multiarea environmental/economic dispatch optimization problems.Two objectives are minimized simultaneously, i.e., total fuel cost and emission. In the proposed algorithm, each solution is represented by a chemical molecule. A novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is designed to dynamically enhance the performance of the proposed algorithm. Then, an ensemble of effective neighborhood approaches is developed, and a selfadaptive neighborhood structure selection mechanism is also embedded in PCRO to increase the search ability while maintaining population diversity. In addition, a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front. Furthermore,a kinetic-energy-based search procedure is developed to enhance the global search ability. Finally, the proposed algorithm is tested on sets of the instances that are generated based on realistic production. Through the analysis of experimental results, the highly effective performance of the proposed PCRO algorithm is favorably compared with several algorithms, with regards to both solution quality and diversity.

Intelligent Optimization Under Multiple Factories: Hybrid Flow Shop Scheduling Problem with Blocking Constraints Using an Advanced Iterated Greedy Algorithm

The distributed hybrid flow shop scheduling problem(DHFSP),which integrates distributed manufacturing models with parallel machines,has gained significant attention.However,in actual scheduling,some adjacent machines do not have buffers between them,resulting in blocking.This paper focuses on addressing the DHFSP with blocking constraints(DBHFSP)based on the actual production conditions.To solve DBHFSP,we construct a mixed integer linear programming(MILP)model for DBHFSP and validate its correctness using the Gurobi solver.Then,an advanced iterated greedy(AIG)algorithm is designed to minimize the makespan,in which we modify the Nawaz,Enscore,and Ham(NEH)heuristic to solve blocking constraints.To balance the global and local search capabilities of AIG,two effective inter-factory neighborhood search strategies and a swap-based local search strategy are designed.Additionally,each factory is mutually independent,and the movement within one factory does not affect the others.In view of this,we specifically designed a memory-based decoding method for insertion operations to reduce the computation time of the objective.Finally,two shaking strategies are incorporated into the algorithm to mitigate premature convergence.Five advanced algorithms are used to conduct comparative experiments with AIG on 80 test instances,and experimental results illustrate that the makespan and the relative percentage increase(RPI)obtained by AIG are 1.0%and 86.1%,respectively,better than the comparative algorithms.

Analysis of the chloroplast genomes of four Pinus species in Northeast China:Insights into hybrid speciation and identification of DNA molecular markers

Species of the Pinus genus provide a classical model for studying hybrid speciation.Although studies on two narrowly distributed species(P inus funebris and P.takahasii)concluded that they originated from two widespread species(P.sylvestris and P.densiflora)via hybrid speciation,the conclusion was based on a low number of informative restriction sites.In this study,we analyzed the sequences of four Pinus chloroplast(cp)genomes(P.sylvestris,P.densiflora,P.funebris and P.takahasii)to clarify whether hybrid speciation was involved.The complete cp-genomes of Pinus species ranged in size from 119,865 to 119,890 bp,similar to other Pinus species.Phylogenetic results based on the whole cp-genomes showed P.sylvestris clustered with P.funebris and P.takahasii,which suggested that P.sylvestris was the paternal parent in hybridization events.In an analysis of simple sequence repeats(SSRs),we detected a total of 69 SSRs repeats among the four Pinus cp-genomes;most were A or T bases.In addition,we identified divergent hotspot regions among the four Pinus cp-genomes(trnE-clpP,cemA-ycf4,petD-rpoA,psbD-trnT,and trnN-chlL),in P.sylvestris(psbD-trnT,trnN-chlL,psbB and rps8)and in P.densiflora(trnE-clpP,petD-rpoA,ycf3 intron,psbD-trnT,and trnN-chlL).The genome information found in this study provides new insights into hybrid speciation in P inus and contributes to a better understanding of the phylogenetic relationships within the Pinus genus.

Structure and regeneration status of woody species in the Munessa Forest,Southern Ethiopia

This study evaluates the structure and regeneration status of woody species in the Munessa Forest,a dry Afromontane forest in southern Ethiopia.Vegetation data were collected using a systematic sampling method.Density and distribution of seedlings,saplings and mature trees were assessed along an altitudinal gradient using quadrats of different sizes.The number of individuals,frequencies,heights and DBH of species>1 m and DBH>2.5 cm were recorded in altitudinal bands of 100 m.Analysis of the vegetation structure shows that the density of woody species decreases as DBH and height class increases.Basal area of stems with DBH>2.5 cm was 53.4 m^(2)ha^(−1).Population structure and regeneration patterns indicate a significant degradation of the forest due to anthropogenic disturbances.Regeneration was better for less valuable woody species than for species with economic and ecological value.This suggests a discontinuous recruitment of these species due to selective cutting of middle and higher diameter classes.Therefore,enrichment planting of high value,endangered species is necessary to maintain them as part of this forest.There is a need to develop and implement an effective forest management plan for sustainable use of these forest resources.

Preparation and Characterization of a New Desulfurizer and Its Performance on Removal of SO₂

Sulfur dioxide is one of the major pollutants resulting from fuel combustion. In this study, CaO and attapulgite were utilized as raw material for synthesizing CaO/attapulgite (CaO/ATP) desulfurizer. The physicochemical characteristics of CaO/ATP desulfurizer were evaluated by various techniques such as XRD, SEM, FT-IR. The performance of samples was studied in dynamic conditions. Major factors affecting on desulfurization such as weight ratio of CaO to total, types of modifiers, roasting time and temperature were investigated. The desulfurization agent synthesized under optimal synthesis conditions with CaO content of 30 wt% and NaOH modifier, and the desulfurization roasting time of 2 hours and roasting temperature of 600°C, exhibit sulfur tolerance of 10.15 wt%. This desulfurizer with excellent absorbency and catalysis of desulfurization, economical and?environment-friendly, could be especially useful in industrial applications.

Metagenomics reveals contrasting energy utilization efficiencies of captive and wild camels(Camelus ferus)

Captive conditions can affect the symbiotic microbiome of animals.In this study,we compared the structural and functional differences of the gastrointestinal microbiomes of wild Bactrian camels(Camelus ferus)between wild and captive populations,as well as their different host energy utilization performances through metagenomics.The results showed that wild-living camels harbored more microbial taxa related to the production of volatile fatty acids,fewer methanogens,and fewer genes encoding enzymes involved in methanogenesis,leading to higher energy utilization efficiency compared to that of captive-living camels.These findings suggest that the wild-living camel fecal microbiome demonstrates a series of adaptive characteristics that enable the host to adjust to a relatively barren field environment.Our study provides novel insights into the mechanisms of wildlife adaptations to habitats from the perspective of the microbiome.

Distributed Flow Shop Scheduling with Sequence-Dependent Setup Times Using an Improved Iterated Greedy Algorithm

To meet the multi-cooperation production demand of enterprises,the distributed permutation flow shop scheduling problem(DPFSP)has become the frontier research in the field of manufacturing systems.In this paper,we investigate the DPFSP by minimizing a makespan criterion under the constraint of sequence-dependent setup times.To solve DPFSPs,significant developments of some metaheuristic algorithms are necessary.In this context,a simple and effective improved iterated greedy(NIG)algorithm is proposed to minimize makespan in DPFSPs.According to the features of DPFSPs,a two-stage local search based on single job swapping and job block swapping within the key factory is designed in the proposed algorithm.We compare the proposed algorithm with state-of-the-art algorithms,including the iterative greedy algorithm(2019),iterative greedy proposed by Ruiz and Pan(2019),discrete differential evolution algorithm(2018),discrete artificial bee colony(2018),and artificial chemical reaction optimization(2017).Simulation results show that NIG outperforms the compared algorithms.

不同生境内啮齿动物对辽东栎幼苗的频率依赖性捕食及其对幼苗生长与存活的影响

啮齿动物对辽东栎(Quercus wutaishanica)种子的侵袭取决于种子的大小及其捕食频率。然而,啮齿动物对幼苗的捕食是否具有频率依赖性还不清楚。本研究在宁夏六盘山区辽东栎次生林内,选取林窗和林下两种生境,按5个种子大小频率(9:1,7:3,5:5,3:7和1:9)移栽萌发生根的辽东栎幼苗,探究啮齿动物对幼苗子叶的频率依赖性捕食及其对幼苗生长与存活的影响。研究结果表明:(i)幼苗移栽初期(1-7天),啮齿动物更偏好大种子建立幼苗的子叶。然而,移栽后8-60天,啮齿动物更偏好小种子建立幼苗的子叶,即表现为正频率依赖性捕食。(ii)尽管幼苗捕食率在林下高于林窗,但经过一个生长周期后,林窗内幼苗存活率高于林下(分别为5.40%和2.00%)。(iii)捕食子叶对辽东栎幼苗生长无显著影响,但顶芽被咬掉后幼苗各生长参数均显著降低(P<0.05)。这些结果不仅为啮齿动物和不同表型辽东栎幼苗的共存提供了新的见解,还揭示了栎树幼苗的更新策略。

极小种群野生植物梓叶槭的种实表型变异特征

表型变异是植物遗传变异与环境异质性相互作用的结果,是植物适应和进化的具体表现。为揭示极小种群植物梓叶槭(Acer catalpifolium)的种实表型在其适应环境过程中的变异特征,明确梓叶槭优质种源地,为该物种的保护提供基础数据,本研究以天然分布的5个小种群的11个种实性状为研究对象,采用巢式方差、变异系数、表型分化系数等多种指标,探讨了其种群间和种群内的表型变异。结果表明:梓叶槭种实表型性状在种群间和种群内均存在着显著的差异,种群内的变异(63.11%)大于种群间的变异(23.61%),种群间平均分化系数为27.23%,分化程度在槭树科植物中相对较大。种子厚度的平均变异系数最高(40.64%),其次是果柄长。翅果千粒重的平均变异系数最小(1.57%),是最稳定的种实性状。都江堰种群的表型多样性最丰富,平武种群的则最低;气象因子对梓叶槭种实表型性状的影响不显著。就种实表型性状而言,虽然雷波种群的翅果最大,平武种群的种子最大,同时两者均具有最大的种子厚度和质量均一度。故平武和雷波种群均可作为梓叶槭优质种质资源的候选地。

利用红外相机技术对四川王朗国家级自然保护区野生动物物种多样性的初步调查

本研究以四川王朗国家级自然保护区为研究区域,利用红外相机对保护区内的主要野生动物进行了初步调查,分析了该区域的物种多样性现状、相机数量和相机工作日与物种数量间的关系以及物种的相对丰富度。结果表明:42台红外相机共拍摄到物种独立照片1,793张,鉴定出野生动物25种,包括大熊猫(Ailuropoda melanoleuca)、四川羚牛(Budorcas tibetanus)和黄喉雉鹑(Tetraophasis szechenyii)3种国家一级重点保护野生动物,黑熊(Ursus thibetanus)、黄喉貂(Martes flavigula)、中华鬣羚(Capricornis milneedwardsii)、中华斑羚(Naemorhedus griseus)等8种国家二级重点保护野生动物。在相机数量增加到23台的时候拍摄到了本次记录的全部25种野生动物,并且在单台相机工作日达到180天时,物种数达到饱和。保护区内物种相对丰富度最高的是血雉(Ithaginis cruentus)(29.28)和毛冠鹿(Elaphodus cephalophus)(15.78);大熊猫的相对丰富度为8.09;红腹角雉(Tragopan temminckii)、中华鬣羚和黄喉雉鹑的相对丰富度在2–5之间;中华斑羚、勺鸡(Pucrasia macrolopha)、黑熊、四川羚牛和蓝马鸡(Crossoptilon auritum)的相对丰富度最低,不到1。综上所述,红外相机能够有效地对野生动物资源进行监测调查,对于相对丰富度较低的物种需要投入更多的精力,这些物种的栖息地保护对于自然保护区的发展至关重要。

Antimony(V) removal from water by iron-zirconium bimetal oxide: Performance and mechanism

A Fe-Zr binary oxide adsorbent has been successfully synthesized using a co-precipitation method. It showed a better performance for antimonate （Sb（V）） removal than zirconium oxide or amorphous ferric oxide. The experimental results showed that the Fe-Zr adsorbent has a capacity of 51 mg/g at an initial Sb（V） concentration of 10 mg/L at pH 7.0. Sb（V） adsorption on the Fe-Zr bimetal oxide is normally an endothermic reaction. Most of the Sb（V） adsorption took place within 3 hr and followed a pseudo second-order rate law. Co-existing anions such as SO42-, NO3 and C1- had no considerable effects on the Sb（V） removal; PO3- had an inhibitory effect to some extent at high concentration; while CO2- and SiO4- showed significant inhibitory effects when they existed in high concentrations. The mechanism of Sb（V） adsorption on the adsorbent was investigated using a combination of zeta potential measurements, XPS, Raman, FT-IR observations and SO42- release determination. The ionic strength dependence and zeta potential measurements indicated that inner-sphere surface complexes were formed after Sb（V） adsorption. Raman and XPS observations demonstrated that both Fe-OH and Zr-OH sites at the surface of the Fe-Zr adsorbent play important roles in the Sb（V） adsorption. FT-IR characterization and SO42- release determination further demonstrated that the exchange of SO2- with Sb（V） also could promote the adsorption process. In conclusion, this adsorbent showed high potential for future application in Sb（V） removal from contaminated water.

An error analysis and optimization method for combined measurement with binocular vision

The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively.

Differences in rheological and fractal properties of conditioned and raw sewage sludge

Rheological tests for raw and conditioned activated sludge （AS） or anaerobic digested sludge （ADS） show that power-law relationships can be used to describe the evolution of several rheological parameters, i.e., limiting viscosity （η∞）, yield stress （τy）, cohesion energy of the sludge network （Ec）, and storage modulus （G＇）, with total suspended solid （TSS） content in raw and conditioned sludge. A gel-like structure that behaves similar to weak-link flocs/aggregates was observed in AS and ADS. As derived from the double-logarithmic plots of G＇-TSS content, the mass fractal dimensions of the raw and conditioned AS or ADS flocs/aggregates were 2.70 and 2.53 or 2.85 and 2.79, respectively. The theological tests also indicate that both polymer conditioning and increased TSS content led to improved elastic behavior, cohesion energy, and yield stress of the sludge network, as well as expanded the corresponding linear viscoelastic range. The porosity of AS or ADS flocs/aggregates will be improved by polymer conditioning.