C#编程入门(四)——.NET Assembly

我们所开发出来的.NET软件被称为Assembly。本文将简单扼要地解说Assembly以及相关的主题。这里所谓的Assembly指的是可执行的软件,并不是指Assembly Language(汇编语言),读者千万不要混淆了。

Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

As computer graphics technology continues to advance,Collision Detection(CD)has emerged as a critical element in fields such as virtual reality,computer graphics,and interactive simulations.CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments,particularly within complex scenarios like virtual assembly,where both high precision and real-time responsiveness are imperative.Despite ongoing developments,current CD techniques often fall short in meeting these stringent requirements,resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems.To address these limitations,this study introduces a novel algorithm that leverages the capabilities of a Backpropagation Neural Network(BPNN)to optimize the structural composition of the Hybrid Bounding Volume Tree(HBVT).Through this optimization,the research proposes a refined Hybrid Hierarchical Bounding Box(HHBB)framework,which is specifically designed to enhance the computational efficiency and precision of CD processes.The HHBB framework strategically reduces the complexity of collision detection computations,thereby enabling more rapid and accurate responses to collision events.Extensive experimental validation within virtual assembly environments reveals that the proposed algorithm markedly improves the performance of CD,particularly in handling complex models.The optimized HBVT architecture not only accelerates the speed of collision detection but also significantly diminishes error rates,presenting a robust and scalable solution for real-time applications in intricate virtual systems.These findings suggest that the proposed approach offers a substantial advancement in CD technology,with broad implications for its application in virtual reality,computer graphics,and related fields.

Evaluating Methods of Visual Assistance for Workers to Improve Quality and Usability in Individualized Kitchen Cabinet Assembly

In times of digitalisation, visual assistance systems in assembly are increasingly important. The design of these assembly systems needs to be highly complex to meet the requirements. Due to the increasing number of variants in production processes, as well as shorter innovation and product life cycles, assistance systems should improve quality and reduce complexity of assembly processes. However, many large kitchen manufacturers still assemble kitchen cabinets manually, due to the high variety of components, such as rails and fittings. This paper focuses on the analysis and evaluation of virtual assistance systems to improve quality and usability in individualised kitchen cabinet assembly processes at a large German manufacturer. A solution is identified and detailed.

A high-quality chromosome-level genome assembly reveals genetics for important traits in eggplant

Eggplant(Solanum melongena L.)is an economically important vegetable crop in the Solanaceae family,with extensive diversity among landraces and close relatives.Here,we report a high-quality reference genome for the eggplant inbred line HQ-1315(S.melongena-HQ)using a combination of Illumina,Nanopore and 10X genomics sequencing technologies and Hi-C technology for genome assembly.The assembled genome has a total size of~1.17 Gb and 12 chromosomes,with a contig N50 of 5.26 Mb,consisting of 36,582 protein-coding genes.Repetitive sequences comprise 70.09%(811.14 Mb)of the eggplant genome,most of which are long terminal repeat(LTR)retrotransposons(65.80%),followed by long interspersed nuclear elements(LINEs,1.54%)and DNA transposons(0.85%).The S.melongena-HQ eggplant genome carries a total of 563 accession-specific gene families containing 1009 genes.In total,73 expanded gene families(892 genes)and 34 contraction gene families(114 genes)were functionally annotated.Comparative analysis of different eggplant genomes identified three types of variations,including singlenucleotide polymorphisms(SNPs),insertions/deletions(indels)and structural variants(SVs).Asymmetric SV accumulation was found in potential regulatory regions of protein-coding genes among the different eggplant genomes.Furthermore,we performed QTL-seq for eggplant fruit length using the S.melongena-HQ reference genome and detected a QTL interval of 71.29–78.26 Mb on chromosome E03.The gene Smechr0301963,which belongs to the SUN gene family,is predicted to be a key candidate gene for eggplant fruit length regulation.Moreover,we anchored a total of 210 linkage markers associated with 71 traits to the eggplant chromosomes and finally obtained 26 QTL hotspots.The eggplant HQ-1315 genome assembly can be accessed at http://eggplant-hq.cn.In conclusion,the eggplant genome presented herein provides a global view of genomic divergence at the whole-genome level and powerful tools for the identification of candidate genes for important traits in eggplant.

FLEXIBLE ASSEMBLY FIXTURING LAYOUT MODELING AND OPTIMIZATION BASED ON GENETIC ALGORITHM

There are many welding fixture layout design problems of flexible parts inbody-in-white assembly process, which directly cause body assemble variation. The fixture layoutdesign quality is mainly influenced by the position and quantity of fixture locators and clamps. Ageneral analysis model of flexible assembles deformation caused by fixture is set up based on'N-2-l' locating principle, in which the locator and damper are treated as the same fixture layoutelements. An analysis model for the flexible part deformation in fixturing is set up in order toobtain the optimization object function and constraints accordingly. The final fixture elementlayout could be obtained through global optimal research by using improved genetic algorithm, whicheffectively decreases fixture elements layout influence on flexible assembles deformation.

High-quality genome assembly of 'Cuiguan' pear (Pyrus pyrifolia) as a reference genome for identifying regulatory genes and epigenetic modifications responsible for bud dormancy

Dormancy-associated MADS-box(DAM)genes serve as crucial regulators of the endodormancy cycle in rosaceous plants.Although pear DAM genes have been identified previously,the lack of a high-quality reference genome and techniques to study gene function have prevented accurate genome-wide analysis and functional verification of such genes.Additionally,the contribution of other genes to the regulation of endodormancy release remains poorly understood.In this study,a high-quality genome assembly for'Cuiguan'pear(Pyrus pyrifolia),which is a leading cultivar with a low chilling requirement cultivated in China,was constructed using PacBio and Hi-C technologies.Using this genome sequence,we revealed that pear DAM genes were tandemly clustered on Chr8 and Chr15 and were differentially expressed in the buds between'Cuiguan'and the high-chilling-requirement cultivar'Suli'during the dormancy cycle.Using a virus-induced gene silencing system,we determined the repressive effects of DAM genes on bud break.Several novel genes potentially involved in the regulation of endodormancy release were identified by RNA sequencing and H3K4me3 chromatin immunoprecipitation sequencing analyses of‘Suli'buds during artificial chilling using the new reference genome.Our findings enrich the knowledge of the regulatory mechanism underlying endodormancy release and chilling requirements and provide a foundation for the practical regulation of dormancy release in fruit trees as an adaptation to climate change.

Research of the Assembly Model Based on Petri Net

Assembly model plans an important role in assembly sequence planning.Flexible assembly system (FAS) is a dis- crete event system (DES),so Petri net,as an important analytical tool for the DES,is used for modeling of an FAS.All of the feasible assembly sequences can be obtained by firing the Petri net model.In order to enhancing the efficiency of the assembly sequence planning,knowledge-based Petri net,combining an usual Petri net with expert’s knowledge and experiences,is proposed to con- struct the assembly model.So the feasible assembly sequences can be reduced greatly,and the optimum assembly sequence could be generated without the combinatorial explosion of solutions.

Optimization of assembly line balancing using genetic algorithm

In a manufacturing industry, mixed model assembly line(MMAL) is preferred in order to meet the variety in product demand. MMAL balancing helps in assembling products with similar characteristics in a random fashion. The objective of this work aims in reducing the number of workstations, work load index between stations and within each station. As manual contribution of workers in final assembly line is more, ergonomics is taken as an additional objective function. Ergonomic risk level of a workstation is evaluated using a parameter called accumulated risk posture(ARP), which is calculated using rapid upper limb assessment(RULA) check sheet. This work is based on the case study of an MMAL problem in Rane(Madras) Ltd.(India), in which a problem based genetic algorithm(GA) has been proposed to minimize the mentioned objectives. The working of the genetic operators such as selection, crossover and mutation has been modified with respect to the addressed MMAL problem. The results show that there is a significant impact over productivity and the process time of the final assembled product, i.e., the rate of production is increased by 39.5% and the assembly time for one particular model is reduced to 13 min from existing 18 min. Also, the space required using the proposed assembly line is only 200 m2 against existing 350 m2. Further, the algorithm helps in reducing workers fatigue(i.e., ergonomic friendly).

Genetic Algorithm for Concurrent Balancing of Mixed-Model Assembly Lines with Original Task Times of Models

The growing global competition compels manufacturing organizations to engage themselves in all productivity improvement activities. In this direction, the consideration of mixed-model assembly line balancing problem and implementing in industries plays a major role in improving organizational productivity. In this paper, the mixed model assembly line balancing problem with deterministic task times is considered. The authors made an attempt to develop a genetic algorithm for realistic design of the mixed-model assembly line balancing problem. The design is made using the originnal task times of the models, which is a realistic approach. Then, it is compared with the generally perceived design of the mixed-model assembly line balancing problem.

Parametric Tolerance Analysis of Mechanical Assembly Using FEA and Cost Competent Tolerance Synthesis Using Neural Network

Tolerance design plays an important role in the modern design process by introducing quality improvements and limiting manufacturing costs. Tolerance synthesis is a procedure that distributes assembly tolerances between components or distributes final part design tolerances between related tolerances. Traditional tolerance design assumes that all objects have rigid geometry, overlooking the role of inertia effects on flexible components of assembly. The variance is increasingly stacked up as components are assembled without considering deformation due to inertia effects. This study deals with the optimal tolerance design for an assembly simultaneously considering manufacturing cost, quality loss and deformation due to inertia effect. An application problem (motor assembly) is used to investigate the effectiveness and efficiency of the proposed methodology.

Adaptive genetic diversity of dominant species contributes to species co-existence and community assembly

The synthesis of evolutionary biology and community ecology aims to understand how genetic variation within one species can shape community properties and how the ecological properties of a community can drive the evolution of a species.A rarely explored aspect is whether the interaction of genetic variation and community properties depends on the species'ecological role.Here we investigated the interactions among environmental factors,species diversity,and the within-species genetic diversity of species with different ecological roles.Using high-throughput DNA sequencing,we genotyped a canopydominant tree species,Parashorea chinensis,and an understory-abundant species,Pittosporopsis kerrii,from fifteen plots in Xishuangbanna tropical seasonal rainforest and estimated their adaptive,neutral and total genetic diversity;we also surveyed species diversity and assayed key soil nutrients.Structural equation modelling revealed that soil nitrogen availability created an opposing effect in species diversity and adaptive genetic diversity of the canopy-dominant Pa.chinensis.The increased adaptive genetic diversity of Pa.chinensis led to greater species diversity by promoting co-existence.Increased species diversity reduced the adaptive genetic diversity of the dominant understory species,Pi.kerrii,which was promoted by the adaptive genetic diversity of the canopy-dominant Pa.chinensis.However,such relationships were absent when neutral genetic diversity or total genetic diversity were used in the model.Our results demonstrated the important ecological interaction between adaptive genetic diversity and species diversity,but the pattern of the interaction depends on the identity of the species.Our results highlight the significant ecological role of dominant species in competitive interactions and regulation of community structure.

Immune and Genetic Algorithm Based Assembly Sequence Planning

In this paper an assembly sequence planning model inspired by natural immune and genetic algorithm (ASPIG) based on the part degrees of freedom matrix (PDFM) is proposed, and a proto system — DSFAS based on the ASPIG is introduced to solve assembly sequence problem. The concept and generation of PDFM and DSFAS are also discussed. DSFAS can prevent premature convergence, and promote population diversity, and can accelerate the learning and convergence speed in behavior evolution problem.

An Optimal Solutions to Job Planning Problems in the Assembly Shop by Timed Petri Net

Job planning (JP) systems shop oriented provide a basis for job shop scheduling and control in organizing short term production activities. This paper presents a method based on timed Petri net (TPN) method that is used to program optimal JP for assembly shop. It includes three parts further. Firstly, an architecture of solutions to JP problems for any kind of shop oriented is presented to define a particular JP for a designated JP problem. Secondly, Petri net model is specified for aircraft part assembly processes. Finally, algorithms for optimizing generation of dynamic mechanism and a simulating case are then discussed. In comparison with traditional methods such as PERT or CPM, it is obviously convenient for planners or schedulers to schedule and manage assembly processes.

Ionic Liquid-Enhanced Assembly of Nanomaterials for Highly Stable Flexible Transparent Electrodes

The controlled assembly of nanomaterials has demon-strated significant potential in advancing technological devices.However,achieving highly efficient and low-loss assembly technique for nanomate-rials,enabling the creation of hierarchical structures with distinctive func-tionalities,remains a formidable challenge.Here,we present a method for nanomaterial assembly enhanced by ionic liquids,which enables the fabrication of highly stable,flexible,and transparent electrodes featuring an organized layered structure.The utilization of hydrophobic and non-volatile ionic liquids facilitates the production of stable interfaces with water,effectively preventing the sedimentation of 1D/2D nanomaterials assembled at the interface.Furthermore,the interfacially assembled nanomaterial monolayer exhibits an alternate self-climbing behavior,enabling layer-by-layer transfer and the formation of a well-ordered MXene-wrapped silver nanowire network film.The resulting composite film not only demonstrates exceptional photoelectric performance with a sheet resistance of 9.4Ωsq^(-1) and 93%transmittance,but also showcases remarkable environmental stability and mechanical flexibility.Particularly noteworthy is its application in transparent electromagnetic interference shielding materials and triboelectric nanogenerator devices.This research introduces an innovative approach to manufacture and tailor functional devices based on ordered nanomaterials.

Assembly Line Balancing Based on Double Chromosome Genetic Algorithm

Aiming at assembly line balancing problem,a double chromosome genetic algorithm(DCGA)is proposed to avoid trapping in local optimum,which is a disadvantage of standard genetic algorithm(SGA).In this algorithm,there are two chromosomes of each individual,and the better one,regarded as dominant chromosome,determines the fitness.Dominant chromosome keeps excellent gene segments to speed up the convergence,and recessive chromosome maintains population diversity to get better global search ability to avoid local optimal solution.When the amounts of chromosomes are equal,the population size of DCGA is half that of SGA,which significantly reduces evolutionary time.Finally,the effectiveness is verified by experiments.

A telomere-to-telomere genome assembly of Zhonghuang 13,a widely-grown soybean variety from the original center of Glycine max

Soybean(Glycine max)stands as a globally significant agricultural crop,and the comprehensive assembly of its genome is of paramount importance for unraveling its biological characteristics and evolutionary history.Nevertheless,previous soybean genome assemblies have harbored gaps and incompleteness,which have constrained in-depth investigations into soybean.Here,we present Telomere-to-Telomere(T2T)assembly of the Chinese soybean cultivar Zhonghuang 13(ZH13)genome,termed ZH13-T2T,utilizing PacBio Hifi and ONT ultralong reads.We employed a multi-assembler approach,integrating Hifiasm,NextDenovo,and Canu,to minimize biases and enhance assembly accuracy.The assembly spans 1,015,024,879 bp,effectively resolving all 393 gaps that previously plagued the reference genome.Our annotation efforts identified 50,564 high-confidence protein-coding genes,707 of which are novel.ZH13-T2T revealed longer chromosomes,421 not-aligned regions(NARs),112 structure variations(SVs),and a substantial expansion of repetitive element compared to earlier assemblies.Specifically,we identified 25.67 Mb of tandem repeats,an enrichment of 5S and 48S rDNAs,and characterized their genotypic diversity.In summary,we deliver the first complete Chinese soybean cultivar T2T genome.The comprehensive annotation,along with precise centromere and telomere characterization,as well as insights into structural variations,further enhance our understanding of soybean genetics and evolution.

Cryptanalysis of a Substitution-Permutation Network Using Gene Assembly in Ciliates

In this paper we provide a novel approach for breaking a significant class of block ciphers, the so-called SPN ciphers, using the process of gene assembly in ciliates. Our proposed scheme utilizes, for the first time, the Turing-powerful potential of gene assembly procedure of ciliated protozoa into the real world computations and has a fewer number of steps than the other proposed schemes to break a cipher. We elaborate notions of formal language theory based on AIR systems, which can be thought of as a modified version of intramolecular scheme to model the ciliate bio-operations, for construction of building blocks necessary for breaking the cipher, and based on these nature-inspired constructions which are as powerful as Turing machines, we propose a theoretical approach for breaking SPN ciphers. Then, we simulate our proposed plan for breaking these ciphers on a sample block cipher based on this structure. Our results show that the proposed scheme has 51.5 percent improvement over the best previously proposed nature-inspired scheme for breaking a cipher.

From self-assembly to quantum guiding: A review of magnetic atomic structures on noble metal surfaces

Recent advances in the study of magnetic atomic structures on noble metal surfaces are reviewed. These include one- dimensional strings, two-dimensional hexagonal superlattices, and novel structures stabilized by quantum guiding. The combined techniques of low-temperature scanning tunneling microscopy, kinetic Monte Carlo simulations, and ab initio calculations reveal that surface-state-mediated adatom-step and adatom-adatom interactions are the driving forces for self- assembly of these structures. The formation conditions are further discussed by comparing various experimental systems and the kinetic Monte Carlo simulations. Using scanning tunneling spectroscopy and tight-binding calculations together, we reveal that the spectra of these well-ordered structures have characteristic peaks induced by electronic scattering processes of the atoms within the local environment. Moreover, it is demonstrated that quantum confinement by means of nano-size corrals has significant influence on adatom diffusion and self-assembly, leading to a quantum-guided self-assembly.

Ontogenetic trait variation and metacommunity effects influence species relative abundances during tree community assembly

Predicting species abundance is one of the most fundamental pursuits of ecology.Combining the information encoded in functional traits and metacommunities provides a new perspective to predict the abundance of species in communities.We applied a community assembly via trait selection model to predict quadrat-scale species abundances using functional trait variation on ontogenetic stages and metacommunity information for over 490 plant species in a subtropical forest and a lowland tropical forest in Yunnan,China.The relative importance of trait-based selection,mass effects,and stochasticity in shaping local species abundances is evaluated using different null models.We found both mass effects and trait selection contribute to local abundance patterns.Trait selection was detectable at all studied spatial scales(0.04e1 ha),with its strength stronger at larger scales and in the subtropical forest.In contrast,the importance of stochasticity decreased with spatial scale.A significant mass effect of the metacommunity was observed at small spatial scales.Our results indicate that tree community assembly is primarily driven by ontogenetic traits and metacommunity effects.Our findings also demonstrate that including ontogenetic trait variation into predictive frameworks allows ecologists to infer ecological mechanisms operating in community assembly at the individual level.

Response and assembly of abundant and rare taxa in Zaopei under different combination patterns of Daqu and pit mud:from microbial ecology to Baijiu brewing microecosystem

The quality and aroma of strong-flavor Baijiu are mainly dependent on Daqu,pit mud(PM),and the interaction of both.However,little is known about how their combination patterns affect the microbiome and metabolome of Zaopei,especially the metabolic function of rare taxa.Here,an experiment on industrial size was designed to assess the effects of 6 combinations(3 kinds of Daqu×2 kinds of PM)on the composition and assembly of different taxa,as well as the flavor profile.The results showed that Zaopei's microbiota was composed of a few abundant taxa and enormous rare taxa,and rare bacterial and abundant fungal subcommunities were significantly affected by combination patterns.The assembly processes of abundant/rare taxa and bacterial/fungal communities were distinct,and environmental changes mediated the balance between stochastic and deterministic processes in rare bacteria assembly.Furthermore,specific combination patterns improved the flavor quality of Zaopei by enhancing the interspecies interaction,which was closely related to rare taxa,especially rare bacteria.These findings highlighted that rare bacteria might be the keystone in involving community interaction and maintaining metabolic function,which provided a scientific foundation for better understanding and regulating the brewing microbiota from the viewpoint of microbial ecology.