Genomic features of meiotic crossovers in diploid potato

Meiotic recombination plays an important role in genome evolution and crop improvement.Potato(Solanum tuberosum L.)is the most important tuber crop in the world,but research about meiotic recombination in potato is limited.Here,we resequenced 2163 F2 clones derived from five different genetic backgrounds and identified 41945 meiotic crossovers.Some recombination suppression in euchromatin regions was associated with large structural variants.We also detected five shared crossover hotspots.The number of crossovers in each F2 individual from the accession Upotato 1 varied from 9 to 27,with an average of 15.5,78.25%of which were mapped within 5 kb of their presumed location.We show that 57.1%of the crossovers occurred in gene regions,with poly-A/T,poly-AG,AT-rich,and CCN repeats enriched in the crossover intervals.The recombination rate is positively related with gene density,SNP density,Class II transposon,and negatively related with GC density,repeat sequence density and Class I transposon.This study deepens our understanding of meiotic crossovers in potato and provides useful information for diploid potato breeding.

Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

Pressure stimulated current in progressive failure process of combined coal-rock under uniaxial compression:Response and mechanism

Effective monitoring of the structural health of combined coal-rock under complex geological conditions by pressure stimulated currents(PSCs)has great potential for the understanding of dynamic disasters in underground engineering.To reveal the effect of this way,the uniaxial compression experiments with PSC monitoring were conducted on three types of coal-rock combination samples with different strength combinations.The mechanism explanation of PSCs are investigated by resistivity test,atomic force microscopy(AFM)and computed tomography(CT)methods,and a PSC flow model based on progressive failure process is proposed.The influence of strength combinations on PSCs in the progressive failure process are emphasized.The results show the PSC responses between rock part,coal part and the two components are different,which are affected by multi-scale fracture characteristics and electrical properties.As the rock strength decreases,the progressive failure process changes obviously with the influence range of interface constraint effect decreasing,resulting in the different responses of PSC strength and direction in different parts to fracture behaviors.The PSC flow model is initially validated by the relationship between the accumulated charges of different parts.The results are expected to provide a new reference and method for mining design and roadway quality assessment.

Coal-rock gas:Concept,connotation and classification criteria

In recent years,great breakthroughs have been made in the exploration and development of natural gas in deep coal-rock reservoirs in Junggar,Ordos and other basins in China.In view of the inconsistency between the industrial and academic circles on this new type of unconventional natural gas,this paper defines the concept of"coal-rock gas"on the basis of previous studies,and systematically analyzes its characteristics of occurrence state,transport and storage form,differential accumulation,and development law.Coal-rock gas,geologically unlike coalbed methane in the traditional sense,occurs in both free and adsorbed states,with free state in abundance.It is generated and stored in the same set of rocks through short distance migration,occasionally with the accumulation from other sources.Moreover,coal rock develops cleat fractures,and the free gas accumulates differentially.The coal-rock gas reservoirs deeper than 2000 m are high in pressure,temperature,gas content,gas saturation,and free-gas content.In terms of development,similar to shale gas and tight gas,coal-rock gas can be exploited by natural formation energy after the reservoirs connectivity is improved artificially,that is,the adsorbed gas is desorbed due to pressure drop after the high-potential free gas is recovered,so that the free gas and adsorbed gas are produced in succession for a long term without water drainage for pressure drop.According to buried depth,coal rank,pressure coefficient,reserves scale,reserves abundance and gas well production,the classification criteria and reserves/resources estimation method of coal-rock gas are presented.It is preliminarily estimated that the coal-rock gas in place deeper than 2000 m in China exceeds 30×10^(12)m^(3),indicating an important strategic resource for the country.The Ordos,Sichuan,Junggar and Bohai Bay basins are favorable areas for large-scale enrichment of coal-rock gas.The paper summarizes the technical and management challenges and points out the research directions,laying a foundation for the management,exploration,and development of coal-rock gas in China.

Suppression of current-induced membrane discharge of bipolar membranes by regulating ion crossover transport

Bipolar membranes(BPMs)exhibit the unique capability to regulate the operating environment of electrochemical system through the water dissociation-combination processes.However,the industrial utilization of BPMs is limited by instability and serious energy consumption.The current-induced membrane discharge(CIMD)at high-current conditions has a negative influence on the performance of anion-exchange membranes,but the underlying ion transport mechanisms in the BPMs remain unclear.Here,the CIMD-coupled Poisson-Nernst-Planck(PNP)equations are used to explore the ion transport mechanisms in the BPMs for both reverse bias and forward bias at neutral and acid-base conditions.It is demonstrated that the CIMD effect in the reverse-bias mode can be suppressed by enhancing the diffusive transport of salt counter-ions(Na^(+)and Cl^(−))into the BPMs,and that in the forward-bias mode with acid-base electrolytes can be suppressed by matching the transport rate of water counter-ions(H_(3)O^(+)and OH^(−)).Suppressing the CIMD can promote the water dissociation in the reverse-bias mode,as well as overcome the plateau of limiting current density and reduce the interfacial blockage of salt co-ions(Cl^(−))in the anion-exchange layer in the forward-bias mode with acid-base electrolytes.Our work highlights the importance of regulating ion crossover transport on improving the performance of BPMs.

Absence of BCS–BEC crossover in FeSe_(0.45)Te_(0.55) superconductor

In iron-based superconductor Fe(Se,Te), a flat band-like feature near the Fermi level was observed around the Brillouin zone center in the superconducting state. It is under debate whether this is the evidence on the presence of the BCS–BEC[Bardeen–Cooper–Schrieffer(BCS), Bose–Einstein condensation(BEC)] crossover in the superconductor. High-resolution laser-based angle-resolved photoemission measurements are carried out on high quality single crystals of FeSe_(0.45)Te_(0.55) superconductor to address the issue. By employing different polarization geometries, we have resolved and isolated the dyz band and the topological surface band, making it possible to study their superconducting behaviors separately. The dyz band alone does not form a flat band-like feature in the superconducting state and the measured dispersion can be well described by the BCS picture. We find that the flat band-like feature is formed from the combination of the dyz band and the topological surface state band in the superconducting state. These results reveal the origin of the flat band-like feature and rule out the presence of BCS-BEC crossover in Fe(Se,Te) superconductor.

Solving the Generalized Traveling Salesman Problem Using Sequential Constructive Crossover Operator in Genetic Algorithm

The generalized travelling salesman problem(GTSP),a generalization of the well-known travelling salesman problem(TSP),is considered for our study.Since the GTSP is NP-hard and very complex,finding exact solutions is highly expensive,we will develop genetic algorithms(GAs)to obtain heuristic solutions to the problem.In GAs,as the crossover is a very important process,the crossovermethods proposed for the traditional TSP could be adapted for the GTSP.The sequential constructive crossover(SCX)and three other operators are adapted to use in GAs to solve the GTSP.The effectiveness of GA using SCX is verified on some GTSP Library(GTSPLIB)instances first and then compared against GAs using the other crossover methods.The computational results show the success of the GA using SCX for this problem.Our proposed GA using SCX,and swap mutation could find average solutions whose average percentage of excesses fromthe best-known solutions is between 0.00 and 14.07 for our investigated instances.

Game Theory Optimization via Diverse Genetic Crossover Intelligence

Game theory is explored via a maze application where combinatorial optimization occurs with the objective of traversing through a defined maze with an aim to enhance decision support and locate the optimal travel sequence while minimizing computation time. This combinatorial optimization approach is initially demonstrated by utilizing a traditional genetic algorithm (GA), followed by the incorporation of artificial intelligence utilizing embedded rules based on domain-specific knowledge. The aim of this initiative is to compare the results of the traditional and rule-based optimization approaches with results acquired through an intelligent crossover methodology. The intelligent crossover approach encompasses a two-dimensional GA encoding where a second chromosome string is introduced within the GA, offering a sophisticated means for chromosome crossover amongst selected parents. Additionally, parent selection intelligence is incorporated where the best-traversed paths or population members are retained and utilized as potential parents to mate with parents selected within a traditional GA methodology. A further enhancement regarding the utilization of saved optimal population members as potential parents is mathematically explored within this literature.

Genetic Optimization via Diverse Crossover Intelligence

An intelligent crossover methodology within the genetic algorithm (GA) is explored within both mathematical and finite element arenas improving both design and solution convergence time. This improved intelligent crossover outperforms the traditional genetic algorithm combined with a rule-based approach utilizing domain specific knowledge developed by Webb, et al. [1]. The encoding of the improved crossover consists of two chromosome strings within the genetic algorithm where the first string represents the design or solution string, and the second string represents chromosome crossover string intelligence. This improved crossover methodology saves the best population members or designs evaluated from each generation and applies crossover chromosome intelligence to the best saved population members paired with globally selected parents. Enhanced features of this crossover methodology employ the random selection of the best designs from the prior generation as a potential parent coupled with alternating intelligence pairing methods. In addition to this approach, two globally selected parents possess the ability to mate utilizing crossover chromosome string intelligence maintaining the integrity of a global GA search. Overall, the final population following crossover employs both global and best generation design chromosome strings to maximize creativity while enhancing the solution search. This is a modification to a conventional GA that can be translated into GA encoding. This technique is explored initially through a Base 10 mathematical application followed by the examination of plate structural optimization considering stress and displacement constraints. Results from crossover intelligence are compared with the conventional genetic algorithm and from Webb, et al. [1] which illustrates the outcome of a two phase genetic optimization algorithm.

Genetic Crossover Operators for the Capacitated Vehicle Routing Problem

We study the capacitated vehicle routing problem(CVRP)which is a well-known NP-hard combinatorial optimization problem(COP).The aim of the problem is to serve different customers by a convoy of vehicles starting from a depot so that sum of the routing costs under their capacity constraints is minimized.Since the problem is very complicated,solving the problem using exact methods is almost impossible.So,one has to go for the heuristic/metaheuristic methods and genetic algorithm(GA)is broadly applied metaheuristic method to obtain near optimal solution to such COPs.So,this paper studies GAs to find solution to the problem.Generally,to solve a COP,GAs start with a chromosome set named initial population,and then mainly three operators-selection,crossover andmutation,are applied.Among these three operators,crossover is very crucial in designing and implementing GAs,and hence,numerous crossover operators were developed and applied to different COPs.There are two major kinds of crossover operators-blind crossovers and distance-based crossovers.We intend to compare the performance of four blind crossover and four distance-based crossover operators to test the suitability of the operators to solve the CVRP.These operators were originally proposed for the standard travelling salesman problem(TSP).First,these eight crossovers are illustrated using same parent chromosomes for building offspring(s).Then eight GAs using these eight crossover operators without any mutation operator and another eight GAs using these eight crossover operators with a mutation operator are developed.These GAs are experimented on some benchmark asymmetric and symmetric instances of numerous sizes and various number of vehicles.Our study revealed that the distance-based crossovers are much superior to the blind crossovers.Further,we observed that the sequential constructive crossover with and without mutation operator is the best one for theCVRP.This estimation is validated by Student’s t-test at 95%confidence level.We further determined a comparative rank of the eight crossovers for the CVRP.

Bandwidth Maximization Approach for Displaced Left-Turn Crossovers Coordination under Heterogeneous Traffic Conditions

As one of the UAIDs(unconventional alternative intersection designs),DLTs(displaced left-turn crossovers)have been presented to mitigate traffic congestion.Although,qualitatively and quantitatively isolated UAIDs outperform their conventional counterparts,there is no simplified procedure to consider the DLTs coordination.Hence,this research investigates the coordination of consecutive DLTs under heterogeneous traffic conditions.To achieve the optimal coordination and provide an efficient coordination control,a bandwidth maximization progression approach was used.Seeking the optimal offset for each pair of consecutive intersections to guarantee the green bandwidth waves along the coordinated corridor,a mixed-integer linear program was adopted.The optimization problem was formulated and solved based on the standard branch-and-bound technique.As a real-world study case,data of three typical intersections located in an arterial corridor in Cairo,Egypt was used.PTV-VISSIM as a microsimulation platform was employed to simulate and evaluate the different signal timing plans.However,to represent the heterogeneous traffic characteristics as close as possible to the reality,different simulation parameters were tuned and validated carefully.The results emphasized the undoubted improvement of coordinated DLTs by different operational performance indices.The total travel time,average delay,the number of stops per vehicle were obviously improved.

Saturated absorption spectrum of cesium micrometric-thin cell with suppressed crossover spectral lines

Micrometric-thin cells(MCs)with alkali vapor atoms have been valuable for research and applications of hyperfine Zeeman splitting and atomic magnetometers under strong magnetic fields.We theoretically and experimentally study the saturated absorption spectra using a 100-μm cesium MC,where the pump and probe beams are linearly polarized with mutually perpendicular polarizations,and the magnetic field is along the pump beam.Because of the distinctive thin chamber of the MC,crossover spectral lines in saturated absorption spectra are largely suppressed leading to clear splittings of hyperfine Zeeman transitions in experiments,and the effect of spatial magnetic field gradient is expected to be reduced.A calculation method is proposed to achieve good agreements between theoretical calculations and experimental results.This method successfully explains the suppression of crossover lines in MCs,as well as the effects of magnetic field direction,propagation and polarization directions of the pump/probe beam on saturated absorption spectrum.The saturated absorption spectrum with suppressed crossover lines is used for laser frequency stabilization,which may provide the potential value of MCs for high spatial resolution strong-field magnetometry with high sensitivity.

面向医工交叉人才培养的基础医学实验教学改革

“基础医学实验”是医工交叉人才培养“基础医学教育”环节中的一门核心专业类课程,而当前的基础医学实验教学模式并不适用于“医工交叉”的人才培养,亟须改革。借鉴我国现有基础医学实验教学模式,基于实验动物福利3R原则,“一鼠多用”,将解剖生理学与细胞生物学、生物化学、遗传学、形态学和免疫组织化学等实验进行整合,形成整合类实验项目,减少实验动物用量;引入虚拟实验,结合翻转课堂,以虚代实;将实验动物伦理纳入理论讲解范畴并通过教师的示范、在实验动物中心设立“小动物信箱”等方式,增强学生对于生命的敬畏。改革经验为国内工科院校医工交叉人才培养环节中基础医学实验课程的开设提供参考。

求解带容量约束车辆路径问题的改进遗传算法

为解决传统遗传算法求解带容量约束的车辆路径问题时收敛速度慢和局部搜索能力差的问题,对传统遗传算法提出一种改进策略。使用基于贪婪策略的启发式交叉算子加强算法接近最优解的能力,加快算法收敛速度,在变异操作中,引入最近邻搜索算子,缩小基因变异范围,使用单点局部插入算子提高算法的局部优化能力。采用精英选择和轮盘赌法结合的选择策略,保持种群多样性以加强算法的全局搜索能力。实例计算测试表明,与传统遗传算法相比,所提算法求解平均偏差降低了70.25%,求解时间减少了87.41%;与ALNS和AGGWOA算法相比,有更高的求解质量和更好的稳定性。

基于改进实数遗传算法的桑叶采摘机结构参数优化

针对遗传算法在求解桑叶采摘机结构优化问题时容易陷入局部最优和求解精度低等问题,提出一种改进实数遗传算法。首先是给出一种基于序的组合适应度函数的轮盘赌选择算子,该算子在轮盘赌的基础上,通过一个自适应变化的参数在两种适应度函数中选择一个,再去计算适应度值;然后设计一种基于方向的改进启发式交叉算子,该算子既保留两个父代个体中较优个体对子代个体的影响,又增加种群中最优个体对子代个体的影响,提高交叉产生有潜力子代的可能性。接着将改进算法应用于摇杆式桑叶采摘机的优化参数设计中,通过与其他算法作仿真对比试验验证算法的优越性,获得采摘机最优参数组合:行走结构速度为24 mm/s、拨动结构角速度为1.2 rad/s、采摘结构速度为440 mm/s,并由运行结果可知整机性能与优化前相比提高13%。最后用优化得到的参数组合进行实地试验,结果显示桑叶采摘机性能提升10.9%,误差较小为2.1%。可见,所提改进实数遗传算法是优化采摘机参数的一种有效算法。

轨道交通地下单渡线配线区间烟控实测及模拟研究

为了明确单渡线配线区间不同排烟设计方案的烟气控制效果,选取某地铁线路的单渡线配线区间,通过现场实测和烟流数值模拟分析,得到影响隧道区间整体排烟能力和气流组织分配的因素。结果表明:单渡线形式下,隧道通风系统的排烟能力主要取决于TVF风机,在无射流风机且仅靠TVF风机的情况下,采用2送2排模式,能满足火灾区段断面风速的要求,且均未发生烟流通过渡线串线的现象;TVF开启台数对起火区间的风速提升显著,但采用4送4排模式会导致烟气过站。

大设计观下殷正声的设计与实践探索

通过人物访谈、口述资料收集、文物对照分析,研究殷正声先生在中国社会发展的进程中,面对不同领域设计任务时,从设计跨界到系统整合的大设计实践的历程。作为上海老一辈设计师中的代表,殷正声先生长达半个多世纪的设计实践,是全产业链视角下上海工业设计发展的缩影。

基于改进蚁群算法的医药冷链物流运输路径优化

为解决大多数模型中制冷成本未考虑预冷参数而导致总成本求解精度不佳的问题,在制冷成本中加入预冷参数,得到新的总成本模型。基于遗传算法与IACO算法,提出了IGACO算法,此算法改进了传统蚁群算法的启发式因子与信息素更新方式,在此基础上加入交叉操作和变异因子,扩大算法搜索范围,进一步避免陷入局部最优的情况。经过试验对比分析,验证了IGACO算法所得出的最优路线、总成本、运行时间、收敛速度在一定程度上都优于其他算法。

基于混合简化粒子群算法的贝叶斯网络结构学习研究

为改善当前贝叶斯网络结构学习算法易陷入局部最优、过早收敛和寻优效率低的问题,进行了混合简化粒子群算法优化贝叶斯网络结构学习的研究。该算法利用最大支撑树约束搜索空间,并提出V-结构与条件相对平均熵相结合的初始定向策略,然后利用爬山策略建立初始粒子群,再利用改进的粒子群优化算法和遗传算法对初始种群迭代优化,在迭代过程中提出条件交叉和变异策略避免粒子的随机发散更新,并结合副粒子增缓策略更新未优化粒子,避免算法陷入局部最优。该算法与其他算法在4种标准网络下进行了仿真实验。实验结果表明,所提算法在ASIA、CAR、CHILD、ALARM网络中相比于MMHC、GS、BNC-PSO、PC-PSO算法BIC评分分别平均高5.775%、5.8%、0.475%、2.75%;汉明距离HD更低,正确率ACC更高。

试论述基于戏剧影视的当代雕塑跨界融合研究

文章旨在探讨基于戏剧影视下的当代雕塑跨界融合,研究跨界合作对于当代艺术发展的意义以及如何实现跨界整合与调度系统。在这个时代,艺术门类的多元包容和科技的发展让跨界合作成为必然趋势。文章还重点分析当代雕塑跨媒介交融的诸多表现形式,阐述雕塑与戏剧影视的跨界合作所带来的新的艺术作品;最后文章强调了跨界知识支持对于媒介间融合的重要性,同时呼吁更多不同领域之间的艺术家进行跨界合作,共同实现“总体艺术”的理想。