Optimal mining sequence for coal faces under a bedding slope:insight from landslide prevention

Repetitive mining beneath bedding slopes is identified as a critical factor in geomorphic disturbances, especially landslides and surface subsidence. Prior research has largely concentrated on surface deformation in plains due to multi-seam coal mining and the instability of natural bedding slopes, yet the cumulative impact of different mining sequences on bedding slopes has been less explored. This study combines drone surveys and geological data to construct a comprehensive three-dimensional model of bedding slopes. Utilizing FLAC3D and PFC2D models, derived from laboratory experiments, it simulates stress, deformation, and failure dynamics of slopes under various mining sequences. Incorporating fractal dimension analysis, the research evaluates the stability of slopes in relation to different mining sequences. The findings reveal that mining in an upslope direction minimizes disruption to overlying strata. Initiating extraction from lower segments increases tensile-shear stress in coal pillar overburdens, resulting in greater creep deformation towards the downslope than when starting from upper segments, potentially leading to localized landslides and widespread creep deformation in mined-out areas. The downslope upward mining sequence exhibits the least fractal dimensions, indicating minimal disturbance to both strata and surface. While all five mining scenarios maintain good slope stability under normal conditions, recalibrated stability assessments based on fractal dimensions suggest that downslope upward mining offers the highest stability under rainfall, contrasting with the lower stability and potential instability risks of upslope downward mining. These insights are pivotal for mining operations and geological hazard mitigation in multi-seam coal exploitation on bedding slopes.

基于D-optimal法优化香菇菌种培养基质配方的研究

为了筛选和优化香菇原种及栽培种的培养基质配方,采用D-optimal设计方法,以麦粒和木屑不同配比为原料优化香菇原种培养基质,以木屑、玉米芯、麸皮不同配比为原料优化香菇栽培种培养基质,以香菇品种L808作为供试菌种,分别以其菌丝萌发期、菌丝长速、满袋期为评价指标,通过对各评价指标的测量,建立了各配比基质与香菇培养基质配方响应值之间的回归模型,从而科学的优化出香菇原种及栽培种栽培基质的配方。试验结果表明,香菇原种栽培基质最优配方为50%麦粒+50%木屑;香菇栽培种栽培基质最优配方为37.69%玉米芯+23.33%麸皮+38.98%木屑。在以上2个配方的栽培基质接种后,香菇菌丝的生长旺盛,萌发期短、满袋期短,且理化性质较优,说明优化得到的栽培基质配方具有较高的可行性,该设计方法也在优化培养料配比上是科学并且可行的。

Mitochondrial targeting sequence of magnetoreceptor MagR:More than just targeting

Iron-sulfur clusters(ISC)are essential cofactors for proteins involved in various biological processes,such as electron transport,biosynthetic reactions,DNA repair,and gene expression regulation.ISC assembly protein IscA1(or MagR)is found within the mitochondria of most eukaryotes.Magnetoreceptor(MagR)is a highly conserved A-type iron and iron-sulfur cluster-binding protein,characterized by two distinct types of iron-sulfur clusters,[2Fe-2S]and[3Fe-4S],each conferring unique magnetic properties.MagR forms a rod-like polymer structure in complex with photoreceptive cryptochrome(Cry)and serves as a putative magnetoreceptor for retrieving geomagnetic information in animal navigation.Although the N-terminal sequences of MagR vary among species,their specific function remains unknown.In the present study,we found that the N-terminal sequences of pigeon MagR,previously thought to serve as a mitochondrial targeting signal(MTS),were not cleaved following mitochondrial entry but instead modulated the efficiency with which iron-sulfur clusters and irons are bound.Moreover,the N-terminal region of MagR was required for the formation of a stable MagR/Cry complex.Thus,the N-terminal sequences in pigeon MagR fulfil more important functional roles than just mitochondrial targeting.These results further extend our understanding of the function of MagR and provide new insights into the origin of magnetoreception from an evolutionary perspective.

Distributed Optimal Formation Control for Unmanned Surface Vessels by a Regularized Game-Based Approach

Dear Editor,This letter explores optimal formation control for a network of unmanned surface vessels(USVs).By designing an individual objective function for each USV,the optimal formation problem is transformed into a noncooperative game.Under this game theoretic framework,the optimal formation is achieved by seeking the Nash equilibrium of the regularized game.A modular structure consisting of a distributed Nash equilibrium seeker and a regulator is proposed.

Optimal synthesis of heat-integrated distillation configurations using the two-column superstructure

In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocolumn configuration.However,this approach frequently necessitates tedious enumeration procedures,resulting in a considerable computational burden.To surmount this formidable challenge,the present study introduces an innovative remedy:The proposition of a superstructure that encompasses both single-column and multiple two-column configurations.Additionally,a simultaneous optimization algorithm is applied to optimize both the process parameters and heat integration structures of the twocolumn configurations.The effectiveness of this approach is demonstrated through a case study focusing on industrial organosilicon separation.The results underscore that the superstructure methodology not only substantially mitigates computational time compared to exhaustive enumeration but also furnishes solutions that exhibit comparable performance.

Suspicious Activities Recognition in Video Sequences Using DarkNet-NasNet Optimal Deep Features

Human Suspicious Activity Recognition(HSAR)is a critical and active research area in computer vision that relies on artificial intelligence reasoning.Significant advances have been made in this field recently due to important applications such as video surveillance.In video surveillance,humans are monitored through video cameras when doing suspicious activities such as kidnapping,fighting,snatching,and a few more.Although numerous techniques have been introduced in the literature for routine human actions(HAR),very few studies are available for HSAR.This study proposes a deep convolutional neural network(CNN)and optimal featuresbased framework for HSAR in video frames.The framework consists of various stages,including preprocessing video frames,fine-tuning deep models(Darknet 19 and Nasnet mobile)using transfer learning,serial-based feature fusion,feature selection via equilibrium feature optimizer,and neural network classifiers for classification.Fine-tuning two models using some hit and trial methods is the first challenge of this work that was later employed for feature extraction.Next,features are fused in a serial approach,and then an improved optimization method is proposed to select the best features.The proposed technique was evaluated on two action datasets,Hybrid-KTH01 and HybridKTH02,and achieved an accuracy of 99.8%and 99.7%,respectively.The proposed method exhibited higher precision compared to existing state-ofthe-art approaches.

Mixture-optimal法优化红枣姜茶饮料配方工艺

目的:优化红枣姜茶饮料的配方,为凉茶饮料的品质提升提供理论依据和技术指导。方法:使用Mixture–optimal对红枣姜茶饮料配方工艺进行优化,通过方差分析、显著性检验等方法验证模型的合理性,得到回归方程,推测出红枣姜茶的最优配方。结果:最优配方为干姜6 g、红枣40 g、肉豆蔻4 g、肉桂3.557 4 g、山药28.442 5 g、百合24 g和红糖30 g。结论:减少干姜和肉豆蔻的添加量,增加红枣、百合和红糖的添加量,会使红枣姜茶的口感更好。

The Application of Nicotiana benthamiana as a Transient Expression Host to Clone the Coding Sequences of Plant Genes

Coding sequences (CDS) are commonly used for transient gene expression, in yeast two-hybrid screening, to verify protein interactions and in prokaryotic gene expression studies. CDS are most commonly obtained using complementary DNA (cDNA) derived from messenger RNA (mRNA) extracted from plant tissues and generated by reverse transcription. However, some CDS are difficult to acquire through this process as they are expressed at extremely low levels or have specific spatial and/or temporal expression patterns in vivo. These challenges require the development of alternative CDS cloning technologies. In this study, we found that the genomic intron-containing gene coding sequences (gDNA) from Arabidopsis thaliana, Oryza sativa, Brassica napus, and Glycine max can be correctly transcribed and spliced into mRNA in Nicotiana benthamiana. In contrast, gDNAs from Triticum aestivum and Sorghum bicolor did not function correctly. In transient expression experiments, the target DNA sequence is driven by a constitutive promoter. Theoretically, a sufficient amount of mRNA can be extracted from the N. benthamiana leaves, making it conducive to the cloning of CDS target genes. Our data demonstrate that N. benthamiana can be used as an effective host for the cloning CDS of plant genes.

AN OPTIMAL CONTROL PROBLEM FOR A LOTKA-VOLTERRA COMPETITION MODEL WITH CHEMO-REPULSION

In this paper we study a bilinear optimal control problem for a diffusive Lotka-Volterra competition model with chemo-repulsion in a bounded domain of ℝ^(ℕ),N=2,3.This model describes the competition of two species in which one of them avoid encounters with rivals through a chemo-repulsion mechanism.We prove the existence and uniqueness of weak-strong solutions,and then we analyze the existence of a global optimal solution for a related bilinear optimal control problem,where the control is acting on the chemical signal.Posteriorly,we derive first-order optimality conditions for local optimal solutions using the Lagrange multipliers theory.Finally,we propose a discrete approximation scheme of the optimality system based on the gradient method,which is validated with some computational experiments.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios.

Optimality在多个场景的时域仿真中高效性的深度研究

随着产品的速率及复杂性越来越高,针对仿真而言,除了要求仿真本身具有非常高的精度外,还对仿真的效率提出了很高的要求。具体到不同的信号模块,如DDR系统或者高速串行信号上,基于速率越来越高,越来越希望仿真给能出“最优解”的配置,例如DDR5颗粒的ODT的最优配置,高速信号芯片的加重均衡的最优配置等参数。那么如何在成百上千种组合的参数中选择相对最优的参数呢?传统的软件只能通过大量的扫描来进行筛选,在仿真时间和工程师的精力两方面都有比较大的耗费。使用Optimality软件,通过分享一些具体的仿真案例,展现软件的智能性,帮助使用者更快速挑选出最优的参数,使DDR及高速串行的仿真工作变得更加轻松,充分体现出Optimality软件的高效性。

Research on the Mechanism of Multi-Sensor Fusion Configuration Based on the Optimal Principle of the Vehicle

In order to address the issue of sensor configuration redundancy in intelligent driving,this paper constructs a multi-objective optimization model that considers cost,coverage ability,and perception performance.And then,combining a specific set of parameters,the NSGA-II algorithm is used to solve the multi-objective model established in this paper,and a Pareto front containing 24 typical configuration schemes is extracted after considering empirical constraints.Finally,using the decision preference method proposed in this paper that combines subjective and objective factors,decision scores are calculated and ranked for various configuration schemes from both cost and performance preferences.The research results indicate that the multi-objective optimization model established in this paper can screen and optimize various configuration schemes from the optimal principle of the vehicle,and the optimized configuration schemes can be quantitatively ranked to obtain the decision results for the vehicle under different preference tendencies.

Optimal Shape Factor and Fictitious Radius in the MQ-RBF:Solving Ill-Posed Laplacian Problems

To solve the Laplacian problems,we adopt a meshless method with the multiquadric radial basis function(MQRBF)as a basis whose center is distributed inside a circle with a fictitious radius.A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function.A sample function is interpolated by theMQ-RBF to provide a trial coefficient vector to compute the merit function.We can quickly determine the optimal values of the parameters within a preferred rage using the golden section search algorithm.The novel method provides the optimal values of parameters and,hence,an optimal MQ-RBF;the performance of the method is validated in numerical examples.Moreover,nonharmonic problems are transformed to the Poisson equation endowed with a homogeneous boundary condition;this can overcome the problem of these problems being ill-posed.The optimal MQ-RBF is extremely accurate.We further propose a novel optimal polynomial method to solve the nonharmonic problems,which achieves high precision up to an order of 10^(−11).

Distributed Minimum-Energy Containment Control of Continuous-Time Multi-Agent Systems by Inverse Optimal Control

Dear Editor,This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems(CTMASs)with respect to the minimum-energy performance index over fixed topology.To achieve this,we firstly investigate the optimal containment control problem using the inverse optimal control method,where all states of followers asymptotically converge to the convex hull spanned by the leaders while some quadratic performance indexes get minimized.A sufficient condition for existence of the distributed optimal containment control protocol is derived.By introducing the parametric algebraic Riccati equation(PARE),it is strictly proved that the global performance index can be used to approximate the standard minimumenergy performance index as the parameters tends to infinity.In consequence,the standard minimum-energy cooperative containment control can be solved by local steady state feedback protocols.

Deciphering TADF Mechanisms in Metal-Free Organic Emitters BrA-HBI:Utilizing Optimally Tuned Range-Separated Functionals for Insight

Metal-free organic emitters,characterized by their thermally activated delayed fluorescence(TADF)properties,offer considerable promise for the creation of highly efficient organic light-emitting diodes(OLEDs).Recently,Shao et al.presented a novel excited state intramolecular proton transfer(ESIPT)system BrA-HBI,demonstrating an emission quantum yield of up to 50%[Adv.Funct.Mater.32,2201256(2022)].However,many open issues cannot be answered solely by experimental means only and require detailed theoretical investigations.For instance,what causes the activation of TADF from the Keto^(*) tautomer and leads to fluorescence quenching in the Enol^(*)form?Herein,we provide a theoretical investigation on the TADF mechanism of the BrA-HBI molecule by optimally tuned range-separated functionals.Our findings reveal that ESIPT occurs in the BrA-HBI molecule.Moreover,we have disclosed the reason for the fluorescence quenching of the Enol^(*)form and determined that the T_(2)state plays a dominant role in the TADF phenomenon.In addition,double hybrid density functionals method was utilized to verify the reliability of optimally tuned range separation functionals on the calculation of the TADF mechanism in BrA-HBI.These findings not only provide a theoretical reference for development of highly efficient organic light-emitting diodes,but also demonstrate the effectiveness of the optimally tuned range-separated functionals in predicting the luminescence properties of TADF molecules.

Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control

Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the policy.In the policy improvement process,the policy gradient based method is employed.

A Special Issue“Planning and Optimal Operation of New-Type Power System”of Global Energy Interconnection

The power system,as an energy hub,plays a crucial role in the transformation of energy production and consumption.On July 19,2023,the International Energy Agency(IEA)released a Global Electricity Market Report for 2023-2024.This report indicates that the development of the world’s energy production is rapidly moving towards the critical point where the proportion of electricity generated from renewable sources surpasses that from non-renewable sources.

Pig pangenome graph reveals functional features of non‑reference sequences

Background The reliance on a solitary linear reference genome has imposed a significant constraint on our compre-hensive understanding of genetic variation in animals.This constraint is particularly pronounced for non-reference sequences(NRSs),which have not been extensively studied.Results In this study,we constructed a pig pangenome graph using 21 pig assemblies and identified 23,831 NRSs with a total length of 105 Mb.Our findings revealed that NRSs were more prevalent in breeds exhibiting greater genetic divergence from the reference genome.Furthermore,we observed that NRSs were rarely found within coding sequences,while NRS insertions were enriched in immune-related Gene Ontology terms.Notably,our investigation also unveiled a close association between novel genes and the immune capacity of pigs.We observed substantial differences in terms of frequencies of NRSs between Eastern and Western pigs,and the heat-resistant pigs exhibited a substantial number of NRS insertions in an 11.6 Mb interval on chromosome X.Additionally,we discovered a 665 bp insertion in the fourth intron of the TNFRSF19 gene that may be associated with the ability of heat tolerance in South-ern Chinese pigs.Conclusions Our findings demonstrate the potential of a graph genome approach to reveal important functional features of NRSs in pig populations.

Phylogenetic, phylogeographic and divergence time analysis of Anopheles subpictus species complex using ITS2 and COI sequences

Objective:To address the phylogenetic and phylogeographic relationship between different lineages of Anopheles(An.)subpictus species complex in most parts of the Asian continent by maximum utilization of Internal Transcriber Spacer 2(ITS2)and cytochrome C oxidase I(COI)sequences deposited at the GenBank.Methods:Seventy-five ITS2,210 COI and 26 concatenated sequences available in the NCBI database were used.Phylogenetic analysis was performed using Bayesian likelihood trees,whereas median-joining haplotype networks and time-scale divergence trees were generated for phylogeographic analysis.Genetic diversity indices and genetic differentiation were also calculated.Results:Two genetically divergent molecular forms of An.subpictus species complex corresponding to sibling species A and B are established.Species A evolved around 37-82 million years ago in Sri Lanka,India,and the Netherlands,and species B evolved around 22-79 million years ago in Sri Lanka,India,and Myanmar.Vietnam,Thailand,and Cambodia have two molecular forms:one is phylogenetically similar to species B.Other forms differ from species A and B and evolved recently in the above mentioned countries,Indonesia and the Philippines.Genetic subdivision among Sri Lanka,India,and the Netherlands is almost absent.A substantial genetic differentiation was obtained for some populations due to isolation by large geographical distances.Genetic diversity indices reveal the presence of a long-established stable mosquito population,at mutation-drift equilibrium,regardless of population fluctuations.Conclusions:An.subpictus species complex consists of more than two genetically divergent molecular forms.Species A is highly divergent from the rest.Sri Lanka and India contain only species A and B.