Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Deep Structure Optimization for Incremental Hierarchical Fuzzy Systems Using Improved Differential Evolution Algorithm

The optimization of the rule base of a fuzzy logic system (FLS) based on evolutionary algorithm has achievednotable results. However, due to the diversity of the deep structure in the hierarchical fuzzy system (HFS) and thecorrelation of each sub fuzzy system, the uncertainty of the HFS’s deep structure increases. For the HFS, a largenumber of studies mainly use fixed structures, which cannot be selected automatically. To solve this problem, thispaper proposes a novel approach for constructing the incremental HFS. During system design, the deep structureand the rule base of the HFS are encoded separately. Subsequently, the deep structure is adaptively mutated basedon the fitness value, so as to realize the diversity of deep structures while ensuring reasonable competition amongthe structures. Finally, the differential evolution (DE) is used to optimize the deep structure of HFS and theparameters of antecedent and consequent simultaneously. The simulation results confirm the effectiveness of themodel. Specifically, the root mean square errors in the Laser dataset and Friedman dataset are 0.0395 and 0.0725,respectively with rule counts of rules is 8 and 12, respectively.When compared to alternative methods, the resultsindicate that the proposed method offers improvements in accuracy and rule counts.

Furnace Temperature Curve Optimization Model Based on Differential Evolution Algorithm

When soldering electronic components onto circuit boards,the temperature curves of the reflow ovens across different zones and the conveyor belt speed significantly influence the product quality.This study focuses on optimizing the furnace temperature curve under varying settings of reflow oven zone temperatures and conveyor belt speeds.To address this,the research sequentially develops a heat transfer model for reflow soldering,an optimization model for reflow furnace conditions using the differential evolution algorithm,and an evaluation and decision model combining the differential evolution algorithm with the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)method.This approach aims to determine the optimal furnace temperature curve,zone temperatures of the reflow oven,and the conveyor belt speed.

Deformable Catalytic Material Derived from Mechanical Flexibility for Hydrogen Evolution Reaction

Deformable catalytic material with excellent flexible structure is a new type of catalyst that has been applied in various chemical reactions,especially electrocatalytic hydrogen evolution reaction(HER).In recent years,deformable catalysts for HER have made great progress and would become a research hotspot.The catalytic activities of deformable catalysts could be adjustable by the strain engineering and surface reconfiguration.The surface curvature of flexible catalytic materials is closely related to the electrocatalytic HER properties.Here,firstly,we systematically summarized self-adaptive catalytic performance of deformable catalysts and various micro–nanostructures evolution in catalytic HER process.Secondly,a series of strategies to design highly active catalysts based on the mechanical flexibility of lowdimensional nanomaterials were summarized.Last but not least,we presented the challenges and prospects of the study of flexible and deformable micro–nanostructures of electrocatalysts,which would further deepen the understanding of catalytic mechanisms of deformable HER catalyst.

Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm

This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

Strengthened Dominance Relation NSGA-Ⅲ Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.

High-speed penetration of ogive-nose projectiles into thick concrete targets:Tests and a projectile nose evolution model

The majority of the projectiles used in the hypersonic penetration study are solid flat-nosed cylindrical projectiles with a diameter of less than 20 mm.This study aims to fill the gap in the experimental and analytical study of the evolution of the nose shape of larger hollow projectiles under hypersonic penetration.In the hypersonic penetration test,eight ogive-nose AerMet100 steel projectiles with a diameter of 40 mm were launched to hit concrete targets with impact velocities that ranged from 1351 to 1877 m/s.Severe erosion of the projectiles was observed during high-speed penetration of heterogeneous targets,and apparent localized mushrooming occurred in the front nose of recovered projectiles.By examining the damage to projectiles,a linear relationship was found between the relative length reduction rate and the initial kinetic energy of projectiles in different penetration tests.Furthermore,microscopic analysis revealed the forming mechanism of the localized mushrooming phenomenon for eroding penetration,i.e.,material spall erosion abrasion mechanism,material flow and redistribution abrasion mechanism and localized radial upsetting deformation mechanism.Finally,a model of highspeed penetration that included erosion was established on the basis of a model of the evolution of the projectile nose that considers radial upsetting;the model was validated by test data from the literature and the present study.Depending upon the impact velocity,v0,the projectile nose may behave as undistorted,radially distorted or hemispherical.Due to the effects of abrasion of the projectile and enhancement of radial upsetting on the duration and amplitude of the secondary rising segment in the pulse shape of projectile deceleration,the predicted DOP had an upper limit.

Multiple Elite Individual Guided Piecewise Search-Based Differential Evolution

The differential evolution(DE)algorithm relies mainly on mutation strategy and control parameters'selection.To take full advantage of top elite individuals in terms of fitness and success rates,a new mutation operator is proposed.The control parameters such as scale factor and crossover rate are tuned based on their success rates recorded over past evolutionary stages.The proposed DE variant,MIDE,performs the evolution in a piecewise manner,i.e.,after every predefined evolutionary stages,MIDE adjusts its settings to enrich its diversity skills.The performance of the MIDE is validated on two different sets of benchmarks:CEC 2014 and CEC 2017(special sessions&competitions on real-parameter single objective optimization)using different performance measures.In the end,MIDE is also applied to solve constrained engineering problems.The efficiency and effectiveness of the MIDE are further confirmed by a set of experiments.

Damage evolution of rock-encased-backfill structure under stepwise cyclic triaxial loading

Rock-encased-backfill(RB)structures are common in underground mining,for example in the cut-andfill and stoping methods.To understand the effects of cyclic excavation and blasting activities on the damage of these RB structures,a series of triaxial stepwise-increasing-amplitude cyclic loading experiments was conducted with cylindrical RB specimens(rock on outside,backfill on inside)with different volume fractions of rock(VF=0.48,0.61,0.73,and 0.84),confining pressures(0,6,9,and 12 MPa),and cyclic loading rates(200,300,400,and 500 N/s).The damage evolution and meso-crack formation during the cyclic tests were analyzed with results from stress-strain hysteresis loops,acoustic emission events,and post-failure X-ray 3D fracture morphology.The results showed significant differences between cyclic and monotonic loadings of RB specimens,particularly with regard to the generation of shear microcracks,the development of stress memory and strain hardening,and the contact forces and associated friction that develops along the rock-backfill interface.One important finding is that as a function of the number of cycles,the elastic strain increases linearly and the dissipated energy increases exponentially.Also,compared with monotonic loading,the cyclic strain hardening characteristics are more sensitive to rising confining pressures during the initial compaction stage.Another finding is that compared with monotonic loading,more shear microcracks are generated during every reloading stage,but these microcracks tend to be dispersed and lessen the likelihood of large shear fracture formation.The transition from elastic to plastic behavior varies depending on the parameters of each test(confinement,volume fraction,and cyclic rate),and an interesting finding was that the transformation to plastic behavior is significantly lower under the conditions of 0.73 rock volume fraction,400 N/s cyclic loading rate,and 9 MPa confinement.All the findings have important practical implications on the ability of backfill to support underground excavations.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

Acute Kidney Injury in the Nephrology Department of the Brazzaville University Hospital: Epidemiological, Clinical and Evolutionary Aspects

Introduction: Acute kidney injury (AKI) is defined as a sudden and reversible deterioration in renal function. It is a life-threatening condition in hospitalized patients. Our objectives were to determine the prevalence of AKI in a nephrology department, list the causes, describe the evolutionary profile and identify the factors associated with death. Patients and Methods: We reviewed the records of patients hospitalised between 1 January 2016 and 31 October 2020 in the nephrology department of Brazzaville University Hospital. We included patients aged at least 18 years whose discharge diagnosis included the item AKI. Study variables were socio-demographic data, clinical and paraclinical signs, stage and type of AKI, etiology and evolutionary profile. Results: Of the 1823 patients hospitalised, 244 (13.38%) were hospitalised for AKI. Of these, 60.2% were boys and 39.8% girls, with an average age of 47 19 years. The average consultation time was 10 6.5 days. AKI was stage 3 in 69.57% of cases. It was functional, organic and obstructive in the order of 55.28%, 36.02% and 8.69%. Dialysis was indicated in 62 patients (38.51%) and performed in 24 patients (14.9%). In-hospital mortality was 27.95%, with an average hospital stay of 9.6 5.8 days. Metabolic acidosis and anemia were the main causes of death in 14.28% and 4.35% of patients respectively. Factors associated with death were male sex, socioeconomic level, coma, indication for dialysis and absence of dialysis, with a p Conclusion: AKI is more common in young adult males. Mortality is relatively low. Improving prognosis requires early management and access to dialysis.

Hydrochemical Characteristics and Evolution of Underground Brine in Lop Nur,Northwestern China

Lop Nur is located at the eastmost end of the Tarim Basin in Xinjiang,Northwestern China.This study reviews the hydrochemical characteristics and evolution of underground brine in Lop Nur,based on analytical data from 429 water samples(mainly brine).It is found that in the NE-SW direction,from the periphery to the Luobei sub-depression,while the hydrochemical type varies from the sodium sulfate subtype(S)to the magnesium sulfate subtype(M),the corresponding brine in the phase diagram transfers from the thenardite phase(Then)area,through the bloedite phase(Blo),epsomite phase(Eps),picromerite phase(Picro),finally reaching the sylvite phase(Syl)area.As for the degree of evolution,the sequence is the periphery<Luobei horizontally and the overlying glauberite brine<the underlying clastic brine vertically.It is concluded that the oxygen and hydrogen isotopic compositions of the brine have evidently been affected through the effects of evaporation and altitude,as well as the changes in local water circulation in recent years.Boron and chloride isotopic compositions show that the glauberite brine is formed under more arid conditions than the clastic one.The strontium isotopic composition indicates that the Lop Nur brine primarily originates from surface water;however,deep recharge may also be involved in the evolution of the brine,according to previous noble gas studies.It is confirmed that the brine in Lop Nur has become enriched with potassium prior to halite precipitation over the full course of the salt lake's evolution.Based on chemical compositions of brine from drillhole LDK01 and previous lithological studies,the evolution of the salt lake can be divided into three stages and it is inferred that the brine in Lop Nur may have undergone at least two significant concentration-dilution periods.

Identification of S-RNase genotype and analysis of its origin and evolutionary patterns in Malus plants

Identification of the S genotype of Malus plants will greatly promote the discovery of new genes,the cultivation and production of apple,the breeding of new varieties,and the origin and evolution of self-incompatibility in Malus plants.In this experiment,88 Malus germplasm resources,such as Aihuahong,Xishuhaitang,and Reguanzi,were used as materials.Seven gene-specific primer combinations were used in the genotype identification.PCR amplification using leaf DNA produced a single S-RNase gene fragment in all materials.The results revealed that 70 of the identified materials obtained a complete S-RNase genotype,while only one S-RNase gene was found in 18 of them.Through homology comparison and analysis,13 S-RNase genotypes were obtained:S_(1)S_(2)(Aihuahong,etc.),S_(1)S_(28)(Xixian Haitang,etc.),S_(1)S_(51)(Hebei Pingdinghaitang),S_(1)S_(3)(Xiangyangcun Daguo,etc.),S_(2)S_(3)(Zhaiyehaitang,etc.),S_(3)S_(51)(Xishan 1),S_(3)S_(28)(Huangselihaerde,etc.),S_(2)S_(28)(Honghaitang,etc.),S_(4)S_(28)(Bo 11),S_(7)S_(28)(Jiuquan Shaguo),S_(10)S_e(Dongchengguan 13),S_(10)S_(21)(Dongxiangjiao)and S_(3)S_(51)(Xiongyue Haitang).Simultaneously,the frequency of the S gene in the tested materials was analyzed.The findings revealed that different S genes had varying frequencies in Malus resources,as well as varying frequencies between intraspecific and interspecific.S_(3) had the highest frequency of 68.18%,followed by S_(1)(42.04%).In addition,the phylogenetic tree and origin evolution analysis revealed that the S gene differentiation was completed prior to the formation of various apple species,that cultivated species also evolved new S genes,and that the S_(50) gene is the oldest S allele in Malus plants.The S_(1),S_(29),and S_(33) genes in apple-cultivated species,on the other hand,may have originated in M.sieversii,M.hupehensis,and M.kansuensis,respectively.In addition to M.sieversii,M.kansuensis and M.sikkimensis may have also played a role in the origin and evolution of some Chinese apples.

Mg/MgO interfaces as efficient hydrogen evolution cathodes causing accelerated corrosion of additive manufactured Mg alloys:A DFT analysis

The corrosion rates of additive-manufactured Mg alloys are higher than their as-cast counterparts,possibly due to increased kinetics for the hydrogen evolution reaction on secondary phases,which may include oxide inclusions.Scanning Kelvin Probe Force Microscopy demonstrated that MgO inclusions could act as cathodes for Mg corrosion,but their low conductivity likely precludes this.However,the density of state calculations through density functional theory using hybrid HSE06 functional revealed overlapping electronic states at the Mg/MgO interface,which facilitates electron transfers and participates in redox reactions.Subsequent determination of the hydrogen absorption energy at the Mg/MgO interface reveals it to be an excellent catalytic site,with HER being found to be a factor of 23x more efficient at the interface than on metallic Mg.The results not only support the plausibility of the Mg/MgO interface being an effective cathode to the adjacent anodic Mg matrix during corrosion but also contribute to the understanding of the enhanced cathodic activities observed during the anodic dissolution of magnesium.

Evolution of molecular structure of TATB under shock loading from transient Raman spectroscopic technique

By combination of the transient Raman spectroscopic measurement and the density functional theoretical calculations,the structural evolution and stability of TATB under shock compression was investigated.Due to the improvement in synchronization control between two-stage light gas gun and the transient Raman spectra acquisition,as well as the sample preparation,the Raman peak of the N-O mode of TATB was firstly observed under shock pressure up to 13.6 GPa,noticeably higher than the upper limit of 8.5 GPa reported in available literatures.By taking into account of the continuous shift of the main peak and other observed Raman peaks,we did not distinguish any structural transition or any new species.Moreover,both the present Raman spectra and the time-resolved radiation of TATB during shock loading showed that TATB exhibits higher chemical stability than previous declaration.To reveal the detailed structural response and evolution of TATB under compression,the density functional theoretical calculations were conducted,and it was found that the pressure make N-O bond lengths shorter,nitro bond angles larger,and intermolecular and intra-molecular hydrogen bond interactions enhanced.The observed red shift of Raman peak was ascribed to the abnormal enhancement of H-bound effect on the scissor vibration mode of the nitro group.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

A Multi-Stage Differential-Multifactorial Evolutionary Algorithm for Ingredient Optimization in the Copper Industry

Ingredient optimization plays a pivotal role in the copper industry,for which it is closely related to the concentrate utilization rate,stability of furnace conditions,and the quality of copper production.To acquire a practical ingredient plan,which should exhibit long duration time with sufficient utilization and feeding stability for real applications,an ingredient plan optimization model is proposed in this study to effectively guarantee continuous production and stable furnace conditions.To address the complex challenges posed by this integer programming model,including multiple coupling feeding stages,intricate constraints,and significant non-linearity,a multi-stage differential-multifactorial evolution algorithm is developed.In the proposed algorithm,the differential evolutionary(DE)algorithm is improved in three aspects to efficiently tackle challenges when optimizing the proposed model.First,unlike traditional time-consuming serial approaches,the multifactorial evolutionary algorithm is utilized to optimize multiple complex models contained in the population of evolutionary algorithm caused by the feeding stability in a parallel manner.Second,a repair algorithm is employed to adjust infeasible ingredient lists in a timely manner.In addition,a local search strategy taking feedback from the current optima and considering the different positions of global optimum is developed to avoiding premature convergence of the differential evolutionary algorithm.Finally,the simulation experiments considering different planning horizons using real data from the copper industry in China are conducted,which demonstrates the superiority of the proposed method on feeding duration and stability compared with other commonly deployed approaches.It is practically helpful for reducing material cost as well as increasing production profit for the copper industry.

Insight into structure evolution of carbon nitrides and its energy conversion as luminescence

A series of carbon nitride(CN)materials represented by graphitic carbon nitride(g-C_(3)N_(4))have been widely used in bioimaging,biosensing,and other fields in recent years due to their nontoxicity,low cost,and high luminescent quantum efficiency.What is more attractive is that the luminescent properties such as wavelength and intensity can be regulated by controlling the structure at the molecular level.Hence,it is time to summarize the related research on CN structural evolution and make a prospect on future developments.In this review,we first summarize the research history and multiple structural evolution of CN.Then,the progress of improving the luminescence performance of CN through structural evolution was discussed.Significantly,the relationship between CN structure evolution and energy conversion in the forms of photoluminescence,chemiluminescence,and electrochemiluminescence was reviewed.Finally,key challenges and opportunities such as nanoscale dispersion strategy,luminous efficiency improving methods,standardization evaluation,and macroscopic preparation of CN are highlighted.

The Clausena lansium genome provides new insights into alkaloid diversity and the evolution of the methyltransferase family

Wampee(Clausena lansium)is an important evergreen fruit tree native to southern China that has a long history of use for medicinal purposes.Here,a chromosome-level genome of C.lansium was constructed with a genome size of 282.9 Mb and scaffold N50 of 30.75 Mb.The assembled genome contains 48.70%repetitive elements and 24,381 protein-coding genes.Comparative genomic analysis showed that C.lansium diverged from Aurantioideae 15.91-24.95 million years ago.Additionally,some expansive and specific gene families related to methyltransferase activity and S-adenosylmethionine-dependent methyltransferase activity were also identified.Further analysis indicated that N-methyltransferase(NMT)is mainly involved in alkaloid biosynthesis and O-methyltransferase(OMT)participates in the regulation of coumarin accumulation in wampee.This suggested that wampee's richness in alkaloids and coumarins might be due to the gene expansions of NMT and OMT.The tandem repeat event was one of the major reasons for the NMT expansion.Hence,the reference genome of C.lansium will facilitate the identification of some useful medicinal compounds from wampee resources and reveal their biosynthetic pathways.

Decoding Retinoblastoma: Differential Gene Expression

Background: Retinoblastoma, the most common intraocular pediatric cancer, presents complexities in its genetic landscape that necessitate a deeper understanding for improved therapeutic interventions. This study leverages computational tools to dissect the differential gene expression profiles in retinoblastoma. Methods: Employing an in silico approach, we analyzed gene expression data from public repositories by applying rigorous statistical models, including limma and de seq 2, for identifying differentially expressed genes DEGs. Our findings were validated through cross-referencing with independent datasets and existing literature. We further employed functional annotation and pathway analysis to elucidate the biological significance of these DEGs. Results: Our computational analysis confirmed the dysregulation of key retinoblastoma-associated genes. In comparison to normal retinal tissue, RB1 exhibited a 2.5-fold increase in expression (adjusted p Conclusions: Our analysis reinforces the critical genetic alterations known in retinoblastoma and unveils new avenues for research into the disease’s molecular basis. The discovery of chemoresistance markers and immune-related genes opens potential pathways for personalized treatment strategies. The study’s outcomes emphasize the power of in silico analyses in unraveling complex cancer genomics.