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.

Characterization and evaluation of brittleness of deep bedded sandstone from the perspective of the whole life-cycle evolution process

The quantitative determination and evaluation of rock brittleness are crucial for the estimation of excavation efficiency and the improvement of hydraulic fracturing efficiency.Therefore,a“three-stage”triaxial loading and unloading stress path is designed and proposed.Subsequently,six brittleness indices are selected.In addition,the evolution characteristics of the six brittleness indices selected are characterized based on the bedding effect and the effect of confining pressure.Then,the entropy weight method(EWM)is introduced to assign weight to the six brittleness indices,and the comprehensive brittleness index Bcis defined and evaluated.Next,the new brittleness classification standard is determined,and the brittleness differences between the two stress paths are quantified.Finally,compared with the previous evaluation methods,the rationality of the proposed comprehensive brittleness index Bcis also verified.These results indicate that the proposed brittleness index Bccan reflect the brittle characteristics of deep bedded sandstone from the perspective of the whole life-cycle evolution process.Accordingly,the method proposed seems to offer reliable evaluations of the brittleness of deep bedded sandstone in deep engineering practices,although further validation is necessary.

Research Progress and Prospects for the Evolution Process and Treatment Technology of Urban Black and Smelly Water

Water is an important material resource for human survival,and with the increasing development of society,the amount of urban industrial wastewater and domestic sewage is gradually increasing.However,wastewater collection and treatment facilities lag behind,so that a large number of wastewater enters urban water,making urban water become gradually black and smelly.In order to provide a good living environment for human beings,a large number of scholars actively explore the treatment technology of black and smelly water.In this paper,the evolution process of black and smelly water was introduced firstly,and then the treatment technology of black and smelly water was summarized.Finally,the prospects for the development of the treatment technology were put forward.

Unstable evolution of railway slope under the rainfall-vibration joint action

Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains.However,as two major factors affecting the stability of railway slopes,few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration.Based on the model test of sandy soil slope,the unstable evolution process of slope under locomotive vibration,rainfall,and rainfall-vibration joint action conditions was simulated in this paper.By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions,the change laws of pore pressure under the influence of vibration and rainfall were explored.The main control factors affecting the stability of slope structure under the joint action conditions were further defined.Combined with the slope failure phenomena under these three conditions,the causes of slope instability resulting from each leading factor were clarified.Finally,according to the above conclusions,the unstable evolution of the slope under the rainfall-vibration joint action was determined.The test results show that the unstable evolution process of sandy soil slope,under the rainfall-vibration joint action,can be divided into:rainfall erosion cracking,vibration promotion penetrating,and slope instability sliding three stages.In the process of slope unstable evolution,rainfall and vibration play the roles of inducing and promoting slide respectively.In addition,the deep cracks,which are the premise for the formation of the sliding surface,and the violent irregular fluctuation of soil pressure,which reflects the near penetration of the sliding surface,constitute the instability characteristics of the railway slope together.This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration,hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.

Erratum to:Microstructure and texture evolution of nonoriented silicon steel during the punching process

The original online version of this article unfortunately contained a mistake.The author’s name in the original online version is incorrect,which is:Xiang Fang,Wei Wang,François Brisset,Anne-Laure Helberg,and Thierry Baudin The correct version is given below.

Carbon Emission Effects Driven by Evolution of Chinese Dietary Structure from 1987 to 2020

Exploring carbon emission effects based on the evolution of residents’ dietary structure to achieve the carbon neutrality goal and mitigate climate change is an important task.This study took China as the research object(data excluding Hong Kong,Macao and Taiwan) and used the carbon emission coefficient method to quantitatively measure the food carbon emissions from 1987–2020,then analyzed the carbon emission effects under the evolution of dietary structure.The results showed that during the study period,the Chinese dietary structure gradually changed to a high-carbon consumption pattern.The dietary structure of urban residents developed to a balanced one,while that of rural residents developed to a high-quality one.During the study period,the per capita food carbon emissions and total food consumption of Chinese showed an increasing trend.The per capita food carbon emissions of residents in urban and rural showed an overall upward trend.The total food carbon emissions in urban increased significantly,while that in rural increased first and then decreased.The influence of beef and mutton on carbon emissions is the highest in dietary structure.Compared with the balanced dietary pattern,the food carbon emissions of Chinese residents had not yet reached the peak,but were evolving to a high-carbon consumption pattern.

Tuning electronic structure of RuO_(2)by single atom Zn and oxygen vacancies to boost oxygen evolution reaction in acidic medium

The poor stability of RuO_(2)electrocatalysts has been the primary obstacles for their practical application in polymer electrolyte membrane electrolyzers.To dramatically enhance the durability of RuO_(2)to construct activity-stability trade-off model is full of significance but challenging.Herein,a single atom Zn stabilized RuO_(2)with enriched oxygen vacancies(SA Zn-RuO_(2))is developed as a promising alternative to iridium oxide for acidic oxygen evolution reaction(OER).Compared with commercial RuO_(2),the enhanced Ru–O bond strength of SA Zn-RuO_(2)by forming Zn-O-Ru local structure motif is favorable to stabilize surface Ru,while the electrons transferred from Zn single atoms to adjacent Ru atoms protects the Ru active sites from overoxidation.Simultaneously,the optimized surrounding electronic structure of Ru sites in SA ZnRuO_(2)decreases the adsorption energies of OER intermediates to reduce the reaction barrier.As a result,the representative SA Zn-RuO_(2)exhibits a low overpotential of 210 mV to achieve 10 mA cm^(-2)and a greatly enhanced durability than commercial RuO_(2).This work provides a promising dual-engineering strategy by coupling single atom doping and vacancy for the tradeoff of high activity and catalytic stability toward acidic OER.

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.

100 W-class green hydrogen production from ammonia at a dual-layer electrode containing a Pt-Ir catalyst for an alkaline electrolytic process

Ammonia allows storage and transport of hydrogen over long distances and is an attractive potential hydrogen carrier.Electrochemical decomposition has recently been used for the conversion of ammonia to hydrogen and is regarded as a future technology for production of CO_(2)-free pure hydrogen.Herein,a heterostructural Pt-Ir dual-layer electrode is developed and shown to achieve successful long-term operation in an ammonia electrolyzer with an anion exchange membrane(AEM).This electrolyzer consisted of eight membra ne electrode assemblies(MEAs)with a total geometric area of 200 cm~2 on the anode side,which resulted in a hydrogen production rate of 25 L h~(-1).We observed the degradation in MEA performance attributed to changes in the anode catalyst layer during hydrogen production via ammonia electrolysis.Furthermore,we demonstrated the relationship between the ammonia oxidation reaction(AOR)and the oxygen evolution reaction(OER).

Evolution of human kidney allograft pathology diagnostics through 30 years of the Banff classification process

The second half of the previous century witnessed a tremendous rise in the number of clinical kidney transplants worldwide.This activity was,however,accompanied by many issues and challenges.An accurate diagnosis and appropriate management of causes of graft dysfunction were and still are,a big challenge.Kidney allograft biopsy played a vital role in addressing the above challenge.However,its interpretation was not standardized for many years until,in 1991,the Banff process was started to fill this void.Thereafter,regular Banff meetings took place every 2 years for the past 30 years.Marked changes have taken place in the interpretation of kidney allograft biopsies,diagnosis,and classification of rejection and other non-rejection pathologies from the original Banff 93 classification.This review attempts to summarize those changes for increasing the awareness and understanding of kidney allograft pathology through the eyes of the Banff process.It will interest the transplant surgeons,physicians,pathologists,and allied professionals associated with the care of kidney transplant patients.

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.

Reinforcement Learning in Process Industries:Review and Perspective

This survey paper provides a review and perspective on intermediate and advanced reinforcement learning(RL)techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms,including fundamental concepts like Markov decision processes and different approaches to RL, such as value-based, policy-based, and actor-critic methods, while also discussing the relationship between classical control and RL. It further reviews the wide-ranging applications of RL in process industries, such as soft sensors, low-level control, high-level control, distributed process control, fault detection and fault tolerant control, optimization,planning, scheduling, and supply chain. The survey paper discusses the limitations and advantages, trends and new applications, and opportunities and future prospects for RL in process industries. Moreover, it highlights the need for a holistic approach in complex systems due to the growing importance of digitalization in the process industries.

Microdynamic mechanical properties and fracture evolution mechanism of monzogabbro with a true triaxial multilevel disturbance method

The far-field microdynamic disturbance caused by the excavation of deep mineral resources and underground engineering can induce surrounding rock damage in high-stress conditions and even lead to disasters.However,the mechanical properties and damage/fracture evolution mechanisms of deep rock induced by microdynamic disturbance under three-dimensional stress states are unclear.Therefore,a true triaxial multilevel disturbance test method is proposed,which can completely simulate natural geostress,excavation stress redistribution(such as stress unloading,concentration and rotation),and subsequently the microdynamic disturbance triggering damaged rock failure.Based on a dynamic true triaxial test platform,true triaxial microdynamic disturbance tests under different frequency and amplitudes were carried out on monzogabbro.The results show that increasing amplitude or decreasing frequency diminishes the failure strength of monzogabbro.Deformation modulus gradually decreases during disturbance failure.As frequency and amplitude increase,the degradation rate of deformation modulus decreases slightly,disturbance dissipated energy increases significantly,and disturbance deformation anisotropy strengthens obviously.A damage model has been proposed to quantitatively characterize the disturbance-induced damage evolution at different frequency and amplitude under true triaxial stress.Before disturbance failure,the micro-tensile crack mechanism is dominant,and the micro-shear crack mechanism increases significantly at failure.With the increase of amplitude and frequency,the micro-shear crack mechanism increases.When approaching disturbance failure,the acoustic emission fractal dimension changes from a stable value to local large oscillation,and finally increases sharply to a high value at failure.Finally,the disturbance-induced failure mechanism of surrounding rock in deep engineering is clearly elucidated.

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Balancing the Quantum Speed Limit and Instantaneous Energy Cost in Adiabatic Quantum Evolution

Adiabatic time-optimal quantum controls are extensively used in quantum technologies to break the constraints imposed by short coherence times.However,practically it is crucial to consider the trade-off between the quantum evolution speed and instantaneous energy cost of process because of the constraints in the available control Hamiltonian.Here,we experimentally show that using a transmon qubit that,even in the presence of vanishing energy gaps,it is possible to reach a highly time-optimal adiabatic quantum driving at low energy cost in the whole evolution process.This validates the recently derived general solution of the quantum Zermelo navigation problem,paving the way for energy-efficient quantum control which is usually overlooked in conventional speed-up schemes,including the well-known counter-diabatic driving.By designing the control Hamiltonian based on the quantum speed limit bound quantified by the changing rate of phase in the interaction picture,we reveal the relationship between the quantum speed limit and instantaneous energy cost.Consequently,we demonstrate fast and high-fidelity quantum adiabatic processes by employing energy-efficient driving strengths,indicating a promising strategy for expanding the applications of time-optimal quantum controls in superconducting quantum circuits.

Multimodal Data-Driven Reinforcement Learning for Operational Decision-Making in Industrial Processes

Dear Editor, This letter proposes a multimodal data-driven reinforcement learning-based method for operational decision-making in industrial processes. Due to the frequent fluctuations of feedstock properties and operating conditions in the industrial processes, existing data-driven methods cannot effectively adjust the operational variables. In addition, multimodal data such as images, audio.

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.

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.