Electrochemical synthesis of value-added chemicals represents a promising approach to address multidisciplinary demands.This technology establishes direct pathways for electricity-to-chemical conversion while signific...Electrochemical synthesis of value-added chemicals represents a promising approach to address multidisciplinary demands.This technology establishes direct pathways for electricity-to-chemical conversion while significantly reducing the carbon footprint of chemical manufacturing.It simultaneously optimizes chemical energy storage and grid management,offering sustainable solutions for renewable energy utilization and overcoming geographical constraints in energy distribution.As a critical nexus between renewable energy and green chemistry,electrochemical synthesis serves dual roles in energy transformation and chemical production,emerging as a vital component in developing carbon-neutral circular economies.Focusing on key small molecules(H_(2)O,CO_(2),N_(2),O_(2)),this comment examines fundamental scientific challenges and practical barriers in electrocatalytic conversion processes,bridging laboratory innovations with industrial-scale implementation.展开更多
Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
Exploring high-performance electrocatalysts for the nitrate reduction reaction(NO_(3)RR)is crucial for environmental nitrate removal and ammonia synthesis.Single-atom collaboration with cluster can provide sufficient ...Exploring high-performance electrocatalysts for the nitrate reduction reaction(NO_(3)RR)is crucial for environmental nitrate removal and ammonia synthesis.Single-atom collaboration with cluster can provide sufficient active sites for catalysts to promote NO_(3)RR,yet the unclear synergistic effect between the two hinders their rational design.Herein,a series of Ir_(3)clusters and metal single atoms co-embedded in graphitic carbon nitride(g-CN)catalysts(Ir_(3)M1)were constructed,and the synergistic effects of Ir_(3)clusters and M1 single atoms on the NO_(3)RR catalytic mechanism and activity were systematically explored using density functional theory(DFT)calculations combined with machine learning.Comprehensive evaluations of structural stability and catalytic activity demonstrate that the synergy between single atoms and clusters effectively balances the adsorption energies of key intermediates,yielding exceptional catalytic performance(the limiting potential of Ir_(3)Ti_(1)can reach−0.22 V).Machine learning models further clarify the synergistic mechanism,where the geometric configurations of clusters serve as critical features for modulating the catalytic activity of single-atom sites,whereas the electronic structures of single atoms directly govern the reactivity of cluster sites.This DFT-machine learning approach provides theoretical guidelines for catalyst design and a predictive framework for efficient NO_(3)RR electrocatalysts.展开更多
Nowadays,higher requirements are put forward to the storage and utilization of energy,and supercapacitor is a kind of energy storage electronic devices.The resulting CA-N,with a specific surface area of 320.6 m^(2)/g ...Nowadays,higher requirements are put forward to the storage and utilization of energy,and supercapacitor is a kind of energy storage electronic devices.The resulting CA-N,with a specific surface area of 320.6 m^(2)/g and a pore volume of 0.28 cm^(3)/g,demonstrated a remarkable supercapacitance of 283.3 F/g.As a mesoporous material,CA-N offers numerous channels for the diffusion and absorption of electrolyte ions.Furthermore,it exhibited an impressive capacity retention rate of 98.48% after 5000 charge-discharge cycles.These outstanding electrochemical properties highlight the potential of CA-N for applications in energy storage.展开更多
The electrocaloric(EC)effect refers to the change in the polarization entropy and/or temperature of dielectric materials when an electric field is applied and removed.EC refrigeration has received increasing interest ...The electrocaloric(EC)effect refers to the change in the polarization entropy and/or temperature of dielectric materials when an electric field is applied and removed.EC refrigeration has received increasing interest as an alternative to conventional refrigeration technologies because it provides both high energy efficiency and zero global warming potential.In this review,we first introduce the thermodynamic fundamentals of the EC effect and the mechanism of EC refrigeration cycles.We then present recent advances in EC cooling technologies,from material improvements to device demonstrations,including a critical analysis of existing material and device characterization methodologies and a discussion of how to reliably measure the parameters of materials and devices.Finally,the current challenges and possible future prospects for EC cooling technology are outlined.展开更多
Radical cycloaddition reactions(RCRs) are highly effective methods for constructing complex carbo-and heterocycles,which are frequently encountered in natural products that exhibit intriguing biological properties and...Radical cycloaddition reactions(RCRs) are highly effective methods for constructing complex carbo-and heterocycles,which are frequently encountered in natural products that exhibit intriguing biological properties and hold significant potential for applications in medicinal chemistry.Radical-mediated cycloaddition strategies,which recycle radical character,are particularly appealing because they require only a catalytic amount of reagent and promise reactions with theoretically high atom economy.This review focuses on recent developments and synthetic applications in RCRs,with an emphasis on visible lightinduced radical photocycloaddition reactions(RPCRs),transition metal-catalyzed approaches,and small molecule-catalyzed methods.By highlighting some outstanding innovations and addressing current challenges,this review aims to identify potential areas for improvement.These advancements will provide more efficient pathways for the synthesis of natural product molecules and offer valuable insights for the development of new synthetic methodologies.展开更多
Electrochemical CO_(2) reduction reaction(CO_(2)RR) into valuable formate provides a strategy for carbon neutrality.Bismuth(Bi) catalysts,attributed to their appropriate energy barrier of OCHO*intermediate,have demons...Electrochemical CO_(2) reduction reaction(CO_(2)RR) into valuable formate provides a strategy for carbon neutrality.Bismuth(Bi) catalysts,attributed to their appropriate energy barrier of OCHO*intermediate,have demonstrated substantial potential for the advancement of electrocatalytic CO_(2) reduction to formate.However,due to the weak bonding of protons(H^(*)) of Bi,the available protonate of CO_(2) on Bi is insufficient,which limits the formation of OCHO^(*).Prediction by theoretical calculation,chlorine doping can effectively promote the dissociation of H_(2)O and thus achieve effective proton supply.We prepare chlorine-doped Bi(Cl-Bi) via an electrochemical conversion strategy for electroreduction of CO_(2) .An obvious improvement of faradaic efficiency(FE) of formate(96.7% at-0.95 V vs.RHE) can be achieved on Cl-Bi,higher than that of Bi(89.4%).Meanwhile,Cl-Bi has the highest formate production rate of 275 μmol h^(-1)cm^(-2)at-0.95 V vs.RHE,which is 1.2 times higher than that of Bi(224 μmol h^(-1)cm^(-2)).In situ characterizations and kinetic analysis reveal that chlorine doping promotes the activation of H_(2)O and supply sufficient protons to promote the protonation of CO_(2) to OCHO^(*),which is consistent with theoretical calculation.The study presents an effective strategy for rational design of highly efficient electrocatalysts to promote green chemical production.展开更多
Hf xTa 1-xC-based ceramics exhibit exceptional thermodynamic stability under extreme temperatures. However, their intrinsic brittleness raises significant concerns about their safe service in extreme environments. Her...Hf xTa 1-xC-based ceramics exhibit exceptional thermodynamic stability under extreme temperatures. However, their intrinsic brittleness raises significant concerns about their safe service in extreme environments. Here, we designed and fabricated HfTaC/W_(2) dual-phase ceramics with robust interface bonding through induction plasma spheroidization. During in situ transmission electron microscopy(TEM) mechanical testing, the dual-phase ceramics exhibited plastic deformation with a fracture strength of(7.6 ± 1.2) GPa and a strain of 23.8% ± 0.18% in nanopillar compression, and a fracture strain of 6.2% under tensile loading. The mechanism of plastic deformation in both compression and tensile tests is attributed to the interactions between dislocations and dual-phase interfaces, as well as the dislocation movement inside the W phase. Thus, our work demonstrates the enhanced plasticity of dual-phase HfTaC_(2)/W with a W network embedded in the HfTaC_(2) matrix than singlephase HfTaC_(2) and provides a paradigm for the development of advanced ceramics that combine strength with enhanced ductility for both functional and structural applications.展开更多
The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ...The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ simulations with varied protocols to evaluate the effectiveness of different descriptors in predicting mechanical properties across both low-and high-pressure regimes.Our findings demonstrate that conventional structural and configurational descriptors fail to correlate with the mechanical response following pressure release,whereas the activation energy descriptor exhibits robust linearity with shear modulus after correcting for pressure effects.Notably,the soft mode parameter emerges as an ideal and computationally efficient alternative for capturing this mechanical behavior.These findings provide critical insights into the influence of pressure on glassy properties,integrating the distinct features of compressed glasses into a unified theoretical framework.展开更多
This review draws attention to the innovative use of arrowroot(Maranta arundinacea)fiber as a unique and underutilized biomass source for nanocrystalline cellulose(NCC)-based nanocomposites,presenting a noteworthy alt...This review draws attention to the innovative use of arrowroot(Maranta arundinacea)fiber as a unique and underutilized biomass source for nanocrystalline cellulose(NCC)-based nanocomposites,presenting a noteworthy alternative to extensively researched materials like wood pulp,bacterial cellulose,and chemically modified NCCs.In contrast to traditional sources,arrowroot possesses a naturally elevated cellulose and diminished lignin content,facilitating more effective NCC extraction requiring reduced chemical input and enabling environmentally friendly processing techniques.The review evaluates the performance of arrowroot-derived nanocomposites against systems documented in the literature,including NCC-based shape memory composites and nanoparticle-reinforced films,demonstrating enhanced tensile strength,improved moisture barrier properties,and thermal stability,as well as potential piezoelectric response.This study recognizes arrowroot as a viable option in the biomass-based nanocellulose sector,providing ecological and functional benefits while tackling significant issues such as process scalability and feedstock variability,thereby offering important insights for the advancement of sustainable materials.展开更多
Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have g...Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have garnered considerable attention due to their softness,conformability,and biocompatibility.However,several challenges remain,including imperfect skin-device interfaces,limited breathability,and insufficient mechanoelectrical stability.On-skin epidermal electronics,distinguished by their excellent conformability,breathability,and mechanoelectrical robustness,offer a promising solution for high-fidelity,long-term health monitoring.These devices can seamlessly integrate with the human body,leading to transformative advancements in future personalized healthcare.This review provides a systematic examination of recent advancements in on-skin epidermal electronics,with particular emphasis on critical aspects including material science,structural design,desired properties,and practical applications.We explore various materials,considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics.We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring,including adhesiveness,breathability,and mechanoelectrical stability.Additionally,we summarize the diverse applications of these devices in monitoring biophysical and physiological signals.Finally,we address the challenges facing these devices and outline future prospects,offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.展开更多
Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudi...Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudinal or sensor-based data,which are not always available in public health contexts.In this article,we propose a novel proto-DT framework for mortality prediction in respiratory health using a large-scale categorical biomedical dataset.This dataset contains 415,711 severe acute respiratory infection cases from the Brazilian Unified Health System,including both COVID-19 and non-COVID-19 patients.Four classification models—extreme gradient boosting(XGBoost),logistic regression,random forest,and a deep neural network(DNN)—are trained using cost-sensitive learning to address class imbalance.The models are evaluated using accuracy,precision,recall,F1-score,and area under the curve(AUC)related to the receiver operating characteristic(ROC).The framework supports simulated interventions by modifying selected inputs and recalculating predicted mortality.Additionally,we incorporate multiple correspondence analysis and K-means clustering to explore model sensitivity.A Python library has been developed to ensure reproducibility.All models achieve AUC-ROC values near or above 0.85.XGBoost yields the highest accuracy(0.84),while the DNN achieves the highest recall(0.81).Scenario-based simulations reveal how key clinical factors,such as intensive care unit admission and oxygen support,affect predicted outcomes.The proposed proto-DT framework demonstrates the feasibility of mortality prediction and intervention simulation using categorical data alone.This framework provides a foundation for data-driven explainable DTs in public health,even in the absence of time-series data.展开更多
Heat exchangers play a crucial role in thermal energy systems,with their performance directly impacting efficiency,cost,and environmental impact.Apowerful technique for performance improvement can be given by passive ...Heat exchangers play a crucial role in thermal energy systems,with their performance directly impacting efficiency,cost,and environmental impact.Apowerful technique for performance improvement can be given by passive enhancement strategies,which are characterized by their dependability and minimal external power requirements.This comprehensive review critically assesses recent advancements in such passive methods to evaluate their heat transfer mechanisms,performance characteristics,and practical implementation challenges.Our methodology involves a systematic and comprehensive analysis of various heat transfer enhancement techniques,including surface modifications,extended surfaces,swirl flow devices,and tube inserts.This approach synthesizes and integrates findings from a broad spectrum of experimental investigations and numerical simulations to establish a cohesive understanding of their performance characteristics and underlyingmechanisms.Based on the findings,passive heat transfer techniques result in significant improvements in thermal performance;for instance,corrugated and roughened surfaces increase the heat transfer coefficient by 50%–200%,and advanced insert geometries,such as modified twisted tapes,can increase it by more than 300%,typically accompanied by significant pressure-drop penalties.However,an important finding is the general trade-off between enhanced heat transfer and higher frictional loss,which requires optimization depending on the applications.Finally,this review also provides recommendations that will document the gaps of various passive techniques in heat exchangers to future address.展开更多
The biodegradable polybutylene succinate(PBS)material offers a sustainable solution for a circular economy to address the global issue of marine plastic waste.Its cross-linkage with non-biodegradable xanthan gum(XG)bi...The biodegradable polybutylene succinate(PBS)material offers a sustainable solution for a circular economy to address the global issue of marine plastic waste.Its cross-linkage with non-biodegradable xanthan gum(XG)biopolymer to ameliorate residual granitic soil(RGS)in arid and semiarid regions can significantly mitigate soil erosion.This study investigates the enhancement of RGS by cross-linking the PBS and XG biopolymers.Employing a multitude of geotechnical tests(liquid limit,linear shrinkage,specific gravity,compaction,and UCS tests)at 3 d,28 d,and 90 d of steam-curing at a controlled temperature of 16℃,the outcomes were validated through scanning electron microscopy(SEM),thermogravimetric analysis(TGA),Fourier transform infrared spectroscopy(FTIR),and Brunauer-Emmett-Teller(BET)analyses.In addition,a comprehensive experimental database of 150 tests and nine parameters from the current study was utilized to model the UCS90-d(i.e.unconfined compressive strength after 90 d of curing)of the PBS-XG-treated RGS mixtures by deploying the random forest(RF)and eXtreme Gradient Boost(XGBoost)methods.The results found that the two biopolymers significantly improve the mechanical properties of RGS,with optimal UCS achieved at specific dosages(0.4PBS,1.5XG,and 0.2PBS+1.5XG dosage levels)and curing times.The UCS of PBS-XG-treated RGS showed up to a 57%increase after 90 d of curing.Furthermore,SEM and FTIR analyses revealed the formation of stronger microstructures and chemical bonds,respectively,whereas BET analysis indicated that pore volume and diameter are critical in affecting UCS.The proposed RF model outperformed XGBoost in predictive accuracy and generalization,demonstrating robustness and versatility.Moreover,SHAP values highlighted the significant impact of input parameters on UCS90-d,with curing time and specific material properties being key determinants.The study concludes with the proposal of a novel PyCharm intuitive graphical user interface as a"UCS Prediction App"for engineers and practitioners to forecast the UCS90-d of granitic residual soil.展开更多
α-Chiral amides are common in pharmaceuticals,agrochemicals,natural products,and peptides,prompting the need for new synthetic methods.Here,we introduce a nickel-catalyzed asymmetric reductive amidation method to syn...α-Chiral amides are common in pharmaceuticals,agrochemicals,natural products,and peptides,prompting the need for new synthetic methods.Here,we introduce a nickel-catalyzed asymmetric reductive amidation method to synthesizeα-chiral amides from benzyl ammonium salts and isocyanates.The key to success is using a chiral 2,2-bipyridine ligand(-)-Ph-SBpy,enabling high yield(up to 95%)and enantiomeric ratio(up to 98:2 er)under mild conditions.Addition of phenol prevents isocyanate polymerization by reversibly forming a carbamate intermediate,enhancing selectivity and efficiency.The synthetic utility is showcased through transformations of the enantioenriched amides,and the mechanism and enantioselectivity are supported by experimental and computational studies.展开更多
Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is p...Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.展开更多
Objective Pharmacopoeias regulate the manufacture of potentised pharmaceutical preparations used in different branches of complementary and integrative medicine.The physicochemical properties and biological activity o...Objective Pharmacopoeias regulate the manufacture of potentised pharmaceutical preparations used in different branches of complementary and integrative medicine.The physicochemical properties and biological activity of these preparations are often investigated in preclinical research,yet no guidelines for experimental research currently exist in this area.The present PrePoP guidelines aim to provide recommendations to promote high-quality,statistically sound,and reproducible preclinical research on potentised preparations.Methods Input was gathered from researchers nominated by the relevant scientific societies using a simplified Delphi consensus approach covering the most relevant aspects of basic research methodology in the field including appropriate controls,sample preparation and handling,and statistics.After three rounds of feedback,a consensus was finally reached on the most important aspects and considerations for conducting high-quality research on potentised preparations.Results We present a series of recommendations on a range of topics including experimental controls,system stability,blinding and randomisation,environmental influences,and procedures for the preparation of potentised samples and controls,and we address some specific challenges of this research field.Conclusion This expert consensus process resulted in a robust set of methodological guidelines for research on potentised preparations and provides a valuable framework that will inform and improve the quality of subsequent research in this emerging field.展开更多
Altered biomechanics due to amputation can contribute to substantial limitations,influencing sporting activities.Individuals with lower extremity amputations or congenital lower limb deficiency are encouraged to parti...Altered biomechanics due to amputation can contribute to substantial limitations,influencing sporting activities.Individuals with lower extremity amputations or congenital lower limb deficiency are encouraged to participate in para-sports.However,to compete in Paralympic sports,the candidate must have an impairment that results in lower extremity loss of function and meets or exceeds the sport's minimum impairment criteria(MIC).This review will focus on the MIC for competitive wheelchair tennis.Limb deficiency is known as one of the MIC used to regulate participation in competitive para-sports since it impacts gait,kinematics,and biomechanics of both the upper and lower body.Notwithstanding,it is questionable whether the MIC concerning limb deficiency is set at the correct level for determining eligibility for participating in Paralympic sports.This study aims to provide an overview of the evidence examining the impact of different partial foot amputation(PFA)levels on gait as a proxy for sporting performance.This scoping review will be based on a 6-step methodological framework and Preferred Reporting Items for Systematic Reviews and Meta-Analysis,extension for scoping reviews(PRISMA-ScR).Studies will be selected from PubMed,Embase,CINAHL,and SPORTDiscus.Two authors will screen the titles/abstracts independently.Selected studies will be scrutinised,and the same authors will extract data.Findings will be relevant to informing the evidence-based development of MIC for lower limb impairment after PFA and may be extrapolated to specific Paralympic sports,including wheelchair tennis.Results will be disseminated through scientific publications and conferences to audiences interested in Paralympic sports.展开更多
Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Num...Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
文摘Electrochemical synthesis of value-added chemicals represents a promising approach to address multidisciplinary demands.This technology establishes direct pathways for electricity-to-chemical conversion while significantly reducing the carbon footprint of chemical manufacturing.It simultaneously optimizes chemical energy storage and grid management,offering sustainable solutions for renewable energy utilization and overcoming geographical constraints in energy distribution.As a critical nexus between renewable energy and green chemistry,electrochemical synthesis serves dual roles in energy transformation and chemical production,emerging as a vital component in developing carbon-neutral circular economies.Focusing on key small molecules(H_(2)O,CO_(2),N_(2),O_(2)),this comment examines fundamental scientific challenges and practical barriers in electrocatalytic conversion processes,bridging laboratory innovations with industrial-scale implementation.
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
基金the financial support from the Shandong Province colleges and universities youth innovation technology plan innovation team project(2022KJ285)the Natural Science Foundation of Shandong Province(ZR2022QE076)+1 种基金the National Natural Science Foundation of China(52202092)the Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China(2023KJ104).
文摘Exploring high-performance electrocatalysts for the nitrate reduction reaction(NO_(3)RR)is crucial for environmental nitrate removal and ammonia synthesis.Single-atom collaboration with cluster can provide sufficient active sites for catalysts to promote NO_(3)RR,yet the unclear synergistic effect between the two hinders their rational design.Herein,a series of Ir_(3)clusters and metal single atoms co-embedded in graphitic carbon nitride(g-CN)catalysts(Ir_(3)M1)were constructed,and the synergistic effects of Ir_(3)clusters and M1 single atoms on the NO_(3)RR catalytic mechanism and activity were systematically explored using density functional theory(DFT)calculations combined with machine learning.Comprehensive evaluations of structural stability and catalytic activity demonstrate that the synergy between single atoms and clusters effectively balances the adsorption energies of key intermediates,yielding exceptional catalytic performance(the limiting potential of Ir_(3)Ti_(1)can reach−0.22 V).Machine learning models further clarify the synergistic mechanism,where the geometric configurations of clusters serve as critical features for modulating the catalytic activity of single-atom sites,whereas the electronic structures of single atoms directly govern the reactivity of cluster sites.This DFT-machine learning approach provides theoretical guidelines for catalyst design and a predictive framework for efficient NO_(3)RR electrocatalysts.
基金supported by Shenzhen Science and Technology Program(No.JCYJ20240813103608012)State Key Laboratory of New Textile Materials andAdvanced Processing Technologies(No.FZ2024019)National Natural Science Foundation of China(No.22104117).
文摘Nowadays,higher requirements are put forward to the storage and utilization of energy,and supercapacitor is a kind of energy storage electronic devices.The resulting CA-N,with a specific surface area of 320.6 m^(2)/g and a pore volume of 0.28 cm^(3)/g,demonstrated a remarkable supercapacitance of 283.3 F/g.As a mesoporous material,CA-N offers numerous channels for the diffusion and absorption of electrolyte ions.Furthermore,it exhibited an impressive capacity retention rate of 98.48% after 5000 charge-discharge cycles.These outstanding electrochemical properties highlight the potential of CA-N for applications in energy storage.
基金supported by the National Key R&D Program of China(Grant Nos.2020YFA0711500 and 2020YFA0711503)the National Natural Science Foundation of China(Grant Nos.T2488302,T2342010,52076127)+5 种基金the Natural Science Foundation of Shanghai(Grant Nos.20ZR1471700,22JC1401800,and 24Z511405472)the State Key Laboratory of Mechanical System and Vibration(Grant Nos.MSVZD202211,MSVZD202301,and MSVZD202401)Shanghai Jiao Tong University 2030 InitiativeShanghai Jiao Tong University Si Yuan Scholar Programthe Student Innovation Center and the Instrumental Analysis Center at Shanghai Jiao Tong Universitysupport by Shanghai Jiao Tong University 2030 Initiative。
文摘The electrocaloric(EC)effect refers to the change in the polarization entropy and/or temperature of dielectric materials when an electric field is applied and removed.EC refrigeration has received increasing interest as an alternative to conventional refrigeration technologies because it provides both high energy efficiency and zero global warming potential.In this review,we first introduce the thermodynamic fundamentals of the EC effect and the mechanism of EC refrigeration cycles.We then present recent advances in EC cooling technologies,from material improvements to device demonstrations,including a critical analysis of existing material and device characterization methodologies and a discussion of how to reliably measure the parameters of materials and devices.Finally,the current challenges and possible future prospects for EC cooling technology are outlined.
基金The financial support from the National Natural Science Foundation of China (Nos.22150410339,W2432012,22301237 and 22171218)the Ministry of Science and Technology China (No.wgxz2022188) is greatly acknowledged。
文摘Radical cycloaddition reactions(RCRs) are highly effective methods for constructing complex carbo-and heterocycles,which are frequently encountered in natural products that exhibit intriguing biological properties and hold significant potential for applications in medicinal chemistry.Radical-mediated cycloaddition strategies,which recycle radical character,are particularly appealing because they require only a catalytic amount of reagent and promise reactions with theoretically high atom economy.This review focuses on recent developments and synthetic applications in RCRs,with an emphasis on visible lightinduced radical photocycloaddition reactions(RPCRs),transition metal-catalyzed approaches,and small molecule-catalyzed methods.By highlighting some outstanding innovations and addressing current challenges,this review aims to identify potential areas for improvement.These advancements will provide more efficient pathways for the synthesis of natural product molecules and offer valuable insights for the development of new synthetic methodologies.
基金financially supported by the Natural Science Foundation of Shandong Province (No.ZR2022QE076)the National Natural Science Foundation of China (No.52202092)the Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China (No.2023KJ104)。
文摘Electrochemical CO_(2) reduction reaction(CO_(2)RR) into valuable formate provides a strategy for carbon neutrality.Bismuth(Bi) catalysts,attributed to their appropriate energy barrier of OCHO*intermediate,have demonstrated substantial potential for the advancement of electrocatalytic CO_(2) reduction to formate.However,due to the weak bonding of protons(H^(*)) of Bi,the available protonate of CO_(2) on Bi is insufficient,which limits the formation of OCHO^(*).Prediction by theoretical calculation,chlorine doping can effectively promote the dissociation of H_(2)O and thus achieve effective proton supply.We prepare chlorine-doped Bi(Cl-Bi) via an electrochemical conversion strategy for electroreduction of CO_(2) .An obvious improvement of faradaic efficiency(FE) of formate(96.7% at-0.95 V vs.RHE) can be achieved on Cl-Bi,higher than that of Bi(89.4%).Meanwhile,Cl-Bi has the highest formate production rate of 275 μmol h^(-1)cm^(-2)at-0.95 V vs.RHE,which is 1.2 times higher than that of Bi(224 μmol h^(-1)cm^(-2)).In situ characterizations and kinetic analysis reveal that chlorine doping promotes the activation of H_(2)O and supply sufficient protons to promote the protonation of CO_(2) to OCHO^(*),which is consistent with theoretical calculation.The study presents an effective strategy for rational design of highly efficient electrocatalysts to promote green chemical production.
基金supported by the National Natural Science Foundation of China (Grant Nos.12202330,52501055)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University (Grant No.YJSJ25017)the Natural Science Basic Research Program of Shaanxi (Grant No.2024JC-YBQN-0459)。
文摘Hf xTa 1-xC-based ceramics exhibit exceptional thermodynamic stability under extreme temperatures. However, their intrinsic brittleness raises significant concerns about their safe service in extreme environments. Here, we designed and fabricated HfTaC/W_(2) dual-phase ceramics with robust interface bonding through induction plasma spheroidization. During in situ transmission electron microscopy(TEM) mechanical testing, the dual-phase ceramics exhibited plastic deformation with a fracture strength of(7.6 ± 1.2) GPa and a strain of 23.8% ± 0.18% in nanopillar compression, and a fracture strain of 6.2% under tensile loading. The mechanism of plastic deformation in both compression and tensile tests is attributed to the interactions between dislocations and dual-phase interfaces, as well as the dislocation movement inside the W phase. Thus, our work demonstrates the enhanced plasticity of dual-phase HfTaC_(2)/W with a W network embedded in the HfTaC_(2) matrix than singlephase HfTaC_(2) and provides a paradigm for the development of advanced ceramics that combine strength with enhanced ductility for both functional and structural applications.
基金supported by the National Natural Science Foundation of China (Grant Nos.T2325004 and 52161160330)the National Natural Science Foundation of China (Grants No.12504233)+2 种基金Advanced MaterialsNational Science and Technology Major Project (Grant No.2024ZD0606900)the Talent Hub for “AI+New Materials” Basic Researchthe Key Research and Development Program of Ningbo (Grant No.2025Z088)。
文摘The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ simulations with varied protocols to evaluate the effectiveness of different descriptors in predicting mechanical properties across both low-and high-pressure regimes.Our findings demonstrate that conventional structural and configurational descriptors fail to correlate with the mechanical response following pressure release,whereas the activation energy descriptor exhibits robust linearity with shear modulus after correcting for pressure effects.Notably,the soft mode parameter emerges as an ideal and computationally efficient alternative for capturing this mechanical behavior.These findings provide critical insights into the influence of pressure on glassy properties,integrating the distinct features of compressed glasses into a unified theoretical framework.
基金the financial support provided by Universiti Putra Malaysiasupported by the Matching Grant(9300489).
文摘This review draws attention to the innovative use of arrowroot(Maranta arundinacea)fiber as a unique and underutilized biomass source for nanocrystalline cellulose(NCC)-based nanocomposites,presenting a noteworthy alternative to extensively researched materials like wood pulp,bacterial cellulose,and chemically modified NCCs.In contrast to traditional sources,arrowroot possesses a naturally elevated cellulose and diminished lignin content,facilitating more effective NCC extraction requiring reduced chemical input and enabling environmentally friendly processing techniques.The review evaluates the performance of arrowroot-derived nanocomposites against systems documented in the literature,including NCC-based shape memory composites and nanoparticle-reinforced films,demonstrating enhanced tensile strength,improved moisture barrier properties,and thermal stability,as well as potential piezoelectric response.This study recognizes arrowroot as a viable option in the biomass-based nanocellulose sector,providing ecological and functional benefits while tackling significant issues such as process scalability and feedstock variability,thereby offering important insights for the advancement of sustainable materials.
基金supported by National Natural Science Foundation of China(Grant Nos.52025055,52375576,52350349)Key Research and Development Program of Shaanxi(Program No.2022GXLH-01-12)+2 种基金Joint Fund of Ministry of Education for Equipment Pre-research(No.8091B03012304)Aeronautical Science Foundation of China(No.2022004607001)the Fundamental Research Funds for the Central Universities(No.xtr072024031).
文摘Continuous monitoring of biosignals is essential for advancing early disease detection,personalized treatment,and health management.Flexible electronics,capable of accurately monitoring biosignals in daily life,have garnered considerable attention due to their softness,conformability,and biocompatibility.However,several challenges remain,including imperfect skin-device interfaces,limited breathability,and insufficient mechanoelectrical stability.On-skin epidermal electronics,distinguished by their excellent conformability,breathability,and mechanoelectrical robustness,offer a promising solution for high-fidelity,long-term health monitoring.These devices can seamlessly integrate with the human body,leading to transformative advancements in future personalized healthcare.This review provides a systematic examination of recent advancements in on-skin epidermal electronics,with particular emphasis on critical aspects including material science,structural design,desired properties,and practical applications.We explore various materials,considering their properties and the corresponding structural designs developed to construct high-performance epidermal electronics.We then discuss different approaches for achieving the desired device properties necessary for long-term health monitoring,including adhesiveness,breathability,and mechanoelectrical stability.Additionally,we summarize the diverse applications of these devices in monitoring biophysical and physiological signals.Finally,we address the challenges facing these devices and outline future prospects,offering insights into the ongoing development of on-skin epidermal electronics for long-term health monitoring.
文摘Mortality prediction in respiratory health is challenging,especially when using large-scale clinical datasets composed primarily of categorical variables.Traditional digital twin(DT)frameworks often rely on longi-tudinal or sensor-based data,which are not always available in public health contexts.In this article,we propose a novel proto-DT framework for mortality prediction in respiratory health using a large-scale categorical biomedical dataset.This dataset contains 415,711 severe acute respiratory infection cases from the Brazilian Unified Health System,including both COVID-19 and non-COVID-19 patients.Four classification models—extreme gradient boosting(XGBoost),logistic regression,random forest,and a deep neural network(DNN)—are trained using cost-sensitive learning to address class imbalance.The models are evaluated using accuracy,precision,recall,F1-score,and area under the curve(AUC)related to the receiver operating characteristic(ROC).The framework supports simulated interventions by modifying selected inputs and recalculating predicted mortality.Additionally,we incorporate multiple correspondence analysis and K-means clustering to explore model sensitivity.A Python library has been developed to ensure reproducibility.All models achieve AUC-ROC values near or above 0.85.XGBoost yields the highest accuracy(0.84),while the DNN achieves the highest recall(0.81).Scenario-based simulations reveal how key clinical factors,such as intensive care unit admission and oxygen support,affect predicted outcomes.The proposed proto-DT framework demonstrates the feasibility of mortality prediction and intervention simulation using categorical data alone.This framework provides a foundation for data-driven explainable DTs in public health,even in the absence of time-series data.
文摘Heat exchangers play a crucial role in thermal energy systems,with their performance directly impacting efficiency,cost,and environmental impact.Apowerful technique for performance improvement can be given by passive enhancement strategies,which are characterized by their dependability and minimal external power requirements.This comprehensive review critically assesses recent advancements in such passive methods to evaluate their heat transfer mechanisms,performance characteristics,and practical implementation challenges.Our methodology involves a systematic and comprehensive analysis of various heat transfer enhancement techniques,including surface modifications,extended surfaces,swirl flow devices,and tube inserts.This approach synthesizes and integrates findings from a broad spectrum of experimental investigations and numerical simulations to establish a cohesive understanding of their performance characteristics and underlyingmechanisms.Based on the findings,passive heat transfer techniques result in significant improvements in thermal performance;for instance,corrugated and roughened surfaces increase the heat transfer coefficient by 50%–200%,and advanced insert geometries,such as modified twisted tapes,can increase it by more than 300%,typically accompanied by significant pressure-drop penalties.However,an important finding is the general trade-off between enhanced heat transfer and higher frictional loss,which requires optimization depending on the applications.Finally,this review also provides recommendations that will document the gaps of various passive techniques in heat exchangers to future address.
基金supported by the National Natural Science Foundation of China(Grant Nos.52379104 and 52090084).
文摘The biodegradable polybutylene succinate(PBS)material offers a sustainable solution for a circular economy to address the global issue of marine plastic waste.Its cross-linkage with non-biodegradable xanthan gum(XG)biopolymer to ameliorate residual granitic soil(RGS)in arid and semiarid regions can significantly mitigate soil erosion.This study investigates the enhancement of RGS by cross-linking the PBS and XG biopolymers.Employing a multitude of geotechnical tests(liquid limit,linear shrinkage,specific gravity,compaction,and UCS tests)at 3 d,28 d,and 90 d of steam-curing at a controlled temperature of 16℃,the outcomes were validated through scanning electron microscopy(SEM),thermogravimetric analysis(TGA),Fourier transform infrared spectroscopy(FTIR),and Brunauer-Emmett-Teller(BET)analyses.In addition,a comprehensive experimental database of 150 tests and nine parameters from the current study was utilized to model the UCS90-d(i.e.unconfined compressive strength after 90 d of curing)of the PBS-XG-treated RGS mixtures by deploying the random forest(RF)and eXtreme Gradient Boost(XGBoost)methods.The results found that the two biopolymers significantly improve the mechanical properties of RGS,with optimal UCS achieved at specific dosages(0.4PBS,1.5XG,and 0.2PBS+1.5XG dosage levels)and curing times.The UCS of PBS-XG-treated RGS showed up to a 57%increase after 90 d of curing.Furthermore,SEM and FTIR analyses revealed the formation of stronger microstructures and chemical bonds,respectively,whereas BET analysis indicated that pore volume and diameter are critical in affecting UCS.The proposed RF model outperformed XGBoost in predictive accuracy and generalization,demonstrating robustness and versatility.Moreover,SHAP values highlighted the significant impact of input parameters on UCS90-d,with curing time and specific material properties being key determinants.The study concludes with the proposal of a novel PyCharm intuitive graphical user interface as a"UCS Prediction App"for engineers and practitioners to forecast the UCS90-d of granitic residual soil.
基金the National Natural Science Foundation of China(Nos.22150410339,W2432012,22301233 and 22171218)the Ministry of Science and Technology China(No.wgxz2022188)。
文摘α-Chiral amides are common in pharmaceuticals,agrochemicals,natural products,and peptides,prompting the need for new synthetic methods.Here,we introduce a nickel-catalyzed asymmetric reductive amidation method to synthesizeα-chiral amides from benzyl ammonium salts and isocyanates.The key to success is using a chiral 2,2-bipyridine ligand(-)-Ph-SBpy,enabling high yield(up to 95%)and enantiomeric ratio(up to 98:2 er)under mild conditions.Addition of phenol prevents isocyanate polymerization by reversibly forming a carbamate intermediate,enhancing selectivity and efficiency.The synthetic utility is showcased through transformations of the enantioenriched amides,and the mechanism and enantioselectivity are supported by experimental and computational studies.
基金supported by National Natural Science Foundation of China(No.52025055 and 52275571)Basic Research Operation Fund of China(No.xzy012024024).
文摘Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.
文摘Objective Pharmacopoeias regulate the manufacture of potentised pharmaceutical preparations used in different branches of complementary and integrative medicine.The physicochemical properties and biological activity of these preparations are often investigated in preclinical research,yet no guidelines for experimental research currently exist in this area.The present PrePoP guidelines aim to provide recommendations to promote high-quality,statistically sound,and reproducible preclinical research on potentised preparations.Methods Input was gathered from researchers nominated by the relevant scientific societies using a simplified Delphi consensus approach covering the most relevant aspects of basic research methodology in the field including appropriate controls,sample preparation and handling,and statistics.After three rounds of feedback,a consensus was finally reached on the most important aspects and considerations for conducting high-quality research on potentised preparations.Results We present a series of recommendations on a range of topics including experimental controls,system stability,blinding and randomisation,environmental influences,and procedures for the preparation of potentised samples and controls,and we address some specific challenges of this research field.Conclusion This expert consensus process resulted in a robust set of methodological guidelines for research on potentised preparations and provides a valuable framework that will inform and improve the quality of subsequent research in this emerging field.
文摘Altered biomechanics due to amputation can contribute to substantial limitations,influencing sporting activities.Individuals with lower extremity amputations or congenital lower limb deficiency are encouraged to participate in para-sports.However,to compete in Paralympic sports,the candidate must have an impairment that results in lower extremity loss of function and meets or exceeds the sport's minimum impairment criteria(MIC).This review will focus on the MIC for competitive wheelchair tennis.Limb deficiency is known as one of the MIC used to regulate participation in competitive para-sports since it impacts gait,kinematics,and biomechanics of both the upper and lower body.Notwithstanding,it is questionable whether the MIC concerning limb deficiency is set at the correct level for determining eligibility for participating in Paralympic sports.This study aims to provide an overview of the evidence examining the impact of different partial foot amputation(PFA)levels on gait as a proxy for sporting performance.This scoping review will be based on a 6-step methodological framework and Preferred Reporting Items for Systematic Reviews and Meta-Analysis,extension for scoping reviews(PRISMA-ScR).Studies will be selected from PubMed,Embase,CINAHL,and SPORTDiscus.Two authors will screen the titles/abstracts independently.Selected studies will be scrutinised,and the same authors will extract data.Findings will be relevant to informing the evidence-based development of MIC for lower limb impairment after PFA and may be extrapolated to specific Paralympic sports,including wheelchair tennis.Results will be disseminated through scientific publications and conferences to audiences interested in Paralympic sports.
文摘Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
