Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics,offering immense potential in energy conversion,biomedical transport,and electromagnetic flow control syst...Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics,offering immense potential in energy conversion,biomedical transport,and electromagnetic flow control systems.Understanding their dynamic behavior under coupled magnetic,rotational,and reactive effects is crucial for the development of efficient thermal management technologies.This study develops a neuro-fuzzy computational framework to examine the dynamics of a reactive Cu–TiO_(2)–H_(2)Ohybrid nanofluid flowing through a squarely elevated Riga tunnel.The governing model incorporates Hall and ion-slip effects,thermal radiation,and first-order chemical reactions under ramped thermo-solutal boundary conditions and rotational electromagnetic forces.Closed-form analytical solutions are derived via the Laplace transform method to describe the transient velocity,temperature,and concentration fields.To complement and validate the analytical model,an artificial neural network(ANN)optimized using the Levenberg–Marquardt backpropagation algorithm(ANN-LMBPA)is trained on datasets generated in Mathematica.Regression and error analyses confirm the model’s predictive robustness,with mean squared errors ranging between 10^(-4) and 10^(-9).In addition,an Adaptive Neuro-Fuzzy Inference System(ANFIS)is developed to estimate the heat transfer rate(HTR),achieving aminimal RMSE of 0.011012 for the heat transfer coefficient(HTC).The findings reveal that rotational motion and Hall–ion slip effects suppress primary velocity but enhance secondary flow,while the modified Hartmann number(Lorentz force)accelerates both components.Thermal radiation increases fluid temperature,whereas higher Schmidt numbers and reaction rates diminish solute concentration.The HTR decreases with increasing radiation and nanoparticle volume fraction,while the mass transfer rate(MTR)improves under stronger chemical reactivity.Overall,the proposed hybrid analytical–AI framework demonstrates high accuracy and efficiency,offering valuable insights for the design and optimization of electromagnetic nanofluid systems in advanced thermal and process engineering applications.展开更多
Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper ...Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper equations are one of the main and most efficient methods for estimating stem volume to any merchantable limit of a species.There is currently no taper equation for Eucalyptus species in Nigeria.Therefore,this study developed taper equations for E.camaldulensis in northern Nigeria.Data for this study were obtained from a private plantation in Jalingo Local Government Area,Taraba State,Nigeria.68 trees were felled and sectioned into 1-m bolt across the stem to a merchantable limit of 5 cm,which were used as the fitting dataset.An additional 22 trees were felled and used to validate the taper equations for stem volume estimation.Seven taper equations were initially fitted to the dataset using nonlinear least squares.The best taper equation was then refitted using a nonlinear mixed-effects approach and calibrated using diameters of one to five sections from the butt end.The taper equations were numerically integrated to obtain the stem volume,which was compared with empirical volume equations.The result shows that the Kozak(Can J For Res 27(5):619-629.10.1139/x97-011,1997)equation,which included eight parameters,provided the best fit for predicting section diameters for under and over bark.The mixed-effects taper equation(NLME-TE)explained most stem diameter variations in the fitting dataset(pseudo-R2:0.986-0.987;RMSE:0.547-0.578 cm)without substantial residual trends.The validation showed that the prediction accuracy of the integrated NLME-TE improved as the number of sectional diameter measurements increased,with at least a 35%reduction in volume estimate error.For practical implementation,two calibration sectional diameter measurements taken from the butt end per tree are recommended.This approach would reduce measurement effort and cost while improving model performance.展开更多
In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typica...In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.展开更多
In manganese electrolysis,electrochemical oscillations and manganese dendrite growth are typical nonlinear phenomena critical for energy consumption reduction.Nonetheless,existing research lacks a deep understanding o...In manganese electrolysis,electrochemical oscillations and manganese dendrite growth are typical nonlinear phenomena critical for energy consumption reduction.Nonetheless,existing research lacks a deep understanding of their underlying mechanisms.In this study,we systematically explored the evolution of anode electrochemical oscillations during manganese electrolysis and designed a square wave circuit to effectively suppress oscillations and dendrite growth while reducing energy consumption.A novel four-dimensional differential equation was introduced to explore the internal dynamic mechanisms of typical nonlinear behaviors.The experimental results showed that while the evolutionary patterns of current and potential oscillation signals were consistent,their waveform directions were opposite.The square wave current effectively suppressed both electrochemical oscillations and the growth of manganese dendrites.Furthermore,compared to direct current electrolysis,the square wave current improved the current efficiency by 3.6%and reduced the energy consumption by 0.32 kW·h·kg^(−1).展开更多
Reconfigurable intelligent surfaces(RISs)not only assist communication but also help the localization of user equipment(UE).This study focuses on indoor localization of UE with a single access point(AP)and multiple RI...Reconfigurable intelligent surfaces(RISs)not only assist communication but also help the localization of user equipment(UE).This study focuses on indoor localization of UE with a single access point(AP)and multiple RISs.First,we propose a two-stage channel estimation scheme where RIS phase shifts are tuned to obtain multiple channel soundings.In the first stage,the newtonized orthogonal matching pursuit algorithm extracts the parameters of multiple paths from the received signals.Then,the LOS path and RISreflected paths are identified.In the second stage,the estimated path gains of RIS-reflected paths with different phase shifts are utilized to determine the angle of arrival(AOA)at the RIS by obtaining the angular pseudo spectrum.Consequently,by taking the AP and RISs as reference points,the linear least squares estimator can locate UE with the estimated AOAs.Simulation results show that the proposed algorithm can realize centimeter-level localization accuracy in the discussed scenarios.Moreover,the higher accuracy of pseudo spectrum,a larger number of channel soundings,and a larger number of reference points can realize higher localization accuracy of UE.展开更多
The 2026 Sanya Chinese New Year Shopping Carnival kicked off on February 7 at Dadonghai Square in Sanya, Hainan Province. Thanks to the Hainan Free Trade Port’s favorable trade policies, specialty products from Vietn...The 2026 Sanya Chinese New Year Shopping Carnival kicked off on February 7 at Dadonghai Square in Sanya, Hainan Province. Thanks to the Hainan Free Trade Port’s favorable trade policies, specialty products from Vietnam,Malaysia, and Indonesia took center stage. Popular with both locals and visitors alike,these products added a vibrant international touch to the fair.展开更多
In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of ...In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of mixture experiments that involve process variables.Prior research has extensively delved into optimal orthogonal block designs for some classic mixture models with process variables.Based on the framework of general blending models,this paper proposes a class of symmetric linear mixture models,which can be regarded as a generalization of many existing ones.Under the orthogonal blocking conditions,orthogonal block designs are devised through Latin squares in the presence of process variables.TheD-,A-,and E-optimality criteria are utilized to obtain optimal designs at the boundary of the simplex in the case of 3 components.As the values of the exponents change,numerically derived optimal design points are presented to illustrate the pattern of their variations,and to verify the consistency of the results with previous research on some specific symmetric general blending models.展开更多
The increasing production and release of synthetic organic chemicals,including pharmaceuticals,into our envi-ronment has allowed these substances to accumulate in our surface water systems.Current purification technol...The increasing production and release of synthetic organic chemicals,including pharmaceuticals,into our envi-ronment has allowed these substances to accumulate in our surface water systems.Current purification technolo-gies have been unable to eliminate these pollutants,resulting in their ongoing release into aquatic ecosystems.This study focuses on cloperastine(CPS),a cough suppressant and antihistamine medication.The environmental impact of CPS usage has become a concern,mainly due to its increased detection during the COVID-19 pandemic.CPS has been found in wastewater treatment facilities,effluents from senior living residences,river waters,and sewage sludge.However,the photosensitivity of CPS and its photodegradation profile remain largely unknown.This study investigates the photodegradation process of CPS under simulated tertiary treatment conditions using UV photolysis,a method commonly applied in some wastewater treatment plants.Several transformation prod-ucts were identified,evaluating their kinetic profiles using chemometric approaches(i.e.,curve fitting and the hard-soft multivariate curve resolution-alternating least squares(HS-MCR-ALS)algorithm)and calculating the reaction quantum yield.As a result,three different transformation products have been detected and correctly identified.In addition,a comprehensive description of the kinetic pathway involved in the photodegradation process of the CPS drug has been provided,including observed kinetic rate constants.展开更多
Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on li...Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on linear processes,leading to poor performance in dynamic nonlinear processes.In this paper,a novel quality-related fault detection method,named DiCAE-PLS,is developed by combining dynamic-inner convolutional autoencoder with PLS.In the proposed DiCAE-PLS method,latent features are first extracted through dynamic-inner convolutional autoencoder (DiCAE) to capture process dynamics and nonlinearity from process variables.Then,a PLS model is established to build the relationship between the extracted latent features and the final product quality.To detect quality-related faults,Hotelling's T^(2) statistic is employed.The developed quality-related fault detection is applied to the widely used industrial benchmark of the Tennessee.展开更多
Lately,the implementation of China’s carbon peaking and carbon neutrality strategy has advanced the rapid development of the new energy industry.The cylindrical battery is extensively used due to its excellent con-si...Lately,the implementation of China’s carbon peaking and carbon neutrality strategy has advanced the rapid development of the new energy industry.The cylindrical battery is extensively used due to its excellent con-sistency,production efficiency,and high safety.Additionally,the cylindrical battery has been recognized as a major form of the future power battery by the series of benchmark car companies such as Tesla and BMW.Nickel-preplated steel(NPS),as the primary structural material for large cylindrical battery,is expected to see rapidly expanding market demand over the next three years.This study systematically introduces the continuous production of NPS for battery shell in Baosteel,including the control of substrate purity,the alloying treatment of the nickel coating layer,and the evaluation of key characteristics of products at the steel shell and battery.Moreover,this study presents the prospects for the application of NPS in square battery shells to foster the low-carbon transformation of new energy battery packaging materials.In conclusion,this study aims to provide a complete set of solutions for material selection,forming,and application technology of NPS products in diverse forms of battery shells.展开更多
Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to ...Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core.To address this limitation,this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer(PKO),a nature-inspired algorithm,to enhance the accuracy of shear strength prediction for CFST columns.Additionally,quantile regression is employed to construct prediction intervals for the ultimate shear force,while the Asymmetric Squared Error Loss(ASEL)function is incorporated to mitigate overestimation errors.The computational results demonstrate that the PKO-XGBoost model delivers superior predictive accuracy,achieving a Mean Absolute Percentage Error(MAPE)of 4.431%and R2 of 0.9925 on the test set.Furthermore,the ASEL-PKO-XGBoost model substantially reduces overestimation errors to 28.26%,with negligible impact on predictive performance.Additionally,based on the Genetic Algorithm(GA)and existing equation models,a strength equation model is developed,achieving markedly higher accuracy than existing models(R^(2)=0.934).Lastly,web-based Graphical User Interfaces(GUIs)were developed to enable real-time prediction.展开更多
Optical two-way time-frequency transfer(O-TWTFT),utilizing optical frequency comb carriers and linear optical sampling,effectively enables space-to-ground optical frequency standard comparisons.Previously reported det...Optical two-way time-frequency transfer(O-TWTFT),utilizing optical frequency comb carriers and linear optical sampling,effectively enables space-to-ground optical frequency standard comparisons.Previously reported detection sensitivities of O-TWTFTs were typically in the nanoWatt level,necessitating high-power optical frequency combs to compensate for significant losses in high-orbit satellite-to-ground passes.Such hardware-based solutions,while effective,tend to be costly.This paper presents a novel data post-processing algorithm to enhance sensitivity.Unlike previous timing methods,which depend solely on optical phase data and discard intensity information—resulting in elevated errors,especially under low-reception power,our approach employs complex least squares(CLS)estimation in the complex frequency domain.By preserving all intermediate data and avoiding noise from phase unwrapping,it achieves superior sensitivity and accuracy.Experiments over a 113-kilometer free-space link validate the algorithm's robustness,delivering a detection sensitivity of0.1 nanoWatts—over tenfold better than prior techniques—despite a 100-decibel link loss,comparable to Earth-Moon optical links.展开更多
The authors extend the marginal coordinate test for predictor contribution(Cook,2004)to the case with multivariate responses.Instead of explicitly specifying the link functions between the responses and the predictors...The authors extend the marginal coordinate test for predictor contribution(Cook,2004)to the case with multivariate responses.Instead of explicitly specifying the link functions between the responses and the predictors,an asymptotic test is proposed under the normality assumption of the predictors as well as an asymmetry assumption about the unknown regression mean function.When these assumptions are violated,the asymptotic test with elliptical trimming and clustering is still valid with desirable numerical performances.展开更多
Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively ...Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively high row weights,the existing blind recognition algorithms based on a candidate set generally perform worse.In this paper,we propose a blind recognition method for LDPC codes,called as tangent function assisted least square(TLS)method,which improves recognition performances by constructing a new cost function.To characterize the constraint degree among received vectors and paritycheck vectors,a feature function based on tangent function is constructed in the proposed algorithm.A cost function based on least square method is also established according to the feature function values satisfying the parity-check relationship.Moreover,the minimum average value in TLS is obtained on the candidate set.Numerical analysis and simulation results show that recognition performances of TLS algorithm are consistent with theoretical results.Compared with existing algorithms,the proposed method possesses better recognition performances.展开更多
Accurate estimation of battery health status plays a crucial role in battery management systems.However,the lack of operational data still affects the accuracy of battery state of health(SOH)estimation.For this reason...Accurate estimation of battery health status plays a crucial role in battery management systems.However,the lack of operational data still affects the accuracy of battery state of health(SOH)estimation.For this reason,a SOH estimation method is proposed based on charging data reconstruction combined with image processing.The charging voltage data is used to train the least squares generative adversarial network(LSGAN),which is validated under different levels of missing data.From a visual perspective,the Gram angle field method is applied to convert one-dimensional time series data into image data.This method fully preserves the time series characteristics and nonlinear evolution patterns,which avoids the difficulties and limited expressive power associated with manual feature extraction.At the same time,the Swin Transformer model is introduced to extract global structures and local details from images,enabling better capture of sequence change trends.Combined with the long short-term memory network(LSTM),this enables accurate estimation of battery SOH.Two different types of batteries are used to validate the test.The experimental results show that the proposed method has good estimation accuracy under different training proportions.展开更多
Based on the generalized reduced R-matrix theory,the R-matrix analysis code(RAC program)was used to analyze the experimental data of all the nuclear reaction channels related to the 5 He system.The current calculation...Based on the generalized reduced R-matrix theory,the R-matrix analysis code(RAC program)was used to analyze the experimental data of all the nuclear reaction channels related to the 5 He system.The current calculations provide accurate and reliable evaluation data and are in good agreement with the experimental data.In this study,self-consistent evaluation data for each reaction were obtained using multi-channel and multi-energy fitting.In particular,the error propagation theory of generalized least squares was used to determine the error of the evaluation data and the covariance matrix of the integral cross section.This R-matrix analysis for the 5 He system has three features.First,for the first time,the error in the evaluation data of the T(d,n)^(4)He reaction cross section and the covariance matrix of the integral cross section are provided.Second,we used only one set of R-matrix parameters to depict the reaction cross section of each reaction channel of the 5 He system for the entire energy region in our work.Third,in this evaluation,we considered some of the latest measured experimental data,especially after 2000.The T(d,n)^(4)He reaction cross section at 0.1 MeV and below was carefully studied.The effect of different energy levels in T(d,n)^(4)He was analyzed,with the energy levels 3/2^(+)making a major contribution to the cross section,and the role of the S-wave and P-wave from 3/2~-determines the lean forward trend of the angular distributions at 0.01–0.1 MeV.展开更多
Functionally graded material(FGM)plates are widely used in various engineering structures owing to their tailor-made mechanical properties,whereas cracked homogeneous plates constitute a canonical setting in fracture ...Functionally graded material(FGM)plates are widely used in various engineering structures owing to their tailor-made mechanical properties,whereas cracked homogeneous plates constitute a canonical setting in fracture mechanics analysis.These two classes of problems respectively embody material non-uniformity and geometric discontinuity,thereby imposing more stringent requirements on numerical methods in terms of high-order field continuity and accurate defect representation.Based on the classical Kirchhoff-Love plate theory,a numerical manifold method(MLS-NMM)incorporating moving least squares(MLS)interpolation is developed for bending analysis of FGM plates and fracture simulation of homogeneous plates with defects.The method constructs an H^(2)-regular approximation with high-order continuous weighting functions and,combined with the separation of mathematical and physical covers,establishes a unified framework that accurately handles material gradients and cracks without mesh reconstruction.For the crack tip,a singular physical cover incorporating the Williams asymptotic field is introduced to achieve local enrichment,enabling the natural capture of displacement discontinuity and stress singularity.Stress intensity factors are extracted using the interaction integral method,and the dimensionless J-integral shows a maximum relative error below 1.2%compared with the reference solution.Numerical results indicate that MLS-NMM exhibits excellent convergence performance:using 676 mathematical nodes,the nondimensional central deflection of both FGM and homogeneous plates agrees with reference solutions with a maximum relative error below 0.81%,and no shear locking occurs.A systematic analysis reveals that for a simply supported on all four edges(SSSS)FGM square plate with a/h=10,the nondimensional central deflection increases by 212%as the gradient index nrises from 0 to 5.For a homogeneous plate containing a central crack with c/a=0.6,the nondimensional central deflection increases by approximately 46%compared with the intact plate.Under weak boundary constraints(e.g.,SFSF),the deformation is markedly amplified,with the deflection reaching more than three times that under strong constraints(SCSC).The proposed method provides an efficient,reconstruction-free numerical tool for high-accuracy bending and fracture analyses of FGM and cracked thin-plate structures.展开更多
Altun Mountains National Nature Reserve Established in 1983,the Altun Mountains National Nature Reserve is located in the eastern Kunlun Mountains,within Ruoqiang County of the Bayingolin Mongol Autonomous Prefecture ...Altun Mountains National Nature Reserve Established in 1983,the Altun Mountains National Nature Reserve is located in the eastern Kunlun Mountains,within Ruoqiang County of the Bayingolin Mongol Autonomous Prefecture in Xinjiang Uygur Autonomous Region.Covering a vast area of 45,000 square km,it stands as one of China’s largest and most pristine protected areas.With an average elevation of 4,580 metres,it represents a quintessential plateau desert ecosystem.展开更多
Although various Climate-Smart Agricultural(CSA) practices are promoted to safeguard agricultural production and food security in the Global South,their adoption remains limited.This study conducted a cross-sectional ...Although various Climate-Smart Agricultural(CSA) practices are promoted to safeguard agricultural production and food security in the Global South,their adoption remains limited.This study conducted a cross-sectional survey using a semi-structured questionnaire between March and April in 2023,with a sample of 231 smallholder farmers covering 5 villages(Purbo Karpara,Rampasa,Monohor Pur,Boro Isubpur,and Char Alapur) in Haor wetlands of Bangladesh.Then,this study examined smallholder farmers' adoption intention of floating farming practice in Haor wetlands of Bangladesh based on an extended Theory of Planned Behaviour(TPB) model.The result demonstrated moderate predictive power of the proposed model,where farmers' attitude,subjective norm,knowledge of floating farming practice,perceived behavioural control,and institutional accessibility jointly explained 11.50% of the total variance in adoption intention,with subjective norm and perceived behavioural control showing significant impact on smallholder farmers' adoption intention.However,key barriers reported by smallholder farmers included unavailability of resources,limited access to modern farming practices,input and credit unavailability,insufficient access to training,and limited access to market system.These findings indicated that improving smallholder farmers' access to extension services and credit facilities,raising awareness,providing training,and guaranteeing access to accurate and timely climate information and early warning systems could significantly improve their adaptive capacity.This study contributes to socio-psychological understanding of smallholder farmers' pro-environmental behaviour and emphasises the need for context-specific interventions to support sustainable livelihoods and resilient agri-food systems in climate-vulnerable regions.展开更多
文摘Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics,offering immense potential in energy conversion,biomedical transport,and electromagnetic flow control systems.Understanding their dynamic behavior under coupled magnetic,rotational,and reactive effects is crucial for the development of efficient thermal management technologies.This study develops a neuro-fuzzy computational framework to examine the dynamics of a reactive Cu–TiO_(2)–H_(2)Ohybrid nanofluid flowing through a squarely elevated Riga tunnel.The governing model incorporates Hall and ion-slip effects,thermal radiation,and first-order chemical reactions under ramped thermo-solutal boundary conditions and rotational electromagnetic forces.Closed-form analytical solutions are derived via the Laplace transform method to describe the transient velocity,temperature,and concentration fields.To complement and validate the analytical model,an artificial neural network(ANN)optimized using the Levenberg–Marquardt backpropagation algorithm(ANN-LMBPA)is trained on datasets generated in Mathematica.Regression and error analyses confirm the model’s predictive robustness,with mean squared errors ranging between 10^(-4) and 10^(-9).In addition,an Adaptive Neuro-Fuzzy Inference System(ANFIS)is developed to estimate the heat transfer rate(HTR),achieving aminimal RMSE of 0.011012 for the heat transfer coefficient(HTC).The findings reveal that rotational motion and Hall–ion slip effects suppress primary velocity but enhance secondary flow,while the modified Hartmann number(Lorentz force)accelerates both components.Thermal radiation increases fluid temperature,whereas higher Schmidt numbers and reaction rates diminish solute concentration.The HTR decreases with increasing radiation and nanoparticle volume fraction,while the mass transfer rate(MTR)improves under stronger chemical reactivity.Overall,the proposed hybrid analytical–AI framework demonstrates high accuracy and efficiency,offering valuable insights for the design and optimization of electromagnetic nanofluid systems in advanced thermal and process engineering applications.
文摘Eucalyptus(Eucalyptus camaldulensis Dehnh.)is an important exotic species in northern Nigeria commonly used for poles and timber.Sustainable management of this resource would require quantifying its volume.Stem taper equations are one of the main and most efficient methods for estimating stem volume to any merchantable limit of a species.There is currently no taper equation for Eucalyptus species in Nigeria.Therefore,this study developed taper equations for E.camaldulensis in northern Nigeria.Data for this study were obtained from a private plantation in Jalingo Local Government Area,Taraba State,Nigeria.68 trees were felled and sectioned into 1-m bolt across the stem to a merchantable limit of 5 cm,which were used as the fitting dataset.An additional 22 trees were felled and used to validate the taper equations for stem volume estimation.Seven taper equations were initially fitted to the dataset using nonlinear least squares.The best taper equation was then refitted using a nonlinear mixed-effects approach and calibrated using diameters of one to five sections from the butt end.The taper equations were numerically integrated to obtain the stem volume,which was compared with empirical volume equations.The result shows that the Kozak(Can J For Res 27(5):619-629.10.1139/x97-011,1997)equation,which included eight parameters,provided the best fit for predicting section diameters for under and over bark.The mixed-effects taper equation(NLME-TE)explained most stem diameter variations in the fitting dataset(pseudo-R2:0.986-0.987;RMSE:0.547-0.578 cm)without substantial residual trends.The validation showed that the prediction accuracy of the integrated NLME-TE improved as the number of sectional diameter measurements increased,with at least a 35%reduction in volume estimate error.For practical implementation,two calibration sectional diameter measurements taken from the butt end per tree are recommended.This approach would reduce measurement effort and cost while improving model performance.
基金supported in part by the National Natural Science Foundation of China(62373070 and 52272388)in part by the Chongqing Natural Science Foundation(CSTB2024NSCQ-QCXMX0054,CSTB2022NSCQ-MSX1225 and CSTC2024YCJH-BGZXM0042)in part by the Key Research and Development Project of Anhui Province(202304a05020060).
文摘In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.
基金support from the Fundamental Research Funds for the Central Universities(2022CDJQY-005,2024CDJXY010)the Guangxi Science and Technology Program(AB24010229)is greatly acknowledged.
文摘In manganese electrolysis,electrochemical oscillations and manganese dendrite growth are typical nonlinear phenomena critical for energy consumption reduction.Nonetheless,existing research lacks a deep understanding of their underlying mechanisms.In this study,we systematically explored the evolution of anode electrochemical oscillations during manganese electrolysis and designed a square wave circuit to effectively suppress oscillations and dendrite growth while reducing energy consumption.A novel four-dimensional differential equation was introduced to explore the internal dynamic mechanisms of typical nonlinear behaviors.The experimental results showed that while the evolutionary patterns of current and potential oscillation signals were consistent,their waveform directions were opposite.The square wave current effectively suppressed both electrochemical oscillations and the growth of manganese dendrites.Furthermore,compared to direct current electrolysis,the square wave current improved the current efficiency by 3.6%and reduced the energy consumption by 0.32 kW·h·kg^(−1).
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant 2242022k60004in part by the National Natural Science Foundation of China(NSFC)under Grants 62261160576,624B2036,W2421087,62422105+1 种基金in part by the Young Elite Scientists Sponsorship Program by CAST 2022QNRC001,and the“Zhishan”Scholars Programs of Southeast Universityin part by the Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)under Grants BE2023022,BE2023022-1 and BE2023022-2.
文摘Reconfigurable intelligent surfaces(RISs)not only assist communication but also help the localization of user equipment(UE).This study focuses on indoor localization of UE with a single access point(AP)and multiple RISs.First,we propose a two-stage channel estimation scheme where RIS phase shifts are tuned to obtain multiple channel soundings.In the first stage,the newtonized orthogonal matching pursuit algorithm extracts the parameters of multiple paths from the received signals.Then,the LOS path and RISreflected paths are identified.In the second stage,the estimated path gains of RIS-reflected paths with different phase shifts are utilized to determine the angle of arrival(AOA)at the RIS by obtaining the angular pseudo spectrum.Consequently,by taking the AP and RISs as reference points,the linear least squares estimator can locate UE with the estimated AOAs.Simulation results show that the proposed algorithm can realize centimeter-level localization accuracy in the discussed scenarios.Moreover,the higher accuracy of pseudo spectrum,a larger number of channel soundings,and a larger number of reference points can realize higher localization accuracy of UE.
文摘The 2026 Sanya Chinese New Year Shopping Carnival kicked off on February 7 at Dadonghai Square in Sanya, Hainan Province. Thanks to the Hainan Free Trade Port’s favorable trade policies, specialty products from Vietnam,Malaysia, and Indonesia took center stage. Popular with both locals and visitors alike,these products added a vibrant international touch to the fair.
基金supported by the National Natural Science Foundation of China[grant numbers 12071329,12471246].
文摘In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of mixture experiments that involve process variables.Prior research has extensively delved into optimal orthogonal block designs for some classic mixture models with process variables.Based on the framework of general blending models,this paper proposes a class of symmetric linear mixture models,which can be regarded as a generalization of many existing ones.Under the orthogonal blocking conditions,orthogonal block designs are devised through Latin squares in the presence of process variables.TheD-,A-,and E-optimality criteria are utilized to obtain optimal designs at the boundary of the simplex in the case of 3 components.As the values of the exponents change,numerically derived optimal design points are presented to illustrate the pattern of their variations,and to verify the consistency of the results with previous research on some specific symmetric general blending models.
基金supported by the grants PID2020-113371RA-C22 and TED2021-130845A-C32,funded by MCIN/AEI/10.13039/501100011033.M.Marín-García,R.González-OlmosC.Gómez-Canela are members of the GESPA group(Grup d’Enginyeria i Simulacióde Processos Ambientals)at IQS-URL,which has been acknowledged as a Consolidated Research Group by the Government of Catalonia(No.2021-SGR-00321)+1 种基金In addition,M.Marín-García has been awarded a public grant for the Investigo Programme,aimed at hiring young job seekers to undertake research and innovation projects under the Recovery,Transformation,and Resilience Plan(PRTR),European Union Next Generation,for the year 2022,through the Government of Catalonia and the Spanish Ministry for Work and Social Economy(No.100045ID16)Ana Belén Cuenca for her support and expertise,which helped to confirm the proposed reaction mechanism involved in the UV photolysis of cloperastine.
文摘The increasing production and release of synthetic organic chemicals,including pharmaceuticals,into our envi-ronment has allowed these substances to accumulate in our surface water systems.Current purification technolo-gies have been unable to eliminate these pollutants,resulting in their ongoing release into aquatic ecosystems.This study focuses on cloperastine(CPS),a cough suppressant and antihistamine medication.The environmental impact of CPS usage has become a concern,mainly due to its increased detection during the COVID-19 pandemic.CPS has been found in wastewater treatment facilities,effluents from senior living residences,river waters,and sewage sludge.However,the photosensitivity of CPS and its photodegradation profile remain largely unknown.This study investigates the photodegradation process of CPS under simulated tertiary treatment conditions using UV photolysis,a method commonly applied in some wastewater treatment plants.Several transformation prod-ucts were identified,evaluating their kinetic profiles using chemometric approaches(i.e.,curve fitting and the hard-soft multivariate curve resolution-alternating least squares(HS-MCR-ALS)algorithm)and calculating the reaction quantum yield.As a result,three different transformation products have been detected and correctly identified.In addition,a comprehensive description of the kinetic pathway involved in the photodegradation process of the CPS drug has been provided,including observed kinetic rate constants.
基金supported in part by the National Natural Science Foundation of China(62573387)the Natural Science Foundation of Zhejiang province,China(LY24F030004)the Fundamental Research Funds of Zhejiang Sci-Tech University(25222139-Y).
文摘Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on linear processes,leading to poor performance in dynamic nonlinear processes.In this paper,a novel quality-related fault detection method,named DiCAE-PLS,is developed by combining dynamic-inner convolutional autoencoder with PLS.In the proposed DiCAE-PLS method,latent features are first extracted through dynamic-inner convolutional autoencoder (DiCAE) to capture process dynamics and nonlinearity from process variables.Then,a PLS model is established to build the relationship between the extracted latent features and the final product quality.To detect quality-related faults,Hotelling's T^(2) statistic is employed.The developed quality-related fault detection is applied to the widely used industrial benchmark of the Tennessee.
文摘Lately,the implementation of China’s carbon peaking and carbon neutrality strategy has advanced the rapid development of the new energy industry.The cylindrical battery is extensively used due to its excellent con-sistency,production efficiency,and high safety.Additionally,the cylindrical battery has been recognized as a major form of the future power battery by the series of benchmark car companies such as Tesla and BMW.Nickel-preplated steel(NPS),as the primary structural material for large cylindrical battery,is expected to see rapidly expanding market demand over the next three years.This study systematically introduces the continuous production of NPS for battery shell in Baosteel,including the control of substrate purity,the alloying treatment of the nickel coating layer,and the evaluation of key characteristics of products at the steel shell and battery.Moreover,this study presents the prospects for the application of NPS in square battery shells to foster the low-carbon transformation of new energy battery packaging materials.In conclusion,this study aims to provide a complete set of solutions for material selection,forming,and application technology of NPS products in diverse forms of battery shells.
基金funded by United Arab Emirates University(UAEU)under the UAEU-AUA grant number G00004577(12N145)with the corresponding grant at Universiti Malaya(UM)under grant number IF019-2024.
文摘Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core.To address this limitation,this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer(PKO),a nature-inspired algorithm,to enhance the accuracy of shear strength prediction for CFST columns.Additionally,quantile regression is employed to construct prediction intervals for the ultimate shear force,while the Asymmetric Squared Error Loss(ASEL)function is incorporated to mitigate overestimation errors.The computational results demonstrate that the PKO-XGBoost model delivers superior predictive accuracy,achieving a Mean Absolute Percentage Error(MAPE)of 4.431%and R2 of 0.9925 on the test set.Furthermore,the ASEL-PKO-XGBoost model substantially reduces overestimation errors to 28.26%,with negligible impact on predictive performance.Additionally,based on the Genetic Algorithm(GA)and existing equation models,a strength equation model is developed,achieving markedly higher accuracy than existing models(R^(2)=0.934).Lastly,web-based Graphical User Interfaces(GUIs)were developed to enable real-time prediction.
基金supported by the National Key Research and Development Programme of China(Grant Nos.2020YFC2200103 and 2020YFA0309800)the National Natural Science Foundation of China(Grant No.T2125010)+4 种基金Strategic Priority Research Programme of Chinese Academy of Sciences(Grant No.XDB35030000)Anhui Initiative in Quantum Information Technologies(Grant No.AHY010100)Key R&D Plan of Shandong Province(Grant No.2021ZDPT01)Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)Innovation Programme for Quantum Science and Technology(Grant Nos.2021ZD0300100,2021ZD0300300,and2021ZD0300903)。
文摘Optical two-way time-frequency transfer(O-TWTFT),utilizing optical frequency comb carriers and linear optical sampling,effectively enables space-to-ground optical frequency standard comparisons.Previously reported detection sensitivities of O-TWTFTs were typically in the nanoWatt level,necessitating high-power optical frequency combs to compensate for significant losses in high-orbit satellite-to-ground passes.Such hardware-based solutions,while effective,tend to be costly.This paper presents a novel data post-processing algorithm to enhance sensitivity.Unlike previous timing methods,which depend solely on optical phase data and discard intensity information—resulting in elevated errors,especially under low-reception power,our approach employs complex least squares(CLS)estimation in the complex frequency domain.By preserving all intermediate data and avoiding noise from phase unwrapping,it achieves superior sensitivity and accuracy.Experiments over a 113-kilometer free-space link validate the algorithm's robustness,delivering a detection sensitivity of0.1 nanoWatts—over tenfold better than prior techniques—despite a 100-decibel link loss,comparable to Earth-Moon optical links.
文摘The authors extend the marginal coordinate test for predictor contribution(Cook,2004)to the case with multivariate responses.Instead of explicitly specifying the link functions between the responses and the predictors,an asymptotic test is proposed under the normality assumption of the predictors as well as an asymmetry assumption about the unknown regression mean function.When these assumptions are violated,the asymptotic test with elliptical trimming and clustering is still valid with desirable numerical performances.
基金Fundamental Research Funds for the Central Universities under Grant 3072025YC0802the National Natural Science Foundation of China under Grant 62001138Heilongjiang Provincial Natural Science Foundation of China under Grant LH2021F009。
文摘Blind recognition of low-density paritycheck(LDPC)codes has gradually attracted more attention with the development of military and civil communications.However,in the case of the paritycheck matrices with relatively high row weights,the existing blind recognition algorithms based on a candidate set generally perform worse.In this paper,we propose a blind recognition method for LDPC codes,called as tangent function assisted least square(TLS)method,which improves recognition performances by constructing a new cost function.To characterize the constraint degree among received vectors and paritycheck vectors,a feature function based on tangent function is constructed in the proposed algorithm.A cost function based on least square method is also established according to the feature function values satisfying the parity-check relationship.Moreover,the minimum average value in TLS is obtained on the candidate set.Numerical analysis and simulation results show that recognition performances of TLS algorithm are consistent with theoretical results.Compared with existing algorithms,the proposed method possesses better recognition performances.
基金supported in part by the National Natural Science Foundation of China(under Grant 62473309,62203352)the Shaanxi Outstanding Youth Science Fund Project(under Grant 2024JC-JCQN-68)+1 种基金the Xi’an Science and Technology Plan Project(under Grant 24GXFW0050)the Xi’an Key Laboratory(under Grant 24ZDSY0015).
文摘Accurate estimation of battery health status plays a crucial role in battery management systems.However,the lack of operational data still affects the accuracy of battery state of health(SOH)estimation.For this reason,a SOH estimation method is proposed based on charging data reconstruction combined with image processing.The charging voltage data is used to train the least squares generative adversarial network(LSGAN),which is validated under different levels of missing data.From a visual perspective,the Gram angle field method is applied to convert one-dimensional time series data into image data.This method fully preserves the time series characteristics and nonlinear evolution patterns,which avoids the difficulties and limited expressive power associated with manual feature extraction.At the same time,the Swin Transformer model is introduced to extract global structures and local details from images,enabling better capture of sequence change trends.Combined with the long short-term memory network(LSTM),this enables accurate estimation of battery SOH.Two different types of batteries are used to validate the test.The experimental results show that the proposed method has good estimation accuracy under different training proportions.
基金supported by Science Challenge Project(No.TZ20180001)。
文摘Based on the generalized reduced R-matrix theory,the R-matrix analysis code(RAC program)was used to analyze the experimental data of all the nuclear reaction channels related to the 5 He system.The current calculations provide accurate and reliable evaluation data and are in good agreement with the experimental data.In this study,self-consistent evaluation data for each reaction were obtained using multi-channel and multi-energy fitting.In particular,the error propagation theory of generalized least squares was used to determine the error of the evaluation data and the covariance matrix of the integral cross section.This R-matrix analysis for the 5 He system has three features.First,for the first time,the error in the evaluation data of the T(d,n)^(4)He reaction cross section and the covariance matrix of the integral cross section are provided.Second,we used only one set of R-matrix parameters to depict the reaction cross section of each reaction channel of the 5 He system for the entire energy region in our work.Third,in this evaluation,we considered some of the latest measured experimental data,especially after 2000.The T(d,n)^(4)He reaction cross section at 0.1 MeV and below was carefully studied.The effect of different energy levels in T(d,n)^(4)He was analyzed,with the energy levels 3/2^(+)making a major contribution to the cross section,and the role of the S-wave and P-wave from 3/2~-determines the lean forward trend of the angular distributions at 0.01–0.1 MeV.
基金supported by Beijing Natural Science Foundation(L233025)。
文摘Functionally graded material(FGM)plates are widely used in various engineering structures owing to their tailor-made mechanical properties,whereas cracked homogeneous plates constitute a canonical setting in fracture mechanics analysis.These two classes of problems respectively embody material non-uniformity and geometric discontinuity,thereby imposing more stringent requirements on numerical methods in terms of high-order field continuity and accurate defect representation.Based on the classical Kirchhoff-Love plate theory,a numerical manifold method(MLS-NMM)incorporating moving least squares(MLS)interpolation is developed for bending analysis of FGM plates and fracture simulation of homogeneous plates with defects.The method constructs an H^(2)-regular approximation with high-order continuous weighting functions and,combined with the separation of mathematical and physical covers,establishes a unified framework that accurately handles material gradients and cracks without mesh reconstruction.For the crack tip,a singular physical cover incorporating the Williams asymptotic field is introduced to achieve local enrichment,enabling the natural capture of displacement discontinuity and stress singularity.Stress intensity factors are extracted using the interaction integral method,and the dimensionless J-integral shows a maximum relative error below 1.2%compared with the reference solution.Numerical results indicate that MLS-NMM exhibits excellent convergence performance:using 676 mathematical nodes,the nondimensional central deflection of both FGM and homogeneous plates agrees with reference solutions with a maximum relative error below 0.81%,and no shear locking occurs.A systematic analysis reveals that for a simply supported on all four edges(SSSS)FGM square plate with a/h=10,the nondimensional central deflection increases by 212%as the gradient index nrises from 0 to 5.For a homogeneous plate containing a central crack with c/a=0.6,the nondimensional central deflection increases by approximately 46%compared with the intact plate.Under weak boundary constraints(e.g.,SFSF),the deformation is markedly amplified,with the deflection reaching more than three times that under strong constraints(SCSC).The proposed method provides an efficient,reconstruction-free numerical tool for high-accuracy bending and fracture analyses of FGM and cracked thin-plate structures.
文摘Altun Mountains National Nature Reserve Established in 1983,the Altun Mountains National Nature Reserve is located in the eastern Kunlun Mountains,within Ruoqiang County of the Bayingolin Mongol Autonomous Prefecture in Xinjiang Uygur Autonomous Region.Covering a vast area of 45,000 square km,it stands as one of China’s largest and most pristine protected areas.With an average elevation of 4,580 metres,it represents a quintessential plateau desert ecosystem.
基金Ghent University,Belgium,for providing the research support for this study。
文摘Although various Climate-Smart Agricultural(CSA) practices are promoted to safeguard agricultural production and food security in the Global South,their adoption remains limited.This study conducted a cross-sectional survey using a semi-structured questionnaire between March and April in 2023,with a sample of 231 smallholder farmers covering 5 villages(Purbo Karpara,Rampasa,Monohor Pur,Boro Isubpur,and Char Alapur) in Haor wetlands of Bangladesh.Then,this study examined smallholder farmers' adoption intention of floating farming practice in Haor wetlands of Bangladesh based on an extended Theory of Planned Behaviour(TPB) model.The result demonstrated moderate predictive power of the proposed model,where farmers' attitude,subjective norm,knowledge of floating farming practice,perceived behavioural control,and institutional accessibility jointly explained 11.50% of the total variance in adoption intention,with subjective norm and perceived behavioural control showing significant impact on smallholder farmers' adoption intention.However,key barriers reported by smallholder farmers included unavailability of resources,limited access to modern farming practices,input and credit unavailability,insufficient access to training,and limited access to market system.These findings indicated that improving smallholder farmers' access to extension services and credit facilities,raising awareness,providing training,and guaranteeing access to accurate and timely climate information and early warning systems could significantly improve their adaptive capacity.This study contributes to socio-psychological understanding of smallholder farmers' pro-environmental behaviour and emphasises the need for context-specific interventions to support sustainable livelihoods and resilient agri-food systems in climate-vulnerable regions.
