The current research of master cylinder pressure estimation mainly relies on hydraulic characteristic or vehicle dynamics.But they are not independently applicable to any environment and have their own scope of applic...The current research of master cylinder pressure estimation mainly relies on hydraulic characteristic or vehicle dynamics.But they are not independently applicable to any environment and have their own scope of application.In addition,about the master cylinder pressure control,there are few studies that can simultaneously balance pressure building accuracy,speed,and prevent pressure overshoot and jitter.In this paper,an adaptative fusion method based on electro-hydraulic characteristic and vehicle mode is proposed to estimate the master cylinder pressure.The fusion strategy is mainly based on the prediction performance of two algorithms under different vehicle speeds,pressures,and ABS states.Apart from this,this article also includes real-time prediction of the friction model based on RLS to improve the accuracy of the electro-hydraulic mode.In order to simultaneously balance pressure control accuracy,response speed,and prevent overshoot and jitter,this article proposes an adaptative LQR controller for MC pressure control which uses fuzzy-logic controller to adjust the weights of LQR controller based on target pressure and difference compared with actual pressure.Through mode-in-loop and hardware-in-loop tests in ramp,step and sinusoidal response,the whole estimation and control system is verified based on real hydraulic system and the performance is satisfactory under these scenes.This research proposes an adaptative pressure estimation and control architecture for integrated electro-hydraulic brake system which could eliminate pressure sensors in typical scenarios and ensure the comprehensive performance of pressure control.展开更多
Flexible zinc-air batteries(FZABs)are featured with safety and high theoretical capacity and become one of the ideal energy supply devices for flexible electronics.However,the lack of cost-effective electrocatalysts r...Flexible zinc-air batteries(FZABs)are featured with safety and high theoretical capacity and become one of the ideal energy supply devices for flexible electronics.However,the lack of cost-effective electrocatalysts remains a major obstacle to their commercialization.Herein,we synthesized a porous dodecahedral nitrogen-doped carbon(NC)material with Co and Mn bimetallic co-embedding(CoxMni-x@NC)as a highly efficient oxygen reduction reaction(ORR)catalyst for ZABs.The incorporation of Mn effectively modulates the electronic structure of Co sites,which may lead to optimized energetics with oxygen-containing intermediates thereby significantly enhancing catalytic performance.Notably,the optimized Co4Mn1@NC catalyst exhibits superior E1/2(0.86 V)and jL(limiting current density,5.96 mA cm-2)compared to Pt/C and other recent reports.Moreover,aqueous ZAB using Co4Mn1@NC as a cathodic catalyst demonstrates a high peak power density of 163.9 mW cm-2 and maintains stable charging and discharging for over 650 h.Furthermore,FZAB based on Co4Mn1@NC can steadily operate within the temperature range of-10 to 40 ℃,demonstrating the potential for practical applications in complex climatic conditions.展开更多
Postural control is based upon the fusion of sensory cues coming from multiple sources requiring continuously adaptation that may be altered due to aging, leading to the poor postural equilibrium in older adults. Ther...Postural control is based upon the fusion of sensory cues coming from multiple sources requiring continuously adaptation that may be altered due to aging, leading to the poor postural equilibrium in older adults. Therefore, the purpose of this study was to examine the adaptation in the relationship between the visual information and the body sway in older adults. Fifteen older (70 ± 7.6 years) and 15 younger adults (19 ± 1.1 years) stood upright inside of a moving room. Each participant performed 7 trials, each lasting 60 s, in which in the first 3 trials the room oscillated at 0.2 Hz, amplitude of 0.6 cm, and peak-to-peak velocity of 0.6 cm/s. In the fourth trial, the room oscillated at 0.2 Hz but with amplitude of 3.5 cm and peak-to-peak velocity of 3.5 cm/s. In the following 3 trials, the room oscillated with the same parameters of the first three trials. Body sway magnitude was examined through mean sway amplitude, and the relationship between visual information and induced body sway was examined through coherence and gain. Visual manipulation induced corresponding body sway in both older and younger adults, with no difference being observed between groups in the first three trials. In the fourth trial, mean sway amplitude, coherence and gain values were higher for the older compared to younger adults. Moreover, in the last three trials, older adults still showed higher gain values than observed for the younger adults. Taken together, these results suggest that older adults adapt to abrupt changes in visual cues, but not with the same magnitude as younger adults. Yet, older adults do not take advantage of experienced sensory changes in order to adapt the use of the vision information in the following experiences, indicating the less capability of adaptation to the sensory changes.展开更多
Purpose:This study aims to develop a transdisciplinary informal curriculum for climate change education(CCE)to increase the adaptive capacity of the small-farm milk-producing sector in Encarnacion de Diaz,Jalisco,M...Purpose:This study aims to develop a transdisciplinary informal curriculum for climate change education(CCE)to increase the adaptive capacity of the small-farm milk-producing sector in Encarnacion de Diaz,Jalisco,México.Design/Approach/Methods:A sustainable rural livelihood framework assessing six types of capital(animal,financial,human,natural,physical,and sociocultural)in a sequential exploratory method design was used to determine the adaptive capacity of 6l milk producers to climate change.Several interrelated aspects of capital are associated with milk producers'vulnerability to climate change.Findings:Dairy farmers'knowledge is based on traditional,historical,and cultural ways of interacting with their environment.Respecting this knowledge allowed us to use their experiential knowledge to co-jointly develop a CCE model to decrease the vulnerability of each of the six identified types of capital,with financial,human,and sociocultural capital being the most vulnerable.Originality/Value:Using local knowledge to cultivate adaptive actions for climate change and reducing the vulnerability of affected communities is essential when developing an informal CCE curriculum.展开更多
In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the op...In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.展开更多
1.Introduction The field of exercise science is experiencing a renaissance,with recent research illuminating the molecular,cellular,and systemic effects of physical activity.This is largely due to the now unequivocal ...1.Introduction The field of exercise science is experiencing a renaissance,with recent research illuminating the molecular,cellular,and systemic effects of physical activity.This is largely due to the now unequivocal evidence that a lack of physical activity,not only has direct effects on the prevalence of non-contagious diseases(NCDs)but has profound additive effects of other risk factors for NCD such as obesity and hypertension.1 The articles in this special topic of Journal of Sport and Health Science(JSHS)are dedicated to research on Exercise biochemistry&metabolism.展开更多
Background:Investigators from low-,middle-,and high-income countries representing 6 continents contributed to the development of the Global Adolescent and Child Physical Activity Questionnaire(GAC-PAQ).The GAC-PAQ is ...Background:Investigators from low-,middle-,and high-income countries representing 6 continents contributed to the development of the Global Adolescent and Child Physical Activity Questionnaire(GAC-PAQ).The GAC-PAQ is designed to assess physical activity(PA)across all key domains(i.e.,school,chores,work/volunteering,transport,free time,outdoor time).It aimed to address multiple gaps in global PA surveillance(e.g.,omission of important PA domains,insufficient cultural adaptation,underrepresentation of rural areas in questionnaire validation studies).The purpose of this study was to assess the content validity of the GAC-PAQ among PA experts,8-to 17-year-olds,and one of their parents/guardians,and to discuss changes made to the questionnaire based on participants'feedback.Methods:Sixty-two experts in PA measurement and/or surveillance from 24 countries completed an online survey that included both closed-and open-ended questions about the content validity of the GAC-PAQ.The proportion of experts who agreed or strongly agreed with the items was calculated.Child-parent/guardian dyads from 15 countries(n=250;10-40 per country)participated in a structured cognitive interview to assess the clarity of the questions and response options,and they were encouraged to provide suggestions to improve clarity and facilitate completion of the questionnaire.Participating countries are:Aotearoa New Zealand,Brazil,Canada,China,Colombia,Czech Republic,India,Malawi,Mexico,Nepal,Nigeria,Spain,Sweden,Thailand,and the United Arab Emirates.Interviews were conducted in 13 different languages and structured by PA domain.Generic images were included to help participants in answering questions about PA intensity.Results:Expert agreement with the items for each domain exceeded 75%,and their qualitative feedback was used to revise the questionnaire before cognitive interviews.In general,participants found the questionnaire to be comprehensive.Adolescents(12-17 years)found it easier than children(8-11 years)to answer the questions.Several children struggled to answer questions about the duration and intensity of activities and/or concepts related to travel modes,active trips,and organized activities.Many parents/guardians were unsure about the frequency,duration,and intensity of their children's or adolescents'PA at school and/or recommended using more culturally relevant and appropriate images.Some participants misunderstood the concept of activities that“make you stronger”(intended to assess resistance activities)and/or struggled to differentiate between work,volunteering,and chores.Conclusion:Participants'feedback was used to develop a revised,simplified,and culturally adapted GAC-PAQ,which will be pilot-tested in all15 countries in an App that will include country-specific images and narration in local languages.Further research is needed to assess the reliability and validity of the revised GAC-PAQ.展开更多
Starting from the foundational static traits underlying the growth and development of flue-cured tobacco, this research conducts a systematic examination of the phenomena and theoretical principles associated with env...Starting from the foundational static traits underlying the growth and development of flue-cured tobacco, this research conducts a systematic examination of the phenomena and theoretical principles associated with environment-driven adaptive changes during its cultivation. It was found that environmental variables-including temperature, light, and moisture-elicit directional shifts in static traits ( e.g. , chemical composition, morphological architecture, and leaf tissue structure) toward enhanced environmental adaptation, characterized by graduality, juvenility, similarity, and correlativity. Upon alterations in ambient conditions, flue-cured tobacco modulates its static traits through integrated physical, chemical, and biological-genetic mechanisms, aiming to optimize resource utilization, mitigate environmental constraints, and preserve internal homeostasis alongside metabolic balance. The investigation further reveals that the adaptive scope of flue-cured tobacco to field environments is malleable and can be extended and elevated via adaptive conditioning commencing at the juvenile stage. In addition, the adaptive alignment between static traits and environmental parameters exerts a substantial impact on the plant s growth dynamics, yield performance, and quality attributes. Beyond its relevance to flue-cured tobacco, the proposed theory offers a meaningful framework for elucidating the pervasive adaptive strategies employed by plants and broader biological systems in response to environmental contingencies.展开更多
Nursing education is undergoing a paradigm shift from skill training to clinical thinking cultivation.The integration of artificial intelligence technology offers technical possibilities for this transformation,but it...Nursing education is undergoing a paradigm shift from skill training to clinical thinking cultivation.The integration of artificial intelligence technology offers technical possibilities for this transformation,but it also brings about a deep tension between the cultivation of humanistic qualities and a standardized training.Based on the analysis of the practical forms of nursing smart education,this paper examines the cognitive gap between the deterministic feedback of virtual simulation systems and the complexity of real clinical scenarios,reveals the potential narrowing effect of data-driven ability profiling on the all-round development of nursing students,and then proposes the design logic of intelligent teaching resources centered on real clinical problems,a hierarchical teaching model with clear human-machine division of labor,and a dynamic assessment mechanism for technology application led by professional nursing teachers,in an attempt to find a balance between technological empowerment and humanistic commitment in smart nursing education.展开更多
With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided b...With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.展开更多
Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary freque...Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary frequency regulation(PFR),this paper proposes a novel hybrid energy storage system(HESS)control strategy based on Newton-Raphson optimization algorithm(NRBO)-VMD and a fuzzy neural network(FNN)for PFR.In the primary power allocation stage,the high inertia and slow response of thermal power units prevent them from promptly responding to the high-frequency components of PFR signals,leading to increased mechanical stress.To address the distinct response characteristics of thermal units and HESS,an NRBO-VMD based decomposition method for PFR signals is proposed,enabling a flexible system response to grid frequency deviations.Within the HESS,an adaptive coordinated control strategy and a State of Charge(SOC)self-recovery strategy are introduced.These strategies autonomously adjust the virtual inertia and droop coefficients based on the depth of frequency regulation and the real-time SOC.Furthermore,a FNN is constructed to perform secondary refinement of the internal power distribution within the HESS.Finally,simulations under various operational conditions demonstrate that the proposed strategy effectively mitigates frequent power adjustments of the thermal unit during PFR,adaptively achieves optimal power decomposition and distribution,maintains the flywheel energy storage’s SOC within an optimal range,and ensures the long-term stable operation of the HESS.展开更多
While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance re...While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance remains underexplored in field investigations.To evaluate the practical applicability of this emerging technique in adverse shallow sea channels,a field experiment was conducted using three communication modes:orthogonal frequency division multiplexing(OFDM),M-ary frequency-shift keying(MFSK),and direct sequence spread spectrum(DSSS)for reinforcement learning-driven adaptive modulation.Specifically,a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio,multipath spread length,and Doppler frequency offset.Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate,surpassing conventional adaptive modulation strategies.展开更多
In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail ...In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail to accurately characterize the complex influence of marine environments.To overcome these challenges,we propose an acoustic physics-informed intelligent path planning framework for underwater target search,integrating three core modules:The acoustic-physical modeling module adopts 3D ray-tracing theory and the active sonar equation to construct a physics-driven sonar detection model,explicitly accounting for environmental factors that influence sonar performance across heterogeneous spaces.The hybrid parallel computing module adopts a message passing interface(MPI)/open multi-processing(Open MP)hybrid strategy for large-scale acoustic simulations,combining computational domain decomposition and physics-intensive task acceleration.The search path optimization module adopts the covariance matrix adaptation evolution algorithm to solve continuous optimization problems of heading angles,which ensures maximum search coverage for targets.Largescale experiments conducted in the Pacific and Atlantic Oceans demonstrate the framework's effectiveness:(1)Precise capture of sonar detection range variations from 5.45 km to 50 km in heterogeneous marine environments.(2)Significant speedup of 453.43×for acoustic physics modeling through hybrid parallelization.(3)Notable improvements of 7.23%in detection coverage and 15.86%reduction in optimization time compared to the optimal baseline method.The framework provides a robust solution for underwater search missions in complex marine environments.展开更多
Accurate prediction and detection of the DNA regions or their underlying structural patterns are constant difficulties for researchers. Feature extraction and functional classification of genomic sequences is an inter...Accurate prediction and detection of the DNA regions or their underlying structural patterns are constant difficulties for researchers. Feature extraction and functional classification of genomic sequences is an interesting area of research. Many computational techniques have already been applied including the artificial neural network （ANN）, nonlinear model, spectrogram and statistical techniques. In this paper, some features are extracted from the wavelet coefficient and second set of features are extracted from the frequency of transition of nucleotides. These two features sets are examined. The purpose was to investigate the abilities of these parameters to predict critical segment in the DNA sequence. The neuro-fuzzy system was used for prediction. The performance of the neuro-fuzzy system was evaluated in terms of training performance and prediction accuracies. Two genomic sequences of the classes： prokaryotic and eukaryotic were used, as an example, （Escherichia coli） and （Caenorhabditis elegans） sequences were selected.展开更多
Cross-band camouflage technology is a critical necessity,enabling personnel and equipment to evade detection across evolving surveillance systems,thereby enhancing survivability and mission success.Herein,this work de...Cross-band camouflage technology is a critical necessity,enabling personnel and equipment to evade detection across evolving surveillance systems,thereby enhancing survivability and mission success.Herein,this work develops a layer-structured composite system based on carbon nanotube(CNT)film comprising ionic liquid(IL)interlayer for infrared(IR)modulation and surface-engineered Cu_(2)O nanoparticles for visible camouflage.The CNT/IL/CNT architecture enables reversible IR emissivity switching(Δε≈0.55)through electrically driven ion intercalation/deintercalation within 2 s,while spray-coated Cu_(2)O nanoparticles(100~400 nm diameter)on the top CNT film layer generate rich structure colors with 90%IR transmittance.This spectral-decoupling design overcomes the traditional trade-off between color visibility and IR transmittance observed in pigment-based systems.Remarkably,due to physical interface coupling,the Cu_(2)O-coated layer-structured system maintains exceptional electrical conductivity,enabling simultaneous electromagnetic interference shielding and electrothermal energy conversion.The integrated system demonstrates long-term operational stability.By unifying visible-IR camouflage,electromagnetic protection,and energy management in a lightweight platform,this work provides an important paradigm for cross-band camouflage technologies.展开更多
Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often stru...Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.展开更多
This paper aims to contribute to the development of spatial criteria for adaptive capacity,which is identified as one important factor for the transition towards more circular housing design.The paper focuses on the k...This paper aims to contribute to the development of spatial criteria for adaptive capacity,which is identified as one important factor for the transition towards more circular housing design.The paper focuses on the kitchen,as an important function of the home which is connected to large resource flows and is exposed to frequent renovations and replacements.This paper identifies spatial characteristics of the kitchen and evaluates their potential to accommodate circular solutions focusing on adaptive capacity.As a first step,previous literature on the spatial characteristics of kitchens and indicators that support adaptability is reviewed.These are then used to develop an analytical framework to assess the adaptive capacity and circularity potential of 3624 kitchens in contemporary Swedish apartments.A qualitative approach in combination with quantitative methods is employed to analyse the selected sample.The main contributions of this paper include its spatial analytical framework,its descriptive presentation of contemporary kitchen and apartment designs,and its adaptive capacity assessment of the studied kitchens.The results point out that although the overcapacity of the floor area of kitchens and apartments can have significance for adaptability,it is not the only determinative spatial characteristics.The windows’location and distribution,the number of door openings and traffic zones,the shafts’location and accessibility from multiple rooms,the room typology and the kitchen typology can improve the adaptive capacity and circularity potential of kitchens and dwellings.The findings show that in contemporary floorplans advantageous design solutions connected to the identified spatial characteristics are not applied in a systematic way.Further research is necessary to define the exact measures of the individual spatial characteristics and their combined application in multiresidential floorplan design.展开更多
The Industry 4.0 revolution is characterized by distributed infrastructures where data must be continuously communicated between hardware nodes and cloud servers.Specific lightweight cryptosystems are needed to protec...The Industry 4.0 revolution is characterized by distributed infrastructures where data must be continuously communicated between hardware nodes and cloud servers.Specific lightweight cryptosystems are needed to protect those links,as the hardware node tends to be resource-constrained.Then Pseudo Random Number Generators are employed to produce random keys,whose final behavior depends on the initial seed.To guarantee good mathematical behavior,most key generators need an unpredictable voltage signal as input.However,physical signals evolve slowly and have a significant autocorrelation,so they do not have enough entropy to support highrandomness seeds.Then,electronic mechanisms to generate those high-entropy signals artificially are required.This paper proposes a robust hyperchaotic circuit to obtain such unpredictable electric signals.The circuit is based on a hyperchaotic dynamic system,showing a large catalog of structures,four different secret parameters,and producing four high entropy voltage signals.Synchronization schemes for the correct secret key calculation and distribution among all remote communicating modules are also analyzed and discussed.Security risks and intruder and attacker models for the proposed solution are explored,too.An experimental validation based on circuit simulations and a real hardware implementation is provided.The results show that the random properties of PRNG improved by up to 11%when seeds were calculated through the proposed circuit.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.52202494,52202495)Chongqing Special Project for Technological Innovation and Application Development(Grant No.CSTB2022TIAD-DEX0014).
文摘The current research of master cylinder pressure estimation mainly relies on hydraulic characteristic or vehicle dynamics.But they are not independently applicable to any environment and have their own scope of application.In addition,about the master cylinder pressure control,there are few studies that can simultaneously balance pressure building accuracy,speed,and prevent pressure overshoot and jitter.In this paper,an adaptative fusion method based on electro-hydraulic characteristic and vehicle mode is proposed to estimate the master cylinder pressure.The fusion strategy is mainly based on the prediction performance of two algorithms under different vehicle speeds,pressures,and ABS states.Apart from this,this article also includes real-time prediction of the friction model based on RLS to improve the accuracy of the electro-hydraulic mode.In order to simultaneously balance pressure control accuracy,response speed,and prevent overshoot and jitter,this article proposes an adaptative LQR controller for MC pressure control which uses fuzzy-logic controller to adjust the weights of LQR controller based on target pressure and difference compared with actual pressure.Through mode-in-loop and hardware-in-loop tests in ramp,step and sinusoidal response,the whole estimation and control system is verified based on real hydraulic system and the performance is satisfactory under these scenes.This research proposes an adaptative pressure estimation and control architecture for integrated electro-hydraulic brake system which could eliminate pressure sensors in typical scenarios and ensure the comprehensive performance of pressure control.
基金supported by the National Natural Science Foundation of China(22275166,51972286and 22005268)the Zhejiang Provincial Natural Science Foundation of China(LZ21E020003and LQ20B010011)+2 种基金the Fundamental Research Funds for the Provincial Universities of Zhe-jiang(RF-B2023002and RF-C-2023025)the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang(2020R01002)China National University Student Innovation and Entrepreneurship Development Program(202310337065).
文摘Flexible zinc-air batteries(FZABs)are featured with safety and high theoretical capacity and become one of the ideal energy supply devices for flexible electronics.However,the lack of cost-effective electrocatalysts remains a major obstacle to their commercialization.Herein,we synthesized a porous dodecahedral nitrogen-doped carbon(NC)material with Co and Mn bimetallic co-embedding(CoxMni-x@NC)as a highly efficient oxygen reduction reaction(ORR)catalyst for ZABs.The incorporation of Mn effectively modulates the electronic structure of Co sites,which may lead to optimized energetics with oxygen-containing intermediates thereby significantly enhancing catalytic performance.Notably,the optimized Co4Mn1@NC catalyst exhibits superior E1/2(0.86 V)and jL(limiting current density,5.96 mA cm-2)compared to Pt/C and other recent reports.Moreover,aqueous ZAB using Co4Mn1@NC as a cathodic catalyst demonstrates a high peak power density of 163.9 mW cm-2 and maintains stable charging and discharging for over 650 h.Furthermore,FZAB based on Co4Mn1@NC can steadily operate within the temperature range of-10 to 40 ℃,demonstrating the potential for practical applications in complex climatic conditions.
文摘Postural control is based upon the fusion of sensory cues coming from multiple sources requiring continuously adaptation that may be altered due to aging, leading to the poor postural equilibrium in older adults. Therefore, the purpose of this study was to examine the adaptation in the relationship between the visual information and the body sway in older adults. Fifteen older (70 ± 7.6 years) and 15 younger adults (19 ± 1.1 years) stood upright inside of a moving room. Each participant performed 7 trials, each lasting 60 s, in which in the first 3 trials the room oscillated at 0.2 Hz, amplitude of 0.6 cm, and peak-to-peak velocity of 0.6 cm/s. In the fourth trial, the room oscillated at 0.2 Hz but with amplitude of 3.5 cm and peak-to-peak velocity of 3.5 cm/s. In the following 3 trials, the room oscillated with the same parameters of the first three trials. Body sway magnitude was examined through mean sway amplitude, and the relationship between visual information and induced body sway was examined through coherence and gain. Visual manipulation induced corresponding body sway in both older and younger adults, with no difference being observed between groups in the first three trials. In the fourth trial, mean sway amplitude, coherence and gain values were higher for the older compared to younger adults. Moreover, in the last three trials, older adults still showed higher gain values than observed for the younger adults. Taken together, these results suggest that older adults adapt to abrupt changes in visual cues, but not with the same magnitude as younger adults. Yet, older adults do not take advantage of experienced sensory changes in order to adapt the use of the vision information in the following experiences, indicating the less capability of adaptation to the sensory changes.
文摘Purpose:This study aims to develop a transdisciplinary informal curriculum for climate change education(CCE)to increase the adaptive capacity of the small-farm milk-producing sector in Encarnacion de Diaz,Jalisco,México.Design/Approach/Methods:A sustainable rural livelihood framework assessing six types of capital(animal,financial,human,natural,physical,and sociocultural)in a sequential exploratory method design was used to determine the adaptive capacity of 6l milk producers to climate change.Several interrelated aspects of capital are associated with milk producers'vulnerability to climate change.Findings:Dairy farmers'knowledge is based on traditional,historical,and cultural ways of interacting with their environment.Respecting this knowledge allowed us to use their experiential knowledge to co-jointly develop a CCE model to decrease the vulnerability of each of the six identified types of capital,with financial,human,and sociocultural capital being the most vulnerable.Originality/Value:Using local knowledge to cultivate adaptive actions for climate change and reducing the vulnerability of affected communities is essential when developing an informal CCE curriculum.
基金Supported by the National Natural Science Foundation of China(12071133)Natural Science Foundation of Henan Province(252300421993)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110005)。
文摘In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.
文摘1.Introduction The field of exercise science is experiencing a renaissance,with recent research illuminating the molecular,cellular,and systemic effects of physical activity.This is largely due to the now unequivocal evidence that a lack of physical activity,not only has direct effects on the prevalence of non-contagious diseases(NCDs)but has profound additive effects of other risk factors for NCD such as obesity and hypertension.1 The articles in this special topic of Journal of Sport and Health Science(JSHS)are dedicated to research on Exercise biochemistry&metabolism.
基金supported by a Project Grant(Grant No.PJT183705)an Early Career Investigator Prize(Grant No.ECP 184184)from the Canadian Institutes of Health Research+7 种基金a Prentice Institute Research Affiliate Fund Grant from the Prentice Institute for Global Population and Economy(Grant No.G00004116)a Te Herenga Waka Victoria University of Wellington Division of Science Health Engineering Architecture and Design Innovation Faculty Strategic Research Grant(Grant No.FSRG-SHEADI-10724)The Thailand Physical Activity Knowledge Development Centre(TPAK)/Thai Health Promotion Foundation provided funding for the cognitive interviews and pilot study in Thailand(Grant No.66-P1-0473)The University Pablo de Olavide provided a scholarship for 2 undergraduate students working on the project(codes PPI2207 and PPI2308)In the Czech Republicthe study was supported by Palacky University IGA(Grant No.IGA_FTK_2023_017)supported by the Division of Intramural Research at the National Institute on Minority Health and Health Disparities of the National Institutes of Healthsupported by the Key Project of the National Philosophy and Social Science Foundation of China(23&ZD197)。
文摘Background:Investigators from low-,middle-,and high-income countries representing 6 continents contributed to the development of the Global Adolescent and Child Physical Activity Questionnaire(GAC-PAQ).The GAC-PAQ is designed to assess physical activity(PA)across all key domains(i.e.,school,chores,work/volunteering,transport,free time,outdoor time).It aimed to address multiple gaps in global PA surveillance(e.g.,omission of important PA domains,insufficient cultural adaptation,underrepresentation of rural areas in questionnaire validation studies).The purpose of this study was to assess the content validity of the GAC-PAQ among PA experts,8-to 17-year-olds,and one of their parents/guardians,and to discuss changes made to the questionnaire based on participants'feedback.Methods:Sixty-two experts in PA measurement and/or surveillance from 24 countries completed an online survey that included both closed-and open-ended questions about the content validity of the GAC-PAQ.The proportion of experts who agreed or strongly agreed with the items was calculated.Child-parent/guardian dyads from 15 countries(n=250;10-40 per country)participated in a structured cognitive interview to assess the clarity of the questions and response options,and they were encouraged to provide suggestions to improve clarity and facilitate completion of the questionnaire.Participating countries are:Aotearoa New Zealand,Brazil,Canada,China,Colombia,Czech Republic,India,Malawi,Mexico,Nepal,Nigeria,Spain,Sweden,Thailand,and the United Arab Emirates.Interviews were conducted in 13 different languages and structured by PA domain.Generic images were included to help participants in answering questions about PA intensity.Results:Expert agreement with the items for each domain exceeded 75%,and their qualitative feedback was used to revise the questionnaire before cognitive interviews.In general,participants found the questionnaire to be comprehensive.Adolescents(12-17 years)found it easier than children(8-11 years)to answer the questions.Several children struggled to answer questions about the duration and intensity of activities and/or concepts related to travel modes,active trips,and organized activities.Many parents/guardians were unsure about the frequency,duration,and intensity of their children's or adolescents'PA at school and/or recommended using more culturally relevant and appropriate images.Some participants misunderstood the concept of activities that“make you stronger”(intended to assess resistance activities)and/or struggled to differentiate between work,volunteering,and chores.Conclusion:Participants'feedback was used to develop a revised,simplified,and culturally adapted GAC-PAQ,which will be pilot-tested in all15 countries in an App that will include country-specific images and narration in local languages.Further research is needed to assess the reliability and validity of the revised GAC-PAQ.
基金Supported by Changsha Tobacco Company Science and Technology Project(2020-2024A04).
文摘Starting from the foundational static traits underlying the growth and development of flue-cured tobacco, this research conducts a systematic examination of the phenomena and theoretical principles associated with environment-driven adaptive changes during its cultivation. It was found that environmental variables-including temperature, light, and moisture-elicit directional shifts in static traits ( e.g. , chemical composition, morphological architecture, and leaf tissue structure) toward enhanced environmental adaptation, characterized by graduality, juvenility, similarity, and correlativity. Upon alterations in ambient conditions, flue-cured tobacco modulates its static traits through integrated physical, chemical, and biological-genetic mechanisms, aiming to optimize resource utilization, mitigate environmental constraints, and preserve internal homeostasis alongside metabolic balance. The investigation further reveals that the adaptive scope of flue-cured tobacco to field environments is malleable and can be extended and elevated via adaptive conditioning commencing at the juvenile stage. In addition, the adaptive alignment between static traits and environmental parameters exerts a substantial impact on the plant s growth dynamics, yield performance, and quality attributes. Beyond its relevance to flue-cured tobacco, the proposed theory offers a meaningful framework for elucidating the pervasive adaptive strategies employed by plants and broader biological systems in response to environmental contingencies.
基金Funding Project for Ideological and Political Model Courses of“Epidemic Fighting”Courses in Henan Province(Project No.:531,2020)University-level Curriculum Ideological and Political Demonstration Course Support Project of Zhengzhou Sias University(Project No.:34,2024)+2 种基金University-level Key Discipline Support Project of Zhengzhou Sias University(Project No.:1,2022)2025 Key Scientific Research Projects of Henan Universities(Project No.:25B360003)Henan Province Private Brand Professional Support Project(Project No.:527,2019)。
文摘Nursing education is undergoing a paradigm shift from skill training to clinical thinking cultivation.The integration of artificial intelligence technology offers technical possibilities for this transformation,but it also brings about a deep tension between the cultivation of humanistic qualities and a standardized training.Based on the analysis of the practical forms of nursing smart education,this paper examines the cognitive gap between the deterministic feedback of virtual simulation systems and the complexity of real clinical scenarios,reveals the potential narrowing effect of data-driven ability profiling on the all-round development of nursing students,and then proposes the design logic of intelligent teaching resources centered on real clinical problems,a hierarchical teaching model with clear human-machine division of labor,and a dynamic assessment mechanism for technology application led by professional nursing teachers,in an attempt to find a balance between technological empowerment and humanistic commitment in smart nursing education.
基金financially supported by the Talent Initiation Fund of Wuxi University(550220008).
文摘With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.
基金supported by the Lanzhou Science and Technology Plan Project(XM1753694781389).
文摘Facing the economic challenges of significant frequency regulation wear and tear on thermal power units and short energy storage lifespan in thermal-energy storage combined systems participating in grid primary frequency regulation(PFR),this paper proposes a novel hybrid energy storage system(HESS)control strategy based on Newton-Raphson optimization algorithm(NRBO)-VMD and a fuzzy neural network(FNN)for PFR.In the primary power allocation stage,the high inertia and slow response of thermal power units prevent them from promptly responding to the high-frequency components of PFR signals,leading to increased mechanical stress.To address the distinct response characteristics of thermal units and HESS,an NRBO-VMD based decomposition method for PFR signals is proposed,enabling a flexible system response to grid frequency deviations.Within the HESS,an adaptive coordinated control strategy and a State of Charge(SOC)self-recovery strategy are introduced.These strategies autonomously adjust the virtual inertia and droop coefficients based on the depth of frequency regulation and the real-time SOC.Furthermore,a FNN is constructed to perform secondary refinement of the internal power distribution within the HESS.Finally,simulations under various operational conditions demonstrate that the proposed strategy effectively mitigates frequent power adjustments of the thermal unit during PFR,adaptively achieves optimal power decomposition and distribution,maintains the flywheel energy storage’s SOC within an optimal range,and ensures the long-term stable operation of the HESS.
基金funding from the National Key Research and Development Program of China(No.2018YFE0110000)the National Natural Science Foundation of China(No.11274259,No.11574258)the Science and Technology Commission Foundation of Shanghai(21DZ1205500)in support of the present research.
文摘While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research,its practical performance remains underexplored in field investigations.To evaluate the practical applicability of this emerging technique in adverse shallow sea channels,a field experiment was conducted using three communication modes:orthogonal frequency division multiplexing(OFDM),M-ary frequency-shift keying(MFSK),and direct sequence spread spectrum(DSSS)for reinforcement learning-driven adaptive modulation.Specifically,a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio,multipath spread length,and Doppler frequency offset.Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate,surpassing conventional adaptive modulation strategies.
基金supported by Natural Science Foundation of Hu'nan Province(2024JJ5409)。
文摘In underwater target search path planning,the accuracy of sonar models directly dictates the accurate assessment of search coverage.In contrast to physics-informed sonar models,traditional geometric sonar models fail to accurately characterize the complex influence of marine environments.To overcome these challenges,we propose an acoustic physics-informed intelligent path planning framework for underwater target search,integrating three core modules:The acoustic-physical modeling module adopts 3D ray-tracing theory and the active sonar equation to construct a physics-driven sonar detection model,explicitly accounting for environmental factors that influence sonar performance across heterogeneous spaces.The hybrid parallel computing module adopts a message passing interface(MPI)/open multi-processing(Open MP)hybrid strategy for large-scale acoustic simulations,combining computational domain decomposition and physics-intensive task acceleration.The search path optimization module adopts the covariance matrix adaptation evolution algorithm to solve continuous optimization problems of heading angles,which ensures maximum search coverage for targets.Largescale experiments conducted in the Pacific and Atlantic Oceans demonstrate the framework's effectiveness:(1)Precise capture of sonar detection range variations from 5.45 km to 50 km in heterogeneous marine environments.(2)Significant speedup of 453.43×for acoustic physics modeling through hybrid parallelization.(3)Notable improvements of 7.23%in detection coverage and 15.86%reduction in optimization time compared to the optimal baseline method.The framework provides a robust solution for underwater search missions in complex marine environments.
文摘Accurate prediction and detection of the DNA regions or their underlying structural patterns are constant difficulties for researchers. Feature extraction and functional classification of genomic sequences is an interesting area of research. Many computational techniques have already been applied including the artificial neural network （ANN）, nonlinear model, spectrogram and statistical techniques. In this paper, some features are extracted from the wavelet coefficient and second set of features are extracted from the frequency of transition of nucleotides. These two features sets are examined. The purpose was to investigate the abilities of these parameters to predict critical segment in the DNA sequence. The neuro-fuzzy system was used for prediction. The performance of the neuro-fuzzy system was evaluated in terms of training performance and prediction accuracies. Two genomic sequences of the classes： prokaryotic and eukaryotic were used, as an example, （Escherichia coli） and （Caenorhabditis elegans） sequences were selected.
基金Financial support from the National Nature Science Foundation of China(No.:52373244)the Foundation of National Science and Technology Key Laboratory(No.:KZ571801)。
文摘Cross-band camouflage technology is a critical necessity,enabling personnel and equipment to evade detection across evolving surveillance systems,thereby enhancing survivability and mission success.Herein,this work develops a layer-structured composite system based on carbon nanotube(CNT)film comprising ionic liquid(IL)interlayer for infrared(IR)modulation and surface-engineered Cu_(2)O nanoparticles for visible camouflage.The CNT/IL/CNT architecture enables reversible IR emissivity switching(Δε≈0.55)through electrically driven ion intercalation/deintercalation within 2 s,while spray-coated Cu_(2)O nanoparticles(100~400 nm diameter)on the top CNT film layer generate rich structure colors with 90%IR transmittance.This spectral-decoupling design overcomes the traditional trade-off between color visibility and IR transmittance observed in pigment-based systems.Remarkably,due to physical interface coupling,the Cu_(2)O-coated layer-structured system maintains exceptional electrical conductivity,enabling simultaneous electromagnetic interference shielding and electrothermal energy conversion.The integrated system demonstrates long-term operational stability.By unifying visible-IR camouflage,electromagnetic protection,and energy management in a lightweight platform,this work provides an important paradigm for cross-band camouflage technologies.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2025-02-01295).
文摘Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.
基金The final revision of this paper was Garried out within the Gircular Kitchen 2.0 project founded by Vastra Gotalandsregionen(project number:20232029)and Formas-A Swedish Research Council for Sustainable Development(project number:202102454).
文摘This paper aims to contribute to the development of spatial criteria for adaptive capacity,which is identified as one important factor for the transition towards more circular housing design.The paper focuses on the kitchen,as an important function of the home which is connected to large resource flows and is exposed to frequent renovations and replacements.This paper identifies spatial characteristics of the kitchen and evaluates their potential to accommodate circular solutions focusing on adaptive capacity.As a first step,previous literature on the spatial characteristics of kitchens and indicators that support adaptability is reviewed.These are then used to develop an analytical framework to assess the adaptive capacity and circularity potential of 3624 kitchens in contemporary Swedish apartments.A qualitative approach in combination with quantitative methods is employed to analyse the selected sample.The main contributions of this paper include its spatial analytical framework,its descriptive presentation of contemporary kitchen and apartment designs,and its adaptive capacity assessment of the studied kitchens.The results point out that although the overcapacity of the floor area of kitchens and apartments can have significance for adaptability,it is not the only determinative spatial characteristics.The windows’location and distribution,the number of door openings and traffic zones,the shafts’location and accessibility from multiple rooms,the room typology and the kitchen typology can improve the adaptive capacity and circularity potential of kitchens and dwellings.The findings show that in contemporary floorplans advantageous design solutions connected to the identified spatial characteristics are not applied in a systematic way.Further research is necessary to define the exact measures of the individual spatial characteristics and their combined application in multiresidential floorplan design.
基金supported by Comunidad de Madrid within the framework of the Multiannual Agreement with Universidad Politecnica de Madrid to encourage research by young doctors(PRINCE).
文摘The Industry 4.0 revolution is characterized by distributed infrastructures where data must be continuously communicated between hardware nodes and cloud servers.Specific lightweight cryptosystems are needed to protect those links,as the hardware node tends to be resource-constrained.Then Pseudo Random Number Generators are employed to produce random keys,whose final behavior depends on the initial seed.To guarantee good mathematical behavior,most key generators need an unpredictable voltage signal as input.However,physical signals evolve slowly and have a significant autocorrelation,so they do not have enough entropy to support highrandomness seeds.Then,electronic mechanisms to generate those high-entropy signals artificially are required.This paper proposes a robust hyperchaotic circuit to obtain such unpredictable electric signals.The circuit is based on a hyperchaotic dynamic system,showing a large catalog of structures,four different secret parameters,and producing four high entropy voltage signals.Synchronization schemes for the correct secret key calculation and distribution among all remote communicating modules are also analyzed and discussed.Security risks and intruder and attacker models for the proposed solution are explored,too.An experimental validation based on circuit simulations and a real hardware implementation is provided.The results show that the random properties of PRNG improved by up to 11%when seeds were calculated through the proposed circuit.
