In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
The rapid advancement of wearable electronic devices has paved the way for a more intelligent and interconnected world.However,ensuring the sustainable energy supply for these devices remains a critical challenge,part...The rapid advancement of wearable electronic devices has paved the way for a more intelligent and interconnected world.However,ensuring the sustainable energy supply for these devices remains a critical challenge,particularly for specialized populations and professionals in demanding environments,where a lack of power can pose life-threatening risks.Herein,we propose a mechanically intelligent biomechanical energy harvesting approach that adapts to complex human motion excitations,thereby improving the energy harvesting performance.Leveraging a mechanical intelligence mechanism,the energy harvester aligns with human physiological habits,selectively activating or deactivating as needed.The system can also adapt to excitations of varying directions,amplitudes,and frequencies.Furthermore,the string tension helps reduce the impact forces on the knee joint during foot strikes.A theoretical model for the biomechanical energy harvesting system is developed to describe its dynamic and electrical characteristics,and a prototype is fabricated and tested under diverse conditions.The experimental results are in good agreement with the simulation trends,validating the effectiveness of the theoretical model.A test subject running at 8 km/h for 90 seconds can successfully power a smartphone for 20 seconds,demonstrating the viability of self-powered applications.This mechanically intelligent biomechanical energy harvesting method holds a promising solution for the sustainable power supply for wearable electronic devices.展开更多
Predator–prey interactions are fundamental to understanding ecosystem stability and biodiversity.In this study,we propose and analyze a stochastic predator–prey model that incorporates two critical ecological factor...Predator–prey interactions are fundamental to understanding ecosystem stability and biodiversity.In this study,we propose and analyze a stochastic predator–prey model that incorporates two critical ecological factors:prey refuge and harvesting.The model also integrates disease transmission within the predator population,adding an important layer of realism.Using rigorous mathematical techniques,we demonstrate the existence and uniqueness of a global positive solution,thereby confirming the model's biological feasibility.We further derive sufficient conditions for two key ecological scenarios:stochastic permanence,which ensures the sustained co-existence of prey and predators over time,and extinction,where one or both populations decline to zero.The interplay between prey refuge and harvesting is thoroughly examined to understand their combined impact on population dynamics.All theoretical results are validated by detailed numerical simulations,highlighting the applicability of the model to real-world ecological systems.From the simulation results,we observed that with an adequate level of prey refuge and predator harvesting,the susceptible predator and prey coexist with extensive oscillations,while the infected predator population was moving towards extinction.In addition,we have investigated the effect of disease transmission on system dynamics.Our results show that,as the transmission rate of disease increases,the susceptible predator approaches extinction,whereas,on the other hand,when it declines,the susceptible predator shows robust oscillations while the infected approaches extinction.In both cases,the prey population demonstrates robust stability due to the prey refuge.Our findings show that the management of harvesting and the prey refuge can be effective ecological tactics for disease control and species protection under stochastic environmental effects.展开更多
Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competiti...Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.展开更多
China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision ...China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision of a community with a shared future.As this vision takes deeper root,many aid projects have moved from blueprint to reality,delivering tangible benefits across towns and villages and improving the lives of ordinary Lao people while further strengthening bilateral ties.展开更多
Understanding the relationship between dry matter yield and nutritive value throughout the growing season will help optimize the cutting intervals between harvests in alfalfa (Medicago sativa L.). The Ogallala Aquifer...Understanding the relationship between dry matter yield and nutritive value throughout the growing season will help optimize the cutting intervals between harvests in alfalfa (Medicago sativa L.). The Ogallala Aquifer is a very important water source when growing alfalfa in Southwest Kansas and unfortunately, the water level of the Ogallala Aquifer is shrinking. The objective of this study was to determine the optimum cutting interval that optimizes dry matter yield and nutritive values of alfalfa. Alfalfa was harvested with different cutting intervals, i.e., every 28, 35, 42 and 49 day, which was equivalent of 5, 4, 4, and 3 cuttings per year, respectively in 2013 and 2014. Based on 2-yr total yield, by delaying alfalfa harvest by 21 days, i.e., from every 28th day to 49th day, alfalfa yield increased by 2.25 Mg/ha whereas by 5.58 Mg/ha by delaying cutting intervals from every 28th day to 42nd day. Although harvesting alfalfa every 42nd day had the same cutting frequency as the 35th day treatment (i.e., 4 cuttings per year), the treatment harvesting every 42nd day had significantly higher alfalfa yield than 35th day cutting interval. Alfalfa yield increased by approximately 20% by delaying one week for harvesting alfalfa from 35th to 42nd day interval, based on dry matter yields of 2013 and 2014. As cutting interval increased from every 28th to 49th day, crude protein (CP) content decreased. In contrast to CP, acid detergent fiber and neutral detergent fiber increased as the cutting interval and stage of maturity increased in 2013 and 2014. The results suggest that alfalfa producers in Southwest Kansas possibly could reduce the cutting frequency from 5 to 4 per year. Cutting interval of every 42nd day between harvests appears to be the optimum when considered a dry matter yield and nutritive values in alfalfa.展开更多
Knee osteoarthritis(OA)is a debilitating condition with limited long-term treatment options.The therapeutic potential of mesenchymal stem cells(MSCs),particularly those derived from bone marrow aspirate concentrate,ha...Knee osteoarthritis(OA)is a debilitating condition with limited long-term treatment options.The therapeutic potential of mesenchymal stem cells(MSCs),particularly those derived from bone marrow aspirate concentrate,has garnered attention for cartilage repair in OA.While the iliac crest is the traditional site for bone marrow harvesting(BMH),associated morbidity has prompted the exploration of alternative sites such as the proximal tibia,distal femur,and proximal humerus.This paper reviews the impact of different harvesting sites on mesenchymal stem cell(MSC)yield,viability,and regenerative potential,emphasizing their relevance in knee OA treatment.The iliac crest consistently offers the highest MSC yield,but alternative sites within the surgical field of knee procedures offer comparable MSC characteristics with reduced morbidity.The integration of harvesting techniques into existing knee surgeries,such as total knee arthroplasty,provides a less invasive approach while maintaining thera-peutic efficacy.However,variability in MSC yield from these alternative sites underscores the need for further research to standardize techniques and optimize clinical outcomes.Future directions include large-scale comparative studies,advanced characterization of MSCs,and the development of personalized harvesting strategies.Ultimately,the findings suggest that optimizing the site of BMH can significantly influence the quality of MSC-based therapies for knee OA,enhancing their clinical utility and patient outcomes.展开更多
Polymeric microwave actuators combining tissue-like softness with programmablemicrowave-responsive deformation hold great promise for mobile intelligentdevices and bionic soft robots. However, their application is cha...Polymeric microwave actuators combining tissue-like softness with programmablemicrowave-responsive deformation hold great promise for mobile intelligentdevices and bionic soft robots. However, their application is challenged by restricted electromagneticsensitivity and intricate sensing coupling. In this study, a sensitized polymericmicrowave actuator is fabricated by hybridizing a liquid crystal polymer with Ti3C2Tx(MXene). Compared to the initial counterpart, the hybrid polymer exhibits unique spacechargepolarization and interfacial polarization, resulting in significant improvements of230% in the dielectric loss factor and 830% in the apparent efficiency of electromagneticenergy harvest. The sensitized microwave actuation demonstrates as the shortenedresponse time of nearly 10 s, which is merely 13% of that for the initial shape memory polymer. Moreover, the ultra-low content of MXene (upto 0.15 wt%) benefits for maintaining the actuation potential of the hybrid polymer. An innovative self-powered sensing prototype that combinesdriving and piezoelectric polymers is developed, which generates real-time electric potential feedback (open-circuit potential of ~ 3 mV) duringactuation. The polarization-dominant energy conversion mechanism observed in the MXene-polymer hybrid structure furnishes a new approachfor developing efficient electromagnetic dissipative structures and shows potential for advancing polymeric electromagnetic intelligent devices.展开更多
High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,inclu...High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported before.Herein,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese doping.Due to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese ions.The HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.展开更多
With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation ...With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.展开更多
Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power sta...Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power stations).To solve the problem,we propose an energy harvesting based task scheduling and resource management framework to provide robust and low-cost edge computing services for smart grid.First,we formulate an energy consumption minimization problem with regard to task offloading,time switching,and resource allocation for mobile devices,which can be decoupled and transformed into a typical knapsack problem.Then,solutions are derived by two different algorithms.Furthermore,we deploy renewable energy and energy storage units at edge servers to tackle intermittency and instability problems.Finally,we design an energy management algorithm based on sampling average approximation for edge computing servers to derive the optimal charging/discharging strategies,number of energy storage units,and renewable energy utilization.The simulation results show the efficiency and superiority of our proposed framework.展开更多
To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subj...To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subjected to Gaussian white noise and galloping excitation,simulating the flapping pattern of a seagull and its interaction with wind force.The equivalent linearization method is utilized to convert the original nonlinear model into the Itôstochastic differential equation by minimizing the mean squared error.Then,the second-order steady-state moments about the displacement,velocity,and voltage are derived by combining the moment analysis theory.The theoretical results are simulated numerically to analyze the stochastic response performance under different noise intensities,wind speeds,stiffness coefficients,and electromechanical coupling coefficients,time domain analysis is also conducted to study the performance of the harvester with different parameters.The results reveal that the mean square displacement and voltage increase with increasing the noise intensity and wind speed,larger absolute values of stiffness coefficient correspond to smaller mean square displacement and voltage,and larger electromechanical coupling coefficients can enhance the mean square voltage.Finally,the influence of wind speed and electromechanical coupling coefficient on the stationary probability density function(SPDF)is investigated,revealing the existence of a bimodal distribution under varying environmental conditions.展开更多
Nowadays, we are witnessing an era marked by the autonomy of wireless devices and sensor networks without the aid of batteries. RF energy harvesting therefore becomes a promising alternative for battery dependence. Th...Nowadays, we are witnessing an era marked by the autonomy of wireless devices and sensor networks without the aid of batteries. RF energy harvesting therefore becomes a promising alternative for battery dependence. This work presents the design of an RF energy harvesting system consisting mainly of a rectenna (antenna and rectification circuit) and an adaptation circuit. First of all, we designed two dipole type antennas. One operates in the GSM 900 MHz band and the other in the GSM 1800 MHz band. The performances of the proposed antennas are provided by the ANSYS HFSS software. Secondly, we proposed two rectification circuits in order to obtain conversion efficiencies at 0 dBm of 64% for the system operating at the frequency of 900 MHz and 37% for the system at the frequency of 1800 MHz RF-DC. The rectifiers used are based on Schottky diodes. For maximum transfer of power between the antenna and the rectification circuit, L-type matching circuits have been proposed. This rectifier offers DC voltage values of 806 mV for the circuit at the frequency of 900 MHz and 616 mV for the circuit at the frequency of 1800 MHz. The adaptation circuits are obtained by carrying out simulations on the ADS (Advanced Design System) software.展开更多
Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives ...Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.展开更多
Optimizing wind energy harvesting performance remains a significant challenge.Machine learning(ML)offers a promising approach for addressing this challenge.This study proposes an ML-based approach using the radial bas...Optimizing wind energy harvesting performance remains a significant challenge.Machine learning(ML)offers a promising approach for addressing this challenge.This study proposes an ML-based approach using the radial basis function neural network(RBFNN)and differential evolution(DE)to predict and optimize the structural parameters(the diameter of the spherical bluff body D,the total spring stiffness k,and the length of the piezoelectric cantilever beam L)of the wind energy harvester(WEH).The RBFNN model is trained with theoretical data and validated with wind tunnel experimental results,achieving the coefficient-of-determination scores R2of 97.8%and 90.3%for predicting the average output power Pavgand aero-electro-mechanical efficiencyηaem,respectively.The DE algorithm is used to identify the optimal parameter combinations for wind speeds U ranging from 2.5 m/s to 6.5 m/s.The maximum Pavgis achieved when D=57.5 mm,k=28.8 N/m,L=112.1 mm,and U=4.6 m/s,while the maximumηaemis achieved when D=52.7 mm,k=29.2 N/m,L=89.2 mm,and U=4.7 m/s.Compared with that of the non-optimized structure,the WEH performance is improved by 28.6%in P_(avg)and 19.1%inη_(aem).展开更多
BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs...BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.展开更多
Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when dat...Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when data are scarce.We introduce a fuzzy–set framework usingα-cut interval analysis to represent imprecise wave heights,periods,added mass,damping,and stiffness as fuzzy numbers.These are incorporated into the multi-body equations of motion and solved via a fuzzy Runge–Kutta scheme across nestedα-levels.A simulation architecture iterates overα-cuts and time-steps to produce interval bounds on heavy responses.A case study off the Karnataka coast,with realistic sea-state data for moderate and severe scenarios,yields heave-amplitude envelopes whose widths quantify response uncertainty.At mid-confidence(α=0.5),moderate seas produce amplitudes of 8.30–9.65 m(±15%),while severe seas yield 7.15–8.90 m(±22%).Envelope narrowing asα→1 confirms that increased parameter confidence reduces prediction spread,and bias analysis against crisp baselines highlights the impact of imprecision on mean responses.This non-probabilistic approach provides interpretable,worst-and best-case motion bounds without requiring large datasets,offering marine engineers robust safety margins and guidance for targeted data collection and real-time uncertainty updating.展开更多
The shortage of freshwater has become a global challenge,exacerbated by global warming and the rapid growth of the world’s population.Researchers across various fields have made numerous attempts to efficiently colle...The shortage of freshwater has become a global challenge,exacerbated by global warming and the rapid growth of the world’s population.Researchers across various fields have made numerous attempts to efficiently collect freshwater for human use.These efforts include seawater desalination through reverse osmosis or distillation,sewage treatment technologies,and atmospheric water harvesting.However,after thoroughly exploring traditional freshwater harvesting methods,it has become clear that bio-inspired fog harvesting technology offers new prospects due to its unique advantages of efficiency and sustainability.This paper systematically introduces the current principles of fog harvesting and wettability mechanism found in nature.It reviews the research status of combining bionic fog harvesting materials with textile science from two distinct dimensions.Additionally,it describes the practical applications of fog harvesting materials in agriculture,industry,and domestic water use,analyzes their prospects and feasibility in engineering projects,discusses potential challenges in practical applications,and envisions future trends and directions for the development of these materials.展开更多
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金Project supported by the National Natural Science Foundation of China(Nos.12202262,12172127,12032015,and 12121002)the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(No.2023QNRC001)the Hunan Province Science and Technology Innovation Program of China(Nos.2025JJ20012 and 2025RC4022)。
文摘The rapid advancement of wearable electronic devices has paved the way for a more intelligent and interconnected world.However,ensuring the sustainable energy supply for these devices remains a critical challenge,particularly for specialized populations and professionals in demanding environments,where a lack of power can pose life-threatening risks.Herein,we propose a mechanically intelligent biomechanical energy harvesting approach that adapts to complex human motion excitations,thereby improving the energy harvesting performance.Leveraging a mechanical intelligence mechanism,the energy harvester aligns with human physiological habits,selectively activating or deactivating as needed.The system can also adapt to excitations of varying directions,amplitudes,and frequencies.Furthermore,the string tension helps reduce the impact forces on the knee joint during foot strikes.A theoretical model for the biomechanical energy harvesting system is developed to describe its dynamic and electrical characteristics,and a prototype is fabricated and tested under diverse conditions.The experimental results are in good agreement with the simulation trends,validating the effectiveness of the theoretical model.A test subject running at 8 km/h for 90 seconds can successfully power a smartphone for 20 seconds,demonstrating the viability of self-powered applications.This mechanically intelligent biomechanical energy harvesting method holds a promising solution for the sustainable power supply for wearable electronic devices.
基金supported by the National Natural Science Foundation of China(Grant No.32271554)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011501)。
文摘Predator–prey interactions are fundamental to understanding ecosystem stability and biodiversity.In this study,we propose and analyze a stochastic predator–prey model that incorporates two critical ecological factors:prey refuge and harvesting.The model also integrates disease transmission within the predator population,adding an important layer of realism.Using rigorous mathematical techniques,we demonstrate the existence and uniqueness of a global positive solution,thereby confirming the model's biological feasibility.We further derive sufficient conditions for two key ecological scenarios:stochastic permanence,which ensures the sustained co-existence of prey and predators over time,and extinction,where one or both populations decline to zero.The interplay between prey refuge and harvesting is thoroughly examined to understand their combined impact on population dynamics.All theoretical results are validated by detailed numerical simulations,highlighting the applicability of the model to real-world ecological systems.From the simulation results,we observed that with an adequate level of prey refuge and predator harvesting,the susceptible predator and prey coexist with extensive oscillations,while the infected predator population was moving towards extinction.In addition,we have investigated the effect of disease transmission on system dynamics.Our results show that,as the transmission rate of disease increases,the susceptible predator approaches extinction,whereas,on the other hand,when it declines,the susceptible predator shows robust oscillations while the infected approaches extinction.In both cases,the prey population demonstrates robust stability due to the prey refuge.Our findings show that the management of harvesting and the prey refuge can be effective ecological tactics for disease control and species protection under stochastic environmental effects.
基金National Social Science Fund of China,No.24BTJ037Significant Project of the National Social Science Foundation of China,No.23&ZD102+1 种基金The Key Research Base for Philosophy and Social Sciences in Hangzhou:ESG and Sustainable Development Research Center,No.25JD053Zhejiang Provincial Statistical Scientific Research Project,No.25TJZZ12。
文摘Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.
基金supported by the Yunnan Provincial Philosophy and Social Science Planning Projectthe Yunnan Academy of Social Sciences。
文摘China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision of a community with a shared future.As this vision takes deeper root,many aid projects have moved from blueprint to reality,delivering tangible benefits across towns and villages and improving the lives of ordinary Lao people while further strengthening bilateral ties.
文摘Understanding the relationship between dry matter yield and nutritive value throughout the growing season will help optimize the cutting intervals between harvests in alfalfa (Medicago sativa L.). The Ogallala Aquifer is a very important water source when growing alfalfa in Southwest Kansas and unfortunately, the water level of the Ogallala Aquifer is shrinking. The objective of this study was to determine the optimum cutting interval that optimizes dry matter yield and nutritive values of alfalfa. Alfalfa was harvested with different cutting intervals, i.e., every 28, 35, 42 and 49 day, which was equivalent of 5, 4, 4, and 3 cuttings per year, respectively in 2013 and 2014. Based on 2-yr total yield, by delaying alfalfa harvest by 21 days, i.e., from every 28th day to 49th day, alfalfa yield increased by 2.25 Mg/ha whereas by 5.58 Mg/ha by delaying cutting intervals from every 28th day to 42nd day. Although harvesting alfalfa every 42nd day had the same cutting frequency as the 35th day treatment (i.e., 4 cuttings per year), the treatment harvesting every 42nd day had significantly higher alfalfa yield than 35th day cutting interval. Alfalfa yield increased by approximately 20% by delaying one week for harvesting alfalfa from 35th to 42nd day interval, based on dry matter yields of 2013 and 2014. As cutting interval increased from every 28th to 49th day, crude protein (CP) content decreased. In contrast to CP, acid detergent fiber and neutral detergent fiber increased as the cutting interval and stage of maturity increased in 2013 and 2014. The results suggest that alfalfa producers in Southwest Kansas possibly could reduce the cutting frequency from 5 to 4 per year. Cutting interval of every 42nd day between harvests appears to be the optimum when considered a dry matter yield and nutritive values in alfalfa.
文摘Knee osteoarthritis(OA)is a debilitating condition with limited long-term treatment options.The therapeutic potential of mesenchymal stem cells(MSCs),particularly those derived from bone marrow aspirate concentrate,has garnered attention for cartilage repair in OA.While the iliac crest is the traditional site for bone marrow harvesting(BMH),associated morbidity has prompted the exploration of alternative sites such as the proximal tibia,distal femur,and proximal humerus.This paper reviews the impact of different harvesting sites on mesenchymal stem cell(MSC)yield,viability,and regenerative potential,emphasizing their relevance in knee OA treatment.The iliac crest consistently offers the highest MSC yield,but alternative sites within the surgical field of knee procedures offer comparable MSC characteristics with reduced morbidity.The integration of harvesting techniques into existing knee surgeries,such as total knee arthroplasty,provides a less invasive approach while maintaining thera-peutic efficacy.However,variability in MSC yield from these alternative sites underscores the need for further research to standardize techniques and optimize clinical outcomes.Future directions include large-scale comparative studies,advanced characterization of MSCs,and the development of personalized harvesting strategies.Ultimately,the findings suggest that optimizing the site of BMH can significantly influence the quality of MSC-based therapies for knee OA,enhancing their clinical utility and patient outcomes.
基金supported by the National Natural Science Foundation of China(No.52373280,52177014,51977009,52273257)。
文摘Polymeric microwave actuators combining tissue-like softness with programmablemicrowave-responsive deformation hold great promise for mobile intelligentdevices and bionic soft robots. However, their application is challenged by restricted electromagneticsensitivity and intricate sensing coupling. In this study, a sensitized polymericmicrowave actuator is fabricated by hybridizing a liquid crystal polymer with Ti3C2Tx(MXene). Compared to the initial counterpart, the hybrid polymer exhibits unique spacechargepolarization and interfacial polarization, resulting in significant improvements of230% in the dielectric loss factor and 830% in the apparent efficiency of electromagneticenergy harvest. The sensitized microwave actuation demonstrates as the shortenedresponse time of nearly 10 s, which is merely 13% of that for the initial shape memory polymer. Moreover, the ultra-low content of MXene (upto 0.15 wt%) benefits for maintaining the actuation potential of the hybrid polymer. An innovative self-powered sensing prototype that combinesdriving and piezoelectric polymers is developed, which generates real-time electric potential feedback (open-circuit potential of ~ 3 mV) duringactuation. The polarization-dominant energy conversion mechanism observed in the MXene-polymer hybrid structure furnishes a new approachfor developing efficient electromagnetic dissipative structures and shows potential for advancing polymeric electromagnetic intelligent devices.
基金supported by the National Natural Science Foundation of China(Grant Nos.52272103 and 52072010)Beijing Natural Science Foundation(Grant Nos.2242029 and JL23004).
文摘High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless sensors.However,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported before.Herein,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese doping.Due to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese ions.The HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.
基金funded by Jilin Province Science and Technology Development Plan Project,grant number 20220203163SF.
文摘With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.
基金supported in part by the National Natural Science Foundation of China under Grant No.61473066in part by the Natural Science Foundation of Hebei Province under Grant No.F2021501020+2 种基金in part by the S&T Program of Qinhuangdao under Grant No.202401A195in part by the Science Research Project of Hebei Education Department under Grant No.QN2025008in part by the Innovation Capability Improvement Plan Project of Hebei Province under Grant No.22567637H
文摘Recently,one of the main challenges facing the smart grid is insufficient computing resources and intermittent energy supply for various distributed components(such as monitoring systems for renewable energy power stations).To solve the problem,we propose an energy harvesting based task scheduling and resource management framework to provide robust and low-cost edge computing services for smart grid.First,we formulate an energy consumption minimization problem with regard to task offloading,time switching,and resource allocation for mobile devices,which can be decoupled and transformed into a typical knapsack problem.Then,solutions are derived by two different algorithms.Furthermore,we deploy renewable energy and energy storage units at edge servers to tackle intermittency and instability problems.Finally,we design an energy management algorithm based on sampling average approximation for edge computing servers to derive the optimal charging/discharging strategies,number of energy storage units,and renewable energy utilization.The simulation results show the efficiency and superiority of our proposed framework.
文摘To further understand the performance of the energy harvesters under the influence of the wind force and the random excitation,this paper investigates the stochastic response of the bio-inspired energy harvesters subjected to Gaussian white noise and galloping excitation,simulating the flapping pattern of a seagull and its interaction with wind force.The equivalent linearization method is utilized to convert the original nonlinear model into the Itôstochastic differential equation by minimizing the mean squared error.Then,the second-order steady-state moments about the displacement,velocity,and voltage are derived by combining the moment analysis theory.The theoretical results are simulated numerically to analyze the stochastic response performance under different noise intensities,wind speeds,stiffness coefficients,and electromechanical coupling coefficients,time domain analysis is also conducted to study the performance of the harvester with different parameters.The results reveal that the mean square displacement and voltage increase with increasing the noise intensity and wind speed,larger absolute values of stiffness coefficient correspond to smaller mean square displacement and voltage,and larger electromechanical coupling coefficients can enhance the mean square voltage.Finally,the influence of wind speed and electromechanical coupling coefficient on the stationary probability density function(SPDF)is investigated,revealing the existence of a bimodal distribution under varying environmental conditions.
文摘Nowadays, we are witnessing an era marked by the autonomy of wireless devices and sensor networks without the aid of batteries. RF energy harvesting therefore becomes a promising alternative for battery dependence. This work presents the design of an RF energy harvesting system consisting mainly of a rectenna (antenna and rectification circuit) and an adaptation circuit. First of all, we designed two dipole type antennas. One operates in the GSM 900 MHz band and the other in the GSM 1800 MHz band. The performances of the proposed antennas are provided by the ANSYS HFSS software. Secondly, we proposed two rectification circuits in order to obtain conversion efficiencies at 0 dBm of 64% for the system operating at the frequency of 900 MHz and 37% for the system at the frequency of 1800 MHz RF-DC. The rectifiers used are based on Schottky diodes. For maximum transfer of power between the antenna and the rectification circuit, L-type matching circuits have been proposed. This rectifier offers DC voltage values of 806 mV for the circuit at the frequency of 900 MHz and 616 mV for the circuit at the frequency of 1800 MHz. The adaptation circuits are obtained by carrying out simulations on the ADS (Advanced Design System) software.
基金supported by the National Natural Science Foundation of China,Nos.82071426,81873784Clinical Cohort Construction Program of Peking University Third Hospital,No.BYSYDL2019002(all to DF)。
文摘Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.
基金Project supported by the National Key R&D Program of China(No.2021YFF0501001)the National Natural Science Foundation of China(Nos.52308315,51922046,and 52192661)+3 种基金the Research Funds of Huazhong University of Science and Technology(No.2023JCYJ014)the China Postdoctoral Science Foundation(No.2023M731206)the Research Funds of China Railway Siyuan Survey and Design Group Co.Ltd.(Nos.KY2023014S,KY2023126S,2021K085,2020K006,and 2020K172)the Autonomous Innovation Fund of Hubei Province of China(No.5003242027)。
文摘Optimizing wind energy harvesting performance remains a significant challenge.Machine learning(ML)offers a promising approach for addressing this challenge.This study proposes an ML-based approach using the radial basis function neural network(RBFNN)and differential evolution(DE)to predict and optimize the structural parameters(the diameter of the spherical bluff body D,the total spring stiffness k,and the length of the piezoelectric cantilever beam L)of the wind energy harvester(WEH).The RBFNN model is trained with theoretical data and validated with wind tunnel experimental results,achieving the coefficient-of-determination scores R2of 97.8%and 90.3%for predicting the average output power Pavgand aero-electro-mechanical efficiencyηaem,respectively.The DE algorithm is used to identify the optimal parameter combinations for wind speeds U ranging from 2.5 m/s to 6.5 m/s.The maximum Pavgis achieved when D=57.5 mm,k=28.8 N/m,L=112.1 mm,and U=4.6 m/s,while the maximumηaemis achieved when D=52.7 mm,k=29.2 N/m,L=89.2 mm,and U=4.7 m/s.Compared with that of the non-optimized structure,the WEH performance is improved by 28.6%in P_(avg)and 19.1%inη_(aem).
文摘BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.
文摘Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when data are scarce.We introduce a fuzzy–set framework usingα-cut interval analysis to represent imprecise wave heights,periods,added mass,damping,and stiffness as fuzzy numbers.These are incorporated into the multi-body equations of motion and solved via a fuzzy Runge–Kutta scheme across nestedα-levels.A simulation architecture iterates overα-cuts and time-steps to produce interval bounds on heavy responses.A case study off the Karnataka coast,with realistic sea-state data for moderate and severe scenarios,yields heave-amplitude envelopes whose widths quantify response uncertainty.At mid-confidence(α=0.5),moderate seas produce amplitudes of 8.30–9.65 m(±15%),while severe seas yield 7.15–8.90 m(±22%).Envelope narrowing asα→1 confirms that increased parameter confidence reduces prediction spread,and bias analysis against crisp baselines highlights the impact of imprecision on mean responses.This non-probabilistic approach provides interpretable,worst-and best-case motion bounds without requiring large datasets,offering marine engineers robust safety margins and guidance for targeted data collection and real-time uncertainty updating.
基金Shandong Provincial Key Research and Development Program(Major Scientific and Technological Innovation Project)(2021CXGC011001)Huafon Microfibre(Jiangsu)Co.Ltd.(2021120011000234)+1 种基金Textile Vision Basic Research Program(J202306)China Postdoctoral Science Foundation(No.2023M732103).
文摘The shortage of freshwater has become a global challenge,exacerbated by global warming and the rapid growth of the world’s population.Researchers across various fields have made numerous attempts to efficiently collect freshwater for human use.These efforts include seawater desalination through reverse osmosis or distillation,sewage treatment technologies,and atmospheric water harvesting.However,after thoroughly exploring traditional freshwater harvesting methods,it has become clear that bio-inspired fog harvesting technology offers new prospects due to its unique advantages of efficiency and sustainability.This paper systematically introduces the current principles of fog harvesting and wettability mechanism found in nature.It reviews the research status of combining bionic fog harvesting materials with textile science from two distinct dimensions.Additionally,it describes the practical applications of fog harvesting materials in agriculture,industry,and domestic water use,analyzes their prospects and feasibility in engineering projects,discusses potential challenges in practical applications,and envisions future trends and directions for the development of these materials.
