Polyploidization is a commonly employed strategy in crop breeding to augment genetic diversity,particularly leveraging the distinctive benefits of additional progressive heterosis or multi-generation heterosis unique ...Polyploidization is a commonly employed strategy in crop breeding to augment genetic diversity,particularly leveraging the distinctive benefits of additional progressive heterosis or multi-generation heterosis unique to polyploidy.Despite genetic disparities between polyploids and diploids,challenges stem from reproductive anomalies,complicating genetic investigations in polyploid systems.Through nearly two decades of intensive research,our team has effectively generated a series of fertile tetraploid lines known as neo-tetraploid rice(NTR),facilitating comparative genetic studies between diploid and tetraploid rice.In this study,we identified diploid counterparts(H3d and H8d)for two NTR lines[Huaduo 3(H3)and Huaduo 8(H8)]and utilized them to create diploid and tetraploid fertile F_(2) populations to assess genotype segregation ratios,recombination rates,and their impact on QTL mapping via bulked segregant analysis combined with sequencing(BSA-seq).Additionally,we assessed yield heterosis in F_(1) and F_(2) generations of two tetraploid populations(H3×H8 and T449×H1),revealing evidence of multi-generation heterosis in polyploid rice.These findings provide valuable insights into the advantages and challenges of polyploid rice breeding.展开更多
[ Objective] The multiple mean generational function （MMGF） method was applied to forecast the annual number of typhoons （TYs） over the Western North Pacific （WNP）. [Method]The method yields a number of predicto...[ Objective] The multiple mean generational function （MMGF） method was applied to forecast the annual number of typhoons （TYs） over the Western North Pacific （WNP）. [Method]The method yields a number of predictors by mean generational function based on the rolling 50- year data of TYs frequency and sunspot number, and was repeated to generate forecasts year after year by optimal subset regression. [ Result] The results showed a reasonably high predictive ability dudng period 2000 -2010, with an average root mean square （RMSE） value of 1.92 and a mean absolute error （MAE） value of 1.64. [ Conclusion] Although the MMGF method needs further validation in the practical operation, it already has strong potential for the improvement of skill at forecasting annual frequency of TYs in the WNP.展开更多
This paper reports on a qualitative research study that examined the experience of expert and novice nurses participating in a new, reflective program of “clinical supervision”, intending to facilitate the transitio...This paper reports on a qualitative research study that examined the experience of expert and novice nurses participating in a new, reflective program of “clinical supervision”, intending to facilitate the transition of new graduate nurses into the workforce. Three patterns emerged during the constructivist inquiry: readiness to reflect, valuing of clinical supervision, and sustainability of the clinical supervision model. The researchers suggest generational sensitivity as a key perspective to consider when developing engaging workplace strategies for millennial nurses. The article offers recommendations for the implementation of clinical supervision and would be of interest to nurse leaders in a clinical setting.展开更多
One of the major concerns in today‘s business world is talent retention and development.Leading and working with multi-generational workforce in the age of digital transformation may seem daunting,but this paper argu...One of the major concerns in today‘s business world is talent retention and development.Leading and working with multi-generational workforce in the age of digital transformation may seem daunting,but this paper argues that it has its advantages in creating opportunities.Through interviews and case studies,this paper discovers that tensions in multi-generational collaboration often occur during the process of setting priorities for a group because different generations might have brought in different levels of capacity and willingness to take risks,and different levels of trust in,and care for people and the organization.The role of design in this context focuses more on capabilities,including observing generational behavioral nuances through practicing empathetic view,inviting people from different age into conversation and actively listening to them through the practice of shifting perspectives,and communicating complex situations through visualization and materialization for people to feel together.If we look at different generations in an organization as natural continuum of knowledge flow,if we see multigenerational workforce as one of driving forces to maintain organizational balance rather than tearing forces,and if we approach generational attributes with honesty,we could steer away from stereotypes and find common grounds to thrive together.展开更多
Climate, weather, and its attributes such as temperature and number of rainy days are essential for the success of many tourism destinations. As climate scientists have determined that climate changes are inevitable, ...Climate, weather, and its attributes such as temperature and number of rainy days are essential for the success of many tourism destinations. As climate scientists have determined that climate changes are inevitable, tourism destinations need to determine how to best manage these changes and mitigate any negative consequences. In addition, the perceived weather and/or climate at a destination can have as much weight on an individual＇s travel experience as the actual weather. The purpose of this study was to examine climate attributes and their importance on a traveler＇s behavior and satisfaction. Two hundred and sixty four surveys were gathered in the Mediterranean regions of Europe in the summer of 2009. Regression analysis revealed that climate attributes play a role in a traveler＇s satisfaction with their choice of a destination, but the traveler does not feel that climate changes are affecting their destinations as a whole. Analysis of variance （ANOVA） determined generational age differences in importance of climate attributes and if climate changes are affecting destinations. Management considerations for destination planners are explored.展开更多
This article explores the social transformation on account of surveillance conception preoccupied through the technology diffusion thanks to the Web 2.0 novel features.The new mediation abstracts the social provisions...This article explores the social transformation on account of surveillance conception preoccupied through the technology diffusion thanks to the Web 2.0 novel features.The new mediation abstracts the social provisions into radical customs of surveillance.It primes the supposition of socialization hitherto to transpire the scrutiny of the mutual rehearses of vertical and horizontal surveillance.Hence,the ultimate conversion keeps on through self-exposition notion in views of social interaction which so far posit the question of the privacy and public boundary owing to the hypothetical undue freedom of self-expression through Web 2.0.Thus,this paper examines the Surveillance Society in a comprehensive scope of the social structure vis-à-vis the ideas of generational submission towards social transformation.Using the dichotomy of digital revolutions,the Digital“Natives”are classified as typically addicted digital consumptions bearing the community outlooks,while Digital“Immigrants”persist in semi obedience along with the traditional adherence.Ultimately,the Panopticon conceptualizes the certainty of social surveillance by dint of proliferation of information flows keen on social conducts automated in both online and offline paths through technological appliances.展开更多
The COVID pandemic has accelerated the growth of ecommerce and reshaped shopping patterns,which in turn impacts trip-making and vehicle miles traveled.The objectives of this study are to define shopping styles and qua...The COVID pandemic has accelerated the growth of ecommerce and reshaped shopping patterns,which in turn impacts trip-making and vehicle miles traveled.The objectives of this study are to define shopping styles and quantify their prevalence in the population,investigate the impact of the pandemic on shopping style transition,understand the generational heterogeneity and other factors that influence shopping styles,and comment on the potential impact of the pandemic on long-term shopping behavior.Two months after the initial shutdown(May/June 2021),we collected ecommerce behavioral data from 313 Sacramento Region households using an online survey.A K-means clustering analysis of shopping behavior across eight commodity types identified five shopping styles,including ecommerce independent,ecommerce dependent,and three mixed modes in-between.We found that the share of ecommerce independent style shifted from 55%pre-pandemic to 27%during the pandemic.Overall,30%kept the same style as pre-pandemic,54%became more ecommerce dependent,and 16%became less ecommerce dependent,with the latter group more likely to view shopping an excuse to get out.Heterogeneity was found across generations.Pre-pandemic,Millennials and Gen Z were the most ecommerce dependent,but during the pandemic they made relatively small shifts toward increased ecommerce dependency.Baby Boomers and the Silent Generation were bimodal,either sticking to in-person shopping or shifting to ecommercedependency during the pandemic.Post-pandemic intentions varied across styles,with households who primarily adopt non-food ecommerce intending to reverse back to in-person shopping,while the highly ecommerce dependent intend to limit future in-store activities.展开更多
This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow con...This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow control technique utilizing a tubercle and vortex generator(VG)close to the leading edge was analyzed numerically for a NACA0015 airfoil.In this study,the Shear Stress Transport(SST)turbulence model was employed in the numerical modelling.Numerical modelling was completed using the ANSYS-Fluent 18.2 solver.Analyses were conducted to investigate the flow pattern and understand the underlying LSB control phenomena that enabled the new passive flow control method to provide this significant performance benefit.The findings indicated that the new concept of passive flow control technique suppressed the formation of an LSB at the suction surface of the NACA0015 airfoil,resulting in a higher lift coefficient and improved aerodynamic performance.Improvements in LSB dynamics and aerodynamic performance through the passive flow control method lead to increased energy output and enhanced stability.展开更多
Nonlinear Rossby waves are used to describe typical wave phenomena in large-scale atmosphere andocean.Owing to the nonlinearity of the involved problems,the weakly nonlinear method,ie the derivative ex-pansion method,...Nonlinear Rossby waves are used to describe typical wave phenomena in large-scale atmosphere andocean.Owing to the nonlinearity of the involved problems,the weakly nonlinear method,ie the derivative ex-pansion method,was mainly used to investigate Rossby waves under the combined effects of the generalizedβ-effect and the basic flow effect.The derivative expansion method has the advantage of capturing the multi-scalecharacteristics of wave processes simultaneously.In the case where the perturbation expansion is independentof secular terms,the nonlinear equations describing the amplitude evolution of nonlinear waves were derived,such as the Korteweg-de Vries equation,the Boussinesq equation and Zakharov-Kuznetsov equation.Both quali-tative and quantitative analyses indicate that the generalizedβ-effect is the key factor inducing the evolution ofRossby solitary waves.展开更多
The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adver...The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adversarial network(GAN)algorithm was proposed.Taking GAN as the basic framework,it combined a depthwise separable convolution module,attention mechanism,and reconstructed convolution module to realize the enhancement of underwater degraded images.Multi-scale features were captured by the depthwise separable convolution module,and the attention mechanism was utilized to enhance attention to important features.The reconstructed convolution module further extracts and fuses local and global features.Experimental results showed that the algorithm performs well in improving the color bias and blurring of underwater images,with PSNR reaching 27.835,SSIM reaching 0.883,UIQM reaching 3.205,and UCIQE reaching 0.713.The enhanced image outperforms the comparison algorithm in both subjective and objective metrics.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
In this study,three specific scenarios of a novel accelerator light source mechanism called steady-state microbunching(SSMB)were studied:longitudinal weak focusing,longitudinal strong focusing,and generalized longitud...In this study,three specific scenarios of a novel accelerator light source mechanism called steady-state microbunching(SSMB)were studied:longitudinal weak focusing,longitudinal strong focusing,and generalized longitudinal strong focusing(GLSF).At present,GLSF is the most promising method for realizing high-power short-wavelength coherent radiation with mild requirements on modulation laser power.Its essence is to exploit the ultrasmall natural vertical emittance of an electron beam in a planar storage ring for efficient microbunching formation,like a partial transverse-longitudinal emittance exchange in the optical laser wavelength range.Based on an in-depth investigation of related beam physics,a solution for a GLSF SSMB storage ring that can deliver 1 kW average-power EUV light is presented.The work in this paper,such as the generalized Courant–Snyder formalism,analysis of theoretical minimum emittances,transverse-longitudinal coupling dynamics,and derivation of the bunching factor and modulation strengths for laser-induced microbunching schemes,is expected to be useful not only for the development of SSMB but also for future accelerator light sources in general that demand increasingly precise electron beam phase space manipulations.展开更多
Virtor(VSG)technology is widely investigated and applied for dual synchronous generatoubly-fed induction generators(DFIGs)to provide virtual inertia.However,under grid faults,the conventional VSG-based DFIG faces chal...Virtor(VSG)technology is widely investigated and applied for dual synchronous generatoubly-fed induction generators(DFIGs)to provide virtual inertia.However,under grid faults,the conventional VSG-based DFIG faces challenges of transient overcurrent and instability.The critical limitation for grid-forming DFIGs to withstand serious grid faults is the rotor-side converter(RSC)’s inability to quickly generate proper rotor voltage to counteract transient electromotive force(EMF),which results in transient overcurrent and damage to the RSC.To fill this gap,this study introduces a novel low-voltage ride-through(LVRT)control strategy for the grid-forming DFIG under symmetrical grid fault conditions.To mitigate transient overcurrent,the core mechanism is to regulate the rotor flux linkage to align with the stator flux linkage in an optimal proportion.Under the proposed control strategy,both post-fault rotor current and required rotor voltage are constrained within operational limits.Moreover,fluctuations in electromagnetic torque are efficiently suppressed during grid disturbances.Consequently,the dynamic stability and power support capacity of the DFIG system remain intact throughout the transient process.Finally,simulation studies and experimental results are provided to verify the feasibility of the proposed approach.展开更多
Generative steganography uses generative stego images to transmit secret message.It also effectively defends against statistical steganalysis.However,most existing methods focus primarily on matching the feature distr...Generative steganography uses generative stego images to transmit secret message.It also effectively defends against statistical steganalysis.However,most existing methods focus primarily on matching the feature distribution of training data,often neglecting the sequential continuity between moves in the game.This oversight can result in unnatural patterns that deviate from real user behavior,thereby reducing the security of the hidden communication.To address this issue,we design a Gomoku agent based on the AlphaZero algorithm.The model engages in self-play to generate a sequence of plausible moves.These moves formthe basis of the stego images.We then apply an attractionmatrix at each step.It guides themove selection so that themoves appearmore natural.Thismethod helps maintain logical flow between moves.It also extends the game length,which increases the embedding capacity.Next,we filter and prioritize the generated moves.The selected moves are embedded into a move pool.Secret message is mapped to thesemoves.It is then embedded step by step as the game progresses.The finalmove sequence constitutes a complete steganographic game record.The receiver can extract the secret message using this record and a predefined mapping rule.Experiments show that our method reaches a maximum embedding capacity of 223 bits per carrier.Detection accuracy is 0.500 under XuNet and 0.498 under YeNet.These results are equal to random guessing,showing strong imperceptibility.The proposed method demonstrates superior concealment,higher embedding capacity,and greater robustness against common image distortions and steganalysis attacks.展开更多
Over the years,Generative Adversarial Networks(GANs)have revolutionized the medical imaging industry for applications such as image synthesis,denoising,super resolution,data augmentation,and cross-modality translation...Over the years,Generative Adversarial Networks(GANs)have revolutionized the medical imaging industry for applications such as image synthesis,denoising,super resolution,data augmentation,and cross-modality translation.The objective of this review is to evaluate the advances,relevances,and limitations of GANs in medical imaging.An organised literature review was conducted following the guidelines of PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses).The literature considered included peer-reviewed papers published between 2020 and 2025 across databases including PubMed,IEEE Xplore,and Scopus.The studies related to applications of GAN architectures in medical imaging with reported experimental outcomes and published in English in reputable journals and conferences were considered for the review.Thesis,white papers,communication letters,and non-English articles were not included for the same.CLAIM based quality assessment criteria were applied to the included studies to assess the quality.The study classifies diverse GAN architectures,summarizing their clinical applications,technical performances,and their implementation hardships.Key findings reveal the increasing applications of GANs for enhancing diagnostic accuracy,reducing data scarcity through synthetic data generation,and supporting modality translation.However,concerns such as limited generalizability,lack of clinical validation,and regulatory constraints persist.This review provides a comprehensive study of the prevailing scenario of GANs in medical imaging and highlights crucial research gaps and future directions.Though GANs hold transformative capability for medical imaging,their integration into clinical use demands further validation,interpretability,and regulatory alignment.展开更多
With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE ...With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE to stimulate students’innovative consciousness and teamwork ability,enabling students to identify some problems in a certain industry or field and creatively propose feasible solutions,and truly achieve the cultivation of new models in software engineering course teaching with the assistance of generative AI tools?This paper presents research and practice on a new model for cultivating software engineering courses that integrates generative AI and OBE,introduces the specific process of teaching reform and practice,and finally explains the achievements of teaching reform.展开更多
In recent years,researchers have leveraged single-agent reinforcement learning to boost educational outcomes and deliver personalized interventions;yet this paradigm provides no capacity for inter-agent interaction.Mu...In recent years,researchers have leveraged single-agent reinforcement learning to boost educational outcomes and deliver personalized interventions;yet this paradigm provides no capacity for inter-agent interaction.Multi-agent reinforcement learning(MARL)overcomes this limitation by allowing several agents to learn simultaneously within a shared environment,each choosing actions that maximize its own or the group's rewards.By explicitly modeling and exploiting agent-to-agent dynamics,MARL can align those interactions with pedagogical goals such as peer tutoring,collaborative problem-solving,or gamified competition,thus opening richer avenues for adaptive and socially informed learning experiences.This survey investigates the impact of MARL on educational outcomes by examining evidence of its effectiveness in enhancing learner performance,engagement,equity,and reducing teacher workload compared to single agent or traditional approaches.It explores the educational domains and pedagogical problems addressed by MARL,identifies the algorithmic families used,and analyzes their influence on learning.The review also assesses experimental settings and evaluation metrics to determine ecological validity,and outlines current challenges and future research directions in applying MARL to education.展开更多
Modern/distributed electric energy systems,with ever larger penetration of renewable(photovoltaic,wind,wave,and hydro)energy sources and time-variable outputs,are in need of stronger/higher frequency and alternating c...Modern/distributed electric energy systems,with ever larger penetration of renewable(photovoltaic,wind,wave,and hydro)energy sources and time-variable outputs,are in need of stronger/higher frequency and alternating current(AC)(direct current(DC))voltage control.In fact,faster and more stable active and reactive power in the presence of frequency and voltage sags and swells is needed.Power electronics-controlled variable speed generators do not have enough energy storage(inertia)for the scope(static synchronous compensators(STATCOMs)included).This is because power electronics tends to decouple the generator from the power system.While virtual inertia control in doubly fed induction generators(DFIGs)offers a partial solution to these problems,a more robust and comprehensive framework is required for advanced grid support.This is how,by extending the dual-excitation principles,the dualaxis excited electric synchronous generators(DE-SG)provide superior flexibility in two variants summarized here:as a multifunctional DFIG and dual-axis vs.single-axis excited synchronous generator(SG),and as a synchronous condenser(SC),with dual DC and AC excitation(as a no-load DFIG with inertia wheel),where variable speed is used to accelerate/decelerate the SC and thus provide additional assistance in frequency stabilization.These solutions,good for short-time transients,are not meant,however,to replace the large bidirectional energy storage systems(pump-hydro,hydrogen,batteries,etc.)which are crucial for the daily inherent variations of output energy in modern power systems with multiple power sources.The present paper offers a summary of techniques used in the dual-axis excited vs.single-axis excited SGs(SE-SGs),and SCs topologies,modeling,and control for better stability in modern multiple-source energy systems.This survey includes multiple case studies to shed light on prominent methods.展开更多
In order to address the issue of overly conservative offline reinforcement learning(RL) methods that limit the generalization of policy in the out-of-distribution(OOD) region,this article designs a surrogate target fo...In order to address the issue of overly conservative offline reinforcement learning(RL) methods that limit the generalization of policy in the out-of-distribution(OOD) region,this article designs a surrogate target for OOD value function based on dataset distance and proposes a novel generalized Q-learning mechanism with distance regularization(GQDR).In theory,we not only prove the convergence of GQDR,but also ensure that the difference between the Q-value learned by GQDR and its true value is bounded.Furthermore,an offline generalized actor-critic method with distance regularization(OGACDR) is proposed by combining GQDR with actor-critic learning framework.Two implementations of OGACDR,OGACDR-EXP and OGACDRSQR,are introduced according to exponential(EXP) and opensquare(SQR) distance weight functions,and it has been theoretically proved that OGACDR provides a safe policy improvement.Experimental results on Gym-MuJoCo continuous control tasks show that OGACDR can not only alleviate the overestimation and overconservatism of Q-value function,but also outperform conservative offline RL baselines.展开更多
基金supported by the National Key Resarch and Development Program of China(Grant No.2023YFD1200802)the Base Bank of Lingnan Rice Germplasm Resources Project,China(Grant No.2024B1212060009).
文摘Polyploidization is a commonly employed strategy in crop breeding to augment genetic diversity,particularly leveraging the distinctive benefits of additional progressive heterosis or multi-generation heterosis unique to polyploidy.Despite genetic disparities between polyploids and diploids,challenges stem from reproductive anomalies,complicating genetic investigations in polyploid systems.Through nearly two decades of intensive research,our team has effectively generated a series of fertile tetraploid lines known as neo-tetraploid rice(NTR),facilitating comparative genetic studies between diploid and tetraploid rice.In this study,we identified diploid counterparts(H3d and H8d)for two NTR lines[Huaduo 3(H3)and Huaduo 8(H8)]and utilized them to create diploid and tetraploid fertile F_(2) populations to assess genotype segregation ratios,recombination rates,and their impact on QTL mapping via bulked segregant analysis combined with sequencing(BSA-seq).Additionally,we assessed yield heterosis in F_(1) and F_(2) generations of two tetraploid populations(H3×H8 and T449×H1),revealing evidence of multi-generation heterosis in polyploid rice.These findings provide valuable insights into the advantages and challenges of polyploid rice breeding.
基金Supported by the Natural Science Fund of Education Department of Anhui Province (KJ2012Z097)
文摘[ Objective] The multiple mean generational function （MMGF） method was applied to forecast the annual number of typhoons （TYs） over the Western North Pacific （WNP）. [Method]The method yields a number of predictors by mean generational function based on the rolling 50- year data of TYs frequency and sunspot number, and was repeated to generate forecasts year after year by optimal subset regression. [ Result] The results showed a reasonably high predictive ability dudng period 2000 -2010, with an average root mean square （RMSE） value of 1.92 and a mean absolute error （MAE） value of 1.64. [ Conclusion] Although the MMGF method needs further validation in the practical operation, it already has strong potential for the improvement of skill at forecasting annual frequency of TYs in the WNP.
文摘This paper reports on a qualitative research study that examined the experience of expert and novice nurses participating in a new, reflective program of “clinical supervision”, intending to facilitate the transition of new graduate nurses into the workforce. Three patterns emerged during the constructivist inquiry: readiness to reflect, valuing of clinical supervision, and sustainability of the clinical supervision model. The researchers suggest generational sensitivity as a key perspective to consider when developing engaging workplace strategies for millennial nurses. The article offers recommendations for the implementation of clinical supervision and would be of interest to nurse leaders in a clinical setting.
文摘One of the major concerns in today‘s business world is talent retention and development.Leading and working with multi-generational workforce in the age of digital transformation may seem daunting,but this paper argues that it has its advantages in creating opportunities.Through interviews and case studies,this paper discovers that tensions in multi-generational collaboration often occur during the process of setting priorities for a group because different generations might have brought in different levels of capacity and willingness to take risks,and different levels of trust in,and care for people and the organization.The role of design in this context focuses more on capabilities,including observing generational behavioral nuances through practicing empathetic view,inviting people from different age into conversation and actively listening to them through the practice of shifting perspectives,and communicating complex situations through visualization and materialization for people to feel together.If we look at different generations in an organization as natural continuum of knowledge flow,if we see multigenerational workforce as one of driving forces to maintain organizational balance rather than tearing forces,and if we approach generational attributes with honesty,we could steer away from stereotypes and find common grounds to thrive together.
文摘Climate, weather, and its attributes such as temperature and number of rainy days are essential for the success of many tourism destinations. As climate scientists have determined that climate changes are inevitable, tourism destinations need to determine how to best manage these changes and mitigate any negative consequences. In addition, the perceived weather and/or climate at a destination can have as much weight on an individual＇s travel experience as the actual weather. The purpose of this study was to examine climate attributes and their importance on a traveler＇s behavior and satisfaction. Two hundred and sixty four surveys were gathered in the Mediterranean regions of Europe in the summer of 2009. Regression analysis revealed that climate attributes play a role in a traveler＇s satisfaction with their choice of a destination, but the traveler does not feel that climate changes are affecting their destinations as a whole. Analysis of variance （ANOVA） determined generational age differences in importance of climate attributes and if climate changes are affecting destinations. Management considerations for destination planners are explored.
文摘This article explores the social transformation on account of surveillance conception preoccupied through the technology diffusion thanks to the Web 2.0 novel features.The new mediation abstracts the social provisions into radical customs of surveillance.It primes the supposition of socialization hitherto to transpire the scrutiny of the mutual rehearses of vertical and horizontal surveillance.Hence,the ultimate conversion keeps on through self-exposition notion in views of social interaction which so far posit the question of the privacy and public boundary owing to the hypothetical undue freedom of self-expression through Web 2.0.Thus,this paper examines the Surveillance Society in a comprehensive scope of the social structure vis-à-vis the ideas of generational submission towards social transformation.Using the dichotomy of digital revolutions,the Digital“Natives”are classified as typically addicted digital consumptions bearing the community outlooks,while Digital“Immigrants”persist in semi obedience along with the traditional adherence.Ultimately,the Panopticon conceptualizes the certainty of social surveillance by dint of proliferation of information flows keen on social conducts automated in both online and offline paths through technological appliances.
基金funded by the University of California Institute of Transportation Studies'California Senate Bill 1 research program and the US Department of Transportation's Telemobility Tier 1 University Transportation Center(UTC).
文摘The COVID pandemic has accelerated the growth of ecommerce and reshaped shopping patterns,which in turn impacts trip-making and vehicle miles traveled.The objectives of this study are to define shopping styles and quantify their prevalence in the population,investigate the impact of the pandemic on shopping style transition,understand the generational heterogeneity and other factors that influence shopping styles,and comment on the potential impact of the pandemic on long-term shopping behavior.Two months after the initial shutdown(May/June 2021),we collected ecommerce behavioral data from 313 Sacramento Region households using an online survey.A K-means clustering analysis of shopping behavior across eight commodity types identified five shopping styles,including ecommerce independent,ecommerce dependent,and three mixed modes in-between.We found that the share of ecommerce independent style shifted from 55%pre-pandemic to 27%during the pandemic.Overall,30%kept the same style as pre-pandemic,54%became more ecommerce dependent,and 16%became less ecommerce dependent,with the latter group more likely to view shopping an excuse to get out.Heterogeneity was found across generations.Pre-pandemic,Millennials and Gen Z were the most ecommerce dependent,but during the pandemic they made relatively small shifts toward increased ecommerce dependency.Baby Boomers and the Silent Generation were bimodal,either sticking to in-person shopping or shifting to ecommercedependency during the pandemic.Post-pandemic intentions varied across styles,with households who primarily adopt non-food ecommerce intending to reverse back to in-person shopping,while the highly ecommerce dependent intend to limit future in-store activities.
基金the Scientific Research Projects Unit of Erciyes University under contract no:FDS-2022-11532 and FOA-2025-14773.
文摘This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow control technique utilizing a tubercle and vortex generator(VG)close to the leading edge was analyzed numerically for a NACA0015 airfoil.In this study,the Shear Stress Transport(SST)turbulence model was employed in the numerical modelling.Numerical modelling was completed using the ANSYS-Fluent 18.2 solver.Analyses were conducted to investigate the flow pattern and understand the underlying LSB control phenomena that enabled the new passive flow control method to provide this significant performance benefit.The findings indicated that the new concept of passive flow control technique suppressed the formation of an LSB at the suction surface of the NACA0015 airfoil,resulting in a higher lift coefficient and improved aerodynamic performance.Improvements in LSB dynamics and aerodynamic performance through the passive flow control method lead to increased energy output and enhanced stability.
文摘Nonlinear Rossby waves are used to describe typical wave phenomena in large-scale atmosphere andocean.Owing to the nonlinearity of the involved problems,the weakly nonlinear method,ie the derivative ex-pansion method,was mainly used to investigate Rossby waves under the combined effects of the generalizedβ-effect and the basic flow effect.The derivative expansion method has the advantage of capturing the multi-scalecharacteristics of wave processes simultaneously.In the case where the perturbation expansion is independentof secular terms,the nonlinear equations describing the amplitude evolution of nonlinear waves were derived,such as the Korteweg-de Vries equation,the Boussinesq equation and Zakharov-Kuznetsov equation.Both quali-tative and quantitative analyses indicate that the generalizedβ-effect is the key factor inducing the evolution ofRossby solitary waves.
文摘The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adversarial network(GAN)algorithm was proposed.Taking GAN as the basic framework,it combined a depthwise separable convolution module,attention mechanism,and reconstructed convolution module to realize the enhancement of underwater degraded images.Multi-scale features were captured by the depthwise separable convolution module,and the attention mechanism was utilized to enhance attention to important features.The reconstructed convolution module further extracts and fuses local and global features.Experimental results showed that the algorithm performs well in improving the color bias and blurring of underwater images,with PSNR reaching 27.835,SSIM reaching 0.883,UIQM reaching 3.205,and UCIQE reaching 0.713.The enhanced image outperforms the comparison algorithm in both subjective and objective metrics.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
基金supported by the National Key Research and Development Program of China(No.2022YFA1603401)National Natural Science Foundation of China(Nos.12035010 and 12342501)+1 种基金Beijing Outstanding Young Scientist Program(No.JWZQ20240101006)the Tsinghua University Dushi Program.
文摘In this study,three specific scenarios of a novel accelerator light source mechanism called steady-state microbunching(SSMB)were studied:longitudinal weak focusing,longitudinal strong focusing,and generalized longitudinal strong focusing(GLSF).At present,GLSF is the most promising method for realizing high-power short-wavelength coherent radiation with mild requirements on modulation laser power.Its essence is to exploit the ultrasmall natural vertical emittance of an electron beam in a planar storage ring for efficient microbunching formation,like a partial transverse-longitudinal emittance exchange in the optical laser wavelength range.Based on an in-depth investigation of related beam physics,a solution for a GLSF SSMB storage ring that can deliver 1 kW average-power EUV light is presented.The work in this paper,such as the generalized Courant–Snyder formalism,analysis of theoretical minimum emittances,transverse-longitudinal coupling dynamics,and derivation of the bunching factor and modulation strengths for laser-induced microbunching schemes,is expected to be useful not only for the development of SSMB but also for future accelerator light sources in general that demand increasingly precise electron beam phase space manipulations.
基金supported by the National Natural Science Foundation of China(No.52477195,No.U25B20204,No.52437009).
文摘Virtor(VSG)technology is widely investigated and applied for dual synchronous generatoubly-fed induction generators(DFIGs)to provide virtual inertia.However,under grid faults,the conventional VSG-based DFIG faces challenges of transient overcurrent and instability.The critical limitation for grid-forming DFIGs to withstand serious grid faults is the rotor-side converter(RSC)’s inability to quickly generate proper rotor voltage to counteract transient electromotive force(EMF),which results in transient overcurrent and damage to the RSC.To fill this gap,this study introduces a novel low-voltage ride-through(LVRT)control strategy for the grid-forming DFIG under symmetrical grid fault conditions.To mitigate transient overcurrent,the core mechanism is to regulate the rotor flux linkage to align with the stator flux linkage in an optimal proportion.Under the proposed control strategy,both post-fault rotor current and required rotor voltage are constrained within operational limits.Moreover,fluctuations in electromagnetic torque are efficiently suppressed during grid disturbances.Consequently,the dynamic stability and power support capacity of the DFIG system remain intact throughout the transient process.Finally,simulation studies and experimental results are provided to verify the feasibility of the proposed approach.
基金funded by theWuxi“Taihu Light”Science and Technology Key Project(Basic Research)(K20241046)the National Natural Science Foundation of China(Grant Nos.62102189,62122032,42305158)+1 种基金the Open Project of the National Engineering Research Center for Sensor Networks(2024YJZXKFKT02)Wuxi University Research Start-up Fund for High-Level Talents(No.2022r043).
文摘Generative steganography uses generative stego images to transmit secret message.It also effectively defends against statistical steganalysis.However,most existing methods focus primarily on matching the feature distribution of training data,often neglecting the sequential continuity between moves in the game.This oversight can result in unnatural patterns that deviate from real user behavior,thereby reducing the security of the hidden communication.To address this issue,we design a Gomoku agent based on the AlphaZero algorithm.The model engages in self-play to generate a sequence of plausible moves.These moves formthe basis of the stego images.We then apply an attractionmatrix at each step.It guides themove selection so that themoves appearmore natural.Thismethod helps maintain logical flow between moves.It also extends the game length,which increases the embedding capacity.Next,we filter and prioritize the generated moves.The selected moves are embedded into a move pool.Secret message is mapped to thesemoves.It is then embedded step by step as the game progresses.The finalmove sequence constitutes a complete steganographic game record.The receiver can extract the secret message using this record and a predefined mapping rule.Experiments show that our method reaches a maximum embedding capacity of 223 bits per carrier.Detection accuracy is 0.500 under XuNet and 0.498 under YeNet.These results are equal to random guessing,showing strong imperceptibility.The proposed method demonstrates superior concealment,higher embedding capacity,and greater robustness against common image distortions and steganalysis attacks.
基金supported by Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under grant number RGP2/540/46.
文摘Over the years,Generative Adversarial Networks(GANs)have revolutionized the medical imaging industry for applications such as image synthesis,denoising,super resolution,data augmentation,and cross-modality translation.The objective of this review is to evaluate the advances,relevances,and limitations of GANs in medical imaging.An organised literature review was conducted following the guidelines of PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses).The literature considered included peer-reviewed papers published between 2020 and 2025 across databases including PubMed,IEEE Xplore,and Scopus.The studies related to applications of GAN architectures in medical imaging with reported experimental outcomes and published in English in reputable journals and conferences were considered for the review.Thesis,white papers,communication letters,and non-English articles were not included for the same.CLAIM based quality assessment criteria were applied to the included studies to assess the quality.The study classifies diverse GAN architectures,summarizing their clinical applications,technical performances,and their implementation hardships.Key findings reveal the increasing applications of GANs for enhancing diagnostic accuracy,reducing data scarcity through synthetic data generation,and supporting modality translation.However,concerns such as limited generalizability,lack of clinical validation,and regulatory constraints persist.This review provides a comprehensive study of the prevailing scenario of GANs in medical imaging and highlights crucial research gaps and future directions.Though GANs hold transformative capability for medical imaging,their integration into clinical use demands further validation,interpretability,and regulatory alignment.
基金supported by the Shanghai Municipal Education Research Project“Exploring the Practical Application of Generative Artificial Intelligence in Cultivating Innovative Thinking and Capabilities of Interdisciplinary Application Technology Talents‘Practice Path’”(C2025299)the university-level postgraduate course project“Software Process Management”(PX-2025251502)of Shanghai Sanda Universitythe key course project at the university level of Shanghai Sanda University,“Introduction to Software Engineering”(PX-5241216).
文摘With the advent of the AI era,how can students effectively utilize generative AI large models to assist in course learning?At the same time,how can teachers utilize generative AI tools and the teaching concept of OBE to stimulate students’innovative consciousness and teamwork ability,enabling students to identify some problems in a certain industry or field and creatively propose feasible solutions,and truly achieve the cultivation of new models in software engineering course teaching with the assistance of generative AI tools?This paper presents research and practice on a new model for cultivating software engineering courses that integrates generative AI and OBE,introduces the specific process of teaching reform and practice,and finally explains the achievements of teaching reform.
文摘In recent years,researchers have leveraged single-agent reinforcement learning to boost educational outcomes and deliver personalized interventions;yet this paradigm provides no capacity for inter-agent interaction.Multi-agent reinforcement learning(MARL)overcomes this limitation by allowing several agents to learn simultaneously within a shared environment,each choosing actions that maximize its own or the group's rewards.By explicitly modeling and exploiting agent-to-agent dynamics,MARL can align those interactions with pedagogical goals such as peer tutoring,collaborative problem-solving,or gamified competition,thus opening richer avenues for adaptive and socially informed learning experiences.This survey investigates the impact of MARL on educational outcomes by examining evidence of its effectiveness in enhancing learner performance,engagement,equity,and reducing teacher workload compared to single agent or traditional approaches.It explores the educational domains and pedagogical problems addressed by MARL,identifies the algorithmic families used,and analyzes their influence on learning.The review also assesses experimental settings and evaluation metrics to determine ecological validity,and outlines current challenges and future research directions in applying MARL to education.
文摘Modern/distributed electric energy systems,with ever larger penetration of renewable(photovoltaic,wind,wave,and hydro)energy sources and time-variable outputs,are in need of stronger/higher frequency and alternating current(AC)(direct current(DC))voltage control.In fact,faster and more stable active and reactive power in the presence of frequency and voltage sags and swells is needed.Power electronics-controlled variable speed generators do not have enough energy storage(inertia)for the scope(static synchronous compensators(STATCOMs)included).This is because power electronics tends to decouple the generator from the power system.While virtual inertia control in doubly fed induction generators(DFIGs)offers a partial solution to these problems,a more robust and comprehensive framework is required for advanced grid support.This is how,by extending the dual-excitation principles,the dualaxis excited electric synchronous generators(DE-SG)provide superior flexibility in two variants summarized here:as a multifunctional DFIG and dual-axis vs.single-axis excited synchronous generator(SG),and as a synchronous condenser(SC),with dual DC and AC excitation(as a no-load DFIG with inertia wheel),where variable speed is used to accelerate/decelerate the SC and thus provide additional assistance in frequency stabilization.These solutions,good for short-time transients,are not meant,however,to replace the large bidirectional energy storage systems(pump-hydro,hydrogen,batteries,etc.)which are crucial for the daily inherent variations of output energy in modern power systems with multiple power sources.The present paper offers a summary of techniques used in the dual-axis excited vs.single-axis excited SGs(SE-SGs),and SCs topologies,modeling,and control for better stability in modern multiple-source energy systems.This survey includes multiple case studies to shed light on prominent methods.
基金supported by the National Natural Science Foundation of China(62373364,62176259)the Key Research and Development Program of Jiangsu Province(BE2022095)。
文摘In order to address the issue of overly conservative offline reinforcement learning(RL) methods that limit the generalization of policy in the out-of-distribution(OOD) region,this article designs a surrogate target for OOD value function based on dataset distance and proposes a novel generalized Q-learning mechanism with distance regularization(GQDR).In theory,we not only prove the convergence of GQDR,but also ensure that the difference between the Q-value learned by GQDR and its true value is bounded.Furthermore,an offline generalized actor-critic method with distance regularization(OGACDR) is proposed by combining GQDR with actor-critic learning framework.Two implementations of OGACDR,OGACDR-EXP and OGACDRSQR,are introduced according to exponential(EXP) and opensquare(SQR) distance weight functions,and it has been theoretically proved that OGACDR provides a safe policy improvement.Experimental results on Gym-MuJoCo continuous control tasks show that OGACDR can not only alleviate the overestimation and overconservatism of Q-value function,but also outperform conservative offline RL baselines.
