Bioprinting is a revolutionary technology within the field of tissue engineering that enables the precise fabrication of three-dimensional(3D)tissue constructs.It combines the principles of engineering and biology to ...Bioprinting is a revolutionary technology within the field of tissue engineering that enables the precise fabrication of three-dimensional(3D)tissue constructs.It combines the principles of engineering and biology to create structures that closely mimic the complexity of native human tissues,facilitating advancements in regenerative medicine and personalized healthcare.This review paper systematically explores the challenges and design requirements in the fabrication of 3D biomimetic tissue constructs,emphasizing the need for advanced bioprinting strategies.Achieving biomimicry involves creating 3D anatomically relevant structures,biomimetic microenvironments,and vascularization.The focus is on overcoming existing bottlenecks through advancements in both fabrication techniques and bio-inks.Future directions in bioprinting are outlined,including multi-modal bioprinting systems,in-situ bioprinting,and the integration of machine learning into bioprinting processes.The critical role of bio-inks and printing methodologies in influencing cell viability is highlighted,providing insights into strategies for enhancing cellular functionality throughout the bioprinting process.Furthermore,the paper addresses post-fabrication considerations,particularly in accelerating tissue maturation,as a pivotal component for advancing the clinical applicability of bioprinted tissues.By navigating through the challenges,innovations,and prospects of advanced bioprinting strategies,this review highlights the transformative impact on tissue engineering.Pushing the boundaries of technological capabilities,these strategies hold the promise of groundbreaking advancements in regenerative medicine and personalized healthcare.Ultimately,the integration of these advanced techniques into bioprinting processes will pave the way for the development of more highly biomimetic and functional bioprinted tissues.展开更多
This study explores the externalities caused by managerial myopia from the perspective of carbon emissions in urban areas.Using panel data from 194 Chinese cities and 1286 listed companies from 2012 to 2021,this study...This study explores the externalities caused by managerial myopia from the perspective of carbon emissions in urban areas.Using panel data from 194 Chinese cities and 1286 listed companies from 2012 to 2021,this study empirically examines the effect of managerial myopia on urban carbon emissions.We integrate the“1+N”policy framework under China’s dual-carbon goals of peaking emssions by 2030 and achieving carbon neutrality by 2060,and propose a dual governance framework.The results show that managerial shortsightedness significantly contributes to urban carbon emissions,and this effect is particularly pronounced in cities with higher levels of carbon emissions and in first-and second-tier central cities.The mediating effect analysis indicate that managerial shortsightedness increases urban carbon emissions by inhibiting corporate green technological innovation.The moderating effect analysis shows that public media attention and government environmental regulation effectively mitigate the adverse impact of managerial myopia on urban carbon emissions.Theoretically,this study reveals the mechanism by which managerial shortsightedness increases urban carbon emissions by inhibiting green technology innovation and emphasizes the key roles of public media attention and government environmental regulation in mitigating this negative effect.This study provides important implications for policy rationale,especially for developing countries,for promoting green innovation and strengthening environmental governance to reduce carbon emissions.展开更多
This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully i...This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully integrated optimisation framework is developed accordingly,combining a single-objective Genetic Algorithm(GA)for design parameter generation,Computer-Aided Geometric Design(CAGD)for the creation of hull geometries and associated fluid domains,and a Reynolds-Averaged Navier-Stokes(RANS)solver for evaluating hydrodynamic performance metrics.This unified approach eliminates manual intervention,enabling automated determination of optimal hull configurations.Three distinct optimisation problems are addressed using the proposed methodology.First,the drag minimisation of a reference afterbody geometry(A1)at zero angle of attack is performed under constraints of fixed length and internal volume for various flow velocities spanning the range from 0.5 to 15 m/s.Second,the lift-to-drag ratio of A1 is maximised at a 6°angle of attack,maintaining constant total length and internal volume.Third,delivered power is minimised for A1 at a 0°angle of attack.The comparative analysis of results from all three optimisation cases reveals hull shapes with practical design significance.Notably,the shape optimised for minimum delivered power outperforms the other two across a range of velocities.Specifically,it achieves reductions in required power by 7.6%,7.8%,10.2%,and 13.04%at velocities of 0.5,1.0,1.5,and 2.152 m/s,respectively.展开更多
A coupled tide-surge-wave model was established to analyze the impacts of radial sand ridges on storm surges in the South Yellow Sea.Numerical topography experiments were designed on the basis of multiple well-verifie...A coupled tide-surge-wave model was established to analyze the impacts of radial sand ridges on storm surges in the South Yellow Sea.Numerical topography experiments were designed on the basis of multiple well-verified types of extreme weather events.The findings demonstrated that the radial sand ridges(RSRs)generally enhanced tidal levels,current velocities,and significant wave heights in the affected area.The nonlinear effects of shallow water in the radial sand ridge area can induce large tide ranges.A unique seabed can cause an increase in current speed from the open sea to the nearshore.Another impact is that subaqueous ridges can result in shallow water conditions,and the degree of depth-induced wave breaking significantly varies.Compared with those in the northern and southern radial sand ridge areas,the tidal levels,current speeds,and wave heights in the middle radial sand ridge area were the highest,which can cause more severe storm surge disasters.Additionally,the wave radiation stress varied obviously under the action of fan-shaped sand ridges.Thus,it is necessary to consider wave-current interactions when modeling storm surges in sand ridges.展开更多
In this study,the flow characteristics around a group of three piers arranged in tandem were investigated both numerically and experimentally.The simulation utilised the volume of fluid(VOF)model in conjunction with t...In this study,the flow characteristics around a group of three piers arranged in tandem were investigated both numerically and experimentally.The simulation utilised the volume of fluid(VOF)model in conjunction with the k–ɛmethod(i.e.,for flow turbulence representations),implemented through the ANSYS FLUENT software,to model the free-surface flow.The simulation results were validated against laboratory measurements obtained using an acoustic Doppler velocimeter.The comparative analysis revealed discrepancies between the simulated and measured maximum velocities within the investigated flow field.However,the numerical results demonstrated a distinct vortex-induced flow pattern following the first pier and throughout the vicinity of the entire pier group,which aligned reasonably well with experimental data.In the heavily narrowed spaces between the piers,simulated velocity profiles were overestimated in the free-surface region and underestimated in the areas near the bed to the mid-stream when compared to measurements.These discrepancies diminished away from the regions with intense vortices,indicating that the employed model was capable of simulating relatively less disturbed flow turbulence.Furthermore,velocity results from both simulations and measurements were compared based on velocity distributions at three different depth ratios(0.15,0.40,and 0.62)to assess vortex characteristic around the piers.This comparison revealed consistent results between experimental and simulated data.This research contributes to a deeper understanding of flow dynamics around complex interactive pier systems,which is critical for designing stable and sustainable hydraulic structures.Furthermore,the insights gained from this study provide valuable information for engineers aiming to develop effective strategies for controlling scour and minimizing destructive vortex effects,thereby guiding the design and maintenance of sustainable infrastructure.展开更多
Fundamental physics often confronts complex symbolic problems with few guiding exemplars or established principles.While artificial intelligence(AI)offers promise,its typical need for vast datasets to learn from hinde...Fundamental physics often confronts complex symbolic problems with few guiding exemplars or established principles.While artificial intelligence(AI)offers promise,its typical need for vast datasets to learn from hinders its use in these information-scarce frontiers.We introduce learning at criticality(LaC),a reinforcement learning scheme that tunes large language models(LLMs)to a sharp learning transition,addressing this information scarcity.At this transition,LLMs achieve peak generalization from minimal data,exemplified by 7-digit base-7 addition-a test of nontrivial arithmetic reasoning.To elucidate this peak,we analyze a minimal concept-network model designed to capture the essence of how LLMs might link tokens.Trained on a single exemplar,this model also undergoes a sharp learning transition.This transition exhibits hallmarks of a second-order phase transition,notably power-law distributed solution path lengths.At this critical point,the system maximizes a“critical thinking pattern”crucial for generalization,enabled by the underlying scale-free exploration.This suggests LLMs reach peak performance by operating at criticality,where such explorative dynamics enable the extraction of underlying operational rules.We demonstrate LaC in quantum field theory:an 8B-parameter LLM,tuned to its critical point by LaC using a few exemplars of symbolic Matsubara sums,solves unseen,higher-order problems,significantly outperforming far larger models.LaC thus leverages critical phenomena,a physical principle,to empower AI for complex,data-sparse challenges in fundamental physics.展开更多
基金support from NTU Presidential Postdoctoral Fellowshipthe support from the National Research Foundation,Singapore,under its NRF Investigatorship(NRFNRFI07-2021-007,Funding Awardee:Wai Yee Yeong)。
文摘Bioprinting is a revolutionary technology within the field of tissue engineering that enables the precise fabrication of three-dimensional(3D)tissue constructs.It combines the principles of engineering and biology to create structures that closely mimic the complexity of native human tissues,facilitating advancements in regenerative medicine and personalized healthcare.This review paper systematically explores the challenges and design requirements in the fabrication of 3D biomimetic tissue constructs,emphasizing the need for advanced bioprinting strategies.Achieving biomimicry involves creating 3D anatomically relevant structures,biomimetic microenvironments,and vascularization.The focus is on overcoming existing bottlenecks through advancements in both fabrication techniques and bio-inks.Future directions in bioprinting are outlined,including multi-modal bioprinting systems,in-situ bioprinting,and the integration of machine learning into bioprinting processes.The critical role of bio-inks and printing methodologies in influencing cell viability is highlighted,providing insights into strategies for enhancing cellular functionality throughout the bioprinting process.Furthermore,the paper addresses post-fabrication considerations,particularly in accelerating tissue maturation,as a pivotal component for advancing the clinical applicability of bioprinted tissues.By navigating through the challenges,innovations,and prospects of advanced bioprinting strategies,this review highlights the transformative impact on tissue engineering.Pushing the boundaries of technological capabilities,these strategies hold the promise of groundbreaking advancements in regenerative medicine and personalized healthcare.Ultimately,the integration of these advanced techniques into bioprinting processes will pave the way for the development of more highly biomimetic and functional bioprinted tissues.
基金supported by the Project of the Ministry of Education Humanities and Social Sciences Youth Fund[Grant No.24YJC 790245].
文摘This study explores the externalities caused by managerial myopia from the perspective of carbon emissions in urban areas.Using panel data from 194 Chinese cities and 1286 listed companies from 2012 to 2021,this study empirically examines the effect of managerial myopia on urban carbon emissions.We integrate the“1+N”policy framework under China’s dual-carbon goals of peaking emssions by 2030 and achieving carbon neutrality by 2060,and propose a dual governance framework.The results show that managerial shortsightedness significantly contributes to urban carbon emissions,and this effect is particularly pronounced in cities with higher levels of carbon emissions and in first-and second-tier central cities.The mediating effect analysis indicate that managerial shortsightedness increases urban carbon emissions by inhibiting corporate green technological innovation.The moderating effect analysis shows that public media attention and government environmental regulation effectively mitigate the adverse impact of managerial myopia on urban carbon emissions.Theoretically,this study reveals the mechanism by which managerial shortsightedness increases urban carbon emissions by inhibiting green technology innovation and emphasizes the key roles of public media attention and government environmental regulation in mitigating this negative effect.This study provides important implications for policy rationale,especially for developing countries,for promoting green innovation and strengthening environmental governance to reduce carbon emissions.
文摘This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully integrated optimisation framework is developed accordingly,combining a single-objective Genetic Algorithm(GA)for design parameter generation,Computer-Aided Geometric Design(CAGD)for the creation of hull geometries and associated fluid domains,and a Reynolds-Averaged Navier-Stokes(RANS)solver for evaluating hydrodynamic performance metrics.This unified approach eliminates manual intervention,enabling automated determination of optimal hull configurations.Three distinct optimisation problems are addressed using the proposed methodology.First,the drag minimisation of a reference afterbody geometry(A1)at zero angle of attack is performed under constraints of fixed length and internal volume for various flow velocities spanning the range from 0.5 to 15 m/s.Second,the lift-to-drag ratio of A1 is maximised at a 6°angle of attack,maintaining constant total length and internal volume.Third,delivered power is minimised for A1 at a 0°angle of attack.The comparative analysis of results from all three optimisation cases reveals hull shapes with practical design significance.Notably,the shape optimised for minimum delivered power outperforms the other two across a range of velocities.Specifically,it achieves reductions in required power by 7.6%,7.8%,10.2%,and 13.04%at velocities of 0.5,1.0,1.5,and 2.152 m/s,respectively.
基金financially supported by the Fundamental Research Funds for the Central Universities(Grant No.B210202031)the National Natural Science Foundation of China(Grant No.41606042)。
文摘A coupled tide-surge-wave model was established to analyze the impacts of radial sand ridges on storm surges in the South Yellow Sea.Numerical topography experiments were designed on the basis of multiple well-verified types of extreme weather events.The findings demonstrated that the radial sand ridges(RSRs)generally enhanced tidal levels,current velocities,and significant wave heights in the affected area.The nonlinear effects of shallow water in the radial sand ridge area can induce large tide ranges.A unique seabed can cause an increase in current speed from the open sea to the nearshore.Another impact is that subaqueous ridges can result in shallow water conditions,and the degree of depth-induced wave breaking significantly varies.Compared with those in the northern and southern radial sand ridge areas,the tidal levels,current speeds,and wave heights in the middle radial sand ridge area were the highest,which can cause more severe storm surge disasters.Additionally,the wave radiation stress varied obviously under the action of fan-shaped sand ridges.Thus,it is necessary to consider wave-current interactions when modeling storm surges in sand ridges.
文摘In this study,the flow characteristics around a group of three piers arranged in tandem were investigated both numerically and experimentally.The simulation utilised the volume of fluid(VOF)model in conjunction with the k–ɛmethod(i.e.,for flow turbulence representations),implemented through the ANSYS FLUENT software,to model the free-surface flow.The simulation results were validated against laboratory measurements obtained using an acoustic Doppler velocimeter.The comparative analysis revealed discrepancies between the simulated and measured maximum velocities within the investigated flow field.However,the numerical results demonstrated a distinct vortex-induced flow pattern following the first pier and throughout the vicinity of the entire pier group,which aligned reasonably well with experimental data.In the heavily narrowed spaces between the piers,simulated velocity profiles were overestimated in the free-surface region and underestimated in the areas near the bed to the mid-stream when compared to measurements.These discrepancies diminished away from the regions with intense vortices,indicating that the employed model was capable of simulating relatively less disturbed flow turbulence.Furthermore,velocity results from both simulations and measurements were compared based on velocity distributions at three different depth ratios(0.15,0.40,and 0.62)to assess vortex characteristic around the piers.This comparison revealed consistent results between experimental and simulated data.This research contributes to a deeper understanding of flow dynamics around complex interactive pier systems,which is critical for designing stable and sustainable hydraulic structures.Furthermore,the insights gained from this study provide valuable information for engineers aiming to develop effective strategies for controlling scour and minimizing destructive vortex effects,thereby guiding the design and maintenance of sustainable infrastructure.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFA1408604 for K.C.and X.C.)the National Natural Science Foundation of China(Grant Nos.12047503,12447103 for K.C.and X.C.,12325501 for P.Z.,and 12275263 for Y.D.and S.H.)+1 种基金the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301900 for Y.D.and S.H.)the Natural Science Foundation of Fujian Province of China(Grant No.2023J02032 for Y.D.and S.H.)。
文摘Fundamental physics often confronts complex symbolic problems with few guiding exemplars or established principles.While artificial intelligence(AI)offers promise,its typical need for vast datasets to learn from hinders its use in these information-scarce frontiers.We introduce learning at criticality(LaC),a reinforcement learning scheme that tunes large language models(LLMs)to a sharp learning transition,addressing this information scarcity.At this transition,LLMs achieve peak generalization from minimal data,exemplified by 7-digit base-7 addition-a test of nontrivial arithmetic reasoning.To elucidate this peak,we analyze a minimal concept-network model designed to capture the essence of how LLMs might link tokens.Trained on a single exemplar,this model also undergoes a sharp learning transition.This transition exhibits hallmarks of a second-order phase transition,notably power-law distributed solution path lengths.At this critical point,the system maximizes a“critical thinking pattern”crucial for generalization,enabled by the underlying scale-free exploration.This suggests LLMs reach peak performance by operating at criticality,where such explorative dynamics enable the extraction of underlying operational rules.We demonstrate LaC in quantum field theory:an 8B-parameter LLM,tuned to its critical point by LaC using a few exemplars of symbolic Matsubara sums,solves unseen,higher-order problems,significantly outperforming far larger models.LaC thus leverages critical phenomena,a physical principle,to empower AI for complex,data-sparse challenges in fundamental physics.
