It has been reported that the PI3K/AKT signaling pathway plays a key role in the pathogenesis of ischemic stroke.As a result,the development of drugs targeting the PI3K/AKT signaling pathway has attracted increasing a...It has been reported that the PI3K/AKT signaling pathway plays a key role in the pathogenesis of ischemic stroke.As a result,the development of drugs targeting the PI3K/AKT signaling pathway has attracted increasing attention from researchers.This article reviews the pathological mechanisms and advancements in research related to the signaling pathways in ischemic stroke,with a focus on the PI3K/AKT signaling pathway.The key findings include the following:(1)The complex pathological mechanisms of ischemic stroke can be categorized into five major types:excitatory amino acid toxicity,Ca^(2+)overload,inflammatory response,oxidative stress,and apoptosis.(2)The PI3K/AKT-mediated signaling pathway is closely associated with the occurrence and progression of ischemic stroke,which primarily involves the NF-κB,NRF2,BCL-2,mTOR,and endothelial NOS signaling pathways.(3)Natural products,including flavonoids,quinones,alkaloids,phenylpropanoids,phenols,terpenoids,and iridoids,show great potential as candidate substances for the development of innovative anti-stroke medications.(4)Recently,novel therapeutic techniques,such as electroacupuncture and mesenchymal stem cell therapy,have demonstrated the potential to improve stroke outcomes by activating the PI3K/AKT signaling pathway,providing new possibilities for the treatment and rehabilitation of patients with ischemic stroke.Future investigations should focus on the direct regulatory mechanisms of drugs targeting the PI3K/AKT signaling pathway and their clinical translation to develop innovative treatment strategies for ischemic stroke.展开更多
Recovering human pose from RGB images and videos has drawn increasing attention in recent years owing to minimum sensor requirements and applicability in diverse fields such as human-computer interaction,robotics,vide...Recovering human pose from RGB images and videos has drawn increasing attention in recent years owing to minimum sensor requirements and applicability in diverse fields such as human-computer interaction,robotics,video analytics,and augmented reality.Although a large amount of work has been devoted to this field,3D human pose estimation based on monocular images or videos remains a very challenging task due to a variety of difficulties such as depth ambiguities,occlusion,background clutters,and lack of training data.In this survey,we summarize recent advances in monocular 3D human pose estimation.We provide a general taxonomy to cover existing approaches and analyze their capabilities and limitations.We also present a summary of extensively used datasets and metrics,and provide a quantitative comparison of some representative methods.Finally,we conclude with a discussion on realistic challenges and open problems for future research directions.展开更多
Angular optical trapping based on Janus microspheres has been proven to be a novel method to achieve controllable rotation.In contrast to natural birefringent crystals,Janus microspheres are chemically synthesized of ...Angular optical trapping based on Janus microspheres has been proven to be a novel method to achieve controllable rotation.In contrast to natural birefringent crystals,Janus microspheres are chemically synthesized of two compositions with different refractive indices.Thus,their structures can be artificially regulated,which brings excellent potential for fine and multi-degree-of-freedom manipulation in the optical field.However,it is a considerable challenge to model the interaction of heterogeneous particles with the optical field,and there has also been no experimental study on the optical manipulation of microspheres with such designable refractive index distributions.How the specific structure affects the kinematic properties of Janus microspheres remains unknown.Here,we report systematic research on the optical trapping and rotating of various ratio-designable Janus microspheres.We employ an efficient T-matrix method to rapidly calculate the optical force and torque on Janus microspheres to obtain their trapped postures and rotational characteristics in the optical field.We have developed a robust microfluidic-based scheme to prepare Janus microspheres.Our experimental results demonstrate that within a specific ratio range,the rotation radii of microspheres vary linearly and the orientations of microsphere are always aligned with the light polarization direction.This is of great importance in guiding the design of Janus microspheres.And their orientations flip at a particular ratio,all consistent with the simulations.Our work provides a reliable theoretical analysis and experimental strategy for studying the interaction of heterogeneous particles with the optical field and further expands the diverse manipulation capabilities of optical tweezers.展开更多
An appropriate decarbonisation pathway is crucial to achieving carbon neutrality in China before 2060.This paper studies decarbonisation pathways for China's energy system between 2020 and 2060 using an open,provi...An appropriate decarbonisation pathway is crucial to achieving carbon neutrality in China before 2060.This paper studies decarbonisation pathways for China's energy system between 2020 and 2060 using an open,provincial,and hourly resolved,networked model within the context of multi‐period planning with myopic investment foresight.Two representative decarbonisation pathways are compared,with particular attention to the synergies of coupling the electricity and heating sectors.An early and steady path in which emissions are strongly reduced in the first decade is more cost‐effective than following a late and rapid path.Early decarbonisation in the electricity sector avoids stranded in-vestments in fossil infrastructure and preserves the carbon budget for later emissions in the difficult‐to‐decarbonise heating sector.Retrofitting the existing coal power plants by adding carbon capture facilities is cost‐effective in both decarbonisation pathways.The hourly and non‐interrupted resolution for a full weather year reveals the balancing strategies of highly renewable,sector‐coupled systems.The significant seasonal variation of heat demand dominates long‐term storage behaviours.展开更多
Learning-based multi-view stereo(MVS)algorithms have demonstrated great potential for depth estimation in recent years.However,they still struggle to estimate accurate depth in texture-less planar regions,which limits...Learning-based multi-view stereo(MVS)algorithms have demonstrated great potential for depth estimation in recent years.However,they still struggle to estimate accurate depth in texture-less planar regions,which limits their reconstruction perform-ance in man-made scenes.In this paper,we propose PlaneStereo,a new framework that utilizes planar prior to facilitate the depth estim-ation.Our key intuition is that pixels inside a plane share the same set of plane parameters,which can be estimated collectively using in-formation inside the whole plane.Specifically,our method first segments planes in the reference image,and then fits 3D plane paramet-ers for each segmented plane by solving a linear system using high-confidence depth predictions inside the plane.This allows us to recov-er the plane parameters accurately,which can be converted to accurate depth values for each point in the plane,improving the depth prediction for low-textured local regions.This process is fully differentiable and can be integrated into existing learning-based MVS al-gorithms.Experiments show that using our method consistently improves the performance of existing stereo matching and MVS al-gorithms on DeMoN and ScanNet datasets,achieving state-of-the-art performance.展开更多
Improved soybean cultivars have been adapted to grow at a wide range of latitudes,enabling expansion of cultivation worldwide.However,the genetic basis of this broad adaptation is still not clear.Here,we report the id...Improved soybean cultivars have been adapted to grow at a wide range of latitudes,enabling expansion of cultivation worldwide.However,the genetic basis of this broad adaptation is still not clear.Here,we report the identification of GmPRR3b as a major flowering time regulatory gene that has been selected during domestication and genetic improvement for geographic expansion.Through a genome-wide association study of a diverse soybean landrace panel consisting of 279 accessions,we identified 16 candidate quantitative loci associated with flowering time and maturity time.The strongest signal resides in the known flowering gene E2,verifying the effectiveness of our approach.We detected strong signals associated with both flowering and maturity time in a genomic region containing GmPRR3b.Haplotype analysis revealed that GmPRR3bH6 is the major form of GmPRR3b that has been utilized during recent breeding of modern cultivars.mRNA profiling analysis showed that GmPRR3bH6 displays rhythmic and photoperiod-dependent expression and is preferentially induced under long-day conditions.Overexpression of GmPRR3bH6 increased main stem node number and yield,while knockout of GmPRR3bH6 using CRISPR/Cas9 technology delayed growth and the floral transition.GmPRR3bH6 appears to act as a transcriptional repressor of multiple predicted circadian clock genes,including GmCCAIa,which directly upregulates J/GmELF3a to modulate flowering time.The causal SNP(Chr12:5520945)likely endows GmPRR3bH6 a moderate but appropriate level of activity,leading to early flowering and vigorous growth traits preferentially selected during broad adaptation of landraces and improvement of cultivars.展开更多
Reconstructing 3D digital models of humans from sensory data is a long-standing problem in computer vision and graphics with a variety of applications in VR/AR,film production,and human–computer interaction,etc.While...Reconstructing 3D digital models of humans from sensory data is a long-standing problem in computer vision and graphics with a variety of applications in VR/AR,film production,and human–computer interaction,etc.While a huge amount of effort has been devoted to developing various capture hardware and reconstruction algorithms,traditional reconstruction pipelines may still suffer from high-cost capture systems and tedious capture processes,which prevent them from being easily accessible.Moreover,the dedicatedly hand-crafted pipelines are prone to reconstruction artifacts,resulting in limited visual quality.To solve these challenges,the recent trend in this area is to use deep neural networks to improve reconstruction efficiency and robustness by learning human priors from existing data.Neural network-based implicit functions have been also shown to be a favorable 3D representation compared to traditional forms like meshes and voxels.Furthermore,neural rendering has emerged as a powerful tool to achieve highly photorealistic modeling and re-rendering of humans by end-to-end optimizing the visual quality of output images.In this article,we will briefly review these advances in this fast-developing field,discuss the advantages and limitations of different approaches,and finally,share some thoughts on future research directions.展开更多
基金supported by the National Natural Science Foundation of China,Nos.82274313(to YD),82204746(to ML),82003982(to TL).
文摘It has been reported that the PI3K/AKT signaling pathway plays a key role in the pathogenesis of ischemic stroke.As a result,the development of drugs targeting the PI3K/AKT signaling pathway has attracted increasing attention from researchers.This article reviews the pathological mechanisms and advancements in research related to the signaling pathways in ischemic stroke,with a focus on the PI3K/AKT signaling pathway.The key findings include the following:(1)The complex pathological mechanisms of ischemic stroke can be categorized into five major types:excitatory amino acid toxicity,Ca^(2+)overload,inflammatory response,oxidative stress,and apoptosis.(2)The PI3K/AKT-mediated signaling pathway is closely associated with the occurrence and progression of ischemic stroke,which primarily involves the NF-κB,NRF2,BCL-2,mTOR,and endothelial NOS signaling pathways.(3)Natural products,including flavonoids,quinones,alkaloids,phenylpropanoids,phenols,terpenoids,and iridoids,show great potential as candidate substances for the development of innovative anti-stroke medications.(4)Recently,novel therapeutic techniques,such as electroacupuncture and mesenchymal stem cell therapy,have demonstrated the potential to improve stroke outcomes by activating the PI3K/AKT signaling pathway,providing new possibilities for the treatment and rehabilitation of patients with ischemic stroke.Future investigations should focus on the direct regulatory mechanisms of drugs targeting the PI3K/AKT signaling pathway and their clinical translation to develop innovative treatment strategies for ischemic stroke.
基金National Natural Science Foundation of China(61806176)the Fundamental Research Funds for the Central Universities(2019QNA5022).
文摘Recovering human pose from RGB images and videos has drawn increasing attention in recent years owing to minimum sensor requirements and applicability in diverse fields such as human-computer interaction,robotics,video analytics,and augmented reality.Although a large amount of work has been devoted to this field,3D human pose estimation based on monocular images or videos remains a very challenging task due to a variety of difficulties such as depth ambiguities,occlusion,background clutters,and lack of training data.In this survey,we summarize recent advances in monocular 3D human pose estimation.We provide a general taxonomy to cover existing approaches and analyze their capabilities and limitations.We also present a summary of extensively used datasets and metrics,and provide a quantitative comparison of some representative methods.Finally,we conclude with a discussion on realistic challenges and open problems for future research directions.
基金National Natural Science Foundation of China(52075383,61927808)National Key Research and Development Program of China(2022YFF0605501).
文摘Angular optical trapping based on Janus microspheres has been proven to be a novel method to achieve controllable rotation.In contrast to natural birefringent crystals,Janus microspheres are chemically synthesized of two compositions with different refractive indices.Thus,their structures can be artificially regulated,which brings excellent potential for fine and multi-degree-of-freedom manipulation in the optical field.However,it is a considerable challenge to model the interaction of heterogeneous particles with the optical field,and there has also been no experimental study on the optical manipulation of microspheres with such designable refractive index distributions.How the specific structure affects the kinematic properties of Janus microspheres remains unknown.Here,we report systematic research on the optical trapping and rotating of various ratio-designable Janus microspheres.We employ an efficient T-matrix method to rapidly calculate the optical force and torque on Janus microspheres to obtain their trapped postures and rotational characteristics in the optical field.We have developed a robust microfluidic-based scheme to prepare Janus microspheres.Our experimental results demonstrate that within a specific ratio range,the rotation radii of microspheres vary linearly and the orientations of microsphere are always aligned with the light polarization direction.This is of great importance in guiding the design of Janus microspheres.And their orientations flip at a particular ratio,all consistent with the simulations.Our work provides a reliable theoretical analysis and experimental strategy for studying the interaction of heterogeneous particles with the optical field and further expands the diverse manipulation capabilities of optical tweezers.
文摘An appropriate decarbonisation pathway is crucial to achieving carbon neutrality in China before 2060.This paper studies decarbonisation pathways for China's energy system between 2020 and 2060 using an open,provincial,and hourly resolved,networked model within the context of multi‐period planning with myopic investment foresight.Two representative decarbonisation pathways are compared,with particular attention to the synergies of coupling the electricity and heating sectors.An early and steady path in which emissions are strongly reduced in the first decade is more cost‐effective than following a late and rapid path.Early decarbonisation in the electricity sector avoids stranded in-vestments in fossil infrastructure and preserves the carbon budget for later emissions in the difficult‐to‐decarbonise heating sector.Retrofitting the existing coal power plants by adding carbon capture facilities is cost‐effective in both decarbonisation pathways.The hourly and non‐interrupted resolution for a full weather year reveals the balancing strategies of highly renewable,sector‐coupled systems.The significant seasonal variation of heat demand dominates long‐term storage behaviours.
文摘Learning-based multi-view stereo(MVS)algorithms have demonstrated great potential for depth estimation in recent years.However,they still struggle to estimate accurate depth in texture-less planar regions,which limits their reconstruction perform-ance in man-made scenes.In this paper,we propose PlaneStereo,a new framework that utilizes planar prior to facilitate the depth estim-ation.Our key intuition is that pixels inside a plane share the same set of plane parameters,which can be estimated collectively using in-formation inside the whole plane.Specifically,our method first segments planes in the reference image,and then fits 3D plane paramet-ers for each segmented plane by solving a linear system using high-confidence depth predictions inside the plane.This allows us to recov-er the plane parameters accurately,which can be converted to accurate depth values for each point in the plane,improving the depth prediction for low-textured local regions.This process is fully differentiable and can be integrated into existing learning-based MVS al-gorithms.Experiments show that using our method consistently improves the performance of existing stereo matching and MVS al-gorithms on DeMoN and ScanNet datasets,achieving state-of-the-art performance.
基金the National Key Research and Development Plan(2016YFD0101005,2016YFD0100201,and 2016YFD0100304)the National Natural Science Foundation of China(31871705 and 31422041)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences,and the Central Public-Interest Scientific Institution Basal Research Fund(Y2016JC13).
文摘Improved soybean cultivars have been adapted to grow at a wide range of latitudes,enabling expansion of cultivation worldwide.However,the genetic basis of this broad adaptation is still not clear.Here,we report the identification of GmPRR3b as a major flowering time regulatory gene that has been selected during domestication and genetic improvement for geographic expansion.Through a genome-wide association study of a diverse soybean landrace panel consisting of 279 accessions,we identified 16 candidate quantitative loci associated with flowering time and maturity time.The strongest signal resides in the known flowering gene E2,verifying the effectiveness of our approach.We detected strong signals associated with both flowering and maturity time in a genomic region containing GmPRR3b.Haplotype analysis revealed that GmPRR3bH6 is the major form of GmPRR3b that has been utilized during recent breeding of modern cultivars.mRNA profiling analysis showed that GmPRR3bH6 displays rhythmic and photoperiod-dependent expression and is preferentially induced under long-day conditions.Overexpression of GmPRR3bH6 increased main stem node number and yield,while knockout of GmPRR3bH6 using CRISPR/Cas9 technology delayed growth and the floral transition.GmPRR3bH6 appears to act as a transcriptional repressor of multiple predicted circadian clock genes,including GmCCAIa,which directly upregulates J/GmELF3a to modulate flowering time.The causal SNP(Chr12:5520945)likely endows GmPRR3bH6 a moderate but appropriate level of activity,leading to early flowering and vigorous growth traits preferentially selected during broad adaptation of landraces and improvement of cultivars.
基金The authors would like to acknowledge the support from NSFC(No.62172364).
文摘Reconstructing 3D digital models of humans from sensory data is a long-standing problem in computer vision and graphics with a variety of applications in VR/AR,film production,and human–computer interaction,etc.While a huge amount of effort has been devoted to developing various capture hardware and reconstruction algorithms,traditional reconstruction pipelines may still suffer from high-cost capture systems and tedious capture processes,which prevent them from being easily accessible.Moreover,the dedicatedly hand-crafted pipelines are prone to reconstruction artifacts,resulting in limited visual quality.To solve these challenges,the recent trend in this area is to use deep neural networks to improve reconstruction efficiency and robustness by learning human priors from existing data.Neural network-based implicit functions have been also shown to be a favorable 3D representation compared to traditional forms like meshes and voxels.Furthermore,neural rendering has emerged as a powerful tool to achieve highly photorealistic modeling and re-rendering of humans by end-to-end optimizing the visual quality of output images.In this article,we will briefly review these advances in this fast-developing field,discuss the advantages and limitations of different approaches,and finally,share some thoughts on future research directions.