Large-scale proteomics studies can refine our understanding of health and disease and enable precision medicine.Here,we provide a detailed atlas of 2,920 plasma proteins linking to diseases(406 prevalent and 660 incid...Large-scale proteomics studies can refine our understanding of health and disease and enable precision medicine.Here,we provide a detailed atlas of 2,920 plasma proteins linking to diseases(406 prevalent and 660 incident)and 986 health-related traits in 53,026 individuals(median follow-up:14.8 years)from the UK Biobank,representing the most comprehensive proteome profiles to date.This atlas revealed 168,100 protein-disease associations and 554,488 protein-trait associations.展开更多
End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods th...End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods that perform full fine-tuning of pretrained video models often incur substantial computational costs,which become particularly pronounced when processing long video sequences.Moreover,the need for precise temporal boundary annotations makes data labeling extremely expensive.In low-resource settings where annotated samples are scarce,direct fine-tuning tends to cause overfitting.To address these challenges,we introduce Dynamic LowRank Adapter(DyLoRA),a lightweight fine-tuning framework tailored specifically for the TAD task.Built upon the Low-Rank Adaptation(LoRA)architecture,DyLoRA adapts only the key layers of the pretrained model via low-rank decomposition,reducing the number of trainable parameters to less than 5%of full fine-tuning methods.This significantly lowers memory consumption and mitigates overfitting in low-resource settings.Notably,DyLoRA enhances the temporal modeling capability of pretrained models by optimizing temporal dimension weights,thereby alleviating the representation misalignment of temporal features.Experimental results demonstrate that DyLoRA-TAD achieves impressive performance,with 73.9%mAP on THUMOS14,39.52%on ActivityNet-1.3,and 28.2%on Charades,substantially surpassing the best traditional feature-based methods.展开更多
In physics,our expectations for system behavior are often guided by intuitive arithmetic.For systems composed of identical units,we anticipate synergy of the contributions from these units,where 1+1=2.Conversely,for s...In physics,our expectations for system behavior are often guided by intuitive arithmetic.For systems composed of identical units,we anticipate synergy of the contributions from these units,where 1+1=2.Conversely,for systems built from opposing units,we expect cancellation of their contributions,where 1-1=0.This intuitive arithmetic has long underpinned our understanding of physical properties of materials,from electronic transport to optical responses.However,scientific breakthroughs often occur when nature reveals ways to circumvent these seemingly fundamental rules,opening new possibilities that challenge our deepest assumptions about material behavior.展开更多
In the field of intelligent surveillance,weakly supervised video anomaly detection(WSVAD)has garnered widespread attention as a key technology that identifies anomalous events using only video-level labels.Although mu...In the field of intelligent surveillance,weakly supervised video anomaly detection(WSVAD)has garnered widespread attention as a key technology that identifies anomalous events using only video-level labels.Although multiple instance learning(MIL)has dominated the WSVAD for a long time,its reliance solely on video-level labels without semantic grounding hinders a fine-grained understanding of visually similar yet semantically distinct events.In addition,insufficient temporal modeling obscures causal relationships between events,making anomaly decisions reactive rather than reasoning-based.To overcome the limitations above,this paper proposes an adaptive knowledgebased guidance method that integrates external structured knowledge.The approach combines hierarchical category information with learnable prompt vectors.It then constructs continuously updated contextual references within the feature space,enabling fine-grained meaning-based guidance over video content.Building on this,the work introduces an event relation analysis module.This module explicitly models temporal dependencies and causal correlations between video snippets.It constructs an evolving logic chain of anomalous events,revealing the process by which isolated anomalous snippets develop into a complete event.Experiments on multiple benchmark datasets show that the proposed method achieves highly competitive performance,achieving an AUC of 88.19%on UCF-Crime and an AP of 86.49%on XD-Violence.More importantly,the method provides temporal and causal explanations derived from event relationships alongside its detection results.This capability significantly advances WSVAD from a simple binary classification to a new level of interpretable behavior analysis.展开更多
The Qinghai-Xizang Plateau,known as the Roof of the World and the Water Tower of Asia,is recognized as the Earth’s Third Pole.It functions as a vital ecological security barrier and a strategic resource reserve for C...The Qinghai-Xizang Plateau,known as the Roof of the World and the Water Tower of Asia,is recognized as the Earth’s Third Pole.It functions as a vital ecological security barrier and a strategic resource reserve for China,while also serving as an important conservation area that reflects the unique culture of the Chinese nation.Conducting the Second Comprehensive Scientific Expedition to the Qinghai-Xizang Plateau is essential for understanding valuable insights into scientific protection of the region.展开更多
Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-de...Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-density matter,understanding planetary science,and laser-driven fusion energy.However,experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics.Over the last decade,the advent of femtosecond brilliant hard X-ray free-electron lasers(XFELs)has opened new horizons to overcome these limitations.Here,for the first time,we present full-scale spatiotemporal measurements of solid-density plasma dynamics,including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse,ultrafast heating and ionization at the main pulse arrival,the laser-driven blast wave,and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction.These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering,resonant X-ray emission spectroscopy,and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.展开更多
Experiments with interacting high-velocity flows in a laser plasma can help answer fundamental questions in plasma physics and improve understanding of the mechanisms behind some astrophysical phenomena,such as the fo...Experiments with interacting high-velocity flows in a laser plasma can help answer fundamental questions in plasma physics and improve understanding of the mechanisms behind some astrophysical phenomena,such as the formation of collisionless shock waves,deceleration of accretion flows,and evolution of solar and stellar flares.This work presents the first direct experimental observations of stagnation and redirection of counterstreaming flows(jets)of laser plasma induced by intense laser pulses with intensity I~2×10^(18) W/cm^(2).Hybrid particlein-cell-fluid modeling,which takes into account the kinetic effects of ion motion and the evolution of the pressure tensor for electrons,demonstrates the compression of counterdirected toroidal self-generated magnetic fields embedded in counterstreaming plasma flows.The enhancement of the toroidal magnetic field in the interaction region results in plasma flow stagnation and redirection of the jets across the line of their initial propagation.展开更多
Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the...Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.展开更多
With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intellig...With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.展开更多
Understanding the proton dynamic behavior in inorganic materials has long been a topic of intense fascination[1],especially in the field of electrochemical energy storage[2].One of the examples is the research of prot...Understanding the proton dynamic behavior in inorganic materials has long been a topic of intense fascination[1],especially in the field of electrochemical energy storage[2].One of the examples is the research of proton transport in transition metal oxides,which dates back to 1971[3]when RuO_(2) was discovered to be capable of storing protons via reversible redox reactions[4].In aqueous electrolytes,the thin film RuO_(2) electrode exhibits a surface pseudocapacitive behavior[5],which could be modified by the structural water in its hydrated form due to the facile Grotthuss hopping mode of protons along the established hydrogen bonds inside the bulk phase[6].Soon later,Goodenough et al.reported the capacitor-like behavior of amorphous MnO_(2)·xH_(2)O electrode in an aqueous KCl electrolyte[7],and further studies on the hydrated MnO_(2) electrodes prepared by sol-gel processes have soon discovered that the intercalation of protons from aqueous electrolytes plays an indispensable role in the charge storage mechanism[8].In recent years,the research interest on rechargeable aqueous batteries has fueled the renaissance of mechanistic study of proton transport in transition metal oxides[9],which can operate as cathodes or anodes via a topotactic insertion mechanism similar to that in Li-ion batteries[10].However,due to the challenges for experimental detection of local chemical environments of the inserted protons,a comprehensive understanding of proton dynamic behavior in these electrodes remains largely lacking.展开更多
In January 2025,the Beijing Chamber of Commerce(Singapore)was officially established.Coinciding with the 35th anniversary of China-Singapore diplomatic relations and the 60th anniversary of Singapore’s independence,i...In January 2025,the Beijing Chamber of Commerce(Singapore)was officially established.Coinciding with the 35th anniversary of China-Singapore diplomatic relations and the 60th anniversary of Singapore’s independence,its founding is part of a timely response to the growing needs of businesses and communities from both Beijing and Singapore to deepen mutual understanding and expand cooperation.As a Chinese person who has lived and worked in Singapore for many years,Feng Jianli,president of the Beijing Chamber of Commerce(Singapore),knows first-hand just how challenging it can be for new immigrants from Beijing to adapt to identity transitions and access local support.The chamber was founded not only to help them take root and thrive,but also to serve as a platform for deeper people-to-people exchange between Singapore and Beijing.展开更多
Fostering understanding between China and Africa through dialogue and exchanges Etienne Bankuwiha,a young sinologist from Burundi and a doctoral student at Nanjing University,received on the afternoon of 13 November t...Fostering understanding between China and Africa through dialogue and exchanges Etienne Bankuwiha,a young sinologist from Burundi and a doctoral student at Nanjing University,received on the afternoon of 13 November the message he had been eagerly awaiting-a reply from Chinese President Xi Jinping.展开更多
As an English traveler,diving into the heart of Chinese culture is like unlocking a world of rich experiences that offer a deeper understanding of the country and its people.Here is how,from my perspective,I have imme...As an English traveler,diving into the heart of Chinese culture is like unlocking a world of rich experiences that offer a deeper understanding of the country and its people.Here is how,from my perspective,I have immersed myself in various facets of Chinese culture.展开更多
1 When we immerse ourselves in the pages of a book,we are transported to worlds beyond our own,gaining insights into the human experience and expanding our understanding of ourselves and others.2 Reading can fill our ...1 When we immerse ourselves in the pages of a book,we are transported to worlds beyond our own,gaining insights into the human experience and expanding our understanding of ourselves and others.2 Reading can fill our lives and purify our souls.I enjoy reading and I love life.I enjoy reading Chinese classics such as the Four Great Classical Novels of Chinese literature.I explore the mythical and wonderful stories of demons and monsters in Journey to the West and experience the boldness of martial art heroes in Water Margin.展开更多
The scientific community has reached firm consensus that humans know less about the ocean than they do about the moon.Even though we have developed submersibles capable of diving to depths of ten thousand meters,our u...The scientific community has reached firm consensus that humans know less about the ocean than they do about the moon.Even though we have developed submersibles capable of diving to depths of ten thousand meters,our understanding of the oceans covering approximately 71 percent of the Earth’s surface remains scarce.A paper published in Science Advances last May noted that only 0.001 percent of the deep seafloor(190 meters or more below Earth’s surface)has been visually observed by scientists,yet this tiny fraction accounts for 95 percent of the total surface area of the oceans around the globe.展开更多
Washington’s disruptive trade wars present both opportunities and challenges to China and Africa.Borders that are crisscrossed more frequently by trade in goods and services are less likely to be besieged by soldiers...Washington’s disruptive trade wars present both opportunities and challenges to China and Africa.Borders that are crisscrossed more frequently by trade in goods and services are less likely to be besieged by soldiers and other armed elements,buttressing the fact that trade dividends are not just related to development,growth,and prosperity,but also include peace and mutual understanding through dialogue among civilisations.展开更多
Calvin Wee first set foot in China at the age of 14—not for a diplomatic forum or a youth initiative,but on a week-long school trip to Guangzhou.Yet even then,the experience left a lasting impression.“We visited a l...Calvin Wee first set foot in China at the age of 14—not for a diplomatic forum or a youth initiative,but on a week-long school trip to Guangzhou.Yet even then,the experience left a lasting impression.“We visited a local school and sat in on several classes,”he recalled.“The math lessons stood out—the students’intensity and focus were striking.In Singapore,we study hard,but this was on another level.”That early glimpse into China’s education system stayed with him,and years later,it resurfaced as he began to engage more deeply with the Chinese language and culture.A pocket-sized wuxia xiaoshuo(martial arts novel),picked up on a whim in a Guangzhou bookstore,opened the door to martial arts fiction—and sparked a lasting interest in Chinese literature and,eventually,China Studies.展开更多
Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action...Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action recognition networks either perform simple temporal fusion through averaging or rely on pre-trained models from image recognition,resulting in limited temporal information extraction capabilities.This work proposes a highly efficient temporal decoding module that can be seamlessly integrated into any action recognition backbone network to enhance the focus on temporal relationships between video frames.Firstly,the decoder initializes a set of learnable queries,termed video-level action category prediction queries.Then,they are combined with the video frame features extracted by the backbone network after self-attention learning to extract video context information.Finally,these prediction queries with rich temporal features are used for category prediction.Experimental results on HMDB51,MSRDailyAct3D,Diving48 and Breakfast datasets show that using TokShift-Transformer and VideoMAE as encoders results in a significant improvement in Top-1 accuracy compared to the original models(TokShift-Transformer and VideoMAE),after introducing the proposed temporal decoder.The introduction of the temporal decoder results in an average performance increase exceeding 11%for TokShift-Transformer and nearly 5%for VideoMAE across the four datasets.Furthermore,the work explores the combination of the decoder with various action recognition networks,including Timesformer,as encoders.This results in an average accuracy improvement of more than 3.5%on the HMDB51 dataset.The code is available at https://github.com/huangturbo/TempDecoder.展开更多
文摘Large-scale proteomics studies can refine our understanding of health and disease and enable precision medicine.Here,we provide a detailed atlas of 2,920 plasma proteins linking to diseases(406 prevalent and 660 incident)and 986 health-related traits in 53,026 individuals(median follow-up:14.8 years)from the UK Biobank,representing the most comprehensive proteome profiles to date.This atlas revealed 168,100 protein-disease associations and 554,488 protein-trait associations.
基金supported by the National Natural Science Foundation of China(Grant No.62266054)the Major Science and Technology Project of Yunnan Province(Grant No.202402AD080002)the Scientific Research Fund of the Yunnan Provincial Department of Education(Grant No.2025Y0302).
文摘End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods that perform full fine-tuning of pretrained video models often incur substantial computational costs,which become particularly pronounced when processing long video sequences.Moreover,the need for precise temporal boundary annotations makes data labeling extremely expensive.In low-resource settings where annotated samples are scarce,direct fine-tuning tends to cause overfitting.To address these challenges,we introduce Dynamic LowRank Adapter(DyLoRA),a lightweight fine-tuning framework tailored specifically for the TAD task.Built upon the Low-Rank Adaptation(LoRA)architecture,DyLoRA adapts only the key layers of the pretrained model via low-rank decomposition,reducing the number of trainable parameters to less than 5%of full fine-tuning methods.This significantly lowers memory consumption and mitigates overfitting in low-resource settings.Notably,DyLoRA enhances the temporal modeling capability of pretrained models by optimizing temporal dimension weights,thereby alleviating the representation misalignment of temporal features.Experimental results demonstrate that DyLoRA-TAD achieves impressive performance,with 73.9%mAP on THUMOS14,39.52%on ActivityNet-1.3,and 28.2%on Charades,substantially surpassing the best traditional feature-based methods.
基金supported by the National Natural Science Foundation of China (Grant No.12374109)the National Key Research and Development Program of China (Grant No.2023YFA1406600)。
文摘In physics,our expectations for system behavior are often guided by intuitive arithmetic.For systems composed of identical units,we anticipate synergy of the contributions from these units,where 1+1=2.Conversely,for systems built from opposing units,we expect cancellation of their contributions,where 1-1=0.This intuitive arithmetic has long underpinned our understanding of physical properties of materials,from electronic transport to optical responses.However,scientific breakthroughs often occur when nature reveals ways to circumvent these seemingly fundamental rules,opening new possibilities that challenge our deepest assumptions about material behavior.
文摘In the field of intelligent surveillance,weakly supervised video anomaly detection(WSVAD)has garnered widespread attention as a key technology that identifies anomalous events using only video-level labels.Although multiple instance learning(MIL)has dominated the WSVAD for a long time,its reliance solely on video-level labels without semantic grounding hinders a fine-grained understanding of visually similar yet semantically distinct events.In addition,insufficient temporal modeling obscures causal relationships between events,making anomaly decisions reactive rather than reasoning-based.To overcome the limitations above,this paper proposes an adaptive knowledgebased guidance method that integrates external structured knowledge.The approach combines hierarchical category information with learnable prompt vectors.It then constructs continuously updated contextual references within the feature space,enabling fine-grained meaning-based guidance over video content.Building on this,the work introduces an event relation analysis module.This module explicitly models temporal dependencies and causal correlations between video snippets.It constructs an evolving logic chain of anomalous events,revealing the process by which isolated anomalous snippets develop into a complete event.Experiments on multiple benchmark datasets show that the proposed method achieves highly competitive performance,achieving an AUC of 88.19%on UCF-Crime and an AP of 86.49%on XD-Violence.More importantly,the method provides temporal and causal explanations derived from event relationships alongside its detection results.This capability significantly advances WSVAD from a simple binary classification to a new level of interpretable behavior analysis.
文摘The Qinghai-Xizang Plateau,known as the Roof of the World and the Water Tower of Asia,is recognized as the Earth’s Third Pole.It functions as a vital ecological security barrier and a strategic resource reserve for China,while also serving as an important conservation area that reflects the unique culture of the Chinese nation.Conducting the Second Comprehensive Scientific Expedition to the Qinghai-Xizang Plateau is essential for understanding valuable insights into scientific protection of the region.
基金funding from Grant No. HIDSS-0002 DASHH (Data Science in Hamburg-Helmholtz Graduate School for the Structure of Matter)partially supported by the Helmholtz Imaging platform through the project “Smart Phase.”
文摘Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-density matter,understanding planetary science,and laser-driven fusion energy.However,experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics.Over the last decade,the advent of femtosecond brilliant hard X-ray free-electron lasers(XFELs)has opened new horizons to overcome these limitations.Here,for the first time,we present full-scale spatiotemporal measurements of solid-density plasma dynamics,including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse,ultrafast heating and ionization at the main pulse arrival,the laser-driven blast wave,and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction.These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering,resonant X-ray emission spectroscopy,and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.
基金supported by Russian Science Foundation Grant No.24-62-00032.
文摘Experiments with interacting high-velocity flows in a laser plasma can help answer fundamental questions in plasma physics and improve understanding of the mechanisms behind some astrophysical phenomena,such as the formation of collisionless shock waves,deceleration of accretion flows,and evolution of solar and stellar flares.This work presents the first direct experimental observations of stagnation and redirection of counterstreaming flows(jets)of laser plasma induced by intense laser pulses with intensity I~2×10^(18) W/cm^(2).Hybrid particlein-cell-fluid modeling,which takes into account the kinetic effects of ion motion and the evolution of the pressure tensor for electrons,demonstrates the compression of counterdirected toroidal self-generated magnetic fields embedded in counterstreaming plasma flows.The enhancement of the toroidal magnetic field in the interaction region results in plasma flow stagnation and redirection of the jets across the line of their initial propagation.
基金supported in part by National Institute of Health(NIH),USA(Grant Nos.:R01GM126189,R01AI164266,and R35GM148196)the National Science Foundation,USA(Grant Nos.DMS2052983,DMS-1761320,and IIS-1900473)+3 种基金National Aero-nautics and Space Administration(NASA),USA(Grant No.:80NSSC21M0023)Michigan State University(MSU)Foundation,USA,Bristol-Myers Squibb(Grant No.:65109)USA,and Pfizer,USAsupported by the National Natural Science Foundation of China(Grant Nos.:11971367,12271416,and 11972266).
文摘Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.
基金supported by the National Natural Science Foundation of China(Nos.62371323,62401380,U2433217,U2333209,and U20A20161)Natural Science Foundation of Sichuan Province,China(Nos.2025ZNSFSC1476)+2 种基金Sichuan Science and Technology Program,China(Nos.2024YFG0010 and 2024ZDZX0046)the Institutional Research Fund from Sichuan University(Nos.2024SCUQJTX030)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,CAAC(Nos.GY2024-01A).
文摘With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.
基金financial support from the National Natural Science Foundation of China(22109003)the Basic and Applied Basic Research Foundation of Guangdong Province(2023A1515011391)+1 种基金Soft Science Research Project of Guangdong Province(No.2017B030301013)the Major Science and Technology Infrastructure Project of Material Genome Big-science Facilities Platform supported by Municipal Development and Reform Commission of Shenzhen.
文摘Understanding the proton dynamic behavior in inorganic materials has long been a topic of intense fascination[1],especially in the field of electrochemical energy storage[2].One of the examples is the research of proton transport in transition metal oxides,which dates back to 1971[3]when RuO_(2) was discovered to be capable of storing protons via reversible redox reactions[4].In aqueous electrolytes,the thin film RuO_(2) electrode exhibits a surface pseudocapacitive behavior[5],which could be modified by the structural water in its hydrated form due to the facile Grotthuss hopping mode of protons along the established hydrogen bonds inside the bulk phase[6].Soon later,Goodenough et al.reported the capacitor-like behavior of amorphous MnO_(2)·xH_(2)O electrode in an aqueous KCl electrolyte[7],and further studies on the hydrated MnO_(2) electrodes prepared by sol-gel processes have soon discovered that the intercalation of protons from aqueous electrolytes plays an indispensable role in the charge storage mechanism[8].In recent years,the research interest on rechargeable aqueous batteries has fueled the renaissance of mechanistic study of proton transport in transition metal oxides[9],which can operate as cathodes or anodes via a topotactic insertion mechanism similar to that in Li-ion batteries[10].However,due to the challenges for experimental detection of local chemical environments of the inserted protons,a comprehensive understanding of proton dynamic behavior in these electrodes remains largely lacking.
文摘In January 2025,the Beijing Chamber of Commerce(Singapore)was officially established.Coinciding with the 35th anniversary of China-Singapore diplomatic relations and the 60th anniversary of Singapore’s independence,its founding is part of a timely response to the growing needs of businesses and communities from both Beijing and Singapore to deepen mutual understanding and expand cooperation.As a Chinese person who has lived and worked in Singapore for many years,Feng Jianli,president of the Beijing Chamber of Commerce(Singapore),knows first-hand just how challenging it can be for new immigrants from Beijing to adapt to identity transitions and access local support.The chamber was founded not only to help them take root and thrive,but also to serve as a platform for deeper people-to-people exchange between Singapore and Beijing.
文摘Fostering understanding between China and Africa through dialogue and exchanges Etienne Bankuwiha,a young sinologist from Burundi and a doctoral student at Nanjing University,received on the afternoon of 13 November the message he had been eagerly awaiting-a reply from Chinese President Xi Jinping.
文摘As an English traveler,diving into the heart of Chinese culture is like unlocking a world of rich experiences that offer a deeper understanding of the country and its people.Here is how,from my perspective,I have immersed myself in various facets of Chinese culture.
文摘1 When we immerse ourselves in the pages of a book,we are transported to worlds beyond our own,gaining insights into the human experience and expanding our understanding of ourselves and others.2 Reading can fill our lives and purify our souls.I enjoy reading and I love life.I enjoy reading Chinese classics such as the Four Great Classical Novels of Chinese literature.I explore the mythical and wonderful stories of demons and monsters in Journey to the West and experience the boldness of martial art heroes in Water Margin.
文摘The scientific community has reached firm consensus that humans know less about the ocean than they do about the moon.Even though we have developed submersibles capable of diving to depths of ten thousand meters,our understanding of the oceans covering approximately 71 percent of the Earth’s surface remains scarce.A paper published in Science Advances last May noted that only 0.001 percent of the deep seafloor(190 meters or more below Earth’s surface)has been visually observed by scientists,yet this tiny fraction accounts for 95 percent of the total surface area of the oceans around the globe.
文摘Washington’s disruptive trade wars present both opportunities and challenges to China and Africa.Borders that are crisscrossed more frequently by trade in goods and services are less likely to be besieged by soldiers and other armed elements,buttressing the fact that trade dividends are not just related to development,growth,and prosperity,but also include peace and mutual understanding through dialogue among civilisations.
文摘Calvin Wee first set foot in China at the age of 14—not for a diplomatic forum or a youth initiative,but on a week-long school trip to Guangzhou.Yet even then,the experience left a lasting impression.“We visited a local school and sat in on several classes,”he recalled.“The math lessons stood out—the students’intensity and focus were striking.In Singapore,we study hard,but this was on another level.”That early glimpse into China’s education system stayed with him,and years later,it resurfaced as he began to engage more deeply with the Chinese language and culture.A pocket-sized wuxia xiaoshuo(martial arts novel),picked up on a whim in a Guangzhou bookstore,opened the door to martial arts fiction—and sparked a lasting interest in Chinese literature and,eventually,China Studies.
基金Shanghai Municipal Commission of Economy and Information Technology,China (No.202301054)。
文摘Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action recognition networks either perform simple temporal fusion through averaging or rely on pre-trained models from image recognition,resulting in limited temporal information extraction capabilities.This work proposes a highly efficient temporal decoding module that can be seamlessly integrated into any action recognition backbone network to enhance the focus on temporal relationships between video frames.Firstly,the decoder initializes a set of learnable queries,termed video-level action category prediction queries.Then,they are combined with the video frame features extracted by the backbone network after self-attention learning to extract video context information.Finally,these prediction queries with rich temporal features are used for category prediction.Experimental results on HMDB51,MSRDailyAct3D,Diving48 and Breakfast datasets show that using TokShift-Transformer and VideoMAE as encoders results in a significant improvement in Top-1 accuracy compared to the original models(TokShift-Transformer and VideoMAE),after introducing the proposed temporal decoder.The introduction of the temporal decoder results in an average performance increase exceeding 11%for TokShift-Transformer and nearly 5%for VideoMAE across the four datasets.Furthermore,the work explores the combination of the decoder with various action recognition networks,including Timesformer,as encoders.This results in an average accuracy improvement of more than 3.5%on the HMDB51 dataset.The code is available at https://github.com/huangturbo/TempDecoder.
