Based on the conventional observation data,daily reanalysis data from NCAR/NCEP,and TBB data derived from FY-2G infrared cloud images in April 2018,a heavy snowfall weather process in central Inner Mongolia from April...Based on the conventional observation data,daily reanalysis data from NCAR/NCEP,and TBB data derived from FY-2G infrared cloud images in April 2018,a heavy snowfall weather process in central Inner Mongolia from April 4 to 6 in 2018 was analyzed.The results show that the low trough at 500 hPa,the southerly wind jet stream at 700 hPa,and the inverted trough on the ground were the main influencing systems causing this blizzard.The transportation of warm and humid air by the southerly wind jet stream at 700 hPa and intense water vapor convergence provided sufficient water vapor conditions for the blizzard,and the moist layer in the blizzard area was deep.The low-level MPV in the blizzard area was<0,and the atmosphere was in a conditional symmetric instability state.The coupling of the upper and lower-level jets induced strong ascending motion.With the invasion of cold air,a low-level cold pad was formed,so that the warm and humid air tilted upward.The secondary circulation updraft triggered by the wet Q vector system released the conditional symmetric instability energy,so that the sloping motion was more intense,and the heavy snowfall appeared.Meanwhile,there was a good correspondence relationship between the blizzard area and the large-value area of low-level wet Q vector divergence.The mesoscale cloud clusters continuously generating,merging,and moving eastward in Hetao area were the direct cause of this blizzard,and the TBB of the cloud clusters was≤-56℃.The blizzard happened in the the edge gradient and large-value area of TBB.展开更多
In the Tianshan region,a complete textile industry chain has been established,covering the entire process from cotton cultivation and chemical fiber production,through spinning,weaving,dyeing,and finishing,and further...In the Tianshan region,a complete textile industry chain has been established,covering the entire process from cotton cultivation and chemical fiber production,through spinning,weaving,dyeing,and finishing,and further extending to apparel,home textiles,and industrial textiles.In November 2025,the first list of five characteristic textile and apparel industry clusters in Xinjiang was officially announced,marking a new stage in the clustering of Xinjiang's textile and apparel industry.Data shows that the total output value of Xinjiang's cotton and textile and apparel industry chain has exceeded 220 billion yuan.With the nation's largest cotton production,a complete industrial chain system,and strong synergistic effects,Xinjiang has become a leading and highly competitive textile industry hub in China.展开更多
The exploration of solvent-driven reversible structural transformation in clusters is crucial for advanced stimulus-responsive optical applications and understanding of structure-property relationships.Herein,we repor...The exploration of solvent-driven reversible structural transformation in clusters is crucial for advanced stimulus-responsive optical applications and understanding of structure-property relationships.Herein,we report a solvent-driven reversible trans-formation between two copper(I)clusters:[Cu(totp)(CH_(3)CN)_(3)][Cu_(2)I_(3)(totp)(DPPPy)]·CH_(3)CN 1 and Cu_(4)I_(4)(DPPPy)_(2)·0.5CH_(2)Cl_(2)2(totp=tri-o-tolylphosphine,DPPPy=2-[diphenylphosphino]pyridine).X-ray radioluminescence and encryption applications were studied based on structure-dependent photophysical properties difference.The noncovalent interaction-mediated space charge transition between isolated ion units of 1 enables more efficient thermally activated delayed fluorescence by reverse intersystem crossing,accounting for structure-dependent luminescence.Notably,compared to 2,1 exhibits a higher scintillation light yield of 14832 photons MeV^(-1),exceeding that of the commercial scintillator Bi_(4)Ge_(3)O_(12)(8000 photons MeV^(-1)),and a low X-ray detection limit of 22.49 nGy s^(-1),far below the typical diagnostic dose(5.5μGy s^(-1)).Furthermore,scintillating film fabricated by 1 achieves X-ray imaging with a high spatial resolution of 16 lp/mm.The reversible structural interconversion enables solvent-responsive luminescent switches,and thus,the dynamic encryption system capable of multistage decryption was developed.This work not only offers new insight into solvent-regulated clusters transformations but also provides a promising strategy for developing high-performance copper(I)clusters-based scintillators and stimulus-responsive optical devices.展开更多
Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to p...Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.展开更多
Recently,hollow carbon nanospheres(HCSs)have garnered significant attention as potential Li metal hosts owing to their unique large voids and ease of fabrication.However,similar to other nanoscale hosts,their practica...Recently,hollow carbon nanospheres(HCSs)have garnered significant attention as potential Li metal hosts owing to their unique large voids and ease of fabrication.However,similar to other nanoscale hosts,their practical performance is limited by inhomogeneous agglomeration,increased binder requirements,and high tortuosity within the electrode.To overcome these problems and high tortuosity within the electrode,this study introduces a pomegranate-like carbon microcluster composed of primary HCSs(P-CMs)as a novel Li metal host.This unique nanostructure can be easily prepared using the spray-drying technique,enabling its mass production.Comprehensive analyses with various tools demonstrate that compared with HCS hosts,the P-CM host requires a smaller amount of binder to fabricate a sufficiently robust and even surface electrode.Furthermore,owing to reduced tortuosity,the well-designed P-CM electrode can provide continuous and shortened pathways for electron/ion transport,accelerating the Li-ion transfer kinetics and prohibiting preferential Li plating at the upper region of the electrode.Due to these characteristics,Li metal can be effectively encapsulated in the large inner voids of the primary HCSs constituting the P-CM,thereby enhancing the electrochemical performance of P-CM hosts in Li metal batteries.Specifically,the Coulombic efficiency of the P-CM host can be maintained at 97%over 100 cycles,with a high Li deposition areal capacity of 3 mAh·cm^(-2)and long cycle life(1000 h,1 mA·cm^(-2),and 1.0 mAh·cm^(-2)).Furthermore,a full cell incorporating a LiFePO4 cathode exhibits excellent cycle life.展开更多
In modern distributed systems and cloud computing architectures,high availability and high scalability are core requirements to ensure the continuous and stable operation of services.As key technologies for achieving ...In modern distributed systems and cloud computing architectures,high availability and high scalability are core requirements to ensure the continuous and stable operation of services.As key technologies for achieving these two goals,high-availability clusters and load-balancing clusters have significant differences in their design concepts and application scenarios,while also maintaining close connections.This paper aims to conduct an in-depth analysis of the core objectives,working principles,technical advantages and disadvantages,and typical application cases of high-availability clusters and load-balancing clusters.By introducing an analogical model of a“restaurant kitchen,”the differences between the two are intuitively explained,and their technical characteristics are compared in detail.Additionally,a detailed practical case is included to specifically demonstrate the collaborative work of high-availability and load-balancing technologies through the construction process of Keepalived and HAProxy.Finally,taking the architecture of a typical e-commerce website as an example,this paper demonstrates the best practice of organically combining the two cluster technologies in a production environment to build a robust and high-performance distributed system.Research shows that understanding the differences between the two and implementing collaborative deployment is the cornerstone of designing modern IT infrastructure.展开更多
Attributed graph clustering plays a vital role in uncovering hidden network structures,but it presents significant challenges.In recent years,various models have been proposed to identify meaningful clusters by integr...Attributed graph clustering plays a vital role in uncovering hidden network structures,but it presents significant challenges.In recent years,various models have been proposed to identify meaningful clusters by integrating both structural and attribute-based information.However,these models often emphasize node proximities without adequately balancing the efficiency of clustering based on both structural and attribute data.Furthermore,they tend to neglect the critical fuzzy information inherent in attributed graph clusters.To address these issues,we introduce a new framework,Markov lumpability optimization,for efficient clustering of large-scale attributed graphs.Specifically,we define a lumped Markov chain on an attribute-augmented graph and introduce a new metric,Markov lumpability,to quantify the differences between the original and lumped Markov transition probability matrices.To minimize this measure,we propose a conjugate gradient projectionbased approach that ensures the partitioning closely aligns with the intrinsic structure of fuzzy clusters through conditional optimization.Extensive experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed framework compared to existing clustering algorithms.This framework has many potential applications,including dynamic community analysis of social networks,user profiling in recommendation systems,functional module identification in biological molecular networks,and financial risk control,offering a new paradigm for mining complex patterns in high-dimensional attributed graph data.展开更多
Accurate description of noncova-lent interactions in large systems is challenging due to the require-ment of high-level electron corre-lation methods.The generalized energy-based fragmentation(GEBF)approach,in conjunc...Accurate description of noncova-lent interactions in large systems is challenging due to the require-ment of high-level electron corre-lation methods.The generalized energy-based fragmentation(GEBF)approach,in conjunc-tion with the domain-based local pair natural orbital(DLPNO)method,has been applied to assess the average binding energies(ABEs)of large benzene clus-ters,specifically(C6H6)13,at the coupled cluster singles and doubles with perturbative triples correction[CCSD(T)]level and the complete basis set(CBS)limit.Utilizing GEBF-DLPNO-CCSD(T)/CBS ABEs as benchmarks,various DFT functionals were evaluated.It was found that several functionals with empirical dispersion correction,including M06-2X-D3,B3LYP-D3(BJ),and PBE-D3(BJ),provide accurate descriptions of the ABEs for(C6H6)13 clusters.Additionally,the M06-2X-D3 functional was used to calculate the ABEs and relative stabili-ties of(C6H6)n clusters for n=11,12,13,14,and 15 revealing that the(C6H6)13 cluster ex-hibits the highest relative stability.These findings align with experimental evidence suggest-ing that n=13 is one of the magic numbers for benzene clusters(C6H6)n,with n≤30.展开更多
Traditional TiO_(2)gas sensing materials face limitations such as difficult energy band adjustment and high operating temperatures.Titanium-oxo clusters(TOCs),molecular analogs of TiO_(2),have shown promise in various...Traditional TiO_(2)gas sensing materials face limitations such as difficult energy band adjustment and high operating temperatures.Titanium-oxo clusters(TOCs),molecular analogs of TiO_(2),have shown promise in various applications but remain underexplored in practical applications of gas sensors.This study synthesized two classical TOCs,Ti_(4)O_(2)(O^(i)Pr)_(10)(1-Nap)_(2)(Ti_(4))and[Ti_(8)O_(8)(OMc)_(16)]·2CH_(3)CN(Ti_(8)),via solvothermal methods and evaluated their performances in detecting triethylamine(TEA)gas in the air for the first time.The Ti_(4)and Ti_(8)sensors exhibited high response values of 7.80 and 5.47,respectively,to 100 ppm TEA at optimal operating temperatures of 80 and 50℃,with excellent selectivity.Response/recovery times were 25/91 s for Ti_(4)and 137/230 s for Tig.Both sensors demonstrated good repeatability and long-term stability.The Ti8 sensor,with its lower operating temperature and superior linear fitting,was used to monitor carp fish freshness,showcasing its practical application potential.Finally,the sensing mechanism is analyzed.This study pioneers the use of TOCs for TEA detection and food freshness monitoring,offering new avenues for chemiresistive gas sensors.展开更多
LiNO_(3) is known to significantly enhance the reversibility of lithium metal batteries;however,the modification of solvation structures in various solvents and its further impact on the interface have not been fully ...LiNO_(3) is known to significantly enhance the reversibility of lithium metal batteries;however,the modification of solvation structures in various solvents and its further impact on the interface have not been fully revealed.Herein,we systematically studied the evolution of solvation structures with increasing LiNO_(3) concentration in both carbonate and ether electrolytes.The results from molecular dynamics simulations unveil that the Li^(+)solvation structure is less affected in carbonate electrolytes,while in ether electrolytes,there is a significant decrease of solvent molecules in Li^(+)coordination,and a larger average size of Li^(+)solvation structure emerges as LiNO_(3) concentration increases.Notably,the formation of large ion aggregates with size of several nanometers(nano-clusters),is observed in ether-based electrolytes at conventional Li^(+)concentration(1 M)with higher NO_(3)^(-) ratio,which is further proved by infrared spectroscopy and small-angle X-ray scattering experiments.The nano-clusters with abundant anions are endowed with a narrow energy gap of molecular orbitals,contributing to the formation of an inorganic rich electrode/electrolyte interphase that enhances the reversibility of lithium stripping/plating with Coulombic efficiency up to 99.71%.The discovery of nano-clusters elucidates the underlying mechanism linking ions/solvent aggregation states of electrolytes to interfacial stability in advanced battery systems.展开更多
Objective:This study aims to investigate the patterns of symptom occurrence in patients experiencing acute exacerbations of chronic obstructive pulmonary disease(AECOPD).It will explore the composition of symptom clus...Objective:This study aims to investigate the patterns of symptom occurrence in patients experiencing acute exacerbations of chronic obstructive pulmonary disease(AECOPD).It will explore the composition of symptom clusters and analyze the correlation between these clusters and health-related quality of life(HRQoL).Methods:A total of 207 patients with AE-COPD were surveyed from a tertiary grade A hospital.Data collection was conducted using three validated instruments:the Basic Information Questionnaire(BIQ),Disease Symptom Survey Questionnaire(MSAS),and Quality of Life Questionnaire(CAT).Statistical software SPSS 22.0 was used to analyze the correlation between symptom clusters and quality of life.Results:Exploratory factor analysis showed that five major symptom clusters existed in the patients,including the psycho-emotional symptom cluster,the sleep-related symptom cluster,the other side effects symptom cluster,the energy deficiency symptom cluster and the cough-loss of appetite symptom cluster,and the severity of the symptom clusters showed a significant negative correlation with the quality of life of the patients(P<0.05).Conclusion:Strengthening the comprehensive management of symptom clusters in patients with AE-COPD can help to effectively reduce the symptom burden of patients,and then significantly improve their quality of life.展开更多
Two-dimensional(2D)materials loaded with single atoms and clusters are being set at the forefront of catalysis due to their distinctive geometric and electronic features.However,the usually-complicated synthesis proce...Two-dimensional(2D)materials loaded with single atoms and clusters are being set at the forefront of catalysis due to their distinctive geometric and electronic features.However,the usually-complicated synthesis procedures impede in-depth clarification of their catalytic mechanisms.To this end,herein we developed an efficient one-step dimension-reduction carbonization strategy,with which we successfully architected a highly-efficient catalyst for oxygen reduction reaction(ORR),featured with symbiotic cobalt single atoms and clusters decorated in two-dimensional(2D)ultra-thin(3.5 nm thickness)nitrogen-carbon nanosheets.The synergistic effects of the two components afford excellent oxygen reduction activity in alkaline media(E_(1/2)=0.823 V vs.RHE)and thereof a high power density(146.61 mW cm^(-2))in an assembled Zn-air battery.As revealed by theoretical calculations,the cobalt clusters can regulate electrons surrounding those individual atoms and affect the adsorption of intermediate species.As a consequence,the derived active sites of single cobalt atoms lead to a significant improvement of the ORR performance.Thus,our work may fuel interests to delicate architectu re of single atoms and clusters coexisting 2D support toward optimal electrocatalytic performance.展开更多
Surface-supported clusters forming by aggregation of excessive adatoms could be the main defects of 2D materials after chemical vapor deposition.They will significantly impact the electronic/magnetic properties.Moreov...Surface-supported clusters forming by aggregation of excessive adatoms could be the main defects of 2D materials after chemical vapor deposition.They will significantly impact the electronic/magnetic properties.Moreover,surface supported atoms are also widely explored for high active and selecting catalysts.Severe deformation,even dipping into the surface,of these clusters can be expected because of the very active edge of clusters and strong interaction between supported clusters and surfaces.However,most models of these clusters are supposed to simply float on the top of the surface because ab initio simulations cannot afford the complex reconstructions.Here,we develop an accurate graph neural network machine learning potential(MLP)from ab initio data by active learning architecture through fine-tuning pre-trained models,and then employ the MLP into Monte Carlo to explore the structural evolutions of Mo and S clusters(1-8 atoms)on perfect and various defective MoS2 monolayers.Interestingly,Mo clusters can always sink and embed themselves into MoS2 layers.In contrast,S clusters float on perfect surfaces.On the defective surface,a few S atoms will fill the vacancy and rest S clusters float on the top.Such significant structural reconstructions should be carefully taken into account.展开更多
Dispersing metals from nanoparticles to clusters is often achieved using ligand protection methods,which exhibit unique properties such as suppressing structure-sensitive side reactions.However,this method is limited ...Dispersing metals from nanoparticles to clusters is often achieved using ligand protection methods,which exhibit unique properties such as suppressing structure-sensitive side reactions.However,this method is limited by the use of different metal precursor salts corresponding to different ligands.An alternative approach,the ion exchange(IE)method,can overcome this limitation to some extent.Nevertheless,there is still an urgent need to address the stabilization of metals(especially precious metals)by using IE method.Here,we reported a Pt cluster catalyst prepared mainly by anchoring Pt atoms via O located near the framework Zn in zincosilicate zeolites and riveted by zeolite surface rings after reduction(reduced Pt/Zn-3-IE).The catalyst can achieve an initial propane conversion of 26%in a pure propane atmosphere at 550℃and shows little deactivation even after 7.5 d of operation.Moreover,the alteration of catalyst by the introduction of framework Zn was also highlighted and interpreted.展开更多
Metal nanoclusters with well-defined atomic structures offer significant promise in the field of catalysis due to their sub-nanometer size and tunable organic-inorganic hybrid structural features.Herein,we successfull...Metal nanoclusters with well-defined atomic structures offer significant promise in the field of catalysis due to their sub-nanometer size and tunable organic-inorganic hybrid structural features.Herein,we successfully synthesized an 11-core copper(Ⅰ)-alkynyl nanocluster(Cu11),which is stabilized by alkynyl ligands derived from a photosensitive rhodamine dye molecule.Notably,this Cu11cluster exhibited excellent photocatalytic hydrogen evolution activity(8.13 mmol g-1h-1)even in the absence of a mediator and noble metal co-catalyst.Furthermore,when Cu11clusters were loaded onto the surface of TiO_(2)nanosheets,the resultant Cu11@TiO_(2)nanocomposites exhibited a significant enhancement in hydrogen evolution efficiency,which is 60 times higher than that of pure TiO_(2)nanosheets.The incorporation of Cu11clusters within the Cu11@TiO_(2)effectively inhibits the recombination of photogenerated electrons and holes,thereby accelerating the charge separation and migration in the composite material.This work introduces a novel perspective for designing highly active copper cluster-based photocatalysts.展开更多
Noncohesive particle clusters are identified and tracked in turbulent flows to determine the breakdown and time evolution of cluster statistics and their implications for interscale mass transfer,which has connections...Noncohesive particle clusters are identified and tracked in turbulent flows to determine the breakdown and time evolution of cluster statistics and their implications for interscale mass transfer,which has connections to the classical turbulent energy cascade and its mass cascade counterpart running in parallel.In particular,the formation and dynamics of sediment and larvae clusters are of interest to coral larvae settlement in coastal regions and particularly the resilience of green-gray coastal protection solutions.Analogous cluster behavior is relevant to cloud microphysics and precipitation initiation,radiation transport and light transmission through colloids and suspensions,heat and mass transfer in particle-laden flows,and viral and pollutant transmission.Following a comparison between various clustering techniques,we adopt a density-based cluster identification algorithm based on its simplicity and efficiency,where particles are clustered based on the number of neighboring particles in their individual spheres of influence.We establish parallels with lattice-based percolation theory,as evident in the power-law scaling of the cluster size distribution near the percolation threshold.The degree of discontinuity of the phase transition associated with this percolation threshold is observed to broaden with larger Stokes numbers and thereby large-scale clustering.The sensitivity of our findings to the employed clustering algorithm is discussed.A novel cluster tracking algorithm is deployed to determine the interscale transfer rate along the particle-number phase-space dimension via accounting of cluster breakup and merger events,extending previous work on the bubble breakup cascade beneath surface breaking waves.Our findings shed light on the interaction between particle clusters and their carrier turbulent flows,with an eye toward transport models incorporating cluster characteristics and dynamics.展开更多
基金Supported by the Meteorological Science and Technology Innovation Project of North China(HBXM202415)Research Project of the Meteorological Bureau of Inner Mongolia Autonomous Region(nmqxkjcx202311).
文摘Based on the conventional observation data,daily reanalysis data from NCAR/NCEP,and TBB data derived from FY-2G infrared cloud images in April 2018,a heavy snowfall weather process in central Inner Mongolia from April 4 to 6 in 2018 was analyzed.The results show that the low trough at 500 hPa,the southerly wind jet stream at 700 hPa,and the inverted trough on the ground were the main influencing systems causing this blizzard.The transportation of warm and humid air by the southerly wind jet stream at 700 hPa and intense water vapor convergence provided sufficient water vapor conditions for the blizzard,and the moist layer in the blizzard area was deep.The low-level MPV in the blizzard area was<0,and the atmosphere was in a conditional symmetric instability state.The coupling of the upper and lower-level jets induced strong ascending motion.With the invasion of cold air,a low-level cold pad was formed,so that the warm and humid air tilted upward.The secondary circulation updraft triggered by the wet Q vector system released the conditional symmetric instability energy,so that the sloping motion was more intense,and the heavy snowfall appeared.Meanwhile,there was a good correspondence relationship between the blizzard area and the large-value area of low-level wet Q vector divergence.The mesoscale cloud clusters continuously generating,merging,and moving eastward in Hetao area were the direct cause of this blizzard,and the TBB of the cloud clusters was≤-56℃.The blizzard happened in the the edge gradient and large-value area of TBB.
文摘In the Tianshan region,a complete textile industry chain has been established,covering the entire process from cotton cultivation and chemical fiber production,through spinning,weaving,dyeing,and finishing,and further extending to apparel,home textiles,and industrial textiles.In November 2025,the first list of five characteristic textile and apparel industry clusters in Xinjiang was officially announced,marking a new stage in the clustering of Xinjiang's textile and apparel industry.Data shows that the total output value of Xinjiang's cotton and textile and apparel industry chain has exceeded 220 billion yuan.With the nation's largest cotton production,a complete industrial chain system,and strong synergistic effects,Xinjiang has become a leading and highly competitive textile industry hub in China.
基金supported by the National Natural Science Foundation of China(21971240 and 22271283)the Natural Science Foundation of Shandong Province(ZR2025QC1361)。
文摘The exploration of solvent-driven reversible structural transformation in clusters is crucial for advanced stimulus-responsive optical applications and understanding of structure-property relationships.Herein,we report a solvent-driven reversible trans-formation between two copper(I)clusters:[Cu(totp)(CH_(3)CN)_(3)][Cu_(2)I_(3)(totp)(DPPPy)]·CH_(3)CN 1 and Cu_(4)I_(4)(DPPPy)_(2)·0.5CH_(2)Cl_(2)2(totp=tri-o-tolylphosphine,DPPPy=2-[diphenylphosphino]pyridine).X-ray radioluminescence and encryption applications were studied based on structure-dependent photophysical properties difference.The noncovalent interaction-mediated space charge transition between isolated ion units of 1 enables more efficient thermally activated delayed fluorescence by reverse intersystem crossing,accounting for structure-dependent luminescence.Notably,compared to 2,1 exhibits a higher scintillation light yield of 14832 photons MeV^(-1),exceeding that of the commercial scintillator Bi_(4)Ge_(3)O_(12)(8000 photons MeV^(-1)),and a low X-ray detection limit of 22.49 nGy s^(-1),far below the typical diagnostic dose(5.5μGy s^(-1)).Furthermore,scintillating film fabricated by 1 achieves X-ray imaging with a high spatial resolution of 16 lp/mm.The reversible structural interconversion enables solvent-responsive luminescent switches,and thus,the dynamic encryption system capable of multistage decryption was developed.This work not only offers new insight into solvent-regulated clusters transformations but also provides a promising strategy for developing high-performance copper(I)clusters-based scintillators and stimulus-responsive optical devices.
基金supported by the Specific Research Fund for Top-notch Talents of Guangdong Provincial Hospital of Chinese Medicine(No.2022KT1188).
文摘Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2020R1C1C1003375)。
文摘Recently,hollow carbon nanospheres(HCSs)have garnered significant attention as potential Li metal hosts owing to their unique large voids and ease of fabrication.However,similar to other nanoscale hosts,their practical performance is limited by inhomogeneous agglomeration,increased binder requirements,and high tortuosity within the electrode.To overcome these problems and high tortuosity within the electrode,this study introduces a pomegranate-like carbon microcluster composed of primary HCSs(P-CMs)as a novel Li metal host.This unique nanostructure can be easily prepared using the spray-drying technique,enabling its mass production.Comprehensive analyses with various tools demonstrate that compared with HCS hosts,the P-CM host requires a smaller amount of binder to fabricate a sufficiently robust and even surface electrode.Furthermore,owing to reduced tortuosity,the well-designed P-CM electrode can provide continuous and shortened pathways for electron/ion transport,accelerating the Li-ion transfer kinetics and prohibiting preferential Li plating at the upper region of the electrode.Due to these characteristics,Li metal can be effectively encapsulated in the large inner voids of the primary HCSs constituting the P-CM,thereby enhancing the electrochemical performance of P-CM hosts in Li metal batteries.Specifically,the Coulombic efficiency of the P-CM host can be maintained at 97%over 100 cycles,with a high Li deposition areal capacity of 3 mAh·cm^(-2)and long cycle life(1000 h,1 mA·cm^(-2),and 1.0 mAh·cm^(-2)).Furthermore,a full cell incorporating a LiFePO4 cathode exhibits excellent cycle life.
文摘In modern distributed systems and cloud computing architectures,high availability and high scalability are core requirements to ensure the continuous and stable operation of services.As key technologies for achieving these two goals,high-availability clusters and load-balancing clusters have significant differences in their design concepts and application scenarios,while also maintaining close connections.This paper aims to conduct an in-depth analysis of the core objectives,working principles,technical advantages and disadvantages,and typical application cases of high-availability clusters and load-balancing clusters.By introducing an analogical model of a“restaurant kitchen,”the differences between the two are intuitively explained,and their technical characteristics are compared in detail.Additionally,a detailed practical case is included to specifically demonstrate the collaborative work of high-availability and load-balancing technologies through the construction process of Keepalived and HAProxy.Finally,taking the architecture of a typical e-commerce website as an example,this paper demonstrates the best practice of organically combining the two cluster technologies in a production environment to build a robust and high-performance distributed system.Research shows that understanding the differences between the two and implementing collaborative deployment is the cornerstone of designing modern IT infrastructure.
基金supported by the National Natural Science Foundation of China(Grant No.72571150)Beijing Natural Science Foundation(Grant No.9182015)。
文摘Attributed graph clustering plays a vital role in uncovering hidden network structures,but it presents significant challenges.In recent years,various models have been proposed to identify meaningful clusters by integrating both structural and attribute-based information.However,these models often emphasize node proximities without adequately balancing the efficiency of clustering based on both structural and attribute data.Furthermore,they tend to neglect the critical fuzzy information inherent in attributed graph clusters.To address these issues,we introduce a new framework,Markov lumpability optimization,for efficient clustering of large-scale attributed graphs.Specifically,we define a lumped Markov chain on an attribute-augmented graph and introduce a new metric,Markov lumpability,to quantify the differences between the original and lumped Markov transition probability matrices.To minimize this measure,we propose a conjugate gradient projectionbased approach that ensures the partitioning closely aligns with the intrinsic structure of fuzzy clusters through conditional optimization.Extensive experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed framework compared to existing clustering algorithms.This framework has many potential applications,including dynamic community analysis of social networks,user profiling in recommendation systems,functional module identification in biological molecular networks,and financial risk control,offering a new paradigm for mining complex patterns in high-dimensional attributed graph data.
基金supported by the National Key R&D Program of China(No.2023YFB3712504)the National Natural Science Foundation of China(Nos.22273038,22073043,and 22033004)。
文摘Accurate description of noncova-lent interactions in large systems is challenging due to the require-ment of high-level electron corre-lation methods.The generalized energy-based fragmentation(GEBF)approach,in conjunc-tion with the domain-based local pair natural orbital(DLPNO)method,has been applied to assess the average binding energies(ABEs)of large benzene clus-ters,specifically(C6H6)13,at the coupled cluster singles and doubles with perturbative triples correction[CCSD(T)]level and the complete basis set(CBS)limit.Utilizing GEBF-DLPNO-CCSD(T)/CBS ABEs as benchmarks,various DFT functionals were evaluated.It was found that several functionals with empirical dispersion correction,including M06-2X-D3,B3LYP-D3(BJ),and PBE-D3(BJ),provide accurate descriptions of the ABEs for(C6H6)13 clusters.Additionally,the M06-2X-D3 functional was used to calculate the ABEs and relative stabili-ties of(C6H6)n clusters for n=11,12,13,14,and 15 revealing that the(C6H6)13 cluster ex-hibits the highest relative stability.These findings align with experimental evidence suggest-ing that n=13 is one of the magic numbers for benzene clusters(C6H6)n,with n≤30.
基金financially supported by Jilin Provincial Scientific and Technological Development Program(No.YDZJ202501ZYTS284)the Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)the National Natural Science Foundation of China(No.51902029)
文摘Traditional TiO_(2)gas sensing materials face limitations such as difficult energy band adjustment and high operating temperatures.Titanium-oxo clusters(TOCs),molecular analogs of TiO_(2),have shown promise in various applications but remain underexplored in practical applications of gas sensors.This study synthesized two classical TOCs,Ti_(4)O_(2)(O^(i)Pr)_(10)(1-Nap)_(2)(Ti_(4))and[Ti_(8)O_(8)(OMc)_(16)]·2CH_(3)CN(Ti_(8)),via solvothermal methods and evaluated their performances in detecting triethylamine(TEA)gas in the air for the first time.The Ti_(4)and Ti_(8)sensors exhibited high response values of 7.80 and 5.47,respectively,to 100 ppm TEA at optimal operating temperatures of 80 and 50℃,with excellent selectivity.Response/recovery times were 25/91 s for Ti_(4)and 137/230 s for Tig.Both sensors demonstrated good repeatability and long-term stability.The Ti8 sensor,with its lower operating temperature and superior linear fitting,was used to monitor carp fish freshness,showcasing its practical application potential.Finally,the sensing mechanism is analyzed.This study pioneers the use of TOCs for TEA detection and food freshness monitoring,offering new avenues for chemiresistive gas sensors.
基金supported by the National Natural Science Foundation of China(No.22372083,52201259)the National Key R&D Program of China(2021YFB2500300)+2 种基金the Fundamental Research Funds for the Central Universities:Nankai University(63241607)the Natural Science Foundation of Tianjin(No.22JCZDJC00380)the Young Elite Scientist Sponsorship Program by CAST.
文摘LiNO_(3) is known to significantly enhance the reversibility of lithium metal batteries;however,the modification of solvation structures in various solvents and its further impact on the interface have not been fully revealed.Herein,we systematically studied the evolution of solvation structures with increasing LiNO_(3) concentration in both carbonate and ether electrolytes.The results from molecular dynamics simulations unveil that the Li^(+)solvation structure is less affected in carbonate electrolytes,while in ether electrolytes,there is a significant decrease of solvent molecules in Li^(+)coordination,and a larger average size of Li^(+)solvation structure emerges as LiNO_(3) concentration increases.Notably,the formation of large ion aggregates with size of several nanometers(nano-clusters),is observed in ether-based electrolytes at conventional Li^(+)concentration(1 M)with higher NO_(3)^(-) ratio,which is further proved by infrared spectroscopy and small-angle X-ray scattering experiments.The nano-clusters with abundant anions are endowed with a narrow energy gap of molecular orbitals,contributing to the formation of an inorganic rich electrode/electrolyte interphase that enhances the reversibility of lithium stripping/plating with Coulombic efficiency up to 99.71%.The discovery of nano-clusters elucidates the underlying mechanism linking ions/solvent aggregation states of electrolytes to interfacial stability in advanced battery systems.
文摘Objective:This study aims to investigate the patterns of symptom occurrence in patients experiencing acute exacerbations of chronic obstructive pulmonary disease(AECOPD).It will explore the composition of symptom clusters and analyze the correlation between these clusters and health-related quality of life(HRQoL).Methods:A total of 207 patients with AE-COPD were surveyed from a tertiary grade A hospital.Data collection was conducted using three validated instruments:the Basic Information Questionnaire(BIQ),Disease Symptom Survey Questionnaire(MSAS),and Quality of Life Questionnaire(CAT).Statistical software SPSS 22.0 was used to analyze the correlation between symptom clusters and quality of life.Results:Exploratory factor analysis showed that five major symptom clusters existed in the patients,including the psycho-emotional symptom cluster,the sleep-related symptom cluster,the other side effects symptom cluster,the energy deficiency symptom cluster and the cough-loss of appetite symptom cluster,and the severity of the symptom clusters showed a significant negative correlation with the quality of life of the patients(P<0.05).Conclusion:Strengthening the comprehensive management of symptom clusters in patients with AE-COPD can help to effectively reduce the symptom burden of patients,and then significantly improve their quality of life.
基金supported by the National Natural Science Foundation of China(51872115 and 12234018)Beijing Synchrotron Radiation Facility(BSRF)4B9A.
文摘Two-dimensional(2D)materials loaded with single atoms and clusters are being set at the forefront of catalysis due to their distinctive geometric and electronic features.However,the usually-complicated synthesis procedures impede in-depth clarification of their catalytic mechanisms.To this end,herein we developed an efficient one-step dimension-reduction carbonization strategy,with which we successfully architected a highly-efficient catalyst for oxygen reduction reaction(ORR),featured with symbiotic cobalt single atoms and clusters decorated in two-dimensional(2D)ultra-thin(3.5 nm thickness)nitrogen-carbon nanosheets.The synergistic effects of the two components afford excellent oxygen reduction activity in alkaline media(E_(1/2)=0.823 V vs.RHE)and thereof a high power density(146.61 mW cm^(-2))in an assembled Zn-air battery.As revealed by theoretical calculations,the cobalt clusters can regulate electrons surrounding those individual atoms and affect the adsorption of intermediate species.As a consequence,the derived active sites of single cobalt atoms lead to a significant improvement of the ORR performance.Thus,our work may fuel interests to delicate architectu re of single atoms and clusters coexisting 2D support toward optimal electrocatalytic performance.
基金supported by the National Natural Science Foundation of China(Grant No.12374253,12074053,12004064)J.G.thanks the Foreign talents project(G2022127004L),The authors also acknowledge computer support from the Shanghai Supercomputer Center,the DUT Supercomputing Center,and the Tianhe supercomputer of Tianjin Center.
文摘Surface-supported clusters forming by aggregation of excessive adatoms could be the main defects of 2D materials after chemical vapor deposition.They will significantly impact the electronic/magnetic properties.Moreover,surface supported atoms are also widely explored for high active and selecting catalysts.Severe deformation,even dipping into the surface,of these clusters can be expected because of the very active edge of clusters and strong interaction between supported clusters and surfaces.However,most models of these clusters are supposed to simply float on the top of the surface because ab initio simulations cannot afford the complex reconstructions.Here,we develop an accurate graph neural network machine learning potential(MLP)from ab initio data by active learning architecture through fine-tuning pre-trained models,and then employ the MLP into Monte Carlo to explore the structural evolutions of Mo and S clusters(1-8 atoms)on perfect and various defective MoS2 monolayers.Interestingly,Mo clusters can always sink and embed themselves into MoS2 layers.In contrast,S clusters float on perfect surfaces.On the defective surface,a few S atoms will fill the vacancy and rest S clusters float on the top.Such significant structural reconstructions should be carefully taken into account.
文摘Dispersing metals from nanoparticles to clusters is often achieved using ligand protection methods,which exhibit unique properties such as suppressing structure-sensitive side reactions.However,this method is limited by the use of different metal precursor salts corresponding to different ligands.An alternative approach,the ion exchange(IE)method,can overcome this limitation to some extent.Nevertheless,there is still an urgent need to address the stabilization of metals(especially precious metals)by using IE method.Here,we reported a Pt cluster catalyst prepared mainly by anchoring Pt atoms via O located near the framework Zn in zincosilicate zeolites and riveted by zeolite surface rings after reduction(reduced Pt/Zn-3-IE).The catalyst can achieve an initial propane conversion of 26%in a pure propane atmosphere at 550℃and shows little deactivation even after 7.5 d of operation.Moreover,the alteration of catalyst by the introduction of framework Zn was also highlighted and interpreted.
基金supported by the National Natural Science Foundation of China(Nos.22371263 and U2004193)Natural Science Foundation of Henan Province(No.232300421225)。
文摘Metal nanoclusters with well-defined atomic structures offer significant promise in the field of catalysis due to their sub-nanometer size and tunable organic-inorganic hybrid structural features.Herein,we successfully synthesized an 11-core copper(Ⅰ)-alkynyl nanocluster(Cu11),which is stabilized by alkynyl ligands derived from a photosensitive rhodamine dye molecule.Notably,this Cu11cluster exhibited excellent photocatalytic hydrogen evolution activity(8.13 mmol g-1h-1)even in the absence of a mediator and noble metal co-catalyst.Furthermore,when Cu11clusters were loaded onto the surface of TiO_(2)nanosheets,the resultant Cu11@TiO_(2)nanocomposites exhibited a significant enhancement in hydrogen evolution efficiency,which is 60 times higher than that of pure TiO_(2)nanosheets.The incorporation of Cu11clusters within the Cu11@TiO_(2)effectively inhibits the recombination of photogenerated electrons and holes,thereby accelerating the charge separation and migration in the composite material.This work introduces a novel perspective for designing highly active copper cluster-based photocatalysts.
文摘Noncohesive particle clusters are identified and tracked in turbulent flows to determine the breakdown and time evolution of cluster statistics and their implications for interscale mass transfer,which has connections to the classical turbulent energy cascade and its mass cascade counterpart running in parallel.In particular,the formation and dynamics of sediment and larvae clusters are of interest to coral larvae settlement in coastal regions and particularly the resilience of green-gray coastal protection solutions.Analogous cluster behavior is relevant to cloud microphysics and precipitation initiation,radiation transport and light transmission through colloids and suspensions,heat and mass transfer in particle-laden flows,and viral and pollutant transmission.Following a comparison between various clustering techniques,we adopt a density-based cluster identification algorithm based on its simplicity and efficiency,where particles are clustered based on the number of neighboring particles in their individual spheres of influence.We establish parallels with lattice-based percolation theory,as evident in the power-law scaling of the cluster size distribution near the percolation threshold.The degree of discontinuity of the phase transition associated with this percolation threshold is observed to broaden with larger Stokes numbers and thereby large-scale clustering.The sensitivity of our findings to the employed clustering algorithm is discussed.A novel cluster tracking algorithm is deployed to determine the interscale transfer rate along the particle-number phase-space dimension via accounting of cluster breakup and merger events,extending previous work on the bubble breakup cascade beneath surface breaking waves.Our findings shed light on the interaction between particle clusters and their carrier turbulent flows,with an eye toward transport models incorporating cluster characteristics and dynamics.
