Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully construct...Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully constructed by coordinatively assembling the semi-rigid multidentate ligand 5-(1-carboxyethoxy)isophthalic acid(H₃CIA)with the Nheterocyclic ligands 1,4-di(4H-1,2,4-triazol-4-yl)benzene(1,4-dtb)and 1,4-di(1H-imidazol-1-yl)benzene(1,4-dib),respectively,around Co^(2+)ions.Single-crystal X-ray diffraction analysis revealed that in both complexes HU23 and HU24,the CIA^(3-)anions adopt aκ^(7)-coordination mode,bridging six Co^(2+)ions via their five carboxylate oxygen atoms and one ether oxygen atom.This linkage forms tetranuclear[Co4(μ3-OH)2]^(6+)units.These Co-oxo cluster units were interconnected by CIA^(3-)anions to assemble into 2D kgd-type structures featuring a 3,6-connected topology.The 2D layers were further connected by 1,4-dtb and 1,4-dib,resulting in 3D pillar-layered frameworks for HU23 and HU24.Notably,despite the similar configurations of 1,4-dtb and 1,4-dib,differences in their coordination spatial orientations lead to topological divergence in the 3D frameworks of HU23 and HU24.Topological analysis indicates that the frameworks of HU23 and HU24 can be simplified into a 3,10-connected net(point symbol:(4^(10).6^(3).8^(2))(4^(3))_(2))and a 3,8-connected tfz-d net(point symbol:(4^(3))_(2)((4^(6).6^(18).8^(4)))),respectively.This structural differentiation confirms the precise regulatory role of ligands on the topology of metal-organic frameworks.Moreover,the ultraviolet-visible absorption spectra confirmed that HU23 and HU24 have strong absorption capabilities for ultraviolet and visible light.According to the Kubelka-Munk method,their bandwidths were 2.15 and 2.08 eV,respectively,which are consistent with those of typical semiconductor materials.Variable-temperature magnetic susceptibility measurements(2-300 K)revealed significant antiferromagnetic coupling in both complexes,with their effective magnetic moments decreasing markedly as the temperature lowered.CCDC:2457554,HU23;2457553,HU24.展开更多
Effective control of gas-phase pollutants(volatile organic compounds(VOCs)and CO)is critical to human health and the ecological environment.Catalytic oxidation is one of the most promising technologies for achieving e...Effective control of gas-phase pollutants(volatile organic compounds(VOCs)and CO)is critical to human health and the ecological environment.Catalytic oxidation is one of the most promising technologies for achieving efficient volatile organic compounds and CO emission control.The subnano cluster catalyst can not only provide catalytic sites with multiple metal atoms,but also maintain full utilization efficiency.Almost all metal atoms in highly dispersed clusters can be used for adsorption and conversion of reactants.Recently,various types of sub-nano clusters,including subnano cluster oxides,have been developed and demonstrated excellent performance in low-temperature gas-phase pollutants combustion.In this mini review,we systematically summarize the structure,physicochemical properties,characterization,and applications of sub-nano cluster catalysts in catalytic oxidation of CO,methane,propane,propylene,toluene and its derivatives,formaldehyde and chlorinated volatile organic compounds.Finally,we have analyzed and discussed the problems and challenges faced by sub-nano cluster catalysts in both basic research and practical applications,providing a scientific basis for the design,synthesis,and application of efficient heterogeneous catalysts for CO and VOCs oxidation.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
In our study we investigated a refractory copper-nickel sulfide ore separation by using a cyclonic-static micro-bubble flotation column (FCSMC). The process mineralogy of the main products was studied. Using a scannin...In our study we investigated a refractory copper-nickel sulfide ore separation by using a cyclonic-static micro-bubble flotation column (FCSMC). The process mineralogy of the main products was studied. Using a scanning electron microscope-energy dispersive system (SEM-EDS) and an X-ray spectrometer the mineral category and content of samples were analyzed. By using a mineral liberation analyzer (MLA) the mineral liberation characteristics were revealed. It is shown that in roughing feed the monomers liberation degree of nickel pyrite and chalcopyrite take up 84.11% and 88.82%, respectively. In tailings, the lost nickel pyrite and chalcopyrite are mainly monomers. Therefore, strengthening the micro-fine particle recovery capacity is the key to increase recovery.展开更多
The effect of micro-bubbles on the turbulent boundary layer in the channel flow with Reynolds numbers (Re) ranging from 0.87 × 105 to 1.23 × 105 is experimentally studied by using particle image velocimetry ...The effect of micro-bubbles on the turbulent boundary layer in the channel flow with Reynolds numbers (Re) ranging from 0.87 × 105 to 1.23 × 105 is experimentally studied by using particle image velocimetry (PIV) measurements.The microbubbles are produced by water electrolysis.The velocity profiles,Reynolds stress and instantaneous structures of the boundary layer,with and without micro-bubbles,are measured and analyzed.The presence of micro-bubbles changes the streamwise mean velocity of the fluid and increases the wall shear stress.The results show that micro-bubbles have two effects,buoyancy and extrusion,which dominate the flow behavior of the mixed fluid in the turbulent boundary layer.The buoyancy effect leads to upward motion that drives the fluid motion in the same direction and,therefore,enhances the turbulence intense of the boundary layer.While for the extrusion effect,the presence of accumulated micro-bubbles pushes the flow structures in the turbulent boundary layer away from the near-wall region.The interaction between these two effects causes the vorticity structures and turbulence activity to be in the region far away from the wall.The buoyancy effect is dominant when the Re is relatively small,while the extrusion effect plays a more important role when Re rises.展开更多
Ship hull form of the underwater area strongly influences the resistance of the ship. The major factor in ship resistance is skin friction resistance. Bulbous bows, polymer paint, water repellent paint （highly water-...Ship hull form of the underwater area strongly influences the resistance of the ship. The major factor in ship resistance is skin friction resistance. Bulbous bows, polymer paint, water repellent paint （highly water-repellent wall）, air injection, and specific roughness have been used by researchers as an attempt to obtain the resistance reduction and operation efficiency of ships. Micro-bubble injection is a promising technique for lowering frictional resistance. The injected air bubbles are supposed to somehow modify the energy inside the turbulent boundary layer and thereby lower the skin friction. The purpose of this study was to identify the effect of injected micro bubbles on a navy fast patrol boat （FPB） 57 m type model with the following main dimensions： L=2 450 ram, B=400 mm, and T=190 mm. The influence of the location of micro bubble injection and bubble velocity was also investigated. The ship model was pulled by an electric motor whose speed could be varied and adjusted. The ship model resistance was precisely measured by a load cell transducer. Comparison of ship resistance with and without micro-bubble injection was shown on a graph as a function of the drag coefficient and Froude number. It was shown that micro bubble injection behind the mid-ship is the best location to achieve the most effective drag reduction, and the drag reduction caused by the micro-bubbles can reach 6%-9%.展开更多
In order to optimize plastic viscosity of 18 mPa·s circulating micro-bubble drilling fluid formula,orthogonal and uniform experimental design methods were applied,and the plastic viscosities of 36 and 24 groups o...In order to optimize plastic viscosity of 18 mPa·s circulating micro-bubble drilling fluid formula,orthogonal and uniform experimental design methods were applied,and the plastic viscosities of 36 and 24 groups of agent were tested,respectively.It is found that these two experimental design methods show drawbacks,that is,the amount of agent is difficult to determine,and the results are not fully optimized.Therefore,multiple regression experimental method was used to design experimental formula.By randomly selecting arbitrary agent with the amount within the recommended range,17 groups of drilling fluid formula were designed,and the plastic viscosity of each experiment formula was measured.Set plastic viscosity as the objective function,through multiple regressions,then quadratic regression model is obtained,whose correlation coefficient meets the requirement.Set target values of plastic viscosity to be 18,20 and 22 mPa·s,respectively,with the trial method,5 drilling fluid formulas are obtained with accuracy of 0.000 3,0.000 1 and 0.000 3.Arbitrarily select target value of each of the two groups under the formula for experimental verification of drilling fluid,then the measurement errors between theoretical and tested plastic viscosity are less than 5%,confirming that regression model can be applied to optimizing the circulating of plastic-foam drilling fluid viscosity.In accordance with the precision of different formulations of drilling fluid for other constraints,the methods result in the optimization of the circulating micro-bubble drilling fluid parameters.展开更多
Laboratory experiments have been conducted to study the flow field in a cyclone static micro-bubble flotation column. The method of Particle Image Velocimetry (PIV) was used. The flow field velocity distribution in bo...Laboratory experiments have been conducted to study the flow field in a cyclone static micro-bubble flotation column. The method of Particle Image Velocimetry (PIV) was used. The flow field velocity distribution in both cross section and longitudinal section within cyclonic zone was studied for different circulating volumes. The cross sectional vortex was also analyzed. The results show that in cross section as the circulating volume increases from 0.187 to 0.350 m 3 /h, the flow velocity ranges from 0 to 0.68 m/s. The flow field is mainly a non-vortex potential flow that forms a free vortex without outside energy input. In the cyclonic region the vortex deviates from the center of the flotation column because a single tangential opening introduces circulating fluid into the column. The tangential component of the velocity plays a defining role in the cross section. In the longitudinal section the velocity ranges from 0 to 0.08 m/s. The flow velocity increases as does the circulating volume. Advantageous mineral separation conditions arise from the combined effects of cyclonic flow in cross and longitudinal section.展开更多
Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy cl...Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.展开更多
Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients a...Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.展开更多
Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subse...Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.展开更多
The pursuit of Ag-based alloys with both high strength and toughness has posed a longstanding chal-lenge.In this study,we investigated the cluster strengthening and grain refinement toughening mecha-nisms in fully oxi...The pursuit of Ag-based alloys with both high strength and toughness has posed a longstanding chal-lenge.In this study,we investigated the cluster strengthening and grain refinement toughening mecha-nisms in fully oxidized AgMgNi alloys,which were internally oxidized at 800℃ for 8 h under an oxy-gen atmosphere.We found that Mg-O clusters contributed to the hardening(138 HV)and strengthening(376.9 MPa)of the AgMg alloy through solid solution strengthening effects,albeit at the expense of duc-tility.To address this limitation,we introduced Ni nanoparticles into the AgMg alloy,resulting in signifi-cant grain refinement within its microstructure.Specifically,the grain size decreased from 67.2μm in the oxidized AgMg alloy to below 6.0μm in the oxidized AgMgNi alloy containing 0.3 wt%Ni.Consequently,the toughness increased significantly,rising from toughness value of 2177.9 MJ m^(-3) in the oxidized AgMg alloy to 6186.1 MJ m^(-3) in the oxidized AgMgNi alloy,representing a remarkable 2.8-fold enhancement.Furthermore,the internally oxidized AgMgNi alloy attained a strength of up to 387.6 MPa,comparable to that of the internally oxidized AgMg alloy,thereby demonstrating the successful realization of concurrent strengthening and toughening.These results collectively offer a novel approach for the design of high-performance alloys through the synergistic combination of cluster strengthening and grain refinement toughening.展开更多
Given customizable crystal structure and intriguing optical properties,lanthanide titanium-oxygen clusters(LTOCs)with atomic-level accuracy have gained a lot of interest.In this study,we prepared[Ln_(9)Ti_(2)(μ4-O)(...Given customizable crystal structure and intriguing optical properties,lanthanide titanium-oxygen clusters(LTOCs)with atomic-level accuracy have gained a lot of interest.In this study,we prepared[Ln_(9)Ti_(2)(μ4-O)(μ3-OH)_(14)(acac)_(17)(CH_(3)O)_(2)(CH_(3)OH)_(3)](Ln=Tb_(x)Eu_(9−x)(x=0,4,6,7,8,9),Hacac=acetylacetone),Tb^(3+)and Eu^(3+)co-doped LTOCs,to modify the optical properties for the luminescence thermometer.In detail,the serial LTOCs display dual characteristic emission peaks of ^(5)D_(4)→^(7)F_(5) for Tb^(3+)and^(5)D_(0)→^(7)F_(2) for Eu^(3+)at 548 and 616 nm,respectively,under 330 nm excitation.Effective energy transfer(ET)between Tb^(3+)ions and Eu^(3+)ions was revealed in terms of both emission spectra and luminescence lifetime.The ^(5)D_(0)→^(7)F_(2) emission intensity of Eu^(3+)ions at 616 nm is maximally enhanced(by a factor of 11.2)with a change in the relative molar ratio of Tb^(3+)to Eu^(3+),along with a change in the ET efficiency of Tb^(3+)→Eu^(3+).In addition,the luminescent color changes from red,orange,yellow,to green.This precise control of the ET process between rare-earth ions allows{Tb_(6)Eu_(3)Ti_(2)}to reach a maximum relative sensitivity of 1.241 K^(−1) at 355 K,which is an enhancement of up to 4.6-fold with respect to the previously reported homonuclear emission,holding great potential in the optical thermometers.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
By systematically reviewing the development status of global carbon dioxide capture,utilization and storage(CCUS)cluster,and comparing domestic and international CCUS industrial models and successful experiences,this ...By systematically reviewing the development status of global carbon dioxide capture,utilization and storage(CCUS)cluster,and comparing domestic and international CCUS industrial models and successful experiences,this study explores the challenges and strategies for the scaled development of the CCUS industry of China.Globally,the CCUS industry has entered a phase of scaled and clustered development.North America has established a system of key technologies in large-scale CO_(2) capture,long-distance pipeline transmission,pipeline network optimization,and large-scale CO_(2) flooding for enhanced oil recovery(CO_(2)-EOR),with relatively mature cluster development and a gradual shift in industrial model from CO_(2)-EOR to geological storage.The CCUS industry of China has developed rapidly across all segments but remains in the early stage of cluster development,facing challenges such as absent business model,insufficient policy support,and technological gaps in core areas.China needs to improve the policy support system to boost enterprises participation across the entire industrial chain,strengthen top-level design and medium-to long-term planning to accelerate demonstration projects construction for whole-process CCUS clusters,advance for a full-chain technological system,including low-cost capture,pipeline optimization and EOR/storage integration technologies,and strengthen personnel training,strengthen discipline construction and university-enterprise research cooperation.展开更多
Thermally activated delayed fluorescence(TADF)materials driven by a through-space charge transfer(TSCT)mechanism have garnered wide interest.However,access of TSCT-TADF molecules with longwavelength emission remains a...Thermally activated delayed fluorescence(TADF)materials driven by a through-space charge transfer(TSCT)mechanism have garnered wide interest.However,access of TSCT-TADF molecules with longwavelength emission remains a formidable challenge.In this study,we introduce a novel V-type DA-D-A’emitter,Trz-mCzCbCz,by using a carborane scaffold.This design strategically incorporates carbazole(Cz)and 2,4,6-triphenyl-1,3,5-triazine(Trz)as donor and acceptor moieties,respectively.Theoretical calculations alongside experimental validations affirm the typical TSCT-TADF characteristics of this luminogen.Owing to the unique structural and electronic attributes of carboranes,Trz-mCzCbCz exhibits an orange-red emission,markedly diverging from the traditional blue-to-green emissions observed in classical Cz and Trz-based TADF molecules.Moreover,bright emission in aggregates was observed for Trz-mCzCbCz with absolute photoluminescence quantum yield(PLQY)of up to 88.8%.As such,we have successfully fabricated five organic light-emitting diodes(OLEDs)by utilizing Trz-mCzCbCz as the emitting layer.It is important to note that both the reverse intersystem crossing process and the TADF properties are profoundly influenced by host materials.The fabricated OLED devices reached a maximum external quantum efficiency(EQE)of 12.7%,with an emission peak at 592 nm.This represents the highest recorded efficiency for TSCT-TADF OLEDs employing carborane derivatives as emitting layers.展开更多
For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Veh...For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.展开更多
The legacy of United States cluster munition use in Laos and Cambodia during the Second Indochina War is residual bomblets that unexpectedly detonate years later, killing and injuring children, farmers, and other civi...The legacy of United States cluster munition use in Laos and Cambodia during the Second Indochina War is residual bomblets that unexpectedly detonate years later, killing and injuring children, farmers, and other civilians. Cluster munitions release dozens of smaller bomblets that rain deadly ammunition on troops, armored tanks, and vegetation, effectively striking broad sections of war zone landscapes in one launch. While many bomblets detonate immediately, others fail to detonate and can lie dormant on the ground for years. The primary objectives of this study were to document the long-term consequences and impacts of the US Air Force bombing of Laos and Cambodia during the Second Indochina War (1959 to 1973). The historical lessons learned by United States should be shared with Russia and Ukraine governments and military. These countries need to discontinue the use of cluster bombs to prevent additional people living along the Russia-Ukraine border from having to live and die with the consequences of unexploded ordnance, including cluster bombs, for the next century.展开更多
Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the...Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.展开更多
文摘Under hydrothermal and solvothermal conditions,two novel cobalt-based complexes,{[Co_(2)(CIA)(OH)(1,4-dtb)]·3.2H_(2)O}n(HU23)and{[Co_(2)(CIA)(OH)(1,4-dib)]·3.5H2O·DMF}n(HU24),were successfully constructed by coordinatively assembling the semi-rigid multidentate ligand 5-(1-carboxyethoxy)isophthalic acid(H₃CIA)with the Nheterocyclic ligands 1,4-di(4H-1,2,4-triazol-4-yl)benzene(1,4-dtb)and 1,4-di(1H-imidazol-1-yl)benzene(1,4-dib),respectively,around Co^(2+)ions.Single-crystal X-ray diffraction analysis revealed that in both complexes HU23 and HU24,the CIA^(3-)anions adopt aκ^(7)-coordination mode,bridging six Co^(2+)ions via their five carboxylate oxygen atoms and one ether oxygen atom.This linkage forms tetranuclear[Co4(μ3-OH)2]^(6+)units.These Co-oxo cluster units were interconnected by CIA^(3-)anions to assemble into 2D kgd-type structures featuring a 3,6-connected topology.The 2D layers were further connected by 1,4-dtb and 1,4-dib,resulting in 3D pillar-layered frameworks for HU23 and HU24.Notably,despite the similar configurations of 1,4-dtb and 1,4-dib,differences in their coordination spatial orientations lead to topological divergence in the 3D frameworks of HU23 and HU24.Topological analysis indicates that the frameworks of HU23 and HU24 can be simplified into a 3,10-connected net(point symbol:(4^(10).6^(3).8^(2))(4^(3))_(2))and a 3,8-connected tfz-d net(point symbol:(4^(3))_(2)((4^(6).6^(18).8^(4)))),respectively.This structural differentiation confirms the precise regulatory role of ligands on the topology of metal-organic frameworks.Moreover,the ultraviolet-visible absorption spectra confirmed that HU23 and HU24 have strong absorption capabilities for ultraviolet and visible light.According to the Kubelka-Munk method,their bandwidths were 2.15 and 2.08 eV,respectively,which are consistent with those of typical semiconductor materials.Variable-temperature magnetic susceptibility measurements(2-300 K)revealed significant antiferromagnetic coupling in both complexes,with their effective magnetic moments decreasing markedly as the temperature lowered.CCDC:2457554,HU23;2457553,HU24.
基金supported by the National Natural Science Foundation of China(No.22506042)the Natural Science Foundation of Henan Province(Nos.252300421710 and 252300421552)the High level Talent Research Launch Fund of Henan University of Technology(No.2024BS061).
文摘Effective control of gas-phase pollutants(volatile organic compounds(VOCs)and CO)is critical to human health and the ecological environment.Catalytic oxidation is one of the most promising technologies for achieving efficient volatile organic compounds and CO emission control.The subnano cluster catalyst can not only provide catalytic sites with multiple metal atoms,but also maintain full utilization efficiency.Almost all metal atoms in highly dispersed clusters can be used for adsorption and conversion of reactants.Recently,various types of sub-nano clusters,including subnano cluster oxides,have been developed and demonstrated excellent performance in low-temperature gas-phase pollutants combustion.In this mini review,we systematically summarize the structure,physicochemical properties,characterization,and applications of sub-nano cluster catalysts in catalytic oxidation of CO,methane,propane,propylene,toluene and its derivatives,formaldehyde and chlorinated volatile organic compounds.Finally,we have analyzed and discussed the problems and challenges faced by sub-nano cluster catalysts in both basic research and practical applications,providing a scientific basis for the design,synthesis,and application of efficient heterogeneous catalysts for CO and VOCs oxidation.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金Projects 2008BAB31B01 supported by the National Key Technology R&D Program in the 11th Five-Year Plan of China50834006 by the National Natural Science Foundation of China
文摘In our study we investigated a refractory copper-nickel sulfide ore separation by using a cyclonic-static micro-bubble flotation column (FCSMC). The process mineralogy of the main products was studied. Using a scanning electron microscope-energy dispersive system (SEM-EDS) and an X-ray spectrometer the mineral category and content of samples were analyzed. By using a mineral liberation analyzer (MLA) the mineral liberation characteristics were revealed. It is shown that in roughing feed the monomers liberation degree of nickel pyrite and chalcopyrite take up 84.11% and 88.82%, respectively. In tailings, the lost nickel pyrite and chalcopyrite are mainly monomers. Therefore, strengthening the micro-fine particle recovery capacity is the key to increase recovery.
基金the National Natural Science Foundation of China(Grant 51609115)the Foundation of National Key Laboratory of Transient Physics(Grant9140C300206150C30143).
文摘The effect of micro-bubbles on the turbulent boundary layer in the channel flow with Reynolds numbers (Re) ranging from 0.87 × 105 to 1.23 × 105 is experimentally studied by using particle image velocimetry (PIV) measurements.The microbubbles are produced by water electrolysis.The velocity profiles,Reynolds stress and instantaneous structures of the boundary layer,with and without micro-bubbles,are measured and analyzed.The presence of micro-bubbles changes the streamwise mean velocity of the fluid and increases the wall shear stress.The results show that micro-bubbles have two effects,buoyancy and extrusion,which dominate the flow behavior of the mixed fluid in the turbulent boundary layer.The buoyancy effect leads to upward motion that drives the fluid motion in the same direction and,therefore,enhances the turbulence intense of the boundary layer.While for the extrusion effect,the presence of accumulated micro-bubbles pushes the flow structures in the turbulent boundary layer away from the near-wall region.The interaction between these two effects causes the vorticity structures and turbulence activity to be in the region far away from the wall.The buoyancy effect is dominant when the Re is relatively small,while the extrusion effect plays a more important role when Re rises.
基金Supported by the Directorate for Research and Community Service,University of Indonesia(RUUI Research Laboratory 2010),Jakarta,Indonesia
文摘Ship hull form of the underwater area strongly influences the resistance of the ship. The major factor in ship resistance is skin friction resistance. Bulbous bows, polymer paint, water repellent paint （highly water-repellent wall）, air injection, and specific roughness have been used by researchers as an attempt to obtain the resistance reduction and operation efficiency of ships. Micro-bubble injection is a promising technique for lowering frictional resistance. The injected air bubbles are supposed to somehow modify the energy inside the turbulent boundary layer and thereby lower the skin friction. The purpose of this study was to identify the effect of injected micro bubbles on a navy fast patrol boat （FPB） 57 m type model with the following main dimensions： L=2 450 ram, B=400 mm, and T=190 mm. The influence of the location of micro bubble injection and bubble velocity was also investigated. The ship model was pulled by an electric motor whose speed could be varied and adjusted. The ship model resistance was precisely measured by a load cell transducer. Comparison of ship resistance with and without micro-bubble injection was shown on a graph as a function of the drag coefficient and Froude number. It was shown that micro bubble injection behind the mid-ship is the best location to achieve the most effective drag reduction, and the drag reduction caused by the micro-bubbles can reach 6%-9%.
基金Project(50304010) supported by the National Natural Science Foundation of China
文摘In order to optimize plastic viscosity of 18 mPa·s circulating micro-bubble drilling fluid formula,orthogonal and uniform experimental design methods were applied,and the plastic viscosities of 36 and 24 groups of agent were tested,respectively.It is found that these two experimental design methods show drawbacks,that is,the amount of agent is difficult to determine,and the results are not fully optimized.Therefore,multiple regression experimental method was used to design experimental formula.By randomly selecting arbitrary agent with the amount within the recommended range,17 groups of drilling fluid formula were designed,and the plastic viscosity of each experiment formula was measured.Set plastic viscosity as the objective function,through multiple regressions,then quadratic regression model is obtained,whose correlation coefficient meets the requirement.Set target values of plastic viscosity to be 18,20 and 22 mPa·s,respectively,with the trial method,5 drilling fluid formulas are obtained with accuracy of 0.000 3,0.000 1 and 0.000 3.Arbitrarily select target value of each of the two groups under the formula for experimental verification of drilling fluid,then the measurement errors between theoretical and tested plastic viscosity are less than 5%,confirming that regression model can be applied to optimizing the circulating of plastic-foam drilling fluid viscosity.In accordance with the precision of different formulations of drilling fluid for other constraints,the methods result in the optimization of the circulating micro-bubble drilling fluid parameters.
基金the State Key Basic Research Program of China (No. 2012CB214905)Key Program of National Natural Science Foundation of China (No. 500834006)the National Natural Science Foundation of China (No. 50974119) for financial support
文摘Laboratory experiments have been conducted to study the flow field in a cyclone static micro-bubble flotation column. The method of Particle Image Velocimetry (PIV) was used. The flow field velocity distribution in both cross section and longitudinal section within cyclonic zone was studied for different circulating volumes. The cross sectional vortex was also analyzed. The results show that in cross section as the circulating volume increases from 0.187 to 0.350 m 3 /h, the flow velocity ranges from 0 to 0.68 m/s. The flow field is mainly a non-vortex potential flow that forms a free vortex without outside energy input. In the cyclonic region the vortex deviates from the center of the flotation column because a single tangential opening introduces circulating fluid into the column. The tangential component of the velocity plays a defining role in the cross section. In the longitudinal section the velocity ranges from 0 to 0.08 m/s. The flow velocity increases as does the circulating volume. Advantageous mineral separation conditions arise from the combined effects of cyclonic flow in cross and longitudinal section.
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.
基金supported by the Foundation of President of Hebei University(XZJJ202303).
文摘Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.
基金supported in part by NIH grants R01NS39600,U01MH114829RF1MH128693(to GAA)。
文摘Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.
基金supported by the National Natural Science Foundation of China(Nos.51977027 and 51967008)the Scientific and Technological Project of Yunnan Precious Metals Lab-oratory(Nos.YPML-2023050250 and YPML-2022050206).
文摘The pursuit of Ag-based alloys with both high strength and toughness has posed a longstanding chal-lenge.In this study,we investigated the cluster strengthening and grain refinement toughening mecha-nisms in fully oxidized AgMgNi alloys,which were internally oxidized at 800℃ for 8 h under an oxy-gen atmosphere.We found that Mg-O clusters contributed to the hardening(138 HV)and strengthening(376.9 MPa)of the AgMg alloy through solid solution strengthening effects,albeit at the expense of duc-tility.To address this limitation,we introduced Ni nanoparticles into the AgMg alloy,resulting in signifi-cant grain refinement within its microstructure.Specifically,the grain size decreased from 67.2μm in the oxidized AgMg alloy to below 6.0μm in the oxidized AgMgNi alloy containing 0.3 wt%Ni.Consequently,the toughness increased significantly,rising from toughness value of 2177.9 MJ m^(-3) in the oxidized AgMg alloy to 6186.1 MJ m^(-3) in the oxidized AgMgNi alloy,representing a remarkable 2.8-fold enhancement.Furthermore,the internally oxidized AgMgNi alloy attained a strength of up to 387.6 MPa,comparable to that of the internally oxidized AgMg alloy,thereby demonstrating the successful realization of concurrent strengthening and toughening.These results collectively offer a novel approach for the design of high-performance alloys through the synergistic combination of cluster strengthening and grain refinement toughening.
基金supported by the National Natural Science Foundation of China(Nos.12174151 and 12304448)the Specific Research Fund of the Innovation Platform for Academicians of Hainan Province(No.YSPTZX202208)+3 种基金Hainan Province Clinical Medical Center(No.QWYH_(2)022341)the Key Laboratory of New Energy and Rare Earth Resource Utilization of the State People’s Committee of China(No.NERE202206)the Department of Science and Technology of Jilin Province(No.20220101059JC)the Key Laboratory of the Ministry of Education for First Aid and Trauma Research(No.KLET-202218).
文摘Given customizable crystal structure and intriguing optical properties,lanthanide titanium-oxygen clusters(LTOCs)with atomic-level accuracy have gained a lot of interest.In this study,we prepared[Ln_(9)Ti_(2)(μ4-O)(μ3-OH)_(14)(acac)_(17)(CH_(3)O)_(2)(CH_(3)OH)_(3)](Ln=Tb_(x)Eu_(9−x)(x=0,4,6,7,8,9),Hacac=acetylacetone),Tb^(3+)and Eu^(3+)co-doped LTOCs,to modify the optical properties for the luminescence thermometer.In detail,the serial LTOCs display dual characteristic emission peaks of ^(5)D_(4)→^(7)F_(5) for Tb^(3+)and^(5)D_(0)→^(7)F_(2) for Eu^(3+)at 548 and 616 nm,respectively,under 330 nm excitation.Effective energy transfer(ET)between Tb^(3+)ions and Eu^(3+)ions was revealed in terms of both emission spectra and luminescence lifetime.The ^(5)D_(0)→^(7)F_(2) emission intensity of Eu^(3+)ions at 616 nm is maximally enhanced(by a factor of 11.2)with a change in the relative molar ratio of Tb^(3+)to Eu^(3+),along with a change in the ET efficiency of Tb^(3+)→Eu^(3+).In addition,the luminescent color changes from red,orange,yellow,to green.This precise control of the ET process between rare-earth ions allows{Tb_(6)Eu_(3)Ti_(2)}to reach a maximum relative sensitivity of 1.241 K^(−1) at 355 K,which is an enhancement of up to 4.6-fold with respect to the previously reported homonuclear emission,holding great potential in the optical thermometers.
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 PetroChina Science and Technology Major Project(2021ZZ01-05)Hainan Merit-based Recruitment Project(ZDYF2024SHFZ147)National Natural Science Foundation of China(NNSC)Project(52474033)。
文摘By systematically reviewing the development status of global carbon dioxide capture,utilization and storage(CCUS)cluster,and comparing domestic and international CCUS industrial models and successful experiences,this study explores the challenges and strategies for the scaled development of the CCUS industry of China.Globally,the CCUS industry has entered a phase of scaled and clustered development.North America has established a system of key technologies in large-scale CO_(2) capture,long-distance pipeline transmission,pipeline network optimization,and large-scale CO_(2) flooding for enhanced oil recovery(CO_(2)-EOR),with relatively mature cluster development and a gradual shift in industrial model from CO_(2)-EOR to geological storage.The CCUS industry of China has developed rapidly across all segments but remains in the early stage of cluster development,facing challenges such as absent business model,insufficient policy support,and technological gaps in core areas.China needs to improve the policy support system to boost enterprises participation across the entire industrial chain,strengthen top-level design and medium-to long-term planning to accelerate demonstration projects construction for whole-process CCUS clusters,advance for a full-chain technological system,including low-cost capture,pipeline optimization and EOR/storage integration technologies,and strengthen personnel training,strengthen discipline construction and university-enterprise research cooperation.
基金supported by the Natural Science Foundation of Jiangsu Province(No.BZ2022007)the National Natural Science Foundation of China(No.92261202)+1 种基金the Ministry of Science and Technology of the People’s Republic of China(No.2021YFE0114800)the Ministry of Science and Higher Education of the Russian Federation(No.075-15-2021-1027).
文摘Thermally activated delayed fluorescence(TADF)materials driven by a through-space charge transfer(TSCT)mechanism have garnered wide interest.However,access of TSCT-TADF molecules with longwavelength emission remains a formidable challenge.In this study,we introduce a novel V-type DA-D-A’emitter,Trz-mCzCbCz,by using a carborane scaffold.This design strategically incorporates carbazole(Cz)and 2,4,6-triphenyl-1,3,5-triazine(Trz)as donor and acceptor moieties,respectively.Theoretical calculations alongside experimental validations affirm the typical TSCT-TADF characteristics of this luminogen.Owing to the unique structural and electronic attributes of carboranes,Trz-mCzCbCz exhibits an orange-red emission,markedly diverging from the traditional blue-to-green emissions observed in classical Cz and Trz-based TADF molecules.Moreover,bright emission in aggregates was observed for Trz-mCzCbCz with absolute photoluminescence quantum yield(PLQY)of up to 88.8%.As such,we have successfully fabricated five organic light-emitting diodes(OLEDs)by utilizing Trz-mCzCbCz as the emitting layer.It is important to note that both the reverse intersystem crossing process and the TADF properties are profoundly influenced by host materials.The fabricated OLED devices reached a maximum external quantum efficiency(EQE)of 12.7%,with an emission peak at 592 nm.This represents the highest recorded efficiency for TSCT-TADF OLEDs employing carborane derivatives as emitting layers.
基金supported by the National Natural Science Foundation of China(No.62271399)the National Key Research and Development Program of China(No.2022YFB1807102)。
文摘For multi-vehicle networks,Cooperative Positioning(CP)technique has become a promising way to enhance vehicle positioning accuracy.Especially,the CP performance could be further improved by introducing Sensor-Rich Vehicles(SRVs)into CP networks,which is called SRV-aided CP.However,the CP system may split into several sub-clusters that cannot be connected with each other in dense urban environments,in which the sub-clusters with few SRVs will suffer from degradation of CP performance.Since Unmanned Aerial Vehicles(UAVs)have been widely used to aid vehicular communications,we intend to utilize UAVs to assist sub-clusters in CP.In this paper,a UAV-aided CP network is constructed to fully utilize information from SRVs.First,the inter-node connection structure among the UAV and vehicles is designed to share available information from SRVs.After that,the clustering optimization strategy is proposed,in which the UAV cooperates with the high-precision sub-cluster to obtain available information from SRVs,and then broadcasts this positioning-related information to other low-precision sub-clusters.Finally,the Locally-Centralized Factor Graph Optimization(LC-FGO)algorithm is designed to fuse positioning information from cooperators.Simulation results indicate that the positioning accuracy of the CP system could be improved by fully utilizing positioning-related information from SRVs.
文摘The legacy of United States cluster munition use in Laos and Cambodia during the Second Indochina War is residual bomblets that unexpectedly detonate years later, killing and injuring children, farmers, and other civilians. Cluster munitions release dozens of smaller bomblets that rain deadly ammunition on troops, armored tanks, and vegetation, effectively striking broad sections of war zone landscapes in one launch. While many bomblets detonate immediately, others fail to detonate and can lie dormant on the ground for years. The primary objectives of this study were to document the long-term consequences and impacts of the US Air Force bombing of Laos and Cambodia during the Second Indochina War (1959 to 1973). The historical lessons learned by United States should be shared with Russia and Ukraine governments and military. These countries need to discontinue the use of cluster bombs to prevent additional people living along the Russia-Ukraine border from having to live and die with the consequences of unexploded ordnance, including cluster bombs, for the next century.
基金supported by the Spanish Ministry of Science and Innovation under Projects PID2022-137680OB-C32 and PID2022-139187OB-I00.
文摘Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.
