In order to get high-performance low voltage varistors,Cr2O3 doped ZnO ceramic thick films were fabricated by modified sol-gel process. The precursors were fabricated by dispersing doped-ZnO ceramic nano-powders in th...In order to get high-performance low voltage varistors,Cr2O3 doped ZnO ceramic thick films were fabricated by modified sol-gel process. The precursors were fabricated by dispersing doped-ZnO ceramic nano-powders in the sols,which were prepared by dissolving zinc acetate dihydrate into 2-methoxyethanol and stabilized by diethanolamine and glacial acetic acid and doped with a concentrated solution of bismuth nitrate,phenylstibonic acid,cobalt nitrate,manganese acetate and chromium nitrate. The results show that ZnCr2O4 phase can form in ZnO based ceramic films doped 1.0%(mole fraction) Cr2O3. Three secondary phases,such as Bi2O3,Zn7Sb2O12,and ZnCr2O4 phases,are detected in the thick films. The Raman spectra show that the intensity and the position of Raman bands of Zn7Sb2O12 and ZnCr2O4 phases change obviously with increasing Cr2O3 doping. The nonlinearity coefficient α of ZnO thick films is 7.0,the nonlinear voltage is 6 V,and the leakage current density is 0.7 μA/mm2.展开更多
An analytical solution is presented for the electromagnetic scattering from an infinite-length metallic carbon nanotube and a carbon nanotube bundle. The scattering field and scattering cross section are predicted usi...An analytical solution is presented for the electromagnetic scattering from an infinite-length metallic carbon nanotube and a carbon nanotube bundle. The scattering field and scattering cross section are predicted using a modal technique based on a Bessel and Hankel function for the electric line source and a quantum conductance function for the carbon nanotube. For the particular case of an isolated armchair （10, 10） carbon nanotube, the scattered field predicted from this technique is in excellent agreement with the measured result. Furthermore, the analysis indicates that the scattering pattern of an isolated carbon nanotube differs from that of the carbon nanotube bundle of identical index （m, n） metallic carbon nanotubes.展开更多
We propose an improved design and numerical study of an optimized tunable plasmonics artificial material resonator in the terahertz regime. We demonstrate that tunability can be realized with a transmission intensity ...We propose an improved design and numerical study of an optimized tunable plasmonics artificial material resonator in the terahertz regime. We demonstrate that tunability can be realized with a transmission intensity as much as - 61% in the lower frequency resonance, which is implemented through the effect of photoconductive switching under photoexcitation.In the higher frequency resonance, we show that spoof surface plasmons along the interface of metal/dielectric provide new types of electromagnetic resonances. Our approach opens up possibilities for the interface of metamaterial and plasmonics to be applied to optically tunable THz switching.展开更多
In recent years, renewable energy resources are utilized to meet the growing energy demand. The integration of renewable energy resources with the grid incorporates power electronic converters for conversion of energy...In recent years, renewable energy resources are utilized to meet the growing energy demand. The integration of renewable energy resources with the grid incorporates power electronic converters for conversion of energy. These power electronic converters introduce power quality issues such as a harmonics, voltage regulation etc. Hence, to improve the power quality issues, this work proposes a new control strategy for a grid interconnected solar system. In this proposed work, a maximum power point tracking (MPPT) scheme has been used to obtain maximum power from the solar system and DC/DC converter is implemented to maintain a constant DC voltage. An active filtering method is utilized to improve the power quality of the grid connected solar system. The proposed system is validated through dynamic simulation using MATLAB/Simulink Power system toolbox and results are delivered to validate the effectiveness of the work.展开更多
The poor electronic conductivity of conversion-type materials(CMs)and the dissolution/diffusion loss of transition metal(TM)ions in electrodes seriously hinder the practical applications of potassium ion batteries.Sim...The poor electronic conductivity of conversion-type materials(CMs)and the dissolution/diffusion loss of transition metal(TM)ions in electrodes seriously hinder the practical applications of potassium ion batteries.Simply optimizing the electrode materials or designing the electrode components is no longer effective in improving the performance of CMs.Binders,as one of the elec-trode components,play a vital role in improving the electrochemical per-formance of batteries.Here we rationally designed FeF_(2) electrodes for the first time by optimizing electrode materials with the introduction of carbon na-notubes(CNTs)and combined with a sodium alginate(SA)binder based on strong interactions.We show that the FeF_(2)@CNTs-SA cathode does not suffer from TM ion dissolution and delivers a high capacity of 184.7 mAh g^(-1) at 10 mA g^(-1).Moreover,the capacity of FeF_(2)@CNTs-SA is as high as 99.2 mAh g^(-1) after 100 cycles at 100 mA g^(-1),which is a twofold increase compared to FeF_(2)@CNTs-PVDF.After calculating the average capacity decay rate per cycle of them,we find that FeF_(2)@CNTs-SA is about one-third lower than FeF_(2)@CNTs-PVDF.Therefore,the SA binder can be broadly used for electrodes comprising several CMs,providing meaningful insights into mechanisms that lead to their improved electrochemical performances.展开更多
Introduction:Seasonal influenza poses a significant public health burden,causing substantial morbidity and mortality worldwide each year.In this context,timely and accurate vaccine strain selection is critical to miti...Introduction:Seasonal influenza poses a significant public health burden,causing substantial morbidity and mortality worldwide each year.In this context,timely and accurate vaccine strain selection is critical to mitigating the impact of influenza outbreaks.This article aims to develop an adaptive,universal,and convenient method for predicting antigenic variation in influenza A(H1N1),thereby providing a scientific basis to enhance the biannual influenza vaccine selection process.Methods:The study integrates adaptive Fourier decomposition(AFD)theory with multiple techniques—including matching pursuit,the maximum selection principle,and bootstrapping—to investigate the complex nonlinear interactions between amino acid substitutions in hemagglutinin(HA)proteins(the primary antigenic protein of influenza virus)and their impact on antigenic changes.Results:Through comparative analysis with classical methods such as Lasso,Ridge,and random forest,we demonstrate that the AFD-type method offers superior accuracy and computational efficiency in identifying antigenic change-associated amino acid substitutions,thus eliminating the need for timeconsuming and expensive experimental procedures.AAW Conclusion:In summary,AFD-based methods represent effective mathematical models for predicting antigenic variations based on HA sequences and serological data,functioning as ensemble algorithms with guaranteed convergence.Following the sequence of indicators specified in I,we perform a series of operations on A_(1),including feature extension,extraction,and rearrangement,to generate a new input dataset for the prediction step.With this newly prepared input,we can compute the predicted results as.展开更多
In the modal analysis and control of nonlinear dynamical systems,participation factors(PFs)of state variables with respect to a critical or selected mode serve as a pivotal tool for simplifying stability studies by fo...In the modal analysis and control of nonlinear dynamical systems,participation factors(PFs)of state variables with respect to a critical or selected mode serve as a pivotal tool for simplifying stability studies by focusing on a subset of highly influential state variables.For linear systems,PFs are uniquely determined by the mode’s composition and shape,which are defined by the system’s left and right eigenvectors,respectively.However,the uniqueness of other types of PFs has not been thoroughly addressed in literatures.This paper establishes sufficient conditions for the uniqueness of nonlinear PFs and five other PF variants,taking into account uncertain scaling factors in a mode’s shape and composition.These scaling factors arise from variations in the choice of physical units,which depend on the value ranges of real-world state variables.Understanding these sufficient conditions is essential for the correct application of PFs in practical stability analysis and control design.展开更多
This paper investigates the electromagnetic radiation characteristics of a metallic, large aspect ratio single walled carbon nanotube antenna in the terahertz frequency region below 12.5 THz. The key features of terah...This paper investigates the electromagnetic radiation characteristics of a metallic, large aspect ratio single walled carbon nanotube antenna in the terahertz frequency region below 12.5 THz. The key features of terahertz pulse have been revealed on the carbon nanotube antenna in comparison with conventional photoconductive switching. The terahertz waveforms, radiation power and their field distributions have been evaluated and are analysed. The Fourier transformed spectra over the whole frequency range demonstrate that the carbon nanotube antenna can be used as radiation source for broadband terahertz applications.展开更多
In India, water wastage in agricultural fields becomes a challengingissue and it is needed to minimize the loss of water in the irrigation process.Since the conventional irrigation system needs massive quantity of wat...In India, water wastage in agricultural fields becomes a challengingissue and it is needed to minimize the loss of water in the irrigation process.Since the conventional irrigation system needs massive quantity of waterutilization, a smart irrigation system can be designed with the help of recenttechnologies such as machine learning (ML) and the Internet of Things (IoT).With this motivation, this paper designs a novel IoT enabled deep learningenabled smart irrigation system (IoTDL-SIS) technique. The goal of theIoTDL-SIS technique focuses on the design of smart irrigation techniquesfor effectual water utilization with less human interventions. The proposedIoTDL-SIS technique involves distinct sensors namely soil moisture, temperature, air temperature, and humidity for data acquisition purposes. The sensordata are transmitted to the Arduino module which then transmits the sensordata to the cloud server for further process. The cloud server performs the dataanalysis process using three distinct processes namely regression, clustering,and binary classification. Firstly, deep support vector machine (DSVM) basedregression is employed was utilized for predicting the soil and environmentalparameters in advances such as atmospheric pressure, precipitation, solarradiation, and wind speed. Secondly, these estimated outcomes are fed intothe clustering technique to minimize the predicted error. Thirdly, ArtificialImmune Optimization Algorithm (AIOA) with deep belief network (DBN)model receives the clustering data with the estimated weather data as inputand performs classification process. A detailed experimental results analysisdemonstrated the promising performance of the presented technique over theother recent state of art techniques with the higher accuracy of 0.971.展开更多
Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial intelligence.Organoids,three-dimensional miniature organ-like structures cultivated fro...Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial intelligence.Organoids,three-dimensional miniature organ-like structures cultivated from stem cells,offer an unparalleled opportunity to simulate complex human organ systems in vitro.Through the convergence of organoid technology and AI,researchers gain the means to accelerate discoveries and insights across various disciplines.Artificial intelligence algorithms enable the comprehensive analysis of intricate organoid behaviors,intricate cellular interactions,and dynamic responses to stimuli.This synergy empowers the development of predictive models,precise disease simulations,and personalized medicine approaches,revolutionizing our understanding of human development,disease mechanisms,and therapeutic interventions.Organoid Intelligence holds the promise of reshaping how we perceive in vitro modeling,propelling us toward a future where these advanced systems play a pivotal role in biomedical research and drug development.展开更多
Solving optimization problems plays a vital role in ensuring the secure and economic operation of distribution systems.To enhance computational efficiency,this paper proposes a general simplification and acceleration ...Solving optimization problems plays a vital role in ensuring the secure and economic operation of distribution systems.To enhance computational efficiency,this paper proposes a general simplification and acceleration method for distribution system optimization problems.Firstly,the capacity boundary and voltage boundary model of distribution systems are established.The relative position between the two boundaries reflects the strength of capacity and voltage constraints,leading to the definition of two critical feeder lengths(CFLs)to quantify these strengths.Secondly,simplification criteria and an acceleration method are proposed.Given a distribution system,if the distance from the end load/DG node to the slack bus is less than the corresponding CFL,we can conclude that the capacity constraints are stricter than the voltage constraints.Then,the distribution system can be simplified by adopting DC power flow model or disregarding the voltage constraints.After that,the reference value tables of CFL are presented.Finally,the effectiveness of the proposed method is verified by exemplifying the method in network reconfiguration and reactive power optimization problems.By implementing the proposed acceleration method,a significant reduction in computation time is achieved while ensuring accuracy.This method applies to most urban distribution systems in optimization problems involving power flow equations or voltage constraints.展开更多
In the present electricity market, where renewable energy power plants have been included in the power systems, there is a lot of unpredictability in the demand and generation. There are many conventional and evolutio...In the present electricity market, where renewable energy power plants have been included in the power systems, there is a lot of unpredictability in the demand and generation. There are many conventional and evolutionary programming techniques used for solving the unit commitment （UC） problem. Dynamic programming （DP） is a conventional algorithm used to solve the deterministic problem. In this paper DP is used to solve the stochastic model of UC problem. The stochastic modeling for load and generation side has been formulated using an approximate state decision approach. The programs were developed in a MATLAB environment and were exten- sively tested for a four-unit eight-hour system. The results obtained from these techniques were validated with the available literature and outcome was good. The commitment is in such a way that the total cost is minimal. The novelty of this paper lies in the fact that DP is used for solving the stochastic UC problem.展开更多
The estimation of evapotranspiration(ETo)is one of the main tools for the control of crop growth and to make a rational use of water resources.To estimate this parameter accurately,it is necessary to have a daily meas...The estimation of evapotranspiration(ETo)is one of the main tools for the control of crop growth and to make a rational use of water resources.To estimate this parameter accurately,it is necessary to have a daily measurement of four meteorological variables,these are:temperature,solar radiation,relative humidity and wind speed.It is not always possible to count on all the variables,that is why there are empirical methods that use a limited number of variables that make an approximate estimate of the ETo value.Each of these models are applicable to different regions with completely different climates.In this paper,a study has been carried out to define the model of ETo estimation that best adapts to the semi-arid region in South India.Two different datasets for the same period from different meteorological stations were used.In addition to the empirical methods for estimating ETo,computer models ANFIS(Adaptive Neuro-Fuzzy Inference System)were implemented.These models consist in the future estimation of a certain parameter by using current variables and a history of variables and past results.The results of this work show that ANFIS 11 model makes the best estimate with RMSD=0.002 and r=0.999.The RITCHIE method is the most suitable empirical model for this region,which reaches RMSD=0.507 and r=0.851.In addition,ranking of equations is elaborated for both datasets for daily estimates of ETo.Finally,comparison is made with the results for each case and thus confirm or reject the convenience of one model over the rest.To achieve this,a series of statistical indicators were used:Index of agreement(d),MAE(Mean absolute error),SEE(Standard error of estimate)and RMSD(Root mean square difference).Moreover,a sensitivity analysis was performed in order to compare and show the stability of the best models when an error is introduced within the input parameters.In this case,the empirical models demonstrate a better performance than the ANFIS models.This work demonstrates that the Ritchie method is a good estimator of the ETo value for a semi-arid region in southern India.In addition,the results of the ANFIS models are promising and could be used as estimation methods.展开更多
In this paper,we present a soil methane emissions suppression approach using swarms of unmanned aerial vehicles(UAVs),by spreading biochar mulch on top of the detected methane emissions area/source.Soil microorganisms...In this paper,we present a soil methane emissions suppression approach using swarms of unmanned aerial vehicles(UAVs),by spreading biochar mulch on top of the detected methane emissions area/source.Soil microorganisms can produce methane and release it into the atmosphere causing climate change such as global warming.However,people lack methods to manage soil methane emissions,especially quantification of methane emissions from the soil.Current measurement and suppression of methane methods are often limited due to the maintenance,installation,and calibration requirements of these sensing systems.To overcome these drawbacks,we present a new method called FADE-MAS2D(Fractional Advection Diffusion Mobile Actuator and Sensor)in which swarming UAVs are applied as optimal coverage control actuators to various methane release scenarios(from single to multi-source disturbances)utilizing an anomalous diffusion model with different time,and space fractional orders subject to wind fields.This strategy is based on the premise that methane diffusion can be modeled as an anomalous diffusion equation,and swarming UAVs can be applied to tackle the optimal coverage control issue.To simulate methane diffusion under the wind,we utilize the fractional calculus to solve the anomalous diffusion equation and define wind force with the drag equation.In addition,we integrated emissions control,UAV control efforts,and UAV location error in our cost function.Finally,we evaluated our approach using simulation experiments with methane diffusion and multiple methane emission sources in the time and space domain,respectively.The results show that when α=0.8 and β=1.8,the shape and emissions of methane perform well.Furthermore,our approach resulted in great control performance with multiple methane emission sources and different wind velocities and directions.展开更多
The properties of terahertz （THz） radiation pulses emitted by a metallic, large aspect ratio carbon nanotube antenna have been studied both in the THz waveforms and field distribution. The peak THz field up to 2.66 ...The properties of terahertz （THz） radiation pulses emitted by a metallic, large aspect ratio carbon nanotube antenna have been studied both in the THz waveforms and field distribution. The peak THz field up to 2.66 and 1.26 kV/cm are observed at the probe points. The proposed antenna is designed to operate for dual frequency applications from 2.36 to 2.58 THz and from 7.27 to 7.5 THz for less than -10 dB return loss.展开更多
Background:Identifying patient-specific flow of signal transduction perturbed by multiple single-nucleotide alterations is critical for improving patient outcomes in cancer cases.However,accurate estimation of mutatio...Background:Identifying patient-specific flow of signal transduction perturbed by multiple single-nucleotide alterations is critical for improving patient outcomes in cancer cases.However,accurate estimation of mutational effects at the pathway level for such patients remains an open problem.While probabilistic pathway topology methods are gaining interest among the scientific community,the overwhelming majority do not account for network perturbation effects from multiple single-nucleotide alterations.Methods:Here we present an improvement of the mutational forks formalism to infer the patient-specific flow of signal transduction based on multiple single-nucleotide alterations,including non-synonymous and synonymous mutations.The lung adenocarcinoma and skin cutaneous melanoma datasets from TCGA Pan-Cancer Atlas have been employed to show the utility of the proposed method.Results:We have comprehensively characterized six mutational forks.The number of mutated nodes ranged from one to four depending on the topological characteristics of a fork.Transitional confidences(TCs)have been computed for every possible combination of single-nucleotide alterations in the fork.The performed analysis demonstrated the capacity of the mutational forks formalism to follow a biologically explainable logic in the identification of high-likelihood signaling routes in lung adenocarcinoma and skin cutaneous melanoma patients.The findings have been largely supported by the evidence from the biomedical literature.Conclusion:We conclude that the formalism has a great chance to enable an assessment of patient-specific flow by leveraging information from multiple single-nucleotide alterations to adjust the transitional likelihoods that are solely based on the canonical view of a disease.展开更多
Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes.Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth pro...Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes.Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product(SBP).Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems,thus restricting data throughput to maintain high SBP at limited frame rates.To address this,we introduce EventLFM,a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy(LFM),a state-of-theart single-shot 3D wide-field imaging technique.The event camera operates on a novel asynchronous readout architecture,thereby bypassing the frame rate limitations inherent to conventional CMOS systems.We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM.Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates.Furthermore,we highlight EventLFM’s capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C.elegans.We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.展开更多
Dear Colleagues,Researchers,and Friends,It is with great excitement and pride that we present to you INTEGRATED CIRCUITS AND SYSTEMS(ICAS).This marks the beginning of an ambitious journey to create a world-class inter...Dear Colleagues,Researchers,and Friends,It is with great excitement and pride that we present to you INTEGRATED CIRCUITS AND SYSTEMS(ICAS).This marks the beginning of an ambitious journey to create a world-class interdisciplinary academic journal in the field of integrated circuits and systems.Our mission at ICAS is to track and showcase the latest cutting-edge research results and advancements in integrated circuits and systems.The scope of our journal focuses on the theories,concepts,and techniques of science and engineering as applied to the interdisciplinary fields in integrated circuits and systems,including materials and devices,circuits,interconnects,design automation,manufacturing and integration,testing and packaging,as well as various applications of integrated circuits and systems.The journal invites contributions disclosing new and significant research as well as results relevant to industries and standards.展开更多
Miniature fluorescence microscopes are a standard tool in systems biology.However,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight ...Miniature fluorescence microscopes are a standard tool in systems biology.However,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth range.Here,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture stop.Placing the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth range.The phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse problem.We provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature objectives.We demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per second.The performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain tissue.Compared with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth range.Our microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.展开更多
It is well-known that the atomic-scale and nano-scale configuration of dopants can play a crucial role in determining the electronic properties of materials.However,predicting such effects is challenging due to the la...It is well-known that the atomic-scale and nano-scale configuration of dopants can play a crucial role in determining the electronic properties of materials.However,predicting such effects is challenging due to the large range of atomic configurations that are possible.Here,we present a case study of how deep learning algorithms can enable bandgap prediction in hybridized boron–nitrogen graphene with arbitrary supercell configurations.A material descriptor that enables correlation of structure and bandgap was developed for convolutional neural networks.Bandgaps calculated by ab initio calculations,and corresponding structures,were used as training datasets.The trained networks were then used to predict bandgaps of systems with various configurations.For 4×4 and 5×5 supercells they accurately predict bandgaps,with a R^(2) of >90% and root-mean-square error of~0.1 eV.The transfer learning was performed by leveraging data generated from small supercells to improve the prediction accuracy for 6×6 supercells.This work will pave a route to future investigation of configurationally hybridized graphene and other 2D materials.Moreover,given the ubiquitous existence of configurations in materials,this work may stimulate interest in applying deep learning algorithms for the configurational design of materials across different length scales.展开更多
基金Project(2004CB619300) supported by the Basic Research Development Program of ChinaProject(NCET-04-0703) supported by the Program for New Century Excellent Talents in University
文摘In order to get high-performance low voltage varistors,Cr2O3 doped ZnO ceramic thick films were fabricated by modified sol-gel process. The precursors were fabricated by dispersing doped-ZnO ceramic nano-powders in the sols,which were prepared by dissolving zinc acetate dihydrate into 2-methoxyethanol and stabilized by diethanolamine and glacial acetic acid and doped with a concentrated solution of bismuth nitrate,phenylstibonic acid,cobalt nitrate,manganese acetate and chromium nitrate. The results show that ZnCr2O4 phase can form in ZnO based ceramic films doped 1.0%(mole fraction) Cr2O3. Three secondary phases,such as Bi2O3,Zn7Sb2O12,and ZnCr2O4 phases,are detected in the thick films. The Raman spectra show that the intensity and the position of Raman bands of Zn7Sb2O12 and ZnCr2O4 phases change obviously with increasing Cr2O3 doping. The nonlinearity coefficient α of ZnO thick films is 7.0,the nonlinear voltage is 6 V,and the leakage current density is 0.7 μA/mm2.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.60871073,60971064,and 51005001)the Open Program of the State Key Laboratory of Millimeter Wave of China(Grant No.K201006)+1 种基金the Special Funds for the Technological and Innovative Talent of Harbin City,China(Grant No.2010RFXXG010)the Youth Foundation of Harbin University of Science and Technology,China(Grant Nos.2009YF025 and 2009YF024)
文摘An analytical solution is presented for the electromagnetic scattering from an infinite-length metallic carbon nanotube and a carbon nanotube bundle. The scattering field and scattering cross section are predicted using a modal technique based on a Bessel and Hankel function for the electric line source and a quantum conductance function for the carbon nanotube. For the particular case of an isolated armchair （10, 10） carbon nanotube, the scattered field predicted from this technique is in excellent agreement with the measured result. Furthermore, the analysis indicates that the scattering pattern of an isolated carbon nanotube differs from that of the carbon nanotube bundle of identical index （m, n） metallic carbon nanotubes.
基金Project supported by the National Natural Science Foundation of China(Grant No.61201075)the Natural Science Foundation of Heilongjiang Province+5 种基金China(Grant No.F2015039)the Young Scholar Project of Heilongjiang Provincial Education BureauChina(Grant No.1254G021)the China Postdoctoral Science Foundation(Grant No.2012M511507)the Science Funds for the Young Innovative Talents of Harbin University of Science and TechnologyChina(Grant No.201302)
文摘We propose an improved design and numerical study of an optimized tunable plasmonics artificial material resonator in the terahertz regime. We demonstrate that tunability can be realized with a transmission intensity as much as - 61% in the lower frequency resonance, which is implemented through the effect of photoconductive switching under photoexcitation.In the higher frequency resonance, we show that spoof surface plasmons along the interface of metal/dielectric provide new types of electromagnetic resonances. Our approach opens up possibilities for the interface of metamaterial and plasmonics to be applied to optically tunable THz switching.
文摘In recent years, renewable energy resources are utilized to meet the growing energy demand. The integration of renewable energy resources with the grid incorporates power electronic converters for conversion of energy. These power electronic converters introduce power quality issues such as a harmonics, voltage regulation etc. Hence, to improve the power quality issues, this work proposes a new control strategy for a grid interconnected solar system. In this proposed work, a maximum power point tracking (MPPT) scheme has been used to obtain maximum power from the solar system and DC/DC converter is implemented to maintain a constant DC voltage. An active filtering method is utilized to improve the power quality of the grid connected solar system. The proposed system is validated through dynamic simulation using MATLAB/Simulink Power system toolbox and results are delivered to validate the effectiveness of the work.
基金supported by the National Nature Science Foundation of China(Nos.U20A20247 and 52101252)the National Key Research and Development Program of Ministry of Science and Technology(2022YFA1402504)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030196)support through the R.A.Bowen Endowed Professorship funds.
文摘The poor electronic conductivity of conversion-type materials(CMs)and the dissolution/diffusion loss of transition metal(TM)ions in electrodes seriously hinder the practical applications of potassium ion batteries.Simply optimizing the electrode materials or designing the electrode components is no longer effective in improving the performance of CMs.Binders,as one of the elec-trode components,play a vital role in improving the electrochemical per-formance of batteries.Here we rationally designed FeF_(2) electrodes for the first time by optimizing electrode materials with the introduction of carbon na-notubes(CNTs)and combined with a sodium alginate(SA)binder based on strong interactions.We show that the FeF_(2)@CNTs-SA cathode does not suffer from TM ion dissolution and delivers a high capacity of 184.7 mAh g^(-1) at 10 mA g^(-1).Moreover,the capacity of FeF_(2)@CNTs-SA is as high as 99.2 mAh g^(-1) after 100 cycles at 100 mA g^(-1),which is a twofold increase compared to FeF_(2)@CNTs-PVDF.After calculating the average capacity decay rate per cycle of them,we find that FeF_(2)@CNTs-SA is about one-third lower than FeF_(2)@CNTs-PVDF.Therefore,the SA binder can be broadly used for electrodes comprising several CMs,providing meaningful insights into mechanisms that lead to their improved electrochemical performances.
基金Supported by Major Project of Guangzhou National Laboratory,(Grant No.GZNL2024A01004)the National Natural Science Foundation of China(Grant No.82361168672)+4 种基金the Science and Technology Development Fund of Macao SAR(Grant No.FDCT 0111/2023/AFJ,0155/2024/RIA2,005/2022/ALC,0128/2022/A,0020/2023/RIB1)National Key Research and Development Program of China(Grant No.2024YFE0214800)Self-supporting Program of Guangzhou Laboratory(Grant No.SRPG22-007)National Key Research and Development Program of China(Grant No.SQ2024YFE0202244)Engineering Technology Research(Development)Center of Ordinary Colleges and Universities in Guangdong Province(Grant No.2024GCZX010).
文摘Introduction:Seasonal influenza poses a significant public health burden,causing substantial morbidity and mortality worldwide each year.In this context,timely and accurate vaccine strain selection is critical to mitigating the impact of influenza outbreaks.This article aims to develop an adaptive,universal,and convenient method for predicting antigenic variation in influenza A(H1N1),thereby providing a scientific basis to enhance the biannual influenza vaccine selection process.Methods:The study integrates adaptive Fourier decomposition(AFD)theory with multiple techniques—including matching pursuit,the maximum selection principle,and bootstrapping—to investigate the complex nonlinear interactions between amino acid substitutions in hemagglutinin(HA)proteins(the primary antigenic protein of influenza virus)and their impact on antigenic changes.Results:Through comparative analysis with classical methods such as Lasso,Ridge,and random forest,we demonstrate that the AFD-type method offers superior accuracy and computational efficiency in identifying antigenic change-associated amino acid substitutions,thus eliminating the need for timeconsuming and expensive experimental procedures.AAW Conclusion:In summary,AFD-based methods represent effective mathematical models for predicting antigenic variations based on HA sequences and serological data,functioning as ensemble algorithms with guaranteed convergence.Following the sequence of indicators specified in I,we perform a series of operations on A_(1),including feature extension,extraction,and rearrangement,to generate a new input dataset for the prediction step.With this newly prepared input,we can compute the predicted results as.
文摘In the modal analysis and control of nonlinear dynamical systems,participation factors(PFs)of state variables with respect to a critical or selected mode serve as a pivotal tool for simplifying stability studies by focusing on a subset of highly influential state variables.For linear systems,PFs are uniquely determined by the mode’s composition and shape,which are defined by the system’s left and right eigenvectors,respectively.However,the uniqueness of other types of PFs has not been thoroughly addressed in literatures.This paper establishes sufficient conditions for the uniqueness of nonlinear PFs and five other PF variants,taking into account uncertain scaling factors in a mode’s shape and composition.These scaling factors arise from variations in the choice of physical units,which depend on the value ranges of real-world state variables.Understanding these sufficient conditions is essential for the correct application of PFs in practical stability analysis and control design.
基金supported by the National Natural Science Foundation of China(Grant No 60571026)the Science and Technology Research Foundation of Heilongjiang Education Bureau of China(Grant No 11531055)
文摘This paper investigates the electromagnetic radiation characteristics of a metallic, large aspect ratio single walled carbon nanotube antenna in the terahertz frequency region below 12.5 THz. The key features of terahertz pulse have been revealed on the carbon nanotube antenna in comparison with conventional photoconductive switching. The terahertz waveforms, radiation power and their field distributions have been evaluated and are analysed. The Fourier transformed spectra over the whole frequency range demonstrate that the carbon nanotube antenna can be used as radiation source for broadband terahertz applications.
文摘In India, water wastage in agricultural fields becomes a challengingissue and it is needed to minimize the loss of water in the irrigation process.Since the conventional irrigation system needs massive quantity of waterutilization, a smart irrigation system can be designed with the help of recenttechnologies such as machine learning (ML) and the Internet of Things (IoT).With this motivation, this paper designs a novel IoT enabled deep learningenabled smart irrigation system (IoTDL-SIS) technique. The goal of theIoTDL-SIS technique focuses on the design of smart irrigation techniquesfor effectual water utilization with less human interventions. The proposedIoTDL-SIS technique involves distinct sensors namely soil moisture, temperature, air temperature, and humidity for data acquisition purposes. The sensordata are transmitted to the Arduino module which then transmits the sensordata to the cloud server for further process. The cloud server performs the dataanalysis process using three distinct processes namely regression, clustering,and binary classification. Firstly, deep support vector machine (DSVM) basedregression is employed was utilized for predicting the soil and environmentalparameters in advances such as atmospheric pressure, precipitation, solarradiation, and wind speed. Secondly, these estimated outcomes are fed intothe clustering technique to minimize the predicted error. Thirdly, ArtificialImmune Optimization Algorithm (AIOA) with deep belief network (DBN)model receives the clustering data with the estimated weather data as inputand performs classification process. A detailed experimental results analysisdemonstrated the promising performance of the presented technique over theother recent state of art techniques with the higher accuracy of 0.971.
基金NIH[R01HD101130,R15HD108720]NSF[CMMI-2130192,CBET-1943798]Research Seed Grants(2021 and 2023)from UNT Research and Innovation Office(H.X.Y.),Syracuse University intramural CUSE grant[II-3245-2022](Z.M.).
文摘Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial intelligence.Organoids,three-dimensional miniature organ-like structures cultivated from stem cells,offer an unparalleled opportunity to simulate complex human organ systems in vitro.Through the convergence of organoid technology and AI,researchers gain the means to accelerate discoveries and insights across various disciplines.Artificial intelligence algorithms enable the comprehensive analysis of intricate organoid behaviors,intricate cellular interactions,and dynamic responses to stimuli.This synergy empowers the development of predictive models,precise disease simulations,and personalized medicine approaches,revolutionizing our understanding of human development,disease mechanisms,and therapeutic interventions.Organoid Intelligence holds the promise of reshaping how we perceive in vitro modeling,propelling us toward a future where these advanced systems play a pivotal role in biomedical research and drug development.
基金supported by the National Natural Science Foundation of China(No.52177105).
文摘Solving optimization problems plays a vital role in ensuring the secure and economic operation of distribution systems.To enhance computational efficiency,this paper proposes a general simplification and acceleration method for distribution system optimization problems.Firstly,the capacity boundary and voltage boundary model of distribution systems are established.The relative position between the two boundaries reflects the strength of capacity and voltage constraints,leading to the definition of two critical feeder lengths(CFLs)to quantify these strengths.Secondly,simplification criteria and an acceleration method are proposed.Given a distribution system,if the distance from the end load/DG node to the slack bus is less than the corresponding CFL,we can conclude that the capacity constraints are stricter than the voltage constraints.Then,the distribution system can be simplified by adopting DC power flow model or disregarding the voltage constraints.After that,the reference value tables of CFL are presented.Finally,the effectiveness of the proposed method is verified by exemplifying the method in network reconfiguration and reactive power optimization problems.By implementing the proposed acceleration method,a significant reduction in computation time is achieved while ensuring accuracy.This method applies to most urban distribution systems in optimization problems involving power flow equations or voltage constraints.
文摘In the present electricity market, where renewable energy power plants have been included in the power systems, there is a lot of unpredictability in the demand and generation. There are many conventional and evolutionary programming techniques used for solving the unit commitment （UC） problem. Dynamic programming （DP） is a conventional algorithm used to solve the deterministic problem. In this paper DP is used to solve the stochastic model of UC problem. The stochastic modeling for load and generation side has been formulated using an approximate state decision approach. The programs were developed in a MATLAB environment and were exten- sively tested for a four-unit eight-hour system. The results obtained from these techniques were validated with the available literature and outcome was good. The commitment is in such a way that the total cost is minimal. The novelty of this paper lies in the fact that DP is used for solving the stochastic UC problem.
文摘The estimation of evapotranspiration(ETo)is one of the main tools for the control of crop growth and to make a rational use of water resources.To estimate this parameter accurately,it is necessary to have a daily measurement of four meteorological variables,these are:temperature,solar radiation,relative humidity and wind speed.It is not always possible to count on all the variables,that is why there are empirical methods that use a limited number of variables that make an approximate estimate of the ETo value.Each of these models are applicable to different regions with completely different climates.In this paper,a study has been carried out to define the model of ETo estimation that best adapts to the semi-arid region in South India.Two different datasets for the same period from different meteorological stations were used.In addition to the empirical methods for estimating ETo,computer models ANFIS(Adaptive Neuro-Fuzzy Inference System)were implemented.These models consist in the future estimation of a certain parameter by using current variables and a history of variables and past results.The results of this work show that ANFIS 11 model makes the best estimate with RMSD=0.002 and r=0.999.The RITCHIE method is the most suitable empirical model for this region,which reaches RMSD=0.507 and r=0.851.In addition,ranking of equations is elaborated for both datasets for daily estimates of ETo.Finally,comparison is made with the results for each case and thus confirm or reject the convenience of one model over the rest.To achieve this,a series of statistical indicators were used:Index of agreement(d),MAE(Mean absolute error),SEE(Standard error of estimate)and RMSD(Root mean square difference).Moreover,a sensitivity analysis was performed in order to compare and show the stability of the best models when an error is introduced within the input parameters.In this case,the empirical models demonstrate a better performance than the ANFIS models.This work demonstrates that the Ritchie method is a good estimator of the ETo value for a semi-arid region in southern India.In addition,the results of the ANFIS models are promising and could be used as estimation methods.
基金support by a CSC Scholarship.DH is supported by an NSF NRT Fellowship-Grant DGE 1633722.
文摘In this paper,we present a soil methane emissions suppression approach using swarms of unmanned aerial vehicles(UAVs),by spreading biochar mulch on top of the detected methane emissions area/source.Soil microorganisms can produce methane and release it into the atmosphere causing climate change such as global warming.However,people lack methods to manage soil methane emissions,especially quantification of methane emissions from the soil.Current measurement and suppression of methane methods are often limited due to the maintenance,installation,and calibration requirements of these sensing systems.To overcome these drawbacks,we present a new method called FADE-MAS2D(Fractional Advection Diffusion Mobile Actuator and Sensor)in which swarming UAVs are applied as optimal coverage control actuators to various methane release scenarios(from single to multi-source disturbances)utilizing an anomalous diffusion model with different time,and space fractional orders subject to wind fields.This strategy is based on the premise that methane diffusion can be modeled as an anomalous diffusion equation,and swarming UAVs can be applied to tackle the optimal coverage control issue.To simulate methane diffusion under the wind,we utilize the fractional calculus to solve the anomalous diffusion equation and define wind force with the drag equation.In addition,we integrated emissions control,UAV control efforts,and UAV location error in our cost function.Finally,we evaluated our approach using simulation experiments with methane diffusion and multiple methane emission sources in the time and space domain,respectively.The results show that when α=0.8 and β=1.8,the shape and emissions of methane perform well.Furthermore,our approach resulted in great control performance with multiple methane emission sources and different wind velocities and directions.
基金the National Natural Science Foundation of China(No.60571026)
文摘The properties of terahertz （THz） radiation pulses emitted by a metallic, large aspect ratio carbon nanotube antenna have been studied both in the THz waveforms and field distribution. The peak THz field up to 2.66 and 1.26 kV/cm are observed at the probe points. The proposed antenna is designed to operate for dual frequency applications from 2.36 to 2.58 THz and from 7.27 to 7.5 THz for less than -10 dB return loss.
文摘Background:Identifying patient-specific flow of signal transduction perturbed by multiple single-nucleotide alterations is critical for improving patient outcomes in cancer cases.However,accurate estimation of mutational effects at the pathway level for such patients remains an open problem.While probabilistic pathway topology methods are gaining interest among the scientific community,the overwhelming majority do not account for network perturbation effects from multiple single-nucleotide alterations.Methods:Here we present an improvement of the mutational forks formalism to infer the patient-specific flow of signal transduction based on multiple single-nucleotide alterations,including non-synonymous and synonymous mutations.The lung adenocarcinoma and skin cutaneous melanoma datasets from TCGA Pan-Cancer Atlas have been employed to show the utility of the proposed method.Results:We have comprehensively characterized six mutational forks.The number of mutated nodes ranged from one to four depending on the topological characteristics of a fork.Transitional confidences(TCs)have been computed for every possible combination of single-nucleotide alterations in the fork.The performed analysis demonstrated the capacity of the mutational forks formalism to follow a biologically explainable logic in the identification of high-likelihood signaling routes in lung adenocarcinoma and skin cutaneous melanoma patients.The findings have been largely supported by the evidence from the biomedical literature.Conclusion:We conclude that the formalism has a great chance to enable an assessment of patient-specific flow by leveraging information from multiple single-nucleotide alterations to adjust the transitional likelihoods that are solely based on the canonical view of a disease.
基金National Institutes of Health(R01NS126596)a grant from 5022-Chan Zuckerberg Initiative DAF,an advised fund of Silicon Valley Community Foundation.
文摘Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes.Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product(SBP).Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems,thus restricting data throughput to maintain high SBP at limited frame rates.To address this,we introduce EventLFM,a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy(LFM),a state-of-theart single-shot 3D wide-field imaging technique.The event camera operates on a novel asynchronous readout architecture,thereby bypassing the frame rate limitations inherent to conventional CMOS systems.We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM.Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates.Furthermore,we highlight EventLFM’s capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C.elegans.We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.
文摘Dear Colleagues,Researchers,and Friends,It is with great excitement and pride that we present to you INTEGRATED CIRCUITS AND SYSTEMS(ICAS).This marks the beginning of an ambitious journey to create a world-class interdisciplinary academic journal in the field of integrated circuits and systems.Our mission at ICAS is to track and showcase the latest cutting-edge research results and advancements in integrated circuits and systems.The scope of our journal focuses on the theories,concepts,and techniques of science and engineering as applied to the interdisciplinary fields in integrated circuits and systems,including materials and devices,circuits,interconnects,design automation,manufacturing and integration,testing and packaging,as well as various applications of integrated circuits and systems.The journal invites contributions disclosing new and significant research as well as results relevant to industries and standards.
基金supported in part by the Defense Advanced Research Projects Agency(DARPA),contract no.N66001-17-C-4015Gordon and Betty Moore Foundation Data-Driven Discovery Initiative(grant GBMF4562)+3 种基金National Institutes of Health(NIH)grant 1R21EY027597-01the National Science Foundation(grant no.1617794)an Alfred P.Sloan Foundation fellowshipfunding from the National Science Foundation Graduate Research Fellowship Program(NSF GRFP).
文摘Miniature fluorescence microscopes are a standard tool in systems biology.However,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth range.Here,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture stop.Placing the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth range.The phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse problem.We provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature objectives.We demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per second.The performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain tissue.Compared with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth range.Our microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.
基金J.L.acknowledges financial support from University of Missouri-Columbia start-up fund,NASA Missouri Space Consortium(Project:00049784)Unite States Department of Agriculture(Award number:2018-67017-27880)+2 种基金This material is based upon work partially supported by the Department of Energy National Energy Technology Laboratory under Award Number DE-FE0031645J.C.acknowledges National Science Foundation(Award numbers:DBI1759934 and IIS1763246)The computations were performed on the HPC resources at the University of Missouri Bioinformatics Consortium(UMBC),supported in part by NSF(award number:1429294).
文摘It is well-known that the atomic-scale and nano-scale configuration of dopants can play a crucial role in determining the electronic properties of materials.However,predicting such effects is challenging due to the large range of atomic configurations that are possible.Here,we present a case study of how deep learning algorithms can enable bandgap prediction in hybridized boron–nitrogen graphene with arbitrary supercell configurations.A material descriptor that enables correlation of structure and bandgap was developed for convolutional neural networks.Bandgaps calculated by ab initio calculations,and corresponding structures,were used as training datasets.The trained networks were then used to predict bandgaps of systems with various configurations.For 4×4 and 5×5 supercells they accurately predict bandgaps,with a R^(2) of >90% and root-mean-square error of~0.1 eV.The transfer learning was performed by leveraging data generated from small supercells to improve the prediction accuracy for 6×6 supercells.This work will pave a route to future investigation of configurationally hybridized graphene and other 2D materials.Moreover,given the ubiquitous existence of configurations in materials,this work may stimulate interest in applying deep learning algorithms for the configurational design of materials across different length scales.
