We present measurements of the optical broadband atmospheric extinction coefficients and the night sky brightness at the Xuyi Observation Station of Purple Mountain Observatory. The measurements are based on CCD imagi...We present measurements of the optical broadband atmospheric extinction coefficients and the night sky brightness at the Xuyi Observation Station of Purple Mountain Observatory. The measurements are based on CCD imaging data taken in the Sloan Digital Sky Survey＇s g, r and i bands with the Xuyi 1.04/1.20m Schmidt Telescope for the Xuyi Schmidt Telescope Photometric Survey of the Galactic Anticenter （XSTPS-GAC）, the photometric part of the Digital Sky Survey of the Galactic Anti-center （DSS-GAC）. The data were collected during more than 140 winter nights from 2009 to 2011. We find that the atmospheric extinction coefficients for the g, r and i bands are 0.69, 0.55 and 0.38 mag/airmass, respectively, based on observations taken on several photometric nights. The night sky brightness determined from images with good quality has median values of 21.7, 20.8 and 20.0 mag arcsec-2 and reaches 22.1, 21.2 and 20.4mag arcsec-2 under the best observing conditions for the g, r and i bands, respectively. The relatively large extinction coefficients compared with other good astronomical observing sites are mainly due to the relatively low elevation （i.e. 180 m） and high humidity at the station.展开更多
Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize...Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize electrical stimulation to directly or indirectly target specific brain regions,modulating neural activity and influencing broader brain networks,thereby regulating cognitive function.Regulating cognitive function involves an understanding of aspects such as perception,learning and memory,attention,spatial cognition,and physical function.To enhance the application of cognitive regulation in the general population,this paper reviews recent publications from the Web of Science to assess the advancements and challenges of invasive and non-invasive stimulation methods in modulating cognitive functions.This review covers various neuromodulation techniques for cognitive intervention,including deep brain stimulation,vagus nerve stimulation,and invasive methods using microelectrode arrays.The non-invasive techniques discussed include transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcutaneous electrical acupoint stimulation,and time interference stimulation for activating deep targets.Invasive stimulation methods,which are ideal for studying the pathogenesis of neurological diseases,tend to cause greater trauma and have been less researched in the context of cognitive function regulation.Non-invasive methods,particularly newer transcranial stimulation techniques,are gentler and more appropriate for regulating cognitive functions in the general population.These include transcutaneous acupoint electrical stimulation using acupoints and time interference methods for activating deep targets.This paper also discusses current technical challenges and potential future breakthroughs in neuromodulation technology.It is recommended that neuromodulation techniques be combined with neural detection methods to better assess their effects and improve the accuracy of non-invasive neuromodulation.Additionally,researching closed-loop feedback neuromodulation methods is identified as a promising direction for future development.展开更多
Wide-temperature applications of sodium-ion batteries(SIBs)are severely limited by the sluggish ion insertion/diffusion kinetics of conversion-type anodes.Quantum-sized transition metal dichalcogenides possess unique ...Wide-temperature applications of sodium-ion batteries(SIBs)are severely limited by the sluggish ion insertion/diffusion kinetics of conversion-type anodes.Quantum-sized transition metal dichalcogenides possess unique advantages of charge delocalization and enrich uncoordinated electrons and short-range transfer kinetics,which are crucial to achieve rapid low-temperature charge transfer and high-temperature interface stability.Herein,a quantum-scale FeS_(2) loaded on three-dimensional Ti_(3)C_(2) MXene skeletons(FeS_(2) QD/MXene)fabricated as SIBs anode,demonstrating impressive performance under wide-temperature conditions(−35 to 65).The theoretical calculations combined with experimental characterization interprets that the unsaturated coordination edges of FeS_(2) QD can induce delocalized electronic regions,which reduces electrostatic potential and significantly facilitates efficient Na+diffusion across a broad temperature range.Moreover,the Ti_(3)C_(2) skeleton reinforces structural integrity via Fe-O-Ti bonding,while enabling excellent dispersion of FeS_(2) QD.As expected,FeS_(2) QD/MXene anode harvests capacities of 255.2 and 424.9 mAh g^(−1) at 0.1 A g^(−1) under−35 and 65,and the energy density of FeS_(2) QD/MXene//NVP full cell can reach to 162.4 Wh kg^(−1) at−35,highlighting its practical potential for wide-temperatures conditions.This work extends the uncoordinated regions induced by quantum-size effects for exceptional Na^(+)ion storage and diffusion performance at wide-temperatures environment.展开更多
Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic...Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.展开更多
In order to address environmental pollution and resource depletion caused by traditional power generation,this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved D...In order to address environmental pollution and resource depletion caused by traditional power generation,this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved Dung Beetle Optimizer(IDBO)with VariationalMode Decomposition(VMD).The IDBO-VMD method is designed to enhance the accuracy and efficiency of wind-speed time-series decomposition and to effectively smooth photovoltaic power fluctuations.This study innovatively improves the traditional variational mode decomposition(VMD)algorithm,and significantly improves the accuracy and adaptive ability of signal decomposition by IDBO selfoptimization of key parameters K and a.On this basis,Fourier transform technology is used to define the boundary point between high frequency and low frequency signals,and a targeted energy distribution strategy is proposed:high frequency fluctuations are allocated to supercapacitors to quickly respond to transient power fluctuations;Lowfrequency components are distributed to lead-carbon batteries,optimizing long-term energy storage and scheduling efficiency.This strategy effectively improves the response speed and stability of the energy storage system.The experimental results demonstrate that the IDBO-VMD algorithm markedly outperforms traditional methods in both decomposition accuracy and computational efficiency.Specifically,it effectively reduces the charge–discharge frequency of the battery,prolongs battery life,and optimizes the operating ranges of the state-of-charge(SOC)for both leadcarbon batteries and supercapacitors.In addition,the energy management strategy based on the algorithm not only improves the overall energy utilization efficiency of the system,but also shows excellent performance in the dynamic management and intelligent scheduling of renewable energy generation.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
A nonfused ring electron acceptor(NFREA),designated as TT-Ph-C6,has been synthesized with the aim of enhancing the power conversion efficiency(PCE)of organic solar cells(OSCs).By integrating asymmetric phenylalkylamin...A nonfused ring electron acceptor(NFREA),designated as TT-Ph-C6,has been synthesized with the aim of enhancing the power conversion efficiency(PCE)of organic solar cells(OSCs).By integrating asymmetric phenylalkylamino side groups,TT-Ph-C6 demonstrates excellent solubility and its crystal structure exhibits compact packing structures with a three-dimensional molecular stacking network.These structural attributes markedly promote exciton diffusion and charge carrier mobility,particularly advantageous for the fabrication of thick-film devices.TT-Ph-C6-based devices have attained a PCE of 18.01%at a film thickness of 100 nm,and even at a film thickness of 300 nm,the PCE remains at 14.64%,surpassing that of devices based on 2BTh-2F.These remarkable properties position TT-Ph-C6 as a highly promising NFREA material for boosting the efficiency of OSCs.展开更多
Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive exa...Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.展开更多
Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence archite...Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence architectures in terms of latency,energy efficiency,and computational power.To achieve this vision,it is of vital importance to scale up the PNNs while simultaneously reducing the high demand on the dimensions required by them.The underlying cause of this strategy is the enormous gap between the scales of photonic and electronic integrated circuits.Here,we demonstrate monolithically integrated optical convolutional processors on thin film lithium niobate(TFLN)that harness inherent parallelism in photonics to enable large-scale programmable convolution kernels and,in turn,greatly reduce the dimensions required by subsequent fully connected layers.Experimental validation achieves high classification accuracies of 96%(86%)on the MNIST(Fashion-MNIST)dataset and 84.6%on the AG News dataset while dramatically reducing the required subsequent fully connected layer dimensions to 196×10(from 784×10)and 175×4(from 800×4),respectively.Furthermore,our devices can be driven by commercial field-programmable gate array systems;a unique advantage in addition to their scalable channel number and kernel size.Our architecture provides a solution to build practical machine learning photonic devices.展开更多
GaInP/GaAs dual-junction solar cell with a conversion efficiency of 25.2% has been fabricated using metalorganic chemical vapor deposition (MOCVD) technique. Quantum efficiencies of the solar cell were measured within...GaInP/GaAs dual-junction solar cell with a conversion efficiency of 25.2% has been fabricated using metalorganic chemical vapor deposition (MOCVD) technique. Quantum efficiencies of the solar cell were measured within a temperature range from 25 to 160°C. The results indicate that the quantum efficiencies of the subcells increase slightly with the increasing temperature. And red-shift phenomena of absorption limit for all subcells are observed by increasing the cell’s work temperature, which are consistent with the viewpoint of energy gap narrowing effect. The short-circuit current density temperature coefficients dJ sc/dT of GaInP subcell and GaAs subcell are determined to be 8.9 and 7.4 μA/cm2/°C from the quantum efficiency data, respectively. And the open-circuit cell voltage temperature coefficients dV oc/dT calculated based on a theoretical equation are ?2.4 mV/°C and ?2.1 mV/°C for GaInP subcell and GaAs subcell.展开更多
Knowledge of cotton crop evapotranspiration(ET)is important in scheduling irrigations,optimizing crop production,and modeling ET and crop growth.The ability to measure,estimate,and predict ET and cotton crop water req...Knowledge of cotton crop evapotranspiration(ET)is important in scheduling irrigations,optimizing crop production,and modeling ET and crop growth.The ability to measure,estimate,and predict ET and cotton crop water requirements can result in better satisfying the crop’s water needs and improving water use efficiency.Weighing lysimeters have been used for many years to measure and study water use,and to develop crop-coefficient functions necessary in estimating ET.Electronic weighing lysimeters,consisting of a steel outer tank and inner tank,electronic loadcell assemblies,and a PVC drain system,were designed,constructed,and installed.Each lysimeter cost approximately US$1700(in 2001)in materials,required two people and 40 hours of labor to construct,and were installed by two people using minimal excavation and hand tools.Daily ET data for cotton were collected from 2003 to 2006 to quantify cotton water-use and to develop crop coefficient functions.Seasonal water use ranged generally from 2 to 8 mm/d.Seasonal water-use patterns varied considerably among growing seasons due to variable environmental and crop-growth conditions,making determination of an“average”crop-coefficient function difficult.展开更多
The efficiency of inductive power links driven by Class-E amplifiers may deteriorate due to variation in the coupling coefficient when the relative position of the radio frequency (RF) coils changes.To solve this prob...The efficiency of inductive power links driven by Class-E amplifiers may deteriorate due to variation in the coupling coefficient when the relative position of the radio frequency (RF) coils changes.To solve this problem,a new design methodology of power links is presented in this paper.The aim of the new design is to use the feedback signal,which is a phase difference between the driving signal and the output current of the Class-E amplifier,to adjust the duty cycle and angular frequency of the driving signal to maintain the optimum state of the inductive power link,and to adjust the supply voltage to keep the output power constant when the coupling coefficient of the RF coils changes.The parameter adjustments with respect to the coupling coefficient and the feedback signal are derived from the design equation of the inductive power link.To validate the feedback control rules,a prototype of the inductive power link was constructed,and its performance validated with the coupling coefficient set at 0.2 and a duty cycle of 0.5.The experimental results showed that,by adjusting the duty cycle,the angular frequency,and the supply voltage,the power link can be kept in optimal operation with a constant output power when the coupling coefficient changes from 0.2 to 0.1 to 0.25.展开更多
Background Radiation detection has been a main interest for researchers as all kind of produced particles in atomic and subatomic physics based on the measurement systems so-called detector.Detection efficiency is one...Background Radiation detection has been a main interest for researchers as all kind of produced particles in atomic and subatomic physics based on the measurement systems so-called detector.Detection efficiency is one of the main parameters in detection system besides many other different parameters of the detector.The detector in experimental physics is an instrument that converts radiation energy into an electrical signal,and this is achieved basically by either ionization or excitation.The choice for any type of a detector(gas-filled,scintillation or semiconductor)for any application depends upon the X-ray of gamma energy range of interest.A working model is therefore developed which is capable of describing the overall NaI(Tl)detection efficiency as a function of several known parameters.Purpose The attenuation coefficients for the bismuth borate glasses with different concentrations were measured using gamma spectroscopy technique.The numerical absolute efficiency calibration of a detector can be determined by In-Situ Object Calibration Software(ISOCS)and Monte Carlo Neutral Particle version 5(MCNP5)techniques which does not require any calibration standards or reference materials.Methods By using the ISOCS and MCNP5 methodologies,the full energy peak efficiency of a scintillator detector(3“X3”NaI(Tl))exposed to Co-60 and Cs-137 gamma ray sources with average accuracy range 0.126–1.224%for the used samples can be detected.The used materials are ternary and are located between the detector and the source to determine the attenuation coefficients for these samples by using the calculated full energy peak efficiencies of a detector.Results The average accuracy ranged from−1.808 to 1.960%for linear attenuation coefficient(μ),while it ranged from−1.999 to 1.888%and from−1.924 to 1.960%for half value layer(HVL)and mass linear attenuation coefficient(μm),respectively.Conclusion The calculated values of the absolute full energy peak efficiency have been used to determine the attenuation coefficients of materials with different concentrations and different densities.The results proved the validation of ISOCS and MCNP to determine the absolute full energy peak efficiency of the detector which can be used to determine the attenuation coefficients for the simulated samples and it is a good tool to be used when experimental methods are not available.展开更多
现有基于红外图像的绝缘子发热缺陷识别方法,存在目标区域提取精度有限、温度提取受环境因素影响较大等问题。为此,本文提出一种复合绝缘子过热识别新方法:首先改进单阶段绝缘子实例分割算法You Only Look At CoefficienTs(YOLACT),引...现有基于红外图像的绝缘子发热缺陷识别方法,存在目标区域提取精度有限、温度提取受环境因素影响较大等问题。为此,本文提出一种复合绝缘子过热识别新方法:首先改进单阶段绝缘子实例分割算法You Only Look At CoefficienTs(YOLACT),引入嵌有Efficient Local Attention(ELA)机制的MobileNetV2作主干网络提升检测速度,融合特征金字塔网络(Feature Pyramid Network,FPN)各层特征图并加入聚焦纯卷积特征提取模块提高特征图质量;然后使用改进算法识别红外图像中复合绝缘子外轮廓,定位其棒芯位置;最后依据红外图像热矩阵获取棒芯温度矩阵,对比温度变化判断是否异常。实际生产环境中,本文方法整体准确率达到975,算法总耗时125ms;改进实例分割算法平均交互比(mIOU)为9297,平均像素准确率(mPA)为9615,每秒帧数(FPS)为19。结果显示,此方法分割定位效果好,能滤除多数环境因素导致的温度识别误差,为绝缘子温度异常识别提供新方案。展开更多
车辆检测是智能交通系统和自动驾驶的重要组成部分。然而,实际交通场景中存在许多不确定因素,导致车辆检测模型的准确率低实时性差。为了解决这个问题,提出了一种快速准确的车辆检测算法——YOLOv8-DEL。使用DGCST(dynamic group convol...车辆检测是智能交通系统和自动驾驶的重要组成部分。然而,实际交通场景中存在许多不确定因素,导致车辆检测模型的准确率低实时性差。为了解决这个问题,提出了一种快速准确的车辆检测算法——YOLOv8-DEL。使用DGCST(dynamic group convolution shuffle transformer)模块代替C2f模块来重构主干网络,以增强特征提取能力并使网络更轻量;添加的P2检测层能使模型更敏锐地定位和检测小目标,同时采用Efficient RepGFPN进行多尺度特征融合,以丰富特征信息并提高模型的特征表达能力;通过结合GroupNorm和共享卷积的优点,设计了一种轻量型共享卷积检测头,在保持精度的前提下,有效减少参数量并提升检测速度。与YOLOv8相比,提出的YOLOv8-DEL在BDD100K数据集和KITTI数据集上,mAP@0.5分别提高了4.8个百分点和1.2个百分点,具有实时检测速度(208.6 FPS和216.4 FPS),在检测精度和速度方面实现了更有利的折中。展开更多
美国联邦政府采购体系以其繁多的法律体系和复杂的监管框架著称。2025年,随着特朗普政府成立政府效率部门(Department of Government Efficiency,DOGE),美国联邦政府正在探索如何通过创新技术和优化流程提高政府效率和透明度。笔者希望...美国联邦政府采购体系以其繁多的法律体系和复杂的监管框架著称。2025年,随着特朗普政府成立政府效率部门(Department of Government Efficiency,DOGE),美国联邦政府正在探索如何通过创新技术和优化流程提高政府效率和透明度。笔者希望通过对DOGE成立1个多月以来在推动美国联邦政府采购预算和监管模式的改革方面所采取的措施,探讨美国联邦政府采购的最新改革动向,包括预算削减与采购规模压缩、采购流程AI化、政府采购社会经济政策目标的调整、对采购组织机构和人员的影响、监管方式的改变,以及DOGE的法律与政治挑战、长期影响和示范效应。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos. 11078006 and 10933004)supported by the Minor Planet Foundation of Purple Mountain Observatory
文摘We present measurements of the optical broadband atmospheric extinction coefficients and the night sky brightness at the Xuyi Observation Station of Purple Mountain Observatory. The measurements are based on CCD imaging data taken in the Sloan Digital Sky Survey＇s g, r and i bands with the Xuyi 1.04/1.20m Schmidt Telescope for the Xuyi Schmidt Telescope Photometric Survey of the Galactic Anticenter （XSTPS-GAC）, the photometric part of the Digital Sky Survey of the Galactic Anti-center （DSS-GAC）. The data were collected during more than 140 winter nights from 2009 to 2011. We find that the atmospheric extinction coefficients for the g, r and i bands are 0.69, 0.55 and 0.38 mag/airmass, respectively, based on observations taken on several photometric nights. The night sky brightness determined from images with good quality has median values of 21.7, 20.8 and 20.0 mag arcsec-2 and reaches 22.1, 21.2 and 20.4mag arcsec-2 under the best observing conditions for the g, r and i bands, respectively. The relatively large extinction coefficients compared with other good astronomical observing sites are mainly due to the relatively low elevation （i.e. 180 m） and high humidity at the station.
基金supported by STI 2030-Major Projects,No.2021ZD0201603(to JL)the Joint Foundation Program of the Chinese Academy of Sciences,No.8091A170201(to JL)+1 种基金the National Natural Science Foundation of China,Nos.T2293730(to XC),T2293731(to XC),T2293734(to XC),62471291(to YW),62121003(to XC),61960206012(to XC),62333020(to XC),and 62171434(to XC)the National Key Research and Development Program of China,Nos.2022YFC2402501(to XC),2022YFB3205602(to XC).
文摘Neuromodulation techniques effectively intervene in cognitive function,holding considerable scientific and practical value in fields such as aerospace,medicine,life sciences,and brain research.These techniques utilize electrical stimulation to directly or indirectly target specific brain regions,modulating neural activity and influencing broader brain networks,thereby regulating cognitive function.Regulating cognitive function involves an understanding of aspects such as perception,learning and memory,attention,spatial cognition,and physical function.To enhance the application of cognitive regulation in the general population,this paper reviews recent publications from the Web of Science to assess the advancements and challenges of invasive and non-invasive stimulation methods in modulating cognitive functions.This review covers various neuromodulation techniques for cognitive intervention,including deep brain stimulation,vagus nerve stimulation,and invasive methods using microelectrode arrays.The non-invasive techniques discussed include transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcutaneous electrical acupoint stimulation,and time interference stimulation for activating deep targets.Invasive stimulation methods,which are ideal for studying the pathogenesis of neurological diseases,tend to cause greater trauma and have been less researched in the context of cognitive function regulation.Non-invasive methods,particularly newer transcranial stimulation techniques,are gentler and more appropriate for regulating cognitive functions in the general population.These include transcutaneous acupoint electrical stimulation using acupoints and time interference methods for activating deep targets.This paper also discusses current technical challenges and potential future breakthroughs in neuromodulation technology.It is recommended that neuromodulation techniques be combined with neural detection methods to better assess their effects and improve the accuracy of non-invasive neuromodulation.Additionally,researching closed-loop feedback neuromodulation methods is identified as a promising direction for future development.
基金supported by the National Nature Science Foundation of China(Nos.52202335 and 52171227)Natural Science Foundation of Jiangsu Province(No.BK20221137)National Key R&D Program of China(2024YFE0108500).
文摘Wide-temperature applications of sodium-ion batteries(SIBs)are severely limited by the sluggish ion insertion/diffusion kinetics of conversion-type anodes.Quantum-sized transition metal dichalcogenides possess unique advantages of charge delocalization and enrich uncoordinated electrons and short-range transfer kinetics,which are crucial to achieve rapid low-temperature charge transfer and high-temperature interface stability.Herein,a quantum-scale FeS_(2) loaded on three-dimensional Ti_(3)C_(2) MXene skeletons(FeS_(2) QD/MXene)fabricated as SIBs anode,demonstrating impressive performance under wide-temperature conditions(−35 to 65).The theoretical calculations combined with experimental characterization interprets that the unsaturated coordination edges of FeS_(2) QD can induce delocalized electronic regions,which reduces electrostatic potential and significantly facilitates efficient Na+diffusion across a broad temperature range.Moreover,the Ti_(3)C_(2) skeleton reinforces structural integrity via Fe-O-Ti bonding,while enabling excellent dispersion of FeS_(2) QD.As expected,FeS_(2) QD/MXene anode harvests capacities of 255.2 and 424.9 mAh g^(−1) at 0.1 A g^(−1) under−35 and 65,and the energy density of FeS_(2) QD/MXene//NVP full cell can reach to 162.4 Wh kg^(−1) at−35,highlighting its practical potential for wide-temperatures conditions.This work extends the uncoordinated regions induced by quantum-size effects for exceptional Na^(+)ion storage and diffusion performance at wide-temperatures environment.
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01264).
文摘Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.
基金funded by the Institute of Smart Energy,Huaiyin Institute of Technology,under Grant No.HIT-ISE-2024-07.
文摘In order to address environmental pollution and resource depletion caused by traditional power generation,this paper proposes an adaptive iterative dynamic-balance optimization algorithm that integrates the Improved Dung Beetle Optimizer(IDBO)with VariationalMode Decomposition(VMD).The IDBO-VMD method is designed to enhance the accuracy and efficiency of wind-speed time-series decomposition and to effectively smooth photovoltaic power fluctuations.This study innovatively improves the traditional variational mode decomposition(VMD)algorithm,and significantly improves the accuracy and adaptive ability of signal decomposition by IDBO selfoptimization of key parameters K and a.On this basis,Fourier transform technology is used to define the boundary point between high frequency and low frequency signals,and a targeted energy distribution strategy is proposed:high frequency fluctuations are allocated to supercapacitors to quickly respond to transient power fluctuations;Lowfrequency components are distributed to lead-carbon batteries,optimizing long-term energy storage and scheduling efficiency.This strategy effectively improves the response speed and stability of the energy storage system.The experimental results demonstrate that the IDBO-VMD algorithm markedly outperforms traditional methods in both decomposition accuracy and computational efficiency.Specifically,it effectively reduces the charge–discharge frequency of the battery,prolongs battery life,and optimizes the operating ranges of the state-of-charge(SOC)for both leadcarbon batteries and supercapacitors.In addition,the energy management strategy based on the algorithm not only improves the overall energy utilization efficiency of the system,but also shows excellent performance in the dynamic management and intelligent scheduling of renewable energy generation.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
基金Financial support from the National Natural Science Foundation of China(22375024,21975031,21734009,51933001,22109080,and 52173174)the Natural Science Foundation of Shandong Province(No.ZR2022YQ45)+2 种基金the Taishan Scholars Program(Nos.tstp20221121 and tsqnz20221134)The Beijing Natural Science Foundation(No.2244073)supported by State Key Laboratory of Bio-Fibers and Eco-Textiles(Qingdao University)(RZ2200002821)is acknowledged.
文摘A nonfused ring electron acceptor(NFREA),designated as TT-Ph-C6,has been synthesized with the aim of enhancing the power conversion efficiency(PCE)of organic solar cells(OSCs).By integrating asymmetric phenylalkylamino side groups,TT-Ph-C6 demonstrates excellent solubility and its crystal structure exhibits compact packing structures with a three-dimensional molecular stacking network.These structural attributes markedly promote exciton diffusion and charge carrier mobility,particularly advantageous for the fabrication of thick-film devices.TT-Ph-C6-based devices have attained a PCE of 18.01%at a film thickness of 100 nm,and even at a film thickness of 300 nm,the PCE remains at 14.64%,surpassing that of devices based on 2BTh-2F.These remarkable properties position TT-Ph-C6 as a highly promising NFREA material for boosting the efficiency of OSCs.
文摘Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs.
基金supported by the National Natural Science Foundation of China (Grant Nos.12192251,12334014,62335019,12134001,1230441812474378)+1 种基金the Quantum Science and Technology National Science and Technology Major Project(Grant No.2021ZD0301403)the Shanghai Municipal Science and Technology Major Project (Grant No.2019SHZDZX01)。
文摘Photonic neural networks(PNNs)of sufficiently large physical dimensions and high operation accuracies are envisaged as ideal candidates for breaking the major bottlenecks in the current artificial intelligence architectures in terms of latency,energy efficiency,and computational power.To achieve this vision,it is of vital importance to scale up the PNNs while simultaneously reducing the high demand on the dimensions required by them.The underlying cause of this strategy is the enormous gap between the scales of photonic and electronic integrated circuits.Here,we demonstrate monolithically integrated optical convolutional processors on thin film lithium niobate(TFLN)that harness inherent parallelism in photonics to enable large-scale programmable convolution kernels and,in turn,greatly reduce the dimensions required by subsequent fully connected layers.Experimental validation achieves high classification accuracies of 96%(86%)on the MNIST(Fashion-MNIST)dataset and 84.6%on the AG News dataset while dramatically reducing the required subsequent fully connected layer dimensions to 196×10(from 784×10)and 175×4(from 800×4),respectively.Furthermore,our devices can be driven by commercial field-programmable gate array systems;a unique advantage in addition to their scalable channel number and kernel size.Our architecture provides a solution to build practical machine learning photonic devices.
文摘GaInP/GaAs dual-junction solar cell with a conversion efficiency of 25.2% has been fabricated using metalorganic chemical vapor deposition (MOCVD) technique. Quantum efficiencies of the solar cell were measured within a temperature range from 25 to 160°C. The results indicate that the quantum efficiencies of the subcells increase slightly with the increasing temperature. And red-shift phenomena of absorption limit for all subcells are observed by increasing the cell’s work temperature, which are consistent with the viewpoint of energy gap narrowing effect. The short-circuit current density temperature coefficients dJ sc/dT of GaInP subcell and GaAs subcell are determined to be 8.9 and 7.4 μA/cm2/°C from the quantum efficiency data, respectively. And the open-circuit cell voltage temperature coefficients dV oc/dT calculated based on a theoretical equation are ?2.4 mV/°C and ?2.1 mV/°C for GaInP subcell and GaAs subcell.
文摘Knowledge of cotton crop evapotranspiration(ET)is important in scheduling irrigations,optimizing crop production,and modeling ET and crop growth.The ability to measure,estimate,and predict ET and cotton crop water requirements can result in better satisfying the crop’s water needs and improving water use efficiency.Weighing lysimeters have been used for many years to measure and study water use,and to develop crop-coefficient functions necessary in estimating ET.Electronic weighing lysimeters,consisting of a steel outer tank and inner tank,electronic loadcell assemblies,and a PVC drain system,were designed,constructed,and installed.Each lysimeter cost approximately US$1700(in 2001)in materials,required two people and 40 hours of labor to construct,and were installed by two people using minimal excavation and hand tools.Daily ET data for cotton were collected from 2003 to 2006 to quantify cotton water-use and to develop crop coefficient functions.Seasonal water use ranged generally from 2 to 8 mm/d.Seasonal water-use patterns varied considerably among growing seasons due to variable environmental and crop-growth conditions,making determination of an“average”crop-coefficient function difficult.
基金Project (No.60271031) supported by the National Natural Science Foundation of China
文摘The efficiency of inductive power links driven by Class-E amplifiers may deteriorate due to variation in the coupling coefficient when the relative position of the radio frequency (RF) coils changes.To solve this problem,a new design methodology of power links is presented in this paper.The aim of the new design is to use the feedback signal,which is a phase difference between the driving signal and the output current of the Class-E amplifier,to adjust the duty cycle and angular frequency of the driving signal to maintain the optimum state of the inductive power link,and to adjust the supply voltage to keep the output power constant when the coupling coefficient of the RF coils changes.The parameter adjustments with respect to the coupling coefficient and the feedback signal are derived from the design equation of the inductive power link.To validate the feedback control rules,a prototype of the inductive power link was constructed,and its performance validated with the coupling coefficient set at 0.2 and a duty cycle of 0.5.The experimental results showed that,by adjusting the duty cycle,the angular frequency,and the supply voltage,the power link can be kept in optimal operation with a constant output power when the coupling coefficient changes from 0.2 to 0.1 to 0.25.
文摘Background Radiation detection has been a main interest for researchers as all kind of produced particles in atomic and subatomic physics based on the measurement systems so-called detector.Detection efficiency is one of the main parameters in detection system besides many other different parameters of the detector.The detector in experimental physics is an instrument that converts radiation energy into an electrical signal,and this is achieved basically by either ionization or excitation.The choice for any type of a detector(gas-filled,scintillation or semiconductor)for any application depends upon the X-ray of gamma energy range of interest.A working model is therefore developed which is capable of describing the overall NaI(Tl)detection efficiency as a function of several known parameters.Purpose The attenuation coefficients for the bismuth borate glasses with different concentrations were measured using gamma spectroscopy technique.The numerical absolute efficiency calibration of a detector can be determined by In-Situ Object Calibration Software(ISOCS)and Monte Carlo Neutral Particle version 5(MCNP5)techniques which does not require any calibration standards or reference materials.Methods By using the ISOCS and MCNP5 methodologies,the full energy peak efficiency of a scintillator detector(3“X3”NaI(Tl))exposed to Co-60 and Cs-137 gamma ray sources with average accuracy range 0.126–1.224%for the used samples can be detected.The used materials are ternary and are located between the detector and the source to determine the attenuation coefficients for these samples by using the calculated full energy peak efficiencies of a detector.Results The average accuracy ranged from−1.808 to 1.960%for linear attenuation coefficient(μ),while it ranged from−1.999 to 1.888%and from−1.924 to 1.960%for half value layer(HVL)and mass linear attenuation coefficient(μm),respectively.Conclusion The calculated values of the absolute full energy peak efficiency have been used to determine the attenuation coefficients of materials with different concentrations and different densities.The results proved the validation of ISOCS and MCNP to determine the absolute full energy peak efficiency of the detector which can be used to determine the attenuation coefficients for the simulated samples and it is a good tool to be used when experimental methods are not available.
文摘现有基于红外图像的绝缘子发热缺陷识别方法,存在目标区域提取精度有限、温度提取受环境因素影响较大等问题。为此,本文提出一种复合绝缘子过热识别新方法:首先改进单阶段绝缘子实例分割算法You Only Look At CoefficienTs(YOLACT),引入嵌有Efficient Local Attention(ELA)机制的MobileNetV2作主干网络提升检测速度,融合特征金字塔网络(Feature Pyramid Network,FPN)各层特征图并加入聚焦纯卷积特征提取模块提高特征图质量;然后使用改进算法识别红外图像中复合绝缘子外轮廓,定位其棒芯位置;最后依据红外图像热矩阵获取棒芯温度矩阵,对比温度变化判断是否异常。实际生产环境中,本文方法整体准确率达到975,算法总耗时125ms;改进实例分割算法平均交互比(mIOU)为9297,平均像素准确率(mPA)为9615,每秒帧数(FPS)为19。结果显示,此方法分割定位效果好,能滤除多数环境因素导致的温度识别误差,为绝缘子温度异常识别提供新方案。
文摘美国联邦政府采购体系以其繁多的法律体系和复杂的监管框架著称。2025年,随着特朗普政府成立政府效率部门(Department of Government Efficiency,DOGE),美国联邦政府正在探索如何通过创新技术和优化流程提高政府效率和透明度。笔者希望通过对DOGE成立1个多月以来在推动美国联邦政府采购预算和监管模式的改革方面所采取的措施,探讨美国联邦政府采购的最新改革动向,包括预算削减与采购规模压缩、采购流程AI化、政府采购社会经济政策目标的调整、对采购组织机构和人员的影响、监管方式的改变,以及DOGE的法律与政治挑战、长期影响和示范效应。
