Quantum dots(QDs),a type of nanoscale semiconductor material with unique optical and electrical properties like adjustable emission and high photoluminescence quantum yields,are suitable for applications in optoelectr...Quantum dots(QDs),a type of nanoscale semiconductor material with unique optical and electrical properties like adjustable emission and high photoluminescence quantum yields,are suitable for applications in optoelectronics.However,QDs are typically degraded under humid and high-temperature circumstances,greatly limiting their practical value.Coating the QD surface with an inorganic silica layer is a feasible method for improving stability and endurance in a variety of applications.This paper comprehensively reviews silica coating methodologies on QD surfaces and explores their applications in optoelectronic domains.Firstly,the paper provides mainstream silica coating approaches,which can be divided into two categories:in-situ hydrolysis of silylating reagents on QD surfaces and template techniques for encapsulation QDs.Subsequently,the recent applications of the silica-coated QDs on optoelectronic fields including light-emitting diodes,solar cells,photodetectors were discussed.Finally,it reviews recent advances in silica-coated QD technology and prospects for future applications.展开更多
Ultra-thin crystalline silicon stands as a cornerstone material in the foundation of modern micro and nano electronics.Despite the proliferation of various materials including oxide-based,polymer-based,carbon-based,an...Ultra-thin crystalline silicon stands as a cornerstone material in the foundation of modern micro and nano electronics.Despite the proliferation of various materials including oxide-based,polymer-based,carbon-based,and two-dimensional(2D)materials,crystal silicon continues to maintain its stronghold,owing to its superior functionality,scalability,stability,reliability,and uniformity.Nonetheless,the inherent rigidity of the bulk silicon leads to incompatibility with soft tissues,hindering the utilization amid biomedical applications.Because of such issues,decades of research have enabled successful utilization of various techniques to precisely control the thickness and morphology of silicon layers at the scale of several nanometres.This review provides a comprehensive exploration on the features of ultra-thin single crystalline silicon as a semiconducting material,and its role especially among the frontier of advanced bioelectronics.Key processes that enable the transition of rigid silicon to flexible form factors are exhibited,in accordance with their chronological sequence.The inspected stages span both prior and subsequent to transferring the silicon membrane,categorized respectively as on-wafer manufacturing and rigid-to-soft integration.Extensive guidelines to unlock the full potential of flexible electronics are provided through ordered analysis of each manufacturing procedure,the latest findings of biomedical applications,along with practical perspectives for researchers and manufacturers.展开更多
BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)adm...BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to fi nd a light-weight,convenient prediction method through machine learning.METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation.RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the fi ve most important features were acuity,arrival transportation,age,shock index,and respiratory rate.CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.展开更多
Electrocatalytic water splitting has been identified as a potential candidate for producing clean hydrogen energy with zero carbon emission.However,the sluggish kinetics of oxygen evolution reaction on the anode side ...Electrocatalytic water splitting has been identified as a potential candidate for producing clean hydrogen energy with zero carbon emission.However,the sluggish kinetics of oxygen evolution reaction on the anode side of the watersplitting device significantly hinders its practical applications.Generally,the efficiency of oxygen evolution processes depends greatly on the availability of cost‐effective catalysts with high activity and selectivity.In recent years,extensive theoretical and experimental studies have demonstrated that cobalt(Co)‐based nanomaterials,especially low‐dimensional Co‐based nanomaterials with a huge specific surface area and abundant unsaturated active sites,have emerged as versatile electrocatalysts for oxygen evolution reactions,and thus,great progress has been made in the rational design and synthesis of Co‐based nanomaterials for electrocatalytic oxygen evolution reactions.Considering the remarkable progress in this area,in this timely review,we highlight the most recent developments in Co‐based nanomaterials relating to their dimensional control,defect regulation(conductivity),electronic structure regulation,and so forth.Furthermore,a brief conclusion about recent progress achieved in oxygen evolution on Co‐based nanomaterials,as well as an outlook on future research challenges,is given.展开更多
Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capa...Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.展开更多
Insect-derived traditional Chinese medicine(TCM)constitutes an essential component of TCM,with the earliest records found in“52 Bingfang”(Prescriptions of fifty-two diseases,which is one of the earliest Chinese medi...Insect-derived traditional Chinese medicine(TCM)constitutes an essential component of TCM,with the earliest records found in“52 Bingfang”(Prescriptions of fifty-two diseases,which is one of the earliest Chinese medical prescriptions).展开更多
Blue carbon ecosystems,including mangroves,seagrasses,and salt marshes,play a crucial role in mitigating climate change by capturing and storing atmospheric CO_(2)at rates exceeding those of terrestrial forests.This s...Blue carbon ecosystems,including mangroves,seagrasses,and salt marshes,play a crucial role in mitigating climate change by capturing and storing atmospheric CO_(2)at rates exceeding those of terrestrial forests.This study explores the potential of HCWs(Human-Controlled Wetlands)in the Italian Venice Lagoon as an underappreciated component of the global blue carbon pool.Using GEE(Google Earth Engine),we conducted a large-scale assessment of carbon sequestration in these wetlands,demonstrating its advantages over traditional in situ methods in addressing spatial variability.Our findings highlight the significance of below-water mud sediments as primary carbon reservoirs,with a TC(Total Carbon)content of 3.81%±0.94%and a stable storage function akin to peat,reinforced by high CEC(Cation Exchange Capacity).GEE analysis identified a redoximorphic zone at a depth of 20-30 cm,where microbial respiration shifts to anaerobic pathways,preventing carbon release and maintaining long-term sequestration.The study also evaluates key factors affecting remote sensing accuracy,including tidal variations,water depth,and sky cover.The strong correlation between field-measured and satellite-derived carbon parameters(R^(2)>0.85)confirms the reliability of our approach.Furthermore,we developed a GEE-based script for monitoring sediment bioturbation,leveraging Sentinel-1 SAR(Synthetic Aperture Radar)and Sentinel-2 optical data to quantify biological disturbances affecting carbon fluxes.Our results underscore the value of HCWs for carbon sequestration,reinforcing the need for targeted conservation strategies.The scalability and efficiency of remote sensing methodologies,particularly GEE,make them essential for the long-term monitoring of blue carbon ecosystems and the development of effective climate mitigation policies.展开更多
Extremely large-scale array(XL-array)communications can significantly improve the transmission rate,spectral efficiency,and spatial resolution,and has great potential in next-generation mobile communication networks.A...Extremely large-scale array(XL-array)communications can significantly improve the transmission rate,spectral efficiency,and spatial resolution,and has great potential in next-generation mobile communication networks.A crucial problem in XLarray communications is to determine the boundary of applicable regions of the plane wave model(PWM)and spherical wave model(SWM).In this paper,we propose new PWM/SWM demarcations for XL-arrays from the viewpoint of channel gain and rank.Four sets of results are derived for four different array setups.First,an equi-power line is derived for a point-touniform linear array(ULA)scenario,where an inflection point is found at±π6 central incident angles.Second,an equi-power surface is derived for a point-touniform planar array(UPA)scenario,and it is proved that cos2(ϕ)cos2(φ)=12 is a dividing curve,where ϕ andφdenote the elevation and azimuth angles,respectively.Third,an accurate and explicit expression of the equi-rank surface is obtained for a ULA-to-ULA scenario.Finally,an approximated expression of the equirank surface is obtained for a ULA-to-UPA scenario.With the obtained closed-form expressions,the equirank surface for any antenna structure and any angle can be well estimated.Furthermore,the effect of scatterers is also investigated,from which some insights are drawn.展开更多
To address the significant degradation of Space-Time Adaptive Processing(STAP)performance when the array elements have mutual coupling and gain/phase errors,a STAP algorithm with adaptive calibration for the above two...To address the significant degradation of Space-Time Adaptive Processing(STAP)performance when the array elements have mutual coupling and gain/phase errors,a STAP algorithm with adaptive calibration for the above two array errors is proposed in this article.First,based on a defined error matrix that simultaneously considers both array mutual coupling and gain/phase errors,a STAP signal model including these errors is given.Then,utilizing the defined signal model,it is demonstrated that the estimation of the defined error matrix can be formulized as a standard convex optimization problem with the low-rank structure of the clutter covariance matrix and the subspace projection theory.Once the defined error matrix is estimated by solving the convex optimization problem,it is illustrated that a STAP method with adaptive calibration of the mutual coupling and gain/phase errors is coined.Analyses also show that the proposed adaptive calibration algorithm only needs one training sample to construct the adaptive weight vector.Therefore,it can achieve a good detection performance even with severe non-homogeneous clutter environments.Finally,the simulation experiments verify the effectiveness of the proposed algorithm and the correctness of the analytical results.展开更多
Inverse Synthetic Aperture Radar(ISAR)images of complex targets have a low Signal-to-Noise Ratio(SNR)and contain fuzzy edges and large differences in scattering intensity,which limits the recognition performance of IS...Inverse Synthetic Aperture Radar(ISAR)images of complex targets have a low Signal-to-Noise Ratio(SNR)and contain fuzzy edges and large differences in scattering intensity,which limits the recognition performance of ISAR systems.Also,data scarcity poses a greater challenge to the accurate recognition of components.To address the issues of component recognition in complex ISAR targets,this paper adopts semantic segmentation and proposes a few-shot semantic segmentation framework fusing multimodal features.The scarcity of available data is mitigated by using a two-branch scattering feature encoding structure.Then,the high-resolution features are obtained by fusing the ISAR image texture features and scattering quantization information of complex-valued echoes,thereby achieving significantly higher structural adaptability.Meanwhile,the scattering trait enhancement module and the statistical quantification module are designed.The edge texture is enhanced based on the scatter quantization property,which alleviates the segmentation challenge of edge blurring under low SNR conditions.The coupling of query/support samples is enhanced through four-dimensional convolution.Additionally,to overcome fusion challenges caused by information differences,multimodal feature fusion is guided by equilibrium comprehension loss.In this way,the performance potential of the fusion framework is fully unleashed,and the decision risk is effectively reduced.Experiments demonstrate the great advantages of the proposed framework in multimodal feature fusion,and it still exhibits great component segmentation capability under low SNR/edge blurring conditions.展开更多
In recent years,artificial intelligence(AI)has demonstrated immense potential in driving breakthroughs in the semiconductor industry,particularly in full-color display technologies.Benefiting from the deep integration...In recent years,artificial intelligence(AI)has demonstrated immense potential in driving breakthroughs in the semiconductor industry,particularly in full-color display technologies.Benefiting from the deep integration of AI,these technologies are experiencing unprecedented innovation and industrial transformation,garnering significant attention.These advancements provide a solid foundation for displays with higher color gamut and resolution.In addition,the integration of deep learning with dimming technologies has enabled new display systems to deliver superior viewing experiences with reduced energy consumption.This review highlights recent progress in four key areas of AI application in full-color display technologies:epitaxial structure design,defect detection and repair,perovskite synthesis,and dynamic dimming.AI-driven advancements in these domains are paving the way for smarter,more efficient display technologies.By leveraging AI’s powerful data processing and optimization capabilities,full-color display systems are poised to achieve enhanced performance,energy efficiency,and user satisfaction,marking a significant step toward a more intelligent and innovative future.展开更多
Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen energy.Herein,Ru/NiMnB spherical cluster pillar(SCP),denoted as Ru/NiMnB,is synthesized using a combination of elect...Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen energy.Herein,Ru/NiMnB spherical cluster pillar(SCP),denoted as Ru/NiMnB,is synthesized using a combination of electro-deposition and hydrothermal reaction.Systematic investigation of Ru doping in the NiMnB matrix revealed significant improvements in electrocatalytic performance.The Ru/NiMnB SCPs demonstrate superior OER/HER activity with low overpotentials of 150 and 103 mV at 50mA/cm^(2)in 1 M KOH,making them highly competitive with state-of-the-art electrocatalysts.Remarkably,the Ru/NiMnB SCPs exhibit a low 2-E cell voltage of 2.80 V at ultra-high current density of 2,000 m A/cm^(2)in 1 M KOH,outperforming the standard benchmark electrodes of RuO_(2)||Pt/C,thereby positioning Ru/NiMnB as one of the best bifunctional electrocatalysts.These SCPs exhibit exceptional high-current characteristics,stability and corrosion resistance,as evidenced by continuous operation at 1,000 mA/cm^(2)high-current density for over 150 h in 6 M KOH at elevated temperatures under harsh industrial conditions.Only a small amount of Ru incorporation significantly enhances the electrocatalytic performances of NiMnB,attributed to increased active sites and improved intrinsic properties such as conductivity,adsorption/desorption capability and reaction rates.Consequently,Ru/NiMnB SCPs present a promising bi-functional electrode concept for efficient green H_(2)production.展开更多
We theoretically investigate a cooling scheme assisted by a quantum well(QW)and coherent feedback within a hybrid optomechanical system.Although the exciton mode in the QW and the mechanical resonator(MR)are initially...We theoretically investigate a cooling scheme assisted by a quantum well(QW)and coherent feedback within a hybrid optomechanical system.Although the exciton mode in the QW and the mechanical resonator(MR)are initially uncoupled,their interaction via the microcavity field leads to an indirect exciton-mode–mechanical-mode coupling.The coherent feedback loop is applied by feeding back a fraction of the output field of the cavity through a controllable beam splitter to the cavity’s input mirror.It is shown that the cooling capability is enhanced by effectively suppressing the Stokes process through coupling with the QW.Furthermore,the effect of the anti-Stokes process is enhanced through the application of the coherent feedback loop.This particular system configuration enables cooling of the mechanical resonator even in the unresolved sideband regime(USR).This study has some important guiding significance in the field of quantum information processing.展开更多
Enhancing the sensitivity of nuclear magnetic resonance(NMR)technology has been the focus of NMR research for decades,which offers the potential to significantly expand its applications in chemistry,biology,and medica...Enhancing the sensitivity of nuclear magnetic resonance(NMR)technology has been the focus of NMR research for decades,which offers the potential to significantly expand its applications in chemistry,biology,and medical imaging.Parahydrogen-induced polarization(PHIP)emerges as a cost-effective approach to substantially enhance the sensitivity of NMR.Nevertheless,the amplification of the ^(1)H signal in PHIP is susceptible to interference from the thermal polarization state ^(1)H NMR signal.Employing RASER(radiofrequency amplification by stimulated emission of radiation)proves effective in mitigating such interference,which can reduce the linewidth and increase the sensitivity at the same time.In this work,we utilized PHIP and RASER to enhance the signal-to-noise ratio(SNR)of a series of biocompatible alkynyl organic acid molecules.The alkynyl acid with the highest enhancement factor was first identified through PASADENA(parahydrogen and synthesis allow dramatically enhanced nuclear alignment)experiments.Subsequently,RASER experiments were carried out through hyperpolarization of 5-hexynoic acid,exploring its signal characteristics under varying flow rates and pressures.The SNR of proton signals of 5-hexynoic acid surpassed 150,000,an 18.62-fold improvement compared with traditional hyperpolarized signals in PASADENA,and a markedly narrowed linewidth of 0.06 Hz.展开更多
Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance ...Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance in multiple-input multipleoutput(MIMO)scenario with antenna selection(AS)scheme.We first derive the analytical expressions of average secrecy capacity(ASC)and secrecy outage probability(SOP)by the first order Marcum Q function.Then,the asymptotic expressions of ASC and SOP in two specific scenarios are further derived.The correctness of analytical and asymptotic expressions is verified by Monte Carlo simulations.The conclusions suggest that the analytical expressions of ASC and SOP are related to the product of transmitting and receiving antennas;increasing the number of antennas is beneficial to ASC and SOP.Besides,when the target rate is set at a low level,strong channel correlation is bad for ASC,but is beneficial to SOP.展开更多
Oceanic dissolved oxygen(DO)in the ocean has an indispensable role on supporting biological respiration,maintaining ecological balance and promoting nutrient cycling.According to existing research,the total DO has dec...Oceanic dissolved oxygen(DO)in the ocean has an indispensable role on supporting biological respiration,maintaining ecological balance and promoting nutrient cycling.According to existing research,the total DO has declined by 2%of the total over the past 50 a,and the tropical Pacific Ocean occupied the largest oxygen minimum zone(OMZ)areas.However,the sparse observation data is limited to understanding the dynamic variation and trend of ocean using traditional interpolation methods.In this study,we applied different machine learning algorithms to fit regression models between measured DO,ocean reanalysis physical variables,and spatiotemporal variables.We demonstrate that extreme gradient boosting(XGBoost)model has the best performance,hereby reconstructing a four-dimensional DO dataset of the tropical Pacific Ocean from 1920 to 2023.The results reveal that XGBoost significantly improves the reconstruction performance in the tropical Pacific Ocean,with a 35.3%reduction in root mean-squared error and a 39.5%decrease in mean absolute error.Additionally,we compare the results with three Coupled Model Intercomparison Project Phase 6(CMIP6)models data to confirm the high accuracy of the 4-dimensional reconstruction.Overall,the OMZ mainly dominates the eastern tropical Pacific Ocean,with a slow expansion.This study used XGBoost to efficiently reconstructing 4-dimensional DO enhancing the understanding of the hypoxic expansion in the tropical Pacific Ocean and we foresee that this approach would be extended to reconstruct more ocean elements.展开更多
A new class of phosphor samples,denoted as Ba_(1-x)Al_(2)Ge_(2)O_(8):xEu^(2+)(BAGO:xEu^(2+))was synthesized using a Pechini-type sol-gel technique and subsequent thermal reduction in CO atmosphere.The morphology and s...A new class of phosphor samples,denoted as Ba_(1-x)Al_(2)Ge_(2)O_(8):xEu^(2+)(BAGO:xEu^(2+))was synthesized using a Pechini-type sol-gel technique and subsequent thermal reduction in CO atmosphere.The morphology and structural characteristics of both the BAGO host lattice and the Eu^(2+)ions activated BAGO phosphors were investigated through field-emission scanning electron microscopy and X-ray diffractometry analyses,respectively.The BAGO host lattice has micro-sized particles and the Rietveld refinement reveals the presence of a monoclinic crystal phase,characterized by the space group I2/c(No.15).Introducing Eu^(2+)ions into Ba^(2+)sites under CO condition reduces the particle size,switching from microscale to nanoscale.Within the near-ultraviolet spectrum(353 nm),the BAGO:xEu^(2+)phosphors exhibit a broadband bluish-green photoluminescence(PL)emission characterized by a peak band at 492 nm.This phenomenon is attributed to the 4f^(6)5d^(1)→4f^(7) electronic transition.The BAGO:0.02Eu^(2+)phosphor shows the strongest bluish-green PL emission,and a co mprehensive description of the concentration quenching mechanism between Eu^(2+)ions is revealed.Additionally,the thermal stability of the optimized BAGO:0.02Eu^(2+)phosphor was investigated,and its activation energy was estimated.Therefore,the synthesized bluish-green BAGO:0.02Eu^(2+)phosphor holds the promise of being a novel and potential candidate for utilization in white light-emitting diode applications.展开更多
In offshore maritime communication sys-tems,base stations(BSs)are employed along the coastline to provide high-speed data service for ves-sels in coastal sea areas.To ensure the line-of-sight propagation of BS-vessel ...In offshore maritime communication sys-tems,base stations(BSs)are employed along the coastline to provide high-speed data service for ves-sels in coastal sea areas.To ensure the line-of-sight propagation of BS-vessel links,high transceiver an-tenna height is required,which limits the number of geographically available sites for BS deployment,and imposes a high cost for realizing effective wide-area coverage.In this paper,the joint user association and power allocation(JUAPA)problem is investigated to enhance the coverage of offshore maritime systems.By exploiting the characteristics of network topology as well as vessels’motion in offshore communica-tions,a multi-period JUAPA problem is formulated to maximize the number of ships that can be simultane-ously served by the network.This JUAPA problem is intrinsically non-convex and subject to mixed-integer constraints,which is difficult to solve either analyt-ically or numerically.Hence,we propose an iterative augmentation based framework to efficiently select the active vessels,where the JUAPA scheme is iteratively optimized by the network for increasing the number of the selected vessels.More specifically,in each itera-tion,the user association variables and power alloca-tion variables are determined by solving two separate subproblems,so that the JUAPA strategy can be up-dated in a low-complexity manner.The performance of the proposed JUAPA method is evaluated by exten-sive simulation,and numerical results indicate that it can effectively increase the number of vessels served by the network,and thus enhances the coverage of off-shore systems.展开更多
Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth...Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.展开更多
Complex-valued double-sideband direct detection(DD)can reconstruct the optical field and achieve a high electrical spectral efficiency(ESE)comparable to that of a coherent homodyne receiver,and DD does not require a c...Complex-valued double-sideband direct detection(DD)can reconstruct the optical field and achieve a high electrical spectral efficiency(ESE)comparable to that of a coherent homodyne receiver,and DD does not require a costly local oscillator laser.However,a fundamental question remains if there is an optimal DD receiver structure with the simplest design to approach the performance of the coherent homodyne detection.This study derives the optimal DD receiver structure with an optimal transfer function to recover a quadrature amplitude modulation(QAM)signal with a near-zero guard band at the central frequency of the signal.We derive the theoretical ESE limit for various detection schemes by invoking Shannon’s formula.Our proposed scheme is closest to coherent homodyne detection in terms of the theoretical ESE limit.By leveraging a WaveShaper to construct the optimal transfer function,we conduct a proof-of-concept experiment to transmit a net 228.85-Gb/s 64-QAM signal over an 80-km single-mode fiber with a net ESE of 8.76 b/s/Hz.To the best of our knowledge,this study reports the highest net ESE per polarization per wavelength for DD transmission beyond 40-km single-mode fiber.For a comprehensive metric,denoted as 2ESE×Reach,we achieve the highest 2ESE×Reach per polarization per wavelength for DD transmission.展开更多
基金supported by the National Natural Science Foundation of China(Nos.62374142 and 22005255)Fundamental Research Funds for the Central Universities(Nos.20720220085 and 20720240064)+2 种基金External Cooperation Program of Fujian(No.2022I0004)Major Science and Technology Project of Xiamen in China(No.3502Z20191015)Xiamen Natural Science Foundation Youth Project(No.3502Z202471002)。
文摘Quantum dots(QDs),a type of nanoscale semiconductor material with unique optical and electrical properties like adjustable emission and high photoluminescence quantum yields,are suitable for applications in optoelectronics.However,QDs are typically degraded under humid and high-temperature circumstances,greatly limiting their practical value.Coating the QD surface with an inorganic silica layer is a feasible method for improving stability and endurance in a variety of applications.This paper comprehensively reviews silica coating methodologies on QD surfaces and explores their applications in optoelectronic domains.Firstly,the paper provides mainstream silica coating approaches,which can be divided into two categories:in-situ hydrolysis of silylating reagents on QD surfaces and template techniques for encapsulation QDs.Subsequently,the recent applications of the silica-coated QDs on optoelectronic fields including light-emitting diodes,solar cells,photodetectors were discussed.Finally,it reviews recent advances in silica-coated QD technology and prospects for future applications.
基金support received from National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIT)(RS-2024-00353768)the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIT)(RS-2025-02217919)+1 种基金funded by the Yonsei Fellowshipfunded by Lee Youn Jae and the KIST Institutional Program Project No.2E31603-22-140 (KJY).
文摘Ultra-thin crystalline silicon stands as a cornerstone material in the foundation of modern micro and nano electronics.Despite the proliferation of various materials including oxide-based,polymer-based,carbon-based,and two-dimensional(2D)materials,crystal silicon continues to maintain its stronghold,owing to its superior functionality,scalability,stability,reliability,and uniformity.Nonetheless,the inherent rigidity of the bulk silicon leads to incompatibility with soft tissues,hindering the utilization amid biomedical applications.Because of such issues,decades of research have enabled successful utilization of various techniques to precisely control the thickness and morphology of silicon layers at the scale of several nanometres.This review provides a comprehensive exploration on the features of ultra-thin single crystalline silicon as a semiconducting material,and its role especially among the frontier of advanced bioelectronics.Key processes that enable the transition of rigid silicon to flexible form factors are exhibited,in accordance with their chronological sequence.The inspected stages span both prior and subsequent to transferring the silicon membrane,categorized respectively as on-wafer manufacturing and rigid-to-soft integration.Extensive guidelines to unlock the full potential of flexible electronics are provided through ordered analysis of each manufacturing procedure,the latest findings of biomedical applications,along with practical perspectives for researchers and manufacturers.
基金supported by the National Key Research and Development Program of China(2021YFC2500803)the CAMS Innovation Fund for Medical Sciences(2021-I2M-1-056).
文摘BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to fi nd a light-weight,convenient prediction method through machine learning.METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation.RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the fi ve most important features were acuity,arrival transportation,age,shock index,and respiratory rate.CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.
基金National Natural Science Foundation of China,Grant/Award Number:22172063Young Taishan Scholars Program,Grant/Award Number:tsqn201812080+1 种基金China Scholarship Council(CSC),Grant/Award Number:202008130132Independent Cultivation Program of Innovation Team of Ji'nan City,Grant/Award Number:2021GXRC052。
文摘Electrocatalytic water splitting has been identified as a potential candidate for producing clean hydrogen energy with zero carbon emission.However,the sluggish kinetics of oxygen evolution reaction on the anode side of the watersplitting device significantly hinders its practical applications.Generally,the efficiency of oxygen evolution processes depends greatly on the availability of cost‐effective catalysts with high activity and selectivity.In recent years,extensive theoretical and experimental studies have demonstrated that cobalt(Co)‐based nanomaterials,especially low‐dimensional Co‐based nanomaterials with a huge specific surface area and abundant unsaturated active sites,have emerged as versatile electrocatalysts for oxygen evolution reactions,and thus,great progress has been made in the rational design and synthesis of Co‐based nanomaterials for electrocatalytic oxygen evolution reactions.Considering the remarkable progress in this area,in this timely review,we highlight the most recent developments in Co‐based nanomaterials relating to their dimensional control,defect regulation(conductivity),electronic structure regulation,and so forth.Furthermore,a brief conclusion about recent progress achieved in oxygen evolution on Co‐based nanomaterials,as well as an outlook on future research challenges,is given.
基金the financial support from the National Key Research and Development Program of China(No.2023YFB3907001)the National Natural Science Foundation of China(Nos.U2233217,62371029)the UK Engineering and Physical Sciences Research Council(EPSRC),China(Nos.EP/M026981/1,EP/T021063/1 and EP/T024917/)。
文摘Interference significantly impacts the performance of the Global Navigation Satellite Systems(GNSS),highlighting the need for advanced interference localization technology to bolster anti-interference and defense capabilities.The Uniform Circular Array(UCA)enables concurrent estimation of the Direction of Arrival(DOA)in both azimuth and elevation.Given the paramount importance of stability and real-time performance in interference localization,this work proposes an innovative approach to reduce the complexity and increase the robustness of the DOA estimation.The proposed method reduces computational complexity by selecting a reduced number of array elements to reconstruct a non-uniform sparse array from a UCA.To ensure DOA estimation accuracy,minimizing the Cramér-Rao Bound(CRB)is the objective,and the Spatial Correlation Coefficient(SCC)is incorporated as a constraint to mitigate side-lobe.The optimization model is a quadratic fractional model,which is solved by Semi-Definite Relaxation(SDR).When the array has perturbations,the mathematical expressions for CRB and SCC are re-derived to enhance the robustness of the reconstructed array.Simulation and hardware experiments validate the effectiveness of the proposed method in estimating interference DOA,showing high robustness and reductions in hardware and computational costs associated with DOA estimation.
基金funded by the National Natural Science Foundation of China(Grant Nos.:82222068,82070423,82270348,and 82173779)the Innovation Team and Talents Cultivation Pro-gram of National Administration of Traditional Chinese Medicine,China(Grant No:ZYYCXTD-D-202206)+1 种基金Fujian Province Science and Technology Project,China(Grant Nos.:2021J01420479,2021J02058,2022J011374,and 2022J02057)Fundamental Research Funds for the Chinese Central Universities,China(Grant No.:20720230070).
文摘Insect-derived traditional Chinese medicine(TCM)constitutes an essential component of TCM,with the earliest records found in“52 Bingfang”(Prescriptions of fifty-two diseases,which is one of the earliest Chinese medical prescriptions).
文摘Blue carbon ecosystems,including mangroves,seagrasses,and salt marshes,play a crucial role in mitigating climate change by capturing and storing atmospheric CO_(2)at rates exceeding those of terrestrial forests.This study explores the potential of HCWs(Human-Controlled Wetlands)in the Italian Venice Lagoon as an underappreciated component of the global blue carbon pool.Using GEE(Google Earth Engine),we conducted a large-scale assessment of carbon sequestration in these wetlands,demonstrating its advantages over traditional in situ methods in addressing spatial variability.Our findings highlight the significance of below-water mud sediments as primary carbon reservoirs,with a TC(Total Carbon)content of 3.81%±0.94%and a stable storage function akin to peat,reinforced by high CEC(Cation Exchange Capacity).GEE analysis identified a redoximorphic zone at a depth of 20-30 cm,where microbial respiration shifts to anaerobic pathways,preventing carbon release and maintaining long-term sequestration.The study also evaluates key factors affecting remote sensing accuracy,including tidal variations,water depth,and sky cover.The strong correlation between field-measured and satellite-derived carbon parameters(R^(2)>0.85)confirms the reliability of our approach.Furthermore,we developed a GEE-based script for monitoring sediment bioturbation,leveraging Sentinel-1 SAR(Synthetic Aperture Radar)and Sentinel-2 optical data to quantify biological disturbances affecting carbon fluxes.Our results underscore the value of HCWs for carbon sequestration,reinforcing the need for targeted conservation strategies.The scalability and efficiency of remote sensing methodologies,particularly GEE,make them essential for the long-term monitoring of blue carbon ecosystems and the development of effective climate mitigation policies.
基金supported in part by the National Natural Science Foundation of China (NSFC) under Grants 62271310 and 62125108in part by the Fundamental Research Funds for the Central Universities of Chinain part by the NSFC under Grant 62431014
文摘Extremely large-scale array(XL-array)communications can significantly improve the transmission rate,spectral efficiency,and spatial resolution,and has great potential in next-generation mobile communication networks.A crucial problem in XLarray communications is to determine the boundary of applicable regions of the plane wave model(PWM)and spherical wave model(SWM).In this paper,we propose new PWM/SWM demarcations for XL-arrays from the viewpoint of channel gain and rank.Four sets of results are derived for four different array setups.First,an equi-power line is derived for a point-touniform linear array(ULA)scenario,where an inflection point is found at±π6 central incident angles.Second,an equi-power surface is derived for a point-touniform planar array(UPA)scenario,and it is proved that cos2(ϕ)cos2(φ)=12 is a dividing curve,where ϕ andφdenote the elevation and azimuth angles,respectively.Third,an accurate and explicit expression of the equi-rank surface is obtained for a ULA-to-ULA scenario.Finally,an approximated expression of the equirank surface is obtained for a ULA-to-UPA scenario.With the obtained closed-form expressions,the equirank surface for any antenna structure and any angle can be well estimated.Furthermore,the effect of scatterers is also investigated,from which some insights are drawn.
基金co-supported by the National Natural Science Foundation of China(No.12374431)。
文摘To address the significant degradation of Space-Time Adaptive Processing(STAP)performance when the array elements have mutual coupling and gain/phase errors,a STAP algorithm with adaptive calibration for the above two array errors is proposed in this article.First,based on a defined error matrix that simultaneously considers both array mutual coupling and gain/phase errors,a STAP signal model including these errors is given.Then,utilizing the defined signal model,it is demonstrated that the estimation of the defined error matrix can be formulized as a standard convex optimization problem with the low-rank structure of the clutter covariance matrix and the subspace projection theory.Once the defined error matrix is estimated by solving the convex optimization problem,it is illustrated that a STAP method with adaptive calibration of the mutual coupling and gain/phase errors is coined.Analyses also show that the proposed adaptive calibration algorithm only needs one training sample to construct the adaptive weight vector.Therefore,it can achieve a good detection performance even with severe non-homogeneous clutter environments.Finally,the simulation experiments verify the effectiveness of the proposed algorithm and the correctness of the analytical results.
文摘Inverse Synthetic Aperture Radar(ISAR)images of complex targets have a low Signal-to-Noise Ratio(SNR)and contain fuzzy edges and large differences in scattering intensity,which limits the recognition performance of ISAR systems.Also,data scarcity poses a greater challenge to the accurate recognition of components.To address the issues of component recognition in complex ISAR targets,this paper adopts semantic segmentation and proposes a few-shot semantic segmentation framework fusing multimodal features.The scarcity of available data is mitigated by using a two-branch scattering feature encoding structure.Then,the high-resolution features are obtained by fusing the ISAR image texture features and scattering quantization information of complex-valued echoes,thereby achieving significantly higher structural adaptability.Meanwhile,the scattering trait enhancement module and the statistical quantification module are designed.The edge texture is enhanced based on the scatter quantization property,which alleviates the segmentation challenge of edge blurring under low SNR conditions.The coupling of query/support samples is enhanced through four-dimensional convolution.Additionally,to overcome fusion challenges caused by information differences,multimodal feature fusion is guided by equilibrium comprehension loss.In this way,the performance potential of the fusion framework is fully unleashed,and the decision risk is effectively reduced.Experiments demonstrate the great advantages of the proposed framework in multimodal feature fusion,and it still exhibits great component segmentation capability under low SNR/edge blurring conditions.
基金upported by the National Natural Science Foundation of China(Grant No.62274138)the Natural Science Foundation of Fujian Province of China(Grant No.2023J06012)+2 种基金the Science and Technology Plan Project in Fujian Province of China(Grant No.2021H0011)the Funda-mental Research Funds for the Central Universities(Grant No.20720230029)the Compound Semiconductor Technology Collaborative Innovation Platform Project of FuXiaQuan National Independent Innovation Demonstration Zone(Grant No.3502ZCQXT2022005).
文摘In recent years,artificial intelligence(AI)has demonstrated immense potential in driving breakthroughs in the semiconductor industry,particularly in full-color display technologies.Benefiting from the deep integration of AI,these technologies are experiencing unprecedented innovation and industrial transformation,garnering significant attention.These advancements provide a solid foundation for displays with higher color gamut and resolution.In addition,the integration of deep learning with dimming technologies has enabled new display systems to deliver superior viewing experiences with reduced energy consumption.This review highlights recent progress in four key areas of AI application in full-color display technologies:epitaxial structure design,defect detection and repair,perovskite synthesis,and dynamic dimming.AI-driven advancements in these domains are paving the way for smarter,more efficient display technologies.By leveraging AI’s powerful data processing and optimization capabilities,full-color display systems are poised to achieve enhanced performance,energy efficiency,and user satisfaction,marking a significant step toward a more intelligent and innovative future.
基金Core Research Institute Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2018R1A6A1A03025242)in part by the research grant of Kwangwoon University in 2024。
文摘Advanced OER/HER electrocatalytic alternatives are crucial for the wide adaptation of green hydrogen energy.Herein,Ru/NiMnB spherical cluster pillar(SCP),denoted as Ru/NiMnB,is synthesized using a combination of electro-deposition and hydrothermal reaction.Systematic investigation of Ru doping in the NiMnB matrix revealed significant improvements in electrocatalytic performance.The Ru/NiMnB SCPs demonstrate superior OER/HER activity with low overpotentials of 150 and 103 mV at 50mA/cm^(2)in 1 M KOH,making them highly competitive with state-of-the-art electrocatalysts.Remarkably,the Ru/NiMnB SCPs exhibit a low 2-E cell voltage of 2.80 V at ultra-high current density of 2,000 m A/cm^(2)in 1 M KOH,outperforming the standard benchmark electrodes of RuO_(2)||Pt/C,thereby positioning Ru/NiMnB as one of the best bifunctional electrocatalysts.These SCPs exhibit exceptional high-current characteristics,stability and corrosion resistance,as evidenced by continuous operation at 1,000 mA/cm^(2)high-current density for over 150 h in 6 M KOH at elevated temperatures under harsh industrial conditions.Only a small amount of Ru incorporation significantly enhances the electrocatalytic performances of NiMnB,attributed to increased active sites and improved intrinsic properties such as conductivity,adsorption/desorption capability and reaction rates.Consequently,Ru/NiMnB SCPs present a promising bi-functional electrode concept for efficient green H_(2)production.
基金supported by the National Natural Science Foundation of China(Grant Nos.62061028 and 62461035)the Key Project of Natural Science Foundation of Jiangxi Province(Grant No.20232ACB202003)+2 种基金the Finance Science and Technology Special“contract system”Project of Nanchang University Jiangxi Province(Grant No.ZBG20230418015)the Natural Science Foundation of Chongqing(Grant No.CSTB2024NSCQ-MSX0412)the Opening Project of Shanghai Key Laboratory of Special Artificial Microstructure Materials and Technology(Grant No.ammt2021A-4).
文摘We theoretically investigate a cooling scheme assisted by a quantum well(QW)and coherent feedback within a hybrid optomechanical system.Although the exciton mode in the QW and the mechanical resonator(MR)are initially uncoupled,their interaction via the microcavity field leads to an indirect exciton-mode–mechanical-mode coupling.The coherent feedback loop is applied by feeding back a fraction of the output field of the cavity through a controllable beam splitter to the cavity’s input mirror.It is shown that the cooling capability is enhanced by effectively suppressing the Stokes process through coupling with the QW.Furthermore,the effect of the anti-Stokes process is enhanced through the application of the coherent feedback loop.This particular system configuration enables cooling of the mechanical resonator even in the unresolved sideband regime(USR).This study has some important guiding significance in the field of quantum information processing.
基金supported by the National Natural Science Foundation of China(grant number:22274050)the Shanghai Science and Technology Commission(contract number:23J21900300)the Fundamental Research Funds for the Central Universities.
文摘Enhancing the sensitivity of nuclear magnetic resonance(NMR)technology has been the focus of NMR research for decades,which offers the potential to significantly expand its applications in chemistry,biology,and medical imaging.Parahydrogen-induced polarization(PHIP)emerges as a cost-effective approach to substantially enhance the sensitivity of NMR.Nevertheless,the amplification of the ^(1)H signal in PHIP is susceptible to interference from the thermal polarization state ^(1)H NMR signal.Employing RASER(radiofrequency amplification by stimulated emission of radiation)proves effective in mitigating such interference,which can reduce the linewidth and increase the sensitivity at the same time.In this work,we utilized PHIP and RASER to enhance the signal-to-noise ratio(SNR)of a series of biocompatible alkynyl organic acid molecules.The alkynyl acid with the highest enhancement factor was first identified through PASADENA(parahydrogen and synthesis allow dramatically enhanced nuclear alignment)experiments.Subsequently,RASER experiments were carried out through hyperpolarization of 5-hexynoic acid,exploring its signal characteristics under varying flow rates and pressures.The SNR of proton signals of 5-hexynoic acid surpassed 150,000,an 18.62-fold improvement compared with traditional hyperpolarized signals in PASADENA,and a markedly narrowed linewidth of 0.06 Hz.
基金supported in part by the National Natural Science Foundation of China under Grants NO.61971161 and 62171151in part by the Foundation of Heilongjiang Touyan Team under Grant NO.HITTY-20190009+3 种基金and in part by the Fundamental Research Funds for the Central Universities under Grant NO.HIT.OCEF.2021012supported in part by the Natural Science Foundation of China under Grant NO.62171160in part by the Fundamental Research Funds for the Central Universities under Grant NO.HIT.OCEF.2022055in part by the Shenzhen Science and Technology Program under Grants NO.JCYJ20190806143212658 and ZDSYS20210623091808025.
文摘Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance in multiple-input multipleoutput(MIMO)scenario with antenna selection(AS)scheme.We first derive the analytical expressions of average secrecy capacity(ASC)and secrecy outage probability(SOP)by the first order Marcum Q function.Then,the asymptotic expressions of ASC and SOP in two specific scenarios are further derived.The correctness of analytical and asymptotic expressions is verified by Monte Carlo simulations.The conclusions suggest that the analytical expressions of ASC and SOP are related to the product of transmitting and receiving antennas;increasing the number of antennas is beneficial to ASC and SOP.Besides,when the target rate is set at a low level,strong channel correlation is bad for ASC,but is beneficial to SOP.
基金The National Natural Science Foundation of China under contract Nos T2421002, 623B2071,and 42125601the National Key R&D Program of China under contract No. 2023YFF0805300
文摘Oceanic dissolved oxygen(DO)in the ocean has an indispensable role on supporting biological respiration,maintaining ecological balance and promoting nutrient cycling.According to existing research,the total DO has declined by 2%of the total over the past 50 a,and the tropical Pacific Ocean occupied the largest oxygen minimum zone(OMZ)areas.However,the sparse observation data is limited to understanding the dynamic variation and trend of ocean using traditional interpolation methods.In this study,we applied different machine learning algorithms to fit regression models between measured DO,ocean reanalysis physical variables,and spatiotemporal variables.We demonstrate that extreme gradient boosting(XGBoost)model has the best performance,hereby reconstructing a four-dimensional DO dataset of the tropical Pacific Ocean from 1920 to 2023.The results reveal that XGBoost significantly improves the reconstruction performance in the tropical Pacific Ocean,with a 35.3%reduction in root mean-squared error and a 39.5%decrease in mean absolute error.Additionally,we compare the results with three Coupled Model Intercomparison Project Phase 6(CMIP6)models data to confirm the high accuracy of the 4-dimensional reconstruction.Overall,the OMZ mainly dominates the eastern tropical Pacific Ocean,with a slow expansion.This study used XGBoost to efficiently reconstructing 4-dimensional DO enhancing the understanding of the hypoxic expansion in the tropical Pacific Ocean and we foresee that this approach would be extended to reconstruct more ocean elements.
基金Project supported by the National Research Foundation of Korea Grant funded by the Korean government(MSIP)(2018R1A6A1A03025708)。
文摘A new class of phosphor samples,denoted as Ba_(1-x)Al_(2)Ge_(2)O_(8):xEu^(2+)(BAGO:xEu^(2+))was synthesized using a Pechini-type sol-gel technique and subsequent thermal reduction in CO atmosphere.The morphology and structural characteristics of both the BAGO host lattice and the Eu^(2+)ions activated BAGO phosphors were investigated through field-emission scanning electron microscopy and X-ray diffractometry analyses,respectively.The BAGO host lattice has micro-sized particles and the Rietveld refinement reveals the presence of a monoclinic crystal phase,characterized by the space group I2/c(No.15).Introducing Eu^(2+)ions into Ba^(2+)sites under CO condition reduces the particle size,switching from microscale to nanoscale.Within the near-ultraviolet spectrum(353 nm),the BAGO:xEu^(2+)phosphors exhibit a broadband bluish-green photoluminescence(PL)emission characterized by a peak band at 492 nm.This phenomenon is attributed to the 4f^(6)5d^(1)→4f^(7) electronic transition.The BAGO:0.02Eu^(2+)phosphor shows the strongest bluish-green PL emission,and a co mprehensive description of the concentration quenching mechanism between Eu^(2+)ions is revealed.Additionally,the thermal stability of the optimized BAGO:0.02Eu^(2+)phosphor was investigated,and its activation energy was estimated.Therefore,the synthesized bluish-green BAGO:0.02Eu^(2+)phosphor holds the promise of being a novel and potential candidate for utilization in white light-emitting diode applications.
基金supported by the National Key Research and Development Program of China under Grant 2018YFA0701601by the Program of Jiangsu Province under Grant NTACT-2024-Z-001.
文摘In offshore maritime communication sys-tems,base stations(BSs)are employed along the coastline to provide high-speed data service for ves-sels in coastal sea areas.To ensure the line-of-sight propagation of BS-vessel links,high transceiver an-tenna height is required,which limits the number of geographically available sites for BS deployment,and imposes a high cost for realizing effective wide-area coverage.In this paper,the joint user association and power allocation(JUAPA)problem is investigated to enhance the coverage of offshore maritime systems.By exploiting the characteristics of network topology as well as vessels’motion in offshore communica-tions,a multi-period JUAPA problem is formulated to maximize the number of ships that can be simultane-ously served by the network.This JUAPA problem is intrinsically non-convex and subject to mixed-integer constraints,which is difficult to solve either analyt-ically or numerically.Hence,we propose an iterative augmentation based framework to efficiently select the active vessels,where the JUAPA scheme is iteratively optimized by the network for increasing the number of the selected vessels.More specifically,in each itera-tion,the user association variables and power alloca-tion variables are determined by solving two separate subproblems,so that the JUAPA strategy can be up-dated in a low-complexity manner.The performance of the proposed JUAPA method is evaluated by exten-sive simulation,and numerical results indicate that it can effectively increase the number of vessels served by the network,and thus enhances the coverage of off-shore systems.
基金supported by the National Natural Science Foundation of China(62122064,62331021,62371410)the Natural Science Foundation of Fujian Province of China(2023J02005 and 2021J011184)+1 种基金the President Fund of Xiamen University(20720220063)the Nanqiang Outstanding Talents Program of Xiamen University.
文摘Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.
基金supported by the National Natural Science Foundation of China(62341508).
文摘Complex-valued double-sideband direct detection(DD)can reconstruct the optical field and achieve a high electrical spectral efficiency(ESE)comparable to that of a coherent homodyne receiver,and DD does not require a costly local oscillator laser.However,a fundamental question remains if there is an optimal DD receiver structure with the simplest design to approach the performance of the coherent homodyne detection.This study derives the optimal DD receiver structure with an optimal transfer function to recover a quadrature amplitude modulation(QAM)signal with a near-zero guard band at the central frequency of the signal.We derive the theoretical ESE limit for various detection schemes by invoking Shannon’s formula.Our proposed scheme is closest to coherent homodyne detection in terms of the theoretical ESE limit.By leveraging a WaveShaper to construct the optimal transfer function,we conduct a proof-of-concept experiment to transmit a net 228.85-Gb/s 64-QAM signal over an 80-km single-mode fiber with a net ESE of 8.76 b/s/Hz.To the best of our knowledge,this study reports the highest net ESE per polarization per wavelength for DD transmission beyond 40-km single-mode fiber.For a comprehensive metric,denoted as 2ESE×Reach,we achieve the highest 2ESE×Reach per polarization per wavelength for DD transmission.
