基于灰度均值的自适应FAST角点检测优化算法

光照不均、突变引起的灰度变化会影响图像特征检测效果。为此,设计一种基于灰度均值的自适应FAST-9-12角点检测算法。首先,利用特征点的延展性设计一种小面积双重检测模板,减少像素点与中心点的比较次数,提高区域正检率和检测速度;其次,依据图像局部灰度均值,在每个像素点检测模板内自适应调整阈值,避免灰度变化影响检测效果;最后,根据柔性非极大值抑制的思想设计角点半径抑制原则,筛选鲁棒性更强的角点。在Inria遥感影像数据集上的实验结果表明,FAST-9-12角点检测速度比FAST-12-16,FAST-9-16两种模板提高22%左右,因自适应阈值的提取方式不易受光照影响,检测准确率分别提高4.16和3.11个百分点,实现了图像特征快速和精准检测。

基于Kano-FAST的瓦楞纸激光印刷设备设计研究

目的推动印刷行业朝更高效的方向迈进,提高印刷设备的易操作性和视觉识别性。方法将Kano和FAST(Function Analysis System Technique)模型引入瓦楞纸激光打印设备设计的前期应用需求分析中,通过问卷的方法获取用户的基本要求,并划分为几个子类型,进而建立Kano的二维功能属性模型。采用FAST法建立功能树,辅助使用Kano模型,从而更精准地分析用户需求,并更好地根据其需求进行优化设计。结果综合运用设计原理,针对性地挖掘瓦楞纸激光印刷设备在造型识别性、操作易用性、生产安全性上存在的问题,进而输出更优解。结论该设计方法的引入有助于为同类型的印刷设备设计提供参考,并引起更多相关厂家的重视,推动印刷行业向更积极的方向发展。

500m口径射电望远镜(FAST)索网结构风致破坏概率评估

大跨空间索网结构风敏感性突出,极易遭受风荷载影响。针对目前缺乏此类结构抗风性能评估方法的问题,以大跨空间索网结构FAST为例,提出一种基于实测风场数据的风致破坏概率分析方法。采集1971年~2020年结构所处地区的大量实测风速数据,通过概率分布拟合建立场地的风灾危险性模型。建立FAST的精细化有限元分析模型并模拟风荷载时程输入,采用非线性动力时程分析对结构的风振反应进行计算,基于概率性需求模型绘制易损性曲线。最后,结合得出的风灾危险性和结构易损性,计算得出FAST结构在所处场地实际风灾环境中的破坏概率。研究表明:该地极限风速为17m/s,风速在0~10m/s的概率最大;在120°、210°和300°风向角下,下拉索均为易损构件,210°风向角上吸风对索网结构最不利;在最不利风向角下,结构达到轻微破坏、中等破坏和严重破坏的总破坏概率分别为1.8359×10^(-4)、1.1499×10^(-5)和1.3202×10^(-6)。

面向FAST的卫星电磁干扰监测技术研究与实现

来自人造卫星的信号是射电天文观测面临的主要射频干扰(radio frequency interference,RFI)之一,这些RFI会将天文信号掩埋,为天文信号的搜寻和分析带来困扰。为了缓减卫星对天文观测的影响,我们在之前的工作中为500 m口径球面射电望远镜(Five-hundred-meter Aperture Spherical radio Telescope,FAST)开发了卫星电磁干扰监测软件,主要包括卫星数据库、观测模块和监测模块。近年来随着多个巨型卫星星座的规划发射以及望远镜观测模式的增多,卫星对射电天文观测的影响更为复杂,已有的软件已经不能满足实际的需要。为此,本文在单个卫星干扰分析的基础上提出了卫星星座的干扰评估方法,并对已有监测软件进行了升级,升级后卫星数据库覆盖更多的在轨卫星及星座信息且能够自动化更新,观测模块能够支持更多种观测模式下的卫星过境预测和干扰评估。在实际天文观测中,通过接在FAST接收机上的频谱仪数据对软件的干扰预测结果进行了实验验证,结果证明升级后的软件能够在多种观测模式下预测可能威胁的卫星以及对应的过境时间,为望远镜观测规划的调整、卫星干扰的规避和接收系统的保护提供重要的支撑。

基于BP神经网络的FAST馈源舱融合测量预测研究

500 m口径球面射电望远镜(Five-hundred-meter Aperture Spherical Radio Telescope,FAST)的跟踪观测需要馈源的空间运动配合,馈源舱主要用于实现馈源的精调定位,因此馈源舱位置的高精度测量对FAST望远镜的高效运行意义重大。但当全站仪设备失效时,无法对采用Kalman算法的GPS/IMU融合测量结果进行修正,导致馈源舱测量精度下降。为了解决这个问题,设计了基于BP(back propagation)神经网络的预测模型,包括数据预处理、模型设计和模型训练验证。模型训练数据为FAST真实测量数据,数据量为40 GB左右。为了验证模型的泛化能力,选取三种运动轨迹数据对模型预测精度进行测试,结果显示,三种运动轨迹下精度都满足15 mm要求。

Unraveling the Fundamental Mechanism of Interface Conductive Network Influence on the Fast‑Charging Performance of SiO‑Based Anode for Lithium‑Ion Batteries

Progress in the fast charging of high-capacity silicon monoxide(SiO)-based anode is currently hindered by insufficient conductivity and notable volume expansion.The construction of an interface conductive network effectively addresses the aforementioned problems;however,the impact of its quality on lithium-ion transfer and structure durability is yet to be explored.Herein,the influence of an interface conductive network on ionic transport and mechanical stability under fast charging is explored for the first time.2D modeling simulation and Cryo-transmission electron microscopy precisely reveal the mitigation of interface polarization owing to a higher fraction of conductive inorganic species formation in bilayer solid electrolyte interphase is mainly responsible for a linear decrease in ionic diffusion energy barrier.Furthermore,atomic force microscopy and Raman shift exhibit substantial stress dissipation generated by a complete conductive network,which is critical to the linear reduction of electrode residual stress.This study provides insights into the rational design of optimized interface SiO-based anodes with reinforced fast-charging performance.

Dual-single-atoms of Pt-Co boost sulfur redox kinetics for ultrafast Li-S batteries

Applications of lithium-sulfur(Li-S)batteries are still limited by the sluggish conversion kinetics from polysulfide to Li_(2)S.Although various single-atom catalysts are available for improving the conversion kinetics,the sulfur redox kinetics for Li-S batteries is still not ultrafast.Herein,in this work,a catalyst with dual-single-atom Pt-Co embedded in N-doped carbon nanotubes(Pt&Co@NCNT)was proposed by the atomic layer deposition method to suppress the shuttle effect and synergistically improve the interconversion kinetics from polysulfides to Li_(2)S.The X-ray absorption near edge curves indicated the reversible conversion of Li_(2)Sx on the S/Pt&Co@NCNT electrode.Meanwhile,density functional theory demonstrated that the Pt&Co@NCNT promoted the free energy of the phase transition of sulfur species and reduced the oxidative decomposition energy of Li_(2)S.As a result,the batteries assembled with S/Pt&Co@NCNT electrodes exhibited a high capacity retention of 80%at 100 cycles at a current density of 1.3 mA cm^(−2)(S loading:2.5 mg cm^(−2)).More importantly,an excellent rate performance was achieved with a high capacity of 822.1 mAh g^(−1) at a high current density of 12.7 mA cm^(−2).This work opens a new direction to boost the sulfur redox kinetics for ultrafast Li-S batteries.

Multilevel carbon architecture of subnanoscopic silicon for fast‐charging high‐energy‐density lithium‐ion batteries

Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and poor fast‐charging capability limiting its commercial applications.Here,we propose a multilevel carbon architecture with vertical graphene sheets(VGSs)grown on surfaces of subnanoscopically and homogeneously dispersed Si–C composite nanospheres,which are subsequently embedded into a carbon matrix(C/VGSs@Si–C).Subnanoscopic C in the Si–C nanospheres,VGSs,and carbon matrix form a three‐dimensional conductive and robust network,which significantly improves the conductivity and suppresses the volume expansion of Si,thereby boosting charge transport and improving electrode stability.The VGSs with vast exposed edges considerably increase the contact area with the carbon matrix and supply directional transport channels through the entire material,which boosts charge transport.The carbon matrix encapsulates VGSs@Si–C to decrease the specific surface area and increase tap density,thus yielding high first Coulombic efficiency and electrode compaction density.Consequently,C/VGSs@Si–C delivers excellent Li‐ion storage performances under industrial electrode conditions.In particular,the full cells show high energy densities of 603.5 Wh kg^(−1)and 1685.5 Wh L^(−1)at 0.1 C and maintain 80.7%of the energy density at 3 C.

基于Kano-FAST-FBS的智能扫地机改良设计研究

目的智能扫地机是智能家居生活中不可或缺的产品,但现有扫地机交互性和功能性趋于一致,为了有效识别居家清扫需求,进一步提升交互性和趣味性,并将其科学转化为产品的功能要素及结构参数,提出一种基于Kano-FAST-FBS模型的产品改良设计方法,以提升智能家居产品的满意度。方法首先,基于Kano模型量化评估智能家居产品的用户需求属性,获得用户需求优先级;其次,运用功能分析系统技术(FAST)将用户需求分别转化为对应的产品功能要素;最后,以功能-行为-结构(FBS)设计模型为基础,实现了产品功能到结构参数的合理映射,进而得到改良产品的各个结构模块,输出最终设计方案。结果以扫地机器人为例,验证了基于Kano-FAST-FBS模型的设计流程。结论在该方法指导下的产品设计能系统地解决用户需求和功能结构模块之间的匹配问题,从而得出更符合用户功能预期的设计方案,并可以为其他类似产品设计提供参考思路。

FAST所受PMT基站电磁干扰及用频防护方法综述

为确定500 m口径球面射电望远镜(Five-hundred-meter Aperture Spherical radio Telescope,FAST)与其周边公众移动通信(Public Mobile Telecommunications,PMT)系统的电磁兼容(electromagnetic compatibility,EMC)特性,本文综合论述了FAST宁静区内中国移动、中国联通和中国电信三大运营商所属PMT基站对其产生的电磁干扰。首先,从射电天文业务的频谱划分谈起,论述了射电天文业务干扰源类型,引出了其运行保护标准,进而针对FAST详细说明了FAST宁静区的用频法规和保护要求;其次,分析了ITU-R建议电波传播预测与干扰分析方法,并通过实地测量验证了该方法的适用性,进一步针对性地分析了PMT基站的电磁辐射传播特性,综合评估了FAST宁静区内PMT基站的干扰情况:FAST宁静区域90.24%的PMT基站在一定程度上均会对FAST产生干扰,而在所选分析条件下,仅有43.14%的数据符合FAST保护要求;最后,针对PMT基站干扰信号的抑制和消除,分析了常用的射电天文射频干扰抑制方法,同时为保障FAST免受PMT基站干扰,从FAST和PMT基站的角度出发论述了可行的用频防护措施,并基于实施难度、经济成本、策略收益和通信质量4类指标建立了防护方法的评估体系,对所提防护方法进行了实例说明。上述研究成果可为保障FAST的安全观测提供技术基础。

基于FAST评分的分级管理模式在急性脑卒中患者急救中的应用

目的:探讨基于FAST评分的分级管理模式在急性脑卒中患者急救中的应用效果。方法:选取2022年1月1日~12月31日收治的126例急性脑卒中患者为研究对象,随机分为对照组和研究组各63例,对照组给予常规急救管理模式,研究组给予基于FAST评分的分级管理模式;比较两组救治时间(包括就诊至评估时间、就诊至接诊时间、就诊至CT检查时间、CT检查至用药时间)、干预前后上下肢Fugl-Meyer评分、神经功能[采用美国国立卫生院卒中量表(NIHSS)]、日常生活活动能力(采用Barthel指数),不良事件发生情况和护理满意度。结果:研究组就诊至评估时间、就诊至接诊时间、就诊至CT检查时间、CT检查至用药时间均短于对照组(P<0.05);干预后,两组上下肢Fugl-Meyer评分、Barthel指数均高于干预前(P<0.05),且研究组高于对照组(P<0.05);干预后,两组NIHSS评分低于干预前(P<0.05),且研究组低于对照组(P<0.05);研究组不良事件发生率低于对照组(P<0.05),护理满意度高于对照组(P<0.05)。结论:将基于FAST评分的分级管理模式应用于急性脑卒中患者急救中,可提高日常生活能力及护理满意度,恢复肢体运动能力、神经功能,减少不良事件的发生。

基于动物创伤模型试验培训FAST超声技术在急诊本科实习生中的应用研究

目的评价基于动物创伤模型试验培训创伤超声重点评估法(FAST)超声技术在急诊本科实习生临床技能培训中的应用效果。方法选取我院2022年1月至2024年3月在我院急诊科的本科实习生65名作为研究对象,随机分为对照组和实验组。对照组采用传统教学方法,实验组按照动物创伤模型教学模式实施教学,比较两组本科实习生出科理论及操作成绩、学习满意度、学习能力和学习行为。结果两组实习生的理论及操作成绩均较培训前有所提高,实验组实习生的理论及操作成绩均明显高于对照组,差异均有统计学意义(均P<0.05)。两组实习生培训后的学习满意度均有所提高,实验组实习生的学习满意度得分明显高于对照组,差异均有统计学意义(均P<0.05)。两组实习生培训后的学习能力得分和学习行为得分均有所提高,实验组得分均明显高于对照组,差异均有统计学意义(均P<0.05)。结论基于动物创伤模型试验培训FAST超声技术能有效提高急诊本科实习生的学习成绩和学习满意度,学习能力明显提高,对提高本科实习生的成长与急诊诊疗水平具有积极意义。

Early identification of stroke through deep learning with multi-modal human speech and movement data

Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

The principle and amelioration of lithium plating in fast-charging lithium-ion batteries

Fast charging is restricted primarily by the risk of lithium(Li)plating,a side reaction that can lead to the rapid capacity decay and dendrite-induced thermal runaway of lithium-ion batteries(LIBs).Investigation on the intrinsic mechanism and the position of Li plating is crucial to improving the fast rechargeability and safety of LIBs.Herein,we investigate the Li plating behavior in porous electrodes under the restricted transport of Li^(+).Based on the theoretical model,it can be concluded that the Li plating on the anodeseparator interface(ASI)is thermodynamically feasible and kinetically advantageous.Meanwhile,the prior deposition of metal Li on the ASI rather than the anode-current collector interface(ACI)is verified experimentally.In order to facilitate the transfer of Li^(+)among the electrode and improve the utilization of active materials without Li plating,a bilayer asymmetric anode composed of graphite and hard carbon(GH)is proposed.Experimental and simulation results suggest that the GH hybrid electrode homogenizes the lithiated-rate throughout the electrode and outperforms the pure graphite electrode in terms of the rate performance and inhibition of Li plating.This work provides new insights into the behavior of Li plating and the rational design of electrode structure.

A review of salivary composition changes induced by fasting and its impact on health

Human saliva is an indispensable fluid that maintains a healthy oral cavity which otherwise can lead to oral diseases(dental caries and periodontitis).In addition,salivary metabolites and microbiome profile provide early detection of systemic diseases such as cancer and obesity.Salivary diagnostic has gained popularity due to its non-invasive sampling technique.Fasting(abstinence from food or drink or both)research for weight loss and improve health is common,but studies using fasting saliva are scarce.Some metabolites in fasting saliva have been reported with interesting results,which can be enhanced by considering different confounding factors.For example,fasting saliva contains higher salivary nitrite,which is related to nitric oxide(NO).NO is a vasodilator supporting the healthy function of endothelial cells and its deficiency is connected to many diseases.The timely supply of NO through exogenous and endogenous means is highlighted and the potential advantage of fasting salivary composition changes in relation to COVID-19 infection is speculated.This review aims to provide a general discussion on the salivary composition,properties,and functions of the whole saliva,including the health benefits of fasting.

Observations of Fast Radio Variations in Microquasars by FAST

Microquasars are the compact objects generally including accreting black holes which produce relativistic jets.The physical mechanisms of jet launching,collimation,and acceleration are poorly understood.Microquasars show strong variability in multi-wavelength observations.In x-rays,the sources show the fast variation features down to millisecond time scales,with the prominent quasiperiodic oscillations(QPOs)around 0.1 Hz–tens of Hz in light curves,however,physical origin of QPOs is still uncertain.FAST as the largest radio telescope provides the opportunity to study fast variability of both radio flux and polarization in microquasars.In the FAST observations from 2020–2022,we reported the first evidence of radio subsecond quasi-periodic oscillations of GRS 1915+105,providing the direct link between QPOs and the dynamics of relativistic jets.These QPOs with the centroid frequency around 5 Hz are transient,accompanied with strong evolution of the spectral index.Combined with multiwavelength observations,we discuss the possible physical models to produce radio QPOs in BH systems:the helical motion of jet knots or precession of the jet base.In near future,high time resolution radio monitoring of microquasars based on FAST is expected to discover more new phenomena in black hole systems,which will be important for understanding the physics in strong gravity.

The effect of fasting plasma glucose on in-hospital mortality after acute myocardial infarction in patients with and without diabetes:findings from a prospective,nationwide,and multicenter registry

OBJECTIVES To evaluate the predictive value of fasting plasma glucose(FPG)for in-hospital mortality in patients with acute myocardial infarction(AMI)with different glucose metabolism status.METHODS We selected 5,308 participants with AMI from the prospective,nationwide,multicenter CAMI registry,of which 2,081 were diabetic and 3,227 were nondiabetic.Patients were divided into high FPG and low FPG groups according to the optim-al cutoff values of FPG to predict in-hospital mortality for diabetic and nondiabetic cohorts,respectively.The primary endpoint was in-hospital mortality.RESULTS Overall,94 diabetic patients(4.5%)and 131 nondiabetic patients(4.1%)died during hospitalization,and the optimal FPG thresholds for predicting in-hospital death of the two cohorts were 13.2 mmol/L and 6.4 mmol/L,respectively.Compared with individuals who had low FPG,those with high FPG were significantly associated with higher in-hospital mortality in diabet-ic cohort(10.1%vs.2.8%;odds ratio[OR]=3.862,95%confidence interval[CI]:2.542-5.869)and nondiabetic cohort(7.4%vs.1.7%;HR=4.542,95%CI:3.041-6.782).After adjusting the potential confounders,this significant association was not changed.Further-more,FPG as a continuous variable was positively associated with in-hospital mortality in single-variable and multivariable models regardless of diabetic status.Adding FPG to the original model showed a significant improvement in C-statistic and net reclassification in diabetic and nondiabetic cohorts.CONCLUSIONS This large-scale registry indicated that there is a strong positive association between FPG and in-hospital mor-tality in AMI patients with and without diabetes.FPG might be useful to stratify patients with AMI.

Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution

We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.

A fast forward computational method for nuclear measurement using volumetric detection constraints

Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sources,the detector response can reflect various types of information of the medium.The Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex environments.However,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response results.Therefore,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is proposed.First,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo simulation.Then,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion model.The environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection volume.Finally,the method is applied to a neutron porosity tool for verification.In various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 p.u.In field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method.

Research on fast detection method of infrared small targets under resourceconstrained conditions

Infrared small target detection is a common task in infrared image processing.Under limited computa⁃tional resources.Traditional methods for infrared small target detection face a trade-off between the detection rate and the accuracy.A fast infrared small target detection method tailored for resource-constrained conditions is pro⁃posed for the YOLOv5s model.This method introduces an additional small target detection head and replaces the original Intersection over Union(IoU)metric with Normalized Wasserstein Distance(NWD),while considering both the detection accuracy and the detection speed of infrared small targets.Experimental results demonstrate that the proposed algorithm achieves a maximum effective detection speed of 95 FPS on a 15 W TPU,while reach⁃ing a maximum effective detection accuracy of 91.9 AP@0.5,effectively improving the efficiency of infrared small target detection under resource-constrained conditions.