Rationally designing electrolyte additives for highly improving cyclability of LiNi_(0.5)Mn_(1.5)O_(4)/Graphite cells

High voltage is necessary for high energy lithium-ion batteries but difficult to achieve because of the highly deteriorated cyclability of the batteries.A novel strategy is developed to extend cyclability of a high voltage lithium-ion battery,LiNi_(0.5)Mn_(1.5)O_(4)/Graphite(LNMO/Graphite)cell,which emphasizes a rational design of an electrolyte additive that can effectively construct protective interphases on anode and cathode and highly eliminate the effect of hydrogen fluoride(HF).5-Trifluoromethylpyridine-trime thyl lithium borate(LTFMP-TMB),is synthesized,featuring with multi-functionalities.Its anion TFMPTMB-tends to be enriched on cathode and can be preferentially oxidized yielding TMB and radical TFMP-.Both TMB and radical TFMP can combine HF and thus eliminate the detrimental effect of HF on cathode,while the TMB dragged on cathode thus takes a preferential oxidation and constructs a protective cathode interphase.On the other hand,LTFMP-TMB is preferentially reduced on anode and constructs a protective anode interphase.Consequently,a small amount of LTFMP-TMB(0.2%)in 1.0 M LiPF6in EC/DEC/EMC(3/2/5,wt%)results in a highly improved cyclability of LNMO/Graphite cell,with the capacity retention enhanced from 52%to 80%after 150 cycles at 0.5 C between 3.5 and 4.8 V.The as-developed strategy provides a model of designing electrolyte additives for improving cyclability of high voltage batteries.

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

Multi-Elemental Analysis and 2D Image Mapping within Roots, Leaves and Seeds from O. glaberrima Rice Plants Using Micro-PIXE Technique

Understanding metal accumulation at organ level in roots, leaves and seeds in O. glaberrima (OG) is crucial for improving physiological and metabolic aspects in growing Asian and African rice in salted areas. The micro-analytical imaging techniques are required to reveal its accumulation and distribution within plant tissues. PIXE studies have been performed to determine different elements in rice plants. The existing microbeam analytical technique at the iThemba LABS will be applied for the 2D image mapping of fresh rice tissues to perform a concentration of low atomic mass elements (such as Al, Si, P, S, Cl, Ca, Ti, Mn, Fe, Cu, Br, Zn and K) with detection limits of typically 1-10 μg/g. Comparison of the distribution of the elements between leaves, root and seed samples using uptake and distribution of elements in particular environmental conditions with potential amount of salt in water have been performed. We are also expecting to indicate metal exclusion as salt tolerance strategies from leaves, root, and seed compartments using matrix correlation between samples and between elements on rice species.

Subsoil tillage enhances wheat productivity,soil organic carbon and available nutrient status in dryland fields

Tillage practices during the fallow period benefit water storage and yield in dryland wheat crops.However,there is currently no clarity on the responses of soil organic carbon(SOC),total nitrogen(TN),and available nutrients to tillage practices within the growing season.This study evaluated the effects of three tillage practices(NT,no tillage;SS,subsoil tillage;DT,deep tillage)over five years on soil physicochemical properties.Soil samples at harvest stage from the fifth year were analyzed to determine the soil aggregate and aggregate-associated C and N fractions.The results indicated that SS and DT improved grain yield,straw biomass and straw carbon return of wheat compared with NT.In contrast to DT and NT,SS favored SOC and TN concentrations and stocks by increasing the soil organic carbon sequestration rate(SOCSR)and soil nitrogen sequestration rate(TNSR)in the 0-40 cm layer.Higher SOC levels under SS and NT were associated with greater aggregate-associated C fractions,while TN was positively associated with soluble organic nitrogen(SON).Compared with DT,the NT and SS treatments improved soil available nutrients in the 0-20 cm layer.These findings suggest that SS is an excellent practice for increasing soil carbon,nitrogen and nutrient availability in dryland wheat fields in North China.

Dose-response effect of pre-exercise carbohydrates under muscle glycogen unavailability:Insights from McArdle disease

Background:This study aimed to determine the effect of different carbohydrate(CHO)doses on exercise capacity in patients with McArdle disease—the paradigm of“exercise intolerance”,characterized by complete muscle glycogen unavailability—and to determine whether higher exogenous glucose levels affect metabolic responses at the McArdle muscle cell(in vitro)level.Methods:Patients with McArdle disease(n=8)and healthy controls(n=9)underwent a 12-min submaximal cycling constant-load bout followed by a maximal ramp test 15 min after ingesting a non-caloric placebo.In a randomized,double-blinded,cross-over design,patients repeated the tests after consuming either 75 g or 150 g of CHO(glucose:fructose=2:1).Cardiorespiratory,biochemical,perceptual,and electromyographic(EMG)variables were assessed.Additionally,glucose uptake and lactate appearance were studied in vitro in wild-type and McArdle mouse myotubes cultured with increasing glucose concentrations(0.35,1.00,4.50,and 10.00 g/L).Results:Compared with controls,patients showed the“classical”second-wind phenomenon(after prior disproportionate tachycardia,myalgia,and excess electromyographic activity during submaximal exercise,all p<0.05)and an impaired endurance exercise capacity(-51%ventilatory threshold and55%peak power output,both p<0.001).Regardless of the CHO dose(p<0.05 for both doses compared with the placebo),CHO intake increased blood glucose and lactate levels,decreased fat oxidation rates,and attenuated the second wind in the patients.However,only the higher dose increased ventilatory threshold(+27%,p=0.010)and peak power output(+18%,p=0.007).In vitro analyses revealed no differences in lactate levels across glucose concentrations in wild-type myotubes,whereas a doseresponse effect was observed in McArdle myotubes.Conclusion:CHO intake exerts beneficial effects on exercise capacity in McArdle disease,a condition associated with total muscle glycogen unavailability.Some of these benefits are dose dependent.

改进DeepLabv3+模型无人机图像农田信息提取

自乡村振兴战略实施以来,无人机作为一种高科技工具为我国智慧农业生产发挥着重要作用。但存在信息提取的精准度不高的问题,特别是对农田边缘和小农田的信息提取精度不高。针对该问题,提出一种以GhostNet为骨干网络的改进DeepLabv3+模型的研究方法。该方法将从骨干网络中提取的特征通过特征金字塔网络(FPN)加强特征提取;将编码器中空洞空间金字塔池化模块(ASPP)的1×1卷积替换成空间感知独立自注意层并将ASPP模块中的扩张率进行一定调整,以提高农田边缘的提取精度;为进一步融合多尺度信息将解码器进行上述同样操作;在不降低模型性能的前提下,将特征堆叠(Concatenate)用特征融合(Add)进行替换,以减少模型的训练参数。实验结果表明,改进DeepLabv3+模型平均交并比(mIoU)可达94.57%,平均像素精度(mPA)可达97.16%,相比于DeepLabv3+模型分别提高了4.53%和2.93个百分点,有效提高了农田边缘和小农田的信息提取精度。

Optical Label-Based Cost-Effective DWDM Optical Network Performance Monitoring Using Low-Bandwidth PD with Novel SRS Mitigation DSP

Large-scale dense wavelength division multiplexing(DWDM)multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks.The existing Labelbased monitoring scheme requires expensive optical demultiplexing components/equipment to avoid the influence of stimulated Raman scattering(SRS),which is not only costly and bulky,but also could not monitor the wavelength channels simultaneously.In this paper,a low-cost,high-accuracy monitoring scheme based on Optical Label Method is proposed for DWDM networks,where the optical channel power and node identification(ID),as the main monitoring targets that both can indicate or evaluate the channel connection status,could be efficiently monitored.In the scheme,a novel digital signal processing(DSP)method of SRS mitigation is proposed and demonstrated,and an asynchronous code-division multiple access(A-CDMA)based digital label encoding and decoding method is adopted to distinguish the node ID so that channel initial added node can be accurately verified,thereby wavelength connection status can be reliably monitored by combining the channel power and node ID information.The simulation results show that each wavelength channel power and node ID can be accurately monitored only by low bandwidth photoelectric detector(PD)under the condition of 80 wavelengths and 10 spans at C-band.

基于LABS技术和FPGA的固态激光雷达测距系统

针对传统固态激光雷达中光束快速扫描控制响应速度和电压控制精度较低的问题,提出了一种基于透镜辅助光束扫描(LABS)技术和现场可编程逻辑门阵列(FPGA)的固态激光雷达测距系统。该系统采用收发一体的结构,系统中的LABS器件由1×16光开关芯片、4×4光纤阵列和透镜组成。根据LABS方案每一级只有一个光开关处于工作状态的特点,通过选择不同的发射器,将光束照亮到透镜的不同位置来实现光束的转向。光束扫描采用FPGA结合外部选通电路进行控制的方式,通过输出电压控制4级马赫-曾德尔干涉仪(MZI)型光开关工作,实现光束的快速切换。实验结果表明,该系统光束转向角度步长为0.35°,最大测距范围可达200 m,9.2 m内的测距误差约为1 cm。

4D label-free proteomic analysis of vitreous from patients with rhegmatogenous retinal detachment

AIM:To identify metabolites,proteins,and related pathways involved in the etiology of rhegmatogenous retinal detachment(RRD)for use as biomarkers in diagnosing and treating RRD.METHODS:Vitreous specimens were collected and liquid chromatography-tandem mass spectrometry analysis was per formed using the four-dimensional label-free technique.Statistically significant differentially expressed proteins,gene ontology(GO)terms,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway representations,and protein interactions were analyzed.RESULTS:Nine specimens were subjected to proteomic analysis.In total,161 proteins were identified as differentially expressed proteins(DEPs),including 53 upregulated proteins and 108 downregulated proteins.GO functional analysis revealed that some DEPs were enriched in neuron-related terms and membrane protein terms.Moreover,KEGG analysis indicated that the cell adhesion molecule metabolic pathway was associated with the greatest number of DEPs.Finally,the evaluation of protein-protein interaction network revealed that DEPs were clustered in neuronal adhesion,apoptosis,inflammation and immune responses,correct protein folding,and glycolysis.CONCLUSION:Proteomic profiling is useful for the exploration of molecular mechanisms that underlie RRD.This study reveals increased expression levels of proteins related to heat shock protein content,glycolysis,and inflammatory responses in RRD.Knowledge regarding biomarkers of RRD pathogenesis may help to prevent the occurrence of RRD in the future.

Controllably partial removal of thiolate ligands from unsupported Au_(25) nanoclusters by rapid thermal treatments for electrochemical CO_(2)reduction

Colloidal synthesis of metal nanoclusters will inevitably lead to the blockage of catalytically active sites by organic ligands.Here,taking[Au_(25)(PET)_(18)]-(PET=2-phenylethanethiol)nanocluster as a model catalyst,this work reports a feasible procedure to achieve the controllably partial removal of thiolate ligands from unsupported[Au_(25)(PET)_(18)]-nanoclusters with the preservation of the core structure.This procedure shortens the processing duration by rapid heating and cooling on the basis of traditional annealing treatment,avoiding the reconfiguration or agglomeration of Au_(25)nanoclusters,where the degree of dethiolation can be regulated by the control of duration.This work finds that a moderate degree of dethiolation can expose the Au active sites while maintaining the suppression of the competing hydrogen evolution reaction.Consequently,the activity and selectivity towards CO formation in electrochemical CO_(2)reduction reaction of Au_(25)nanoclusters can be promoted.This work provides a new approach for the removal of thiolate ligands from atomically precise gold nanoclusters.

ChatGPT的工作原理、关键技术及未来发展趋势

ChatGPT是自然语言处理领域的一项重要技术突破,专注于对话生成任务,在多种任务中表现出卓越的性能。主要探讨ChatGPT的演变历程、关键技术,并分析了其未来可能的发展方向。首先,介绍了ChatGPT的模型架构和技术演进过程。随后,重点讨论了ChatGPT的关键技术,包括提示学习与指令微调、思维链、人类反馈强化学习。然后,分析了由于基于概率生成原理所造成的固有局限,包括事实性错误、垂直领域深度性弱、潜在的恶意应用风险、可解释性及模型实时性差等。最后,探讨了其在典型应用中存在的问题和相应的解决途径,包括在训练评估过程中考虑道德和安全性因素,以降低潜在风险;结合外部专家知识和迁移学习,以提高模型对特定领域的理解能力,更好地适应特定任务场景;引入多模态数据,以提高模型信息理解能力,增强模型通用性和泛化性。通过对ChatGPT模型框架、技术演变与关键技术的分析,为深入理解ChatGPT提供帮助;结合原理分析其固有缺陷,并结合实际应用中存在的问题,挖掘未来可能的研究方向,为自然语言处理领域的深入研究提供有益参考。

Solvent engineering towards scalable fabrication of high-quality perovskite films for efficient solar modules

Over the last decade,remarkable progress has been made in metal halide perovskite solar cells(PSCs),which have been a focus of emerging photovoltaic techniques and show great potential for commercialization.However,the upscaling of small-area PSCs to large-area solar modules to meet the demands of practical applications remains a significant challenge.The scalable production of high-quality perovskite films by a simple,reproducible process is crucial for resolving this issue.Furthermore,the crystallization behavior in the solution-processed fabrication of perovskite films can be strongly influenced by the physicochemical properties of the precursor inks,which are significantly affected by the employed solvents and their interactions with the solutes.Thus,a comprehensive understanding of solvent engineering for fabricating perovskite films over large areas is urgently required.In this paper,we first analyze the role of solvents in the solution-processed fabrication of large-area perovskite films based on the classical crystal nucleation and growth mechanism.Recent efforts in solvent engineering to improve the quality of perovskite films for solar modules are discussed.Finally,the basic principles and future challenges of solvent system design for scalable fabrication of high-quality perovskite films for efficient solar modules are proposed.

Silicon Labs力助蓝牙定位技术多场景应用

随着蓝牙技术的普及,诸多行业都选择蓝牙而非传统的RF设备作为定位技术,并从中受益。蓝牙技术由蓝牙技术联盟(SIG)认证并提供标准化的无线技术解决方案,可在许多现有产品中轻松获得。因此,许多企业都在大力投资蓝牙领域以扩展其功能、进一步延长电池寿命并提升产品销量。

图计算体系结构和系统软件关键技术综述

图计算作为分析事物之间关联关系的重要工具,近年来已成为各国政府及公司争夺的关键技术.学术界和工业界在图计算体系结构和系统软件关键技术方面取得了一定进展.然而,现实场景图计算大多具有动态变化、应用需求复杂多样等特征.这给图计算在基础理论、体系架构和系统软件关键技术方面提出了新的需求,同时也带来了新的挑战.为应对这些挑战,科研人员提出了一系列图计算系统或图计算加速器,通过高性能计算、并行计算等技术来优化图计算过程.综述国内外图计算体系结构和系统软件关键技术的研究发展现状,对国内外研究的最新进展进行归纳、比较和分析,并结合国家发展战略和重大应用需求,选取与我国国计民生密切相关的领域,从典型应用分析总结图计算相关技术的行业进展.最后,就未来的技术挑战和研究方向进行展望.

口服葡萄糖耐量试验1h血糖对糖尿病前期的诊断和鉴别价值

目的:探讨口服葡萄糖耐量试验(OGTT)1 h血糖对糖尿病前期的诊断和鉴别价值。方法:收集2019年6月至2022年6月于北京中医药大学东直门医院门诊及住院行OGTT的受试者1 206例,其中血糖正常412例,糖尿病前期358例,糖尿病436例。比较3组OGTT不同时点血糖与空腹血糖(FPG)、空腹胰岛素(FINS)、稳态模型胰岛素抵抗指数(HOMA-IR)、胰岛β细胞分泌功能指数(HOMA-β)水平;采用ROC曲线分析OGTT 1 h血糖对糖尿病前期的诊断和鉴别价值。结果:3组OGTT各时点血糖均为糖尿病组>糖尿病前期组>血糖正常组(P<0.05)。FPG、HOMA-IR糖尿病组>糖尿病前期组>血糖正常组,FINS、HOMA-β糖尿病组<糖尿病前期组<血糖正常组(P<0.05)。ROC曲线分析结果显示,OGTT 1 h血糖诊断糖尿病前期的AUC(95%CI)为0.758(0.724~0.792),以敏感度最大选取最佳切点值,该值为9.35 mmol/L,此时敏感度为0.701,特异度为0.709;OGTT 1 h血糖对糖尿病和糖尿病前期鉴别的AUC(95%CI)为0.956(0.942~0.969),以敏感度最大选取最佳切点值,该值为12.55 mmol/L,此时敏感度为0.901,特异度为0.908。结论:OGTT 1 h血糖对糖尿病前期具有一定的诊断和鉴别价值。

教育大模型的发展现状、创新架构及应用展望

从通用大模型到教育大模型,是人工智能大模型技术深化发展的重要趋势。基于对教育大模型发展现状、典型案例、潜在挑战的分析,文章认为教育大模型是适用于教育场景、具有超大规模参数、融合通用知识和专业知识训练形成的人工智能模型,是大模型技术、知识库技术及各类智能教育技术的集成,能够推动人类学习和机器学习的双向建构,进而提出了应用驱动、共建共享的创新架构和“以学习者为中心”的未来应用场景,旨在建立人工智能大模型与各类数字化教育应用的开放接口,持续训练和完善能够更好地解决教育专业问题的教育场景模型,形成让广大师生常态化使用的智能教育开放模型集群和知识库,在提炼和萃取深度教育知识的同时,破解人工智能教育应用中的风险和挑战。

基于光储混合配置的级联H桥型光伏逆变器功率平衡策略

级联H桥(cascade H-bridge,CHB)变换器由于其模块化结构,已成为大规模光伏(photovoltaic,PV)并网逆变器的优选方案。然而,在不同光照强度和温度下,不同区域PV组件之间发电功率不同,导致CHB变换器相间输出功率不均衡、不稳定等问题。为此,文中提出一种基于CHB结构的光储混合电能路由,在三相CHB光伏逆变器中配置少量的储能模块,利用光储协同控制,维持CHB内部功率稳定,消除分布式PV在相间产生的不均衡功率,且变换器输出功率能够时刻满足网侧上层功率调度,提高了光伏电站的稳定性。针对系统安全区域,在载波移相调制策略下,全桥子模块传输的功率受到约束,并对光伏和储能模块的配置作详细分析。最后,通过仿真以及实验验证所提拓扑及控制策略的正确性和有效性。

基于LIO-SAM建图和激光视觉融合定位的温室自主行走系统

为解决传统导航方案在温室内无法应对光照变化大、作物行间距窄、接收GPS信号差等问题,该研究提出了基于即时定位与地图构建技术的激光视觉融合式自主导航算法。该系统利用三维激光雷达VLP-16(Velodyne LiDAR,VLP-16)和惯性测量单元获取温室环境信息,采用基于紧耦合的雷达惯导定位建图(tightly-coupled lidar inertial odometry via smoothing and mapping,LIO-SAM)算法构建导航地图,基于轮式里程计和视觉里程计采用扩展卡尔曼滤波器算法实现局部定位,融合激光点云配准算法和自适应蒙特卡洛定位算法实现全局定位。同时,在自主行走系统应用A*算法规划全局路径和动态窗口算法规划局部路径,从而实现自主导航。试验结果表明,LIO-SAM算法构建的温室导航地图最大相对误差、最大绝对误差和均方根误差分别为9.9%、0.081和0.063 m,在温室内改进后的定位算法横向偏差小于0.020 m,纵向偏差小于0.090 m;当自主行走系统以0.15、0.30和0.50 m/s的速度运行时,横向偏差、纵向偏差和航向偏角的平均值分别小于0.120 m、0.10 m和8.5°,标准差分别小于0.070 m、0.140 m和6.6°。该导航方案满足自主行走系统在温室内高精度建图、定位和导航的需求,可为自主移动平台提供理论与技术支撑。

从知识困境到认知陷阱:生成式技术驱动型信息生态系统安全问题研究

生成式技术驱动型信息生态系统以生成式人工智能技术为核心,对整个信息环境中的知识传递与共享、认知流动与扩散过程发挥支撑和推动作用。然而,这种创新型的信息生态系统也伴随着知识安全和认知安全问题的出现。本文从知识环境和认知环境两个层面入手,对生成式技术驱动型信息生态系统的特点、优势与风险进行深入剖析,探索如何在符合人类价值观和社会伦理的前提下,充分发挥生成式人工智能的潜力,推动构建高效、安全、可持续发展的生成式技术驱动型信息生态系统。

一种可解释的云平台任务终止状态预测方法

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