Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

“Instruction-Category” Approach of Test Suite Construction for Oven Embedded System

Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.

EG-STC: An Efficient Secure Two-Party Computation Scheme Based on Embedded GPU for Artificial Intelligence Systems

This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.

CL2ES-KDBC:A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks.In this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT intrusions.Then,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value precisely.In addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the classifier.The effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other factors.Computational analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.

Teaching Reform and Practice of Embedded System Design Based on Outcome-Based Education

Embedded system design is the core course of the telecommunication major in engineering universities,which combines software and hardware through embedded development boards.Aiming at the problems existing in traditional teaching,this paper proposes curriculum teaching reform based on the outcome-based education(OBE)concept,including determining course objectives,reforming teaching modes and methods,and improving the curriculum assessment and evaluation system.After two semesters of practice,this method not only enhances students’learning initiative but also improves teaching quality.

Simultaneous multi-material embedded printing for 3D heterogeneous structures

In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With the embedded printing method,complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity.However,the current sequential multi-material embedded printing method faces a major challenge,which is the inevitable trade-off between the printed structural integrity and printing precision.Here,we propose a simultaneous multi-material embedded printing method.With this method,we can easily print firmly attached and high-precision multilayer structures.With multiple individually controlled nozzles,different biomaterials can be precisely deposited into a single crevasse,minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure.We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally,and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium,on the 3D morphology of the printed filament.We demonstrate the printing of double-layer thin-walled structures,each layer less than 200μm,as well as intestine and liver models with 5%gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination.The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods.The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.

TCM-HIN2Vec:A strategy for uncovering biological basis of heart qi deficiency pattern based on network embedding and transcriptomic experiment

Objective:To elucidate the biological basis of the heart qi deficiency(HQD)pattern,an in-depth understanding of which is essential for improving clinical herbal therapy.Methods: We predicted and characterized HQD pattern genes using the new strategy,TCM-HIN2Vec,which involves heterogeneous network embedding and transcriptomic experiments.First,a heterogeneous network of traditional Chinese medicine(TCM)patterns was constructed using public databases.Next,we predicted HQD pattern genes using a heterogeneous network-embedding algorithm.We then analyzed the functional characteristics of HQD pattern genes using gene enrichment analysis and examined gene expression levels using RNA-seq.Finally,we identified TCM herbs that demonstrated enriched interactions with HQD pattern genes via herbal enrichment analysis.Results: Our TCM-HIN2Vec strategy revealed that candidate genes associated with HQD pattern were significantly enriched in energy metabolism,signal transduction pathways,and immune processes.Moreover,we found that these candidate genes were significantly differentially expressed in the transcriptional profile of mice model with heart failure with a qi deficiency pattern.Furthermore,herbal enrichment analysis identified TCM herbs that demonstrated enriched interactions with the top 10 candidate genes and could potentially serve as drug candidates for treating HQD.Conclusion: Our results suggested that TCM-HIN2Vec is capable of not only accurately identifying HQD pattern genes,but also deciphering the basis of HQD pattern.Furthermore our finding indicated that TCM-HIN2Vec may be further expanded to develop other patterns,leading to a new approach aimed at elucidating general TCM patterns and developing precision medicine.

Advances of embedded resistive random access memory in industrial manufacturing and its potential applications

Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to enhance performance.Among them,resistive random access memory(RRAM)has gained significant attention due to its numerousadvantages over traditional memory devices,including high speed(<1 ns),high density(4 F^(2)·n^(-1)),high scalability(~nm),and low power consumption(~pJ).This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potentialapplications.It provides a brief introduction to the concepts and advantages of RRAM,discusses the key factors that impact its industrial manufacturing,and presents the commercial progress driven by cutting-edge nanotechnology,which has been pursued by manysemiconductor giants.Additionally,it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing,with a particular emphasis on its role in neuromorphic computing.Finally,the review discusses thecurrent challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.

A chaotic hierarchical encryption/watermark embedding scheme for multi-medical images based on row-column confusion and closed-loop bi-directional diffusion

Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.

Thin-Shell Wormholes Admitting Conformal Motions in Spacetimes of Embedding Class One

This paper discusses the feasibility of thin-shell wormholes in spacetimes of embedding class one admitting a one-parameter group of conformal motions. It is shown that the surface energy density σis positive, while the surface pressure is negative, resulting in , thereby signaling a violation of the null energy condition, a necessary condition for holding a wormhole open. For a Morris-Thorne wormhole, matter that violates the null energy condition is referred to as “exotic”. For the thin-shell wormholes in this paper, however, the violation has a physical explanation since it is a direct consequence of the embedding theory in conjunction with the assumption of conformal symmetry. These properties avoid the need to hypothesize the existence of the highly problematical exotic matter.

ARM-Based Embedded System Platform and Its Portability Research

Taking ARM as the hardware platform, the embedded system is built from both hardware and software aspects with the application as the center. In the hardware design, build the hardware platform scheme, design the schematic diagram as well as PCB, complete the hardware debugging, and ensure the system hardware platform function;in the software design, optimize the three-stage pipeline structure of ARM instruction system, design the instruction set, install the embedded system on the virtual machine, build the cross-toolchain, and set up the correct NFS network file system. Finish the design of the ARM-based embedded system platform, combined with the hardware requirements of the experimental platform, transplant the powerful Uboot as the Bootloader of the system, and further transplant the Linux-2.6. 32 kernel to the system start the operation normally, and finally, build the root file to finish the study of its portability.

A Discussion on the Establishment That a Fibre Metric on the Positive Definite Real Inner-Product of a Properly Embedded Smooth Submanifold Be Always Extended to a Riemannian Metric on the Positive Definite Real Inner-Product

Let M be a smooth manifold and S ⊆ M a properly embedded smooth submanifold. Suppose that we have a fibre metric on TM|s i.e. a positive definite real inner-product on TpM for all p ∈ S, which depends smoothly on p ∈ S. The purpose of this article is to figure out that the fibre metric on TM|s can always be extended to a Riemannian metric on TM from a special perspective.

Implementation of High-Q Embedded Band Pass Filter in Wireless Communication

At 12.8 MHz center frequency,the advanced miniaturized polymer-based planar high quality factor(Q)passive elements embedded bandpassfilter works in the L-band.Because most of the demands operate inside the spectrum,the wideband or high-speed operation necessary to enhance must be acquired in microwave frequency ranges.The channel has a quiet,high-performance micro-filter with wideband rejection.Capacitors and inductors are used in the high quality factor(Q)passive components,and related networks are incorporated in thefilter.Embedded layers are concatenated using Three-Dimensional Integrated Circuit(3D-IC)integration,parasitics are removed,and interconnection losses are negotiated using de-embedding methods.A wireless application-based Liquid Crystalline Polymer(LCP)viewpoint is employed as a substrate material in this work.The polymer processes,their properties,and the incorporated high-Q Band Pass Filter Framework.The suggestedfilter model is computed and manufactured utilizing the L-band frequency spectrum,decreasing total physical length by 31%while increasing bandwidth by 45%.

Experimental Study of Moso Bamboo to-Steel Connections with Embedded Grouting Materials

Moso bamboos have attracted excessive attention as a renewable green building material to the concept of sustainable development.In this paper,the 20 bolted Moso bamboo connection specimens with embedded steel plates and grouting materials were designed according to connection configurations with different bolt diameters and end distance of bolt holes,and their bearing capacities and failure modes were analyzed by static tension tests.According to the test results of all connectors,the failure modes of the specimens are divided into four categories,and the effects of bolt diameter and bolt hole end distance on the connection bearing capacity and failure mode are analyzed.The test results show that the deformation and failure process can be divided into four stages.The main influence factor of connector bearing capacity is bolt diameter.Connectors can be divided into four failure modes,and brittle failure can be avoided by adopting certain structural measures.Filling with grouting material can improve the bearing capacity of joints.Due to the large variability of bamboo,further experiments are needed.

胸腹腔镜微创手术联合食管-胃三层包埋吻合在食管癌快速康复中的应用

目的:探究胸腹腔镜微创手术联合食管-胃三层包埋吻合在食管癌快速康复中的应用效果。方法:选取2019年2月—2021年2月在扬中市人民医院接受治疗的68例食管癌患者作为研究对象,按随机数表法将患者分为对照组和观察组,各34例。对照组采用胸腔镜食管癌根治术联合管型吻合器行端侧吻合加间断缝合包埋,观察组采用胸腹腔镜微创手术联合食管-胃三层包埋吻合。比较两组手术总时间、胸腹部操作时间、颈部操作时间、术后首次下床时间、术后首次排气时间、术后首次排便时间、术后住院时间及术后并发症发生情况。结果:观察组手术总时间、胸腹部操作时间、颈部操作时间、术后首次下床时间、术后首次排气时间、术后首次排便时间、术后住院时间短于对照组,术后吻合口瘘、肺部感染、心律失常、胃排空延迟、术后鼻咽不适感发生率低于对照组,差异有统计学意义(P<0.05)。结论:胸腹腔镜微创手术联合食管-胃三层包埋吻合在食管癌快速康复中的应用效果较好,手术用时少,术后恢复快,并发症少,利于患者的术后康复。

基于SPI-RRV指数中国气象干旱及其风险时空演变特征研究

为全面揭示变化环境下我国多维气象干旱特征,耦合气象干旱指数(SPI)和可靠性-回弹性-脆弱性(RRV)指数,提出了一种基于SPI-RRV指数的干旱风险评价方法,定量评价了中国气象干旱及其风险的时空演变特征。结果表明:SPI-RRV指数具有特征稳定和时空可比性强的特点,能够较为准确地评估气象干旱风险时空演变特征;南方平均干旱栅格比、干旱月占比和频次大于北方,湿润区和半湿润区干旱历时短、烈度大,半干旱区和干旱区干旱历时长、烈度相对较小;干旱高风险区转移具有显著年代际变化规律,空间上从西北向西南地区转移。

深部煤储层孔裂隙结构对煤层气赋存的影响-以鄂尔多斯盆地东缘大宁-吉县区块为例

深部煤储层孔隙–裂缝结构对深部煤层气资源潜力评价和勘探开发具有重要意义。选取鄂尔多斯盆地东缘大宁–吉县区块DJ57井本溪组5个煤岩样品为研究对象,在煤岩煤质参数测试的基础上,采用气体吸附法、高压压汞法和微米CT扫描等测试手段,对深部煤储层中的纳米级孔隙-微米级裂缝进行多尺度定量表征,综合评价不同尺度的孔裂隙结构特征。再结合渗透率和甲烷等温吸附试验,探讨了微观孔裂隙对深部煤储层中煤层气的赋存和渗流的影响。研究结果表明:基于多种孔隙表征方法对深部煤储层孔裂隙进行多尺度定量表征,其孔裂隙体积分布类型主要以“U”型为主,呈现出微孔与微裂缝并存双峰态,主要集中在0.3~1.5 nm和>100μm的范围内。其中,微孔(<2 nm)、介孔(2~50 nm)、宏孔(50 nm~10μm)和微裂缝(>10μm)体积平均分别占总孔裂隙体积的80.18%,6.70%,1.65%和11.47%。随着微孔发育而吸附气量呈增大的趋势,微孔可以提供大量吸附点位,为深部煤层气的吸附和赋存提供场所。随着微裂缝发育而游离气量呈增大的趋势,微裂缝可以提供大量储集空间,为深部煤层气的富集提供空间条件。此外,微裂缝在三维空间中相互连通,形成网状结构,连通性强。随着微裂缝越发育,煤储层渗透率越大,微裂缝增强了煤层气的渗流能力。纳米级孔隙和微米级裂隙发育特征分别控制着深部煤层气吸附能力和开发潜力。

水资源-能源-粮食-生态系统耦合协调及驱动力分析

为加深对我国水资源、能源、粮食、生态系统协同演变趋势的认识,构建水资源-能源-粮食-生态多维系统指标体系,运用耦合协调度模型对我国2005—2020年水资源-能源-粮食-生态系统耦合协调度进行评价,并采用多因素归因分析法进行驱动力分析。结果表明:我国水资源-能源-粮食-生态系统耦合协调度从2005年的0.55增长到2020年的0.84,各地区耦合协调度从勉强协调发展水平过渡到中级协调发展水平,各子系统对耦合协调度上升的驱动分别经历了由粮食子系统到生态子系统再到水资源子系统主导的过程;能源子系统的贡献率虽然比较小,但是未来可能是各地区提升水资源-能源-粮食-生态系统多维系统协调发展水平的突破口。

基于“心-脉-神”互言探讨肝心同治冠心病合并抑郁(双心疾病)的理论研究

双心疾病作为“血脉之心”与“神明之心”同病的复合疾病,已经成为现代社会影响人类健康的主流问题之一,其中的冠心病合并抑郁属于临床中常见的发病类型。冠心病是一种严重威胁健康的心血管疾病,焦虑和抑郁是其不良预后的潜在危险因素。冠心病合并抑郁属中医“胸痹”“郁证”范畴,“心藏脉,脉舍神”,心脏对生命活动具有重要的控制和调节作用,“从心论治”使机体心主神明、心主血脉功能正常发挥。心血管疾病与情志病是密不可分的,胸痹患者心脉不畅,肝失疏泄,痰瘀互结,气机郁滞加重,由此引发情志的改变。双心疾病与中医的“心主血脉”“心主神明”“肝主藏血”“肝主疏泄”功能失常密切相关,“心”与“肝”的状态失衡是导致疾病进展的主要因素,故“肝心同治”是调节关键病机-肝心失调的必由之法,以疏肝解郁、调气和血为主。基于对“从心论治”“心-脉-神”与“肝心同治”的理论探讨,结合现代科学技术,旨在为防治冠心病合并抑郁提供新的思路与机制预测。

基于UPLC-QTOF-MS解析苦荞黄酮组成及药理学网络分析

为优化苦荞黄酮提取工艺并明确其具体成分结构和含量及药理作用,本研究以四川省凉山彝族自治州甘洛县优质苦荞为研究对象,对超声提取苦荞黄酮工艺进行了优化,采用超高效液相色谱-四级杆-飞行时间质谱(UPLC-QTOF-MS)对主要黄酮成分进行结构鉴定,并采用超高效液相色谱-三重四级杆质谱联用仪对鉴定到的黄酮进行准确定量,同时利用中药系统药理学(TCMSP)系统分析其网络药理学特性。结果表明,超声辅助乙醇提取苦荞黄酮的最优条件为乙醇浓度90%(V/V)、超声功率140 W、超声温度70℃、超声时间60 min、提取溶剂与苦荞原料比50∶1(mL·g^(-1)),该条件下,提取液中共鉴定到黄酮16种,其中芦丁、表儿茶素和儿茶素含量分别达到115.81、72.99和23.08μg·mL^(-1)。这16种黄酮在防治心血管疾病、慢性炎症性疾病上具有重要作用。本研究可为苦荞精深加工综合利用尤其是功能性苦荞产品开发利用奠定基础。