快速响应的NV色心微波传感器实现及测量

高精度微波快速测量技术是电磁频谱分析监测的核心,微波测量技术为微波传感器的高精度测量提供了可能。通过建立NV色心空间磁场能级响应频率精密调谐模型,结合NV色心光学宽场成像技术,实现了高精度、响应快可调的微波测量。首先,通过连续光探测磁共振(ODMR)技术,结合宽场成像技术,通过像素级磁场强度-微波频率转化关系,实现宽场成像的微波测量;进而将连续扫频技术转变为施加定频进行检测,通过同步监测频点不同的响应特性,验证了测试结果的有效性。以上结果为高精度固态量子频谱分析仪、高瞬时带宽频谱微波传感器提供了重要技术基础。

Security Challenges of Virtualization Hypervisors in Virtualized Hardware Environment

The concept of virtualization machines is not new, but it is increasing vastly and gaining popularity in the IT world. Hypervisors are also popular for security as a means of isolation. The virtualization of information technology infrastructure creates the enablement of IT resources to be shared and used on several other devices and applications;this increases the growth of business needs. The environment created by virtualization is not restricted to any configuration physically or execution. The resources of a computer are shared logically. Hypervisors help in virtualization of hardware that is a software interact with the physical system, enabling or providing virtualized hardware environment to support multiple running operating system simultaneously utilizing one physical server. This paper explores the benefits, types and security issues of Virtualization Hypervisor in virtualized hardware environment.

近红外光调制下金刚石NV色心自旋动力学与电荷态转化研究

对金刚石氮-空位(nitrogen-vacancy,NV)色心电子自旋态进行光学操控的过程中,近红外光是一种重要手段,对色心自旋态和电荷态布居能产生显著影响,定量研究近红外光对NV色心自旋动力学的作用具有重要意义。文章用实验测量室温下532 nm激光连续激发单个NV色心产生的荧光时间曲线,并建立七能级模型进行数值模拟,得到各自旋能级间跃迁速率;在此基础上用1040 nm激光对色心荧光时间曲线进行调制,实验数据与数值模拟结果相吻合。研究结果表明,近红外光对金刚石NV色心自旋态的影响主要体现在对电荷态转化速率的提高上,使用功率为40 mW的1040 nm激光和532 nm激光一起照射,可以将电离速率和复合速率分别提升约15倍和30倍。

DLC膜对金刚石纳米柱NV色心发光收集强度的影响

金刚石氮空位(NV)色心发光收集强度的提高是实现单光子源技术的关键。本工作将锥状的类金刚石(DLC)梯度减反膜引入纳米柱色心单光子源中,旨在从色心的自发辐射速率与光子收集效率两方面提高NV色心的发光收集强度。采用时域有限差分(FDTD)法对带有DLC膜的金刚石纳米柱复合结构进行了光学仿真,探究了不同结构参数的DLC薄膜对金刚石纳米柱NV色心光子收集强度、出射效率及自发辐射速率的影响,并且通过优化得到了最大收集强度下的结构参数。仿真结果表明,引入DLC膜能够使金刚石纳米柱中NV色心获得更高的光子出射效率(≥1%),并且能够改变纳米柱内部电场分布,使色心自发辐射速率增加16.8%,最终使光子的总收集强度增加15.5%。

Investigating the Implications of Virtualization for Digital Forensics

Research in virtualization technology has gained significant developments in recent years, which brings not only opportunities to the forensic community, but challenges as well. This paper discusses the potential roles of virtualization in digital forensics, examines the recent progresses which use the virtualization techniques to support modem computer forensics. The influences on digital forensics caused by virtualization technology are identified. Tools and methods in common digital forensic practices are analyzed, and experiences of our practice and reflections in this field are shared.

Influence of static cartoons combined with dynamic virtual environments on preoperative anxiety of preschool-aged children undergoing surgery

BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.

A Concurrent Security Monitoring Method for Virtualization Environments

Recently,virtualization technologies have been widely used in industry.In order to monitor the security of target systems in virtualization environments,conventional methods usually put the security monitoring mechanism into the normal functionality of the target systems.However,these methods are either prone to be tempered by attackers or introduce considerable performance overhead for target systems.To address these problems,in this paper,we present a concurrent security monitoring method which decouples traditional serial mechanisms,including security event collector and analyzer,into two concurrent components.On one hand,we utilize the SIM framework to deploy the event collector into the target virtual machine.On the other hand,we combine the virtualization technology and multi-core technology to put the event analyzer into a trusted execution environment.To address the synchronization problem between these two concurrent components,we make use of Lamport's ring buffer algorithm.Based on the Xen hypervisor,we have implemented a prototype system named COMO.The experimental results show that COMO can monitor the security of the target virtual machine concurrently within a little performance overhead.

基于深度学习的NV色心轴向快速识别

文章提出一种利用NV色心的角向偏振光成像图快速确定NV色心轴向的深度学习方法。NV色心的光致发光特性与排列在垂直于NV色心对称轴平面上的2个正交偶极子有关,利用角向偏振光可以得到NV轴对应的正交光学偶极子的成像图;通过数字仿真可以模拟不同NV轴向在角向偏振光作用下的成像图案,以此构建数据集并搭建神经网络进行学习;将神经网络模型作为NV成像图和其轴向之间的映射,从而根据给定的成像图直接得出NV色心的部分轴向值,再依据金刚石晶格中的角度约束关系,得到金刚石中NV色心的完整轴向。基于NV色心的角向偏振光成像图,在保证识别精度的前提下,实现对NV轴向的实时确定,提高以NV轴向为前置条件的各项工作(如磁场重构等)的效率。

基于金刚石NV色心的电流传感技术及其标准化研究初探

为推进量子化电流传感技术的落地应用,探讨了基于金刚石NV色心的电流传感技术,初步研究了其标准化技术。首先,介绍了金刚石NV色心的结构和物理特性,分析了基于金刚石NV色心的光学特性及自旋量子相干性的电流传感测量原理,研究了磁噪声抑制、磁测量灵敏度提升和测量芯片小型化等实用化技术;然后,分析了基于金刚石NV色心的电流传感测量技术的技术优势和标准化需求,提出了标准体系建设建议,为基于金刚石NV色心的电流传感技术研究、设备研制及传感测量系统落地应用提供技术支撑。

采用磁屏蔽环结构的金刚石NV色心全光直流互感器系统

针对目前电力系统对电流互感器的精度与灵敏度提出的更高要求,提出了一种基于金刚石氮-空位(NV)色心的全光直流互感器的系统方案,系统包括光源模块、激光反馈模块、激光分束模块、一次传感探头模块、激光分频模块、光电转换模块以及信号采集和数据处理模块。对系统中的磁屏蔽环进行了结构的设计与仿真,并对仿真结果进行了实验验证。最后搭建了单通道实验验证系统,系统实测结果表明,设计的全光直流互感器在5 000 A大电流下无磁屏蔽时可以达到0.35%的测量精度,加入磁屏蔽环后测量精度提升到了0.06%,从而为基于金刚石NV色心的全光直流互感器的研制提供了参考。

Preparing highly entangled states of nanodiamond rotation and NV center spin

A nanodiamond with an embedded nitrogen-vacancy(NV)center is one of the experimental systems that can be coherently manipulated within current technologies.Entanglement between NV center electron spin and mechanical rotation of the nanodiamond plays a fundamental role in building a quantum network connecting these microscopic and mesoscopic degrees of motions.Here we present a protocol to asymptotically prepare a highly entangled state of the total quantum angular momentum and electron spin by adiabatically boosting the external magnetic field.

Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

Effects of virtual agents on interaction efficiency and environmental immersion in MR environments

Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.

基于无微波金刚石NV色心测磁技术的电流测量应用

为了在特高压(UHV)环境下使用氮-空位(NV)色心量子测量技术,研究了金刚石主轴与磁场夹角对相应曲线及电流测量精度的影响。构建金刚石氮-空位七能级超精细结构模型,根据仿真结果得到不同磁场方向下最高灵敏度范围和最佳测量范围,从而确定探头的最佳放置角度。基于无微波金刚石氮-空位技术搭建了直流大电流测量实验平台,测试了100~5000A范围内荧光电压对电流的响应曲线。实验结果表明,该平台对5000A直流电流测量误差在0.25%以内。作为无源器件,无微波金刚石氮-空位色心测磁传感器全光纤信号传输具备良好耐压性能,同时可在室温下工作,并具有结构紧凑、灵敏度高、抗电磁干扰能力强等优势,适用于特高压环境下的直流电流测量,为传统电力行业检测提供了新的检测方法。

Design and simulation of an accelerometer based on NV center spin–strain coupling

The nitrogen-vacancy (NV) center quantum systems have emerged as versatile tools in the field of precision measurement because of their high sensitivity in spin state detection and miniaturization potential as solid-state platforms.In this paper,an acceleration sensing scheme based on NV spin–strain coupling is proposed,which can effectively eliminate the influence of the stray noise field introduced by traditional mechanical schemes.Through the finite element simulation,it is found that the measurement bandwidth of this ensemble NV spin system ranges from 3 kHz to hundreds of kHz with structure√optimization.The required power is at the sub-μW level,corresponding to a noise-limited sensitivity of 6.7×10^(-5) /√Hz.Compared with other types of accelerometers,this micro-sized diamond sensor proposed here has low power consumption,exquisite sensitivity,and integration potential.This research opens a fresh perspective to realize an accelerometer with appealing comprehensive performance applied in biomechanics and inertial measurement fields.

金刚石NV色心磁力仪测磁性能优化

金刚石NV色心以其高磁场灵敏度、常温工作等优势成为一种非常有前景的磁场传感器。本文介绍了NV色心测磁原理,设计并搭建了基于NV色心的磁测量系统,通过激光-荧光差分光路将噪声降低至约1/8,使用微波混频调制方法将ODMR谱线斜率提升2.5倍左右,最终基于NV色心浓度<300 ppb的金刚石样品实现了0.934 nT/Hz^(1/2)的磁场测量灵敏度。同时设计了基于双微波调制解调的NV测磁系统,并在10 kHz采样率下实现了1.76×10^(-4)的测量不确定度,基于阿伦方差分析方法,在0.2 s统计时间条件下测量不确定度达到10 ppm。

Light-Activated Virtual Sensor Array with Machine Learning for Non-Invasive Diagnosis of Coronary Heart Disease

Early non-invasive diagnosis of coronary heart disease(CHD)is critical.However,it is challenging to achieve accurate CHD diagnosis via detecting breath.In this work,heterostructured complexes of black phosphorus(BP)and two-dimensional carbide and nitride(MXene)with high gas sensitivity and photo responsiveness were formulated using a self-assembly strategy.A light-activated virtual sensor array(LAVSA)based on BP/Ti_(3)C_(2)Tx was prepared under photomodulation and further assembled into an instant gas sensing platform(IGSP).In addition,a machine learning(ML)algorithm was introduced to help the IGSP detect and recognize the signals of breath samples to diagnose CHD.Due to the synergistic effect of BP and Ti_(3)C_(2)Tx as well as photo excitation,the synthesized heterostructured complexes exhibited higher performance than pristine Ti_(3)C_(2)Tx,with a response value 26%higher than that of pristine Ti_(3)C_(2)Tx.In addition,with the help of a pattern recognition algorithm,LAVSA successfully detected and identified 15 odor molecules affiliated with alcohols,ketones,aldehydes,esters,and acids.Meanwhile,with the assistance of ML,the IGSP achieved 69.2%accuracy in detecting the breath odor of 45 volunteers from healthy people and CHD patients.In conclusion,an immediate,low-cost,and accurate prototype was designed and fabricated for the noninvasive diagnosis of CHD,which provided a generalized solution for diagnosing other diseases and other more complex application scenarios.

SFC placement and dynamic resource allocation based on VNF performance-resource function and service requirement in cloud-edge environment

With the continuous development of network func-tions virtualization(NFV)and software-defined networking(SDN)technologies and the explosive growth of network traffic,the requirement for computing resources in the network has risen sharply.Due to the high cost of edge computing resources,coordinating the cloud and edge computing resources to improve the utilization efficiency of edge computing resources is still a considerable challenge.In this paper,we focus on optimiz-ing the placement of network services in cloud-edge environ-ments to maximize the efficiency.It is first proved that,in cloud-edge environments,placing one service function chain(SFC)integrally in the cloud or at the edge can improve the utilization efficiency of edge resources.Then a virtual network function(VNF)performance-resource(P-R)function is proposed to repre-sent the relationship between the VNF instance computing per-formance and the allocated computing resource.To select the SFCs that are most suitable to deploy at the edge,a VNF place-ment and resource allocation model is built to configure each VNF with its particular P-R function.Moreover,a heuristic recur-sive algorithm is designed called the recursive algorithm for max edge throughput(RMET)to solve the model.Through simula-tions on two scenarios,it is verified that RMET can improve the utilization efficiency of edge computing resources.

Effects and Causes of VR-Supported Interpreting Learning Environment on the Interpretation Classroom Anxiety of Student Interpreter

Interpreting activity is considered a high-anxiety activity due to its immediacy, multitasking, complexity of cognitive processing, and uncertainty of cognitive processing. Research has shown that interpreting anxiety, as the biggest emotional obstacle in the interpreting process, is the main emotional factor that leads to individual differences in interpreting. Students often claim to have fear or anxiety behaviors in interpreting exams, interpreting competitions, and interpreting classes. However, the research on interpreting teaching attaches importance to the cultivation of language knowledge, cultural knowledge, and interpreting skills, and does not pay enough attention to emotional factors such as motivation and anxiety in interpreting learning, which makes it difficult for the cultivated interpreters to meet the requirements of professional practice. In recent years, virtual reality technology (VR) has been gradually applied in the field of foreign language and interpreting teaching for creating a real, interactive and experiential language learning environment. Situated Learning Theory stresses that the fundamental mechanism for learning to take place is for individuals to participate in the real context in which knowledge is generated, and to realize the construction of knowledge through the interaction with the community of practice and the environment. Virtual reality technology can satisfy the needs of language learners for real contexts by providing learners with immersive, imaginative and interactive scenario simulations, and has a certain positive effect on alleviating learning anxiety. Therefore, relying on the virtual simulation course “United Nations Kubuqi International Desert Ecological Science and Technology Innovation International Volunteer Language Service Practical Training System”, this paper adopts a combination of quantitative and qualitative analyses to investigate the interpretation anxiety level of the interpreter trainees and the factors affecting them in the VR situation to help them discover effective responses to interpreter anxiety.

Autonomous VR Exposure Therapy for Anxiety Disorders Using Conversational AI—Ethical and Technical Implications and Preliminary Results

The need for psychotherapy is very high and the lack of care causes a lot of suffering and high costs. This paper presents an interdisciplinary approach to creating an AI-guided exposure therapy for fear of heights in virtual reality (VR). First, ethical principles for the use of conversational AI in psychotherapy were translated into technical requirements and made measurable. Based on this, an autonomous virtual reality exposure therapy was iteratively developed with a therapist. The feasibility and implementation of the ethical principles were tested with a patient. The patient was very satisfied with the VR setup. The AI therapist was also rated positively, although there is still room for improvement regarding conversational skills. Overall, the paper shows how AI can contribute responsibly to improving the psycho-therapeutic supply. It also provides guidelines that make ethical principles tangible and measurable for developers.