On the Integration of Dramaticity and Virtuality in English Movie Creation——Take "The Number One Player" as An Example

English movie works have a unique style.From the newly released"Number One Player",The research problem is mainly to discover the dramatic narrative style and the characteristics of virtuality.

Reality-Virtuality Fusional Campus Environment:An Online 3D Platform Based on OpenSimulator

This paper presents a reality-virtual fusional campus environment.It is an online 3D platform with some aspects of real information merged together.The whole platform is based on OpenSimulator with detailed geo-models to represent the university campus.Some preliminary experiments were done to integrate the realistic information with the virtual campus for making the geo-environment not only with detailed indoor and outdoor models,but also with the real representations of the physical world.The overall motivation is to provide a framework with strong support for reality-virtuality fusional modeling in a collaborative 3D online platform for research purposes.

Spatial Heterogeneity of Embedded Water Consumption from the Perspective of Virtual Water Surplus and Deficit in the Yellow River Basin,China

Virtual water trade(VWT)provides a new perspective for alleviating water crisis and has thus attracted widespread attention.However,the heterogeneity of virtual water trade inside and outside the river basin and its influencing factors remains further study.In this study,for better investigating the pattern and heterogeneity of virtual water trade inside and outside provincial regions along the Yellow River Basin in 2015 using the input-output model(MRIO),we proposed two new concepts,i.e.,virtual water surplus and virtual water deficit,and then used the Logarithmic Mean Divisia Index(LMDI)model to identify the inherent mechanism of the imbalance of virtual water trade between provincial regions along the Yellow River Basin and the other four regions in China.The results show that:1)in provincial regions along the Yellow River Basin,the less developed the economy was,the larger the contribution of the agricultural sector in virtual water trade,while the smaller the contribution of the industrial sector.2)Due to the large output of agricultural products,the upstream and midstream provincial regions of the Yellow River Basin had a virtual water surplus,with a net outflow of virtual water of 2.7×10^(8) m^(3) and 0.9×10^(8) m^(3),respectively.3)provincial regions along the Yellow River Basin were in a virtual water deficit with the rest of China,and the decisive factor was the active degree of trade with the outside.This study would be beneficial to illuminate the trade-related water use issues in provincial regions along the Yellow River Basin,which has farreaching practical signific-ance for alleviating water scarcity.

Wear dependent virtual flow rate sensor for progressing cavity pumps with deformable stator

This contribution presents a novel wear dependent virtual flow rate sensor for single stage single lobe progressing cavity pumps. We study the wear-induced material loss of the pump components and the impact of this material loss on the volumetric efficiency. The results are combined with an established backflow model to implement a backflow calculation procedure that is adaptive to wear. We use a laboratory test setup with a highly abrasive fluid and operate a pump from new to worn condition to validate our approach. The obtained measurement data show that the presented virtual sensor is capable of calculating the flow rate of a pump being subject to wear during its regular operation.

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.

Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach

This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.

Performance Comparison of Hyper-V and KVM for Cryptographic Tasks in Cloud Computing

As the extensive use of cloud computing raises questions about the security of any personal data stored there,cryptography is being used more frequently as a security tool to protect data confidentiality and privacy in the cloud environment.A hypervisor is a virtualization software used in cloud hosting to divide and allocate resources on various pieces of hardware.The choice of hypervisor can significantly impact the performance of cryptographic operations in the cloud environment.An important issue that must be carefully examined is that no hypervisor is completely superior in terms of performance;Each hypervisor should be examined to meet specific needs.The main objective of this study is to provide accurate results to compare the performance of Hyper-V and Kernel-based Virtual Machine(KVM)while implementing different cryptographic algorithms to guide cloud service providers and end users in choosing the most suitable hypervisor for their cryptographic needs.This study evaluated the efficiency of two hypervisors,Hyper-V and KVM,in implementing six cryptographic algorithms:Rivest,Shamir,Adleman(RSA),Advanced Encryption Standard(AES),Triple Data Encryption Standard(TripleDES),Carlisle Adams and Stafford Tavares(CAST-128),BLOWFISH,and TwoFish.The study’s findings show that KVM outperforms Hyper-V,with 12.2%less Central Processing Unit(CPU)use and 12.95%less time overall for encryption and decryption operations with various file sizes.The study’s findings emphasize how crucial it is to pick a hypervisor that is appropriate for cryptographic needs in a cloud environment,which could assist both cloud service providers and end users.Future research may focus more on how various hypervisors perform while handling cryptographic workloads.

用于重建物理和虚拟抓取的可重构数据手套

In this work,we present a reconfigurable data glove design to capture different modes of human hand-object interactions,which are critical in training embodied artificial intelligence(AI)agents for fine manipulation tasks.To achieve various downstream tasks with distinct features,our reconfigurable data glove operates in three modes sharing a unified backbone design that reconstructs hand gestures in real time.In the tactile-sensing mode,the glove system aggregates manipulation force via customized force sensors made from a soft and thin piezoresistive material;this design minimizes interference during complex hand movements.The virtual reality(VR)mode enables real-time interaction in a physically plausible fashion:A caging-based approach is devised to determine stable grasps by detecting collision events.Leveraging a state-of-the-art finite element method,the simulation mode collects data on fine-grained four-dimensionalmanipulation events comprising hand and object motions in three-dimensional space and how the object's physical properties(e.g.,stress and energy)change in accordance with manipulation over time.Notably,the glove system presented here is the first to use high-fidelity simulation to investigate the unobservable physical and causal factors behind manipulation actions.In a series of experiments,we characterize our data glove in terms of individual sensors and the overall system.More specifically,we evaluate the system's three modes by①recording hand gestures and associated forces,②improving manipulation fluency in VR,and③producing realistic simulation effects of various tool uses,respectively.Based on these three modes,our reconfigurable data glove collects and reconstructs fine-grained human grasp data in both physical and virtual environments,thereby opening up new avenues for the learning of manipulation skills for embodied AI agents.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

Proposal for a realtime Einstein-synchronization-defined satellite virtual clock

Realization of high performance satellite onboard clock is vital for various positioning, navigation, and timing applications. For further improvement of the synchronization-based satellite time and frequency references, we propose a geosynchronous(GEO) satellite virtual clock concept based on ground–satellite synchronization and present a beacon transponder structure for its implementation(scheduled for launch in 2025), which does not require atomic clocks to be mounted on the satellite. Its high performance relies only on minor modifications to the existing transponder structure of GEO satellites. We carefully model the carrier phase link and analyze the factors causing link asymmetry within the special relativity. Considering that performance of such synchronization-based satellite clocks is primarily limited by the link's random phase noise, which cannot be adequately modeled, we design a closed-loop experiment based on commercial GEO satellites for pre-evaluation. This experiment aims at extracting the zero-means random part of the ground-satellite Ku-band carrier phase via a feedback loop. Ultimately, we obtain a 1σ value of 0.633 ps(two-way link), following the Gaussian distribution. From this result, we conclude that the proposed real-time Einstein-synchronization-defined satellite virtual clock can achieve picosecond-level replication of onboard time and frequency.

Mental health in the virtual world:Challenges and opportunities in the metaverse era

Current rates of mental illness are worrisome.Mental illness mainly affects females and younger age groups.The use of the internet to deliver mental health care has been growing since 2020 and includes the implementation of novel mental health treatments using virtual reality,augmented reality,and artificial intelligence.A new three dimensional digital environment,known as the metaverse,has emerged as the next version of the Internet.Artificial intelligence,augmented reality,and virtual reality will create fully immersive,experiential,and interactive online environments in the metaverse.People will use a unique avatar to do anything they do in their“real”lives,including seeking and receiving mental health care.In this opinion review,we reflect on how the metaverse could reshape how we deliver mental health treatment,its opportunities,and its challenges.

A virtual thermometer for ultrahigh-temperature-pressure experiments in a large-volume press

Ultrahigh-temperature-pressure experiments are crucial for understanding the physical and chemical properties of matter.The recent development of boron-doped diamond(BDD)heaters has made such melting experiments possible in large-volume presses.However,estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained,owing to the lack of a suitable thermometer.Here,we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K.The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes,the actual sizes of cell assemblies after compression,the effects of the electrode,thermocouple and anvil,and the heat dissipation by the pressure-transmitting medium.The virtual thermometer reproduces the power-temperature relationships of ultrahigh-temperature-pressure experiments below 2600 K at press loads of 2.8-7.9 MN(~19 to 28 GPa)within experimental uncertainties.The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power-temperature relationships below 2600 K.Furthermore,our model shows that the temperature distribution inside a BDD heater(19-26 K/mm along the radial direction and<83 K/mm along the longitudinal direction)is more homogeneous than those inside conventional heaters such as graphite or LaCrO_(3) heaters(100-200 K/mm).Our study thus provides a reliable virtual thermometer for ultrahigh-temperature experiments using BDD heaters in Earth and material sciences.

An intelligent control method based on artificial neural network for numerical flight simulation of the basic finner projectile with pitching maneuver

In this paper,an intelligent control method applying on numerical virtual flight is proposed.The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect.Firstly,a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed.In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow,a numerical simulation of the basic finner projectile without control is carried out.The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation.Secondly,combined with the real-time control requirements of aerodynamic,attitude and displacement parameters of the projectile during the flight process,the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative)control strategy and the intelligent PID control strategy respectively.The intelligent PID controller based on BP(Back Propagation)neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters.Compared with the traditional PID controller,the concerned control variable overshoot,rise time,transition time and steady state error and other performance indicators have been greatly improved,and the higher the learning efficiency or the inertia coefficient,the faster the system,the larger the overshoot,and the smaller the stability error.The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.

A Tri-mode of Mock-Walker Cells

This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature(SST).The associated precipitation in the mock-Walker cells exhibits three different modes,including a single peak of precipitation over the SST maximum(mode 1),symmetric double peaks of precipitation straddling the SST maximum(mode 2),and a single peak of precipitation on one side of the SST maximum(mode 3).The three modes are caused by three distinct convective activity center migration traits.Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes.When the SST gradient is large,the virtual effect may be strong enough to overcome the temperature effect,generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center.The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.

Digital twin-and extended reality-based telepresence for collaborative robot programming in the 6G perspective

In the context of Industry 4.0,a paradigm shift from traditional industrial manipulators to Collaborative Robots(CRs)is ongoing,with the latter serving ever more closely humans as auxiliary tools in many production processes.In this scenario,continuous technological advancements offer new opportunities for further innovating robotics and other areas of next-generation industry.For example,6G could play a prominent role due to its human-centric view of the industrial domains.In particular,its expected dependability features will pave the way for new applications exploiting highly effective Digital Twin(DT)-and eXtended Reality(XR)-based telepresence.In this work,a novel application for the above technologies allowing two distant users to collaborate in the programming of a CR is proposed.The approach encompasses demanding data flows(e.g.,point cloud-based streaming of collaborating users and robotic environment),with network latency and bandwidth constraints.Results obtained by analyzing this approach from the viewpoint of network requirements in a setup designed to emulate 6G connectivity indicate that the expected performance of forthcoming mobile networks will make it fully feasible in principle.

Simplified prediction models for acoustic installation effects of train-mounted equipment

Acoustic models of railway vehicles in standstill and pass-by conditions can be used as part of a virtual certification process for new trains.For each piece of auxiliary equipment,the sound power measured on a test bench is combined with meas-ured or predicted transfer functions.It is important,however,to allow for installation effects due to shielding by fairings or the train body.In the current work,fast-running analytical models are developed to determine these installation effects.The model for roof-mounted sources takes account of diffraction at the corner of the train body or fairing,using a barrier model.For equipment mounted under the train,the acoustic propagation from the sides of the source is based on free-field Green’s functions.The bottom surfaces are assumed to radiate initially into a cavity under the train,which is modelled with a simple diffuse field approach.The sound emitted from the gaps at the side of the cavity is then assumed to propagate to the receivers according to free-field Green’s functions.Results show good agreement with a 2.5D boundary element model and with measurements.Modelling uncertainty and parametric uncertainty are evaluated.The largest variability occurs due to the height and impedance of the ground,especially for a low receiver.This leads to standard deviations of up to 4 dB at low frequencies.For the roof-mounted sources,uncertainty over the location of the corner used in the equivalent barrier model can also lead to large standard deviations.

Breaking the optical efficiency limit of virtual reality with a nonreciprocal polarization rotator

A catadioptric lens structure,also known as pancake lens,has been widely used in virtual reality(VR)displays to reduce the formfactor.However,the utilization of a half mirror(HM)to fold the optical path thrice leads to a significant optical loss.The theoretical maximum optical efficiency is merely 25%.To transcend this optical efficiency constraint while retaining the foldable characteristic inherent to traditional pancake optics,in this paper,we propose a theoretically lossless folded optical system to replace the HM with a nonreciprocal polarization rotator.In our feasibility demonstration experiment,we used a commercial Faraday rotator(FR)and reflective polarizers to replace the lossy HM.The theoretically predicted 100%efficiency can be achieved approximately by using two high-extinction-ratio reflective polarizers.In addition,we evaluated the ghost images using a micro-OLED panel in our imaging system.Indeed,the ghost images can be suppressed to undetectable level if the optics are with antireflection coating.Our novel pancake optical system holds great potential for revolutionizing next-generation VR displays with lightweight,compact formfactor,and low power consumption.

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.

Exploration of cyclooxygenase-2 inhibitory peptides from walnut dreg proteins based on in silico and in vitro analysis

Walnut dreg protein hydrolysates(WDPHs)exhibit a variety of biological activities,however,the cyclooxygenase-2(COX-2)inhibitory peptide of WDPHs remain unclear.The aim of this study was to rapidly screen for such peptides in WDPHs through a combination of in silico and in vitro analysis.In total,1262 peptide sequences were observed by nano liquid chromatography/tandem mass spectrometry(nano LC-MS/MS)and 4 novel COX-2 inhibitory peptides(AGFP,FPGA,LFPD,and VGFP)were identified.Enzyme kinetic data indicated that AGFP,FPGA,and LFPD displayed mixed-type COX-2 inhibition,whereas VGFP was a non-competitive inhibitor.This is mainly because the peptides form hydrogen bonds and hydrophobic interactions with residues in the COX-2 active site.These results demonstrate that computer analysis combined with in vitro evaluation allows for rapid screening of COX-2 inhibitory peptides in walnut protein dregs.

Virtual Power Plants for Grid Resilience: A Concise Overview of Research and Applications

The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.