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.

Special Vehicle Target Detection and Tracking Based on Virtual Simulation Environment and YOLOv5-Block+DeepSort Algorithm

In the process of dense vehicles traveling fast,there will be mutual occlusion between vehicles,which will lead to the problem of deterioration of the tracking effect of different vehicles,so this paper proposes a research method of virtual simulation video vehicle target tracking based on you only look once(YOLO)v5s and deep simple online and realtime tracking(DeepSort).Given that the DeepSort algorithm is currently the most effective tracking method,this paper merges the YOLOv5 algorithm with the DeepSort algorithm.Then it adds the efficient channel attention networks(ECA-Net)focusing mechanism at the back for the cross-stage partial bottleneck with 3 convolutions(C3)modules about the YOLOv5 backbone network and before the up-sampling of the Neck feature pyramid.The YOLOv5 algorithm adopts expected intersection over union(EIOU)instead of complete intersection over union(CIOU)as the loss function of the target frame regression.The improved YOLOv5 algorithm is named YOLOv5-Block.The experimental results show that in the special vehicle target detection(TD)and tracking in the virtual simulation environment,The YOLOv5-Block algorithm has an average accuracy(AP)of 99.5%,which significantly improves the target recognition correctness for typical occlusion cases,and is 1.48 times better than the baseline algorithm.After the virtual simulation video sequence test,multiple objects tracking accuracy(MOTA)and various objects tracking precision(MOTP)improved by 10.7 and 1.75 percentage points,respectively,and the number of vehicle target identity document(ID)switches decreased.Compared with recent mainstream vehicle detection and tracking models,the YOLOv5-Block+Deepsort algorithm can accurately and continuously complete the detection and tracking tasks of special vehicle targets in different scenes.

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.

Towards engineering a portable platform for laparoscopic pre-training in virtual reality with haptic feedback

Background Laparoscopic surgery is a surgical technique in which special instruments are inserted through small incision holes inside the body.For some time,efforts have been made to improve surgical pre training through practical exercises on abstracted and reduced models.Methods The authors strive for a portable,easy to use and cost-effective Virtual Reality-based(VR)laparoscopic pre-training platform and therefore address the question of how such a system has to be designed to achieve the quality of today's gold standard using real tissue specimens.Current VR controllers are limited regarding haptic feedback.Since haptic feedback is necessary or at least beneficial for laparoscopic surgery training,the platform to be developed consists of a newly designed prototype laparoscopic VR controller with haptic feedback,a commercially available head-mounted display,a VR environment for simulating a laparoscopic surgery,and a training concept.Results To take full advantage of benefits such as repeatability and cost-effectiveness of VR-based training,the system shall not require a tissue sample for haptic feedback.It is currently calculated and visually displayed to the user in the VR environment.On the prototype controller,a first axis was provided with perceptible feedback for test purposes.Two of the prototype VR controllers can be combined to simulate a typical both-handed use case,e.g.,laparoscopic suturing.A Unity based VR prototype allows the execution of simple standard pre-trainings.Conclusions The first prototype enables full operation of a virtual laparoscopic instrument in VR.In addition,the simulation can compute simple interaction forces.Major challenges lie in a realistic real-time tissue simulation and calculation of forces for the haptic feedback.Mechanical weaknesses were identified in the first hardware prototype,which will be improved in subsequent versions.All degrees of freedom of the controller are to be provided with haptic feedback.To make forces tangible in the simulation,characteristic values need to be determined using real tissue samples.The system has yet to be validated by cross-comparing real and VR haptics with surgeons.

Permanent Magnet Temperature Estimation for PMSMs Using Virtual Position-offset Injection

This paper proposes a virtual position-offset injection based permanent magnet temperature estimation approach for permanent magnet synchronous machines(PMSMs). The concept of virtual position-offset injection is mathematically transforming the machine model to a virtual frame with a position-offset. The virtual frame temperature estimation model is derived to calculate the permanent magnet temperature(PMT) directly from the measurements with computation efficiency. The estimation model involves a combined inductance term, which can simplify the establishment of saturation compensation model with less measurements. Moreover, resistance and inverter distorted terms are cancelled in the estimation model, which can improve the robustness to the winding temperature rise and inverter distortion. The proposed approach can achieve simplified computation in temperature estimation and reduced memory usage in saturation compensation. While existing model-based approaches could be affected by either the need of resistance and inverter information or complex saturation compensation. Experiments are conducted on the test machine to verify the proposed approach under various operating conditions.

Audio2AB:Audio-driven collaborative generation of virtual character animation

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of success.However,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient attention.Methods Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body animations.This parameterization method can be used to drive full-body animations of virtual characters and improve their portability.In the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial data.The Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio features.Finally,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss function.Results By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape weights.Therefore,different 3D virtual character animations could be created through parameterization.Conclusions The experimental results showed that the proposed method could generate significant gestures and facial animations.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

Human-Machine Symbiosis:Philosophical Reflection on Virtual Human

Virtual human is the simulation of human under the synthesis of virtual reality,artificial intelligence,and other technologies.Modern virtual human technology simulates both the external characteristics and the internal emotions and personality of humans.The relationship between virtual human and human is a concrete expression of the modern symbiotic relationship between human and machine.This human-machine symbiosis can either be a fusion of the virtual human and the human or it can cause a split in the human itself.

Virtual Reality-Based Mirror Therapy for Upper Extremity Function among Stroke Patients:A Meta-analysis and Systematic Review

[Objectives]To investigate the evidence-based effect of virtual reality-based mirror therapy system(VR-MT)on upper extremity function among stroke patients.[Methods]A systematic electronic searching of the Medline,PubMed,Web of Science and CNKI was initially performed up to June 10,2024.The risk of bias of the included studies was evaluated using RevMan 5.4 software based on the Cochrane Handbook for Systematic Reviews.The random-effects model or fixed-effects models was employed to estimate the standardized mean difference(SMD).The subgroup analyses were conducted exploring theVR-MT type(immersive or non-immersive)and comparing with MT or control group.[Results]In total 8 studies with a total of 273 stroke patients were included in this review.The pooled analysis of these trials showed a statistically significant enhancement inFMA-UE scores(6 studies,SMD=0.72,[95%CI 0.37 to 1.06];P<0.0001,I^(2)=31%)and Box and Block Test(BBT)(3 studies,SMD=0.49,[95%C/0.05 to 0.93];P=0.03,I^(2)=0%),rather than Manual Function Test(MFT)scores(3 studies,SMD=0.38,[95%CI-0.09 to 0.84];P=0.11,I^(2)=0%)following the application of reality-based mirror therapy.Additionally,the subgroup analysis results indicated that immersive VR-MT can significantly improve FMA-UE(5studies,SMD=0.73,[95%CI 0.24 to 1.23];P=0.004,I^(2)=43%).In contrast,the overall effect of non-immersive VR-MT was non-significant(2 studies,SMD=0.33,[95%CI-0.69 to 1.34];P=0.53,I^(2)=72%).[Conclusions]In this systematic review and meta-analysis,our findings indicate that immersiveVR-MT has the potential to improve upper extremity function among stroke patients.

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.

GRU-integrated constrained soft actor-critic learning enabled fully distributed scheduling strategy for residential virtual power plant

In this study,a novel residential virtual power plant(RVPP)scheduling method that leverages a gate recurrent unit(GRU)-integrated deep reinforcement learning(DRL)algorithm is proposed.In the proposed scheme,the GRU-integrated DRL algorithm guides the RVPP to participate effectively in both the day-ahead and real-time markets,lowering the electricity purchase costs and consumption risks for end-users.The Lagrangian relaxation technique is introduced to transform the constrained Markov decision process(CMDP)into an unconstrained optimization problem,which guarantees that the constraints are strictly satisfied without determining the penalty coefficients.Furthermore,to enhance the scalability of the constrained soft actor-critic(CSAC)-based RVPP scheduling approach,a fully distributed scheduling architecture was designed to enable plug-and-play in the residential distributed energy resources(RDER).Case studies performed on the constructed RVPP scenario validated the performance of the proposed methodology in enhancing the responsiveness of the RDER to power tariffs,balancing the supply and demand of the power grid,and ensuring customer comfort.

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.

Diagnostic efficacy of virtual organ computer-assisted analysis in measuring the volume ratio of subchorionic hematoma with serum progesterone

BACKGROUND Subchorionic hematoma(SCH)is a common complication in early pregnancy characterized by the accumulation of blood between the uterine wall and the chorionic membrane.SCH can lead to adverse pregnancy outcomes such as miscarriage,preterm birth,and other complications.Early detection and accurate assessment of SCH are crucial for appropriate management and improved pregnancy outcomes.AIM To evaluate the diagnostic efficacy of virtual organ computer-assisted analysis(VOCAL)in measuring the volume ratio of SCH to gestational sac(GS)combined with serum progesterone on early pregnancy outcomes in patients with SCH.METHODS A total of 153 patients with SCH in their first-trimester pregnancies between 6 and 11 wk were enrolled.All patients were followed up until a gestational age of 20 wk.The parameters of transvaginal two-dimensional ultrasound,including the circumference of SCH(Cs),surface area of SCH(Ss),circumference of GS(Cg),and surface area of GS(Sg),and the parameters of VOCAL with transvaginal three-dimensional ultrasound,including the three-dimensional volume of SCH(3DVs)and GS(3DVg),were recorded.The size of the SCH and its ratio to the GS size(Cs/Cg,Ss/Sg,3DVs/3DVg)were recorded and compared.RESULTS Compared with those in the normal pregnancy group,the adverse pregnancy group had higher Cs/Cg,Ss/Sg,and 3DVs/3DVg ratios(P<0.05).When 3DVs/3DVg was 0.220,the highest predictive performance predicted adverse pregnancy outcomes,resulting in an AUC of 0.767,and the sensitivity,specificity were 70.2%,75%respectively.VOCAL measuring 3DVs/3DVg combined with serum progesterone gave a diagnostic AUC of 0.824 for early pregnancy outcome in SCH patients,with a high sensitivity of 82.1%and a specificity of 72.1%,which showed a significant difference between AUC.CONCLUSION VOCAL-measured 3DVs/3DVg effectively quantifies the severity of SCH,while combined serum progesterone better predicts adverse pregnancy outcomes.

Virtual Keyboard:A Real-Time Hand Gesture Recognition-Based Character Input System Using LSTM and Mediapipe Holistic

In the digital age,non-touch communication technologies are reshaping human-device interactions and raising security concerns.A major challenge in current technology is the misinterpretation of gestures by sensors and cameras,often caused by environmental factors.This issue has spurred the need for advanced data processing methods to achieve more accurate gesture recognition and predictions.Our study presents a novel virtual keyboard allowing character input via distinct hand gestures,focusing on two key aspects:hand gesture recognition and character input mechanisms.We developed a novel model with LSTM and fully connected layers for enhanced sequential data processing and hand gesture recognition.We also integrated CNN,max-pooling,and dropout layers for improved spatial feature extraction.This model architecture processes both temporal and spatial aspects of hand gestures,using LSTM to extract complex patterns from frame sequences for a comprehensive understanding of input data.Our unique dataset,essential for training the model,includes 1,662 landmarks from dynamic hand gestures,33 postures,and 468 face landmarks,all captured in real-time using advanced pose estimation.The model demonstrated high accuracy,achieving 98.52%in hand gesture recognition and over 97%in character input across different scenarios.Its excellent performance in real-time testing underlines its practicality and effectiveness,marking a significant advancement in enhancing human-device interactions in the digital age.

Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches.

Integrating Virtual Reality and Energy Analysis with BIM to Optimize Window-to-Wall Ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall Ratio (WWR), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWR, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWR and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual Reality (VR), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

Discussion on the Construction and Application of Virtual Reality-Based Curriculum Resources for Kindergarten Education

The construction of early childhood curriculum resources serves as a vital vehicle and precondition for the implementation of collective teaching activities in kindergartens.However,traditional curriculum resources based on graphic language or the linguistic descriptions of early childhood educators often fail to provide children with an immersive experience during collective teaching activities,leading to a lack of initiative and interest in learning.This paper discusses the methods for building a kindergarten curriculum resource library and,based on this foundation,employs virtual reality technology for three-dimensional modeling of the library to enrich the curriculum resources in kindergartens.Furthermore,this paper proposes to train early childhood educators in virtual reality technology to enhance their abilities to operate and utilize virtual reality equipment,which can emphasize the children’s central role in the learning process,better achieve educational goals,and improve teaching outcomes.

Research on the Dual-Creation Talent Training Model of New Energy Automobile Based on Virtual Simulation

At present,as China vigorously develops new energy automobiles,the social demand for related talents has increased significantly,so the relevant institutions need to optimize and adjust the talent training mode to help the development of new energy automobiles.This paper summarizes the existing problems of China’s new energy automobile talent training mode,and analyzes the significance of the virtual simulation-based dual-creation talent training mode of new energy automobile and its specific implementation strategies,in order to provide references for the relevant personnel.

Hybrid Teaching Reform of Veterinary Microbiology Based on the Combination of Virtual Simulation and Problem-Based Learning

The Veterinary Microbiology course is centered around the diagnosis and testing of pathogenic microorganisms,with the core value of“moral education and character development.”It reconstructs multidimensional teaching resources by integrating disciplinary achievements with clinical cases and implements a hybrid teaching approach combining virtual simulation and problem-based learning(PBL)through the“three stages+four models+three reflections”framework.Dual-qualification teachers employ various teaching methods,create a“six-in-one”model for ideological and political education,and conduct formative assessments based on the principles of diversified objectives and process emphasis.The hybrid teaching reform addresses issues such as fragmented knowledge,insufficient class hours,weak animal disease diagnostic abilities among students,limited application and expansion of knowledge points,and students’lack of proactive critical thinking skills.The application of hybrid teaching has shown significant advantages and effectiveness,providing a reference for teaching reform in similar microbiology courses.

Construction and Practice of First-Class Courses on Virtual Simulation Experimental Teaching of Urban Overpasses

Virtual simulation experiment,as a new way to promote the digital transformation of education,has a broad development prospect and application value.The civil engineering experimental volume and space are huge,it has a long construction period,is highly dangerous,and is difficult to experiment with.In order to solve the contradiction between the traditional theory teaching of civil engineering and the engineering training of students,the construction of virtual simulation experimental teaching courses with a high degree of realism,intuition,and accuracy can be used as a useful supplement and innovation of experimental and practical teaching.This paper takes the virtual simulation experimental teaching course of urban overpasses as an example,introduces the necessity and practicability of the course construction,and describes the experimental principle structure of the course,the simulation scene design,the experimental teaching process,the experimental method,etc.The course has achieved good application results,and it has been recognized as the first-class virtual simulation teaching course of the Chongqing Municipal Government,which provides certain references to the construction of the same type of courses in the civil engineering profession.