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.

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.

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.

An impact sensitivity assessment method of spacecraft based on virtual exterior wall

The impact sensitivity assessment of spacecraft is to obtain the probability of spacecraft encountering the OD/M(orbital debris or meteoroid),which is a prerequisite for survivability assessment of on-orbit spacecraft.An impact sensitivity assessment method of spacecraft based on virtual exterior wall was proposed to improve the computational efficiency.This method eliminates determination of the outermost surface elements of the spacecraft before generating the debris rays,which are assumed to originate from a non-concave virtual wall that completely wraps the spacecraft.The Dist Mesh method was adopted for the generating of the virtual wall to ensure its mesh quality.The influences of the sizes,mesh densities,shapes of the virtual wall on the efficiency and accuracy were considered to obtain the best combination of the size and mesh density of the wall and spacecraft.The results of this method were compared with those of S3DE(Survivability of Spacecraft in Space Debris Environment),BUMPER,MDPANTO,ESABASE2/Debris to verify the feasibility of the method.The PCHIP(Piecewise Cubic Hermite Interpolating Polynomial)was used to fit the size vs.flux relationship of the space debris to acquire the impact probability of OD/M with arbitrary size on the spacecraft.

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.

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.

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.

Opinions of Students on the Contribution of the DIVA 3D Virtual Dissection Table to the Teaching of Anatomy at the Faculty of Medicine and Odontostomatology of Bamako

Objective: Study the contribution of the DIVA 3D dissection table in the teaching of anatomy at the Faculty of Medicine and Odontology of Bamako. Material and Methods: This was a qualitative study carried out from November 1 to December 30, 2023 at the clinical and morphological anatomy laboratory of the Faculty of Medicine and Odontostomatology of Bamako. Included in this study were students who participated in practical and tutorial sessions. The variables studied during this study were: the previous performance of dissection on a cadaver by the students, the opinion of the students on dissection on a cadaver, the replacement of dissection on a cadaver by virtual dissection in the absence of a body, the level student satisfaction. Results: We surveyed 130 participants. The average age was 22 ± 0.2 years with extremes of 17 and 29 years. 95.3% of participants were students. According to 66.7% of participants, virtual dissection is a good palliative in the absence of a corpse. 95.3% of participants found using the virtual dissection table easy with an average of 7.88 ± 1.4. The overall assessment was well rated by 99.3% of participants. Conclusion: According to the results of this study, the virtual dissection table should be improved by integrating commented videos. The use of the DIVA 3D virtual dissection table during practical and tutorial sessions is well appreciated by the students. We believe that the teaching of anatomy using 3D digital technology should be included in the study programs of the Faculty of Medicine and Odontostomatology.

Personalized assessment and training of neurosurgical skills in virtual reality:An interpretable machine learning approach

Background Virtual reality technology has been widely used in surgical simulators,providing new opportunities for assessing and training surgical skills.Machine learning algorithms are commonly used to analyze and evaluate the performance of participants.However,their interpretability limits the personalization of the training for individual participants.Methods Seventy-nine participants were recruited and divided into three groups based on their skill level in intracranial tumor resection.Data on the use of surgical tools were collected using a surgical simulator.Feature selection was performed using the Minimum Redundancy Maximum Relevance and SVM-RFE algorithms to obtain the final metrics for training the machine learning model.Five machine learning algorithms were trained to predict the skill level,and the support vector machine performed the best,with an accuracy of 92.41%and Area Under Curve value of 0.98253.The machine learning model was interpreted using Shapley values to identify the important factors contributing to the skill level of each participant.Results This study demonstrates the effectiveness of machine learning in differentiating the evaluation and training of virtual reality neurosurgical performances.The use of Shapley values enables targeted training by identifying deficiencies in individual skills.Conclusions This study provides insights into the use of machine learning for personalized training in virtual reality neurosurgery.The interpretability of the machine learning models enables the development of individualized training programs.In addition,this study highlighted the potential of explanatory models in training external skills.

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.

Edge computing oriented virtual optical network mapping scheme based on fragmentation prediction

As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.

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.

Chemical simulation teaching system based on virtual reality and gesture interaction

Background Most existing chemical experiment teaching systems lack solid immersive experiences,making it difficult to engage students.To address these challenges,we propose a chemical simulation teaching system based on virtual reality and gesture interaction.Methods The parameters of the models were obtained through actual investigation,whereby Blender and 3DS MAX were used to model and import these parameters into a physics engine.By establishing an interface for the physics engine,gesture interaction hardware,and virtual reality(VR)helmet,a highly realistic chemical experiment environment was created.Using code script logic,particle systems,as well as other systems,chemical phenomena were simulated.Furthermore,we created an online teaching platform using streaming media and databases to address the problems of distance teaching.Results The proposed system was evaluated against two mainstream products in the market.In the experiments,the proposed system outperformed the other products in terms of fidelity and practicality.Conclusions The proposed system which offers realistic simulations and practicability,can help improve the high school chemistry experimental education.

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.

Research and Application of Caideng Model Rendering Technology for Virtual Reality

With the development of virtual reality (VR) technology, more and more industries are beginning to integrate with VR technology. In response to the problem of not being able to directly render the lighting effect of Caideng in digital Caideng scenes, this article analyzes the lighting model. It combines it with the lighting effect of Caideng scenes to design an optimized lighting model algorithm that fuses the bidirectional transmission distribution function (BTDF) model. This algorithm can efficiently render the lighting effect of Caideng models in a virtual environment. And using image optimization processing methods, the immersive experience effect on the VR is enhanced. Finally, a Caideng roaming interactive system was designed based on this method. The results show that the frame rate of the system is stable during operation, maintained above 60 fps, and has a good immersive experience.

Academic Stress Assessment Using Virtual Reality as an Educational Tool in Spine Surgery

Introduction: The evaluation of academic stress in medical students and residents is a topic of significant interest, given the considerable challenges they face during their learning process with traditional teaching methods. The use of technologies like virtual reality presents an opportunity to enhance their skills through simulations and training. The main objective of this study is to qualitatively assess the stress levels experienced by medical students and residents by integrating virtual reality into their current learning methods, aiming to improve their ability to manage stressors in their practice. Material and Methods: A questionnaire was conducted with 12 medical students and 12 Traumatology and orthopedics residents. The purpose of the questionnaire was to evaluate the levels of academic stress using the SISCO inventory. The stress levels were calculated by transforming average values into percentages, and the following criteria were assigned: 0 to 33% for Mild Stress, 34 to 66% for Moderate Stress, and 67 to 100% for Deep Stress. Then, a virtual reality class focused on spine surgery was provided. Both medical students and residents were trained using the Non Nocere SharpSurgeon software platform and Oculus Quest 2 virtual reality glasses. At the end of the session, a second questionnaire related to the practice with virtual reality was conducted with the same evaluation criteria and a comparative analysis was carried out. Results: 12 undergraduate students from Hospital Angeles Mexico, CDMX and 12 traumatology and orthopedics residents at Hospital Santa Fe, Bogota were evaluated. The students in CDMX reported an average qualitative stress of 28.50% during habitual practices, which decreased to an average of 14.67% after virtual reality practice. Residents in Bogotá experienced an average qualitative stress of 30.50% with their current learning methods but this reduced to an average of 13.92% after using virtual reality. These findings indicate that the use of virtual reality has a positive impact on reducing stress levels qualitatively. Conclusions: The use of virtual reality as a learning method for medical students and residents qualitatively improves stress levels. Further studies are required to define the potential uses of Virtual Reality to improve learning methods and emotional state in medical students and residents and for a quantitative assessment to validate the training as certified learning methods.

Virtual reality tools for training in gastrointestinal endoscopy:A systematic review

BACKGROUND Virtual reality(VR)has emerged as an innovative technology in endoscopy training,providing a simulated environment that closely resembles real-life scenarios and offering trainees a valuable platform to acquire and enhance their endoscopic skills.This systematic review will critically evaluate the effectiveness and feasibility of VR-based training compared to traditional methods.AIM To evaluate the effectiveness and feasibility of VR-based training compared to traditional methods.By examining the current state of the field,this review seeks to identify gaps,challenges,and opportunities for further research and implementation of VR in endoscopic training.METHODS The study is a systematic review,following the guidelines for reporting systematic reviews set out by the PRISMA statement.A comprehensive search command was designed and implemented and run in September 2023 to identify relevant studies available,from electronic databases such as PubMed,Scopus,Cochrane,and Google Scholar.The results were systematically reviewed.RESULTS Sixteen articles were included in the final analysis.The total number of participants was 523.Five studies focused on both upper endoscopy and colonoscopy training,two on upper endoscopy training only,eight on colonoscopy training only,and one on sigmoidoscopy training only.Gastrointestinal Mentor virtual endoscopy simulator was commonly used.Fifteen reported positive results,indicating that VR-based training was feasible and acceptable for endoscopy learners.VR technology helped the trainees enhance their skills in manipulating the endoscope,reducing the procedure time or increasing the technical accuracy,in VR scenarios and real patients.Some studies show that the patient discomfort level decreased significantly.However,some studies show there were no significant differences in patient discomfort and pain scores between VR group and other groups.CONCLUSION VR training is effective for endoscopy training.There are several well-designed randomized controlled trials with large sample sizes,proving the potential of this innovative tool.Thus,VR should be more widely adopted in endoscopy training.Furthermore,combining VR training with conventional methods could be a promising approach that should be implemented in training.