Comparing Hand Gestures and a Gamepad Interface for Locomotion in Virtual Environments

Hand gesture is a new and promising interface for locomotion in virtual environments. While several previous studies have proposed different hand gestures for virtual locomotion, little is known about their differences in terms of performance and user preference in virtual locomotion tasks. In the present paper, we presented three different hand gesture interfaces and their algorithms for locomotion, which are called the Finger Distance gesture, the Finger Number gesture and the Finger Tapping gesture. These gestures were inspired by previous studies of gesture-based locomotion interfaces and are typical gestures that people are familiar with in their daily lives. Implementing these hand gesture interfaces in the present study enabled us to systematically compare the differences between these gestures. In addition, to compare the usability of these gestures to locomotion interfaces using gamepads, we also designed and implemented a gamepad interface based on the Xbox One controller. We conducted empirical studies to compare these four interfaces through two virtual locomotion tasks. A desktop setup was used instead of sharing a head-mounted display among participants due to the concern of the Covid-19 situation. Through these tasks, we assessed the performance and user preference of these interfaces on speed control and waypoints navigation. Results showed that user preference and performance of the Finger Distance gesture were close to that of the gamepad interface. The Finger Number gesture also had close performance and user preference to that of the Finger Distance gesture. Our study demonstrates that the Finger Distance gesture and the Finger Number gesture are very promising interfaces for virtual locomotion. We also discuss that the Finger Tapping gesture needs further improvements before it can be used for virtual walking

ComCLIP: Training-Free Compositional Image and Text Matching

Contrastive Language-Image Pretraining (CLIP) has demonstrated great zero-shot performance for image-text matching because of its holistic use of natural language supervision that covers large-scale, open-world visual concepts. However, it is still challenging to adapt CLIP to compositional image and text matching -- a more challenging image and matching mask requiring the model understanding of compositional word concepts and visual components. Towards better compositional generalization in zero-shot image and text matching, in this paper, we study the problem from a causal perspective: the erroneous semantics of individual entities are essentially confounders that cause the matching failure. Therefore, we propose a novel training-free compositional CLIP model (ComCLIP). ComCLIP disentangles input images into subjects, objects, and action sub-images and composes CLIP's vision encoder and text encoder to perform evolving matching over compositional text embedding and sub-image embeddings. In this way, ComCLIP can mitigate spurious correlations introduced by the pretrained CLIP models and dynamically assess the contribution of each entity when performing image and text matching. Experiments on compositional image-text matching on SVO and ComVG and general image-text retrieval on Flickr8K demonstrate the effectiveness of our plug-and-play method, which boosts the zero-shot inference ability of CLIP even without further training or fine-tuning of CLIP

MMCosine: Multi-Modal Cosine Loss Towards Balanced Audio-Visual Fine-Grained Learning

Audio-visual learning helps to comprehensively understand the world by fusing practical information from multiple modalities. However, recent studies show that the imbalanced optimization of uni-modal encoders in a joint-learning model is a bottleneck to enhancing the model's performance. We further find that the up-to-date imbalance-mitigating methods fail on some audio-visual fine-grained tasks, which have a higher demand for distinguishable feature distribution. Fueled by the success of cosine loss that builds hyperspherical feature spaces and achieves lower intra-class angular variability, this paper proposes Multi-Modal Cosine loss, MMCosine. It performs a modality-wise $L_2$ normalization to features and weights towards balanced and better multi-modal fine-grained learning. We demonstrate that our method can alleviate the imbalanced optimization from the perspective of weight norm and fully exploit the discriminability of the cosine metric. Extensive experiments prove the effectiveness of our method and the versatility with advanced multi-modal fusion strategies and up-to-date imbalance-mitigating methods

OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control

In this work, we introduce OmniDrones, an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim. It employs a bottom-up design approach that allows users to easily design and experiment with various application scenarios on top of GPU-parallelized simulations. It also offers a range of benchmark tasks, presenting challenges ranging from single-drone hovering to over-actuated system tracking. In summary, we propose an open-sourced drone simulation platform, equipped with an extensive suite of tools for drone learning. It includes 4 drone models, 5 sensor modalities, 4 control modes, over 10 benchmark tasks, and a selection of widely used RL baselines. To showcase the capabilities of OmniDrones and to support future research, we also provide preliminary results on these benchmark tasks. We hope this platform will encourage further studies on applying RL to practical drone systems.Comment: Submitted to IEEE RA-

The design of low-frequency, low-g piezoelectric micro energy harvesters

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 107-112).A low-frequency, low-g piezoelectric MEMS energy harvester has been designed. Theoretically, this new generation energy harvester will generate electric power from ambient vibrations in the frequency range of 200~30OHz at excitation amplitude of 0.5g. Our previous energy harvester successfully resolved the gain-bandwidth dilemma and increased the bandwidth two orders of magnitude. By utilizing a doubly clamed beam resonator, the stretching strain triggered at large deflection stiffens the beam and transforms the dynamics to nonlinear regime, and increases the bandwidth. However, the high resonance frequency (1.3kHz) and the high-g acceleration requirement (4-5g) shown in the testing experiments limited the applications of this technology. To improve the performance of the current energy harvesters by lowering the operating frequency and excitation level, different designs have been generated and investigated. Moreover, a design framework has been formulated to improve the design in a systematic way with higher accuracy. Based on this design framework, parameter optimization has been carried out, and a quantitative design with enhanced performance has been proposed. Preliminary work on fabrication and testing setup has been done to prepare for the future experimental verification of the new design.by Ruize Xu.S.M

Growth hormone-releasing hormone agonist attenuates vascular calcification in diabetic db/db mice

IntroductionVascular calcification (VC) is an independent risk factor for cardiovascular diseases. VC increases mortality of all-causes. VC is one of most common cardiovascular complications in type II diabetes. So far, no therapy has been proven to be effective in treatment of clinical VC. The present study investigated the therapeutic effects of MR409, an agonistic analog of growth hormone-releasing hormone (GHRH-A), on VC in diabetic db/db mice.Method and resultDiabetic mice were injected with MR409 subcutaneously every day for 8 weeks. Long-term treatment with MR409 improved serum lipid profile and endothelium-dependent relaxation to acetylcholine, and reduced vascular structural injury in diabetic mice without affecting serum growth hormone level. Echocardiography showed that calcium plaques present in heart valve of diabetic mice disappeared in diabetic mice after treatment with MR409. MR409 inhibited vascular calcium deposition associated with a marked reduction in the expressions of osteogenic-regulated alkaline phosphatase (ALP) and transcription osteogenic marker gene Runx2 in diabetic mice. MR409 also inhibited vascular reactive oxygen species (ROS) generation and upregulated the expressions of anti-calcifying protein Klotho in diabetic mice.DiscussionOur results demonstrate that GHRH-A MR409 can effectively attenuate VC and heart valve calcification, and protect against endothelial dysfunction and vascular injury in diabetic mice without significantly affecting pituitary-growth hormone axis. The mechanisms may involve upregulation of anti-calcifying protein Klotho and reduction in vascular ROS and the expression of redox sensitive osteogenic genes Runx2 and ALP. GHRH-A may represent a new pharmacological strategy for treatment of VC and diabetics associated cardiovascular complications

Comparative genetic architectures of schizophrenia in East Asian and European populations

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations

Low-Frequency, Low-G MEMS Piezoelectric Energy Harvester

This paper reports the design, modeling and fabrication of a novel MEMS device for low-frequency, low-g vibration energy harvesting. The new design is based on bi-stable buckled beam structure. To implement the design at MEMS scale, we further proposed to employ residual stress in micro-fabricated thin films. With an electromechanical lumped model, the multi-layer beam could be designed to achieve bi-stability with desired frequency range and excitation amplitude. A macro-scale prototype has been built and tested to verifies the prediction of the performance enhancement of the bi-stable beam at low frequencies. A MEMS scale prototype has been fabricated and tested to verify the frequency range at low excitation amplitude. The MEMS device shows wide operating frequency range from 50Hz to 150Hz at 0.2g without external proof mass. The same device with external proof mass has lower frequency range (< 10Hz) with boosted deflection amplitude.SUTD-MIT International Design Centre (IDC

A Partial Order OWA Operator for Solving the OWA Weighing Dilemma

Prior weights are necessary for the application of ordered weighted averaging (OWA) operators, but obtaining them is expensive and contentious, which restricts the application of operators. To address the weighting issue, the weight space is used to &#x201C;replace&#x201D; the conventional weight vector, and the operator comparison is then extended to a partial order comparison on the weight space. The results show that the partial order OWA operator can be used as long as the weight order is clear, that is, there is no need to take accurate values. The evaluation result is represented by a Hasse diagram. The partial order OWA operator retains the properties of the conventional operator, and the running cost is low. It can be seen from the example that the partial order OWA operator solves the time weight problem. It can compare, sort, and optimize data using the Hasse graph, and it can also implement hierarchical clustering. The comparison results have strong robustness