Induced surface and curvature tension equation of state for hadron resonance gas in finite volumes and its relation to morphological thermodynamics

Here, we develop an original approach to investigate the grand canonical partition function of the multicomponent mixtures of Boltzmann particles with hard-core interaction in finite and even small systems of the volumes above 20 fm3. The derived expressions of the induced surface tension equation of state (EoS) are analyzed in detail. It is shown that the metastable states, which can emerge in the finite systems with realistic interaction, appear at very high pressures at which the hadron resonance gas, most probably, is not applicable at all. It is shown how and under what conditions the obtained results for finite systems can be generalized to include into a formalism the equation for curvature tension. The applicability range of the obtained equations of induced surface and curvature tensions for finite systems is discussed and their close relations to the equations of the morphological thermodynamics are established. The hadron resonance gas model on the basis of the obtained advanced EoS is worked out. Also, this model is applied to analyze the chemical freeze-out of hadrons and light nuclei with the number of (anti-) baryons not exceeding 4. Their multiplicities were measured by the ALICE Collaboration in the central lead–lead collisions at the center-of-mass energy [Formula: see text] TeV.

Accuracy measurement of HoloLens2 IMUs in medical environments

As augmented reality devices become more available, collaborative work in the augmented space is expected to increase. Knowing the position of participants allows for realistic interaction rather than passive participation. The HoloLens 2’s camera and IMUs fuse data to locate the device. In this paper, accuracy and repeatability of the HoloLens2 position finding was analysed to provide a quantitative measure of pose repeatability and deviation from a path while in motion. Deviation from a circular path was found to be below 5 mm per 628 mm travelled.

Effect of 2.5D haptic feedback on virtual object perception via a stylus

As touch screen technologies advanced, a digital stylus has become one of the essential accessories for a smart device. However, most of the digital styluses so far provide limited tactile feedback to a user. Therefore we focused on the limitation and noted the potential that a digital stylus may offer the sensation of realistic interaction with virtual environments on a touch screen using a 2.5D haptic system. Thus, we developed a haptic stylus with SMA (Shape Memory Alloy) and a 2.5D haptic rendering algorithm to provide lateral skin-stretch feedback to mimic the interaction force between fingertip and a stylus probing over a bumpy surface. We conducted two psychophysical experiments to evaluate the effect of 2.5D haptic feedback on the perception of virtual object geometry. Experiment 1 investigated the human perception of virtual bump size felt via the proposed lateral skin-stretch stylus and a vibrotactile stylus as reference. Experiment 2 tested the participants’ ability to count the number of virtual bumps rendered via the two types of haptic styluses. The results of Experiment 1 indicate that the participants felt the size of virtual bumps rendered with lateral skin-stretch stylus significantly sensitively than the vibrotactile stylus. Similarly, the participants counted the number of virtual bumps rendered with the lateral skin-stretch stylus significantly better than with the vibrotactile stylus. A common result of the two experiments is a significantly longer mean trial time for the skin-stretch stylus than the vibrotactile stylus.

Realism Matters. Eye movements in VR reveal prior tool knowledge, intended interaction, and end-state comfort planning

Seminal studies on human cognitive behavior have been conducted in controlled laboratory settings, demonstrating that visual attention is mainly goal-directed and allocated based on the action performed. However, it is unclear how far these results generalize to cognition in more naturalistic settings. The present study investigates active inference processes revealed by eye movements during interaction with familiar and novel tools with two levels of realism of the performed action. We presented participants with 3D tool models that were either familiar or unfamiliar, oriented congruent or incongruent to their handedness, and asked participants to interact with them by either lifting or using. Importantly, we used the same experimental design in two setups. In the first experiment, participants interacted with a VR controller; in the second, they performed the task with a more realistic interaction setup that allowed differentiated hand and finger movements. We used linear mixed models to determine the odds of fixations on the tool effector vs. handle before action initiation. The results show that participants fixate more on the tool's effector part before action initiation during the use task for unfamiliar tools. Furthermore, under more natural interaction conditions, subjects fixate more on the tool's handle as a function of the tool's orientation, well before the action was executed. Secondly, the spatial viewing bias on the tool reveals early fixations are associated with the task and familiarity of the tools. In contrast, later fixations are associated with the manual planning of the interaction. In sum, the findings from the experiments suggest that fixations are made in a task-oriented way to extract the mechanical properties of the tools to plan the intended action well before action initiation. Further, in more natural conditions, fixations are made towards proximal goals of optimally planning the grasp even when the perceived action on the tools is identical. Thus, the realism of the action in a virtual environment seems to be as important as the sensory stimulation.

A novel no-sensors 3D model reconstruction from monocular video frames for a dynamic environment

Occlusion awareness is one of the most challenging problems in several fields such as multimedia, remote sensing, computer vision, and computer graphics. Realistic interaction applications are suffering from dealing with occlusion and collision problems in a dynamic environment. Creating dense 3D reconstruction methods is the best solution to solve this issue. However, these methods have poor performance in practical applications due to the absence of accurate depth, camera pose, and object motion.This paper proposes a new framework that builds a full 3D model reconstruction that overcomes the occlusion problem in a complex dynamic scene without using sensors’ data. Popular devices such as a monocular camera are used to generate a suitable model for video streaming applications. The main objective is to create a smooth and accurate 3D point-cloud for a dynamic environment using cumulative information of a sequence of RGB video frames. The framework is composed of two main phases. The first uses an unsupervised learning technique to predict scene depth, camera pose, and objects’ motion from RGB monocular videos. The second generates a frame-wise point cloud fusion to reconstruct a 3D model based on a video frame sequence. Several evaluation metrics are measured: Localization error, RMSE, and fitness between ground truth (KITTI’s sparse LiDAR points) and predicted point-cloud. Moreover, we compared the framework with different widely used state-of-the-art evaluation methods such as MRE and Chamfer Distance. Experimental results showed that the proposed framework surpassed the other methods and proved to be a powerful candidate in 3D model reconstruction.

Complex-Valued Pix2pix—Deep Neural Network for Nonlinear Electromagnetic Inverse Scattering

Nonlinear electromagnetic inverse scattering is an imaging technique with quantitative reconstruction and high resolution. Compared with conventional tomography, it takes into account the more realistic interaction between the internal structure of the scene and the electromagnetic waves. However, there are still open issues and challenges due to its inherent strong non-linearity, ill-posedness and computational cost. To overcome these shortcomings, we apply an image translation network, named as Complex-Valued Pix2pix, on the inverse scattering problem of electromagnetic field. Complex-Valued Pix2pix includes two parts of Generator and Discriminator. The Generator employs a multi-layer complex valued convolutional neural network, while the Discriminator computes the maximum likelihoods between the original value and the reconstructed value from the aspects of the two parts of the complex: real part and imaginary part, respectively. The results show that the Complex-Valued Pix2pix can learn the mapping from the initial contrast to the real contrast in microwave imaging models. Moreover, due to the introduction of discriminator, Complex-Valued Pix2pix can capture more features of nonlinearity than traditional Convolutional Neural Network (CNN) by confrontation training. Therefore, without considering the time cost of training, Complex-Valued Pix2pix may be a more effective way to solve inverse scattering problems than other deep learning methods. The main improvement of this work lies in the realization of a Generative Adversarial Network (GAN) in the electromagnetic inverse scattering problem, adding a discriminator to the traditional Convolutional Neural Network (CNN) method to optimize network training. It has the prospect of outperforming conventional methods in terms of both the image quality and computational efficiency.

Nuclear matter distributions of neutron rich 6He, 11Li, 14Be and 17B halo nuclei studied by the Bear–Hodgson potential

The radial wave functions of the Bear–Hodgson potential have been used to study the ground state features such as the proton, neutron and matter densities and the associated rms radii of two neutrons halo 6He, [Formula: see text]Li, [Formula: see text]Be and [Formula: see text]B nuclei. These halo nuclei are treated as a three-body system composed of core and outer two-neutron [Formula: see text]. The radial wave functions of the Bear–Hodgson potential are used to describe the core and halo density distributions. The interaction of core-neutron takes the Bear–Hodgson potential form. The outer two neutrons of 6He and [Formula: see text]Li interact by the realistic interaction REWIL whereas those of [Formula: see text]Be and [Formula: see text]B interact by the realistic interaction of HASP. The obtained results show that this model succeeds in reproducing the neutron halo in these nuclei. From the calculated densities, it is found that 6He, [Formula: see text]Li, [Formula: see text]Be and [Formula: see text]B have a long tail in neutron and matter densities which is consistent with the experimental data. Elastic charge form factors for these halo nuclei are analyzed via the plane wave Born approximation.

Usability of Food Size Aids in Mobile Dietary Reporting Apps for Young Adults: Randomized Controlled Trial

Background Young adults are more likely to use self-managed dietary reporting apps. However, there is scant research examining the user experience of different measurement approaches for mobile dietary reporting apps when dealing with a wide variety of food shapes and container sizes. Objective Field user experience testing was conducted under actual meal conditions to assess the accuracy, efficiency, and subjective reaction of three food portion measurement methods embedded in a developed mobile app. Key-in–based aid (KBA), commonly used in many current apps, relies on the user’s ability to key in volumes or weights. Photo-based aid (PBA) extends traditional assessment methods, allowing users to scroll, observe, and select a reduced-size image from a set of options. Gesture-based aid (GBA) is a new experimental approach in which the user makes finger movements on the screen to roughly describe food portion boundaries accompanied by a background reference. Methods A group of 124 young adults aged 19 to 26 years was recruited for a head-to-head randomized comparison and divided into 3 groups: a KBA (n=42) control group and PBA (n=41) and GBA (n=41) experimental groups. In total, 3 meals (ie, breakfast, lunch, and dinner) were served in a university cafeteria. Participants were provided with 25 dishes and beverages for selection, with a variety of food shapes and containers that reflect everyday life conditions. The accuracy of and time spent on realistic interaction during food portion estimation and the subjective reaction of each aid were recorded and analyzed. Results Participants in the KBA group provided the highest accuracy in terms of hash brown weight (P=.004) and outperformed PBA or GBA for many soft drinks in cups. PBA had the best results for a cylindrical hot dog (P<.001), irregularly shaped pork chop (P<.001), and green tea beverage (660 mL; P<.001). GBA outperformed PBA for most drinks, and GBA outperformed KBA for some vegetables. The GBA group spent significantly more time assessing food items than the KBA and PBA groups. For each aid, the overall subjective reaction based on the score of the System Usability Scale was not significantly different. Conclusions Experimental results show that each aid had some distinguishing advantages. In terms of user acceptance, participants considered all 3 aids to be usable. Furthermore, users’ subjective opinions regarding measurement accuracy contradicted the empirical findings. Future work will consider the use of each aid based on food or container shape and integrate the various advantages of the 3 different aids for better results. Our findings on the use of portion size aids are based on realistic and diverse food items, providing a useful reference for future app improvement of an effective, evidence-based, and acceptable feature. Trial Registration International Standard Randomized Controlled Trial Registry ISRCTN36710750; http://www.controlled-trials.com/ISRCTN36710750.

Identification and characterization of differentially expressed genes in Caenorhabditis elegans in response to pathogenic and nonpathogenic Stenotrophomonas maltophilia

Background: Stenotrophomonas maltophilia is an emerging nosocomial pathogen that causes infection in immunocompromised patients. S. maltophilia isolates are genetically diverse, contain diverse virulence factors, and are variably pathogenic within several host species. Members of the Stenotrophomonas genus are part of the native microbiome of C. elegans , being found in greater relative abundance within the worm than its environment, suggesting that these bacteria accumulate within C. elegans . Thus, study of the C. elegans-Stenotrophomonas interaction is of both medical and ecological significance. To identify host defense mechanisms, we analyzed the C. elegans transcriptomic response to S. maltophilia strains of varying pathogenicity: K279a, an avirulent clinical isolate, JCMS, a virulent strain isolated in association with soil nematodes near Manhattan, KS, and JV3, an even more virulent environmental isolate. Results: Overall, we found 145 genes that are commonly differentially expressed in response to pathogenic S. maltophilia strains, 89% of which are upregulated, with many even further upregulated in response to JV3 as compared to JCMS. There are many more JV3-specific differentially expressed genes (225, 11% upregulated) than JCMS-specific differentially expressed genes (14, 86% upregulated), suggesting JV3 has unique pathogenic mechanisms that could explain its increased virulence. We used connectivity within a gene network model to choose pathogen-specific and strain-specific differentially expressed candidate genes for functional analysis. Mutations in 13 of 22 candidate genes caused significant differences in C. elegans survival in response to at least one S. maltophilia strain, although not always the strain that induced differential expression, suggesting a dynamic response to varying levels of pathogenicity. Conclusions: Variation in observed pathogenicity and differences in host transcriptional responses to S. maltophilia strains reveal that strain-specific mechanisms play important roles in S. maltophilia pathogenesis. Furthermore, utilizing bacteria closely related to strains found in C. elegans natural environment provides a more realistic interaction for understanding host-pathogen response.