GPX7 reduces chondrocyte inflammation and extracellular matrix degradation triggered by IL­1ß, via a mechanism mediated by ferroptosis.

During osteoarthritis (OA), chondrocytes become highly active, with increased matrix synthesis and inflammatory cytokine­induced catabolic pathways. Early intervention strategies targeting pathological changes may attenuate or halt disease progression. The present study aimed to reveal the role of glutathione peroxidase (GPX)7 in OA. For this purpose, a research model was established by inducing C28/I2 human chondrocytes with interleukin (IL)­1ß, and the expression level of GPX7 was determined. To explore its roles, C28/I2 cells were transfected to gain GPX7 overexpression. The effects of GPX7 overexpression on intracellular inflammation, extracellular matrix (ECM) degradation, apoptosis and ferroptosis were then evaluated. In addition, the cells were treated with the ferroptosis inducer, erastin, and its effects on the aforementioned phenotypes were assessed. The level of GPX7 was decreased in response to IL­1ß treatment, and GPX7 overexpression suppressed cellular inflammation, ECM degradation and apoptosis. Moreover, the reduction of lipid peroxidation, ferrous ions and transferrin indicated that GPX7 overexpression inhibited ferroptosis. Subsequently, inflammation, ECM degradation and apoptosis were found to be promoted in the cells upon treatment with erastin. These findings suggested that the regulatory role of GPX7 may be mediated by a pathway involving ferroptosis. On the whole, the present study revealed that GPX7 reduces IL­1ß­induced chondrocyte inflammation, apoptosis and ECM degradation partially through a mechanism involving ferroptosis. The results of the present study lay a theoretical foundation for subsequent OA­related research and may enable the development of translational strategies for the treatment of OA.

Evaluation of a Standard Dietary Regimen Combined with Heat-Inactivated Lactobacillus gasseri HM1, Lactoferrin-Producing HM1, and Their Sonication-Inactivated Variants in the Management of Metabolic Disorders in an Obesity Mouse Model.

This study investigated the impact of incorporating various inactivated probiotic formulations, with or without recombinant lactoferrin (LF) expression, into a standard chow diet on metabolic-related disorders in obese mice. After inducing obesity through a 13-week high-fat diet followed by a standard chow diet, mice received daily oral administrations of different probiotics for 6 weeks using the oral gavage approach. These probiotic formulations consisted of a placebo (MRS), heat-inactivated Lactobacillus gasseri HM1 (HK-HM1), heat-killed LF-expression HM1 (HK-HM1/LF), sonication-killed HM1 (SK-HM1), and sonication-killed LF-expression HM1 (SK-HM1/LF). The study successfully induced obesity, resulting in worsened glucose tolerance and insulin sensitivity. Interestingly, the regular diet alone improved glucose tolerance, and the addition of inactivated probiotics further enhanced this effect, with SK-HM1/LF demonstrating the most noticeable improvement. However, while regular dietary intervention alone improved insulin sensitivity, probiotic supplementation did not provide additional benefits in this aspect. Inflammation in perirenal and epididymal fat tissues was partially alleviated by the regular diet and further improved by probiotics, particularly by SK-HM1, which showed the most significant reduction. Additionally, HK-HM1 and HK-HM1/LF supplements could contribute to the improvement of serum total triglycerides or total cholesterol, respectively. Overall, incorporating inactivated probiotics into a regular diet may enhance metabolic indices, and recombinant LF may offer potential benefits for improving glucose tolerance.

Human-robot facial coexpression.

Large language models are enabling rapid progress in robotic verbal communication, but nonverbal communication is not keeping pace. Physical humanoid robots struggle to express and communicate using facial movement, relying primarily on voice. The challenge is twofold: First, the actuation of an expressively versatile robotic face is mechanically challenging. A second challenge is knowing what expression to generate so that the robot appears natural, timely, and genuine. Here, we propose that both barriers can be alleviated by training a robot to anticipate future facial expressions and execute them simultaneously with a human. Whereas delayed facial mimicry looks disingenuous, facial coexpression feels more genuine because it requires correct inference of the human's emotional state for timely execution. We found that a robot can learn to predict a forthcoming smile about 839 milliseconds before the human smiles and, using a learned inverse kinematic facial self-model, coexpress the smile simultaneously with the human. We demonstrated this ability using a robot face comprising 26 degrees of freedom. We believe that the ability to coexpress simultaneous facial expressions could improve human-robot interaction.

Functional nanoporous graphene superlattice.

Two-dimensional (2D) superlattices, formed by stacking sublattices of 2D materials, have emerged as a powerful platform for tailoring and enhancing material properties beyond their intrinsic characteristics. However, conventional synthesis methods are limited to pristine 2D material sublattices, posing a significant practical challenge when it comes to stacking chemically modified sublattices. Here we report a chemical synthesis method that overcomes this challenge by creating a unique 2D graphene superlattice, stacking graphene sublattices with monodisperse, nanometer-sized, square-shaped pores and strategically doped elements at the pore edges. The resulting graphene superlattice exhibits remarkable correlations between quantum phases at both the electron and phonon levels, leading to diverse functionalities, such as electromagnetic shielding, energy harvesting, optoelectronics, and thermoelectrics. Overall, our findings not only provide chemical design principles for synthesizing and understanding functional 2D superlattices but also expand their enhanced functionality and extensive application potential compared to their pristine counterparts.

LSR-YOLO: A High-Precision, Lightweight Model for Sheep Face Recognition on the Mobile End.

The accurate identification of sheep is crucial for breeding, behavioral research, food quality tracking, and disease prevention on modern farms. As a result of the time-consuming, expensive, and unreliable problems of traditional sheep-identification methods, relevant studies have built sheep face recognition models to recognize sheep through facial images. However, the existing sheep face recognition models face problems such as high computational costs, large model sizes, and weak practicality. In response to the above issues, this study proposes a lightweight sheep face recognition model named LSR-YOLO. Specifically, the ShuffleNetv2 module and Ghost module were used to replace the feature extraction module in the backbone and neck of YOLOv5s to reduce floating-point operations per second (FLOPs) and parameters. In addition, the coordinated attention (CA) module was introduced into the backbone to suppress non-critical information and improve the feature extraction ability of the recognition model. We collected facial images of 63 small-tailed Han sheep to construct a sheep face dataset and further evaluate the proposed method. Compared to YOLOv5s, the FLOPs and parameters of LSR-YOLO decreased by 25.5% and 33.4%, respectively. LSR-YOLO achieved the best performance on the sheep face dataset, and the mAP@0.5 reached 97.8% when the model size was only 9.5 MB. The experimental results show that LSR-YOLO has significant advantages in recognition accuracy and model size. Finally, we integrated LSR-YOLO into mobile devices and further developed a recognition system to achieve real-time recognition. The results show that LSR-YOLO is an effective method for identifying sheep. The method has high recognition accuracy and fast recognition speed, which gives it a high application value in mobile recognition and welfare breeding.

Effect of a moderate-intensity comprehensive exercise program on body composition, muscle strength, and physical performance in elderly females with sarcopenia.

Objective: This study aimed at examining an eight-week moderate-intensity comprehensive exercise training program on the parameters of sarcopenia in elderly females. Methods: A total of 49 community-dwelling elderly females with sarcopenia (65.5 ± 2.5) were assigned randomly to an experiment group (EG, n = 25) and a control group (CG, n = 24). In the EG, an eight-week comprehensive exercise training program was implemented, in 1 h, 3 times per week, a total of 24 sessions. The CG only received health public education per two weeks, a total of 4 times. Subsequently, the differences between the two groups were tested through two-way repeated ANOVA. Results: ASM, SMM, and SMI in the EG were significantly improved by 0.26 kg, 0.18 kg, and 0.10 kg/m2, respectively. Group-by-time interactions were significantly different on the ASM [F (1,47) = 6.25, η2 = 0.12] and SMI [F (1,47) = 6.77, η2 = 0.13]. Muscle strength was improved 0.8 kg in the EG. Significant group-by-time interaction differences were reported in the handgrip strength [F (1,47) = 6.8, η2 = 0.13] after the eight-week intervention. Compared with the baseline, gait speed was improved a 0.05 m/s and 5-time chair stand was decreased a 0.27 s in the EG. Group-by-time interactions were significantly different in 5-time chair stand [F (1, 47) = 6.35, η2 = 0.12]. Conclusions: The moderate-intensity comprehensive exercise was confirmed as a safe and convenient exercise program. Although a load of training intensity is not sufficient to improve the gait speed, this exercise protocol is promising in delaying overall results in community-dwelling sarcopenia elderly females and contributes to the improvement of muscle mass, handgrip strength, and 5TCS.

Experimental Insights into Conformational Ensembles of Assembled ß-Sheet Peptides.

Deciphering the conformations and interactions of peptides in their assemblies offers a basis for guiding the rational design of peptide-assembled materials. Here we report the use of scanning tunneling microscopy (STM), a single-molecule imaging method with a submolecular resolution, to distinguish 18 types of coexisting conformational substates of the ß-strand of the 8-37 segment of human islet amyloid polypeptide (hIAPP 8-37). We analyzed the pairwise peptide-peptide interactions in the hIAPP 8-37 assembly and found 82 interconformation interactions within a free energy difference of 3.40 kBT. Besides hIAPP 8-37, this STM method validates the existence of multiple conformations of other ß-sheet peptide assemblies, including mutated hIAPP 8-37 and amyloid-ß 42. Overall, the results reported in this work provide single-molecule experimental insights into the conformational ensemble and interpeptide interactions in the ß-sheet peptide assembly.

Self-catalyzed Co, N-doped carbon nanotubes-grafted hollow carbon polyhedrons as efficient trifunctional electrocatalysts for zinc-air batteries and self-powered overall water splitting.

It is still essential and challenging to explore inexpensive and versatile electrocatalysts for oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER), for the development of rechargeable zinc-air batteries (ZABs) and overall water splitting. Herein, a rambutan-like trifunctional electrocatalyst is fabricated by re-growth of secondary zeolitic imidazole frameworks (ZIFs) on ZIF-8-derived ZnO and the following carbonization treatment. Co nanoparticles (NPs) are encapsulated into N-doped carbon nanotubes (NCNT) grafted N-enriched hollow carbon (NHC) polyhedrons to form the Co-NCNT@NHC catalyst. The strong synergy between the N-doped carbon matrix and Co NPs endows Co-NCNT@NHC with trifunctional catalytic activity. The Co-NCNT@NHC displays a half-wave potential of 0.88 V versus RHE for ORR in alkaline electrolyte, an overpotential of 300 mV at 20 mA cm-2 for OER, and an overpotential of 180 mV at 10 mA cm-2 for HER. Impressively, a water electrolyzer is successfully powered by two rechargeable ZABs in series, with Co-NCNT@NHC as the 'all-in-one' electrocatalyst. These findings are inspiring for the rational fabrication of high-performance and multifunctional electrocatalysts intended for the practical application of integrated energy-related systems.

Design of a self-cleanable multilevel anticounterfeiting interface through covalent chemical modulation.

Counterfeit products have posed a significant threat to consumers safety and the global economy. To address this issue, extensive studies have been exploring the use of coatings with unclonable, microscale features for authentication purposes. However, the ease of readout, and the stability of these features against water, deposited dust, and wear, which are required for practical use, remain challenging. Here we report a novel class of chemically functionalizable coatings with a combination of a physically unclonable porous topography and distinct physiochemical properties (e.g., fluorescence, water wettability, and water adhesion) obtained through orthogonal chemical modifications (i.e., 1,4-conjugate addition reaction and Schiff-base reaction at ambient conditions). Unprecedentedly, a self-cleanable and physically unclonable coating is introduced to develop a multilevel anticounterfeiting interface. We demonstrate that the authentication of the fluorescent porous topography can be verified using deep learning. More importantly, the spatially selective chemical modifications can be read with the naked eye via underwater exposure and UV light illumination. Overall, the results reported in this work provide a facile basis for designing functional surfaces capable of independent and multilevel decryption of authenticity.

Calcium alginate gels-functionalized polyurethane foam decorated with silver nanoparticles as an antibacterial agent for point-of-use water disinfection.

This paper reports the preparation of calcium alginate gels-functionalized PUF decorated with AgNPs (CA/PUF@Ag) by in situ reduction of Ag+ ions to form AgNPs with weakly reducing glycerol in CA/PUF composite. The water-adsorbing capacity, chemical structure, crystalline nature, elemental composition and morphologies of the composite were characterized. The Ag release behavior of CA/PUF@Ag was investigated. The inhibition zone test, time-dependent co-culture assay, test tube test, and antibacterial filtration experiment with Escherichia coli as an indicator of bacterial contamination were conducted to explore the antimicrobial efficacy. Results indicated that the CA/PUF@Ag prepared at 0.25 % w/v of SA could absorb more water with a higher swelling ratio of 8.0 g/g than that of PUF@Ag (6.0 g/g), which was subsequently squeezed by minimal pressure stimuli. The CA/PUF@Ag had a larger initial AgNPs loading amount (8.48 mg/g), lower Ag release concentration (44.35 µg/L) and lower Ag release rate (0.27 %) after 14 days tests than those of PUF@Ag (7.93 mg/g, 80.87 µg/L and 0.60 % respectively). The CA/PUF@Ag was highly reusable because bacterial cells in the squeezed water recovered from the composite were completely inactivated over five cycles of operation, and exhibited good antibacterial efficacy as an antibacterial filter in a flow test.

Therapeutic effects of orally administration of viable and inactivated probiotic strains against murine urinary tract infection.

Urinary tract infections (UTIs) are highly prevalent bacterial infections that pose significant health risks. Specific probiotic strains have been recommended for UTI control and management of antibiotic resistance. Otherwise, para-probiotics, defined as inactivated probiotic cells, offer potential advantages by minimizing risks associated with live microorganisms. However, the effectiveness of heat-killed probiotic strains against UTIs remains uncertain. Additionally, lactoferrin (LF), an iron-binding glycoprotein, exhibits immunomodulatory, antimicrobial, and anti-inflammatory properties. Recently, we had developed recombinant LF-expression probiotics, which can display considerate antibacterial activities against select food-borne pathogens in vitro. Thus, the present study aimed to evaluate the antibacterial activities of heat-killed natural and recombinant LF-expressing probiotics against UTIs in vitro and in vivo. Firstly, using in vitro assays, we assessed the antibacterial activity of heat-killed natural and recombinant LF-expressing probiotics against uropathogenic Escherichia coli and Klebsiella pneumoniae. Among the tested probiotics, 10 heat-killed LF-expressing strains displayed superior antibacterial efficacy compared to 12 natural probiotics. Based on their potent in vitro activity, selected probiotics were formulated into three probiotic mixtures: viable probiotic mixture (LAB), heat-killed probiotic mixture (HK-LAB), and heat-killed LF-expressing probiotic mixture (HK-LAB/LF). To further evaluate the therapeutic potential of these probiotic mixtures in vivo, we established a murine model of UTIs by intraurethral administration of E. coli to 40 female C57BL/6JNarl mice on day 0. Subsequently, mice received oral gavage of placebo, LAB, HK-LAB, or HK-LAB/LF for 21 consecutive days (n = 8 per group). An additional control group (n = 8) received ampicillin treatment for 7 days. To assess protective effects against re-infection or UTI relapse, all mice were challenged with E. coli on day 22 and E. coli plus K. pneumoniae on day 25. Results from the murine UTI model demonstrated that placebo administration did not reduce bacteriuria throughout the experiment. Conversely, supplementation with ampicillin, HK-LAB/LF, HK-LAB, or LAB significantly (p < 0.05) reduced daily bacteriuria by 103 to 104-fold on days 1, 3, 5, and 14, respectively. Furthermore, all four therapeutic treatments improved the bacteriological cure rate (BCR) with varying levels of efficacy. For the 7-day treatment course, the BCR was 25% (placebo), 62.5% (ampicillin), 37.5% (LAB), 37.5% (HK-LAB), and 62.5% (HK-LAB/LF). For the 21-day treatment course, the BCR was 25% (placebo), 75% (ampicillin), 37.5% (LAB), 37.5% (HK-LAB), and 75% (HK-LAB/LF). Notably, HK-LAB and HK-LAB/LF demonstrated superior therapeutic efficacy compared to viable LAB in treating UTIs. Overall, regarding BCR, the three probiotic mixtures can provide benefits against UTI in mice, but ampicillin therapy remains the most efficient among the four treatments. Furthermore, there was no significant difference between pre- and post-challenge courses for the two instances of re-challenging uropathogens in all mice groups, as bacteriuria levels remained below 103 CFU/mL, implying that adaptive responses of mice may help reduce the risk of recurrent UTIs. In conclusion, our results provide new evidence that oral administration of heat-killed probiotic mixtures can confer significant therapeutic efficacy against UTIs in a murine model.

Fully body visual self-modeling of robot morphologies.

Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions without trying them out in physical reality. Recent progress in fully data-driven self-modeling has enabled machines to learn their own forward kinematics directly from task-agnostic interaction data. However, forward kinematic models can only predict limited aspects of the morphology, such as the position of end effectors or velocity of joints and masses. A key challenge is to model the entire morphology and kinematics without prior knowledge of what aspects of the morphology will be relevant to future tasks. Here, we propose that instead of directly modeling forward kinematics, a more useful form of self-modeling is one that could answer space occupancy queries, conditioned on the robot's state. Such query-driven self-models are continuous in the spatial domain, memory efficient, fully differentiable, and kinematic aware and can be used across a broader range of tasks. In physical experiments, we demonstrate how a visual self-model is accurate to about 1% of the workspace, enabling the robot to perform various motion planning and control tasks. Visual self-modeling can also allow the robot to detect, localize, and recover from real-world damage, leading to improved machine resiliency.

Visualizing the Knowledge Domain in Health Education: A Scientometric Analysis Based on CiteSpace.

OBJECTIVES: This study aimed to visualize the evidence in the global research on health education to better improve the nation's health literacy and to guide future research. METHOD: We searched the Web of Science (Core Collection) electronic databases. The search strategies: topic: ("Health Education" OR "Education, Health" OR "Community Health Education" OR "Education, Community Health" OR "Health Education, Community") AND document: (Article) AND language:(English). Articles of evidence from January 2011 to December 2021 with those words in the title or abstract or keywords will be included in this review. We used the Citespace 5.6.R5 (64-bit) to investigate and determine the thematic patterns, and emerging trends of the knowledge domain, and presented a narrative account of the findings. RESULT: We analyzed 10,273 eligible articles. It showed that BMC Public Health displays the most prolific journals. Author MARCO PAHOR is highlighted in health education. The University of Sydney has published the most studies about health education. The USA plays an important role in these studies. Specifically, the visualization shows several hotspots: disease prevalence surveys and a specific population of knowledge, attitude and practice surveys, health intervention, chronic and non-communicable management, youth-health action, sexual and reproductive health, and physical activity promotion. Furthermore, document co-citation analysis indicated that there are 10 main clusters, which means the research front in health education. Meanwhile, by the citation detected, COVID-19, has achieved universal health coverage in related studies, however, public health education and the health workforce might be more popular in the coming years. CONCLUSION: Health education is an effective measure to shift the concept of public health and improve healthy living standards. The present study facilitates an extensive understanding of the basic knowledge and research frontiers that are pivotal for the developmental process of health education and allows scholars to visualize the identification modes and tendencies.

Automated discovery of fundamental variables hidden in experimental data.

All physical laws are described as mathematical relationships between state variables. These variables give a complete and non-redundant description of the relevant system. However, despite the prevalence of computing power and artificial intelligence, the process of identifying the hidden state variables themselves has resisted automation. Most data-driven methods for modelling physical phenomena still rely on the assumption that the relevant state variables are already known. A longstanding question is whether it is possible to identify state variables from only high-dimensional observational data. Here we propose a principle for determining how many state variables an observed system is likely to have, and what these variables might be. We demonstrate the effectiveness of this approach using video recordings of a variety of physical dynamical systems, ranging from elastic double pendulums to fire flames. Without any prior knowledge of the underlying physics, our algorithm discovers the intrinsic dimension of the observed dynamics and identifies candidate sets of state variables.

The Effects of Visual Backgrounds in the Virtual Environments on the Postural Stability of Standing.

A photorealistic scene in a head mount display (HMD) is considered high fidelity and associated with postural stability similar to that in the real world, but the effects of visual background under different standing conditions have not been examined. Thirty-four healthy adults performed four standing (standardized, narrow, tandem and one-leg) tasks in three scenes with an HMD, while viewing one of three scenes: a real room (real scene, RS), a photorealistic scene (VrS) and a blank scene (BS). The effects of the visual scenes and standing tasks on sway parameters were analyzed. Romberg quotients (RQs) of the sway parameters were compared between RS and VrS with reference to BS to compare visual contribution to posture stability. Sway parameters were similar during all three scenes during the standardized and narrow standing tasks, but higher in VrS and BS conditions than in the RS condition during the tandem and one-leg standing tasks. The effects of visual scenes on postural stability showed a significant interaction with the standing tasks. The BS/VsR and BS/RS ratios were close to 1.0 for the standardized and narrow standing tasks, and the magnitude of increase was lower for BS/VsR than BS/RS during the tandem and one-leg standing tasks, indicating different levels of visual dependence. The effects of virtual scenes on postural stability were task-dependent. Adjusting the amount of visual stimuli and choosing tasks with higher postural demands may result in synergic effects, but the influence of visual environments should be examined with consideration of visual targeting.

Co/CoOx heterojunctions encapsulated N-doped carbon sheets via a dual-template-guided strategy as efficient electrocatalysts for rechargeable Zn-air battery.

Developing highly efficient oxygen electrocatalysts is of vital importance for rechargeable Zn-air batteries (ZABs). Herein, Co/CoOx nano-heterojunctions encapsulated into nitrogen-doped carbon sheets (NCS@Co/CoOx) are fabricated via a dual-template-guided approach by using zeolitic imidazolate frameworks (ZIFs) as templates. The synergistic integration of structural and compositional advantages endows such catalyst with superior catalytic properties to benchmark noble-metal catalysts. To be specific, the hierarchical micro/mesopores affords massive mass transport channels and maximizes the exposure of accessible active sites, whereas the NCS matrix accelerates electron transfer and prevents the self-aggregation of active species during the electrocatalytic reaction. Moreover, abundant and synergistic Co-based active sites (CoO, Co3O4, Co-Nx) greatly promote the catalytic activity. As the cathode of both liquid and flexible solid-state ZABs, excellent device properties are achieved, outperforming those assembled with commercial Pt/C+RuO2 catalyst. This work presents a feasible and cost-effective strategy for developing oxygen electrocatalysts derived from ZIFs templates.

Bibliometric Analysis on Research Trend of Accidental Falls in Older Adults by Using Citespace-Focused on Web of Science Core Collection (2010-2020).

The present study aimed to identify the trends in research on accidental falls in older adults over the last decade. The MeSH (Medical Subject Headings) and entry terms were applied in the Web of Science Core Collection. Relevant studies in English within articles or reviews on falls in older adults were included from 2010 to 2020. Moreover, CiteSpace 5.6.R5 (64-bit) was adopted for analysis with scientific measurements and visualization. Cooper Cyrus, Stephen R Lord, Minoru Yamada, Catherine Sherrington, and others have critically impacted the study of falls in older adults. Osteoporosis, dementia, sarcopenia, hypertension, osteosarcopenia, traumatic brain injury, frailty, depression, and fear of falling would be significantly correlated with falls in older adults. Multiple types of exercise can provide effective improvements in executive cognitive performance, gait performance, quality of life, and can also lower the rates of falls and fall-related fractures. Fall detection, hospitalization, classification, symptom, gender, and cost are the current research focus and development direction in research on falls in older adults. The prevention of falls in older adults is one of the most important public health issues in today's aging society. Although lots of effects and research advancements had been taken, fall prevention still is uncharted territory for too many older adults. Service improvements can exploit the mentioned findings to formulate policies, and design and implement exercise programs for fall prevention.

Visual behavior modelling for robotic theory of mind.

Behavior modeling is an essential cognitive ability that underlies many aspects of human and animal social behavior (Watson in Psychol Rev 20:158, 1913), and an ability we would like to endow robots. Most studies of machine behavior modelling, however, rely on symbolic or selected parametric sensory inputs and built-in knowledge relevant to a given task. Here, we propose that an observer can model the behavior of an actor through visual processing alone, without any prior symbolic information and assumptions about relevant inputs. To test this hypothesis, we designed a non-verbal non-symbolic robotic experiment in which an observer must visualize future plans of an actor robot, based only on an image depicting the initial scene of the actor robot. We found that an AI-observer is able to visualize the future plans of the actor with 98.5% success across four different activities, even when the activity is not known a-priori. We hypothesize that such visual behavior modeling is an essential cognitive ability that will allow machines to understand and coordinate with surrounding agents, while sidestepping the notorious symbol grounding problem. Through a false-belief test, we suggest that this approach may be a precursor to Theory of Mind, one of the distinguishing hallmarks of primate social cognition.

Facially expressive humanoid robotic face.

Realistic humanoid robots have emerged in the last two decades but the emotional intelligence of these machines has been limited. To teach humanoids how to emotionally communicate with humans, researchers have been increasingly relying on machine learning algorithms. While the software used to implement machine learning algorithms is largely open source, facially expressive humanoid robots are expensive and inaccessible to most people, thus limiting the number of researchers in this field. This paper aims to aid potential artificial intelligence researchers by providing a relatively inexpensive, open-source robot that can serve as a platform for research into emotional communication between humans and machines. Eva, the robot described in this paper, is an adult-sized humanoid head that can emulate human facial expressions, head movements, and speech through the use of 25 muscles, including 12 facial muscles that can produce a maximum skin displacement of 15 mm.

Reliability and Validity of a Virtual Reality-Based System for Evaluating Postural Stability.

Postural stability is an important indicator of balance and is commonly evaluated in neurorehabilitation. We proposed a system based on a virtual reality (HTC Vive) system with a tracker at the lumbar area. The position data of the tracker were obtained through detection of the sensors on the tracker by the VR system. The reliability and validity of these sway parameters to measure postural stability were evaluated. Twenty healthy adults had their postural sway measured with this system and a force platform system under four stance conditions, with wide- or narrow-stance and eyes open or closed. The path data from both systems were computed to obtain the following parameters: the mean distance and the mean velocity in the medial-lateral and anterior-posterior directions and the 95% confidence ellipse area. The reliability of the Vive-based sway measures was tested with intraclass correlation coefficients (ICCs). The convergent validity was tested against the center of pressure (COP) parameters from the force platform system. Finally, the discriminative validity was tested for the above four conditions. The results indicated that the Vive-based sway parameters had moderate to high reliability (ICCs: 0.56 ~ 0.90) across four conditions and correlated moderately to very highly with the COP parameters ( r = 0.420  âˆ¼  0.959 ). Bland-Altman plotting showed generally good agreement, with negative offset for the Vive-based sway parameters. The sway parameters obtained by the Vive-based system also discriminated well among the tasks. In conclusion, the results support this system as a simple and easy-to-use tool to evaluate postural stability with acceptable reliability and validity.