Toward Optimized VR/AR Ergonomics: Modeling and Predicting User Neck Muscle Contraction

Ergonomic efficiency is essential to the mass and prolonged adoption of VR/AR experiences. While VR/AR head-mounted displays unlock users' natural wide-range head movements during viewing, their neck muscle comfort is inevitably compromised by the added hardware weight. Unfortunately, little quantitative knowledge for understanding and addressing such an issue is available so far. Leveraging electromyography devices, we measure, model, and predict VR users' neck muscle contraction levels (MCL) while they move their heads to interact with the virtual environment. Specifically, by learning from collected physiological data, we develop a bio-physically inspired computational model to predict neck MCL under diverse head kinematic states. Beyond quantifying the cumulative MCL of completed head movements, our model can also predict potential MCL requirements with target head poses only. A series of objective evaluations and user studies demonstrate its prediction accuracy and generality, as well as its ability in reducing users' neck discomfort by optimizing the layout of visual targets. We hope this research will motivate new ergonomic-centered designs for VR/AR and interactive graphics applications. Source code is released at: https://github.com/NYU-ICL/xr-ergonomics-neck-comfort.Comment: ACM SIGGRAPH 2023 Conference Proceeding

Variational principles for Feldman-Katok metric mean dimension

We introduce the notion of Feldman-Katok metric mean dimensions in this note. We show metric mean dimensions defined by different metrics coincide under weak tame growth of covering numbers, and establish variational principles for Feldman-Katok metric mean dimensions in terms of FK Katok $\epsilon$-entropy and FK local $\epsilon$-entropy function.Comment: 12 page

Representations of Chinese Women Warriors in the Cinemas of Hong Kong, Mainland China and Taiwan since 1980.

The subject of this thesis is the depiction of Chinese women warriors in the cinemas of Hong Kong, Taiwan and Mainland China since 1980. Women warriors have been a popular feature of Western media since the 1970s influenced by the second wave women's movement, and have become a significant topic of academic study. However, Chinese women warriors are combined with and referred to as 'Asian' women without consideration of their cultural differences. Furthermore, although representations of women warriors in the cinemas of Hong Kong, Mainland China and Taiwan may share some similarities, they also exhibit different regional features. This thesis attempts to reveal regional differences in the representations of women warriors in Chinese language films and their sociocultural contexts since 1980. An important goal of such research is to contribute to the study of the 'woman warrior' phenomenon in Chinese cinemas, in the hope that it will arouse interest in the field. This thesis also aims to focus attention on the changing status of Chinese women in different communities. Since gender is a global issue, it is hoped that the feminist perspective adopted here will stimulate interest among film specialists, not only in Chinese women in films, but also in the broader field of gender studies

Force-Aware Interface via Electromyography for Natural VR/AR Interaction

While tremendous advances in visual and auditory realism have been made for virtual and augmented reality (VR/AR), introducing a plausible sense of physicality into the virtual world remains challenging. Closing the gap between real-world physicality and immersive virtual experience requires a closed interaction loop: applying user-exerted physical forces to the virtual environment and generating haptic sensations back to the users. However, existing VR/AR solutions either completely ignore the force inputs from the users or rely on obtrusive sensing devices that compromise user experience. By identifying users' muscle activation patterns while engaging in VR/AR, we design a learning-based neural interface for natural and intuitive force inputs. Specifically, we show that lightweight electromyography sensors, resting non-invasively on users' forearm skin, inform and establish a robust understanding of their complex hand activities. Fuelled by a neural-network-based model, our interface can decode finger-wise forces in real-time with 3.3% mean error, and generalize to new users with little calibration. Through an interactive psychophysical study, we show that human perception of virtual objects' physical properties, such as stiffness, can be significantly enhanced by our interface. We further demonstrate that our interface enables ubiquitous control via finger tapping. Ultimately, we envision our findings to push forward research towards more realistic physicality in future VR/AR.Comment: ACM Transactions on Graphics (SIGGRAPH Asia 2022

SAMScore: A Semantic Structural Similarity Metric for Image Translation Evaluation

Image translation has wide applications, such as style transfer and modality conversion, usually aiming to generate images having both high degrees of realism and faithfulness. These problems remain difficult, especially when it is important to preserve semantic structures. Traditional image-level similarity metrics are of limited use, since the semantics of an image are high-level, and not strongly governed by pixel-wise faithfulness to an original image. Towards filling this gap, we introduce SAMScore, a generic semantic structural similarity metric for evaluating the faithfulness of image translation models. SAMScore is based on the recent high-performance Segment Anything Model (SAM), which can perform semantic similarity comparisons with standout accuracy. We applied SAMScore on 19 image translation tasks, and found that it is able to outperform all other competitive metrics on all of the tasks. We envision that SAMScore will prove to be a valuable tool that will help to drive the vibrant field of image translation, by allowing for more precise evaluations of new and evolving translation models. The code is available at https://github.com/Kent0n-Li/SAMScore

Relationship between four tumor-associated bio-markers and prognosis of gastric cancer

Purpose: To investigate the relationship between prognosis of gastric cancer (GC) and the expression of P53, Epidermal growth factor receptor (EGFR), Human epidermal growth factor receptor-2 (HER-2), and Vascular endothelial growth factor (VEGF).Methods: One hundred and forty-seven patients admitted to People's Liberation Army General Hospital (Beijing, China) with diagnosis of locally advanced GC were enrolled in the study. Follow-up data were obtained by outpatient review or telephone follow-up. Expressions of P53, EGFR, HER-2 and VEGF were determined by immunohistochemical staining. The relationship between protein expression, clinico-pathological factors, disease-free survival time (DFS) and overall survival (OS) were analyzed.Results: The expressions of EGER, HER-2, P53 and VEGF in GC were 17.7, 17.0, 41.0 and 55.9%, respectively. The expressions of EGFR and P53 were positively correlated (r = 0.306, p < 0.05), while the expressions of VEGF and HER-2 were negatively correlated (r = -0.2, p < 0.05). The expressions of EGFR, HER-2 and VEGF were not related to the clinico-pathological factors (p > 0.05) while expression of P53 was related only to histological grade (p < 0.05). Univariate analysis showed that OS and DFS were longer (p < 0.05) when P53 was lowly expressed. Multiple-factor analysis revealed that histological grade, infiltration depth and P53 expression were independent factors that influenced DFS.Conclusion: These results indicate that the expression of P53, EGFR, HER2 and VEGF can be used to predict prognosis of GC and screening of patients’ benefits from adjuvant chemotherapy.Keywords: Gastric cancer, Prognosis, Biomarkers, Adjuvant chemotherap

First-principles computational investigation of nitrogen-doped carbon nanotubes as anode materials for lithium-ion and potassium-ion batteries.

Significant research efforts, mostly experimental, have been devoted to finding high-performance anode materials for lithium-ion and potassium-ion batteries; both graphitic carbon-based and carbon nanotube-based materials have been generating huge interest. Here, first-principles calculations are performed to investigate the possible effects of doping defects and the varying tube diameter of carbon nanotubes (CNTs) on their potential for battery applications. Both adsorption and migration of Li and K are studied for a range of pristine and nitrogen-doped CNTs, which are further compared with 2D graphene-based counterparts. We use detailed electronic structure analyses to reveal that different doping defects are advantageous for carbon nanotube-based and graphene-based models, as well as that curved CNT walls help facilitate the penetration of potassium through the doping defect while showing a negative effect on that of lithium

Inflammatory bowel disease and rheumatoid arthritis share a common genetic structure

BackgroundThe comorbidity rate of inflammatory bowel disease (IBD) and rheumatoid arthritis (RA) is high; nevertheless, the reasons behind this high rate remain unclear. Their similar genetic makeup probably contributes to this comorbidity.MethodsBased on data obtained from the genome-wide association study of IBD and RA, we first assessed an overall genetic association by performing the linkage disequilibrium score regression (LDSC) analysis. Further, a local correlation analysis was performed by estimating the heritability in summary statistics. Next, the causality between the two diseases was analyzed by two-sample Mendelian randomization (MR). A genetic overlap was analyzed by the conditional/conjoint false discovery rate (cond/conjFDR) method.LDSC with specific expression of gene analysis was performed to identify related tissues between the two diseases. Finally, GWAS multi-trait analysis (MTAG) was also carried out.ResultsIBD and RA are correlated at the genomic level, both overall and locally. The MR results suggested that IBD induced RA. We identified 20 shared loci between IBD and RA on the basis of a conjFDR of <0.01. Additionally, we identified two tissues, namely spleen and small intestine terminal ileum, which were commonly associated with both IBD and RA.ConclusionHerein, we proved the presence of a polygenic overlap between the genetic makeup of IBD and RA and provided new insights into the genetic architecture and mechanisms underlying the high comorbidity between these two diseases