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Head tracking in head-mounted displays (HMDs) enables users to explore a 360-degree virtual scene with free head movements. However, for seated use of HMDs such as users sitting on a chair or a couch, physically turning around 360-degree is not possible. Redirection techniques decouple tracked physical motion and virtual motion, allowing users to explore virtual environments with more flexibility. In seated situations with only head movements available, the difference of stimulus might cause the detection thresholds of rotation gains to differ from that of redirected walking. Therefore we present an experiment with a two-alternative forced-choice (2AFC) design to compare the thresholds for seated and standing situations. Results indicate that users are unable to discriminate rotation gains between 0.89 and 1.28, a smaller range compared to the standing condition. We further treated head amplification as an interaction technique and found that a gain of 2.5, though not a hard threshold, was near the largest gain that users consider applicable. Overall, our work aims to better understand human perception of rotation gains in seated VR and the results provide guidance for future design choices of its applications., Comment: Submitted to IEEE TVCG

In this paper, we consider an exceptional study of differentially private stochastic gradient descent (SGD) algorithms in the stochastic convex optimization (SCO). The majority of the existing literature requires that the losses have additional assumptions, such as the loss functions with Lipschitz, smooth and strongly convex, and uniformly bounded of the model parameters, or focus on the Euclidean (i.e. l 2 d ) setting. However, these restrictive requirements exclude many popular losses, including the absolute loss and the hinge loss. By loosening the restrictions, we proposed two differentially private SGD without shuffle model and with shuffle model algorithms (in short, DP-SGD-NOS and DP-SGD-S) for the α , L -Hölder smooth loss by adding calibrated Laplace noise under no shuffling scheme and shuffling scheme in the l p d -setting for p ∈ 1,2 . We provide privacy guarantees by using advanced composition and privacy amplification techniques. We also analyze the convergence bounds of the DP-SGD-NOS and DP-SGD-S and obtain the optimal excess population risks O 1 / n + d log 1 / δ / n ϵ and O 1 / n + d log 1 / δ log n / δ / n 4 + α / 2 1 + α ϵ up to logarithmic factors with gradient complexity O n 2 − α / 1 + α + n . It turns out that the optimal utility bound with the shuffle model is superior to the bound without the shuffle model, which is consistent with the previous work. In addition, the DP-SGD-S achieves the optimal utility bound with the O n gradient computations of linearity for α ≥ 1 / 2 . There is a significant tradeoff between α , L -Hölder smooth losses and gradient complexity for differential privacy of SGD without shuffle model and with shuffle model.

Redirected Walking (RDW) algorithms aim to impose several types of gains on users immersed in Virtual Reality and distort their walking paths in the real world, thus enabling them to explore a larger space. Since collision with physical boundaries is inevitable, a reset strategy needs to be provided to allow users to reset when they hit the boundary. However, most reset strategies are based on simple heuristics by choosing a seemingly suitable solution, which may not perform well in practice. In this paper, we propose a novel optimization-based reset algorithm adaptive to different RDW algorithms. Inspired by the approach of finite element analysis, our algorithm splits the boundary of the physical world by a set of endpoints. Each endpoint is assigned a reset vector to represent the optimized reset direction when hitting the boundary. The reset vectors on the edge will be determined by the interpolation between two neighbouring endpoints. We conduct simulation-based experiments for three RDW algorithms with commonly used reset algorithms to compare with. The results demonstrate that the proposed algorithm significantly reduces the number of resets.

This article is devoted to discussing the problem of global Mittag-Leffler synchronization (GMLS) for the Caputo-type fractional-order fuzzy delayed inertial neural networks (FOFINNs). First of all, both inertial and fuzzy terms are taken into account in the system. For the sake of reducing the influence caused by the inertia term, the order reduction is achieved by the measure of variable substitution. The introduction of fuzzy terms can evade fuzziness or uncertainty as much as possible. Subsequently, a nonlinear delayed controller is designed to achieve GMLS. Utilizing the inequality techniques, Lyapunov’s direct method for functions and Razumikhin theorem, the criteria for interpreting the GMLS of FOFINNs are established. Particularly, two inferences are presented in two special cases. Additionally, the availability of the acquired results are further confirmed by simulations.

Cholangiocarcinoma is a highly aggressive malignant tumor disease with the increasing incidence and mortality. It’s urgent to identify specific biomarkers for cholangiocarcinoma treatment and diagnosis. Recent studies have noted the importance of lncRNAs in cancer and the following downstream mechanism with miRNAs network has been a hotspot. This work aimed to discover the role of lncRNA HCG18 and its possible downstream mechanism in cholangiocarcinoma tumor progression. Initially, through bioinformatics tools, we observed abnormal expression of lncRNA HCG18 in cholangiocarcinoma. In vitro experiments like (CCK-8, EdU, colony formation, flow cytometry, transwell, wound healing assays) and animal study confirmed that lncRNA HCG18 served as a cancer-promoting gene, promoted cancer proliferation, migration and invasion abilities. Besides, we found cancer cell-secreted exosomes transitted HCG18 to surrounding tumor cells and accelerated tumor growth and metastasis. After that, we confirmed HCG18 directly interacted with miR-424-5p through FISH, RIP and dual luciferase reporter assays with negative modulation. The inhibition of miR-424-5p reversed the HCG18 knockdown induced suppression on cholangiocarcinoma cancer cells. More specific, miR-424-5p targeted to SOX9 contributed to cholangiocarcinoma growth and metastasis through mediating PI3K/AKT pathway. In conclusion, these findings provide solid evidence of lncRNAs/miRNAs regulation in cholangiocarcinoma progression.

This paper discusses a class issue of finite-time lag projective synchronization (FTLPS) of delayed fractional-order quaternion-valued neural networks (FOQVNNs) with parameter uncertainties, which is solved by a non-decomposition method. Firstly, a new delayed FOQVNNs model with uncertain parameters is designed. Secondly, two types of feedback controller and adaptive controller without sign functions are designed in the quaternion domain. Based on the Lyapunov analysis method, the non-decomposition method is applied to replace the decomposition method that requires complex calculations, combined with some quaternion inequality techniques, to accurately estimate the settling time of FTLPS. Finally, the correctness of the obtained theoretical results is testified by a numerical simulation example.

Recently, some authors studied the distributive equations for continuous t-norms and some families of usual classes of uninorms over overlap functions in Refs. 25 and 32, but lacked a complete characterization of the distributivity on idempotent uninorms and overlap or grouping functions widely used in image processing. As a supplement to the previous results, in this article we fully characterize the distributivity equations of idempotent uninorms over these two functions by virtue of the associated functions of idempotent uninorms. Moreover, we also discuss the distributivity conditions of above two special functions over idempotent uninorms, yet find in this case that the associated functions of idempotent uninorms must satisfy particular conditions and those two functions usually are a class of special aggregation functions with a constant domain whose value equals to the neutral element of the idempotent uninorm.

A “top-down” strategy has been demonstrated to transform gasification residue carbon into a Ni–N–C single atom catalyst at gram scale.

With the recent rise of Metaverse, online multiplayer VR applications are becoming increasingly prevalent worldwide. Allowing users to move easily in virtual environments is crucial for high-quality experiences in such collaborative VR applications. This paper focuses on redirected walking technology (RDW) to allow users to move beyond the confines of the limited physical environments (PE). The existing RDW methods lack the scheme to coordinate multiple users in different PEs, and thus have the issue of triggering too many resets for all the users. We propose a novel multi-user RDW method that is able to significantly reduce the overall reset number and give users a better immersive experience by providing a more continuous exploration. Our key idea is to first find out the "bottleneck" user that may cause all users to be reset and estimate the time to reset, and then redirect all the users to favorable poses during that maximized bottleneck time to ensure the subsequent resets can be postponed as much as possible. More particularly, we develop methods to estimate the time of possibly encountering obstacles and the reachable area for a specific pose to enable the prediction of the next reset caused by any user. Our experiments and user study found that our method outperforms existing RDW methods in online VR applications.

The mass concentration of fine particulate matter (PM2.5; diameters less than 2.5 μm) estimated from geostationary satellite aerosol optical depth (AOD) data can supplement the network of ground monitors with high temporal (hourly) resolution. Estimates of PM2.5 over the United States were derived from NOAA’s operational geostationary satellites’ Advanced Baseline Imager (ABI) AOD data using a geographically weighted regression with hourly and daily temporal resolution. Validation versus ground observations shows a mean bias of −21.4% and −15.3% for hourly and daily PM2.5 estimates, respectively, for concentrations ranging from 0 to 1000 μg m−3. Because satellites only observe AOD in the daytime, the relation between observed daytime PM2.5 and daily mean PM2.5 was evaluated using ground measurements; PM2.5 estimated from ABI AODs were also examined to study this relationship. The ground measurements show that daytime mean PM2.5 has good correlation (r > 0.8) with daily mean PM2.5 in most areas of the United States, but with pronounced differences in the western United States due to temporal variations caused by wildfire smoke; the relation between the daytime and daily PM2.5 estimated from the ABI AODs has a similar pattern. While daily or daytime estimated PM2.5 provides exposure information in the context of the PM2.5 standard (>35 μg m−3), the hourly estimates of PM2.5 used in nowcasting show promise for alerts and warnings of harmful air quality. The geostationary satellite based PM2.5 estimates inform the public of harmful air quality 10 times more than standard ground observations (1.8 versus 0.17 million people per hour). Significance Statement Fine particulate matter (PM2.5; diameters less than 2.5 μm) are generated from smoke, dust, and emissions from industrial, transportation, and other sectors. They are harmful to human health and even lead to premature mortality. Data from geostationary satellites can help estimate surface PM2.5 exposure by filling in gaps that are not covered by ground monitors. With this information, people can plan their outdoor activities accordingly. This study shows that availability of hourly PM2.5 observations covering the entire continental United States is more informative to the public about harmful exposure to pollution. On average, 1.8 million people per hour can be informed using satellite data compared to 0.17 million people per hour based on ground observations alone.

Therapeutic drug monitoring (TDM) has played an important role in clinical medicine for precise dosing. Currently, chromatographic technology and immunoassay detection are widely used in TDM and have met most of the needs of clinical drug therapy. However, some problems still exist in practical applications, such as complicated operation and the influence of endogenous substances. Surface plasmon resonance (SPR) has been applied to detect the concentrations of small molecules, including pesticide residues in crops and antibiotics in milk, which indicates its potential for in vivo drug detection. In this study, a new SPR-based biosensor for detecting chloramphenicol (CAP) in blood samples was developed and validated using methodological verification, including precision, accuracy, matrix effect, and extraction recovery rate, and compared with the classic ultra-performance liquid chromatography-ultraviolet (UPLC-UV) method. The detection range of SPR was 0.1-50 ng/mL and the limit of detection was 0.099 ± 0.023 ng/mL, which was lower than that of UPLC-UV. The intra-day and inter-day accuracies of SPR were 98%-114% and 110%-122%, which met the analysis requirement. The results show that the SPR biosensor is identical to UPLC-UV in the detection of CAP in rat blood samples; moreover, the SPR biosensor has better sensitivity. Therefore, the present study shows that SPR technology can be used for the detection of small molecules in the blood samples and has the potential to become a method for therapeutic drug monitoring.

The Siberian roe deer (Capreolus pygargus) is a widely distributed ungulate in northeast China. Due to a series of human disturbance activities such as large-scale forest cutting, deforestation and reclamation, road construction in the past, the appearance and internal structure of forest vegetation in the habitat of Siberian roe have changed significantly. At the same time, Siberian roe population had a series of ecological adaptation responses in the face of such habitat changes. Therefore, two typical vegetation types with differences were selected in the Muling Forest, China. We used nutritional ecology and microbial metagenomic analysis techniques to compare the nutritional selection strategy and the structure and functional characteristics of faecal microbiota of Siberian roe groups in two vegetation types. The results showed that the α diversity of dietary and gut microbes of deer in Natural Forest was higher than that in Plantation Forest. However, the gut microbes of the Plantation Forest group contained more unique enzymes in the functional pathways of carbon metabolism and biosynthesis of amino acids. This study suggests that habitat type is associated with plant community composition, and contributes to changes in the intake proportions of major macronutrients by altering the availability, quality, and composition of certain edible plants. Feeding behaviour may be an important regulatory factor of gut microbiota structure and function of deer. The metabolic function of gut microbiota to different nutrients may affect the microbial community structure. Therefore, our results suggest that the gut microbes of Siberian roe may have coevolved with their diets, and reflect the adaptability of deer populations to environmental changes (e.g., vegetation type). Our study provides new insights into how spatial heterogeneity affects nutrition and microecosystems by describing the interactions among the environment, diet, and symbiotic gut microbes in wild ungulates.

Despite several synthetic approaches that have been developed for α-deuterated amino acids, the synthesis of β-deuterated amino acids has remained a challenge. Herein, we disclose a palladium catalyzed H/D exchange protocol for a β-deuterated N-protected amino amide, which can be converted to a β-deuterated amino acid simply by removal of protecting groups. This protocol is highly efficient, simply manipulated, and appliable for deuterium-labeling of many amino amides. In addition, deuterium labeling of phenylalanine derivatives was also successful when pivalic acid served as an additive to promote the H/D exchange process.

Rapidly developing Redirected Walking (ROW) technologies have enabled VR applications to immerse users in large virtual environments (VE) while actually walking in relatively small physical environments (PE). When an unavoidable collision emerges in a PE, the ROW controller suspends the user's immersive experience and resets the user to a new direction in PE. Existing ROW methods mainly aim to reduce the number of resets. However, from the perspective of the user experience, when users are about to reach a point of interest (POI) in a VE, reset interruptions are more likely to have an impact on user experience. In this paper, we propose a new ROW method, aiming to keep resets occurring at a longer distance from the virtual target, as well as to reduce the number of resets. Simulation experiments and real user studies demonstrate that our method outperforms state-of-the-art ROW methods in the number of resets and dramatically increases the distance between the reset locations and the virtual targets.

The accurate prediction and evaluation of stress and displacement fields of surrounding rock is the fundamental premise for the deformation control of soft rock tunnels under high geo-stress condition. However, due to the complicated mechanical characteristics of soft rock with confining pressure influence, the current numerical simulation method usually regards the mechanical parameters of surrounding rock as constant and ignores the variation of these parameters in the simulation process, which leads to results that cannot accurately reflect the mechanical behavior of surrounding rock. Therefore, this paper firstly investigates the effect of confining pressure on deformation and strength parameters for soft rock and proposes corresponding variable models for mechanical parameters with the confining pressure influence. Secondly, a transversal loop discriminant update procedure is proposed and introduced into the iteration calculation process of FLAC3D, thus forming an improved numerical simulation method. This improved method can integrally consider the mechanical parameter variation of surrounding rock with variable confining pressure and realize the automatic update for such a parameter with its variable stress state. Finally, as an application example, an improved expression of longitudinal deformation profile (LDP) for tunnels considering the confining pressure influence is proposed based on numerous simulation results for a soft rock tunnel obtained by this proposed method.

Japanese encephalitis virus (JEV), the causative agent of Japanese encephalitis (JE), is an importantly zoonotic, vector-borne virus widely prevalent in Asia. Although JE has been well controlled in China, its prevalence remains a huge threat to the pig industry as well as human health. Herein, we report on our molecular and serological investigations of JEV among pigs from different regions in Hunan Province of China from 2019 to 2021. Collectively, 19.27% (583/3026, 95% Confidential Interval (CI) 17.86-20.68) of sampled pigs were positive for JEV IgG antibody as revealed by indirect enzyme-linked immunosorbent assay, and the seroprevalence of JEV among pigs was significantly associated with the development stage and breeding scale (