Anticontrol of Chaos for a Class of Delay Difference Equations Based on Heteroclinic Cycles Connecting Repellers

This paper is concerned with anticontrol of chaos for a class of delay difference equations via the feedback control technique. The controlled system is first reformulated into a high-dimensional discrete dynamical system. Then, a chaotification theorem based on the heteroclinic cycles connecting repellers for maps is established. The controlled system is proved to be chaotic in the sense of both Devaney and Li-Yorke. An illustrative example is provided with computer simulations

Chaos in a Discrete Delay Population Model

This paper is concerned with chaos in a discrete delay population model. The map of the model is proved to be chaotic in the sense of both Devaney and Li-Yorke under some conditions, by employing the snap-back repeller theory. Some computer simulations are provided to visualize the theoretical result

Critical Acceptance Factors of Cloud-Based Public Health Records

Personal health records (PHR) is a tool that can be used to assist patients in health management, and cloud-based PHR is expected to effectively integrate medical resources and information, elevate overall healthcare quality, and reduce unnecessary medical costs. This study tends to explore the factors that affect users’ intention to use with regard to the Microsoft HealthVault hybrid cloud health system in Taiwan. A research model combined with Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-Technology Fit (TTF) models as well as perceived risks and trust is proposed including 10 hypotheses. After conducting a series survey, in total, 254 valid questionnaires in Taiwan were received. Some preliminary findings are discussed, and it is hoped that this model can be used to explore the key factors influencing usage intent toward the HealthVault

A thorough analysis of the performance of delay distribution models for IEEE 802.11 DCF

International audienceDeriving the complete distribution of the end-to-end delay in a wireless multi-hop network is of paramount interest when delay-sensitive flows have to be conveyed over such networks. First works have proposed models to derive the total delay distribution of networks assuming the well-known IEEE802.11 DCF medium access (MAC) protocol. Current derivations can be decomposed into two main steps: (i) the calculation of the total delay probability generating function (PGF) and (ii) its numerical inversion. We show in this paper that there is a need for a thorough performance evaluation of these models since both steps introduce errors, naming modeling and inversion errors. We argue that both types of errors have to be analyzed separately to characterize the accuracy of the analytical derivations of the literature. Therefore, this paper defines two performance evaluation metrics that measure the magnitude of both types of errors. Both metrics are illustrated to select and optimize the most accurate model to calculate the single-hop end-to-end delay distribution of nodes using the IEEE802.11 DCF MAC protocol. The most accurate model is extended to calculate the end-to-end delay distribution for a 2-hop wireless communication

NeTO:Neural Reconstruction of Transparent Objects with Self-Occlusion Aware Refraction-Tracing

We present a novel method, called NeTO, for capturing 3D geometry of solid transparent objects from 2D images via volume rendering. Reconstructing transparent objects is a very challenging task, which is ill-suited for general-purpose reconstruction techniques due to the specular light transport phenomena. Although existing refraction-tracing based methods, designed specially for this task, achieve impressive results, they still suffer from unstable optimization and loss of fine details, since the explicit surface representation they adopted is difficult to be optimized, and the self-occlusion problem is ignored for refraction-tracing. In this paper, we propose to leverage implicit Signed Distance Function (SDF) as surface representation, and optimize the SDF field via volume rendering with a self-occlusion aware refractive ray tracing. The implicit representation enables our method to be capable of reconstructing high-quality reconstruction even with a limited set of images, and the self-occlusion aware strategy makes it possible for our method to accurately reconstruct the self-occluded regions. Experiments show that our method achieves faithful reconstruction results and outperforms prior works by a large margin. Visit our project page at \url{https://www.xxlong.site/NeTO/

Towards a new approach for the description of shapes from multimodal data

The construction of a Virtual Environments (VE) requires a long iterative modeling and modification process. Depending on the final purposes, many actors can be involved both in the early conception and in the detailed specification of what has to be included and how it has to be organized. These actors may have different knowledge and expertise. It is therefore important to define tools easy usable even by nonprofessionals in order to facilitate the VE specification and setup. Such tools should allow the incomplete specification of details and the reuse of existing assets and data, either 2D images or 3D models. In this perspective, the work presented in this paper proposes a new shape description model for the management of objects and assemblies, resulting from the combination of multimodal data, together with their intrinsic properties. Based on such a model high level methods and tools directly working on components (either 2D or 3D) can be developed. Thus making easier the solution specification by the application domain experts, which can thus better integrated within the VE design process. This new shape description model is thought to be used as an intermediary model shared between the various actors in the generation process of VEs to keep the link and digital chain between them. The concepts of this model are proposed and illustrated through a first implementation

Reusing heterogeneous data for the conceptual design of shapes in virtual environments

Today, digital data such as 2D images, 3D meshes and 3D point clouds are widely used to design virtual environments (VE). Most of the time, only one type of those multimodal data is used to describe and specify the shapes of the objects. However, a single object can be seen as a combination of components linked with constraints specifying the relationships and the rigid transformations defining their arrangement. Thus, the definition of new methods able to combine any kind of multimodal data in an easy way would allow non-experts of VE to rapidly mock up objects and scenes. In this paper, we propose a new shape description model together with its associated constraints toolbox enabling the description of complex shapes from multimodal data. Not only rigid transformations are considered but also scale modifications according to the specified context of the constraint setting. The heterogeneous virtual objects (i.e., composed by scalable multimodal components) then result from the resolution of a constraint satisfaction problem through an optimization approach. The proposed approach is illustrated and validated with examples obtained using our prototype software.The work has been partially supported by the VISIONAIR project funded by the European Commission under Grant Agreement 262044, the French National project Co-DIVE and by the Italian National Project ‘‘Tecnologie e sistemi innovativi per la fabbrica del futuro e Made in Italy.’

The Pyroptosis-Related Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Gastric Cancer

Gastric cancer (GC) is one of the leading causes of cancer-related deaths and shows high levels of heterogeneity. The development of a specific prognostic model is important if we are to improve treatment strategies. Pyroptosis can arise in response to H. pylori, a primary carcinogen, and also in response to chemotherapy drugs. However, the prognostic evaluation of GC to pyroptosis is insufficient. Consensus clustering by pyroptosis-related regulators was used to classify 618 patients with GC from four GEO cohorts. Following Cox regression with differentially expressed genes, our prognosis model (PS-score) was built by LASSO-Cox analysis. The TCGA-STAD cohort was used as the validation set. ESTIMATE, CIBERSORTx, and EPIC were used to investigate the tumor microenvironment (TME). Immunotherapy cohorts by blocking PD1/PD-L1 were used to investigate the treatment response. The subtyping of GC based on pyroptosis-related regulators was able to classify patients according to different clinical traits and TME. The difference between the two subtypes identified in this study was used to develop a prognosis model which we named “PS-score.” The PS-score could predict the prognosis of patients with GC and his/her overall survival time. A low PS-score implies greater inflammatory cell infiltration and better response of immunotherapy by PD1/PD-L1 blockers. Our findings provide a foundation for future research targeting pyroptosis and its immune microenvironment to improve prognosis and responses to immunotherapy

Conception of a global dispatching system for metauniverse in internet of everything sky-earth computing (i) beyond cloud computing

In order to overcome the serious defects of information mechanism and promote the rationalization of resource allocation, this series of research proposes a hyper-cyber world computing mode which combines the traditional computing mode in various professional application fields with the modern computing mode in the field of information network technology (represented by distributed computing, grid computing, cloud computing and cluster computing), It can be called the Sky-Earth Computing (SEC). Here, “Sky (or Heaven)” metaphors the information world in the field of digital network technology, and “Earth” metaphors the real world in various professional application fields. Facing the ecosphere of metauniverse in Internet of everything, we propose to provide a customized global service dispatcher (GSD) and its enhanced version of the world-wise brain (WWB) with the user as the center. The global service dispatcher to be developed should have at least three functions: unified standard measurement system, supply-demand intelligent docking system, and integrated dispatching center system. Through the development and implementation of super metauniverse system engineering technology, let every user become the center of their own all-interconnected ecosphere (AIE)