Passivity-Sliding Mode Control of Uncertain Chaotic Systems with Stochastic Disturbances

This paper is concerned with the stabilization problem of uncertain chaotic systems with stochastic disturbances. A novel sliding function is designed, and then a sliding mode controller is established such that the trajectory of the system converges to the sliding surface in a finite time. Using a virtual state feedback control technique, sufficient condition for the mean square asymptotic stability and passivity of sliding mode dynamics is derived via linear matrix inequality (LMI). Finally, a simulation example is presented to show the validity and advantage of the proposed method

On Isometric Extension in the Space ( )

We study the problem of isometric extension on a sphere of the space ( ). We give an affirmative answer to Tingley's problem in the space ( )

Some Properties of l

We provide a representation of elements of the space lp(A,X) for a locally convex space X and 1≤p<∞ and determine its continuous dual for normed space X and 1<p<∞. In particular, we study the extension and characterization of isometries on lp(N,X) space, when X is a normed space with an unconditional basis and with a symmetric norm. In addition, we give a simple proof of the main result of G. Ding (2002)

RAWIW: RAW Image Watermarking Robust to ISP Pipeline

Invisible image watermarking is essential for image copyright protection. Compared to RGB images, RAW format images use a higher dynamic range to capture the radiometric characteristics of the camera sensor, providing greater flexibility in post-processing and retouching. Similar to the master recording in the music industry, RAW images are considered the original format for distribution and image production, thus requiring copyright protection. Existing watermarking methods typically target RGB images, leaving a gap for RAW images. To address this issue, we propose the first deep learning-based RAW Image Watermarking (RAWIW) framework for copyright protection. Unlike RGB image watermarking, our method achieves cross-domain copyright protection. We directly embed copyright information into RAW images, which can be later extracted from the corresponding RGB images generated by different post-processing methods. To achieve end-to-end training of the framework, we integrate a neural network that simulates the ISP pipeline to handle the RAW-to-RGB conversion process. To further validate the generalization of our framework to traditional ISP pipelines and its robustness to transmission distortion, we adopt a distortion network. This network simulates various types of noises introduced during the traditional ISP pipeline and transmission. Furthermore, we employ a three-stage training strategy to strike a balance between robustness and concealment of watermarking. Our extensive experiments demonstrate that RAWIW successfully achieves cross-domain copyright protection for RAW images while maintaining their visual quality and robustness to ISP pipeline distortions

Torque Split Strategy for Parallel Hybrid Electric Vehicles with an Integrated Starter Generator

This paper presents a torque split strategy for parallel hybrid electric vehicles with an integrated starter generator (ISG-PHEV) by using fuzzy logic control. By combining the efficiency map and the optimum torque curve of the internal combustion engine (ICE) with the state of charge (SOC) of the batteries, the torque split strategy is designed, which manages the ICE within its peak efficiency region. Taking the quantified ICE torque, the quantified SOC of the batteries, and the quantified ICE speed as inputs, and regarding the output torque demanded on the ICE as an output, a fuzzy logic controller (FLC) with relevant fuzzy rules has been developed to determine the optimal torque distribution among the ICE, the ISG, and the electric motor/generator (EMG) effectively. The simulation results reveal that, compared with the conventional torque control strategy which uses rule-based controller (RBC) in different driving cycles, the proposed FLC improves the fuel economy of the ISG-PHEV, increases the efficiency of the ICE, and maintains batteries SOC within its operation range more availably

High level expression of human epithelial β-defensins (hBD-1, 2 and 3) in papillomavirus induced lesions

BACKGROUND: Epithelial defensins including human β-defensins (hBDs) and α-defensins (HDs) are antimicrobial peptides that play important roles in the mucosal defense system. However, the role of defensins in papillomavirus induced epithelial lesions is unknown. RESULTS: Papilloma tissues were prospectively collected from 15 patients with recurrent respiratory papillomatosis (RRP) and analyzed for defensins and chemokine IL-8 expression by quantitative, reverse-transcriptase polymerase chain reaction (RT-PCR) assays. HBD-1, -2 and -3 mRNAs were detectable in papilloma samples from all RRP patients and the levels were higher than in normal oral mucosal tissues from healthy individuals. Immunohistochemical analysis showed that both hBD-1 and 2 were localized in the upper epithelial layers of papilloma tissues. Expression of hBD-2 and hBD-3 appeared to be correlated as indicated by scatter plot analysis (r = 0.837, p < 0.01) suggesting that they were co-inducible in papillomavirus induced lesions. Unlike hBDs, only low levels of HD5 and HD6 were detectable in papillomas and in oral mucosa. CONCLUSION: Human β-defensins are upregulated in respiratory papillomas. This novel finding suggests that hBDs might contribute to innate and adaptive immune responses targeted against papillomavirus-induced epithelial lesions

Method and application of carbon emission calculation for ultra-high voltage (UHV) project construction

[Objective] As one of the seven key areas of “new infrastructure” development during China’s 14th Five-Year Plan period, the ultra-high voltage (UHV) projects are the backbone of China’s new power system and is of great significance to the transmission of clean energy. This study constructed a theoretical and methodological system suitable for the carbon emission measurement of UHV project construction in China, in order to clarify the carbon cost of project construction and assist project carbon management and the construction of new power systems under China’s “dual carbon” goals. [Methods] Based on the life cycle assessment method, this study broke through the cost list-based measurement system and for the first time constructed the carbon source emission inventory system for UHV project construction from the perspective of carbon footprint. On this basis, a grouping calculation method for project construction carbon emissions was proposed, which enhances the applicability and accuracy of the method. The calculation and carbon emission reduction potential evaluation of the ±800 kV UHVDC transmission project from Longdong to Shandong were conducted as an example. [Results] The results show that: (1) The method constructed in this article simplifies the calculation work to a certain extent, ensuring a relatively scientific and effective calculation of carbon emissions in the construction of ultra large transmission projects; (2) The overall carbon emissions in the construction phase are 3.367×106 tCO2e, with the main source of carbon emissions coming from non-traceable projects, accounting for 67.140% of the total; (3) The carbon emissions of unit investment are 1.667 tCO2e/10000 yuan, and the unit carbon emissions level of the large-scale super project in the power sector has not been improved. [Conclusion] The results verify the applicability of the carbon emission calculation method for UHV project construction formed in this study. The method provides a theoretical support for establishing carbon cost budgets for UHV projects in China, improving carbon emission management capabilities during the project construction phase, and assisting project carbon emission reductions. The study also revealed that fully utilizing the existing power grid foundation to plan project site selection and construction, innovating construction technology, introducing green materials, and application of digital technology in project construction management are highly promising paths of carbon emission reduction

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N&nbsp;=&nbsp;30) or the active control group (N&nbsp;=&nbsp;30). Both groups were trained for 20 sessions during 4&nbsp;weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N&nbsp;=&nbsp;101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p&nbsp;=&nbsp;.030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p&nbsp;=&nbsp;.025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training