APPAS: A Privacy-Preserving Authentication Scheme Based on Pseudonym Ring in VSNs

Vehicular social networks (VSNs) provide a variety of services for users based on social relationships through vehicular ad hoc networks (VANETs). During the communication in VSNs, vehicles are at risk of exposure to privacy information. Consequently, how to guarantee the security and privacy of vehicles is a critical issue. Ring signature is an effective mechanism to achieve anonymous authentication and communication. However, how to establish rings and how to select ring members become open problems. In this paper, a privacy-preserving scheme based on the pseudonym ring in VSNs is proposed. Hierarchical network architecture and trust model are established. A series of authentication protocols are then elaborated. According to the security and performance analysis, the proposed scheme is more robust and efficient compared with the typical ones

Exact Solution Analysis of Strongly Convex Programming for Principal Component Pursuit

In this paper, we address strongly convex programming for principal component analysis, which recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. In this paper, we firstly provide sufficient conditions under which the strongly convex models lead to the exact low-rank matrix recovery. Secondly, we also give suggestions that will guide us how to choose suitable parameters in practical algorithms. Finally, the proposed result is extended to the principal component pursuit with reduced linear measurements and we provide numerical experiments

Stable Analysis of Compressive Principal Component Pursuit

Compressive principal component pursuit (CPCP) recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. Pervious works mainly focus on the analysis of the existence and uniqueness. In this paper, we address its stability. We prove that the solution to the related convex programming of CPCP gives an estimate that is stable to small entry-wise noise. We also provide numerical simulation results to support our result. Numerical results show that the solution to the related convex program is stable to small entry-wise noise under board condition

Exact Solution Analysis of Strongly Convex Programming for Principal Component Pursuit

In this paper, we address strongly convex programming for principal component analysis, which recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. In this paper, we firstly provide sufficient conditions under which the strongly convex models lead to the exact low-rank matrix recovery. Secondly, we also give suggestions that will guide us how to choose suitable parameters in practical algorithms. Finally, the proposed result is extended to the principal component pursuit with reduced linear measurements and we provide numerical experiments

A Two-Stage Method to Test the Robustness of the Generalized Approximate Message Passing Algorithm

We propose a two-stage method to test the robustness of the generalized approximate message passing algorithm (GAMP). A pursuit process based on the marginal posterior probability is inserted in the standard GAMP algorithm to find the support of a sparse vector, and a revised GAMP process is used to estimate the amplitudes of the support. The numerical experiments with simulation and real world data confirm the robustness and performance of our proposed algorithm

Restricted Isometry Property of Principal Component Pursuit with Reduced Linear Measurements

The principal component prsuit with reduced linear measurements (PCP_RLM) has gained great attention in applications, such as machine learning, video, and aligning multiple images. The recent research shows that strongly convex optimization for compressive principal component pursuit can guarantee the exact low-rank matrix recovery and sparse matrix recovery as well. In this paper, we prove that the operator of PCP_RLM satisfies restricted isometry property (RIP) with high probability. In addition, we derive the bound of parameters depending only on observed quantities based on RIP property, which will guide us how to choose suitable parameters in strongly convex programming

A testing device for intrinsically safe multi-circuit protection power supply

In order to solve problems of inconvenient operation, complicated process and low accuracy of existing test methods of intrinsically safe power supply, a testing device for intrinsically safe multi- circuit protection power supply was designed. The device consists of adaptive voltage module and adaptive current module, control module, and has testing functions of intrinsically safe power supply and safety power supply module with 12, 18, 24 V power supply. Adaptive voltage module loads input power with rated voltage value to measured intrinsically safe power supply when tested voltage, output power end of measured intrinsically safe power supply is no-load, control module managements output voltage value of adaptive voltage module, and monitors output voltage of safety protection circuit at the corresponding levels is normal or not, so as to realize voltage testing at the corresponding levels; Adaptive voltage module loads input power with rated voltage value to measured intrinsically safe power supply when tested current, adaptive current module is loaded to output power end of measured intrinsically safe power supply, control module managements load current value of adaptive current module, and monitors output voltage of safety protection circuit at the corresponding levels is normal or not, so as to realize current testing at the corresponding levels; Control module can control switch ammong multiple protection circuit testing. The test results show that the device can automatically identify different voltage grade of intrinsically safe power supply, automatically load different power load, and can automatically warn and accurately analyze performance of the power supply, which implements automation and intellectualization of testing of intrinsically safe multi-circuit protection power supply

SOCS3 Methylation Predicts a Poor Prognosis in HBV Infection-Related Hepatocellular Carcinoma

Suppressor of cytokine signaling 3 (SOCS3) plays crucial roles in JAK/STAT signaling pathway inhibition in hepatocellular carcinoma (HCC). However, the methylation status of SOCS3 in HBV infection-related HCC and the relationship between SOCS3 methylation and the clinical outcome remain unknown. Here, we reported that in HCC tumor tissues, two regions of the CpG island (CGI) in the SOCS3 promoter were subjected to methylation analysis and only the region close to the translational start site of SOCS3 was hypermethylated. In HCC tumor tissues, SOCS3 showed an increased methylation frequency and intensity compared with that in the adjacent non-tumor tissues. Moreover, SOCS3 expression was significantly down-regulated in HCC cell lines and tumor tissues, and this was inversely correlated with methylation. Kaplan–Meier curve analysis revealed that in patients with an hepatitis B virus (HBV) infection background, SOCS3 hypermethylation was significantly correlated with a poor clinical outcome of HCC patients. Our findings indicated that SOCS3 hypermethylation has already happened in non-tumor tissues and increased in both frequency and intensity in tumor tissues. This suggests that the methylation of SOCS3 could predict a poor prognosis in HBV infection-related HCC patients

Coupling multi-physics models to corrosion fatigue prognosis of high-strength bolts in floating offshore wind turbine towers

Floating wind offshore turbines (FOWTs) tap into the immense Aeolian resource in deep-water oceans. The turbine structure, especially in ring-flange (RF) connections, are highly prone to corrosion fatigue (C-F) dete- rioration due to the combination of strong wind-wave loads, structural flexibility, and high corrosivity. This study provides innovative insights into the C-F deterioration of FOWT towers by integrating site-specific data, material test results, multi-physics simulations, and deterioration models. A probabilistic C-F (PCF) evolution model is tailored for bolts in RF connections, accounting for multiple failure modes. Concurrently, the corrosion test data are adopted to estimate the corrosion rate from the site-specific ambient conditions, including the temperature, humidity and airborne salinity. The result indicates a strong correlation between wind-wave spatial distribution and C-F damage, for which the critical bolt aligns with high-velocity winds. Meanwhile, the bolt deterioration is accelerated under high corrosivity, risking premature failures. Moreover, compared with the traditional fixed-bottom foundation, the floating platform amplifies the tower dynamics in both mean value and variation, which in turns escalate stress ranges in bolts. The findings underscore the importance of monitoring C- F deterioration in FOWT structures and highlight the potential of condition-based maintenance

Identification of differentially expressed genes associated with the enhancement of X-ray susceptibility by RITA in a hypopharyngeal squamous cell carcinoma cell line (FaDu)

Next generation sequencing and bio-informatic analyses were conducted to investigate the mechanism of reactivation of p53 and induction of tumor cell apoptosis (RITA)-enhancing X-ray susceptibility in FaDu cells