Secure multi-path routing for Internet of Things based on trust evaluation

In the realm of the Internet of Things (IoT), ensuring the security of communication links and evaluating the safety of nodes within these links remains a significant challenge. The continuous threat of anomalous links, harboring malicious switch nodes, poses risks to data transmission between edge nodes and between edge nodes and cloud data centers. To address this critical issue, we propose a novel trust evaluation based secure multi-path routing (TESM) approach for IoT. Leveraging the software-defined networking (SDN) architecture in the data transmission process between edge nodes, TESM incorporates a controller comprising a security verification module, a multi-path routing module, and an anomaly handling module. The security verification module ensures the ongoing security validation of data packets, deriving trust scores for nodes. Subsequently, the multi-path routing module employs multi-objective reinforcement learning to dynamically generate secure multiple paths based on node trust scores. The anomaly handling module is tasked with handling malicious switch nodes and anomalous paths. Our proposed solution is validated through simulation using the Ryu controller and P4 switches in an SDN environment constructed with Mininet. The results affirm that TESM excels in achieving secure data forwarding, malicious node localization, and the secure selection and updating of transmission paths. Notably, TESM introduces a minimal 12.4% additional forwarding delay and a 5.46% throughput loss compared to traditional networks, establishing itself as a lightweight yet robust IoT security defense solution

Facile template-free synthesis of vertically aligned polypyrrole nanosheets on nickel foams for flexible all-solid-state asymmetric supercapacitors

This paper reports a novel and remarkably facile approach towards vertically aligned nanosheets on three-dimensional (3D) Ni foams. Conducting polypyrrole (PPy) sheets were grown on Ni foam through the volatilization of the environmentally friendly solvent from an ethanol–water solution of pyrrole (Py), followed by the polymerization of the coated Py in ammonium persulfate (APS) solution. The PPy-decorated Ni foams and commercial activated carbon (AC) modified Ni foams were employed as the two electrodes for the assembly of flexible all-solid-state asymmetric supercapacitors. The sheet-like structure of PPy and the macroporous feature of the Ni foam, which render large electrode–electrolyte interfaces, resulted in good capacitive performance of the supercapacitors. Moreover, a high energy density of ca. 14 Wh kg−1 and a high power density of 6.2 kW kg−1 were achieved for the all-solid-state asymmetric supercapacitors due to the wide cell voltage window

Radiomic Machine Learning and External Validation Based on 3.0 T mpMRI for Prediction of Intraductal Carcinoma of Prostate With Different Proportion

PurposeTo assess the association of radiomics features based on multiparametric MRI (mpMRI) with the proportion of intraductal carcinoma of prostate (IDC-P) and validate the predictive models.Materials and MethodsWe retrospectively included pre-treatment MR images of prostate cancer (PCa) with IDC components of high proportion (≥10%, hpIDC-P), low proportion (<10%, lpIDC-P), and pure acinar adenocarcinoma (PAC) from our institution for training and internal validation and cooperated cohort for external validation. Normalized images of T2WI, diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) map, and dynamic contrast enhanced (DCE) sequences were used for radiomics modeling. The clinical model was built based on serum total prostate specific antigen (tPSA) and Gleason score (GS), and the integrated model was the combination of Rad-score and clinicopathological data. The discrimination ability was assessed by area under the receiver operating characteristic curve (ROC-AUC) in the internal and external validation sets and compared by DeLong test.ResultsOverall, 97 patients with hpIDC-P, 87 lpIDC-P, and 78 PAC were included for training and internal validation, and 11, 16, and 19 patients for external validation. The integrated model for predicting hpIDC-P got the best ROC-AUC of 0.88 (95%CI = 0.83-0.93) in internal and 0.86 (95%CI = 0.72-1.0) in external validation, which both outperformed clinical models (AUC=0.78, 95% CI = 0.72-0.85, AUC=0.69, 95% CI = 0.5-0.85, respectively) based solely on GS, and the radiomics model (AUC=0.85, 95% CI = 0.79-0.91) was slightly inferior to the integrated model and better than the clinical model in internal dataset. The integrated model for predicting lpIDC-P outperformed both radiomics and clinical models in the internal dataset, while slightly inferior to the integrated model for predicting hpIDC-P.ConclusionsRadiomics signature improved differentiation of both hpIDC-P and lpIDC-P versus PAC when compared with the clinical model based on Gleason score, and was validated in an external cohort

Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

Optimal Strategies for Elderly Public Transport Service Based on Impact-Asymmetry Analysis: A Case Study of Harbin

The difficulty of travel for the elderly is a challenge for urban management. Quantifying the satisfaction of public transport services from the perspective of the elderly is a people-oriented scientific research method. Based on the survey data of 2019 and 2020 and by selecting the interview data of people over retirement age before analyzing the non-linear relationship between bus service elements and elderly satisfaction by the impact-asymmetry analysis and gradient boosting decision trees, the optimization strategy of ground public transportation for the elderly in Harbin was obtained. The results show that the following five factors have the greatest impact on overall satisfaction, namely, site broadcasting, complaint handling, awning facilities, driver driving habits, and the punctuality of bus operation. Among them, “awning,” the “punctuality of bus operation,” and “drivers’ driving habits” should be given priority to improve. The conclusion of this study provides a theoretical basis for the accurate optimization of public transport services

Optimal Strategies for Elderly Public Transport Service Based on Impact-Asymmetry Analysis: A Case Study of Harbin

The difficulty of travel for the elderly is a challenge for urban management. Quantifying the satisfaction of public transport services from the perspective of the elderly is a people-oriented scientific research method. Based on the survey data of 2019 and 2020 and by selecting the interview data of people over retirement age before analyzing the non-linear relationship between bus service elements and elderly satisfaction by the impact-asymmetry analysis and gradient boosting decision trees, the optimization strategy of ground public transportation for the elderly in Harbin was obtained. The results show that the following five factors have the greatest impact on overall satisfaction, namely, site broadcasting, complaint handling, awning facilities, driver driving habits, and the punctuality of bus operation. Among them, “awning,” the “punctuality of bus operation,” and “drivers’ driving habits” should be given priority to improve. The conclusion of this study provides a theoretical basis for the accurate optimization of public transport services

City Green Economy Evaluation: Empirical Evidence from 15 Sub-Provincial Cities in China

City green economy plays an important role in the development of low-carbon economy and the achievement of sustainable development of economy, society and ecological environment. From the perspective of economy, society, environment and resources, the evaluation of the green economy in urban areas tends to offer us a new insight into the green economy of cities. This paper is about the creation of a novel urban green economy evaluation model and its application. First of all, we established a city green economy evaluation index system based on R cluster analysis and coefficient of variation. Secondly, based on the nonlinear weighted utilizing entropy weight method, a city green economy evaluation model is established based on inferior constraints. Thirdly, by comparing the differences between evaluation rankings under inferior constraints and non-inferior constraints, the advantageous factors and the disadvantageous ones in urban green economy development are obtained. The proposed model has been verified with the data on 15 sub-provincial cities in China. Empirical analysis results show that: (1) The proposed approach can accurately find out the advantageous and disadvantageous factors for each sub-provincial city; (2) In the evaluation of green economy development, the order of importance of the three criterion layers is X1 Economy development > X2 Social livelihood of the people > X3 Resources and environment; (3) Local governments should implement differential, reasonable policies in order to improve their green economy development. Moreover, our research is not only significant for developing green economy in China’s sub-provincial cities, but also serves as a reference for the development of green economy in other cities in the world