Month: April 2024

Abstract

The successful deployment of an Intrusion Detection System (IDS) in the Internet of Things (IoT) is subject to two primary criteria: the detection method and the deployment strategy. IDS schemes should take into account that IoT devices often have limited resources. Thus, IDS should be limited in devices’ memory and power usage. In this paper, we design, implement, and evaluate an effective cross-layer lightweight IDS scheme for the IoT (RPL-IDS). The proposed IDS scheme cooperates with the RPL routing protocol using its selected parents as distributed agents. A lightweight artificial neural network (ANN) model is deployed in these agents to detect malicious traffic and collaborates with a centralized system. According to the topology built by the Routing Protocol for Low-Power and Lossy Networks (RPL), these agents are automatically selected, i.e., the routers (parents) of the topology are chosen to act as IDS agents. We implemented RPL-IDS using the Contiki operating system and then comprehensively evaluated it with the Cooja simulator. Experimental results indicate that RPL-IDS is lightweight and can be deployed on devices with limited resources. Most state-of-the-art IDS schemes do not consider the limitation of resources of IoT devices, making them impractical for deployment in many IoT applications. Furthermore, the proposed RPL-IDS demonstrated one of the highest detection rates in the literature while incurring an insignificant energy overload, allowing for scalability in large-scale networks.

Abstract

The first law of geography is one of the most important concepts in geographical analysis, revealing the significant role of spatial proximity. At present, some current international relation studies or geographic network analysis studies tend to build corresponding network models according to different themes, but the most basic level of geographic neighborhoods is intentionally or unintentionally neglected in those processes. Based on the adjacency relationship between the terrestrial countries in the world, the model of the terrestrial adjacency network (TAN) is constructed. The model includes almost all land-based countries and is divided into three main regions, respectively, Eurasia, Africa, and America. On the mathematical model of these regions, we analyze the geospatial structure and network evolution of the adjacent networks utilizing statistical methods and network analysis methods. This study helps to map and understand the geographical attributes and characteristics of countries from the perspective of holistic structure, aiming to provide a quantitative reference for subsequent research on international relations and geographic computing. Moreover, despite some limitations, TAN represents a new advance in geographical network analysis that can be further applied by overlaying more attribute data.

Abstract

Human trafficking represents the second most profitable criminal activity in the world. Here, based on the snowball sampling method, we obtained a novel dataset of a human trafficking network on the southern border of Mexico. This dataset was used to construct an unweighted and undirected graph that represents the interactions of the trafficking network. Our analysis reveals a moderate level of centralization at 44.32% and a medium density of 0.401, indicative of a structural balance that facilitates the coordination of criminal activities without a single actor’s dominance. Addressing the challenge posed by the network’s minimal cohesiveness, which hampers the sharing of resources among members, we assess four dismantling strategies: random removal, targeting hubs and brokers, a human capital-focused approach, and Generalized Network Dismantling (GND). Our findings underscore the efficacy of targeting moderately connected actors, a strategy that disrupts the network’s resilience and operational capacity by severing important but inconspicuous connections, thereby destabilizing the network’s efficiency subtly and avoiding immediate alert to the dismantling activities. This work is a significant contribution to the field of criminal network modeling and analysis.

Abstract

Purpose of Review

Cardiovascular disease (CVD) is a leading cause of death and chronic disability worldwide. Yet, despite extensive intervention strategies the number of persons affected by CVD continues to rise. Thus, there is great interest in unveiling novel mechanisms that may lead to new treatments. Considering this dilemma, recent focus has turned to the neuroimmune mechanisms involved in CVD pathology leading to a deeper understanding of the brain’s involvement in disease pathology. This review provides an overview of new and salient findings regarding the neuroimmune mechanisms that contribute to CVD.

Recent Findings

The brain contains neuroimmune niches comprised of glia in the parenchyma and immune cells at the brain’s borders, and there is strong evidence that these neuroimmune niches are important in both health and disease. Mechanistic studies suggest that the activation of glia and immune cells in these niches modulates CVD progression in hypertension and heart failure and contributes to the inevitable end-organ damage to the brain.

Summary

This review provides evidence supporting the role of neuroimmune niches in CVD progression. However, additional research is needed to understand the effects of prolonged neuroimmune activation on brain function.

Abstract

We investigate the characteristics and mechanisms of persistent wet-cold events (PWCEs) with different types of cold-air paths. Results show that the cumulative single-station frequency of the PWCEs in the western part of South China is higher than that in the eastern part. The pattern of single-station frequency of the PWCEs are “Yangtze River (YR) uniform” and “east–west inverse”. The YR uniform pattern is the dominant mode, so we focus on this pattern. The cold-air paths for PWCEs of the YR uniform pattern are divided into three types—namely, the west, northwest and north types—among which the west type accounts for the largest proportion. The differences in atmospheric circulation of the PWCEs under the three types of paths are obvious. The thermal inversion layer in the lower troposphere is favorable for precipitation during the PWCEs. The positive water vapor budget for the three types of PWCEs mainly appears at the southern boundary.