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In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

A Mobile ad hoc network (MANET) is a wireless, self-configuring network, dynamic in nature and works without any topology. Due to its widespread usage in many heterogeneous networks like Internet of Things (IoT) and the requirement for communication with heterogeneous devices, MANET is receiving more attention. Important data is gathered using smart devices or IoT sensors. These sensors communicate with one another independently within the range. Their energy levels and computing resources are restricted and they migrate frequently as topology is quiet active. Due to the energy constraints, nodes in the network behave selfishly and drop the packets during communication. Identification of the trustworthy and energy efficient nodes is essential for ensuring secure data transmission. The proposed method Energy Trust-Based Approach (ETA) combines trust, energy and reliable routing. Based on trust and energy values, nodes are involved in routing. This method identifies trusted nodes based on direct, indirect, past experiences and estimates their energy levels such that routing is performed only with the trusted nodes whose residual energy exceeds the determined threshold. Efficiency of the routing can be enhanced by calculating the energy levels of the trust adopted nodes in the network. The proposed ETA method ensures efficient routing between source and destination with the involvement of trustworthy and energy efficient intermediate nodes. The proposed work is simulated using Network Simulator (NS-2) and compared with other approaches, Trusted Energy Secured Ad hoc On Demand Vector scheme (TES-AODV), Secure Trust along with Adaptive Trust Threshold Method (STAT) and Ad hoc on demand vector routing (AODV). The simulation results have shown efficiency over the performance metrics like Packet delivery ratio PDLR with an increase of 5.34%, 4% decrease in Packet drop ratio PDR, 8% improvement in Throughput, 9% improvement in Residual energy, 8% reduction in Latency, 1.4% reduction in Overhead, 1,4 h increment in Network lifetime and 9% decrease in Delay. Thus ETA ensures stable, secured and trusted data transmission compared to simple AODV, STAT and TES-AODV.

This article analyzes the connectivity of multihop radio networks in a log-normal shadow fading environment. Assuming the nodes have equal transmission capabilities and are randomly distributed according to a homogeneous Poisson process, we give a tight lower bound for the minimum node density that is necessary to obtain an almost surely connected subnetwork on a bounded area of given size. We derive an explicit expression for this bound, compute it in a variety of scenarios, and verify its tightness by simulation. The numerical results can be used for the practical design and simulation of wireless sensor and ad hoc networks. In addition, they give insight into how fading affects the topology of multihop networks. It is explained why a high fading variance helps the network to become connected. [PUBLICATION ABSTRACT]

Background The atrioventricular node (AVN) plays a critical role in coordinating the sequential activation and contraction of the heart’s chambers by transmitting electrical impulses from the sinoatrial node (SAN) to the ventricles via the His-Purkinje system. Besides its primary function, the AVN can generate intrinsic pacemaker activity when the SAN fails, and it serves as an important pharmacological target for controlling ventricular rate in the case of atrial arrhythmias. Despite its clinical significance, detailed electrophysiological studies of the AVN have been challenging due to difficulties in isolating viable AVN cells. The dense cellular network and complex structure of the AVN hinder enzymatic digestion, often leading to low yield and poor cell viability. Traditional isolation methods—such as adapting SAN cell protocols or employing the Langendorff perfusion technique—are limited by inadequate enzymatic penetration and preferential perfusion of the ventricular region, which significantly hampers the yield and viability of AVN cells for electrophysiological studies. Therefore, it is necessary to develop an optimized method to isolate high-quality AVN cells. Methods A refined method that does not rely on the Langendorff technique was used to isolate AVN cells from adult mice. Immunofluorescent imaging was used to confirm the presence of HCN4-positive cells. Patch clamp techniques were employed to record action potentials and ionic currents in AVN cells. Intracellular Ca 2+ transients and sarcomere length measurements were obtained using the IonOptix system. Results We have developed an improved non-Langendorff perfusion technique that combines targeted enzymatic digestion with enhanced perfusion of the AVN region. By cannulating and ligating the aorta and packing the perfusion cannula tip with gauze, we achieved uniform enzyme distribution throughout the AVN area. This innovation results in a high yield of viable AVN cells that maintain their electrophysiological properties, making them suitable for advanced analyses such as patch-clamp recordings and calcium transient measurements. Conclusions Our method provides a strong platform for investigating the physiological and pathological roles of the AVN. This approach has the potential to aid in the development of novel therapeutic strategies for atrioventricular conduction disorders.

Network survivability is the ability of a network to stay connected under failures and attacks, which is a fundamental issue to the design and performance evaluation of wireless ad hoc networks. In this paper, we focus on the analysis of network survivability in the presence of node misbehaviors and failures. First, we propose a novel semi-Markov process model to characterize the evolution of node behaviors. As an immediate application of the proposed model, we investigate the problem of node isolation where the effects of denial-of-service (DoS) attacks are considered. Then, we present the derivation of network survivability and obtain the lower and upper bounds on the topological survivability for k-connected networks. We find that the network survivability degrades very quickly with the increasing likelihood of node misbehaviors, depending on the requirements of disjoint outgoing paths or network connectivity. Moreover, DoS attacks have a significant impact on the network survivability, especially in dense networks. Finally, we validate the proposed model and analytical result by simulations and numerical analysis, showing the effects of node misbehaviors on both topological survivability and network performance.

Smart meters are one of the key components of intelligent power grids. Wireless mesh networks based on smart meters could provide customer-oriented information on electricity use to the operational control systems, which monitor power grid status and estimate electric power demand. Using this information, an operational control system could regulate devices within the smart grid in order to provide electricity in a cost-efficient manner. Ensuring the availability of the smart meter mesh network is therefore a critical factor in securing the soundness of an intelligent power system. Wormhole attacks can be one of the most difficult-to-address threats to the availability of mesh networks, and although many methods to nullify wormhole attacks have been tried, these have been limited by high computational resource requirements and unnecessary overhead, as well as by the lack of ability of such methods to respond to attacks. In this paper, an effective defense mechanism that both detects and responds to wormhole attacks is proposed. In the proposed system, each device maintains information on its neighbors, allowing each node to identify replayed packets. The effectiveness and efficiency of the proposed method is analyzed in light of additional computational message and memory complexities.

Connectivity is a fundamental issue in research on wireless sensor networks. However, unreliable and asymmetric links have a great impact on the global quality of connectivity (QoC). By assuming the deployment of nodes a homogeneous Poisson point process and eliminating the border effect, this paper derives an explicit expression of node non-isolation probability as the upper bound of one-connectivity, based on an analytical link model which incorporates important parameters such as path loss exponent, shadowing variance of channel, modulation, encoding method etc. The derivation has built a bridge over the local link property and the global network connectivity, which makes it clear to see how various parameter impact the QoC. Numerical results obtained further confirm the analysis and can be used as reference for practical design and simulation of wireless ad hoc and sensor networks. Besides, we find giant component size a good relaxed measure of connectivity in some applications that do not require full connectivity.

This paper aims to propose a framework for optimizing performance in cluster-based wireless sensor networks (WSNs) with constrains of energy consumption, delay and connectivity. For the limitation of energy storage being discussed a lot, many researches try to find more solutions to improve it. But, the other index of wireless sensor networks may be deteriorated by many routings which are dedicated to optimizing energy consumption. Thereby, multi-objectives optimization is one of significant issues in WSNs. The model of isolation nodes probability for connectivity in the clusterbased networks is adopted for the issue. Not only will the performance of Leach and existing multiobjectives optimization methods be compared under the proposed framework, but also will the performance of networks in different size of scenarios be analyzed. Simulation results show that the proposed framework combining NSGA can provide an effective sensing in terms of energy consumption, delay and connectivity in the cluster-based networks.

Peripheral tuberculous lymphadenitis accounts for ∼10% of tuberculosis cases in the United States. Epidemiologic characteristics include a 1.4:1 female-to-male ratio, a peak age range of 30—40 years, and dominant foreign birth, especially East Asian. Patients present with a 1—2 month history of painless swelling of a single group of cervical lymph nodes. Definitive diagnosis is by culture or nucleic amplification of Mycobacterium tuberculosis; demonstration of acid fast bacilli and granulomatous inflammation may be helpful. Excisional biopsy has the highest sensitivity at 80%, but fine-needle aspiration is less invasive and may be useful, especially in immunocompromised hosts and in resource-limited settings. Antimycobacterial therapy remains the cornerstone of treatment, but response is slower than with pulmonary tuberculosis; persistent pain and swelling are common, and paradoxical upgrading reactions may occur in 20% of patients. The role of steroids is controversial. Initial excisional biopsy deserves consideration for both optimal diagnosis and management of the otherwise slow response to therapy.

Human immunodeficiency virus 1 (HIV-1) reservoir cells persist lifelong despite antiretroviral treatment 1 , 2 but may be vulnerable to host immune responses that could be exploited in strategies to cure HIV-1. Here we used a single-cell, next-generation sequencing approach for the direct ex vivo phenotypic profiling of individual HIV-1-infected memory CD4 + T cells from peripheral blood and lymph nodes of people living with HIV-1 and receiving antiretroviral treatment for approximately 10 years. We demonstrate that in peripheral blood, cells harbouring genome-intact proviruses and large clones of virally infected cells frequently express ensemble signatures of surface markers conferring increased resistance to immune-mediated killing by cytotoxic T and natural killer cells, paired with elevated levels of expression of immune checkpoint markers likely to limit proviral gene transcription; this phenotypic profile might reduce HIV-1 reservoir cell exposure to and killing by cellular host immune responses. Viral reservoir cells harbouring intact HIV-1 from lymph nodes exhibited a phenotypic signature primarily characterized by upregulation of surface markers promoting cell survival, including CD44, CD28, CD127 and the IL-21 receptor. Together, these results suggest compartmentalized phenotypic signatures of immune selection in HIV-1 reservoir cells, implying that only small subsets of infected cells with optimal adaptation to their anatomical immune microenvironment are able to survive during long-term antiretroviral treatment. The identification of phenotypic markers distinguishing viral reservoir cells may inform future approaches for strategies to cure and eradicate HIV-1. A proteogenomic profiling analysis of single cells from the blood and lymph nodes of individuals living with HIV-1 reveals that CD4 + memory T cells harbouring intact provirus show signatures associated with resistance to immune-mediated killing and cell survival.