UHEED - an unequal clustering algorithm for wireless sensor networks

Prolonging the lifetime of wireless sensor networks has always been a determining factor when designing and deploying such networks. Clustering is one technique that can be used to extend the lifetime of sensor networks by grouping sensors together. However, there exists the hot spot problem which causes an unbalanced energy consumption in equally formed clusters. In this paper, we propose UHEED, an unequal clustering algorithm which mitigates this problem and which leads to a more uniform residual energy in the network and improves the network lifetime. Furthermore, from the simulation results presented, we were able to deduce the most appropriate unequal cluster size to be used

On the performance, availability and energy consumption modelling of clustered IoT systems

Wireless sensor networks (WSNs) form a large part of the ecosystem of the Internet of Things (IoT), hence they have numerous application domains with varying performance and availability requirements. Limited resources that include processing capability, queue capacity, and available energy in addition to frequent node and link failures degrade the performance and availability of these networks. In an attempt to efficiently utilise the limited resources and to maintain the reliable network with efficient data transmission; it is common to select a clustering approach, where a cluster head is selected among the diverse IoT devices. This study presents the stochastic performance as well as the energy evaluation model for WSNs that have both node and link failures. The model developed considers an integrated performance and availability approach. Various duty cycling schemes within the medium-access control of the WSNs are also considered to incorporate the impact of sleeping/idle states that are presented using analytical modeling. The results presented using the proposed analytical models show the effects of factors such as failures, various queue capacities and system scalability. The analytical results presented are in very good agreement with simulation results and also present an important fact that the proposed models are very useful for identification of thresholds between WSN system characteristics

Packet arrival analysis in wireless sensor networks

Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs

Does the assumption of exponential arrival distributions in wireless sensor networks hold?

Wireless Sensor Networks have seen a tremendous growth in various application areas despite prominent performance and availability challenges. One of the common configurations to prolong the lifetime and deal with the path loss phenomena having a multi-hop set-up with clusters and cluster heads to relay the information. Although researchers continue to address these challenges, the type of distribution for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. The general practice in published works is to compare an empirical exponential arrival distribution of wireless sensor networks with a theoretical exponential distribution in a Q-Q plot diagram. In this paper, we show that such comparisons based on simple eye checks are not sufficient since, in many cases, incorrect conclusions may be drawn from such plots. After estimating the Maximum Likelihood parameters of empirical distributions, we generate theoretical distributions based on the estimated parameters. By conducting Kolmogorov-Smirnov Test Statistics for each generated inter-arrival time distributions, we find out, if it is possible to represent the traffic into the cluster head by using theoretical distribution. Empirical exponential arrival distribution assumption of wireless sensor networks holds only for a few cases. There are both theoretically known such as Gamma, Log-normal and Mixed Log-Normal of arrival distributions and theoretically unknown such as non-Exponential and Mixed cases of arrival in wireless sensor networks. The work is further extended to understand the effect of delay on inter-arrival time distributions based on the type of medium access control used in wireless sensor networks

Cardiac Impairment Evaluated by Transesophageal Echocardiography and Invasive Measurements in Rats Undergoing Sinoaortic Denervation

Background: Sympathetic hyperactivity may be related to left ventricular (LV) dysfunction and baro- and chemoreflex impairment in hypertension. However, cardiac function, regarding the association of hypertension and baroreflex dysfunction, has not been previously evaluated by transesophageal echocardiography (TEE) using intracardiac echocardiographic catheter.Methods and Results: We evaluated exercise tests, baroreflex sensitivity and cardiovascular autonomic control, cardiac function, and biventricular invasive pressures in rats 10 weeks after sinoaortic denervation (SAD). the rats (n = 32) were divided into 4 groups: 16 Wistar (W) with (n = 8) or without SAD (n = 8) and 16 spontaneously hypertensive rats (SHR) with (n = 8) or without SAD (SHRSAD) (n = 8). Blood pressure (BP) and heart rate (HR) did not change between the groups with or without SAD; however, compared to W, SHR groups had higher BP levels and BP variability was increased. Exercise testing showed that SHR had better functional capacity compared to SAD and SHRSAD. Echocardiography showed left ventricular (LV) concentric hypertrophy; segmental systolic and diastolic biventricular dysfunction; indirect signals of pulmonary arterial hypertension, mostly evident in SHRSAD. the end-diastolic right ventricular (RV) pressure increased in all groups compared to W, and the end-diastolic LV pressure increased in SHR and SHRSAD groups compared to W, and in SHRSAD compared to SAD.Conclusions: Our results suggest that baroreflex dysfunction impairs cardiac function, and increases pulmonary artery pressure, supporting a role for baroreflex dysfunction in the pathogenesis of hypertensive cardiac disease. Moreover, TEE is a useful and feasible noninvasive technique that allows the assessment of cardiac function, particularly RV indices in this model of cardiac disease.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ São Paulo, Fac Med, Cardiomyopathy Unit, Heart Inst InCor,Hosp Clin, São Paulo, BrazilUniv São Paulo, Fac Med, Hypertens Unit, Heart Inst InCor,Hosp Clin, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biosci, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biosci, São Paulo, BrazilWeb of Scienc

Cholinergic stimulation by pyridostigmine bromide before myocardial infarction prevent cardiac and autonomic dysfunction

Inflammatory processes and cardiovascular autonomic imbalance are very relevant characteristic of the enormous dynamic process that is a myocardial infarction (MI). In this sense, some studies are investigating pharmacological therapies using acetylcholinesterase inhibitors, such as pyridostigmine bromide (PYR), aiming to increase parasympathetic tone after MI. Here we hypothesized that the use of PYR before the MI might bring an additional positive effect to the autonomic function, and consequently, in the inflammatory response and cardiac function. The present study aimed to evaluate left ventricular function, baroreflex sensitivity, autonomic modulation, and inflammatory profile in PYR- treated rats previously to MI. Methods: Male Wistar rats (250-300 g) were treated for 60 days with PYR. After treatment, they were submitted to the MI. After the MI, the autonomic and ventricular function were evaluated, as well as the systemic, left ventricle, and adipose tissue inflammatory profile. Results: PYR, performed before MI, prevented HR increase, systolic function impairment, baroreflex sensitivity drop, as well as pulse interval variance, RMSSD, blood pressure and parasympathetic modulation reduction in treated rats compared to untreated rats. Also, this positive functional changes may have been a result of the reduced inflammatory parameters in the left ventricle (IFN-alpha, IL-6, and IL-1 beta), as well as increased IL-10 expression and IL-10/TNF-alpha ratio in treated animals before MI. Conclusion: Prior treatment with PYR prevents impairment of the autonomic nervous system after MI, which may be associated with the attenuated expression of inflammatory factors and heart dysfunction9CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPsem informação2013/14788-9; 2014/06669-

Dynamic Resistance Training Improves Cardiac Autonomic Modulation and Oxidative Stress Parameters in Chronic Stroke Survivors: A Randomized Controlled Trial

Stroke survivors are at substantial risk of recurrent cerebrovascular event or cardiovascular disease. Exercise training offers nonpharmacological treatment for these subjects; however, the execution of the traditional exercise protocols and adherence is constantly pointed out as obstacles. Based on these premises, the present study investigated the impact of an 8-week dynamic resistance training protocol with elastic bands on functional, hemodynamic, and cardiac autonomic modulation, oxidative stress markers, and plasma nitrite concentration in stroke survivors. Twenty-two patients with stroke were randomized into control group (CG, n=11) or training group (TG, n=11). Cardiac autonomic modulation, oxidative stress markers, plasma nitrite concentration, physical function and hemodynamic parameters were evaluated before and after 8 weeks. Results indicated that functional parameters (standing up from the sitting position (P=0.011) and timed up and go (P=0.042)) were significantly improved in TG. Although not statistically different, both systolic blood pressure (Δ=-10.41 mmHg) and diastolic blood pressure (Δ=-8.16 mmHg) were reduced in TG when compared to CG. Additionally, cardiac autonomic modulation (sympathovagal balance-LF/HF ratio) and superoxide dismutase were improved, while thiobarbituric acid reactive substances and carbonyl levels were reduced in TG when compared to the CG subjects. In conclusion, our findings support the hypothesis that dynamic resistance training with elastic bands may improve physical function, hemodynamic parameters, autonomic modulation, and oxidative stress markers in stroke survivors. These positive changes would be associated with a reduced risk of a recurrent stroke or cardiac event in these subjects

Quantum efficiency measurement system for large area CsI photodetectors

A proximity focusing freon/CsI RICH detector has been built for kaon physics at Thomas Jefferson National Accelerator Facility (TJNAF or Jefferson Lab), Hall A. The Cherenkov photons are detected by a UV photosensitive CsI film which has been obtained by vacuum evaporation. A dedicated evaporation facility for large area photocathodes has been built for this task. A measuring system has been built to allow the evaluation of the absolute quantum efficiency (QE) just after the evaporation. The evaporation facility is described here, as well as the quantum efficiency measurement device. Results of the QE on-line measurements, for the first time on large area photocathodes, are reported

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management