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In this paper, the parameter estimation problem based on diffusion least-mean-squares strategies is analyzed from a coalitional game theoretical perspective. Specifically, while selfishly minimizing only their own mean-square costs, the nodes in a network form coalitions that benefit them. Due to its nature, the problem is modeled as a nontransferable game and two scenarios are studied, one where each node's payoff includes only a suitable estimation accuracy criterion and another one in which a graph-based communication cost is also considered. In the former scenario, we first analyze the nonemptiness of the core of the games corresponding to traditional diffusion strategies, and then, the analysis is extended to a recently proposed node-specific parameter estimation setting where the nodes have overlapped but different estimation interests. In the latter scenario, after formulating a coalitional graph game and providing sufficient conditions for its core nonemptiness, we propose a distributed graph formation algorithm, based on merge-and-split approach, which converges to a stable coalition structure.

Sudden occlusion of an artery caused by a thrombus or emboli is the most frequent cause of acute brain ischemia (ABI). Carotid endarterectomy (CEA) represents the gold standard for preventing strokes of carotid origin. However, neuronal damage caused by ischemia and/or reperfusion may contribute to a poor clinical outcome after CEA. In response to shear stress caused by hypoxic-ischemic conditions in patients undergoing CEA, stimulation of the hypothalamic-pituitaryadrenal axis leads to biological responses known as hypermetabolic stress, characterized by hemodynamic, metabolic, inflammatory and immunological changes. These changes maintain homeostasis and assist recovery, but an unregulated inflammatory response could lead to further tissue damage and death of neurons. Nitric oxide (NO) is an important signaling molecule involved in several physiological and pathological processes, including ABI. However, an excess of NO could have detrimental effects. We hypothesized that the hypoxic-ischemic state induced by carotid clamping leads to overexpression of inducible NO synthase and that uncontrolled production of NO could adversely affect outcome after CEA. © 2018 Elsevier Ltd

The problem of range-migrating target detection in a compound-Gaussian clutter is studied here. We assume a target to have a range-walk of a few range cells during the coherent processing interval, when observed by wideband radar with high range resolution. Two CFAR detectors are proposed assuming different correlation properties of clutter over range. The detectors' performance is studied via numerical simulations and a significant improvement over existing techniques is demonstrated.

We consider a target selection problem for multitarget tracking in a multifunction radar network from a gametheoretic perspective. The problem is formulated as a noncooperative game. The radars are considered to be players in this game with utilities modeled using a proper tracking accuracy criterion and their strategies are the observed targets whose number is known. Initially, for the problem of coordination, the Nash equilibria are characterized and, in order to find equilibria points, a distributed algorithm based on the bestresponse dynamics is proposed. Afterwards, the analysis is extended to the case of partial target observability and radar connectivity and heterogeneous interests among radars. The solution concept of correlated equilibria is employed and a distributed algorithm based on the regret-matching is proposed. The proposed algorithms are shown to perform well compared to the centralized approach of significantly higher complexity

An altered hepatic lipid metabolism involves multifactorial pathologies such as hepatic inflammation, insulin resistance and oxidative stress. Immunity has an essential role in the regulation of glucose and lipid metabolism in the liver. Inducible nitric oxide (NO) synthase (iNOS) has been proposed as an important factor that interplays between immunity and energy metabolism and also in the pathogenesis of obesity-linked insulin resistance. In the liver, locally produced NO plays a protective role during inflammation, and the balance of NO protective and cytotoxic effects is very important. This review is focused on understanding the molecular mechanisms of iNOS regulation in the state of altered hepatic lipid metabolism, which is critical for developing new strategies for treatment of hepatic disorders.

In this work, we address the so-called sensor reachback problem for Wireless Sensor Networks, which consists in collecting the measurements acquired by a large number of sensor nodes into a sink node which has major computational and power capabilities. Focused on applications such as Structural Health Monitoring, we propose a cooperative communication protocol that exploits the spatio-temporal correlations of the sensor measurements in order to save energy when transmitting the information to the sink node in a non-stationary environment. In addition to cooperative communications, the protocol is based on two well-studied adaptive filtering techniques, Least Mean Squares and Recursive Least Squares, which trade off computational complexity and reduction in the number of transmissions to the sink node. Finally, experiments with real acceleration measurements, obtained from the Canton Tower in China, are included to show the effectiveness of the proposed method.

Background The sodium/potassium- adenosine- triphosphatase (Na+/K+-ATPase) is an important mediator in vasculature tone and contractility, and its abnormal regulation has been implicated in many diseases such as obesity, insulin resistance, diabetes, and hypertension. Decreased Na+/K+-ATPase abundance and its altered isoform expression induce cardiomyocytes death and cardiac dysfunction, possibly leading to the development of myocardial dilation and heart failure. Therefore, the regulation of Na+/K+-ATPase activity/expression could be important in treatment and possible prevention of cardio-metabolic diseases. A number of hormones and environmental factors regulate the function of Na+/K+-ATPase in response to changing cellular requirements. Estradiol and insulin like growth factor-1 (IGF-1) are among potent hormones that positively regulate Na+/K+- ATPase activity or de novo synthesis of α - and β - subunits. Both estradiol and IGF-1 have a huge therapeutic potential in treatment of vasculopathy in cardio-metabolic diseases. Methods We searched the MEDLINE and PUBMED databases for all English and non-English articles with an English abstract from April 1978 to May 2016. The main data search terms were: Na+/K+-ATPase; estradiol and Na+/K+-ATPase; estradiol, Na+/K+-ATPase and CVS; estradiol, Na+/K+-ATPase and CVD; estradiol, Na+/K+- ATPase and obesity; estradiol, Na+/K+-ATPase and diabetes; estradiol, Na+/K+-ATPase and hypertension; IGF-1; IGF-1 and Na+/K+-ATPase; IGF-1, Na+/K+-ATPase and CVS; IGF-1, Na+/K+-ATPase and CVD; IGF-1, Na+/K+- ATPase and obesity; IGF-1, Na+/K+-ATPase and diabetes; IGF-1, Na+/K+-ATPase and hypertension. Results The present review discusses the latest data from animal and human studies which focus on the effects of estradiol and IGF-1 on Na+/K+-ATPase regulation in physiological and pathophysiological conditions in cardiovascular system. Conclusion Understanding the molecular mechanisms of estradiol and IGF-1 action on Na+/K+-ATPase in humans, may help resolving outstanding issues and developing new strategies for the protection and treatment of cardiovascular diseases.

In this work, a prediction-error-based method that aims to reduce the amount of data transmission and storage in structural health monitoring wireless sensor networks (WSN) while keeping the damage detection capabilities intact is presented. WSNs offer tremendous promise for accurate and continuous structural monitoring using a dense array of inexpensive sensors and possess many advantages over conventional wired systems, particularly for large civil infrastructures. This paper validates the studied approach with the data collected during a test on a three-story steel frame mounted at the ELSA laboratory of the EU Joint Research Center in Ispra, Italy. The frame is tested with and without steel bracing, which results in non-sway behavior and sway frame responses. The excitation is provided by a shaker mounted on top of the frame. Accelerometer signals are collected by a multi-channel data acquisition system. The proposed method has been tested extensively via recorded experimental data and it offers considerable saving in transmitted energy while at the same time keeping the ability to detect changes or damage in the structure.

In this paper, a track selection problem for multi-target tracking in a multifunction radar network is studied using the concepts from game theory. The problem is formulated as a non-cooperative game, and specifically as an anti-coordination game, where each player aims to differ from what other players do. The players' utilities are modeled using a proper tracking accuracy criterion and, under different assumptions on the structure of these utilities, the corresponding Nash equilibria are characterized. To find an equilibrium, a distributed algorithm based on the best-response dynamics is proposed. Finally, computer simulations are carried out to verify the effectiveness of the proposed algorithm in a multi-target tracking scenario., Accepted for ICASSP 2016 conference

Copeptin is a sensitive and more stable surrogate marker for arginine vasopressin. In this study, we evaluated copeptin levels in carotid endarterectomy (CEA) patients, perioperatively, to determine whether copeptin levels can be related to carotid artery cross clamping (CC) time and to postoperative neurological outcomes. Copeptin, interleukin 6, C-reactive protein, cortisol, and brain natriuretic peptide were measured preoperatively (T1) and 3 hours postoperatively (T3) as well as intraoperatively (T2). We recruited 77 patients. Values of copeptin rose gradually over the observed times: T1 = 7.9 (6.4-9.6), T2 = 12.6 (9.3-16.8), and T3 = 72.3 (49.1-111.2) pmol/L. There was a significant difference for repeated measurement ( P = .000, P = .000, and P = .000). Duration of carotid artery CC during CEA does not affect postoperative copeptin level (CC ≤ 13 minutes: 106.8 ± 93.6 pmol/L, CC > 13 minutes: 96.7 ± 89.1 pmol/L; P = .634). Preoperative copeptin level was significantly higher in patients with ulcerated plaque morphology. Activation of the stress axis in patients undergoing CEA results in copeptin elevation. Duration of CC during CEA does not affect postoperative copeptin levels.

In this paper, the parameter estimation problem based on diffusion least mean squares strategies is studied from a coalitional game theoretical perspective. The problem has been modeled as a non-transferable coalitional game and two scenarios have been considered, one where the value function includes only a suitable estimation accuracy criterion and another one in which the cost of coalition formation is taken into account as well. In the former scenario, we first analyze the non-emptiness of the core of the games corresponding to traditional diffusion strategies, and then, we extend the analysis to a recently proposed node-specific parameter estimation setting where the nodes have overlapped but different estimation interests. In the latter scenario, we employ a distributed coalition formation algorithm, based on merge-and-split steps, which converges to a stable coalition structure.

A distributed adaptive algorithm is proposed to solve a node-specific parameter estimation problem where nodes are interested in estimating parameters of local interest and parameters of global interest to the whole network. To address the different node-specific parameter estimation problems, this novel algorithm relies on a diffusion-based implementation of different Least Mean Squares (LMS) algorithms, each associated with the estimation of a specific set of local or global parameters. Although all the different LMS algorithms are coupled, the diffusion-based implementation of each LMS algorithm is exclusively undertaken by the nodes of the network interested in a specific set of local or global parameters. To illustrate the effectiveness of the proposed technique we provide simulation results in the context of cooperative spectrum sensing in cognitive radio networks., 5 pages, 2 figures, Published in Proc. IEEE ICASSP, Florence, Italy, May 2014

A distributed adaptive algorithm is proposed to solve a node-specific parameter estimation problem where nodes are interested in estimating parameters of local interest, parameters of common interest to a subset of nodes and parameters of global interest to the whole network. To address the different node-specific parameter estimation problems, this novel algorithm relies on a diffusion-based implementation of different Least Mean Squares (LMS) algorithms, each associated with the estimation of a specific set of local, common or global parameters. Coupled with the estimation of the different sets of parameters, the implementation of each LMS algorithm is only undertaken by the nodes of the network interested in a specific set of local, common or global parameters. The study of convergence in the mean sense reveals that the proposed algorithm is asymptotically unbiased. Moreover, a spatial-temporal energy conservation relation is provided to evaluate the steady-state performance at each node in the mean-square sense. Finally, the theoretical results and the effectiveness of the proposed technique are validated through computer simulations in the context of cooperative spectrum sensing in Cognitive Radio networks., Comment: 13 pages, 6 figures

We introduce an adaptive distributed technique that is suitable for node-specific parameter estimation in an adaptive network where each node is interested in a set of parameters of local interest as well as a set of network global parameters. The estimation of each set of parameters of local interest is undertaken by a local Least Mean Squares (LMS) algorithm at each node. At the same time and coupled with the previous local estimation processes, an incremental mode of cooperation is implemented at all nodes in order to perform an LMS algorithm which estimates the parameters of global interest. In the steady state, the new distributed technique converges to the MMSE solution of a centralized processor that is able to process all the observations. To illustrate the effectiveness of the proposed technique we provide simulation results in the context of cooperative spectrum sensing in cognitive radio networks.

Wireless Sensor Networks (WSNs) have recently received great attention from the scientific community, because they hold the key to revolutionize many aspects of the industry and our life. The process of collecting the measurements, acquired by a sensor network into a central sink node, constitutes one of the main challenges in this area of research and is often referred to as the sensor reachback problem. In this work, we extend a recently proposed power and rate allocation algorithm so as to be able to take into account possible cooperation between the nodes in the WSN. The derived power and rate allocation algorithm considers Distributed Source Coding (DSC), in order to reduce the amount of information that must be transmitted to the sink. Under the assumption that there are several very bad channels between nodes and the sink, our method achieves both a lower peak power threshold, as well as reduced total power consumption.

Alzheimer's disease (AD) is a complex and progressive neurodegenerative disorder, and represents the most common form of dementia. The number of people affected by AD is estimated to be doubled by the year of 2050, and more than 100 million people worldwide will be affected by this disease. Still, there is no reliable diagnostic test which would indicate pre-symptomatic conditions or an increased risk of developing AD. The only drugs approved by the FDA belong to the cholinesterase inhibitors (ChEI) group, such as donepezil, rivastigmine, galantamine and memantine that belongs to a class of drugs named receptor NMDA antagonists. Most mainstream pharmacotherapeutic approaches act by slowing the progression of the condition rather than to treat or prevent the cause of AD. In this review we are presenting literature data from recent research related to new avenues in the classical approach to prevention and treatment of AD.