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Summary: Recent technological advances led to the rapid and uncontrolled proliferation of intelligent surveillance systems (ISSs), serving to supervise urban areas. Driven by pressing public safety and security requirements, modern cities are being transformed into tangled cyber‐physical environments, consisting of numerous heterogeneous ISSs under different administrative domains with low or no capabilities for reuse and interaction. This isolated pattern renders itself unsustainable in city‐wide scenarios that typically require to aggregate, manage, and process multiple video streams continuously generated by distributed ISS sources. A coordinated approach is therefore required to enable an interoperable ISS for metropolitan areas, facilitating technological sustainability to prevent network bandwidth saturation. To meet these requirements, this paper combines several approaches and technologies, namely the Internet of Things, cloud computing, edge computing and big data, into a common framework to enable a unified approach to implementing an ISS at an urban scale, thus paving the way for the metropolitan intelligent surveillance system (MISS). The proposed solution aims to push data management and processing tasks as close to data sources as possible, thus increasing performance and security levels that are usually critical to surveillance systems. To demonstrate the feasibility and the effectiveness of this approach, the paper presents a case study based on a distributed ISS scenario in a crowded urban area, implemented on clustered edge devices that are able to off‐load tasks in a “horizontal” manner in the context of the developed MISS framework. As demonstrated by the initial experiments, the MISS prototype is able to obtain face recognition results 8 times faster compared with the traditional off‐loading pattern, where processing tasks are pushed “vertically” to the cloud. [ABSTRACT FROM AUTHOR]

Aims The release of the B-type natriuretic peptide ( BNP) is increased in heart failure ( HF), a condition associated with oxidative stress. BNP is known to exert anti-inflammatory effects including suppression of neutrophil superoxide ( O2−) release. However, BNP-based restoration of homeostasis in HF is inadequate, and the equivocal clinical benefit of a recombinant BNP, nesiritide, raises the possibility of attenuated response to BNP. We therefore tested the hypothesis that BNP-induced suppression of neutrophil O2− generation is impaired in patients with acute HF. Methods and results We have recently characterized suppression of neutrophil O2− generation ( PMA- or fMLP-stimulated neutrophil burst) by BNP as a measure of its physiological activity. In the present study, BNP response was compared in neutrophils of healthy subjects ( n = 29) and HF patients ( n = 45). Effects of BNP on fMLP-induced phosphorylation of the NAD(P)H oxidase subunit p47phox were also evaluated. In acute HF patients, the suppressing effect of BNP (1 µmol/L) on O2− generation was attenuated relative to that in healthy subjects ( P < 0.05 for both PMA and fMLP). Analogously, BNP inhibited p47phox phosphorylation in healthy subjects but not in HF patients ( P < 0.05). However, O2−-suppressing effects of the cell-permeable cGMP analogue (8- pCPT-cGMP) were preserved in acute HF. Conventional HF treatment for 5 weeks partially restored neutrophil BNP responsiveness ( n = 25, P < 0.05), despite no significant decrease in plasma NT-proBNP levels. Conclusions BNP inhibits neutrophil O2− generation by suppressing NAD(P)H oxidase assembly. This effect is impaired in acute HF patients, with partial recovery during treatment. [ABSTRACT FROM AUTHOR]

Background and Purpose Nitrite ( NO2−) has recently been shown to represent a potential source of NO, in particular under hypoxic conditions. The aim of the current study was to compare the haemodynamic effects of NO2− in healthy volunteers and patients with stable congestive heart failure ( CHF). Experimental Approach The acute haemodynamic effects of brachial artery infusion of NO2− (0.31 to 7.8 μmol·min−1) was assessed in normal subjects ( n = 20) and CHF patients ( n = 21). Key Results NO2− infusion was well tolerated in all subjects. Forearm blood flow ( FBF) increased markedly in CHF patients at NO2− infusion rates which induced no changes in normal subjects ( anova: F = 5.5; P = 0.02). Unstressed venous volume ( UVV) increased even with the lowest NO2− infusion rate in all subjects (indicating venodilation), with CHF patients being relatively hyporesponsive compared with normal subjects ( anova: F = 6.2; P = 0.01). There were no differences in venous blood pH or oxygen concentration between groups or during NO2− infusion. Venous plasma NO2− concentrations were lower in CHF patients at baseline, and rose substantially less with NO2− infusion, without incremental oxidative generation of nitrate, consistent with accelerated clearance in these patients. Plasma protein-bound NO concentrations were lower in CHF patients than normal subjects at baseline. This difference was attenuated during NO2− infusion. Prolonged NO2− exposure in vivo did not induce oxidative stress, nor did it induce tolerance in vitro. Conclusions and Implications The findings of arterial hyper-responsiveness to infused NO2− in CHF patients, with evidence of accelerated transvascular NO2− clearance (presumably with concomitant NO release) suggests that NO2− effects may be accentuated in such patients. These findings provide a stimulus for the clinical exploration of NO2− as a therapeutic modality in CHF. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things is underpinned by the global penetration of network‐connected smart devices continuously generating extreme amounts of raw data to be processed in a timely manner. Supported by Cloud and Fog/Edge infrastructures – on the one hand, and Big Data processing techniques – on the other, existing approaches, however, primarily adopt a vertical offloading model that is heavily dependent on the underlying network bandwidth. That is, (constrained) network communication remains the main limitation to achieve truly agile IoT data management and processing. This paper aims to bridge this gap by defining Clustered Edge Computing – a new approach to enable rapid data processing at the very edge of the IoT network by clustering edge devices into fully functional decentralized ensembles, capable of workload distribution and balancing to accomplish relatively complex computational tasks. This paper also proposes ECStream Processing that implements Clustered Edge Computing using Stream Processing techniques to enable dynamic in‐memory computation close to the data source. By spreading the workload among a cluster of collocated edge devices to process data in parallel, the proposed approach aims to improve performance, thereby supporting agile data management. The experimental results confirm that such a distributed in‐memory approach to data processing at the very edge of an IoT network can outperform currently adopted Cloud‐enabled architectures, and has the potential to address a wide range of IoT‐related data‐intensive time‐critical scenarios. [ABSTRACT FROM AUTHOR]