A customizable multi-agent system for distributed data mining

We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances

BodyCloud: a SaaS approach for community body sensor networks

Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals

Fault tolerant decentralised K-Means clustering for asynchronous large-scale networks

The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale

Modeling and simulation of cantilever beam for wind energy harvesting

Energy Harvesting (EH) is the science that studies the conversion of energy dispersed in environment into a different and more useful form of energy, mainly the electrical one. In recent years, several energy-harvesting devices using piezoelectric materials have been developed to transform environmental vibrations into electrical energy. Since most piezoelectric energy harvesters are in form of cantilevered beams, the aim of this paper is to model and simulate a cantilever beam as energy harvester from wind-induced vibrations. The behavior of a cantilever beam with a fixed configuration (dimensions, materials, boundaries and shape) subjected to wind pressure was observed in an experimental apparatus and the reaction of the same device was described with a mathematical model based on piezoelectric constitutive equations and mechanical equilibrium equations. The device was simulated with the Comsol Multiphysics software that implements the equations of the mathematical model by the Finite Element Method (FEM). The experimental results were used to validate the simulation environment and their comparison with calculated results allows an appropriate choice of the most suitable piezoelectric material, among natural crystals, piezo ceramics, piezo polymers and piezocomposites, for this type of cantilever

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed

Treatment of young children with CNS-positive acute lymphoblastic leukemia without cranial radiotherapy

Background: Due to the long-term sequelae of cranial radiotherapy (CRT), contemporary treatment protocols for children with acute lymphoblastic leukemia (ALL) aim to limit the use of prophylactic CRT. For patients with central nervous system (CNS) involvement with ALL at diagnosis, the use of CRT remains common. Children \u3c5 years of age are a particularly challenging subgroup in whom the consequences of CRT can be devastating. Procedure: This study retrospectively describes the overall (OS) and event-free survival (EFS) of young children (1-5 years) who were treated for CNS-positive ALL at the Hospital for Sick Children between 2000 and 2013. Results: Of a total of 19 patients, two were treated with upfront CRT, both as part of the conditioning regimen prior to HSCT. All patients received intensification of CNS-directed chemotherapy by triple intra-thecal chemotherapy (84.2%), use of dexamethasone in induction (57.9%) and maintenance (66.7%), and high-dose methotrexate (77.8%). The OS was 84.2±8.4% and EFS was 79.0±9.4% with a median follow-up time of 4.3 years (range, 2.6-8.2). The cumulative incidence of CNS relapse was 5.2±5.1%. Conclusions: We conclude that omission of CRT from the treatment of young children with ALL involving the CNS is associated with acceptable survival and avoids potentially devastating late effects in this group

Proofs of nonlocality without inequalities revisited

We discuss critically the so-called nonlocality without inequalities proofs for bipartite quantum states, we generalize them and we analyze their relation with the Clauser-Horne inequality.Comment: 8 pages, RevTex; to be published on PL

Diffraction-free light droplets for axially-resolved volume imaging

An ideal direct imaging system entails a method to illuminate on command a single diffraction-limited region in a generally thick and turbid volume. The best approximation to this is the use of large-aperture lenses that focus light into a spot. This strategy fails for regions that are embedded deep into the sample, where diffraction and scattering prevail. Airy beams and Bessel beams are solutions of the Helmholtz Equation that are both non-diffracting and self-healing, features that make them naturally able to outdo the effects of distance into the volume but intrinsically do not allow resolution along the propagation axis. Here, we demonstrate diffraction-free self-healing three-dimensional monochromatic light spots able to penetrate deep into the volume of a sample, resist against deflection in turbid environments, and offer axial resolution comparable to that of Gaussian beams. The fields, formed from coherent mixtures of Bessel beams, manifest a more than ten-fold increase in their undistorted penetration, even in turbid milk solutions, compared to diffraction-limited beams. In a fluorescence imaging scheme, we find a ten-fold increase in image contrast compared to diffraction-limited illuminations, and a constant axial resolution even after four Rayleigh lengths. Results pave the way to new opportunities in three-dimensional microscopy

Improvement of neuropsychological performances and reduction of immune-activation markers after probiotic supplementation and change of life-style in an HIV positive male: targeting the microbiota to act on gut-brain axis

The gut-brain axis is widely in uenced by the intestinal microbiota and dysbiosis is consequently associated with a large dysregulation of its functions. Probiotic supplementation, reducing the harmful effects of dysbiosis, has shown positive effects not only on gut and brain functions, but also on the control of the dangerous effects of immune activation. Mounting evidence has shown that neurocognitive impairment can be a secondary to the impairment of the microbiota-gut-brain axis in HIV positive patients. In this case report we analyzed the im- provement of neurocognitive performances associated with a reduction of levels of peripheral immune-activa- tion, after 6 months of probiotic supplementation. In this case, the achieved result may have been in uenced by a more comprehensive modi cation of the patient’s lifestyle with the introduction of a controlled diet and regular physical activity. Our observations suggest that integrate antiretroviral therapy and non-pharmacological tools into an overall approach, can be a useful strategy to control some non-AIDS related diseases

Breaking the Contrast Limit in Single-Pass Fabry-Pérot Spectrometers

The development of high-resolution Fabry-Pérot interferometers has enabled a wide range of scientific and technological advances—ranging from the characterization of material properties to the more fundamental studies of quasi particles in condensed matter. Spectral contrast is key to measuring weak signals and can reach a 103 peak-to-background ratio in a single-pass assembly.At its heart, this limit is a consequence of an unbalanced field amplitude across multiple interfering paths, with an ensuing reduced fringe visibility. Using a high-resolution, high-throughput virtually imaged phased array spectrometer, we demonstrate an intensity-equalization method to achieve an unprecedented 1000-fold increase in spectral contrast in a single-stage, single-pass configuration. To validate the system, we obtain the Brillouin spectrum of water at high scattering concentrations where, unlike with the standard scheme, the inelastic peaks are highly resolved. Our method brings the interferometer close to its ultimate limits and allows rapid high-resolution spectral analysis in a wide range of fields, including Brillouin spectroscopy, mechanical imaging, and molecular fingerprinting