Data as a Service (DaaS) for sharing and processing of large data collections in the cloud

Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.Peer ReviewedPostprint (author's final draft

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics

The accurate and efficient solution of Maxwell's equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation applications. Therefore, many efforts are focussed on the development of new and more efficient approach to solve Maxwell's equation. The interest in CEM applications is growing on. Several problems, hard to figure out few years ago, can now be easily addressed thanks to the reliability and flexibility of new technologies, together with the increased computational power. This technology evolution opens the possibility to address large and complex tasks. Many of these applications aim to simulate the electromagnetic behavior, for example in terms of input impedance and radiation pattern in antenna problems, or Radar Cross Section for scattering applications. Instead, problems, which solution requires high accuracy, need to implement full wave analysis techniques, e.g., virtual prototyping context, where the objective is to obtain reliable simulations in order to minimize measurement number, and as consequence their cost. Besides, other tasks require the analysis of complete structures (that include an high number of details) by directly simulating a CAD Model. This approach allows to relieve researcher of the burden of removing useless details, while maintaining the original complexity and taking into account all details. Unfortunately, this reduction implies: (a) high computational effort, due to the increased number of degrees of freedom, and (b) worsening of spectral properties of the linear system during complex analysis. The above considerations underline the needs to identify appropriate information technologies that ease solution achievement and fasten required elaborations. The authors analysis and expertise infer that Grid Computing techniques can be very useful to these purposes. Grids appear mainly in high performance computing environments. In this context, hundreds of off-the-shelf nodes are linked together and work in parallel to solve problems, that, previously, could be addressed sequentially or by using supercomputers. Grid Computing is a technique developed to elaborate enormous amounts of data and enables large-scale resource sharing to solve problem by exploiting distributed scenarios. The main advantage of Grid is due to parallel computing, indeed if a problem can be split in smaller tasks, that can be executed independently, its solution calculation fasten up considerably. To exploit this advantage, it is necessary to identify a technique able to split original electromagnetic task into a set of smaller subproblems. The Domain Decomposition (DD) technique, based on the block generation algorithm introduced in Matekovits et al. (2007) and Francavilla et al. (2011), perfectly addresses our requirements (see Section 3.4 for details). In this chapter, a Grid Computing infrastructure is presented. This architecture allows parallel block execution by distributing tasks to nodes that belong to the Grid. The set of nodes is composed by physical machines and virtualized ones. This feature enables great flexibility and increase available computational power. Furthermore, the presence of virtual nodes allows a full and efficient Grid usage, indeed the presented architecture can be used by different users that run different applications

Enhancing Job Scheduling of an Atmospheric Intensive Data Application

Nowadays, e-Science applications involve great deal of data to have more accurate analysis. One of its application domains is the Radio Occultation which manages satellite data. Grid Processing Management is a physical infrastructure geographically distributed based on Grid Computing, that is implemented for the overall processing Radio Occultation analysis. After a brief description of algorithms adopted to characterize atmospheric profiles, the paper presents an improvement of job scheduling in order to decrease processing time and optimize resource utilization. Extension of grid computing capacity is implemented by virtual machines in existing physical Grid in order to satisfy temporary job requests. Also scheduling plays an important role in the infrastructure that is handled by a couple of schedulers which are developed to manage data automaticall

Evaluation of different Bacillus thuringiensis sv kurstaki formulations against Lymantria dispar and Malacosoma neustria larvae infesting Quercus suber trees

Lepidopteran defoliators such as Lymantria dispar and Malacosoma neustria represent a major concern for cork oak forest, especially during population outbreaks. To contain their infestations over large areas, the use of entomopathogenic microorganisms such as Bacillus thuringiensis serovar kurstaki (Btk) is one of the available option. However, the features of the microbial control agent formulations represent a key factor for the success of application programs. The results of two years efficacy trials with different formulations of Btk, conducted in 2012 and 2013 in a cork oak forest in North-Western Sardinia, are reported. In the first year, trials were carried out on a M. neustria population, while in the second year a mixed population of L. dispar and M. neustria was involved. Trials included two formulations of Btk strain EG 2348 (Rapax® and Rapax Experimental) in comparison with two other commercial formulations (Foray 48B® and Delfin®). Both formulations of Btk strain EG 2348 proved to be effective in controlling the two pest species, showing a forest protection potential comparable to that of the reference products, Foray 48B® and Delfin®, containing spores and insecticidal Cry proteins of strains HD-1 and SA-11, respectively. Also the defoliation levels were significantly higher in untreated control trees than in treated ones

Potential impact of Entomophaga maimaiga Humber, Shimazu, and Soper (Entomophthorales Entomophthoraceae) on the lepidopteran fauna inhabiting cork forests in Sardinia (Italy).

Periodic outbreaks of forest defoliators like the gypsy moth cause severe impact to the forest ecosystem, which is normally counterbalanced by the action of their natural enemies, including predators, parasitoids, and entomopathogens. Among the latter, the host-specific fungus Entomophaga maimaiga can be very effective under favourable conditions. Whilst its close evolutionary relationship with gypsy moth, this entomopathogen has never been detected in certain forest areas where L. dispar is a common pest. The results of three years laboratory assays with two different strains of E. maimaiga from Bulgaria and Croatia against Lepidopteran species inhabiting cork oak forests in Sardinia are reported. Significant toxicity and virulence against gypsy moth larvae exposed to soil contaminated with resting spores of the fungus was detected for both strains, even if the strain from Bulgaria was significantly more effective. Significant lethal effects were observed also on M. neustria larvae, but a successful development and reproduction of the fungus within insect cadavers was detected only in the gypsy moth. No significant effects were observed on other Lepidopteran species.  Given a proper choice of candidate strains, the introduction of E. maimaiga in Sardinia, to manage the disruptive action of the gypsy moth would be desirable

SISTEMA E METODO PER ESEGUIRE OPERAZIONI SU UN OGGETTO TRAMITE DRONI

A system for executing an operation on an object (O) by means of a fleet of drones (20) equipped with tools for executing said operation. The system comprises: - processing means (10) adapted to receive as input information for calculating the trajectories required for bringing the fleet of drones (20) into the desired position for the execution of said operation, wherein said processing means (10) are adapted to transmit flight trajectories and instructions for executing the operation on the object (O) to said fleet of drones (20), - a local positioning system (L) comprising a plurality of anchor nodes in Ultra- Wide- Band technology (UWB-A1,UWB-A2,UWB-A3,UWB-Ax,UWB-AN) arranged around said object (O) along the sides of the surfaces of the ideal polyhedron that circumscribes the object (O). Each drone (20) of said fleet is equipped with: - a UWB transceiver (26) in communication with said anchor nodes (UWB-A1,UWB- A2,UWB-A3,UWB-Ax,UWB-AN), wherein each drone (20) is at all times in communication with at least four anchor nodes (UWB-A1,UWB-A2,UWB-A3,UWB- Ax,UWB-AN), and - a plurality of ultrasound sensors (24) for measuring the distance of each drone (20) from the other drones and from obstacles, wherein said fleet of drones (20), by following the way points (WP) of said trajectories sent by said processing means (10), executes said operation on said object (O) by means of said tools

Toll-like receptor 2 promotes breast cancer progression and resistance to chemotherapy

Cancer stem cells (CSCs) are the main drivers of disease progression and chemotherapy resistance in breast cancer. Tumor progression and chemoresistance might then be prevented by CSC-targeted therapies. We previously demonstrated that Toll-like Receptor (TLR)2 is overexpressed in CSCs and fuels their self-renewal. Here, we show that high TLR2 expression is linked to poor prognosis in breast cancer patients, therefore representing a candidate target for breast cancer treatment. By using a novel mammary cancer-prone TLR2(KO) mouse model, we demonstrate that TLR2 is required for CSC pool maintenance and for regulatory T cell induction. Accordingly, cancer-prone TLR2(KO) mice display delayed tumor onset and increased survival. Transplantation of TLR2(WT) and TLR2(KO) cancer cells in either TLR2(WT) or TLR2(KO) hosts shows that tumor initiation is mostly sustained by TLR2 expression in cancer cells. TLR2 host deficiency partially impairs cancer cell growth, implying a pro-tumorigenic effect of TLR2 expression in immune cells. Finally, we demonstrate that doxorubicin-induced release of HMGB1 activates TLR2 signaling in cancer cells, leading to a chemotherapy-resistant phenotype. Unprecedented use of TLR2 inhibitors in vivo reduces tumor growth and potentiates doxorubicin efficacy with no negative impact on the host immune system, opening new perspectives for the treatment of breast cancer patients