StoRM: A Manager for Storage Resource in Grid

Nowadays, data intensive applications demand high-performance and large-storage systems capable of serving up to various Petabytes of storage space. Therefore, common solutions adopted in data centres include Storage Area Networks (SAN) and cluster parallel file systems, such as GPFS from IBM and Lustre from Sun Microsystems. In order to make these storage system solutions available in modern Data Grid architectures, standard interfaces are needed. The Grid Storage Resource Manager (SRM) interface is one of these standard interfaces. Grid storage services implementing the SRM standard provide common capabilities and advanced functionality such as dynamic space allocation and file management on shared storage systems. In this paper, we describe StoRM (STOrage Resource Manager). StoRM is a flexible and high-performing implementation of the standard SRM interface version 2.2. The software architecture of StoRM allows for an easy integration to different underlying storage systems via a plug-in mechanism. In particular, StoRM takes advantage from storage systems based on cluster file systems. Currently, StoRM is installed and used in production in various data centres, including the WLCG Italian Tier-1. In addition, Economics and Financial communities, as represented by the EGRID Project, adopt StoRM in production as well

An efficient strategy for the collection and storage of large volumes of data for computation

In recent years, there has been an increasing amount of data being produced and stored, which is known as Big Data. The social networks, internet of things, scientific experiments and commercial services play a significant role in generating a vast amount of data. Three main factors are important in Big Data; Volume, Velocity and Variety. One needs to consider all three factors when designing a platform to support Big Data. The Large Hadron Collider (LHC) particle accelerator at CERN consists of a number of data-intensive experiments, which are estimated to produce a volume of about 30 PB of data, annually. The velocity of these data that are propagated will be extremely fast. Traditional methods of collecting, storing and analysing data have become insufficient in managing the rapidly growing volume of data. Therefore, it is essential to have an efficient strategy to capture these data as they are produced. In this paper, a number of models are explored to understand what should be the best approach for collecting and storing Big Data for analytics. An evaluation of the performance of full execution cycles of these approaches on the monitoring of the Worldwide LHC Computing Grid (WLCG) infrastructure for collecting, storing and analysing data is presented. Moreover, the models discussed are applied to a community driven software solution, Apache Flume, to show how they can be integrated, seamlessly

Surgical and postsurgical wound care in hidradenitis suppurativa

Hidradenitis suppurativa (HS) is a chronic inflammatory disorder. Several medical treatments, with varying degree of efficacy, have been developed. However, in most cases of advanced (HS), the definitive treatment option is often represented by surgical excisions. Surgical techniques, reconstructive approach, and local wound care should be accurately designed in order to obtain the best result. In this letter, we analyzed the possible surgical treatments and local wound care. A literature review was performed on the various surgical treatments, reconstructive techniques, and local wound care. Surgical treatment is a common therapeutic modality for HS. Different surgical reconstructive techniques and postsurgical wound care approaches are described for the management of HS patients. There were few high-quality evidence-based studies evaluating the surgical management of HS. Many disparate HS severity scores were used in these studies making comparison between them difficult. Nonetheless, research into different surgical approaches and wound care management has increased substantially in the past decade and has given patients more surgical therapeutic strategies. The description of the best combinations and timing of surgery, wound care and medical therapies, will be a matter of future research for the definition of the optimal management of HS patient

Mesenchymal stromal cells promote the proliferation of basal stem cells and efficient epithelization in organotypic models of wound healing

Adipose derived mesenchymal stromal cells (ADSCs) represent a fascinating tool in the scenario of wound healing and regenerative medicine. Recent data already demonstrated that ADSCs could exert a stimulatory action on epithelial cells through secretion of soluble factors. The aim of the present study was to assess how ADSCs guide wound re-epithelization in vitro in the presence of keratinocytes. We used an organotypic model of wound healing and we seeded keratinocytes on a ADSC-induced dermal matrix. Conventional hematoxylin–eosin stain and immunohistochemistry staining for Ki67, p63 and pan-keratins were performed at different timepoints. Histological sections of organotypic cultures showed complete coverage of the ADSC-induced matrix by keratinocytes. Proliferation of basal stem cells was found to be the main mechanism responsible for epithelization of the dermis. In conclusion, ADSC do not only stimulate dermal regeneration through collagen deposition but also promote epithelization

Mesenchymal stem cells for the treatment of psoriasis: a comprehensive review

Mesenchymal stem cells (MSCs) have recently been shown to have not only regenerative capabilities but also immunomodulating properties. For this reason, they are currently under investigation in clinical trials for the treatment of several autoimmune systemic disorders. Psoriasis is a systemic immune-mediated disease for which MSCs could have therapeutic potential. We analysed the existing literature with regard to MSC-based strategies for the treatment of psoriasis, using the MEDLINE, Embase, Scopus and Cochrane Library electronic databases from inception to the date of study. A number of studies confirm the involvement of MSCs in psoriasis pathogenesis and therefore designate MSCs as an important potential therapeutic tool in this setting. Preclinical data are mostly based on imiquimod-induced murine models of psoriasis, and confirm the anti-inflammatory and immunomodulatory action of MSCs in the setting of psoriasis. Six patients affected by psoriasis were described in four clinical studies. Despite significant differences in terms of therapeutic protocols and clinical outcomes, the MSC-based regimens were efficacious in 100% of the cases. Despite more data still being needed, MSCs could be a promising therapy for psoriasis

A modular multipurpose, parameter centered electronic health record architecture

Health Information Technology is playing a key role in healthcare. Specifically, the use of electronic health records has been found to bring about most significant improvements in healthcare quality, mainly as relates to patient management, healthcare delivery and research support. Health record systems adoption has been promoted in many countries to support efficient, high quality integrated healthcare. The objective of this work is the implementation of an Electronic Health Record system based on a relational database. The system architecture is modular and based on the concentration of specific pathology related parameters in one module, therefore the system can be easily applied to different pathologies. Several examples of its application are described. It is intended to extend the system integrating genomic data

Centroid moment tensor catalog with 3D lithospheric wavespeed model. The 2016–2017 Central Apennines sequence

Moment tensor inversions of broadband velocity data are usually managed by adopting Green's functions for 1D layered seismic wave speed models. This assumption can impact on source parameter estimates in regions with complex 3D heterogeneous structures and discontinuities in rock properties. In this work, we present a new centroid moment tensor (CMT) catalog for the Amatrice-Visso-Norcia (AVN) seismic sequence based on a recently generated 3D wave speed model for the Italian lithosphere. Forward synthetic seismograms and Fréchet derivatives for CMT-3D inversions of 159 earthquakes with Mw ≥ 3.0 are simulated using a spectral-element method (SEM) code. By comparing the retrieved solutions with those from time domain moment tensor (TDMT) catalog, obtained with a 1D wave speed model calibrated for Central Apennines (Italy), we observe a remarkable degree of consistency in terms of source geometry, kinematics, and magnitude. Significant differences are found in centroid depths, which are more accurately estimated using the 3D model. Finally, we present a newly designed parameter, τ, to better quantify and compare a-posteriori the reliability of the obtained MT solutions. τ measures the goodness of fit between observed and synthetic seismograms accounting for differences in amplitude, arrival time, percentage of fitted seconds, and the usual L2-norm estimate. The CMT-3D solutions represent the first Italian CMT catalog based on a full-waveform 3D wave speed model. They provide reliable source parameters with potential implications for the structures activated during the sequence. The developed approach can be readily applied to more complex Italian regions where 1D models are underperforming and not representative of the area