Multivariate Statistical Analysis for Water Demand Modeling

The actual level of water demand is the driving force behind the hydraulic dynamics in water distribution systems. Consequently, it is crucial to estimate it as accurately as possible in order to result in reliable simulation models. In this paper, a copula-based multivariate analysis has been proposed and used for demand prediction for given return period. The analysis is applied to water consumption data collected in the water distribution network of Palermo (Italy). The approach showed to produce consisted demand patterns and to be a powerful tool to be coupled with water distribution network models for design or analysis problems. (C) 2014 Published by Elsevier Ltd

Correlation between parodontal indexes and orthodontic retainers: prospective study in a group of 16 patients

Purpose. Fixed retainers are used to stabilize dental elements after orthodontic treatment. Being it a permanent treatment, it is necessary to instruct patients about a constant and continuous monitoring of their periodontal conditions and a correct oral hygiene. The aim of this study was to highlight the possible adverse effects of bonded retainers on parameters correlated to the health conditions of periodontal tissues. Materials and methods. We selected 16 patients, under treatment in the Orthodontics Department of University of Bari Dental School, who had undergone a lingual retainer insertion at the end of the orthodontic treatment. The patients were then divided into two groups (Control Group and Study Group) and monitored for 3 and 36 months, respectively. The following indexes were taken into consideration: gingival index (GI), plaque index (PI) and the presence of calculus (Calculus Index, CI), the probing depth and the presence of gingival recession on the six inferior frontal dental elements. Results. After the observation was carried out, any of the patients showed periodontal sockets and gingival recession. In the Study Group, only 1 patient had a PI score=3, the 7 left had scores between 0.66 and 2.83. In the Control Group, one patient had score=0, the other ones showed values between 0.5 and 1.66. The mean GI in the Study Group peaked at a score of 2.83, the minimum was 0.66; whereas in the Control Group the maximum value was 2 and the minimum 0.66. The CI in the Group Study was between 1 and 2. In the Control Group it was absent in only 1 patient, whereas in the remaining 7, it had a value between 0.3 and 1. The clinical data were studied by means of the Wilcoxon test. We found a statistically significant difference for what concerns the Plaque Indexes (PI) (P>0.05) and Calculus Indexes (CI) (P>0.1) in both groups, with higher scores in the Study Group, having retainers for 36 months. Any statistically significant difference was calculated for the GI. Conclusions. We can therefore conclude that patients with lingual retainers need periodontal hygiene and treatment as to prevent, in the course of time, periodontal damages non-detectable in short-term

Definition of Water Meter Substitution Plans based on a Composite Indicator

This paper presents a water meter substitution plan based on a composite "Replacement indicator" which was defined and compared with common substitution strategies based on meter age and on run-to-fail approaches. The methodology was applied to one of the 17 sub-networks in which the Palermo city water distribution network (Italy) is divided. The analysis was carried out considering a substitution budget limitation and the results showed that the use of "Replacement indicator" outperform the classical substitution strategies based on meter age because it takes into account some other variables that may affect meter precision and wearing. (C) 2013 The Authors. Published by Elsevier Ltd

WIN55,212-2-induced expression of Mir-29b1 favours the suppression of osteosarcoma cell migration in a SPARC-independent manner

WIN55,212-2 (WIN) is a synthetic agonist of cannabinoid receptors that displays promising antitumour properties. The aim of this study is to demonstrate that WIN is able to block the migratory ability of osteosarcoma cells and characterize the mechanisms involved. Using wound healing assay and zymography, we showed that WIN affects cell migration and reduces the activity of the metalloproteases MMP2 and MMP9. This effect seemed to be independent of secreted protein acidic and rich in cysteine (SPARC), a matricellular protein involved in tissue remodeling and extracellular matrix deposition. SPARC release was indeed prevented by WIN, and SPARC silencing by RNA interference did not influence the effect of the cannabinoid on cell migration. WIN also increased the release of extracellular vesicles and dramatically upregulated miR-29b1, a key miRNA that modulates cell proliferation and migration. Interestingly, reduced cell migration was observed in stably miR-29b1-transfected cells, similarly to WIN-treated cells. Finally, we show the absence of SPARC in the extracellular vesicles released by osteosarcoma cells and no changes in SPARC level in miR-29b1 overexpressing cells. Overall, these findings suggest that WIN markedly affects cell migration, dependently on miR-29b1 and independently of SPARC, and can thus be considered as a potential innovative therapeutic agent in the treatment of osteosarcoma

Energy Recovery in Water Distribution Networks. Implementation of Pumps as Turbine in a Dynamic Numerical Model

In complex networks characterized by the presence of private tanks, water managers usually apply intermittent distribution, thus reducing the water volumes supplied to the users, or use Pressure Reduction Valves (PRV) for controlling pressure in the network. The application of Pump As Turbines (PATs) appears as an alternative and sustainable solution to either control network pressure as well as to produce energy. In the present paper, the hydrodynamic model, already presented by De Marchis et al. (2011) was further developed introducing the dynamic analysis of PATs. The model was applied to a district of Palermo network (Italy) characterized by intermittent distribution and by inequities among the user in term of water supply. (C) 2013 The Authors. Published by Elsevier Ltd

High prevalence of hepatitis C virus infection in patients with B-cell lymphoproliferative disorders in Italy.

Starting from the observation that a number of consecutive patients with non-Hodgkin's lymphoma (NHL) resulted positive for hepatitis C virus (HCV) antibodies on routine testing, we set up a survey for HCV contact prevalence in all patients with lymphoproliferative disorders (LPD) followed in our institution. We searched for HCV antibodies by a thirdgeneration ELISA technique, followed by a confirmation test (RIBA III); serum viral RNA and HCV genotype were investigated by a RT-PCR technique. We screened a total of 315 patients suffering from B-NHL (91), multiple myeloma (56), MGUS (48), chronic lymphocytic leukemia (57), Waldentrom's macroglobulinemia (13), Hodgkin's disease (HD)(43), and T-NHL (9). While only I of 52 patients with a non-B-LPD (HD or T-NHL) had signs of HCV contact (i.e., 1.9%, which is in the range of the normal population in the South of Italy), 59 of 263 patients with a B-LPD (22.4%) had HCV antibodies or RNA, or both, with no major differences among the various types of disorders, except for WM, in which the rate was higher (61.5%). The same prevalence was found for patients tested at diagnosis or during the follow-up, and in transfused or never-transfused patients. Only a few patients were aware of having a liver disease; one-half of HCV-positive patients never had transaminase increase. A review of data from Central and Northern Italy is included, showing similar findings; a report from Japan has confirmed such an association, while limited surveys in England have not revealed any correlation. These findings may have important biological and clinical implications

A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks

Background: Several problems in network biology and medicine can be cast into a framework where entities are represented through partially labeled networks, and the aim is inferring the labels (usually binary) of the unlabeled part. Connections represent functional or genetic similarity between entities, while the labellings often are highly unbalanced, that is one class is largely under-represented: for instance in the automated protein function prediction (AFP) for most Gene Ontology terms only few proteins are annotated, or in the disease-gene prioritization problem only few genes are actually known to be involved in the etiology of a given disease. Imbalance-aware approaches to accurately predict node labels in biological networks are thereby required. Furthermore, such methods must be scalable, since input data can be large-sized as, for instance, in the context of multi-species protein networks. Results: We propose a novel semi-supervised parallel enhancement of COSNet, an imbalance-aware algorithm build on Hopfield neural model recently suggested to solve the AFP problem. By adopting an efficient representation of the graph and assuming a sparse network topology, we empirically show that it can be efficiently applied to networks with millions of nodes. The key strategy to speed up the computations is to partition nodes into independent sets so as to process each set in parallel by exploiting the power of GPU accelerators. This parallel technique ensures the convergence to asymptotically stable attractors, while preserving the asynchronous dynamics of the original model. Detailed experiments on real data and artificial big instances of the problem highlight scalability and efficiency of the proposed method. Conclusions: By parallelizing COSNet we achieved on average a speed-up of 180x in solving the AFP problem in the S. cerevisiae, Mus musculus and Homo sapiens organisms, while lowering memory requirements. In addition, to show the potential applicability of the method to huge biomolecular networks, we predicted node labels in artificially generated sparse networks involving hundreds of thousands to millions of nodes