WATER POLICY AND THE SUSTAINABILITY OF IRRIGATED SYSTEMS IN ITALY

The management of water resources is today one of the main issues in most countries. In Italy, as in many other European countries, irrigation is the main sector using water and hence it is at the centre of the water policy agenda. Water management for irrigation requires suitable policy tools able to meet social objectives and private behaviour. The legal framework in the European Union is today faced with the new Water Framework Directive (60/2000), that sets up new criteria for water management, regulation and pricing. Among other things, the Water Framework Directive introduces the principle of full cost recovery and the polluter pays principle for water users. For many areas of Italy, this may be a significant shift compared to present payment criteria, based on traditional rights, area prices, and only a partial cost recovery from final users. The objective of this paper is to analyse the problem of water regulation for irrigated agriculture, through a simulation model based on the integration of a mathematical decision making model and a principal agent. The methodology allows to quantify water demand and optimal regulation from the point of view of the policy maker. The results show major impacts of water availability and prices on farm income. The adoption of a mix of pricing instruments related at the same time to charges associated to crop mix, water consumption and pollution can significantly improve water policy efficacy.Resource /Energy Economics and Policy,

Predator and detritivore niche width helps to explain biocomplexity of experimental detritus-based food webs in four aquatic and terrestrial ecosystems

In the study of food webs, the existence and explanation of recurring patterns, such as the scale invariance of linkage density, predator–prey ratios and mean chain length, constitute long-standing issues. Our study focused on litter-associated food webs and explored the influence of detritivore and predator niche width (as d13C range) on web topological structure. To compare patterns within and between aquatic and terrestrial ecosystems and take account of intra-habitat variability, we constructed 42 macroinvertebrate patch-scale webs in four different habitats (lake, lagoon, beech forest and cornfield), using an experimental approach with litterbags. The results suggest that although web differences exist between ecosystems, patterns are more similar within than between aquatic and terrestrial web types. In accordance with optimal foraging theory, we found that the niche width of predators and prey increased with the number of predators and prey taxa as a proportion of total taxa in the community. The tendency was more marked in terrestrial ecosystems and can be explained by a lower per capita food level than in aquatic ecosystems, particularly evident for predators. In accordance with these results, the number of links increased with the number of species but with a significantly sharper regression slope for terrestrial ecosystems. As a consequence, linkage density, which was found to be directly correlated to niche width, increased with the total number of species in terrestrial webs, whereas it did not change significantly in aquatic ones, where connectance scaled negatively with the total number of species. In both types of ecosystem, web robustness to rare species removal increased with connectance and the niche width of predators. In conclusion, although limited to litter-associated macroinvertebrate assemblages, this study highlights structural differences and similarities between aquatic and terrestrial detrital webs, providing field evidence of the central role of niche width in determining the structure of detritus-based food webs and posing foraging optimisation constraints as a general mechanistic explanation of food web complexity differences within and between ecosystem types

Low molecular weight Adiponectin increases the mortality risk in very old patients

Despite its beneficial role on insulin resistance and atherosclerosis, adiponectin has been frequently reported as an independent positive predictor of cardiovascular mortality. Very few information is available regarding adiponectin isoforms and mortality, in particular in advanced aging. Baseline serum levels of Total Adiponectin and its circulating isoforms (HMW-, MMW-, LMW-Adiponectin) were measured in 97 old patients (mean age: 79 years). Patients were followed up for all-cause mortality (study end-point) for an average of 76.4 ±37.3 months. A positive association was observed for LMW-Ad and all-cause mortality (HR: 1.13, 95% CI: 1.05-1,22, p: 0.002). After multivariate adjustment for age, sex and a previous history of myocardial infarction, higher levels of LMW-Ad were significantly associated with all-cause mortality (HR: 1.11, 95% CI: 1.02-1.21; p: 0.017). Interestingly neither total adiponectin neither the other two circulating isoforms (MMW- and HMW-Ad) showed any significant association with the study end-point. Our data suggest that the association between high serum adiponectin levels and increased mortality rate in elderly is contingent to an unbalanced circulating levels of adiponectin isoforms. The present results support the hypothesis that high levels of Low Molecular Weight adiponectin are a biomarker for mortality risk in very old patients

Acquired ptosis associated with oculomotor and contralateral facial nerve synkinesis: the first reported case

Evidence of oculomotor nerve (ON) synkinesis is a common occurrence following both acquired and congenital III nerve palsy. It is generally accepted that aberrant regeneration is the likely aetiology of synkinesis in acquired III nerve palsy, following intracranial aneurysm, trauma, compressive neoplasms, cavernous sinus thrombosis and basilar meningitis

Increased levels of DNA methyltransferases are associated with the tumorigenic capacity of prostate cancer cells

DNA methylation might be the earliest somatic genome changes in prostate cancer that also play an important role in the process of tumor invasion, growth and metastasis. In recent years, several inhibitors of DNA methyltransferases (DNMTis) have been developed and evaluated in pre-clinical models and in clinical trials. While these compounds are effective in the treatment of hematological conditions, clinical trials in solid tumors and in prostate cancer have shown limited or no efficacy. This may be attributed to inappropriate dose regimens leading to toxicity-related adverse events. As with other anti-target compounds, one of the obstacles encountered with DNMTis in prostate cancer could be the inability to select patients for the clinical studies as well as the inability to monitor the efficacy of the drug if not the conclusion of the study. Primary cultures derived from human prostatic tissues harvested from patients with benign prostatic hyperplasia (BPH) and prostate cancer (PCa) as well as neoplastic and non-neoplastic prostate cell lines were tested for DNMT expression/activity and to monitor azacitidine molecular efficacy. We observed that in primary cultures the levels of DNMT activity as well as the protein levels of DNMT1, DNMT3a and DNMT3b were higher in cultures derived from PCa compared to BPH tissue samples and significantly higher in cultures derived from PCa with Gleason scores ≥7 compared to those observed in cultures derived from Gleason scores <7. In addition, DNMT activity as well as DNMT1, DNMT3a and DNMT3b levels were higher in PCa cell lines compared to their non-neoplastic counterparts. Although DNMT activity was higher in high tumorigenic/aggressive PCa cell lines compared to low tumorigenic/aggressive cell lines, only the levels of DNMT3a and DNMT3b were significantly higher in the first group of cells, suggesting that DNMT1 activity is related to the transition to non-neoplastic versus neoplastic phenotype whereas the de novo methylation enzymes were mainly related to progression. Nevertheless, the comparison in the more aggressive PC3 cell derivatives (PC3-LN4 cells) also possessed higher levels of DNMT1 compared to PC3 and PC3M from which these cells were derived. Collectively, our results confirm previous data on the increased methylation in more aggressive tumors supporting the use of DNMTis in advanced prostate cancer. In addition, since glutathione S-transferase-π (GSTP1) was re-expressed or its protein levels were increased after treatment with non-toxic azacitidine doses and since GSTP1 can easily be measured in patient sera, the monitoring of this protein may aide in the evaluation of therapy in future clinical trials

Seismic Retrofit of a Multispan Prestressed Concrete Girder Bridge with Friction Pendulum Devices

The paper deals with the proposal and application of a procedure for the seismic retrofit of an existing multispan prestressed concrete girder bridge defined explicitly for the use of friction pendulum devices as an isolation system placed between piers top and deck. First, the outcomes of the seismic risk assessment of the existing bridge, performed using an incremental noniterative Nonlinear Static Procedure, based on the Capacity Spectrum Method as well as the Inelastic Demand Response Spectra, are described and discussed. Then, a specific multilevel design process, based on a proper application of the hierarchy of strength considerations and the Direct Displacement-Based Design approach, is adopted to dimension the FPD devices. Furthermore, to assess the impact of the FPD nonlinear behaviour on the bridge seismic response, a device model that reproduces the variation of the normal force and friction coefficient, the bidirectional coupling, and the large deformation effects during nonlinear dynamic analyses was used. Finally, the paper examines the effects of the FPD modelling parameters on the behaviour of the retrofitted bridge and assesses its seismic response with the results pointing out the efficiency of the adopted seismic retrofit solution

Gene co-expression analyses: an overview from microarray collections in Arabidopsis thaliana

4noBioinformatics web-based resources and databases are precious references for most biological laboratories worldwide. However, the quality and reliability of the information they provide depends on them being used in an appropriate way that takes into account their specific features. Huge collections of gene expression data are currently publicly available, ready to support the understanding of gene and genome functionalities. In this context, tools and resources for gene co-expression analyses have flourished to exploit the ‘guilty by association' principle, which assumes that genes with correlated expression profiles are functionally related. In the case of Arabidopsis thaliana, the reference species in plant biology, the resources available mainly consist of microarray results. After a general overview of such resources, we tested and compared the results they offer for gene co-expression analysis. We also discuss the effect on the results when using different data sets, as well as different data normalization approaches and parameter settings, which often consider different metrics for establishing co-expression. A dedicated example analysis of different gene pools, implemented by including/excluding mutant samples in a reference data set, showed significant variation of gene co-expression occurrence, magnitude and direction. We conclude that, as the heterogeneity of the resources and methods may produce different results for the same query genes, the exploration of more than one of the available resources is strongly recommended. The aim of this article is to show how best to integrate data sources and/or merge outputs to achieve robust analyses and reliable interpretations, thereby making use of diverse data resources an opportunity for added value.openembargoed_20170219Di Salle, Pasquale; Incerti, Guido; Colantuono, Chiara; Chiusano, Maria LuisaDi Salle, Pasquale; Incerti, Guido; Colantuono, Chiara; Chiusano, Maria Luis

A survey study on Industry 4.0 readiness level of Italian small and medium enterprises

Abstract The Industry 4.0 (I4.0) paradigm is considered one of the most trending topics in the academic and industrial context, that involves emerging technologies that can make the processes increasingly integrated and provide digital solutions for supporting companies towards the greater flexibility required by the market. To date, the scientific literature strongly addressed the development of enabling technologies and the assessment of their impacts in different industrial contexts. However, there is a lack of studies providing empirical evidence about how manufacturing companies are facing the digital transformation, in particular for smaller industrial realities. For this reason, this paper aims to study the knowledge, readiness, and dissemination level of the I4.0 paradigm and enabling technologies for Italian Micro, Small, and Medium Enterprises (MSMEs). A web-based survey was conducted, and 77 companies were interviewed. The survey results underline that MSMEs still have limited knowledge about I4.0 and are not well prepared for its implementation

Hysteresis Modeling in Iron-Dominated Magnets Based on a Multi-Layered Narx Neural Network Approach

A full-fledged neural network modeling, based on a Multi-layered Nonlinear Autoregressive Exogenous Neural Network (NARX) architecture, is proposed for quasi-static and dynamic hysteresis loops, one of the most challenging topics for computational magnetism. This modeling approach overcomes drawbacks in attaining better than percent-level accuracy of classical and recent approaches for accelerator magnets, that combine hybridization of standard hysteretic models and neural network architectures. By means of an incremental procedure, different Deep Neural Network Architectures are selected, fine-tuned and tested in order to predict magnetic hysteresis in the context of electromagnets. Tests and results show that the proposed NARX architecture best fits the measured magnetic field behavior of a reference quadrupole at CERN. In particular, the proposed modeling framework leads to a percent error below 0.02% for the magnetic field prediction, thus outperforming state of the art approaches and paving a very promising way for future real time applications