Utility Scale Ground Mounted Photovoltaic Plants with Gable Structure and Inverter Oversizing for Land-Use Optimization

The paper proposes an effective layout for ground-mounted photovoltaic systems with a gable structure and inverter oversizing, which allows an optimized use of the land and, at the same time, guarantees a valuable return on investment. A case study is presented to show the technical, economic, and environmental advantages compared with conventional “fixed-tilt” and “sun-tracking” ground-mounted photovoltaic installations. The main advantage of this solution is that it maximizes the energy produced per unit of land area used; but, also considering the economic metrics, the net present value of the proposed PV arrangement solution results in a greater annual volume of energy produced and therefore of net revenues and cash flows, and greater than the compared conventional solution with modules exposed in an optimal fixed position or which make use of sun-tracking systems

The enzymatic oxidation of cysteamine to hypotaurine. Purification and properties of the enzyme.

The enzyme oxidizing cysteamine to hypotaurine has been extracted from horse kidney and purified. The final product behaves as a single protein when analyzed in the ultracentrifuge, by starch gel electrophoresis, and by filtration on dextran gels. The sedimentation coefficient of the pure product is s20, w = 5.9. The molecular weight determined by the Yphantis procedure (22) is 83,000. Nonheme iron is contained in the amount of 1 atom per molecule of enzyme. Spectrophoto-metric analyses indicate absence of nonprotein chromophores in the visible and in the near ultraviolet range. The complete amino acid composition has been determined by ion exchange chromatography. The effect of sulfide, methylene blue, and hydroxylamine, which act as cofactor-like compounds, has been studied. Of the substrates assayed (cysteamine, cysteine, cysteine ethyl and methyl esters, and reduced glutathione), only cysteamine is oxidized to the sulfinic derivative in the presence of the cofactor-like compounds named

Perfusion index variations in clinically and hemodynamically stable preterm newborns in the first week of life

<p>Abstract</p> <p>Background</p> <p>The perfusion index, derived from the pulse oximeter signal, seems to be an accurate predictor for high illness severity in newborns. The aim of this study was to determine the perfusion index values of clinically and hemodynamically stable preterm newborns in the first week of life.</p> <p>Methods</p> <p>Perfusion index recordings were performed on the first, third and seventh day of life on 30 preterm newborns. Their state of health was assessed according to clinical and behaviour evaluation and to the Score for Neonatal Acute Physiology.</p> <p>Results</p> <p>The median(interquartile range) perfusion index values were 0.9(0.6) on the first, 1.2(1.0) on the third, and 1.3(0.9) on the seventh day, with a significant increase between the first and the third day.</p> <p>Conclusions</p> <p>Perfusion index proved to be an easily applicable, non-invasive method for monitoring early postnatal changes in peripheral perfusion. Its trend during the first week of life suggests that its clinical application should take age into account. Further studies are needed to obtain reference perfusion index values from a larger sample of preterm newborns, to identify specific gestational age-related cut-off values for illness and to test the role of perfusion index in monitoring critically ill neonates.</p

Finding unexplained human behaviors in Social Networks

Detection of human behavior in On-line Social Networks (OSNs) has become a very important challenge for a wide range of appli- cations, such as security, marketing, parent controls and so on, opening a wide range of novel research areas, which have not been fully addressed yet. In this paper, we present a two-stage method for finding unexplained (and potentially anomalous) behaviors in social networks. First, we use Markov chains to automatically learn from the social network graph a number of models of human behaviors (normal behaviors); the second stage applies an activity detection framework based on the concept of possible words to detect all unexplained activities with respect to the well-known behaviors. Some preliminary experiments using Facebook data show the approach efficiency and effectiveness. Copyright © (2014) by Universita Reggio Calabria & Centro di Competenza (ICT-SUD) All rights reserved

SDS-resistant Active and Thermostable Dimers Are Obtained from the Dissociation of Homotetrameric β-Glycosidase from Hyperthermophilic Sulfolobus solfataricus in SDS

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Impact of mangrove forests degradation on biodiversity and ecosystem functioning

Abstract Mangroves are amongst the most productive marine ecosystems on Earth, providing a unique habitat opportunity for many species and key goods and services for human beings. Mangrove habitats are regressing at an alarming rate, due to direct anthropogenic impacts and global change. Here, in order to assess the effects of mangrove habitat degradation on benthic biodiversity and ecosystem functioning, we investigated meiofaunal biodiversity (as proxy of benthic biodiversity), benthic biomass and prokaryotic heterotrophic production (as proxies of ecosystem functioning) and trophic state in a disturbed and an undisturbed mangrove forests. We report here that disturbed mangrove area showed a loss of 20% of benthic biodiversity, with the local extinction of four Phyla (Cladocera, Kynorincha, Priapulida, Tanaidacea), a loss of 80% of microbial-mediated decomposition rates, of the benthic biomass and of the trophic resources. The results of this study strengthen the need to preserve mangrove forests and to restore those degraded to guarantee the provision of goods and services needed to support the biodiversity and functioning of wide portions of tropical ecosystems

Impact-based flash-flood forecasting system: Sensitivity to high resolution numerical weather prediction systems and soil moisture

In recent years, continuous improvements have been made in weather forecasting and flood prediction with great benefit from Early Warning Systems (EWSs). Despite the continuous quest for innovation from the scientific and user communities, EWSs remain based mostly on hazard forecast, and the information on possible consequences and potential impacts is generally missing. In this work, a methodology for quantitative real-time impact assessment for flash floods is presented. The methodology uses a multi-model ensemble approach and considers soil moisture uncertainty. Moreover, the flood forecasting chain, which normally provides only the discharge probability of exceeding a given threshold, is extended to include a fully 2D hydraulic model and a damage estimation model to quantitatively assess impacts in terms of economic losses and the people involved. The procedure was tested on recent flood events occurring in Genoa in northwestern Italy. This paper discusses the potential challenges and opportunities offered by this approach in the decision-making workflow in an operational context