Neural network approach to parton distributions fitting

We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.Comment: 4 pages, 5 eps figures. Talk given by Andrea Piccione at the "X International Workshop on Advanced Computing and Analysis Techniques in Physics Research", ACAT 2005, DESY-Zeuthen, Germany, 22-27 May 2005. Corrected fig.

Exploring life forms for linking Orthopteran assemblage and grassland plant community:

AbstractOrthopterans are well known to represent the majority of insect biomass in many grassland ecosystems. However, the verification of a relationship between the traditional descriptors of orthopteran assemblage structure and plant community patterns is not straightforward. We explore the usefulness of the concept of life forms to provide insights on such ecosystem level relationship. For this purpose, thirty sample sites in semi-natural calcareous grasslands were classified according to the relative proportion of dominant herbaceous plant life forms. Orthopteran species were grouped in four categories, based on the Bei-Bienko's life form categorization. The association among plant communities, orthopteran assemblages and environmental factors was tested by means of canonical correspondence analysis. Orthoptera groups were found to be associated with distinct plant communities, also indicating the effect of vegetation change on orthopteran assemblages. In particular, geobionta species were associated with all the most disturbed plant communities, while chortobionta and thamnobionta seemed to be dependent on better preserved grassland types. Therefore, the use of life forms could help informing on the relationships of orthopteran assemblages with grassland conservation state. Information on such community relationships at the local scale could also assist managers in the interpretation of habitat change maps in terms of biodiversity changes

Neural network determination of parton distributions: the nonsinglet case

We provide a determination of the isotriplet quark distribution from available deep--inelastic data using neural networks. We give a general introduction to the neural network approach to parton distributions, which provides a solution to the problem of constructing a faithful and unbiased probability distribution of parton densities based on available experimental information. We discuss in detail the techniques which are necessary in order to construct a Monte Carlo representation of the data, to construct and evolve neural parton distributions, and to train them in such a way that the correct statistical features of the data are reproduced. We present the results of the application of this method to the determination of the nonsinglet quark distribution up to next--to--next--to--leading order, and compare them with those obtained using other approaches.Comment: 46 pages, 18 figures, LaTeX with JHEP3 clas

VR WebGIS: an OpenSource approach to 3D real-time landscape management

OpenSource philosophy has reached to unexpected goals. The diffusion of OpenSource tools is increased quite a lot, but also the quality of the tools is improving. Their usability is slowing going even towards communities not exactly skilled in advanced programming. Open movement is penetrated in many sectors, often subverting, thank to its social impact, the traditional rules of companies and research institutions, pulling down sometimes hierarchies and pushing on innovative ideas because of their validity and values. [...]Peer Reviewe

VR WebGIS: an OpenSource approach to 3D real-time landscape management

OpenSource philosophy has reached to unexpected goals. The diffusion of OpenSource tools is increased quite a lot, but also the quality of the tools is improving. Their usability is slowing going even towards communities not exactly skilled in advanced programming. Open movement is penetrated in many sectors, often subverting, thank to its social impact, the traditional rules of companies and research institutions, pulling down sometimes hierarchies and pushing on innovative ideas because of their validity and values. [...]Peer Reviewe

Geomorphological Evolution of Volcanic Cliffs in Coastal Areas: The Case of Maronti Bay (Ischia Island)

The morphoevolution of coastal areas is due to the interactions of multiple continental and marine processes that define a highly dynamic environment. These processes can occur as rapid catastrophic events (e.g., landslides, storms, and coastal land use) or as slower continuous processes (i.e., wave, tidal, and current actions), creating a multi-hazard scenario. Maronti Bay (Ischia Island, Southern Italy) can be classified as a pocket beach that represents an important tourist and environmental area for the island, although it has been historically affected by slope instability, sea cliff recession, and coastal erosion. In this study, the historical morphoevolution of the shoreline was analysed by means of a dataset of aerial photographs and cartographic information available in the literature over a 25-year period. Furthermore, the role of cliff recession and its impact on the beach was also explored, as in recent years, the stability condition of the area was worsened by the occurrence of a remarkable landslide in 2019. The latter was reactivated following a cloudburst on the 26th of November 2022 that affected the whole Island and was analysed with the Dem of Difference technique. It provided an estimate of the mobilised volumes and showed how the erosion and deposition areas were distributed and modified by wave action. The insights from this research can be valuable in developing mitigation strategies and protective measures to safeguard the surrounding environment and ensure the safety of residents and tourists in this multi-hazard environment

Parton distributions: determining probabilities in a space of functions

We discuss the statistical properties of parton distributions within the framework of the NNPDF methodology. We present various tests of statistical consistency, in particular that the distribution of results does not depend on the underlying parametrization and that it behaves according to Bayes' theorem upon the addition of new data. We then study the dependence of results on consistent or inconsistent datasets and present tools to assess the consistency of new data. Finally we estimate the relative size of the PDF uncertainty due to data uncertainties, and that due to the need to infer a functional form from a finite set of data.Comment: 11 pages, 8 figures, presented by Stefano Forte at PHYSTAT 2011 (to be published in the proceedings

DETC2003/PTG-48000 APPLICATION OF A MULTIAXIAL FATIGUE CRITERION FOR THE EVALUATION OF LIFE OF GEARS OF COMPLEX GEOMETRY

ABSTRACT Gears can show significant biaxial stress state at tooth root fillet, due to the way they are loaded and their particular geometry. This biaxial stress state can show a significant variability in principal axes during meshing. Moreover loads may have non predictable components that can be evaluated with the aid of recorded data from complex spectra. In these conditions, commonly adopted approaches for fatigue evaluation may be unsuitable for a reliable fatigue life prediction. This work is aimed at discussing a computer implementation of a fatigue life prediction method suitable for multiaxial stress states and constant amplitude or random loading. For random loading a counting procedure to extract cycles from complex load histories is discussed. This method, proposed by Vidal et al., is based on the r.m.s. value of a damage indicator over all the planes through the point where the fatigue life calculation is made. Miner's rule is used for the evaluation of the overall damage. The whole fatigue life of the component is evaluated in terms of the numbers of repetitions of the loading block. FEM data are used to evaluate stresses under load. The implementation was validated using test data found in the technical literature. Examples of applications to gears are finally discussed

Fitting Parton Distribution Data with Multiplicative Normalization Uncertainties

We consider the generic problem of performing a global fit to many independent data sets each with a different overall multiplicative normalization uncertainty. We show that the methods in common use to treat multiplicative uncertainties lead to systematic biases. We develop a method which is unbiased, based on a self--consistent iterative procedure. We demonstrate the use of this method by applying it to the determination of parton distribution functions with the NNPDF methodology, which uses a Monte Carlo method for uncertainty estimation.Comment: 33 pages, 5 figures: published versio