Search results for "Simulation."
showing 10 items of 4779 documents
Predicting mobile apps spread: An epidemiological random network modeling approach
2017
[EN] The mobile applications business is a really big market, growing constantly. In app marketing, a key issue is to predict future app installations. The influence of the peers seems to be very relevant when downloading apps. Therefore, the study of the evolution of mobile apps spread may be approached using a proper network model that considers the influence of peers. Influence of peers and other social contagions have been successfully described using models of epidemiological type. Hence, in this paper we propose an epidemiological random network model with realistic parameters to predict the evolution of downloads of apps. With this model, we are able to predict the behavior of an app…
Evaluation of the bending behaviour of laminated glass beams via electronic speckle pattern interferometry
2017
The paper is devoted to the experimental analysis of the kinematical and mechanical behaviour of laminated glass beam structures. In particular, the utilized laminated glass specimens are composed of two glass layers bonded by a polymer layer constituted by Ethylene-vinyl acetate whose thickness has been nominally considered as constant for all the specimens. The experimental behaviour of the analyzed specimens is deduced by applying Electronic Speckle- Pattern Interferometry technique; actually, among optical methods this technique (handled by phase-stepping technique) is very effective to obtain a full-field displacement map and to numerically achieve the longitudinal strain. In particula…
Discovery of benzimidazole-based Leishmania mexicana cysteine protease CPB2.8ΔCTE inhibitors as potential therapeutics for leishmaniasis
2018
Abstract: Chemotherapy is currently the only effective approach to treat all forms of leishmaniasis. However, its effectiveness is severely limited due to high toxicity, long treatment length, drug resistance, or inadequate mode of administration. As a consequence, there is a need to identify new molecular scaffolds and targets as potential therapeutics for the treatment of this disease. We report a small series of 1,2‐substituted‐1H‐benzo[d]imidazole derivatives (9ad) showing affinity in the submicromolar range (Ki = 0.150.69 μM) toward Leishmania mexicanaCPB2.8ΔCTE, one of the more promising targets for antileishmanial drug design. The compounds confirmed activity in vitro against intrace…
Big Data Processing in the ATLAS Experiment: Use Cases and Experience
2015
Abstract The physics goals of the next Large Hadron Collider run include high precision tests of the Standard Model and searches for new physics. These goals require detailed comparison of data with computational models simulating the expected data behavior. To highlight the role which modeling and simulation plays in future scientific discovery, we report on use cases and experience with a unified system built to process both real and simulated data of growing volume and variety.
Big Data in metagenomics: Apache Spark vs MPI.
2020
The progress of next-generation sequencing has lead to the availability of massive data sets used by a wide range of applications in biology and medicine. This has sparked significant interest in using modern Big Data technologies to process this large amount of information in distributed memory clusters of commodity hardware. Several approaches based on solutions such as Apache Hadoop or Apache Spark, have been proposed. These solutions allow developers to focus on the problem while the need to deal with low level details, such as data distribution schemes or communication patterns among processing nodes, can be ignored. However, performance and scalability are also of high importance when…
Deep learning and process understanding for data-driven Earth system science
2017
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybri…
Cropland and grassland management
2014
According to the latest National Inventory, the Italian agricultural sector is a source of GHGs with 34.5 Mt of CO2 eq in 2009, corresponding to 7 % of the total emissions (excluding LULUCF). In particular, more than half (19.1 Mt of CO2 eq) are N2O emissions from soils. Although the national methodology is in accordance with Tier 1 and 2 approaches proposed by the IPCC (2006), still empirical emission factors are used to assess the emission from fertilizer (e.g. 0.0125 kg N2O–N kg−1 N from synthetic fertilizers). Disaggregated data at sub-national level, including models and inventory measurement systems required by higher order methods (i.e. Tier 3), are not available in Italy so far and …
A Derivation of the Vlasov-Stokes System for Aerosol Flows from the Kinetic Theory of Binary Gas Mixtures
2016
In this short paper, we formally derive the thin spray equation for a steady Stokes gas, i.e. the equation consists in a coupling between a kinetic (Vlasov type) equation for the dispersed phase and a (steady) Stokes equation for the gas. Our starting point is a system of Boltzmann equations for a binary gas mixture. The derivation follows the procedure already outlined in [Bernard-Desvillettes-Golse-Ricci, arXiv:1608.00422 [math.AP]] where the evolution of the gas is governed by the Navier-Stokes equation.
A new compact formulation for the discrete p-dispersion problem
2017
Abstract This paper addresses the discrete p -dispersion problem (PDP) which is about selecting p facilities from a given set of candidates in such a way that the minimum distance between selected facilities is maximized. We propose a new compact formulation for this problem. In addition, we discuss two simple enhancements of the new formulation: Simple bounds on the optimal distance can be exploited to reduce the size and to increase the tightness of the model at a relatively low cost of additional computation time. Moreover, the new formulation can be further strengthened by adding valid inequalities. We present a computational study carried out over a set of large-scale test instances i…
A Practical Perspective: The Effect of Ligand Conformers on the Negative Image-Based Screening.
2019
Negative image-based (NIB) screening is a rigid molecular docking methodology that can also be employed in docking rescoring. During the NIB screening, a negative image is generated based on the target protein’s ligand-binding cavity by inverting its shape and electrostatics. The resulting NIB model is a drug-like entity or pseudo-ligand that is compared directly against ligand 3D conformers, as is done with a template compound in the ligand-based screening. This cavity-based rigid docking has been demonstrated to work with genuine drug targets in both benchmark testing and drug candidate/lead discovery. Firstly, the study explores in-depth the applicability of different ligand 3D conformer…