Lorentz Integral Transform for Inclusive and Exclusive Cross Sections with the Lanczos Method

The Lorentz Integral Transform (LIT) method is reformulated via the Lanczos algorithm both for inclusive and exclusive reactions. The new technique is tested for the total photoabsorption cross section of 3H and 4He. Due to the rapid convergence of the algorithm one has a decrease in cpu time by two orders of magnitude, but at the same time an excellent agreement with the results of a conventional LIT calculation. The present work opens up the possibility of ab initio calculations for inclusive and exclusive processes for A greater equal 6 with inclusion of complete final state interactions.Comment: LaTeX, 13 pages, 3 ps figure

Deep Learning-Driven Extraction of Superluminescent Diodes Parameters

We present a deep learning-based method for the automatic extraction of physical parameters from optical spectra and power values of a chirped, tapered, dual-section quantum dot superluminescent diode. The neural network is able to estimate a set of parameters that are capable of reproducing the behavior of the target device with high accuracy

WO3-Doped Indium Oxide Thick Films for Ozone Detection at Low Temperature

Ozone, a strong oxidizing gas, has dramatically increased its concentration in the troposphere during the last decades. Since high O3 concentrations are hazardous to human health, the development of effective methods and economic devices to detect this gas is an urgent need. In this frame, In2O3 is well known as an n-type ozone sensitive and selective material, generally displaying its optimal sensing capability in the temperature range 200–350 °C. To enhance the sensing capability of In2O3 and to decrease its operative temperature, in this work, commercial In2O3 powders were doped with 2.5 wt. % WO3. Pure and doped-In2O3 materials were used to develop sensing devices by screen-printing technology. Resistance measurements were performed in the temperature range 25 °C–150 °C under 200–500 ppb O3. Best results were obtained at 75 °C with sensor’s responses as high as 40 under 200 ppb of ozone

Sol–gel-entrapped pH indicator for monitoring pH variations in cementitious materials:

Sensors for pH evaluation of concrete were made by a sol–gel process with alizarin yellow as pH indicator. The optical absorbance was measured with a visible spectrophotometer coupled with optical fibers. Results showed that the sensors had good reversibility, reproducibility, and fast response time

Technology Modelling and Technology Innovation

Working Paper Ircres-CNR 03/2016. This work concerns an extension of a mathematical model of technology developed at the Santa Fe Institute in the late nineties. It is based on analogies existing between technological and biological evolution and not on economic principles. This extension has the purpose to make the model useful in the studies of the innovation process. The model considers technology activity, independently of possible economic purposes, and having its own properties, structure, processes as well as an evolution independently by economic factors but more similar to biologic evolution. Considered purpose of technology is reaching of a technical result and not necessarily an economic result. The model considers technology as a structured set of technological operations that may be represented by a graph or matrix. That opens a description of a technology in term of technological spaces and landscapes, as well as in term of spaces of technologies, in which it is possible to represent search of optimal and evolutive paths of technologies, changes in their efficiency and measure of their radical degree linked to their technological competitiveness. The model is presented in a descriptive way and its mathematical development is presented in annex. The main applications of the model concern the use of the defined radical degree of a technology linked to its technological competitiveness. In this way it is explained the existence of Red Queen Regimes, characterized by continuous technical but not economical developments, among firms producing the same product. Such regimes are disrupted only by the entering of a technology with a high radical degree. Changes in operational structure of technologies may suggest the existence of three types of technology innovations, the first concerning learning by doing and consisting in minor changes giving incremental innovations, the second and the third, both able to obtain radical innovations through R&D activity, but the second exploiting scientific results and the third based only on a combinatory process of pre-existing technologies. This last way of innovation may explain the innovative potential, existing for example in Italian industrial districts, without resorting to any scientific research. 

RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks

Neural Architecture Search (NAS) algorithms aim at finding efficient Deep Neural Network (DNN) architectures for a given application under given system constraints. DNNs are computationally-complex as well as vulnerable to adversarial attacks. In order to address multiple design objectives, we propose RoHNAS , a novel NAS framework that jointly optimizes for adversarial-robustness and hardware-efficiency of DNNs executed on specialized hardware accelerators. Besides the traditional convolutional DNNs, RoHNAS additionally accounts for complex types of DNNs such as Capsule Networks. For reducing the exploration time, RoHNAS analyzes and selects appropriate values of adversarial perturbation for each dataset to employ in the NAS flow. Extensive evaluations on multi - Graphics Processing Unit (GPU) - High Performance Computing (HPC) nodes provide a set of Pareto-optimal solutions, leveraging the tradeoff between the above-discussed design objectives. For example, a Pareto-optimal DNN for the CIFAR-10 dataset exhibits 86.07% accuracy, while having an energy of 38.63 mJ, a memory footprint of 11.85 MiB, and a latency of 4.47 ms

Automated model for characterization of VCSEL circuit-level parameters using machine learning

We propose a machine learning-based model to extract physical parameters characterizing stationary and dynamic behavior of a VCSEL. The model is trained with circuit-level simulations of light-current and S21 characteristics. Excellent results are achieved as a relative prediction error

Computational Modeling of Magnesium Hydroxide Precipitation and Kinetics Parameters Identification

Magnesium is a critical raw material and its recovery as Mg(OH)2 from saltwork brines can be realized via precipitation. The effective design, optimization, and scale-up of such a process require the development of a computational model accounting for the effect of fluid dynamics, homogeneous and heterogeneous nucleation, molecular growth, and aggregation. The unknown kinetics parameters are inferred and validated in this work by using experimental data produced with a T2mm-mixer and a T3mm-mixer, guaranteeing fast and efficient mixing. The flow field in the T-mixers is fully characterized by using the k-ε turbulence model implemented in the computational fluid dynamics (CFD) code OpenFOAM. The model is based on a simplified plug flow reactor model, instructed by detailed CFD simulations. It incorporates Bromley's activity coefficient correction and a micro-mixing model for the calculation of the supersaturation ratio. The population balance equation is solved by exploiting the quadrature method of moments, and mass balances are used for updating the reactive ions concentrations, accounting for the precipitated solid. To avoid unphysical results, global constrained optimization is used for kinetics parameters identification, exploiting experimentally measured particle size distribution (PSD). The inferred kinetics set is validated by comparing PSDs at different operative conditions both in the T2mm-mixer and the T3mm-mixer. The developed computational model, including the kinetics parameters estimated for the first time in this work, will be used for the design of a prototype for the industrial precipitation of Mg(OH)2 from saltwork brines in an industrial environment

Nanoprobes to interrogate nonspecific interactions in lipid bilayers: from defect-mediated adhesion to membrane disruption

When a lipid membrane approaches a material/nanomaterial, nonspecific adhesion may occur. The interactions responsible for nonspecific adhesions can either preserve the membrane integrity or lead to its disruption. Despite the importance of the phenomenon, there is still a lack of clear understanding of how and why nonspecific adhesions may originate different resulting scenarios and how these interaction scenarios can be interrogated. This work aims at bridging this gap by investigating the interplay between cationic electrostatic and hydrophobic interactions in modulating the membrane stability during nonspecific adhesion phenomena. Here, the stability of the membrane has been studied employing anisotropic nanoprobes in zwitterionic lipid membranes with the support of coarse-grained molecular dynamics simulations to interpret the experimental observations. Lipid membrane electrical measurements and nanoscale visualization in combination with molecular dynamics simulations revealed the phenomena driving nonspecific adhesion. Any interaction with the lipidic bilayer is defect-mediated involving cationic electrostatically-driven lipid extractions and hydrophobicallydriven chains protrusion, whose interplay determines the existence of a thermodynamic optimum for the membrane structural integrity. These findings unlock unexplored routes to exploit nonspecific adhesion in lipid membranes. The proposed platform can act as a straightforward probing tool to locally interrogate interactions between synthetic materials and lipid membranes for the design of antibacterials, antivirals, and scaffolds for tissue engineering

La educación en el entorno empresarial: el desafío de la innovación

No es novedad que las Pequeñas y Medianas Empresas (PyMES) son la base del entramado productivo de un país, y que generan un impacto positivo que excede el beneficio que recibe el propio empresario; porque se difunde por toda la sociedad. En un contexto cada vez más competitivo y cambiante, los empresarios PyMES enfrentan una serie de retos que están vinculados con factores externos y aspectos internos. Frecuentemente este tipo de empresa suele encontrarse menos dotada que las grandes en recursos o capacidades, para moderar el efecto del entorno en el que se desenvuelven sobre su plan de negocios. La necesidad de formación en mandos medios de una PyME del norte de la Provincia de Santa Fe y la convicción que la Universidad, comprometida y parte de una misma sociedad, debe ser capaz de articular saberes y recursos, atendiendo a las particulares necesidades de desarrollo de la región, han confluido en la formulación y ejecución de un proyecto de fortalecimiento de capacidades de innovación, en el marco del cual se puso a prueba un modelo de capacitación diseñado interdisciplinariamente por el equipo de autoras. La capacitación, desarrollada en modalidad virtual, representó un desafío. La misma fue responsabilidad del Departamento Educación a Distancia de la Escuela de Posgrado de la Facultad de Ciencias Exactas, Ingeniería y Agrimensura de la Universidad Nacional de Rosario. Si bien la adecuación del proceso formativo a momentos y tiempos de los destinatarios, en su propio entorno laboral, ha sido una fortaleza, la necesidad de reproducir a distancia mecanismos complejos, y muchas veces sutiles, requirió del diseño de un dispositivo de formación que articulara contenidos y estrategias de motivación y promoción de la participación, respondiendo positivamente a expectativas, objetivos y necesidades. Este trabajo propone el análisis de las debilidades y fortalezas de la adaptación de la capacitación virtual a la capacitación empresarial, tomando como objeto de análisis la experiencia realizada en el diseño e impartición del curso virtual “Cómo desarrollar y evaluar un plan de negocio eficaz en su Empresa Institución u Organización”, diseñado a medida de la PyME en cuestión para responder a las necesidades formativas planteadas por los directivos de la misma