Primitive model electrolytes. A comparison of the HNC approximation for the activity coefficient with Monte Carlo data

Accuracy of the mean activity coefficient expression (Hansen-Vieillefosse-Belloni equation), valid within the hypernetted chain (HNC) approximation, was tested in a wide concentration range against new Monte Carlo (MC) data for +1:-1 and +2:-2 primitive model electrolytes. The expression has an advantage that the excess chemical potential can be obtained directly, without invoking the time consuming Gibbs-Duhem calculation. We found the HNC results for the mean activity coefficient to be in good agreement with the machine calculations performed for the same model. In addition, the thermodynamic consistency of the HNC approximation was tested. The mean activity coefficients, calculated via the Gibbs-Duhem equation, seem to follow the MC data slightly better than the Hansen-Vieillefosse-Belloni expression. For completeness of the calculation, the HNC excess internal energies and osmotic coefficients are also presented. These results are compared with the calculations based on other theories commonly used to describe electrolyte solutions, such as the mean spherical approximation, Pitzer's extension of the Debye-H\"uckel theory, and the Debye-H\"uckel limiting law.Comment: 15 pages, 6 figure

Charting molecular free-energy landscapes with an atlas of collective variables

Collective variables (CVs) are a fundamental tool to understand molecular flexibility, to compute free energy landscapes, and to enhance sampling in molecular dynamics simulations. However, identifying suitable CVs is challenging, and is increasingly addressed with systematic data-driven manifold learning techniques. Here, we provide a flexible framework to model molecular systems in terms of a collection of locally valid and partially overlapping CVs: an atlas of CVs. The specific motivation for such a framework is to enhance the applicability and robustness of CVs based on manifold learning methods, which fail in the presence of periodicities in the underlying conformational manifold. More generally, using an atlas of CVs rather than a single chart may help us better describe different regions of conformational space. We develop the statistical mechanics foundation for our multi-chart description and propose an algorithmic implementation. The resulting atlas of data-based CVs are then used to enhance sampling and compute free energy surfaces in two model systems, alanine dipeptide and ß-D-glucopyranose, whose conformational manifolds have toroidal and spherical topologies

Motivation and benefits of implementation and certification according ISO 9001 – the Portuguese experience

The aim of the research is to analyze the different aspects associated with the motivation and benefits of certified ISO 9001 companies in Portugal. A total of 426 certified Portuguese companies were surveyed. The response rate was equal to 61.03 percent. Our results suggest that the main motivation for certification were “improvement of quality”, “improvement of company image”, “marketing advantage”, “give empowerment to workers / capturing workers knowledge” and “cost reduction”. The main benefits that Portuguese companies have gained from the referred certification have been, among others, the improvement of “procedures”, beneficial effect on the “company’s image”, the improvement of quality products/services, increase of the “customer satisfaction”, improvement of “on-time delivery”; improvement the “morale” of workers’ increase in productivity and decrease of “production costs”, among others. The surveyed firms belong only to the Minho region of the north of Portugal. This paper aims to provide a contribution to the research related to the motivation and benefits associated to the quality management systems. The selection of the motives and benefits were validated through statistical analysis and the relationship between expected and perceived benefits was discussed

The estimation of the return on firms’ investments – as to ISO 9001

The aim of this paper was to estimate the return on investment in QMS (quality management systems) certification undertaken in Portuguese firms, according to the ISO 9000 series. A total of 426 certified Portuguese firms were surveyed. The response rate was 61.03 percent. The different payback periods were validated through statistical analysis and the relationship between expected and perceived payback periods was discussed. This study suggests that a firm’s sector of activity, size and degree of internationalization are related to the length of the investment in QMS certification recovery period. Furthermore, our findings suggest, that the time taken to obtain the certification is not directly related to the economic component of the certification. The majority of Portuguese firms (58.9%) took up to three years to recoup their investment and 35.5% of companies said they had not yet recovered the initial investment made. The recoup of investment was measured by the increase in the number of customers and consequent volume of deliveries, improved profitability and productivity of the company, improvement of competitive position and performance (cost savings), reduction in the number of external complaints and internal defects/scrap, achievement of some important clientele, among others. We compared our work to similar studies undertaken in other countries. This paper provides a contribution to the research related to the return on investment for costs related to the certification QMS according to ISO 9000. This paper provides a valuable contribution to the field and is one of the first studies to undertake this type of analysis in Portugal

Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables

Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. Given their importance, there is need for systematic methods that effectively identify CVs for complex systems. In recent years, nonlinear manifold learning has shown its ability to automatically characterize molecular collective behavior. Unfortunately, these methods fail to provide a differentiable function mapping high-dimensional configurations to their low-dimensional representation, as required in enhanced sampling methods. We introduce a methodology that, starting from an ensemble representative of molecular flexibility, builds smooth and nonlinear data-driven collective variables (SandCV) from the output of nonlinear manifold learning algorithms. We demonstrate the method with a standard benchmark molecule, alanine dipeptide, and show how it can be non-intrusively combined with off-the-shelf enhanced sampling methods, here the adaptive biasing force method. We illustrate how enhanced sampling simulations with SandCV can explore regions that were poorly sampled in the original molecular ensemble. We further explore the transferability of SandCV from a simpler system, alanine dipeptide in vacuum, to a more complex system, alanine dipeptide in explicit water.Peer ReviewedPostprint (published version

A Highly Optimized Skeleton for Unbalanced and Deep Divide-And-Conquer Algorithms on Multi-Core Clusters

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Efficiently implementing the divide-and-conquer pattern of parallelism in distributed memory systems is very relevant, given its ubiquity, and difficult, given its recursive nature and the need to exchange tasks and data among the processors. This task is noticeably further complicated in the presence of multi-core systems, where hybrid parallelism must be exploited to attain the best performance, and when unbalanced and deep workloads are considered, as additional measures must be taken to load balance and avoid deep recursion problems. In this manuscript a parallel skeleton that fulfills all these requirements while providing high levels of usability is presented. In fact, the evaluation shows that our proposal is on average 415.32% faster than MPI codes and 229.18% faster than MPI + OpenMP benchmarks, while offering an average improvement in the programmability metrics of 131.04% over MPI alternatives and 155.18% over MPI + OpenMP solutions.This research was supported by the Ministry of Science and Innovation of Spain (PID2019-104184RB-I00 and PID2019-104834GB-I00, AEI/FEDER/EU, 10.13039/501100011033) and the predoctoral Grant of Millán Álvarez Ref. BES-2017-081320), and by the Xunta de Galicia co-founded by the European Regional Development Fund (ERDF) under the Consolidation Programme of Competitive Reference Groups (ED431C 2018/19 and ED431C 2021/30). We acknowledge also the support from the Centro Singular de Investigación de Galicia “CITIC” and the Centro Singular de Investigación en Tecnoloxías Intelixentes “CiTIUS”, funded by Xunta de Galicia and the European Union (European Regional Development Fund- Galicia 2014-2020 Program), by Grants ED431G 2019/01 and ED431G 2019/04. We also acknowledge the Centro de Supercomputación de Galicia (CESGA). Open Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureXunta de Galicia; ED431C 2018/19Xunta de Galicia; ED431C 2021/30Xunta de Galicia; ED431G 2019/01Xunta de Galicia; ED431G 2019/0

Classification of red grapes according to their state of ripeness using a low-cost multispectral device

[ES] El objetivo del presente trabajo fue evaluar la idoneidad de un sensor multiespectral de bajo costo para la determinación del estado de maduración de uvas tintas. El dispositivo propuesto se basa en un sensor multiespectral, con 18 bandas de detección en el rango entre los 410 y los 940 nm. La recogida de muestras se llevó a cabo en un viñedo comercial situado en Rociana del Condado, Huelva. El dispositivo propuesto se utilizó para adquirir la respuesta espectral de 80 racimos de uva en condiciones de laboratorio. Tras esto, cada una de las muestras fue analizada mediante métodos estándar de laboratorio para obtener indicadores objetivos de su estado de maduración (sólidos solubles totales y acidez). Los 18 valores de reflectancia ofrecidos por el sensor fueron usados como datos de entrada para entrenar redes neuronales artificiales para la clasificación de las muestras de uva en función de los parámetros objetivo. Los resultados obtenidos fueron prometedores, lo cual allana el camino hacia la implementación de un sistema para la monitorización del estado de maduración de uvas asequible para los vinicultores.[EN] The present work aims to evaluate a low-cost multispectral device for non-destructive grape ripening status assessment. The proposed device is based on a multispectral sensor, with a spectral response of 18 channels in a range from 410 to 940 nm. The experimental validation was carried out in a commercial vineyard in Rociana del Condado, Huelva. The proposed device was used to analyze 80 grape samples under laboratory conditions. After being processed with the proposed device the grape samples were analyzed with standard chemical methods to generate ground truth values of ripening status indicators (solid soluble content, and acidity). The 18-reflectance data corresponding to the spectral channels of the employed sensor, were used as input variables for developing artificial neural network models to classify the berries samples based on the mentioned ripeness indicators. The obtained results were promising, which paves the way for the implementation of a portable grape ripening appraisal system affordable for grape growers