International harmonization of product standards and firm heterogeneity in international trade

As free trade areas have proliferated and statutory tariffs have been dramatically reduced in recent decades, non-tariff barriers (NTBs) to international trade have risen in importance. Destination-specific product standards are one of the major types of NTBs as they impose additional costs on exporters and increase the time required to bring a product to market. This paper examines the response of U.S. manufacturing firms to a reduction of this NTB by looking at the harmonization of European product standards to international norms in the electronics sector. Using a highly detailed dataset that links U.S. international trade transactions to U.S. firms and a new industry-level database of EU product standards, the author finds that harmonization increases U.S. exports to the EU and that this increase is due to more U.S. firms entering the EU market –the extensive margin of trade. New entrants to the EU region are drawn mainly from the most productive set of firms already exporting to developing markets before harmonization -the extensive margin of trade composition. These firms are characterized by being smaller and less productive than the firms that were already exporting to the EU before harmonization. Furthermore, harmonization decreases export sales at existing exporters -the intensive margin of trade. These findings are consistent with a model featuring the role of product standards heterogeneity across market destinations and productivity heterogeneity across firms. These results suggest that working toward a harmonization of product rules across markets could be a supportive policy to encourage small and medium size firms'ability to enter new export markets.Markets and Market Access,E-Business,Information Security&Privacy,Economic Theory&Research,Labor Policies

Eco-innovation practices’ adoption in the automotive industry

Eco-innovation is a construct that is gaining increasing interest from academics and researchers since it is commonly considered in the literature as one of the strategies that allow manufacturing companies not only to significantly reduce the negative impacts on the environment but also the generation of pollutants. However, little is known about the adoption of eco-innovation practices in manufacturing companies, particularly in the automotive industry. Therefore, this research has as main objective to fill this gap in the literature and explore the interdependence between eco-innovation of products, processes and management. The study is conducted through a research framework consisting of 3 measurement scales, 14 items and 3 hypotheses and an extensive review of the literature. A self-administered questionnaire was distributed to a sample of 460 companies in the automotive and auto parts industry in Mexico. Data were analyzed through Confirmatory Factor Analysis, Descriptive Statistics and Structural Equation Modelling. The results obtained show that product eco-innovation, process eco-innovation and management eco-innovation are good indicators for the adoption of eco-innovation practices for companies in the automotive and auto parts industry. The paper addresses a research gap in the academic literature in the eco-innovation field by providing evidence on the interdependence between eco-innovation of products, processes and management and the implementation of their practices in the automotive industry.N/

A study of time-based features and regularity of manipulation to improve the detection of eating activity periods during free living

This thesis considers the problem of detecting when people eat by tracking their wrist motion. The goal of this work is to automatically detect the start and stop times of these eating activities. It builds upon previous work done by our research group, which developed an algorithm for automatically detecting peaks in activities associated with food preparation and clean-up. This peak detector is then used for segmenting data. These segments are then classified as eating or non-eating activities using a naive Bayes classifier based on probabilities obtained from computing different features in each segment. The original work introduced 4 features, all of them based on sensor readings. In this thesis we introduce a set of 3 new features to improve the detection of eating and non-eating activity periods: regularity of manipulation, time since last eating activity and cumulative eating time. We discuss the main concepts behind them, introducing the idea of time-based features. We then we test our new features under the framework developed by our group. Detection including regularity of manipulation, in combination with the original 4 features, achieved an overall accuracy of 79%. The accuracy obtained including time since last eating activity reached 69% and cumulative eating time, an overall accuracy of 64%. Finally, we compare these results to the original work and later discuss and characterize results based on our findings

Biocultural Diversity Conservation: A Global Sourcebook

Review of Biocultural Diversity Conservation: A Global Sourcebook. Luisa Maffi and Ellen Woodley. 2010. Earthscan, London. Pp. 304. $57.95 (paperback). ISBN 978-1-84407-921-6

Modeling the AC Electrokinetic Behavior of Semiconducting Spheres

We study theoretically the dielectrophoresis and electrorotation of a semiconducting microsphere immersed in an aqueous electrolyte. To this end, the particle polarizability is calculated from first principles for arbitrary thickness of the Debye layers in liquid and semiconductor. We show that the polarizability dispersion arises from the combination of two relaxation interfacial phenomena: charging of the electrical double layer and the Maxwell–Wagner relaxation. We also calculate the particle polarizability in the limit of thin electrical double layers, which greatly simplifies the analytical calculations. Finally, we show the model predictions for two relevant materials (ZnO and doped silicon) and discuss the limits of validity of the thin double layer approximation

Dipolophoresis and Travelling-Wave Dipolophoresis of Metal Microparticles

We study theoretically and numerically the electrokinetic behavior of metal microparticles immersed in aqueous electrolytes. We consider small particles subjected to non-homogeneous ac electric fields and we describe their motion as arising from the combination of electrical forces (dielectrophoresis) and the electroosmotic flows on the particle surface (induced-charge electrophoresis). The net particle motion is known as dipolophoresis. We also study the particle motion induced by travelling electric fields. We find analytical expressions for the dielectrophoresis and induced-charge electrophoresis of metal spheres and we compare them with numerical solutions. This validates our numerical method, which we also use to study the dipolophoresis of metal cylinders.Spanish Research Agency MCI under contract PGC2018-099217-B-I00

Improving edge finite element assembly for geophysical electromagnetic modelling on shared-memory architectures

This work presents a set of node-level optimizations to perform the assembly of edge finite element matrices that arise in 3D geophysical electromagnetic modelling on shared-memory architectures. Firstly, we describe the traditional and sequential assembly approach. Secondly, we depict our vectorized and shared-memory strategy which does not require any low level instructions because it is based on an interpreted programming language, namely, Python. As a result, we obtained a simple parallel-vectorized algorithm whose runtime performance is considerably better than sequential version. The set of optimizations have been included to the work-flow of the Parallel Edge-based Tool for Geophysical Electromagnetic Modelling (PETGEM) which is developed as open-source at the Barcelona Supercomputing Center. Finally, we present numerical results for a set of tests in order to illustrate the performance of our strategy.This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 644202. The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (www.hpc4e.eu), grant agreement No. 689772. Authors gratefully acknowledge the support from the Mexican National Council for Science and Technology (CONACYT). All numerical tests were performed on the MareNostrum supercomputer of the Barcelona Supercomputing Center - Centro Nacional de Supercomputación (www.bsc.es).Peer ReviewedPostprint (author's final draft