Key Components of Collaborative Research in the Context of Environmental Health: A Scoping Review

In a collaborative research process, the participation of interdisciplinary researchers and multi-sectoral stakeholders supports the co-creation, translation, and exchange of new knowledge. Following a scoping review methodology, we explored the collaborative research processes in the specific context of environment and human health research. Initially, our literature search strategy identified 1,328 publications. After several phases of reviewing and applying screening criteria to titles, abstracts, and full text, 45 publications were selected for final review. Data were charted by different topics and then collated, summarized, and analyzed thematically. From the different experiences and research approaches analyzed, we identified comprehensive details of the key components, facilitators, challenges, and best practices that impact the collaborative research process. Specifically, we identified the following seven emerging themes: (a) allocating time and resources, (b) addressing disciplinary and sectoral issues, (c) building relationships, (d) ensuring representation, (e) embedding participation in the research, (f) supporting ongoing collaboration, and (g) developing knowledge translation and exchange

Vibration-based adaptive novelty detection method for monitoring faults in a kinematic chain

Postprint (published version

Magnetic Flux Analysis for the Condition Monitoring of Electric Machines: A Review

[EN] Magnetic flux analysis is a condition monitoring technique that is drawing the interest of many researchers and motor manufacturers. The great enhancements and reduction in the costs and dimensions of the required sensors, the development of advanced signal processing techniques that are suitable for flux data analysis, along with other inherent advantages provided by this technology are relevant aspects that have allowed the proliferation of flux-based techniques. This paper reviews the most recent scientific contributions related to the development and application of flux-based methods for the monitoring of rotating electric machines. Particularly, aspects related to the main sensors used to acquire magnetic flux signals as well as the leading signal processing and classification techniques are commented. The discussion is focused on the diagnosis of different types of faults in the most common rotating electric machines used in industry, namely: squirrel cage induction machines (SCIM), wound rotor induction machines (WRIM), permanent magnet machines (PMM) and wound field synchronous machines (WFSM). A critical insight of the techniques developed in the area is provided and several open challenges are also discussed.This work was supported by the Spanish 'Ministerio de Ciencia Innovación y Universidades' and FEDER program in the framework of the "Proyectos de I+D de Generación de Conocimiento del Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnologico del Sistema de I+D+i, Subprograma Estatal de Generacion de Conocimiento" reference PGC2018-095747-B-I00 and by the Consejo Nacional de Ciencia y Tecnología under CONACyT Scholarship with key code 2019-000037-02NACF. Paper no. TII-20-5308.Zamudio-Ramírez, I.; Osornio-Rios, RA.; Antonino-Daviu, J.; Razik, H.; Romero-Troncoso, RDJ. (2022). Magnetic Flux Analysis for the Condition Monitoring of Electric Machines: A Review. IEEE Transactions on Industrial Informatics. 18(5):2895-2908. https://doi.org/10.1109/TII.2021.30705812895290818

EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations

This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several factors as nonstationary effects, close modal frequencies, and noisy environments, which are common situations where several techniques reported in literature fail. The EEMD and MUSIC methods are used to decompose the vibration signal into a set of IMFs (intrinsic mode functions) and to identify the natural frequencies of a structure, respectively. The effectiveness of the proposed methodology has been validated and tested with synthetic signals and under real operating conditions. The experiments are focused on extracting the natural frequencies of a truss-type scaled structure and of a bridge used for both highway traffic and pedestrians. Results show the proposed methodology as a suitable solution for natural frequencies identification of structures from free and ambient vibration signals

An overview of the MILAGRO 2006 Campaign: Mexico City emissions and their transport and transformation

MILAGRO (Megacity Initiative: Local And Global Research Observations) is an international collaborative project to examine the behavior and the export of atmospheric emissions from a megacity. The Mexico City Metropolitan Area (MCMA) – one of the world's largest megacities and North America's most populous city – was selected as the case study to characterize the sources, concentrations, transport, and transformation processes of the gases and fine particles emitted to the MCMA atmosphere and to evaluate the regional and global impacts of these emissions. The findings of this study are relevant to the evolution and impacts of pollution from many other megacities. The measurement phase consisted of a month-long series of carefully coordinated observations of the chemistry and physics of the atmosphere in and near Mexico City during March 2006, using a wide range of instruments at ground sites, on aircraft and satellites, and enlisting over 450 scientists from 150 institutions in 30 countries. Three ground supersites were set up to examine the evolution of the primary emitted gases and fine particles. Additional platforms in or near Mexico City included mobile vans containing scientific laboratories and mobile and stationary upward-looking lidars. Seven instrumented research aircraft provided information about the atmosphere over a large region and at various altitudes. Satellite-based instruments peered down into the atmosphere, providing even larger geographical coverage. The overall campaign was complemented by meteorological forecasting and numerical simulations, satellite observations and surface networks. Together, these research observations have provided the most comprehensive characterization of the MCMA's urban and regional atmospheric composition and chemistry that will take years to analyze and evaluate fully. In this paper we review over 120 papers resulting from the MILAGRO/INTEX-B Campaign that have been published or submitted, as well as relevant papers from the earlier MCMA-2003 Campaign, with the aim of providing a road map for the scientific community interested in understanding the emissions from a megacity such as the MCMA and their impacts on air quality and climate. This paper describes the measurements performed during MILAGRO and the results obtained on MCMA's atmospheric meteorology and dynamics, emissions of gases and fine particles, sources and concentrations of volatile organic compounds, urban and regional photochemistry, ambient particulate matter, aerosol radiative properties, urban plume characterization, and health studies. A summary of key findings from the field study is presented.Mexico. Comisión Ambiental MetropolitanaMexico. Ministry of the EnvironmentConsejo Nacional de Ciencia y Tecnología (Mexico)Petróleos MexicanosNational Science Foundation (U.S.). Atmospheric Chemistry ProgramAtmospheric Sciences Program (U.S.)United States. National Aeronautics and Space Administration. Radiation Science Progra

A method for encoding clinical datasets with SNOMED CT

<p>Abstract</p> <p>Background</p> <p>Over the past decade there has been a growing body of literature on how the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) can be implemented and used in different clinical settings. Yet, for those charged with incorporating SNOMED CT into their organisation's clinical applications and vocabulary systems, there are few detailed encoding instructions and examples available to show how this can be done and the issues involved. This paper describes a heuristic method that can be used to encode clinical terms in SNOMED CT and an illustration of how it was applied to encode an existing palliative care dataset.</p> <p>Methods</p> <p>The encoding process involves: identifying input data items; cleaning the data items; encoding the cleaned data items; and exporting the encoded terms as output term sets. Four outputs are produced: the SNOMED CT reference set; interface terminology set; SNOMED CT extension set and unencodeable term set.</p> <p>Results</p> <p>The original palliative care database contained 211 data elements, 145 coded values and 37,248 free text values. We were able to encode ~84% of the terms, another ~8% require further encoding and verification while terms that had a frequency of fewer than five were not encoded (~7%).</p> <p>Conclusions</p> <p>From the pilot, it would seem our SNOMED CT encoding method has the potential to become a general purpose terminology encoding approach that can be used in different clinical systems.</p

The mechanical hybrid vehicle: an investigation of a flywheel-based vehicular regenerative energy capture system

Capturing braking energy by regeneration into an onboard energy storage unit offers the potential to reduce significantly the fuel consumption of vehicles. A common technique is to generate electricity in the motors of a hybrid electric vehicle when braking, and to use this to charge an onboard electrochemical battery. However, such batteries are costly, bulky, and generally not amenable to fast charging as this affects battery life and capacity. In order to overcome these problems, a mechanical energy storage system capable of accepting and delivering surges of power is proposed and investigated. A scale physical model of the system, based around a flywheel, a planetary gear set, and a brake, was built and operated in a laboratory. Tests showed that the proposed system could be used to store and provide braking energy between a flywheel and a vehicle, the latter emulated by an air-drag dynamometer. This validated the operating principle of the system and its computational model. Further, a computational analysis of a full-size vehicle incorporating the mechanical energy storage system was conducted. The results showed that the utilization of this system in a vehicle, when compared with a conventional vehicle, led to reductions in emissions and fuel consumption

A Novel Methodology for Power Quality Disturbances Detection and Classification in Industrial Facilities

The industrial facilities inject noise to the power line. Concerning this issue, researchers are focusing their effort on developing new techniques for analyzing the power quality of the power net. This work presents a novel methodology for power quality disturbances detection and classification based on the Harris hawks optimization algorithm and discrete wavelet transforms decomposition of the signal