Vibration-Based Structural Health Monitoring Using Piezoelectric Transducers and Parametric t-SNE.

In this paper, we evaluate the performance of the so-called parametric t-distributed stochastic neighbor embedding (P-t-SNE), comparing it to the performance of the t-SNE, the non-parametric version. The methodology used in this study is introduced for the detection and classification of structural changes in the field of structural health monitoring. This method is based on the combination of principal component analysis (PCA) and P-t-SNE, and it is applied to an experimental case study of an aluminum plate with four piezoelectric transducers. The basic steps of the detection and classification process are: (i) the raw data are scaled using mean-centered group scaling and then PCA is applied to reduce its dimensionality; (ii) P-t-SNE is applied to represent the scaled and reduced data as 2-dimensional points, defining a cluster for each structural state; and (iii) the current structure to be diagnosed is associated with a cluster employing two strategies: (a) majority voting; and (b) the sum of the inverse distances. The results in the frequency domain manifest the strong performance of P-t-SNE, which is comparable to the performance of t-SNE but outperforms t-SNE in terms of computational cost and runtime. When the method is based on P-t-SNE, the overall accuracy fluctuates between 99.5% and 99.75%.

Damage Identification in Structural Health Monitoring: A Brief Review from its Implementation to the Use of Data-Driven Applications.

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.

Public Transport Strikes and Their Relationships With Air Pollution, Mortality, and Hospital Admissions.

There is limited suggestive evidence of relationships between public transport strikes and either increased air pollution or worse population health. In this study we aimed to assess whether public transport strikes were associated with increases in health events (overall, cardiovascular and respiratory mortality, and cardiovascular and respiratory hospitalizations). We also explored whether air pollution mediated those associations. We used data from the city of Barcelona (Spain) for the period 2005-2016 on strikes, health events, and ambient air pollution (nitrogen dioxide, nitrogen monoxide, particulate matter (PM) with an aerodynamic diameter ≤10 µm, PM with an aerodynamic diameter ≤2.5µm, PM with an aerodynamic diameter ≤1µm, number of particles with a diameter greater than 5 nm per cm3 (particle number concentration), and black carbon). We used linear and quasi-Poisson regression models to explore the associations between air pollution and public transport strikes and between public transport strikes and health outcomes. We also investigated potential causal mediation by air pollution. Overall, this study suggested that public transport strikes are associated with increased overall mortality, respiratory mortality, and respiratory hospitalizations. However, our findings suggest that such increases are not mediated by the increase in air pollution. Our results indicate the need to further investigate these relationships and potential mechanisms.

A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE †.

This work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to represent the local structure of high-dimensional data in a low-dimensional space. The steps of the detection and classification procedure are: (i) the data collected are scaled using mean-centered group scaling (MCGS); (ii) then principal component analysis (PCA) is applied to reduce the dimensionality of the data set; (iii) t-SNE is applied to represent the scaled and reduced data as points in a plane defining as many clusters as different structural states; and (iv) the current structure to be diagnosed will be associated with a cluster or structural state based on three strategies: (a) the smallest point-centroid distance; (b) majority voting; and (c) the sum of the inverse distances. The combination of PCA and t-SNE improves the quality of the clusters related to the structural states. The method is evaluated using experimental data from an aluminum plate with four piezoelectric transducers (PZTs). Results are illustrated in frequency domain, and they manifest the high classification accuracy and the strong performance of this method.

Effect of public transport strikes on air pollution levels in Barcelona (Spain).

Public transport strikes can lead to an increase of the number of private vehicle trips, which in turn can increase air pollution levels. We aimed to estimate the change in air pollution concentrations during public transport strikes in the city of Barcelona (Spain). Data on strikes of the metro, train or bus systems were collected from government records (2005-2016). We collected daily concentrations of NOx; particulate matter with an aerodynamic diameter smaller than 10µm (PM10), 2.5µm (PM2.5), and 1µm (PM1); particle number concentration (N); black carbon (BC) and CO from research and official monitoring stations. We fitted linear regression models for each pollutant with the strike indicator as an independent variable, and models were adjusted for day of the week, month, year, and holiday periods. During the study period, there were 208days affected by a strike of the metro (28), train (106) or bus (91) systems. Half of the strikes were partial, most of them were single-day strikes, there was little overlap between strikes of the different transport systems, and all strikes had to comply with mandatory minimal services. When pooling all types of strikes, NOx and BC showed higher levels during strike days in comparison with non-strike days (increase between 4.1% and 7.7%, with higher increases for NO). The increases in these concentrations were more evident during full day and multiday metro strikes. In conclusion, alterations in public transport have consequences on air quality. This highlights the importance of public transport in reducing air pollution concentrations in cities.

The association of air pollution and greenness with mortality and life expectancy in Spain: A small-area study.

BACKGROUND: Air pollution exposure has been associated with an increase in mortality rates, but few studies have focused on life expectancy, and most studies had restricted spatial coverage. A limited body of evidence is also suggestive for a beneficial association between residential exposure to greenness and mortality, but the evidence for such an association with life expectancy is still very scarce. OBJECTIVE: To investigate the association of exposure to air pollution and greenness with mortality and life expectancy in Spain. METHODS: Mortality data from 2148 small areas (average population of 20,750 inhabitants, and median population of 7672 inhabitants) covering Spain for years 2009-2013 were obtained. Average annual levels of PM10, PM2.5, NO2 and O3 were derived from an air quality forecasting system at 4×4km resolution. The normalized difference vegetation index (NDVI) was used to assess greenness in each small area. Air pollution and greenness were linked to standardized mortality rates (SMRs) using Poisson regression and to life expectancy using linear regression. The models were adjusted for socioeconomic status and lung cancer mortality rates (as a proxy for smoking), and accounted for spatial autocorrelation. RESULTS: The increase of 5µg/m3 in PM10, NO2 and O3 or of 2µg/m3 in PM2.5 concentration resulted in a loss of life in years of 0.90 (95% credibility interval CI: 0.83, 0.98), 0.13 (95% CI: 0.09, 0.17), 0.20years (95% CI: 0.16, 0.24) and 0.64 (0.59, 0.70), respectively. Similar associations were found in the SMR analysis, with stronger associations for PM2.5 and PM10, which were associated with an increased mortality risk of 3.7% (95% CI: 3.5%, 4.0%) and 5.7% (95% CI: 5.4%, 6.1%). For greenness, a protective effect on mortality and longer life expectancy was only found in areas with lower socioeconomic status. CONCLUSIONS: Air pollution concentrations were associated to important reductions in life expectancy. The reduction of air pollution should be a priority for public health.

Air pollution and atherosclerosis: a cross-sectional analysis of four European cohort studies in the ESCAPE study.

BACKGROUND: In four European cohorts, we investigated the cross-sectional association between long-term exposure to air pollution and intima-media thickness of the common carotid artery (CIMT), a preclinical marker of atherosclerosis. METHODS: Individually assigned levels of nitrogen dioxide, nitrogen oxides, particulate matter ≤ 2.5 µm (PM2.5), absorbance of PM2.5 (PM2.5abs), PM10, PMcoarse, and two indicators of residential proximity to highly trafficked roads were obtained under a standard exposure protocol (European Study of Cohorts for Air Pollution Effects-ESCAPE study) in the Stockholm area (Sweden), the Ausburg and Ruhr area (Germany), and the Girona area (Spain). We used linear regression and meta-analyses to examine the association between long-term exposure to air pollution and CIMT. RESULTS: The meta-analysis with 9,183 individuals resulted in an estimated increase in CIMT (geometric mean) of 0.72% (95% CI: -0.65%, 2.10%) per 5-µg/m3 increase in PM2.5 and 0.42% (95% CI: -0.46%, 1.30%) per 10-5/m increase in PM2.5abs. Living in proximity to high traffic was also positively but not significantly associated with CIMT. Meta-analytic estimates for other pollutants were inconsistent. Results were similar across different adjustment sets and sensitivity analyses. In an extended meta-analysis for PM2.5 with three other previously published studies, a 0.78% (95% CI: -0.18%, 1.75%) increase in CIMT was estimated for a 5-µg/m3 contrast in PM2.5. CONCLUSIONS: Using a standardized exposure and analytical protocol in four European cohorts, we found that cross-sectional associations between CIMT and the eight ESCAPE markers of long-term residential air pollution exposure did not reach statistical significance. The additional meta-analysis of CIMT and PM2.5 across all published studies also was positive but not significant.

Short-term effects of particulate matter constituents on daily hospitalizations and mortality in five South-European cities: results from the MED-PARTICLES project.

BACKGROUND: Few recent studies examined acute effects on health of individual chemical species in the particulate matter (PM) mixture, and most of them have been conducted in North America. Studies in Southern Europe are scarce. The aim of this study is to examine the relationship between particulate matter constituents and daily hospital admissions and mortality in five cities in Southern Europe. METHODS: The study included five cities in Southern Europe, three cities in Spain: Barcelona (2003-2010), Madrid (2007-2008) and Huelva (2003-2010); and two cities in Italy: Rome (2005-2007) and Bologna (2011-2013). A case-crossover design was used to link cardiovascular and respiratory hospital admissions and total, cardiovascular and respiratory mortality with a pre-defined list of 16 PM10 and PM2.5 constituents. Lags 0 to 2 were examined. City-specific results were combined by random-effects meta-analysis. RESULTS: Most of the elements studied, namely EC, SO4(2-), SiO2, Ca, Fe, Zn, Cu, Ti, Mn, V and Ni, showed increased percent changes in cardiovascular and/or respiratory hospitalizations, mainly at lags 0 and 1. The percent increase by one interquartile range (IQR) change ranged from 0.69% to 3.29%. After adjustment for total PM levels, only associations for Mn, Zn and Ni remained significant. For mortality, although positive associations were identified (Fe and Ti for total mortality; EC and Mg for cardiovascular mortality; and NO3(-) for respiratory mortality) the patterns were less clear. CONCLUSIONS: The associations found in this study reflect that several PM constituents, originating from different sources, may drive previously reported results between PM and hospital admissions in the Mediterranean area.

High blood pressure and long-term exposure to indoor noise and air pollution from road traffic.

BACKGROUND: Traffic noise has been associated with prevalence of hypertension, but reports are inconsistent for blood pressure (BP). To ascertain noise effects and to disentangle them from those suspected to be from traffic-related air pollution, it may be essential to estimate people's noise exposure indoors in bedrooms. OBJECTIVES: We analyzed associations between long-term exposure to indoor traffic noise in bedrooms and prevalent hypertension and systolic (SBP) and diastolic (DBP) BP, considering long-term exposure to outdoor nitrogen dioxide (NO2). METHODS: We evaluated 1,926 cohort participants at baseline (years 2003-2006; Girona, Spain). Outdoor annual average levels of nighttime traffic noise (Lnight) and NO2 were estimated at postal addresses with a detailed traffic noise model and a land-use regression model, respectively. Individual indoor traffic Lnight levels were derived from outdoor Lnight with application of insulations provided by reported noise-reducing factors. We assessed associations for hypertension and BP with multi-exposure logistic and linear regression models, respectively. RESULTS: Median levels were 27.1 dB(A) (indoor Lnight), 56.7 dB(A) (outdoor Lnight), and 26.8 µg/m3 (NO2). Spearman correlations between outdoor and indoor Lnight with NO2 were 0.75 and 0.23, respectively. Indoor Lnight was associated both with hypertension (OR = 1.06; 95% CI: 0.99, 1.13) and SBP (ß = 0.72; 95% CI: 0.29, 1.15) per 5 dB(A); and NO2 was associated with hypertension (OR = 1.16; 95% CI: 0.99, 1.36), SBP (ß = 1.23; 95% CI: 0.21, 2.25), and DBP (ß⊇= 0.56; 95% CI: -0.03, 1.14) per 10 µg/m3. In the outdoor noise model, Lnight was associated only with hypertension and NO2 with BP only. The indoor noise-SBP association was stronger and statistically significant with a threshold at 30 dB(A). CONCLUSION: Long-term exposure to indoor traffic noise was associated with prevalent hypertension and SBP, independently of NO2. Associations were less consistent for outdoor traffic Lnight and likely affected by collinearity.

Association of long-term exposure to traffic-related air pollution with blood pressure and hypertension in an adult population-based cohort in Spain (the REGICOR study).

BACKGROUND: Long-term exposure to traffic-related air pollution may increase blood pressure (BP) and induce hypertension. However, evidence supporting these associations is limited, and they may be confounded by exposure to traffic noise and biased due to inappropriate control for use of BP-lowering medications. OBJECTIVES: We evaluated the associations of long-term traffic-related air pollution with BP and prevalent hypertension, adjusting for transportation noise and assessing different methodologies to control for BP-lowering medications. METHODS: We measured systolic (SBP) and diastolic BP (DBP) at baseline (years 2003-2005) in 3,700 participants, 35-83 years of age, from a population-based cohort in Spain. We estimated home outdoor annual average concentrations of nitrogen dioxide (NO2) with a land-use regression model. We used multivariate linear and logistic regression. RESULTS: A 10-µg/m3 increase in NO2 levels was associated with 1.34 mmHg (95% CI: 0.14, 2.55) higher SBP in nonmedicated individuals, after adjusting for transportation noise. Results were similar in the entire population after adjusting for medication, as commonly done, but weaker when other methods were used to account for medication use. For example, when 10 mmHg were added to the measured SBP levels of medicated participants, the association was ß = 0.78 (95% CI: -0.43, 2.00). NO2 was not associated with hypertension. Associations of NO2 with SBP and DBP were stronger in participants with cardiovascular disease, and the association with SBP was stronger in those exposed to high traffic density and traffic noise levels ≥ 55 dB(A). CONCLUSIONS: We observed a positive association between long-term exposure to NO2 and SBP, after adjustment for transportation noise, which was sensitive to the methodology used to account for medication.

Measurement error in epidemiologic studies of air pollution based on land-use regression models.

Land-use regression (LUR) models are increasingly used to estimate air pollution exposure in epidemiologic studies. These models use air pollution measurements taken at a small set of locations and modeling based on geographical covariates for which data are available at all study participant locations. The process of LUR model development commonly includes a variable selection procedure. When LUR model predictions are used as explanatory variables in a model for a health outcome, measurement error can lead to bias of the regression coefficients and to inflation of their variance. In previous studies dealing with spatial predictions of air pollution, bias was shown to be small while most of the effect of measurement error was on the variance. In this study, we show that in realistic cases where LUR models are applied to health data, bias in health-effect estimates can be substantial. This bias depends on the number of air pollution measurement sites, the number of available predictors for model selection, and the amount of explainable variability in the true exposure. These results should be taken into account when interpreting health effects from studies that used LUR models.

Association between long-term exposure to traffic-related air pollution and subclinical atherosclerosis: the REGICOR study.

BACKGROUND: Epidemiological evidence of the effects of long-term exposure to air pollution on the chronic processes of atherogenesis is limited. OBJECTIVE: We investigated the association of long-term exposure to traffic-related air pollution with subclinical atherosclerosis, measured by carotid intima media thickness (IMT) and ankle-brachial index (ABI). METHODS: We performed a cross-sectional analysis using data collected during the reexamination (2007-2010) of 2,780 participants in the REGICOR (Registre Gironí del Cor: the Gerona Heart Register) study, a population-based prospective cohort in Girona, Spain. Long-term exposure across residences was calculated as the last 10 years' time-weighted average of residential nitrogen dioxide (NO2) estimates (based on a local-scale land-use regression model), traffic intensity in the nearest street, and traffic intensity in a 100 m buffer. Associations with IMT and ABI were estimated using linear regression and multinomial logistic regression, respectively, controlling for sex, age, smoking status, education, marital status, and several other potential confounders or intermediates. RESULTS: Exposure contrasts between the 5th and 95th percentiles for NO2 (25 µg/m3), traffic intensity in the nearest street (15,000 vehicles/day), and traffic load within 100 m (7,200,000 vehicle-m/day) were associated with differences of 0.56% (95% CI: -1.5, 2.6%), 2.32% (95% CI: 0.48, 4.17%), and 1.91% (95% CI: -0.24, 4.06) percent difference in IMT, respectively. Exposures were positively associated with an ABI of > 1.3, but not an ABI of < 0.9. Stronger associations were observed among those with a high level of education and in men ≥ 60 years of age. CONCLUSIONS: Long-term traffic-related exposures were associated with subclinical markers of atherosclerosis. Prospective studies are needed to confirm associations and further examine differences among population subgroups.

Carotid intima-media thickness in the Spanish population: reference ranges and association with cardiovascular risk factors.

INTRODUCTION AND OBJECTIVES: Carotid intima-media thickness as measured with ultrasonography is an inexpensive and noninvasive predictor of cardiovascular events. The objectives of this study were to determine the population reference ranges of carotid intima-media thickness for individuals aged 35-84 years in Spain and to analyze the association of carotid intima-media thickness with cardiovascular risk factors (age, smoking, diabetes, pulse pressure, lipid profile, and body mass index). METHODS: Population-based cross-sectional study conducted in Gerona (Spain). We described the mean and maximal values of carotid intima-media thickness of the carotid artery and of its 3 segments (common carotid, carotid bulb and internal carotid). We assessed cardiovascular risk factors and analyzed their association with carotid intima-media thickness using adjusted linear regression models. RESULTS: A total of 3161 individuals (54% women) were included, with mean age 58 years. Men showed significantly higher mean common carotid intima-media thickness than did women (0.71 vs 0.67 mm). The strongest predictors of this measure were age (coefficients for 10-year increase: 0.65 and 0.58 for women and men, respectively), smoking in men (coefficient: 0.26), high-density lipoprotein cholesterol in women (coefficient for 10 mg/dL, increase: -0.08) and pulse pressure in both sexes (coefficients for 10 mmHg increase: 0.08 and 0.23 for women and men, respectively). The results were similar for the mean carotid intima-media thickness of all the segments. CONCLUSIONS: This population-based study presents the reference ranges for carotid intima-media thickness in the Spanish population. The main determinants of carotid intima-media thickness were age and pulse pressure in both sexes.

[Intervention of the family physician in alcoholism: a review of operative strategies]. / Intervención del médico familiar en alcoholismo. Revisión de estrategias operativas.

The actions of secondary prevention of alcohol abuse and alcoholism in the primary medical attention confront barriers that difficult their attention, beginning with those of the patient him or herself, those of the family physician and the multidisciplinary staff, and finally, those corresponding to the system of attention itself. The objective of this study is to show a review of international literature and experiences in Mexico, which present secondary prevention strategies that facilitate the family physician his or her performance in the containment of alcoholism through early detection and brief intervention. In this paper, we present an operative model that the World Health Organization made in 2001 as an advice of its experts on the problem, combining early detection through the application of the "Identification test of disorders due to alcohol addiction, abuse and/or dependence" (AUDIT) and based on the score obtained, it applies an intervention strategy that goes from the simple piece of advice to the brief therapy and if it is necessary, the derivation.