1,721,049 research outputs found
Air quality in Tehran, Iran : evaluating acute health effects and modeling the long-term spatial variability
Full text linkThe burden of disease due to air pollution can be very large because of its acute and chronic effects. This dissertation focused on these two key challenges in the megacity of Tehran, Iran. First, it assessed short-term exposure to ambient air pollutants and their association with daily mortality. Second, it assessed long-term exposures for different air pollutants, which is a prerequisite for the investigation of their chronic health effects. The first part found that the effect of air pollutants on mortality was immediate, and that it increased steadily over a period of weeks. The second part found that concentrations of various air pollutants were very high in Tehran, comparable with those reported for other megacities in Asia. Further, spatial land-use regression (LUR) models were developed for multiple pollutants, and showed that the city center was the most polluted area. Even so, more than 80% of Tehran had benzene concentrations above air quality standard of 5 µg/m3 set by European Union and Iranian Government. The thesis also included a systematic review of the global literature on LUR models for volatile organic compounds and found that the study in Tehran has been the largest to assess all BTEX (benzene, toluene, ethylbenzene, and xylenes) species in a megacity. The methods and models developed for this PhD dissertation opened up new avenues for the next generation of air pollution monitoring, modelling, and epidemiology in Iran
Concurrent spatiotemporal daily land use regression modeling and missing data imputation of fine particulate matter using distributed space-time Expectation Maximization
No full textIn this study, a spatiotemporal land use regression (LUR) model using Distributed Space-Time Expectation Maximization (D-STEM) software was developed. We trained the model using daily mean ambient particulate matter ≤ 2.5 μm (PM2.5) data measured hourly in 2015 at 30 regulatory monitoring network stations within the megacity of Tehran, Iran. Since a substantial amount of measured data were missing (48% of the total number of daily PM2.5 observations), we used the D-STEM to impute missing data and compared the missing imputation performance between different fitted models and the mean substitution method. We used h-block cross-validation (h-block CV) method in order to account for spatial autocorrelation in the model building and validation. In the imputation of missing data, the D-STEM LUR model had a mean absolute percentage error (MAPE) of 25.3%, outperforming the mean substitution method, which resulted in MAPE of 28.3%. The spatiotemporal R-squared was 0.73 and the average CV R-squared of 2-block and 5-block cross-validations was 0.60. These values were 0.68 and 0.47 when the spatial aspect of the LUR model was assessed, and 0.995 and 0.992 when the temporal aspect of the LUR model was assessed. This study demonstrated the competence of D-STEM software in spatiotemporal modeling, missing data imputation, and mapping of daily ambient PM2.5 at a very high spatial resolution (20 m x 20 m). These estimations are available for future research, especially for epidemiological studies on short- and/or long-term health effects of ambient PM2.5. Generally, we found D-STEM as a promising tool for spatiotemporal LUR modeling of ambient air pollution, especially for those models that rely on regulatory network monitoring stations with a considerable amount of missing data
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The flip side of the coin:Exploring the environmental and health impacts of proof-of-work cryptocurrency mining
No full textBlockchain technology, the backbone of cryptocurrency, is under scrutiny due to the environmental and health hazards linked to its energy-consuming Proof-of-Work (PoW) mining process. This review study provides a comprehensive analysis of the global health implications of PoW mining and cryptocurrency, with a focus on environmental sustainability and human health. The research utilized both traditional databases (PubMed and Web of Science) and additional primary sources. The study underscores the high energy consumption and carbon emissions of Bitcoin mining, despite ongoing debates comparing cryptocurrency to conventional finance. The review calls for immediate interventions, including the exploration of renewable energy sources and a transition from PoW to more sustainable consensus mechanisms. A case study on China's carbon policies highlights the necessity for effective regulatory measures. The findings reiterate the environmental and health risks associated with PoW cryptocurrency mining, including its resource-intensive procedures, reliance on non-renewable energy, and emission of air pollutants. The review emphasizes the urgent need for global regulation and a transition to more sustainable consensus mechanisms, such as Proof-of-Stake (PoS), to reduce the industry's impact on climate and human health.Blockchain technology, the backbone of cryptocurrency, is under scrutiny due to the environmental and health hazards linked to its energy-consuming Proof-of-Work (PoW) mining process. This review study provides a comprehensive analysis of the global health implications of PoW mining and cryptocurrency, with a focus on environmental sustainability and human health. The research utilized both traditional databases (PubMed and Web of Science) and additional primary sources. The study underscores the high energy consumption and carbon emissions of Bitcoin mining, despite ongoing debates comparing cryptocurrency to conventional finance. The review calls for immediate interventions, including the exploration of renewable energy sources and a transition from PoW to more sustainable consensus mechanisms. A case study on China's carbon policies highlights the necessity for effective regulatory measures. The findings reiterate the environmental and health risks associated with PoW cryptocurrency mining, including its resource-intensive procedures, reliance on non-renewable energy, and emission of air pollutants. The review emphasizes the urgent need for global regulation and a transition to more sustainable consensus mechanisms, such as Proof-of-Stake (PoS), to reduce the industry's impact on climate and human health.</p
Short-term air pollution exposure and mortality in Brazil: Investigating the susceptible population groups.
No full textThis is the first study to examine the association between ambient air pollution (PM2.5, O3, and NO2) and mortality (in different population groups by sex and age) based on a nationwide death record across Brazil over a 15-year period (2003-2017). We used a time-series analytic approach with a distributed lag model. Our study population includes 2,872,084 records of deaths in Brazil between 2003 and 2017. Men accounted for a higher proportion of deaths, with 58% for all-cause mortality, 54% for respiratory mortality, and 52% for circulatory mortality. Most individuals were over 65 years of age. Our results suggest an association between air pollution and mortality in Brazil. The direction, statistical significance, and effect size of these associations varied considerably by type of air pollutant, region, and population group (sex and age group). In particular, the older population group (>65 years) was most affected. The national meta-analysis for the entire data set (without stratification by sex and age) showed that for every 10 μg/m3 increase in PM2.5 concentration, the risk of death from respiratory diseases increased by 2.93% (95%CI: 1.42; 4.43). For every 10 ppb increase in O3, there is a 2.21% (95%CI: 0.59; 3.83) increase in the risk of all-cause mortality for the group of all people between 46 and 65 years old, and a 3.53% (95%CI: 0.34; 6.72) increase in the risk of circulatory mortality for the group of women, all ages. For every 10 ppb increase in NO2, the risk of respiratory mortality increases by 17.56% (95%CI: 4.44; 30.64) and the risk of all-cause mortality by 5.63% (95%CI: 1.83; 9.44). The results of our study provide epidemiological evidence that air pollution is associated with a higher risk of cardiorespiratory mortality in Brazil. Given the lack of nationwide studies on air pollution in Brazil, our research is an important contribution to the local and international literature that can provide better support to policymakers to improve air quality and public health
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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