1000 resultados para Hot Tearing


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Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

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Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

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The transition of disc-like chromium hydroxide nanomaterials to chromium oxide nanomaterials has been studied by hot stage Raman spectroscopy. The structure and morphology of α-CrO(OH) synthesised using hydrothermal treatment was confirmed by X-ray diffraction and transmission electron microscopy. The Raman spectrum of α-CrO(OH) is characterised by two intense bands at 823 and 630 cm-1 attributed to ν1 CrIII-O symmetric stretching mode, bands at 1179 cm-1 attributed to CrIII-OH δ deformation modes. No bands are observed above 3000 cm-1. The absence of characteristic OH vibrational bands may be due to short hydrogen bonds in the α-CrO(OH) structure. Upon thermal treatment of α-CrO(OH), new Raman bands are observed at 599, 542, 513, 396, 344 and 304 cm-1, which are attributed to Cr2O3. This hot-stage Raman study shows that the transition of α-CrO(OH) to Cr2O3 occurs before 350 °C.

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Chromium oxide gel material was synthesised and appeared to be X-ray amorphous. The changes in the structure of the synthetic chromium oxide gel were investigated using hot-stage Raman spectroscopy based upon the results of thermogravimetric analysis. The thermally decomposed product of the synthetic chromium oxide gel in nitrogen atmosphere was confirmed to be crystalline Cr2O3 as determined by the hot-stage Raman spectra. Two bands were observed at 849 and 735 cm-1 in the Raman spectrum at 25 °C, which were attributed to the symmetric stretching modes of O-CrIII-OH and O-CrIII-O. With temperature increase, the intensity of the band at 849 cm-1 decreased, while the band at 735 cm-1 increased. These changes in intensity are attributed to the loss of OH groups and formation of O-CrIII-O units in the structure. A strongly hydrogen bonded water H-O-H bending band was found at 1704 cm-1 in the Raman spectrum of the chromium oxide gel, however this band shifted to around 1590 cm-1 due to destruction of the hydrogen bonds upon thermal treatment. Six new Raman bands were observed at 578, 540, 513, 390, 342 and 303 cm-1 attributed to the thermal decomposed product Cr2O3. The use of the hot-stage Raman microscope enabled low-temperature phase changes brought about through dehydration and dehydroxylation to be studied.

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This study used the Australian Environmental Health Risk Assessment Framework to assess the human health risk of dioxin exposure through foods for local residents in two wards of Bien Hoa City, Vietnam. These wards are known hot-spots for dioxin and a range of stakeholders from central government to local levels were involved in this process. Publications on dioxin characteristics and toxicity were reviewed and dioxin concentrations in local soil, mud, foods, milk and blood samples were used as data for this risk assessment. A food frequency survey of 400 randomly selected households in these wards was conducted to provide data for exposure assessment. Results showed that local residents who had consumed locally cultivated foods, especially fresh water fish and bottom-feeding fish, free-ranging chicken, duck, and beef were at a very high risk, with their daily dioxin intake far exceeding the tolerable daily intake recommended by the WHO. Based on the results of this assessment, a multifaceted risk management program was developed and has been recognized as the first public health program ever to have been implemented in Vietnam to reduce the risks of dioxin exposure at dioxin hot-spots.

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A brief travel article about Chile

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Background There are minimal reports of seasonal variations in chronic heart failure (CHF)-related morbidity and mortality beyond the northern hemisphere. Aims and methods We examined potential seasonal variations with respect to morbidity and all-cause mortality over more than a decade in a cohort of 2961 patients with CHF from a tertiary referral hospital in South Australia subject to mild winters and hot summers. Results Seasonal variation across all event-types was observed. CHF-related morbidity peaked in winter (July) and was lowest in summer (February): 70 (95% CI: 65 to 76) vs. 33 (95% CI: 30 to 37) admissions/1000 at risk (p<0.005). All-cause admissions (113 (95% CI: 107 to 120) vs. 73 (95% CI 68 to 79) admissions/1000 at risk, p<0.001) and concurrent respiratory disease (21% vs. 12%,p<0.001) were consistently higher in winter. 2010 patients died, mortality was highest in August relative to February: 23 (95% CI: 20 to 27) vs. 12 (95% CI: 10 to 15) deaths per 1000 at risk, p<0.001. Those aged 75 years or older were most at risk of seasonal variations in morbidity and mortality. Conclusion Seasonal variations in CHF-related morbidity and mortality occur in the hot climate of South Australia, suggesting that relative (rather than absolute) changes in temperature drive this global phenomenon.

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Extreme temperatures have been shown to have a detrimental effect on health. Hot temperatures can increase the risk of mortality, particularly in people suffering from cardiorespiratory diseases. Given the onset of climate change, it is critical that the impact of temperature on health is understood, so that effective public health strategies can correctly identify vulnerable groups within the population. However, while effects on mortality have been extensively studied, temperature–related morbidity has received less attention. This study applied a systematic review and meta–analysis to examine the current literature relating to hot temperatures and morbidity.

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The purpose of this article is to suggest a possible “meta” approach of the project management field—the unit of analysis—respectful of the various perspectives in existence, while providing an integrative ontological and epistemological framework. In order to do so, I first suggest what could be perceived as being the state of the field and its main constituting “school of thoughts.” Then I open the debate on what could be the ontological and epistemological perspectives enabling us to better take into account the diversity we face in considering the richness of the field. Based on these developments, I propose to address project management as a complex integrative knowledge field, which eventually will lead us to consider “modeling—developing specific convention—to do ingeniously” as acting and learning mode in the management of projects.

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In Strong v Woolworth Ltd (t/as Big W) (2012) 285 ALR 420 the appellant was injured when she fell at a shopping centre outside the respondent’s premises. The appellant was disabled, having had her right leg amputated above the knee and therefore walked with crutches. One of the crutches came into contact with a hot potato chip which was on the floor, causing the crutch to slip and the appellant to fall. The appellant sued in negligence, alleging that the respondent was in breach of its duty of care by failing to institute and maintain a cleaning system to detect spillages and foreign objects within its sidewalk sales area. The issue before the High Court was whether it could be established on the balance of probabilities as to when the hot chip had fallen onto the ground so as to prove causation in fact...

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ABSTRACT Objectives: To investigate the effect of hot and cold temperatures on ambulance attendances. Design: An ecological time series study. Setting and participants: The study was conducted in Brisbane, Australia. We collected information on 783 935 daily ambulance attendances, along with data of associated meteorological variables and air pollutants, for the period of 2000–2007. Outcome measures: The total number of ambulance attendances was examined, along with those related to cardiovascular, respiratory and other non-traumatic conditions. Generalised additive models were used to assess the relationship between daily mean temperature and the number of ambulance attendances. Results: There were statistically significant relationships between mean temperature and ambulance attendances for all categories. Acute heat effects were found with a 1.17% (95% CI: 0.86%, 1.48%) increase in total attendances for 1 °C increase above threshold (0–1 days lag). Cold effects were delayed and longer lasting with a 1.30% (0.87%, 1.73%) increase in total attendances for a 1 °C decrease below the threshold (2–15 days lag). Harvesting was observed following initial acute periods of heat effects, but not for cold effects. Conclusions: This study shows that both hot and cold temperatures led to increases in ambulance attendances for different medical conditions. Our findings support the notion that ambulance attendance records are a valid and timely source of data for use in the development of local weather/health early warning systems.

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Objectives: To investigate the effect of hot and cold temperatures on ambulance attendances. Design: An ecological time series study. Setting and participants: The study was conducted in Brisbane, Australia. We collected information on 783 935 daily ambulance attendances, along with data of associated meteorological variables and air pollutants, for the period of 2000–2007. Outcome measures: The total number of ambulance attendances was examined, along with those related to cardiovascular, respiratory and other non-traumatic conditions. Generalised additive models were used to assess the relationship between daily mean temperature and the number of ambulance attendances. Results: There were statistically significant relationships between mean temperature and ambulance attendances for all categories. Acute heat effects were found with a 1.17% (95% CI: 0.86%, 1.48%) increase in total attendances for 1 °C increase above threshold (0–1 days lag). Cold effects were delayed and longer lasting with a 1.30% (0.87%, 1.73%) increase in total attendances for a 1 °C decrease below the threshold (2–15 days lag). Harvesting was observed following initial acute periods of heat effects, but not for cold effects. Conclusions: This study shows that both hot and cold temperatures led to increases in ambulance attendances for different medical conditions. Our findings support the notion that ambulance attendance records are a valid and timely source of data for use in the development of local weather/health early warning systems.

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This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.