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1.
JMIR Mhealth Uhealth ; 10(9): e39532, 2022 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-36083624

RESUMO

BACKGROUND: Although climate change is one of the biggest global health threats, individual-level and short-term data on direct exposure and health impacts are still scarce. Wearable electronic devices (wearables) present a potential solution to this research gap. Wearables have become widely accepted in various areas of health research for ecological momentary assessment, and some studies have used wearables in the field of climate change and health. However, these studies vary in study design, demographics, and outcome variables, and existing research has not been mapped. OBJECTIVE: In this review, we aimed to map existing research on wearables used to detect direct health impacts and individual exposure during climate change-induced weather extremes, such as heat waves or wildfires. METHODS: We conducted a scoping review according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework and systematically searched 6 databases (PubMed [MEDLINE], IEEE Xplore, CINAHL [EBSCOhost], WoS, Scopus, Ovid [MEDLINE], and Google Scholar). The search yielded 1871 results. Abstracts and full texts were screened by 2 reviewers (MK and IM) independently using the inclusion and exclusion criteria. The inclusion criteria comprised studies published since 2010 that used off-the-shelf wearables that were neither invasive nor obtrusive to the user in the setting of climate change-related weather extremes. Data were charted using a structured form, and the study outcomes were narratively synthesized. RESULTS: The review included 55,284 study participants using wearables in 53 studies. Most studies were conducted in upper-middle-income and high-income countries (50/53, 94%) in urban environments (25/53, 47%) or in a climatic chamber (19/53, 36%) and assessed the health effects of heat exposure (52/53, 98%). The majority reported adverse health effects of heat exposure on sleep, physical activity, and heart rate. The remaining studies assessed occupational heat stress or compared individual- and area-level heat exposure. In total, 26% (14/53) of studies determined that all examined wearables were valid and reliable for measuring health parameters during heat exposure when compared with standard methods. CONCLUSIONS: Wearables have been used successfully in large-scale research to measure the health implications of climate change-related weather extremes. More research is needed in low-income countries and vulnerable populations with pre-existing conditions. In addition, further research could focus on the health impacts of other climate change-related conditions and the effectiveness of adaptation measures at the individual level to such weather extremes.


Assuntos
Mudança Climática , Dispositivos Eletrônicos Vestíveis , Exercício Físico , Humanos , Sono , Tempo (Meteorologia)
2.
Radiat Prot Dosimetry ; 198(13-15): 938-942, 2022 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-36083741

RESUMO

The radiation dose rate from radionuclides released by the spent nuclear fuel reprocessing plant in Rokkasho, Japan, was assessed for a year specified in the safety review during which the weather conditions were not significantly different from those of the other 10 y. However, the actual year-by-year variation in annual radiation dose rate was not examined. A model system for evaluating the dose rate from the radionuclides released into the atmosphere was constructed. In this study, the radiation dose rate in the weather conditions of 24 weather bins was estimated for a standard year by the model. The annual maximum dose rate from 1959 to 2012 was estimated using a simplified method that integrated the dose rates of each weather bin in the standard year by estimating the annual frequency of the bin in the target year. We obtained ~1.3 as the maximum/minimum ratio of the annual maximum dose rate.


Assuntos
Doses de Radiação , Monitoramento de Radiação , Humanos , Radioisótopos do Iodo/análise , Japão , Monitoramento de Radiação/métodos , Tempo (Meteorologia)
3.
PLoS One ; 17(9): e0271373, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36048836

RESUMO

Globally, 21 percent of young women are married before their 18th birthday. Despite some progress in addressing child marriage, it remains a widespread practice, in particular in South Asia. While household predictors of child marriage have been studied extensively in the literature, the evidence base on macro-economic factors contributing to child marriage and models that predict where child marriage cases are most likely to occur remains limited. In this paper we aim to fill this gap and explore region-level indicators to predict the persistence of child marriage in four countries in South Asia, namely Bangladesh, India, Nepal and Pakistan. We apply machine learning techniques to child marriage data and develop a prediction model that relies largely on regional and local inputs such as droughts, floods, population growth and nightlight data to model the incidence of child marriages. We find that our gradient boosting model is able to identify a large proportion of the true child marriage cases and correctly classifies 77% of the true marriage cases, with a higher accuracy in Bangladesh (92% of the cases) and a lower accuracy in Nepal (70% of cases). In addition, all countries contain in their top 10 variables for classification nighttime light growth, a shock index of drought over the previous and the last two years and the regional level of education, suggesting that income shocks, regional economic activity and regional education levels play a significant role in predicting child marriage. Given the accuracy of the model to predict child marriage, our model is a valuable tool to support policy design in countries where household-level data remains limited.


Assuntos
Desenvolvimento Econômico , Casamento , Bangladesh , Criança , Países em Desenvolvimento , Economia , Feminino , Humanos , Aprendizado de Máquina , Fatores Socioeconômicos , Tempo (Meteorologia)
4.
Int J Mol Sci ; 23(17)2022 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-36077328

RESUMO

Magnetorheological elastomer (MRE) materials have the potential to be used in a wide range of applications that require long-term service in hostile environments. These widespread applications will result in the emergence of MRE-specific durability issues, where durability refers to performance under in-service environmental conditions. In response, the outdoor tropical climatic environment, combined with the effects of weathering, will be the primary focus of this paper, specifically the photodegradation of the MRE. In this study, MRE made of silicone rubber (SR) and 70 wt% micron-sized carbonyl iron particles (CIP) were prepared and subjected to mechanical and rheological testing to evaluate the effects under natural weathering. Magnetorheological elastomer samples were exposed to the natural weathering conditions of a tropical climate in Kuala Lumpur, Malaysia, for 30 days. To obtain a comprehensive view of MRE degradation during natural weathering, mechanical testing, rheology, and morphological evaluation were all performed. The mechanical and rheological properties test results revealed that after 30 days of exposure and known meteorological parameters, Young's modulus and storage modulus increased, while elongation at break decreased. The degradation processes of MRE during weathering, which are responsible for their undesirable change, were given special attention. With the help of morphological evidence, the relationship between these phenomena and the viscoelastic properties of MRE was comprehensively defined and discussed.


Assuntos
Elastômeros , Clima Tropical , Reologia , Elastômeros de Silicone , Tempo (Meteorologia)
5.
Artigo em Inglês | MEDLINE | ID: mdl-36078547

RESUMO

Psychiatric patients are particularly vulnerable to strong weather stimuli, such as foehn, a hot wind that occurs in the alps. However, there is a dearth of research regarding its impact on mental health. This study investigated the impact of foehn wind among patients of a psychiatric hospital located in a foehn area in the Swiss Alps. Analysis was based on anonymized datasets obtained from routine records on admission and discharge, including the Brief Symptom Checklist (BSCL) questionnaire, as well as sociodemographic parameters (age, sex, and diagnosis). Between 2013 and 2020, a total of 10,456 admission days and 10,575 discharge days were recorded. All meteorological data were extracted from the database of the Federal Office of Meteorology and Climatology of Switzerland. We estimated the effect of foehn on the BSCL items using a distributed lag model. Significant differences were found between foehn and non-foehn admissions in obsession-compulsion, interpersonal sensitivity, depression, anxiety, phobic anxiety, paranoid ideation, and general severity index (GSI) (p < 0.05). Our findings suggest that foehn wind events may negatively affect specific mental health parameters in patients. More research is needed to fully understand the impact of foehn's events on mental health.


Assuntos
Hospitais Psiquiátricos , Vento , Humanos , Meteorologia , Suíça/epidemiologia , Tempo (Meteorologia)
6.
Environ Monit Assess ; 194(10): 722, 2022 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-36056971

RESUMO

A physiographic-based multilinear regression model supported by GIS was developed to estimate spatial rainfall variability in the Southwest Iberian Peninsula. The area study includes a wide diversity of landscape features and comprises four Portuguese regions and one Spanish province (totalizing 28,860 km2). The region suffers a very strong Mediterranean influence, with a major cleavage between winter and summer seasons. Thus, the analysis was carried out separately for the wet (October to March) and dry (April to September) semesters. From an initial set of 10 explanatory physiographic variables, five were selected to be used in the multilinear regression, as they allowed generating models by map algebra that fitted well with the last 40 years of monthly rainfall data records. These records were obtained from 163 weather stations, filtered from an initial set of 230 (142 stations in Portugal and 88 in Spain). The correlation between the physiographic-based multilinear regression model and a model obtained by interpolation from rainfall historical data showed to be good or very good in approximately 75% of the area under study. Results show that physiographic-based models can be effectively used to estimate rainfall where there is a lack of rain gauges, or to densify spatial resolution of rainfall between rain gauges.


Assuntos
Monitoramento Ambiental , Chuva , Estações do Ano , Espanha , Tempo (Meteorologia)
7.
Ying Yong Sheng Tai Xue Bao ; 33(9): 2557-2562, 2022 Sep.
Artigo em Chinês | MEDLINE | ID: mdl-36131673

RESUMO

We observed behavior response of overwintering Aythya baeri to different weather conditions by using fixed point-based observation and scanning sampling methods, at Henan Minquan National Wetland Park during November to December 2018. The results showed that, on sunny days, the dominant behaviors of A. baeri were resting, flying, and locomotion (65.5%), the second were foraging and maintaining (31.9%). The daily behavioral rhythm was foraging in the morning, resting at noon, and foraging and maintain in the afternoon. The flying usually occurred before the peak of foraging. The locomotion behavior was mostly accompanied by other behaviors, which positively associated with foraging and negatively correlated with resting. A. baeri increased resting and foraging in rainy days compared with that in sunny days. The dominant behaviors were resting, foraging and locomotion (76.5%), and maintaining and flying were the secondary (20.3%). The peaks of foraging and resting postponed to the evening, while the flying and maintaining were significantly decreased. Compared with the sunny days, the resting, foraging, locomotion and maintaining behaviors were increased in mist days, and flying was decreased. The peak of foraging delayed to the noon and afternoon, and that of resting postponed to the afternoon. The dominant behaviors were resting, locomotion and foraging (70.6%), while maintaining and flying behavior were the secondary (27.5%). In summary, there are variations in time allocation of A. baeri behaviors, activity rhythm and dominant behaviors due to the change of weather conditions during wintering. To overcome the bad weather conditions in rainy and mist days, A. baeri would allocate more time on foraging for increasing energy intake, and more resting time for reducing energy consumption.


Assuntos
Comportamento Animal , Tempo (Meteorologia) , Animais , Estações do Ano , Luz Solar
8.
Lancet Planet Health ; 6(9): e714-e725, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-36087602

RESUMO

BACKGROUND: A link between weather and aggression in the offline world has been established across a variety of societal settings. Simultaneously, the rapid digitalisation of nearly every aspect of everyday life has led to a high frequency of interpersonal conflicts online. Hate speech online has become a prevalent problem that has been shown to aggravate mental health conditions, especially among young people and marginalised groups. We examine the effect of temperature on the occurrence of hate speech on the social media platform Twitter and interpret the results in the context of the interlinkage between climate change, human behaviour, and mental health. METHODS: In this quantitative empirical study, we used a supervised machine learning approach to identify hate speech in a dataset containing around 4 billion geolocated tweets from 773 cities across the USA between May 1, 2014 and May 1, 2020. We statistically evaluated the changes in daily hate tweets against changes in local temperature, isolating the temperature influence from confounding factors using binned panel-regression models. FINDINGS: The prevalence of hate tweets was lowest at moderate temperatures (12 to 21°C) and marked increases in the number of hate tweets were observed at hotter and colder temperatures, reaching up to 12·5% (95% CI 8·0-16·5) for cold temperature extremes (-6 to -3°C) and up to 22·0% (95% CI 20·5-23·5) for hot temperature extremes (42 to 45°C). Outside of the moderate temperature range, the hate tweets also increased as a proportion of total tweeting activity. The quasi-quadratic shape of the temperature-hate tweet curve was robust across varying climate zones, income quartiles, religious and political beliefs, and both city-level and state-level aggregations. However, temperature ranges with the lowest prevalence of hate tweets were centred around the local temperature mean and the magnitude of the increases in hate tweets for hot and cold temperatures varied across the climate zones. INTERPRETATION: Our results highlight hate speech online as a potential channel through which temperature alters interpersonal conflict and societal aggression. We provide empirical evidence that hot and cold temperatures can aggravate aggressive tendencies online. The prevalence of the results across climatic and socioeconomic subgroups points to limitations in the ability of humans to adapt to temperature extremes. FUNDING: Volkswagen Foundation.


Assuntos
Ódio , Mídias Sociais , Adolescente , Humanos , Fala , Temperatura , Tempo (Meteorologia)
9.
Nat Commun ; 13(1): 5145, 2022 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-36050311

RESUMO

Existing weather forecasting models are based on physics and use supercomputers to evolve the atmosphere into the future. Better physics-based forecasts require improved atmospheric models, which can be difficult to discover and develop, or increasing the resolution underlying the simulation, which can be computationally prohibitive. An emerging class of weather models based on neural networks overcome these limitations by learning the required transformations from data instead of relying on hand-coded physics and by running efficiently in parallel. Here we present a neural network capable of predicting precipitation at a high resolution up to 12 h ahead. The model predicts raw precipitation targets and outperforms for up to 12 h of lead time state-of-the-art physics-based models currently operating in the Continental United States. The results represent a substantial step towards validating the new class of neural weather models.


Assuntos
Aprendizado Profundo , Simulação por Computador , Previsões , Redes Neurais de Computação , Tempo (Meteorologia)
10.
J R Soc Interface ; 19(193): 20220361, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-36000226

RESUMO

UK grasslands perform important environmental and economic functions, but their future productivity under climate change is uncertain. Spring hay yields from 1902 to 2016 at one site (the Park Grass Long Term Experiment) in southern England under four different fertilizer regimes were modelled in response to weather (seasonal temperature and rainfall). The modelling approach applied comprised: (1) a Bayesian model comparison to model parametrically the heteroskedasticity in a gamma likelihood function; (2) a Bayesian varying intercept multiple regression model with an autoregressive lag one process (to incorporate the effect of productivity in the previous year) of the response of hay yield to weather from 1902 to 2016. The model confirmed that warmer and drier years, specifically, autumn, winter and spring, in the twentieth and twenty-first centuries reduced yield. The model was applied to forecast future spring hay yields at Park Grass under different climate change scenarios (HadGEM2 and GISS RCP 4.5 and 8.5). This application indicated that yields are forecast to decline further between 2020 and 2080, by as much as 48-50%. These projections are specific to Park Grass, but implied a severe reduction in grassland productivity in southern England with climate change during the twenty-first century.


Assuntos
Mudança Climática , Poaceae , Teorema de Bayes , Poaceae/fisiologia , Estações do Ano , Tempo (Meteorologia)
12.
J Dairy Sci ; 105(10): 8298-8315, 2022 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-35940919

RESUMO

Dairy cows are motivated to access dry lying surfaces and will seek protection from wind and rain, but winter conditions may limit these opportunities when cows are managed outdoors. The primary aim of this observational study was to determine the effects of weather and paddock soil conditions on lying behavior of dairy cows managed outdoors during winter and fed crop in situ, a practice occurring in New Zealand with year-round grazing of dairy cows. A secondary aim was to characterize eating and ruminating behaviors during winter weather and paddock soil conditions. Four groups (99 nonlactating, pregnant cows each) were managed on 4 outdoor paddock areas on the same farm; the groups were fed pasture silage and grazed either kale (2 groups) or fodder beet (2 groups). Behaviors were recorded using validated leg-based (lying behavior) and ear-based (eating and ruminating time) accelerometers on 30 focal cows in each group over 32 d. Soil depth and wetness were scored daily at 25 points along 4 transects within each paddock area using recognized technical measures (penetrometer, soil volumetric water content), which were compared with practical tools for farmer use (ruler, moisture meter, percentage of sites in paddock scored as dry, wet, sodden, or with surface water pooling). Rainfall occurred most days during the study (mean 1.6 mm/d; maximum 12.2 mm/d), resulting in wet and muddy paddocks (mud depth with ruler: mean 6 cm, maximum 18 cm; paddock sites scored as wet or sodden: mean 34%, maximum 100%; paddock sites with surface water pooling: mean 27%, maximum 100%). Group lying time was 9.6 ± 2.3 h/d (mean ± standard deviation); however, 21% of cows consistently lay less than 8 h/d (to a minimum of 4.9 h/d). A mixed regression model tested the effects of daily weather and paddock soil conditions on daily lying time, with group as the observational unit, day as repeated measure, crop type as a fixed effect, crop type interactions with explanatory variables, and random intercepts of group and paddock within group. Lying time was less on the day of and day after rainfall (24 and 29 min/d less for 1 mm increase in rainfall, respectively). Two days after rainfall, lying time rebounded to about 1 h longer than before the rainfall. On the day after the heaviest rainfall event, group average lying time was only 2.5 ± 1.9 h/d (mean ± standard deviation); in 2 groups, 30% and 38% of cows, respectively, did not lie down at all for 24 h. Lying time decreased with deteriorating paddock soil conditions, especially with increasing surface water pooling, suggesting that this may be a useful measure to estimate the quality of the lying surface. Descriptively, ruminating time appeared to decrease with increased surface water pooling, possibly due to decreased lying time. Our results demonstrated that dairy cows could experience periods of short or no lying time during inclement weather and muddy paddock soil conditions. Prior rainfall and surface water pooling may be useful measures to determine if lying time, and thus animal welfare, are compromised.


Assuntos
Indústria de Laticínios , Solo , Animais , Comportamento Animal , Bovinos , Indústria de Laticínios/métodos , Feminino , Lactação , Gravidez , Água , Tempo (Meteorologia)
13.
Water Res ; 223: 118968, 2022 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-35988331

RESUMO

Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the "true" value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.


Assuntos
Metais Pesados , Praguicidas , Hidrocarbonetos Policíclicos Aromáticos , Poluentes Químicos da Água , Monitoramento Ambiental , Metais Pesados/análise , Praguicidas/análise , Preparações Farmacêuticas , Hidrocarbonetos Policíclicos Aromáticos/análise , Chuva , Água/análise , Poluentes Químicos da Água/análise , Tempo (Meteorologia)
14.
Ann Glob Health ; 88(1): 63, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35974983

RESUMO

Caribbean small island developing states are highly exposed to climate change impacts. Incorporating weather and climate information into public health decisions can promote resilience to climate change's adverse health effects, but regionally it is not common practice. We implemented a project to enhance dialogue between climate and public health specialists in Puerto Rico and Dominica. First, we conducted environmental scans of public health vulnerability in the context of weather and climate for both islands. Then, we convened stakeholders to discuss the scan results and identify priorities for climate and health. A shared priority was increasing climate and health knowledge; thus, we developed several educational initiatives. In this viewpoint, we discuss our process for conducting environmental scans, building capacity and partnerships, and translating knowledge-to-action around climate and health.


Assuntos
Mudança Climática , Saúde Pública , Dominica , Humanos , Porto Rico , Tempo (Meteorologia)
15.
Proc Natl Acad Sci U S A ; 119(35): e2207889119, 2022 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-35994640

RESUMO

Since about 1980, the tropical Pacific has been anomalously cold, while the broader tropics have warmed. This has caused anomalous weather in midlatitudes as well as a reduction in the apparent sensitivity of the climate associated with enhanced low-cloud abundance over the cooler waters of the eastern tropical Pacific. Recent modeling work has shown that cooler temperatures over the Southern Ocean around Antarctica can lead to cooler temperatures over the eastern tropical Pacific. Here we suggest that surface wind anomalies associated with the Antarctic ozone hole can cause cooler temperatures over the Southern Ocean that extend into the tropics. We use the short-term variability of the Southern Annular Mode of zonal wind variability to show an association between surface zonal wind variations over the Southern Ocean, cooling over the Southern Ocean, and cooling in the eastern tropical Pacific. This suggests that the cooling of the eastern tropical Pacific may be associated with the onset of the Antarctic ozone hole.


Assuntos
Mudança Climática , Clima , Perda de Ozônio , Regiões Antárticas , Temperatura Baixa , Ozônio/análise , Oceano Pacífico , Temperatura , Tempo (Meteorologia) , Vento
16.
Artigo em Inglês | MEDLINE | ID: mdl-35954843

RESUMO

By using the convection-resolving weather research and forecasting simulation, a convective rainfall event over the middle portions of the eastern foothills of the Taihang Mountains in North China is investigated in this study. The influences of the cold front and complex topography on the initiation and maintenance of the convective system are analyzed. Results show two reasons why the convective clusters are initiated near noon on the hillsides at an elevation of 800 m. First, a local topographic convergence zone usually appears on the eastern slope of the Taihang Mountains near noon in May. Second, such a topographic convergence zone is enhanced by a cold front system and then triggers the convective clusters. Subsequently, the convective cells strengthen when moving downslope and weaken when moving eastward on the plain. When moving downslope, the atmospheric stratification is convectively unstable, and the mountain-plains solenoid (MPS) is strong near the foot of the mountain. The large amount of water vapor carried by the MPS-induced easterly wind is forced to ascend by topographic obstructions, and therefore the convective cells develop. As a result, heavy rainfall occurs on the hillsides with an elevation of 200-600 m. When the convective cells move eastward on the plain, the atmospheric stratification is stable, and the MPS is weak. Thus, convective activities weaken. Moreover, the results reveal that the mesoscale convergence line, slope gradient and slope aspect of the local terrain, local atmospheric instability, and the MPS play different roles in maintaining the convective system at elevations of 200-600 m along the eastern foothills of the Taihang Mountains.


Assuntos
Tempo (Meteorologia) , Vento , China , Temperatura Baixa
17.
Artigo em Inglês | MEDLINE | ID: mdl-35955016

RESUMO

PURPOSE: To evaluate the impact of high-temperature environments on bus drivers' physiology and reaction times, and to provide a basis for driver occupational health management. METHODS: The physiological and reaction indexes of 24 bus drivers under different temperatures were investigated. The statistical analysis method was used to analyze the changes in drivers' physiological stress, the relationship between stress and response ability, and a safe driving time. The Kaplan-Meier survival function was used to analyze the survival rate of bus drivers under different temperatures and driving times. RESULTS: The results showed that body temperature, heart rate, physiological strain index (PSI), and reaction ability were significantly different among different compartment temperatures. PSI was positively correlated with reaction ability. The safe driving time was 80 min, 73 min, and 53 min, respectively, at 32 °C, 36 °C, and 40 °C. The survival rate decreased to less than 60% at 36 °C when driving continuously for 73 min; it decreased to 20% at 40 °C when driving for 53 min, and it was 0 for 75 min. CONCLUSIONS: High-temperature environments lead to heat stress of bus drivers, physiological indexes have changed significantly, and behavioral ability is also decreased. The higher the temperature, the lower the survival rate. Improvement measures can be taken from the aspects of convection, conduction, and behavior to ensure the bus driver's physiological health and driving safety under high temperatures and to improve the survival rate.


Assuntos
Condução de Veículo , Saúde do Trabalhador , Acidentes de Trânsito , Tempo de Reação , Tempo (Meteorologia)
18.
PLoS One ; 17(8): e0270356, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35980969

RESUMO

In recent years, small objects detection has received extensive attention from scholars for its important value in application. Some effective methods for small objects detection have been proposed. However, the data collected in real scenes are often foggy images, so the models trained with these methods are difficult to extract discriminative object features from such images. In addition, the existing small objects detection algorithms ignore the texture information and high-level semantic information of tiny objects, which limits the improvement of detection performance. Aiming at the above problems, this paper proposes a texture and semantic integrated small objects detection in foggy scenes. The algorithm focuses on extracting discriminative features unaffected by the environment, and obtaining texture information and high-level semantic information of small objects. Specifically, considering the adverse impact of foggy images on recognition performance, a knowledge guidance module is designed, and the discriminative features extracted from clear images by the model are used to guide the network to learn foggy images. Second, the features of high-resolution images and low-resolution images are extracted, and the adversarial learning method is adopted to train the model to give the network the ability to obtain the texture information of tiny objects from low-resolution images. Finally, an attention mechanism is constructed between feature maps of the same scale and different scales to further enrich the high-level semantic information of small objects. A large number of experiments have been conducted on data sets such as "Cityscape to Foggy" and "CoCo". The mean prediction accuracy (mAP) has reached 46.2% on "Cityscape to Fogg", and 33.3% on "CoCo", which fully proves the effectiveness and superiority of the proposed method.


Assuntos
Algoritmos , Semântica , Terapia Comportamental , Conhecimento , Tempo (Meteorologia)
19.
Vet Parasitol ; 309: 109770, 2022 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-35921740

RESUMO

Outbreaks of cattle lungworm disease (Dictyocaulus viviparus) are explosive and costly. The unpredictability of the disease often encourages farmers to apply blanket anthelmintic treatments to the herd, which impede the acquisition of immunity, increase the risk of drug resistance, and interfere with efforts to reduce anthelmintic use against ubiquitous gastrointestinal nematodes. Improving our understanding of the factors which lead to a high risk of infection with lungworm, (including climatic pressure), would support a more targeted management. We present GLOWORM-FL-DV, the first mathematical model of the free-living stages of D. viviparus. The ecology of D. viviparus is unique compared with other strongylid nematodes due to its relationship with Pilobilus spp. fungi, which enhance the transmission potential. The role of the fungi was therefore incorporated into the model framework, informed by laboratory observations of Pilobolus spp. development and sporulation. The thermal niche of D. viviparus was characterised based on published and laboratory observations. Mortality of parasitic larvae increased significantly below 0oC, and larval development occurred above 1.4oC, whereas the estimated minimum temperature for migration via Pilobolus spp. was 8.8oC. Model predictions were compared with antibody levels in bulk milk tank samples collected at two-weekly intervals from eight dairy herds across Great Britain over two grazing seasons. The model predicted high levels of larval abundance on pasture 46 days (38-52 days) before a rise in antibody levels and 22-26 days before the onset of clinical signs. The model assesses the impact of climate and weather on lungworm larval availability at pasture and provides a framework for the development of a risk forecasting system. This could help to focus vigilance for clinical signs at high-risk times and facilitate the targeted use of anthelmintics to prevent outbreaks, in support of sustainable parasite control.


Assuntos
Doenças dos Bovinos , Clima , Infecções por Dictyocaulus , Modelos Teóricos , Animais , Bovinos , Doenças dos Bovinos/parasitologia , Dictyocaulus , Infecções por Dictyocaulus/epidemiologia , Infecções por Dictyocaulus/parasitologia , Fezes/parasitologia , Fungos , Larva , Estações do Ano , Tempo (Meteorologia)
20.
PLoS One ; 17(8): e0271904, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35984856

RESUMO

Research on the occurrence and the final size of wildland fires typically models these two events as two separate processes. In this work, we develop and apply a compound process framework for jointly modelling the frequency and the severity of wildland fires. Separate modelling structures for the frequency and the size of fires are linked through a shared random effect. This allows us to fit an appropriate model for frequency and an appropriate model for size of fires while still having a method to estimate the direction and strength of the relationship (e.g., whether days with more fires are associated with days with large fires). The joint estimation of this random effect shares information between the models without assuming a causal structure. We explore spatial and temporal autocorrelation of the random effects to identify additional variation not explained by the inclusion of weather related covariates. The dependence between frequency and size of lightning-caused fires is found to be negative, indicating that an increase in the number of expected fires is associated with a decrease in the expected size of those fires, possibly due to the rainy conditions necessary for an increase in lightning. Person-caused fires were found to be positively dependent, possibly due to dry weather increasing human activity as well as the amount of dry few. For a test for independence, we perform a power study and find that simply checking whether zero is in the credible interval of the posterior of the linking parameter is as powerful as more complicated tests.


Assuntos
Incêndios , Relâmpago , Incêndios Florestais , Atividades Humanas , Humanos , Tempo (Meteorologia)
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