Background: The number of meteoropaths, or people negatively affected by weather conditions, is rising dramatically. Meteoropathy is developing rapidly due to ever poorer adaptations of people to changes in weather conditions. Strong weather stimuli may not only exacerbate symptoms in people with diseases of the cardiovascular and respiratory systems but may also induce aggressive behavior. Researchers have shown that patients suffering from mental illnesses are most vulnerable to changes in the weather and postulate a connection between the seasons and aggressive behavior.
Methods: The goal of the study was to analyze the relationship between coercive measures and weather factors. The researchers identified what meteorological conditions prevailed on days with an increased number of incidents of aggressive behavior leading to the use of physical coercion towards patients in a psychiatric hospital in Poland. In order to determine the impact of weather conditions on the frequency at which physical coercion measures were used, the hospital’s “coercion sheets” from 1 January 2015 to 31 March 2017 were analyzed.
The data were correlated with meteorological data. In order to determine the relationship between the occurrence of specific weather conditions and the number of coercive interventions (N), researchers utilized Spearman’s rank correlation analysis together with two-dimensional scatter diagrams (dependency models), multiple regression, stepwise regression, frequencies, and conditional probability (%).
Results: Lower barometric pressure and foehn wind increased aggressive behavior in patients that led to coercive measures. For temperature (positive correlation) and humidity (negative correlation), there was a poor but Gentaur Barometric, Humidity & Temperature Monitoring statistically significant correlation. Conclusions: Monitoring weather conditions might be useful in predicting and preventing aggression by patients who are susceptible to weather changes.
Effects of climate and air pollution factors on outpatient visits for eczema: a time series analysis
Eczema resulting from external and internal factors accounts for the biggest global burden of disability owing to skin disease. This study aimed to determine an association between environmental factors and outpatient clinic visits for eczema. We collected data on dermatology clinic outpatient visits for eczema between January 2013 and July 2019. Data concerning environmental factors during this period were collated using national air quality network and air monitoring measurement parameters, namely barometric pressure, relative humidity, air temperature, and air pollutant concentrations, such as sulfur dioxide (SO2) and particulate matter (PM10).
- A distributed lag nonlinear model was used to investigate the relationship among eczema, environmental factors, and lagged effects. In total, 27,549 outpatient visits for eczema were recorded.
- In both single-factor and multiple-factor lag models, the effects of a 10-µg/m3 increase in PM10 and SO2 values had significantly positive effects on the number of daily outpatient visits over a total 5 days of lag after adjusting for temperature, the number of daily outpatient visits increased with 0.87%, 7.65% and 0.69%, 5.34%, respectively. Relative humidity (RR = 1.3870, 95% CI 1.3117-1.4665) and pressure (RR = 1.0394, 95% CI 1.0071-1.0727) had significantly positive effects on the number of daily outpatients in single-factor lag models.
- However, temperature had a significantly negative effect on them in the number of daily outpatients (RR = 0.9686, 95% CI 0.9556-0.9819). Exposure to air pollution exacerbated eczema. Outpatient visits for eczema were found to have strong positive associations with changes in PM10 levels.
Characteristics of PM2.5 Concentrations across Beijing during 2013-2015.
High concentrations of particulate matter (PM2.5) and frequent air pollution episodes in Beijing have attracted widespread attention. This paper utilizes data from the new air pollution network in China to examine the current spatial and temporal variability of PM2.5 at 12 monitoring sites in Beijing over a recent 2-year period (April 2013) to March 2015). The long term (2-year) average concentration was 83 µg·m-3, well above Chinese and international standards. Across the region, annual average concentrations varied by 20 µg·m-3 (25% of the average level), with lower levels in suburban areas compared to periurban and urban areas, which had similar concentrations.
The spatial variation in PM2.5 concentrations was associated with several land use and economic variables, including the fraction of vegetated land and building construction activity, which together explained 71% of the spatial variation. Daily air quality was characterized as “polluted” (above 75 µg·m-3) on 36 to 47% of days, depending on site. There were 77 pollution episodes during the study period (defined as two or more consecutive days with Beijing-wide 24-hour average concentrations over 75 µg·m-3), and 2 to 5 episodes occurred each month, including summer months.
The longest episode lasted 9 days and daily concentrations exceeded 450 µg·m-3. Daily PM2.5 levels were autocorrelated (rlag1 = 0.516) and associated with many meteorological variables, including barometric pressure, relative humidity, hours of sunshine, surface and ambient temperature, precipitation and scavenging coefficient, and wind direction.
Parsimonious models with meteorological and autoregressive terms explained over 60% of the variation in daily PM2.5 levels. The first autoregressive term and hours of sunshine were the most important variables in these models, however, the latter variable is PM2.5-dependent and thus not an explanatory variable. The present study can serve as a baseline to compare the improved air quality in Beijing expected in future years.
Sprint Running Performance Monitoring: Methodological and Practical Considerations.
The aim of this review is to investigate methodological concerns associated with sprint performance monitoring, more specifically the influence and magnitude of varying external conditions, technology and monitoring methodologies not directly related to human physiology. The combination of different starting procedures and triggering devices can cause up to very large time differences, which may be many times greater than performance changes caused by years of conditioning. Wind, altitude, temperature, barometric pressure and humidity can all combine to yield moderate time differences over short sprints.
Sprint performance can also be affected by the athlete’s clothing, principally by its weight rather than its aerodynamic properties. On level surfaces, the track compliance must change dramatically before performance changes larger than typical variation can be detected. An optimal shoe bending stiffness can enhance performance by a small margin. Fully automatic timing systems, dual-beamed photocells, laser guns and high-speed video are the most accurate tools for sprint performance monitoring.
Manual timing and single-beamed photocells should be avoided over short sprint distances (10-20 m) because of large absolute errors. The validity of today’s global positioning systems (GPS) technology is satisfactory for long distances (>30 m) and maximal velocity in team sports, but multiple observations are still needed as reliability is questionable.
Based on different approaches used to estimate the smallest worthwhile performance change and the typical error of sprint measures, we have provided an assessment of the usefulness of speed evaluation from 5 to 40 m. Finally, we provide statistical guidelines to accurately assess changes in individual performance; i.e. considering both the smallest worthwhile change in performance and the typical error of measurement, which can be reduced while repeating the number of trials.
NBS Humidity Monitor - EACH |
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Gentodenz |
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Recombinant Cibotium barometz Ribulose bisphosphate carboxylase large chain (rbcL) |
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Recombinant Cibotium barometz Ribulose bisphosphate carboxylase large chain (rbcL) |
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1-Step Polymorphs, Human Cell Separation |
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GMP Recombinant Human Interleukin-4 (IL-4) |
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Rye Agar A |
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Rye Agar B |
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Porcine Parvovirus Antibody Elisa Test Kit |
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QuantiChrom Hemoglobin Assay Kit |
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50ml TC Tubes, Conical, 440 units/box |
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