sunshine duration
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AIM: To investigate fluctuation of intraocular pressure (IOP) and seasonal variation of 24-hour IOP during one year in healthy participants METHODS: Totally 13 young healthy volunteers participated in this study. IOP was measured with Canon TX-20 at about 8:00-9:00 a.m. from Monday to Friday every week for a whole year. They also underwent 24-hour IOP examination every three months. Blood pressure, heart rate, temperature, humidity, atmosphere pressure, sunshine duration and other environment parameters were recorded. RESULTS: The yearly fluctuation curve showed IOP in the summer months were lower than other seasons. In the multivariable generalized estimating equation analysis, IOP had a negative correlation with both temperature and sunshine duration (P<0.05). There also was a seasonal effect on 24-hour IOP. However, all intraclass correlation coefficients values of minimum, maximum and average of the 24-hour IOP and each individual IOP were less than 0.30. CONCLUSION: IOP is trend to be higher in cold days than warm days. IOP have negative association with both environmental temperature and duration of sunshine. On a season-to-season basis, 24-hour IOP is not highly reproducible in healthy volunteers.

Thirty-year periods are treated in climatology as spans with relatively representative and stable climatic patterns, which can be used for calculating climate normals. Annual and seasonal series of circulation types were used to compare two 30-year sub-periods, 1961–1990 and 1991–2020, the second one being strongly influenced by recent global warming. This analysis was conducted according to the objective classification of circulation types and the climatic characteristics of sunshine duration, temperature, humidity, precipitation, and wind speed as calculated for the territory of the Czech Republic during the 1961–2020 period. For both sub-periods, their statistical characteristics were calculated, and the statistical significance of differences between them was evaluated. There was a statistically significant increase in the annual frequencies of anticyclonic circulation types and a significant decrease in cyclonic circulation types during 1991–2020 compared with 1961–1990. Generally, in both 30-year periods, significant differences in means, variability, characteristics of distribution, density functions, and linear trends appear for all climatic variables analysed except precipitation. This indicates that the recent 30-year “normal” period of 1991–2020, known to be influenced more by recent climate change, is by its climatic characteristics unrepresentative of the stable climatic patterns of previous 30-year periods.

Objective: This study aimed to investigate the possible association among vitamin D, screen time and other factors that might affect the concentration of vitamin D in children with autism spectrum disorder (ASD).Methods: In total, 306 children with ASD were recruited, and data, including their age, sex, height, weight, screen time, time of outdoor activity, ASD symptoms [including Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS) and Autism Diagnostic Observation Schedule–Second Edition (ADOS-2)] and vitamin D concentrations, were collected. A multiple linear regression model was used to analyze the factors related to the vitamin D concentration.Results: A multiple linear regression analysis showed that screen time (β = −0.122, P = 0.032), age (β = −0.233, P < 0.001), and blood collection month (reflecting sunshine duration) (β = 0.177, P = 0.004) were statistically significant. The vitamin D concentration in the children with ASD was negatively correlated with screen time and age and positively correlated with sunshine duration.Conclusion: The vitamin D levels in children with ASD are related to electronic screen time, age and sunshine duration. Since age and season are uncontrollable, identifying the length of screen time in children with ASD could provide a basis for the clinical management of their vitamin D nutritional status.

Abstract The objectives of this work carried out in the Central African Republic are to propose new correlations between the components of solar radiation and the sunshine duration on a horizontal surface on the ground, and then to make an evaluation of the solar potential in the cities of Bambari, Birao and Bangui. Polynomial regression models were used and their parameters were estimated by the ordinary least squares method. A statistical evaluation allowed us to compare the performance of the models. The best correlations are then used to estimate the global and diffuse radiation. In the city of Birao, the estimated global radiation is around 6 kWh/m2.j and the diffuse radiation around 2 kWh/m2.j ; in Bambari the global radiation is around 5.4 kWh/m2.j and the diffuse around 2.3 kWh/m2.j ; in Bangui the global radiation is around 5 kWh/m2.j and the diffuse radiation around 2.3 kWh/m2.j. The potential solar in all these regions is very favorable for small and large-scale solar photovoltaic applications.

BackgroundAccumulated researches revealed that both fine particulate matter (PM2.5) and sunlight exposure may be a risk factor for obesity, while researches regarding the potential effect modification by sunlight exposure on the relationship between PM2.5 and obesity are limited. We aim to investigate whether the effect of PM2.5 on obesity is affected by sunlight exposure among the general population in China.MethodsA sample of 47,204 adults in China was included. Obesity and abdominal obesity were assessed based on body mass index, waist circumference and waist-to-hip ratio, respectively. The five-year exposure to PM2.5 and sunlight were accessed using the multi-source satellite products and a geochemical transport model. The relationship between PM2.5, sunshine duration, and the obesity or abdominal obesity risk was evaluated using the general additive model.ResultsThe proportion of obesity and abdominal obesity was 12.6% and 26.8%, respectively. Levels of long-term PM2.5 ranged from 13.2 to 72.1 μg/m3 with the mean of 46.6 μg/m3. Each 10 μg/m3 rise in PM2.5 was related to a higher obesity risk [OR 1.12 (95% CI 1.09-1.14)] and abdominal obesity [OR 1.10 (95% CI 1.07-1.13)]. The association between PM2.5 and obesity varied according to sunshine duration, with the highest ORs of 1.56 (95% CI 1.28-1.91) for obesity and 1.66 (95% CI 1.34-2.07) for abdominal obesity in the bottom quartile of sunlight exposure (3.21-5.34 hours/day).ConclusionLong-term PM2.5 effect on obesity risk among the general Chinese population are influenced by sunlight exposure. More attention might be paid to reduce the adverse impacts of exposure to air pollution under short sunshine duration conditions.

Storage of the foods obtained by plant and animal production is as important as their cultivation. Crops cultivated around the world lose 28-36% of total yield during the process from agricultural land to consumption. With the most of this loss occurs after harvest and harvest, it can be reduced by suitable machines and appropriate methods to be used. Niğde is in third place in the list of cities with the highest apple production in Turkey. In addition, it is seen that the potential of the region to benefit from solar energy is quite high with 8.02 hours of daily sunshine duration and 1550-1800 kWh m-2 total solar radiation values. In line with the information given, Niğde province stands out as an important opportunity for apple drying processes using solar-powered drying methods. In this study, suitable drying methods that can be used for agricultural products in general and methods that can be used in Niğde province have been investigated and with the using the information obtained from previous studies related to the region its examined that the solar drying system and machines that can be developed for the province of Niğde are specified.

The 2019 novel coronavirus disease (COVID-19) has become a severe public health and social problem worldwide. A limitation of the existing literature is that multiple environmental variables have not been frequently elaborated, which is why the overall effect of the environment on COVID-19 has not been conclusive. In this study, we used generalized additive model (GAM) to detect the relationship between meteorological and air pollution variables and COVID-19 in four urban agglomerations in China and made comparisons among the urban agglomerations. The four urban agglomerations are Beijing-Tianjin-Hebei (BTH), middle reaches of the Yangtze River (MYR), Yangtze River Delta (YRD), and the Pearl River Delta (PRD). The daily rates of average precipitation, temperature, relative humidity, sunshine duration, and atmospheric pressure were selected as meteorological variables. The PM2.5, PM10, sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) contents were selected as air pollution variables. The results indicated that meteorological and air pollution variables tended to be significantly correlated. Moreover, the nature of the relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and meteorological and air pollution variables (i.e., linear or nonlinear) varied with urban agglomerations. Among the variance explained by GAMs, BTH had the highest value (75.4%), while MYR had the lowest value (35.2%). The values of the YRD and PRD were between the above two, namely 45.6% and 62.2%, respectively. The findings showed that the association between SARS-CoV-2 and meteorological and air pollution variables varied in regions, making it difficult to obtain a relationship that is applicable to every region. Moreover, this study enriches our understanding of SARS-CoV-2. It is required to create awareness within the government that anti-COVID-19 measures should be adapted to the local meteorological and air pollution conditions.

Potential of a classic adaptive neuro-fuzzy inference system (ANFIS) was evaluated in the current study for estimating the daily dew point temperature (Tdew). The study area consists of two stations located in Iran, namely the Rasht and Urmia. The daily Tdew time series of the studied stations were modeled through the other effective variables comprising minimum air temperature (Tmin), extraterrestrial radiation (Ra), vapor pressure deficit (VPD), sunshine duration (n), and relative humidity (RH). The correlation coefficients between the input and output parameters were utilized to determine the most effective inputs. Furthermore, novel hybrid models were proposed in this study in order to increase the estimation accuracy of Tdew. For this purpose, two optimization algorithms named bee colony optimization (BCO) and dragonfly algorithm (DFA) were coupled on the classic ANFIS. It was concluded that the hybrid models (i.e., ANFIS-BCO and ANFIS-DFA) demonstrated better performances compared to the classic ANFIS. The full-input pattern of the coupled models, specifically the ANFIS-DFA, was found to present the most accurate results for both the selected stations. Therefore, the developed hybrid models can be proposed as alternatives to the classic ANFIS to accurately estimate the daily Tdew.

Background Previous studies reported that changes in weather and phases of moon are associated with medical emergencies and injuries. However, such studies were limited to hospital or community level without explaining the combined effects of weather and moon phases. We investigated whether changes in weather and moon phases affected emergency department (ED) visits due to fall injuries (FIs) based on nationwide emergency patient registry data. Methods Nationwide daily data of ED visits after FI were collected from 11 provinces (7 metropolitan cities and 4 rural provinces) in Korea between January 2014 and December 2018. The daily number of FIs was standardized into FI per million population (FPP) in each province. A multivariate regression analysis was conducted to elucidate the relationship between weather factors and moon phases with respect to daily FPP in each province. The correlation between weather factors and FI severity was also analyzed. Results The study analyzed 666,912 patients (418,135 in metropolitan and 248,777 in rural areas) who visited EDs on weekdays. No regional difference was found in age or gender distribution between the two areas. Precipitation, minimum temperature and wind speed showed a significant association with FI in metropolitan areas. In addition, sunshine duration was also substantial risk factors for FI in rural areas. The incidence of FIs was increased on full moon days than on other days in rural areas. Injury severity was associated with weather factors such as minimum temperature, wind speed, and cloud cover. Conclusion Weather changes such as precipitation, minimum temperature, and wind speed are associated with FI in metropolitan and rural areas. In addition, sunshine duration and full moon are significantly associated with FI incidence only in rural areas. Weather factors are associated with FI severity.

Abstract We determined the time scale of normalized difference vegetation index (NDVI) response to drought and used trend and correlation analyses to explore the spatial and temporal variability characteristics of the NDVI and SPEI and their sensitivity to climatic factors in southwest China from 2000 to 2020. We used a partial derivative approach to calculate the contributions of six climatic factors and human activities to the interannual variation in the NDVI. The results demonstrated that from 2000 to 2020, the annual mean NDVI in southwest China showed a slight decreasing trend at a rate of 0.0001 y−1. The NDVI had the highest sensitivity to the standardized precipitation and evapotranspiration index on a 12-month time scale. The NDVI exhibited a 1-year delayed response to drought. The SPEI has the highest sensitivity to precipitation. The percentage of pixels with a positive correlation between NDVI and precipitation, mean temperature, temperature difference, mean relative humidity, mean wind speed, and sunshine duration in the study area was 31.73%, 46.81%, 35.49%, 25.76%, 39.36%, and 39.89%, respectively. The average contributions of these six climatic factors to the interannual variation of NDVI were 0.00029, 0.00046, −0.00007, 0.00007, 0.0008, and 0.00001 y−1, respectively. The NDVI had the highest sensitivity to mean temperature and the lowest sensitivity to mean relative humidity. The average contributions of climatic factors and human activities to interannual variability in southwest China were 0.00156 and 0.00012 y−1, respectively. The positive influence of climatic factors on the NDVI was stronger than that of human activities. This study provides a theoretical basis for the sustainable management of the regional ecological environment.