The Climate Hazard Group InfraRed Precipitation with Stations (CHIRPS) dataset was examined for its variability and performance in explaining precipitation variations, forecasting, and drought monitoring in Southeast Asia (SEA) for the period of 1981–2020. By using time-series analysis, the Standardized Precipitation Index (SPI), and the Autoregressive Integrated Moving Average (ARIMA) model this study established a data-driven approach for estimating the future trends of precipitation. The ARIMA model is based on the Box Jenkins approach, which removes seasonality and keeps the data stationary while forecasting future patterns. Depending on the series, ARIMA model annual estimates can be read as a blend of recent observations and long-term historical trend. Methods for determining 95 percent confidence intervals for several SEA countries and simulating future annual and seasonal precipitation were developed. The results illustrates that Bangladesh and Sri Lanka were chosen as the countries with the greatest inaccuracies. On an annual basis, Afghanistan has the lowest Mean Absolute Error (MAE) values at 33.285 mm, while Pakistan has the highest at 35.149 mm. It was predicted that these two countries would receive more precipitation in the future as compared to previous years.
The coronavirus pandemic (COVID-19) has impacted the usual global movement patterns, atmospheric pollutants, and climatic parameters. The current study sought to assess the impact of the COVID-19 lockdown on urban mobility, atmospheric pollutants, and Pakistan’s climate. For the air pollution assessment, total column ozone (O3), sulphur dioxide (SO2), and tropospheric column nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI), aerosol optical depth (AOD) data from the Multi-angle Imaging Spectroradiometer (MISR), and dust column mass density (PM2.5) data from the MERRA-2 satellite were used. Furthermore, these datasets are linked to climatic parameters (temperature, precipitation, wind speed). The Kruskal–Wallis H test (KWt) is used to compare medians among k groups (k > 2), and the Wilcoxon signed-rank sum test (WRST) is for analyzing the differences between the medians of two datasets. To make the analysis more effective, and to justify that the variations in air quality parameters are due to the COVID-19 pandemic, a Generalized Linear Model (GLM) was used. The findings revealed that the limitations on human mobility have lowered emissions, which has improved the air quality in Pakistan. The results of the study showed that the climatic parameters (precipitation, Tmax, Tmin, and Tmean) have a positive correlation and wind speed has a negative correlation with NO2 and AOD. This study found a significant decrease in air pollutants (NO2, SO2, O3, AOD) of 30–40% in Pakistan during the strict lockdown period. In this duration, the highest drop of about 28% in NO2 concentrations has been found in Karachi. Total column O3 did not show any reduction during the strict lockdown, but a minor decline was depicted as 0.38% in Lahore and 0.55% in Islamabad during the loosening lockdown. During strict lockdown, AOD was reduced up to 23% in Islamabad and 14.46% in Lahore. The results of KWt and WRST evident that all the mobility indices are significant (p < 0.05) in nature. The GLM justified that restraining human activities during the lockdown has decreased anthropogenic emissions and, as a result, improved air quality, particularly in metropolitan areas.
In Myanmar, social media has evidently impacted on human behaviors after 2010 year and this condition is declining prospect of Myanmar Traditions and Cultures. Polite consciences of Myanmar people become disappearing year after year by using social media. This study was conducted for 12 years in Myanmar among general population of 4952 people. 82% of people are deviant with Myanmar Culture and 81.6% are transforming their behaviors to rude with deviation of Tradition of Myanmar. When youths under 18 years, they were used to marry illegally and 68.2% have adulterous liaison from social media dating. The children who are not adults cannot concentrate their study and this fact is directly impact on Education of Myanmar. The physical health became prospect in bad situation due to emission of microwaves from smart devices.
Purpose: Cataract is the leading cause of blindness worldwide, and is particularly common in low- and middle-income countries. Our study aims to identify the predictors for and barriers to acceptance of cataract surgery in Kenya, Bangladesh and the Philippines. Methods: Cases were individuals aged ≥50 years and with best corrected VA of <6/24 in the better eye due to cataract who were identified through population-based surveys and community-based case detection. Cases were asked why they had not attended for surgery. They were offered free cataract surgery and followed-up at one year. Non-acceptors were interviewed to identify barriers to accepting surgery. Results: Of all participants, 58.6% attended for cataract surgery in Kenya, 53.9% Bangladesh and 47.1% the Philippines. Younger age was a predictor for attendance for surgery in all three countries. In Bangladesh and Kenya, male gender and psychosocial score were predictors. At baseline "cost" and "unaware of cataract" were most frequently reported barriers to uptake of surgery in the three settings. At follow-up, "surgical services inaccessible" was one of the two most frequently reported barriers in Kenya and the Philippines while "fear" was most frequently reported in Bangladesh and the Philippines. There were no consistent predictors of the most frequently reported barriers across the different settings. Conclusions: Future services need to focus on increasing uptake among older people and women. Cost is often reported as a barrier but this may conceal more complicated underlying barriers which need to be explored through in-depth qualitative research. Implications for RehabilitationCataract is the leading cause of blindness worldwide, and is particularly common in low- and middle-income countries.Evidence suggests that even when surgical services are available, there can be a lack of demand and low utilization resulting from barriers to uptake.Older cataract patients, females and especially older females are least likely to attend for surgery.Future cataract surgical programmes should put special emphasis on targeting and increasing uptake in these groups.
This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p < 0.05 to be statistically significant. We observed significant (p < 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p < 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan.
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