Measurements and models show that enhanced aerosol concentrations can modify macro- and micro-physical properties of clouds. Here, we examine the effect of aerosols on continental mesoscale ...convective cloud systems during the Indian summer monsoon and find that these aerosol-cloud interactions have a net cooling effect at the surface and the top-of-atmosphere. Long-term (2002-2016) satellite data provide evidence of aerosol-induced cloud invigoration effect (AIvE) during the Indian summer monsoon. The AIvE leads to enhanced formation of thicker stratiform anvil clouds at higher altitudes. These AIvE-induced stratiform anvil clouds are also relatively brighter because of the presence of smaller sized ice particles. As a result, AIvE-induced increase in shortwave cloud radiative forcing is much larger than longwave cloud radiative forcing leading to the intensified net cooling effect of clouds over the Indian summer monsoon region. Such aerosol-induced cooling could subsequently decrease the surface diurnal temperature range and have significant feedbacks on lower tropospheric turbulence in a warmer and polluted future scenario.
Indian subcontinent is greatly vulnerable to air pollution, especially during the winter season. Here, we use 15 years (2003-2017) of satellite and model reanalysis datasets over India and adjoining ...Seas to estimate the trend in hazy days (i.e. days with high aerosol loading) during the dry winter season (November to February). The number of hazy days is increasing at the rate of ~2.6 days per year over Central India. Interestingly, this is higher than over the Indo-Gangetic Plain (~1.7 days/year), a well known global hotspot of particulate pollution. Consistent increasing trends in absorbing aerosols are also visible in the recent years. As a result, the estimated atmospheric warming trends over Central India are two-fold higher than that over Indo-Gangetic Plain. This anomalous increment in hazy days over Central India is associated with the relatively higher increase in biomass burning over the region. Moreover, the trend in aerosol loading over the Arabian Sea, which is located downwind to Central India, is also higher than that over the Bay of Bengal during the dry winter season. Our findings not only draw attention to the rapid deteriorating air quality over Central India, but also underline the significance of increasing biomass burning under the recent climate change.
Given the inherent characteristics of the Hajj pilgrimage, the event is a risk for tuberculosis (TB) infection. Early diagnosis and appropriate management of TB cases by knowledgeable and skilled ...healthcare workers (HCWs) are key in improving patients' outcome and preventing transmission during the Hajj mass gathering and globally.
We conducted a cross-sectional study to assess knowledge, attitude and practice (KAP) of HCWs deployed during the 2016 Hajj regarding TB and its management using an anonymous self-administered questionnaire.
Data was collected from 540 HCWs from 13 hospitals. HCWs originated from 17 countries and included physicians, nurses and other non-administrative HCWs. Nearly half of HCWs declared having experience dealing with TB patients. In general, HCWs had average knowledge (mean knowledge score of 52%), above average attitude (mean attitude score of 73%) and good practice (mean practice score of 85%) regarding TB, based on our scoring system and cut-off points. Knowledge gaps were identified in relation to the definition of MDR-/XDR-TB and LTBI, smear microscopy results, length of standard TB treatment for drug-sensitive TB, 2nd line anti-TB drugs, BCG vaccination, and appropriate PPE to be used with active PTB patients. Poor attitudes were found in relation to willingness to work in TB clinic/ward and to the management and treatment of TB patients. Poor practices were reported for commencing anti-TB treatment on suspected TB cases before laboratory confirmation and not increasing natural ventilation in TB patients' rooms. Age, gender, nationality, occupation, length of work experience and experience dealing with TB patients were associated with knowledge scores. Age and occupation were associated with attitude scores while length of work experience and occupation were associated with practice scores. There was a weak but statistically significant positive correlation between score for knowledge and attitude (rs = 0.11, p = 0.009) and attitude and practice (rs = 0.13, p = 0.002).
While the results of the study are encouraging, important knowledge gaps and some poor attitudes and practices regarding TB were identified among HCWs during Hajj. This calls for multifaceted interventions to improve HCWs KAP regarding TB including tailored, periodic TB education and training aimed at boosting knowledge and improving behaviour.
Sustainable electricity production is an energy-efficient strategy aimed at both economic progress and environmental conservation. The power generation sector is the major contributor to global ...emissions and waste. The scope of circular economy in the power production sector with investments in waste minimization and emission reduction was not discussed in previous studies. In this context, a circular sustainable smart electric supply chain system is introduced in this paper with an aim of maximizing the profit with the minimum amount of emissions and waste generated from the power generation units. The power plant in this system consists of four power generation units that generate electricity from coal, waste, wind, and solar plants. A smart grid management system is used in this system for an efficient power supply according to the demands of the customer, and it enhances the system to distribute the power from renewable energies. In this system, the carbon dioxide from the thermal plants is captured and converted to natural gas to reduce emissions. Municipal and industrial waste is transformed into composite fuel to generate electricity. The profit for each unit and the customer’s demand for electricity depends on the circularity index. Linear demand versus linear and logistical cases of unit profit was considered. This study theoretically and numerically maximizes the profit of the system with optimal power consumption, circularity index of electricity, and green and waste minimization investment as per the carbon cap policy. To find the optimal strategies for maximum profit, an algorithm was developed. Sensitivity analysis is done to determine the fluctuations in the profit, emission cost, waste cost, circularity index, and power consumption due to the variations in parameters. The wise allocation of power generation from each unit and reduce energy loss by installing efficient storage devices will result in a higher profit. A system with the high efficacy of green techniques to reduce emissions, a smart grid to minimize waste, higher taxes to regulate emissions, and a rise in the amount of production of electricity from renewable sources will result in a greener power system that gains more profit than conventional systems. The key findings state that electric supply chain systems can obtain a good profit in a more sustainable manner than conventional systems.
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•A circular sustainable smart electric supply chain system with four power generation units in a single power plant.•Smart power grid management system to minimize waste by enhancing the power generation from renewable energy sources.•Optimize the profit with an optimal circularity index, power consumption, and investment under the carbon cap.•The high efficacy of techniques that minimize waste and carbon capture results in a sustainable and profitable system.
Cloud feedbacks continue to alter with climate change, which remains the largest source of uncertainty in global climate. Raindrop size distribution (DSD) is a fundamental characteristic of cloud ...microphysical and dynamical processes. This study characterizes the DSD and its response to cloud microphysical properties during the Indian Summer Monsoon season (June-October 2013–2015). The derived rain rate varied from 0.50 to 395.4 mm/h, which was segregated into stratiform rain (mean and standard deviation of 2.12 ± 1.24 mm/h) and convective rain (13.10 ± 14.45 mm/h). We found that as the convective DSD mode diameter gradually shifts to a larger drop size with increasing rain rate, the number concentration of small-sized rain drops decreased by about three orders of magnitude. While the mass-weighted mean diameter and normalized DSD scaling parameter were significantly higher for convective rain than stratiform rain, the normalized DSD scaling parameter was lowest for both convective and stratiform rain compared to previous studies over this region. The stratiform DSD was more skewed towards large raindrop size at a high cloud effective radius compared to a low cloud effective radius. However, the opposite response of the DSD for convective rain suggests the predominance of small-sized cloud/ice hydrometeors. This finding was further corroborated by the presence of narrower DSD at high cloud droplet number concentration compared to a low cloud droplet number concentration for the convective rain. The low wind shear and high convective available potential energy for convective rain further substantiated the persistent convective cores during monsoon accompanied by the formation of large size raindrops in the convective systems. Such a distinct response of DSD to different rain regimes could help in the short-term prediction of extreme rainfall events.
•Characterization of raindrop size distributions for convective and stratiform rain.•Instantaneous cloud microphysical properties and raindrop size distributions relation.•Response of raindrop size distributions to meteorological conditions.
A dataset is indispensable to answer the research questions of clinical research studies. Inaccurate data lead to ambiguous results, and the removal of errors results in increased cost. The aim of ...this Quality Improvement Project (QIP) was to improve the Data Quality (DQ) by enhancing conformance and minimizing data entry errors.
This is a QIP which was conducted in the Department of Biostatistics using historical datasets submitted for statistical data analysis from the department's knowledge base system. Forty-five datasets received for statistical data analysis, were included at baseline. A 12-item checklist based on six DQ domains (i) completeness (ii) uniqueness (iii) timeliness (iv) accuracy (v) validity and (vi) consistency was developed to assess the DQ. The checklist was comprised of 12 items; missing values, un-coded values, miscoded values, embedded values, implausible values, unformatted values, missing codebook, inconsistencies with the codebook, inaccurate format, unanalyzable data structure, missing outcome variables, and missing analytic variables. The outcome was the number of defects per dataset. Quality improvement DMAIC (Define, Measure, Analyze, Improve, Control) framework and sigma improvement tools were used. Pre-Post design was implemented using mode of interventions. Pre-Post change in defects (zero, one, two or more defects) was compared by using chi-square test.
At baseline, out of forty-five datasets; six (13.3%) datasets had zero defects, eight (17.8%) had one defect, and 31(69%) had ≥2 defects. The association between the nature of data capture (single vs. multiple data points) and defective data was statistically significant (p = 0.008). Twenty-one datasets were received during post-intervention for statistical data analysis. Seventeen (81%) had zero defects, two (9.5%) had one defect, and two (9.5%) had two or more defects. The proportion of datasets with zero defects had increased from 13.3 to 81%, whereas the proportion of datasets with two or more defects had decreased from 69 to 9.5% (p = < 0.001).
Clinical research study teams often have limited knowledge of data structuring. Given the need for good quality data, we recommend training programs, consultation with data experts prior to data structuring and use of electronic data capturing methods.
Reduced intensity conditioning (RIC) transplantation is increasingly offered to older patients with acute myeloblastic leukemia. We have previously shown that a RIC allograft, particularly from a ...sibling donor, is beneficial in intermediate-risk patients aged 35-65 years. We here present analyses from the NCRI AML16 trial extending this experience to older patients aged 60-70 inclusive lacking favorable-risk cytogenetics. Nine hundred thirty-two patients were studied, with RIC transplant in first remission given to 144 (sibling n=52, matched unrelated donor n=92) with a median follow-up for survival from complete remission of 60 months. Comparisons of outcomes of patients transplanted versus those not were carried out using Mantel-Byar analysis. Among the 144 allografted patients, 93 had intermediate-risk cytogenetics, 18 had adverse risk and cytogenetic risk group was unknown for 33. In transplanted patients survival was 37% at 5 years, and while the survival for recipients of grafts from siblings (44%) was better than that for recipients of grafts from matched unrelated donors (34%), this difference was not statistically significant (P=0.2). When comparing RIC versus chemotherapy, survival of patients treated with the former was significantly improved (37% versus 20%, hazard ratio = 0.67 0.53-0.84; P<0.001). When stratified by Wheatley risk group into good, standard and poor risk there was consistent benefit for RIC across risk groups. When stratified by minimal residual disease status after course 1, there was consistent benefit for allografting. The benefit for RIC was seen in patients with a FLT3 ITD or NPM1 mutation with no evidence of a differential effect by genotype. We conclude that RIC transplantation is an attractive option for older patients with acute myeloblastic leukemia lacking favorable-risk cytogenetics and, in this study, we could not find a group that did not benefit.
Frequently used models, such as the HAS-BLED, ATRIA, ORBIT, and GARFIELD-AF evaluate the risk of bleeding when using an anticoagulant, for example warfarin, in patients with non-valvular atrial ...fibrillation. Limited studies are available reporting a model with a good discriminative ability to predict the bleeding risk score when using direct oral anticoagulants.
Patient data were collected from King Abdulaziz Medical City, King Fahad Cardiac Center, and Prince Sultan Cardiac Center in Riyadh, from outpatients, inpatients, or primary care clinics. In total, 1722 patients with a prescription for a new oral anticoagulant, Dabigatran, Rivaroxaban, or Apixaban, were enrolled. A resampling approach for variable selection was used and a five-fold cross-validation to assess the model fit and misclassification probabilities. The analysis used the receiver operating characteristics curve (ROC) and the concordance (c) statistic to assess the validation models' discriminative power. The final penalized likelihood parameters were used for the development of the risk prediction tool. The accuracy of a classification and the prediction are reported with the sensitivity, specificity, and Brier score.
Bleeding occurred in 11.15% of cases, of which 23.08% required a blood transfusion and 51.65% had a reduction in haemoglobin of more than 2 gm. The variable selection model identified 15 predictors associated with major bleeding. The discriminative ability of the model was good (c-statistic 0.75, p = 0.035). The Brier score of the model was 0.095. With a fixed cut-off probability value of 0.12 for the logistic regression equation, the sensitivity was 72.7%, and the specificity 66.3%.
This model demonstrated a good performance in predicting the bleeding risk in Arab patients treated with novel oral anticoagulants. This easy to use bleeding risk score will allow the clinician to quickly classify patients according to their risk category, supporting close monitoring and follow-up for high-risk patients, without laboratory and radiological monitoring.
The study aimed to assess the mental health outcomes and associated factors among health care workers during COVID 19 in Saudi Arabia.
We conducted a cross-sectional survey of health care workers ...from tertiary care and ministry of health Centers across the Central, Eastern, and Western regions of Saudi Arabia. There were 1,130 participants in the survey, and we collected demographic and mental health measurements from the participants.
The magnitude of symptoms of depression, anxiety, and insomnia was measured using the original version of 9-item patient health questionnaire (PHQ-9), the 7-item generalized anxiety disorder scale (GAD-7), and 7-item insomnia severity index (ISI). We use the multiple logistic regression analysis to identify the associated risk factors of individual outcomes.
The scores on the PHQ-9 showed that the largest proportion of health care workers (76.93%) experienced only normal to mild depression (50.83 and 26.1%, respectively). The scores on the GAD-7 showed that the largest proportion of health care workers (78.88%) experienced minimal to mild anxiety (50.41 and 28.47%, respectively). The scores on the ISI showed that the largest proportion of health care workers (85.83%) experienced absence to subthreshold insomnia (57.08 and 28.75%, respectively). The risk factors for depression in health care workers were Saudi, living with family, working from an isolated room at home and frontline worker. For anxiety, being female was risk factor and for insomnia, being frontline worker was risk factor.
It was observed that the symptoms of depression, anxiety, and insomnia were reported in a lower proportion of health care workers in our study. The participants who were female, frontline workers, Saudi, living with family, and working from home in isolated rooms were predisposed to developing psychological disorders.
A circular supply chain consists of emission and wastes minimization technologies with a remarkable gain in profit, which is the aim of any industry that is concerned about environmental ...conservation. One of the most critical hurdles to the transition to sustainability is waste management. This study proposes a circular sustainable integrated model in a plastic reforming industry with investment in 3D printing techniques to minimize waste, emission reduction, and ordering cost reduction and it led to optimal profit. The customer's demand and the unit profit depend on the circularity index of the item. This paper looked at three scenarios with partial backlogging: (a) linear demand versus linear unit profit; (b) linear demand versus exponential unit profit; and (c) linear demand versus logistic unit profit. An algorithm was used to optimize the profit of the plastic reforming industry with optimal values of ordering quantity, circularity index, and investment in waste minimization, emission reduction, and ordering cost under carbon cap policy. This model establishes that the plastic reforming industry will get more profit and an optimal level of circularity index when it works with high efficiency of emission and waste minimization technologies under low investment, a rise in the carbon tax, and less opportunity cost. Sensitivity analysis and managerial framework in the plastic reforming industry were given to realize the sensitivity of decision variables with variation in key parameters.
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•Optimum circular economic supply chain model with emission minimization, and 3D printing technology to minimize waste.•Optimizes the profit of the plastic reforming industry with optimum investment, ordering quantity, and cost of ordering.•Sensitivity analysis and managerial framework in the plastic reforming industry with optimal strategies illustrated.•High efficacy of emission and waste minimization technologies and circularity indexed products leads to more profit.
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