Forecasting seasonal hydrologic response in major river basins.

Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts

Facile extraction and characterization of calcium hydroxide from paper mill waste sludge of Bangladesh

Herein, paper mill waste sludge (PMS) from two different sources has been investigated to extract calcium hydroxide, Ca(OH)2 by a facile and inexpensive extraction process. PMS samples, collected from local paper mill plants of Bangladesh, were the main precursors wherein HCl and NaOH were used for chemical treatment. The as-synthesized products were analysed by a variety of characterization tools including X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) elemental analyses. Our studies confirm that the extracted product contains Ca(OH)2 as a major content, albeit it also includes CaCO3 phase owing to the inescapable carbonation process from the surrounding environment. The particle size of the synthesized products is in the range of 450–500 nm estimated from SEM micrographs. The crystallite domain size of the same estimated from XRD analyses and was found to be approximately 47 and 31 nm respectively for product-A and product-B considering major (101) Bragg peak of Ca(OH)2. The yield percentage of the isolated products is about 65% for samples collected from both sources

Description of patients who died within 30 days of surgery.

Description of patients who died within 30 days of surgery.</p

Surgical procedures categorized by CPT coding.

BackgroundThe COVID-19 pandemic has significantly impacted the surgical practice throughout the world, including elective surgical care. This study investigated the characteristics of patients undergoing elective surgery, the prevalence of COVID-19 infection, the surgical procedures performed, and 30-day mortality in general and pediatric surgical settings in selected tertiary-level hospitals in Bangladesh from November 2020 to August 2021.MethodsThis serial cross-sectional study included 264 patients scheduled for elective surgeries during the study period. All patients underwent COVID-19 real-time polymerase chain reaction (RT-PCR) testing within 24 hours before surgery. Data on age, sex, common comorbidities, surgical procedures, and 30-day mortality were collected and analyzed. Furthermore, comparisons were made between COVID-19 positive and negative patients.ResultsThe prevalence of COVID-19 infection among patients was 10.6%. Older age, a history of major surgery within the last three months, hypertension, and diabetes mellitus were significantly associated with COVID-19 infection. All COVID-19-negative patients underwent surgery, while only 46.4% of COVID-19-positive patients underwent surgery. The most common surgical procedures were related to the digestive system, breast, and urinary system. Only one patient (0.4%) died within 30 days after surgery among the COVID-19-negative patients, whereas two patients (7.1%) died among the COVID-19-positive patients: one before surgery and one after surgery.ConclusionsThis study provides valuable insights into the characteristics, burden of COVID-19 infection, and 30-day mortality of patients undergoing elective surgery in tertiary care centers in Bangladesh during the pandemic.</div