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A comprehensive assessment of the forecast skill of various meteorological indices over the Indian region from different numerical weather prediction (NWP) models is lacking in the literature. In this study the performance of four NWP models, namely Global Ensemble Forecast System (GEFSv12), European Center for Medium Range Forecasting (ECMWF), Climate Forecast System (CFSv2) and Indian Institute of Tropical Meteorology (IITM) towards forecasting of precipitation, temperature and associated meteorological indices, is evaluated at short to medium timescales across the Indian region. Further, the effect of ocean atmospheric (OA) oscillations on the precipitation/temperature forecast skill from the different NWP models is also assessed. Results show that the NWP models are better in predicting the meteorological indices than the quantitative forecasts. The ECMWF model was found to be the best for PCP forecasting with CFSv2 performing poorly. For temperature the GEFSv12 model performance was the lowest, compared to rest of the models. The models show poor skill in forecasting monsoon season precipitation compared to non‐monsoon and the temperature forecasts from the NWP models are particularly poor for the northern basins. Skilful temperature forecasts are observed in the Northwestern, Indo‐Gangetic and Central basins for the CFSv2 and ECMWF models. The forecast skill of precipitation indices are higher in the northwestern, central and Indo‐Gangetic basins compared to the rest. The skill of precipitation indices, namely rainy days, extreme rainy days and consecutive wet days, is higher during the monsoon seasons while the prediction skill of consecutive dry days is higher during the non‐monsoon season. OA analysis revealed that the ENSO phases have dominant effect on the forecast skill of the precipitation only. The temperature and meteorological indices forecasts are not affected significantly by the OA phases. The outcomes of this study have implications towards irrigation scheduling and water resources management decision making in India. [ABSTRACT FROM AUTHOR]

Compound dry hot events (CDHEs), where hot events and droughts coexist, have received a lot of attention lately due to their catastrophic effects on the economy, environment and human health. In this study, we use two CDHE indices, the Standardized Compound Event Indicator (SCEI) and the Standardized Dry and Hot Index (SDHI), to assess changes in CDHE characteristics (severity, frequency, spatial extent) over the historical past and future CMIP6 simulations across the Indian subcontinent. To understand the role of the drought index selected on CDHE characterization two drought indices namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are employed in the calculation of the CDHE indices. Further, the role of climatic oscillations such as El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Equatorial Indian Ocean Monsoon Oscillation and Indian Ocean Dipole in modulating CDHE characteristics have also been explored. Results show that SPI and SPEI based CDHE indices exhibit contrasting trends in northern India, while similar trends are observed in southern India in the historical past. Also, more frequent, extended, and severe CDHEs are reported by CDHE indices calculated using SPEI than by SPI. Temperature is found to be the dominant factor contributing to increases in CDHEs in the recent past and ENSO phases significantly modulate the severity and frequency of CDHE events in India. CMIP6 simulations generally report an increase in CDHE events for a 3°C global warming scenario. Overall, our findings show that the choice of the drought index has a greater impact on CDHE characterization than the choice of the CDHE index itself. Results from this study provide useful information towards understanding the risk of CDHEs in India under global warming and urge for the development and implementation of adaptation and mitigation measures. [ABSTRACT FROM AUTHOR]

INTRODUCTION: HIV fourth-generation assay, designed for the detection of HIV p24 antigen along with anti-HIV antibodies of both immunoglobulin M and immunoglobulin G type against HIV 1 and HIV 2 viral antigens, have helped in the early detection of HIV infection and supports in minimizing the transmission risk in the acute phase of infection. The objective of this study was to evaluate the analytical and clinical performance of HIV fourth-generation assay based on enhanced chemiluminescence technology. MATERIALS AND METHODS: The analytical performance of the assay was evaluated in terms of accuracy, precision, limit of detection, type of sample (serum vs. plasma), cross-reactivity (with other transfusion transmissible infections markers), and interference (with endogenous substances). Proficiency control material included kit-controls, archived known positive donor samples, third-party controls, and World Health Organization (WHO)/National Institute for Biological Standards and Controls (NIBSC, MHRA, UK) controls. The clinical performance was evaluated using routine donor and patient samples received during the study period. RESULTS: HIV fourth-generation assay showed reliable and reproducible results measured in terms of coefficient of variation % with kit-controls, archived known positive donor samples, third-party controls, and WHO international standards for anti-HIV 1 and 2 antibodies, HIV1 p24 antigens and HIV2 p26 antigen controls. The analytical sensitivity of the HIV fourth-generation assay was found to be 0.1 IU/mL of HIV1 p24 antigen control and there was no cross-reactivity or interference observed. In the clinical performance of the assay, HIV fourth-generation assay showed reliable performance in both donor and patient samples. CONCLUSION: HIV fourth-generation assay meets the requirements for its use as a screening assay for HIV infection based on the analytical and clinical performance of the assay. [ABSTRACT FROM AUTHOR]

Background Following a massive outbreak of the coronavirus disease 2019 (COVID-19) pandemic, a significant number of survivors are still suffering from residual symptoms and complications. We designed a preliminary study to evaluate such symptom spectra in COVID-19 patients who had been discharged from the hospital. Methods A telephone interview was conducted with 100-randomly chosen hospital-discharged COVID-19 survivors from the electronic patient record. The interview structure and method were developed by a panel of experts. A specially trained group conducted the interviews and data collection. The statistical analysis was performed in accordance with the data type (continuous and categorical). Group comparisons were also done between intensive care unit (ICU) versus general ward admission, and patients discharged between 3 and 12 weeks versus more than 12 weeks. Additionally, world clouds were used for better visualization of various prevalent symptoms. Results Eighty-two participants were finally included for interview after preliminary screening. Fifty-three patients (64.6%) were male participants; 74.4% had at least one symptom. In general, fatigue, cough, insomnia, and shortness of breath were the most common persistent symptoms. Symptoms were more prevalent among the patients discharged from ICU compared with those discharged from the general ward. Cough, loss of appetite, depression, and incoherence were more common in patients after 12 weeks of hospital discharge. Conclusion There is a wide range of persistent symptoms in the COVID-19 survivors who have been discharged from the hospital. Some symptoms arise or persisted even after 12 weeks. Based on the study results, available literature, and expert consensus, an assessment form has been developed that could be used for further research and clinical assessment of similar problems. Large-scale epidemiological study (longitudinal and cross-sectional) is needed to understand the nature and prevalence of the postacute phase of COVID-19 at the country level. The results of this study could inform the stakeholders and policymakers for taking necessary steps toward a further decision. [ABSTRACT FROM AUTHOR]

A novel hierarchical method for finding tracer clouds from weather satellite images is proposed. From the sequence of cloud images, different features such as mean, standard deviation, busyness, and entropy are extracted. Based on these features, clouds are segmented using the k-means clustering algorithm and considering the coldest cloud segment, potential regions for tracer clouds are identified. These regions are represented by a set of features. All such steps are repeated for images taken at three consecutive time instants. Then, simulated annealing is used to establish an association between cloud segments of successive image frames. In this way, several chains of associated cloud regions are found and are ranked using fuzzy reasoning. The method has been tested in several image sequences, and its results are validated by determining cloud motion vector from the associated chains of tracers. Index Terms--Association of regions, best tracer cloud, cloud motion vector (CMV), feature vector, tracer cloud.

The interface of freshwater and saltwater plays an important role in the economic and social dynamics along the coast and estuaries. Droughts in coastal areas have ecological impacts and affect socioeconomic dynamics and public health. In this study, we developed a bivariate and multivariate drought index that can quantify and indicate drought conditions in coastal, bay, and estuarine areas by integrating the meteorological and hydrological drought variables. The bivariate coastal drought index (BCDI) was developed using copula theory, which includes streamflow and salinity levels in the bay areas. Further, the entropy-weighted Euclidean distance method was used to develop the multivariate coastal drought (MCDI) index using precipitation, salinity, and streamflow datasets. Both the BCDI and MCDI were able to capture the major drought events occurring in the southeast region (2000, 2007, and 2011–2012) of the United States. Correlation analysis showed that both the BCDI and MCDI were highly correlated with the standardized univariate drought indices. One of the better features of the MCDI was that it was able to capture the dynamics and trends of the variables involved and, thus, was a better indicator of droughts in the coastal regions. Hit rates and false alarm ratios showed that both the indices were able to capture the droughts in coastal regions. The coastal drought indices developed in the study can be used by the National Integrated Drought Information System (NIDIS) and other agencies as drought indicators for coastal regions, along the coastal regions, estuaries, and bays in the United States. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Semi-automated equipment using Column agglutination technology (CAT) is widely used where centrifugation and incubation are automated but substantial amount of the work is still executed manually. Larger laboratories are moving towards automation to eliminate errors, reducing exposure to bio-hazardous samples, assuring traceability, reliability, turnaround time (TAT) and throughput. Moving towards automation and greater reliability, we therefore, decided to install an automated immunohematological (IH) analyzer "Vision". In this study we evaluated reliability and performance before clearing "Vision" for routine use. MATERIALS AND METHODS: Study was conducted in the Department of Transfusion-Medicine. The primary objective was to assess the reliability of results and compare with routine use semi-automated BIOVUE system (Reference system). Secondary objective was to evaluate the performance (TAT and throughput) of the Vision to handle routine and emergency workload. RESULTS: Total of 1276 known samples were used to assess 2640 pre-transfusion tests (1229 ABO/Rh D typing; 1229 antibody screening; 54 antibody identification; 86 crossmatch and 42 DAT). All 1229 ABO Rh typing results were concordant between the two systems. Overall agreement between the Vision IH analyzer and reference system for ABO Rh typing was 99.95%. All antibody screening, crossmatch and DAT results were concordant between the two systems. TAT of Vision was substantially shorter than the reference system for all test profiles. CONCLUSION: Based on study results, Vision was approved for routine use in laboratory. It was found to be reliable with considerably shorter TAT and capable of handling high throughput of immunohematological tests. [ABSTRACT FROM AUTHOR]

In southwestern Georgia, increased groundwater withdrawal for irrigation in the Lower Flint River Basin (LFRB) is greatly affecting the supply of freshwater to downstream regions during drought years. This study was undertaken to understand the sensitivity of groundwater components to changes in irrigation pumping scenarios during droughts in the highly connected karst Upper Floridan Aquifer (UFA) and assess the effectiveness of irrigation shutdown on stream-aquifer fluxes. This study was done using the United States Geological Survey (USGS) MODular Finite-Element Groundwater model (MODFE). The model was run for the water year 2011 and changes in simulated groundwater-budget components for monthly irrigation pumping rates of 50%, 75%, 100%, 125%, 150%, and 200% of that indicated by metered irrigation systems were quantified. The effect of irrigation shutdown in the vulnerable Spring Creek subwatershed was also investigated. Results show that increasing irrigation pumping in the study area decreased aquifer storage, induced recharge to the UFA (vertical leakage), and induced recharge from streams into the UFA. During the months of May-September 2011, doubling of irrigation pumping induced nearly double the recharge rate into the UFA from streams and effected a 10% decrease in discharge rate from the UFA to streams. Analysis of irrigation shutdown indicates that eliminating irrigation pumping from the Spring Creek watershed alone facilitated an increase in baseflow of 46 x 104 m³=day, or about two-thirds the total increase in baseflow that would be realized from eliminating irrigation pumping within the entire LFRB. [ABSTRACT FROM AUTHOR]

Intravenous (IV) drug abuse has been well established to be the source of transfer of infections, such as HIV, hepatitis C virus, and hepatitis B virus. However, often overlooked fact is that IV drug abusers have a potential for developing alloimmunization due to universal practice of flushing/washing out the syringe by own blood to rinse out the drug in the syringe. We present here a case of a 28-year-old man who presented with a rather unique predicament of having developed four different alloantibodies after exposure to allogenic blood through IV drug abuse. This case was detected promptly due to routine usage of type and screen policy for all the patients receiving transfusion. Such screening for atypical antibodies must be instituted to preemptively identify these antibodies and arrange compatible blood, which could have been difficult otherwise, at short notice during routine crossmatch. This is the first of its kind case ever reported from India and has no precedence. [ABSTRACT FROM AUTHOR]

61-year old male patient was admitted to the hospital with clinical picture of hemolytic anemia with hemoglobinuria. Patient was suspected to have Infectious Mononucleosis (IM) with Auto Immune Hemolytic Anemia (AIHA). DAT was positive with anti-C3d specificity. Donath Landsteiner (DL) test was positive; confirming Paroxysmal Cold Hemoglobinuria (PCH). The final diagnosis was IM with PCH. Patient was managed conservatively and discharged after seven days. DL test specifically detects a biphasic autoantibody (IgG type) that binds to RBCs at cold temperatures, and fixes complement on the RBC membrane. However RBCs are only lysed upon warming to 37C when complement cascade proceeds to completion. [ABSTRACT FROM AUTHOR]

The lower Apalachicola-Chattahoochee-Flint River Basin in the Southeast United States represents a major agricultural area underlain by the highly productive karstic Upper Floridan aquifer (UFA). During El Niño Southern Oscillation-induced droughts, intense groundwater withdrawal for irrigation lowers streamflow in the Flint River due to its hydraulic connectivity with the UFA and threatens the habitat of the federally listed and endangered aquatic biota. This study assessed the compounding hydrologic effects of increased irrigation pumping during drought years (2010-2012) on stream-aquifer water exchange (stream-aquifer flux) between the Flint River and UFA using the United States Geological Survey modular finite element groundwater flow model. Principal component and K-means clustering analyses were used to identify critical stream reaches and tributaries that are adversely affected by irrigation pumping. Additionally, the effectiveness of possible water restriction scenarios on stream-aquifer flux was also analysed. Moreover, a cost-benefit analysis of acreage buyout procedure was conducted for various water restriction scenarios. Results indicate that increased groundwater withdrawal in Water Year 2011 decreased baseflow in the lower Apalachicola-Chattahoochee-Flint River Basin, particularly, in Spring Creek, where irrigation pumping during April, June, and July changed the creek condition from a gaining to losing stream. Results from sensitivity analysis and simulated water restrictions suggest that reducing pumping in selected sensitive areas is more effective in streamflow recovery (approximately 78%) than is reducing irrigation intensity by a prescribed percentage of current pumping rates, such as 15% or 30%, throughout the basin. Moreover, analysis of acreage buyout indicates that restrictions on irrigation withdrawal can have significant impacts on stream-aquifer flux in the Basin, especially in critical watersheds such as Spring and Ichawaynochaway Creeks. The proposed procedure for ranking of stream reaches (sensitivity analysis) in this study can be replicated in other study areas/models. This study provides useful information to policymakers for devising alternate irrigation water withdrawal policies during droughts for maintaining flow levels in the study area. [ABSTRACT FROM AUTHOR]

Patients of β-thalassemia major are dependent on regular blood transfusions for their entire lifetime. Development of antibodies against red blood cell (RBC) antigen which may be alloantibody or autoantibody, several times as a result of frequent red cell component transfusions, further complicates the subsequent transfusion therapy. Among the autoantibodies, warm-reactive autoantibodies are commoner and interfere in the pretransfusion testing. These RBC autoantibodies present in patient's serum potentially react with all the cells of antibody identification panel giving “pan-reactive” picture and making alloantibody identification complex. In this report, we present our approach in a thalassemia patient who presented with warm-type autoimmune hemolytic anemia, low hemoglobin of 5.8 g/dl, and three significant alloantibodies (anti-D, anti-S, and anti-Jk b) which were masked by pan-reactive warm autoantibody(s). Differential adsorption was used to unmask underlying alloantibodies. We suggest that differential adsorption procedure is an effective and efficient method for autoantibody adsorption, detection, and identification of masked alloantibody(s), especially in patients with low hemoglobin and history of recent blood transfusion. [ABSTRACT FROM AUTHOR]

Landform attributes derived from digital elevation models (DEMs) are the most commonly used factors to predict soil depths on hillslopes. However, the selection of an appropriate algorithm to calculate terrain attributes and identify an optimal DEM resolution remains ambiguous. In this study, we propose a method to use high-resolution DEM and spatial soil depth data to obtain terrain attributes and identify the optimal DEM resolution to predict soil depths at hillslope scales. A geophysical method (ground penetrating radar, GPR) was used to investigate the reasons for the optimal DEM resolution findings. Point-scale soil depth from 116 sites and elevation data were collected from two adjacent headwater hillslopes (H1: 0.42 ha and H2: 0.31 ha) at the Hemuqiao hydrological experimental station in Southeast China. The elevation datasets were collected using a total station at a variable spacing level and were then used to derived DEMs at nine spatial resolutions: 0.25, 0.50, 0.75, 1.00, 2.00, 3.50, 5.00, 7.50 and 10.00 m. Nine primary and secondary topographic attributes using the nine spatial resolution DEMs were then derived. Two different algorithms (D8 and D ∞) for calculating contributing areas and related secondary topographic attributes were compared. We used and compared both linear (multiple linear regression, MLR) and non-linear (artificial neural network, ANN) models for soil depth prediction. Results demonstrated that the two models performed well for predicting soil depth. Specifically, MLR performed better than the non-linear model of ANNs. Additionally, we found that the multiple-direction algorithm (D ∞) allowed flow divergence and avoided abrupt changes in soil depth predictions (orphan cells) and should be adopted for model construction. The D ∞ algorithm performed better in divergent areas, such as ridges and side slopes, and the D ∞ algorithm also worked well in convergent areas, such as valleys. Moreover, our results demonstrated that moderate (e.g., 2.00 m) resolution topographic attributes, instead of the finest resolution, achieved the best prediction with the lowest root mean square error (RMSE) and mean absolute error (MAE) and the highest values of the coefficient of determination (R 2 ). Moreover, the GPR results indicated that the valley accumulated more soils than side-slope areas, and a sharp increase in soil depth was found in areas adjacent to the valley. Comparing the optimal DEM resolution and valley width obtained by GPR, we found that average valley width ( AVW ) should be considered a good measure for choosing the optimal DEM resolution for soil depth prediction. [ABSTRACT FROM AUTHOR]

Background Unexpected allo-antibody identification is difficult serological test requiring in-depth knowledge of antibody behavior, identification rules, knowledge of zygosity of antigens and dosage phenomenon. Software which uses an algorithm based on characteristics of antibodies is now available to interpret specificity of allo-antibody. A study was undertaken to evaluate the effectiveness of one such software (Resolvigen) for antibody identification compared with manual antibody identification method. Materials and Methods The study was a retrospective observational study where 238 allo-antibody results were re-evaluated using Resolvigen software (Ortho Clinical Diagnostics, Johnson and Johnson, Raritan, NJ, USA) and agreement between manual and software approaches was studied. Resolvigen software was also evaluated for usefulness, ease of use and predicted future usage by administering investigators a questionnaire with Likert scale. Results Agreement between the results of manual and automated methods ranged from 98.6% for single antibody to 65% for two antibodies ( p  = 0.000). Resolvigen software came out as very useful, easy to use, and with high predicted future usage. Conclusion This study concludes that Resolvigen can either replace manual method or be used as adjuvant to routine manual method. [ABSTRACT FROM AUTHOR]

ABO subgroups or weaker variants of A or B are group A or B subjects whose erythrocytes give a weak or negative reaction serologically with anti-A or Anti – B antisera respectively. Occurrence of these subgroups may lead to an ABO discrepancy which often puts transfusion services in a quandary. ABO subgroups which present as ABO discrepancies can be missed if reverse grouping is not performed. This study was planned to estimate the prevalence of different subgroups which can present as an ABO discrepancy in Indian population, and provide an insight to transfusion services for identification of subgroups serologically. A cross-sectional, analytical study was performed at a tertiary healthcare based blood bank on whole blood donors and patients from January 2017 to July 2018. All suspected type II and Type IV (with Anti-A1) ABO discrepant samples were projected to an algorithmic testing process, to confirm discrepancy and then narrow down to the probable subgroup. A total of 33 subgroup discrepancies; 26 of A group and 7 of B group were identified out of 73,380 patient and 35,279 donor samples tested for blood grouping. Following the algorithm, the overall prevalence of weak subgroups which can present as an ABO discrepancy was found to be 1 in 3293 or 0.03% in our population by serological testing. Out of the discrepancies caused by subgroups, the prevalence of subgroups of A were 0.0101%, 0.0018%, 0.0009%, 0.0027%, 0.0027% and 0.0018% for A2 with anti-A1, A3, Aend, Ax, Am and Ael respectively while those of B were 0.009%, 0.0009%, 0.0009% and 0.009% for B3, Bx, Bm and Bel respectively. Algorithmic approach for resolution of ABO discrepancies caused by subgroups helps in identifying the subgroup which is important because these individuals may be mistyped as group O individuals. [ABSTRACT FROM AUTHOR]

Conclusions: This scientific article emphasizes the importance of a policy for antibody screening of all blood donors as a step to further improve blood safety. We also report the incidence of red blood cell (RBC) alloimmunization in healthy blood donors obtained using a cross-sectional prospective study from September 2017 to January 2019 in the Department of Transfusion Medicine of a tertiary care referral and teaching institute in northern India. The indirect antiglobulin test (IAT) for unexpected RBC antibodies was performed by the conventional tube test with pooled group O RBCs on all donor units irrespective of their D status. Samples with positive IATs were sent to the Immune Hematology Reference Laboratory for further immunohematolo-gy workup, maintaining predefined optimal storage and transport conditions. Of the 10,390 donors studied, 9959 were males and 431 were females. The incidence of unexpected antibodies (antibodies other than those of the ABO blood system) among the blood donors was found to be 0.18 percent (19 of 10,390 with 25 alloantibodies). Of the 19 alloimmunized donors, 16 (84.2%) were male (alloimmunization rate 0.16%, 16 of 9959) and 3 (15.8%) were female (alloimmunization rate 0.69%, 3 of 431) (p = 0.01; chi-square test). In our study, the most frequent alloantibodies identified were of the Lewis blood group system (17 of 25 [68%] in 14 of the 19 alloimmunized donors). The second most common allo-antibodies belonged to the Rh blood group system (4 of 25 [16%] in 3 of the 19 alloimmunized donors), followed by those of the MNS blood group system (3 of 25 [12%] in 2 of 19 alloimmunized donors). Anti-K was found in one donor (1 of 25 [4%]). Based on the results of the study, we recommend that a policy of routinely performing IATs on all donor units, irrespective of their D status, be adopted as an essential component of safe blood transfusion practices.

Conclusions: Red blood cell alloimmunization to antigens other than D, such as C, c, E, e, and antigens in the Kell, MNS, and Duffy blood group systems, has emerged as an important cause of hemolytic disease of the fetus and newborn (HDFN). Antibody screening for these antibodies is not routinely practiced for all antenatal patients in developing countries, mainly because of financial constraints. Here we report a rare case of HDFN due to dual antibodies to Rh and Kidd blood group system antigens: anti-E and anti-Jka. This case report highlights the importance of routine and regular antenatal screening of all pregnant women for proper monitoring and follow-up.

Conclusions: When an antibody is detected, its specificity should be determined and its likely clinical significance should be assessed. When one antibody has been identified, it becomes necessary to confirm the presence of additional significant antibodies to ensure that compatible blood is provided to the patient. To perform this confirmation, specific reagent red blood cells (RBCs) are selected; these are called selected cells. Though the most common use of selected cells is for antibody confirmation, they can also be used for several other immunohematologic applications. In a developing country like India, the performance of antibody screening for unexpected antibodies on a routine basis is a comparatively new phenomenon, and those laboratories performing advanced immunohematologic testing would need to use selected cells to arrive at an accurate conclusion. This report defines selected cells and enumerates sources of these RBCs. Detailed immunohematologic applications are discussed with applicable case studies.