Developing a Customized Composite Drought Index for Pakistan

Pakistan experiences frequent and intense agricultural drought, varying spatially and temporally. Prolonged dry conditions often result in failed crop production. Using multiple variables, different components of drought can be captured across a multitude of climatic zones and throughout different seasons. Developing a composite drought index (CDI), specific for each district, will provide a more complete view of agricultural drought and enhance early warning systems

Assessment of knowledge, attitudes and practice among the post graduate students of dentistry and physiotherapy towards adverse drug reactions reporting and pharmacovigilance at a tertiary care centre at Indore, India

Background: Pharmacovigilance knowledge and training in post graduate student doctors is key factor for proper implementation of PvPI. Often the dentists and physiotherapists who are also one of the main stakeholders for ADR reporting are neglected for training and knowledge regarding pharmacovigilance. This study was planned to evaluate the knowledge and awareness of pharmacovigilance in post graduate students in tertiary care centre in Indore.Methods: It was a single point cross sectional questionnaire-based study conducted in a tertiary care Institute MGM Medical College and M.Y. Hospital in the state of Madhya Pradesh at Indore. It was conducted among post graduate student doctors from dentistry and physiotherapy. Total of 55 questionnaires were distributed, 50 of them were returned back and were analysed.Results: Overall knowledge level was average. 90% knew about ADR while 80% were aware about PVPI. 10% knew about local AMC at Indore while only 04% knew global centre for Pharmacovigilance is at Sweden Uppsala. 88% thought Med watch as global database for ADR against only 12% knew its Vigibase. 90% thought ADR reporting is necessary. 96% thought it should be included in UG curriculum. 98% had not reported any ADR till date while 84% had not seen an ADR form.Conclusions: Post graduate doctors are the prime candidates to impart the importance of pharmacovigilance. The study strongly suggested that there was a great need to create awareness and impart training among the post graduate doctors to improve the reporting of ADRs

Fast iterative solvers for thin structures

a b s t r a c t For very large systems of equations arising from 3D finite element formulation, pre-conditioned iterative solvers are preferred over direct solvers due to their reduced memory requirements. However, in the finite-element analysis of thin structures such as beam and plate structures, iterative solvers perform poorly due to the presence of poor quality elements. In particular, their efficiency drops significantly with increase in the aspect ratio of such structures. In this paper, we propose a dual-representation based multi-grid framework for efficient iterative analysis of thin structures. The proposed iterative solvers are relatively insensitive to the quality of the elements since they exploit classical beam and plate theories to spectrally complement 3D finite element analysis. This leads to significant computational gains, as supported by the numerical experiments

Spectrophotometric assessment of effect of aqueous extract of Aloe vera on rabbit erythrocytes in varying concentrations of saline

Background: Hemolytic disorders are one of the prime reasons for frequent blood transfusions which involves lots of costs and sufferings to the patient. This study was undertaken to determine the effect of water soluble extract of Aloe vera on rabbit erythrocytes in varying concentrations of NaCl from 0.9% (isotonic) to 0.15% (hypotonic).Methods: Aqueous extract of Aloe vera (AVE) 200mg/kg was orally administered to rabbits in the test group while control group was given 1ml of distilled water (DW). Blood was withdrawn from rabbits, centrifuged and suspension in 1ml of normal saline was made. 20 microliter of red blood cells suspension from both control and test groups was added to normal saline of varying concentrations from 0.9% to 0.15% NaCl which were quantitatively analysed for hemolysis by UV spectrophotometer. Data was analysed by unpaired t test and P <0.05 was considered statistically significant.Results: The difference in percentage of hemolysis in both test and control groups was not statistically significant. Therefore, acute administration of water soluble extract of Aloe vera (200mg/kg) did not have protective effect on rabbit erythrocytes against hypotonic solution of normal saline.Conclusions: Aloe vera might be useful for the treatment of oxidative stress-related human disorders by virtue of its antioxidant activity and may have a role in prevention of hemolysis which needs to be explored by further studies

Comparisons of Two Spatial Implementations of a Crop Model Using Remotely Sensed Observations over Southeastern United States

Global food security is one of the most pressing issues of the current century, particularly for developing nations. Agricultural simulation models can be a key component in testing new technologies, seeds and cultivars etc. However, inaccurate input information, model related errors and the mode of implementation can also add to model uncertainties. In this study, the crop model is implemented in two separate fashions: a)gridded (GriDSSAT model) and b) using random spatial ensembles (RHEAS model). This is done in the Southeastern US to evaluate and understand the modelperformance over a region data availabilities. Once the model performance is assessed, multiple satellite based earth observation parameters such as soil moisture, vegetation index etc. can be assimilated into crop models to reduce input and model related uncertainties particularly in data limited regions. In this study, the National Agricultural Statistical Services (NASS) reported yield data at county levels are used for comparison andvalidation purposes. The GriDSSAT model estimation of corn yields in comparison with the reported NASS yields showed an overall RMSD of nearly 3720 (kg/ha) whereas RMSD for the RHEAS model implementation was 3550 (kg/ha). Overall the GriDSSAT model had negative bias of nearly 2400 kg/ha (except for 2013) while RHEAS had a slight positive bias of 400 kg/ha (approx.)

Development of a Drought and Yield Assessment System in Kenya

Dependence on rainfed agriculture in a highly variable climate, renders crop and livestock production vulnerable to impacts of drought in Kenya. Stakeholders in the region have highlighted the need for timely and actionable detailed early warning information on drought and its implication on crop productivity. Here we apply the Regional Hydrological Extremes Assessment System (RHEAS) to estimate current and future drought conditions onset, severity, recovery, and duration) and expected productivity outlooks

An Initial Assessment of a SMAP Soil Moisture Disaggregation Scheme Using TIR Surface Evaporation Data over the Continental United States

The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of 0.022 and 0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E

GC51F-1132: Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance

No abstract availabl

Modeling Soil Moisture Profiles in Irrigated Fields by the Principle of Maximum Entropy

Vertical soil moisture profiles based on the principle of maximum entropy (POME) were validated using field and model data and applied to guide an irrigation cycle over a maize field in north central Alabama (USA). The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles that occur in the particular soil and climate regime that prevails in the study area. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with minimal losses (about 1.9% of total applied water). However, the results for finely-textured (silty clay) soils were problematic in that some plant stress did develop due to insufficient applied water. Soil moisture states in these soils fell to around 31% of available moisture content, but only on the last day of the drying side of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, such as the Southeastern United States

Detecting Desert Locust Breeding Grounds: A Satellite-Assisted Modeling Approach

The objective of this study is to evaluate the ability of soil physical characteristics (i.e., texture and moisture conditions) to better understand the breeding conditions of desert locust (DL). Though soil moisture and texture are well-known and necessary environmental conditions for DL breeding, in this study, we highlight the ability of model-derived soil moisture estimates to contribute towards broader desert locust monitoring activities. We focus on the recent DL upsurge in East Africa from October 2019 though June 2020, utilizing known locust observations from the United Nations Food and Agriculture Organization (FAO). We compare this information to results from the current literature and combine the two datasets to create “optimal thresholds” of breeding conditions. When considering the most optimal conditions (all thresholds met), the soil texture combined with modeled soil moisture content predicted the estimated DL egg-laying period 62.5% of the time. Accounting for the data errors and uncertainties, a 3 × 3 pixel buffer increased this to 85.2%. By including soil moisture, the areas of optimal egg laying conditions decreased from 33% to less than 20% on average