Search results for: Devesh Jaiswal

Authors: Rajeev Ravindran, Amit K. Jaiswal

Abstract:

Lignocellulose is the largest reservoir of inexpensive, renewable source of carbon. It is composed of lignin, cellulose and hemicellulose. Cellulose and hemicellulose is composed of reducing sugars glucose, xylose and several other monosaccharides which can be metabolised by microorganisms to produce several value added products such as biofuels, enzymes, aminoacids etc. Enzymatic treatment of lignocellulose leads to the release of monosaccharides such as glucose and xylose. However, factors such as the presence of lignin, crystalline cellulose, acetyl groups, pectin etc. contributes to recalcitrance restricting the effective enzymatic hydrolysis of cellulose and hemicellulose. In order to overcome these problems, pre-treatment of lignocellulose is generally carried out which essentially facilitate better degradation of lignocellulose. A range of pre-treatment strategy is commonly employed based on its mode of action viz. physical, chemical, biological and physico-chemical. However, existing pretreatment strategies result in lower sugar yield and formation of inhibitory compounds. In order to overcome these problems, we proposes a novel pre-treatment, which utilises the superior oxidising capacity of alkaline potassium permanganate assisted by ultra-sonication to break the covalent bonds in spent coffee waste to remove recalcitrant compounds such as lignin. The pre-treatment was conducted for 30 minutes using 2% (w/v) potassium permanganate at room temperature with solid to liquid ratio of 1:10. The pre-treated spent coffee waste (SCW) was subjected to enzymatic hydrolysis using enzymes cellulase and hemicellulase. Shake flask experiments were conducted with a working volume of 50mL buffer containing 1% substrate. The results showed that the novel pre-treatment strategy yielded 7 g/L of reducing sugar as compared to 3.71 g/L obtained from biomass that had undergone dilute acid hydrolysis after 24 hours. From the results obtained it is fairly certain that ultrasonication assists the oxidation of recalcitrant components in lignocellulose by potassium permanganate. Enzyme hydrolysis studies suggest that ultrasound assisted alkaline potassium permanganate pre-treatment is far superior over treatment by dilute acid. Furthermore, SEM, XRD and FTIR were carried out to analyse the effect of the new pre-treatment strategy on structure and crystallinity of pre-treated spent coffee wastes. This novel one-step pre-treatment strategy was implemented under mild conditions and exhibited high efficiency in the enzymatic hydrolysis of spent coffee waste. Further study and scale up is in progress in order to realise future industrial applications.

Keywords: spent coffee waste, alkaline potassium permanganate, ultra-sonication, physical characterisation

Procedia PDF Downloads 315

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

Abstract:

Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 111

Authors: Richa Jaiswal, Vidisha Sharma, Amulya Rattan, Sushma Sagar, Subodh Kumar, Amit Gupta, Biplab Mishra, Maneesh Singhal

Abstract:

Background: Adequate nutritional support and daily patient monitoring have an independent therapeutic role in the successful management of high output fistulae and early recovery after abdominal trauma. Case presentation: An 18-year-old girl was brought to AIIMS emergency with alleged history of fall of a heavy weight (electric motor) over abdomen. She was evaluated as per Advanced Trauma Life Support(ATLS) protocols and diagnosed to have significant abdominal trauma. After stabilization, she was referred to Trauma center. Abdomen was guarded and focused assessment with sonography for trauma(FAST) was found positive. Complete duodenojejunal(DJ) junction transection was found at laparotomy, and end-to-end repair was done. However, patient was re-explored in view of biliary peritonitis on post-operative day3, and anastomotic leak was found with sloughing of duodenal end. Resection of non-viable segments was done followed by side-to-side anastomosis. Unfortunately, the anastomosis leaked again, this time due to a post-anastomotic kink, diagnosed on dye study. Due to hostile abdomen, the patient was planned for supportive care, with plan of build-up and delayed definitive surgery. Percutaneous transheptic biliary drainage (PTBD) and STSG were required in the course as well. Nutrition: In intensive care unit (ICU), major goals of nutritional therapy were to improve wound healing, optimize nutrition, minimize enteral feed associated complications, reduce biliary fistula output, and prepare the patient for definitive surgeries. Feeding jejunostomy (FJ) was started from day 4 at the rate of 30ml/h along with total parenteral nutrition (TPN) and intra-venous (IV) micronutrients support. Due to high bile output, bile refeed started from day 13.After 23 days of ICU stay, patient was transferred to general ward with body mass index (BMI)<11kg/m2 and serum albumin –1.5gm%. Patient was received in the ward in catabolic phase with high risk of refeeding syndrome. Patient was kept on FJ bolus feed at the rate of 30–50 ml/h. After 3–4 days, while maintaining patient diet book log it was observed that patient use to refuse feed at night and started becoming less responsive with every passing day. After few minutes of conversation with the patient for a couple of days, she complained about enteral feed discharge in urine, mild pain and sign of dumping syndrome. Dye study was done, which ruled out any enterovesical fistula and conservative management were planned. At this time, decision was taken for continuous slow rate feeding through commercial feeding pump at the rate of 2–3ml/min. Drastic improvement was observed from the second day in gastro-intestinal symptoms and general condition of the patient. Nutritional composition of feed, TPN and diet ranged between 800 and 2100 kcal and 50–95 g protein. After STSG, TPN was stopped. Periodic diet counselling was given to improve oral intake. At the time of discharge, serum albumin level was 2.1g%, weight – 38.6, BMI – 15.19 kg/m2. Patient got discharge on an oral diet. Conclusion: Successful management of post-traumatic proximal high output fistulae is a challenging task, due to impaired nutrient absorption and enteral feed associated complications. Strategic- and goal-based nutrition support can salvage such critically ill patients, as demonstrated in the present case.

Keywords: nutritional monitoring, nutritional support, duodenal fistula, abdominal trauma

Procedia PDF Downloads 232