58 research outputs found
Pre-Treatment and Characterization of Water Hyacinth Biomass (WHB) for Enhanced Xylose Production Using Dilute Alkali Treatment Method
No full textLignocellulosic biomass from water hyacinth, a readily available waste material, holds potential for producing commercial products such as xylose, which can be further converted into value-added products like xylitol. However, the complex structure of lignocellulosic biomass necessitates energy-intensive processes to release fermentable sugars. Chemical pre-treatment methods, such as alkali pre-treatment, offer a viable approach to degrade lignocellulose biomass. In this study, water hyacinth biomass (WHB) was treated with 3% potassium hydroxide and subjected to autoclaving to hydrolyse the sample. The total xylose released during the process was quantified using a UV-Vis spectrophotometer and was found to 0.253 g/g of water hyacinth biomass when the sample was treated for 20 min at 2% biomass concentration. The morphological changes in the treated biomass compared to the untreated sample were analysed using Field Emission Scanning Electron Microscopy (FE-SEM). Crystallinity alterations were evaluated through X-Ray Diffraction (XRD), while Fourier-Transform Infrared Spectroscopy (FTIR) was employed to study the changes in chemical states of the biomass. The primary objective of this study was to identify a reliable pre-treatment method for processing water hyacinth biomass, facilitating the efficient release of fermentable sugars for downstream applications
Casteism in Practice: Some Personal Reflections
No full textIn this lecture, the author discussed caste on the basis of his personal, day-to-day experience. He also discusses the views of Gandhi, Ambedkar, and Tagore on caste
Microflora from leaf debris is suitable for treatment of starch industry wastewater
No full textBiological treatment of industrial waste is a widely practiced technique that generates comparatively less environmentally hazardous waste than other chemical treatment processes. Wet milling of maize generates huge amount of wastewater (5 m3/ton) of low pH with organic matter and nutrients. Anaerobic methanogenic and aerobic bacteria are mostly highly sensitive to low pH. The treatment of wastewater causes huge cost of chemical neutralization or hydraulic recirculation for maintaining neutral pH. In the present study, different microbial consortia isolated from cow dung, active sludge from an anaerobic reactor for treatment of industrial wastewater, and leaf debris from benthic soil were screened for tolerance against low pH and for potential of chemical oxygen demand (COD) removal in order to find out an alternative microbial population for industrial water treatment at low pH. The most effective consortia found from leaf debris were further investigated for optimal operation. The microscopic analysis of leaf debris sludge showed abundance of Gram-negative methanococci, which was found tolerant to low pH in plate culture method. On further investigation for COD removal from starch industry effluent, they were found to be most effective at pH 5 with highest COD removal rate of 70% and lowest biomass generation of 81%. Hence, it was concluded that the low pH-tolerant methanogen bacteria, enriched from leaf debris sludge, is highly beneficial for anaerobic treatment of wastewater from several industries including corn starch industry by reducing cost of operation for neutralization to neutral pH and through reducing excess waste sludge production by the treatment system
Fuzzy Modeling to Evaluate the Effect of Temperature on Batch Transesterification of Jatropha Curcas for Biodiesel Production
No full textBiodiesel is an alternative source of fuel that can be synthesized from edible, non-edible and waste oils through transesterification. Firstly Transesterification reaction of Jatropha Curcas oil with butanol in the ratio of 1:25 investigated by using of sodium hydroxide catalyst with mixing intensity of 250 rpm in isothermal batch reactor. Secondly the fuzzy model of the temperature is developed. Performance was evaluated by comparing fuzzy model with the batch kinetic data. Fuzzy models were developed using adaptive neuro-fuzzy inference system (ANFIS
Are population size and diverse climatic conditions the driving factors for next COVID-19 pandemic epicenter in India?
No full textAlthough a nationwide lockdown was imposed in India amid COVID-19 outbreak since March 24, 2020, the COVID-19 infection is increasing day-by-day. Till June 10, 2021 India has recorded 29,182,072 COVID cases and 359,695 deaths. A number of factors help to influence COVID-19 transmission rate and prevalence. Accordingly, the present study intended to integrate the climatic parameters, namely ambient air temperature (AT) and relative humidity (H) with population mass (PM) to determine their influence for rapid transmission of COVID-19 in India. The sensibility of AT, H and PM parameters on COVID-19 transmission was investigated based on receiver operating characteristics (ROC) classification model. The results depicted that AT and H models have very low sensibility (i.e., lower area under curve value 0.26 and 0.37, respectively compared with AUC value 0.5) to induce virus transmission and discrimination between infected people and healthy ones. Contrarily, PM model is highly sensitive (AUC value is 0.912, greater than AUC value 0.5) towards COVID-19 transmission and discrimination between infected people and healthy ones and approximate population of 2.25 million must impose like social distancing, personal hygiene, etc. as strategic management policy. Therefore, it is predicted, India could be the next epicenter of COVID-19 outbreak because of its over population
Optimization of Substitution Matrix for Sequence Alignment of Major Capsid Proteins of Human Herpes Simplex Virus
No full textProtein sequence alignment has become an informative tool in modern molecular biology research. A number of substitution matrices have been readily available for sequence alignments, but it is challenging task to compute optimal matrices for alignment accuracy. Here, we used the parameter optimization procedure to select the optimal Q of substitution matrices for major viral capsid protein of human herpes simplex virus. Results predict that Blosum matrix is most accurate on alignment benchmarks, and Blosum 60 provides the optimal Q in all substitution matrices. PAM 200 matrices results slightly below than Blosum 60, while VTML matrices are intermediate of PAM and VT matrices under dynamic programming
Assessment of aquatic ecological health: A comparative study between cistern-made and ‘Natural’ earthen-made waterbody
No full textEcological health of two waterbodies i.e., cistern-made and ‘natural’ earthen-made waterbody was compared in the present study based on temporal variations of physicochemical and biological parameters. Number of physicochemical parameters [transparency, temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (DO), total hardness (TH), total alkalinity (TA), biochemical oxygen demands (BOD), nitrate, phosphate and chlorophyll a (Chl a)], and biological parameters, e.g., zooplankton community and aquatic macrophytes were studied seasonally. Zooplankton communitiy comprised six arthropods and two rotifers. SIMPER analysis depicted that Moina sp., Daphnia sp., and Cyclops sp. were dominant species in cistern pond while Cyclops sp., Daphnia sp., Keratella sp. and Brachionus sp. were dominant in earthen natural pond. Abundance of species was highest in summer followed by post-rainy and winter in both the ponds while maximum abundance of zooplankton was recorded in summer. Species richness peaked in winter in natural pond, while in cistern pond species richness and diversity raised in summer. Multivariate analyses depicted significant temporal variation in zooplankton species in both the conditions. RELATE analysis revealed that temporal variation in species distribution and zooplankton community was significantly correlated with environmental parameters. Moreover, biological-environmental best matching (BIO-ENV) analyses indicated that water temperature, pH, TH and BOD (for cistern pond) and water temperature, EC and TSS (for earthen natural pond) were the main driving forces for temporal variations in species distribution and zooplankton community. Additionally, correlation analysis depicted that Moina sp., Daphnia sp., Diaptomus sp., Cyclops sp., Cypris sp., Bosmina sp., and species abundance was positively (significant) correlated with transparency, water temperature, and Chl a in natural pond. On the other hand, correlation analysis depicted that zooplankton species, species abundance, evenness and diversity were positively correlated with water temperature, DO, BOD and Chl a in cistern pond. Moreover, abundance of aquatic macrophytes were limited in three basic groups, namely free floating [(Lemna sp. (Major), Lemna sp. (Minor), Azolla sp., Pistia sp. and Eichhornia sp.], rooted submerged [Hydrilla sp., Ceratophyllum sp.] and rooted emerged [Nymphaes sp. and Ipomoea sp.]. Further, trophic state index (TSI) value revealed that both the ponds are hyper-eutrophic (‘natural’ waterbody > cistern waterbody) with a strong temporal variations. Therefore, these data could be used as water quality community-based bio-assessment tool as well as basis of water quality management plans to monitor the pollution level or conservation of aquatic ecology
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