Optimization of cultural conditions for anaerobically treated distillery effluent bioremediation by an isolate Pseudomonas putida SAG45

The present study deals with the decolourisation and detoxification of distillery effluent by an isolate SAG45. Soil samples were collected from the affected disposal sites of distillery effluent treatment plant. The isolate showed the highest bioremediation of 79.5% within 4 days of cultivation in the melanoidin pigment broth. The isolate showed higher decolourisation at pH 8.0 and temperature 37 oC. However, it gives 58.9% decolourisation with 5% (v/v) distillery effluent within 8 days. Toxicity test was also carried out to assess the toxicity of distillery effluent on seed germination

Applications of submerged fermentation for biodegradation and decolourisation of melanoidins by an isolate Alcaligenes denitrificans SAG5

In laboratory conditions a bacterium was isolated, which was identified as Alcaligenes denitrificans SAG5.. The optimum decolourisation (72.6%) of melanoidin was achieved at pH 7.5 and temperature 37 °C within 4-6 days fermentation. The toxicity evaluation of distillery effluent with mung bean (Vigna radiata) revealed that the raw effluent is highly toxic as compared to treated effluent. This indicated that the effluent after bacterial treatment is ecofriendly

Monitoring process variability and root cause analysis in paper box production

In this paper, monitoring procedure for process variability in multivariate setting based on individual observations which is a combination of (i) Hotelling’s T 2 control chart in detecting out of control signal and (ii) implementation of Mason, Young and Tracy (MYT) decomposition and structure analysis technique for root cause analysis is introduced. The advantages of this procedure will be shown by using the case of a paper box production process in one of the Malaysian manufacturing companies. The successful application of this multivariate approach could act as a stimulant for most industries to imitate in process monitoring. Moreover, the computation efficiency in root cause analysis enables quality’s multiple characteristics to be monitored simultaneously. Based on the findings, the core issue that needs to be a matter of concern by the management team is the closure tap of the box. This process variation should be solved immediately to avoid the products’ quality from further deteriorating

Impact of phosphamidon and its metabolites on histopathology of the liver, gill and intestine of Labeo rohita

Impact of phosphamidon, an organophosphorus pesticide and its metabolites viz. dimethyl phosphoric acid and 2-chloro 2-diethyl carbamoylmethyl vinyl acid on histopathology of a common teleost, Labeo rohita was studied by exposing the fish to sub-lethal concentrations which were taken as 1/3rd of LC50 and were equal to 0.0123 ppm for phosphamidon, 0.0160 ppm for dimethyl phosphoric acid and 0.0167 ppm for 2-chloro 2-diethyl carbamoylmethyl vinyl acid respectively. The results revealed that hepatocytes in the liver were markedly swollen and exhibited hydropic degeneration. Fusion of primary lamellae and moderate congestion of blood vessels were evident in the gill. Intestine showed degeneration of mucosa and cellular infiltration in sub-mucosa. LC50 values and histopathological photomicrographs suggest that phosphamidon is more toxic as compared to dimethyl phosphoric and 2-chloro 2-diethyl carbamoylmethyl vinyl acid

Copper, zinc, iron and manganese in sediments and in the rock oyster Saccostrea cucullata in Mumbai coast

Sediment and oyster (Saccostrea cucullata) samples were collected at Dhanda, a fishing village in Mumbai, Maharashtra. The samples were analysed for copper, zinc, iron and manganese contents. Metal concentrations in the sediments and bioaccumulated levels in oysters were correlated. There is no positive correlation between the total sedimentary levels of metals analysed and the bioaccumulated levels of respective metals in oyster. A positive correlation between the bioavailable fractions of zinc, iron and manganese, and the bioaccumulated levels exists. Copper, however, shows a negative correlation with respect to the bioaccumulated levels

Nutrient profile of pond water in north-eastern state of Tripura and impact of water acidity on aquaculture productivity

Physicochemical parameters of 31 fish pond water samples of Tripura were studied to ascertain the nutrient profile of acidic soil zone and the impact of water acidity towards aquaculture productivity. The pH was acidic (mean 6.63±0.44) with high Fe (mean1.04±0.40 mglˉ¹) and AI (mean 2.67±2.41 mglˉ¹) contents. These were mostly responsible for pond water acidity and poor productivity with low nitrogen, phosphate and total alkalinity. The study also showed strong negative relationship between water pH and redox potential (R²=0.5251). However, pH was positively significant with electrical conductivity. The roles of redox potential and electrical conductivity in water acidity were found highly important. Available calcium content was also found low (mean 2.91±2.96 mglˉ¹). Elevating level of pH of pond water could be the possible management practices in acidic water so that such unproductive water might be productive enough with higher phosphate and nitrogen levels for better biological production

Clustering for binary data sets by using genetic algorithm-incremental K-means

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental Kmeans (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers

E-Recruiting : Anforderungen und Präferenzen von HR-Professionals

Karnal bunt disease in wheat is caused by hemibiotrophic fungus, Tilletia indica that has been placed as quarantine pest in more than 70 countries. Despite its economic importance, little knowledge about the molecular components of fungal pathogenesis is known. In this study, first time the genome sequence of T. indica has been deciphered for unraveling the effectors' functions of molecular pathogenesis of Karnal bunt disease. The T. indica genome was sequenced employing hybrid approach of PacBio Single Molecule Real Time (SMRT) and Illumina HiSEQ 2000 sequencing platforms. The genome was assembled into 10,957 contigs (N50 contig length 3 kb) with total size of 26.7 Mb and GC content of 53.99%. The number of predicted putative genes were 11,535, which were annotated with Gene Ontology databases. Functional annotation of Karnal bunt pathogen genome and classification of identified effectors into protein families revealed interesting functions related to pathogenesis. Search for effectors' genes using pathogen host interaction database identified 135 genes. The T. indica genome sequence and putative genes involved in molecular pathogenesis would further help in devising novel and effective disease management strategies including development of resistant wheat genotypes, novel biomarkers for pathogen detection and new targets for fungicide development