Influence of nitrogen sources on production of &#946b-galactosidase by Aspergillus niger

The study was undertaken to enhance the production of b-galactosidase using five organic nitrogen sources with wheat bran as a substrate under solid state fermentation. The microbial source Aspergillus niger and its DG-resistant mutant that were grown in medium with initial pH of 5.5 in 250 ml flasks at 30°C for 144 h and sample was harvested after every 24 h and analysed for substrate consumption, cell mass formation and enzyme production. All the nitrogen sources, ammonium sulphate, corn steep liquor, diammonium phosphate, fish meal and urea showed significant results. However, higher values of enzyme activity of 168.0 and 371.15 IU/l/h, parent and mutant, respectively, was obtained from sample in which corn steep liquor was used as a nitrogen source as compared tocontrol (73.1 and 176.3 IU/l/h in parent and mutant, respectively). The effect of nitrogen sources was also found significant in both the organisms but higher in mutant organism (2.2 fold). It is concluded that enzyme production enhanced 2.7 fold by use of suitable production medium under optimum cultural conditions and that the mutant derivative of A. niger can be exploited for hyper production of this enzyme

Barriers to green supply chain management: An emerging economy context

© 2019 Elsevier Ltd Green supply chain management is attracting increasing attention as a way to decrease the adverse environmental effects of industries worldwide. However, considering the context of an emerging economy like Bangladesh, green supply chain management is still in its inception and has not been widely embraced in the textile industry, and therefore barriers hindering its adoption in emerging economy context demand a comprehensive investigation. This research reviews the viewpoints and hurdles in adopting green supply chain management practices in the context of the Bangladeshi textile industry. A questionnaire survey of Bangladeshi textile practitioners of operations and supply chain management division, having a sample size of thirty, was undertaken to identify the barriers, and a hierarchical cluster analysis technique was used in the detailed analysis of this data. Opinions were sought from experts on the significance of the resulting clusters, considering the relative importance of the barriers. Fifteen barriers to the adoption of green supply chain management were identified in the review of the literature, with these barriers then analyzed by using the data collected from Bangladeshi textile industry practitioners. The research indicates that the most important barrier is that there is low demand from customers and financial constraint resulting from short term little financial benefit to businesses, with lack of government regulations also a commonly faced barrier in adopting green supply chain initiatives. This study will provide valuables insights to practitioners and relevant policy makers about the barriers prevailing in the emerging economies towards the adoption of green supply chain management practices, which, in turn, can guide to undertake appropriate steps for alleviating those barriers

Optimization of a stand - alone renewable energy system for a small load requirement

Optimization of a stand-alone Renewable Energy (RE) system involves selecting the best RE resources and components, and sizing the system accordingly to get the most efficient and cost-effective solution. Design and optimization of an RE power system to serve the lighting in a University of the South Pacific car park was carried out using HOMER software and compared to manual calculations. Resource analysis showed that on average the site received 3.8 kWh m−2 day−1 of solar energy, with 1,387 full sun hours annually. Monthly average wind speed of 3.88 m s−1 at 10 m above ground level extrapolated to 15 m (the hub height of the wind turbine) resulted in an average wind speed of 4 m s−1, with power density of 70 Wm−2. With this wind resource, a Whisper 100 wind turbine would be in operation for approximately 50 % of the time in the year. The complementary nature of solar and wind resources showed good potential for a solar-wind hybrid system. In this study three possible systems—a PV system, a wind power system, and a hybrid power system (PV-wind)—were analyzed. It was found that a hybrid system is the best and most cost-effective option, as it is able to provide reliable power whilst minimizing the need for battery storage compared to a single RE power system. The optimum system comprised 0.270 kWp PV combined with a 900 W Whisper wind turbine with total battery storage capacity of 440 Ah at 12 V. Manual calculations yielded results similar to the HOMER simulations

Heavy Metal Levels in Vegetables and Soil Cultivated with Industrial Wastewater from Different Sites of Chunian and Jamber, District, Kasur

In human diet, vegetables play important role to maintain the physiological conditions. Due to anthropogenic activities and pollution, the food items become contaminated. The present study was performed to evaluate the level of heavy metals in the vegetables irrigated with wastewater across Chunian and Jamber, district, Kasur. Level of heavy metals from the study area like Zinc, Lead and chromium in the soil, water and vegetables was compared. The four sites of each city and 10 vegetables e.g. potato, radish, carrot, fenugreek, spinach, tomato, Onion, Turnip, Cauliflower, Pangalo were selected to conduct the experiment. The vegetables were irrigated with industrial wastewater and the concentration of heavy metals was measured by the atomic absorption spectrophotometer (AAS). We concluded that the level of heavy metals was beyond the FAO limits in irrigated water due to industrial waste. In Jamber and Chunian, the level of Zn and Pb was high and beyond the FAO safe limits in the all water sample, the level of Cr was much higher only in the water sample of one site from Jamber. The concentration of zinc was higher in soil samples as compared to lead and chromium. Zn and Pb in vegetables of study area were labeled as priority pollutants but this concentration was within the safe limits set by FAO. However, constant inspection of heavy metals is recommended to avoid accumulation in the food chain and thus avoid human health risks. Keywords: Atomic absorption spectrophotometer, Heavy metals, Industrial wastewater, Vegetables

Calcitization of aragonitic bryozoans in Cenozoic tropical carbonates from East Kalimantan, Indonesia

© The Author(s) 2016. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The file attached is the published version of the article

Brain Tumor Segmentation from Multi-Spectral MR Image Data Using Random Forest Classifier

The development of brain tumor segmentation techniques based on multi-spectral MR image data has relevant impact on the clinical practice via better diagnosis, radiotherapy planning and follow-up studies. This task is also very challenging due to the great variety of tumor appearances, the presence of several noise effects, and the differences in scanner sensitivity. This paper proposes an automatic procedure trained to distinguish gliomas from normal brain tissues in multi-spectral MRI data. The procedure is based on a random forest (RF) classifier, which uses 80 computed features beside the four observed ones, including morphological ones, gradients, and Gabor wavelet features. The intermediary segmentation outcome provided by the RF is fed to a twofold post-processing, which regularizes the shape of detected tumors and enhances the segmentation accuracy. The performance of the procedure was evaluated using the 274 records of the BraTS 2015 train data set. The achieved overall Dice scores between 85-86% represent highly accurate segmentation