Snowpack response in the Assiniboine-Red River basin associated with projected global warming of 1.0 °C to 3.0 °C

This study assesses snow response in the Assiniboine-Red River basin, located in the Lake Winnipeg watershed, due to anthropogenic climate change. We use a process-based distributed snow model driven by an ensemble of eight statistically downscaled global climate models (GCMs) to project future changes under policy-relevant global mean temperature (GMT) increases of 1.0 °C to 3.0 °C above the pre-industrial period. Results indicate that basin scale seasonal warmings generally exceed the GMT increases, with greater warming in winter months. The majority of GCMs project wetter winters and springs, and drier summers, while autumn could become either drier or wetter. An analysis of snow water equivalent (SWE) responses under GMT changes reveal higher correlations of snow cover duration (SCD), snowmelt rate, maximum SWE (SWE_max) and timing of SWE_max with winter and spring temperatures compared to precipitation, implying that these variables are predominantly temperature controlled. Consequently, under the GMT increases from 1.0 °C to 3.0 °C, the basin will experience successively shorter SCD, slower snowmelt, smaller monthly SWE and SWE_max, earlier SWE_max, and a transition from snow-dominated to rain-snow hybrid regime. Further, while the winter precipitation increases for some GCMs compensate the temperature-driven changes in SWE, the increases for most GCMs occur as rainfall, thus limiting the positive contribution to snow storage. Overall, this study provides a detailed diagnosis of the snow regime changes under the policy-relevant GMT changes, and a basis for further investigations on water quantity and quality changes.     

Optimisation of immobilisation conditions for chick pea β-galactosidase (CpGAL) to alkylamine glass using response surface methodology and its applications in lactose hydrolysis

Response surface methodology was advantageously used to optimally immobilise a β-galactosidase from chick pea onto alkylamine glass using Box–Behnken experimental design, resulting in an overall 91% immobilisation efficiency. Analysis of variance was performed to determine the adequacy and significance of the quadratic model. Immobilised enzyme showed a shift in the optimum pH; however, optimum temperature remained unaffected. Thermal denaturation kinetics demonstrated significant improvement in thermal stability of the enzyme after immobilisation. Galactose competitively inhibits the enzyme in both soluble and immobilised conditions. Lactose in milk whey was hydrolysed at comparatively higher rate than that of milk. Immobilised enzyme showed excellent reusability with retention of more than 82% enzymatic activity after 15 uses. The immobilised enzyme was found to be fairly stable in both dry and wet conditions for three months with retention of more than 80% residual activity.     

Smart grid sensor data collection,communication, and networking: a tutorial

The smart grid is an innovative energy network that will improve the conventional electrical grid network to be more reliable, cooperative, responsive, and economical. Within the context of the new capabilities, advanced data sensing, communication, and networking technology will play a significant role in shaping the future of the smart grid. The smart grid will require a flexible and efficient framework to ensure the collection of timely and accurate information from various locations in power grid to provide continuous and reliable operation. This article presents a tutorial on the sensor data collection, communications, and networking issues for the smart grid. First, the applications of data sensing in the smart grid are reviewed. Then, the requirements for data sensing and collection, the corresponding sensors and actuators, and the communication and networking architecture are discussed. The communication technologies and the data communication network architecture and protocols for the smart grid are described. Next, different emerging techniques for data sensing, communications, and sensor data networking are reviewed. The issues related to security of data sensing and communications in the smart grid are then discussed. To this end, the standardization activities and use cases related to data sensing and communications in the smart grid are summarized. Finally, several open issues and challenges are outlined. Copyright © 2012 John Wiley & Sons, Ltd.     

A β-galactosidase from chick pea (Cicer arietinum) seeds: Its purification,biochemical properties and industrial applications

A β-galactosidase from Cicer arietinum seeds has been purified to apparent electrophoretic homogeneity using a combination of various fractionation and chromatographic techniques, giving a final specific activity of 220 units mg⁻¹, with approximately 1840 fold purification. Analysis of the protein by SDS–PAGE revealed two subunits with molecular masses of 48 and 38 kDa, respectively. These bands were further confirmed with LC–MS/MS, indicating that Chick pea β-galactosidase (CpGAL) is a heterodimer. Molecular mass was determined to be 85 kDa by Superose-12 FPLC column, which is in agreement with the molecular mass suggested by mass spectroscopy to be 83 kDa. The optimum pH of the enzyme was 2.8 and it hydrolysed o-nitrophenyl β-d galactopyranoside (ONPG) with a K_m value of 1.73 mM at 37 °C. The energy of activation (E_a) calculated in the range of 35 to 60 °C, using Arrhenius equation, was determined to be 11.32 kcal mol⁻¹. The enzyme could also hydrolyse lactose, with an optimum pH of 4.0 at 40 °C. K_m and E_a for lactose hydrolysis was found to be 10 mM and 10.57 kcal mol⁻¹, respectively. The enzyme was found to be comparatively thermostable showing maximum activity at 60 °C for both ONPG and lactose. Galactose was found to be the competitive inhibitor. β-Galactosidase also exhibited glycoproteineous properties when applied on Con-A Sepharose column. The enzyme was localised in germinated seeds with X-gal activity staining and shown to be expressed prominently at grown radical tip and seed coat. Sequence alignment of CpGAL with other known plant β-galactosidase showed high amino acid sequence homology.     

Improving within-genus tree species discrimination using the discrete wavelet transform applied to airborne hyperspectral data

Discrete wavelet analysis was assessed for its utility in aiding discrimination of three pine species (Pinus spp.) using airborne hyperspectral data (AVIRIS). Two different sets of Haar wavelet features were compared to each other and to calibrated radiance, as follows: (1) all combinations of detail and final level approximation coefficients and (2) wavelet energy features rather than individual coefficients. We applied stepwise discriminant techniques to reduce data dimensionality, followed by discriminant techniques to determine separability. Leave-one-out cross validation was used to measure the classification accuracy. The most accurate (74.2%) classification used all combinations of detail and approximation coefficients, followed by the original radiance (66.7%) and wavelet energy features (55.1%). These results indicate that application of the discrete wavelet transform can improve species discrimination within the Pinus genus.     

Fabrication of a potentiometric/amperometric bifunctional enzyme microbiosensor

We report the fabrication and functional characterization of a needle-type bifunctional enzyme microbiosensor that has, as technical novelty, simultaneously integrated a potentiometric and amperometric detection of an enzyme-catalyzed reaction at the tip of a pulled glass micropipet. The construction involved immobilizing an enzyme onto the platinized outer tip surface using the precipitation of electrodeposition paint with direct entrapment of the biocomponent in the slowly growing polymer film. Products of enzyme-substrate reaction could then be targeted in a dual-detection mode on one hand with the covered Pt layer at the tip region as amperometric detector and on the other hand with a proton-selective liquid membrane-based potentiometric sensor inside the open pipet tip. Completing and testing bifunctional glucose microsensors demonstrated the functionality of the proposed strategy. Synchronized amperometric and potentiometric detection of the addition of a glucose standard to a buffer solution became evident by observing stepwise increases in the amperometric H2O2 oxidation current and corresponding increases in the potential of the pH-selective sensor, which translates to a local pH decrease around the tip due to hydrolysis of enzymatically formed gluconic acid.     

Low temperature growth of boron nitride nanotubes on substrates

High growth temperatures (>1100 degrees C), low production yield, and impurities have prevented research progress and applications of boron nitride nanotubes (BNNTs) in the past 10 years. Here, we show that BNNTs can be grown on substrates at 600 degrees C. These BNNTs are constructed of high-order tubular structures and can be used without purification. Tunneling spectroscopy indicates that their band gap ranges from 4.4 to 4.9 eV.