Immobilization of glucoamylase on magnetic poly(styrene) particles

Magnetic poly(styrene) particles including active groups were prepared for enzyme immobilization without any activation process. Glucoamylase, which is widely used in industry, was immobilized onto these particles. The effects of pH, buffer concentration, and temperature on immobilization were investigated; moreover, the effect of immobilization temperature on immobilized glucoamylase activity was determined for the hydrolysis of maltose. The acetate buffer with the concentration of 6 × 10⁻⁴ M at pH 4 and 20–30°C was found as the most suitable medium for the immobilization of the glucoamylase. The amount of bound protein is 8 mg/g particle with the immobilization yield of 70%. The maximum activity obtained with immobilized glucoamylase is approximately 70% of the free one. © 1999 John Wiley & Sons, Inc. J Appl Polym Sci 72: 69–73, 1999     

A Novel Approach to Limit Chemical Deterioration of Gilthead Sea Bream (Sparus aurata) Fillets: Coating with Electrospun Nanofibers as Characterized by Molecular,Thermal, and Microstructural Properties

Coating of sea bream fillets with thymol loaded chitosan based electrospun nanofibers (TLCN) and chitosan based nanafibers (CN) has been presented a novel approach to delay chemical deterioration. We assessed CN and TLCN with respect of scanting of total volatile basic nitrogen (TVBN), trimethylamine (TMA), thiobarbituric acid (TBA) deterioration during cold storage condition. Electrospinning process was applied to obtain TLCN and CN. Both of nanofibers obtained from biopolymer and bioactive material were cylindrical, smooth, beadless. Thermal, molecular, zeta potential (ZP), and surface properties of the groups were investigated, revealing that CN indicated molecular interactions with thymol in nanofibers, reduce in physical properties of these structures, thermal decomposition (an alteration in mass of CN and TLCN at temperatures below 190 °C, corresponding to 20.53% and 19.97%, respectively) and also dispersion stabilities (ζ potential) of CN and TLCN were determined 33.68 ± 3.35 and 21.85 ± 1.96 mV, respectively. TVBN and TMA stability analyses demonstrated that CN and TLCN were both effective in delaying chemical deterioration of fish fillets, furthermore TLCN was more effective against chemical deterioration. TBA analyses results of fish fillets indicated that CN and TLCN delayed rancidity in fish meat as compared to control group samples. The presented study results suggested that coating of the sea bream fillets with CN and TLCN would be a promising approach to delay the chemical deterioration of fish fillets.     

Effect of an organic compound (Methyl Red) interfacial layer on the calculation of characteristic parameters of an Al/Methyl Red/p-Si sandwich Schottky barrier diode

An Al/Methyl Red/p-Si sandwich Schottky barrier diode (SBD) has been fabricated by adding a solution of the organic compound Methyl Red in chloroform onto a p-Si substrate, and then evaporating the solvent. Current-voltage (I-V) measurements of the Al/Methyl Red/p-Si sandwich SBD have been carried out at room temperature and in the dark. The Al/Methyl Red/p-Si sandwich SBD demonstrated rectifying behavior. Barrier height (BH) and ideality factor values of 0.855 eV and 1.19, respectively, for this device have been determined from the forward-bias I-V characteristics. The Al/Methyl Red/p-Si sandwich SBD showed non-ideal I-V behavior with the value of ideality factor greater than unity. The energy distribution of the interface state density determined from I-V characteristics increases exponentially with bias from 3.68 × 10¹² cm^− 2 eV^− 1 at (0.81 − E_v) eV to 9.99 × 10¹³ cm^− 2 eV^− 1 at (0.69 − E_v) eV.     

Parallel four‐dimensional Haralick texture analysis for disk‐resident image datasets

Texture analysis is one possible method of detecting features in biomedical images. During texture analysis, texture‐related information is found by examining local variations in image brightness. Four‐dimensional (4D) Haralick texture analysis is a method that extracts local variations along space and time dimensions and represents them as a collection of 14 statistical parameters. However, application of the 4D Haralick method on large time‐dependent image datasets is hindered by data retrieval, computation, and memory requirements. This paper describes a parallel implementation using a distributed component‐based framework of 4D Haralick texture analysis on PC clusters. The experimental performance results show that good performance can be achieved for this application via combined use of task‐ and data‐parallelism. In addition, we show that our 4D texture analysis implementation can be used to classify imaged tissues. Copyright © 2006 John Wiley & Sons, Ltd.     

LONG‐TERM VEGETATION DYNAMICS AFTER HIGH‐DENSITY SEEDLING ESTABLISHMENT: IMPLICATIONS FOR RIPARIAN RESTORATION AND MANAGEMENT

Human disturbances have contributed to the deterioration of many western US rivers in the past century. Cottonwood‐willow communities, present historically along the Colorado River, protect watersheds and provide wildlife habitat, but are now among the most threatened forests. As a result, restoration efforts have increased to re‐establish and maintain cottonwood‐willow stands. While successful establishment has been observed using multiple strategies with varying investments, few projects are evaluated to quantify efficacy and determine long‐term sustainability. We monitored a seeded cottonwood‐willow site over a five‐year period beginning in 2007, with particular interest in how density affected vegetation diversity and stand structure over time. Fremont cottonwood (Populus fremontii) and volunteer tamarisk (Tamarix ramosissma) were the only abundant riparian trees at the site after one year. P. fremontii, compared to T. ramosissma, had higher growth rates, lower mortality, and dominated overstory and total cover each year. Vegetation diversity decreased from 2007–2009, but was similar from 2009–2011 as a result of decreased herbaceous and increased shrub species richness. Diversity was highest in the lowest density class (1‐12 stems/m²), but similar among all other classes (13–24, 25–42, 43+). High initial woody species densities resulted in single‐stemmed trees with depressed terminal and radial growths. Allometry, relating height to DBH at different densities, could prove to be an important tool for long‐term restoration management and studying habitat suitability. Understanding long‐term trends at densely‐planted or seeded sites can benefit restoration managers who aim to establish specific community structure and vegetation diversity for wildlife habitat. Copyright © 2012 John Wiley & Sons, Ltd.     

Differential Scanning Calorimetry Analysis of Goat Fats: Comparison of Chemical Composition and Thermal Properties

The physical–chemical properties, fatty acid composition and thermal properties of goat subcutaneous (SF), tallow (TF) and intestinal (IF) fats were determined. SF differed from other fat types with respect to its lower melting (41.6 °C), lower saponification (190.3 mg KOH/g) and higher iodine (40.4) values as compared to those of other fats. Goat fat types contained palmitic acid (C_16:0), stearic acid (C_18:0), oleic acid (C_18:1ω9) and linoleic acid (C_18:2ω6) as the major components of the fatty acid composition (23.06–23.52, 22.95–39.03, 21.94–36.16 and 1.96–2.22%, respectively). A differential scanning calorimetry (DSC) study revealed that two characteristic peaks were detected in both crystallization and melting curves. Major peaks (T _peak) of TF and IF were similar and determined as 34.02–35.24 and 9.95–10.72 °C, respectively for the crystallization peaks and 15.11–18.26 and 50.70–52.76 °C, respectively for the melting peaks in the DSC curves; but those of SF (27.14 and 4.36 °C for crystallization peaks and 8.39 and 44.93 °C for melting peaks) differed remarkably from those of other fat types.     

The enhancement of the cell-based GIS analyses with fuzzy processing capabilities

In order to store and process natural phenomena in Geographic Information Systems (GIS) it is necessary to model the real world to form computational representation. Since classical set theory is used in conventional GIS softwares to model uncertain real world, the natural variability in the environmental phenomena cannot be modeled appropriately. Because, pervasive imprecision of the real world is unavoidably reduced to artificially precise spatial entities when the conventional crisp logic is used for modeling.An alternative approach is the fuzzy set theory, which provides a formal framework to represent and reason with uncertain information. In addition, linguistic variable concept in a fuzzy logic system is useful for communicating concepts and knowledge with human beings. FuzzyCell is a system designed and implemented to enhance commercial GIS software, namely ArcMap^® with fuzzy set theory. FuzzyCell allows users to (a) incorporate human knowledge and experience in the form of linguistically defined variables into GIS-based spatial analyses, (b) handle imprecision in the decision-making processes, and (c) approximate complex ill-defined problems in decision-making processes and classification. It provides eight membership functions, inference methods, methods for rule aggregation, operators for set operations and methods for defuzzification.The operation of FuzzyCell is presented through case studies, which demonstrate its application for classification and decision-making processes. This paper shows how fuzzy logic approach may contribute to a better representation and reasoning with imprecise concepts, which are inherent characteristics of geographic data stored and processed in GIS.     

Visualization of large data sets with the Active Data Repository

We implement ray-casting-based volume rendering and isosurface rendering methods using the Active Data Repository (ADR) for visualizing out-of-core data sets. We have developed the ADR object-oriented framework to provide support for applications that employ range queries with user-defined mapping and aggregation operations on large-scale multidimensional data. ADR targets distributed-memory parallel machines with one or more disks attached to each node. It is designed as a set of modular services implemented in C++, which can be customized for application-specific processing. The ADR runtime system supports common operations such as memory management, data retrieval, and scheduling of processing across a parallel machine     

Optimizing the execution of multiple data analysis queries on parallel and distributed environments

We investigate techniques for efficiently executing multiquery workloads from data and computation-intensive applications in parallel and/or distributed computing environments. In this context, we describe a database optimization framework that supports data and computation reuse, query scheduling, and active semantic caching to speed up the evaluation of multiquery workloads. Its most striking feature is the ability of optimizing the execution of queries in the presence of application-specific constructs by employing a customizable data and computation reuse model. Furthermore, we discuss how the proposed optimization model is flexible enough to work efficiently irrespective of the parallel/distributed environment underneath. In order to evaluate the proposed optimization techniques, we present experimental evidence using real data analysis applications. For this purpose, a common implementation for the queries under study was provided according to the database optimization framework and deployed on top of three distinct experimental configurations: a shared memory multiprocessor, a cluster of workstations, and a distributed computational Grid-like environment.