Production and characteristics comparison of crude beta-glucosidases produced by microorganisms Thermoascus aurantiacus e Aureobasidium pullulans in agricultural wastes

The purified beta-glucosidase of Aureobasidium pullulans ER-16 is one of more thermostable enzyme reported to date. Considering the unfeasibility of using purified enzyme for industrial application, it was interesting to analyze this property for the crude enzyme. Thermophilic fungus Thermoascus aurantiacus CBMAI-756 and mesophilic A. pullulans ER-16 were cultivated in different hemicellulosic materials on solid-state cultivation for beta-glucosidase production. Wheat bran was most appropriate for beta-glucosidase production by both microorganisms. T. aurantiacus exhibited maximum enzyme production (7.0 U/ml or 70 U/g) at 48-72 h and A. pullulans a maximum (1.3 U/ml or 13 U/g) at 120 h. Maximum activities were at 75 degrees C with optimum pH at 4.5 and 4.0, for T aurantiacus and A. pullulans, respectively. A. pullulans`s beta-glucosidase was more pH stable (4.5-10.0 against 4.5-8.0) and more thermostable (90% after 1 h at 75 degrees C against 85% after 1 h at 70 degrees C) than the enzyme from the thermophilic T. aurantiacus. The t((1/2)) at 80 degrees C were 50 and 12.5 min for A. pullulans and T. aurantiascus, respectively. These data confirm the high thermostability of crude beta-glucosidase from A. pullulans. Both beta-glucosidases were strongly inhibited by glucose, but ethanol significantly increased the activity of the enzyme from T. aurantiacus. (C) 2008 Elsevier Inc. All rights reserved.

Formal derivation of finite state machines for class testing

Previous work on generating state machines for the purpose of class testing has not been formally based. There has also been work on deriving state machines from formal specifications for testing non-object-oriented software. We build on this work by presenting a method for deriving a state machine for testing purposes from a formal specification of the class under test. We also show how the resulting state machine can be used as the basis for a test suite developed and executed using an existing framework for class testing. To derive the state machine, we identify the states and possible interactions of the operations of the class under test. The Test Template Framework is used to formally derive the states from the Object-Z specification of the class under test. The transitions of the finite state machine are calculated from the derived states and the class's operations. The formally derived finite state machine is transformed to a ClassBench testgraph, which is used as input to the ClassBench framework to test a C++ implementation of the class. The method is illustrated using a simple bounded queue example.

Patents and the CGIAR system of International Agricultural Research Centres' germplasm collections under the International Treaty on Plant Genetic Resources for Food and Agriculture

A key controversy in negotiating the International Treaty on Plant Genetic Resources for Food and Agriculture, and the likely long-term effectiveness of the agreement, is the way in which the intellectual property provisions are interpreted and applied to the key genetic resources forming the Consultative Group on International Agricultural Research (CGIAR) system of International Agricultural Research Centres' (IARC) collections. This paper reviews the intellectual property provisions in the treaty and examines the likely consequences from patenting under the Patents Act 1990 over materials derived from these collections. The consequence is argued to be significant and, over time, these practices are likely to deplete the usefulness of these collections and undermine the relevance of the treaty. The paper concludes that Australia's interests might best be served by arguing that access to these collections, and the other materials under the treaty, be subject to a non-exclusive, royalty free licence for any use of the derived materials to develop useful new plant varieties.

Reshaping the global agricultural landscape: perspectives from Brazil

This article highlights the main changes observed in Brazilian agriculture and analyzes the connections of the observed changes in global agriculture. My approach to the analysis focuses the main drivers of changes, where institutions play a central role. Three driving forces are are considered: first, the effects of global demand for food, fiber, and energy; second, the sustainability debate; and third, the bio-energy paradigm. Each driver presents both local as well as global effects. The article does not emphasize the impact changes in Brazil had on the global agricultural landscape but argues that the impacts run from local and global changes, which cannot be discussed separately.

Customer Perception about Loyalty Programs in Agricultural Market: a case study

This study discusses the use of loyalty programs and Customer perception in, agricultural market. The theoretical review includes relationship marketing, its objectives, dimensions and instruments, and loyalty programs. The method for the empirical part consisted on qualitative research, through a case study conducted at one of the largest crop protection chemical companies in Brazil. The case is representative once this company was pioneer in its segment in adopting the customer relationship management. (CRM) approach to-their clients: It has been a consensus that customer relationship is a tool to amplify the Customer share. This.,is so, due the. increasing competition generated by the entrance of generic products and the retaliation actions adopted by the multinational groups. The case study includes a market overview, a description of the company, its loyalty program, the image of the program from the customer`s perspective, and the main results acquired with the CRM program. The Study also presents some recommendations for-companies that are pursuing strategies to. increase their customer share through loyalty programs.

A history of agricultural production at Neolithic Catalhoyuk East, Turkey

A history of agricultural production is proposed for Neolithic Catalhoyuk East, central Turkey, using archaeobotanical, environmental, population and settlement studies. In the aceramic early phase of site occupation, intensive strategies developed as changes in population and environment caused stress on food supplies produced within a limited territory. Food exchange may have been part of the social means by which Catalhoyuk and nearby contemporary settlements amalgamated into the single site of the main occupation phase. Population change, inherited territories and continuing environmental impact led to the development of an extensive system of agriculture using widely dispersed dry soils, with an intensive regime applied to nearby alluvial soils. Social tensions caused by the evolution of this system contributed to the fissioning of the site by the Chalcolithic.

Limited ecoclinal variation found in Malva parviflora (small-flowered mallow) across the Mediterranean-climatic agricultural region of Western Australia

Malva parviflora L. populations were collected from 24 locations across the Mediterranean-climatic agricultural region of Western Australia and grown in Perth in a common garden experiment. Seventeen morphometric and taxonomic measurements were taken and genetic variation was investigated by performing principal components analysis (PCA). Taxonomic measurements confirmed that all plants used in the study were M. parviflora. Greater variation occurred within populations than between populations. Separation between populations was only evident between northern and southern populations along principal components 2 (PC2), which was due mainly to flowering time. Flowering time and consequently photoperiod were highly correlated with latitude and regression analysis revealed a close relationship (r(2) = 0.6). Additionally, the pollination system of M. parviflora was examined. Plants were able to self-pollinate without the need for external vectors and the pollen ovule ratio (31 +/- 1.3) revealed that M. parviflora is most likely to be an obligate inbreeder with a slight potential for outcrossing. The limited variation of M. parviflora enhances the likelihood of suitable control strategies being effective across a broad area.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.