First metabolomic approach of the epiphytic bacteria-marine diatom Haslea ostrearia relationships

The marine diatom Haslea ostrearia [1] produces a water-soluble blue-pigment named marennine [2] of economic interest. But the lack of knowledge of the ecological conditions, under which this microalga develops in its natural ecosystem, more especially bacteria H. ostrearia interactions, prevents any optimization of its culture in well-controlled conditions. The structure of the bacterial community was analyzed by PCR-TTGE before and after the isolation of H. ostrearia cells recovered from 4 localities, to distinguish the relative part of the biotope and the biocenose and eventually to describe the temporal dynamic of the structure of the bacterial community at two time-scales. The differences in genetic fingerprints, more especially high between two H. ostrearia isolates (HO-R and HO-BM) showed also the highest differences in the bacterial structure [3] as the result of specific metabolomics profiles. The non-targeted metabolomic investigation showed that these profiles were more distinct in case of bacteria-alga associations than for the H. ostrearia monoculture Here we present a Q-TOF LC/MS metabolomic fingerprinting approach [3]: - to investigate differential metabolites of axenic versus non axenic H. ostrearia cultures. - to focus on the specific metabolites of a bacterial surrounding associated with the activation or inhibition of the microalga growing. The Agilent suite of data processing software makes feature finding, statistical analysis, and identification easier. This enables rapid transformation of complex raw data into biologically relevant metabolite information.

Preliminary metabolomic approach on the bacterial structure community of Haslea ostrearia

The marine diatom Haslea ostrearia [1] produces a water-soluble blue-pigment named marennine [2] of economic interest. But the lack of knowledge of the ecological conditions, under which this microalga develops in its natural ecosystem, more especially bacteria H. ostrearia interactions, prevents any optimization of its culture in well-controlled conditions. The structure of the bacterial community was analyzed by PCR-TTGE before and after the isolation of H. ostrearia cells recovered from 4 localities, to distinguish the relative part of the biotope and the biocenose and eventually to describe the temporal dynamic of the structure of the bacterial community at two time-scales. The differences in genetic fingerprints, more especially high between two H. ostrearia isolates (HO-R and HO-BM) showed also the highest differences in the bacterial structure [3] as the result of specific metabolomics profiles. The non-targeted metabolomic investigation showed that these profiles were more distinct in case of bacteria-alga associations than for the H. ostrearia monoculture Here we present a Q-TOF LC/MS metabolomic fingerprinting approach [3]: - to investigate differential metabolites of axenic versus non axenic H. ostrearia cultures. - to focus on the specific metabolites of a bacterial surrounding associated with the activation or inhibition of the microalga growing. The Agilent suite of data processing software makes feature finding, statistical analysis, and identification easier. This enables rapid transformation of complex raw data into biologically relevant metabolite information.

Anatomical biomarkers of body composition in oncological population: application and development of artificial intelligences

In the Era of precision medicine and big medical data sharing, it is necessary to solve the work-flow of digital radiological big data in a productive and effective way. In particular, nowadays, it is possible to extract information “hidden” in digital images, in order to create diagnostic algorithms helping clinicians to set up more personalized therapies, which are in particular targets of modern oncological medicine. Digital images generated by the patient have a “texture” structure that is not visible but encrypted; it is “hidden” because it cannot be recognized by sight alone. Thanks to artificial intelligence, pre- and post-processing software and generation of mathematical calculation algorithms, we could perform a classification based on non-visible data contained in radiological images. Being able to calculate the volume of tissue body composition could lead to creating clasterized classes of patients inserted in standard morphological reference tables, based on human anatomy distinguished by gender and age, and maybe in future also by race. Furthermore, the branch of “morpho-radiology" is a useful modality to solve problems regarding personalized therapies, which is particularly needed in the oncological field. Actually oncological therapies are no longer based on generic drugs but on target personalized therapy. The lack of gender and age therapies table could be filled thanks to morpho-radiology data analysis application.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

Non-Destructive Evaluation of Iowa Pavements Phase 2: Development of a Fully Automated Software System for Rapid Analysis/Processing of the Falling Weight Deflectometer Data, 2009

The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for rapid processing of the FWD data along with a user manual. The software system automatically reads the FWD raw data collected by the JILS-20 type FWD machine that Iowa DOT owns, processes and analyzes the collected data with the rapid prediction algorithms developed during the phase I study. This system smoothly integrates the FWD data analysis algorithms and the computer program being used to collect the pavement deflection data. This system can be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team. This report describes the developed software in detail and can also be used as a user-manual for conducting simulation studies and detailed analyses. *********************** Large File ***********************

A Multilingual Query Processing System using Software Agents

The goal of this work was developing a query processing system using software agents. Open Agent Architecture framework is used for system development. The system supports queries in both Hindi and Malayalam; two prominent regional languages of India. Natural language processing techniques are used for meaning extraction from the plain query and information from database is given back to the user in his native language. The system architecture is designed in a structured way that it can be adapted to other regional languages of India. . This system can be effectively used in application areas like e-governance, agriculture, rural health, education, national resource planning, disaster management, information kiosks etc where people from all walks of life are involved.

Scalable software architecture for on-line multi-camera video processing

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead

Thermal food processing optimization: Algorithms and software

The algorithms and graphic user interface software package ?OPT-PROx? are developed to meet food engineering needs related to canned food thermal processing simulation and optimization. The adaptive random search algorithm and its modification coupled with penalty function?s approach, and the finite difference methods with cubic spline approximation are utilized by ?OPT-PROx? package (http://tomakechoice. com/optprox/index.html). The diversity of thermal food processing optimization problems with different objectives and required constraints are solvable by developed software. The geometries supported by the ?OPT-PROx? are the following: (1) cylinder, (2) rectangle, (3) sphere. The mean square error minimization principle is utilized in order to estimate the heat transfer coefficient of food to be heated under optimal condition. The developed user friendly dialogue and used numerical procedures makes the ?OPT-PROx? software useful to food scientists in research and education, as well as to engineers involved in optimization of thermal food processing.

DEVELOPMENT OF INTEGRATED BIOPROCESSING TECHNOLOGIES FOR THE PRODUCTION OF PECTIC OLIGOSACCHARIDES (POS) FROM AGRO-PROCESSING RESIDUES

This research deals with the production of pectic oligosaccharides (POS) from agro-industrial residues, with specific focus on development of continuous cross flow enzyme membrane reactor. Pectic oligosaccharides have recently gained attention due to their prebiotic activity. Lack of information on the continuous production of POS from agro-industrial residues formed the basis for the present study. Four residues i.e sugar beet pulp, onion hulls, pressed pumpkin cake and berry pomace were taken to study their pectin content. Based on the presence of higher galacturonic acid and arabinose (both homogalacturonan and rhamnogalacturonan) in sugar beet pulp and galacturonic acid (only homogalacturonan) in onion hulls, further optimization of different extraction methods of pectin (causing minimum damage to pectic chain) from these residues were done. The most suitable extractant for sugar beet pulp and onion hulls were nitric acid and sodium hexametaphosphate respectively. Further the experiments on the continuous production of POS from sugar beet pulp in an enzyme membrane reactor was initiated. Several optimization experiments indicated the optimum enzyme (Viscozyme) as well as feed concentration (25 g/L) to be used for producing POS from sugar beet pulp in an enzyme membrane reactor. The results highlighted that steady state POS production with volumetric and specific productivity of 22g/L/h and 11 g/gE/h respectively could be achieved by continuous cross flow filtration of sugar beet pulp pectic extract over 10 kDa membrane at residence time of 20 min. The POS yield of about 80% could be achieved using above conditions. Also, in this thesis preliminary experiments on the production and characterization of POS from onion hulls were conducted. The results revelaed that the most suitable enzyme for POS production from onion hulls is endo-polygalacturonase M2. The POS produced from onion hulls were present in the form of DP1 -DP10 in substituted as well as unsubstituted forms. This study clearly demonstrates that continuous production of POS from pectin rich sources can be achieved by using cross flow continuous enzyme membrane reactor.

Software for Expert Information Processing During Carrying out the Examinations

The system of the automated carrying out of examinations is described. Opportunities of system, its architecture and structure of communications between functional subsystems are resulted. Features of the subsystems making system are described. Types of questions which can be used at carrying out of examination are listed. In the near future the working version of system will be ready to input in commercial operation.

Anodic porous alumina structural characteristics study based on SEM image processing and analysis

The present work reports the porous alumina structures fabrication and their quantitative structural characteristics study based on mathematical morphology analysis by using the SEM images. The algorithm used in this work was implemented in 6.2 MATLAB software. Using the algorithm it was possible to obtain the distribution of maximum, minimum and average radius of the pores in porous alumina structures. Additionally, with the calculus of the area occupied by the pores, it was possible to obtain the porosity of the structures. The quantitative results could be obtained and related to the process fabrication characteristics, showing to be reliable and promising to be used to control the pores formation process. Then, this technique could provide a more accurate determination of pore sizes and pores distribution. (C) 2008 Elsevier Ltd. All rights reserved.

Partial automation of database processing of simulation outputs from L-systems models of plant morphogenesis

Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Simulação, em software adequado, da sintomatologia vibracional de avarias mecânicas de máquinas rotativas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica na Área de Manutenção e Produção