Quali-quantitative study of the phenolic and polyphenolic compounds and their antioxidant capacity in vegetal matrix processed with different technologies

Food technologies today mean reducing agricultural food waste, improvement of food security, enhancement of food sensory properties, enlargement of food market and food economies. Food technologists must be high-skilled technicians with good scientific knowledge of food hygiene, food chemistry, industrial technologies and food engineering, sensory evaluation experience and analytical chemistry. Their role is to apply the modern vision of science in the field of human nutrition, rising up knowledge in food science. The present PhD project starts with the aim of studying and improving frozen fruits quality. Freezing process in very powerful in preserve initial raw material characteristics, but pre-treatment before the freezing process are necessary to improve quality, in particular to improve texture and enzymatic activity of frozen foods. Osmotic Dehydration (OD) and Vacuum Impregnation (VI), are useful techniques to modify fruits and vegetables composition and prepare them to freezing process. These techniques permit to introduce cryo-protective agent into the food matrices, without significant changes of the original structure, but cause a slight leaching of important intrinsic compounds. Phenolic and polyphenolic compounds for example in apples and nectarines treated with hypertonic solutions are slightly decreased, but the effect of concentration due to water removal driven out from the osmotic gradient, cause a final content of phenolic compounds similar to that of the raw material. In many experiment, a very important change in fruit composition regard the aroma profile. This occur in strawberries osmo-dehydrated under vacuum condition or under atmospheric pressure condition. The increment of some volatiles, probably due to fermentative metabolism induced by the osmotic stress of hypertonic treatment, induce a sensory profile modification of frozen fruits, that in some way result in a better acceptability of consumer, that prefer treated frozen fruits to untreated frozen fruits. Among different processes used, a very interesting result was obtained with the application of a osmotic pre-treatment driven out at refrigerated temperature for long time. The final quality of frozen strawberries was very high and a peculiar increment of phenolic profile was detected. This interesting phenomenon was probably due to induction of phenolic biological synthesis (for example as reaction to osmotic stress), or to hydrolysis of polymeric phenolic compounds. Aside this investigation in the cryo-stabilization and dehydrofreezing of fruits, deeper investigation in VI techniques were carried out, as studies of changes in vacuum impregnated prickly pear texture, and in use of VI and ultrasound (US) in aroma enrichment of fruit pieces. Moreover, to develop sensory evaluation tools and analytical chemistry determination (of volatiles and phenolic compounds), some researches were bring off and published in these fields. Specifically dealing with off-flavour development during storage of boiled potato, and capillary zonal electrophoresis (CZE) and high performance liquid chromatography (HPLC) determination of phenolic compounds.

Microfluidic microbial fuel cell fabrication and rapid screening of electrochemically microbes

The demand for novel renewable energy sources, together with the new findings on bacterial electron transport mechanisms and the progress in microbial fuel cell design, have raised a noticeable interest in microbial power generation. Microbial fuel cell (MFC) is an electrochemical device that converts organic substrates into electricity via catalytic conversion by microorganism. It has represented a continuously growing research field during the past few years. The great advantage of this device is the direct conversion of the substrate into electricity and in the future, MFC may be linked to municipal waste streams or sources of agricultural and animal waste, providing a sustainable system for waste treatment and energy production. However, these novel green technologies have not yet been used for practical applications due to their low power outputs and challenges associated with scale-up, so in-depth studies are highly necessary to significantly improve and optimize the device working conditions. For the time being, the micro-scale MFCs show great potential in the rapid screening of electrochemically active microbes. This thesis presents how it will be possible to optimize the properties and design of the micro-size microbial fuel cell for maximum efficiency by understanding the MFC system. So it will involve designing, building and testing a miniature microbial fuel cell using a new species of microorganisms that promises high efficiency and long lifetime. The new device offer unique advantages of fast start-up, high sensitivity and superior microfluidic control over the measured microenvironment, which makes them good candidates for rapid screening of electrode materials, bacterial strains and growth media. It will be made in the Centre of Hybrid Biodevices (Faculty of Physical Sciences and Engineering, University of Southampton) from polymer materials like PDMS. The eventual aim is to develop a system with the optimum combination of microorganism, ion exchange membrane and growth medium. After fabricating the cell, different bacteria and plankton species will be grown in the device and the microbial fuel cell characterized for open circuit voltage and power. It will also use photo-sensitive organisms and characterize the power produced by the device in response to optical illumination.

Development of the Heat and Energy Concept Inventory: Preliminary Results on the Prevalence and Persistence of Engineering Students' Misconceptions

BACKGROUND Students frequently hold a number of misconceptions related to temperature, heat and energy. There is not currently a concept inventory with sufficiently high internal reliability to assess these concept areas for research purposes. Consequently, there is little data on the prevalence of these misconceptions amongst undergraduate engineering students. PURPOSE (HYPOTHESIS) This work presents the Heat and Energy Concept Inventory (HECI) to assess prevalent misconceptions related to: (1) Temperature vs. Energy, (2) Temperature vs. Perceptions of Hot and Cold, (3) Factors that affect the Rate vs. Amount of Heat Transfer and (4) Thermal Radiation. The HECI is also used to document the prevalence of misconceptions amongst undergraduate engineering students. DESIGN/METHOD Item analysis, guided by classical test theory, was used to refine individual questions on the HECI. The HECI was used in a one group, pre-test-post-test design to assess the prevalence and persistence of targeted misconceptions amongst a population of undergraduate engineering students at diverse institutions. RESULTS Internal consistency reliability was assessed using Kuder-Richardson Formula 20; values were 0.85 for the entire instrument and ranged from 0.59 to 0.76 for the four subcategories of the HECI. Student performance on the HECI went from 49.2% to 54.5% after instruction. Gains on each of the individual subscales of the HECI, while generally statistically significant, were similarly modest. CONCLUSIONS The HECI provides sufficiently high estimates of internal consistency reliability to be used as a research tool to assess students' understanding of the targeted concepts. Use of the instrument demonstrates that student misconceptions are both prevalent and resistant to change through standard instruction.

Engineering design motivations : a qualitative and quantitative analysis of university students

What motivates students to perform and pursue engineering design tasks? This study examines this question by way of three Learning Through Service (LTS) programs: 1) an on-going longitudinal study examining the impacts of service on engineering students, 2) an on-going analysis of an international senior design capstone program, and 3) an on-going evaluation of an international graduate-level research program. The evaluation of these programs incorporates both qualitative and quantitative methods, utilizing surveys, questionnaires, and interviews, which help to provide insight on what motivates students to do engineering design work. The quantitative methods were utilized in analyzing various instruments including: a Readiness assessment inventory, Intercultural Development Inventory, Sustainable Engineering through Service Learning survey, the Impacts of Service on Engineering Students’ survey, Motivational narratives, as well as some analysis for interview text. The results of these instruments help to provide some much needed insight on how prepared students are to participate in engineering programs. Additional qualitative methods include: Word clouds, Motivational narratives, as well as interview analysis. This thesis focused on how these instruments help to determine what motivates engineering students to pursue engineering design tasks. These instruments aim to collect some more in-depth information than the quantitative instruments will allow. Preliminary results suggest that of the 120 interviews analyzed Interest/Enjoyment, Application of knowledge and skills, as well as gaining knowledge are key motivating factors regardless of gender or academic level. Together these findings begin to shed light on what motivates students to perform engineering design tasks, which can be applied for better recruitment and retention in university programs.

Sediment yield reduction in an agricultural watershed

With proper application of Best Management Practices (BMPs), the impact from the sediment to the water bodies could be minimized. However, finding the optimal allocation of BMP can be difficult, since there are numerous possible options. Also, economics plays an important role in BMP affordability and, therefore, the number of BMPs able to be placed in a given budget year. In this study, two methodologies are presented to determine the optimal cost-effective BMP allocation, by coupling a watershed-level model, Soil and Water Assessment Tool (SWAT), with two different methods, targeting and a multi-objective genetic algorithm (Non-dominated Sorting Genetic Algorithm II, NSGA-II). For demonstration, these two methodologies were applied to an agriculture-dominant watershed located in Lower Michigan to find the optimal allocation of filter strips and grassed waterways. For targeting, three different criteria were investigated for sediment yield minimization, during the process of which it was found that the grassed waterways near the watershed outlet reduced the watershed outlet sediment yield the most under this study condition, and cost minimization was also included as a second objective during the cost-effective BMP allocation selection. NSGA-II was used to find the optimal BMP allocation for both sediment yield reduction and cost minimization. By comparing the results and computational time of both methodologies, targeting was determined to be a better method for finding optimal cost-effective BMP allocation under this study condition, since it provided more than 13 times the amount of solutions with better fitness for the objective functions while using less than one eighth of the SWAT computational time than the NSGA-II with 150 generations did.

New Trends in Networking, Computing, E-learning, Systems Sciences, and Engineering

This book provides the latest in a series of books growing out of the International Joint Conferences on Computer, Information and Systems Sciences and Engineering. It includes chapters in the most advanced areas of Computing, Informatics, Systems Sciences and Engineering. It has accessible to a wide range of readership, including professors, researchers, practitioners and students. This book includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Informatics, and Systems Sciences, and Engineering. It includes selected papers form the conference proceedings of the Ninth International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 2013). Coverage includes topics in: Industrial Electronics, Technology & Automation, Telecommunications and Networking, Systems, Computing Sciences and Software Engineering, Engineering Education, Instructional Technology, Assessment, and E-learning.

Ontologies and Methods for Interoperability of Engineering Analysis Models (EAMS) in an E-Design Environment

ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

Proceedings of the Twelfth Annual Biochemical Engineering Symposium

This work presents the proceedings of the twelfth symposium which was held at Kansas State University on April 24, 1982. Since a number of the contributions will be published in detail elsewhere, only brief reports are included here. Some of the reports describe current progress with respect to ongoing projects. Requests for further information should be directed to Dr. Peter Reilly at Iowa State University, Dr. V. G. Murphy at Colorado State University, Dr. Rakesh Bajpai at University of Missouri, Dr. Ed Clausen at University of Arkansas, Dr. L. T. Fan and Dr. L. E. Erickson at Kansas State University. ContentsA Kinetic Analysis of Oleaginous Yeast Fermentation by Candida curvata on Whey Permeate, B.D. Brown and K.H. Hsu, Iowa State University Kinetics of Biofouling in Simulated Water Distribution Systems Using CSTR, T.M. Prakash, University of Missouri Kinetics of Gas Production by C. acetobutylicum, Michael Doremus, Colorado State University Large Scale Production of Methane from Agricultural Residues, O.P. Doyle, G.C. Magruder, E.C. Clausen, and J.L. Gaddy, University of Arkansas The Optimal Process Design for Enzymatic Hydrolysis of Wheat Straw, M.M Gharpuray and L.T. Fan, Kansas State University Extractive Butanol Fermentation, Michael Sierks, Colorado State University Yields Associated with Ethyl Alcohol Production, M.D. Oner, Kansas State University Estimation of Growth Yield and Maintenance Parameters for Microbial Growth on Corn Dust, B.O. Solomon, Kansas State University Milling of Ensiled Corn, Andrzej Neryng, Iowa State University Protein Extraction from Alfalfa, Ravidranath Joshi, Colorado State University Analysis of Disaccharides by Capillary Gas Chromatography, Z.L. Nikolov, Iowa State University Characterization of High Viscosity Fermentations in Tower Fermentors, S.A. Patel and C.H. Lee, Kansas State University Utilization of Sugars in Sorghum Molasses by Clostridium acetobutylicum B. Hong, K.C. Shin, and L.T. Fan, Kansas State University

Prediction of bendig load capacity of timber beams by finite element method simulation of knots and grain deviation

A finite element model was used to simulate timberbeams with defects and predict their maximum load in bending. Taking into account the elastoplastic constitutive law of timber, the prediction of fracture load gives information about the mechanisms of timber failure, particularly with regard to the influence of knots, and their local graindeviation, on the fracture. A finite element model was constructed using the ANSYS element Plane42 in a plane stress 2D-analysis, which equates thickness to the width of the section to create a mesh which is as uniform as possible. Three sub-models reproduced the bending test according to UNE EN 408: i) timber with holes caused by knots; ii) timber with adherent knots which have structural continuity with the rest of the beam material; iii) timber with knots but with only partial contact between knot and beam which was artificially simulated by means of contact springs between the two materials. The model was validated using ten 45 × 145 × 3000 mm beams of Pinus sylvestris L. which presented knots and graindeviation. The fracture stress data obtained was compared with the results of numerical simulations, resulting in an adjustment error less of than 9.7%

Impacts and adaptive capacity as drivers for prioritizing agricultural adaptation to climate change in Europe

In the face of likely climate change impacts policy makers at different spatial scales need access to assessment tools that enable informed policy instruments to be designed. Recent scientific advances have facilitated the development of improved climate projections, but it remains to be seen whether these are translated into effective adaptation strategies. This paper uses existing databases on climate impacts on European agriculture and combines them with an assessment of adaptive capacity to develop an interdisciplinary approach for prioritising policies. It proposes a method for identifying relevant policies for different EU countries that are representative of various agroclimatic zones. Our analysis presents a framework for integrating current knowledge of future climate impacts with an understanding of the underlying socio-economic, agricultural and environmental traits that determine a region’s capacity for adapting to climate change.

LiDAR simulation in modelled orchards to optimise the use of terretrial laser scanners and derived vegetative measures

Light detection and ranging (LiDAR) technology is beginning to have an impact on agriculture. Canopy volume and/or fruit tree leaf area can be estimated using terrestrial laser sensors based on this technology. However, the use of these devices may have different options depending on the resolution and scanning mode. As a consequence, data accuracy and LiDAR derived parameters are affected by sensor configuration, and may vary according to vegetative characteristics of tree crops. Given this scenario, users and suppliers of these devices need to know how to use the sensor in each case. This paper presents a computer program to determine the best configuration, allowing simulation and evaluation of different LiDAR configurations in various tree structures (or training systems). The ultimate goal is to optimise the use of laser scanners in field operations. The software presented generates a virtual orchard, and then allows the scanning simulation with a laser sensor. Trees are created using a hidden Markov tree (HMT) model. Varying the foliar structure of the orchard the LiDAR simulation was applied to twenty different artificially created orchards with or without leaves from two positions (lateral and zenith). To validate the laser sensor configuration, leaf surface of simulated trees was compared with the parameters obtained by LiDAR measurements: the impacted leaf area, the impacted total area (leaves and wood), and th impacted area in the three outer layers of leaves.

Reliability and quality in the area of statistical thinking in Engineering

There is remarkable growing concern about the quality control at the time, which has led to the search for methods capable of addressing effectively the reliability analysis as part of the Statistic. Managers, researchers and Engineers must understand that 'statistical thinking' is not just a set of statistical tools. They should start considering 'statistical thinking' from a 'system', which means, developing systems that meet specific statistical tools and other methodologies for an activity. The aim of this article is to encourage them (engineers, researchers and managers) to develop a new way of thinking.

Physics and Mathematics in the Engineering Curriculum: Correlation with Applied Subjects

This paper presents a study in which the relationship between basic subjects (Mathematics and Physics) and applied engineering subjects (related to Machinery, Electrical Engineering, Topography and Buildings) in higher engineering education curricula is evaluated. The analysis has been conducted using the academic records of 206 students for five years. Furthermore, 34 surveys and personal interviews were conducted to analyze the connections between the contents taught in each subject and to identify student perceptions of the correlation with other subjects or disciplines. At the same time, the content of the different subjects have been analyzed to verify the relationship among the disciplines.Aproper coordination among subjects will allow students to relate and interconnect topics of different subjects, even with the ones learnt in previous courses, while also helping to reduce dropout rates and student failures in successfully accomplishing the different courses.