Modeling of allergen proteins found in sea food products

Shellfish are a source of food allergens, and their consumption is the cause of severe allergic reactions in humans. Tropomyosins, a family of muscle proteins, have been identified as the major allergens in shellfish and mollusks species. Nevertheless, few experimentally determined three-dimensional structures are available in the Protein Data Base (PDB). In this study, 3D models of several homologous of tropomyosins present in marine shellfish and mollusk species (Chaf 1, Met e1, Hom a1, Per v1, and Pen a1) were constructed, validated, and their immunoglobulin E binding epitopes were identified using bioinformatics tools. All protein models for these allergens consisted of long alpha-helices. Chaf 1, Met e1, and Hom a1 had six conserved regions with sequence similarities to known epitopes, whereas Per v1 and Pen a1 contained only one. Lipophilic potentials of identified epitopes revealed a high propensity of hydrophobic amino acids in the immunoglobulin E binding site. This information could be useful to design tropomyosin-specific immunotherapy for sea food allergies.

Mathematical modeling of microwave dried celery leaves and determination of the effective moisture diffusivities and activation energy

Celery (Apium graveolens L. var. secalinum Alef) leaves with 50��0.07 g weight and 91.75��0.15% humidity (~11.21 db) were dried using 8 different microwave power densities ranging between 1.8-20 W g-1, until the humidity fell down to 8.95��0.23% (~0.1 db). Microwave drying processes were completed between 5.5 and 77 min depending on the microwave power densities. In this study, measured values were compared with predicted values obtained from twenty thin layer drying theoretical, semi-empirical and empirical equations with a new thin layer drying equation. Within applied microwave power density; models whose coefficient and correlation (R��) values are highest were chosen as the best models. Weibull distribution model gave the most suitable predictions at all power density. At increasing microwave power densities, the effective moisture diffusivity values ranged from 1.595 10-10 to 6.377 10-12 m2 s-1. The activation energy was calculated using an exponential expression based on Arrhenius equation. The linear relationship between the drying rate constant and effective moisture diffusivity gave the best fit.

Modeling and kinetic study of bio-ethanol production from soy protein concentrate by-product

Abstract The aim of this work was to evaluate a non-agitated process of bioethanol production from soybean molasses and the kinetic parameters of fermentation using a strain of Saccharomyces cerevisiae (ATCC�� 2345). Kinetic experiment was conducted in medium with 30% (w v-1) of soluble solids without supplementation or pH adjustment. The maximum ethanol concentration was in 44 hours, the ethanol productivity was 0.946 g L-1 h-1, the yield over total initial sugars (Y1) was 47.87%, over consumed sugars (Y2) was 88.08% and specific cells production rate was 0.006 h-1. The mathematical polynomial was adjusted to the experimental data and provided very similar parameters of yield and productivity. Based in this study, for one ton of soybean molasses can be produced 103 kg of anhydrous bioethanol.

Customer Need Assessment for Differentiation in Building Information Modeling

Building Information Modeling ��� BIM is widely spreading in the Architecture, Engineering, and Construction (AEC) industries. Manufacturers of building elements are also starting to provide more and more objects of their products. The ideal availability and distribution for these models is not yet stabilized. Usual goal of a manufacturer is to get their model into design as early as possible. Finding the ways to satisfy customer needs with a superior service would help to achieve this goal. This study aims to seek what case company���s customers want out of the model and what they think is the ideal way to obtain these models and what are the desired functionalities for this service. This master���s thesis uses a modified version of lead user method to gain understanding of what the needs are in a longer term. In this framework also benchmarking of current solutions and their common model functions is done. Empirical data is collected with survey and interviews. As a result this thesis provides understanding that what is the information customer uses when obtaining a model, what kind of model is expected to be achieved and how is should the process optimally function. Based on these results ideal service is pointed out.

Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities��� returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994���2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa k��ytt��ytymist����n ja jatkaa t��t�� uutta k��ytt��ytymist�� useiden periodien ajan, eiv��tk�� hy��dykefutuurien tuotot tee t��h��n poikkeusta. T��m��n ominaisuuden johdosta lineaaristen mallien sijasta ep��lineaariset mallit pystyv��t tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyv��t vangitsemaan t��m��n ominaisuuden ja siksi niist�� on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. T��m�� tutkimus k��ytt���� Markov regiiminvaihtomallia kuvaamaan yksitt��isten energiafutuurien tuottojen k��ytt��ytymist��, sill�� tutkimukset osoittavat hy��dykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvitt����, kuinka monta regiimi�� tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseill�� ja mitk�� ovat n��iden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan m����ritt��m��ll�� regiimien lukum����r�� tilastotieteellisen testauksen menetelmin sek�� tutkimalla energiafutuureja yksitt��in; ei indeksi- tai alaindeksitasolla. Tutkimuksessa k��ytet����n p��iv��-, viikko- ja kuukausiaikasarjoja Brent-raaka��ljyn, WTI-raaka��ljyn, maakaasun, l��mmitys��ljyn ja poltto��ljyn tuotoista aikav��lilt�� 1994���2014, silt�� osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien m����r��,jonka j��lkeen Markov regiiminvaihtomallia hy��dynt��en m����ritet����n yksitt��isten regiimientuottojakaumien ominaisuudet sek�� regiimien v��linen transitiomatriisi. Tulokset regiimien lukum����r��n osalta osoittavat, ett�� energiafutuurien p��iv��kohtaisten tuottojen aikasarjoissa regiimien lukum����r�� vaihtelee kolmen ja kuuden v��lill��. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukum����r�� on kaksi. Kun regiimej�� on enemm��n kuin kaksi, on prosessilla taipumus muodostaa regiimeist�� koostuvia ryhmi��. Prosessi pysyy ryhm��n sis��ll�� yleens�� pitk����n, koska todenn��k��isyys siirty�� ryhm����n kuuluvien regiimien v��lill�� on suuri. Yksitt��iset regiimit ryhm��n sis��ll�� eiv��t kuitenkaan ole kovin pysyvi��. N��in ollen prosessi vaihtelee ryhm��n sis��isten regiimien v��lill�� tiuhaan. Regiimit, jotka eiv��t kuulu ryhm����n, ovat yleens�� pysyvi��, mutta prosessi ajautuu niihin vain harvoin, sill�� todenn��k��isyys siirty�� muista regiimeist�� niihin on pieni. Tutkimuksen tulokset osoittavat my��s, ett�� prosesseissa, joita ohjaa kaksi regiimi��, n��m�� regiimit eiv��t v��ltt��m��tt�� ole pysyv��t bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, ett�� bear-markkinatilanne on energiafutuureissa selv��sti v��hemm��n pysyv��.

Threat modeling a factory environment using Microsoft Security Development Lifecycle methodology

The number of security violations is increasing and a security breach could have irreversible impacts to business. There are several ways to improve organization security, but some of them may be difficult to comprehend. This thesis demystifies threat modeling as part of secure system development. Threat modeling enables developers to reveal previously undetected security issues from computer systems. It offers a structured approach for organizations to find and address threats against vulnerabilities. When implemented correctly threat modeling will reduce the amount of defects and malicious attempts against the target environment. In this thesis Microsoft Security Development Lifecycle (SDL) is introduced as an effective methodology for reducing defects in the target system. SDL is traditionally meant to be used in software development, principles can be however partially adapted to IT-infrastructure development. Microsoft threat modeling methodology is an important part of SDL and it is utilized in this thesis to find threats from the Acme Corporation���s factory environment. Acme Corporation is used as a pseudonym for a company providing high-technology consumer electronics. Target for threat modeling is the IT-infrastructure of factory���s manufacturing execution system. Microsoft threat modeling methodology utilizes STRIDE ���mnemonic and data flow diagrams to find threats. Threat modeling in this thesis returned results that were important for the organization. Acme Corporation now has more comprehensive understanding concerning IT-infrastructure of the manufacturing execution system. On top of vulnerability related results threat modeling provided coherent views of the target system. Subject matter experts from different areas can now agree upon functions and dependencies of the target system. Threat modeling was recognized as a useful activity for improving security.

A software engineering approach to distributed systems for composite modeling

The goal of this thesis is to define and validate a software engineering approach for the development of a distributed system for the modeling of composite materials, based on the analysis of various existing software development methods. We reviewed the main features of: (1) software engineering methodologies; (2) distributed system characteristics and their effect on software development; (3) composite materials modeling activities and the requirements for the software development. Using the design science as a research methodology, the distributed system for creating models of composite materials is created and evaluated. Empirical experiments which we conducted showed good convergence of modeled and real processes. During the study, we paid attention to the matter of complexity and importance of distributed system and a deep understanding of modern software engineering methods and tools.

Dynamic modeling and simulation of the airflow cleaning device

The objective of the work is to study the flow behavior and to support the design of air cleaner by dynamic simulation.In a paper printing industry, it is necessary to monitor the quality of paper when the paper is being produced. During the production, the quality of the paper can be monitored by camera. Therefore, it is necessary to keep the camera lens clean as wood particles may fall from the paper and lie on the camera lens. In this work, the behavior of the air flow and effect of the airflow on the particles at different inlet angles are simulated. Geometries of a different inlet angles of single-channel and double-channel case were constructed using ANSYS CFD Software. All the simulations were performed in ANSYS Fluent. The simulation results of single-channel and double-channel case revealed significant differences in the behavior of the flow and the particle velocity. The main conclusion from this work are in following. 1) For the single channel case the best angle was 0 degree because in that case, the air flow can keep 60% of the particles away from the lens which would otherwise stay on lens. 2) For the double channel case, the best solution was found when the angle of the first inlet was 0 degree and the angle of second inlet was 45 degree . In that case, the airflow can keep 91% of particles away from the lens which would otherwise stay on lens.

Business modeling in turbulent environments

This study presents an agile tool set for the business modeling in companies, entering the turbulent environment. The study���s aim is to explore business modeling techniques and their tooling by utilizing a case study of a Finnish media monitoring company, expanding to the Russian market. This work proposes a tailored ���two-approach��� of business modeling development that analyzes both the past and future conditions of two key factors of business modeling for companies ��� internal and external environments. The study explores a case company by investigating the benefits and disadvantages of firm���s present business modeling tools, developing a new tooling and applying it to the case company. Among primary data utilization, such as interviews with media monitoring industry analysts and representatives of the competing companies, and academic experts, study leans up on the comprehensive analysis of Russian media monitoring niche and its players. This study benefits the business modeling research area and combines traditional analysis tools, such as market, PESTLE and competitor analyses, in a systemic manner, with the business modeling techniques. This transformation proceeds through applying of the integrated scenario, heat map and critical design issues��� analyses in the societal, industrial and competitive context of turbulent environments. The practical outcome of this approach is the development of agile business modeling tool set, customizable by company���s requirements.

Isolation of DNA sequences with homology to a degenerate FaRP oligonucleotide from the crayfish Procambarus clarkii

The neuropeptide Th1RFamide with the sequence Phe-Met-Arg-Phe-amide was originally isolated in the clam Macrocallista nimbosa (price and Greenberg, 1977). Since its discovery, a large family ofFl\1RFamide-related peptides termed FaRPs have been found to be present in all major animal phyla with functions ranging from modulation of neuronal activity to alteration of muscular contractions. However, little is known about the genetics encoding these peptides, especially in invertebrates. As FaRP-encoding genes have yet to be investigated in the invertebrate Malacostracean subphylum, the isolation and characterization ofFaRP-encoding DNA and mRNA was pursued in this project. The immediate aims of this thesis were: (1) to amplify mRNA sequences of Procambarus clarkii using a degenerate oligonucleotide primer deduced from the common amino acid sequence ofisolated Procambarus FaRPS, (2) to determine if these amplification products encode FaRP gene sequences, and (3) to create a selective cDNA library of sequences recognized by the degenerate oligonucleotide primer. The polymerase chain reaction - rapid amplification of cDNA ends (PCR-RACE) is a procedure in which a single gene-specific primer is used in conjunction with a generalized 3' or 5' primer to amplify copies ofthe region between a single point in the transcript and the 3' or 5' end of cDNA of interest (Frohman et aI., 1988). PCRRACE reactions were optimized with respect to primers used, buffer composition, cycle number, nature ofgenetic substrate to be amplified, annealing, extension and denaturation temperatures and times, and use of reamplification procedures. Amplification products were cloned into plasmid vectors and recombinant products were isolated, as were the recombinant plaques formed in the selective cDNA library. Labeled amplification products were hybridized to recombinant bacteriophage to determine ligated amplification product presence. When sequenced, the five isolated PCR-RACE amplification products were determined not to possess FaRP-encoding sequences. The 200bp, 450bp, and 1500bp sequences showed homology to the Caenorhabditis elegans cosmid K09A11, which encodes for cytochrome P450; transfer-RNA; transposase; and tRNA-Tyr, while the 500bp and 750bp sequences showed homology with the complete genome of the Vaccinia virus. Under the employed amplification conditions the degenerate oligonucleotide primer was observed to bind to and to amplify sequences with either 9 or 10bp of 17bp identity. The selective cDNA library was obselVed to be of extremely low titre. When library titre was increased, white. plaques were isolated. Amplification analysis of eight isolated Agt11 sequences from these plaques indicated an absence of an insertion sequence. The degenerate 17 base oligonucleotide primer synthesized from the common amino acid sequence ofisolated Procambarus FaRPs was thus determined to be non-specific in its binding under the conditions required for its use, and to be insufficient for the isolation and identification ofFaRP-encoding sequences. A more specific primer oflonger sequence, lower degeneracy, and higher melting temperature (TJ is recommended for further investigation into the FaRP-encoding genes of Procambarlls clarkii.

Isolation and analysis of a corprinus cinereus DNA fragment showing homology to a fimbrial cDNA from ustilago violacea

Surface proteinaceous fibrils, termed fimbriae, were first identified on gram negative bacteria in the 1940s. Fungal fimbriae, discovered some 25 years later, are found on members of all fungal classes. In the present study, polyclonal antiserum raised against the fimbrial proteins of U. vio/acea were used in order to identify antigenically related proteins from Coprinus cinereus and Schizophy//um commune. Two polypeptides with molecular masses of 37 and 39 kDa from C. cinereus were observed and confirm earlier results. A single previously unidentified 50 kDa polypeptide in S. commune crossreacted with the antiserum. The 50 kDa protein was found to consist of 3 isoforms with isoelectric points ranging from 5.6 to 5.8. A fimbrial cDNA derived from U. vio/acea was used to identify DNA restriction fragments from C. cinereus and S. commune showing homology to the fimbrial transcript of U. vio/acea. Heterologous hybridization with this cDNA was used in order to screen a C. cinereus genomic DNA library. A single clone, A2-3A, with a 14 kbp insert showed strong homology to the pfim3-1 cDNA. The region of homology, a 700 bp Xba I fragment, was subcloned into pUG19. This plasmid was refered to as pXX8. DNA sequence determinations of pXX8 and adjacent fragments from A2-3A suggested that the cloned DNA was a portion of the rONA repeat encoding the small subunit rRNA. DNA sequence analysis of pfim3-1 yielded an incomplete open reading frame. The predicted amino acid sequence codes for a 206 amino acid, 22 kDa polypeptide which contains a domain similar to a transmembrane domain from rat leukocyte antigen, GDS3. As well, an untranslated 576 nucleotide domain showed 81 % homology to pXX8 and 830/0 homology to the 188 rRNA sequence of Ustilago maydis. This sequence was found adjacent to a region of adenine-thymine base pairs presumed to represent the polyadenylation sequence of the fimbrial transcript. The size and extent of homology is sufficient to account for the hybridization of pfim3-1 to rDNA. It is suggested that this domain represents a completely novel regulatory domain within eukaryotes that may enable the observed rapid regeneration of fimbriae in U. violacea.

Modeling Metal Protein Complexes from Experimental Extended X-ray Absorption Fine Structure using Computational Intelligence

Experimental Extended X-ray Absorption Fine Structure (EXAFS) spectra carry information about the chemical structure of metal protein complexes. However, pre- dicting the structure of such complexes from EXAFS spectra is not a simple task. Currently methods such as Monte Carlo optimization or simulated annealing are used in structure refinement of EXAFS. These methods have proven somewhat successful in structure refinement but have not been successful in finding the global minima. Multiple population based algorithms, including a genetic algorithm, a restarting ge- netic algorithm, differential evolution, and particle swarm optimization, are studied for their effectiveness in structure refinement of EXAFS. The oxygen-evolving com- plex in S1 is used as a benchmark for comparing the algorithms. These algorithms were successful in finding new atomic structures that produced improved calculated EXAFS spectra over atomic structures previously found.