Détermination de l'antigène HLA-G soluble dans le liquide folliculaire et dans le milieu de culture d'embryons comme indicateur du succès d'un traitement par FIV-ICSI [Soluble human leukocyte antigen-G (sHLA-G) in follicular fluid and embryo culture medium and its impact on pregnancy prediction in IVF-ICSI treatment]

In IVF around 70% of embryos fail to implant. Often more than one embryo is transferred in order to enhance the chances of pregnancy, but this is at the price of an increased multiple pregnancy risk. In the aim to increase the success rate with a single embryo, research projects on prognostic factors of embryo viability have been initiated, but no marker has found a routine clinical application to date. Effects of soluble human leukocyte antigen-G (sHLA-G) on both NK cell activity and on Th1/Th2 cytokine balance suggest a role in the embryo implantation process, but the relevance of sHLA-G measurements in embryo culture medium and in follicular fluid (FF) are inconsistent to date. In this study, we have investigated the potential of sHLA-G in predicting the achievement of a pregnancy after IVF-ICSI in a large number of patients (n = 221). sHLA-G was determined in media and in FF by ELISA. In both FF and embryo medium, no significant differences in sHLA-G concentrations were observed between the groups "pregnancy" and "implantation failure", or between the groups "ongoing" versus "miscarried pregnancies". Our results do not favour routine sHLA-G determinations in the FF nor in embryo conditioned media, with the current assay technology available.

Le projet "SYNAPSY": un point de rencontre entre clinique et neurosciences [The "SYNAPSY" project: where psychiatrists and neuroscientists meet].

The National Center of Competence in Research project "SYNAPSY" aims at identifying certain mechanisms of psychiatric and cognitive disorders, in order to improve the understanding and the genesis of such pathologies, and to promote the development of better diagnostic tools and of new therapeutic approaches. It provides an excellent opportunity for clinical psychiatrists and neuroscientists to develop a synergic mode of collaboration. On the basis of questions stemming from clinical practice and in the frame of patients cohorts, various research projects in neuroscience should lead to progresses that may have a considerable impact on clinical practice.

Iowa DOT Library Services, Collection, & Technology Assessment, TR-670, 2014

Assesses the impact of library services on research projects, proposes methods to improve the impact of library services on research projects, assesses current library technology systems and proposes upgrades, assesses current library collection infrastructure and propose upgrades, especially in regards to collection damage from water or fire; ascertains patron interest in mobile technologies and suggest development based on interest.

When several queens reign: how polygyny affects social life in ants

Astract: The aim of this thesis was to investigate how the presence of multiple queens (polygyny) affects social organization in colonies of the ant Formica exsecta. This is important because polygyny results in reduced relatedness among colony members and therefore reflects a potential paradox for altruistic cooperation being explained by inclusive fitness theory. The reason for this is that workers in polygynous colonies rear no longer only their siblings (high inclusive fitness gain) but also more distantly ox even unrelated brood (low or no inclusive fitness gain). All research projects conducted in this thesis are novel and significant contributions to the understanding of the social evolution of insect societies. We used a mixture of experimental and observational methodologies in laboratory and field colonies of F. exsecta to examine four important aspects of social life that are impacted by polygyny. First, we investigated the influence of queen number on colony sex allocation and found that the number of queens present in a colony significantly affects colony sex ratio investment. The data were consistent with the queen-replenishment hypothesis, which is based on the observation that newly mated queens are often recruited back to their parental nest. According to this theory, colonies containing many queens should only produce males due to local resource competition (i.e. related queens compete for common resources), whereas colonies hosting few queens benefit most from producing new queens to ensure colony survival. Second, we examined how reproduction is partitioned among nestmate queens. We detected a novel pattern of reproductive partitioning whereby a high proportion of queens were completely specialized in the production of only a subset of offspring classes produced within a colony, which might translate into great differences in reproductive success between queens. Third, we could demonstrate that F. exsecta workers indiscriminately reared highly related and unrelated brood although such nepotistic behaviour (preferential rearing of relatives) would be predicted by inclusive fitness theory. The absence of nepotism is probably best explained by its negative effects on overall colony efficiency. Finally, we conducted a detailed population genetic analysis, which revealed that the genetic population structure is different for queens and workers. Our data were best explained with queens forming family-based groups (multicolonial population structure), whereas workers from several nests seemed to be grouped into larger unites (unicolonial population structure) with workers moving freely between neighbouring nests. Altogether, the presented work significantly increased our understanding of the complex organization of polygynous social insect colonies and shows how an important life history trait such as queen number affects social organization at various levels. Résumé: Le but de cette thèse était d'étudier comment la présence de plusieurs reines par colonie (polygynie) influence la vie sociale chez la fourmi Formica exsecta. Ce sujet est important parce que la polygynie chez les insectes sociaux présente un passible paradoxe au niveau de la théorie du "fitness inclusive". Ce paradoxe est basé sur le fait que les ouvrières n'élèvent plus uniquement leurs frères et soeurs (gain de "fitness inclusive" maximale), mais également des individus moins ou pas du tout apparentés (gain de "fitness inclusive" réduit ou absent). Tous les projets de recherche présentés au cours de cette thèse apportent une meilleure compréhension et connaissance au niveau de l'organisation des colonies chez les insectes sociaux. Nous avons employé des méthodes d'observation et de laboratoire afin de mettre en évidence des aspects importants de la vie sociale chez les fourmis influencés par la polygynie. Quatre aspects ont été caractérisés : (1) l'influence du nombre de reines sur le sexe ratio produit par la colonie. Nous avons démontré que les colonies contenant beaucoup de reines produisaient rarement des reines tandis que les colonies contenant peu de reines souvent investissaient beaucoup de ressources dans la production des reines. Ces résultats sont en accord avec la "queen-replenishment hypothesis" qui est basé sur l'observation que les nouvelles reines sont recrutées dans la colonie où elles étaient nées. Cette hypothèse postule que la production des reines est défavorable dans les colonies contenant beaucoup de reines, parce que ces reines apparentées, rentrent en compétition pour des ressources communes. Au contraire, la production des reines est favorable dans des colonies contenant peu de reines afin d'assurer la survie de la colonie ; (2) comment les reines dans une colonie répartissent leur reproduction. Nous avons mis en évidence un nouveau pattern de cette répartition où une grande proportion de reines est complètement spécialisée dans la production d'un seul type de couvain ce qui probablement aboutit à des différences significatives entre reines dans le succès reproducteur ; (3) la capacité des ouvrières à discriminer un couvain de soeur d'un couvain non apparenté. Les résultats ont montré que les ouvrières ne font pas de discrimination entre le couvain de soeur et le couvain non apparenté ce qui n'est pas en accord avec la théorie de la "fitness inclusive". Cette absence de discrimination est probablement due à des effets négatifs comme par exemple la diminution de la production du couvain; (4) la structure génétique d'une population de F. exsecta. Nous avons mis en évidence que la structure génétique entre des groupes de reines est significativement différente de la structure génétique entre des groupes d'ouvrières. Les données suggèrent que les reines forment des groupes basés sur une structure familiale tandis que les ouvrières sont groupées dans des unités plus grandes.

Another way of thinking about ADHD: the predictive role of early attachment deprivation in adolescents' level of symptoms.

PURPOSE: Attention deficit and hyperactivity disorder (ADHD) is one of the most frequent disorders in childhood and adolescence. Both neurocognitive and environmental factors have been related to ADHD. The current study contributes to the documentation of the predictive relation between early attachment deprivation and ADHD. METHOD: Data were collected from 641 adopted adolescents (53.2 % girls) aged 11-16 years in five countries, using the DSM oriented scale for ADHD of the Child Behavior Checklist (CBCL) (Achenbach and Rescorla, Manual for the ASEBA school-age forms and profiles. University of Vermont, Research Center for Children, Youth and Families, Burlington, 2001). The influence of attachment deprivation on ADHD symptoms was initially tested taking into consideration several key variables that have been reported as influencing ADHD at the adoptee level (age, gender, length of time in the adoptive family, parents' educational level and marital status), and at the level of the country of origin and country of adoption (poverty, quality of health services and values). The analyses were computed using the multilevel modeling technique. RESULTS: The results showed that an increase in the level of ADHD symptoms was predicted by the duration of exposure to early attachment deprivation, estimated from the age of adoption, after controlling for the influence of adoptee and country variables. The effect of the age of adoption was also demonstrated to be specific to the level of ADHD symptoms in comparison to both the externalizing and internalizing behavior scales of the CBCL. CONCLUSION: Deprivation of stable and sensitive care in infancy may have long-lasting consequences for children's development.

A protocol for a systematic review on the impact of unpublished studies and studies published in the gray literature in meta-analyses.

BACKGROUND: Meta-analyses are particularly vulnerable to the effects of publication bias. Despite methodologists' best efforts to locate all evidence for a given topic the most comprehensive searches are likely to miss unpublished studies and studies that are published in the gray literature only. If the results of the missing studies differ systematically from the published ones, a meta-analysis will be biased with an inaccurate assessment of the intervention's effects.As part of the OPEN project (http://www.open-project.eu) we will conduct a systematic review with the following objectives:â-ª To assess the impact of studies that are not published or published in the gray literature on pooled effect estimates in meta-analyses (quantitative measure).â-ª To assess whether the inclusion of unpublished studies or studies published in the gray literature leads to different conclusions in meta-analyses (qualitative measure). METHODS/DESIGN: Inclusion criteria: Methodological research projects of a cohort of meta-analyses which compare the effect of the inclusion or exclusion of unpublished studies or studies published in the gray literature.Literature search: To identify relevant research projects we will conduct electronic searches in Medline, Embase and The Cochrane Library; check reference lists; and contact experts.Outcomes: 1) The extent to which the effect estimate in a meta-analyses changes with the inclusion or exclusion of studies that were not published or published in the gray literature; and 2) the extent to which the inclusion of unpublished studies impacts the meta-analyses' conclusions.Data collection: Information will be collected on the area of health care; the number of meta-analyses included in the methodological research project; the number of studies included in the meta-analyses; the number of study participants; the number and type of unpublished studies; studies published in the gray literature and published studies; the sources used to retrieve studies that are unpublished, published in the gray literature, or commercially published; and the validity of the methodological research project.Data synthesis: Data synthesis will involve descriptive and statistical summaries of the findings of the included methodological research projects. DISCUSSION: Results are expected to be publicly available in the middle of 2013.

Development of LRFD Design Procedures for Bridge Piles in Iowa – Field Testing of Steel H-Piles in Clay, Sand, and Mixed Soils and Data Analysis (Volume II), TR-583, 2011

In response to the mandate on Load and Resistance Factor Design (LRFD) implementations by the Federal Highway Administration (FHWA) on all new bridge projects initiated after October 1, 2007, the Iowa Highway Research Board (IHRB) sponsored these research projects to develop regional LRFD recommendations. The LRFD development was performed using the Iowa Department of Transportation (DOT) Pile Load Test database (PILOT). To increase the data points for LRFD development, develop LRFD recommendations for dynamic methods, and validate the results of LRFD calibration, 10 full-scale field tests on the most commonly used steel H-piles (e.g., HP 10 x 42) were conducted throughout Iowa. Detailed in situ soil investigations were carried out, push-in pressure cells were installed, and laboratory soil tests were performed. Pile responses during driving, at the end of driving (EOD), and at re-strikes were monitored using the Pile Driving Analyzer (PDA), following with the CAse Pile Wave Analysis Program (CAPWAP) analysis. The hammer blow counts were recorded for Wave Equation Analysis Program (WEAP) and dynamic formulas. Static load tests (SLTs) were performed and the pile capacities were determined based on the Davisson’s criteria. The extensive experimental research studies generated important data for analytical and computational investigations. The SLT measured load-displacements were compared with the simulated results obtained using a model of the TZPILE program and using the modified borehole shear test method. Two analytical pile setup quantification methods, in terms of soil properties, were developed and validated. A new calibration procedure was developed to incorporate pile setup into LRFD.

Development of LRFD Procedures for Bridge Pile Foundations in Iowa Volume III: Recommended Resistance Factors with Consideration of Construction Control and Setup, TR-584, 2012

The Federal Highway Administration (FHWA) mandated utilizing the Load and Resistance Factor Design (LRFD) approach for all new bridges initiated in the United States after October 1, 2007. As a result, there has been a progressive move among state Departments of Transportation (DOTs) toward an increased use of the LRFD in geotechnical design practices. For the above reasons, the Iowa Highway Research Board (IHRB) sponsored three research projects: TR-573, TR-583 and TR-584. The research information is summarized in the project web site (http://srg.cce.iastate.edu/lrfd/). Two reports of total four volumes have been published. Report volume I by Roling et al. (2010) described the development of a user-friendly and electronic database (PILOT). Report volume II by Ng et al. (2011) summarized the 10 full-scale field tests conducted throughout Iowa and data analyses. This report presents the development of regionally calibrated LRFD resistance factors for bridge pile foundations in Iowa based on reliability theory, focusing on the strength limit states and incorporating the construction control aspects and soil setup into the design process. The calibration framework was selected to follow the guidelines provided by the American Association of State Highway and Transportation Officials (AASHTO), taking into consideration the current local practices. The resistance factors were developed for general and in-house static analysis methods used for the design of pile foundations as well as for dynamic analysis methods and dynamic formulas used for construction control. The following notable benefits to the bridge foundation design were attained in this project: 1) comprehensive design tables and charts were developed to facilitate the implementation of the LRFD approach, ensuring uniform reliability and consistency in the design and construction processes of bridge pile foundations; 2) the results showed a substantial gain in the factored capacity compared to the 2008 AASHTO-LRFD recommendations; and 3) contribution to the existing knowledge, thereby advancing the foundation design and construction practices in Iowa and the nation.

Improving Concrete Overlay Construction, TR-600, 2010

Several road construction projects involving concrete overlays at the state and county levels in Iowa in 2009 were studied for construction techniques and methods. The projects that were evaluated consisted of sites in four Iowa counties: Osceola, Worth, Poweshiek, and Johnson counties. The construction techniques and methods that were studied included concrete overlays and material usage. By evaluating these methods, highway agencies can explore different ways of making road construction less costly and can minimize the amount of time that the traveling public is exposed to road construction.

Du traitement précoce des sujets à risque aux risques du traitement précoce. Le dilemme de la prévention des troubles psychotiques [From early treatment of psychosis risk to the risks of early intervention: the dilemma of psychosis prevention].

While the development of early psychosis intervention programs have improved outcome of such disorders, primary prevention strategies are still out of reach. The elaboration, over the last 15 years, of scales and criteria to identify populations at high risk for psychosis is a real progress, but their low specificity is still a major obstacle to their use outside of research projects. For this reason, even if "ultra high risk", subjects present with real psychiatric disorders and sometimes significant decrease in functioning level, the fact that only a small proportion will eventually develop full blown psychosis will probably lead to the rejection of a "psychosis risk syndrom" from the future DSM-V classification.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Embankment Quality and Assessment of Moisture Control Implementation, TR-677, 2016

A specification for contractor moisture quality control (QC) in roadway embankment construction has been in use for approximately 10 years in Iowa on about 190 projects. The use of this QC specification and the development of the soils certification program for the Iowa Department of Transportation (DOT) originated from Iowa Highway Research Board (IHRB) embankment quality research projects. Since this research, the Iowa DOT has applied compaction with moisture control on most embankment work under pavements. This study set out to independently evaluate the actual quality of compaction using the current specifications. Results show that Proctor tests conducted by Iowa State University (ISU) using representative material obtained from each test section where field testing was conducted had optimum moisture contents and maximum dry densities that are different from what was selected by the Iowa DOT for QC/quality assurance (QA) testing. Comparisons between the measured and selected values showed a standard error of 2.9 lb/ft3 for maximum dry density and 2.1% for optimum moisture content. The difference in optimum moisture content was as high as 4% and the difference in maximum dry density was as high as 6.5 lb/ft3 . The difference at most test locations, however, were within the allowable variation suggested in AASHTO T 99 for test results between different laboratories. The ISU testing results showed higher rates of data outside of the target limits specified based on the available contractor QC data for cohesive materials. Also, during construction observations, wet fill materials were often observed. Several test points indicated that materials were placed and accepted at wet of the target moisture contents. The statistical analysis results indicate that the results obtained from this study showed improvements over results from previous embankment quality research projects (TR-401 Phases I through III and TR-492) in terms of the percentage of data that fell within the specification limits. Although there was evidence of improvement, QC/QA results are not consistently meeting the target limits/values. Recommendations are provided in this report for Iowa DOT consideration with three proposed options for improvements to the current specifications. Option 1 provides enhancements to current specifications in terms of material-dependent control limits, training, sampling, and process control. Option 2 addresses development of alternative specifications that incorporate dynamic cone penetrometer or light weight deflectometer testing into QC/QA. Option 3 addresses incorporating calibrated intelligent compaction measurements into QC/QA.

Evaluation of Recycled Rubber in Asphalt Concrete, HR-330, Construction Report, 1991

Discarded tires present major disposal and environmental problems. The recycling of those tires in asphalt cement concrete is what this research deals with. The Iowa DOT and the University of Northern Iowa (UNI) are evaluating the use of discarded tires in asphalt rubber cement and rubber chip mixes. The project is located on US 61 between Blue Grass and Muscatine in Muscatine County. It contains four rubberized asphalt sections and control sections. One section consists of reacted rubber asphalt cement used in both the binder and surface courses, and one section, both lanes, contains a rubber chip mix. The reacted rubber asphalt and the rubber chip mixes were laid in July 1991. The project construction went well with a few problems of shoving and cracking of the mat. This report contains information about procedures and tests that were run and those that will be run. It also has a cost comparison since this is a major concern with the use of asphalt rubber. Evaluation of this project will continue for five years. Three more research projects containing rubberized asphalt were constructed in 1991 and another is to be constructed in 1992.

Paperikoneen vesi- ja energiatehokkuuden parantaminen

Työn tavoitteena oli laatia reaaliaikaiset vesi- ja energiatasenäytöt Stora Enso PublicationPaper Veitsiluodon tehtaalle, paperikone 5:lle. Tavoitteena oli myös simuloida kyseisen paperikonelinjan vesitase. Aluksi työssä piirrettiin lohkokaaviot taseita varten paperikoneen kaikista vettä tai energiaa sisältävistä jakeista. Näitä yksinkertaistettuja lohkokaavioita hyväksi käyttäen laadittiin taseidenlaskentakaavat, jotka testattiin tarkastuslaskelmien avulla. Vesi- ja energiataseista tehtiin myös suunnitelmat prosessinohjausjärjestelmän tasenäytöiksi. FlowMac-simulointiohjelmalla rakennetun paperikone 5 vesitaseen simulointimallin tulosten oikeellisuutta arvioitiin herkkyysanalyysin avulla. Tehdyn herkkyysanalyysin tuloksien perusteella voidaan olettaa, että simulointimalli toimii luotettavasti. Tämän vesitaseen simulointimallin avulla tarkasteltiin kiekkosuotimien uudistamisen vaikutuksia paperikonelinjan vesitaseeseen. Tarkastelussa huomattiin, että vaihtamalla kiekkosuotimien syöttöventtiilit kolmea jaetta tuottaviksi, voitaisiin flotaatioallas ja suihkuveden kaarisihti poistaa käytöstä. Tulevaisuudessa simulointimallia voidaan käyttää myös monilla muilla eri tavoin hyödyksi kyseisellä paperikoneella. Työssä laaditut vesi- ja energiataseet saatiin niin tarkoiksi kuin se nykyisiä mittauksia hyödyntäen on mahdollista. Jostaseita haluttaisiin tarkentaa, olisi paperikonelinjalle syytä lisätä joitakin mittauksia. Myös työssä tehty vesitaseen simulointi FlowMac:lla onnistui hyvin mutta kyseisessä ohjelmassa havaittiin silti joitakin kehittämistarpeita. Työn tuloksien perusteella vettä ja energiaa voitaisiin mahdollisesti säästää paperikone 5:llä esimerkiksi laimennussäätöisen perälaatikon avulla, kiekkosuotimien uusimisella sekä kenkäpuristimen käyttöönotolla. Jatkotutkimuskohteita voisivat olla esimerkiksi paperikone 5:n lämpötase, kemiallisesti puhdistetun veden tulolämpötilan nostaminen, hiomon suodosveden ylimääräisen lämmön hyödyntäminen paperikone 5 kirkassuodoksen lämmittämisen jälkeen, lämmön talteenotossa lämmitysvesikennon ja prosessivesikennon järjestyksen vaihtaminen sekä vastaavien vesi- ja energiataseiden laatiminen paperikone 1:lle ja hiomolle.

Effectiveness of antioxidants in preventing oxidation of palm oil enriched with heme iron: A model for iron fortification in baked products

Bakery products such as biscuits, cookies, and pastries represent a good medium for iron fortification in food products, since they are consumed by a large proportion of the population at risk of developing iron deficiency anemia, mainly children. The drawback, however, is that iron fortification can promote oxidation. To assess the extent of this, palm oil added with heme iron and different antioxidants was used as a model for evaluating the oxidative stability of some bakery products, such as baked goods containing chocolate. The palm oil samples were heated at 220°C for 10 min to mimic the conditions found during a typical baking processing. The selected antioxidants were a free radical scavenger (tocopherol extract (TE), 0 and 500 mg/kg), an oxygen scavenger (ascorbyl palmitate (AP), 0 and 500 mg/kg), and a chelating agent (citric acid (CA), 0 and 300 mg/kg). These antioxidants were combined using a factorial design and were compared to a control sample, which was not supplemented with antioxidants. Primary (peroxide value and lipid hydroperoxide content) and secondary oxidation parameters (p-anisidine value, p-AnV) were monitored over a period of 200 days in storage at room temperature. The combination of AP and CA was the most effective treatment in delaying the onset of oxidation. TE was not effective in preventing oxidation. The p-AnV did not increase during the storage period, indicating that this oxidation marker was not suitable for monitoring oxidation in this model.