Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Multivariate genetic divergence and hybrid performance of cacao (Theobroma cacao L.)

Genetic distances among cacao cultivars were calculated through multivariate analysis, using the D2 statistic, to examine racial group classification and to assess heterotic hybrids. A 5 x 5 complete diallel was evaluated. Over a five-year period (1986-1990), five cultivars of the S1 generation, pertaining to the Lower Amazon Forastero and Trinitario racial groups and 20 crosses between the corresponding S0 parents were analyzed, based upon five yield components - number of healthy and collected fruits per plant (NHFP and NCFP), wet seed weight per plant and per fruit (WSWP and WSWF), and percentage of diseased fruits per plant (PDFP). The diversity analysis suggested a close relationship between the Trinitario and Lower Amazon Forastero groups. A correlation coefficient (r) was calculated to determine the association between genetic diversity and heterosis. Genetic distance of parents by D2 was found to be linearly related to average performance of hybrids for WSWP and WSWF (r = 0.68, P < 0.05 and r = 0.76, P < 0.05, respectively). The heterotic performance for the same components was also correlated with D2, both with r = 0.66 (P < 0.05). A relationship between genetic divergence and combining ability effects was suggested because the most divergent cultivar exhibited a high general combining ability, generating the best performing hybrids. Results indicated that genetic diversity estimates can be useful in selecting parents for crosses and in assessing relationships among cacao racial groups.

Calculation of breed direct and maternal genetic fractions and breed specific direct and maternal heterozygosity for crossbreeding data

Teaching, research, and herd breeding applications may require calculation of breed additive contributions for direct and maternal genetic effects and fractions of heterozygosity associated with breed specific direct and maternal heterosis effects. These coefficients can be obtained from the first NB rows of a pseudo numerator relationship matrix where the first NB rows represent fractional contributions by breed to each animal or group representing a specific breed cross. The table begins with an NB x NB identity matrix representing pure breeds. Initial animals or representative crosses must be purebreds or two-breed crosses. Parents of initial purebreds are represented by the corresponding column and initial two-breed cross progeny by the two corresponding columns of the identity matrix. After that, usual rules are used to calculate the NB column entries corresponding to breeds for each animal. The NB entries are fractions of genes expected to be contributed by each of the pure breeds and correspond to the breed additive direct fractions. Entries in the column corresponding to the dam represent breed additive maternal fractions. Breed specific direct heterozygosity coefficients are entries of an NB x NB matrix formed by the outer product of the two NB by 1 columns associated with sire and dam of the animal. One minus sum of the diagonals represents total direct heterozygosity. Similarly, the NB x NB matrix formed by the outer product of columns associated with sire of dam and dam of dam contains breed specific maternal heterozygosity coefficients. These steps can be programmed to create covariates to merge with data. If X represents these coefficients for all unique breed crosses, then the reduced row echelon form function of MATLAB or SAS can be used on X to determine estimable functions of additive breed direct and maternal effects and breed specific direct and maternal heterosis effects

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Water deprivation and the double- depletion hypothesis: common neural mechanisms underlie thirst and salt appetite

Water deprivation-induced thirst is explained by the double-depletion hypothesis, which predicts that dehydration of the two major body fluid compartments, the extracellular and intracellular compartments, activates signals that combine centrally to induce water intake. However, sodium appetite is also elicited by water deprivation. In this brief review, we stress the importance of the water-depletion and partial extracellular fluid-repletion protocol which permits the distinction between sodium appetite and thirst. Consistent enhancement or a de novo production of sodium intake induced by deactivation of inhibitory nuclei (e.g., lateral parabrachial nucleus) or hormones (oxytocin, atrial natriuretic peptide), in water-deprived, extracellular-dehydrated or, contrary to tradition, intracellular-dehydrated rats, suggests that sodium appetite and thirst share more mechanisms than previously thought. Water deprivation has physiological and health effects in humans that might be related to the salt craving shown by our species.

What ethologically based models have taught us about the neural systems underlying fear and anxiety

Classical Pavlovian fear conditioning to painful stimuli has provided the generally accepted view of a core system centered in the central amygdala to organize fear responses. Ethologically based models using other sources of threat likely to be expected in a natural environment, such as predators or aggressive dominant conspecifics, have challenged this concept of a unitary core circuit for fear processing. We discuss here what the ethologically based models have told us about the neural systems organizing fear responses. We explored the concept that parallel paths process different classes of threats, and that these different paths influence distinct regions in the periaqueductal gray - a critical element for the organization of all kinds of fear responses. Despite this parallel processing of different kinds of threats, we have discussed an interesting emerging view that common cortical-hippocampal-amygdalar paths seem to be engaged in fear conditioning to painful stimuli, to predators and, perhaps, to aggressive dominant conspecifics as well. Overall, the aim of this review is to bring into focus a more global and comprehensive view of the systems organizing fear responses.

Genetic diversity and phenotypic variability of phytoplankton populations in the Baltic Sea

En av naturens mest grundläggande aspekter är den enorma mängd av variation som existerar mellan arter. Denna variation har lett oss till att klassificera olika organismer på basis av morfologiska skillnader och på senare tid till att jämföra genetiska skillnader på individens nivå. Den marina kiselalgen Skeletonema marinoi är en av de vanligaste växtplanktonarter i Östersjön under vårblomningen och anses viktig för den årliga produktionen. En av mina främsta målsättningar var att beskriva den intra-specifika diversiteten hos denna art längs med miljögradienter i Östersjön. Ett annat mål var att klargöra de faktorer som eventuellt är involverade i konfigurationen av genetisk diversitet och differentiering. Med hjälp av genetiska markörer visade jag att den genetiska diversiteten hos S. marinoi populationer i Östersjön är lägre jämfört med populationer i östra delen av Nordsjön. Arten är genetiskt uppdelad så att en utpräglad population förekommer i Östersjön och en annan, genetiskt åtskild population förekommer norr om de Danska sunden. Resultaten visar att de genetiskt åtskilda populationerna är anpassade till lokala salinitetsförhållanden. Genflödet mellan populationerna korrelerade kraftigt med havströmmar i området. Mina studier avslöjade även omfattande variation av fenotypiska, ekologiskt vikitga särdrag hos olika kloner. Djurplankton som äter kiselalger kunde modifiera den klonala mångfalden av fenotypiskt variabla S. marinoi populationer. En ökad klonal mångfald ledde till högre prestationsförmåga i fråga om primär produktion och stabiliserade ekofysiologiska funktioner. Som visas i denna avhandling består en art allt som oftast av åtskilliga genetiska varianter med fenotypiska skillnader. Kunskap om sådana intra-specifika skillnader är en förutsättning för att vi skall kunna förstå var och varför arter förekommer. Denna kunskap utgör även en grund för prognoser som siktar på att förutspå huruvida arter kan anpassa sig till framtida miljöförhållanden. ------------------------------------------------------ Suunnaton määrä variaatioita eliölajien välillä on perustavanlaatuinen ominaisuus luonnossa. Perinteisesti tätä monimuotoisuutta on käytetty organismien luokittelemiseen eri lajeihin niiden morfologisten eroavaisuuksien perusteella. Hiljattain myös geneettisten erojen huomioimista yksilötasolla on hyödynnetty lajien luokittelemisessa. Merialueilla esiintyvä piilevä, Skeletonema marinoi on yksi Itämeren tavallisimmista kasviplanktonlajeista kevätkukinnan aikana. Tavoitteenani oli selventää geneettistä ja fenotyyppistä monimuotoisuutta pitkin Itämeren ympäristögradienttejä. Geneettisen monimuotoisuuteen ja erkaantumiseen vaikuttavien tekijöiden selvittäminen oli tärkeä aspekti väitöstutkimuksessani. Geneettisiä markkereita käyttämällä pystyin toteamaan, että S. marinoi levän geneettinen monimuotoisuus on Itämeressä merkittävästi alhaisempi kuin läheisessä Pohjanmeren itäosassa. Tutkittu laji jakautuu geneettisesti yhteen erilliseen populaatioon Itämeressä ja toiseen selvästi erottuvaan populaatioon Tanskan salmien pohjoispuolella. Kokeellisten tulosten perusteella nämä geneettisesti erilaistuneet populaatiot ovat kumpikin sopeutuneet paikalliseen veden suolapitoisuuteen. Populaatioiden välisen geenivirran ja merivirtojen luoman yhteyden välillä havaittiin vahva korrelaatio. Tutkimukseni paljastivat myös laajaa vaihtelua Skeletonema-kloonien ekologisesti tärkeissä ominaisuuksissa. Kokeellisten tutkimusteni perusteella laiduntajat pystyivät muuttamaan geneettisten kloonien lukumäärää monimuotoisissa S. marinoi populaatioissa. Lisääntynyt kloonien lukumäärä paransi perustuotantokykyä ja vakautti ekofysiologisia toimintoja. Kuten tässä väitöstutkimuksessa osoitetaan, lajit koostuvat useimmiten lukuisista geneettisistä muunnelmista, jotka eroavat usein fenotyypeiltään. Ymmärtääksemme missä tietyt lajit esiintyvät ja miksi, tarvitsemme tietoa lajien sisäisistä vaihteluista. Tämä tieto on tarpeellista, jotta voimme ennustaa lajien sopeutumista tuleviin ympäristönmuutoksiin.

Genetic, prenatal and postnatal determinants of weight gain and obesity in young children – The STEPS Study

Genetic, Prenatal and Postnatal Determinants of Weight Gain and Obesity in Young Children – The STEPS Study University of Turku, Faculty of Medicine, Department of Paediatrics, University of Turku Doctoral Program of Clinical Investigation (CLIPD), Turku Institute for Child and Youth Research. Conditions of being overweight and obese in childhood are common health problems with longlasting effects into adulthood. Currently 22% of Finnish boys and 12% of Finnish girls are overweight and 4% of Finnish boys and 2% of Finnish girls are obese. The foundation for later health is formed early, even before birth, and the importance of prenatal growth on later health outcomes is widely acknowledged. When the mother is overweight, had high gestational weight gain and disturbances in glucose metabolism during pregnancy, an increased risk of obesity in children is present. On the other hand, breastfeeding and later introduction of complementary foods are associated with a decreased obesity risk. In addition to these, many genetic and environmental factors have an effect on obesity risk, but the clustering of these factors is not extensively studied. The main objective of this thesis was to provide comprehensive information on prenatal and early postnatal factors associated with weight gain and obesity in infancy up to two years of age. The study was part of the STEPS Study (Steps to Healthy Development), which is a follow-up study consisting of 1797 families. This thesis focused on children up to 24 months of age. Altogether 26% of boys and 17% of girls were overweight and 5% of boys and 4% of girls were obese at 24 months of age according to New Finnish Growth references for Children BMI-for-age criteria. Compared to children who remained normal weight, the children who became overweight or obese showed different growth trajectories already at 13 months of age. The mother being overweight had an impact on children’s birth weight and early growth from birth to 24 months of age. The mean duration of breastfeeding was almost 2 months shorter in overweight women in comparison to normal weight women. A longer duration of breastfeeding was protective against excessive weight gain, high BMI, high body weight and high weight-for-length SDS during the first 24 months of life. Breast milk fatty acid composition differed between overweight and normal weight mothers, and overweight women had more saturated fatty acids and less n-3 fatty acids in breast milk. Overweight women also introduced complementary foods to their infants earlier than normal weight mothers. Genetic risk score calculated from 83 obesogenic- and adiposity-related single nucleotide polymorphisms (SNPs) showed that infants with a high genetic risk for being overweight and obese were heavier at 13 months and 24 months of age than infants with a low genetic risk, thus possibly predisposing to later obesity in obesogenic environment. Obesity Risk Score showed that children with highest number of risk factors had almost 6-fold risk of being overweight and obese at 24 months compared to children with lowest number of risk factors. The accuracy of the Obesity Risk Score in predicting overweight and obesity at 24 months was 82%. This study showed that many of the obesogenic risk factors tend to cluster within children and families and that children who later became overweight or obese show different growth trajectories already at a young age. These results highlight the importance of early detection of children with higher obesity risk as well as the importance of prevention measures focused on parents. Keywords: Breastfeeding, Child, Complementary Feeding, Genes, Glucose metabolism, Growth, Infant Nutrition Physiology, Nutrition, Obesity, Overweight, Programming

Genetic diversity and comparison of physicochemical and nutritional characteristics of six quinoa (Chenopodium quinoa willd.) genotypes cultivated in Chile

The present study was focused on the analysis of agronomical, nutritional, physicochemical, and antioxidant properties of six genetically different quinoa (Chenopodium quinoa Willd) genotypes cultivated in three distinctive geographical zones of Chile. Ancovinto and Cancosa genotypes from the northern Altiplano (19 ºS), Cáhuil and Faro from the central region (34 ºS), and Regalona and Villarica from the southern region (39 ºS) are representative of high genetic differentiation among the pooled samples, in particular between Altiplano and the central-southern groups. A Common-Garden Assay at 30 ºS showed significant differences among seed origins in all morphometric parameters and also in yields. Altiplano genotypes had larger panicule length but no seed production. A significant influence of the different quinoa genotypes on chemical composition and functional properties was also observed. Protein concentration ranged from 11.13 to 16.18 g.100 g-1 d.m., while total dietary fiber content ranged from 8.07-12.08 g.100 g-1 d.m., and both were the highest in Villarrica ecotype. An adequate balance of essential amino acids was also observed. Sucrose was the predominant sugar in all genotypes. Antioxidant activity was high in all genotypes, and it was highest in Faro genotype (79.58% inhibition).

Acceptance of a food of animal origin obtained through genetic modification and cloning in South America: a comparative study among university students and working adults

AbstractWith the aim of comparing the acceptance of milk obtained from cloned, genetically modified (GM) and conventionally bred cows among working adults and university students, and identifying and characterizing typologies among both subsamples in terms of their preferences, a survey was applied to 400 people in southern Chile, distributed using a simple allocation among the subsamples. Using a conjoint analysis, it was found that consumers preferred milk from a conventional cow. Using a cluster analysis, in both subsamples two segments sensitive to production technology were identified. Rejection of cloning was greatest among university students, whereas a higher proportion of working adults rejected GM. The segments differed in terms of area of residence, knowledge about GM, and milk consumption habits. Contrary to what was expected, no differences were found according to education, gender or degree of satisfaction with food-related life.

Genetic variation and evolutionary divergence within and among populations, species, and genera of the Cambarinae

Seven crayfish species from three genera of the subfamily Cambarinae were electrophoretically examined for genetic variation at a total of twenty-six loci. Polymorphism was detected primarily at three loci: Ao-2, Lap, and Pgi. The average heterozygosities over-all loci for each species were found to be very low when compared to most other invertebrate species that have been examined electrophoretically. With the exception of Cambarus bartoni, the interpopulation genetic identities are high within any given species. The average interspecific identities are somewhat lower and the average intergeneric identities are lower still. Populations, species and genera conform to the expected taxonomic progression. The two samples of ~ bartoni show high genetic similarity at only 50 percent of the loci compared. Locus by locus identity comparisons among species yield U-shaped distributions of genetic identities. Construction of a phylogenetic dendrogram using species mean genetic distances values shows that species grouping is in agreement with morphological taxonomy with the exception of the high similarity between Orconectespropinquus and Procambarus pictus. This high similarity suggests the possibility of a regulatory change between the two species. It appears that the low heterozygosities, high interpopulation genetic identities, and taxonomic mispositioning can all be explained on the basis of low mutation rates.

Automatic Structure Generation using Genetic Programming and Fractal Geometry

Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design.

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM

Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.