Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

Applications and Benefits of Adaptive Pulsed GMAW

In ship and offshore terminal construction, welded cross sections are thick and the number of welds very high. Consequently, there are two aspects of great importance; cost and heat input. Reduction in the welding operation time decreases the costs of the work force and avoids excessive heat, preventing distortion and other weld defects. The need to increase productivity while using a single wire in the GMAW process has led to the use of a high current and voltage to improve the melting rate. Unfortunately, this also increases the heat input. Innovative GMAW processes, mostly implemented for sheet plate sections, have shown significant reduction in heat input (Q), low distortion and increase in welding speed. The aim of this study is to investigate adaptive pulsed GMAW processes and assess relevant applications in the high power range, considering possible benefits when welding thicker sections and high yield strength steel. The study experimentally tests the usability of adaptive welding processes and evaluates their effects on weld properties, penetration and shapes of the weld bead.The study first briefly reviews adaptive GMAW to evaluate different approaches and their applications and to identify benefits in adaptive pulsed. Experiments are then performed using Synergic Pulsed GMAW, WiseFusionTM and Synergic GMAW processes to weld a T-joint in a horizontal position (PB). The air gap between the parts ranges from 0 to 2.5 mm. The base materials are structural steel grade S355MC and filler material G3Si1. The experiment investigates heat input, mechanical properties and microstructure of the welded joint. Analysis of the literature reveals that different approaches have been suggested using advanced digital power sources with accurate waveform, current, voltage, and feedback control. In addition, studies have clearly indicated the efficiency of lower energy welding processes. Interest in the high power range is growing and a number of different approaches have been suggested. The welding experiments in this study reveal a significant reduction of heat input and a weld microstructure with the presence of acicular ferrite (AF) beneficial for resistance to crack propagation. The WiseFusion bead had higher dilution, due to the weld bead shape, and low defects. Adaptive pulse GMAW processes can be a favoured choice when welding structures with many welded joints. The total heat reduction mitigates residual stresses and the bead shape allows a higher amperage limit. The stability of the arc during the process is virtually spatter free and allows an increase in welding speed.

Fetal alcohol spectrum disorders in Finnish children and adolescents : diagnosis, cognition, behavior, adaptation and brain metabolic alterations

Alcohol consumption during pregnancy can potentially affect the developing fetus in devastating ways, leading to a range of physical, neurological, and behavioral alterations most accurately termed Fetal Alcohol Spectrum Disorders (FASD). Despite the fact that it is a preventable disorder, prenatal alcohol exposure today constitutes a leading cause of intellectual disability in the Western world. In Western countries where prevalence studies have been performed the rates of FASD exceed, for example, autism spectrum disorders, Down’s syndrome and cerebral palsy. In addition to the direct effects of alcohol, children and adolescents with FASD are often exposed to a double burden in life, as their neurological sequelae are accompanied by adverse living surroundings exposing them to further environmental risk. However, children with FASD today remain remarkably underdiagnosed by the health care system. This thesis forms part of a larger multinational research project, The Collaborative Initiative on Fetal Alcohol Spectrum Disorders (the CIFASD), initiated by the National Institute of Alcohol Abuse and Alcoholism (NIAAA) in the U.S.A. The general aim of the present thesis was to examine a cohort of children and adolescents growing up with fetal alcohol-related damage in Finland. The thesis consists of five studies with a broad focus on diagnosis, cognition, behavior, adaptation and brain metabolic alterations in children and adolescents with FASD. The participants consisted of four different groups: one group with histories of prenatal exposure to alcohol, the FASD group; one IQ matched contrast group mostly consisting of children with specific learning disorder (SLD); and two typically-developing control groups (CON1 and CON2). Participants were identified through medical records, random sampling from the Finnish national population registry and email alerts to students. Importantly, the participants in the present studies comprise a group of very carefully clinically characterized children with FASD as the studies were performed in close collaboration with leading experts in the field (Prof. Edward Riley and Prof. Sarah Mattson, Center for Behavioral Teratology, San Diego State University, U.S.A; Prof. Eugene Hoyme, Sanford School of Medicine, University of South Dakota, U.S.A.). In the present thesis, the revised Institute of Medicine diagnostic criteria for FASD were tested on a Finnish population and found to be a reliable tool for differentiating among the subgroups of FASD. A weighted dysmorphology scoring system proved to be a valuable additional adjunct in quantification of growth deficits and dysmorphic features in children with FASD (Study 1). The purpose of Study 2 was to clarify the relationship between alcohol-related dysmorphic features and general cognitive capacity. Results showed a significant correlation between dysmorphic features and cognitive capacity, suggesting that children with more severe growth deficiency and dysmorphic features have more cognitive limitations. This association was, however, only moderate, indicating that physical markers and cognitive capacity not always go hand in hand in individuals with FASD. Behavioral problems in the FASD group proved substantial compared to the typically developing control group. In Study 3 risk and protective factors associated with behavioral problems in the FASD group were explored further focusing on diagnostic and environmental factors. Two groups with elevated risks for behavioral problems emerged: length of time spent in residential care and a low dysmorphology score proved to be the most pervasive risk factor for behavioral problems. The results underscore the clinical importance of appropriate services and care for less visibly alcohol affected children and highlight the need to attend to children with FASD being raised in institutions. With their background of early biological and psychological impairment compounded with less opportunity for a close and continuous caregiver relationship, such children seem to run an especially great risk of adverse life outcomes. Study 4 focused on adaptive abilities such as communication, daily living skills and social skills, in other words skills that are important for gradually enabling an independent life, maintain social relationships and allow the individual to become integrated into society. The results showed that adaptive abilities of children and adolescents growing up with FASD were significantly compromised compared to both typically-developing peers and IQ-matched children with SLD. Clearly different adaptive profiles were revealed where the FASD group performed worse than the SLD group, who in turn performed worse than the CON1 group. Importantly, the SLD group outperformed the FASD group on adaptive behavior in spite of comparable cognitive levels. This is the first study to compare adaptive abilities in a group of children and adolescents with FASD relative to both a contrast group of IQ-matched children with SLD and to a group of typically-developing peers. Finally, in Study 5, through magnetic resonance spectroscopic imaging (MRS) evidence of longstanding neurochemical alterations were observed in adolescents and young adults with FASD related to alcohol exposure in utero 14-20 years earlier. Neurochemical alterations were seen in several brain areas: in frontal and parietal cortices, corpus callosum, thalamus and frontal white matter areas as well as in the cerebellar dentate nucleus. The findings are compatible with neuropsychological findings in FASD. Glial cells seemed to be more affected than neurons. In conclusion, more societal efforts and resources should be focused on recognizing and diagnosing FASD, and supporting subgroups with elevated risk of poor outcome. Without adequate intervention children and adolescents with FASD run a great risk of marginalization and social maladjustment, costly not only to society but also to the lives of the many young people with FASD.

Eri MAG-hitsausprosessien ja -parametrien vaikutus suurlujuusteräksestä valmistetun otsapienahitsin äärikestävyyteen, muodonmuutoskykyyn ja vauriomuotoon

Työssä tutkittiin Ruukki Oyj:n suorasammutetusta S960QC-teräksestä valmistetun kuormaakantavan levyjen ristiliitoksen pienahitsien lujuutta, muodonmuutoskykyä ja vaurioitumismekanismia laajaan kokeelliseen aineistoon perustuen. Tärkeimpänä muuttujana koematriisissa olivat eri MAG-hitsausprosessit. Perinteisen kuumakaarihitsauksen vertailukohteena oli Kemppi Oy:n uusi adaptiivinen valokaaren pituutta säätävä WiseFusion-hitsaustoiminto kuuma- ja pulssikaarihitsauksessa. Näiden kolmen hitsausprosessin rinnalla varioitiin erisuuruisia a-mittoja, eri hitsauslisäaineita ja hitsin erikylkisyyttä. Lisäksi juuritunkeuman estämisen vaikutusta hitsien käyttäytymiseen tutkittiin täydentävällä koesarjalla, jossa tunkeuman muodostuminen estettiin levyjen väliin asetetulla volframilevyllä. Työn perimmäisenä tavoitteena oli selvittää syy aiemmassa tutkimuksessa havaitulle pienahitsien vaurioitumiselle leikkautumalla sularajaa pitkin. Sularajan suhteellista pituutta saadaan kasvatettua estämällä hitsin juuritunkeuma ja absoluuttista pituutta saadaan lisää kateettipoikkeaman avulla. Lisäksi tutkimuksessa oli tarkoitus tuoda esille suurlujuusteräksisen liitoksen eri mitoituslähtökohdat (mm. lämmöntuonnin kontrollointi). Tämän vuoksi hitsausparametrit mitattiin jännitteen ja virran hetkellisiin arvoihin perustuen, jolloin kuuma- ja pulssikaarihitsauksen laskennalliset hitsaustehot ovat vertailukelpoisia. Koehitseistä valmistettiin hieet hitsien tarkan geometrian määrittämiseksi ja liitoksen mekaaniset ominaisuudet tutkittiin vetokokeella. Tulosten perusteella sularajavaurio aktivoituu pulssikaarella hitsatuissa koekappaleissa. Tämä aiheutunee pulssi- ja kuumakaarihitsauksen sularajan mikrorakenteiden eroavaisuudesta. Sularajavaurio näyttää huonontavan hitsien muodonmuutoskykyä, mutta jatkokokeita tuloksen verifioimiseksi on tehtävä. S960QC-teräkselle ominaisen pehmenneen vyöhykkeen vaurio ei aktivoitunut, vaikka Ruukin antamat jäähtymisaikasuositukset ylitettiin reilusti.

Adaptive Routing Approaches for Networked Many-Core Systems

Through advances in technology, System-on-Chip design is moving towards integrating tens to hundreds of intellectual property blocks into a single chip. In such a many-core system, on-chip communication becomes a performance bottleneck for high performance designs. Network-on-Chip (NoC) has emerged as a viable solution for the communication challenges in highly complex chips. The NoC architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication challenges such as wiring complexity, communication latency, and bandwidth. Furthermore, the combined benefits of 3D IC and NoC schemes provide the possibility of designing a high performance system in a limited chip area. The major advantages of 3D NoCs are the considerable reductions in average latency and power consumption. There are several factors degrading the performance of NoCs. In this thesis, we investigate three main performance-limiting factors: network congestion, faults, and the lack of efficient multicast support. We address these issues by the means of routing algorithms. Congestion of data packets may lead to increased network latency and power consumption. Thus, we propose three different approaches for alleviating such congestion in the network. The first approach is based on measuring the congestion information in different regions of the network, distributing the information over the network, and utilizing this information when making a routing decision. The second approach employs a learning method to dynamically find the less congested routes according to the underlying traffic. The third approach is based on a fuzzy-logic technique to perform better routing decisions when traffic information of different routes is available. Faults affect performance significantly, as then packets should take longer paths in order to be routed around the faults, which in turn increases congestion around the faulty regions. We propose four methods to tolerate faults at the link and switch level by using only the shortest paths as long as such path exists. The unique characteristic among these methods is the toleration of faults while also maintaining the performance of NoCs. To the best of our knowledge, these algorithms are the first approaches to bypassing faults prior to reaching them while avoiding unnecessary misrouting of packets. Current implementations of multicast communication result in a significant performance loss for unicast traffic. This is due to the fact that the routing rules of multicast packets limit the adaptivity of unicast packets. We present an approach in which both unicast and multicast packets can be efficiently routed within the network. While suggesting a more efficient multicast support, the proposed approach does not affect the performance of unicast routing at all. In addition, in order to reduce the overall path length of multicast packets, we present several partitioning methods along with their analytical models for latency measurement. This approach is discussed in the context of 3D mesh networks.

Comparison of two methods of tear sampling for protein quantification by Bradford method

The aim of this study was to compare two methods of tear sampling for protein quantification. Tear samples were collected from 29 healthy dogs (58 eyes) using Schirmer tear test (STT) strip and microcapillary tubes. The samples were frozen at -80ºC and analyzed by the Bradford method. Results were analyzed by Student's t test. The average protein concentration and standard deviation from tears collected with microcapillary tube were 4.45mg/mL ±0.35 and 4,52mg/mL ±0.29 for right and left eyes respectively. The average protein concentration and standard deviation from tears collected with Schirmer Tear Test (STT) strip were and 54.5mg/mL ±0.63 and 54.15mg/mL ±0.65 to right and left eyes respectively. Statistically significant differences (p<0.001) were found between the methods. In the conditions in which this study was conducted, the average protein concentration obtained with the Bradford test from tear samples obtained by Schirmer Tear Test (STT) strip showed values higher than those obtained with microcapillary tube. It is important that concentration of tear protein pattern values should be analyzed according the method used to collect tear samples.

Actively crafting customer value or merely representing a solution? Linking value-based selling to salesperson performance

Value-based selling is a salesperson behavioral mode which concentrates on generating superior customer value. Although service dominant logic emphasizes customer value as a central tenet for achieving strategic objectives, sales management literature has predominantly circumvented the subject matter of customer value. The purpose of this thesis is to demonstrate the distinctiveness and positive sales performance outcomes of value-based selling. Additionally, performance outcomes of value-based selling are contrasted with other key sales behaviors, selling skills and motivational orientations. As a part of this thesis, large-scale survey of 730 respondents was collected. The survey was tailored for the needs of a value-based selling research group led by Ph.D. Harri Terho. The research group used convenience sampling to select the salespeople of 25 medium- and large-scale companies in Finland which currently either practice value-based selling or consider developing these activities. This thesis contains three key findings: value-based selling is established as a distinct sales behavior, it relates directly and positively to salesperson performance and it explains the link between customer-oriented selling and salesperson performance. Value-based selling relates to salesperson performance especially in the following GICS-sectors: energy, industrials and materials. However, relationship selling relates to performance strongest in the energy sector and adaptive selling in industrials sector. In sum, it is evident that actively crafting customer value is a successful sales behavior in many business-to-business marketing environments while other sales behaviors, excluding customer-oriented selling, still uphold their significance.

The genetics of behaviour and other adaptive traits in nine-spined sticklebacks (Pungitius pungitius)

One of the main goals in current evolutionary biology research is to identify genes behind adaptive phenotypic variations. The advances in genomic technologies have made it possible to identify genetic loci behind these variations, also concerning non-model species. This thesis investigates the genetics of the behaviour and other adaptive traits of the nine-spined stickleback (Pungitius pungitius) through the application of different genetic approaches. Fennoscandian nine-spined stickleback populations express large phenotypical differences especially in behaviour, life –history traits and morphology. However the underlying genetic bases for these phenotypical differences have not been studied in detail. The results of the project will lay the foundation for further genetics studies and provide valuable information for our understanding of the genetics of the adaptive divergence of the nine-spined stickleback. A candidate gene approach was used to develop microsatellite markers situating close to candidate genes for behaviour in the nine-spined stickleback. Altogether 13 markers were developed and these markers were used in the subsequent studies with the anonymous random markers and physiologically important gene markers which are already currently available for nine-spined sticklebacks. It was shown that heterozygosity correlated with behaviour in one of the marine nine-spined stickleback populations but with contrasting effects: correlations with behaviour were negative when using physiological gene markers and positive with random markers. No correlation was found between behavioural markers and behaviour. From the physiological gene markers, a strong correlation was found between osmoregulation-related gene markers and behaviour. These results indicate that both local (physiological) and general (random) effects are important in the shaping of behaviour and that heterozygosity– behaviour correlations are population dependent. In this thesis a second linkage map for nine-spined sticklebacks was constructed. Compared to the earlier nine-spined stickleback linkage map, genomic rearrangements were observed between autosomal (LG7) and sex-determing (LG12) linkage groups. This newly constructed map was used in QTL mapping studies in order to locate genomic regions associated with pelvic structures, behaviour and body size/growth. One major QTL was found for pelvic structures and Pitx1 gene was related to these traits as was predicted from three-spined stickleback studies, but this was in contrast to earlier nine-spined stickleback study. The QTL studies also revealed that behaviour and body size/growth were genetically more complex by having more QTL than pelvic traits. However, in many cases, pelvic structure, body size/growth and behaviour were linked to similar map locations indicating possible pleiotropic effects of genes locating in these QTL regions. Many of the gene related markers resided in the QTL area. In the future, studying these possible candidate genes in depth might reveal the underlying mechanism behind the measured traits.

An Hp-Adaptive Hierarchical Formulation for the Boundary Element Method Applied to Elasticity in Two Dimensions

This paper presents an HP-Adaptive Procedure with Hierarchical formulation for the Boundary Element Method in 2-D Elasticity problems. Firstly, H, P and HP formulations are defined. Then, the hierarchical concept, which allows a substantial reduction in the dimension of equation system, is introduced. The error estimator used is based on the residual computation over each node inside an element. Finally, the HP strategy is defined and applied to two examples.

Improving quality at the preanalytical phase of blood sampling : literature review

Julkaisumaa: 158 TW TWN Taiwan

Mathematics inspired by Darwin. Adaptive dynamics of dispersal and cooperation

In 1859, Charles Darwin published his theory of evolution by natural selection, the process occurring based on fitness benefits and fitness costs at the individual level. Traditionally, evolution has been investigated by biologists, but it has induced mathematical approaches, too. For example, adaptive dynamics has proven to be a very applicable framework to the purpose. Its core concept is the invasion fitness, the sign of which tells whether a mutant phenotype can invade the prevalent phenotype. In this thesis, four real-world applications on evolutionary questions are provided. Inspiration for the first two studies arose from a cold-adapted species, American pika. First, it is studied how the global climate change may affect the evolution of dispersal and viability of pika metapopulations. Based on the results gained here, it is shown that the evolution of dispersal can result in extinction and indeed, evolution of dispersalshould be incorporated into the viability analysis of species living in fragmented habitats. The second study is focused on the evolution of densitydependent dispersal in metapopulations with small habitat patches. It resulted a very surprising unintuitive evolutionary phenomenon, how a non-monotone density-dependent dispersal may evolve. Cooperation is surprisingly common in many levels of life, despite of its obvious vulnerability to selfish cheating. This motivated two applications. First, it is shown that density-dependent cooperative investment can evolve to have a qualitatively different, monotone or non-monotone, form depending on modelling details. The last study investigates the evolution of investing into two public-goods resources. The results suggest one general path by which labour division can arise via evolutionary branching. In addition to applications, two novel methodological derivations of fitness measures in structured metapopulations are given.

Adaptive value of ryegrass biotypes with low-level resistance and susceptible to the herbicide fluazifop and competitive ability with the wheat culture

Ryegrass is the main weed in wheat crop, causing yield loss due to competition by environmental resources. The objectives of this study were to estimate the fitness cost of ryegrass biotypes with low-level resistance and susceptible to fluazifop and to investigate the relative competitive ability of these biotypes between themselves and against the crop. Thus, fitness cost and competitive ability experiments were conducted under greenhouse conditions. For the fitness cost experiments, the low-level resistant ryegrass biotypes and those susceptible to fluazifop were used. For competitive ability, the treatments were arranged in a replacement series, with five proportions of the wheat cultivar FUNDACEP Horizonte and the low-level resistant and susceptible ryegrass biotypes 100:0, 75:25, 50:50, 25:75 and 0:100. Competitive analysis was carried out through diagrams applied to the replacement experiments and use of relative competitiveness indices. Variables evaluated were plant height, in the fitness cost experiment, and leaf area and shoot dry biomass in both experiments. The ryegrass biotypes show overall similar fitness cost and competitive ability. The wheat cultivar FUNDACEP Horizonte is superior in competitive ability to the ryegrass biotype with low-level resistance and equivalent to the susceptible biotype.

Adaptive control of Hydraulic Drive

Adaptive control systems are one of the most significant research directions of modern control theory. It is well known that every mechanical appliance’s behavior noticeably depends on environmental changes, functioning-mode parameter changes and changes in technical characteristics of internal functional devices. An adaptive controller involved in control process allows reducing an influence of such changes. In spite of this such type of control methods is applied seldom due to specifics of a controller designing. The work presented in this paper shows the design process of the adaptive controller built by Lyapunov’s function method for the Hydraulic Drive. The calculation needed and the modeling were conducting with MATLAB® software including Simulink® and Symbolic Math Toolbox™ etc. In the work there was applied the Jacobi matrix linearization of the object’s mathematical model and derivation of the suitable reference models based on Newton’s characteristic polynomial. The intelligent adaptive to nonlinearities algorithm for solving Lyapunov’s equation was developed. Developed algorithm works properly but considered plant is not met requirement of functioning with. The results showed confirmation that adaptive systems application significantly increases possibilities in use devices and might be used for correction a system’s behavior dynamics.

Tropical inselbergs: habitat types, adaptive strategies and diversity patterns

Inselbergs are isolated rock outcrops that rise abruptly above the surrounding plains. Granitic and gneissic inselbergs are geologically and geomorphologically old and occur throughout a broad spectrum of climatic zones. They form microclimatically and edaphically dry growth sites that support a highly specialized vegetation. Based on physiognomic criteria a number of habitat types can be distinguished that are widespread on inselbergs (e.g. ephemeral flush vegetation, monocotyledonous mats, rock pools). Three hot spots of global inselberg plant diversity can be identified which are both rich in species and endemics: a) southeastern Brazil, b) Madagascar and c) southwestern Australia.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.