Life designing: A paradigm for career construction in the 21st century

At the beginning of the 21st century, a new social arrangement of work poses a series of questions and challenges to scholars who aim to help people develop their working lives. Given the globalization of career counseling, we decided to address these issues and then to formulate potentially innovative responses in an international forum. We used this approach to avoid the difficulties of creating models and methods in one country and then trying to export them to other countries where they would be adapted for use. This article presents the initial outcome of this collaboration, a counseling model and methods. The life-designing model for career intervention endorses five presuppositions about people and their work lives: contextual possibilities, dynamic processes, non-linear progression, multiple perspectives, and personal patterns. Thinking from these five presuppositions, we have crafted a contextualized model based on the epistemology of social constructionism, particularly recognizing that an individual's knowledge and identity are the product of social interaction and that meaning is co-constructed through discourse. The life-design framework for counseling implements the theories of self-constructing [Guichard, J. (2005). Life-long self-construction. International Journal for Educational and Vocational Guidance, 5, 111-124] and career construction [Savickas, M. L. (2005). The theory and practice of career construction. In S. D. Brown & R. W. Lent (Eds.), Career development and counselling: putting theory and research to work (pp. 42-70). Hoboken, NJ: Wiley] that describe vocational behavior and its development. Thus, the framework is structured to be life-long, holistic, contextual, and preventive.

The Impact of Housing Market Segmentation between Tourists and Residents on the Hedonic Price for Landscape Quality

Market segmentation is an important issue when estimating the implicit price for an environmental amenity from a surrogate market like property. This paper tests the hypothesis of a segmentation of the housing market between tourists and residents and computes the implicit price for natural landscape quality in Swiss alpine resorts. The results show a clear segmentation between both groups of consumers, although tests also show that the estimated coefficient for landscape is similar in the tourists' model and in the residents'. However, since the functional form is non linear, the nominal - rather than relative - value of a change in natural landscape quality is higher in the tourist housing market than in the residents'. Hence, considering the segmentation of the market between tourists and residents is essential in order to provide valid estimates of the nominal implicit price of natural landscape quality.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Environmental data mining and modeling based on machine learning algorithms and geostatistics

The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

Quantitative modelling of transcription factor binding sites

Abstract One of the most important issues in molecular biology is to understand regulatory mechanisms that control gene expression. Gene expression is often regulated by proteins, called transcription factors which bind to short (5 to 20 base pairs),degenerate segments of DNA. Experimental efforts towards understanding the sequence specificity of transcription factors is laborious and expensive, but can be substantially accelerated with the use of computational predictions. This thesis describes the use of algorithms and resources for transcriptionfactor binding site analysis in addressing quantitative modelling, where probabilitic models are built to represent binding properties of a transcription factor and can be used to find new functional binding sites in genomes. Initially, an open-access database(HTPSELEX) was created, holding high quality binding sequences for two eukaryotic families of transcription factors namely CTF/NF1 and LEFT/TCF. The binding sequences were elucidated using a recently described experimental procedure called HTP-SELEX, that allows generation of large number (> 1000) of binding sites using mass sequencing technology. For each HTP-SELEX experiments we also provide accurate primary experimental information about the protein material used, details of the wet lab protocol, an archive of sequencing trace files, and assembled clone sequences of binding sequences. The database also offers reasonably large SELEX libraries obtained with conventional low-throughput protocols.The database is available at http://wwwisrec.isb-sib.ch/htpselex/ and and ftp://ftp.isrec.isb-sib.ch/pub/databases/htpselex. The Expectation-Maximisation(EM) algorithm is one the frequently used methods to estimate probabilistic models to represent the sequence specificity of transcription factors. We present computer simulations in order to estimate the precision of EM estimated models as a function of data set parameters(like length of initial sequences, number of initial sequences, percentage of nonbinding sequences). We observed a remarkable robustness of the EM algorithm with regard to length of training sequences and the degree of contamination. The HTPSELEX database and the benchmarked results of the EM algorithm formed part of the foundation for the subsequent project, where a statistical framework called hidden Markov model has been developed to represent sequence specificity of the transcription factors CTF/NF1 and LEF1/TCF using the HTP-SELEX experiment data. The hidden Markov model framework is capable of both predicting and classifying CTF/NF1 and LEF1/TCF binding sites. A covariance analysis of the binding sites revealed non-independent base preferences at different nucleotide positions, providing insight into the binding mechanism. We next tested the LEF1/TCF model by computing binding scores for a set of LEF1/TCF binding sequences for which relative affinities were determined experimentally using non-linear regression. The predicted and experimentally determined binding affinities were in good correlation.

Jatkuvavaletun teräksen leikkaussuunnitelman optimointi

Teollisuuden tuotannon eri prosessien optimointi on hyvin ajankohtainen aihe. Monet ohjausjärjestelmät ovat ajalta, jolloin tietokoneiden laskentateho oli hyvin vaatimaton nykyisiin verrattuna. Työssä esitetään tuotantoprosessi, joka sisältää teräksen leikkaussuunnitelman muodostamisongelman. Valuprosessi on yksi teräksen valmistuksen välivaiheita. Siinä sopivaan laatuun saatettu sula teräs valetaan linjastoon, jossa se jähmettyy ja leikataan aihioiksi. Myöhemmissä vaiheissa teräsaihioista muokataan pienempiä kokonaisuuksia, tehtaan lopputuotteita. Jatkuvavaletut aihiot voidaan leikata tilauskannasta riippuen monella eri tavalla. Tätä varten tarvitaan leikkaussuunnitelma, jonka muodostamiseksi on ratkaistava sekalukuoptimointiongelma. Sekalukuoptimointiongelmat ovat optimoinnin haastavin muoto. Niitä on tutkittu yksinkertaisempiin optimointiongelmiin nähden vähän. Nykyisten tietokoneiden laskentateho on kuitenkin mahdollistanut raskaampien ja monimutkaisempien optimointialgoritmien käytön ja kehittämisen. Työssä on käytetty ja esitetty eräs stokastisen optimoinnin menetelmä, differentiaalievoluutioalgoritmi. Tässä työssä esitetään teräksen leikkausoptimointialgoritmi. Kehitetty optimointimenetelmä toimii dynaamisesti tehdasympäristössä käyttäjien määrittelemien parametrien mukaisesti. Työ on osa Syncron Tech Oy:n Ovako Bar Oy Ab:lle toimittamaa ohjausjärjestelmää.

Early, low-level auditory-somatosensory multisensory interactions impact reaction time speed.

Several lines of research have documented early-latency non-linear response interactions between audition and touch in humans and non-human primates. That these effects have been obtained under anesthesia, passive stimulation, as well as speeded reaction time tasks would suggest that some multisensory effects are not directly influencing behavioral outcome. We investigated whether the initial non-linear neural response interactions have a direct bearing on the speed of reaction times. Electrical neuroimaging analyses were applied to event-related potentials in response to auditory, somatosensory, or simultaneous auditory-somatosensory multisensory stimulation that were in turn averaged according to trials leading to fast and slow reaction times (using a median split of individual subject data for each experimental condition). Responses to multisensory stimulus pairs were contrasted with each unisensory response as well as summed responses from the constituent unisensory conditions. Behavioral analyses indicated that neural response interactions were only implicated in the case of trials producing fast reaction times, as evidenced by facilitation in excess of probability summation. In agreement, supra-additive non-linear neural response interactions between multisensory and the sum of the constituent unisensory stimuli were evident over the 40-84 ms post-stimulus period only when reaction times were fast, whereas subsequent effects (86-128 ms) were observed independently of reaction time speed. Distributed source estimations further revealed that these earlier effects followed from supra-additive modulation of activity within posterior superior temporal cortices. These results indicate the behavioral relevance of early multisensory phenomena.

Korkeakappa-massan suotatuvuus

Työn tarkoituksena oli tutkia korkeakappa-massan suotautuvuutta sekä etsiä uusia analyysimenetelmiä korkeakappa-massan karakterisoimiseksi. Työssä pyrittiin määrittämään tekijöitä, jotka vaikuttavat korkeakappa-massan suotautumiseen. Työn kirjallisessa osassa tarkasteltiin aluksi yleisesti keiton teoriaa, minkä jälkeen käsiteltiin jauhatusta ja tarkemmin korkeakappa-massan hienovaraisempaa jauhatusta eli kuidutusta. Seuraavaksi käsiteltiin suodatusta ja sen teoriaa sekä suodatukseen vaikuttavia tekijöitä. Massan pesusta esitettiin perusteet ja teoriaa. Lopuksi tarkasteltiin massan karakterisointia eri lähestymistavoilla sekä kuitujen perusominaisuuksia. Kokeellisessa osassa verrattiin LTY:n koesuodatuslaitteistolla tehdyillä suodatuskokeilla korkeakappa-massaisen sellukakun suotautuvuutta eri paine-eroilla, suodoksen eri hienoainepitoisuuksilla sekä ennen ja jälkeen sellutehtaallatapahtuneen kuidutuksen. Savonlinnassa sijaitsevalla laitteistolla tehtiin syrjäytystestejä ennen ja jälkeen kuidutusta otetuilla sellumassoilla. Lisäksi ennenja jälkeen kuidutusta otettuja sellumassanäytteitä karakterisoitiin mm. kuituanalysaattorilla, huokoskoko- ja ominaispinta-ala-analyyseillä sekä SEM-kuvilla. Suodatuskokeissa hienoainepitoisuudella ei ollut merkitystä permeabiliteettiin mitattujen suodosvirtausten perusteella. Kuten Darcyn lain perusteella voitiin olettaa, kakun paine-eron kasvaessa permeabiliteetti kasvoi. Vaikutus ei ollut kuitenkaan lineaarinen paine-eroon verrattuna vaan kakun permeabiliteetti kasvoi enemmän tietyllä paine-erovälillä. Tämä paine-eroväli vaihteli hieman riippuen oliko sellumassa otettu ennen vai jälkeen kuidutusta. Lappeenrannassa tehdyissä suodatuskokeissa ei ennen ja jälkeen kuidutusta otetuilla näytteillä ollut selvää eroa permeabiliteeteissa, mutta Savonlinnan syrjäytystesteissä ero syrjäytymisnopeudessa oli selvä. Ennen ja jälkeen kuidutusta otettujen sellumassojen kuituanalysaattorituloksissa ja SEM-kuvissa ei havaittu eroa näytteiden välillä, mutta massojen huokoskoko muuttui kuidutuksen vaikutuksesta.

Absorptiivinen kapasiteetti käytäntölähtöisessä innovaatiotoiminnassa Päijät-Hämeessä

Tutkimuksessa arvioidaan millaisia kyvykkyyksiä toimijoiltavaaditaan, jotta voidaan edistää verkostoja palvelevan innovaatiopolitiikan toteutumista ja toteuttaa käytäntölähtöistä innovaatiotoimintaa. Empiirinen osa tarkastelee Päijät-Hämeen toimijoiden asenneympäristöä ja toimimisen valmiuksia käytäntölähtöisen innovaatiotoiminnan tarpeisiin sopivaksi. Osaaminen kerääntyy yliopistopaikkakunnille ulkoisten suurtuotannon etujen mukaisesti. Ne alueet, joilla ei ole yliopistoa joutuvat luomaan muunlaista innovaatiokyvykkyyttä saavuttaakseen kilpailuetua. Siksi Päijät-Hämeen visiona on tulla johtavaksi käytäntölähtöisen innovaatiotoiminnan alueeksi hyvien toimintamallien ja tehokkaiden tiedonsiirtomekanismien avulla. Tämä vaatii alueen toimijoilta mm. korkeaa absorptiivista kapasiteettia ja heikkoja linkkejä alueen ulkopuolelle. Työn empiirinen osa koostuu 12:sta puolistrukturoidusta haastattelusta sekä kyselytutkimuksesta. Tiedonluonti ja -siirto alueelle nähtiin pääasiassa tutkimusmaailman tehtävänä, mutta varianssianalyysin perusteella tutkimusmaailma ei itse nähnyt olevansa siinä asemassa. Yhteisen kielen puuttuminen tutkimus- ja käytännön työelämän väliltä nähtiin puutteena.

Influence of stationary phase and eluent properties on chromatographic separation of carbohydrates

In this thesis, the sorption and elastic properties of the cation-exchange resins were studied to explain the liquid chromatographic separation of carbohydrates. Na+, Ca2+ and La3+ form strong poly(styrene-co-divinylbenzene) (SCE) as well as Na+ and Ca2+ form weak acrylic (WCE) cation-exchange resins at different cross-link densities were treated within this work. The focus was on the effects of water-alcohol mixtures, mostly aqueous ethanol, and that of the carbohydrates. The carbohydrates examined were rhamnose, xylose, glucose, fructose, arabinose, sucrose, xylitol and sorbitol. In addition to linear chromatographic conditions, non-linear conditions more typical for industrial applications were studied. Both experimental and modeling aspectswere covered. The aqueous alcohol sorption on the cation-exchangers were experimentally determined and theoretically calculated. The sorption model includes elastic parameters, which were obtained from sorption data combined with elasticity measurements. As hydrophilic materials cation-exchangers are water selective and shrink when an organic solvent is added. At a certain deswelling degree the elastic resins go through glass transition and become as glass-like material. Theincreasing cross-link level and the valence of the counterion decrease the sorption of solvent components in the water-rich solutions. The cross-linkage or thecounterions have less effect on the water selectivity than the resin type or the used alcohol. The amount of water sorbed is higher in the WCE resin and, moreover, the WCE resin is more water selective than the corresponding SCE resin. Theincreased aliphatic part of lower alcohols tend to increase the water selectivity, i.e. the resins are more water selective in 2-propanol than in ethanol solutions. Both the sorption behavior of carbohydrates and the sorption differences between carbohydrates are considerably affected by the eluent composition and theresin characteristics. The carbohydrate sorption was experimentally examined and modeled. In all cases, sorption and moreover the separation of carbohydrates are dominated by three phenomena: partition, ligand exchange and size exclusion. The sorption of hydrophilic carbohydrates increases when alcohol is added into the eluent or when carbohydrate is able to form coordination complexes with the counterions, especially with multivalent counterions. Decreasing polarity of the eluent enhances the complex stability. Size exclusion effect is more prominent when the resin becomes tighter or carbohydrate size increases. On the other hand,the elution volumes between different sized carbohydrates decreases with the decreasing polarity of the eluent. The chromatographic separation of carbohydrateswas modeled, using rhamnose and xylose as target molecules. The thermodynamic sorption model was successfully implemented in the rate-based column model. The experimental chromatographic data were fitted by using only one adjustable parameter. In addition to the fitted data also simulated data were generated and utilized in explaining the effect of the eluent composition and of the resin characteristics on the carbohydrate separation.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

Climate and human forcing of Alpine river flow

River flow in Alpine environments is likely to be highly sensitive to climate change because of the effects of warming upon snow and ice, and hence the intra-annual distribution of river runoff. It is also likely to be influenced strongly by human impacts both upon hydrology (e.g. flow abstraction) and river regulation. This paper compares the river flow and sediment flux of two Alpine drainage basins over the last 5 to 7 decades, one that is largely unimpacted by human activities, one strongly impacted by flow abstraction for hydroelectricity. The analysis shows that both river flow and sediment transport capacity are strongly dependent upon the effects of temperature and precipitation availability upon snow accumulation. As the latter tends to increase annual maximum flows, and given the non-linear form of most sediment transport laws, current warming trends may lead to increased sedimentation in Alpine rivers. However, extension to a system impacted upon by flow abstraction reveals the dominant effect that human activity can have upon river sedimentation but also how human response to sediment management has co-evolved with climate forcing to make disentangling the two very difficult.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Base temperature and simulation model for nodes appearance in cape gooseberry (Physalis peruviana L.)

Data was analyzed on development of the solanaceen fruit crop Cape gooseberry to evaluate how well a classical thermal time model could describe node appearance in different environments. The data used in the analysis were obtained from experiments conducted in Colombia in open fields and greenhouse condition at two locations with different climate. An empirical, non linear segmented model was used to estimate the base temperature and to parameterize the model for simulation of node appearance vs. time. The base temperature (Tb) used to calculate the thermal time (TT, ºCd) for node appearance was estimated to be 6.29 ºC. The slope of the first linear segment was 0.023 nodes per TT and 0.008 for the second linear segment. The time at which the slope of node apperance changed was 1039.5 ºCd after transplanting, determined from a statistical analysis of model for the first segment. When these coefficients were used to predict node appearance at all locations, the model successfully fit the observed data (RSME=2.1), especially for the first segment where node appearance was more homogeneous than the second segment. More nodes were produced by plants grown under greenhouse conditions and minimum and maximum rates of node appearance rates were also higher.

Reliability of P-drive in occupational therapy following a short training session: A promising instrument measuring seniors' on-road driving competencies

Introduction Occupational therapists could play an important role in facilitating driving cessation for ageing drivers. This, however, requires an easy-to-learn, standardised on-road evaluation method. This study therefore investigates whether use of P-drive' could be reliably taught to occupational therapists via a short half-day training session. Method Using the English 26-item version of P-drive, two occupational therapists evaluated the driving ability of 24 home-dwelling drivers aged 70 years or over on a standardised on-road route. Experienced driving instructors' on-road, subjective evaluations were then compared with P-drive scores. Results Following a short half-day training session, P-drive was shown to have almost perfect between-rater reliability (ICC2,1=0.950, 95% CI 0.889 to 0.978). Reliability was stable across sessions including the training phase even if occupational therapists seemed to become slightly less severe in their ratings with experience. P-drive's score was related to the driving instructors' subjective evaluations of driving skills in a non-linear manner (R-2=0.445, p=0.021). Conclusion P-drive is a reliable instrument that can easily be taught to occupational therapists and implemented as a way of standardising the on-road driving test.