984 resultados para Polyharmonic distortion modeling. X-parameters. Test-Bench. Planar structures. PHD
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The Proctor test is time-consuming and requires sampling of several kilograms of soil. Proctor test parameters were predicted in Mollisols, Entisols and Vertisols of the Pampean region of Argentina under different management systems. They were estimated from a minimum number of readily available soil properties (soil texture, total organic C) and management (training data set; n = 73). The results were used to generate a soil compaction susceptibility model, which was subsequently validated using a second group of independent data (test data set; n = 24). Soil maximum bulk density was estimated as follows: Maximum bulk density (Mg m-3) = 1.4756 - 0.00599 total organic C (g kg-1) + 0.0000275 sand (g kg-1) + 0.0539 management. Management was equal to 0 for uncropped and untilled soils and 1 for conventionally tilled soils. The established models predicted the Proctor test parameters reasonably well, based on readily available soil properties. Tillage systems induced changes in the maximum bulk density regardless of total organic matter content or soil texture. The lower maximum apparent bulk density values under no-tillage require a revision of the relative compaction thresholds for different no-tillage crops.
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Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments
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Selostus: Ayrshire-ensikoiden koelypsykohtaisen maidontuotannon perinnölliset tunnusluvut laktaation eri vaiheissa
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In this paper we present a new method to track bonemovements in stereoscopic X-ray image series of the kneejoint. The method is based on two different X-ray imagesets: a rotational series of acquisitions of the stillsubject knee that will allow the tomographicreconstruction of the three-dimensional volume (model),and a stereoscopic image series of orthogonal projectionsas the subject performs movements. Tracking the movementsof bones throughout the stereoscopic image series meansto determine, for each frame, the best pose of everymoving element (bone) previously identified in the 3Dreconstructed model. The quality of a pose is reflectedin the similarity between its simulated projections andthe actual radiographs. We use direct Fourierreconstruction to approximate the three-dimensionalvolume of the knee joint. Then, to avoid the expensivecomputation of digitally rendered radiographs (DRR) forpose recovery, we reformulate the tracking problem in theFourier domain. Under the hypothesis of parallel X-raybeams, we use the central-slice-projection theorem toreplace the heavy 2D-to-3D registration of projections inthe signal domain by efficient slice-to-volumeregistration in the Fourier domain. Focusing onrotational movements, the translation-relevant phaseinformation can be discarded and we only consider scalarFourier amplitudes. The core of our motion trackingalgorithm can be implemented as a classical frame-wiseslice-to-volume registration task. Preliminary results onboth synthetic and real images confirm the validity ofour approach.
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The slow-phase velocity of nystagmus is one of the most sensitive parameters of vestibular function and is currently the standard for evaluating the caloric test. However, the assessment of this parameter requires recording the response by using nystagmography. The aim of this study was to evaluate whether frequency and duration of the caloric nystagmus, as measured by using a clinical test with Frenzel glasses, could predict the result of the recorded test. The retrospective analysis of 222 caloric test results recorded by means of electronystagmography has shown a good association between the 3 parameters for unilateral weakness. The asymmetry observed in the velocity can be predicted by a combination of frequency and duration. On the other hand, no relationship was observed between the parameters for directional preponderance. These results indicate that a clinical caloric test with frequency and duration as parameters can be used to predict the unilateral weakness, which would be obtained by use of nystagmography. We propose an evaluation of the caloric test on the basis of diagrams combining the 3 response parameters.
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The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.
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Debris flows and related landslide processes occur in many regions all over Norway and pose a significant hazard to inhabited areas. Within the framework of the development of a national debris flows susceptibility map, we are working on a modeling approach suitable for Norway with a nationwide coverage. The discrimination of source areas is based on an index approach, which includes topographic parameters and hydrological settings. For the runout modeling, we use the Flow-R model (IGAR, University of Lausanne), which is based on combined probabilistic and energetic algorithms for the assessment of the spreading of the flow and maximum runout distances. First results for different test areas have shown that runout distances can be modeled reliably. For the selection of source areas, however, additional factors have to be considered, such as the lithological and quaternary geological setting, in order to accommodate the strong variation in debris flow activity in the different geological, geomorphological and climate regions of Norway.
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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.
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Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.
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A change in paradigm is needed in the prevention of toxic effects on the nervous system, moving from its present reliance solely on data from animal testing to a prediction model mostly based on in vitro toxicity testing and in silico modeling. According to the report published by the National Research Council (NRC) of the US National Academies of Science, high-throughput in vitro tests will provide evidence for alterations in"toxicity pathways" as the best possible method of large scale toxicity prediction. The challenges to implement this proposal are enormous, and provide much room for debate. While many efforts address the technical aspects of implementing the vision, many questions around it need also to be addressed. Is the overall strategy the only one to be pursued? How can we move from current to future paradigms? Will we ever be able to reliably model for chronic and developmental neurotoxicity in vitro? This paper summarizes four presentations from a symposium held at the International Neurotoxicology Conference held in Xi"an, China, in June 2011. A. Li reviewed the current guidelines for neurotoxicity and developmental neurotoxicity testing, and discussed the major challenges existing to realize the NCR vision for toxicity testing. J. Llorens reviewed the biology of mammalian toxic avoidance in view of present knowledge on the physiology and molecular biology of the chemical senses, taste and smell. This background information supports the hypothesis that relating in vivo toxicity to chemical epitope descriptors that mimic the chemical encoding performed by the olfactory system may provide a way to the long term future of complete in silico toxicity prediction. S. Ceccatelli reviewed the implementation of rodent and human neural stem cells (NSCs) as models for in vitro toxicity testing that measures parameters such as cell proliferation, differentiation and migration. These appear to be sensitive endpoints that can identify substances with developmental neurotoxic potential. C. Sun ol reviewed the use of primary neuronal cultures in testing for neurotoxicity of environmental pollutants, including the study of the effects of persistent exposures and/or in differentiating cells, which allow recording of effects that can be extrapolated to human developmental neurotoxicity.
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The building industry has a particular interest in using clinching as a joining method for frame constructions of light-frame housing. Normally many clinch joints are required in joining of frames.In order to maximise the strength of the complete assembly, each clinch joint must be as sound as possible. Experimental testing is the main means of optimising a particular clinch joint. This includes shear strength testing and visual observation of joint cross-sections. The manufacturers of clinching equipment normally perform such experimental trials. Finite element analysis can also be used to optimise the tool geometry and the process parameter, X, which represents the thickness of the base of the joint. However, such procedures require dedicated software, a skilled operator, and test specimens in order to verify the finite element model. In addition, when using current technology several hours' computing time may be necessary. The objective of the study was to develop a simple calculation procedure for rapidly establishing an optimum value for the parameter X for a given tool combination. It should be possible to use the procedure on a daily basis, without stringent demands on the skill of the operator or the equipment. It is also desirable that the procedure would significantly decrease thenumber of shear strength tests required for verification. The experimental workinvolved tests in order to obtain an understanding of the behaviour of the sheets during clinching. The most notable observation concerned the stage of the process in which the upper sheet was initially bent, after which the deformation mechanism changed to shearing and elongation. The amount of deformation was measured relative to the original location of the upper sheet, and characterised as the C-measure. By understanding in detail the behaviour of the upper sheet, it waspossible to estimate a bending line function for the surface of the upper sheet. A procedure was developed, which makes it possible to estimate the process parameter X for each tool combination with a fixed die. The procedure is based on equating the volume of material on the punch side with the volume of the die. Detailed information concerning the behaviour of material on the punch side is required, assuming that the volume of die does not change during the process. The procedure was applied to shear strength testing of a sample material. The sample material was continuously hot-dip zinc-coated high-strength constructional steel,with a nominal thickness of 1.0 mm. The minimum Rp0.2 proof stress was 637 N/mm2. Such material has not yet been used extensively in light-frame housing, and little has been published on clinching of the material. The performance of the material is therefore of particular interest. Companies that use clinching on a daily basis stand to gain the greatest benefit from the procedure. By understanding the behaviour of sheets in different cases, it is possible to use data at an early stage for adjusting and optimising the process. In particular, the functionality of common tools can be increased since it is possible to characterise the complete range of existing tools. The study increases and broadens the amount ofbasic information concerning the clinching process. New approaches and points of view are presented and used for generating new knowledge.
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Kuvien laatu on tutkituimpia ja käytetyimpiä aiheita. Tässä työssä tarkastellaan värin laatu ja spektrikuvia. Työssä annetaan yleiskuva olemassa olevista pakattujen ja erillisten kuvien laadunarviointimenetelmistä painottaen näiden menetelmien soveltaminen spektrikuviin. Tässä työssä esitellään spektriväriulkomuotomalli värikuvien laadunarvioinnille. Malli sovelletaan spektrikuvista jäljennettyihin värikuviin. Malli pohjautuu sekä tilastolliseen spektrikuvamalliin, joka muodostaa yhteyden spektrikuvien ja valokuvien parametrien välille, että kuvan yleiseen ulkomuotoon. Värikuvien tilastollisten spektriparametrien ja fyysisten parametrien välinen yhteys on varmennettu tietokone-pohjaisella kuvamallinnuksella. Mallin ominaisuuksien pohjalta on kehitetty koekäyttöön tarkoitettu menetelmä värikuvien laadunarvioinnille. On kehitetty asiantuntija-pohjainen kyselymenetelmä ja sumea päättelyjärjestelmä värikuvien laadunarvioinnille. Tutkimus osoittaa, että spektri-väri –yhteys ja sumea päättelyjärjestelmä soveltuvat tehokkaasti värikuvien laadunarviointiin.
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Background. Molecular tests for breast cancer (BC) risk assessment are reimbursed by health insurances in Switzerland since the beginning of year 2015. The main current role of these tests is to help oncologists to decide about the usefulness of adjuvant chemotherapy in patients with early stage endocrine-sensitive and human epidermal growth factor receptor 2 (HER2)-negative BC. These gene expression signatures aim at predicting the risk of recurrence in this subgroup. One of them (OncotypeDx/OT) also predicts distant metastases rate with or without the addition of cytotoxic chemotherapy to endocrine therapy. The clinical utility of these tests -in addition to existing so-called "clinico-pathological" prognostic and predictive criteria (e.g. stage, grade, biomarkers status)-is still debated. We report a single center one year experience of the use of one molecular test (OT) in clinical decision making. Methods. We extracted from the CHUV Breast Cancer Center data base the total number of BC cases with estrogen-receptor positive (ER+), HER2-negative early breast cancer (node negative (pN0) disease or micrometastases in up to 3 lymph nodes) operated between September 2014 and August 2015. For the cases from this group in which a molecular test had been decided by the tumor board, we collected the clinicopathologic parameters, the initial tumor board decision, and the final adjuvant systemic therapy decision. Results. A molecular test (OT) was done in 12.2% of patients with ER + HER2 negative early BC. The median age was 57.4 years and the median invasive tumor size was 1.7 cm. These patients were classified by ODX testing (Recurrence Score) into low-, intermediate-, and high risk groups, respectively in 27.2%, 63.6% and 9% of cases. Treatment recommendations changed in 18.2%, predominantly from chemotherapyendocrine therapy to endocrine treatment alone. Of 8 patients originally recommended chemotherapy, 25% were recommended endocrine treatment alone after receiving the Recurrence Score result. Conclusions. Though reimbursed by health insurances since January 2015, molecular tests are used moderately in our institution as per the decision of the multidisciplinary tumor board. It's mainly used to obtain a complementary confirmation supporting the decision of no chemotherapy. The OncotypeDx Recurrence Score results were in the intermediate group in 66% of the 9 tested cases but contributed to avoid chemotherapy in 2 patients during the last 12 months.
The effects of real time control of welding parameters on weld quality in plasma arc keyhole welding
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Joints intended for welding frequently show variations in geometry and position, for which it is unfortunately not possible to apply a single set of operating parameters to ensure constant quality. The cause of this difficulty lies in a number of factors, including inaccurate joint preparation and joint fit up, tack welds, as well as thermal distortion of the workpiece. In plasma arc keyhole welding of butt joints, deviations in the gap width may cause weld defects such as an incomplete weld bead, excessive penetration and burn through. Manual adjustment of welding parameters to compensate for variations in the gap width is very difficult, and unsatisfactory weld quality is often obtained. In this study a control system for plasma arc keyhole welding has been developed and used to study the effects of the real time control of welding parameters on gap tolerance during welding of austenitic stainless steel AISI 304L. The welding tests demonstrated the beneficial effect of real time control on weld quality. Compared with welding using constant parameters, the maximum tolerable gap width with an acceptable weld quality was 47% higher when using the real time controlled parameters for a plate thickness of 5 mm. In addition, burn through occurred with significantly larger gap widths when parameters were controlled in real time. Increased gap tolerance enables joints to be prepared and fit up less accurately, saving time and preparation costs for welding. In addition to the control system, a novel technique for back face monitoring is described in this study. The test results showed that the technique could be successfully applied for penetration monitoring when welding non magnetic materials. The results also imply that it is possible to measure the dimensions of the plasma efflux or weld root, and use this information in a feedback control system and, thus, maintain the required weld quality.