Axial buckling load of partially encased columns under fire

Partially encased columns have significant fire resistant. However, it is not possible to assess the fire resistance of such members simply by considering the temperature of the steel. The presence of concrete increases the mass and thermal inertia of the member and the variation of temperature within the cross section, in both the steel and concrete components. The annex G of EN1994-1-2 allows to calculate the load carrying capacity of partially encased columns, for a specific fire rating time, considering the balanced summation method. New formulas will be used to calculate the plastic resistance to axial compression and the effective flexural stiffness. These two parameters are used to calculate the buckling resistance. The finite element method is used to compare the results of the elastic critical load for different fire ratings of 30 and 60 minutes. The buckling resistance is also calculated by the finite element method, using an incremental and iterative procedure. This buckling resistance is also compared with the simple calculation method, evaluating the design buckling curve that best fits the results.

ALK rearrangement in a selected population of advanced non small cell lung cancer patients. FISH and inmunohistochemistry diagnostic methods, prevalence and clinical outcomes

Anaplastic lymphoma kinase (ALK) rearrangements represents a new driver oncogenic event in non-small cell lung cancer (NSCLC). ALK positive patients account for a 1-7% of NSCLC patients. The objective of this study is to know the prevalence and clinical characteristics of ALK positive patients in a cohort of NSCLC patients and to compare inmunohistochemistry with D5F3 monoclonal antibody with gold standard method fluorescence in situ hybridation

Fluid flow and dispersion predictions in porous media by utilizing advanced numerical methods

Diplomityön tavoitteena oli tarkastella numeerisen virtauslaskennan avulla virtaukseen liittyviä ilmiöitä ja kaasun dispersiota. Diplomityön sisältö on jaettu viiteen osaan; johdantoon, teoriaan, katsaukseen virtauksen mallinnukseen huokoisessa materiaalissa liittyviin tutkimusselvityksiin, numeeriseen mallinnukseen sekä tulosten esittämiseen ja johtopäätöksiin. Diplomityön alussa kiinnitettiin huomiota erilaisiin kokeellisiin, numeerisiin ja teoreettisiin mallinnusmenetelmiin, joilla voidaan mallintaa virtausta huokoisessa materiaalissa. Kirjallisuusosassa tehtiin katsaus aikaisemmin julkaistuihin puoliempiirisiin ja empiirisiin tutkimusselvityksiin, jotka liittyvät huokoisen materiaalin aiheuttamaan painehäviöön. Numeerisessa virtauslaskenta osassa rakennettiin ja esitettiin huokoista materiaalia kuvaavat numeeriset mallit käyttäen kaupallista FLUENT -ohjelmistoa. Työn lopussa arvioitiin teorian, numeerisen virtauslaskennan ja kokeellisten tutkimusselvitysten tuloksia. Kolmiulotteisen huokoisen materiaalinnumeerisessa mallinnuksesta saadut tulokset vaikuttivat lupaavilta. Näiden tulosten perusteella tehtiin suosituksia ajatellen tulevaa virtauksen mallinnusta huokoisessa materiaalissa. Osa tässä diplomityössä esitetyistä tuloksista tullaan esittämään 55. Kanadan Kemiantekniikan konferenssissa Torontossa 1619 Lokakuussa 2005. ASME :n kansainvälisessä tekniikan alan julkaisussa. Työ on hyväksytty esitettäväksi esitettäväksi laskennallisen virtausmekaniikan (CFD) aihealueessa 'Peruskäsitteet'. Lisäksi työn yksityiskohtaiset tulokset tullaan lähettämään myös CES:n julkaisuun.

Review and comparison of effective delayed neutron fraction calculation methods with Monte Carlo codes

The calculation of the effective delayed neutron fraction, beff , with Monte Carlo codes is a complex task due to the requirement of properly considering the adjoint weighting of delayed neutrons. Nevertheless, several techniques have been proposed to circumvent this difficulty and obtain accurate Monte Carlo results for beff without the need of explicitly determining the adjoint flux. In this paper, we make a review of some of these techniques; namely we have analyzed two variants of what we call the k-eigenvalue technique and other techniques based on different interpretations of the physical meaning of the adjoint weighting. To test the validity of all these techniques we have implemented them with the MCNPX code and we have benchmarked them against a range of critical and subcritical systems for which either experimental or deterministic values of beff are available. Furthermore, several nuclear data libraries have been used in order to assess the impact of the uncertainty in nuclear data in the calculated value of beff .

Bioactive sol-gel glasses at the atomic scale:the complementary use of advanced probe and computer modeling methods

Sol-gel-synthesized bioactive glasses may be formed via a hydrolysis condensation reaction, silica being introduced in the form of tetraethyl orthosilicate (TEOS), and calcium is typically added in the form of calcium nitrate. The synthesis reaction proceeds in an aqueous environment; the resultant gel is dried, before stabilization by heat treatment. These materials, being amorphous, are complex at the level of their atomic-scale structure, but their bulk properties may only be properly understood on the basis of that structural insight. Thus, a full understanding of their structure-property relationship may only be achieved through the application of a coherent suite of leading-edge experimental probes, coupled with the cogent use of advanced computer simulation methods. Using as an exemplar a calcia-silica sol-gel glass of the kind developed by Larry Hench, in the memory of whom this paper is dedicated, we illustrate the successful use of high-energy X-ray and neutron scattering (diffraction) methods, magic-angle spinning solid-state NMR, and molecular dynamics simulation as components to a powerful methodology for the study of amorphous materials.

(18)F-FDG PET After 2 Cycles of ABVD Predicts Event-Free Survival in Early and Advanced Hodgkin Lymphoma

Our objective was to assess the prognostic value of (18)F-FDG PET after 2 cycles of chemotherapy using doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) in Hodgkin lymphoma (HL) patients overall and in subgroups of patients with early and advanced stages and with low and high risks according to the International Prognostic Score (IPS). Methods: One hundred fifteen patients with newly diagnosed HL were prospectively included in the study. All underwent standard ABVD therapy followed by consolidation radiotherapy in cases of bulky disease. After 2 cycles of ABVD, the patients were evaluated with PET (PET2). Prognostic analysis compared the 3-y event-free survival (EFS) rate to the PET2 results, clinical data, and IPS. Results: Of the 104 evaluated patients, 93 achieved complete remission after first-line therapy. During a median follow-up of 36 mo, relapse or disease progression was seen in 22 patients. Treatment failure was seen in 16 of the 30 PET2-positive patients and in only 6 of the 74 PET2-negative patients. PET2 was the only significant prognostic factor. The 3-y EFS was 53.4% for PET2-positive patients and 90.5% for PET2-negative ones (P < 0.001). When patients were categorized according to low or high IPS risk and according to early or advanced stage of disease, PET2 was also significantly associated with treatment outcome. Conclusion: PET2 is an accurate and independent predictor of EFS in HL. A negative interim (18)F-FDG PET result is highly predictive of treatment success in overall HL patients, as well as in subgroups with early or advanced-stage disease and with low or high IPS risk.

Adhesive selection for single lap bonded joints: Experimentation and advanced techniques for strength prediction

The integrity of multi-component structures is usually determined by their unions. Adhesive-bonding is often used over traditional methods because of the reduction of stress concentrations, reduced weight penalty, and easy manufacturing. Commercial adhesives range from strong and brittle (e.g., Araldite® AV138) to less strong and ductile (e.g., Araldite® 2015). A new family of polyurethane adhesives combines high strength and ductility (e.g., Sikaforce® 7888). In this work, the performance of the three above-mentioned adhesives was tested in single lap joints with varying values of overlap length (LO). The experimental work carried out is accompanied by a detailed numerical analysis by finite elements, either based on cohesive zone models (CZM) or the extended finite element method (XFEM). This procedure enabled detailing the performance of these predictive techniques applied to bonded joints. Moreover, it was possible to evaluate which family of adhesives is more suited for each joint geometry. CZM revealed to be highly accurate, except for largely ductile adhesives, although this could be circumvented with a different cohesive law. XFEM is not the most suited technique for mixed-mode damage growth, but a rough prediction was achieved.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

The emergence of forensic nursing and advanced nursing practice in Switzerland: an innovative case study consultation.

BACKGROUND AND METHODS: The objectives of this article were to systematically describe and examine the novel roles and responsibilities assumed by nurses in a forensic consultation for victims of violence at a University Hospital in French-speaking Switzerland. Utilizing a case study methodology, information was collected from two main sources: (a) discussion groups with nurses and forensic pathologists and (b) a review of procedures and protocols. Following a critical content analysis, the roles and responsibilities of the forensic nurses were described and compared with the seven core competencies of advanced nursing practice as outlined by Hamric, Spross, and Hanson (2009). RESULTS: Advanced nursing practice competencies noted in the analysis included "direct clinical practice," "coaching and guidance," and "collaboration." The role of the nurse in terms of "consultation," "leadership," "ethics," and "research" was less evident in the analysis. DISCUSSION AND CONCLUSION: New forms of nursing are indeed practiced in the forensic clinical setting, and our findings suggest that nursing practice in this domain is following the footprints of an advanced nursing practice model. Further reflections are required to determine whether the role of the forensic nurse in Switzerland should be developed as a clinical nurse specialist or that of a nurse practitioner.

The Emergence of Forensic Nursing and Advanced Nursing Practice in Switzerland: An Innovative Case Study Consultation.

BACKGROUND AND METHODS:: The objectives of this article were to systematically describe and examine the novel roles and responsibilities assumed by nurses in a forensic consultation for victims of violence at a University Hospital in French-speaking Switzerland. Utilizing a case study methodology, information was collected from two main sources: (a) discussion groups with nurses and forensic pathologists and (b) a review of procedures and protocols. Following a critical content analysis, the roles and responsibilities of the forensic nurses were described and compared with the seven core competencies of advanced nursing practice as outlined by Hamric, Spross, and Hanson (2009). RESULTS:: Advanced nursing practice competencies noted in the analysis included "direct clinical practice," "coaching and guidance," and "collaboration." The role of the nurse in terms of "consultation," "leadership," "ethics," and "research" was less evident in the analysis. DISCUSSION AND CONCLUSION:: New forms of nursing are indeed practiced in the forensic clinical setting, and our findings suggest that nursing practice in this domain is following the footprints of an advanced nursing practice model. Further reflections are required to determine whether the role of the forensic nurse in Switzerland should be developed as a clinical nurse specialist or that of a nurse practitioner.

Ultra-performance liquid chromatography mass spectrometry and sensitive bioassay methods for quantification of posaconazole plasma concentrations after oral dosing.

Posaconazole (POS) is a new antifungal agent for prevention and therapy of mycoses in immunocompromised patients. Variable POS pharmacokinetics after oral dosing may influence efficacy: a trough threshold of 0.5 ?g/ml has been recently proposed. Measurement of POS plasma concentrations by complex chromatographic techniques may thus contribute to optimize prevention and management of life-threatening infections. No microbiological analytical method is available. The objective of this study was to develop and validate a new simplified ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method and a sensitive bioassay for quantification of POS over the clinical plasma concentration range. The UPLC-MS/MS equipment consisted of a triple quadrupole mass spectrometer, an electrospray ionization (ESI) source, and a C(18) analytical column. The Candida albicans POS-hypersusceptible mutant (MIC of 0.002 ?g/ml) ?cdr1 ?cdr2 ?flu ?mdr1 ?can constructed by targeted deletion of multidrug efflux transporters and calcineurin genes was used for the bioassay. POS was extracted from plasma by protein precipitation with acetonitrile-methanol (75%/25%, vol/vol). Reproducible standard curves were obtained over the range 0.014 to 12 (UPLC-MS/MS) and 0.028 to 12 ?g/ml (bioassay). Intra- and interrun accuracy levels were 106% ± 2% and 103% ± 4% for UPLC-MS/MS and 102% ± 8% and 104% ± 1% for bioassay, respectively. The intra- and interrun coefficients of variation were 7% ± 4% and 7% ± 3% for UPLC-MS/MS and 5% ± 3% and 4% ± 2% for bioassay, respectively. An excellent correlation between POS plasma concentrations measured by UPLC-MS/MS and bioassay was found (concordance, 0.96). In 26 hemato-oncological patients receiving oral POS, 27/69 (39%) trough plasma concentrations were lower than 0.5 ?g/ml. The UPLC-MS/MS method and sensitive bioassay offer alternative tools for accurate and precise quantification of the plasma concentrations in patients receiving oral posaconazole.

ADVANCED NUMERICAL METHODS FOR SIMULATING MICROBUBBLE IN AN AERATED MIXING TANK

Fluid mixing in mechanically agitated tanks is one of the major unit operations in many industries. Bubbly flows have been of interest among researchers in physics, medicine, chemistry and technology over the centuries. The aim of this thesis is to use advanced numerical methods for simulating microbubble in an aerated mixing tank. Main components of the mixing tank are a cylindrical vessel, a rotating Rushton turbine and the air nozzle. The objective of Computational Fluid Dynamics (CFD) is to predict fluid flow, heat transfer, mass transfer and chemical reactions. The CFD simulations of a turbulent bubbly flow are carried out in a cylindrical mixing tank using large eddy simulation (LES) and volume of fluid (VOF) method. The Rushton turbine induced flow is modeled by using a sliding mesh method. Numerical results are used to describe the bubbly flows in highly complex liquid flow. Some of the experimental works related to turbulent bubbly flow in a mixing tank are briefly reported. Numerical simulations are needed to complete and interpret the results of the experimental work. Information given by numerical simulations has a major role in designing and scaling-up mixing tanks. The results of this work have been reported in the following scientific articles: ·Honkanen M., Koohestany A., Hatunen T., Saarenrinne P., Zamankhan P., Large eddy simulations and PIV experiments of a two-phase air-water mixer, in Proceedings of ASME Fluids Engineering Summer Conference (2005). ·Honkanen M., Koohestany A., Hatunen T., Saarenrinne P., Zamankhan P., Dynamical States of Bubbling in an Aerated Stirring Tank, submitted to J. Computational Physics.

Advanced control methods for reducing nitrogen oxides in a fluidized bed boiler

Tämän työn tarkoituksena oli löytää keinoja erään leijukerroskattilan typenoksidipäästöjen vähentämiseksi. Koska päästöt olivat jo alunperin alhaiset leijukerrostekniikan ja hybridin SNCR/SCR –typenpoistolaitteiston ansiosta, päätettiin päästöjä lähteä vähentämään parantamalla ammoniakkiruiskutuksen säätöä. Alkuperäinen ammoniakkiruiskutuksen säätö oli liian hidas, jotta satunnaisten häiriöiden aiheuttamat typenoksidipiikit olisi pystytty poistamaan. Ammoniakkiruiskutusta parannettiin lisäämällä jokaiseen ammoniakkilinjaan mäntäpumput, joiden avulla ammoniakkia voidaan syöttää sinne, missä sitä eniten tarvitaan. Ammoniakkiruiskutuksen säätöön kehitettiin uusi sumeaan logiikkaan perustuva säätäjä. Myös muita kehittyneitä säätömenetelmiä kuten neuroverkkoa hyödynnettiin säätäjän kehityksessä. Ammoniakkiruiskutuksen säätäjää testattiin menestyksekkäästi Ruotsissa Brista Kraftin Märstassa sijaitsevalla voimalaitoksella

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.