986 resultados para Value Functions


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In this study the theoretical part was created to make comparison between different Value at Risk models. Based on that comparison one model was chosen to the empirical part which concentrated to find out whether the model is accurate to measure market risk. The purpose of this study was to test if Volatility-weighted Historical Simulation is accurate in measuring market risk and what improvements does it bring to market risk measurement compared to traditional Historical Simulation. Volatility-weighted method by Hull and White (1998) was chosen In order to improve the traditional methods capability to measure market risk. In this study we found out that result based on Historical Simulation are dependent on chosen time period, confidence level and how samples are weighted. The findings of this study are that we cannot say that the chosen method is fully reliable in measuring market risk because back testing results are changing during the time period of this study.

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The finding that tissue δ15N values increase with protein catabolism has led researchers to apply this value to gauge nutritive condition in vertebrates. However, its application to marine mammals has in most occasions failed. We investigated the relationship between δ15N values and the fattening/fasting cycle in a model species, the fin whale, a migratory capital breeder that experiences severe seasonal variation in body condition. We analyzed two tissues providing complementary insights: one with isotopic turnover (muscle) and one that keeps a permanent record of variations in isotopic values (baleen plates). In both tissues δ15N values increased with intensive feeding but decreased with fasting, thus contradicting the pattern previously anticipated. The apparent inconsistency during fasting is explained by the fact that a) individuals migrate between different isotopic isoscapes, b) starvation may not trigger significant negative nitrogen balance, and c) excretion drops and elimination of 15N-depleted urine is minimized. Conversely, when intensive feeding is resumed in the northern grounds, protein anabolism and excretion start again, triggering 15N enrichment. It can be concluded that in whales and other mammals that accrue massive depots of lipids as energetic reserves and which have limited access to drinking water, the δ15N value is not affected by fasting and therefore cannot be used as an indicatior of nutritive condition.

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OBJECTIVE: Several smaller single-center studies have reported a prognostic role for Ki-67 labeling index in prostate cancer. Our aim was to test whether Ki-67 is an independent prognostic marker of biochemical recurrence (BCR) in a large international cohort of patients treated with radical prostatectomy (RP). METHODS: Ki-67 immunohistochemical staining on prostatectomy specimens from 3,123 patients who underwent RP for prostate cancer was retrospectively performed. Univariable and multivariable Cox regression models were used to assess the association of Ki-67 status with BCR. RESULTS: Ki-67 positive status was observed in 762 (24.4 %) patients and was associated with lymph node involvement (LNI) (p = 0.039). Six hundred and twenty-one (19.9 %) patients experienced BCR. The estimated 3-year biochemical-free survivals were 85 % for patients with negative Ki-67 status and 82.1 % for patients with positive Ki-67 status (log-rank test, p = 0.014). In multivariable analysis that adjusted for the effects of age, preoperative PSA, RP Gleason sum, seminal vesicle invasion, extracapsular extension, positive surgical margins, lymphovascular invasion, and LNI, Ki-67 was significantly associated with BCR (HR = 1.19; p = 0.019). Subgroup analysis revealed that Ki-67 is associated with BCR in patients without LNI (p = 0.004), those with RP Gleason sum 7 (p = 0.015), and those with negative surgical margins (p = 0.047). CONCLUSION: We confirmed Ki-67 as an independent predictor of BCR after RP. Ki-67 could be particularly informative in patients with favorable pathologic characteristics to help in the clinical decision-making regarding adjuvant therapy and optimized follow-up scheduling.

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Introduction: B-type natriuretic peptide (BNP) is a biomarker of myocardial stress. In children, the value of preoperative BNP on postoperative outcome is unclear. The aim of this study was to determine the predictive value of preoperative NT-proBNP on postoperative outcome in children after congenital heart surgery. Results: Ninety-seven patients were included in the study with a median age of 3.3 years [0.7-5.2]. Preoperative median NT-proBNP was 412 pg/ml [164-1309]. NT-proBNP was above the P95 reference value for age in 56 patients (58%). Preoperative NT-proBNP was significantly higher in patients who had mechanical ventilation duration of more than 2 days (1156 pg/ml [281-1951] vs. 267 pg/ml [136-790], p=0.003) and who stayed more than 6 days in the pediatric intensive care unit (727 pg/ml [203-1951] vs. 256 pg/ml [136-790], p=0.007). However, preoperative NT-proBNP was not significantly higher in patients with an increased inotropic score, a prolonged cardiopulmonary bypass time or an increased surgical risk category. Conclusions: An elevated preoperative NT-proBNP reflects hemodynamic status and cardiac dysfunction, and therefore is a valuable adjunct in predicting a complicated postoperative course. ___________________________________ Introduction: Le peptide natriurétique type B (BNP) est un marqueur reflétant le stress myocardique. Dans la population pédiatrique, la signification des valeurs préopératoire de BNP, en particulier sur l'évolution postopératoire, n'est pas clairement établie. Le but de l'étude est de déterminer la valeur prédictive de la partie NT sérique du BNP (NT-proBNP) sur l'évolution post opératoire d'enfants porteur d'une cardiopathie congénitale et ayant eu une chirurgie cardiaque. Résultats: Nonante-sept enfants ont été inclus dans l'étude, avec un âge médian de 3.3 ans [0.7-5.2]. La valeur médiane du NT-proBNP préopératoire était de 412 pg/ml [164-1309]. Le NT-proBNP préopératoire était supérieur au P95 des valeurs de référence pour l'âge chez 56 patients (58%). Le NT-proBNP préopératoire était significativement plus élevé chez les patients ayant eu plus de deux jours de ventilation mécanique dans la période postopératoire (1156 pg/ml [281-1951] vs. 267 pg/ml [136-790], p=0.003) et ayant été hospitalisés plus de 6 jours dans l'unité de soins intensifs pédiatrique (727 pg/ml [203-1951] vs. 256 pg/ml [136-790], p=0.007). Par contre, le NT-proBNP préopératoire n'était pas significativement plus élevé chez les patients ayant eu un score d'inotrope élevé pendant leur hospitalisation aux soins intensifs, un temps de circulation extracorporelle prolongé ou ayant subi une chirurgie avec un risque chirurgical élevé. Conclusions: Un NT-proBNP sérique élevé en préopératoire reflète l'importance du stress myocardique induit par l'hémodynamique et la dysfonction myocardique, il est un marqueur qui permet d'améliorer l'identification des patients à risque d'avoir une évolution post opératoire compliquée.

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Very large molecular systems can be calculated with the so called CNDOL approximate Hamiltonians that have been developed by avoiding oversimplifications and only using a priori parameters and formulas from the simpler NDO methods. A new diagonal monoelectronic term named CNDOL/21 shows great consistency and easier SCF convergence when used together with an appropriate function for charge repulsion energies that is derived from traditional formulas. It is possible to obtain a priori molecular orbitals and electron excitation properties after the configuration interaction of single excited determinants with reliability, maintaining interpretative possibilities even being a simplified Hamiltonian. Tests with some unequivocal gas phase maxima of simple molecules (benzene, furfural, acetaldehyde, hexyl alcohol, methyl amine, 2,5 dimethyl 2,4 hexadiene, and ethyl sulfide) ratify the general quality of this approach in comparison with other methods. The calculation of large systems as porphine in gas phase and a model of the complete retinal binding pocket in rhodopsin with 622 basis functions on 280 atoms at the quantum mechanical level show reliability leading to a resulting first allowed transition in 483 nm, very similar to the known experimental value of 500 nm of "dark state." In this very important case, our model gives a central role in this excitation to a charge transfer from the neighboring Glu(-) counterion to the retinaldehyde polyene chain. Tests with gas phase maxima of some important molecules corroborate the reliability of CNDOL/2 Hamiltonians.

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One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

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We all make decisions of varying levels of importance every day. Because making a decision implies that there are alternative choices to be considered, almost all decision involves some conflicts or dissatisfaction. Traditional economic models esteem that a person must weight the positive and negative outcomes of each option, and based on all these inferences, determines which option is the best for that particular situation. However, individuals rather act as irrational agents and tend to deviate from these rational choices. They somewhat evaluate the outcomes' subjective value, namely, when they face a risky choice leading to losses, people are inclined to have some preference for risk over certainty, while when facing a risky choice leading to gains, people often avoid to take risks and choose the most certain option. Yet, it is assumed that decision making is balanced between deliberative and emotional components. Distinct neural regions underpin these factors: the deliberative pathway that corresponds to executive functions, implies the activation of the prefrontal cortex, while the emotional pathway tends to activate the limbic system. These circuits appear to be altered in individuals with ADHD, and result, amongst others, in impaired decision making capacities. Their impulsive and inattentive behaviors are likely to be the cause of their irrational attitude towards risk taking. Still, a possible solution is to administrate these individuals a drug treatment, with the knowledge that it might have several side effects. However, an alternative treatment that relies on cognitive rehabilitation might be appropriate. This project was therefore aimed at investigate whether an intensive working memory training could have a spillover effect on decision making in adults with ADHD and in age-matched healthy controls. We designed a decision making task where the participants had to select an amount to gamble with the chance of 1/3 to win four times the chosen amount, while in the other cases they could loose their investment. Their performances were recorded using electroencephalography prior and after a one-month Dual N-Back training and the possible near and far transfer effects were investigated. Overall, we found that the performance during the gambling task was modulated by personality factors and by the importance of the symptoms at the pretest session. At posttest, we found that all individuals demonstrated an improvement on the Dual N-Back and on similar untrained dimensions. In addition, we discovered that not only the adults with ADHD showed a stable decrease of the symptomatology, as evaluated by the CAARS inventory, but this reduction was also detected in the control samples. In addition, Event-Related Potential (ERP) data are in favor of an change within prefrontal and parietal cortices. These results suggest that cognitive remediation can be effective in adults with ADHD, and in healthy controls. An important complement of this work would be the examination of the data in regard to the attentional networks, which could empower the fact that complex programs covering the remediation of several executive functions' dimensions is not required, a unique working memory training can be sufficient. -- Nous prenons tous chaque jour des décisions ayant des niveaux d'importance variables. Toutes les décisions ont une composante conflictuelle et d'insatisfaction, car prendre une décision implique qu'il y ait des choix alternatifs à considérer. Les modèles économiques traditionnels estiment qu'une personne doit peser les conséquences positives et négatives de chaque option et en se basant sur ces inférences, détermine quelle option est la meilleure dans une situation particulière. Cependant, les individus peuvent dévier de ces choix rationnels. Ils évaluent plutôt les valeur subjective des résultats, c'est-à-dire que lorsqu'ils sont face à un choix risqué pouvant les mener à des pertes, les gens ont tendance à avoir des préférences pour le risque à la place de la certitude, tandis que lorsqu'ils sont face à un choix risqué pouvant les conduire à un gain, ils évitent de prendre des risques et choisissent l'option la plus su^re. De nos jours, il est considéré que la prise de décision est balancée entre des composantes délibératives et émotionnelles. Ces facteurs sont sous-tendus par des régions neurales distinctes: le chemin délibératif, correspondant aux fonctions exécutives, implique l'activation du cortex préfrontal, tandis que le chemin émotionnel active le système limbique. Ces circuits semblent être dysfonctionnels chez les individus ayant un TDAH, et résulte, entre autres, en des capacités de prise de décision altérées. Leurs comportements impulsifs et inattentifs sont probablement la cause de ces attitudes irrationnelles face au risque. Cependant, une solution possible est de leur administrer un traitement médicamenteux, en prenant en compte les potentiels effets secondaires. Un traitement alternatif se reposant sur une réhabilitation cognitive pourrait être appropriée. Le but de ce projet est donc de déterminer si un entrainement intensif de la mémoire de travail peut avoir un effet sur la prise de décision chez des adultes ayant un TDAH et chez des contrôles sains du même âge. Nous avons conçu une tâche de prise de décision dans laquelle les participants devaient sélectionner un montant à jouer en ayant une chance sur trois de gagner quatre fois le montant choisi, alors que dans l'autre cas, ils pouvaient perdre leur investissement. Leurs performances ont été enregistrées en utilisant l'électroencéphalographie avant et après un entrainement d'un mois au Dual N-Back, et nous avons étudié les possibles effets de transfert. Dans l'ensemble, nous avons trouvé au pré-test que les performances au cours du jeu d'argent étaient modulées par les facteurs de personnalité, et par le degré des sympt^omes. Au post-test, nous avons non seulement trouvé que les adultes ayant un TDAH montraient une diminutions stable des symptômes, qui étaient évalués par le questionnaire du CAARS, mais que cette réduction était également perçue dans l'échantillon des contrôles. Les rsultats expérimentaux mesurés à l'aide de l'éléctroencéphalographie suggèrent un changement dans les cortex préfrontaux et pariétaux. Ces résultats suggèrent que la remédiation cognitive est efficace chez les adultes ayant un TDAH, mais produit aussi un effet chez les contrôles sains. Un complément important de ce travail pourrait examiner les données sur l'attention, qui pourraient renforcer l'idée qu'il n'est pas nécessaire d'utiliser des programmes complexes englobant la remédiation de plusieurs dimensions des fonctions exécutives, un simple entraiment de la mémoire de travail devrait suffire.

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The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

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Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.