830 resultados para Gradient-based approaches
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INTRODUCTION: Dendritic cells (DCs) are the most important antigen-presenting cell population for activating antitumor T-cell responses; therefore, they offer a unique opportunity for specific targeting of tumors. AREAS COVERED: We will discuss the critical factors for the enhancement of DC vaccine efficacy: different DC subsets, types of in vitro DC manufacturing protocol, types of tumor antigen to be loaded and finally different adjuvants for activating them. We will cover potential combinatorial strategies with immunomodulatory therapies: depleting T-regulatory (Treg) cells, blocking VEGF and blocking inhibitory signals. Furthermore, recommendations to incorporate these criteria into DC-based tumor immunotherapy will be suggested. EXPERT OPINION: Monocyte-derived DCs are the most widely used DC subset in the clinic, whereas Langerhans cells and plasmacytoid DCs are two emerging DC subsets that are highly effective in eliciting cytotoxic T lymphocyte responses. Depending on the type of tumor antigens selected for loading DCs, it is important to optimize a protocol that will generate highly potent DCs. The future aim of DC-based immunotherapy is to combine it with one or more immunomodulatory therapies, for example, Treg cell depletion, VEGF blockage and T-cell checkpoint blockage, to elicit the most optimal antitumor immunity to induce long-term remission or even cure cancer patients.
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Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.
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Le Coran et la Sunna (la tradition du prophète Muḥammad) relatée dans les aḥâdîth (les traditions orales du Prophète) représentent la source éternelle d’inspiration et de savoir à laquelle les Musulmans se réfèrent pour agir, réagir et interagir. Par le fait même, tout au long de l’histoire musulmane, ces sources sacrées ont été à la base des relations des Musulmans avec autrui, incluant les Chrétiens. Les trois éléments majeurs de différenciation entre l’islam et le christianisme sont : la nature divine de Jésus, la trinité ainsi que la crucifixion et la mort de Jésus sur la croix. La position tranchée du Coran quant aux deux premiers points ne laisse place à aucun débat académique. Cependant, l’ambiguïté du texte coranique quant à la crucifixion de Jésus et sa mort a favorisé de nombreux débats entre mufassirûn (les exégètes du Coran). Cette thèse est une analyse textuelle des deux passages coraniques qui traitent de cette troisième différence. Pour cette étude textuelle et intertextuelle, les tafâsîr (interprétations du Coran) de huit mufassirûn appartenant à différentes madhâhib (écoles d’interprétation) et périodes de l’histoire des relations musulmanes-chrétiennes sont utilisés en combinaison avec certaines approches et méthodes récentes telles que : historico-critique et critique rédactionnelle. De plus, trois nouvelles théories développées dans la thèse enrichissent les outils herméneutiques de la recherche : la « théorie des cinq couches de sens », la « théorie des messages coraniques doubles » et la « théorie de la nature humaine tripartite ». À la lumière de ces théories et méthodes, il apparaît que l’ambiguïté coranique au sujet de la crucifixion et de la mort de Jésus est une invitation claire de la part du Coran incitant les Musulmans et les Chrétiens à vivre avec cette ambiguïté insoluble. La conclusion de cette thèse contribue directement à de meilleures relations musulmanes-chrétiennes, renforçant l’appel coranique (Coran 3:64, 103) à ces deux communautés leurs demandant de se cramponner aux points communs majeurs, d’intégrer leurs différences mineures et de consacrer leurs énergies pour une vie harmonieuse entre eux et laisser le reste dans les mains du Dieu qu’ils ont en commun.
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Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a current field course module, this project describes the implementation of two test Problem-Based Learning activities and testing and improvement using several different and complementary means of evaluation. By the end of a 2-year program of design, implementation, testing, and reflection and re-evaluation, two robust, engaging activities have been developed that provide an enhanced and diverse learning environment in the field course. The results suggest that Problem-Based Learning techniques would be a useful addition to the meteorology curriculum and suggestions for courses and activities that may benefit from this approach are included in the conclusions.
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Using a canonical formulation, the stability of the rotational motion of artificial satellites is analyzed considering perturbations due to the gravity gradient torque. Here Andoyer's variables are used to describe the rotational motion. One of the approaches that allow the analysis of the stability of Hamiltonian systems needs the reduction of the Hamiltonian to a normal form. Firstly equilibrium points are found. Using generalized coordinates, the Hamiltonian is expanded in the neighborhood of the linearly stable equilibrium points. In a next step a canonical linear transformation is used to diagonalize the matrix associated to the linear part of the system. The quadratic part of the Hamiltonian is normalized. Based in a Lie-Hori algorithm a semi-analytic process for normalization is applied and the Hamiltonian is normalized up to the fourth order. Once the Hamiltonian is normalized up to order four, the analysis of stability of the equilibrium point is performed using the theorem of Kovalev and Savichenko. This semi-analytical approach was applied considering some data sets of hypothetical satellites. For the considered satellites it was observed few cases of stable motion. This work contributes for space missions where the maintenance of spacecraft attitude stability is required.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Server responsiveness and scalability are more important than ever in today’s client/server dominated network environments. Recently, researchers have begun to consider cluster-based computers using commodity hardware as an alternative to expensive specialized hardware for building scalable Web servers. In this paper, we present performance results comparing two cluster-based Web servers based on different server infrastructures: MAC-based dispatching (LSMAC) and IP-based dispatching (LSNAT). Both cluster-based server systems were implemented as application-space programs running on commodity hardware. We point out the advantages and disadvantages of both systems. We also identify when servers should be clustered and when clustering will not improve performance.
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Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.
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Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.
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Inflammatory Bowel Diseases (IBD) are intestinal chronic relapsing diseases which ethiopathogenesis remains uncertain. Several group have attempted to study the role of factors involved such as genetic susceptibility, environmental factors such as smoke, diet, sex, immunological factors as well as the microbioma. None of the treatments available satisfy several criteria at the same time such as safety, long-term remission, histopatological healing, and specificity. We used two different approaches for the development of new therapeutic treatment for Inflammatory Bowel Disease. The first is focused on the understanding of the potential role of functional food and nutraceuticals nutrients in the treatment of IBD. To do so, we investigated the role of Curcuma longa in the treatment of chemical induced colitis in mice model. Since Curcma Longa has been investigated for its antinflammatory role related to the TNFα pathway as well investigators have reported few cases of patients with ulcerative colites treated with this herbs, we harbored the hypothesis of a role of Curcuma Longa in the treatment f IBD as well as we decided to assess its role in intestinal motility. The second part is based on an immunological approach to develop new drugs to induce suppression in Crohn’s disease or to induce mucosa immunity such as in colonrectal tumor. The main idea behind this approach is that we could manipulate relevant cell-cell interactions using synthetic peptides. We demonstrated the role of the unique interaction between molecules expressed on intestinal epithelial cells such as CD1d and CEACAM5 and on CD8+ T cells. In normal condition this interaction has a role for the expansion of the suppressor CD8+ T cells. Here, we characterized this interaction, we defined which are the epitope involved in the binding and we attempted to develop synthetic peptides from the N domain of CEACAM5 in order to manipulate it.
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This paper describes a method for DRR generation as well as for volume gradients projection using hardware accelerated 2D texture mapping and accumulation buffering and demonstrates its application in 2D-3D registration of X-ray fluoroscopy to CT images. The robustness of the present registration scheme are guaranteed by taking advantage of a coarse-to-fine processing of the volume/image pyramids based on cubic B-splines. A human cadaveric spine specimen together with its ground truth was used to compare the present scheme with a purely software-based scheme in three aspects: accuracy, speed, and capture ranges. Our experiments revealed an equivalent accuracy and capture ranges but with much shorter registration time with the present scheme. More specifically, the results showed 0.8 mm average target registration error, 55 second average execution time per registration, and 10 mm and 10° capture ranges for the present scheme when tested on a 3.0 GHz Pentium 4 computer.