698 research outputs found

    Computing the set of Epsilon-efficient solutions in multiobjective space mission design

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    In this work, we consider multiobjective space mission design problems. We will start from the need, from a practical point of view, to consider in addition to the (Pareto) optimal solutions also nearly optimal ones. In fact, extending the set of solutions for a given mission to those nearly optimal signiïŹcantly increases the number of options for the decision maker and gives a measure of the size of the launch windows corresponding to each optimal solution, i.e., a measure of its robustness. Whereas the possible loss of such approximate solutions compared to optimal—and possibly even ‘better’—ones is dispensable. For this, we will examine several typical problems in space trajectory design—a biimpulsive transfer from the Earth to the asteroid Apophis and two low-thrust multigravity assist transfers—and demonstrate the possible beneïŹt of the novel approach. Further, we will present a multiobjective evolutionary algorithm which is designed for this purpose

    Improved archiving and search strategies for multi agent collaborative search

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    This paper presents a new archiving strategy and some modified search heuristics for the Multi Agent Collaborative Search algorithm (MACS). MACS is a memetic scheme for multi-objective optimisation that combines the local exploration of the neighbourhood of some virtual agents with social actions to advance towards the Pareto front. The new archiving strategy is based on the physical concept of minimising the potential energy of a cloud of points each of which repels the others. Social actions have been modified to better exploit the information in the archive and local actions dynamically adapt the maximum number of coordinates explored in the pattern search heuristic. The impact of these modifications is tested on a standard benchmark and the results are compared against MOEA/D and a previous version of MACS. Finally, a real space related problem is tackled

    A study on using genetic niching for query optimisation in document retrieval

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    International audienceThis paper presents a new genetic approach for query optimisation in document retrieval. The main contribution of the paper is to show the effectiveness of the genetic niching technique to reach multiple relevant regions of the document space. Moreover, suitable merging procedures have been proposed in order to improve the retrieval evaluation. Experimental results obtained using a TREC sub-collection indicate that the proposed approach is promising for applications

    Differential activation of JNK1 isoforms by TRAIL receptors modulate apoptosis of colon cancer cell lines

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    Tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) induces apoptosis on binding to its receptors, death receptor 4 and 5 (DR4, DR5). TRAIL can also activate c-Jun N-terminal kinase (JNK) through the adaptor molecules, TNF receptor-associated factor 2 (TRAF2) and receptor-interacting protein (RIP). The role of JNK in TRAIL-induced tumour cell apoptosis is unclear. In this study, we demonstrate that JNK is activated by TRAIL in colon cancer cells. Inhibition of JNK with L-JNKI reduced rhTRAIL-induced cell death but enhanced cell death induced by selective activation of DR4 or DR5. This difference was unrelated to receptor internalisation or differential activation of c-Jun, but activation of different JNK isoforms. Our data demonstrate that JNK1, but not JNK2 is activated by rhTRAIL in the examined colon cancer cell lines. Although rhTRAIL activated both the long and short isoforms of JNK1, selective activation of DR4 or DR5 led to predominant activation of the short JNK1 isoforms (JNK1α1 and/or JNK1ÎČ1). Knockdown of JNK1α1 by shRNA enhanced apoptosis induced by TRAIL, agonistic DR4 or DR5 antibodies. On the other hand, knockdown of the long JNK1 isoforms (JNK1α2 and JNK1ÎČ2) had the opposite effect; it reduced TRAIL-induced cell death. These data indicate that the short JNK1 isoforms transmit an antiapoptotic signal, whereas the long isoforms (JNK1α2 or JNK1ÎČ2) act in a proapoptotic manner

    Machine Learning in Automated Text Categorization

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    The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

    A rational approach for generating cardiac troponin I selective Spiegelmers

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    We report the first protein selective Spiegelmers of diagnostic relevance by rational identification of a target epitope and reverse screening of Spiegelmer candidates following the selection procedure. Application of the presented approach resulted in isolation of cardiac troponin I selective Spiegelmers with low nanomolar dissociation constant and functionality in serum

    Clinical Factors Associated with Long-Term Complete Remission versus Poor Response to Chemotherapy in HIV-Infected Children and Adolescents with Kaposi Sarcoma Receiving Bleomycin and Vincristine: A Retrospective Observational Study

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    Kaposi sarcoma (KS) is the most common HIV-associated malignancy in children and adolescents in Africa. Pediatric KS is distinct from adult disease. We evaluated the clinical characteristics associated with long-term outcomes. We performed a retrospective observational analysis of 70 HIV-infected children and adolescents with KS less than 18 years of age diagnosed between 8/2010 and 6/2013 in Lilongwe, Malawi. Local first-line treatment included bleomycin and vincristine plus nevirapine-based highly active anti-retroviral therapy (HAART). Median age was 8.6 years (range 1.7-17.9); there were 35 females (50%). Most common sites of presentation were: lymph node (74%), skin (59%), subcutaneous nodules (33%), oral (27%), woody edema (24%), and visceral (16%). Eighteen (26%) presented with lymphadenopathy only. Severe CD4 suppression occurred in 28%. At time of KS diagnosis, 49% were already on HAART. Overall, 28% presented with a platelet count \u3c 100 x 109/L and 37% with hemoglobin \u3c 8 g/dL. The 2-year event-free (EFS) and overall survival (OS) were 46% and 58% respectively (median follow-up 29 months, range 15-50). Multivariable analysis of risk of death and failure to achieve EFS demonstrated that visceral disease (odds ratios [OR] 19.08 and 11.61, 95% CI 2.22-163.90 and 1.60-83.95 respectively) and presenting with more than 20 skin/oral lesions (OR 9.57 and 22.90, 95% CI 1.01-90.99 and 1.00-524.13 respectively) were independent risk factors for both. Woody edema was associated with failure to achieve EFS (OR 7.80, 95% CI 1.84-33.08) but not death. Univariable analysis revealed that lymph node involvement was favorable for EFS (OR 0.28, 95% CI 0.08-0.99), while T1 TIS staging criteria, presence of cytopenias, and severe immune suppression were not associated with increased mortality. Long-term complete remission is achievable in pediatric KS, however outcomes vary according to clinical presentation. Based on clinical heterogeneity, treatment according to risk-stratification is necessary to improve overall outcomes
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