124 research outputs found

    Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control

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    This paper presents a branch-and-lift algorithm for solving optimal control problems with smooth nonlinear dynamics and potentially nonconvex objective and constraint functionals to guaranteed global optimality. This algorithm features a direct sequential method and builds upon a generic, spatial branch-and-bound algorithm. A new operation, called lifting, is introduced, which refines the control parameterization via a Gram-Schmidt orthogonalization process, while simultaneously eliminating control subregions that are either infeasible or that provably cannot contain any global optima. Conditions are given under which the image of the control parameterization error in the state space contracts exponentially as the parameterization order is increased, thereby making the lifting operation efficient. A computational technique based on ellipsoidal calculus is also developed that satisfies these conditions. The practical applicability of branch-and-lift is illustrated in a numerical example. © 2013 Springer Science+Business Media New York

    Plantas medicinais de um remascente de Floresta Ombrófila Mista Altomontana, Urupema, Santa Catarina, Brasil

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    CONTEXT: Recent studies have implicated proinflammatory responses in the mechanism of type 1 diabetes (T1D). OBJECTIVE: Our objective was to evaluate the safety and effects of therapy with the anti-inflammatory serum protein alpha1-antitrypsin (AAT) on islet function and innate immunity in recent-onset patients. DESIGN AND SETTING: This was an open-label phase I trial at the Barbara Davis Center for Childhood Diabetes, University of Colorado Denver. PATIENTS: Twelve recently diagnosed subjects with T1D with detectable C-peptides were included in the study. INTERVENTION: Eight consecutive weekly infusions of 80 mg/kg of AAT were given. MAIN OUTCOME MEASURES: PATIENTS were monitored for adverse effects of AAT therapy, C-peptide responses to a mixed-meal tolerance test, and toll-like receptor (TLR)-induced cellular IL-1beta in monocytes and myeloid dendritic cells (mDCs). RESULTS: No adverse effects were detected. AAT led to increased, unchanged, or moderately reduced levels of C-peptide responses compared with baseline in 5 patients. The total content of TLR4-induced cellular IL-1beta in monocytes at 12 months after AAT therapy was 3-fold reduced compared with baseline (P < .05). Furthermore, at baseline, 82% of monocytes produced IL-1beta, but at 12 months after therapy, the level decreased to 42%. Similar reductions were observed using TLR7/8 and TLR3 agonists in monocytes and mDCs. Unexpectedly, the reduction in cellular IL-1beta was observed only 9 and 12 months after treatment but not in untreated diabetics. Improved beta-cell function in the 5 AAT-treated individuals correlated with lower frequencies of monocytes and mDCs producing IL-1beta compared with subjects without improvement of islet function (P < .04 and P < .02, respectively). CONCLUSIONS: We hypothesize that AAT may have a beneficial effect on T1D in recently diagnosed patients that is associated with downmodulation of IL-1beta

    UNICAP: Efficient Decision Support for Academic Resource and Capacity Management

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    Abstract. Growing complexity of the data and processes to be managed, as well as the transition from strict governmental regulation towards autonomy make academic institutions a significant consumer of advanced software solutions. Strategic management requires a comprehensive analysis of large data volumes from heterogeneous sources, often imprecise and incomplete. Our aim is to assist university policy-makers in building strategic action plans in the field of resource distribution and teaching capacity utilization through explicit modeling and testing of diverse development strategies. The proposed decision support system (DSS), called UNICAP (acronym for university&apos;s capacity planning), is aimed at optimizing the academic decision making by allowing simulation and evaluation of strategic plans. We conclude by presenting a case study, carried by the planning experts of our university who used UNICAP filled with &quot;real &quot; university’s data.
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