917 resultados para Directed Acyclic Graph
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The Sznajd model is a sociophysics model that is used to model opinion propagation and consensus formation in societies. Its main feature is that its rules favor bigger groups of agreeing people. In a previous work, we generalized the bounded confidence rule in order to model biases and prejudices in discrete opinion models. In that work, we applied this modification to the Sznajd model and presented some preliminary results. The present work extends what we did in that paper. We present results linking many of the properties of the mean-field fixed points, with only a few qualitative aspects of the confidence rule (the biases and prejudices modeled), finding an interesting connection with graph theory problems. More precisely, we link the existence of fixed points with the notion of strongly connected graphs and the stability of fixed points with the problem of finding the maximal independent sets of a graph. We state these results and present comparisons between the mean field and simulations in Barabasi-Albert networks, followed by the main mathematical ideas and appendices with the rigorous proofs of our claims and some graph theory concepts, together with examples. We also show that there is no qualitative difference in the mean-field results if we require that a group of size q > 2, instead of a pair, of agreeing agents be formed before they attempt to convince other sites (for the mean field, this would coincide with the q-voter model).
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Proposed is a symbol-based decision-directed algorithm for blind equalisation of quadrature amplitude modulation (QAM) signals using a decision feedback scheme. Independently of QAM order, it presents: (i) an error equal to zero when the equaliser output coincides with the transmitted signal; (ii) simultaneous recovery of the modulus and phase of the signal; (iii) a misadjustment close to that of the normalised least-mean squares algorithm; (iv) fast convergence; and (v) the avoidance of degenerative solutions. Additionally, its stability is ensured when the step-size is properly chosen.
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This paper reports results for directed flow v(1) and elliptic flow v(2) of charged particles in Cu + Cu collisions at root s(NN) = 22.4 GeV at the Relativistic Heavy Ion Collider. The measurements are for the 0-60% most central collisions, using charged particles observed in the STAR detector. Our measurements extend to 22.4-GeV Cu + Cu collisions the prior observation that v1 is independent of the system size at 62.4 and 200 GeV and also extend the scaling of v(1) with eta/y(beam) to this system. The measured v(2)(p(T)) in Cu + Cu collisions is similar for root s(NN) throughout the range 22.4 to 200 GeV. We also report a comparison with results from transport model (ultrarelativistic quantum molecular dynamics and multiphase transport model) calculations. The model results do not agree quantitatively with the measured v(1)(eta), v(2)(p(T)), and v(2)(eta).
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A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.
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In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.
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Objective To evaluate the changes in tissue perfusion parameters in dogs with severe sepsis/septic shock in response to goal-directed hemodynamic optimization in the ICU and their relation to outcome. Design Prospective observational study. Setting ICU of a veterinary university medical center. Animals Thirty dogs with severe sepsis or septic shock caused by pyometra who underwent surgery and were admitted to the ICU. Measurements and Main Results Severe sepsis was defined as the presence of sepsis and sepsis-induced dysfunction of one or more organs. Septic shock was defined as the presence of severe sepsis plus hypotension not reversed with fluid resuscitation. After the presumptive diagnosis of sepsis secondary to pyometra, blood samples were collected and clinical findings were recorded. Volume resuscitation with 0.9% saline solution and antimicrobial therapy were initiated. Following abdominal ultrasonography and confirmation of increased uterine volume, dogs underwent corrective surgery. After surgery, the animals were admitted to the ICU, where resuscitation was guided by the clinical parameters, central venous oxygen saturation (ScvO2), lactate, and base deficit. Between survivors and nonsurvivors it was observed that the ScvO2, lactate, and base deficit on ICU admission were each related independently to death (P = 0.001, P = 0.030, and P < 0.001, respectively). ScvO2 and base deficit were found to be the best discriminators between survivors and nonsurvivors as assessed via receiver operator characteristic curve analysis. Conclusion Our study suggests that ScvO2 and base deficit are useful in predicting the prognosis of dogs with severe sepsis and septic shock; animals with a higher ScvO2 and lower base deficit at admission to the ICU have a lower probability of death.
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STAR's measurements of directed flow (v(1)) around midrapidity for pi(+/-), K-+/-, K-S(0), p, and (p) over bar in Au + Au collisions at root s(NN) = 200 GeV are presented. A negative v(1) (y) slope is observed for most of produced particles (pi(+/-), K-+/-, K-S(0), p, and (p) over bar). In 5%-30% central collisions, a sizable difference is present between the v(1)(y) slope of protons and antiprotons, with the former being consistent with zero within errors. The v(1) excitation function is presented. Comparisons to model calculations (RQMD, UrQMD, AMPT, QGSM with parton recombination, and a hydrodynamics model with a tilted source) are made. For those models which have calculations of v(1) for both pions and protons, none of them can describe v(1()y) forpions and protons simultaneously. The hydrodynamics model with a tilted source as currently implemented cannot explain the centrality dependence of the difference between the v(1)(y) slopes of protons and antiprotons.
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Suramin is a polysulphonated naphthylurea with inhibitory activity against the human secreted group IIA phospholipase A(2) (hsPLA2GIIA), and we have investigated suramin binding to recombinant hsPLA2GIIA using site-directed mutagenesis and molecular dynamics (MD) simulations. The changes in suramin binding affinity of 13 cationic residue mutants of the hsPLA2GIIA was strongly correlated with alterations in the inhibition of membrane damaging activity of the protein. Suramin binding to hsPLA2GIIA was also studied by MD simulations, which demonstrated that altered intermolecular potential energy of the suramin/mutant complexes was a reliable indicator of affinity change. Although residues in the C-terminal region play a major role in the stabilization of the hsPLA2GIIA/suramin complex, attractive and repulsive hydrophobic and electrostatic interactions with residues throughout the protein together with the adoption of a bent suramin conformation, all contribute to the stability of the complex. Analysis of the h5PLA2GIIA/suramin interactions allows the prediction of the properties of suramin analogues with improved binding and higher affinities which may be candidates for novel phospholipase A(2) inhibitors. (C) 2012 Elsevier Inc. All rights reserved.
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Abstract Introduction Several studies have shown that maximizing stroke volume (or increasing it until a plateau is reached) by volume loading during high-risk surgery may improve post-operative outcome. This goal could be achieved simply by minimizing the variation in arterial pulse pressure (ΔPP) induced by mechanical ventilation. We tested this hypothesis in a prospective, randomized, single-centre study. The primary endpoint was the length of postoperative stay in hospital. Methods Thirty-three patients undergoing high-risk surgery were randomized either to a control group (group C, n = 16) or to an intervention group (group I, n = 17). In group I, ΔPP was continuously monitored during surgery by a multiparameter bedside monitor and minimized to 10% or less by volume loading. Results Both groups were comparable in terms of demographic data, American Society of Anesthesiology score, type, and duration of surgery. During surgery, group I received more fluid than group C (4,618 ± 1,557 versus 1,694 ± 705 ml (mean ± SD), P < 0.0001), and ΔPP decreased from 22 ± 75 to 9 ± 1% (P < 0.05) in group I. The median duration of postoperative stay in hospital (7 versus 17 days, P < 0.01) was lower in group I than in group C. The number of postoperative complications per patient (1.4 ± 2.1 versus 3.9 ± 2.8, P < 0.05), as well as the median duration of mechanical ventilation (1 versus 5 days, P < 0.05) and stay in the intensive care unit (3 versus 9 days, P < 0.01) was also lower in group I. Conclusion Monitoring and minimizing ΔPP by volume loading during high-risk surgery improves postoperative outcome and decreases the length of stay in hospital. Trial registration NCT00479011
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[EN]Many different complex systems depend on a large number n of mutually independent random Boolean variables. The most useful representation for these systems –usually called complex stochastic Boolean systems (CSBSs)– is the intrinsic order graph. This is a directed graph on 2n vertices, corresponding to the 2n binary n-tuples (u1, . . . , un) ∈ {0, 1} n of 0s and 1s. In this paper, different duality properties of the intrinsic order graph are rigorously analyzed in detail. The results can be applied to many CSBSs arising from any scientific, technical or social area…
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[EN] This paper deals with the study of some new properties of the intrinsic order graph. The intrinsic order graph is the natural graphical representation of a complex stochastic Boolean system (CSBS). A CSBS is a system depending on an arbitrarily large number n of mutually independent random Boolean variables. The intrinsic order graph displays its 2n vertices (associated to the CSBS) from top to bottom, in decreasing order of their occurrence probabilities. New relations between the intrinsic ordering and the Hamming weight (i.e., the number of 1-bits in a binary n-tuple) are derived. Further, the distribution of the weights of the 2n nodes in the intrinsic order graph is analyzed…
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[EN]A complex stochastic Boolean system (CSBS) is a system depending on an arbitrary number n of stochastic Boolean variables. The analysis of CSBSs is mainly based on the intrinsic order: a partial order relation defined on the set f0; 1gn of binary n-tuples. The usual graphical representation for a CSBS is the intrinsic order graph: the Hasse diagram of the intrinsic order. In this paper, some new properties of the intrinsic order graph are studied. Particularly, the set and the number of its edges, the degree and neighbors of each vertex, as well as typical properties, such as the symmetry and fractal structure of this graph, are analyzed…
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Alzheimer's disease (AD) and cancer represent two of the main causes of death worldwide. They are complex multifactorial diseases and several biochemical targets have been recognized to play a fundamental role in their development. Basing on their complex nature, a promising therapeutical approach could be represented by the so-called "Multi-Target-Directed Ligand" approach. This new strategy is based on the assumption that a single molecule could hit several targets responsible for the onset and/or progression of the pathology. In particular in AD, most currently prescribed drugs aim to increase the level of acetylcholine in the brain by inhibiting the enzyme acetylcholinesterase (AChE). However, clinical experience shows that AChE inhibition is a palliative treatment, and the simple modulation of a single target does not address AD aetiology. Research into newer and more potent anti-AD agents is thus focused on compounds whose properties go beyond AChE inhibition (such as inhibition of the enzyme β-secretase and inhibition of the aggregation of beta-amyloid). Therefore, the MTDL strategy seems a more appropriate approach for addressing the complexity of AD and may provide new drugs for tackling its multifactorial nature. In this thesis, it is described the design of new MTDLs able to tackle the multifactorial nature of AD. Such new MTDLs designed are less flexible analogues of Caproctamine, one of the first MTDL owing biological properties useful for the AD treatment. These new compounds are able to inhibit the enzymes AChE, beta-secretase and to inhibit both AChE-induced and self-induced beta-amyloid aggregation. In particular, the most potent compound of the series is able to inhibit AChE in subnanomolar range, to inhibit β-secretase in micromolar concentration and to inhibit both AChE-induced and self-induced beta-amyloid aggregation in micromolar concentration. Cancer, as AD, is a very complex pathology and many different therapeutical approaches are currently use for the treatment of such pathology. However, due to its multifactorial nature the MTDL approach could be, in principle, apply also to this pathology. Aim of this thesis has been the development of new molecules owing different structural motifs able to simultaneously interact with some of the multitude of targets responsible for the pathology. The designed compounds displayed cytotoxic activity in different cancer cell lines. In particular, the most potent compounds of the series have been further evaluated and they were able to bind DNA resulting 100-fold more potent than the reference compound Mitonafide. Furthermore, these compounds were able to trigger apoptosis through caspases activation and to inhibit PIN1 (preliminary result). This last protein is a very promising target because it is overexpressed in many human cancers, it functions as critical catalyst for multiple oncogenic pathways and in several cancer cell lines depletion of PIN1 determines arrest of mitosis followed by apoptosis induction. In conclusion, this study may represent a promising starting pint for the development of new MTDLs hopefully useful for cancer and AD treatment.
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The MTDL (multi-target-directed ligand) design strategy is used to develop single chemical entities that are able to simultaneously modulate multiple targets. The development of such compounds might disclose new avenues for the treatment of a variety of pathologies (e.g. cancer, AIDS, neurodegenerative diseases), for which an effective cure is urgently needed. This strategy has been successfully applied to Alzheimer’s disease (AD) due to its multifactorial nature, involving cholinergic dysfunction, amyloid aggregation, and oxidative stress. Despite many biological entities have been recognized as possible AD-relevant, only four achetylcholinesterase inhibitors (AChEIs) and one NMDA receptor antagonist are used in therapy. Unfortunately, such compounds are not disease-modifying agents behaving only as cognition enhancers. Therefore, MTDL strategy is emerging as a powerful drug design paradigm: pharmacophores of different drugs are combined in the same structure to afford hybrid molecules. In principle, each pharmacophore of these new drugs should retain the ability to interact with its specific site(s) on the target and, consequently, to produce specific pharmacological responses that, taken together, should slow or block the neurodegenerative process. To this end, the design and synthesis of several examples of MTDLs for combating neurodegenerative diseases have been published. This seems to be the more appropriate approach for addressing the complexity of AD and may provide new drugs for tackling the multifactorial nature of AD, and hopefully stopping its progression. According to this emerging strategy, in this work thesis different classes of new molecular structures, based on the MTDL approach, have been developed. Moreover, curcumin and its constrained analogs have currently received remarkable interest as they have a unique conjugated structure which shows a pleiotropic profile that we considered a suitable framework in developing MTDLs. In fact, beside the well-known direct antioxidant activity, curcumin displays a wide range of biological properties including anti-inflammatory and anti-amyloidogenic activities and an indirect antioxidant action through activation of the cytoprotective enzyme heme oxygenase (HO-1). Thus, since many lines of evidence suggest that oxidative stess and mitochondria impairment have a cental role in age-related neurodegenerative diseases such as AD, we designed mitochondria-targeted antioxidants by connecting curcumin analogs to different polyamine chains that, with the aid of electrostatic force, might drive the selected antioxidant moiety into mitochondria.
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Präsentiert wird ein vollständiger, exakter und effizienter Algorithmus zur Berechnung des Nachbarschaftsgraphen eines Arrangements von Quadriken (Algebraische Flächen vom Grad 2). Dies ist ein wichtiger Schritt auf dem Weg zur Berechnung des vollen 3D Arrangements. Dabei greifen wir auf eine bereits existierende Implementierung zur Berechnung der exakten Parametrisierung der Schnittkurve von zwei Quadriken zurück. Somit ist es möglich, die exakten Parameterwerte der Schnittpunkte zu bestimmen, diese entlang der Kurven zu sortieren und den Nachbarschaftsgraphen zu berechnen. Wir bezeichnen unsere Implementierung als vollständig, da sie auch die Behandlung aller Sonderfälle wie singulärer oder tangentialer Schnittpunkte einschließt. Sie ist exakt, da immer das mathematisch korrekte Ergebnis berechnet wird. Und schließlich bezeichnen wir unsere Implementierung als effizient, da sie im Vergleich mit dem einzigen bisher implementierten Ansatz gut abschneidet. Implementiert wurde unser Ansatz im Rahmen des Projektes EXACUS. Das zentrale Ziel von EXACUS ist es, einen Prototypen eines zuverlässigen und leistungsfähigen CAD Geometriekerns zu entwickeln. Obwohl wir das Design unserer Bibliothek als prototypisch bezeichnen, legen wir dennoch größten Wert auf Vollständigkeit, Exaktheit, Effizienz, Dokumentation und Wiederverwendbarkeit. Über den eigentlich Beitrag zu EXACUS hinaus, hatte der hier vorgestellte Ansatz durch seine besonderen Anforderungen auch wesentlichen Einfluss auf grundlegende Teile von EXACUS. Im Besonderen hat diese Arbeit zur generischen Unterstützung der Zahlentypen und der Verwendung modularer Methoden innerhalb von EXACUS beigetragen. Im Rahmen der derzeitigen Integration von EXACUS in CGAL wurden diese Teile bereits erfolgreich in ausgereifte CGAL Pakete weiterentwickelt.