Charge-symmetry breaking, rho-omega mixing, and the quark propagator

The momentum dependence of the ρ0-ω mixing contribution to charge-symmetry breaking (CSB) in the nucleon-nucleon interaction is compared in a variety of models. We focus in particular on the role that the structure of the quark propagator plays in the predicted behaviour of the ρ0-ω mixing amplitude. We present new results for a confining (entire) quark propagator and for typical propagators arising from explicit numerical solutions of quark Dyson-Schwinger equations We compare these to hadronic and free quark calculations The implications for our current understanding of CSB experiments is discussed.

Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning

Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert). Many conventional active learning algorithms focus on refining the decision boundary, at the expense of exploring new regions that the current hypothesis misclassifies. We propose a new active learning algorithm that balances such exploration with refining of the decision boundary by dynamically adjusting the probability to explore at each step. Our experimental results demonstrate improved performance on data sets that require extensive exploration while remaining competitive on data sets that do not. Our algorithm also shows significant tolerance of noise.

An algorithm for the strip packing problem using collision free region and exact fitting placement

The irregular shape packing problem is approached. The container has a fixed width and an open dimension to be minimized. The proposed algorithm constructively creates the solution using an ordered list of items and a placement heuristic. Simulated annealing is the adopted metaheuristic to solve the optimization problem. A two-level algorithm is used to minimize the open dimension of the container. To ensure feasible layouts, the concept of collision free region is used. A collision free region represents all possible translations for an item to be placed and may be degenerated. For a moving item, the proposed placement heuristic detects the presence of exact fits (when the item is fully constrained by its surroundings) and exact slides (when the item position is constrained in all but one direction). The relevance of these positions is analyzed and a new placement heuristic is proposed. Computational comparisons on benchmark problems show that the proposed algorithm generated highly competitive solutions. Moreover, our algorithm updated some best known results. (C) 2012 Elsevier Ltd. All rights reserved.

A comparison of CA125, HE4, risk ovarian malignancy algorithm (ROMA), and risk malignancy index (RMI) for the classification of ovarian masses

OBJECTIVE: Differentiation between benign and malignant ovarian neoplasms is essential for creating a system for patient referrals. Therefore, the contributions of the tumor markers CA125 and human epididymis protein 4 (HE4) as well as the risk ovarian malignancy algorithm (ROMA) and risk malignancy index (RMI) values were considered individually and in combination to evaluate their utility for establishing this type of patient referral system. METHODS: Patients who had been diagnosed with ovarian masses through imaging analyses (n = 128) were assessed for their expression of the tumor markers CA125 and HE4. The ROMA and RMI values were also determined. The sensitivity and specificity of each parameter were calculated using receiver operating characteristic curves according to the area under the curve (AUC) for each method. RESULTS: The sensitivities associated with the ability of CA125, HE4, ROMA, or RMI to distinguish between malignant versus benign ovarian masses were 70.4%, 79.6%, 74.1%, and 63%, respectively. Among carcinomas, the sensitivities of CA125, HE4, ROMA (pre-and post-menopausal), and RMI were 93.5%, 87.1%, 80%, 95.2%, and 87.1%, respectively. The most accurate numerical values were obtained with RMI, although the four parameters were shown to be statistically equivalent. CONCLUSION: There were no differences in accuracy between CA125, HE4, ROMA, and RMI for differentiating between types of ovarian masses. RMI had the lowest sensitivity but was the most numerically accurate method. HE4 demonstrated the best overall sensitivity for the evaluation of malignant ovarian tumors and the differential diagnosis of endometriosis. All of the parameters demonstrated increased sensitivity when tumors with low malignancy potential were considered low-risk, which may be used as an acceptable assessment method for referring patients to reference centers.

rho(0) photoproduction in AuAu collisions at root s(NN)=62.4 GeV measured with the STAR detector

Vector mesons may be photoproduced in relativistic heavy-ion collisions when a virtual photon emitted by one nucleus scatters from the other nucleus, emerging as a vector meson. The STAR Collaboration has previously presented measurements of coherent rho(0) photoproduction at center of mass energies of 130 GeV and 200 GeV in AuAu collisions. Here, we present a measurement of the cross section at 62.4 GeV; we find that the cross section for coherent rho(0) photoproduction with nuclear breakup is 10.5 +/- 1.5 +/- 1.6mb at 62.4 GeV. The cross-section ratio between 200 GeV and 62.4 GeV is 4.4 +/- 0.6, less than is predicted by most theoretical models. It is, however, proportionally much larger than the previously observed 15% +/- 55% increase between 130 GeV and 200 GeV.

A direct D-bar reconstruction algorithm for recovering a complex conductivity in 2D

A direct reconstruction algorithm for complex conductivities in W-2,W-infinity(Omega), where Omega is a bounded, simply connected Lipschitz domain in R-2, is presented. The framework is based on the uniqueness proof by Francini (2000 Inverse Problems 6 107-19), but equations relating the Dirichlet-to-Neumann to the scattering transform and the exponentially growing solutions are not present in that work, and are derived here. The algorithm constitutes the first D-bar method for the reconstruction of conductivities and permittivities in two dimensions. Reconstructions of numerically simulated chest phantoms with discontinuities at the organ boundaries are included.

Does videothoracoscopy improve clinical outcomes when implemented as part of a pleural empyema treatment algorithm?

OBJECTIVE: We aimed to evaluate whether the inclusion of videothoracoscopy in a pleural empyema treatment algorithm would change the clinical outcome of such patients. METHODS: This study performed quality-improvement research. We conducted a retrospective review of patients who underwent pleural decortication for pleural empyema at our institution from 2002 to 2008. With the old algorithm (January 2002 to September 2005), open decortication was the procedure of choice, and videothoracoscopy was only performed in certain sporadic mid-stage cases. With the new algorithm (October 2005 to December 2008), videothoracoscopy became the first-line treatment option, whereas open decortication was only performed in patients with a thick pleural peel (>2 cm) observed by chest scan. The patients were divided into an old algorithm (n = 93) and new algorithm (n = 113) group and compared. The main outcome variables assessed included treatment failure (pleural space reintervention or death up to 60 days after medical discharge) and the occurrence of complications. RESULTS: Videothoracoscopy and open decortication were performed in 13 and 80 patients from the old algorithm group and in 81 and 32 patients from the new algorithm group, respectively (p < 0.01). The patients in the new algorithm group were older (41 +/- 1 vs. 46.3 +/- 16.7 years, p=0.014) and had higher Charlson Comorbidity Index scores [0(0-3) vs. 2(0-4), p = 0.032]. The occurrence of treatment failure was similar in both groups (19.35% vs. 24.77%, p= 0.35), although the complication rate was lower in the new algorithm group (48.3% vs. 33.6%, p = 0.04). CONCLUSIONS: The wider use of videothoracoscopy in pleural empyema treatment was associated with fewer complications and unaltered rates of mortality and reoperation even though more severely ill patients were subjected to videothoracoscopic surgery.

Morphological heterogeneity of Paracoccidioides brasiliensis: relevance of the Rho-like GTPase PbCDC42

Paracoccidioides brasiliensis budding pattern and polymorphic growth were previously shown to be closely linked to the expression of PbCDC42 and to influence the pathogenesis of the fungus. In this work we conducted a detailed morphogenetic evaluation of the yeast-forms of 11 different clinical and environmental P. brasiliensis isolates comprising four phylogenetic lineages (S1, PS2, PS3 and Pb01-like), as well as a PbCDC42 knock-down strain. High variations in the shape and size of mother and bud cells of each isolate were observed but we did not find a characteristic morphologic profile for any of the phylogenetic groups. In all isolates studied, the bud size and shape were demonstrated to be highly dependent on the mother cell. Importantly, we found strong correlations between PbCDC42 expression and both the shape of mother and bud cells and the size of the buds in all isolates and the knock-down strain. Our results suggested that PbCDC42 expression can explain approximately 80% of mother and bud cell shape and 19% of bud cell size. This data support PbCDC42 expression level as being a relevant predictor of P. brasiliensis morphology. Altogether, these findings quantitatively describe the polymorphic nature of the P. brasiliensis yeast form and provide additional support for the key role of PbCDC42 expression on yeast cell morphology.

Generating unconstrained two-dimensional non-guillotine cutting patterns by a Recursive Partitioning Algorithm

In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011

Immunohistochemical expression of Rho GTPases in ameloblastomas

Rho GTPases are proteins that regulate cell cycle, shape, polarization, invasion, migration, and apoptosis, which are important characteristics of normal and neoplastic cells. Rho GTPases expression has been reported in normal tooth germ and several pathologies; however, it has not been evaluated in ameloblastomas. The aim of this study was to analyze the expression and distribution of RhoA, RhoB, Rac1, and Cdc42 Rho GTPases in solid and unicystic ameloblastomas. Three-micrometer sections from paraffin- embedded specimens were evaluated by using an avidin- biotin immunohistochemical method with antibodies against the proteins mentioned above. RhoA and RhoB staining was observed in a high number of cells (P < 0.05) and greater intensity in non-polarized ones. Rac1 was not observed, andCdc42 didnot showany statistical differences between the number of non-polarized and basal positive cells (P > 0.05). Upon comparing the studied ameloblastomas, a higher number of positive cells in the unicystic variant was observed than that in the solid one (P < 0,05). The results obtained suggest that theseGTPases could play a role in the ameloblastoma neoplastic epithelial cell phenotype determination (polarized or non-polarized), as well as in variant (solid or unicystic) and subtype (follicular or plexiform) determination. Furthermore, they could participate in solid ameloblastoma invasion mechanisms. J Oral Pathol Med (2012) 41: 400-407

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

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.

Rho-kinase inhibition attenuates airway responsiveness, inflammation, matrix remodeling, and oxidative stress activation induced by chronic inflammation

Possa SS, Charafeddine HT, Righetti RF, da Silva PA, Almeida-Reis R, Saraiva-Romanholo BM, Perini A, Prado CM, Leick-Maldonado EA, Martins MA, Tiberio ID. Rho-kinase inhibition attenuates airway responsiveness, inflammation, matrix remodeling, and oxidative stress activation induced by chronic inflammation. Am J Physiol Lung Cell Mol Physiol 303: L939-L952, 2012. First published September 21, 2012; doi:10.1152/ajplung.00034.2012.-Several studies have demonstrated the importance of Rho-kinase in the modulation of smooth muscle contraction, airway hyperresponsiveness, and inflammation. However, the effects of repeated treatment with a specific inhibitor of this pathway have not been previously investigated. We evaluated the effects of repeated treatment with Y-27632, a highly selective Rho-kinase inhibitor, on airway hyperresponsiveness, oxidative stress activation, extracellular matrix remodeling, eosinophilic inflammation, and cytokine expression in an animal model of chronic airway inflammation. Guinea pigs were subjected to seven ovalbumin or saline exposures. The treatment with Y-27632 (1 mM) started at the fifth inhalation. Seventy-two hours after the seventh inhalation, the animals' pulmonary mechanics were evaluated, and exhaled nitric oxide (E-NO) was collected. The lungs were removed, and histological analysis was performed using morphometry. Treatment with Y-27632 in sensitized animals reduced E-NO concentrations, maximal responses of resistance, elastance of the respiratory system, eosinophil counts, collagen and elastic fiber contents, the numbers of cells positive for IL-2, IL-4, IL-5, IL-13, inducible nitric oxide synthase, matrix metalloproteinase-9, tissue inhibitor of metalloproteinase-1, transforming growth factor-beta, NF-kappa B, IFN-gamma, and 8-iso-prostaglandin F2 alpha contents compared with the untreated group (P < 0.05). We observed positive correlations among the functional responses and inflammation, remodeling, and oxidative stress pathway activation markers evaluated. In conclusion, Rho-kinase pathway activation contributes to the potentiation of the hyperresponsiveness, inflammation, the extracellular matrix remodeling process, and oxidative stress activation. These results suggest that Rho-kinase inhibitors represent potential pharmacological tools for the control of asthma.

Localising and quantifying damage by means of a multi-chromosome genetic algorithm

This paper presents a structural damage detection methodology based on genetic algorithms and dynamic parameters. Three chromosomes are used to codify an individual in the population. The first and second chromosomes locate and quantify damage, respectively. The third permits the self-adaptation of the genetic parameters. The natural frequencies and mode shapes are used to formulate the objective function. A numerical analysis was performed for several truss structures under different damage scenarios. The results have shown that the methodology can reliably identify damage scenarios using noisy measurements and that it results in only a few misidentified elements. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.