Entropy, complexity and disequilibrium in compact stars

We used the statistical measurements of information entropy, disequilibrium and complexity to infer a hierarchy of equations of state for two types of compact stars from the broad class of neutron stars, namely, with hadronic composition and with strange quark composition. Our results show that, since order costs energy. Nature would favor the exotic strange stars even though the question of how to form the strange stars cannot be answered within this approach. (C) 2012 Elsevier B.V. All rights reserved.

Minimal Landau background gauge on the lattice

We present the first numerical implementation of the minimal Landau background gauge for Yang-Mills theory on the lattice. Our approach is a simple generalization of the usual minimal Landau gauge and is formulated for the general SU(N) gauge group. We also report on preliminary tests of the method in the four-dimensional SU(2) case, using different background fields. Our tests show that the convergence of the numerical minimization process is comparable to the case of a null background. The uniqueness of the minimizing functional employed is briefly discussed.

Probing neutralino properties in minimal supergravity with bilinear R-parity violation

Supersymmetric models with bilinear R-parity violation can account for the observed neutrino masses and mixing parameters indicated by neutrino oscillation data. We consider minimal supergravity versions of bilinear R-parity violation where the lightest supersymmetric particle is a neutralino. This is unstable, with a large enough decay length to be detected at the CERN Large Hadron Collider. We analyze the Large Hadron Collider potential to determine the lightest supersymmetric particle properties, such as mass, lifetime and branching ratios, and discuss their relation to neutrino properties.

Mini-Mental State Examination sentence writing among community-dwelling elderly adults in Brazil: text fluency and grammar complexity

Background: In normal aging, the decrease in the syntactic complexity of written production is usually associated with cognitive deficits. This study was aimed to analyze the quality of older adults' textual production indicated by verbal fluency (number of words) and grammatical complexity (number of ideas) in relation to gender, age, schooling, and cognitive status. Methods: From a probabilistic sample of community-dwelling people aged 65 years and above (n = 900), 577 were selected on basis of their responses to the Mini-Mental State Examination (MMSE) sentence writing, which were submitted to content analysis; 323 were excluded as they left the item blank or performed illegible or not meaningful responses. Education adjusted cut-off scores for the MMSE were used to classify the participants as cognitively impaired or unimpaired. Total and subdomain MMSE scores were computed. Results: 40.56% of participants whose answers to the MMSE sentence were excluded from the analyses had cognitive impairment compared to 13.86% among those whose answers were included. The excluded participants were older and less educated. Women and those older than 80 years had the lowest scores in the MMSE. There was no statistically significant relationship between gender, age, schooling, and textual performance. There was a modest but significant correlation between number of words written and the scores in the Language subdomain. Conclusions: Results suggest the strong influence of schooling and age over MMSE sentence performance. Failing to write a sentence may suggest cognitive impairment, yet, instructions for the MMSE sentence, i.e. to produce a simple sentence, may limit its clinical interpretation.

IDM - A New Parallel Methodology to Calculate the Determinant of Matrices of the Order n, with Computational Complexity O(n)

This paper presents a new parallel methodology for calculating the determinant of matrices of the order n, with computational complexity O(n), using the Gauss-Jordan Elimination Method and Chio's Rule as references. We intend to present our step-by-step methodology using clear mathematical language, where we will demonstrate how to calculate the determinant of a matrix of the order n in an analytical format. We will also present a computational model with one sequential algorithm and one parallel algorithm using a pseudo-code.

Impact of pretransplant minimal residual disease after cord blood transplantation for childhood acute lymphoblastic leukemia in remission: an Eurocord, PDWP-EBMT analysis

To address the prognostic value of minimal residual disease (MRD) before unrelated cord blood transplantation (UCBT) in children with acute lymphoblastic leukemia (ALL), we analyzed 170 ALL children transplanted in complete remission (CR) after myeloablative conditioning regimen. In all, 72 (43%) were in first CR (CR1), 77 (45%) in second CR (CR2) and 21 (12%) in third CR (CR3). The median interval from MRD quantification to UCBT was 18 days. All patients received single-unit UCBT. Median follow-up was 4 years. Cumulative incidence (CI) of day-60 neutrophil engraftment was 85%. CI of 4 years relapse was 30%, incidence being lower in patients with negative MRD before UCBT (hazard ratio (HR) = 0.4, P = 0.01) and for those transplanted in CR1 and CR2 (HR = 0.3, P = 0.002). Probability of 4 years leukemia-free survival (LFS) was 44%, (56, 44 and 14% for patients transplanted in CR1, CR2 and CR3, respectively (P = 0.0001)). Patients with negative MRD before UCBT had better LFS after UCBT compared with those with positive MRD (54% vs 29%; HR = 2, P = 0.003). MRD assessment before UCBT for children with ALL in remission allows identifying patients at higher risk of relapse after transplantation. Approaches that may decrease relapse incidence in children given UCBT with positive MRD should be investigated to improve final outcomes. Leukemia (2012) 26, 2455-2461; doi:10.1038/leu.2012.123

Minimal alterations on the enamel surface by micro-abrasion: in vitro roughness and wear assessments

Objective: To evaluate the in vitro changes on the enamel surface after a micro-abrasion treatment promoted by different products. Material and Methods: Fifty (50) fragments of bovine enamel (15 mm × 5 mm) were randomly assigned to five groups (n=10) according to the product utilized: G1 (control)= silicone polisher (TDV), G2= 37% phosphoric acid (3M/ESPE) + pumice stone (SS White), G3= Micropol (DMC Equipment), G4= Opalustre (Ultradent) and G5= Whiteness RM (FGM Dental Products). Roughness and wear were the responsible variables used to analyze these surfaces in four stages: baseline, 60 s and 120 s after the micro-abrasion and after polishing, using a Hommel Tester T1000 device. After the tests, a normal distribution of data was verified, with repeated ANOVA analyses (p?0.05) which were used to compare each product in different stages. One-way ANOVA and Tukey tests were applied for individual comparisons between the products in each stage (p?0.05). Results: Means and standard deviations of roughness and wear (µm) after all the promoted stages were: G1=7.26(1.81)/13.16(2.67), G2=2.02(0.62)/37.44(3.33), G3=1.81(0.91)/34.93(6.92), G4=1.92(0.29)/38.42(0.65) and G5=1.98(0.53)/33.45(2.66). At 60 seconds, all products tended to produce less surface roughness with a variable gradual decrease over time. After polishing, there were no statistically significant differences between the groups, except for G1. Independent of the product utilized, the enamel wear occurred after the micro-abrasion. Conclusions: In this in vitro study, enamel micro-abrasion presented itself as a conservative approach, regardless of the type of the paste compound utilized. These products promoted minor roughness alterations and minimal wear. The use of phosphoric acid and pumice stone showed similar results to commercial products for the micro-abrasion with regard to the surface roughness and wear.

Minimal and mild endometriosis negatively impact on pregnancy outcome

Endometriosis, a highly prevalent gynecological disease, can lead to infertility in moderate to severe cases. Whether minimal stages are associated with infertility is still unclear. The purpose of this systematic review is to present studies regarding the association between pregnancy rates and the presence of early stages of endometriosis. Studies regarding infertility, minimal (stage I, American Society of Reproductive Medicine [ASRM]) and mild (stage II, ASRM) endometriosis were identified by searching on the MEDLINE database from 1985 to September 2011 using the following MESH terms: endometriosis; infertility; minimal; mild endometriosis; pregnancy rate. 1188 articles published between January of 1985 and November of 2011 were retrieved; based on their titles, 1038 citations were excluded. Finally, after inclusion and exclusion criteria, 16 articles were selected to be part of this systematic review. Several reasons have been discussed in the literature to explain the impact of minimal endometriosis on fertility outcome, such as: ovulatory dysfunction, impaired folliculogenesis, defective implantation, decrease embryo quality, abnormal immunological peritoneal environment, and luteal phase problems. Despite the controversy involving the topic, the largest randomized control trial, published by Marcoux et al. in 1997 found a statistically different pregnancy rate after resection of superficial endometrial lesions. Earlier stages of endometriosis play a critical role in infertility, and most likely negatively impact pregnancy outcomes. Further studies into stage I endometriosis, especially randomized controlled trials, still need to be conducted.

The complexity of narrative interferes in the use of conjunctions in children with specific language impairment

PURPOSE: To verify the use of conjunctions in narratives, and to investigate the influence of stimuli's complexity over the type of conjunctions used by children with specific language impairment (SLI) and children with typical language development. METHODS: Participants were 40 children (20 with typical language development and 20 with SLI) with ages between 7 and 10 years, paired by age range. Fifteen stories with increasing of complexity were used to obtain the narratives; stories were classified into mechanical, behavioral and intentional, and each of them was represented by four scenes. Narratives were analyzed according to occurrence and classification of conjunctions. RESULTS: Both groups used more coordinative than subordinate conjunctions, with significant decrease in the use of conjunctions in the discourse of SLI children. The use of conjunctions varied according to the type of narrative: for coordinative conjunctions, both groups differed only between intentional and behavioral narratives, with higher occurrence in behavioral ones; for subordinate conjunctions, typically developing children's performance did not show differences between narratives, while SLI children presented fewer occurrences in intentional narratives, which was different from other narratives. CONCLUSION: Both groups used more coordinative than subordinate conjunctions; however, typically developing children presented more conjunctions than SLI children. The production of children with SLI was influenced by stimulus, since more complex narratives has less use of subordinate conjunctions.

Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks

Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provade a very Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that interferences can be performed in time linear in the number of nodes if there is a single observed node. Because our proof is construtive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynominal-time algorithm for SQPn. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.

Role of M2 muscarinic receptor in the airway response to methacholine of mice selected for minimal or maximal acute inflammatory response

Airway smooth muscle constriction induced by cholinergic agonists such as methacholine (MCh), which is typically increased in asthmatic patients, is regulated mainly by muscle muscarinic M3 receptors and negatively by vagal muscarinic M2 receptors. Here we evaluated basal (intrinsic) and allergen-induced (extrinsic) airway responses to MCh. We used two mouse lines selected to respond maximally (AIRmax) or minimally (AIRmin) to innate inflammatory stimuli. We found that in basal condition AIRmin mice responded more vigorously to MCh than AIRmax. Treatment with a specific M2 antagonist increased airway response of AIRmax but not of AIRmin mice. The expression of M2 receptors in the lung was significantly lower in AIRmin compared to AIRmax animals. AIRmax mice developed a more intense allergic inflammation than AIRmin, and both allergic mouse lines increased airway responses to MCh. However, gallamine treatment of allergic groups did not affect the responses to MCh. Our results confirm that low or dysfunctional M2 receptor activity is associated with increased airway responsiveness to MCh and that this trait was inherited during the selective breeding of AIRmin mice and was acquired by AIRmax mice during allergic lung inflammation

CID: an efficient complexity-invariant distance for time series

The ubiquity of time series data across almost all human endeavors has produced a great interest in time series data mining in the last decade. While dozens of classification algorithms have been applied to time series, recent empirical evidence strongly suggests that simple nearest neighbor classification is exceptionally difficult to beat. The choice of distance measure used by the nearest neighbor algorithm is important, and depends on the invariances required by the domain. For example, motion capture data typically requires invariance to warping, and cardiology data requires invariance to the baseline (the mean value). Similarly, recent work suggests that for time series clustering, the choice of clustering algorithm is much less important than the choice of distance measure used.In this work we make a somewhat surprising claim. There is an invariance that the community seems to have missed, complexity invariance. Intuitively, the problem is that in many domains the different classes may have different complexities, and pairs of complex objects, even those which subjectively may seem very similar to the human eye, tend to be further apart under current distance measures than pairs of simple objects. This fact introduces errors in nearest neighbor classification, where some complex objects may be incorrectly assigned to a simpler class. Similarly, for clustering this effect can introduce errors by “suggesting” to the clustering algorithm that subjectively similar, but complex objects belong in a sparser and larger diameter cluster than is truly warranted.We introduce the first complexity-invariant distance measure for time series, and show that it generally produces significant improvements in classification and clustering accuracy. We further show that this improvement does not compromise efficiency, since we can lower bound the measure and use a modification of triangular inequality, thus making use of most existing indexing and data mining algorithms. We evaluate our ideas with the largest and most comprehensive set of time series mining experiments ever attempted in a single work, and show that complexity-invariant distance measures can produce improvements in classification and clustering in the vast majority of cases.