Describing fatigue crack growth and load ratio effects in Al 2524 T3 alloy with an enhanced exponential model

The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range Delta K. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub-critical crack propagation behavior of Al 2524-T3 alloy, commonly used in aircraft engineering applications. It was demonstrated that besides adequately correlating the load ratio effects, the exponential model also accounts for the slight deviations from linearity shown by the experimental curves. A comparison with Elber, Kujawski and "Unified Approach" models allowed for verifying the better performance, when confronted to the other tested models, presented by the exponential model. (C) 2012 Elsevier Ltd. All rights reserved.

QUASI-TOPOLOGICAL QUANTUM FIELD THEORIES AND Z(2) LATTICE GAUGE THEORIES

We consider a two-parameter family of Z(2) gauge theories on a lattice discretization T(M) of a three-manifold M and its relation to topological field theories. Familiar models such as the spin-gauge model are curves on a parameter space Gamma. We show that there is a region Gamma(0) subset of Gamma where the partition function and the expectation value h < W-R(gamma)> i of the Wilson loop can be exactly computed. Depending on the point of Gamma(0), the model behaves as topological or quasi-topological. The partition function is, up to a scaling factor, a topological number of M. The Wilson loop on the other hand, does not depend on the topology of gamma. However, for a subset of Gamma(0), < W-R(gamma)> depends on the size of gamma and follows a discrete version of an area law. At the zero temperature limit, the spin-gauge model approaches the topological and the quasi-topological regions depending on the sign of the coupling constant.

Systematics of the Oswaldoi Complex (Anopheles, Nyssorhynchus) in South America

Abstract Background Effective malaria control relies on accurate identification of those Anopheles mosquitoes responsible for the transmission of Plasmodium parasites. Anopheles oswaldoi s.l. has been incriminated as a malaria vector in Colombia and some localities in Brazil, but not ubiquitously throughout its Neotropical range. This evidence together with variable morphological characters and genetic differences supports that An. oswaldoi s.l. compromises a species complex. The recent fully integrated redescription of An. oswaldoi s.s. provides a solid taxonomic foundation from which to molecularly determine other members of the complex. Methods DNA sequences of the Second Internal Transcribed Spacer (ITS2 - rDNA) (n = 192) and the barcoding region of the Cytochrome Oxidase I gene (COI - mtDNA) (n = 110) were generated from 255 specimens of An. oswaldoi s.l. from 33 localities: Brazil (8 localities, including the lectotype series of An. oswaldoi), Ecuador (4), Colombia (17), Trinidad and Tobago (1), and Peru (3). COI sequences were analyzed employing the Kimura-two-parameter model (K2P), Bayesian analysis (MrBayes), Mixed Yule-Coalescent model (MYC, for delimitation of clusters) and TCS genealogies. Results Separate and combined analysis of the COI and ITS2 data sets unequivocally supported four separate species: two previously determined (An. oswaldoi s.s. and An. oswaldoi B) and two newly designated species in the Oswaldoi Complex (An. oswaldoi A and An. sp. nr. konderi). The COI intra- and inter-specific genetic distances for the four taxa were non-overlapping, averaging 0.012 (0.007 to 0.020) and 0.052 (0.038 to 0.064), respectively. The concurring four clusters delineated by MrBayes and MYC, and four independent TCS networks, strongly confirmed their separate species status. In addition, An. konderi of Sallum should be regarded as unique with respect to the above. Despite initially being included as an outgroup taxon, this species falls well within the examined taxa, suggesting a combined analysis of these taxa would be most appropriate. Conclusions: Through novel data and retrospective comparison of available COI and ITS2 DNA sequences, evidence is shown to support the separate species status of An. oswaldoi s.s., An. oswaldoi A and An. oswaldoi B, and at least two species in the closely related An. konderi complex (An. sp. nr. konderi, An. konderi of Sallum). Although An. oswaldoi s.s. has never been implicated in malaria transmission, An. oswaldoi B is a confirmed vector and the new species An. oswaldoi A and An. sp. nr. konderi are circumstantially implicated, most likely acting as secondary vectors.

Molecular evolution of primate immunodeficiency viruses and hepatitis delta virus

Primate immunodeficiency viruses, or lentiviruses (HIV-1, HIV-2, and SIV), and hepatitis delta virus (HDV) are RNA viruses characterized by rapid evolution. Infection by primate immunodeficiency viruses usually results in the development of acquired immunodeficiency syndrome (AIDS) in humans and AIDS-like illnesses in Asian macaques. Similarly, hepatitis delta virus infection causes hepatitis and liver cancer in humans. These viruses are heterogeneous within an infected patient and among individuals. Substitution rates in the virus genomes are high and vary in different lineages and among sites. Methods of phylogenetic analysis were applied to study the evolution of primate lentiviruses and the hepatitis delta virus. The following results have been obtained: (1) The substitution rate varies among sites of primate lentivirus genes according to the two parameter gamma distribution, with the shape parameter $\alpha$ being close to 1. (2) Primate immunodeficiency viruses fall into species-specific lineages. Therefore, viral transmissions across primate species are not as frequent as suggested by previous authors. (3) Primate lentiviruses have acquired or lost their pathogenicity several times in the course of evolution. (4) Evidence was provided for multiple infections of a North American patient by distinct HIV-1 strains of the B subtype. (5) Computer simulations indicate that the probability of committing an error in testing HIV transmission depends on the number of virus sequences and their length, the divergence times among sequences, and the model of nucleotide substitution. (6) For future investigations of HIV-1 transmissions, using longer virus sequences and avoiding the use of distant outgroups is recommended. (7) Hepatitis delta virus strains are usually related according to the geographic region of isolation. (8) Evolution of HDV is characterized by the rate of synonymous substitution being lower than the nonsynonymous substitution rate and the rate of evolution of the noncoding region. (9) There is a strong preference for G and C nucleotides at the third codon positions of the HDV coding region. ^

Modeling the formation and aging of secondary organic aerosols during CalNex 2010

Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle- and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA that formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model–measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate-volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model–measurement agreement for mass concentration. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the recent parameterizations overpredict urban SOA formation at long photochemical ages (3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35 %, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71(+-3) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μgm-3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies and which is higher on weekends. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr-1 of SOA globally, or 17% of global SOA, one third of which is likely to be non-fossil.

Generalised integrable λ- and η-deformations and their relation

We construct two-parameter families of integrable λ -deformations of two-dimensional field theories. These interpolate between a CFT (a WZW/gauged WZW model) and the non-Abelian T-dual of a principal chiral model on a group/symmetric coset space. In examples based on the SU(2) WZW model and the SU(2)/U(1) exact coset CFT, we show that these deformations are related to bi-Yang–Baxter generalisations of η-deformations via Poisson–Lie T-duality and analytic continuation. We illustrate the quantum behaviour of our models under RG flow. As a byproduct we demonstrate that the bi-Yang–Baxter σ-model for a general group is one-loop renormalisable.

The calculation of Afρ and mass loss rate for comets

Ab initio calculations of Afρ are presented using Mie scattering theory and a Direct Simulation Monte Carlo (DSMC) dust outflow model in support of the Rosetta mission and its target 67P/Churyumov-Gerasimenko (CG). These calculations are performed for particle sizes ranging from 0.010 μm to 1.0 cm. The present status of our knowledge of various differential particle size distributions is reviewed and a variety of particle size distributions is used to explore their effect on Afρ , and the dust mass production View the MathML sourcem˙. A new simple two parameter particle size distribution that curtails the effect of particles below 1 μm is developed. The contributions of all particle sizes are summed to get a resulting overall Afρ. The resultant Afρ could not easily be predicted a priori and turned out to be considerably more constraining regarding the mass loss rate than expected. It is found that a proper calculation of Afρ combined with a good Afρ measurement can constrain the dust/gas ratio in the coma of comets as well as other methods presently available. Phase curves of Afρ versus scattering angle are calculated and produce good agreement with observational data. The major conclusions of our calculations are: – The original definition of A in Afρ is problematical and Afρ should be: qsca(n,λ)×p(g)×f×ρqsca(n,λ)×p(g)×f×ρ. Nevertheless, we keep the present nomenclature of Afρ as a measured quantity for an ensemble of coma particles.– The ratio between Afρ and the dust mass loss rate View the MathML sourcem˙ is dominated by the particle size distribution. – For most particle size distributions presently in use, small particles in the range from 0.10 to 1.0 μm contribute a large fraction to Afρ. – Simplifying the calculation of Afρ by considering only large particles and approximating qsca does not represent a realistic model. Mie scattering theory or if necessary, more complex scattering calculations must be used. – For the commonly used particle size distribution, dn/da ∼ a−3.5 to a−4, there is a natural cut off in Afρ contribution for both small and large particles. – The scattering phase function must be taken into account for each particle size; otherwise the contribution of large particles can be over-estimated by a factor of 10. – Using an imaginary index of refraction of i = 0.10 does not produce sufficient backscattering to match observational data. – A mixture of dark particles with i ⩾ 0.10 and brighter silicate particles with i ⩽ 0.04 matches the observed phase curves quite well. – Using current observational constraints, we find the dust/gas mass-production ratio of CG at 1.3 AU is confined to a range of 0.03–0.5 with a reasonably likely value around 0.1.

Intrinsic oxidative stress in cancer cells: A biochemical basis for therapeutic selectivity using ROS -generating agents

A major goal of chemotherapy is to selectively kill cancer cells while minimizing toxicity to normal cells. Identifying biological differences between cancer and normal cells is essential in designing new strategies to improve therapeutic selectivity. Superoxide dismutases (SOD) are crucial antioxidant enzymes required for the elimination of superoxide (O2·− ), a free radical produced during normal cellular metabolism. Previous studies in our laboratory demonstrated that 2-methoxyestradiol (2-ME), an estradiol derivative, inhibits the function of SOD and selectively kills human leukemia cells without exhibiting significant cytotoxicity in normal lymphocytes. The present work was initiated to examine the biochemical basis for the selective anticancer activity of 2-ME. Investigations using two-parameter flow cytometric analyses and ROS scavengers established that O2·− is a primary and essential mediator of 2-ME-induced apoptosis in cancer cells. In addition, experiments using SOD overexpression vectors and SOD knockout cells found that SOD is a critical target of 2-ME. Importantly, the administration of 2-ME resulted in the selective accumulation of O 2·− and apoptosis in leukemia and ovarian cancer cells. The preferential activity of 2-ME was found to be due to increased intrinsic oxidative stress in these cancer cells versus their normal counterparts. This intrinsic oxidative stress was associated with the upregulation of the antioxidant enzymes SOD and catalase as a mechanism to cope with the increase in ROS. Furthermore, oxygen consumption experiments revealed that normal lymphocytes decrease their respiration rate in response to 2-ME-induced oxidative stress, while human leukemia cells seem to lack this regulatory mechanism. This leads to an uncontrolled production of O2·−, severe accumulation of ROS, and ultimately ROS-mediated apoptosis in leukemia cells treated with 2-ME. The biochemical differences between cancer and normal cells identified here provide a basis for the development of drug combination strategies using 2-ME with other ROS-generating agents to enhance anticancer activity. The effectiveness of such a combination strategy in killing cancer cells was demonstrated by the use of 2-ME with agents/modalities such as ionizing radiation and doxorubicin. Collectively, the data presented here strongly suggests that 2-ME may have important clinical implications for the selective killing of cancer cells. ^

UMA ANÁLISE DA RELAÇÃO ENTRE VARIÁVEIS MACROECONÔMICAS E O COMPORTAMENTO DAS AÇÕES DE MAIOR LIQUIDEZ DO ÍNDICE IBOVESPA

As ações de maior liquidez do índice IBOVESPA, refletem o comportamento das ações de um modo geral, bem como a relação das variáveis macroeconômicas em seu comportamento e estão entre as mais negociadas no mercado de capitais brasileiro. Desta forma, pode-se entender que há reflexos de fatores que impactam as empresas de maior liquidez que definem o comportamento das variáveis macroeconômicas e que o inverso também é uma verdade, oscilações nos fatores macroeconômicos também afetam as ações de maior liquidez, como IPCA, PIB, SELIC e Taxa de Câmbio. O estudo propõe uma análise da relação existente entre variáveis macroeconômicas e o comportamento das ações de maior liquidez do índice IBOVESPA, corroborando com estudos que buscam entender a influência de fatores macroeconômicos sobre o preço de ações e contribuindo empiricamente com a formação de portfólios de investimento. O trabalho abrangeu o período de 2008 a 2014. Os resultados concluíram que a formação de carteiras, visando a proteção do capital investido, deve conter ativos com correlação negativa em relação às variáveis estudadas, o que torna possível a composição de uma carteira com risco reduzido.

Bifurcation analysis of a dynamic power system with SVC devices

Bifurcation analysis is a very useful tool for power system stability assessment. In this paper, detailed investigation of power system bifurcation behaviour is presented. One and two parameter bifurcation analysis are conducted on a 3-bus power system. We also examined the impact of FACTS devices on power system stability through Hopf bifurcation analysis by taking static Var compensator (SVC) as an example. A simplified first-order model of the SVC device is included in the 3-bus sample system. Real and reactive powers are used as bifurcation parameter in the analysis to compare the system oscillatory properties with and without SVC. The simulation results indicate that the linearized system model with SVC enlarge the voltage stability boundary by moving Hopf bifurcation point to higher level of loading conditions. The installation of SVC increases the dynamic stability range of the system, however complicates the Hopf bifurcation behavior of the system

UMA ANÁLISE DA RELAÇÃO ENTRE VARIÁVEIS MACROECONÔMICAS E O COMPORTAMENTO DAS AÇÕES DE MAIOR LIQUIDEZ DO ÍNDICE IBOVESPA

As ações de maior liquidez do índice IBOVESPA, refletem o comportamento das ações de um modo geral, bem como a relação das variáveis macroeconômicas em seu comportamento e estão entre as mais negociadas no mercado de capitais brasileiro. Desta forma, pode-se entender que há reflexos de fatores que impactam as empresas de maior liquidez que definem o comportamento das variáveis macroeconômicas e que o inverso também é uma verdade, oscilações nos fatores macroeconômicos também afetam as ações de maior liquidez, como IPCA, PIB, SELIC e Taxa de Câmbio. O estudo propõe uma análise da relação existente entre variáveis macroeconômicas e o comportamento das ações de maior liquidez do índice IBOVESPA, corroborando com estudos que buscam entender a influência de fatores macroeconômicos sobre o preço de ações e contribuindo empiricamente com a formação de portfólios de investimento. O trabalho abrangeu o período de 2008 a 2014. Os resultados concluíram que a formação de carteiras, visando a proteção do capital investido, deve conter ativos com correlação negativa em relação às variáveis estudadas, o que torna possível a composição de uma carteira com risco reduzido.

Dynamic models of exchange rate dependence using option prices and historical returns

Models for the conditional joint distribution of the U.S. Dollar/Japanese Yen and Euro/Japanese Yen exchange rates, from November 2001 until June 2007, are evaluated and compared. The conditional dependency is allowed to vary across time, as a function of either historical returns or a combination of past return data and option-implied dependence estimates. Using prices of currency options that are available in the public domain, risk-neutral dependency expectations are extracted through a copula repre- sentation of the bivariate risk-neutral density. For this purpose, we employ either the one-parameter \Normal" or a two-parameter \Gumbel Mixture" specification. The latter provides forward-looking information regarding the overall degree of covariation, as well as, the level and direction of asymmetric dependence. Specifications that include option-based measures in their information set are found to outperform, in-sample and out-of-sample, models that rely solely on historical returns.

Periphyton light transmission relationships in Florida Bay and the Florida Keys, USA

Light transmission was measured through intact, submerged periphyton communities on artificial seagrass leaves. The periphyton communities were representative of the communities on Thalassia testudinum in subtropical seagrass meadows. The periphyton communities sampled were adhered carbonate sediment, coralline algae, and mixed algal assemblages. Crustose or film-forming periphyton assemblages were best prepared for light transmission measurements using artificial leaves fouled on both sides, while measurements through three-dimensional filamentous algae required the periphyton to be removed from one side. For one-sided samples, light transmission could be measured as the difference between fouled and reference artificial leaf samples. For two-sided samples, the percent periphyton light transmission to the leaf surface was calculated as the square root of the fraction of incident light. Linear, exponential, and hyperbolic equations were evaluated as descriptors of the periphyton dry weight versus light transmission relationship. Hyperbolic and exponential decay models were superior to linear models and exhibited the best fits for the observed relationships. Differences between the coefficients of determination (r2) of hyperbolic and exponential decay models were statistically insignificant. Constraining these models for 100% light transmission at zero periphyton load did not result in any statistically significant loss in the explanatory capability of the models. In most all cases, increasing model complexity using three-parameter models rather than two-parameter models did not significantly increase the amount of variation explained. Constrained two-parameter hyperbolic or exponential decay models were judged best for describing the periphyton dry weight versus light transmission relationship. On T. testudinum in Florida Bay and the Florida Keys, significant differences were not observed in the light transmission characteristics of the varying periphyton communities at different study sites. Using pooled data from the study sites, the hyperbolic decay coefficient for periphyton light transmission was estimated to be 4.36 mg dry wt. cm−2. For exponential models, the exponential decay coefficient was estimated to be 0.16 cm2 mg dry wt.−1.

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.

Knowledge Modeling for The Outcome of Brain Stereotactic Radiosurgery

Purpose: To build a model that will predict the survival time for patients that were treated with stereotactic radiosurgery for brain metastases using support vector machine (SVM) regression.

Methods and Materials: This study utilized data from 481 patients, which were equally divided into training and validation datasets randomly. The SVM model used a Gaussian RBF function, along with various parameters, such as the size of the epsilon insensitive region and the cost parameter (C) that are used to control the amount of error tolerated by the model. The predictor variables for the SVM model consisted of the actual survival time of the patient, the number of brain metastases, the graded prognostic assessment (GPA) and Karnofsky Performance Scale (KPS) scores, prescription dose, and the largest planning target volume (PTV). The response of the model is the survival time of the patient. The resulting survival time predictions were analyzed against the actual survival times by single parameter classification and two-parameter classification. The predicted mean survival times within each classification were compared with the actual values to obtain the confidence interval associated with the model’s predictions. In addition to visualizing the data on plots using the means and error bars, the correlation coefficients between the actual and predicted means of the survival times were calculated during each step of the classification.

Results: The number of metastases and KPS scores, were consistently shown to be the strongest predictors in the single parameter classification, and were subsequently used as first classifiers in the two-parameter classification. When the survival times were analyzed with the number of metastases as the first classifier, the best correlation was obtained for patients with 3 metastases, while patients with 4 or 5 metastases had significantly worse results. When the KPS score was used as the first classifier, patients with a KPS score of 60 and 90/100 had similar strong correlation results. These mixed results are likely due to the limited data available for patients with more than 3 metastases or KPS scores of 60 or less.

Conclusions: The number of metastases and the KPS score both showed to be strong predictors of patient survival time. The model was less accurate for patients with more metastases and certain KPS scores due to the lack of training data.