Adaptive sequence evolution in a color gene involved in the formation of the characteristic egg-dummies of male haplochromine cichlid fishes.

BACKGROUND: The exceptionally diverse species flocks of cichlid fishes in East Africa are prime examples of parallel adaptive radiations. About 80% of East Africa's more than 1 800 endemic cichlid species, and all species of the flocks of Lakes Victoria and Malawi, belong to a particularly rapidly evolving lineage, the haplochromines. One characteristic feature of the haplochromines is their possession of egg-dummies on the males' anal fins. These egg-spots mimic real eggs and play an important role in the mating system of these maternal mouthbrooding fish. RESULTS: Here, we show that the egg-spots of haplochromines are made up of yellow pigment cells, xanthophores, and that a gene coding for a type III receptor tyrosine kinase, colony-stimulating factor 1 receptor a (csf1ra), is expressed in egg-spot tissue. Molecular evolutionary analyses reveal that the extracellular ligand-binding and receptor-interacting domain of csf1ra underwent adaptive sequence evolution in the ancestral lineage of the haplochromines, coinciding with the emergence of egg-dummies. We also find that csf1ra is expressed in the egg-dummies of a distantly related cichlid species, the ectodine cichlid Ophthalmotilapia ventralis, in which markings with similar functions evolved on the pelvic fin in convergence to those of the haplochromines. CONCLUSION: We conclude that modifications of existing signal transduction mechanisms might have evolved in the haplochromine lineage in association with the origination of anal fin egg-dummies. That positive selection has acted during the evolution of a color gene that seems to be involved in the morphogenesis of a sexually selected trait, the egg-dummies, highlights the importance of further investigations of the comparative genomic basis of the phenotypic diversification of cichlid fishes.

On the Chern classes and the Euler characteristic for nonsingular complete intersections

It is shown that Hirzebruch's result on the Chern classes of a complete intersection of nonsingular hypersurfaces in general position in PN(C), is also valid for any nonsingular complete intersection. Then rela- tions between Euler characteristic, class and Milnor number are pointed out.

Characteristic of Dystrustepts in the Venezuelan Andes

The majority (60 %) of the soils in the Venezuelan Andes are Inceptisols, a large percentage of which are classified as Dystrustepts by the US Soil Taxonomy, Second Edition of 1999. Some of these soils were classified as Humitropepts (high organic - C-OC-soils) and Dystropepts by the Soil Taxonomy prior to 1999, but no equivalent large group was created for high-OC soils in the new Ustepts suborder. Dystrusepts developed on different materials, relief and vegetation. Their properties are closely related with the parent material. Soils developed on transported deposits or sediments have darker and thicker A horizons, a slightly acid reaction, greater CEC and OC contents than upland slope soils. Based on the previous classification into large groups (Humitropepts and Dystropepts) we found that: Humitropepts have a slightly less acid and higher values of CEC than Dystropepts. These properties or characteristics seem to be related to the fact that Humitropepts have a higher clay and OC content than the Dystropepts. Canonical discrimination analysis showed that the variables that discriminate the two great soil groups from each other are OC and silt. Data for Humitropepts are grouped around the OC vector (defining axis 3, principal component analysis), while Dystropepts are associated with the clay and sand vectors, with significant correlation. Given the importance of OC for soil properties, we propose the creation of a new large group named Humustepts for the order Inceptisol, suborder Ustepts.

Aggregate stability by the "high energy moisture characteristic" method in an oxisol under differentiated management

Studies testing the High Energy Moisture Characteristic (HEMC) technique in tropical soils are still incipient. By this method, the effects of different management systems can be evaluated. This study investigated the aggregation state of an Oxisol under coffee with Brachiaria between crop rows and surface-applied gypsum rates using HEMC. Soil in an experimental area in the Upper São Francisco region, Minas Gerais, was studied at depths of 0.05 and 0.20 m in coffee rows. The treatments consisted of 0, 7, and 28 Mg ha-1 of agricultural gypsum rates distributed on the soil surface of the coffee rows, between which Brachiaria was grown and periodically cut, and compared with a treatment without Brachiaria between coffee rows and no gypsum application. To determine the aggregation state using the HEMC method, soil aggregates were placed in a Büchner funnel (500 mL) and wetted using a peristaltic pump with a volumetric syringe. The wetting was applied increasingly at two pre-set speeds: slow (2 mm h-1) and fast (100 mm h-1). Once saturated, the aggregates were exposed to a gradually increasing tension by the displacement of a water column (varying from 0 to 30 cm) to obtain the moisture retention curve [M = f (Ψ) ], underlying the calculation of the stability parameters: modal suction, volume of drainable pores (VDP), stability index (slow and fast), VDP ratio, and stability ratio. The HEMC method conferred sensitivity in quantifying the aggregate stability parameters, and independent of whether gypsum was used, the soil managed with Brachiaria between the coffee rows, with regular cuts discharged in the crop row direction, exhibited a decreased susceptibility to disaggregation.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Proteomic analysis of membrane rafts of melanoma cells identifies protein patterns characteristic of the tumor progression stage.

The molecular mechanisms controlling the progression of melanoma from a localized tumor to an invasive and metastatic disease are poorly understood. In the attempt to start defining a functional protein profile of melanoma progression, we have analyzed by LC-MS/MS the proteins associated with detergent resistant membranes (DRMs), which are enriched in cholesterol/sphingolipids-containing membrane rafts, of melanoma cell lines derived from tumors at different stages of progression. Since membrane rafts are involved in several biological processes, including signal transduction and protein trafficking, we hypothesized that the association of proteins with rafts can be regulated during melanoma development and affect protein function and disease progression. We have identified a total of 177 proteins in the DRMs of the cell lines examined. Among these, we have found groups of proteins preferentially associated with DRMs of either less malignant radial growth phase/vertical growth phase (VGP) cells, or aggressive VGP and metastatic cells suggesting that melanoma cells with different degrees of malignancy have different DRM profiles. Moreover, some proteins were found in DRMs of only some cell lines despite being expressed at similar levels in all the cell lines examined, suggesting the existence of mechanisms controlling their association with DRMs. We expect that understanding the mechanisms regulating DRM targeting and the activity of the proteins differentially associated with DRMs in relation to cell malignancy will help identify new molecular determinants of melanoma progression.

Is it the grain size or the characteristic pore size that controls the induced polarization relaxation time of clean sands and sandstones?

There is a wide range of evidence to suggest that permeability can be constrained through of induced polarization measurements. For clean sands and sandstones, current mechanistic models of induced polarization predict a relationship between the low-frequency time constant inferred from induced polarization measurements and the grain diameter. A number of observations do, however, disagree with this and indicate that the observed relaxation behavior is rather governed by the so-called dynamic pore radius L. To test this hypothesis, we have developed a set of new scaling relationships, which allow the relaxation time to be computed from the pore size and the permeability to be computed from both the Cole-Cole time constant and the formation factor. Moreover, these new scaling relationships can be also used to predict the dependence of the Cole-Cole time constant as a function of the water saturation under unsaturated conditions. Comparative tests of the proposed new relationships with regard to various published experimental results for saturated clean sands and sandstones as well as for partially saturated clean sandstones, do indeed confirm that the dynamic pore radius L is a much more reliable indicator of the observed relaxation behavior than grain-size-based models.

Detection of Raga-characteristic phrases from Hindustani Classical Music Audio

Melodic motifs form essential building blocks in Indian Classical music. The motifs, or key phrases, providestrong cues to the identity of the underlying raga in both Hindustani and Carnatic styles of Indian music. Automatic identification and clustering of similar motifs is relevant in this context. The inherent variations in various instances of a characteristic phrase in a bandish (composition)performance make it challenging to identify similar phrases in a performance. A nyas svara (long note)marks the ending of these phrases. The proposed method does segmentation of phrases through identification ofnyas and computes similarity with the reference characteristic phrase.

A characteristic EEG pattern in 4p-syndrome: case report and review of the literature.

Deletions on the short arm of chromosome 4 cause Wolf-Hirschhorn syndrome (WHS) and Pitt-Rogers-Danks syndrome (PRDS). WHS is associated with severe growth and mental retardation, microcephaly, a characteristic facies and congenital malformations. The PRDS phenotype is similar to WHS but generally less severe. Seizures occur in the majority of WHS and PRDS patients. Sgrò et al. [17] described a stereotypic electroclinical pattern in four unrelated WHS patients, consisting of intermittent bursts of 2-3 Hz high voltage slow waves with spike wave activity in the parietal areas during drowsiness and sleep associated with myoclonic jerks. We report a patient with PRDS and the typical EEG pattern and review 14 WHS patients with similar EEG findings reported in the literature. CONCLUSION: Awareness and recognition of the characteristic electroclinical findings in Wolf-Hirschhorn syndrome and Pitt-Rogers-Danks syndrome might help in the early diagnosis of such patients.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

The Bonenblust-Hille inequality for homogeneous polynomials is hypercontractive

The Bohnenblust-Hille inequality says that the $\ell^{\frac{2m}{m+1}}$ -norm of the coefficients of an $m$-homogeneous polynomial $P$ on $\Bbb{C}^n$ is bounded by $\| P \|_\infty$ times a constant independent of $n$, where $\|\cdot \|_\infty$ denotes the supremum norm on the polydisc $\mathbb{D}^n$. The main result of this paper is that this inequality is hypercontractive, i.e., the constant can be taken to be $C^m$ for some $C>1$. Combining this improved version of the Bohnenblust-Hille inequality with other results, we obtain the following: The Bohr radius for the polydisc $\mathbb{D}^n$ behaves asymptotically as $\sqrt{(\log n)/n}$ modulo a factor bounded away from 0 and infinity, and the Sidon constant for the set of frequencies $\bigl\{ \log n: n \text{a positive integer} \le N\bigr\}$ is $\sqrt{N}\exp\{(-1/\sqrt{2}+o(1))\sqrt{\log N\log\log N}\}$.

Receiver operating characteristic (ROC) curve for classification of18F-NaF uptake on PET/CT

Abstract Objective: To assess the cutoff values established by ROC curves to classify18F-NaF uptake as normal or malignant. Materials and Methods: PET/CT images were acquired 1 hour after administration of 185 MBq of18F-NaF. Volumes of interest (VOIs) were drawn on three regions of the skeleton as follows: proximal right humerus diaphysis (HD), proximal right femoral diaphysis (FD) and first vertebral body (VB1), in a total of 254 patients, totalling 762 VOIs. The uptake in the VOIs was classified as normal or malignant on the basis of the radiopharmaceutical distribution pattern and of the CT images. A total of 675 volumes were classified as normal and 52 were classified as malignant. Thirty-five VOIs classified as indeterminate or nonmalignant lesions were excluded from analysis. The standardized uptake value (SUV) measured on the VOIs were plotted on an ROC curve for each one of the three regions. The area under the ROC (AUC) as well as the best cutoff SUVs to classify the VOIs were calculated. The best cutoff values were established as the ones with higher result of the sum of sensitivity and specificity. Results: The AUCs were 0.933, 0.889 and 0.975 for UD, FD and VB1, respectively. The best SUV cutoffs were 9.0 (sensitivity: 73%; specificity: 99%), 8.4 (sensitivity: 79%; specificity: 94%) and 21.0 (sensitivity: 93%; specificity: 95%) for UD, FD and VB1, respectively. Conclusion: The best cutoff value varies according to bone region of analysis and it is not possible to establish one value for the whole body.

The performance and the characteristic field of a centrifugal compressor

Tässä työssä tarkastellaan radiaalikompressorin puristusprosessiin liittyvä peruslaskenta. Ilmankosteuden vaikutukset laskentaan huomioidaan ja kompressorin tunnuskenttä esitellään tässä työssä. Esimerkkinä lasketaan pisteitä kompressorin tunnuskentästä.

Performance characteristic of moving average trading rules in the Finnish stock market

The thesis examines the profitability of DMAC trading rules in the Finnish stock market over the 1996-2012 period. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC strategies based on individual stock trading portfolios to the performance of index trading strategies based on the trading on the index (OMX Helsinki 25) that consists of the same stocks. Besides, the market frictions including transaction costs and taxes are taken into account, and the results are reported from both institutional and individual investor’s perspective. Performance characteristic of DMAC rules are evaluated by simulating 19,900 different trading strategies in total for two non- overlapping 8-year sub-periods, and decomposing the full-sample-period performance of DMAC trading strategies into distinct bullish- and bearish-period performances. The results show that the best DMAC rules have predictive power on future price trends, and these rules are able to outperform buy-and-hold strategy. Although the performance of the DMAC strategies is highly dependent on the combination of moving average lengths, the best DMAC rules of the first sub-period have also performed well during the latter sub-period in the case of individual stock trading strategies. According to the results, the outperformance of DMAC trading rules over buy-and-hold strategy is mostly attributed to their superiority during the bearish periods, and particularly, during stock market crashes.