172 resultados para Kummer function
Resumo:
Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.
Structural Insights into Saccharomyces cerevisiae Msh4-Msh5 Complex Function Using Homology Modeling
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The Msh4-Msh5 protein complex in eukaryotes is involved in stabilizing Holliday junctions and its progenitors to facilitate crossing over during Meiosis I. These functions of the Msh4-Msh5 complex are essential for proper chromosomal segregation during the first meiotic division. The Msh4/5 proteins are homologous to the bacterial mismatch repair protein MutS and other MutS homologs (Msh2, Msh3, Msh6). Saccharomyces cerevisiae msh4/5 point mutants were identified recently that show two fold reduction in crossing over, compared to wild-type without affecting chromosome segregation. Three distinct classes of msh4/5 point mutations could be sorted based on their meiotic phenotypes. These include msh4/5 mutations that have a) crossover and viability defects similar to msh4/5 null mutants; b) intermediate defects in crossing over and viability and c) defects only in crossing over. The absence of a crystal structure for the Msh4-Msh5 complex has hindered an understanding of the structural aspects of Msh4-Msh5 function as well as molecular explanation for the meiotic defects observed in msh4/5 mutations. To address this problem, we generated a structural model of the S. cerevisiae Msh4-Msh5 complex using homology modeling. Further, structural analysis tailored with evolutionary information is used to predict sites with potentially critical roles in Msh4-Msh5 complex formation, DNA binding and to explain asymmetry within the Msh4-Msh5 complex. We also provide a structural rationale for the meiotic defects observed in the msh4/5 point mutations. The mutations are likely to affect stability of the Msh4/5 proteins and/or interactions with DNA. The Msh4-Msh5 model will facilitate the design and interpretation of new mutational data as well as structural studies of this important complex involved in meiotic chromosome segregation.
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Ellipsometric measurements in a wide spectral range (from 0.05 to 6.5 eV) have been carried out on the organic semiconducting polymer, poly2-methoxy-5-(3',7'-dimethyloctyloxy)-1,4-phenylene-vinylene] (MDMO-PPV), in both undoped and doped states. The real and imaginary parts of the dielectric function and the refractive index are determined accurately, provided that the layer thickness is measured independently. After doping, the optical properties show the presence of new peaks, which could be well-resolved by spectroscopic ellipsometry. Also for the doped material, the complex refractive index, with respect to the dielectric function, has been determined. The broadening of the optical transitions is due to the delocalization of polarons at higher doping level. The detailed information about the dielectric function as well as refractive index function obtained by spectroscopic ellipsometry allows not only qualitative but also quantitative description of the optical properties of the undoped/doped polymer. For the direct characterization of the optical properties of MDMO-PPV, ellipsometry turns out to be advantageous compared to conventional reflection and transmission measurements.
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Blastocyst hatching is critical for successful implantation leading to pregnancy. Its failure causes infertility. The phenomenon of blastocyst hatching in humans is poorly understood and the available information on this stems from studies of rodents such as mice and hamsters. We and others showed that hamster blastocyst hatching is characterized by firstly blastocyst deflation followed by a dissolution of the zona pellucida (zona) and accompanied by trophectodermal projections (TEPs). We also showed that embryo-derived cathepsins (Cat) proteases, specifically Cat-L, -B and -P act as zonalysins and are responsible for hatching. In this study, we show the expression and function of one of the potential regulators of embryogenesis, cyclooxygenase (COX)-2 during blastocyst development and hatching. The expression of COX-2 mRNA and protein was observed in 8-cell through hatched blastocyst stages and it was also localized to blastocysts TEPs. Specific COX-2 inhibitors, NS-398 and CAY-10404, inhibited blastocyst hatching; percentages achieved were only 28.4 5.3 and 32.3 5.4, respectively, compared with 90 with untreated embryos. Interestingly, inhibitor-treated blastocysts failed to deflate, normally observed during hatching. Supplementation of prostaglandins (PGs)-E-2 or -I-2 to cultured embryos reversed the inhibitors effect on hatching and also the deflation behavior. Importantly, the levels of mRNA and protein of Cat-L, -B and -P showed a significant reduction in the inhibitor-treated embryos compared with untreated embryos, although its mechanism remains to be examined. These data provide the first evidence that COX-2 is critical for blastocyst hatching in the golden hamster.
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Global efforts in macromolecular crystallography started in the thirties of the last century. However, definitive results began to emerge only in the late fifties and the early sixties. India has a long tradition in crystallography. The country had a head start in theoretical and computational structural biology, thanks to the efforts of G.N. Ramachandran and his colleagues in the fifties and the sixties. However, macromolecular crystallography got off the ground in India only in the eighties, particularly after the Bangalore group received adequate support from the Department of Science and Technology under their Thrust Area Programme. The Bangalore centre was also identified as a national nucleus for the development of the area in the country. Since then work in the area has spread widely and is being carried out by several groups, mainly led by scientists trained at Bangalore or their descendents, in about thirty institutions in India. In addition to the Department of Science and Technology, the effort is now supported by other agencies like the Department of Biotechnology and the Council of Scientific and Industrial Research. The problems addressed by macromolecular crystallographers in India encompass almost all aspects of modern biology. Indian efforts in macromolecular crystallography have also become an important component of the international efforts in the area.
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We extend our analysis of transverse single spin asymmetry in electroproduction of J/ψ to include the effect of the scale evolution of the transverse momentum dependent (TMD) parton distribution functions and gluon Sivers function. We estimate single spin asymmetry for JLab, HERMES, COMPASS, and eRHIC energies using the color evaporation model of charmonium production, using an analytically obtained approximate solution of TMD evolution equations discussed in the literature. We find that there is a reduction in the asymmetry compared with our predictions for the earlier case considered by us, wherein the Q2 dependence came only from DGLAP evolution of the unpolarized gluon densities and a different parametrization of the TMD Sivers function was used.
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The poison gland and Dufour's gland are the two glands associated with the sting apparatus in female Apocrita (Hymenoptera). While the poison gland usually functions as an integral part of the venom delivery system, the Dufour's gland has been found to differ in its function in various hymenopteran groups. Like all exocrine glands, the function of the Dufour's gland is to secrete chemicals, but the nature and function of the secretions varies in different taxa. Functions of the Dufour's gland secretions range from serving as a component of material used in nest building, larval food, and pheromones involved in communicative functions that are important for both solitary and social species. This review summarizes the different functions reported for the Dufour's gland in hymenopterans, illustrating how the Dufour's gland secretions can be adapted to give rise to various functions in response to different challenges posed by the ways of life followed by different taxa. Aspects of development, structure, chemistry and the evolution of different functions are also touched upon briefly.
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The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.
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We analytically evaluate the large deviation function in a simple model of classical particle transfer between two reservoirs. We illustrate how the asymptotic long-time regime is reached starting from a special propagating initial condition. We show that the steady-state fluctuation theorem holds provided that the distribution of the particle number decays faster than an exponential, implying analyticity of the generating function and a discrete spectrum for its evolution operator.
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We generalize the method of A. M. Polyakov, Phys. Rev. E 52, 6183 (1995)] for obtaining structure-function relations in turbulence in the stochastically forced Burgers equation, to develop structure-function hierarchies for turbulence in three models for magnetohydrodynamics (MHD). These are the Burgers analogs of MHD in one dimension Eur. Phys. J.B 9, 725 (1999)], and in three dimensions (3DMHD and 3D Hall MHD). Our study provides a convenient and unified scheme for the development of structure-function hierarchies for turbulence in a variety of coupled hydrodynamical equations. For turbulence in the three sets of MHD equations mentioned above, we obtain exact relations for third-order structure functions and their derivatives; these expressions are the analogs of the von Karman-Howarth relations for fluid turbulence. We compare our work with earlier studies of such relations in 3DMHD and 3D Hall MHD.
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Mitochondria are indispensable organelles implicated in multiple aspects of cellular processes, including tumorigenesis. Heat shock proteins play a critical regulatory role in accurately delivering the nucleus-encoded proteins through membrane-bound presequence translocase (Tim23 complex) machinery. Although altered expression of mammalian presequence translocase components had been previously associated with malignant phenotypes, the overall organization of Tim23 complexes is still unsolved. In this report, we show the existence of three distinct Tim23 complexes, namely, B1, B2, and A, involved in the maintenance of normal mitochondrial function. Our data highlight the importance of Magmas as a regulator of translocase function and in dynamically recruiting the J-proteins DnaJC19 and DnaJC15 to individual translocases. The basic housekeeping function involves translocases B1 and B2 composed of Tim17b isoforms along with DnaJC19, whereas translocase A is nonessential and has a central role in oncogenesis. Translocase B, having a normal import rate, is essential for constitutive mitochondrial functions such as maintenance of electron transport chain complex activity, organellar morphology, iron-sulfur cluster protein biogenesis, and mitochondrial DNA. In contrast, translocase A, though dispensable for housekeeping functions with a comparatively lower import rate, plays a specific role in translocating oncoproteins lacking presequence, leading to reprogrammed mitochondrial functions and hence establishing a possible link between the TIM23 complex and tumorigenicity.
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Classification of pharmacologic activity of a chemical compound is an essential step in any drug discovery process. We develop two new atom-centered fragment descriptors (vertex indices) - one based solely on topological considerations without discriminating atomor bond types, and another based on topological and electronic features. We also assess their usefulness by devising a method to rank and classify molecules with regard to their antibacterial activity. Classification performances of our method are found to be superior compared to two previous studies on large heterogeneous data sets for hit finding and hit-to-lead studies even though we use much fewer parameters. It is found that for hit finding studies topological features (simple graph) alone provide significant discriminating power, and for hit-to-lead process small but consistent improvement can be made by additionally including electronic features (colored graph). Our approach is simple, interpretable, and suitable for design of molecules as we do not use any physicochemical properties. The singular use of vertex index as descriptor, novel range based feature extraction, and rigorous statistical validation are the key elements of this study.
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In this paper we establish that the Lovasz theta function on a graph can be restated as a kernel learning problem. We introduce the notion of SVM-theta graphs, on which Lovasz theta function can be approximated well by a Support vector machine (SVM). We show that Erdos-Renyi random G(n, p) graphs are SVM-theta graphs for log(4)n/n <= p < 1. Even if we embed a large clique of size Theta(root np/1-p) in a G(n, p) graph the resultant graph still remains a SVM-theta graph. This immediately suggests an SVM based algorithm for recovering a large planted clique in random graphs. Associated with the theta function is the notion of orthogonal labellings. We introduce common orthogonal labellings which extends the idea of orthogonal labellings to multiple graphs. This allows us to propose a Multiple Kernel learning (MKL) based solution which is capable of identifying a large common dense subgraph in multiple graphs. Both in the planted clique case and common subgraph detection problem the proposed solutions beat the state of the art by an order of magnitude.
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The effect of structure height on the lightning striking distance is estimated using a lightning strike model that takes into account the effect of connecting leaders. According to the results, the lightning striking distance may differ significantly from the values assumed in the IEC standard for structure heights beyond 30m. However, for structure heights smaller than about 30m, the results show that the values assumed by IEC do not differ significantly from the predictions based on a lightning attachment model taking into account the effect of connecting leaders. However, since IEC assumes a smaller striking distance than the ones predicted by the adopted model one can conclude that the safety is not compromised in adhering to the IEC standard. Results obtained from the model are also compared with Collection Volume Method (CVM) and other commonly used lightning attachment models available in the literature. The results show that in the case of CVM the calculated attractive distances are much larger than the ones obtained using the physically based lightning attachment models. This indicates the possibility of compromising the lightning protection procedures when using CVM. (C) 2014 Elsevier B.V. All rights reserved.
Resumo:
Inference of molecular function of proteins is the fundamental task in the quest for understanding cellular processes. The task is getting increasingly difficult with thousands of new proteins discovered each day. The difficulty arises primarily due to lack of high-throughput experimental technique for assessing protein molecular function, a lacunae that computational approaches are trying hard to fill. The latter too faces a major bottleneck in absence of clear evidence based on evolutionary information. Here we propose a de novo approach to annotate protein molecular function through structural dynamics match for a pair of segments from two dissimilar proteins, which may share even <10% sequence identity. To screen these matches, corresponding 1 mu s coarse-grained (CG) molecular dynamics trajectories were used to compute normalized root-mean-square-fluctuation graphs and select mobile segments, which were, thereafter, matched for all pairs using unweighted three-dimensional autocorrelation vectors. Our in-house custom-built forcefield (FF), extensively validated against dynamics information obtained from experimental nuclear magnetic resonance data, was specifically used to generate the CG dynamics trajectories. The test for correspondence of dynamics-signature of protein segments and function revealed 87% true positive rate and 93.5% true negative rate, on a dataset of 60 experimentally validated proteins, including moonlighting proteins and those with novel functional motifs. A random test against 315 unique fold/function proteins for a negative test gave >99% true recall. A blind prediction on a novel protein appears consistent with additional evidences retrieved therein. This is the first proof-of-principle of generalized use of structural dynamics for inferring protein molecular function leveraging our custom-made CG FF, useful to all. (C) 2014 Wiley Periodicals, Inc.