Breakup coupling effects on near-barrier quasi-elastic scattering of (6,7)Li on (144)Sm

Excitation functions of quasi-elastic scattering at backward angles have been measured for the (6,7)Li + (144)Sm systems at near-barrier energies, and fusion barrier distributions have been extracted from the first derivatives of the experimental cross sections with respect to the bombarding energies. The data have been analyzed in the framework of continuum discretized coupled-channel calculations, and the results have been obtained in terms of the influence exerted by the inclusion of different reaction channels, with emphasis on the role played by the projectile breakup.

Structure of (46)Ti at low excitation energy

The nucleus (46)Ti has been studied with the reaction (42)Ca((7)Li,p2n)(46)Ti at a bombarding energy of 31 MeV. Thin target foils backed with a thick Au layer were used. Five new levels of negative parity were observed. Several lifetimes have been determined with the Doppler shift attenuation method. Low-lying experimental negative-parity levels are assigned to three bands with K(pi) = 3, 0, and 4, which are interpreted in terms of the large-scale shell model, considering particle-hole excitations from d(3/2) and s(1/2) orbitals. Shell model calculations were performed using a few effective interactions. However, good agreement was not achieved in the description of either negative- or positive-parity low-lying levels.

Near- and subbarrier elastic and quasielastic scattering of the weakly bound (6)Li projectile on (144)Sm

High-precision data of backward-angle elastic and quasielastic scattering for the weakly bound (6)Li projectile on (144)Sm target at deep-sub-barrier, near-, and above-barrier energies were measured. From the deep-sub-barrier data, the surface diffuseness of the nuclear interacting potential was studied. Barrier distributions were extracted from the first derivatives of the elastic and quasielastic excitation functions. It is shown that sequential breakup through the first resonant state of the (6)Li is an important channel to be included in coupled-channels calculations, even at deep-sub-barrier energies.

Effects of the target spin on the reaction mechanism of the (16)O+(63)Cu system

Precise quasielastic and alpha-transfer excitation functions, at theta(lab) = 161 degrees, have been measured at energies near the Coulomb barrier for the (16)O + (63)Cu system. This is the first time reported quasielastic barrier distribution for a medium odd-A nucleus target deduced from the data. Additional elastic scattering angular distributions data available in the literature for this system were also used in the investigation of the role of several individual channels in the reaction dynamics, by comparing the data with free-parameter coupled-channels calculations. In order to do so, the nucleus-nucleus bare potential has a double-folding potential as the real component and only a very short-range imaginary potential. The quasielastic barrier distribution has been shown to be a powerful tool in this analysis at the barrier region. A high collectivity of the (63)Cu was observed, mainly due to the strong influence of its 5/2-and 7/2-states on all reaction channels investigated. A striking influence of the reorientation of the ground-state target-spin on the elastic cross sections, taken at backward angles, was also observed.

Near-barrier quasielastic scattering as a sensitive tool to derive nuclear matter diffuseness

Quasielastic excitation functions for the (16,18)O + (60)Ni systems were measured at energies near and below the Coulomb barrier, at the backward angle theta(LAB) = 161 degrees. The corresponding quasielastic barrier distributions were derived. The data were compared with predictions from coupled channel calculations using a double-folding potential as a bare potential. For the (16)O-induced scattering, good agreement was obtained for the barrier distribution by using the projectile default nuclear matter diffuseness obtained from the Sao Paulo potential systematic, that is, 0.56 fm. However, for the (18)O-induced scattering, good agreement was obtained only when the projectile nuclear matter diffuseness was changed to 0.62 fm. Therefore, in this paper we show how near-barrier quasielastic scattering can be used as a sensitive tool to derive nuclear matter diffuseness.

Electromagnetic Wave Scattering by Schwarzschild Black Holes

We analyze the scattering of a planar monochromatic electromagnetic wave incident upon a Schwarzschild black hole. We obtain accurate numerical results from the partial wave method for the electromagnetic scattering cross section and show that they are in excellent agreement with analytical approximations. The scattering of electromagnetic waves is compared with the scattering of scalar, spinor, and gravitational waves. We present a unified picture of the scattering of all massless fields for the first time.

Experimental and theoretical study of two-photon absorption in nitrofuran derivatives: Promising compounds for photochemotherapy

We report experimental and theoretical studies of the two-photon absorption spectrum of two nitrofuran derivatives: nitrofurantoine, (1-(5-nitro-2-furfurilideneamine)-hidantoine) and quinifuryl, 2-(5`-nitro-2`-furanyl) ethenyl-4-{N-[4`-(N,N-diethylamino)-1`-methylbutyl]carbamoyl} quinoline. Both molecules are representative of a family of 5-nitrofuran-ethenyl-quinoline drugs that have been demonstrated to display high toxicity to various species of transformed cells in the dark. We determine the two-photon absorption cross-section for both compounds, from 560 to 880 nm, which present peak values of 64 GM for quinifuryl and 20 GM for nitrofurantoine (1 GM = 1 x 10(-50) cm(4).s.photon(-1)). Besides, theoretical calculations employing the linear and quadratic response functions were carried out at the density functional theory level to aid the interpretations of the experimental results. The theoretical results yielded oscillator strengths, two-photon transition probabilities, and transition energies, which are in good agreement with the experimental data. A higher number of allowed electronic transitions was identified for quinifuryl in comparison to nitrofurantoine by the theoretical calculations. Due to the planar structure of both compounds, the differences in the two-photon absorption cross-section values are a consequence of their distinct conjugation lengths. (c) 2011 American Institute of Physics. [doi:10.1063/1.3514911]

Spontaneous long and short-range ferroelectric ordering in Pb(0.55)La(0.30)TiO(3) ceramics

In this work, we investigated the temperature dependence of short and long-range ferroelectric ordering in Pb(0.55)La(0.30)TiO(3) relaxor composition. High-resolution x-ray powder diffraction measurements revealed a clear spontaneous macroscopic cubic-to-tetragonal phase transition in the PLT relaxor sample at similar to 60 K below the maximum of the dielectric constant peak (T(m)). Indeed, the x-ray diffraction (XRD) data showed that at 300 K (above T(m) but below the Burns temperature, T(B)) the long-range order structure corresponds to a macroscopic cubic symmetry, space group number 221 (Pm-3m), whereas the data collected at 20 K revealed a macroscopic tetragonal symmetry, space group number 99 (P4mm) with c/a=1.0078, that is comparable to that of a normal ferroelectric. These results show that for samples with tetragonal composition, the long-range ferroelectric order may be recovered spontaneously at cryogenics temperatures, in contrast to ferroelectric samples with rhombohedral symmetry. On the other hand, x-ray absorption spectroscopy investigations intriguingly revealed the existence of local tetragonal disorder around Ti atoms for temperatures far below T(m) and above T(B), for which the sample presents macroscopic tetragonal and cubic symmetries, respectively. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3431024]

The role of oxygen vacancy in the photoluminescence property at room temperature of the CaTiO(3)

In this paper, electron paramagnetic resonance, photoluminescence (PL) emission, and quantum mechanical calculations were used to observe and understand the structural order-disorder of CaTiO(3), paying special attention to the role of oxygen vacancy. The PL phenomenon at room temperature of CaTiO(3) is directly influenced by the presence of oxygen vacancies that yield structural order-disorder. These oxygen vacancies bonded at Ti and/or Ca induce new electronic states inside the band gap. Ordered and disordered CaTiO(3) was obtained by the polymeric precursor method. (C) 2009 American Institute of Physics. [DOI: 10.1063/1.3190524]

Short-range structure of Pb(1-x)Ba(x)Zr(0.65)Ti(0.35)O(3) ceramic compounds probed by XAS and Raman scattering techniques

Ti K-edge x-ray absorption near-edge spectroscopy (XANES) and Raman scattering were used to study the solid solution effects on the structural and vibrational properties of Pb(1-x)Ba(x)Zr(0.65)Ti(0.35)O(3) with 0.0 < x < 0.40. Compared with x-ray diffraction techniques, which indicates that the average crystal symmetry changes with the substitution of Pb by Ba ions or with temperature variations for samples with x=0.00, 0.10, and 0.20, local structural probes such as XANES and Raman scattering results demonstrate that at local level, the symmetry changes are much less prominent. Theoretical XANES spectra calculation corroborate with the interpretation of the XANES experimental data.

Purification, crystallization and preliminary crystallographic analysis of the catalytic domain of the extracellular cellulase CBHI from Trichoderma harzianum

The filamentous fungus Trichoderma harzianum has a considerable cellulolytic activity that is mediated by a complex of enzymes which are essential for the hydrolysis of microcrystalline cellulose. These enzymes were produced by the induction of T. harzianum with microcrystalline cellulose (Avicel) under submerged fermentation in a bioreactor. The catalytic core domain (CCD) of cellobiohydrolase I (CBHI) was purified from the extracellular extracts and submitted to robotic crystallization. Diffraction-quality CBHI CCD crystals were grown and an X-ray diffraction data set was collected under cryogenic conditions using a synchrotron-radiation source.

Sublattice magnetism in sigma-phase Fe(100-x)Vx (x=34.4, 39.9, and 47.9) studied via zero-field (51)V NMR

The successful measurements of a sublattice magnetism with (51)V NMR techniques in the sigma-phase Fe(100-x)V(x) alloys with x=34.4, 39.9, and 47.9 are reported. Vanadium atoms, which were revealed to be present on all five crystallographic sites, are found to be under the action of the hyperfine magnetic fields produced by the neighboring Fe atoms, which allow the observation of (51)V NMR signals. Their nuclear magnetic properties are characteristic of a given site, which strongly depend on the composition. Site A exhibits the strongest magnetism while site D is the weakest. The estimated average magnetic moment per V atom decreases from 0.36 mu(B) for x=34.4 to 0.20 mu(B) for x=47.9. The magnetism revealed at V atoms is linearly correlated with the magnetic moment of Fe atoms, which implies that the former is induced by the latter.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.