In situ impedance spectroscopy study of the electrochemical corrosion of Ti and Ti-6Al-4V in simulated body fluid at 25 degrees C and 37 degrees C

The corrosion resistance of Ti and Ti-6Al-4V was investigated through electrochemical impedance spectroscopy, EIS, potentiodynamic polarisation curves and UV-Vis spectrophotometry. The tests were done in Hank solution at 25 degrees C and 37 degrees C. The EIS measurements were done at the open circuit potential at specific immersion times. An increase of the resistance as a function of the immersion time was observed, for Ti (at 25 degrees C and 37 degrees C), and for Ti-6Al-4V (at 25 degrees C), which was interpreted as the formation and growth of a passive film on the metallic surfaces. (C) 2009 Elsevier Ltd. All rights reserved.

Beyond the average: Detecting global singular nodes from local features in complex networks

Deviations from the average can provide valuable insights about the organization of natural systems. The present article extends this important principle to the systematic identification and analysis of singular motifs in complex networks. Six measurements quantifying different and complementary features of the connectivity around each node of a network were calculated, and multivariate statistical methods applied to identify singular nodes. The potential of the presented concepts and methodology was illustrated with respect to different types of complex real-world networks, namely the US air transportation network, the protein-protein interactions of the yeast Saccharomyces cerevisiae and the Roget thesaurus networks. The obtained singular motifs possessed unique functional roles in the networks. Three classic theoretical network models were also investigated, with the Barabasi-Albert model resulting in singular motifs corresponding to hubs, confirming the potential of the approach. Interestingly, the number of different types of singular node motifs as well as the number of their instances were found to be considerably higher in the real-world networks than in any of the benchmark networks. Copyright (C) EPLA, 2009

A complex network approach to text summarization

Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization strategies. In this paper, we employ concepts and metrics of complex networks to select sentences for an extractive summary. The graph or network representing one piece of text consists of nodes corresponding to sentences, while edges connect sentences that share common meaningful nouns. Because various metrics could be used, we developed a set of 14 summarizers, generically referred to as CN-Summ, employing network concepts such as node degree, length of shortest paths, d-rings and k-cores. An additional summarizer was created which selects the highest ranked sentences in the 14 systems, as in a voting system. When applied to a corpus of Brazilian Portuguese texts, some CN-Summ versions performed better than summarizers that do not employ deep linguistic knowledge, with results comparable to state-of-the-art summarizers based on expensive linguistic resources. The use of complex networks to represent texts appears therefore as suitable for automatic summarization, consistent with the belief that the metrics of such networks may capture important text features. (c) 2008 Elsevier Inc. All rights reserved.

Seeking for simplicity in complex networks

Complex networks can be understood as graphs whose connectivity properties deviate from those of regular or near-regular graphs, which are understood as being ""simple"". While a great deal of the attention so far dedicated to complex networks has been duly driven by the ""complex"" nature of these structures, in this work we address the identification of their simplicity. The basic idea is to seek for subgraphs whose nodes exhibit similar measurements. This approach paves the way for complementing the characterization of networks, including results suggesting that the protein-protein interaction networks, and to a lesser extent also the Internet, may be getting simpler over time. Copyright (C) EPLA, 2009

Interaction of polysaccharide-protein complex from Agaricus blazei with Langmuir and Langmuir-Blodgett films of phospholipids

The use of natural substances in health applications may be hampered by the difficulties in establishing the mechanisms of action, especially at molecular-level. The protein-polysaccharide complex extracted from the mushroom Agaricus blazei Murill, referred to as CAb, has been considered for treating various diseases with probable interaction with cell membranes. In this study, we investigate the interaction between CAb and a cell membrane model represented by a Langmuir monolayer of dimyristoyl phosphatidic acid (DMPA). CAb affects the structural properties of DMPA monolayers causing expansion and increasing compressibility. In addition, interaction with DMPA polar heads led to neutralization of the electrical double layer, yielding a zero surface potential at large areas per molecule. CAb remained at the interface even at high surface pressures, which allowed transfer of Langmuir-Blodgett (LB) films onto solid supports with the CAb-DMPA mixture. The mass transferred, according to quartz crystal microbalance (QCM) measurements, increased linearly with the number of deposited layers. With UV-vis absorption, fluorescence and FTIR spectroscopies, we confirmed that the LB films contain polysaccharides, proteins and DMPA. Therefore, the CAb biological action must be attributed not only to polysaccharides but also to proteins in the complex. (C) 2008 Elsevier Inc. All rights reserved.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Dendrimer-assisted immobilization of alcohol dehydrogenase in nanostructured films for biosensing: Ethanol detection using electrical capacitance measurements

The selective determination of alcohol molecules either in aqueous solutions or in vapor phase is of great importance for several technological areas. In the last years, a number of researchers have reported the fabrication of highly sensitive sensors for ethanol detection, based upon specific enzymatic reactions occurring at the surface of enzyme-containing electrodes. In this study, the enzyme alcohol dehydrogenase (ADH) was immobilized in a layer-by-layer fashion onto Au-interdigitated electrodes (IDEs), in conjunction with layers of PAMAM dendrimers. The immobilization process was followed in Teal time using quartz crystal microbalance (QCM), indicating that an average mass of 52.1 ng of ADH was adsorbed at each deposition step. Detection was carried out using a novel strategy entirely based upon electrical capacitance measurements, through which ethanol could be detected at concentrations of 1 part per million by volume (ppmv). (C) 2007 Elsevier B.V. All rights reserved.

Concentric characterization and classification of complex network nodes: Application to an institutional collaboration network

Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.

Complex networks analysis of manual and machine translations

Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.

A pattern recognition approach to complex networks

Complex networks exist in many areas of science such as biology, neuroscience, engineering, and sociology. The growing development of this area has led to the introduction of several topological and dynamical measurements, which describe and quantify the structure of networks. Such characterization is essential not only for the modeling of real systems but also for the study of dynamic processes that may take place in them. However, it is not easy to use several measurements for the analysis of complex networks, due to the correlation between them and the difficulty of their visualization. To overcome these limitations, we propose an effective and comprehensive approach for the analysis of complex networks, which allows the visualization of several measurements in a few projections that contain the largest data variance and the classification of networks into three levels of detail, vertices, communities, and the global topology. We also demonstrate the efficiency and the universality of the proposed methods in a series of real-world networks in the three levels.

The Catalytic Acid in the Dephosphorylation of the Cdk2-pTpY/CycA Protein Complex by Cdc25B Phosphatase

The development of anticancer therapeutics that target Cdc25 phosphatases is now an active area of research. A complete understanding of the Cdc25 catalytic mechanism would certainly allow a more rational inhibitor design. However, the identity of the catalytic acid used by Cdc25 has been debated and not established unambiguously. Results of molecular dynamics simulations with a calibrated hybrid potential for the first reaction step catalyzed by Cdc25B in complex with its natural substrate, the Cdk2-pTpY/CycA protein complex, are presented here. The calculated reaction free-energy profiles are in very good agreement with experimental measurements and are used to discern between different proposals for the general acid. In addition, the simulations give useful insight on interactions that can be explored for the design of inhibitors specific to Cdc25.

Under flow impedimetric measurements using magnetic particles for label-free detection affinity target

The necessity to adapt sensors based on electrochemical techniques for high throughput analysis control increases the interest to develop new analytical systems able to perform measurements under buffer now. In this report we explored the possibility of employing a new system to make impedimetric measurements to detect the interaction between proteins and small molecules. The well-known biotin-streptavidin interaction was adopted to evaluate the proposed assembly. This system allows us to perform experiments under flow. Magnetic beads functionalized with streptavidin were used and first characterized using AFM and FTIR. Non-faradic impedance spectroscopy allowed the detection of the biotin-streptavidin interaction. Using our new system and under a flow of PBS buffer, 5 10-5 M of biotin was detected with a stable signal. (c) 2007 Elsevier B.V. All rights reserved.

Evidences for charge-transfer complex formation in the benzene adsorption on sulfated TiO2-a resonance Raman spectroscopy investigation

Benzene adsorbed on highly acidic sulfated TiO2 (S-TiO2) shows an intriguing resonance Raman (RR) effect, with excitation in the blue-violet region. There are very interesting spectral features: the preferential enhancement of the e(2g) mode (1595 cm(-1)) in relation to the a(1g) mode (ring-breathing mode at 995 cm(-1)) and the appearance of bands at 1565 and 1514 cm(-1). The band at 1565 cm(-1) is probably one of the components of the e(2g) split band, originally a doubly degenerate mode (8a, 8b) in neat benzene, and the band at 1514 cm(-1) is assigned to the 19a mode, an inactive mode in neat benzene. These facts indicate a lowering of symmetry in adsorbed benzene, which may be caused by a strong interaction between S-TiO2 and the benzene molecule with formation of a benzene to Ti (IV) charge transfer (CT) complex or by the formation of a benzene radical cation species. However, the RR spectra of the adsorbed benzene cannot be assigned to the benzene radical cation because the observed wavenumber of the ring-breathing mode does not have the value expected for this species. Moreover, it was found by ESR measurements that the amount of radicals was very low, and so it was concluded that a CT complex is the species that originates the RR spectra. The most favorable intensification of the band at 1595 cm(-1) in the RR spectra of benzene/S-TiO2 at higher excitation energy corroborates this hypothesis, as an absorption band in this energy range, assigned to a CT transition, is observed. Copyright (C) 2008 John Wiley & Sons, Ltd.

Voltammetric determination of L-dopa using an electrode modified with trinuclear ruthenium ammine complex (Ru-red) supported on Y-type zeolite

The L-dopa is the immediate precursor of the neurotransmitter dopamine. Unlike dopamine, L-dopa easily enters the central nervous system and is used in the treatment of Parkinson's disease. A sensitive and selective method is presented for the voltammetric determination of L-dopa in pharmaceutical formulations using a carbon paste electrode modified with trinuclear ruthenium ammine complex [(NH3)(5)Ru-III-O-Ru-IV(NH3)(4)-O-Ru-III(NH3)(5)](6+) (Ru-red) incorporated in NaY zeolite. The parameters which influence on the electrode response (paste composition, potential scan rate, pH and interference) were also investigated. The optimum conditions were found to an electrode composition (m/m) of 25% zeolite containing 6.7% Ru, 50% graphite and 25% mineral oil in acetate buffer at pH 4.8. Voltammetric peak currents showed a linear response for L-dopa concentration in the range between 1.2 x 10(-4) and 1.0 x 10(-2) Mol l(-1) (r = 0.9988) with a detection limit of 8.5 x 10(-5) mol l(-1). The variation coefficient for a 1.0 x 10(-3) mol l(-1) L-dopa (n = 10) was 5.5%. The results obtained for L-dopa in pharmaceutical formulations (tablet) was in agreement with compared official method. In conclusion, this study has illustrated that the proposed electrode modified with Ru-red incorporated zeolite is suitable valuable for selective measurements of L-dopa. (C) 2004 Elsevier B.V. All rights reserved.

Molecularly organized Langmuir-Blodgett films from a ruthenium biphosphine complex

Langmuir-Blodgett (LB) films from a ruthenium complex mer-[RuCl3 (dppb)(4-Mepy)] (dppb = PPh2 (CH2)(4)-PPh2; 4-Mepy = 4-methylpyridine), termed Ru-Pic, display a distinct color, which is different from the coloration exhibited by cast films or chloroform solutions. The solution and cast films are red, while the LB films are green-bluish. The manifestation of the blue color in the LB film finds its explanation in a unique absorption band at 690 nm, which is associated with the oxidation of the phosphine moieties. Fluorescence emission and absorption-reflection infrared spectroscopy measurements revealed the molecular organization in the LB films. In contrast, cast films showed a random distribution of complexes. Surface-enhanced Raman scattering was also used in an attempt to identify the main interactions in Ru-Pic.