Environmental factors shaping the distribution of common wintering waterbirds in a lake ecosystem with developed shoreline

In this study, we tested whether the spatial distribution of waterbirds is influenced by shoreline urbanization or other habitat characteristics. We conducted monthly censuses along shoreline sections of a continental lake (Lake Balaton, Hungary) to assess the abundance of 11 common species that use this lake as a feeding and staging area during migration and winter. We estimated the degree of urbanization of the same shoreline sections and also measured other habitat characteristics (water depth, extent of reed cover, biomass of zebra mussels, distances to waste dumps and to other wetlands). We applied linear models and model averaging to identify habitat variables with high relative importance for predicting bird distributions. Bird abundance and urbanization were strongly related only in one species. Other habitat variables exhibited stronger relationships with bird distribution: (1) diving ducks and coots preferred shoreline sections with high zebra mussel biomass, (2) gulls preferred sites close to waste dumps, and (3) the abundances of several species were higher on shoreline sections close to other wetlands. Our findings suggest that the distribution of waterbirds on Lake Balaton is largely independent of shoreline urbanization and influenced by food availability and connectivity between wetlands

Estimation of protein secondary structure from FTIR spectra using neural networks.

Secondary structure of proteins have been predicted using neural networks (NN) from their Fourier transform infrared spectra. Leave-one-out approach has been used to demonstrate the applicability of the method. A form of cross-validation is used to train NN to prevent the overfitting problem. Multiple neural network outputs are averaged to reduce the variance of predictions. The networks realized have been tested and rms errors of 7.7% for alpha -helix, 6.4% for beta -sheet and 4.8% for turns have been achieved. These results indicate that the methodology introduced is effective and estimation accuracies are in some cases better than those previously reported in the literature

Using artificially generated spectral data to improve protein secondary structure prediction from Fourier transform infrared spectra of proteins.

Secondary structures of proteins have been predicted using neural networks from their Fourier transform infrared spectra. To improve the generalization ability of the neural networks, the training data set has been artificially increased by linear interpolation. The leave-one-out approach has been used to demonstrate the applicability of the method. Bayesian regularization has been used to train the neural networks and the predictions have been further improved by the maximum-likelihood estimation method. The networks have been tested and standard error of prediction (SEP) of 4.19% for alpha helix, 3.49% for beta sheet, and 3.15% for turns have been achieved. The results indicate that there is a significant decrease in the SEP for each type of structure parameter compared to previous works

Structural and mechanical characteristics of nanohydroxyapatite doped with zinc and chloride

In this study, hydroxylapatite (HA) doped with Zn2+ and/or Cl- ions was synthesised by precipitation method and sintered at 1100 degrees C for 1 h. Densities of the samples were measured by the Archimedes method. Zn2+ addition increased the density significantly, while Cl- increased the density insignificantly. Hydroxylapatite phase and inconsiderable amount of CaO phase were detected in some samples according to the X-ray diffraction results. Cl- added samples (2.5 mol.-%) increased the hexagonal unit cell volume of HA. Characteristic PO43- and OH- bands of HA were detected in Fourier transform infrared spectroscopy. Cl- related band was also observed at a wavenumber of 3497 cm(-1). Grain sizes of the samples decreased with Cl- addition and increased with Zn2+ addition according to the SEM images. Zn2+ and Cl- addition improved the microhardness of pure HA. Fracture toughness of the samples decreased with Cl- and Zn2+ addition. When compared with other compositions, 2Zn2.5ClHA produced the best results in terms of mechanical properties

Melatonin strongly interacts with zwitterionic model membranes-evidence from Fourier transform infrared spectroscopy and differential scanning calorimetry

PubMed ID: 15737332Interactions of melatonin with zwitterionic dipalmitoyl phosphatidylcholine (DPPC) multilamellar liposomes (MLVs) were investigated as a function of temperature and melatonin concentration (1-30 mol%) by using two noninvasive techniques, namely Fourier transform infrared (FTIR) spectroscopy and differential scanning calorimetry (DSC). The investigation of the C-H, CO, and PO2 - antisymmetric double stretching modes in FTIR spectra and DSC studies reveal that melatonin changes the physical properties of the DPPC bilayers by decreasing the main phase transition temperature, abolishing the pretransition, ordering the system in the gel phase, and increasing the dynamics of the system both in the gel and liquid crystalline phases. It also causes significant decrease in the wavenumber for the CO stretching and PO 2 - antisymmetric double bond stretching bands, which indicates strong hydrogen bonding The results imply that melatonin locates in the interfacial region of the membrane. Furthermore, in the DSC curve, more than one signal is observed at high melatonin concentrations (24 and 30 mol%), which indicates melatonin-induced phase separation in DPPC membranes. © 2005 Elsevier B.V. All rights reserved.BAP-01-08-DPT.2003K120920-13 Ege ÜniversitesiThis work was supported by Ege University Research Fund 2001 Fen 069 and State Planning Organization of Turkey (PROJECT No: BAP-01-08-DPT.2003K120920-13). -