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Monthly near-surface temperature anomalies from several gridded datasets (GISTEMP, Berkeley Earth, MLOST, HadCRUT4, 20th Century Reanalysis) were investigated and compared with regard to the presence of components attributable to external climate forcings (anthropogenic, solar and volcanic) and to major internal climate variability modes (El Niño/Southern Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation and variability characterized by the Trans-Polar Index). Multiple linear regression was used to separate components related to individual explanatory variables in local monthly temperatures as well as in their global means, over the 1901-2010 period. Strong correlations of temperature and anthropogenic forcing were confirmed for most of the globe, whereas only weaker and mostly statistically insignificant connections to solar activity were indicated. Imprints of volcanic forcing were found to be largely insignificant in the local temperatures, in contrast to the clear volcanic signature in their global averages. An attention was also paid to the manifestations of short-term time shifts in the responses to the forcings, and to differences in the spatial fingerprints detected from individual temperature datasets: it is shown that although the resemblance of the response patterns is usually strong, some regional contrasts appear. Noteworthy differences from the other datasets were found especially for the 20th Century Reanalysis, particularly for the components attributable to anthropogenic and volcanic forcing over land, but also in some of the teleconnection patterns related to the internal variability modes. [ABSTRACT FROM AUTHOR]

Abstract: Hydroxyapatite layers with silver doping from 0.06at.% to 14at.% were prepared by laser deposition. The films'' physical properties such as morphology, composition, crystallinity, Young''s modulus and microhardness were measured. Films were amorphous or polycrystalline in dependence on deposition temperature (from RT to 600°C). Antibacterial properties were tested using Escherichia coli and Bacillus subtilis cells. The antibacterial efficacy changed with silver doping from 4% to 100%. Cytotoxicity was studied by a direct contact test. Depending on doping and crystallinity the films were either non-toxic or mildly toxic. [Copyright &y& Elsevier]

Diamond-like carbon (DLC) thin films are frequently used for coating of implants. The problem of DLC layers lies in bad layer adhesion to metal implants. Chromium is used as a dopant for improvement of adhesion of DLC films. DLC and Cr-DLC layers were deposited on silicon, Ti6Al4V and CoCrMo substrates by a hybrid technology using combination of pulsed laser deposition (PLD) and magnetron sputtering. The topology of layers was studied using SEM, AFM and mechanical profilometer. Carbon and chromium content and concentration of trivalent and toxic hexavalent chromium bonds were determined by XPS and WDS. It follows from the scratch tests that Cr doping improved adhesion of DLC layers. Ethylene glycol, diiodomethane and deionized water were used to measure the contact angles. The surface free energy (SFE) was calculated. The antibacterial properties were studied using Pseudomonas aeruginosa and Staphylococcus aureus bacteria. The influence of SFE, hydrophobicity and surface roughness on antibacterial ability of doped layers is discussed., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Initial errors in weather prediction grow in time and, as they become larger, their growth slows down and then stops at an asymptotic value. Time of reaching this saturation point represents the limit of predictability. This paper studies the asymptotic values and time limits in a chaotic atmospheric model for five initial errors, using ensemble prediction method (model's data) as well as error approximation by quadratic and logarithmic hypothesis and their modifications. We show that modified hypotheses approximate the model's time limits better, but not without serious disadvantages. We demonstrate how hypotheses can be further improved to achieve better match of time limits with the model. We also show that quadratic hypothesis approximates the model's asymptotic value best and that, after improvement, it also approximates the model's time limits better for almost all initial errors and time lengths.