Whiskers, cones and pyramids created in sputtering by ion bombardment

A thorough study of the role which foreign atoms play in cone formation during sputtering of metals revealed many experimental facts. Two types of cone formation were distinquished, deposit cones and seed cones. Twenty-six combinations of metals for seed cone formation were tested. The sputtering yield variations with composition for combinations which form seed cones were measured. It was demonstrated that whisker growth becomes a common occurrence when low melting point material is sputter deposited on a hot nonsputtered high melting point electrode

Investigation of sputtering effects on the moon's surface Eleventh quarterly status report, 25 Oct. 1965 - 24 Jan. 1966

Implications of Lunar 9 moon probe, sputtering yield reduction due to surface roughness, water formation by solar wind bombardment, photometric function of moon, and chemical sputterin

A model of ant route navigation driven by scene familiarity

In this paper we propose a model of visually guided route navigation in ants that captures the known properties of real behaviour whilst retaining mechanistic simplicity and thus biological plausibility. For an ant, the coupling of movement and viewing direction means that a familiar view specifies a familiar direction of movement. Since the views experienced along a habitual route will be more familiar, route navigation can be re-cast as a search for familiar views. This search can be performed with a simple scanning routine, a behaviour that ants have been observed to perform. We test this proposed route navigation strategy in simulation, by learning a series of routes through visually cluttered environments consisting of objects that are only distinguishable as silhouettes against the sky. In the first instance we determine view familiarity by exhaustive comparison with the set of views experienced during training. In further experiments we train an artificial neural network to perform familiarity discrimination using the training views. Our results indicate that, not only is the approach successful, but also that the routes that are learnt show many of the characteristics of the routes of desert ants. As such, we believe the model represents the only detailed and complete model of insect route guidance to date. What is more, the model provides a general demonstration that visually guided routes can be produced with parsimonious mechanisms that do not specify when or what to learn, nor separate routes into sequences of waypoints

Investigation of sputtering effects on the moon's surface Quarterly status report, 25 Apr. - 2 Sep. 1966

Sputtering effects from solar wind on lunar surface investigated by ion bombardment of metal powde

Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets

Identifying weather patterns that frequently lead to extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Here, we propose an automated method for recognizing atmospheric rivers (ARs) in climate data using topological data analysis and machine learning. The method provides useful information about topological features (shape characteristics) and statistics of ARs. We illustrate this method by applying it to outputs of version 5.1 of the Community Atmosphere Model version 5.1 (CAM5.1) and the reanalysis product of the second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). An advantage of the proposed method is that it is threshold-free – there is no need to determine any threshold criteria for the detection method – when the spatial resolution of the climate model changes. Hence, this method may be useful in evaluating model biases in calculating AR statistics. Further, the method can be applied to different climate scenarios without tuning since it does not rely on threshold conditions. We show that the method is suitable for rapidly analyzing large amounts of climate model and reanalysis output data.</p

Active machine learning for transmembrane helix prediction

Abstract Background About 30% of genes code for membrane proteins, which are involved in a wide variety of crucial biological functions. Despite their importance, experimentally determined structures correspond to only about 1.7% of protein structures deposited in the Protein Data Bank due to the difficulty in crystallizing membrane proteins. Algorithms that can identify proteins whose high-resolution structure can aid in predicting the structure of many previously unresolved proteins are therefore of potentially high value. Active machine learning is a supervised machine learning approach which is suitable for this domain where there are a large number of sequences but only very few have known corresponding structures. In essence, active learning seeks to identify proteins whose structure, if revealed experimentally, is maximally predictive of others. Results An active learning approach is presented for selection of a minimal set of proteins whose structures can aid in the determination of transmembrane helices for the remaining proteins. TMpro, an algorithm for high accuracy TM helix prediction we previously developed, is coupled with active learning. We show that with a well-designed selection procedure, high accuracy can be achieved with only few proteins. TMpro, trained with a single protein achieved an F-score of 94% on benchmark evaluation and 91% on MPtopo dataset, which correspond to the state-of-the-art accuracies on TM helix prediction that are achieved usually by training with over 100 training proteins. Conclusion Active learning is suitable for bioinformatics applications, where manually characterized data are not a comprehensive representation of all possible data, and in fact can be a very sparse subset thereof. It aids in selection of data instances which when characterized experimentally can improve the accuracy of computational characterization of remaining raw data. The results presented here also demonstrate that the feature extraction method of TMpro is well designed, achieving a very good separation between TM and non TM segments

Organsko-geohemijska korelacija nekih nafti depresije Drmno (južni deo panonskog basena, Jugoslavija)

The results of an investigation of crude oils originating from the Sirakovo and Bradarac-Maljurevac localities (southern part of the Pannonian Basin) are reported in this paper. The aim was to estimate the organic geochemical similarity of the crude oils fi om the DI mno (Kostolac) depression oil fields. The nine selected samples originated from reservoir. rocks of various depths. Reliable source and organic geochemical maturation parameters served as the basis for the correlation studies. The similar origin of the investigated DI mno depression crude oils was corroborated, characterized by a significant participation of terrestrial precursor biomass. They were shown to be of relatively low maturity and to have been formed during the earlier stages of the diagenet- ic-catagenetic sequence of processes leading to the formation of crude oils, most probably in source rocks of Tertiary age, corresponding to vitrinite reflectances between Ro = 0.70 % and Ro = 0.80%. The crude oils from Bradarac-Maljurevac seemed to be somewhat less homogeneous with respect to organic geochemical parameters compared to Sirakovo crude oils.U ovom radu ispitivani su uzorci sirovih nafti depresije Drmno (Kostolac) sa lokaliteta Sirakovo i Bradarac-Maljurevac. Cilj rada bio je da se proceni organsko-geohemijska ujednačenost nafti naftnih polja depresije Drmno. Izabrani su uzorci koji potiču iz rezervoarskih stena sa različitih dubina i u njima su određeni grupni i specifični izvorni i maturacioni organsko-geohemijski parametri. Potvrđeno je da ispitivani uzorci depresije Drmno imaju slično poreklo koje karakteriše veći udeo terestrijalne prekursorske biomase. Ispitivane nafte su nešto nižeg stepena maturisanosti i nastale su u ranijim fazama dijagenetsko-katagenetske sekvencije formiranja nafte kojima odgovaraju vrednosti refleksije vitrinita između Ro = 0,70 % i Ro = 0,80 %. Najverovatnije su nastale u izvornim stenama tercijarne starosti. Nafte sa lokaliteta Bradarac-Maljurevac karakteriše nešto niži nivo organsko-geohemijske homogenosti nego nafte sa lokaliteta Sirakovo

Sensitivity of Tropical Cyclone Rainfall to Idealized Global Scale Forcings

Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socio-economic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date, and still represents a major challenge. Our capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by our understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here we use a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. CLIVAR Hurricane Working Group activity to examine TC response to idealized global-scale perturbations: the doubling of CO2, uniform 2K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO2 scenario (on the order of 5% globally), and an increase in TC rainfall rates associated with a uniform increase of 2K in SST (both alone and in combination with CO2 doubling; on the order of 10-20% globally)

Quasi-Elastic Scattering, Random Fields and phonon-coupling effects in PbMg1/3Nb2/3O3

The low-energy part of the vibration spectrum in PbMg$_{1/3}$Nb$_{2/3}$O$_3$ (PMN) relaxor ferroelectric has been studied by neutron scattering above and below the Burns temperature, T$_d$. The transverse acoustic and the lowest transverse optic phonons are strongly coupled and we have obtained a model for this coupling. We observe that the lowest optic branch is always underdamped. A resolution-limited central peak and quasi-elastic scattering appear in the vicinity of the Burns temperature. It is shown that it is unlikely that the quasi-elastic scattering originates from the combined effects of coupling between TA and TO phonons with an increase of the damping of the TO phonon below T$_d$. The quasi-elastic scattering has a peak as a function of temperature close to the peak in the dielectric constant while the intensity of the central peak scattering increases strongly below this temperature. These results are discussed in terms of a random field model for relaxors

Identification of genomic regions involved in tolerance to drought stress and drought stress induced leaf senescence in juvenile barley

BACKGROUND: Premature leaf senescence induced by external stress conditions, e.g. drought stress, is a main factor for yield losses in barley. Research in drought stress tolerance has become more important as due to climate change the number of drought periods will increase and tolerance to drought stress has become a goal of high interest in barley breeding. Therefore, the aim is to identify quantitative trait loci (QTL) involved in drought stress induced leaf senescence and drought stress tolerance in early developmental stages of barley (Hordeum vulgare L.) by applying genome wide association studies (GWAS) on a set of 156 winter barley genotypes. RESULTS: After a four weeks stress period (BBCH 33) leaf colour as an indicator of leaf senescence, electron transport rate at photosystem II, content of free proline, content of soluble sugars, osmolality and the aboveground biomass indicative for drought stress response were determined in the control and stress variant in greenhouse pot experiments. Significant phenotypic variation was observed for all traits analysed. Heritabilities ranged between 0.27 for osmolality and 0.61 for leaf colour in stress treatment and significant effects of genotype, treatment and genotype x treatment were estimated for most traits analysed. Based on these phenotypic data and 3,212 polymorphic single nucleotide polymorphisms (SNP) with a minor allele frequency >5 % derived from the Illumina 9 k iSelect SNP Chip, 181 QTL were detected for all traits analysed. Major QTLs for drought stress and leaf senescence were located on chromosome 5H and 2H. BlastX search for associated marker sequences revealed that respective SNPs are in some cases located in proteins related to drought stress or leaf senescence, e.g. nucleotide pyrophosphatase (AVP1) or serine/ threonin protein kinase (SAPK9). CONCLUSIONS: GWAS resulted in the identification of many QTLs involved in drought stress and leaf senescence of which two major QTLs for drought stress and leaf senescence were located on chromosome 5H and 2H. Results may be the basis to incorporate breeding for tolerance to drought stress or leaf senescence in barley breeding via marker based selection procedures. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-015-0524-3) contains supplementary material, which is available to authorized users