52,563 research outputs found

    Variability of the winter wind waves and swell in the North Atlantic and North Pacific as revealed by the Voluntary Observing Ship data

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    This paper analyses secular changes and interannual variability in the wind wave, swell, and significant wave height (SWH) characteristics over the North Atlantic and North Pacific on the basis of wind wave climatology derived from the visual wave observations of voluntary observing ship (VOS) officers. These data are available from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) collection of surface meteorological observations for 1958–2002, but require much more complicated preprocessing than standard meteorological variables such as sea level pressure, temperature, and wind. Visual VOS data allow for separate analysis of changes in wind sea and swell, as well as in significant wave height, which has been derived from wind sea and swell estimates. In both North Atlantic and North Pacific midlatitudes winter significant wave height shows a secular increase from 10 to 40 cm decade−1 during the last 45 yr. However, in the North Atlantic the patterns of trend changes for wind sea and swell are quite different from each other, showing opposite signs of changes in the northeast Atlantic. Trend patterns of wind sea, swell, and SWH in the North Pacific are more consistent with each other. Qualitatively the same conclusions hold for the analysis of interannual variability whose leading modes demonstrate noticeable differences for wind sea and swell. Statistical analysis shows that variability in wind sea is closely associated with the local wind speed, while swell changes can be driven by the variations in the cyclone counts, implying the importance of forcing frequency for the resulting changes in significant wave height. This mechanism of differences in variability patterns of wind sea and swell is likely more realistic than the northeastward propagation of swells from the regions from which the wind sea signal originates

    Two hard spheres in a pore: Exact Statistical Mechanics for different shaped cavities

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    The Partition function of two Hard Spheres in a Hard Wall Pore is studied appealing to a graph representation. The exact evaluation of the canonical partition function, and the one-body distribution function, in three different shaped pores are achieved. The analyzed simple geometries are the cuboidal, cylindrical and ellipsoidal cavities. Results have been compared with two previously studied geometries, the spherical pore and the spherical pore with a hard core. The search of common features in the analytic structure of the partition functions in terms of their length parameters and their volumes, surface area, edges length and curvatures is addressed too. A general framework for the exact thermodynamic analysis of systems with few and many particles in terms of a set of thermodynamic measures is discussed. We found that an exact thermodynamic description is feasible based in the adoption of an adequate set of measures and the search of the free energy dependence on the adopted measure set. A relation similar to the Laplace equation for the fluid-vapor interface is obtained which express the equilibrium between magnitudes that in extended systems are intensive variables. This exact description is applied to study the thermodynamic behavior of the two Hard Spheres in a Hard Wall Pore for the analyzed different geometries. We obtain analytically the external work, the pressure on the wall, the pressure in the homogeneous zone, the wall-fluid surface tension, the line tension and other similar properties

    The Prevalence and Control of Bacillus and Related Spore-Forming Bacteria in the Dairy Industry

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    peer-reviewedMilk produced in udder cells is sterile but due to its high nutrient content, it can be a good growth substrate for contaminating bacteria. The quality of milk is monitored via somatic cell counts and total bacterial counts, with prescribed regulatory limits to ensure quality and safety. Bacterial contaminants can cause disease, or spoilage of milk and its secondary products. Aerobic spore-forming bacteria, such as those from the genera Sporosarcina, Paenisporosarcina, Brevibacillus, Paenibacillus, Geobacillus and Bacillus, are a particular concern in this regard as they are able to survive industrial pasteurization and form biofilms within pipes and stainless steel equipment. These single or multiple-species biofilms become a reservoir of spoilage microorganisms and a cycle of contamination can be initiated. Indeed, previous studies have highlighted that these microorganisms are highly prevalent in dead ends, corners, cracks, crevices, gaskets, valves and the joints of stainless steel equipment used in the dairy manufacturing plants. Hence, adequate monitoring and control measures are essential to prevent spoilage and ensure consumer safety. Common controlling approaches include specific cleaning-in-place processes, chemical and biological biocides and other novel methods. In this review, we highlight the problems caused by these microorganisms, and discuss issues relating to their prevalence, monitoring thereof and control with respect to the dairy industry.NG is funded by the Teagasc Walsh Fellowship Scheme and through the Irish Dairy Levy funded project ‘Thermodur-Out.

    Remote sensing for Mapping TSM concentration in Mahakam Delta: an analytical approach

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    The Indonesian coastal zones have always been under heavy pressures, including those from fisheries, oil industries and sea transportation. The presence of these activities carry a large portion of risk in damaging the environment as well as in destroying the marine resources, leading to the need for an integrated management approach based on an environmental information system that is comprehensive and multi-disciplinary in nature. The Mahakam Delta has the same general problems as other coastal regions in Indonesia. The method is based on bio optical modeling. The forward water analysis comprised the laboratory measurements of water quality (TSM and Chl) and Inherent Optical Properties (IOPs) to derive Spesific Inherent Optical properties (SIOPs). SIOPs (of water, TSM, Chl and CDOM), coefficient f and B were used to developed R(0-) model. The inverse atmosphere analysis comprised the image preprocessing (i.e. geometric correction, atmospheric correction, air-water interface correction). The last step is inverse water analysis, which comprised the development of algorithm and image processing to develop TSM concentration maps. The spectrometer measurements collected in the field were used for obtaining the subsurface irradiance reflectance. The subsurface irradiance reflectance R(0-) is the ratio of upwelling (Ewu) and downwelling irradiance (Ewd) just beneath the water surface. There are some discrepancies from matching R(0-) model and R(0-) measured in the field, especially in the blue region and NIR region. The reason of the discrepancies could be due to the fact that the Q factor (the angular distribution factor of spectral radiance) is still not understood completely. This model is very susceptible to the decrease of the proportional factor f, and to the increase of the backscattering probability B. The results indicates that red band of satellite sensor is sensitive to detect higher TSM concentration. For Mahakam Delta, red band algorithm was used to derive TSM map, since higher TSM concentration occurred in the delta

    A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration

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    Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep learning methods, notably convolutional neural networks (ConvNets), can be used for image registration. Thus far training of ConvNets for registration was supervised using predefined example registrations. However, obtaining example registrations is not trivial. To circumvent the need for predefined examples, and thereby to increase convenience of training ConvNets for image registration, we propose the Deep Learning Image Registration (DLIR) framework for \textit{unsupervised} affine and deformable image registration. In the DLIR framework ConvNets are trained for image registration by exploiting image similarity analogous to conventional intensity-based image registration. After a ConvNet has been trained with the DLIR framework, it can be used to register pairs of unseen images in one shot. We propose flexible ConvNets designs for affine image registration and for deformable image registration. By stacking multiple of these ConvNets into a larger architecture, we are able to perform coarse-to-fine image registration. We show for registration of cardiac cine MRI and registration of chest CT that performance of the DLIR framework is comparable to conventional image registration while being several orders of magnitude faster.Comment: Accepted: Medical Image Analysis - Elsevie

    Development and Application of a Statistically-Based Quality Control for Crowdsourced Air Temperature Data

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    In urban areas, dense atmospheric observational networks with high-quality data are still a challenge due to high costs for installation and maintenance over time. Citizen weather stations (CWS) could be one answer to that issue. Since more and more owners of CWS share their measurement data publicly, crowdsourcing, i.e., the automated collection of large amounts of data from an undefined crowd of citizens, opens new pathways for atmospheric research. However, the most critical issue is found to be the quality of data from such networks. In this study, a statistically-based quality control (QC) is developed to identify suspicious air temperature (T) measurements from crowdsourced data sets. The newly developed QC exploits the combined knowledge of the dense network of CWS to statistically identify implausible measurements, independent of external reference data. The evaluation of the QC is performed using data from Netatmo CWS in Toulouse, France, and Berlin, Germany, over a 1-year period (July 2016 to June 2017), comparing the quality-controlled data with data from two networks of reference stations. The new QC efficiently identifies erroneous data due to solar exposition and siting issues, which are common error sources of CWS. Estimation of T is improved when averaging data from a group of stations within a restricted area rather than relying on data of individual CWS. However, a positive deviation in CWS data compared to reference data is identified, particularly for daily minimum T. To illustrate the transferability of the newly developed QC and the applicability of CWS data, a mapping of T is performed over the city of Paris, France, where spatial density of CWS is especially high.DFG, 322579844, Hitzewellen in Berlin, Deutschland - StadtklimamodifkationenBMBF, 01LP1602A, Verbundprojekt Stadtklima: Evaluierung von Stadtklimamodellen (Modul B), 3DO Teilprojekt 1: Dreidimensionales Monitoring atmosphärischer Prozesse in Berli

    Correspondence in OT syntax and minimal link effects

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    The aim of this paper is the exploration of an optimality theoretic architecture for syntax that is guided by the concept of "correspondence": syntax is understood as the mechanism of "translating" underlying representations into a surface form. In minimalism, this surface form is called "Phonological Form" (PF). Both semantic and abstract syntactic information are reflected by the surface form. The empirical domain where this architecture is tested are minimal link effects, especially in the case of "wh"-movement. The OT constraints require the surface form to reflect the underlying semantic and syntactic representations as maximally as possible. The means by which underlying relations and properties are encoded are precedence, adjacency, surface morphology and prosodic structure. Information that is not encoded in one of these ways remains unexpressed, and gets lost unless it is recoverable via the context. Different kinds of information are often expressed by the same means. The resulting conflicts are resolved by the relative ranking of the relevant correspondence constraints

    Biopolymer-based structuring of liquid oil into soft solids and oleogels using water-continuous emulsions as templates

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    Physical trapping of a hydrophobic liquid oil in a matrix of water-soluble biopolymers was achieved using a facile two-step process by first formulating a surfactant-free oil-in-water emulsion stabilized by biopolymers (a protein and a polysaccharide) followed by complete removal of the water phase (by either high- or low-temperature drying of the emulsion) resulting in structured solid systems containing a high concentration of liquid oil (above 97 wt %). The microstructure of these systems was revealed by confocal and cryo-scanning electron microscopy, and the effect of biopolymer concentrations on the consistency of emulsions as well as the dried product was evaluated using a combination of small-amplitude oscillatory shear rheometry and large deformation fracture studies. The oleogel prepared by shearing the dried product showed a high gel strength as well as a certain degree of thixotropic recovery even at high temperatures. Moreover, the reversibility of the process was demonstrated by shearing the dried product in the presence of water to obtain reconstituted emulsions with rheological properties comparable to those of the fresh emulsion
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