In-situ revascularisation for secondary aorto-enteric fistulae: the success of silver-coated Dacron is closely linked to a suitable bowel repair.

OBJECTIVES: The purpose of this study was to assess short- and mid-term results of in-situ revascularisation (ISR) using silver-coated Dacron prostheses and bowel repair for management of secondary aorto-enteric fistulae (SAEF). DESIGN: Single-centre retrospective chart review. MATERIAL AND METHODS: This study includes all the patients treated by ISR using silver-coated Dacron for SAEF between 2006 and 2010. Primary end points were mortality and survival rates. Secondary end points were reinfection-free survival and secondary patency rates. RESULTS: Eighteen male patients with SAEF with a median age of 64 years were operated by ISR using silver-coated Dacron during the study period without operative death. The 30-day mortality was 22% and the in-hospital mortality rate was 39%. Indeed, during hospitalisation, a duodenal leak was observed in four patients including three who died. Four others patients died due to multi-system organ failure. Median follow-up was 16 months (range 1-66). The survival rate at 12 months was 55%. One duodenal leak was observed leading to death. The reinfection-free survival and the secondary patency rates at 12 months were 60% and 89%, respectively. CONCLUSION: In-situ revascularisation with silver-coated Dacron provides acceptable results in terms of mortality. This treatment may be useful for simple vascular reconstruction and allow greater attention to bowel repair that is a determinant in short- and mid-term survival.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

Wet chemical silver treatment of endotracheal tubes to produce antibacterial surfaces.

Mechanically ventilated patients in hospitals are subjected to an increased risk of acquiring nosocomial pneumonia that sometimes has a lethal outcome. One way to minimize the risk could be to make the surfaces on endotracheal tubes antibacterial. In this study, bacterial growth was inhibited or completely prevented by silver ions wet chemically and deposited onto the tube surface. Through the wet chemical treatment developed here, a surface precipitate was formed containing silver chloride and a silver stearate salt. The identity and morphology of the surface precipitate was studied using x-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy, and x-ray powder diffraction. Leaching of silver ions into solution was examined, and bacterial growth on the treated surfaces was assayed using Pseudomonas aeruginosa wild type (PAO1) bacteria. Furthermore, the minimum inhibitory concentration of silver ions was determined in liquid- and solid-rich growth medium as 23 and 18 microM, respectively, for P. aeruginosa.

Social structure varies with elevation in an Alpine ant.

Insect societies vary greatly in social organization, yet the relative roles of ecological and genetic factors in driving this variation remain poorly understood. Identifying how social structure varies along environmental gradients can provide insights into the ecological conditions favouring alternative social organizations. Here, we investigate how queen number variation is distributed along elevation gradients within a socially polymorphic ant, the Alpine silver ant Formica selysi. We sampled low- and high-elevation populations in multiple Alpine valleys. We show that populations belonging to different drainage basins are genetically differentiated. In contrast, there is little genetic divergence between low- and high-elevation populations within the same drainage basin. Thus, elevation gradients in each of the drainage basins represent independent contrasts. Whatever the elevation, all well-sampled populations are socially polymorphic, containing both monogynous (= one queen) and polygynous (= multiple queen) colonies. However, the proportion of monogynous colonies per population increases at higher elevation, while the effective number of queens in polygynous colonies decreases, and this pattern is replicated in each drainage basin. The increased prevalence of colonies with a single queen at high elevation is correlated with summer and winter average temperature, but not with precipitation. The colder, unpredictable and patchy environment encountered at higher elevations may favour larger queens with the ability to disperse and establish incipient monogynous colonies independently, while the stable and continuous habitat in the lowlands may favour large, fast-growing polygynous colonies. By highlighting differences in the environmental conditions favouring monogynous or polygynous colonies, this study sheds light on the ecological factors influencing the distribution and maintenance of social polymorphism.

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

Silver nanoparticle production by the fungus Fusarium oxysporum: nanoparticle characterisation and analysis of antifungal activity against pathogenic yeasts

The microbial synthesis of nanoparticles is a green chemistry approach that combines nanotechnology and microbial biotechnology. The aim of this study was to obtain silver nanoparticles (SNPs) using aqueous extract from the filamentous fungus Fusarium oxysporum as an alternative to chemical procedures and to evaluate its antifungal activity. SNPs production increased in a concentration-dependent way up to 1 mM silver nitrate until 30 days of reaction. Monodispersed and spherical SNPs were predominantly produced. After 60 days, it was possible to observe degenerated SNPs with in additional needle morphology. The SNPs showed a high antifungal activity against Candida and Cryptococcus , with minimum inhibitory concentration values ≤ 1.68 µg/mL for both genera. Morphological alterations of Cryptococcus neoformans treated with SNPs were observed such as disruption of the cell wall and cytoplasmic membrane and lost of the cytoplasm content. This work revealed that SNPs can be easily produced by F. oxysporum aqueous extracts and may be a feasible, low-cost, environmentally friendly method for generating stable and uniformly sized SNPs. Finally, we have demonstrated that these SNPs are active against pathogenic fungi, such as Candida and Cryptococcus .

Efficiency of Gumbel analyses for determining extreme daily precipitation in Switzerland

Gumbel analyses were carried out on rainfall time-series at 151 locations in Switzerland for 4 different periods of 30 years in order to estimate daily extreme precipitation for a return period of 100 years. Those estimations were compared with maximal daily values measured during the last 100 years (1911-2010) to test the efficiency of these analyses. This comparison shows that these analyses provide good results for 50 to 60% locations in this country from rainfall time-series 1961-1990 and 1980-2010. On the other hand, daily precipitation with a return period of 100 years is underestimated at most locations from time-series 1931-1960 and especially 1911-1940. Such underestimation results from the increase of maximal daily precipitation recorded from 1911 to 2010 at 90% locations in Switzerland.

Spatial relationship between the atmospheric circulation and the precipitation measured in the western Swiss Alps by means of the analogue method

An adaptation technique based on the synoptic atmospheric circulation to forecast local precipitation, namely the analogue method, has been implemented for the western Swiss Alps. During the calibration procedure, relevance maps were established for the geopotential height data. These maps highlight the locations were the synoptic circulation was found of interest for the precipitation forecasting at two rain gauge stations (Binn and Les Marécottes) that are located both in the alpine Rhône catchment, at a distance of about 100 km from each other. These two stations are sensitive to different atmospheric circulations. We have observed that the most relevant data for the analogue method can be found where specific atmospheric circulation patterns appear concomitantly with heavy precipitation events. Those skilled regions are coherent with the atmospheric flows illustrated, for example, by means of the back trajectories of air masses. Indeed, the circulation recurrently diverges from the climatology during days with strong precipitation on the southern part of the alpine Rhône catchment. We have found that for over 152 days with precipitation amount above 50 mm at the Binn station, only 3 did not show a trajectory of a southerly flow, meaning that such a circulation was present for 98% of the events. Time evolution of the relevance maps confirms that the atmospheric circulation variables have significantly better forecasting skills close to the precipitation period, and that it seems pointless for the analogue method to consider circulation information days before a precipitation event as a primary predictor. Even though the occurrence of some critical circulation patterns leading to heavy precipitation events can be detected by precursors at remote locations and 1 week ahead (Grazzini, 2007; Martius et al., 2008), time extrapolation by the analogue method seems to be rather poor. This would suggest, in accordance with previous studies (Obled et al., 2002; Bontron and Obled, 2005), that time extrapolation should be done by the Global Circulation Model, which can process atmospheric variables that can be used by the adaptation method.

Metallic and nonmetallic shine in luster: An elastic ion backscattering study

Luster is a metal glass nanocomposite layer first produced in the Middle East in early Islamic times ( 9th AD) made of metal copper or silver nanoparticles embedded in a silica-based glassy matrix. These nanoparticles are produced by ion exchange between Cu+ and Ag+ and alkaline ions from the glassy matrix and further growth in a reducing atmosphere. The most striking property of luster is its capability of reflecting light like a continuous metal layer and it was unexpectedly found to be linked to one single production parameter: the presence of lead in the glassy matrix composition. The purpose of this article is to describe the characteristics and differences of the nanoparticle layers developed on lead rich and lead free glasses. Copper luster layers obtained using the ancient recipes and methods are analyzed by means of elastic ion backscattering spectroscopy associated with other analytical techniques. The depth profile of the different elements is determined, showing that the luster layer formed in lead rich glasses is 5–6 times thinner and 3–4 times Cu richer. Therefore, the metal nanoparticles are more densely packed in the layer and this fact is related to its higher reflectivity. It is shown that lead influences the structure of the metal nanoparticle layer through the change of the precipitation kinetics

City of Silver City, Auditor of State's Report on Reaudit, For the Period July 1, 2002 through June 30, 2003

City Audit Report

Generation of Simulated Daily Precipitation and Air and Soil Temperatures, January 2000

This paper describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Parameter estimates are reported for Brookings, SD, and Boone, IA, to illustrate the procedure. The use of this parametric model to generate stochastic time series of daily weather is then summarized. A soil temperature model is described that determines daily average, maximum, and minimum soil temperatures based on air temperatures and precipitation, following a lagged process due to soil heat storage and other factors.

Silver space-time trellis-coded modulation

Silver Code (SilC) was originally discovered in [1–4] for 2×2 multiple-input multiple-output (MIMO) transmission. It has non-vanishing minimum determinant 1/7, slightly lower than Golden code, but is fast-decodable, i.e., it allows reduced-complexity maximum likelihood decoding [5–7]. In this paper, we present a multidimensional trellis-coded modulation scheme for MIMO systems [11] based on set partitioning of the Silver Code, named Silver Space-Time Trellis Coded Modulation (SST-TCM). This lattice set partitioning is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions. Viterbi algorithm is applied for trellis decoding, while the branch metrics are computed by using a sphere-decoding algorithm. It is shown that the proposed SST-TCM performs very closely to the Golden Space-Time Trellis Coded Modulation (GST-TCM) scheme, yetwith a much reduced decoding complexity thanks to its fast-decoding property.

Cooperative Lakes Area Monitoring Project-Silver Lake, 2007

Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.