809 research outputs found
An Innovative Dynamic Test Method for Piles
The system described involves using solid propellant fuels to accelerate a reaction mass of the test pile. The force required to accelerate the reaction mass upwards acts equally downward on the pile. Very high forces be may applied to the pile in a controlled, linearly increasing manner. The duration of the applied load is approximately 100 milliseconds. This rate of loading is slow enough to allow the pile and soil to react together as a composite rigid body. The effects combine to produce pile and soil response no longer dominated by the transfer of force via stress pulse (as with impact). State of the art instrumentation systems are used to obtain test data. Displacement is monitored directly using a laser datum and integrated receiver located at the center axis of the pile. Force is also monitored directly using a calibrated load cell
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Application of Sentinel-2A data for pasture biomass monitoring using a physically based radiative transfer model
A large proportion of the global land surface is covered by pasture. The advent of the Sentinel satellites program provides free datasets with good spatiotemporal resolution that can be a valuable source of information for monitoring pasture resources. We combined optical remote sensing data (proximal hyperspectral and Sentinel 2A) with a radiative transfer model (PROSAIL) to estimate leaf area index (LAI), and biomass, in a dairy farming context. Three sites in Southern England were used: two pasture farms that differed in pasture type and management, and a set of small agronomy trial plots with different mixtures of grasses, legumes and herbs, as well as pure perennial ryegrass. The proximal and satellite spectral data were used to retrieve LAI via PROSAIL model inversion, which were compared against field observations of LAI. The potential of bands of Sentinel 2A that corresponded with a 10 m resolution was studied by convolving narrow spectral bands (from a handheld hyperspectral sensor) into Sentinel 2A bands (10 m). Retrieved LAI, using these spectrally resampled S2A data, compared well with measured LAI, for all sites, even for those with mixed species cover (although retrieved LAI was somewhat overestimated for pasture mixtures with high LAI). This proved the suitability of 10 m Sentinel 2A spectral bands for capturing LAI dynamics for different types of pastures. We also found that inclusion of 20 m bands in the inversion scheme did not lead to any further improvement in retrieved LAI. Sentinel 2A image based retrieval yielded good agreement with LAI measurements obtained for a typical perennial ryegrass based pasture farm. LAI retrieved in this way was used to create biomass maps (that correspond to indirect biomass measurements by Rising Plate Meter (RPM)), for mixed-species paddocks for a farm for which limited field data were available. These maps compared moderately well with farmer-collected RPM measurements for this farm. We propose that estimates of paddock-averaged and within-paddock variability of biomass are more reliably obtained from a combined Sentinel 2A-PROSAIL approach, rather than by manual RPM measurements. The physically based radiative transfer model inversion approach outperformed the Normalised Difference Vegetation Index based retrieval method, and does not require site specific calibrations of the inversion scheme
The Roots of Diversity: Below Ground Species Richness and Rooting Distributions in a Tropical Forest Revealed by DNA Barcodes and Inverse Modeling
F. Andrew Jones is with the Smithsonian Tropical Research Institute, David L. Erickson is with the Smithsonian Institution, Moises A. Bernal is with the Smithsonian Tropical Research Institute and UT Austin, Eldredge Bermingham is with the Smithsonian Tropical Research Institute, W. John Kress is with the Smithsonian Institution, Edward Allen Herre is with the Smithsonian Tropical Research Institute, Helene C. Muller-Landau is with the Smithsonian Tropical Research Institute, Benjamin L. Turner is with the Smithsonian Tropical Research Institute.Background -- Plants interact with each other, nutrients, and microbial communities in soils through extensive root networks. Understanding these below ground interactions has been difficult in natural systems, particularly those with high plant species diversity where morphological identification of fine roots is difficult. We combine DNA-based root identification with a DNA barcode database and above ground stem locations in a floristically diverse lowland tropical wet forest on Barro Colorado Island, Panama, where all trees and lianas >1 cm diameter have been mapped to investigate richness patterns below ground and model rooting distributions. Methodology/Principal Findings -- DNA barcode loci, particularly the cpDNA locus trnH-psba, can be used to identify fine and small coarse roots to species. We recovered 33 species of roots from 117 fragments sequenced from 12 soil cores. Despite limited sampling, we recovered a high proportion of the known species in the focal hectare, representing approximately 14% of the measured woody plant richness. This high value is emphasized by the fact that we would need to sample on average 13 m2 at the seedling layer and 45 m2 for woody plants >1 cm diameter to obtain the same number of species above ground. Results from inverse models parameterized with the locations and sizes of adults and the species identifications of roots and sampling locations indicates a high potential for distal underground interactions among plants. Conclusions -- DNA barcoding techniques coupled with modeling approaches should be broadly applicable to studying root distributions in any mapped vegetation plot. We discuss the implications of our results and outline how second-generation sequencing technology and environmental sampling can be combined to increase our understanding of how root distributions influence the potential for plant interactions in natural ecosystems.FAJ acknowledges the support of a Tupper postdoctoral fellowship in tropical biology and the National Science Foundation (DEB 0453665). Funding was provided by the Smithsonian Institution Global Earth Observatory, the Smithsonian Tropical Research Institute/Center for Tropical Forest Sciences endowment fund, and the Smithsonian Tropical Research Institute/Frank Levinson fund. We would like to thank Autoridad Nacional del Ambiente and the Smithsonian Tropical Research Institute for processing research permits. We thank S. Hubbell and R. Condit for access to plot data, S. Schnitzer for liana census data (NSF DEB 0613666), and L. Comita and S. Hubbell for access to seedling data (NSF DEB 0075102 and DEB 0823728). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Marine Scienc
Investigation of surface integrity in laser-assisted machining of nickel based superalloy
While laser-assisted machining can significantly improve the machinability of nickel-based superalloy, the mechanism of surface integrity evolution and its influence on the material functional performance is still not clear. The present study gives a comprehensive investigation on the surface integrity of laser-assisted milling (LAMill) process with an in-depth study of the mechanism of chip formation, microstructural and mechanical alternations, supported by key outcomes from the two constitutive processes, conventional milling (CMill) and single laser scanning (LS). Although the high thermal affected layer in LAMill process has been removed through the cutting chips, a significant bending effect has been found in both the LAMill and LS workpiece. More interestingly, a combined impact of the residual stress from LS and CMill has been found on LAMill workpiece while a lattice evolution has been revealed regarding both the thermal and mechanical influence. Specifically, inadequate fatigue performance on LAMill and LS workpiece has been found due to the high thermal effect in the superficial layer regarding the residual tensile stress distribution and microstructure variation. While LAMill is generally considered as a promising machining method with improved machinability of difficult-to-cut materials, this research shows a poor workpiece functional performance (fatigue) and justifies its application prospect
Severe respiratory illness caused by a novel coronavirus, in a patient transferred to the United Kingdom from the Middle East, September 2012
Coronaviruses have the potential to cause severe transmissible human disease, as demonstrated by the severe acute respiratory syndrome (SARS) outbreak of 2003. We describe here the clinical and virological features of a novel coronavirus infection causing severe respiratory illness in a patient transferred to London, United Kingdom, from the Gulf region of the Middle East
A meta-analysis of state-of-the-art electoral prediction from Twitter data
Electoral prediction from Twitter data is an appealing research topic. It
seems relatively straightforward and the prevailing view is overly optimistic.
This is problematic because while simple approaches are assumed to be good
enough, core problems are not addressed. Thus, this paper aims to (1) provide a
balanced and critical review of the state of the art; (2) cast light on the
presume predictive power of Twitter data; and (3) depict a roadmap to push
forward the field. Hence, a scheme to characterize Twitter prediction methods
is proposed. It covers every aspect from data collection to performance
evaluation, through data processing and vote inference. Using that scheme,
prior research is analyzed and organized to explain the main approaches taken
up to date but also their weaknesses. This is the first meta-analysis of the
whole body of research regarding electoral prediction from Twitter data. It
reveals that its presumed predictive power regarding electoral prediction has
been rather exaggerated: although social media may provide a glimpse on
electoral outcomes current research does not provide strong evidence to support
it can replace traditional polls. Finally, future lines of research along with
a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table
Effects of zinc on leaf decomposition by fungi in streams : studies in microcosms
The effect of zinc on leaf decomposition by aquatic fungi was studied in microcosms. Alder leaf disks were precolonized for 15 days at the source of the Este River, and exposed to different zinc concentrations during 25 days. Leaf mass loss, fungal biomass (based on ergosterol concentration), fungal production (rates of [1-14C]acetate incorporation into ergosterol), sporulation rates and species richness of aquatic hyphomycetes were determined. At the source of the Este River decomposition of alder leaves was fast and 50% of the initial mass was lost in 25 days. A total of 18 aquatic hyphomycete species were recorded during 42 days of leaf immersion. Articulospora tetracladia was the dominant species, followed by Lunulospora curvula and two unidentified species with sigmoid conidia. Cluster analysis suggested that zinc concentration and exposure time affected the structure of aquatic hyphomycete assemblages, even though richness had not been severely affected. Both zinc concentration and exposure time significantly affected leaf mass loss, fungal production and sporulation, but not fungal biomass. Zinc exposure reduced leaf mass loss, inhibited fungal production and affected fungal reproduction by either stimulating or inhibiting sporulation rates. The results of this work suggested zinc pollution might depress leaf decomposition in streams due to changes in the structure and activity of aquatic fungi.Fundação para a Ciência e a Tecnologia (FCT) – Programa Operacional “Ciência, Tecnologia, Inovação” (POCTI) - POCTI/34024/BSE/2000
A preliminary study of genetic factors that influence susceptibility to bovine tuberculosis in the British cattle herd
Associations between specific host genes and susceptibility to Mycobacterial infections such as tuberculosis have been reported in several species. Bovine tuberculosis (bTB) impacts greatly the UK cattle industry, yet genetic predispositions have yet to be identified. We therefore used a candidate gene approach to study 384 cattle of which 160 had reacted positively to an antigenic skin test (‘reactors’). Our approach was unusual in that it used microsatellite markers, embraced high breed diversity and focused particularly on detecting genes showing heterozygote advantage, a mode of action often overlooked in SNP-based studies. A panel of neutral markers was used to control for population substructure and using a general linear model-based approach we were also able to control for age. We found that substructure was surprisingly weak and identified two genomic regions that were strongly associated with reactor status, identified by markers INRA111 and BMS2753. In general the strength of association detected tended to vary depending on whether age was included in the model. At INRA111 a single genotype appears strongly protective with an overall odds ratio of 2.2, the effect being consistent across nine diverse breeds. Our results suggest that breeding strategies could be devised that would appreciably increase genetic resistance of cattle to bTB (strictly, reduce the frequency of incidence of reactors) with implications for the current debate concerning badger-culling
Natural T cell–mediated protection against seasonal and pandemic Influenza: results of the Flu Watch cohort study
Rationale: A high proportion of influenza infections are asymptomatic. Animal and human challenge studies and observational studies suggest T cells protect against disease among those infected, but the impact of T-cell immunity at the population level is unknown.
Objectives: To investigate whether naturally preexisting T-cell responses targeting highly conserved internal influenza proteins could provide cross-protective immunity against pandemic and seasonal influenza.
Methods: We quantified influenza A(H3N2) virus–specific T cells in a population cohort during seasonal and pandemic periods between 2006 and 2010. Follow-up included paired serology, symptom reporting, and polymerase chain reaction (PCR) investigation of symptomatic cases.
Measurements and Main Results: A total of 1,414 unvaccinated individuals had baseline T-cell measurements (1,703 participant observation sets). T-cell responses to A(H3N2) virus nucleoprotein (NP) dominated and strongly cross-reacted with A(H1N1)pdm09 NP (P < 0.001) in participants lacking antibody to A(H1N1)pdm09. Comparison of paired preseason and post-season sera (1,431 sets) showed 205 (14%) had evidence of infection based on fourfold influenza antibody titer rises. The presence of NP-specific T cells before exposure to virus correlated with less symptomatic, PCR-positive influenza A (overall adjusted odds ratio, 0.27; 95% confidence interval, 0.11–0.68; P = 0.005, during pandemic [P = 0.047] and seasonal [P = 0.049] periods). Protection was independent of baseline antibodies. Influenza-specific T-cell responses were detected in 43%, indicating a substantial population impact.
Conclusions: Naturally occurring cross-protective T-cell immunity protects against symptomatic PCR-confirmed disease in those with evidence of infection and helps to explain why many infections do not cause symptoms. Vaccines stimulating T cells may provide important cross-protective immunity
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