92 research outputs found
Influence of ac ageing on space charge dynamics in LDPE
No full textPolymeric materials have been widely used as insulation in power industry due to their excellent electrical properties. However, these properties deteriorate in time irreversibly when the material is subjected to electric stress. Although space charge is believed to play an important role in ac ageing, exact mechanisms are poorly understood due to very limited experimental data. In the present work efforts have been made to investigate the influence of ac ageing on space charge dynamics in low-density polyethylene (LDPE). LDPE films with 200mm were aged at 50 kV/mm at 50 Hz for various times at ambient temperature. Space charge dynamics in the samples prior to and after ageing were monitored using the pulsed electroacoustic (PEA) technique under dc electric stress. The results indicate that there is a significant amount of homocharge accumulation in the unaged sample due to charge injection. These injected charges are the captured by the deep traps originated from the interface between crystalline and amorphous regions in LDPE. Ageing under ac condition does not necessarily lead to an increase in amount of charge in the bulk but leads to an increase in mobility of charge carriers. Chemical analysis by infrared spectroscope (FTIR) reveals there are chemical changes taken place in the bulk of the material after ac ageing. It is believed that the chemical changes introduce shallow traps which promote the movement of charge carriers in the bulk. Consequently, the injected charges spread across the sample
Pharmacological blockade of G-protein coupled receptors : interventions to alter expression or internalization
No full textUsing Convex Optimization to Efficiently Apportion Tracer and Pollutant Sources From Point Concentration Observations
No full textRivers transport elements, minerals, chemicals, and pollutants produced in their upstream basins. A sample from a river is a mixture of all of its upstream sources, making it challenging to pinpoint the contribution from each individual source. Here, we show how a nested sample design and convex optimization can be used to efficiently unmix downstream samples of a well‐mixed, conservative tracer in a steady state system into the contributions of their upstream sources. Our approach is significantly faster than previous methods. We represent the river's sub‐catchments, defined by sampling sites, using a directed acyclic graph. This graph is used to build a convex optimization problem which, thanks to its convexity, can be quickly solved to global optimality—in under a second on desktop hardware for data sets of ∼100 samples or fewer. Uncertainties in the upstream predictions can be generated using Monte Carlo resampling. We provide an open‐source implementation of this approach in Python. The inputs required are straightforward: a table containing sample locations and observed tracer concentrations, along with a D8 flow‐direction raster map. As a case study, we use this method to map the elemental geochemistry of sediment sources for rivers draining the Cairngorms mountains, UK. This method could be extended to non‐conservative and non‐steady state tracers. We also show, theoretically, how multiple tracers could be simultaneously inverted to recover upstream run‐off or erosion rates as well as source concentrations. Overall, this approach can provide valuable insights to researchers in various fields, including water quality, geochemical exploration, geochemistry, hydrology, and wastewater epidemiology
Scale‐Dependent Flow Directions of Rivers and the Importance of Subplate Support
No full textLarge rivers play crucial roles in determining locations of civilization, biodiversity, and efflux to the oceans. The paths they take across Earth's surface vary with scale. At long‐wavelengths rivers can have simple flow paths. At smaller scales, in meanders for example, their paths change rapidly as a consequence of lithology, biota, and other environmental variables. It is not straightforward to identify the scales at which river planforms are set. We overcome these issues by developing a spectral (wavelet) methodology to map flow‐directions as a function of distance and scale. This methodology allows short‐wavelength features (e.g., meanders) to be filtered from river flow‐paths. With short‐wavelength structure removed, the flow‐directions of rivers in Western USA correlate with long‐wavelength gravity anomalies suggesting control by subplate support. This relationship is replicated by an ensemble of landscape evolution models. These results combined suggest that drainage at large scales, O(103) km, is set by subplate support
Capacity limits for the detection of changing visual features
No full textCapacity limits in visual attention have traditionally been studied using static arrays of elements from which an observer must detect a target defined by a certain visual feature or combination of features. In the current study we use this visual search paradigm, with accuracy as the dependent variable, to examine attentional capacity limits for different visual features undergoing change over time. In Experiment 1, detectability of a single changing target was measured under conditions where the type of change (size, speed, colour), the magnitude of change, the set size and homogeneity of the unchanging distractors were all systematically varied. Psychometric function slopes were calculated for different experimental conditions and ‘change thresholds’extracted from these slopes were used in Experiment 2, in which multiple supra-threshold changes were made, simultaneously, either to a single or to two or three different stimulus elements. These experiments give an objective psychometric paradigm for measuring changes in visual features over time. Results favour object-based accounts of visual attention, and show consistent differences in the allocation of attentional capacity to different perceptual dimensions
Major‐element composition of sediments in terms of weathering and provenance: Implications for crustal recycling
No full textThe elemental composition of a sediment is set by the composition of its protolith and modified by weathering, sorting, and diagenesis. An important problem is deconvolving these contributions to a sediment's composition to arrive at information about processes that operate on the Earth's surface. We approach this problem by developing a predictive and invertible model of sedimentary major‐element composition. We compile a dataset of sedimentary rock, river sediment, soil, and igneous rock compositions. Principal component analysis of the dataset shows that most variation can be simplified to a small number of variables. We thus show that any sediment's composition can be described with just two vectors of igneous evolution and weathering. We hence define a model for sedimentary composition as a combination of these processes. A 1:1 correspondence is observed between predictions and independent data. The log‐ratios ln(K2O/MgO) and ln(Al2O3/Na2O) are found to be simple proxies for, respectively, the model's protolith and weathering indices. Significant deviations from the model can be explained by sodium‐calcium exchange. Using this approach, we show that the major‐element composition of the upper continental crust has been modified by weathering and we calculate the amount of each element that it must have lost to modify it to its present composition. By extrapolating modern weathering rates over the age of the crust we conclude that it has not retained a significant amount of the necessarily produced weathering restite. This restite has likely been subducted into the mantle, indicating a crust‐to‐mantle recycling rate of 1.33 ± 0.89×1013 kg yr‐1
Major Element Composition of Sediments in Terms of Weathering and Provenance: Implications for Crustal Recycling
No full textAbstract The elemental composition of a sediment is set by the composition of its protolith and modified by weathering, sorting, and diagenesis. An important problem is deconvolving these contributions to a sediment's composition to arrive at information about processes that operate on the Earth's surface. We approach this problem by developing a predictive and invertible model of sedimentary major element composition. We compile a data set of sedimentary rock, river sediment, soil, and igneous rock compositions. Principal component analysis of the data set shows that most variation can be simplified to a small number of variables. We thus show that any sediment's composition can be described with just two vectors of igneous evolution and weathering. We hence define a model for sedimentary composition as a combination of these processes. A 1:1 correspondence is observed between predictions and independent data. The log ratios and are found to be simple proxies for, respectively, the model's protolith and weathering indices. Significant deviations from the model can be explained by sodium‐calcium exchange. Using this approach, we show that the major element composition of the upper continental crust has been modified by weathering, and we calculate the amount of each element that it must have lost to modify it to its present composition. By extrapolating modern weathering rates over the age of the crust, we conclude that it has not retained a significant amount of the necessarily produced weathering restite. This restite has likely been subducted into the mantle, indicating a crust‐to‐mantle recycling rate of 1.33 ± 0.89 ×10 13 kg·year −1 .
Key Points Weathering and provenance dominate fine‐grained sedimentary elemental composition Protolith composition and weathering intensity are determined from a sediment's composition The upper continental crust is recycled into the mantle at a rate of 1.33 ± 0.89 10 13 kg·year −
Proceedings of the South Dakota Academy of Science, 1926–1927, volume 11.
No full textProceedings of the South Dakota Academy of Science, 1926–1927, volume 11.
The table of contents lists officers of the Academy, reports from the Committee on Affiliation with the A.A.A.S., the Committee on Extending the Services of the Academy, the Committee on Membership, the Ecological Conservation Committee, the Committee on Resolutions, and minutes.
The following papers were presented at the thirteenth annual meeting of the South Dakota Academy of Science held on May 20 and 21: Conservation of Bird Life by A. P. Larrabee, The Cicindelidae (Tiger Beetles) of South Dakota by G. I. Gilbertson, Observations on the Effect of Sulphur Dioxide on Native and Introduced Vegetation by Arthur T. Evans, A Third Report Upon the Membracidae (Tree-Hoppers) of South Dakota by H. C. Severin, Additions to the List of Fishes of South Dakota by E. P. Churchill, The Food of Bullheads in Certain Lakes of Eastern South Dakota (Preliminary Report) by Louella E. Cable, Iodine and Goiter (no author listed), The History of the Geography of South Dakota Before 1804 by Wm. H. Powers, The Relation of Mathematics Aptitude to Other Aptitudes by R. D. Sinclair, Flora of the Upper Missouri Valley by W. H. Powers, Price and Production Relationship by Owen L. Dawson, and South Dakota\u27s Animal Health Laboratory by Dr. C. C. Lipp
Apportioning sources of chemicals of emerging concern along an urban river with inverse modelling
No full textConcentrations of chemicals in river water provide crucial information for assessing environmental exposure and risks from fertilisers, pesticides, heavy metals, illicit drugs, pathogens, pharmaceuticals, plastics and perfluorinated substances, among others. However, using concentrations measured along waterways (e.g., from grab samples) to identify sources of contaminants and understand their fate is complicated by mixing of chemicals downstream from diverse diffuse and point sources (e.g., agricultural runoff, wastewater treatment plants). To address this challenge, a novel inverse modelling approach is presented. Using waterway network topology, it quantifies locations and concentrations of contaminant sources upstream by inverting concentrations measured in water samples. It is computationally efficient and quantifies uncertainty. The approach is demonstrated for 13 contaminants of emerging concern (CECs) in an urban stream, the R. Wandle (London, UK). Mixing (the forward problem) was assumed to be conservative, and the location of sources and their concentrations were treated as unknowns to be identified. Calculated CEC source concentrations, which ranged from below detection limit (a few ng/L) up to 1μg/L, were used to predict concentrations of chemicals downstream. Using this approach, >90% of data were predicted within observational uncertainty. Principal component analysis of calculated source concentrations revealed signatures of two distinct chemical sources. First, pharmaceuticals and insecticides were associated with a subcatchment containing a known point source of treated effluent from a wastewater treatment plant. Second, illicit drugs and salicylic acid were associated with multiple sources, interpreted as input from untreated sewage including Combined Sewer Overflows (CSOs), misconnections, runoff and direct disposal throughout the catchment. Finally, a simple algorithmic approach that incorporates network topology was developed to design sampling campaigns to improve resolution of source apportionment. Inverse modelling of contaminant measurements can provide objective means to apportion sources in waterways from spot samples in catchments on a large scale
Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions
No full textAbstract The geochemistry of river sediments is routinely used to obtain information about geologic and environmental processes occurring upstream. For example, downstream samples are used to constrain chemical weathering and physical erosion rates upstream, as well as the locations of mineral deposits or contaminant sources. Previous work has shown that, by assuming conservative mixing, the geochemistry of downstream samples can be reliably predicted given a known source region geochemistry. In this study, we tackle the inverse problem and “unmix” the composition of downstream river sediments to produce geochemical maps of drainage basins (i.e., source regions). The scheme is tested in a case study of rivers draining the Cairngorms, UK. The elemental geochemistry of the <150 μm fraction of 67 samples gathered from the beds of channels in this region is used to invert for concentrations of major and trace elements upstream. A smoothed inverse problem is solved using the Nelder‐Mead optimization algorithm. Predictions of source region geochemistry are assessed by comparing the spatial distribution of 22 elements of different affinities (e.g., Be, Li, Mg, Ca, Rb, U, V) using independent geochemical survey data. The inverse approach makes reliable predictions of the major and trace element concentration in first order river sediments. We suggest this scheme could be a novel means to generate geochemical baselines across drainage basins and within river channels
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