Long Term Trends in Resource Exergy Consumption and Useful Work Supplies in the UK, 1900-2000

Our aim is to explain historical economic growth in the UK economy by introducing an empirical measure for useful work derived from natural resource energy inputs into an augmented production function. To do this, we estimate the long-term (1900-2000) trends in resource exergy supply and conversion to useful work in the United Kingdom. The exergy resources considered included domestic consumption of coal, crude oil and petroleum products, natural gas, nuclear and renewable resources (including biomass). All flows of exergy were allocated to an end use such as providing heat, light, transport, human and animal work and electrical power. For each end-use we estimated a time dependent efficiency of conversion from exergy to useful work. The 3-factor production function (of capital, labour and useful work) is able to reproduce the historic trajectory of economic growth without recourse to any exogenous assumptions of technological progress or total factor productivity. The results indicate that useful work derived from natural resource exergy is an important factor of production.exergy, energy, efficiency, economic growth, United Kingdom

Obtaining malignant melanoma indicators through statistical analysis of 3D skin surface disruptions

Background/purpose: It has been observed that disruptions in skin patterns are larger for malignant melanoma (MM) than benign lesions. In order to extend the classification results achieved for 2D skin patterns, this work intends to investigate the feasibility of lesion classification using 3D skin surface texture, in the form of surface normals acquired from a previously built six-light photometric stereo device. Material and methods: The proposed approach seeks to separate MM from benign lesions through analysis of the degree of surface disruptions in the tilt and slant direction of surface normals, so called skin tilt pattern and skin slant pattern. A 2D Gaussian function is used to simulate a normal region of skin for comparison with a lesion's observed tilt and slant patterns. The differences associated with the two patterns are estimated as the disruptions in the tilt and slant pattern respectively for lesion classification. Results: Preliminary studies on11 MMs and 28 benign lesions have given Receiver operating characteristic areas of 0.73 and 0.85 for tilt and slant pattern, respectively, which are better than 0.65 previously obtained for the skin line direction using the same samples. Conclusions: This paper has demonstrated an important application of 3D skin texture for computer-assisted diagnosis of MM in vivo. By taking advantage of the extra dimensional information, preliminary studies suggest that some improvements over the existing 2D skin line pattern approach for the differentiation between MM and benign lesions. © 2009 John Wiley & Sons A/S

In vivo measurement of skin microrelief using photometricstereo in the presence of interreflections

This paper proposes and describes an implementation of a novel photometric stereo based technique for in vivo assessment of three-dimensional (3D) skin topographyin the presence of interreflections. The proposed method illuminates skin with red, green, and blue colored lights and uses the resulting variation in surface gradients tomitigate the effects of interreflections. Experiments were carried out on Caucasian, Asian and African American subjects to demonstrate the accuracy of our methodand to validate the measurements produced by our system. Our method produced significant improvement in 3D surface reconstruction for all Caucasian, Asian and African American skin types. The results also illustrate the differences in recovered skin topography due to non-diffuse Bidirectional reflectance distribution function(BRDF) for each color illumination used, which also concur with the existing multispectral BRDF data available for skin

Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction.

From Europe PMC via Jisc Publications RouterHistory: ppub 2021-10-01, epub 2021-10-21Publication status: PublishedHere we apply hyperspectral bright field imaging to collect computed tomographic images with excellent energy resolution (~ 1 keV), applying it for the first time to map the distribution of stain in a fixed biological sample through its characteristic K-edge. Conventionally, because the photons detected at each pixel are distributed across as many as 200 energy channels, energy-selective images are characterised by low count-rates and poor signal-to-noise ratio. This means high X-ray exposures, long scan times and high doses are required to image unique spectral markers. Here, we achieve high quality energy-dispersive tomograms from low dose, noisy datasets using a dedicated iterative reconstruction algorithm. This exploits the spatial smoothness and inter-channel structural correlation in the spectral domain using two carefully chosen regularisation terms. For a multi-phase phantom, a reduction in scan time of 36 times is demonstrated. Spectral analysis methods including K-edge subtraction and absorption step-size fitting are evaluated for an ex vivo, single (iodine)-stained biological sample, where low chemical concentration and inhomogeneous distribution can affect soft tissue segmentation and visualisation. The reconstruction algorithms are available through the open-source Core Imaging Library. Taken together, these tools offer new capabilities for visualisation and elemental mapping, with promising applications for multiply-stained biological specimens

Optimal cDNA microarray design using expressed sequence tags for organisms with limited genomic information

BACKGROUND: Expression microarrays are increasingly used to characterize environmental responses and host-parasite interactions for many different organisms. Probe selection for cDNA microarrays using expressed sequence tags (ESTs) is challenging due to high sequence redundancy and potential cross-hybridization between paralogous genes. In organisms with limited genomic information, like marine organisms, this challenge is even greater due to annotation uncertainty. No general tool is available for cDNA microarray probe selection for these organisms. Therefore, the goal of the design procedure described here is to select a subset of ESTs that will minimize sequence redundancy and characterize potential cross-hybridization while providing functionally representative probes. RESULTS: Sequence similarity between ESTs, quantified by the E-value of pair-wise alignment, was used as a surrogate for expected hybridization between corresponding sequences. Using this value as a measure of dissimilarity, sequence redundancy reduction was performed by hierarchical cluster analyses. The choice of how many microarray probes to retain was made based on an index developed for this research: a sequence diversity index (SDI) within a sequence diversity plot (SDP). This index tracked the decreasing within-cluster sequence diversity as the number of clusters increased. For a given stage in the agglomeration procedure, the EST having the highest similarity to all the other sequences within each cluster, the centroid EST, was selected as a microarray probe. A small dataset of ESTs from Atlantic white shrimp (Litopenaeus setiferus) was used to test this algorithm so that the detailed results could be examined. The functional representative level of the selected probes was quantified using Gene Ontology (GO) annotations. CONCLUSIONS: For organisms with limited genomic information, combining hierarchical clustering methods to analyze ESTs can yield an optimal cDNA microarray design. If biomarker discovery is the goal of the microarray experiments, the average linkage method is more effective, while single linkage is more suitable if identification of physiological mechanisms is more of interest. This general design procedure is not limited to designing single-species cDNA microarrays for marine organisms, and it can equally be applied to multiple-species microarrays of any organisms with limited genomic information

Identification of low-confidence regions in the pig reference genome (Sscrofa10.2)

Many applications of high throughput sequencing rely on the availability of an accurate reference genome. Variant calling often produces large data sets that cannot be realistically validated and which may contain large numbers of false-positives. Errors in the reference assembly increase the number of false-positives. While resources are available to aid in the filtering of variants from human data, for other species these do not yet exist and strict filtering techniques must be employed which are more likely to exclude true-positives. This work assesses the accuracy of the pig reference genome (Sscrofa10.2) using whole genome sequencing reads from the Duroc sow whose genome the assembly was based on. Indicators of structural variation including high regional coverage, unexpected insert sizes, improper pairing and homozygous variants were used to identify low quality (LQ) regions of the assembly. Low coverage (LC) regions were also identified and analyzed separately. The LQ regions covered 13.85% of the genome, the LC regions covered 26.6% of the genome and combined (LQLC) they covered 33.07% of the genome. Over half of dbSNP variants were located in the LQLC regions. Of CNVRs identified in a previous study, 86.3% were located in the LQLC regions. The regions were also enriched for gene predictions from RNA-seq data with 42.98% falling in the LQLC regions. Excluding variants in the LQ, LC or LQLC from future analyses will help reduce the number of false-positive variant calls. Researchers using WGS data should be aware that the current pig reference genome does not give an accurate representation of the copy number of alleles in the original Duroc sow’s genome

High-energy synchrotron X-ray tomography coupled with digital image correlation highlights likely failure points inside ITER toroidal field conductors

From Springer Nature via Jisc Publications RouterHistory: received 2021-02-01, accepted 2021-10-22, registration 2021-11-09, pub-electronic 2021-11-30, online 2021-11-30, collection 2021-12Publication status: PublishedFunder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/M010619/1Abstract: Two sections of heat-treated (HT) and non-heat-treated (NHT) Cable-in-Conduit Conductor (CICC) of a design similar to the ITER tokomak have been imaged using very high energy X-ray tomography at the ESRF beamline ID19. The sample images were collected at four temperatures down to 77 K. These results showed a greater degree of movement, bundle distortion and touching strands in the NHT sample. The HT sample showed non-linear movements with temperature especially close to 77 K; increasing non-circularity of the superconducting fibre bundles towards the periphery of the CICC, and touching bundles throughout the CICC. The images have highlighted where future design might improve potential weakness, in particular at the outer perimeters of the conductor and the individual sub-cable, ‘petal’ wraps

Marine Genomics: A clearing-house for genomic and transcriptomic data of marine organisms

BACKGROUND: The Marine Genomics project is a functional genomics initiative developed to provide a pipeline for the curation of Expressed Sequence Tags (ESTs) and gene expression microarray data for marine organisms. It provides a unique clearing-house for marine specific EST and microarray data and is currently available at . DESCRIPTION: The Marine Genomics pipeline automates the processing, maintenance, storage and analysis of EST and microarray data for an increasing number of marine species. It currently contains 19 species databases (over 46,000 EST sequences) that are maintained by registered users from local and remote locations in Europe and South America in addition to the USA. A collection of analysis tools are implemented. These include a pipeline upload tool for EST FASTA file, sequence trace file and microarray data, an annotative text search, automated sequence trimming, sequence quality control (QA/QC) editing, sequence BLAST capabilities and a tool for interactive submission to GenBank. Another feature of this resource is the integration with a scientific computing analysis environment implemented by MATLAB. CONCLUSION: The conglomeration of multiple marine organisms with integrated analysis tools enables users to focus on the comprehensive descriptions of transcriptomic responses to typical marine stresses. This cross species data comparison and integration enables users to contain their research within a marine-oriented data management and analysis environment

People, places and policies – trying to account for health inequalities in impoverished neighbourhoods

Objective : We consider associations between individual, household and area-level characteristics and self-reported health.Method : Data is taken from baseline surveys undertaken in 13 socio-economically disadvantaged neighbourhoods in Victoria (n=3,944). The neighbourhoods are sites undergoing Neighbourhood Renewal (NR), a State government initiative redressing place-based disadvantage.Analysis :This focused on the relationship between area and compositional factors and self-reported health. Area was coded into three categories; LGA, NR residents living in public housing (NRPU) and NR residents who lived in private housing (NRPR). Compositional factors included age, gender, marital status, identifying as a person with a disability, level of education, unemployment and receipt of pensions/benefits.Results : There was a gradient in socio-economic disadvantage on all measures. People living in NR public housing were more disadvantaged than people living in NR private housing who, in turn, were more disadvantaged than people in the same LGA. NR public housing residents reported the worst health status and LGA residents reported the best.Conclusions : Associations between compositional characteristics of disability, educational achievement and unemployment income and poorer self-reported health were shown. They suggested that area characteristics, with housing policies, may be contributing to differences in self-reported health at the neighbourhood level.Implications : The clustering of socio-economic disadvantage and health outcomes requires the integration of health and social support interventions that address the circumstances of people and places.<br /