Faster Magnet Sorting with a Threshold Acceptance Algoirithm
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Abstract not provided.
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The project objective is to use advanced compositional and thermophysical characterization methods from INL to support the evaluation of new production pathways (partnered with MTU) to biopower applications under the guidance of an industrial partner operating the in U.S. power sector (CE). Ultimately, this project aims to create a uniform feedstock from non-recyclable wastes that can be used in bioenergy and biomaterials, which torrefaction and preprocessing strategies are critical to achieving this goal.
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To optimise segregation at source, and hence minimise waste production, NUVIA have developed and utilised the Gamma Excavation Monitor (GEM) system. The GEM was designed for land remediation projects, to provide a rapid screening tool for excavator buckets of material. Following successful deployment in the UK, including the Olympic Park site in London, and two major Magnox land remediation projects, the first GEM unit was deployed to Canadian Nuclear Laboratories' (CNL) Chalk River Laboratory (CRL) in 2016. The GEM unit was fitted with a plastic scintillator detector; recent developments have included the utilisation of a sodium iodide. The system is initiated by the presence of an excavator bucket above the detector which triggers proximity switches that automatically start the counting routine. At the end of a short count time, typically 10 seconds, the materials category is indicated by means of a traffic light system, based on either the gross gamma activity or a photo-peak. Using this instrument, material determined not to be radioactive can be re-used on-site. In addition to the traffic light system, results are also transmitted wirelessly to a tablet device. These combined features allow operation of the system without the need to have operatives near the mechanical excavator bucket; therefore, eliminating a significant industrial hazard. Deployments of the GEM on the CRL site have included Storm Water Management project, within the CRL controlled area, and the Foundation Road Landfill Project. The use of the GEM in these projects enabled in-situ decisions to be made regarding the segregation and sentencing of soil rather than having to wait for the analysis of samples; saving time and cost to the project. The Building 492 project involved the excavation of soil within a supervised area to prepare for the installation of modular trailer units. For this specific job, the GEM was calibrated to ensure soil met clearance criteria as stipulated in the Nuclear Substances and Radiation Devices Regulations (Canadian Nuclear Safety Commission; SOR/2000-207). A total of 326 loads of soil were monitored during this project and re-assurance sampling conducted by CNL corroborated the results produced by the GEM system. (authors)
During decommissioning of buildings and the related release of nuclear sites, large amounts of bulk materials such as soil must be measured for clearance. These measurements are required to demonstrate that for example potentially contaminated soil is below the respective radiological limits. Doing so also helps to minimize the amount of bulk material which has to be disposed of as nuclear waste. NUKEM Technologies Engineering Services GmbH (NUKEM) applies their FREMES technology in a project at the former fuel element factory of FBFC International at Dessel, Belgium. The purpose is to measure and check for potential contamination within the excavated soil. The project started in 2017 with design and procurement of the necessary equipment. In October 2017 the FREMES system was installed at the site. After installation and an extensive test program the FREMES facility went fully into operation in July 2018. Original foreseen to measure between 4.000 and 8.000 tons of material, it has currently (mid 2019) measured 23.600 tons. It is expected that another 5.000 tons still have to be measured before the project successfully ends. (authors)
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Highlights: • Tiered approach to waste sorting ensures flexibility and facilitates comparison of solid waste composition data. • Food and miscellaneous wastes are the main fractions contributing to the residual household waste. • Separation of food packaging from food leftovers during sorting is not critical for determination of the solid waste composition. - Abstract: Sound waste management and optimisation of resource recovery require reliable data on solid waste generation and composition. In the absence of standardised and commonly accepted waste characterisation methodologies, various approaches have been reported in literature. This limits both comparability and applicability of the results. In this study, a waste sampling and sorting methodology for efficient and statistically robust characterisation of solid waste was introduced. The methodology was applied to residual waste collected from 1442 households distributed among 10 individual sub-areas in three Danish municipalities (both single and multi-family house areas). In total 17 tonnes of waste were sorted into 10–50 waste fractions, organised according to a three-level (tiered approach) facilitating comparison of the waste data between individual sub-areas with different fractionation (waste from one municipality was sorted at “Level III”, e.g. detailed, while the two others were sorted only at “Level I”). The results showed that residual household waste mainly contained food waste (42 ± 5%, mass per wet basis) and miscellaneous combustibles (18 ± 3%, mass per wet basis). The residual household waste generation rate in the study areas was 3–4 kg per person per week. Statistical analyses revealed that the waste composition was independent of variations in the waste generation rate. Both, waste composition and waste generation rates were statistically similar for each of the three municipalities. While the waste generation rates were similar for each of the two housing types (single-family and multi-family house areas), the individual percentage composition of food waste, paper, and glass was significantly different between the housing types. This indicates that housing type is a critical stratification parameter. Separating food leftovers from food packaging during manual sorting of the sampled waste did not have significant influence on the proportions of food waste and packaging materials, indicating that this step may not be required.
ABSTRACT Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this “uncultivated majority” remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes . Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages. IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism.
The global nuclear industry has a growing volume of nuclear waste which needs to be scanned, sorted according to its activity and material type, then processed into the correct waste packages for long term storage and disposal. It is vital that there is a detailed understanding of the waste inventory stored in long term waste containers, as knowledge of their contents could predict or prevent any adverse effects in storage. The numerous 'scan and sort' tables which are currently used at many different facilities around the world to sort waste into their correct containers are human operated and require very slow gamma scanning procedures combined with educated guesswork to manually sort the waste. This often leads to excessive conservatisms, with placement of lower activity wastes in higher activity containers, which in turn costs significantly more to store. In the United Kingdom it costs UK Pounds 46 k per cubic meter to store intermediate level waste compared to just UK Pound 2.9 k per cubic meter to store low level waste according to a 2008 Department of Energy and Climate Change report in the UK. A proposed solution to this problem, is the use of a robotic manipulator to automatically inspect the 'scan and sort table' in order to produce an accurate 3D model of the table's waste contents and attach an overlaid radiation map. The radiation map contains spectrometry data and can in consequence be used to distinguish and locate specific radioisotopes. The 3D model should be as accurate as possible in order to allow for a second robot arm with an attached gripper to grasp the objects and place them into their designated long-term storage container. Various scanning procedures are explored in this study including basic raster scanning, adaptive raster scanning and point sampling. The optimal solution will in practice be defined by the required application and activity level of the wastes being inspected. The results presented in this study indicate that it is possible to produce a centimeter accurate 3D model of a mixed assortment of components on a nuclear waste 'scan and sort' table. In addition, it was shown that the waste objects emitting radiation could be accurately identified and located, with an overlaid radiation map. This study is applicable across the nuclear waste management sector. Many of the ideas and concepts developed in this study are applicable in other decommissioning settings for example, dismantling of legacy gloveboxes or routine inspection of nuclear waste packages in storage. (authors)
Municipal solid waste (MSW) generation is quickly increasing due to population growth, industrialization, and urbanization. Current sorting technologies, e.g., optical sorters have low sortation efficiency and produce contaminated sorted materials unsuitable for downstream valorization. This study evaluates a novel artificial neural network (ANN)-based MSW sortation system through sorting efficiencies, economic performance, and environmental impacts. ANN system can sort up to 8 plastic types and all organic waste (i.e., food, yard, and paper waste) with 99% and 93% recovery efficiency, respectively, compared to optical sortation which could separate only polyvinyl chloride (PVC) plastic ultimately producing mixed plastics (except PVC) and organics streams as products. Nonetheless, their sortation costs are similar, $28.7 for ANN-based sortation and $28 for optical sortation per metric ton (Mt) of MSW at processing capacity of 94,860 metric tons (Mt)/yr of MSW in the United States. Additionally, ANN system produced high purity feedstocks for downstream valorization. A biochar pyrolysis plant modeled to process 3.6 and 14 Mt/h of sorted yard waste outperformed biochar production from mixed organic fraction (MOF), achieving 8% lower production cost and 34% lower global warming impact (1.37 kg CO 2 eq. per kg) compared to biochar derived from mixed organic feedstock (2.08 kg CO 2 eq.).
Purpose: The purpose of this study was to develop a novel algorithm to create a robust internal respiratory signal (IRS) for retrospective sorting of four-dimensional (4D) computed tomography (CT) images. Methods: The proposed algorithm combines information from the Fourier transform of the CT images and from internal anatomical features to form the IRS. The algorithm first extracts potential respiratory signals from low-frequency components in the Fourier space and selected anatomical features in the image space. A clustering algorithm then constructs groups of potential respiratory signals with similar temporal oscillation patterns. The clustered group with the largest number of similar signals is chosen to form the final IRS. To evaluate the performance of the proposed algorithm, the IRS was computed and compared with the external respiratory signal from the real-time position management (RPM) system on 80 patients. Results: In 72 (90%) of the 4D CT data sets tested, the IRS computed by the authors’ proposed algorithm matched with the RPM signal based on their normalized cross correlation. For these data sets with matching respiratory signals, the average difference between the end inspiration times (Δt{sub ins}) in the IRS and RPM signal was 0.11 s, and only 2.1% of Δt{sub ins} were more than 0.5 s apart. In the eight (10%) 4D CT data sets in which the IRS and the RPM signal did not match, the average Δt{sub ins} was 0.73 s in the nonmatching couch positions, and 35.4% of them had a Δt{sub ins} greater than 0.5 s. At couch positions in which IRS did not match the RPM signal, a correlation-based metric indicated poorer matching of neighboring couch positions in the RPM-sorted images. This implied that, when IRS did not match the RPM signal, the images sorted using the IRS showed fewer artifacts than the clinical images sorted using the RPM signal. Conclusions: The authors’ proposed algorithm can generate robust IRSs that can be used for retrospective sorting of 4D CT data. The algorithm is completely automatic and requires very little processing time. The algorithm is cost efficient and can be easily adopted for everyday clinical use.
Purpose: To develop a quantitative decision making metric for automatically detecting irregular breathing using a large patient population that received phase-sorted 4DCT. Methods: This study employed two patient cohorts. Cohort#1 contained 256 patients who received a phasesorted 4DCT. Cohort#2 contained 86 patients who received three weekly phase-sorted 4DCT scans. A previously published technique used a single abdominal surrogate to calculate the ratio of extreme inhalation tidal volume to normal inhalation tidal volume, referred to as the κ metric. Since a single surrogate is standard for phase-sorted 4DCT in radiation oncology clinical practice, tidal volume was not quantified. Without tidal volume, the absolute κ metric could not be determined, so a relative κ (κrel) metric was defined based on the measured surrogate amplitude instead of tidal volume. Receiver operator characteristic (ROC) curves were used to quantitatively determine the optimal cutoff value (jk) and efficiency cutoff value (τk) of κrel to automatically identify irregular breathing that would reduce the image quality of phase-sorted 4DCT. Discriminatory accuracy (area under the ROC curve) of κrel was calculated by a trapezoidal numeric integration technique. Results: The discriminatory accuracy of ?rel was found to be 0.746. The key values of jk and tk were calculated to be 1.45 and 1.72 respectively. For values of ?rel such that jk≤κrel≤τk, the decision to reacquire the 4DCT would be at the discretion of the physician. This accounted for only 11.9% of the patients in this study. The magnitude of κrel held consistent over 3 weeks for 73% of the patients in cohort#3. Conclusion: The decision making metric, ?rel, was shown to be an accurate classifier of irregular breathing patients in a large patient population. This work provided an automatic quantitative decision making metric to quickly and accurately assess the extent to which irregular breathing is occurring during phase-sorted 4DCT.
Background:Metagenomics and single cell genomics provide a window into the genetic repertoire of yet uncultivated microorganisms, but both methods are usually taxonomically untargeted. The combination of fluorescence in situ hybridization (FISH) and fluorescence activated cell sorting (FACS) has the potential to enrich taxonomically well-defined clades for genomic analyses. Methods:Cells hybridized with a taxon-specific FISH probe are enriched based on their fluorescence signal via flow cytometric cell sorting. A recently developed FISH procedure, the hybridization chain reaction (HCR)-FISH, provides the high signal intensities required for flow cytometric sorting while maintaining the integrity of the cellular DNA for subsequent genome sequencing. Sorted cells are subjected to shotgun sequencing, resulting in targeted metagenomes of low diversity. Results: Pure cultures of different taxonomic groups were used to (1) adapt and optimize the HCR-FISH protocol and (2) assess the effects of various cell fixation methods on both the signal intensity for cell sorting and the quality of subsequent genome amplification and sequencing. Best results were obtained for ethanol-fixed cells in terms of both HCR-FISH signal intensity and genome assembly quality. Our newly developed pipeline was successfully applied to a marine plankton sample from the North Sea yielding good quality metagenome assembled genomes from a yet uncultivated flavobacterial clade. Conclusions: With the developed pipeline, targeted metagenomes at various taxonomic levels can be efficiently retrieved from environmental samples. The resulting metagenome assembled genomes allow for the description of yet uncharacterized microbial clades.
This research project is aiming to assess the carbon dioxide sealing capacity of most common seal-rocks, such as shales and non-fractured limestones, by analyzing the role of textural and compositional parameters of those rocks. We hypothesize that sealing capacity is controlled by textural and/or compositional parameters of caprocks. In this research, we seek to evaluate the importance of textural and compositional parameters affecting the sealing capacity of caprocks. The conceptual framework involves two testable end-member hypotheses concerning the sealing capacity of carbon dioxide reservoir caprocks. Better understanding of the elements controlling sealing quality will advance our knowledge regarding the sealing capacity of shales and carbonates. Due to relatively low permeability, shale and non-fractured carbonate units are considered relatively impermeable formations which can retard reservoir fluid flow by forming high capillary pressure. Similarly, these unites can constitute reliable seals for carbon dioxide capture and sequestration purposes. This project is a part of the comprehensive project with the final aim of studying the caprock sealing properties and the relationship between microscopic and macroscopic characteristics of seal rocks in depleted gas fields of Oklahoma Panhandle. Through this study we examined various seal rock characteristics to infer about their respective effects on sealing capacity in special case of replacing reservoir fluid with super critical carbon dioxide (scCO 2 ). To assess the effect of textural and compositional properties on scCO 2 maximum retention column height we collected 30 representative core samples in caprock formations in three counties (Cimarron, Texas, Beaver) in Oklahoma Panhandle. Core samples were collected from various seal formations (e.g., Cherokee, Keys, Morrowan) at different depths. We studied the compositional and textural properties of the core samples using several techniques. Mercury Injection Porosimetry (MIP), Scanning Electron Microscopy SEM, and Sedigraph measurements are used to assess the pore-throat-size distribution, sorting, texture, and grain size of the samples. Also, displacement pressure at 10% mercury saturation (Pd) and graphically derived threshold pressure (P c ) were determined by MIP technique. SEM images were used for qualitative study of the minerals and pores texture of the core samples. Moreover, EDS (Energy Dispersive X-Ray Spectrometer), BET specific surface area, and Total Organic Carbon (TOC) measurements were performed to study various parameters and their possible effects on sealing capacity of the samples. We found that shales have the relatively higher average sealing threshold pressure (P c ) than carbonate and sandstone samples. Based on these observations, shale formations could be considered as a promising caprock in terms of retarding scCO 2 flow and leakage into above formations. We hypothesized that certain characteristics of shales (e.g., 3 fine pore size, pore size distribution, high specific surface area, and strong physical chemical interaction between wetting phase and mineral surface) make them an efficient caprock for sealing super critical CO 2 . We found that the displacement pressure at 10% mercury saturation could not be the ultimate representative of the sealing capacity of the rock sample. On the other hand, we believe that graphical method, introduced by Cranganu (2004) is a better indicator of the true sealing capacity. Based on statistical analysis of our samples from Oklahoma Panhandle we assessed the effects of each group of properties (textural and compositional) on maximum supercritical CO 2 height that can be hold by the caprock. We conclude that there is a relatively strong positive relationship (+.40 to +.69) between supercritical CO 2 column height based on P c and hard/ soft mineral content index (ratio of minerals with Mohs hardness more than 5 over minerals with Mohs hardness less than 5) in both shales and limestone samples. Average median pore radius and porosity display a strong negative correlation with supercritical CO 2 retention column height. Also, increasing bulk density is positively correlated with the supercritical CO 2 retention column height. One of the most important factors affecting sealing capacity and consequently the height of supercritical CO 2 column is sorting of the pore throats. We observed a strong positive correlation between pore throat sorting and height of CO 2 retention column, especially in shales. This correlation could not be observed in limestone samples. It suggests that the pore throat sorting is more controlling the sealing capacity in shales and shales with well sorted pore throats are the most reliable lithology as seal. We observed that Brunauer–Emmett–Teller (BET) surface area shows a very strong correlation with CO 2 retention column height in limestone samples while BET surface area did not display significant correlation in shales. Pore structure based on SEM micrographs exhibits strong correlation with CO 2 retention column height in limestones. Both intercrystalline and vuggy structures have negative correlations while intergranular texture has positive correlation in limestone with respect to CO 2 retention column height. Textural effects observed on SEM micrographs did not show statistically significant correlation with supercritical CO 2 retention column height in shale samples. Finally, we showed that increasing hard/soft mineral index is strongly correlated with the displacement pressure in limestone samples. Vuggy texture displays a relatively strong and negative correlation with displacement pressure values at 10% mercury saturation in shale samples.