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Landfill site trees: Potential source or sink of greenhouse gases?
Tree stems can transport greenhouse gases (GHGs) produced belowground to the atmosphere. Previous studies in natural wetland and upland ecosystems have quantified tree stem fluxes of methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O). However, tree stem GHG fluxes have not previously been measured in the context of managed environments. The work presented in this thesis aimed to quantify GHG fluxes from tree stems on closed landfill sites.
To investigate the potential for trees growing on closed landfill sites to act as conduits for GHGs produced belowground to the atmosphere, GHG fluxes were measured from tree stem and soil surfaces. In situ measurements from a closed landfill site in the UK were examined for spatial and temporal patterns and evaluated against data from a comparable non-landfill area. Measurements were also conducted from landfill sites in the UK with varying management practices and different tree species present. The resulting flux values were scaled up to estimate the magnitude of tree stem GHG fluxes from closed landfills at a national level.
The findings presented here show evidence of tree mediated GHG transport on closed landfill sites and temporal variations in fluxes from tree stems were also observed, with generally higher fluxes in the summer months. Stem CH4 fluxes varied between trees growing on landfill sites with different management practices. Additionally, stem N2O fluxes displayed spatial patterns, with decreasing emissions at increased height from the forest floor, indicating an underground source. Evidence suggested that GHG fluxes from closed landfills are influenced by factors including the quantity of GHG produced in the waste (linked to the age of the site), the susceptibility of the area to waterlogging and landfill management techniques put in place upon closure (for example, clay caps, cover soils and gas extraction). Upscaled CH4 and N2O flux values from tree stems on closed landfill sites corresponded to less than 1% of the total CH4 and N2O emissions reported from UK landfills in 2020.
Overall, results indicated that measuring soil fluxes alone from forested landfill sites would result in an underestimation of the total surface fluxes. However, the emission rates from tree stems on closed landfills observed in this thesis do not exceed those in natural ecosystems. Therefore, with careful planning and management, the recommendation is that trees can be planted on closed landfill sites in the UK without emitting atypical levels of GHGs. However, including gas fluxes from tree stems on closed landfills would increase the accuracy of GHG budgets at national and global levels
Applications and Properties of Magnetic Nanoparticles
This Special Issue aimed to cover the new developments in the synthesis and characterization of magnetic nanoconstructs ranging from conventional metal oxide nanoparticles to novel molecule-based or hybrid multifunctional nano-objects. At the same time, the focus was on the potential of these novel magnetic nanoconstructs in several possible applications, e.g. sensing, energy storage, and nanomedicine
Data Tiling for Sparse Computation
Many real-world data contain internal relationships. Efficient analysis of these relationship data is crucial for important problems including genome alignment, network vulnerability analysis, ranking web pages, among others. Such relationship data is frequently sparse and analysis on it is called sparse computation. We demonstrate that the important technique of data tiling is more powerful than previously known by broadening its application space. We focus on three important sparse computation areas: graph analysis, linear algebra, and bioinformatics. We demonstrate data tiling's power by addressing key issues and providing significant improvements---to both runtime and solution quality---in each area. For graph analysis, we focus on fast data tiling techniques that can produce well-structured tiles and demonstrate theoretical hardness results. These tiles are suitable for graph problems as they reduce data movement and ultimately improve end-to-end runtime performance. For linear algebra, we introduce a new cache-aware tiling technique and apply it to the key kernel of sparse matrix by sparse matrix multiplication. This technique tiles the second input matrix and then uses a small, summary matrix to guide access to the tiles during computation. Our approach results in the fastest known implementation across three distinct CPU architectures. In bioinformatics, we develop a tiling based de novo genome assembly pipeline. We start with reads and develop either a graph or hypergraph that captures internal relationships between reads. This is then tiled to minimize connections while maintaining balance. We then treat each resulting tile independently as the input to an existing, shared-memory assembler. Our pipeline improves existing state-of-the-art de novo genome assemblers and brings both runtime and quality improvements to them on both real-world and simulated datasets.Ph.D
Maturation of the modern human skeleton
Background: Maturation is the process of becoming mature and reaching the adult state. Maturation occurs in all body systems, but two well-studied maturation processes that occur during modern human growth are skeletal and sexual maturation. Both processes can be studied on dry bone. Variations between individuals and populations are attributed to genetics and environmental influences. Research into maturation can provide new insights into past lives and modern human biology.
Aim: This research examines maturation and development in modern humans using archaeological skeletal collections from England and Scotland. This research looks explicitly at epiphyseal fusion and puberty to determine if the age of occurrence and sequence of these growth events changed between the Iron Age (< 800 BC) and the Post-Mediaeval (1855 AD) period.
Materials: Two hundred and sixty-one skeletons from different periods across England and Scotland were analysed. This included 11 skeletons from Broadstairs (2000 to 350 BC), twenty-four skeletons from Roman Cirencester (69 to 406 AD), thirty-nine skeletons from Anglo-Saxon Chichester, Cirencester, Newcastle, and Auldhame (434 to 1178 AD), one hundred and eighty skeletons from Mediaeval Canterbury, Cirencester, York, and Auldhame (1000 to 1537 AD), and 7 Post-Mediaeval skeletons from Sheffield and Auldhame (1500 to 1855 AD).
Method: An average age-at-death was calculated for each skeleton, mainly from dentition. A stage of fusion (Stage 1: unfused, Stage 2: partially fused, and Stage 3: completely fused) was then assessed for various epiphyses found in the skull, neck, shoulder, elbow, wrist, hip, knee and ankle. Age-at-fusion of each epiphyseal site, order of the fusion sequence and pubertal phase (assessed using selected fusion sites and other elements) were then compared between groupings of skeletons based on social status, archaeological site and time period. Statistical tests were conducted on the data. This included; a goodness-of-fit chi-square to determine if there was a significant relationship between age and fusion, a Mann-Whitney U test to assess significant differences between pubertal phases across the time periods. A binomial logistic regression determined whether age-at-fusion could be distinguished between skeletons of different social statuses. A multiple regression analysis was employed to determine if age-at-fusion could be predicted from multiple variables.
Results: Statistically significant associations between age and fusion indicate four sites (anterior arch and posterior synchondrosis of the atlas, the dentocentral and neurocentral junctions of the axis, and metacarpals 2 - 5, proximal and middle phalangeal epiphyses of the hand) which can contribute to age-at-death estimates for Mediaeval skeletons. Age-at-fusion did not differ significantly between high and low-status skeletons from Mediaeval St Gregory's or when compared between Mediaeval archaeological sites. The cervical vertebrae were the exception.
Skeletal maturation was significantly delated in the proximal radius during the Anglo-Saxon period compared to the Mediaeval period, although several other fusion sites in the Anglo-Saxon appendicular skeleton approached significance. Age at pubertal phase did not differ when compared between the archaeological periods or within the Mediaeval period. Finally, a typical sequence of fusion was discerned: Elbow - (Hip) - Ankle - (Shoulder) - Knee - Wrist. Slight variations in the sequence occurred throughout British history, a similar finding reported by previous research.
Conclusion: This is the first in-depth examination of epiphyseal fusion throughout British history. A key strength of this research is that the same methodology was applied throughout, and therefore comparisons made between data are not influenced by methodological bias. Limited variation in age-at-fusion among the Mediaeval sites is likely due, in part, to similarities in the diet of the sites examined here. Delayed maturation in the Anglo-Saxon period coincided with political and economic unrest that could have affected physical development. Results support the idea that age-at-puberty has only begun to decrease for certain pubertal phases. Only the placement of the shoulder in the sequence of fusion differed in this research compared to previous analyses, and this is likely due to a difference in methodology rather than physiology
Antimicrobial Peptides Aka Host Defense Peptides – From Basic Research to Therapy
This Special Issue reprint will address the most current and innovative developments in the field of HDP research across a range of topics, such as structure and function analysis, modes of action, anti-microbial effects, cell and animal model systems, the discovery of novel host-defense peptides, and drug development
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
Laplacian regularized eikonal equation with Soner boundary condition on polyhedral meshes
In this paper, we propose a numerical algorithm based on a cell-centered
finite volume method to compute a distance from given objects on a
three-dimensional computational domain discretized by polyhedral cells.
Inspired by the vanishing viscosity method, a Laplacian regularized eikonal
equation is solved and the Soner boundary condition is applied to the boundary
of the domain to avoid a non-viscosity solution. As the regularization
parameter depending on a characteristic length of the discretized domain is
reduced, a corresponding numerical solution is calculated. A convergence to the
viscosity solution is verified numerically as the characteristic length becomes
smaller and the regularization parameter accordingly becomes smaller. From the
numerical experiments, the second experimental order of convergence in the
norm error is confirmed for smooth solutions. Compared to solve a
time-dependent form of eikonal equation, the Laplacian regularized eikonal
equation has the advantage of reducing computational cost dramatically when a
more significant number of cells is used or a region of interest is far away
from the given objects. Moreover, the implementation of parallel computing
using domain decomposition with -ring face neighborhood structure can be
done straightforwardly by a standard cell-centered finite volume code
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
Label errors have been found to be prevalent in popular text, vision, and
audio datasets, which heavily influence the safe development and evaluation of
machine learning algorithms. Despite increasing efforts towards improving the
quality of generic data types, such as images and texts, the problem of
mislabel detection in graph data remains underexplored. To bridge the gap, we
explore mislabelling issues in popular real-world graph datasets and propose
GraphCleaner, a post-hoc method to detect and correct these mislabelled nodes
in graph datasets. GraphCleaner combines the novel ideas of 1) Synthetic
Mislabel Dataset Generation, which seeks to generate realistic mislabels; and
2) Neighborhood-Aware Mislabel Detection, where neighborhood dependency is
exploited in both labels and base classifier predictions. Empirical evaluations
on 6 datasets and 6 experimental settings demonstrate that GraphCleaner
outperforms the closest baseline, with an average improvement of 0.14 in F1
score, and 0.16 in MCC. On real-data case studies, GraphCleaner detects real
and previously unknown mislabels in popular graph benchmarks: PubMed, Cora,
CiteSeer and OGB-arxiv; we find that at least 6.91% of PubMed data is
mislabelled or ambiguous, and simply removing these mislabelled data can boost
evaluation performance from 86.71% to 89.11%.Comment: ICML 202
Course Manual on Fundamentals of Artificial Reefs for Improving Marine Fisheries in India
Artificial reefs are set on the seabed to enhance the growth of marine floral and faunal
benthic communities which simulate natural settings for promoting fish aggregations and
provide the base for the propagation of resident populations within sheltered structures.
They are being used in several parts of the world to promote habitat recovery and enhance
reef-dependant resources. The advantage of artificial reefs is in developing fishing grounds
close to shore, easily accessible to traditional and non-destructive fishing methods, ensuring
the sustainability of both, the habitat, and the resources therein
Computational modelling of the effect of side chain chemistry on the micro-structure and electrolyte interactions of mixed transport polymers
As we scale up our use of energy storage facilities to meet the demands of the future, the prob- lems associated with current energy storage technologies will grow to unacceptable levels. In this work I explore how we can develop high performing polymers for use as cathode materials in energy storage devices operating with aqueous electrolytes. Energy storage devices using these materials have the potential for low cost production and safe operation. Through a combination of atomistic simulation methods, this thesis relates aspects of the polymer chemistry to their microstructural properties, and subsequently to their ability to operate successfully as electrodes.Open Acces
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