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Negative thermal expansion and phase transitions in the Niobium Oxyfluoride solid solution: NbO₂₋ₓF₁₊ₓ
Get PDFThe thermal expansion of functional materials is a significant property in any
applications involving significant temperature changes. Engineering and tuning
low thermal expansion is important for devices ranging from solid oxide fuel cells
to optical components in telescopes, where maintaining shape and stability are
vital. Whilst most materials expand rapidly on heating, a small minority exhibit
very low or negative thermal expansion (NTE). Expanding the range of these NTE
materials and fully understanding their thermal expansion origins is vital for the
design of multi-functional, low thermal expansion materials.
The cubic, ReO₃-type, structure is associated with NTE through flexibility of
octahedral tilt vibrations which lead to contraction on heating. The niobium
oxyfluoride solid solution, NbO₂₋ₓF₁₊ₓ, maintains a cubic ReO₃-type structure with
flexible oxygen:fluorine composition, thus providing an ideal system for
exploration of anion driven effects. This system is utilised in this thesis to explore
the impact of oxygen:fluorine composition on thermal expansion and phase
transitions as well as the fundamental chemistry and physics underpinning this.
A novel mechanism for the tuning of NTE through anion doping is uncovered in
this thesis as well as the first example of NTE in a mixed anion material.
Chapter One provides an overview of the importance of thermal expansion, a
review of the origins of NTE and current NTE materials. The ReO₃-type structure,
the origins of NTE and cubic to rhombohedral phase transitions are reviewed.
Chapter Two follows on from this with a review of the underlying physics of
thermal and pressure behaviour from the perspective of phonons, equations of
state and Landau theory. The experimental and computational methodology
(powder diffraction, pair distribution function analysis and density functional
theory) used through the project are introduced.
Chapter Three will outline the synthesis and characterisation of the NbO₂₋ₓF₁₊ₓ
solid solution from x = 0 to x = 0.6. The composition is confirmed through
magnetic susceptibility and lattice parameter trends. The thermal decomposition
properties are also explored through thermogravimetric analysis to confirm the
presence of fluorine doping. Variable temperature powder X-ray diffraction is
used to characterise the thermal expansion behaviour. This is found to vary from
positive thermal expansion (NbO2F) to zero and then negative thermal expansion
(NbO1.4F1.6). The latter of which has a mean volumetric coefficient of thermal
expansion of −5 ppm K⁻¹. This novel NTE can be related to a thermal dependence
of the anion displacement parameters, confirming transverse anion motion to
drive the shift in thermal expansion. Unusual high temperature hysteresis in the
thermal expansion is also identified.
Chapter Four uses both neutron and X-ray powder diffraction at variable
temperature and pressure to explore the cubic to rhombohedral phase
transitions of NbO₂₋ₓF₁₊ₓ. A low temperature phase transition in NbO₂F is
confirmed whilst the fluorine doped samples remain cubic at all temperatures.
The high-pressure, rhombohedral, phase transition is also found to be inhibited
by fluorine doping with the transition pressure shifting from 0.3 GPa in NbO₂F to
1.3 GPa in NbO₁.₇F₁.₃. This confirms predictions from existing density functional
theory (DFT) modelling indicating the cubic ReO₃-type structure is stabilised by
fluorine doping.
In Chapter Five, the origins of the thermal expansion and phase transitions in
NbO₂₋ₓF₁₊ₓ are explored through DFT phonon calculations and X-ray Pair
Distribution Function (PDF) analysis. High symmetry models of NbO₂F and
NbOF₂ are constructed and the phonon dispersions and Grüneisen parameters
are calculated. Soft modes with negative Grüneisen parameter have a negative
contribution to thermal expansion. These are identified at the Brillouin zone
boundary corresponding to octahedral tilting modes, confirming these modes as
key to thermal expansion. A mode with much more negative Grüneisen
parameter is identified in NbO₂F, consistent with a more favourable phase
transition under pressure in this composition. This instability to octahedral
tilting is attributed to a second order Jahn-Teller effect which is inhibited in
fluorine doped phases. X-ray PDF analysis at low temperature is consistent with
a 1D ordering of oxygen and fluorine in all compositions. Significant local static
distortion of both the Nb and anions is identified in all phases but found to be
smaller in the fluorine doped phases. A reduction in local distortion is able to
favour structural NTE which therefore accounts for the observed thermal
expansion behaviour. NTE in the oxyfluorides can therefore be understood in
terms of static vs dynamic anion displacements.
Chapter Six summarises the key conclusions of this thesis and outlines potential
future work on the NbO₂₋ₓF₁₊ₓ system. A review of existing materials and
conclusions of this thesis are used to construct design rules for the discovery of
novel mixed anion NTE materials. Some candidates are proposed from existing
ReO3-type oxyfluorides which may exhibit NTE
Microwave remote sensing of snow and the lower atmosphere in polar regions
Get PDFEurope faces an increasing vulnerability to frequent extreme weather events, requiring enhanced predictive capabilities within the high latitudes through improved Numerical Weather Prediction (NWP) models. Currently, limited data availability due to sparse weather station networks prevents high-latitude predictive accuracy. Microwave sounding radiances, notably at 50 and 183 GHz, offer vital atmospheric temperature and humidity profile data, vital for correcting forecast initial conditions. However, challenges arise from variable snow and sea ice emissions, inhibiting data assimilation into forecast models. The refinement of snow emissivity modelling enables atmospheric observation assimilation, thereby improving NWP models.
This thesis presents a coupling of two models to illustrate the assimilation of microwave radiances into NWP models: the Factorial Snow Model (FSM) simulates snow microphysical properties influencing microwave emissions and the Snow Microwave Radiative Transfer (SMRT) model accurately simulates microwave emissivity across frequencies.
Initial research integrates and validates these models using data from Trail Valley Creek (TVC), Northwest Territories, Canada. Comparison of in-situ snow pit data with FSM-generated snowpack profiles reveals a precise simulation of density and snow grain size profiles characteristic of Arctic tundra snowpacks. However, FSM fails to capture variability in snow pit profiles. Coupling FSM with SMRT, simulated brightness temperatures (T₈) at 89 GHz are compared to ground-based radiometer observations. SMRT's superior performance using FSM-simulated snow inputs (mean error: -4.4 K) contrasts with snow pit data (mean error: 11.9 K). Sensitivity tests indicate snow grain size as the most influential factor in snow surface emissivity.
In the thesis's concluding phase, SMRT-driven simulations expand to the NWP grid scale across frequencies from 10.65 to 234 GHz. T₈ generally increases with frequency, except at atmospheric window channels (157 and 243 GHz). Spatial variability, frequency-dependent, is minimal at the lowest (≤ 18.7 GHz)
and highest frequencies (≥ 118 GHz) due to reduced scattering. Intermediate frequencies (37 and 89 GHz) exhibit greater spatial variability due to increased snowpack scattering.
In summary, large spatial and temporal variations in Arctic tundra snow emissivity highlight the necessity for precise emissivity simulations grounded in accurately modelled or observed microphysical snow properties. This approach contrasts with the static emissivity values prevalent in many NWP systems
Study of Major Histocompatibility Complex (MHC) allelic diversity and haplotyping structures in livestock populations
No full textThe Major Histocompatibility Complex (MHC) plays a crucial role in the immune system by binding peptides within the peptide-binding groove and presenting them to T-cell receptors (TCR). This interaction enables T-cells to detect abnormal peptide-MHC complexes, signalling potential infections or pathological conditions. The extensive polymorphism in MHC genes, especially in their peptide-binding regions, allows the presentation of a wide variety of antigenic peptides, enhancing the immune system's adaptability. Understanding diversity of the MHC system is crucial for elucidating immune responses in all species. MHC molecules are classified into two groups: MHC class I (MHCI) and MHC class II (MHCII), each with distinct structures, functions and level of polymorphism. Currently, publicly available data on MHC in agricultural species are limited, not only in terms of sequence availability but also regarding in-depth studies on MHC diversity, expression, and haplotype structural characteristics. To address this, we developed a method to sequence the hypervariable peptide-binding domains of MHCI and MHCII using the Illumina MiSeq platform. Initially, this protocol was applied to a diverse group of cattle breeds from regions where indigenous populations consist of either Bos indicus or African Bos taurus. The method was subsequently adapted for its use in horses and sheep.
This study mainly focused on the development of a comprehensive bioinformatics pipeline for analysing Next Generation Sequencing (NGS) data for identification of MHC alleles and accurately identifying MHCI and MHCII haplotypes. The developed workflow processes raw sequencing data to filter out artefacts and assigns haplotypes with precision. We first used a dataset of Holstein-Friesian cattle to develop and validate the MHC typing method. The modular design of the pipeline was adapted to analyse MHC haplotype structures in different farm species, allowing efficiently characterized MHC repertoire across multiple livestock populations. We also identified novel MHC alleles and haplotypes within each population, significantly expanding the known MHC repertoire in cattle, sheep and horse. To further refine our understanding of MHCI, we sequenced full-length MHCI genes using the Pacific BioSciences (PacBio) platform. Combined with high-quality MiSeq data, this approach enabled full sequence characterization of MHCI genes, providing a robust and detailed insight into their diversity.
The data generated through this method provided a comprehensive framework for studying the complex MHC haplotype structures in horses and sheep for the first time. It also enabled the exploration of gene associations within MHCI and MHCII haplotypes. Additionally, the approach highlighted the varying levels of MHC diversity across different cattle breeds. By leveraging MHC genes as markers, this analysis estimated haplotype complexity shaped by linkage disequilibrium (LD) and recombination within the MHC region.
This system provides a rapid, reliable approach for screening MHC alleles or haplotypes in populations, significantly improving the resolution and accuracy of MHC typing in farm animals. These findings offer valuable insights into immune function and genetic diversity, contributing to breeding programs, disease resistance studies and immunopeptidomics
Relating-with epistemic injustice: affects, movement, towards a creative-relational inquiry
No full textThis thesis engages with assemblage/ethnography and creative-relational inquiry to explore epistemic injustice as affective, relational and always in motion. It follows fractured, shifting movements, resisting linearity and containment. Thinking with ‘the posts’ (post-structuralism, post-humanism) this work doesn’t escape the messiness but rather finds a way to put it forward, showing how research never is, but rather always goes on.
Initially framed as delving with ‘three ethnographic entry points’ (personal, cultural, and the academy), this inquiry spilled elsewhere, attending to the accumulative force of events (Stewart, 2008) as inherently affective. Assemblage/ethnography emerged as a way of reading-thinking-writing with forces, hauntings, desires, intimacies and relational entanglements, shifting epistemic injustice from a fixed concept to something that moves, circulates and unfolds.
Samay moves through this inquiry, not as a metaphor, but as a force, a breath, an unsettling and sustaining of/for relational presence(s). It does not offer comfort or resolution but reminds us to pay attention to what resists capture, to what breathes far beyond the words. Samay carries (among other things) this thesis forward, interrupting and holding together fragments of a piece of work that does not conclude but lingers.
The processual nature of the writing itself is at the heart of this work, taking the inquiry to be mindful of what ‘I’ and ‘other’ is being produced and the implications of it. Unconventional articulations (Manning, 2013) are made, between memories, sensed experiences, alternative realities, metaphors, (among others) which bring light to the different ways to consider the relationality of research and mental health practices, transgenerational histories, social sciences research, human relations, or university structures to the overall theme of epistemic injustice.
I follow hooks, expand on them, relate to concepts (Deleuze & Guattari, 1994) not as simply detached inanimate elements, but as moving, accumulation of, processual relationships. Sometimes I show myself more than the concepts, sometimes it is the other way around, sometimes you’ll find yourself near the accounts, or at times be disconnected; there are distances, intensities, and potencies that are simultaneously far and close, expanding and contracting, personal and social, present-past-future; an inquiry that takes you into these spaces in between and with(in) them
Stability of evaporating sessile droplets comprising of volatile binary mixtures
Get PDFThis thesis investigates the evaporation dynamics and stability of evaporating sessile
droplets comprised of volatile binary component mixtures. This is carried out by building, developing and utilising two new theoretical modelling linear stability analysis
approaches on a lubrication model as well as implementing experimental approaches
to analyse thin, volatile binary droplets. The primary focus is on understanding the
influence of solutal Marangoni effects, surface tension and concentration gradients
on droplet stability at the contact line.
Firstly, the stability of thin volatile droplets comprising of binary mixtures deposited
on a heated substrate is examined using a linear stability analysis approach under
the quasi-steady state approximation (QSSA). A base state is first established using
lubrication theory approximation on a one sided model. The QSSA analysis is performed by freezing the transient base state at an early time instance and applying
small perturbations to the governing base state equations and boundary conditions.
The results from the first theoretical modelling stability analysis approach indicate
that the addition of a second component significantly destabilises the droplet, with
high growth rates and wavenumbers revealing several competing modes of instability.
Secondly, to gain further insight into the stability droplet dynamics, a transient growth
linear stability analysis (TGA) is conducted, incorporating a time-dependent element
to provide a comprehensive picture of the instabilities occurring in thin volatile binary
component droplets. Results from the two stability analysis methods on our theoretical
model highlight the concentration and surface tension as strong dominant destabilising factors, suggesting instabilities arise due to the increase in solutal Marangoni
flows with the addition of another component in the droplet.
Thirdly, experimental investigations are conducted to complement the initial theoretical modelling predictions. Experiments are performed examining the behaviour of thin
droplets comprising of binary ethanol-water mixtures of varying concentrations on a
very smooth heated hydrophilic glass substrate. Detached waves or ’spokes’ are identified and observed around the droplet contact line during spreading and evaporation,
attributed to the presence of the second more volatile component, ethanol. These
visual contact line instabilities are compared to the theoretical predictions observed
from the two linear stability analysis approaches.
This thesis demonstrates how combining linear stability modelling with thermal imaging experiments yields a holistic understanding of interfacial instability in volatile
binary droplets. The results confirm the critical role of concentration gradients and
surface tension gradients in destabilising the flow at the droplet contact line, offering
qualitative agreement between experiments and theoretical modelling predictions.
This shows that solutal Marangoni effects play a critical role in driving instability
formation localised at the droplet edge contact line. The insights gained from this
research offer a valuable foundation for further research and contribute to a deeper
understanding of the complex behaviour of evaporation volatile binary droplets and
their stability dynamics.This thesis investigates the evaporation dynamics and stability of evaporating sessile
droplets comprised of volatile binary component mixtures. This is carried out by building,
developing and utilising two new theoretical modelling linear stability analysis
approaches on a lubrication model as well as implementing experimental approaches
to analyse thin, volatile binary droplets. The primary focus is on understanding the
influence of solutal Marangoni effects, surface tension and concentration gradients
on droplet stability at the contact line.
Firstly, the stability of thin volatile droplets comprising of binary mixtures deposited
on a heated substrate is examined using a linear stability analysis approach under
the quasi-steady state approximation (QSSA). A base state is first established using
lubrication theory approximation on a one sided model. The QSSA analysis is performed
by freezing the transient base state at an early time instance and applying
small perturbations to the governing base state equations and boundary conditions.
The results from the first theoretical modelling stability analysis approach indicate
that the addition of a second component significantly destabilises the droplet, with
high growth rates and wavenumbers revealing several competing modes of instability.
Secondly, to gain further insight into the stability droplet dynamics, a transient growth
linear stability analysis (TGA) is conducted, incorporating a time-dependent element
to provide a comprehensive picture of the instabilities occurring in thin volatile binary
component droplets. Results from the two stability analysis methods on our theoretical
model highlight the concentration and surface tension as strong dominant destabilising
factors, suggesting instabilities arise due to the increase in solutal Marangoni
flows with the addition of another component in the droplet.
Thirdly, experimental investigations are conducted to complement the initial theoretical
modelling predictions. Experiments are performed examining the behaviour of thin
droplets comprising of binary ethanol-water mixtures of varying concentrations on a
very smooth heated hydrophilic glass substrate. Detached waves or ’spokes’ are ideniii
tified and observed around the droplet contact line during spreading and evaporation,
attributed to the presence of the second more volatile component, ethanol. These
visual contact line instabilities are compared to the theoretical predictions observed
from the two linear stability analysis approaches.
This thesis demonstrates how combining linear stability modelling with thermal imaging
experiments yields a holistic understanding of interfacial instability in volatile
binary droplets. The results confirm the critical role of concentration gradients and
surface tension gradients in destabilising the flow at the droplet contact line, offering
qualitative agreement between experiments and theoretical modelling predictions.
This shows that solutal Marangoni effects play a critical role in driving instability
formation localised at the droplet edge contact line. The insights gained from this
research offer a valuable foundation for further research and contribute to a deeper
understanding of the complex behaviour of evaporation volatile binary droplets and
their stability dynamics
Evaluating and optimising the AArch64 ecosystem for HPC
Get PDFIn recent years, Arm-based processors have become a viable alternative to Intel or
AMD CPUs for HPC systems. To make this possible, hardware and software evolved
greatly to meet the complex performance needs of HPC applications. In this thesis,
we assess the readiness of the AArch64 ecosystem for mainstream HPC usage, and
provide improvements to the areas we found to be lacking. We start by performing a
preliminary evaluation of the maturity of the support and performance of the AArch64
ecosystem as of 2020, when production-grade AArch64 HPC systems were emerging.
This led us to find: new optimisation opportunities enabled by AArch64’s features,
such as its novel scalable vector extension (SVE); generally competitive hardware
performance, although with some classes of code patterns showing reduced performance
on certain microarchitectures; and generally mature support from the surrounding
software ecosystem, in particular compilers, despite a few instances of suboptimal code
generation. These observations motivated the majority of the work of this thesis, as
summarised below, with the goal of improving the maturity of the AArch64 ecosystem
further.
In particular, we explore the usage of AArch64’s scalable vector extension (SVE) to
vectorise number-theoretic transforms (NTTs). We show that SVE enables the efficient
implementation of 64-bit modular arithmetic operations, including modular multiplication.
This enables the efficient vectorisation of NTT loops and other large integer
arithmetic codes, which was previously not possible with traditional single instruction
multiple data (SIMD) architectures as these architectures lack crucial instructions to
efficiently implement 64-bit modular multiplication. We test and evaluate our SVE
implementation on the Fujitsu A64FX processor in an HPE Apollo 80 system. Furthermore,
we implement a distributed NTT for the computation of large-scale exact integer
convolutions. We evaluate this transform on Arm-based HPE Apollo 70, Cray XC50,
and HPE Apollo 80 systems, where we demonstrate good scalability to thousands of
cores. Further, we demonstrate how these methods can be utilised to count the number
of Goldbach partitions of all even numbers to large limits. Employing a total of 2048
Marvell ThunderX2 cores, we carry out the computation to the world-record limit of
2⁴⁰.
Furthermore, we evaluate the performance of compare-and-swap (CAS) operations,
implemented via traditional load/store-exclusive (LL-SC) instruction pairs or the newer
CAS instructions introduced with the Armv8.1-A large system extension (LSE), on
several high-performance Arm-based CPUs such as the A64FX, ThunderX2, and
Graviton3. We observe that CAS and LL-SC instructions can lead to fundamentally
different performance profiles, revealing shortcomings in some implementations. On
the A64FX, for example, the newer CAS instructions, preferred by compilers and
libraries over the older LL-SC pairs, can in some instances lead to a quadratic increase
in average time per successful CAS operation as the number of threads contending
for the operation increases, whilst the traditional LL-SC approach shows the expected
constant behaviour. For high thread counts, this difference translates into a speedup of
more than 20× when using LL-SC instructions. We characterise the conditions under
which the LL-SC or CAS approaches are preferable on each CPU, and the speedup that
can be realised by favouring one strategy over the other.
Finally, we explore the performance of the main optimising compiler toolchains
currently available for AArch64 processors on the recently released NVIDIA Grace
CPU. We consider the Arm Compiler for Linux (ACFL), GCC, LLVM and the NVIDIA
HPC (NVHPC) compilers. We evaluate the quality of the code generated by these
compilers using the RAJA Performance Suite (RAJAPerf) to understand the cases
where each compiler does best, and why. We find that compilers mostly generate
well optimised code on baseline sequential runs, with the gap between the fastest and
slowest being 8% on average. Threaded parallel runs show a larger variation, with
this gap increasing to approximately 33% on average. We investigate those kernels
where LLVM performs worst relative to the remaining compilers in detail and propose
optimisations to improve code generation in those cases. We show scenarios where the
default compiler behaviour produces suboptimal code and where adjusting compiler
flags, such as those controlling loop unrolling or vectorisation decisions, can improve
performance significantly. In cases where this is insufficient, we propose changes at
the compiler level necessary to enable improved code generation and unlock further
optimisations. These improvements account for speedups of over 70% in some kernels.
Overall, we conclude that the AArch64 ecosystem has reached maturity and the few
corner cases that remain pose no real challenge to its widespread adoption in HPC
Scottish Landfill Tax: lower rate review
Get PDFThe report provides an initial evidence base to assess the effectiveness of the lower tax rate and explores potential changes to better support a low-carbon, circular economy. It examines the most common materials, their environmental impact, the feasibility of diversion and the range potential options to explore for policy reform
Improving complex reasoning in large language models
Get PDFThis thesis studies complex reasoning in language models. We use the term reasoning to refer to tasks that would require a human to perform slow deliberate, step-by-step thinking (instead of providing an intuitive and instantaneous response) , such as mathematical and scientific reasoning, commonsense reasoning, logical reasoning, and strategic reasoning. We use reasoning capability to collectively refer to the ability to solve tasks requiring complex sub-problem decomposition and detailed step-by-step analysis.
Our motivation for studying reasoning in language models stems from intriguing theoretical properties (e.g., how scaling laws relate to emergent abilities) and their vast application potential. From an application perspective, we envisage large language models (LLMs) to become the next-generation computational platforms, just like operating systems, and aim to build a new application ecosystem upon LLMs. This vision naturally requires the underlying base model to be able to reason over various complex real-world scenarios. From a modeling perspective, complex reasoning is viewed as a typical ability that emerges with scaling: given other conditions being proper (e.g., given clean data and stable training process), the more compute one spends, the more likely the model has stronger reasoning capability.
We start by reviewing the learning paradigms of large language models, and then discuss fundamental methods for improving reasoning along multiple stages of the model development pipeline. Typically, modern language model development consists of four stages: pretraining, instruction finetuning, reinforcement learning from human feedback, and in-context learning after model deployment. This thesis discusses improving reasoning by in-context learning, finetuning, and learning from feedback. For in-context learning, we propose complexity-based prompting, and demonstrate that the model’s scientific and logical reasoning performance consistently improves as the complexity of in-context demonstrations improves. This work achieved state-of-the-art performance on the GSM8K [Cobbe et al., 2021] and MATH [Hendrycks et al.] datasets at the time it was proposed and has influenced follow-on work by highlighting the importance of data complexity. For instruction tuning, we devise a detailed recipe for
specializing smaller language models on mathematical reasoning tasks. We highlight the importance of chain-of-though formatted data, the use of a finetuned checkpoint, and the balance between capabilities of different directions. This work significantly improved small models’ GSM8K and other math performance by the time it was proposed and has consistently influenced follow-on work by highlighting the importance of capability balancing. For learning from AI feedback, we show the possibility of constructing a self-improving agent on strategic reasoning tasks by letting agents play against and criticize each other, and show that the ability to self-improve is strongly correlated with the base model and how much it aligns with human instructions. Finally, we review the current state-of-the-art models, highlighting the benchmark saturation problem and the importance of constructing new challenging datasets. We further discuss future directions on multimodal scaling and iterative learning from human, environment, and AI feedback
Post-glacial fluvial dynamics of the British Isles
No full textThroughout the Quaternary, ice sheets and glaciers episodically expanded to cover
up to 30 percent of the Earth’s surface. Many of these areas are now ice-free due to
climatic warming after approximately 14.5 ka. Rivers are the main erosional agents
and drivers of landscape evolution in post-glacial landscapes; however, their response
to past glaciations is notoriously complex. Key challenges associated with understanding
fluvial processes in post-glacial landscapes originate from the glacial modification
of hillslopes and channels, such as decoupling of hillslopes from channels
due to the over-deepening and widening of valleys by glaciers, or extensive glacial
sediment drapes (e.g., till, moraines, paraglacial terraces) which influence sediment
supply and transport capacity. Additionally, Glacial Isostatic Adjustment (GIA) results
in considerable spatial and temporal variations in relative sea-levels, which set the
base-levels of rivers. Rivers communicate changes in base-level to the rest of the
landscape by the upstream propagation of transient signals. Relatively little research
has quantified geomorphic processes in post-glacial landscapes in post-orogenic
regions. Much geomorphological research has focused on unglaciated landscapes
and glaciated landscapes in tectonically active regions.
In the first part of this thesis, I explore the controls on erosion rates in the post-glacial
Feshie basin, Scotland. Erosion rates are inferred from the concentration of in-situ
cosmogenic radionuclides (CRN) measured in river sands. When erosion rates are
calculated based on the common assumption of basin-wide homogeneity of erosion,
I counter-intuitively find no correlation between erosion rates and topographic metrics
(e.g. slope). To explain the concentrations, I suggest that sediment is sourced from
both the ‘background’ hillslopes and paraglacial terraces. I test this hypothesis with a
mixing model, which indicates that the observed distribution of CRN concentrations
can be explained if terrace escarpments have cm-scale retreat rates during large flood
events. These results highlight the on-going glacial legacy on landscape evolution.
In the second part of this thesis, I explore controls of fluvial grain sizes in Scotland.
I document river surface grain sizes at 300 locations through a citizen science survey.
I then investigate whether grain sizes can be correlated and predicted from
environmental variables (e.g., basin slope, flow distance from headwaters) through
Spearman’s correlation statistics and random forest regression modelling. In contrast
to other studies that have primarily focused on non-glaciated landscapes, we find no
apparent controls on surface grain sizes in channels across Scotland. I suggest that
Scotland’s post-glacial legacy drives the lack of sedimentological trends, which aligns
with the interpretations from the first research chapter.
In the third part of this thesis, I explore the response of rivers to base-level rise
(which is largely driven by GIA) and coastal erosion in Southern England. Emerging
research suggests that coastal erosion can initiate the formation of migrating
knickpoints. Through topographic analysis, I find that some rivers have migrating
knickpoints in Southern England. I then investigate the fluvial and coastal factors influencing
these knickpoints at the regional scale, as outlined by previous research. I find
a clear lithological control: channels underlain by more resistant rocks consistently
incise at their outlets, compared to less resistant rocks, for a given drainage area (<
25km2). However, I find no drainage area or coastal erosion rate control.
Overall, this thesis contributes to the growing body of research quantifying landscape
evolution in regions affected by glaciation. Importantly, I find that post-glacial landscapes
in post-orogenic terrains are largely influenced by the glacial legacy more
than 10 ka after deglaciation. Moreover, I find that past glaciations influence river
processes in regions that have not been glaciated through base-level rise from GIA
Is the Women, Peace, and Security Agenda Still Relevant for Afghanistan?
Get PDFThis policy brief looks at the progress and setbacks of women’s rights in Afghanistan and the different approaches and interventions under the WPS Agenda. It first provides a comprehensive analysis of gains made from 2001 to 2021, followed by the Taliban’s policies over the past three years and their devastating impact on women’s rights and participation. It then evaluates the application and limitations of the WPS Agenda in Afghanistan, identifying the exclusion of Afghan women from peace processes, increasing restrictions on their rights, and inconsistent and often inadequate international engagement as critical challenges. Finally, this brief provides actionable recommendations for policymakers, member states, and stakeholders, integrating lessons from experiences in other conflict-affected regions
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