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Synthesising conversational speech using found data
Get PDFEnd-to-end speech synthesis models perform well when trained with clean read speech
data. Modelling conversational speech, the form of speech that we use every day, however,
is more challenging. First, we lack high-quality conversational datasets that are suitable for
training speech synthesis models. Second, conversational data is highly variable, containing
challenging spontaneous phenomena, such as overlapping speech and laughter. Third,
each conversational utterance is embedded in a communicative context, and there are many
contextual factors which must be accounted for. Finally, there exists a significant
knowledge gap with respect to our understanding of both speech perception and speech
production in context, both in the fields of speech technology and speech science.
In this work, we addressed these issues in three parts. In Part 1, we examined three
factors that potentially affect the evaluation of speech synthesis output in context, namely
the task instructions, between-sentence textual dependency and the prosodic realisation of
the utterances. We found that task instructions can affect ratings, and we found that
presenting speech in context narrows the gap of Mean Opinion Scores between the
contextually appropriate utterance and the non-appropriate utterance. This suggests that
MOS might not be sufficiently sensitive to evaluate speech synthesis in context. We
conclude that more targeted evaluation is necessary to capture contextual effects.
In Part 2, we present two studies on improving conversational prosody using found
data and controllable synthesis. In the first study, we find that training a model on a data
mixture of found conversational speech (questions and answers) and read speech can
improve the realisation of questions as measured by an increase in preferences for our
datamix model over the baseline, which was only trained on read speech. For answers, no
significant difference between the systems was found. In the second study, we used a
linguistically-motivated word-level F0 representations based on Legendre Polynomial
coefficients to condition a FastPitch model, allowing us to control the intonation of an
utterance. We found that conditioning a model on these representations increases to
similarity of the F0 contours between the system output and the target output over the
baseline and a categorically-conditioned model. The proposed representations can then be
used to explore patterns in conversational speech.
In Part 3, we present two case studies investigating the impact of context on an
utterance’s prosodic realisation. In the first study, we used found data and our intonation
representations from Part 2 to explore prosodic variation on the discourse marker “well”.
Using clusters from the data exploration, we synthesised 20 different renditions of a
positive polarity utterance, well yes, and a negative polarity utterance, well no, and
performed a listening test to assess the degree of agreement perceived by listeners. We found
that the prosodic rendition of the utterance can affect the perceived agreement or
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disagreement of the speaker highlighting an example of the prosody-pragmatics interface.
In the second study, we used found data to explore turn-taking cues in conversation. We
found that conditioning a FastPitch speech synthesis model on turn-taking information
leads to perceptible differences in the turn-finality of an utterance as measured in subjective
listening tests. We showed that we can use speech synthesis to generate stimuli which reflect
the global trends in the training data and that this method can complement corpus research
in phonetics
Testing deep neural networks across different computational configurations
Get PDFDeep Neural Networks (DNNs) typically consist of complex architectures and require enormous processing power. Consequently, developers and researchers use Deep Learning (DL) frameworks to build them (e.g., Keras and PyTorch), apply compiler optimizations to improve their inference time performance (e.g., constant folding and operator fusion), and deploy them on hardware accelerators to parallelize their computations (e.g., GPUs and TPUs). We concisely refer to these aspects as the computational environment of Deep Neural Networks.
However, the extent to which the behavior of a DNN model (i.e., output label inference correctness and computation times) is affected when different configurations are selected across the computational environment, is overlooked in the literature. For example, if a DNN model is deployed on two different GPU devices, will it give the same predictions, and how will its computation times deviate across the devices? Given that DNNs are deployed on safety-critical domains (e.g., autonomous driving), it is important to understand the extent to which DNNs are affected by these aspects.
For that purpose, we present DeltaNN, a tool that allows DNN model compilation and deployment under different configurations, as well as comparison of model behavior across them. Using DeltaNN, we conducted a set of experiments on widely used Convolutional Neural Network (CNN) models performing image classification. We built these models using different DL frameworks, converted them across different DL framework configurations, compiled on a set of optimizations and deployed on GPU devices of varying capabilities.
Our experiments with different configurations led to two main observations: (1) while DNNs typically generate the same predictions across different GPU devices and compiler optimization settings, this is not true when utilizing different DL frameworks, and especially when converting from one DL framework to another (e.g., converting from Keras to PyTorch), a common practice across developers to enable model portability and extensibility; and (2) optimizations are not a panacea of inference time improvement across different devices, as the same optimization strategies that improve execution times on high-end GPUs were found to degrade them when applied on models deployed on low-end GPUs.
To mitigate the faults related to the conversion process, we implemented a framework called FetaFix. FetaFix performs automatic fault detection by comparing a number of aspects across the source and the converted target DNN model, such as model parameters, hyperparameters and structure. It then applies a number of fault repair strategies related to these aspects and checks how the converted model performs in comparison to its source counterpart. FetaFix was able to repair 93% of the problematic cases identified by DeltaNN.
Finally, we explored the effects of faults present in the target hardware acceleration device code towards DNN model correctness. Inspired by traditional mutation testing, we built MutateNN, a tool that generates DNN model mutants containing target device code faults. We then generated a number of faults in the target device code of numerous CNN models performing classification and evaluated how these models behaved across different hardware acceleration devices. We observed that faults related to conditional operations, as well as drastic changes in arithmetic types, considerably affected model correctness.
We conclude that different configurations of computational environment aspects can affect DNN model behavior. Our contributions summarize to (1) an empirical study on how the computational environment affects DNN model behavior, performed by a tool (DeltaNN) implemented specifically for that purpose, (2) a framework (FetaFix) that automatically detects faults related to model input, structure and parameters in converted DNN models across DL frameworks and repairs them, and (3) a utility (MutateNN) that introduces faults in the target code of DNN models associated with deployment on different hardware acceleration devices, and evaluates the effects of these faults on model correctness
A genomic perspective on speciation and hybridisation in Antirrhinum
Get PDFRapidly speciating lineages are important for generating diversity. However, the factors underlying the origins of diversity in evolutionary radiations are not well understood. Adaptive introgression has been identified as one potential cause of rapid speciation. The plant genus Antirrhinum provides an ideal study system to explore the potential role adaptive introgression may play in rapid speciation.
Antirrhinum species can be split into three morphological sections: Antirrhinum, Streptosepalum and Kickxiella. There has been recurrent evolution of species with the alpine Kickxiella morphology. One possibility behind this recurrent evolution is that it is caused by adaptive introgression of genes responsible for the Kickxiella morphology. The overall aim of this thesis is to determine how the Kickxiella morphology evolved multiple times in the Antirrhinum genus. First, I used RAD sequencing and whole genome sequencing datasets to build phylogenetic trees for Antirrhinum (Chapter 2). Phylogenetic trees produced conflicting results for how many times the Kickxiella morphology may have evolved. There was a high level of discordance present in the phylogenies, potentially caused by both incomplete lineage sorting and hybridisation. Hybridisation across the genus was supported by the lack of runs of homozygosity and the potential geographic clustering present in the chloroplast phylogeny rather than the species tree observed from the nuclear genome. D-statistic and phylogeny-based analyses were used to test for evidence of introgression between Kickxiella groups to determine support for the recurrent evolution of Kickxiella species via introgression (Chapter 3). Using short read whole genome sequence data D-statistics identified regions of the genome with signal of introgression between Kickxiella groups. However, genes contained within these regions were not clearly associated with the Kickxiella morphology and regions with signal of introgression were short, suggesting any introgression events occurred sufficient generations ago for introgressed regions to be eroded by recombination. Finally, a pangenome for the genus Antirrhinum was built using genome assemblies from across the Antirrhinum genus (Chapter 4). This aids the identification of structural variants that are shared across Kickxiella samples and may underlie their morphology. From the pangenome over 82,000 structural variants with a minimum length of 50 bp were identified across the genus. Two structural variants were found in all Kickxiella species and absent from other species, however they were not clearly associated with any aspect of Kickxiella morphology.
Overall, these findings suggest that standing genetic variation or de novo mutations at the nucleotide level may be responsible for the repeated evolution of the Kickxiella morphology. These findings offer insights into the evolutionary complexity that may have shaped the rapid evolution of the Antirrhinum genus
Magneto-structural investigations of N/O chelate ligands in 3d metal clusters
Get PDFMagnetic materials are ubiquitous in modern society, finding applications across information technology, healthcare and transport. The move to molecule-based magnets looks to exploit the quantum nature of molecules for quantum technologies, including quantum computing. Before any such application can be made practical chemists must first make and physically characterise the proposed molecules in order to develop detailed magneto-structural correlations. The first stage in this process is ligand design. Amongst the most successful choices are N/O chelate ligands. These ligands are small and flexible, possessing the ability to both chelate and bridge metal centres. This has led to the isolation and characterisation of numerous paramagnetic 3d transition metal clusters ranging in nuclearity, oxidation state and topology.
Chapter 1 summarises the most impactful N/O-supported 3d metal clusters reported in the literature, discussing the magnetic properties they display. These include single molecule and singe ion magnets, clusters displaying large spin ground states, enhanced magneto-caloric effects and geometric spin frustration.
Chapter 2 describes the synthesis and characterisation of a series of [Mᴵᴵ₄] cubanes (M = Mn, Co‒Zn) and the larger nuclearity clusters [Mnᴵᴵᴵ₂Mnᴵᴵ₁₂] and [Mnᴵᴵᴵ₁₄Mnᴵᴵ₄], built with (3,5-dimethyl-1H-pyrazol-1-yl)methanol (HL¹), and a [Niᴵᴵ₁₄] wheel supported by 3,5-dimethylpyrazole (HL²). Magnetic measurements for the cubanes reveal ferro- and antiferromagnetic exchange interactions for M = Ni, Cu and M = Mn, Co, respectively, the origin of the differences being the different M-O-M angles. Competing exchange interactions are present in [Mn₁₈] and [Mn₁₄], with the former possessing SMM behaviour. [Ni₁₄] displays ferromagnetic nearest neighbour exchange interactions leading to a S=14 ground state. DFT calculations are consistent with the experimental magnetic measurements, revealing the importance of the bridging Cl ions in determining the sign of the exchange.
Chapter 3 reports the synthesis and characterisation of a family of [Mnᴵᴵᴵ₂Mnᴵᴵ₂] butterflies, two [Mnᴵᴵᴵ₃Mnᴵᴵ₄] clusters with different topologies and a novel [Mnᴵᴵᴵ₁₂Mnᴵᴵ₈] cluster that consists of two supertetrahedra. All are supported by (1-methyl-1H-imidazol-2-yl)methanol (HL3). Magnetic studies reveal that butterflies and one of the [Mn₇] clusters possess both ferro- and antiferromagnetic exchange interactions, with three of the butterflies being SMMs, while the [Mn₇] Anderson Wheel displays dominant ferromagnetic exchange interactions. The [Mn₂₀] cluster can be described as two ferromagnetic {Mn₁₀} supertetrahedra, coupled mutually by a weak antiferromagnetic interaction, which leads to an enhanced magnetocaloric effect.
Chapter 4 details the synthesis and characterisation of novel odd- [Feᴵᴵᴵ₁₁Mᴵᴵ₄] and even- [Feᴵᴵᴵ₁₂Mᴵᴵ₄] numbered wheels (Mᴵᴵ = Co, Zn), supported by the ligand triethanolamine. Magnetic susceptibility and magnetization measurements on the Zn analogues revealed strong antiferromagnetic interactions leading to a frustrated S = 1/2 ground state in the former and a S = 0 ground state in the latter.
Chapter 5 summarises the main findings of the thesis and identifies areas for future study and growth
Global land use dynamics in agriculture and forestry under socioeconomic and climate change scenarios
No full textAs global demand for natural resources continues to grow, the land system is experiencing increasing pressure to provide food, materials, and energy. Achieving sustainable land management is a common goal for landowners and policymakers to ensure we can meet society's present and future needs. Given the uncertainties surrounding the world's socioeconomic and climate trajectory, it is essential to consider a variety of potential scenarios for how the land system might develop. Existing research on future land use change suffers from a lack of diversity in the models and scenarios explored, leading to gaps in our understanding of the impacts of land use policies. This thesis examines global land use dynamics, focusing on how long-term changes in demand for agricultural and forestry products will impact global land use patterns. It addresses existing research gaps by providing novel, spatially detailed global land use change scenarios using the Land System Modular Model (LandSyMM). This global land use modelling framework simulates the demand for agricultural and forestry commodities, land use change, and international trade, using realistic, biophysically derived crop and forest yield responses.
The first part of this research investigates the response of global forest management to changes in wood demand. Forests are a prominent component of the Earth’s land cover and are valued for their diverse ecosystem services. Global demand for wood is projected to increase in all scenarios explored here, driven by population and economic growth. Results reveal that forest management will likely intensify in the following decades in most wood-producing regions, thus putting additional pressure on forest ecosystems. Reducing the impact of human land use on natural ecosystems is an integral part of policies aimed at mitigating climate change and preserving biodiversity. Subsequently, the thesis assesses the potential to reduce the global agricultural land footprint by comparing the land use requirements of bioenergy, photovoltaics, and agrivoltaics. Results show that substituting energy crops for photovoltaic panels reduces cropland expansion, fertiliser use, and irrigation water withdrawal. By combining solar energy generation with crop production (agrivoltaics), a higher land use efficiency is achieved, leading to further reductions in cropland expansion and loss of natural land cover. In all scenarios explored here, land use outcomes are strongly influenced by international trade, which is increasingly important in shaping global land use patterns. Using the United Kingdom as a case study, the final research chapter of this thesis investigates the importance of trade for global land use patterns by quantifying the global land footprint of the UK’s food and feed imports. Results reveal the global interconnectedness of the food and land system, thus highlighting the environmental consequences for exporting countries. This thesis illustrates some of the key factors that shape global land use in the context of changing demand for natural resources
Perinatal mental health care: a thematic synthesis of fathers’ support needs for involuntary pregnancy loss and a qualitative exploration of engaging partners with community perinatal mental health teams in NHS Scotland from fathers’ lived experiences and practitioners’ perspectives
Get PDFBACKGROUND:
Poor parental mental health during the perinatal period (pregnancy to twelve months post-birth) can have detrimental psychosocial impacts on parents, infants, and families. Such growing evidence has influenced policy initiatives and clinical guidelines, including investment since 2019 in the development of specialist Perinatal and Infant Mental Health (PIMH) services in Scotland’s National Health Service (NHS). Emerging literature reveals that fathers, like mothers, can experience adverse health outcomes in response to involuntary pregnancy loss, and partners (i.e., non-birthing parents) can play a vital role in mothers’ perinatal mental health, as well as have their own well-being needs during the perinatal period. Less is known about how best to support fathers for involuntary pregnancy loss and no study to date has explored partners’ engagement with specialist Community Perinatal Mental Health Teams (CPMHTs), comprised in PIMH services in NHS Scotland, which are currently funded for childbearing mothers as patients. This thesis set out to address these research gaps.
OBJECTIVES:
This thesis aimed to (1) systematically synthesise recent qualitative findings about fathers’ support needs for involuntary pregnancy loss; and (2) explore partners’ engagement with CPMHTs in NHS Scotland from both partners’ lived experiences and practitioners’ perspectives. Taken together, this thesis endeavours to identify recommendations to improve the quality and inclusivity of perinatal mental health care, which is anticipated to help maximise treatment outcomes for parents, infants, and families.
METHODS:
A systematic search of published primary studies via five electronic databases and Google Scholar identified 23 eligible papers for the thematic synthesis of qualitative data pertaining to fathers’ reported support needs for involuntary pregnancy loss. Methodological quality of each included study was assessed using the Critical Appraisal Skills Programme tool. In the empirical study, a qualitative design was employed for conducting semi-structured interviews via video-call or telephone with two fathers and four practitioners to explore experiences of partners’ engagement with CPMHTs in NHS Scotland. Interviews were audio recorded and transcribed verbatim for the reflexive thematic analysis of interview data.
RESULTS:
The thematic synthesis identified four major themes comprising fathers’ care preferences and support needs for involuntary pregnancy loss: Healthcare system factors; Contextual factors; Personal factors; and External factors. In the empirical study, reflexive thematic analysis identified three main themes and seven sub-themes revealing shared meanings of data across interviews regarding partners’ engagement with CPMHTs: (1) partners – supporters of mothers’ perinatal care; (2) engaging partners – best practice; and (3) partners matter.
CONCLUSIONS:
The thematic synthesis highlights the need for more active and public recognition of fathers’ grief in response to involuntary pregnancy loss and implementation of male-oriented supports across healthcare, occupational, social, and community settings. Future research is needed to distinguish between mothers’ and fathers’ care requirements for involuntary pregnancy loss along with understanding practitioners’ experiences of delivering bereavement care to men to ensure inclusive service provision. Findings derived from the reflexive thematic analysis in the empirical study strengthen the recognition of partners as supporters of mothers’ perinatal mental health and reveal strategies for optimally engaging partners with CPMHTs that consider mothers as the index patients, adapting care to partners’ individual life circumstances, and practitioners’ inclusive approach. Findings also recommend supporting partners’ perinatal related well-being on a multi-level basis and through partnership working
How the United Nations Can Turn Afghanistan’s Seat Into a Path Forward
No full textThis paper examines Afghanistan’s seat at the United Nations, which reflects the country’s broader political reality of uncertainty and inertia. Four years after the collapse of the Islamic Republic, the question of who should represent Afghanistan at the UN remains in limbo. The Taliban claim the seat, the remnants of the former government hold it without voting rights, and the UN defers decision. This paper proposes to the UN Secretary-General, the UN General Assembly, and Afghanistan’s movements, to treat the status of the seat as an opportunity for constructive diplomacy, analysing different possible scenarios and arguing in favour of a joint nomination as the most strategic option for Afghanistan
Engineering the fast growing and highly productive cyanobacterium Synechococcus sp. PCC 11901
No full textSynechococcus sp. PCC 11901 (PCC 11901) is a new cyanobacteria strain exhibiting
fast and sustained growth and biomass accumulation, making it an interesting and potentially
revolutionary host strain for biotechnology. At the time of starting the PhD project, very limited
information was available apart from a first report published in literature (Wlodarczyk et al.
2020). The overarching goal of my thesis is to develop PCC 11901 as a chassis strain for
cyanobacterial biotechnology.
In this thesis I first reviewed the current state of the art in cyanobacteria biotechnology,
with emphasis on where new fast-growing strains like PCC 11901 can excel and what
molecular and computational tools are needed to maximise their use towards carbon negative
emissions technologies (NETs). I highlight the potential of cyanobacterial biorefineries based
on these new strains in making NETs more cost-effective, as this has been the main bottleneck
in the uptake of cyanobacteria-based solutions by industry.
I next developed a CyanoGate-based synthetic biology toolkit which significantly
expanded our ability to engineer PCC 11901 by characterising new and existing standard
parts (neutral sites, constitutive and inducible promoters, transcriptional terminators). I
performed a proof-of-concept study of conditional knockdown of essential genes using
CRISPRi and a novel markerless genome editing strategy using CRISPR/Cas12a. This
extensive toolkit is a major milestone in engineering PCC 11901 and has been made available
through Addgene, an open vector repository for the research community. This toolkit chapter
is complemented by collaborative published papers (Mills et al., 2022; Mager et al., 2023).
I then performed an RNA-seq study of PCC 11901 to understand the transcriptomic
landscape of this fast-growing strain and find out differentially expressed genes across
different growth phases/densities in comparison to Synechococcus sp. PCC 7002, a strain
with 96% genome similarity but does not exhibit the maximum growth densities reached by
PCC 11901. In this chapter I generated the first RNA-seq dataset of PCC 11901 at different
growth densities, which will ultimately be a valuable resource to inform future engineering
work this strain.
Finally, to demonstrate the potential of PCC 11901 for biotechnology, I explored its
capability as a platform for the bioproduction of high-value plant-derived products. First is the
small, taste-modifying protein monellin, and second is the terpenoid α-bisabolene. I adapted
and developed a phycobiliprotein (cpcB) fusion strategy to improve protein expression, and
optimised growth conditions which led to increased protein and enzyme production. The
results in this chapter set the stage for PCC 11901 as a viable photoautotrophic host for
sustainable bioproduction
Transforming hemodialysis with new materials: an experimental and modelling approach
No full textHemodialysis (HD) is the renal replacement treatment for 2.6 million patients affected by end-stage kidney disease, with the aim of replacing renal functionality, namely the removal of excess fluid, electrolytes rebalancing and clearance of uremic toxins (UTs). The treatment is delivered in 2-3 sessions per week, in hospital. HD has a severe impact on patients’ lifestyle and the discontinuous delivery of the therapy results in vascular stress, post-session hangover and reduced life expectancy. The lack of access to affordable HD resulted in 1.2 million deaths in 2017. HD is based on the exchange of UTs (e.g. urea, creatinine and uric acid), through a semipermeable membrane, with a solution, named dialysate. Every session demands for more than 100 L of dialysate, representing a strong constraint on accessibility and delivery of HD. The development of a regeneration unit for dialysate is the enabling technology for envisioning a portable or wearable artificial kidney (WAK), improving accessibility, lifestyle and life expectancy.
The current state-of-art of strategies for dialysate regeneration is presented in this work, with an assessment of performance, stability and manufacture. Existing technologies for WAKs involve enzymatic or electrochemical conversion of urea, that is the most abundant and hard-to-remove compound, but issues for patient’s safety have been raised, due to the formation of harmful chemicals and poor biocompatibility. Adsorption represents the most attractive technique for UTs removal, being intrinsically safe with no side-products generation. Mixed matrix membranes are composite materials made of adsorptive particles dispersed in a porous polymeric matrix, coupling adsorption of UTs, optimized fluid dynamics and low energy consumption in a single material.
This work aimed at the assessment of commercial and novel nanoporous materials, through the experimental measurement of static adsorption of urea and creatinine for zeolites, mesoporous silica and covalent organic frameworks (COFs). Comparison with literature data showed agreement for zeolites, while mesoporous silica adsorbed less urea than literature showed. Up to our best knowledge, no other experimental data for urea adsorption on COFs are available in literature. MMMs made of zeolite in cellulose acetate were fabricated through non-solvent inverse phase separation, optimized over porogen, composition and casting temperature. The use of glycerol as a porogen preserved the microstructure after the filler incorporation in the matrix, with a permeability higher than 4000 L m-2 h-1 bar-1. However, adsorption capacities of the nanoporous materials tested were not compatible with the performances required for WAK. For such reason, adsorbents were the focus of a screening campaign, based on molecular modelling of COFs.
COFs are materials made of organic building units, which assemble covalently, forming periodic and highly porous frameworks. The high number of units available allows to tailor their porosity, in terms of size and chemical environment. Furthermore, they offer stability in moist conditions and in acidic or basic environment. However, COFs have been scarcely studied for water and UTs sorption.
Excess chemical potential at infinite dilution of water, urea, creatinine and uric acid was calculated in COFs available in CURATED COF databases through the particle insertion method, shortlisting the best candidates for urea. The nanoporous materials were ranked considering the binding strength toward UTs and the selectivity with respect to water and the other UTs. The impact of pore functionalization in COFs was revealed to play a fundamental role in the binding properties toward urea at infinite dilution. Nonetheless, the elemental composition of heteroatoms in the framework’s structure, pore size and available surface area appeared to be inadequate parameters to describe the urea adsorption.
Adsorption was further studied on the validation set of COFs, for which nitrogen and water adsorption data are available in literature, and for CONN, IISERP-COF3, CPF-2, TFB-COF, COF-JLU4 and JUC-505 AA COFs, selected to be the best candidates for urea adsorption. Grand Canonical Monte Carlo (GCMC) and Transition Matrix Monte Carlo (TMMC) simulations were used to enquire the thermodynamics of binding and characterize the binding sites population.
Nitrogen adsorption at 77 K was simulated with TRAPPE and IFF models, compared to experimental data using Brunauer–Emmett–Teller theory, to investigate the consistency of force fields used and departure from experimental data for all the COFs. GCMC and TMMC showed good agreement. Furthermore, the comparison of simulated and experimental isotherms showed discrepancies ascribable to the difference between the crystal structures and the crystallinity of synthetized COFs.
Conversely from nitrogen, simulations of water adsorption in COFs through GCMC and TMMC evidenced an important difference, related to the convergence issues in GCMC. For the validation set, the isotherms from TMMC were compared with experimental water adsorption, evidencing departures from experiments, consistent with what was observed in nitrogen adsorption. Water adsorption was studied to reveal mechanism of binding, since the water co-adsorbs with UTs, and describes the hydrophilicity of COFs. Isotherms, heats of adsorption, radial distribution functions, contributions of electrostatics and Van der Waals forces were computed and used in the discussion of the materials behaviour.
This work aimed at the experimental testing of adsorbents for urea and creatinine, optimization of mixed matrix membrane for dialysate regeneration and the use of molecular modelling to accelerate material discovery for adsorption of uremic toxins from spent dialysate. Development of adsorbents tailored for UTs adsorption is the strategy proposed to dialysate regeneration, that is ultimately the key for the design of portable and wearable devices for hemodialysis
Aesthetics of protest: understanding art and activism in the Chilean student movement of 2011-2013
No full textThis thesis offers a critical examination of protest art created during the Chilean student movement of 2011-2013. It focuses on analysing the conditions of production of artworks and interventions created specifically by art students during this period. While existing literature on social movements and protest art predominantly centres on art and activism in the Global North, the artistic production of the Chilean student movement remains understudied. This study addresses this gap in scholarship, particularly given the movement's impact on educational reforms and its contribution to the ongoing debates around social justice in Latin America and Chilean politics more broadly.
This thesis employs a qualitative, interdisciplinary methodology drawing on conjunctural analysis and social movement theory. Semi-structured interviews with the artists who created the artworks provided valuable insights into their collaborative creative processes and intentions. Exploring press documents and conducting extensive archival research further enriched the understanding of the creation context of the artworks and art interventions. This combined approach allowed for an in-depth examination of the art's production background and aesthetics of the protest.
This research underscores the importance of considering the cultural, political, and historical context, as well as the conditions of production and resources, in shaping protest art. The analysis of this protest art comprises various forms of collective action, visual strategies, and protest repertoires as key elements that inform the meanings of Chilean protest art created by 2011-2013. By examining these contextual factors, this research not only provides insights into the specific case of the Chilean student movement of 2011-2013 but also contributes to broader discussions on the interplay between art, activism, and social change in contemporary societies
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