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Automated machine learning for positive-unlabelled learning
Get PDFPositive-Unlabelled (PU) learning is a field of machine learning that aims to learn classifiers from data consisting of labelled positive and unlabelled instances, which can be in reality positive or negative, but whose label is unknown. Many PU learning methods have been proposed over the last two decades, so many so that selecting an optimal method for a given PU learning task presents a challenge. Our previous work has addressed this by proposing GA-Auto-PU, the first Automated Machine Learning (Auto-ML) system for PU learning. In this work, we propose two new PU learning Auto-ML systems: BO-Auto-PU, based on a Bayesian Optimisation (BO) approach, and EBO-Auto-PU, based on a novel evolutionary/BO approach. We present an extensive evaluation of the three Auto-ML systems, comparing them to each other and to well-established PU learning methods across 60 datasets (20 datasets, each with 3 versions). The results of the comparison show statistically significant improvements in predictive accuracy over the baseline methods, as well as large improvements in computational time for the newly proposed Auto-PU systems over the original Auto-PU system
Falling on Fertile Ground: National Identity Rhetoric and Its Appeal to Those High in National Narcissism
No full textCollective narcissism refers to the belief that one's group is superior to others but lacks external recognition. When applied to the national level, this concept is known as national narcissism. National narcissistic rhetoric, which emphasises a nation's greatness and sense of entitlement, frequently features in populist messaging. This thesis investigates whether such rhetoric actively influences individuals' levels of national narcissism or primarily appeals to those already predisposed to this sentiment, thereby mobilising them. Employing experimental methods, the thesis utilises social media and AI-generated stimuli to examine how national identity rhetoric operates in digital environments. Key findings reveal that while positive national identity rhetoric can influence levels of national narcissism in specific contexts, individuals high in national narcissism are particularly receptive to messages portraying their nation in a favourable light. This demonstrates how pre-existing sentiments shape responses to national identity cues. When exposed to rhetoric that promotes their nation, individuals high in national narcissism are more likely to express intentions to vote, support the speaker, be persuaded by such rhetoric, share and engage with such content on social media. The findings also highlight how leaders can mobilise audiences by strategically leveraging national identity rhetoric, particularly when they are perceived as similar and representative of the public
Deformation measurements of 3D printed lattice-structured materials through image analysis
No full textMeasuring the deformation under loading conditions is a crucial part of any material characterization. Image analysis is a robust technology that determines the full-field deformation of a structure without interfering with its properties. These measurements are significantly challenging for lattice-structured materials due to the detailed geometries involved in the region of measurements. Furthermore, despite the advancements in Digital Image Correlation (DIC) techniques, there is a need for comprehensive performance analysis of different DIC software and alternative deformation measurement model development for complex geometric materials such as 3D-printed lattice-structured materials. Therefore, this research aims to investigate the deformation measurement of 3D-printed lattice-structured materials under compressive load using advanced image analysis techniques through validation and comparison of results.
This study encompasses the performance analysis of a well-known commercial DIC software, an open-source DIC software, and a proposed Imaging Technique-based deformation analysis model for the full-field deformation measurement of 3D-printed lattice-structured materials. The results obtained from these techniques are compared with Finite Element simulations to validate their accuracy. The study also incorporates image segmentation for pre-processing images to improve the results. Five lattice types (Cubic, FCC, FCCZ, BCC and BCCZ) fabricated from PLA and TPU materials have been used to analyse their mechanical response under compressive loading.
Results demonstrate that DIC analysis accurately portrays each material's unique deformation pattern. The commercial DIC software is efficient with a 7% deviation from the testing machine data for deformation in the Y direction, while the proposed Imaging Technique-based model shows a 6% deviation. In addition, the performance of the open-source DIC software improves after incorporating pre-processed images. This research also investigates the influence of several factors on the results, including speckle pattern on the surface, image resolution, background information, and illumination.
This research establishes a unique dataset for lattice-structure deformation analysis and demonstrates the effectiveness of image-based measurement techniques for complex geometric materials. The findings highlight the potential of advanced image analysis techniques in improving the accuracy of deformation measurements and contribute to the development of more reliable and efficient DIC methods
The Cypriot vernacular farmstead: the relationship with its inhabitants and the environment, its environmental behaviour and adaptation in time
No full textReviewing the existing literature, there is an important research gap related to the examination of the Cypriot farmstead as a distinct building typology of vernacular architecture, despite the fact that the traditional dwelling has been investigated to a certain degree. Therefore, the aim of this dissertation is to study and understand the Cypriot vernacular farmstead, its relationship with its inhabitants and the environment, its environmental behaviour and its adaptation over time. For its investigations, this work draws analytical tools and ideas from the theories of Rapoport (1969) and Oliver (1976, 2006), as well as from bioclimatic design and sustainable architecture theories. For its implementation, it employed a multiple case study research design with three Cypriot vernacular farmsteads as cases, located within one rural settlement and still in use by their original owners and descendants. Extensive field studies included qualitative and quantitative research methods, i.e. participant and non-participant observation, interviews, focus groups, in-situ documentations, environmental monitoring and post-occupancy evaluation surveys.
Research findings showed that these farmsteads differed from rural houses because they were situated in communities' fringes within larger land plots, and developed as conglomerates of varying building types, juxtaposed linearly around multiple open-air working areas; an assemblage that has been continuously mutated and morphed over time, depending on the complex interplay of several determining and modifying factors. More specifically, a farmstead's overall placement and orientation, form and spatial configuration, materiality and construction, functionality, use and operation are influenced by socio-cultural, economic, technological and environmental factors, along with inhabitants' ever-changing living needs, diverse activities and functional-occupational demands. Each farmstead exhibits a centrality, multiplicability and/or additivity of forms and a multi-purpose functionality of spaces, which enable it to resiliently and versatilely adapt to satisfy inhabitants' needs, through morphological reformations, spatial re-organizations and integration of new functions and uses, regardless of changes in habitation status and operational mode. In addition, its embedded bioclimatism and intuitively-applied sustainability enables occupants to utilize passive cooling and heating strategies, take advantage of vegetation, exploit climatic phenomena and mitigate conditions, to create relatively comfortable indoor and outdoor living and working spaces. Gradually, all farmsteads evolved from subsistence farms, into agricultural, livestock farming, light-industrial, goods-producing and service-rendering businesses. Presently and based on future prospects, some farmsteads still function, albeit with reduced agricultural activities. Others have been transformed into vacationing villas for visiting descendants or rented-out as agro-tourism accommodations. Under different circumstances, several farmsteads have either acquired altogether different purposes and uses, or sold to new owners. In worst cases, they have been abandoned. Consequently, these recorded phenomena show a constantly transformative relationship between the farmstead and its owners. Relatively, at a theoretical level, this study revealed and purposed the notion of the "farmstead and inhabitant relationship", which arises mainly from the process of satisfying inhabitants' needs in the building, i.e. through architecture; an operation which also shapes the form and function of the farmhouse, its supportive buildings and outdoor areas.
There is an urgency and a necessity to record and study these vernacular farmsteads, because as they are still in use today, they are undergoing tremendous arbitrary and uncontrolled modifications that change their original authentic architectural character and historical value, as well as their bioclimatic-sustainable characteristics and environmental behaviour. It is also imperative to preserve and protect them, as valuable existing building stock of the countryside, since they contribute to a great degree to the primary and secondary sectors of the Cypriot economy. Based on its findings, this research offers valuable lessons and good practices for the restoration and reuse of vernacular farmsteads, as well as provides viable solutions to bioclimatic design and sustainability, environmental building behaviour and energy performance in relation to inhabitant thermal comfort, and as applied to existing traditional and newly-constructed buildings. Lastly, due to its interdisciplinary approach, multiple case studies and extensive field studies with fully-integrated qualitative and quantitative research methods, which present a significant theoretical, practical and methodological value, this study makes important recommendations for future research
Effects of ambient humidity and surface topography on fingermark recovery from PLA 3D‐printed surfaces
Get PDFThe increasing accessibility of 3D printing, made possible by the affordability of equipment and materials, has led to its widespread adoption in both domestic and industrial applications, with polylactic acid (PLA) being a commonly used material. The layer-by-layer deposition process in fused deposition modeling creates surface texture variations that significantly influence the development and recovery of latent fingermarks. This study examined the effect of raster lines on fingermark development by depositing latent fingermarks on the X, Y, and Z faces of 3D-printed PLA objects. Powder development was applied both along and against the 3D print grain. Development against the grain caused excess powder accumulation within raster lines, partially obscuring ridge detail. In contrast, applying powder along the grain minimized accumulation, enabling clearer visualization of ridge features. Top and side surfaces generally yielded higher quality grades, attributed to smoother surfaces from better interlayer bonding. However, raster lines created discontinuities in ridge transfer, hindering coincident sequence determination. Cyanoacrylate ester fuming effectively addressed this limitation, producing continuous ridge detail on top and side surfaces, and leading to higher quality grades
Assessing the livelihood vulnerability of rural Guyanese communities due to accelerating environmental change
No full textEnvironmental change is increasing vulnerability for many local communities worldwide. This can affect social, health, economic, environmental and cultural values, and challenges our ability to achieve Sustainable Development Goals. Previous research has quantified such community vulnerability using indices such as the Livelihood Vulnerability Index (LVI) and the Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) to assess the impacts of climate change on the livelihoods of local communities. However, there remains a gap in our understanding regarding how the vulnerability of communities is impacted by industries that lead to environmental degradation such as mining and logging, and how these may interact with changes linked to climate change such as increased intensity and duration of floods and droughts. We address this, utilising the LVI, LVI-IPCC and a livelihood-based analysis, by quantifying the vulnerability of four rural (primarily Indigenous) communities in Guyana, northern Amazon. We assessed the degree to which these communities and households are exposed, sensitive and have adaptive capacity towards a changing environment and climate and identify key community and household-level components contributing to that vulnerability. We find that communities and households dependent on mining and logging displayed lower overall vulnerability yet exhibited heightened sensitivity to environmental change due to natural resource depletion and degradation. In contrast, subsistence-based communities faced higher overall vulnerability, partly attributed to their susceptibility to flooding and lack of livelihood diversification. Our research improves our understanding of the processes and factors that predict vulnerability in rural communities and can help to guide the development of appropriate interventions
A lightweight and rapid bidirectional search algorithm
Get PDFPath planning in mobile robotics is critical for efficient navigation in complex environments. To date, grid-based planning remains a popular choice due to its simple spatial representation, integration with sensor data and the ability to encode motion constraints. This work contributes to this direction by proposing a novel and complete grid-based algorithm, LiteRBS (Lightweight and Rapid Bidirectional Search), optimised for computational efficiency and scalability. The algorithm balances aggressive bidirectional, forward search heuristics with a fallback strategy to reserve queues. Evaluated extensively against well-known algorithms like A*, bidirectional A*, Jump Point Search (JPS) and Shortest Path Faster Algorithm (SPFA), LiteRBS demonstrates statistically and practically significant reductions in memory usage (79%–96%), node expansion (40%–92%) and runtime (83%–98%), the latter remaining density-invariant across increasing spatial and environmental complexity. It handles non-central merges by dynamically adjusting search targets in each direction to “attract” nodes rapidly towards convergence. This yields flat search overhead as the problem scales to large and crowded maps. Real-world deployment on a Turtlebot3 robot demonstrates its responsiveness under partial observability and dynamic obstacle conditions. Overall, LiteRBS offers a scalable, lightweight and practical solution for the navigation of terrestrial robots in complex, resource-constrained environments
Emotions and perceptions predict local communities' attitudes toward the conservation of large carnivores
Get PDFUnderstanding local communities' emotions and attitudes toward large carnivores is crucial for promoting coexistence, yet few studies have examined how emotions and perceptions shape these attitudes. We conducted interviews with 292 rural residents living in 30 villages around Golestan National Park, northeastern Iran. With Bayesian ordinal regression models, we assessed how fear, happiness and pride, damage experiences, perceived ecotourism benefits, and perceived population status influence local communities' attitudes toward the conservation of leopard, wolf, and brown bear. We found that happiness and pride, along with the perception that carnivores provide ecotourism benefits, substantially influenced attitudes. This pattern was consistent across species, with generally high support for the conservation of all three species. Respondents expressed fear of leopards and bears, and the perception of declining populations increased support for their conservation. In contrast, perceiving a high wolf population was associated with reduced positive attitudes. Furthermore, direct experiences of carnivore-related damage (e.g., livestock losses and crop damage) were linked to general dislike of all three species, further diminishing positive attitudes. These findings highlight the importance of emotions such as fear, happiness and pride, as well as perceptions of population status, ecotourism benefits, and damage in shaping human–carnivore interactions. Addressing these factors, particularly by mitigating fear of carnivores, in decision-making processes could help offset the costs of living alongside these animals, thereby enhancing positive attitudes and promoting coexistence with large carnivores
A multiscale quantitative systems pharmacology model for the development and optimization of mRNA vaccines
Get PDFThe unprecedented effort to cope with the COVID‐19 pandemic has unlocked the potential of mRNA vaccines as a powerful technology, set to become increasingly pervasive in the years to come. As in other areas of drug development, mathematical modeling is a pivotal tool to support and expedite the mRNA vaccine development process. This study introduces a Quantitative Systems Pharmacology (QSP) model that captures key immune responses following mRNA vaccine administration, encompassing both tissue‐level and molecular‐level events. The model mechanistically describes the biological processes from the uptake of mRNA by antigen‐presenting cells at the injection site to the subsequent release of antibodies into the bloodstream. This two‐layer model represents a first attempt to link the molecular mechanisms leading to antigen expression with the immune response, paving the way for the future integration of specific vaccine attributes, such as mRNA sequence features and nanotechnology‐based delivery systems. Calibrated specifically for the BNT162b2 SARS‐CoV‐2 vaccine, the model has undergone successful validation across various dosing regimens and administration schedules. The results underscore the model's effectiveness in optimizing dosing strategies and highlighting critical differences in immune responses, particularly among low‐responder groups such as the elderly. Furthermore, the model's adaptability has been demonstrated through its calibration for other mRNA vaccines, such as the Moderna mRNA‐1273 vaccine, emphasizing its versatility and broad applicability in mRNA vaccine research and development
Researching LGBTQ+ homelessness and building social justice in the UK & the US: methods, ethics, recruitment
Get PDFLGBTQ+ homelessness research is an emerging area growing in importance in the UK, the US, Canada and Europe. Research to date indicates that methodology and participant recruitment are particularly challenging for this group. Sexual orientation and gender identity, as well as homelessness and poverty are taboo topics that are often stigmatized. Homelessness for LGBTQ+ people is therefore under-reported both by third sector organizations and governments. The scale of the problem is difficult to determine, resulting in the de-prioritization of support, funding and policy change. Drawing on research outcomes from projects in England, Scotland and the US, this paper explores possibilities for conducting research into LGBTQ+ homelessness can happen, and why such research is vital to world-building and epistemic justice. We consider the delicate question of whether we can accurately and ethically produce data on LGBTQ+ homelessness, what the repercussions are for those currently experiencing homelessness, and whether it is still important to pursue such research given the potential harms
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