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Marine Fungi and Their Diversity in Coral Reefs
Full text linkReef-building corals support a wide range of species from microorganisms to reef sharks and manta rays. However, the impact of anthropogenic stress is beginning to show, with increases in the frequency of coral bleaching having knock-on effects for the wider reef community. In recent years, research has begun to show interest in the role microbes play within reefs. Some are suggesting they may hold the answer to the crisis that is unfolding (e.g. the use of microbes to mitigate heat stress or disease susceptibility in corals) (Peixoto et al., 2021). To date, most of this research has focused on prokaryotes and the coral algal symbionts, Symbiodiniaceae, while other microbial groups such as protists and fungi have received considerably less attention (Ainsworth et al., 2017; Bonacolta et al., 2023). The few studies that have explored the impacts of fungal communities on corals have tended to focused on the pathogenic nature (Le Campion-Alsumard et al., 1995), and only recently have people proposed they may be beneficial although a lot is still unknown (Roik et al., 2022). This thesis addresses several aims, including, aiming to further understanding of fungal diversity throughout the coral, as well as aiming to understand how fungal communities within the coral respond to external factors, all of which intend to increase our overall understanding of fungi in corals. Chapter 1 consists of an overview of our knowledge of fungi in the marine environment and fungi associated with corals. Chapter 2 explores how fungal diversity is distributed across coral compartments by separating different compartments (mucus, tissue and skeleton), and using molecular techniques to identify the fungal species found in each compartment. Here I found there were significant differences of the fungal diversity between the compartments (mucus and skeleton), but not between the mucus and tissue and the tissue and skeleton. There were also similarities between mucus and the surrounding environmental pools (sediment and water). In Chapter 3, the final chapter, spatial and temporal factors affecting coral fungal diversity were investigated, by collecting samples from multiple reefs, over multiple time points and across different depths, using molecular techniques to analyse the fungal communities. Surprisingly and in contrast to bacteria, the mycobiome was unchanged across space and time. However, similarities between the fungal diversity found in the coral mucus and the environmental pools of in situ corals were shown, supporting the findings of Chapter 2, which also saw similarities between the fungal communities in the mucus and environmental pools. Therefore, this thesis adds to our understanding of coral associated fungal species in terms of compartmentalisation and response to temporal and spatial factors
Necrology: Becoming Soil
No full textSharples’ curatorial project NECROLOGY, functioned as both exhibition and practice-led study—a speculative site of mourning offering an interface with absences, transitions, rituals, suspensions, shrines, and exhumations. The exhibition speculated on material afterlives, ecological grief, and the economies and systems of death(care) and loss.
As part of the exhibition, Sharples invited haptonomic professional Rosalie Bak to facilitate Becoming Soil—a participatory workshop situated between the exhibition space and the burial grounds of St Mary’s in Wirksworth. In Becoming Soil, living human bodies came together to co-sense what it is like to relate to non/living matters and materialities. Drawing on principles from the field of Haptonomy (the practice and study of human relationality and the phenomena of touch) participants were invited to make way for a more sensorial encounter with body, soil and death-care. Unfolding in three parts: ‘Noticing’, ‘Being with/in’, ‘Fermenting’, the creative and somatic exercises played with themes such as tenderness, intentionality, attention and affective touch, while also engaging with the exhibition space, works and surrounding landscapes. An audio-recording with site-specific meditation further guided participants to creep, leak and flow through all surrounding material, temporal, fleshy and microbial entanglements after which they gathered in a process of collective processing of the experience. The ink that was used in the creation of the collective work was made from the ferments of decomposing organic matter.
Guided by New Materialist thought and developed in collaboration with the New Materialist Reading/Research Group (NMRG) and Playing Fields – two artist-led curatorial initiatives – NECROLOGY foregrounds the curatorial as a method of critical analysis and ontological mediation. Calling on Rosi Braidotti’s articulation of an affirmative ethics of mourning, Sharples cultivates a space in which death and loss are recognised as generative, and in a continual process of becoming. Rather than a static presentation of objects, NECROLOGY unfolds as a field of relational intensities, where curatorial practice closes the space between academic discourse and embodied artistic processes.
Curated by Victoria Sharples at Haarlem Artspace in partnership with New Materialist Reading/Research Group (NMRG) & Playing Fields.
Supported by the AHE Academic Theme Funding, University of Derby
RSA Revealing Social Capital Policy Roundtable
No full textRhiannon Jones was invited to participate in the policy roundtable for the RSA.
This closed table discussion involved Revealing Social Capital is a major study into social connection in the UK. It reveals that
friendships across socioeconomic lines have a strong relationship with future earnings and
social mobility.The research was funded by Nuffield Foundation and carried out
by an international consortium including BIT (Behavioural Insights Team), together with
Meta, Stripe Partners, the RSA, Neighbourly Lab, and researchers from Stanford and
Opportunity Insights.
The roundtable brought together experts, policy makers and practitioners from the field of social capital to explore how this evidence can inform policy
decisions and identify interventions and levers that can be designed to improve economic connectedness across the UK
Mapping age and disability through performance in African Orature and theatre performance
No full textThe complexity of conceptualising the elderly and disabled people in oral and written interpretations in Buganda (Uganda) results from the subtle interplay between perceptions of their mental and physical disabled bodies and the correlated invisibility attributed to them in social and political representations. Still, performance as a field allows diverse mappings and offers multiple approaches that enable artists to view practices such as narratives, songs, recitation, and drama, as spaces where age could be explored. My purpose in this study is to observe the range of contemporary questions concerning Ugandan performance in order to map the presence of discourses of age and disability that may be in song-texts, and dramatic texts where they have been embedded. My study of the nature of the Baganda proverbs, songs, folktales as well as Uganda plays whose discourses dramatise age and disability politics, reveals that these performance forms constitute a wealthy connection to the traditional and contemporary constructions of age and disability in Uganda. The essay draws examples from Baganda artists Robert Serumaga, John Ruganda, Elvania Zirimu’s dramas, and Albert Sempeke, to demonstrate their interest in agedness, disability and performance
Voice-based early diagnosis of Parkinson’s Disease using spectrogram features and AI models
Full text linkParkinson’s disease (PD) is a progressive neurodegenerative disorder that significantly affects motor functions, including speech production. Voice analysis offers a less invasive, faster and more cost-effective approach for diagnosing and monitoring PD over time. This research introduces an automated system to distinguish between PD and non-PD individuals based on speech signals using state-of-the-art signal processing and machine learning (ML) methods. A publicly available voice dataset (Dataset 1, 81 samples) containing speech recordings from PD patients and non-PD individuals was used for model training and evaluation. Additionally, a small supplementary dataset (Dataset 2, 15 samples) was created although excluded from experiment, to illustrate potential future extensions of this work. Features such as Mel-frequency cepstral coefficients (MFCCs), spectrograms, Mel spectrograms and waveform representations were extracted to capture key vocal impairments related to PD, including diminished vocal range, weak harmonics, elevated spectral entropy and impaired formant structures. These extracted features were used to train and evaluate several ML models, including support vector machine (SVM), XGBoost and logistic regression, as well as deep learning (DL)architectures such as deep neural networks (DNN), convolutional neural networks (CNN) combined with long short-term memory (LSTM), CNN + gated recurrent unit (GRU) and bidirectional LSTM (BiLSTM). Experimental results show that DL models, particularly BiLSTM, outperform traditional ML models, achieving 97% accuracy and an AUC of 0.95. The comprehensive feature extraction from both datasets enabled robust classification of PD and non-PD speech signals. These findings highlight the potential of integrating acoustic features with DL methods for early diagnosis and monitoring of Parkinson’s Disease
Molecular solar thermal energy storage system based functional devices
No full textThe increasing global energy demand, coupled with the detrimental environmental effects of fossil fuel dependence, has made the development of alternative energy storage systems a critical priority. Among the various renewable energy technologies, solar energy emerges as a promising solution due to its abundance, inexhaustibility, and lack of greenhouse gas emissions during operation. However, efficient and reliable storage of solar energy remains a significant challenge. Molecular solar thermal energy storage (MOST) systems offer an innovative approach by capturing solar energy at the molecular level. MOST systems rely on organic photoswitchable molecules that store solar energy in chemical bonds, which can later be released as heat on-demand. These systems combine high energy density with long-term stability, making them a viable option for sustainable energy storage. This chapter delves into the design strategies and challenges associated with MOST-based functional devices, highlighting experimental insights and case studies that span from lab-scale demonstrations to potential upscaled applications. By emphasising intuitive MOST-based device designs and their integration with other existing technologies for hybrid applications, this exploration seeks to inspire advancements in the development of next-generation MOST systems
What Citizens in the U.S. and UK Know About Media Regulation and Why It Matters
Full text linkA few weeks after the new Trump administration came into office, Vice President JD Vance was in Munich chiding policy makers for daring to put restrictions on social media content in Europe. His comment reflected an American naïveté about media regulation and its existence outside of the United States. It also reflected the differing traditions of free speech that have evolved on each side of the Atlantic (Rosenthal, 2022). The episode raises an interesting question, though, about what the public knows about media regulation and how this unique aspect of press knowledge associates with broader values and perceptions of democratic health. To answer this question, we engage in a cross-national comparison of the UK and U.S. Based on previous research in the UK (Firmstone et al, 2024, Gibson et al, 2022), levels of awareness are low. And yet informed public opinion and greater levels of news literacy could be an important ally in the effort to clean up a polluted and often exploitative digital media environment, which casts an increasingly long and dark shadow over democratic elections.
In keeping with the conference theme, we explore the importance of connecting public understanding of and appreciation for mainstream journalism via knowledge of regulation and its intended purposes to not only provide access to information the public can trust but also uphold norms of fairness important to democracy. To assess the state of knowledge about media regulation and attitudes towards the values that underpin it, this study reports on public understanding of regulation in the UK and U.S. using comparable survey data from two country wide representative samples fielded in Spring 2025. We then compare these findings with earlier surveys with comparable items that were fielded by the authors in 2019 (US) and 2022 (UK). The analysis reports on knowledge levels among respondents in both national contexts, across different points in time, then correlates high and low knowledge holding with several key indicators of democratic health, including media cynicism, political (system) efficacy, trust in institutions, support for normative journalistic values, and support for authoritarianism.
We expect to find that higher levels of understanding correlate with more support for democratic norms, while lower levels will be associated with a weakened democratic outlook, including low political efficacy, trust in institutions, and press values but heightened support for authoritarian models of governance. Our assumption here is that lack of awareness of procedural protections against press excesses will align with a low quality news diet and low trust in institutions, fostering a jaded outlook about the state of democratic health. Given the greater presence of press regulators in the UK context, we expect British respondents to have more knowledge about media regulation than Americans
Development of three Higher Education Professional Learning Networks in response to COVID-19: A case study
No full textThe COVID-19 (SARS-CoV-2) pandemic brought in-person teaching to an abrupt halt in March 2020 posing the problem of how to continue to deliver undergraduate courses remotely. This paper presents a detailed case study of three international online Higher Education (HE) teaching networks, formed to address the critical need to support laboratory teaching in the UK and Australia. The study employed a sequential mixed methods design using an online survey followed by structured discussions with network leads. The findings show these networks provided a space that was previously missing for knowledge development, building confidence, supporting collaboration, and reduced isolation of members. COVID-19 created a common purpose triggering the formation of these communities, but multiple factors contributed to their continued success: individuals prioritised engagement; both participants and their contributions were welcomed, and they subsequently felt able to lead change. The research found that the three networks fit the framework for Professional Learning Networks (PLN) providing a useful template for Higher Education PLNs operating anywhere in the world
Qualitative study of Q4.0 awareness, challenges, readiness, and core skills: A Middle East perspective
No full textPurpose: This study explores the underexamined concept of Quality 4.0 (Q4.0), an evolution of digital quality management rooted in Industry 4.0 (I4.0). The study investigates its awareness, benefits, challenges, readiness factors, and core skills in the Middle East. Furthermore, the article provides a conceptual framework guiding organizations interested in Q4.0 adoption in the region.
Design/Approach/Methodology: A qualitative approach involving 14 semi-structured interviews with quality management experts was adopted. Data were analyzed using the constant comparative method, resulting in a conceptual framework that delineates key aspects of Q4.0 implementation.
Findings: Results reveal that limited strategic vision, leadership commitment, resistance to change, and inadequate digital infrastructure impede Q4.0 adoption, while robust digital structure, adaptive management styles, and a change-friendly organizational culture are critical readiness factors. Both technical and soft skills, including data analytics, AI, communication, and leadership, emerged as essential for effective integration.
Research Limitations: The focus on the Middle East may limit broader generalizability. Relying on qualitative research introduces potential interviewer bias. Lastly, excluding customers, suppliers, or regulators limits the understanding of the Q4.0 ecosystem on a holistic level. Practical Implications: Managers can utilize the proposed framework to evaluate organizational readiness, guide resource allocation, and design targeted skill-building initiatives. The insights also
support strategic investments in digital infrastructure and change-management processes.
Originality: By situating Q4.0 in a Middle Eastern setting, this study extends digital quality management literature, offering region-specific insights and a foundation for future research beyond predominantly Western-focused investigations
Myoelectric temporal patching: leveraging long temporal memory for effective sEMG pattern recognition
No full textRobust myoelectric control is essential for advancing lower limbs active assistive devices and prosthetics. Feature extraction from surface Electromyographic (sEMG) signals serves as a fundamental component influencing the performance of such controllers. While deep learning models, such as Long Short-Term Memory (LSTM) networks, have been increasingly used to extract hidden features from raw sEMG data by leveraging temporal contexts in laboratory studies, the use of such models on prosthetic controllers is often associated with large memory and computational overheads, thus necessitating expensive hardware. To address these challenges, this study proposes a novel handcrafted feature extraction method, termed Myoelectric Temporal Patching (MTP), that works on extracting multi-signal features from patches within the short-segments of sEMG and propagating information across the windows, to capture both short- and long-term temporal dynamics of sEMG signals, without the high computational burden. Two pattern recognition experiments were conducted to validate the proposed method: gait phase recognition using the SIAT-LLMD dataset and locomotion mode recognition using the MyoPace dataset. Results demonstrated that the MTP feature set consistently outperformed (p < 0.0001) traditional and spatial feature sets across three machine learning models—Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The proposed method achieved peak accuracies of 85.11% in gait phase recognition and 87.70% in locomotion mode recognition when using SVM. These findings underscore the effectiveness of the proposed temporal features in decoding lower-limb motion intentions, emphasizing the critical role of temporal dynamics of sEMG signals