30796 research outputs found
Sort by
Material Classification using Visio-Tactile Sensor for Haptic Feedback Generation
Get PDFThe flexibility, versatility and enhanced perception of visio-tactile sensors could be beneficial for advanced robotic systems and other applications requiring precise haptic feedback. In this paper, we present a comprehensive framework that combines material classification and haptic feedback through the use of GelSight sensors. The study includes the creation of a diverse material dataset, consisting of 13 material classes of 42 distinct indoor and outdoor items, each item with multiple video samples captured over different regions and pressing conditions by human-held GelSight mini sensors. We introduce a method for detecting pressing events from recorded video samples and extracting key frames that capture important material features. We employ both traditional and deep learning-based feature extraction techniques to model material characteristics. These features are then used to classify materials with high accuracy through supervised learning methods using different image resolutions. For the traditional approach, Histogram of Oriented Gradients (HOG) feature descriptor combined with SVM gives 95.41% accuracy using the new image dataset. After fine-tuning five pre-trained models for transfer learning on our dataset, Dense-Net121 (96.42%), InceptionV3 (96.32%), and VGG16 (95.77%) models show promising results, and the ensemble of these 3 fine-tuned models provides highest accuracy of 97.63%. The results demonstrate the feasibility of using GelSight-based material classification for haptic feedback, with potential implications for virtual reality, robotic manipulation, and human-computer interaction applications
The interstitial lung disease patient pathway:from referral to diagnosis
Get PDFBACKGROUND: Suspected interstitial lung disease (ILD) patients may be referred to an ILD-specialist centre or a non-ILD-specialist centre for diagnosis and treatment. Early referral and management of patients at ILD-specialist centres has been shown to improve survival and reduce hospitalisations. The COVID-19 pandemic has affected the ILD patient diagnostic pathway and prompted centres to adapt. This study investigates and contrasts ILD patient pathways in ILD-specialist and non-ILD-specialist centres, focusing on referrals, caseloads, diagnostic tools, multi-disciplinary team (MDT) meeting practices and resource accessibility.METHODS: Conducted as a cross-sectional study, a global self-selecting survey ran from September 2022 to January 2023. Participants included ILD specialists and healthcare professionals (HCPs) from ILD-specialist centres and non-ILD-specialist centres.RESULTS: Of 363 unique respondents from 64 countries, 259 were from ILD-specialist centres and 104 from non-ILD-specialist centres. ILD centres had better resource availability, exhibiting higher utilisation of diagnostic tests (median: 12 tests) than non-ILD centres (nine tests) and better access to specialist professions attending MDT meetings (median: six professions at meeting) in specialist centres than non-ILD centres (three professions at meeting). Transitioning to virtual MDT meetings allowed HCPs from other locations to join meetings in nearly 90% of all centres, increasing regular participation in 60% of specialist centres and 72% of non-ILD centres. For treatment of patients, specialist centres had better access to antifibrotic drugs (91%) compared to non-ILD centres (60%).CONCLUSIONS: Diagnostic pathways for ILD patients diverged between specialist centres and non-ILD centres. Disparities in resource and specialist availability existed between centres.</p
Mean ocean temperature change and decomposition of the benthic δ <sup>18</sup>O record over the past 4.5 million years
Get PDFWe use a recent reconstruction of global mean sea surface temperature change relative to preindustrial (1GMSST) over the last 4.5 Myr together with independent proxy-based reconstructions of bottom water (1BWT) or deep-ocean (1DOT) temperatures to infer changes in mean ocean temperature (1MOT). Three independent lines of evidence show that the ratio of 1MOT /1GMSST, which is a measure of ocean heat storage efficiency (HSE), increased from ∼ 0.5 to ∼ 1 during the Middle Pleistocene Transition (MPT, 1.5–0.9 Ma), indicating an increase in ocean heat uptake (OHU) at this time. The first line of evidence comes from global climate models; the second from proxy-based reconstructions of 1BWT, 1MOT, and 1GMSST; and the third from decomposing a global mean benthic δ 18O stack (δ 18O b) into its temperature (δ 18O T) and seawater (δ 18O sw) components. Regarding the latter, we also find that further corrections in benthic δ 18O, probably due to some combination of a long-term diagenetic overprint and to the carbonate ion effect, are necessary to explain reconstructed Pliocene sea-level highstands inferred from δ 18O sw. We develop a simple conceptual model that invokes an increase in OHU and HSE during the MPT in response to changes in deep-ocean circulation driven largely by surface forcing of the Southern Ocean. Our model accounts for heat uptake and temperature in the non-polar upper ocean (0–2000 m) that is mainly due to wind-driven ventilation, while changes in the deeper ocean (> 2000 m) in both polar and non-polar waters occur due to high-latitude deepwater formation. We propose that deepwater formation was substantially reduced prior to the MPT, effectively decreasing HSE. We attribute these changes in deepwater formation across the MPT to long-term cooling which caused a change starting ∼ 1.5 Ma from a highly stratified Southern Ocean due to warm SSTs and reduced sea-ice extent to a Southern Ocean which, due to colder SSTs and increased sea-ice extent, had a greater vertical exchange of water masses.</p
Sensing Pico‐Newton Plasmonic Forces and Jerks of LSPR Biochips Using Simple UV‐Visible Spectroscopy
Get PDFLocalized surface plasmon resonances (LSPRs) involve the oscillation of free electrons, leading to the maximum absorption of light by nanostructures at a specific wavelength. This absorption generates an action force exerted by the light on the nanostructures, with a corresponding reaction force—equal in magnitude but opposite in direction—arising from the plasmonic resonances. Additionally, the optical force exerted by light on nanostructures results in jerks or changes in its reaction force over time as it interacts with light. Through mathematical modeling, the reaction forces and jerks on large‐area LSPR chips are determined using basic absorbance and reflection measurements performed with UV‐Visible spectroscopy on gold nanomushrooms. The system tested, immunoglobulin G (IgG) antibody and its complementary antibody complex, revealed forces of 6 and 6.26 pN respectively. These main findings and especially the equations for reaction force and jerk, enhance our understanding of absorbance and reflection spectra obtained from UV‐Visible spectroscopy. The developed model can be applied to analyze light‐induced forces experienced by micro/nano/bio material systems using simple UV‐Visible spectroscopy techniques
Non-pharmacological interventions for the treatment of depression in mid-to-older age minority ethnic populations: a scoping review
Get PDFPeople from minority ethnic (ME) backgrounds are at greater risk of developing depression but are less likely to receive treatment, perpetuated by health inequalities. Non-pharmacological interventions are recommended as the first-line treatment for depression. This scoping review aimed to map international evidence on non-pharmacological interventions for depression in ME populations aged 40 and above. A scoping review was conducted using Medline, PsycINFO, CINAHL, Psychology and Behavioral Sciences Collection, AMED and Embase. Twenty-one studies were included. Six interventions were identified: Cognitive Behavior Therapy, Behavioral Activation, Mindfulness-based, Reminiscence Therapy, Logo-Autobiography and Social Group intervention. Interventions were adapted for ME populations via translation of materials and to the ‘local context’ such as incorporating cultural norms and understanding of depression. This review found a lack of non-pharmacological interventions for depression in people of ME background in the UK. This review indicates a need for non-pharmacological interventions for depression in ME populations in the UK. Recruiting people of ME backgrounds over the age of 40 for randomized controlled trials requires prioritization. It is recommended that non-pharmacological interventions for depression are culturally adapted and co-produced with ME populations
Plasmonic Geometry-Induced Viscoelastic Biocomplex Formation with Optical Concealment, Liquid Slips, and Soundscapes in Bioassays
Get PDFPlasmonic nanoparticles (NPs), typically made up of gold or silver, are widely used in point-of-care bio- and chemical sensing due to their role in enhancing detection sensitivity. Key NP properties influencing sensing performance include the material type, NP size, and geometry. While much research has focused on material and size optimization, less attention has been given to understand NP geometry effects and interactions with biomolecules involved in the bioassay. In this context, we investigate the interfacial propertiesof the biocomplex formed by spherical-shaped gold nanoparticles(AuNPs) and gold nanostars (AuNSts) during a sandwich assay using localized surface plasmon resonance (LSPR) and quartz crystal microbalance with dissipation (QCM-D). The chosen model to study the biocomplex specifically detects interleukin-6 (IL-6). Our results show that AuNSts, with their anisotropic shape and higher surface area, form antibody−antigen complexes more effectively than AuNPs. AuNSts also create a softer, more hydrated layer due to their complex geometry, which leads to larger liquid slips. Lastly, we showed that AuNSts avoid optical concealment at high IL-6concentrations, unlike AuNPs, making them more reliable for detecting a wider range of concentrations. These findings highlight the importance of optimizing NP geometry for improved bio/chemical sensor performance
Teaching Critical Thinking in Sport Sociology
Get PDFCan Chat Generative Pre-Trained Transformer or “ChatGPT” and other Large Language Models (LLMs) be used to create challenging and creative assignments for undergraduate students? This article explores the use of ChatGPT as an interview proxy for students. Drawing inspiration from the medical community’s concept of the simulated patient, ChatGPT was employed to act as an imagined proxy for a figure from the world of sports. Students in an undergraduate “Politics of Sport” course conducted interviews with the ChatGPT proxy using questions derived from peer-reviewed academic research. The assignment had two main objectives: to challenge students to engage meaningfully with academic research and apply it to real-world situations by simulating real-world conditions and to help students consider the limitations of ChatGPT when handling real-world scenarios. Despite some issues that arose during the module, student feedback and coursework indicated that this approach was engaging, fun, and creative for students. It is suggested that this method could be effectively applied across various academic disciplines
What works, how and in which contexts when using digital health to support parents/carers to implement intensive speech and language therapy at home for children with speech sound disorder? A realist review
Get PDFPurposeDigital health solutions to support parent-implemented interventions alongsidedirect speech and language therapist (SLT) input could help increase interventionintensity for children with speech sound disorder (SSD) to meet evidence-basedrecommendations. This realist review explores the factors which could make intensive parent-implemented digital interventions for children with SSD effective, and how this complex intervention might work in different contexts.MethodsRealist review methodology was adopted to explore what works, why, how, for which parents/carers, and in what circumstances. Realist methods aimed to understand the active ingredients, contexts, and associated outcomes of this complex intervention. Preliminary theories were developed to describe how and why digital parent implemented interventions work for children with SSD. Data was extracted from 43 papers to test and refine preliminary theories. Behaviour change theories were used to explain how the intervention works in practice.ResultsA set of 20 explanatory theories were developed to depict how and why digitalparent-implemented interventions work in different contexts. Theories covered five areas: child-participation; the child-parent-SLT dynamic; parent-training; partnership and collaboration; intervention intensity. The theories describe mechanisms of the intervention and how these are responded to in different situations. Findings highlight the importance of intensive intervention for children with SSD.ConclusionsThis realist review adds new in-depth insight into how digital parent-implemented interventions work, for whom, and why. This new understanding has potential to support future successful digital parent-implemented interventions and increase intervention intensity for children with SSD globally. Implications for services and the potential of emerging digital health approaches to promote parent-implemented interventions are discussed
Explainable Artificial Intelligence Driven Segmentation for Cervical Cancer Screening
Get PDFCervical cancer remains an important global health challenge among women. Early and accurate identification of abnormal cervical cells is crucial for effective treatment and improved survival rates. This paper addresses the development of a novel weakly supervised segmentation framework that combines binary classification, Explainable Artificial Intelligence (XAI) techniques, and GraphCut to automate cervical cancer screening. Unlike traditional segmentation methods that rely on pixel-level annotations of medical images, which are costly, laborious, and require expertise in medical imaging, our approach leverages classification-driven insights to segment the nucleus, cytoplasm, and background regions. A key innovation of our framework is the use of XAI techniques such as Grad-CAM++ and LRP combined with GraphCut, to enable annotation-free segmentation using only classification-level labels. This represents a pioneering application of explainability techniques in the context of cervical cancer screening. Among the classification models explored, including fine-tuned variants of VGGNet and XceptionNet, VGG16-Adapted128 achieved the highest performance, marked by an accuracy of 0.94, precision of 0.94, recall of 0.94, and an F1 score of 0.94. This novel segmentation framework employed LRP and GradCAM++ as XAI techniques to gain insight into the decision-making process of classification models, with GradCAM++ demonstrating greater effectiveness. The performance of these XAI methods was assessed through both visual inspection and quantitative metrics, including entropy and pixel flipping. This innovative approach to segmentation is formally introduced through two algorithms detailed in this paper. The weakly supervised segmentation framework achieved a Dice Similarity Coefficient (DSC) of 62.05% and an Intersection over Union (IoU) of 61.89%. In addition, it has received high satisfaction ratings from expert evaluations and has been seamlessly integrated into a user-friendly Web application, offering clinicians a transparent and reliable tool to improve the precision of decision-making in the detection of cervical cancer. Although this work represents an early step, it lays a strong foundation for advancing XAI-driven, weakly supervised segmentation techniques in medical imaging, particularly in resource-constrained cervical cancer screening contexts.</p
Exploring Facilitators and Disruptors of Polarization During Adolescence within Contested Settings: A Case Study of Catholic and Protestant Youth in Northern Ireland
Get PDFToday’s adolescents must find ways to engage in a shared reality, especially in settings marked by intergroup conflict, as a prerequisite for reducing conflict and building collective solutions to societal problems. Polarization processes (epistemic) have been notably overlooked within this critical developmental period. This qualitative case study addresses this gap by identifying key socializing actors and settings within established theoretical frameworks (Ecological Systems Theory, Social Identity, and Intergroup Contact) using in-depth interview data from 45 Catholic and Protestant adolescents living in post-conflict Northern Ireland. Inductive analysis was conducted with the interview data. Findings reveal the importance of family, friends, school, and media as intersecting socializing actors for adolescents. Intergroup contact among peers from different ethno-religious backgrounds disrupted adolescents’ engagement in polarizing and divisive rhetoric. Lastly, adolescents perceived educational actors and settings as less influential than their personal connections to peers and family. Directions for future research leveraging intergroup contact to enhance adolescents’ information networks and educational interventions are discussed