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Innovation in Music: Innovation Pathways
No full textInnovation in Music: Innovation Pathways brings together cutting-edge research on new innovations in the field of music production, technology, performance, and business. With contributions from a host of well-respected researchers and practitioners, this volume provides crucial coverage on the relationship between innovation and rebellion.Including chapters on mixing desks, digital ethics, soundscapes, immersive audio, and computer-assisted music, this book is recommended reading for music industry researchers working in a range of fields, as well as professionals interested in industry innovations
Cross-cultural adaptation and validation of the German version of the Birth Satisfaction Scale-Revised (BSS-R)
Get PDFBackground: Up to one third of women are dissatisfied with their birth experience. A negative birth experience can have detrimental outcomes, making an early detection of dissatisfaction with the birth experience very important. The Birth Satisfaction Scale-Revised (BSS-R) is a multi-dimensional measure of birth satisfaction, which has been translated into several languages. The current study aimed to translate and validate a German version of the BSS-R (DE-BSS-R). Methods: A total of 3747 German women, who were participating in the cross-sectional study INVITE, completed the DE-BSS-R 3–4 months postpartum. The factor structure of the DE-BSS-R was tested using confirmatory factor analysis. Moreover, internal consistency as well as known-groups discriminant, divergent, convergent, and predictive validity were evaluated. Results: Both the tri-dimensional and the bi-factor measurement model of the original BSS-R showed excellent fit to the data. Internal consistency was acceptable for the total score and the subscale Women’s personal attributes, but just below the recommended cut-off for the subscales Stress experienced during labour and Quality of care. However, Cronbach’s alpha did not differ significantly from the acceptable alpha values of the original BSS-R. Women with a non-instrumental vaginal birth had significantly higher birth satisfaction than women with an instrumental birth (instrumental vaginal, caesarean section). The DE-BSS-R showed good divergent, convergent, and predictive validity. Conclusions: Overall, the German cross-cultural adaptation of the BSS-R showed excellent psychometric properties. Both the total score and the three subscale scores are valid to quickly measure German women’s satisfaction with birth in research and clinical practice
Adversarial Robustness of Vision in Open Foundation Models
Get PDFWith the increase in deep learning, it becomes increasingly difficult to understand the model in which AI systems can identify objects. Thus, an adversary could aim to modify an image by adding unseen elements, which will confuse the AI in its recognition of an entity. This paper thus investigates the adversarial robustness of LLaVA-1.5-13B and Meta's Llama 3.2 Vision-8B-2. These are tested for untargeted PGD (Projected Gradient Descent) against the visual input modality, and empirically evaluated on the Visual Question Answering (VQA) v2 dataset subset. The results of these adversarial attacks are then quantified using the standard VQA accuracy metric. This evaluation is then compared with the accuracy degradation (accuracy drop) of LLaVA and Llama 3.2 Vision. A key finding is that Llama 3.2 Vision, despite a lower baseline accuracy in this setup, exhibited a smaller drop in performance under attack compared to LLaVA, particularly at higher perturbation levels. Overall, the findings confirm that the vision modality represents a viable attack vector for degrading the performance of contemporary open-weight VLMs, including Meta's Llama 3.2 Vision. Furthermore, they highlight that adversarial robustness does not necessarily correlate directly with standard benchmark performance and may be influenced by underlying architectural and training factors. INDEX TERMS Llama, visual question answering, projected gradient descent, vision-language models
XRDNet: a Novel Explainable Residual Dense Fusion Network for Alzheimer’s Disease Recognition from MRI Images
No full textAlzheimer’s disease (AD) is a chronic neurodegenerative disorder that significantly contributes to the global burden of dementia, affecting over 55 million individuals worldwide. Early detection of AD is crucial for timely intervention and effective management of symptoms. Traditional diagnostic methods, such as cognitive tests, MRI, and PET scans, are often costly, invasive, and not readily accessible, especially in low- and middle-income countries. Machine learning (ML) and deep learning (DL) methods have great potential by taking advantage of big clinical and imaging data to achieve accurate and non-invasive early diagnosis. This paper presents a new XRD-SCFNet model, integrating the merits of DenseNet and residual networks along with Spatial Context Fusion (SCF) blocks, for AD stage classification based on MRI images. The proposed XRD-SCFNet model integrates dense connections to preserve low-level features, residual connections to enable deep hierarchical feature learning, and SCF blocks to bridge the gap between local and global features. Bayesian optimization is employed for hyperparameter tuning, and conformal prediction is used to provide confidence intervals for model predictions, enhancing interpretability and reliability. The XRD-SCFNet model achieved an overall accuracy of 96.5% and demonstrated robust performance across all stages of AD, thus providing a very accurate and efficient solution for Alzheimer’s disease stage classification based on MRI images
Testing the Use of “Clinical Checks” With the International Trauma Questionnaire to Measure PTSD and Complex PTSD
Get PDFBackground: The International Trauma Questionnaire (ITQ) is the most widely used measure of ICD-11 Posttraumatic Stress Disorder (PTSD) and Complex PTSD (CPTSD). This self-report scale has been used to estimate prevalence rates of these disorders in general population and clinical samples but concerns abound that prevalence estimates derived from self-report measures are too high. To address this concern, we previously introduced the concept of adding ‘clinical checks’ to self-report measures to ensure initial responses reflected the intended clinical meaning of the scale item. Here we provide a rationale for adding clinical checks to the ITQ, describe the process of developing them, and demonstrate their effect at the symptom, cluster, and disorder levels in a general population sample.Methods: A team of researchers and clinicians, including those who developed the ITQ, developed clinical checks for all ITQ items. These were tested using data from a non-probability quota-based representative sample of adults from the United Kingdom (N = 975). Results: Use of clinical checks led to decreases in symptom endorsements ranging from 18.0% to 43.9%, and symptom cluster requirements from 19.1% to 35.9%. Disorder prevalence estimates without the clinical checks were 5.4% for PTSD and 9.5% for CPTSD. With the clinical checks, prevalence estimates dropped to 3.8% for PTSD (relative decrease = 29.6%) and 4.9% for CPTSD (relative decrease = 48.4%). Conclusion: Clinical checks can be easily embedded into the ITQ and have a significant effect on prevalence estimates. We contextualise these results in relation to existing literature on population prevalence estimates derived from clinical interviews, and discrepancies between clinical interviews and self-report measures
Evaluating ‘Study Skills’: What’s the context?
Get PDFStudy Skills in any guise are integral to Higher Education worldwide, existing to help student success. Some argue generic or bolt-on Study Skills do not help with success, others that embedded Study Skills do, but no-one advocates actually evaluating Study Skills in a context of success defined as helping with student educational gain and attainment in their specific subjects. Instead, many evaluate them in arguably inappropriate contexts of a silo or bubble of Study Skills such as attendance or perceived improvements in Study Skills. Indeed, when Study Skills are found effective for success, they are often embedded or delivered in the subject context, but it is not suggested they actually be evaluated in that context. We outline what we consider to be inappropriate contexts for evaluation, and appropriate ones, and outline theory from thinkers such as Mikhail Bakhtin regarding the key role of context and discuss key issues of definitions, silos, and decontextualised metrics. We suggest Study Skills be evaluated by asking: ‘What’s the context? to make them effective in helping aim for student success. We suggest ways to do this, such as through student module evaluations, module reports, or objective student analysis by a third party
Prevalence of information- and advice-seeking by patients for newly prescribed medicines and interventions to promote these behaviours: scoping reviews
Get PDFObjectivesTo conduct scoping reviews to assess the prevalence of information- and advice-seeking by patients from pharmacy personnel for newly prescribed medicines, and interventions to promote these behaviours.MethodsStandard scoping review methods were used and reported using the PRISMA-ScR checklist. Searches were conducted of electronic databases: Medline (via Ovid), Embase (via Ovid), Cinahl (via EBSCO host), and PsycINFO. MeSH terms and keywords were used. The inclusion period was 2010–2024. Independent, duplicate screening, data extraction, and quality appraisal was undertaken. Quality assessment was undertaken using validated tools.Key findingsTwo studies were identified: prevalence (n = 1) and intervention (n = 1). Information was most frequently sought for dosage information and drug side effects. The intervention study evaluated the feasibility and acceptability of a computer kiosk to provide counselling and medication-related advice. The methodological quality varied from low (prevalence n = 1) to moderate (n = 2).ConclusionsThere is paucity of empirical data regarding the extent to which patients engage with information- and advice-seeking and the effectiveness of interventions to promote these behaviours. Knowledge about medicine increases the likelihood of medication adherence and intended health outcomes. This research has identified a knowledge gap in terms of the prevalence of information- and advice-seeking by patients for prescription medicines and the effectiveness of interventions to promote these behaviours. Effective strategies are needed to promote these behaviours to increase adherence and therapeutic benefit, and decrease waste and iatrogenic disease
Utilising on-farm risk assessment data for the management of Johne’s Disease in dairy cattle in Northern Ireland
No full textJohne’s disease (JD) causes weight loss, diarrhoea, and reduced milk yields in clinically infected cattle. In 2020, Animal Health and Welfare Northern Ireland (AHWNI) launched a voluntary JD control programme (JDCP) which focuses on bio-exclusion, biocontainment and market reassurance. Authorised veterinary practitioners (AVPs) conduct a Veterinary Risk Assessment and Management Plan (VRAMP) and use this information to make up to three recommendations. Between August 2022 and January 2024, 2,274 herds enrolled in the NI JDCP and conducted up to three VRAMPs. This study characterised the JD-related risks and veterinary recommendations, identified the risks related to confirmed cases of JD and assessed if farmers changed their practices in response to AVP recommendations. AVPs assigned risk scores to management practices. Practices related to the calving area, particularly an absence of or delayed snatch calving, demonstrated the highest average risk score. Thematic analysis highlighted five main themes within AVP recommendations, including the use of diagnostic testing and management of calving areas. Multivariable binomial logistic regression identified five management practices which significantly increased the likelihood of herds having had a confirmed case of JD, including the segregation of clinically infected or test-positive cows from the rest of the herd in the calving area. Analysis of the risk scores and responses to closed questions from 278 herds which conducted first and second VRAMPs suggested that farmers had not changed their JD-related management practices in response to AVP recommendations. These findings simultaneously outline the challenges in JD control, reinforce the use of VRAMPs in identifying JD-related risks, demonstrate the harmonisation in AVP recommendation themes and provide data which can be considered by industry and policy makers
Semantic-Driven Approach for Validation of IoT Streaming Data in Trustable Smart City Decision-Making and Monitoring Systems
Get PDFEnsuring the trustworthiness of data used in real-time analytics remains a critical challenge in smart city monitoring and decision-making. This is because the traditional data validation methods are insufficient for handling the dynamic and heterogeneous nature of Internet of Things (IoT) data streams. This paper describes a semantic IoT streaming data validation approach to provide a semantic IoT data model and process IoT streaming data with the semantic stream processing systems to check the quality requirements of IoT streams. The proposed approach enhances the understanding of smart city data while supporting real-time, data-driven decision-making and monitoring processes. A publicly available sensor dataset collected from a busy road in Milan city is constructed, annotated and semantically processed by the proposed approach and its architecture. The architecture, built on a robust semantic-based system, incorporates a reasoning technique based on forward rules, which is integrated within the semantic stream query processing system. It employs serialized Resource Description Framework (RDF) data formats to enhance stream expressiveness and enables the real-time validation of missing and inconsistent data streams within continuous sliding-window operations. The effectiveness of the approach is validated by deploying multiple RDF stream instances to the architecture before evaluating its accuracy and performance (in terms of reasoning time). The approach underscores the capability of semantic technology in sustaining the validation of IoT streaming data by accurately identifying up to 99% of inconsistent and incomplete streams in each streaming window. Also, it can maintain the performance of the semantic reasoning process in near real time. The approach provides an enhancement to data quality and credibility, capable of providing near-real-time decision support mechanisms for critical smart city applications, and facilitates accurate situational awareness across both the application and operational levels of the smart city
Forensic Joint Photographic Experts Group (JPEG) Watermarking for Disk Image Leak Attribution: An Adaptive Discrete Cosine Transform–Discrete Wavelet Transform (DCT-DWT) Approach
Get PDFThis paper presents a novel forensic watermarking method for digital evidence distribution in non-cloud environments. The approach addresses the critical need for the secure sharing of Joint Photographic Experts Group (JPEG) images in forensic investigations. The method utilises an adaptive Discrete Cosine Transform–Discrete Wavelet Transform (DCT-DWT) domain technique to embed a 64-bit watermark in both stand-alone JPEGs and those within forensic disk images. This occurs without alterations to disk structure or complications to the chain of custody. The system implements uniform secure randomisation and recipient-specific watermarks to balance security with forensic workflow efficiency. This work presents the first implementation of forensic watermarking at the disk image level that preserves structural integrity and enables precise leak source attribution. It addresses a critical gap in secure evidence distribution methodologies. The evaluation occurred on extensive datasets: 1124 JPEGs in a forensic disk image, 10,000 each of BOSSBase 256 × 256 and 512 × 512 greyscale images, and 10,000 COCO2017 coloured images. The results demonstrate high imperceptibility with average Peak Signal-to-Noise Ratio (PSNR) values ranging from 46.13 dB to 49.37 dB across datasets. The method exhibits robust performance against geometric attacks with perfect watermark recovery (Bit Error Rate (BER) = 0) for rotations up to 90° and scaling factors between 0.6 and 1.5. The approach maintains compatibility with forensic tools like Forensic Toolkit FTK and Autopsy. It performs effectively under attacks including JPEG compression (QF ≥ 60), filtering, and noise addition. The technique achieves high feature match ratios between 0.684 and 0.690 for a threshold of 0.70, with efficient processing times (embedding: 0.0347 s to 0.1187 s; extraction: 0.0077 s to 0.0366 s). This watermarking technique improves forensic investigation processes, particularly those that involve sensitive JPEG files. It supports leak source attribution, preserves evidence integrity, and provides traceability throughout forensic procedures
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