A two-stage architecture for identifying and locating the source of pain using novel multi-domain binary patterns of EDA

Pain, an extremely unpleasant sensory experience, lacks an objective diagnostic test for accurate measurement. When individuals are unable to communicate, identifying and locating pain becomes crucial for improving treatment outcomes. Despite numerous studies on pain identification, a reliable consensus has yet to be reached. This study, utilising the AI4Pain dataset, aims to establish a strong correlation between Electrodermal Activity (EDA) signal features and the presence of acute pain, as well as clarify the relationship between classified signals and the pain's location. To this end, EDA signals were recorded from 61 subjects while inducing electrical pain in either of two anatomical locations (hand and forearm) for each subject. The EDA data underwent preprocessing to eliminate irrelevant information using a Butterworth IIR bandpass filter and a median filter. A novel feature descriptor called Multi-Domain Binary Patterns (MDBP) was proposed for this research. These MDBPs were combined with time domain features, and a reduced feature vector was obtained using Minimum Redundancy Maximum Relevance (MRMR). The resulting vector then formed the input of ensemble classification algorithms. The proposed method consists of two stages: The first stage focuses on pain detection, while the second stage focuses on pain localisation. Using leave-one-subject-out cross-validation, the proposed method achieved an accuracy of 77.9% in pain detection (Stage I), while the pain localisation experiment (Stage II) resulted in an accuracy of 69.67%. The efficacy of the proposed method was also validated through the publicly available BioVid database.</p

A Unified Deep Learning-Based EEG Biometric Authentication System for Cross-Session Scenarios

Advancements in technology have heightened concerns over personal privacy and security. Electroencephalogram (EEG) signals, valued for their unique and non-forgeable characteristics, have garnered increasing interest for biometric verification. Yet challenges persist in real-world applications, including poor performance in cross-session recognition, lack of generalizability, and narrow focus on specific EEG elicitation protocols. In this paper, we propose a deep learning-based EEG biometric verification system. Our approach introduces advancements in feature extraction: starting with Fast Fourier Transform (FFT) for converting signals to frequency domain, followed by feature mining through a convolutional autoencoder. User verification is accomplished using a Convolutional Neural Network (CNN), known for its superior performance in data mining and classification tasks. In addition, to evaluate the generalizability of the proposed method, extensive experiments are carried out with EEG data collected under seven distinct signal elicitation protocols and over two different recording sessions. Results highlight the stability and reliability of the our method cross diverse scenarios. Comparative analysis with state-of-the-art approaches for EEG biometrics shows that our method excels in robust feature extraction, resulting in better verification performance.</p

Physiological and Biomechanical Characteristics of Inline Speed Skating:A Systematic Scoping Review

The physiological and biomechanical characteristics of inline speed skating have not been systematically mapped nor research evidence synthesized. The aim was to identify and synthesize novel elements across studies, including participant characteristics, outcomes measures, experimental protocol, main outcomes and other relevant information, to inform evidence-based guidelines and recommendations. Following the PRISMA 2020 guidelines, a systematic search of databases was conducted to identify relevant studies. The extracted data were charted and synthesized to summarize the physiological and biomechanical aspects of inline speed skating. From 272 records, 22 studies met the defined criteria. Studies related to inline speed skating focused primarily on physiological variables (n = 14) and lower limb muscles function, with limited evidence on biomechanics of inline speed skating (n = 5) and the combination of biomechanics and physiology (n = 3). An overall unclear risk of bias was observed (59% of studies). Although studies have examined physiological and biomechanical variables, continuous physiological and biomechanical assessments of skaters performing different skills on both straight and curved tracks have not been conducted. Therefore, well-planned physiological and biomechanics studies are required to uncover underexplored areas in research and support the development of sport-specific studies.</p

The Effects of Refractive Imbalance on Binocular Vision Status, Reading Performance, and Vision-Related Reading Difficulty Symptoms in Expert Readers

PURPOSE: To investigate how refractive imbalance affects binocular vision parameters, reading performance, and vision-related reading difficulty symptomatology after short periods of reading with different simulated ophthalmic lens power conditions in expert adult readers.METHODS: Eighteen adult participants (18-35 years of age) were recruited. They were expert readers, defined as currently studying, or previously studied to, at least a bachelor's degree tertiary education level. Refractive imbalance conditions were simulated by placing -2.00, -1.00, 0.00, +1.00, and +2.00 diopters (D) ophthalmic lenses in front of the dominant eye over their full refractive error correction. For each condition, participants were required to read sets of three paragraphs from the background section of an academic journal paper, after which reading comprehension, reading speed, symptomatology, visual acuity, and binocular vision status were assessed for each set through refractive imbalance conditions.RESULTS: A significant reduction of binocular visual acuity was observed for distance (+2.00 D condition) and near (±2.00 D conditions) viewing distances. The greater the refractive imbalance stimulus provided to the dominant eye monocularly, the more underfocused the binocular accommodative response. Simulated refractive imbalance did not affect reading speed and comprehension. Stereoacuity and subjective vision-related reading difficulty symptoms worsened with increased absolute refractive imbalance.CONCLUSIONS: Simulated refractive imbalance did not affect reading performance for the short reading task but resulted in statistically significant reductions in clarity, increased binocular difficulties, and visual discomfort. During reading, full correction of refractive imbalance is beneficial and recommended.</p

Validating adverse events in administrative healthcare data in ireland:a retrospective chart review study

BACKGROUND: Pneumonia, urinary tract infections, pressure ulcers and delirium are adverse events that affect older inpatients. Accurate administrative data are key to improving patient safety and healthcare quality. The aim of the study was to validate Hospital In-Patient Enquiry (HIPE) data on the occurrence of pneumonia, urinary tract infections, pressure ulcers and delirium in older patients discharged from an acute hospital in Ireland through retrospective chart review.METHODS: A cohort of one thousand randomly selected admissions of inpatients aged over 65 from a university, tertiary hospital in 2022 were reviewed using a two-stage retrospective chart review. The researchers, healthcare professionals and patient representatives co-produced a study-specific chart review protocol and data collection instrument. HIPE data were validated by comparing the chart review data to the HIPE data. Since HIPE only codes the presence of the respective adverse event once, the comparisons between the HIPE data and the chart review data were carried out at admission level.RESULTS: Of the 1,000 admissions reviewed, 231 (23.1%) contained at least one adverse event. At event level, 373 adverse events were identified including 133 pressure ulcers in 71 admissions, 101 delirium episodes in 100 admissions, 84 pneumonia episodes in 79 admissions and 55 urinary tract infections in 52 admissions. Of the 302 adverse events found in chart review on admission level, 96 (31.8%) of these were coded in the HIPE data and flagged by the Hospital Acquired Diagnosis indicator. Compared with chart review data, the overall sensitivity of the administrative data was low, and the specificity was high. The positive predictive values varied, and the negative predictive values were generally high. In HIPE data, 42 adverse events were found that were not identified in the chart review.CONCLUSIONS: The results demonstrate that HIPE data may not accurately represent these specific adverse events as experienced by older patients. Improving the accuracy of these data may facilitate benchmarking of adverse events across hospitals and countries and provide opportunities for improvements in patient safety.</p

Parametric design in construction:a new paradigm for quality management and defect reduction

In the realm of construction, the iterative occurrence of design defects during the latter stages frequently jeopardizes building quality, leading to considerable repercussions. Despite extensive research into the causation of design and construction defects and methods to enhance quality outcomes, a noticeable gap persists in comprehensively understanding how parametric design influences building quality. Hence, this study probes the intricate relationship between parametric design and building quality, aiming to forge a conceptual framework that encapsulates their interplay and collective impact on construction excellence. Through a meticulous literature review, the pivotal elements such as design defects, documentation errors, construction technologies, building performance, defect management, cost and time efficiencies, and quality control mechanisms were investigated. The research delineates the pivotal factors that bolster building quality and curtail defects, with a spotlight on integrating parametric design into the fabric of construction quality management. By weaving together current literature insights and focusing on a symbiotic integration of parametric design, this study contributes a novel conceptual framework that stands to advance architectural practices and elevate the paradigm of building quality.</p

Generative optimization of building blocks for density, solar and structural performance

This study addresses the challenge of performance-informed building blocks generation by developing a generative design framework that simultaneously optimizes building massing, density distribution, and solar and structural performance. As energy consumption, carbon emissions, and material efficiency become increasingly critical in building engineering, there is a growing need for integrated methodologies that combine architectural form exploration with quantifiable performance objectives. The aim of this research is to formulate and validate a modular, cell-based algorithm that generates building configurations optimized for solar gain, thermal comfort, and structural efficiency. The methodology employs parametric design tools, including Grasshopper and Python, alongside simulation engines such as Ladybug for solar radiation analysis and Karamba for finite element structural evaluation. Multi-objective optimization is conducted using the Octopus application to identify Pareto-optimal solutions across competing criteria. The proposed approach is validated using a mid-rise residential block case in Tehran, demonstrating its effectiveness under real-world regulatory and climatic constraints. Findings show significant improvements in seasonal solar performance and reductions in structural deflection, with up to 248 % more winter solar gain and 4.6 % lower displacement compared to conventional designs. The key contribution of this research lies in its integration of environmental and structural simulation within an automated generative workflow that ensures both design adaptability and engineering feasibility. The novelty of the study is in bridging early-stage form generation with detailed performance feedback, providing a scalable method for sustainable and structurally sound building design. The proposed framework is adaptable to various site contexts and can inform future advances in computational building engineering.</p

Adaptive Façades for High-Rise Residential Buildings:A Qualitative Analysis of the Design Parameters and Methods

The design and construction of adaptive façades have garnered increasing attention as a means to enhance the energy performance and sustainability of high-rise residential buildings. Adaptive façades can dynamically respond to environmental conditions, reducing reliance on energy-intensive systems and improving occupant comfort. Despite their potential, research on adaptive façade systems in the context of high-rise residential buildings, particularly in Australia, remains limited. This study aims to bridge this gap by identifying the key design parameters, challenges, and optimisation methods for adaptive façades. Through a combination of a comprehensive literature review and 15 semi-structured interviews with industry experts, this research provides insights into the design and performance of adaptive façades. The key findings reveal that the successful implementation of adaptive façades depends on a range of factors, including material choices, shading system typologies, and advanced simulation tools for energy performance analysis. A significant outcome of the study is the development of a conceptual framework that incorporates these design elements with environmental factors and building energy simulation, offering a structured approach to optimise adaptive façade performance. The framework assists architects and engineers in creating energy-efficient, sustainable high-rise residential buildings tailored to the Australian context. Additionally, the study highlights critical challenges, such as financial barriers, regulatory gaps, and the need for improved maintenance strategies, which must be addressed to facilitate the broader adoption of adaptive façades in the residential sector.</p

Evaluating the therapeutic use of music to address anxiety for women undergoing gynaecological and fertility treatments

BACKGROUND: Music has been effectively used to address anxiety associated with medical treatments across broad applications. However, scant evidence exists about using music to reduce the significant anxiety experienced by women undergoing gynaecological procedures and fertility treatments. Such anxiety relates to the nature of procedures/examinations, invasiveness of the procedures, uncertainty around expectations, and intimate body part exposure, potentially affecting outcomes in triggering sympathetic nervous system responses. Music potentially contributes to anxiety management via known physiological and emotional effects. This funded collaborative project investigates therapeutic uses of music to address anxiety before and during gynaecology and fertility procedures, in order to assist participants with reducing their anxiety. METHODS: Participants attending office, day surgery and other hospital procedures (N = 41) completed validated self-report surveys before and after procedures, listening to specific music via a purpose-designed Music Star. Additional contextual and qualitative data was sought to understand the nature of the experience for the women. RESULTS: Results of this study indicated that the music intervention appeared to have a significant effect of reducing anxiety for women awaiting gynaecological and fertility procedures (p &lt; .001, r = .82). CONCLUSIONS: The use of music forms an acceptable intervention to decrease anxiety in this context and can enhance the experience of women during treatment. Such an increased use of music can provide anxiety management benefits to women undergoing gynaecological and fertility treatments, with these experiences suggesting potential educational benefits to support women through this extremely stressful and complex stage of their life.</p