Where next for global climate deliberation:From proof of concept to a role in transformation

Building on the proof of concept that was the 2021 Global Assembly on the Climate and Ecological Crisis, we explore an expanded and even institutionalized role for effective and consequential citizen deliberation in global climate governance. Such an expanded role could not just strengthen citizen voices in negotiations, but also counter vested interests, promote civic learning, enhance the legitimacy of governance, foster global solidarity, and generate reflective input to galvanize policies.</p

Asthma medication usage after environmental exposure to wildfire smoke:A systematic review

Asthma is a chronic respiratory condition exacerbated by exposure to particulate air pollution. Smoke from landscape fires has been associated with increased mortality, asthma-related admissions to emergency and other hospital departments, and uptake in primary care services. With climate change and more frequent landscape fires, healthcare systems must prepare for disaster, including surges in asthma medication demand. Past reviews have not resolved the direction and magnitude of the association between PM 2.5 exposure during landscape fires and asthma medication use. The aim of this review was to investigate the relationship between exposure to landscape fire smoke and the use of asthma medications. We conducted a systematic review of PubMed, Scopus, and Web of Science, identifying peer-reviewed articles that examined asthma medication usage following environmental exposure to landscape fire smoke. After a full-text review, we identified twelve articles, three from Canada, three from the USA and six from Australia, with five being retrospective cohort studies. Despite differences in study design, outcome and exposure assessment, the included studies reported a consistent increase in asthma medication use after exposure to wildfires. There is consistent evidence that exposure to wildfire smoke is associated with an increase in the use of reliever medications, particularly salbutamol. Increases in other asthma management medications were also consistently identified. Increases in demand for asthma medications after exposure to wildfire smoke highlight the urgent need to address the growing frequency and intensity of wildfires driven by climate change. </p

Coronavirus research topics, tracking twenty years of research

Research publications aimed at understanding the various aspects of Coronaviruses, particularly COVID-19, have significantly shaped our knowledge base. While the urgency to monitor COVID-19 in real-time has decreased, the continual influx of new research of monthly articles underscores the importance of systematic review and analysis to deepen our understanding of the pandemic’s broad impact. To explore research trends and innovations in this space, we developed a pipeline using natural language processing techniques. This pipeline systematically catalogues and synthesises the vast array of research articles, leading to the creation of a dataset with more than eight hundred thousand articles from July 2002 to May 2024. This paper describes the content of this dataset and provides the necessary information to make this dataset accessible and reusable for future research. Our approach aggregates and organises global research related to Coronaviruses into thematic clusters such as vaccine development, public health strategies, infection mechanisms, mental health issues, and economic consequences. Also, we have leveraged the contribution of health experts to review and revise the dataset.</p

Novel Clinical Assessment of Visual, Vestibular, Somatosensory, and Autonomic Function:Establishing Test Re-Test Reliability in a Healthy Population

Introduction: Maintaining balance is a complex process involving the integration of information from the visual, vestibular, and somatosensory (VVS) systems, along with autonomic nervous system (ANS) function. Traditional assessments of these systems are often expensive, limited to specialised settings or focus on overall balance outcomes, potentially overlooking deficits in the individual systems. This study aimed to evaluate the test-retest reliability of a novel, fully portable clinical assessment tool designed to provide objective measures for individual components of the VVS system and ANS function. Methods: Twenty-eight participants (aged 20–88 years), with no comorbidities and meeting Australian physical activity guidelines, completed the protocol twice. The novel clinical assessment tool comprised of two systems: (1) a virtual reality-type headset incorporating eye-tracking to evaluate visual-vestibular function (smooth pursuit and voluntary saccades), and autonomic function (pupil light reflex); and (2) the Active Movement Extent Discrimination Apparatus (AMEDA) for somatosensory function. Reliability was assessed using two-way mixed-effects model (consistency type, single rater) Intraclass Correlation Coefficients (ICC 3,1) calculated in R-studio. The standard error of measurement (SEM) and minimal detectable change (MDC) was also calculated. Bland-Altman plots were utilised to visualise the agreement between two test repeats. Results: Each metric demonstrated at least moderate to good test re-test reliability: left and right AMEDA (ICC = 0.69 and 0.75), smooth pursuit (ICC = 0.67), voluntary saccades (ICC = 0.53), autonomic response delay (ICC = 0.80), parasympathetic function (ICC = 0.86), and sympathetic function (ICC = 0.89). Discussion: This study supports the reliability of a new, fully portable clinical assessment tool to assess VVS and ANS function. By demonstrating the reliability of this new streamlined tool for evaluating the VVS and ANS systems, the findings of this study has the potential to enhance clinical practice and research in falls prevention and balance rehabilitation.</p

Diagnostic analytics for the mixed Poisson INGARCH model with applications

In statistical diagnosis and sensitivity analysis, the local influence method plays a crucial role and is sometimes more advantageous than other methods. The mixed Poisson integer-valued generalized autoregressive conditional heteroscedastic (INGARCH) model is built on a flexible family of mixed Poisson distributions. It not only encompasses the negative binomial INGARCH model but also allows for the introduction of the Poisson-inverse Gaussian INGARCH model and the Poisson generalized hyperbolic secant INGARCH model. This paper applies the local influence analysis method to count time series data within the framework of the mixed Poisson INGARCH model. For parameter estimation, the Expectation-Maximization algorithm is utilized. In the context of local influence analysis, two global influence methods (generalized Cook distance and Q-distance) and four perturbations–case weights perturbation, data perturbation, additive perturbation, and scale perturbation–are considered to identify influential points. Finally, the feasibility and effectiveness of the proposed methods are demonstrated through simulations and analysis of a real data set.</p

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