University of Wollongong

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    Using rapid response system trigger clusters to characterize patterns of clinical deterioration among hospitalized adult patients

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    Background: Many rapid response system (RRS) events are activated using multiple triggers. However, the patterns in which multiple RRS triggers occur together to activate RRS events are unknown. The purpose of this study was to identify these patterns (RRS trigger clusters) and determine their association with outcomes among hospitalized adult patients. Methods: RRS events among adult patients from January 2015 to December 2019 in the Get With The Guidelines- Resuscitation registry\u27s MET module were examined (n = 134,406). Cluster analysis methods were performed to identify RRS trigger clusters. Pearson\u27s chi-squared and ANOVA tests were used to examine differences in patient characteristics across RRS trigger clusters. Multilevel logistic regressions were used to examine the associations between RRS trigger clusters and outcomes. Results: Six RRS trigger clusters were identified. Predominant RRS triggers for each cluster were: tachypnea, new onset difficulty in breathing, decreased oxygen saturation (Cluster 1); tachypnea, decreased oxygen saturation, staff concern (Cluster 2); respiratory depression, decreased oxygen saturation, mental status changes (Cluster 3); tachycardia, staff concern (Cluster 4); mental status changes (Cluster 5); hypotension, staff concern (Cluster 6). Significant differences in patient characteristics were observed across clusters. Patients in Clusters 3 and 6 had an increased likelihood of in-hospital cardiac arrest (p \u3c 0.01). All clusters had an increased risk of mortality (p \u3c 0.01). Conclusions: We discovered six novel RRS trigger clusters with differing relationships to adverse patient outcomes. RRS trigger clusters may prove crucial in clarifying the associations between RRS events and adverse outcomes and aiding in clinician decision-making during RRS events

    Narrative Review of the Pharmacodynamics, Pharmacokinetics, and Tox-icities of Illicit Synthetic Cannabinoid Receptor Agonists

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    Background: Synthetic cannabinoid receptor agonists (SCRAs) are the most diverse class of new psychoactive substances worldwide, with approximately 300 unique SCRAs identified to date. While the use of this class of drug is not particularly prevalent, SCRAs are associated with several deaths every year due to their severe toxicity. Methods: A thorough examination of the literature identified 15 new SCRAs with a significant clinical impact between 2015 and 2021. Results: These 15 SCRAs have been implicated in 154 hospitalizations and 209 deaths across the US, Europe, Asia, and Australasia during this time period. Conclusion: This narrative review provides pharmacodynamic, pharmacokinetic, and toxicologic data for SCRAs as a drug class, including an in-depth review of known pharmacological properties of 15 recently identified and emerging SCRAs for the benefit of researchers, policy makers, and clinicians who wish to be informed of developments in this field

    Fast and random charging of electric vehicles and its impacts: State-of-the-art technologies and case studies

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    The era of the electrified transportation system is fast approaching. Although the socioeconomic and environmental benefits of electric vehicles (EVs) have contributed to their large-scale utilization, it has also created a huge load demand on the existing power grids throughout the world. Moreover, fast, super-fast, and ultra-super-fast charging stations are under development, some of which are now in the markets. These have the potential to cause power quality issues such as charging transients, rapid voltage fluctuations, and harmonics in the power grids. Moreover, EVs can participate as mobile storage to provide vehicle-to-grid (V2G) support and ancillary services. There are still some barriers to the wide implementation of V2G systems. This paper addresses these issues and provides a review of the state-of-the-art EV technologies and their impacts on power grids. This paper also investigates the impacts of random and fluctuating EV fast-charging loads on the electric power grids, mainly considering the random connection of EVs to the power grids through DC fast-charging stations as the principal source of fluctuating EV loads. A practical electrical grid of Wollongong, New South Wales, Australia has been considered in this work to separately analyze the impacts of constant current (CC) and constant voltage (CV) charging modes upon the grid. Furthermore, design and modeling of three different commercial DC fast charger connections (CHAdeMO, SAE CCS, and ChargePoint Express 200), with separate CC-CV charging modes of the DC fast chargers have been incorporated. To quantify the impacts, two separate scenarios were examined using a simulation platform, with case studies conducted to determine the impacts on the power grid. The first scenario involved three fast charging stations, while the second scenario featured ten stations that were able to charge six and twenty electric vehicles respectively, with various load combinations considered. Each of these scenarios was analyzed under different conditions to evaluate their impact on the grid, using factors such as voltage drops, maximum power demand, current, and voltage total harmonic distortion (THD) for the transformer that was connected to the charging stations. The study results indicated that the power systems were affected more significantly by random and fluctuating EV fast-charging loads, compared to normal EV slow-charging loads

    Highly selective gas sensors for formaldehyde detection based on ZnO@ZIF‑8 core-shell heterostructures

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    Formaldehyde is a hazardous volatile organic pollutant commonly found indoors, making selective and accurate detection of formaldehyde crucial. To achieve this, ZnO@ZIF-8 core-shell heterostructures were fabricated using the sacrificial template method, where the 3D ZnO flower-like structures served as the core material. This innovative approach utilizing the ZIF-8 shell as a “selective gas filter” offers a novel pathway for enhancing the selectivity of formaldehyde sensors. Subsequent investigations revealed that the thickness of the ZIF-8 shell significantly influences the material\u27s performance. Among various configurations tested, the 2-ZnO@ZIF-8 sensor demonstrates the best formaldehyde detection properties, including high response (5 ppm, 5.03), excellent selectivity, short response and recovery times (29/40 s), excellent long-term stability, and a low theoretical detection limit (12.86 ppb) at 175 °C. The enhanced sensing properties can be attributed to the ZIF-8 surface\u27s high adsorption energy for formaldehyde molecules and the selective screening of gas molecules by ZIF-8. Overall, our study presents a promising strategy for developing highly selective gas sensors for formaldehyde detection, with the potential to contribute to improved indoor air quality monitoring and safety measures

    Children\u27s physical activity and sedentary behaviour in before school care: An observational study

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    Objective: In Australia, less than one quarter of children aged 5–12 years meet national physical activity (PA) guidelines. Before school care operates as part of Out of School Hours Care (OSHC) services and provide opportunities for children to meet their daily PA recommendations. The aim of this study was to explore factors associated with children meeting 15 min of moderate-to-vigorous-intensity physical activity (MVPA) while attending before school care. Methods: A cross-sectional study was conducted in 25 services in New South Wales, Australia. Each service was visited twice between March and June 2021. Staff behaviours and PA type and context were captured using staff interviews and the validated System for Observing Staff Promotion of Physical Activity and Nutrition (SOSPAN) time sampling tool. Child PA data were collected using Actigraph accelerometers and associations between program practices and child MVPA analysed. Results: PA data were analysed for 654 children who spent an average of 39.2% (±17.6) of their time sedentary; 45.4% (±11.4) in light PA; and 14.9% (±11.7) in MVPA. Only 17% of children (n = 112) reached ≥15 min MVPA, with boys more likely to achieve this. Children were more likely to meet this recommendation in services where staff promoted and engaged in PA; PA equipment was available; children were observed in child-led free play; and a written PA policy existed. Conclusions: Before school care should be supported to improve physical activity promotion practices by offering staff professional development and guidance on PA policy development and implementation practices

    Time is brain, so we must BEFAST: Improving stroke identification and triage in a rural emergency department

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    Objective: Shoalhaven District Memorial Hospital is a rural (MM3) secondary hospital which is over an hour travel time from the nearest tertiary centre. The objective of the present study was to pilot the implementation of the BEFAST (Balance, Eyes, Face, Arms, Speech and Time) stroke screening tool at the ED, and determine whether its usage improved timely stroke detection. Methods: During initial implementation and training (October–December 2019), triage nurses consulted with senior medical officers before activating stroke calls. Data were collected for the subsequent 24 months (January 2020–2022), and retrospective records for confirmed strokes during a 24-month period prior to BEFAST implementation (October 2017–2019) were also collected. The main outcome measures were triage category, CT scan result time, discharge destination, length of stay (LOS) and Modified Rankin Score (MRS). Results: After BEFAST implementation, patients (n = 268) were three times more likely to be triaged at category 1 or 2, and door-to-CT scan time was reduced by 20.7 min on average. More patients were discharged to their usual residence and more quickly (LOS 7.9 vs 11.1 days). MRS 90 days after stroke was less, and patients were nearly twice as likely to experience an improvement in neurological symptoms. Conclusions: Patient outcomes were improved after implementation of the BEFAST stroke triage tool. More stroke patients were identified upon presentation to the ED, and in a timely fashion. For those with a stroke diagnosis, time-critical interventions can take place earlier, allowing patients to return home sooner, and with less disability

    Mitigating the Adverse Effects of Long-Tailed Data on Deep Learning Models

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    When the data distribution in a dataset is highly imbalanced or long-tailed, it can severely affect the effectiveness of a deep network model. This drop in performance is caused due to the biased classifier, which favours the head-class samples because these samples have more dominant features compared to the tail-class samples. Addressing this challenge requires not only capturing subtle inter-class differences and intra-class similarities but also effectively utilising limited data for the minority classes. Supervised contrastive learning (SCL) and transfer of angle information from head classes to tail classes have recently been proposed to address the problem of long-tail classification. For a well-balanced dataset, SCL demonstrates effectiveness by pulling together samples from the same classes while pushing away samples from different classes. However, when applied to long-tailed datasets, SCL could become biased towards the head-class samples. On the other hand, the method of transfer of angle information aims to address the challenges posed by long-tailed image classification; however, it lacks in achieving both intra-class compactness and inter-class separability. To address the shortcomings and exploit the strengths of both of these approaches, we propose a unique hybrid method that seamlessly integrates supervised contrastive learning and angular variance to mitigate the adverse effects of long-tailed data on deep learning models for image classification. We name our method as Supervised Angular Contrastive Learning (SACL). In our experiments on long-tailed datasets with different class imbalance ratios, we demonstrate that our method outperforms most of the existing baseline approaches

    OTFS and Delay-Doppler Domain Modulation: Signal Detection and Channel Estimation

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    It is envisioned that reliable communications in high-mobility scenarios at high carrier frequencies will play a vital role in the sixth-generation (6G) wireless networks. In these scenarios, the orthogonal frequency-division multiplexing (OFDM) modulation, which has been widely used in both the fourth-generation (4G) and the emerging fifth-generation (5G) wireless networks, is vulnerable to severe Doppler spread. Recently, the orthogonal time-frequency space (OTFS) modulation or general delay-Doppler domain modulation, which conveniently accommodates the channel dynamics via modulating information in the delay-Doppler domain, has emerged as a promising signal waveform for high-mobility wireless communications. In this chapter, we provide an overview of the OTFS waveform and discuss the most fundamental signal processing tasks in an OTFS system: signal detection and channel estimation. We also discuss a range of promising research opportunities and potential applications of delay-Doppler domain modulation in 6G wireless networks

    Universal architecture and defect engineering dual strategy for hierarchical antimony phosphate composite toward fast and durable sodium storage

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    Antimony (Sb)-based anode materials are feasible candidates for sodium-ion batteries (SIBs) due to their high theoretical specific capacity and excellent electrical conductivity. However, they still suffer from volume distortion, structural collapse, and ionic conduction interruption upon cycling. Herein, a hierarchical array-like nanofiber structure was designed to address these limitations by combining architecture engineering and anion tuning strategy, in which SbPO4−x with oxygen vacancy nanosheet arrays are anchored on the surface of interwoven carbon nanofibers (SbPO4−x@CNFs). In particular, bulky PO43− anions mitigate the large volume distortion and generate Na3PO4 with high ionic conductivity, collectively improving cyclic stability and ionic transport efficiency. The abundant oxygen vacancies substantially boost the intrinsic electronic conductivity of SbPO4, further accelerating the reaction dynamics. In addition, hierarchical fibrous structures provide abundant active sites, construct efficient conducting networks, and enhance the electron/ion transport capacity. Benefiting from the advanced structural design, the SbPO4−x@CNFs electrodes exhibit outstanding cycling stability (1000 cycles at 1.0 A g−1 with capacity decay of 0.05% per cycle) and rapid sodium storage performance (293.8 mA h g−1 at 5.0 A g−1). Importantly, systematic in-/ex-situ techniques have revealed the “multi-step conversion-alloying” reaction process and the “battery-capacitor dual-mode” sodium-storage mechanism. This work provides valuable insights into the design of anode materials for advanced SIBs with elevated stability and superior rate performance

    Compliance of the food industry with mandated salt target levels in South Africa: Towards development of a monitoring and surveillance framework

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    This study evaluated the compliance of the food industry with mandated sodium target levels in South Africa for 13 categories of processed foods included in the sodium regulation R.214, and assessed whether there were differences between the sodium content provided on the product and the chemically analysed values. An in-store survey was done (February-June 2021) to collect sodium content data on the nutrition information panels of packaged foods (n = 1103). Commonly consumed brands for nine of the food categories, were physically sampled (n = 198) for sodium content analysis using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Analysed sodium and food label values were compared with maximum permitted targets. According to food labels, 75% of food products had sodium levels at or below targeted limits. For the categories of bread, dry gravy powders and savoury sauce powders, and processed meat (uncured), \u3e 30% of products had sodium levels above legislated targets. The least compliant food category was uncured processed meat which exceeded targets. Sodium levels declared on the packaging were similar to or higher than analytical sodium values, except for uncured processed meat (P \u3c 0.05). According to food labelling and chemical analytical data, 70 – 75% of food products were compliant with the legislated sodium targets

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