116320 research outputs found
Sort by
Impact of cocrystal dissolution-supersaturation-precipitation (DSP) behaviour on drug permeation across the PermeaPad® biomimetic barrier
Get PDFDirectional active noise control for drone noise reduction.
Get PDFDrones have become essential tools for applications ranging from aerial surveillance to last-mile delivery, raising concerns about noise pollution in populated environments. This paper presents a directional active noise control (ANC) framework that targets far-field noise reduction, rather than local suppression. A virtual microphone-based ANC algorithm is employed, using a near-drone microphone array to attenuate noise in a specific region. Experiments in a semi-anechoic chamber show an average reduction of 4.78 dB in the 1500-2400 Hz band and up to 10 dB at harmonic frequencies, highlighting the promise of directional ANC for quieter drone operations in sensitive settings
Forecasting ballast performance under fast heavy haul trains using an Analytical – Machine Learning Track (AMLT) model
No full textFor ballasted railway tracks catering to fast heavy-haul trains, it is pertinent to consider the dynamic amplification of ballast permanent response with speeds to optimise track maintenance. This paper presents an analytical-machine learning track (AMLT) model to analyse the influence of heavy-haul trains operating at different speeds on permanent vertical strains (εv) and breakage of ballast (BBI). Using a physics-based analytical model, the elasto-dynamic response considering Rayleigh-wave propagation is captured. This response is then used as an input to data-driven models for εv and BBI developed using a Genetic Algorithm integrated with an Artificial Neural Network (GA-ANN), trained with past laboratory data using relevant input parameters. Results showed that both εv and BBI increase with train speeds, and their amplification is significantly greater than the dynamic stress amplification factor. By using operational thresholds for εv and BBI, a new performance-based limiting speed is proposed which can be used as an alternative to critical speed for heavy-haul trains. In contrast to critical speed, the limiting speed is much lower and is also dependent on the axle load and the age of ballast. Furthermore, the influence of stiff subgrade and higher confining stress on limiting speeds are presented with implications to practice
Evaluating Paediatric Injury Hospitalisations From Indoor Trampoline Parks Across Australia: A Multi-Centre Study.
No full textAIM: The introduction and increasing popularity of indoor trampoline facilities has seen increases in the incidence of trampoline park injuries (TPIs), particularly amongst the paediatric population. A challenge to the development of effective injury prevention interventions is the limited study pool of detailed activity and outcome data to provide better understanding of the characteristics of injurious events. METHODS: A cross-sectional study of individuals under 16 years of age hospitalised after TPI from November 2018 to December 2021 was conducted. Patient demographics and TPI characteristics were collected through prospective case notifications from clinicians across Australia, via the Australian Paediatric Surveillance Unit. Additional data were collected using retrospective medical record review at two major paediatric centres in Australia. RESULTS: In total, 48 cases of TPIs were reported: median age was 9.5 years with 28 (58.3%) being males. The most common injury mechanism was a fall on the trampoline (n = 34, 72.3%). The most commonly injured body region was upper limb (n = 27, 56.3%), followed by lower limb (n = 11, 22.9%): all limb injuries involved a fracture. Most patients required operative intervention (n = 37, 90.2%). CONCLUSIONS: The results from this study suggest that serious injuries continue to occur at trampoline parks, and thus remain an injury concern that requires attention. This issue needs to be addressed with consistent application of the Australian Standard, along with other injury prevention initiatives
Unplug, Mute, Avoid: Investigating smart speaker users' privacy protection behaviours in Saudi Homes
Get PDFSmart speakers are increasingly integrated into domestic life worldwide, yet their privacy risks remain underexplored in non-Western cultural contexts. This study investigates how Saudi Arabian users of smart speakers navigate privacy concerns within collectivist, gendered, and often multigenerational households. Using cultural probes followed by semi-structured interviews with 16 participants, we uncover everyday privacy-protective behaviours including unplugging devices, muting microphones, and avoiding voice interactions altogether. These practices are shaped not only by individual risk perceptions but also by household norms, room configurations, and interpersonal dynamics. We contribute empirical insights from an underrepresented region, theoretical extensions to contextual integrity frameworks, and design directions for culturally responsive voice interfaces. This work expands the global conversation on smart speaker privacy and informs more inclusive HCI practices in increasingly diverse smart home environments
Dynamic Performance of Reinforced Rubberized Concrete Beams Supplemented with Waste Tyre Steel Fibres
No full textThis study explores the dynamic behavior of High-Performance Reinforced Rubberized Concrete (RuC) beams. RuC was formulated using locally sourced materials, incorporating supplementary cementitious materials as a cement replacement, with rubber partially replacing sand. A novel blend of 10 mm and 7 mm coarse aggregates, enhanced with Waste Tyre Steel Fibres (WTSF) up to 2%, was employed. This novel material exhibited a compressive strength of 86.4 MPa at 28 days, which further increased to 92.56 MPa after 140 days. Dynamic performance of RuC beams were assessed through drop-weight testing, which involved subjecting the reinforced RuC beams to high-energy impacts to evaluate their impact resistance. The impact testing revealed that reinforced RuC beams supplemented with WTSF performed significantly better, compared to standard RuC beams without WTSF. Moreover, the inclusion of WTSF resulted in increased peak impact forces reaching a peak impact force with 2% WTSF of 424.57 kN—17.6% higher than beams with 1% WTSF supplementation and nearly 65% greater than control RuC beam, while mid-span deflection was reduced by 16% in RuC beams supplemented with WTSF. These results highlight WTSF’s crucial role in enhancing the dynamic behavior of RuC beams, offering a sustainable and high-performance option for structural applications
Targeting trophoblast cell mitochondrial dysfunction in preeclampsia via drug repurposing.
Get PDFPreeclampsia is a multifactorial pregnancy disorder characterized by the new onset of hypertension and organ damage. Mitochondrial dysfunction is central to preeclampsia pathogenesis leading to placental dysfunction and oxidative stress. This study aims to elucidate the mechanisms of mitochondrial dysfunction in first-trimester trophoblast cells and to assess the therapeutic potential of aspirin, metformin, resveratrol, and a FKBPL-based peptide (AD-01) as a strategy to improve trophoblast mitochondrial health. A 2D in vitro model using the first trimester ACH-3Ps trophoblasts were developed to mimic preeclampsia-like conditions, including hypoxia-inducible factor (HIF)-1α activation (DMOG, 100 μM), mitochondrial dysfunction (Rho-6G, 1 μg/mL), or inflammation (TNF-α, 10 ng/ml). Cells were treated for 48 h with metformin (0.5 mM), resveratrol (15 μM), AD-01 (100 nM), or aspirin (0.5 mM), in the presence of DMOG, Rho-6G or TNF--α. Mitochondrial dynamics were assessed by immunofluorescence staining, the Seahorse XF Mito Stress Test, and RT-qPCR for key genes expression regulating mitochondrial fusion (mfn1), fission (dnm1l), and autophagy (atg5, map1lc3b). Preeclampsia-mimicking stimuli significantly altered mitochondrial networks by reducing mitochondrial size (p <0.05-0.0001), increasing circularity (p < 0.05-0.0001), and decreasing mitochondrial number per cell (p < 0.0001). Metformin notably restored mitochondrial architecture under inflammatory stress, normalized mfn1 (p < 0.05) and atg5 expression (p < 0.001), and improved cellular bioenergetics. Aspirin improved mitochondrial morphology under hypoxic conditions and reduced oxygen consumption (p < 0.01). Resveratrol and AD-01 showed context-dependent protective effects, including reduced basal respiration under inflammatory stress (p < 0.0001). These findings demonstrate that hypoxia, inflammation, and mitochondrial dysfunction contribute to mitochondrial pathology in preeclampsia and highlight aspirin, metformin, resveratrol, and AD-01 as promising targeted therapies. Tailored interventions may improve mitochondrial health and pregnancy outcomes in women with preeclampsia
Whole cell microalgae: Potential to transform industry waste into sustainable ruminant feed.
Get PDFMicroalgae offer an innovative solution for utilizing industrial waste to produce sustainable ruminant feed. With strong carbon capture capabilities, they play a vital role in biological carbon capture and utilization. Advances in biotechnology enable the use of industrial waste streams, offering a pathway to reducing carbon emissions and cultivation costs. Extensive research highlights microalgae's nutritional and anti-methanogenic benefits for ruminants, yet they remain commercially unutilized in feed. To address cultivation limitations, this review explores advancements in algae carbon capture biotechnology and proposes brewery waste to support algae cultivation. In addition, the challenges and bottlenecks that remain to be overcome for future commercial translation of this strategy are presented. This review establishes a theoretical solution for integrating microalgae into high-emission industries like breweries and utilization of algae biomass to reduce agricultural emissions
Detecting and Understanding Hateful Contents in Memes Through Captioning and Visual Question-Answering
No full textMemes are widely used for humor and cultural commentary, but they are increasingly exploited to spread hateful content. Due to their multimodal nature, hateful memes often evade traditional text-only or image-only detection systems, particularly when they employ subtle or coded references. To address these challenges, we propose a multimodal hate detection framework that integrates key components: OCR to extract embedded text, captioning to describe visual content neutrally, sub-label classification for granular categorization of hateful content, RAG for contextually relevant retrieval, and VQA for iterative analysis of symbolic and contextual cues. This enables the framework to uncover latent signals that simpler pipelines fail to detect. Experimental results on the Facebook Hateful Memes dataset reveal that the proposed framework exceeds the performance of unimodal and conventional multimodal models in both accuracy and AUC-ROC
EDeformNet: Estimating Fishing Net Deformations from Sparse Observations
No full textThis paper introduces EDeformNet, a novel method for real-time 3D reconstruction of fishing nets using sparse positional measurements. Currently, net deployment during large-scale fishing operations is challenging as the submerged lattice deformations that occur in response to the various environmental factors are not visible to the vessel operator. EDeformNet extends Embedded Deformation Graphs (EDGs), a commonly used technique in template-based nonrigid 3D reconstruction that allows control of embedded spaces through sparse control point correspondences. These can be suitably derived from acoustic tracking beacons attached to the net. EDeformNet enhances the standard EDG optimization scheme by including constraints that preserve surface normals at control points and guard distances between vertices in the template mesh. These improvements are proven to enable an accurate representation of the complex deformations and movements typical in purse seine nets, the fishing technique where the algorithm has been tested, which standard EDG is unable to attain. Moreover, EDeformNet also proposes a tailored strategy that dynamically adjusts the net template according to the known length of the deployed portion of the fishing net. This approach reconstructs exclusively the submerged portion of the fishing net, avoiding extraneous data from above-water sections and enhancing accuracy under realistic fishing conditions. The proposed method is validated using realistic 3D physics simulations in Blender, where quantifiable comparisons demonstrate that EDeformNet effectively captures the spatial dynamics of purse-seining. Compared to standard EDG, EDeformNet achieves superior performance, resulting in at least a 25% improvement across the array of challenging temporal scenarios studied
Data sources:
Access Repository Dashboard
Do you manage OPUS? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!