116320 research outputs found
Sort by
Inhibition of Microcystis aeruginosa Kützing by seven submerged macrophytes and the influence of season and decomposing plant leachate
No full textCertain macrophytes can release allelopathic compounds that inhibit nuisance cyanobacterial growth. To determine the allelopathic potential of submerged macrophytes species native to southeastern Australia, plant filtrate laboratory bioassays were performed against a toxic strain of Microcystis aeruginosa under nutrient-enriched conditions. Macrophytes were collected from Prospect Reservoir, located in Sydney, Australia, during three austral seasons, and plant material was incubated under light and dark conditions. Seven submerged macrophyte species were screened and antialgal effects were identified through the comparison of final cell density and lag phase duration to a control. Growth inhibition was identified in all species, including, for the first time, Vallisneria australis and Potamogeton octandrus, both from genera previously considered allelopathically weak. Filtrates from summer-collected plants and leachate from decomposing plants (dark-incubated) promoted growth inhibition. A higher total phenolic content (TPC) was measured in dark-incubated plant filtrates, and a weak positive relationship between TPC and lag phase duration was observed. A high variability in inhibitive effects was observed indicating variable allelochemical production within individual plants. These findings suggest that allelochemical release may be more widespread among submerged macrophytes than previously assumed
The effectiveness of eHealth-based cardiovascular disease risk communication: a systematic review and meta-analysis.
Full text linkThis study aimed to systematically review and meta-analyze the effectiveness of eHealth-based cardiovascular disease (CVD) risk communication and its impact on health-related outcomes. Twenty-three RCTs were included. The eHealth-based CVD risk communication showed significant improvements in controlling systolic blood pressure (P = 0.03), low-density lipoprotein (P = 0.02), physical activity (P = 0.003), smoking cessation (P = 0.004), disease awareness (P = 0.002), and quality of life (P = 0.03). No significant effects were found for other outcomes, including diastolic blood pressure, total cholesterol, and overall risk scores. These findings provide valuable insights into the potential role of eHealth-based risk communication in CVD prevention. In addition, existing risk communication interventions are multicomponent, and future research could standardize intervention components and optimize intervention elements using the Behavior Change Techniques Taxonomy and factorial designs, while developing targeted risk communication strategies for different populations to improve health outcomes
Barriers to and enablers of Pakistani pharmaceutical export to regulated markets: regulatory perspective.
Full text linkBACKGROUND: The pharmaceutical sector in Pakistan has grown over a period; however, there are certain barriers within the framework that regulate the growth and export of pharmaceuticals in the country. The purpose of this study was to highlight the current challenges for the pharmaceuticals' export from Pakistan, especially to countries with stringent regulatory authorities (SRAs), from a regulatory perspective, and to identify the facilitators that may help resolve these challenges. METHODS: In this qualitative study, data were collected from the participants from the regional offices of Drug Regulatory Authority of Pakistan (DRAP), located in Lahore, Islamabad, and Quetta. Regulatory participants with a minimum experience of 6 years and the designation of an assistant director or above were recruited through purposive sampling. Semi-structured interviews were used to collect information from regulatory experts. Inductive thematic content analysis was employed to conclude the data.Data analysis generated 5 themes and 20 categories/codes. Poor export performance and pharmaceutical growth was attributed to barriers such as: inadequate industrial research and development, non-compliance with the current standards of good manufacturing practices (cGMP), absence of regulatory requirements for high-tech equipment, insufficient academia-industry collaboration, shortage of locally manufactured active pharmaceutical ingredients and lack of support from the government. Accreditation with international organisations such as the World Health Organisation and the Pharmaceutical Inspection Co-operation Scheme was considered deficient. DRAP, in coordination with the Trade Development Authority, could enhance pharmaceutical exports. Addressing the above challenges could boost the export and expand international market share of Pakistani Pharmaceuticals in countries with SRAs. CONCLUSION: The cGMP compliance, regulatory assistance, and appropriate research and development, including bioequivalence studies, could contribute to export enhancement to SRA countries. Further, the exports from Pakistan to countries with SRAs could be enhanced with DRAP's coordination with the trade development authority of Pakistan
Sustainable Optimization Design of Architectural Space Based on Visual Perception and Multi-Objective Decision Making
Full text linkThis study proposes an integrated computational framework that combines deep learning-based visual perception analysis with multi-criteria decision making to optimize indoor architectural layouts in terms of both visual coherence and sustainability. The framework initially employs a deep learning method leveraging edge pixel feature recombination to extract critical spatial layout features and determine key visual focal points. A fusion model is then constructed to preprocess visual representations of interior layouts. Subsequently, an evolutionary deep learning algorithm is adopted to optimize parameter convergence and enhance feature extraction accuracy. To support comprehensive evaluation and decision making, an improved Analytic Hierarchy Process (AHP) is integrated with the entropy weight method, enabling the fusion of objective, data-driven weights with subjective expert judgments. This dual-focus framework addresses two pressing challenges in architectural optimization: sensitivity to building-specific spatial features and the traditional disconnect between perceptual analysis and sustainability metrics. Experimental results on a dataset of 25,400 building images demonstrate that the proposed method achieves a feature detection accuracy of 92.3%, surpassing CNN (73.6%), RNN (68.2%), and LSTM (75.1%) baselines, while reducing the processing time to under 0.95 s and lowering the carbon footprint to 17.8% of conventional methods. These findings underscore the effectiveness and practicality of the proposed model in facilitating intelligent, sustainable architectural design
Multimodal Inverse Attention Network with Intrinsic Discriminant Feature Exploitation for Fake News Detection
No full textMultimodal fake news detection has garnered significant attention due to its profound implications for social security. While existing approaches have contributed to understanding cross-modal consistency, they often fail to leverage modal-specific representations and explicit discrepant features. To address these limitations, we propose a Multimodal Inverse Attention Network (MIAN), a novel framework that explores intrinsic discriminative features based on news content to advance fake news detection. Specifically, MIAN introduces a hierarchical learning module that captures diverse intra-modal relationships through local-to-global and local-to-local interactions, thereby generating enhanced unimodal representations to improve the identification of fake news at the intra-modal level. Additionally, a cross-modal interaction module employs a co-attention mechanism to establish and model dependencies between the refined unimodal representations, facilitating seamless semantic integration across modalities. To explicitly extract inconsistency features, we propose an inverse attention mechanism that effectively highlights the conflicting patterns and semantic deviations introduced by fake news in both intra- and inter-modality. Extensive experiments on benchmark datasets demonstrate that MIAN significantly outperforms state-of-the-art methods, underscoring its pivotal contribution to advancing social security through enhanced multimodal fake news detection
Queering (Un)Certainty in International Criminal Law: Reflections on the International Criminal Tribunal for the Former Yugoslavia
No full textInternational criminal law (ICL) is often understood as embodying certainty. The classification of crimes according to international humanitarian law, the jurisdictions of courts and tribunals, and the designation of innocence and guilt all aim to produce a definitive account of law and violence. ICL attempts to excise the messy, the uncertain, and the political from its practice despite these logics being intrinsic to international law. This chapter grapples with the (un)certainties of ICL. Drawing on my queer reading of the International Criminal Tribunal for the former Yugoslavia (‘ICTY’ or ‘the Tribunal’), the chapter explores how queering can problematise the violence(s) of ICL. It identifies three (un)certainties at/of the ICTY that queer work can disrupt: the law/violence dichotomy, the plural discourses of gender and sexuality, and the queer logics that make violence legible in international law. These offer important interventions for deconstructing ICL as a (violent) form of global governance and for exposing both the subtle, explicit, and complicated ways in which power constitutes the (un)certainty of international law. By queering (un)certainties, the chapter argues for a reimagining of the international (criminal) law project, one that advocates for queerer futures beyond the cis-heteronormative, civilisational, and carceral frames of the ICTY
Geographic signatures in the oral resistome: a comparative metagenomic analysis of healthy individuals from Thailand and Norway.
Full text linkBACKGROUND: The oral cavity is an important yet understudied reservoir of antimicrobial resistance genes (ARGs), potentially shaped by geographic variation in antibiotic usage. OBJECTIVE: To compare the oral resistomes of healthy adults from Thailand and Norway, two countries with contrasting antimicrobial use practices, using shotgun metagenomic sequencing. DESIGN: Stimulated saliva samples were collected from healthy adults in Thailand (n = 43) and Norway (n = 50). ARGs were identified with AMRPlusPlus against the MEGARes database, and microbial taxonomy was profiled with KrakenUniq. Diversity metrics, ordination, and clustering analyses assessed resistome and microbiome structures. RESULTS: Thai samples exhibited significantly greater ARG richness, evenness, and diversity (p < 0.001), driven by higher abundances of multi-biocide, nucleoside, and copper resistance genes. Norwegian samples were enriched in aminoglycoside, sulfonamide, and quaternary ammonium compound resistance genes. Both cohorts shared core oral genera, but Thai samples showed greater taxonomic richness without differences in overall microbiome diversity. Non-metric multidimensional scaling and PERMANOVA revealed stronger geographic separation for resistomes (R² = 0.639) than microbiomes (R² = 0.382). Co-occurrence networks highlighted structured associations between ARG groups and bacterial genera, suggesting ecological influences beyond taxonomic composition. CONCLUSIONS: These results reveal distinct geographic signatures in the oral resistome that are not fully explained by microbiome structure, reflecting the influence of local ecological and societal factors, including antimicrobial exposure. The findings highlight the oral cavity as a dynamic ARG reservoir and support its inclusion in regional antimicrobial resistance surveillance to inform public health strategies
Establishing a Black-Box Benchmarking Framework for Commercial AI Object Detection Systems in Heavy Industries
No full textCommercial AI-driven object detection systems are increasingly deployed in heavy industries to enhance safety and efficiency. However, the absence of standardised benchmarking frameworks limits the ability to objectively assess system reliability, increasing the risk of bias, inconsistencies, and susceptibility to manipulation. This paper presents the first structured black-box benchmarking methodology for complete AI object detection systems in heavy industries. The methodology evaluates systems (hardware + software) independently of their internal algorithms through video-based testing, ensuring a fair, reproducible, and industry-relevant assessment.
The approach integrates controlled monitor-based experimen-
tal testing, automated performance analysis, and contextual
weighting of errors to provide transparent and comparable
evaluations. Intrinsic challenges, such as detection latency
and system misclassification, are examined through a rigorous
testbed design. Results reveal systematic biases in monitor-
based evaluation, including display configuration effects, high-
lighting key considerations for reliable system assessment. The
framework enables vendor-neutral comparisons, improves real-
world reliability assessments, and provides stakeholders with
actionable insights for deploying AI object detection systems in
high-risk environments
Osteogenic Differentiation of Mesenchymal Stem Cells Induced by Geometric Mechanotransductive 3D-Printed Poly-(L)-Lactic Acid Matrices.
Full text linkBone-related defects present a key challenge in orthopaedics. The current gold standard, autografts, poses significant limitations, such as donor site morbidity, limited supply, and poor morphological adaptability. This study investigates the potential of scaffold geometry to induce osteogenic differentiation of human adipose-derived stem cells (hADSCs) through mechanotransduction, without the use of chemical inducers. Four distinct poly-(L)-lactic acid (PLA) scaffold architectures-Traditional Cross (Tc), Triangle (T), Diamond (D), and Gyroid (G)-were fabricated using fused filament fabrication (FFF) 3D printing. hADSCs were cultured on these scaffolds, and their response was evaluated utilising an alkaline phosphatase (ALP) assay, immunofluorescence, and extensive proteomic analyses. The results showed the D scaffold to have the highest ALP activity, followed by Tc. Proteomics results showed that more than 1200 proteins were identified in each scaffold with unique proteins expressed in each scaffold, respectively Tc-204, T-194, D-244, and G-216. Bioinformatics analysis revealed structures with complex curvature to have an increased expression of proteins involved in mid- to late-stage osteogenesis signalling and differentiation pathways, while the Tc scaffold induced an increased expression of signalling and differentiation pathways pertaining to angiogenesis and early osteogenesis
Analysing the Usefulness of Circular Strategies to Improve Supply Chain Resilience Against Demand Changes
Full text linkDemand changes in a supply chain are common events and can hurt its resilience and profitability. It is important to develop appropriate strategies to mitigate demand changes in supply chains. This study develops mathematical modelling and simulation approaches to deal with demand changes using circular strategies. First, a mathematical model is developed to design a supply chain under ideal situations. Then, the model is revised to analyse the impacts of demand changes and further extended to analyse the usefulness of circular strategies to mitigate increased demand. The anyLogistix simulation approach is used to solve the mathematical models and analyse the results of the distribution of an Australian smartphone brand. A sensitivity analysis is also conducted to investigate the impacts of key variables on cost, profit, and demand fulfilment. The results indicate that there will be significant losses in profit and demand fulfilment if the increased demand is not dealt with appropriately. The results also demonstrate a significant benefit of using circular strategies, such as repair and reuse, to improve demand fulfilment and profitability by mitigating the increased demand. This study is unique in the literature as it investigates the usefulness of circular strategies, such as repair and reuse, quantitatively to mitigate increased demand and improve supply chain resilience performance, such as total profit and demand fulfilment. Decision-makers can use the developed models and simulation approaches and the findings to make decisions on how to apply repair and reuse strategies for a smartphone distribution system and to improve its resilience and sustainable performance
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!