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Hierarchical rotating-bending metamaterials for simultaneous mechanical vibration suppression and electricity generation
Full text linktriangular joints between dodecagon unit cells. The proposed structure is additively manufactured from thermoplastic polyurethane (TPU) and further analyzed through finite element analysis (FEA) to explore the deformation mechanisms. Under compression, the high-stiffness triangular joints rotate, inducing bending in adjacent walls, resulting in enhanced stability and quasi-zero-stiffness (QZS) features. Local deformation mechanisms include pure bending, bending combined with shear, and simultaneous shrinkage and expansion. To harness these local deformations, piezo elements integration strategies are proposed. A piezo bender (PB) is adhered to regions experiencing pure bending, lead zirconate titanate (PZT) patches are attached where bending and shear coexist, and piezo stacks are applied at locations with shrinkage and expansion. Experimental results show that before and after gluing piezo elements, the structure exhibits obvious vibration isolation performance, which is independent of the number of unit cells. From the frequency transfer functions, at 10 Hz, where vibration isolation arises, the PB and piezo stack generate power around 8.6 and 2.6 μWg , respectively, while PZT generates power around 11 nW/g. At a higher frequency of 200 Hz, the PB generates a power of 32 nW/g, piezo stack generates a power of 7.6 nW/g, and PZT generates a power of 2.9 nW/g. The proposed hierarchical metamaterials provides multifunctional capabilities, simultaneously isolating vibrations and generating electricity. They facilitate versatile solutions in vibration/stiffness control of engineering structures, like wearable devices, home appliances, vehicle parts, and civil infrastructures, by providing self-powered sensing and energy generation ability
Exploring the perceived impact of immigrant groups in Guyana: an analysis of emerging issues in the socio-economic and political contexts
No full textAdaptive curriculum design in a transnational dual masters programme
No full textTransnational education (TNE) programmes frequently encounter tensions between maintaining academic rigour and addressing local contextual realities. This case study examines a part-time dual-award MSc in Financial Technology (FinTech), jointly delivered by a UK public university and a private higher education institution (HEI) in the Philippines. Framed through the glonacal agency heuristic, the paper explores how curriculum design and delivery are shaped by global academic standards, national regulatory frameworks, and local student needs. Drawing on institutional reflections and student feedback, the study analyses the programme’s adaptive curriculum strategy, quality assurance mechanisms, and industry-aligned content. The dual-award structure, where each institution confers its own qualification, requires careful coordination to meet the standards of the UK’s Quality Assurance Agency (QAA), the UK’s Office for Students (OfS) and the Philippines’ Commission on Higher Education (CHED). Findings reveal that local agency plays a decisive role in ensuring contextual relevance, particularly for the challenges faced by mid-career professionals balancing part-time study with urban constraints. The paper contributes to the TNE literature by illustrating a practical model of cross-border delivery that integrates academic compliance, student responsiveness, and collaborative governanc
Flavonoid-rich extracts of Nelumbo nucifera leaves alleviate obesity in HFD-fed mice via microbiota-dependent modulation of brown fat thermogenesis
No full textEthnopharmacological relevance: Nelumbo nucifera Gaertn (lotus) leaf is a commonly used traditional Chinese herbal medicine with a wide range of pharmacological properties, especially lipid-lowering and weight-loss effects. Accumulating evidence highlights activation of the thermogenic program of brown adipose tissue (BAT) as a promising anti-obesity strategy. However, it remains unclear whether such beneficial metabolic effects induced by the lotus leaf are related to its regulatory role in BAT function.
Aim of the study: This work aims to investigate whether the lotus leaf reduces obesity by activating BAT and to elucidate whether the mechanism behind it is related to the regulation of gut microbiota.
Material and methods: A mouse model of obesity was established using a high-fat diet (HFD), and the anti-obesity effect of flavonoid-rich lotus leaf extract (LLE) was determined in vivo. An animal energy metabolism monitoring system confirmed that LLE promoted energy expenditure. Then, RT-qPCR, immunohistochemistry, and Western blotting were conducted to detect the expression of genes and proteins involved in BAT thermogenesis. Subsequently, the underlying mechanisms were demonstrated by 16 S rRNA gene sequencing and non-targeted metabolism analysis. Finally, fecal microbiota transplantation (FMT) was performed to investigate the LLE-dependent alleviation of obesity via the gut microbiota-BAT axis.
Results: Our study demonstrated that LLE effectively reduced weight gain, ameliorated glucolipid disorders, and enhanced energy expenditure in HFD-fed mice. Notably, LLE augmented BAT activity by increasing thermogenic markers (e.g., SIRT1, PGC-1α, UCP1) and repressing inflammatory responses, potentially through activation of β3-AR/AMPK/p38 signaling pathways. Importantly, LLE could mitigate HFD-induced microbial dysbiosis (decrease in Proteobacteria, Verrucomicbiota, Acidobacteriota, Bacteroides, Dubosiella, and increase in Bilophila, Tyzzerella, Oscillibacter, Akkermansia, and Alistipes) and significantly altered 5 metabolite pathways, especially primary bile acid biosynthesis and linoleic acid metabolism. The FMT experiment confirmed that the microbial changes induced by LLE were associated with reduced body weight, enhanced energy expenditure, increased BAT activity, and thermogenesis.
Conclusions: Collectively, our findings reveal that lotus leaf promotes brown fat thermogenesis by modulating gut microbiota, identifying it as a promising new treatment target for obesity
Mindfulness-based interventions for gambling disorder: a systematic review
Full text linkBackground and Aims: Gambling disorder (GD) presents significant psychological, financial, and social consequences. Mindfulness-based interventions (MBIs) have emerged as promising adjunctive treatments. However, the evidence base remains heterogeneous. The present systematic review evaluated the current empirical literature on MBIs for GD, focusing on their efficacy, methodological quality, and limitations.
Methods: Scopus, PubMed, Web of Science, EBSCO, and PsycINFO were searched for English-language studies published between 2012 and April 2025. The final sample comprised 12 studies: five randomized controlled trials, one controlled pilot study, two repeated-measures studies, one mixed-methods study, and three single-group pretest–posttest studies. A narrative synthesis evaluated MBI impacts.
Results: MBIs consistently reduced gambling frequency and cravings while enhancing psychological outcomes. Studies combining mindfulness with cognitive behavioral therapy showed significant declines in problem gambling behavior. Psychological distress and cravings also decreased notably across interventions. The mindfulness components employed varied in focus and application, adding nuance to outcome interpretation. However, it remains unclear to what extent the observed effects can be attributed to mindfulness-specific mechanisms.
Discussion and Conclusions: MBIs show promise as a complementary treatment for gambling disorders, although small sample sizes and methodological limitations suggest a need for more robust research
Deutsche Städte im Klimawandel: Herausforderungen für Politik, Verwaltung und Gesellschaft
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Optimizing the accuracy and efficiency of camera trap image analysis: evaluating AI model performance and a semi-automated workflow
Full text linkThe widespread adoption of camera trap surveys for wildlife monitoring has generated a substantial volume of ecological data, yet processing constraints persist due to the time-consuming process of manual image classification and the reliability of automated systems. This study assesses the performance of Conservation AI’s UK Mammals model in classifying three species—Western European hedgehogs (Erinaceus europaeus), red foxes (Vulpes vulpes), and European badgers (Meles meles)—from a subsample of 234 records from camera trap images collected through a citizen science initiative across residential gardens. This analysis was repeated after retraining the model to assess improvement in model performance. Initial model outputs demonstrated high precision (>0.80) for foxes and hedgehogs but low recall (<0.50) for hedgehogs, with the lowest recall probability of 0.12 at the 95% confidence threshold (CT). Following retraining, model performance improved substantially across all metrics, with average F1-scores (weighted average of precision and recall across the three species tested) improving at all CTs, though discrepancies with human classifications remained statistically significant. Based on performance results from this study, we present a semi-automated, three-step workflow incorporating an artificially intelligent (AI) generalist object detector (MegaDetector), an AI species-specific classifier (Conservation AI), and manual validation. Where privacy concerns restrict citizen science contributions, our pipeline offers an alternative that accelerates camera trap data analysis whilst maintaining classification accuracy. The findings provide baseline performance estimates of Conservation AI’s UK Mammals model and present an approach that offers a practical solution to improve the efficiency of using camera traps in ecological research and conservation planning. We also highlight the importance of continuous AI model training, the value of citizen science in expanding training datasets, and the need for adaptable workflows in camera trap studies