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Evaluating the Quantitative Accuracy and Application of DNA Metabarcoding for Dietary Reconstruction in Ruminants
No full textDNA metabarcoding offers a powerful, non-invasive tool to identify dietary composition with high taxonomic resolution, yet its quantitative accuracy and bias remain a well-recognised limitation across taxa and sample types. This universal challenge is particularly evident in herbivores, where plant material introduces additional amplification constraints. This study evaluates the accuracy of DNA metabarcoding in reconstructing the diets of sheep under controlled feeding trials involving high and low digestibility forage, using two widely used plant DNA barcodes (ITS2 and trnL). A secondary trial tested the detectability and proportional representation of a target species, Medicago sativa, when added to the diet in varying amounts (1%, 5%, 10%). ITS2 provided greater species-level resolution, while trnL showed broader taxonomic coverage but reduced precision. Both markers distinguished diet treatments effectively; however, faecal DNA showed proportional discrepancies from vegetation input, particularly under low-digestibility conditions. M. sativa was reliably detected even at 1% inclusion but was consistently overrepresented in sequence reads. Our findings highlight the strengths and limitations of DNA metabarcoding for herbivore diet studies and underscore the importance of marker choice and the effects of differential digestion biases. These findings demonstrate the need for multi-marker approaches and calibration controls in dietary studies, especially when quantitative interpretation is required. Despite limitations in quantitative accuracy, faecal DNA metabarcoding provides valuable insights into herbivore diet composition and preferences, with future refinements expected to improve its resolution and reliability for ecological monitoring and grazing management.</p
Solution-Phase and Mechanochemical Synthesis and Antimicrobial Activity of New Thiazolo[3,2-a]Pyridine-6-Sulfonamides
No full textThis study focuses on the development of environmentally friendly and efficient synthetic routes for novel thiazolo[3,2-a]pyridine-6-sulfonamide derivatives with potential antimicrobial properties. Using a one-pot multi-component approach, these heterocyclic compounds were synthesized both in solution and under solvent-free mechanochemical conditions. Reactions between 1-(4-oxothiazolidin-2-ylidene)-N-phenylmethane sulfonamide, malononitrile, and aryl aldehydes led to two distinct classes of sulfonamides depending on the stoichiometry of the aldehydes used. A range of these compounds, along with structurally related analogues, was evaluated for antimicrobial activity against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Bacillus cereus. Five derivatives demonstrated significant activity, particularly against S. aureus, highlighting their potential as lead compounds in the development of new antibacterial agents.</p
LPIA palaeo-fjords:new insights from northern Namibia
No full textA detailed understanding of the features produced beneath ice sheets, in terms of both their spatial distribution and their genesis, is crucial for a correct reading of the glacial record. An assemblage of features cut into crystalline bedrock in northern Namibia were produced approximately 300 myr ago during the Late Paleozoic Ice Age and exhibit an outstanding array of structures contained within deep palaeo-fjords, capped by glaciogenic rocks of the basal Dwyka Group. With the exception of a handful of recent studies in the last 3 years, this area has been largely ignored since the mid-twentieth century. By utilizing large-scale aerial and close-range photogrammetry, we map the subglacial substrate in the Eastern Hoarusib palaeovalley at an unprecedented resolution, marking the first time that large swarms of striae and other subglacial bedforms, such as crescentic markings, have been mapped. Quantitative analyses of macroscale ice flow features include around 17 000 measurements, reducing uncertainty regarding ice flow direction. In the Gomatum palaeovalley, c. 100 km to the SW, we utilize detailed micromorphology and sedimentological analyses to examine basal Dwyka Group strata, recognizing delicate dropstone-bearing laminae and micro-imbrication in heterolithic deposits (fining-upward sandstones and siltstones, rhythmic couplets) lying approximately 50–60 m above the present valley floor. These deposits are interpreted as ice-rafted debris and unidirectional current deposits, which testify to the presence of lingering ice during the transgression of the palaeovalleys. More widely, we argue that the quantitative photogrammetric approaches showcased herein could be more widely adopted in studies of the deep time glacial record and possibly benefit the research of Quaternary fjord systems
Welsh Cultural Identity and the Eighteenth-Century Evangelical Revival
No full textSignificant developments in the eighteenth and nineteenth centuries led to a new definition in public discourse of what it meant to be Welsh for a substantial proportion of the population. This work explores the nature of the cultural identity which emerged through the influence of the evangelical revival, making use of the works of William Williams, Pantycelyn, to consider how that identity was fashioned and what its lasting impact was
Unsupervised multimodal thick cloud removal for optical remote sensing images via adversarial learning
No full textCloud contamination is a common degradation in optical remote sensing images, adversely affecting the application of such images. Deep-learning-based cloud removal algorithms with auxiliary information have received increasing attention in recent years. Most of these methods rely on georeferenced, cloud-free optical images from other periods as references. However, the inherent gap between the reference and the target images often leads to inaccurate reconstruction. Unsupervised methods have also been proposed, mitigating the gap issue by eliminating the need for reference images. Yet, they typically and solely rely on reconstruction loss during training, often resulting in unnatural outcomes. To tackle these limitations, we propose ALM-CR (Adversarial Learning–based Multimodal Cloud Removal), an unsupervised two-stage framework that leverages synthetic aperture radar (SAR) as auxiliary input. The first stage performs SAR-to-optical translation for structural and approximate spectral recovery, followed by SAR-optical fusion to restore fine-grained spectral details. The proposed adversarial learning strategy removes the need for temporal reference images, enabling precise reconstruction of cloud-covered images while preventing overfitting. Experimental results demonstrate that our method surpasses existing unsupervised methods on both reference and no-reference metrics, and reconstructs spectral information more consistently than supervised methods.</p
Chain Length and Degree of Saturation of Cooking Fats Influence the Inherent Glycemic Potential of Dietary Starches
Full text linkLipid-induced digestive resistance could be an affordable management strategy to lower the glycemic amplitude of dietary starch. This study evaluated the influence of fatty acid (FA) composition, chain length, and saturation of five cooking fats—ghee (GH), coconut oil (CO), sunflower oil (SO), mustard oil (MO), and til oil (TO)—on the inherent glycemic potential (IGP) of starches from pearl millet (PM) and rice. Starch–lipid (S-L) complexes were analyzed using in vitro starch hydrolysis kinetics. The inclusion of cooking fats in starches resulted in higher resistant starch (RS) content, which was attributed to the formation of stable S-L structures. Fourier transform infrared spectroscopy and x-ray diffraction revealed that GH and MO-induced complexes exhibited longer and shorter starch molecule assemblies in PM and rice, which ultimately limited the IGP to 57.13% and 58.87%, respectively. Subsequently, the in vitro glucose diffusion assay validated the lesser glucose bioavailability from MO-induced starch complexes in the system, revealing the correlation among chain length and degree of saturation of cooking fats in the context of IGP of dietary starches. Henceforth, by understanding these S-L interactions, newer food prototypes could be designed in the near future.</p
3C:Confidence-guided clustering and contrastive learning for unsupervised person re-identification
No full textUnsupervised person re-identification (Re-ID) aims to learn a feature network with cross-camera retrieval capability in unlabelled datasets. Although pseudo-label based methods have achieved great progress in Re-ID, their effectiveness in complex scenarios is hindered by three unresolved challenges: (i) Noisy pseudo-labels due to disturbed clustering. (ii) Camera-biased clusters that lack diversity. (iii) Unreliable hard samples that amplify noise in contrastive learning. To address these issues, a Confidence-guided Clustering and Contrastive learning (3C) framework is proposed in this paper. The 3C framework presents three confidence degrees: (i) in the clustering stage, the confidence of the discrepancy between samples and clusters is proposed to implement a harmonic discrepancy clustering algorithm (HDC); (ii) in the forward-propagation training stage, the confidence of the camera diversity of a cluster is evaluated using a novel camera information entropy (CIE), and clusters with high CIE will play the leading role in model training; and (iii) in the back-propagation training stage, the confidence of the hard sample in each cluster is designed and further used in a confidence integrated harmonic discrepancy (CHD), to select the informative sample for updating the memory for contrastive learning. Extensive experiments on three popular Re-ID benchmarks demonstrated the superiority of the proposed framework. In particular, the 3C framework achieved state-of-the-art results: 86.7%/94.7%, 45.3%/73.1% and 47.1%/90.6% in term of mAP/Rank-1 accuracy on Market-1501, MSMT17 and VeRi-776, respectively.<br/
Genocide:Emergence of Evil in the Absence of Justice
No full textReview of Being Human: Political Modernity and Hospitality in Kurdistan-Iraq, by Fazil Moradi, New Brunswick, NJ, Rutgers University Press, 2024, 210 pp., US$150 (hardcover), ISBN 978197883170
Effects of sensory and environmental labelling of plant-based products on consumer acceptance:Context, energy density and framing factors
No full textThere is growing pressure to replace animal-sourced proteins with plant-based proteins. Consumer studies suggest sensory properties and environment are the major factors impacting adoption of PBFs, but few studies have contrasted these factors. Knowing that health labels negatively impact sensory experience, we tested whether environmental labels had the same negative impact. Using an online survey, volunteers (N = 328) were randomly assigned to one of three label contexts: sensory (emphasizing taste and texture), environmental (highlighting sustainability and environmental impact), or control (no specific messaging), where they evaluated eight plant-based alternative foods. Each product was enhanced by either a positive or a negatively valanced framing statement, with half the foods higher, and half lower, in energy density (ED). Participants rated expected liking, wanting and likely recommendation, and estimated what they would pay for each food. For liking and recommending, there was no significant difference between environmental and sensory contexts (p = 0.94), but both were significantly higher than control (p = 0.0006), while for expected wanting only the sensory exceeded the control (p = 0.0014). The amount willing to pay was significantly higher in the environmental than sensory (p = 0.0005) or control (p < 0.0001) contexts, which did not differ significantly (p = 0.49). For all four measures, higher ED foods were rated significantly more positively than lower ED (p < 0.001), while the effect of environment on purchase price was magnified by higher ED foods (p < 0.001). Positive framing statements were rated significantly higher than negative framing for liking (p < 0.001), wanting (p < 0.001) and recommending (p = 0.022), but not for purchase (p = 0.30). When habitual diet (plant-based or not) was included in the exploratory analyses, it only altered acceptance of lower energy-dense products in the control context. Overall, these data suggest that the use of environmental descriptors may enhance consumer expectations and willingness to pay more to the same degree as sensory descriptors, providing various strategies for marketers and product developers to promote PBFs based on messages that best fit the brand identity and expand the PBFs narrative beyond health
QuTiP 5:The Quantum Toolbox in Python
Full text linkQuTiP, the Quantum Toolbox in Python (Johansson et al., 2012, Johansson et al., 2013), has been at the forefront of open-source quantum software for the past 13 years. It is used as a research, teaching, and industrial tool, and has been downloaded millions of times by users around the world. Here we introduce the latest developments in QuTiP v5, which are set to have a large impact on the future of QuTiP and enable it to be a modern, continuously developed and popular tool for another decade and more. We summarize the code design and fundamental data layer changes as well as efficiency improvements, new solvers, applications to quantum circuits with QuTiP-QIP, and new quantum control tools with QuTiP-QOC. Additional flexibility in the data layer underlying all “quantum objects” in QuTiP allows us to harness the power of state-of-the-art data formats and packages like JAX, CuPy, and more. We explain these new features with a series of both well-known and new examples. The code for these examples is available in a static form on GitHub (https://github.com/qutip/qutip-paper-v5-examples) and as continuously updated and documented notebooks in the qutip-tutorials package (https://github.com/qutip/qutip-tutorials).</p