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MiMapper:A Cloud-Based Multi-Hazard Mapping Tool for Nepal
Get PDFNepal is highly susceptible to natural hazards, including earthquakes, flooding, and landslides, all of which may occur independently or in combination. Climate change is projected to increase the frequency and intensity of these natural hazards, posing growing risks to Nepal’s infrastructure and development. To the authors’ knowledge, the majority of existing geohazard research in Nepal is typically limited to single hazards or localised areas. To address this gap, MiMapper was developed as a cloud-based, open-access multi-hazard mapping tool covering the full national extent. Built on Google Earth Engine and using only open-source spatial datasets, MiMapper applies an Analytical Hierarchy Process (AHP) to generate hazard indices for earthquakes, floods, and landslides. These indices are combined into an aggregated hazard layer and presented in an interactive, user-friendly web map that requires no prior GIS expertise. MiMapper uses a standardised hazard categorisation system for all layers, providing pixel-based scores for each layer between 0 (Very Low) and 1 (Very High). The modal and mean hazard categories for aggregated hazard in Nepal were Low (47.66% of pixels) and Medium (45.61% of pixels), respectively, but there was high spatial variability in hazard categories depending on hazard type. The validation of MiMapper’s flooding and landslide layers showed an accuracy of 0.412 and 0.668, sensitivity of 0.637 and 0.898, and precision of 0.116 and 0.627, respectively. These validation results show strong overall performance for landslide prediction, whilst broad-scale exposure patterns are predicted for flooding but may lack the resolution or sensitivity to fully represent real-world flood events. Consequently, MiMapper is a useful tool to support initial hazard screening by professionals in urban planning, infrastructure development, disaster management, and research. It can contribute to a Level 1 Integrated Geohazard Assessment as part of the evaluation for improving the resilience of hydropower schemes to the impacts of climate change. MiMapper also offers potential as a teaching tool for exploring hazard processes in data-limited, high-relief environments such as Nepal.</p
Human Activity Recognition with Noise-Injected Time-Distributed AlexNet
Get PDFThis study investigates the integration of biologically inspired noise injection with a time-distributed adaptation of the AlexNet architecture to enhance the performance and robustness of human activity recognition (HAR) systems. It is a critical field in computer vision which involves identifying and interpreting human actions from video sequences and has applications in healthcare, security and smart environments. The proposed model is based on an adaptation of AlexNet, originally developed for static image classification and not inherently suited for modelling temporal sequences for video action classification tasks. While our time-distributed AlexNet efficiently captures spatial and temporal features and suitable for video classification. However, its performance can be limited by overfitting and poor generalisation to unseen scenarios, to address these challenges, Gaussian noise was introduced at the input level during training, inspired by neural mechanisms observed in biological sensory processing to handle variability and uncertainty. Experiments were conducted on the EduNet, UCF50 and UCF101 datasets. The EduNet dataset was specifically designed for educational environments and we evaluate the impact of noise injection on model accuracy, stability and overall performance. The proposed bio-inspired noise-injected time-distributed AlexNet achieved an overall accuracy of 91.40% and an F1 score of 92.77%, outperforming other state-of-the-art models. Hyperparameter tuning, particularly optimising the learning rate, further enhanced model stability, reflected in lower standard deviation values across multiple experimental runs. These findings demonstrate that the strategic combination of noise injection with time-distributed architectures improves generalisation and robustness in HAR, paving the way for resource-efficient and real-world-deployable deep learning systems.</p
Quinoxaline-based anti-schistosomal compounds have potent anti-plasmodial activity
Get PDFThe human pathogens Plasmodium and Schistosoma are each responsible for over 200 million infections annually, especially in low- and middle-income countries. There is a pressing need for new drug targets for these diseases, driven by emergence of drug-resistance in Plasmodium and an overall dearth of drug targets against Schistosoma. Here, we explored the opportunity for pathogen-hopping by evaluating a series of quinoxaline-based anti-schistosomal compounds for their activity against P. falciparum. We identified compounds with low nanomolar potency against 3D7 and multidrug-resistant strains. In vitro resistance selections using wildtype and mutator P. falciparum lines revealed a low propensity for resistance. Only one of the series, compound 22, yielded resistance mutations, including point mutations in a non-essential putative hydrolase pfqrp1, as well as copy-number amplification of a phospholipid-translocating ATPase, pfatp2, a potential target. Notably, independently generated CRISPR-edited mutants in pfqrp1 also showed resistance to compound 22 and a related analogue. Moreover, previous lines with pfatp2 copy number variations were similarly less susceptible to challenge with the new compounds. Finally, we examined whether the predicted hydrolase activity of PfQRP1 underlies its mechanism of resistance, showing that both mutation of the putative catalytic triad and a more severe loss of function mutation elicited resistance. Collectively, we describe a compound series with potent activity against two important pathogens and their potential target in P. falciparum.</p
Flavonoids from sour jujube leaves:Ultrasound-assisted extraction, UPLC-QQQ-MS/MS quantification, and ameliorative effect on DSS-induced ulcerative colitis in mice
Get PDFTo valorize sour jujube (Ziziphus acidojujuba) leaves, this work focused on the extraction, quantification, and bioactivity assessment of flavonoids. First, ultrasound-assisted extraction (UAE) was employed to extract total flavonoids from sour jujube leaves (SJL-TF), with the procedure optimized through single-factor design and response surface methodology (RSM). SJL-TF yield reached 48.47 ± 0.36 mg/g under optimal circumstances, which included 61 % ethanol as extraction medium, an ultrasound power of 300 W, an extraction time of 33 min, and a liquid–solid ratio of 16 mL/g, showing higher extraction efficiency in comparison to the traditional Soxhlet extraction method. Scanning electron microscopy (SEM) analysis indicated that ultrasound treatment severely damaged the structural integrity of sour jujube leaves, which was more conducive to improving the SJL-TF yield. Then, polyamide resin chromatography was used to purify the crude SJL-TF extracts, increasing the SJL-TF purity by 3.2-fold to 74.58 ± 0.63 %. By developing and validating a UPLC-QQQ-MS/MS method, ten main flavonoids in SJL-TF extracts, including catechin, rutin, isoquercetin, narirutin, nicotiflorin, quercitrin, phlorizin, luteolin, quercetin, and apigenin, were successfully detected concurrently for quality control purposes. Furthermore, the purified SJL-TF showed a strong ameliorative effect on dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in mice, as evidenced by significant mitigation of colonic inflammation and pathological damage. Thus, this work will contribute to improving the application of sour jujube leaves, especially in the pharmaceutical sector.</p
European Biometric Borders and (Im)Mobilities in West Africa:Reflections on Migrant Strategies for Border Circumvention and Subversion
Get PDFThis article argues that the European biometric ID installations and securitization practices at West African borders harm African migrants and compromise the security goals of Europe and Africa. Using Niger's experience, I contend that migrants' poor adaption to the biometric border processes is closely connected to their identity conflicts, as well as their atomization and weakening of their social integration. The new border security measures are implicated in the state's criminalizing and dehumanizing practices which migrants and borderbrokers experience every day. I coin two concepts, namely, biometric reborderization and agentic deborderization, to draw close attention to ways by which the European biometric projects are significantly reconfiguring African borders. These borders now represent both a dynamic space for migration control, and contested sites of biometric circumvention and subversion by biometric noncompliant migrants who constantly negotiate alternative means for mobilities. Moral mobility agents contest/circumvent European biometric reborderization via the use of parallel border routes.<br/
PAMS:The Perseus Arm Molecular Survey–I. Survey description and first results
Get PDFThe external environments surrounding molecular clouds vary widely across galaxies such as the Milky Way, and statistical samples of clouds are required to understand them. We present the Perseus Arm Molecular Survey (PAMS), a James Clerk Maxwell Telescope (JCMT) survey combining new and archival data of molecular-cloud complexes in the outer Perseus spiral arm in 12CO, 13CO, and C18O (J = 3–2). With a survey area of ∼8 deg2, PAMS covers well-known complexes such as W3, W5, and NGC 7538 with two fields at l ≈ 110◦ and l ≈ 135◦. PAMS has an effective resolution of 17 arcsec, and rms sensitivity of Tmb = 0.7–1.0 K in 0.3 km s−1 channels. Here we present a first look at the data, and compare the PAMS regions in the Outer Galaxy with Inner Galaxy regions from the CO Heterodyne Inner Milky Way Plane Survey (CHIMPS). By comparing the various CO data with maps of H2 column density from Herschel, we calculate representative values for the CO-to-H2 column-density X-factors, which are X12CO (3−2) = 4.0 × 1020 and X13CO (3−2) = 4.0 × 1021 cm−2 (K km s−1)−1 with a factor of 1.5 uncertainty. We find that the emission profiles, size–linewidth, and mass–radius relationships of 13CO-traced structures are similar between the Inner and Outer Galaxy. Although PAMS sources are slightly more massive than their Inner Galaxy counterparts for a given size scale, the discrepancy can be accounted for by the Galactic gradient in gas-to-dust mass ratio, uncertainties in the X-factors, and selection biases. We have made the PAMS data publicly available, complementing other CO surveys targeting different regions of the Galaxy in different isotopologues and transitions.</p
What do complementary and alternative medicines mean to UK dairy farmers and how do they use them?
Get PDFBackground: Complementary and alternative medicine (CAM) is used by some farmers to support herd health management practices. There is concern by a large majority of the veterinary community, who consider CAM to be counter to evidence-based practice. Little is known about what and how CAM is used on farms, and it is not clear which products or practices are encompassed by what farmers consider to be CAM. This paper reports on a study exploring the use of CAM on dairy farms in the UK.Methods: Twenty farms with a range of management systems and herd sizes were recruited. Interviews were conducted with 24 farmers via face-to-face, telephone or videoconferencing modalities necessitated by the Covid-19 movement restrictions. 16 farms were visited to collect observational data using ethnographic fieldnotes and photographs. Interviews were conducted using topic guides and explored participants' experience of CAM and potential influence on antibiotic use. Interviews were audio recorded, transcribed, and thematically analysed using NViVo software.Results A range of views and conceptualisation of CAM was identified among the participating dairy farmers. CAM was not usually seen as one particular product or health management tool but encompassed a range of health management strategies and philosophies. Results: indicated that some farmers explore and engage with a range of complementary and alternative medicines and approaches to animal health on dairy farms. Some farmers considered food products, shop bought products, environmental enrichment, in-depth animal observations and technology to form part of their CAM approach. Farmers associated CAM with holistic health management and animal welfare. CAM formed part of a wider ethos regarding holistic farming and land use and was sometimes used to support them in avoiding overuse of antibiotics.Discussion: Farmers use CAM, and their conceptualisation of it is complex. Several resources and stakeholders were consulted by farmers to understand CAM and conventional medicine. Farmers interest in CAM warrants further consideration. This may support dairy farmers to reduce antimicrobial use responsibly, with veterinary support
Horizontal portability:A proposal for representing place-based relational values in research and policy
Get PDFRelational values feature prominently in recent international efforts to protect global biodiversity. In this article, we provide a conceptual approach for researchers, facilitators and policy-makers to adequately represent place-based relational values in assessments of nature's value that inform practice and policy.We suggest employing horizontal portability as an alternative and complement to the dominant mode of assessing nature's value via vertical subsumption. Vertical subsumption is a process through which particular values are generalised into overarching categories to conform to more general value concepts and thereby stripped of their place-specific meanings. In contrast, horizontal portability is introduced here as a conceptual approach that maintains the contextual rootedness of place-based local expressions of value while also communicating them across places, knowledge systems, and communities. The movement (i.e. ‘porting’) is ‘horizontal’ because it allows relational values rooted in a particular biocultural context to speak to different contexts on equal terms.We discuss how research on the value of nature and people –nature relationships can support horizontal portability.Finally, we provide recommendations for the application of horizontal portability that promotes more plurality and greater inclusion of place-based relational values in research, policy and action
The SARAO MeerKAT Galactic Plane Survey extended source catalogue
Get PDFWe present a catalogue of extended radio sources from the SARAO MeerKAT Galactic Plane Survey (SMGPS). Compiled from 56 survey tiles and covering approximately 500 deg 2 across the first, third, and fourth Galactic quadrants, the catalogue includes 16 534 extended and diffuse sources with areas larger than 5 synthesised beams. Of them, 3891 (24% of the total) are confidently associated with known Galactic radio-emitting objects in the literature, such as HII regions, supernova remnants, planetary nebulae, luminous blue variables, and Wolf-Rayet stars. A significant fraction of the remaining sources, 5462 (33%), are candidate extragalactic sources, while 7181 (43%) remain unclassified. Isolated radio filaments are excluded from the catalogue. The diversity of extended sources underscores MeerKAT's contribution to the completeness of censuses of Galactic radio emitters, and its potential for new scientific discoveries. For the catalogued sources, we derived basic positional and morphological parameters, as well as flux density estimates, using standard aperture photometry. This paper describes the methods followed to generate the catalogue from the original SMGPS tiles, detailing the source extraction, characterisation, and crossmatching procedures. Additionally, we analyse the statistical properties of the catalogued populations.</p
Classification of mammographic abnormalities using convolutional neural networks
Get PDFDistinguishing between benign and malignant mammography images is a complex task even for experimented radiologists and, to deal with this issue, researchers developed computer-aided diagnosis systems. This study introduces a machine learning model to classify mammography images into benign and malignant classes. We extract region of interests using the appropriate mask for each mammography image, and we feed it into a modified LeNet model. We add two parallel convolutional blocks to the original LeNet architecture, and we notice a significant increase in the performance. We pre-train the model on the DMID dataset and a subset of the BCDR dataset, and we test it on the remaining subset. The modified lightweight model reached an accuracy of 99%