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Distributed detection and bandwidth allocation with hybrid quantized and full-precision observations over multiplicative fading channels
No full textA hybrid detector that fuses both quantized and full-precision observations is proposed for weak signal detection under additive and multiplicative Gaussian noise. We first derive a locally most powerful test (LMPT)–based hybrid detector from the composite probability distribution of the compound observations received by the fusion center, and then analyze its asymptotic detection performance. Subsequently, we optimize the sensor-wise quantization thresholds to achieve near-optimal asymptotic performance at the local sensor level. Moreover, we propose a mixed-integer linear programming approach to solve the optimization problem of transmission bandwidth allocation accounting for bandwidth constraints and error-prone channels. Finally, simulation results demonstrate the superiority of the proposed hybrid detector and the bandwidth allocation strategy, especially in challenging error-prone channel conditions
Towards a sheaf cohomology theory for C<sup>*</sup>-algebras
No full textIn joint work with Pere Ara (Barcelona), we are in the process of develop-ing a full sheaf cohomology theory for noncommutative C*-algebras. In this survey, we discuss the difficulties arising from the fact that the appropriate categories of operator module sheaves over sheaves of C*-algebras are non-Abelian and, therefore, the homol- ogy theory needed has to be set in the more general framework of exact categories.</p
Periodontitis and incident cognitive decline and dementia: a 15-year prospective cohort study of older men residing in Northern Ireland
No full textBackgroundPeriodontitis is a chronic bacterial infection that elicits systemic inflammation. While retrospective studies have linked periodontal pathogens with Alzheimer's disease (AD) and dementia, few have combined cognitive assessments, pathogen exposure, and inflammatory markers.ObjectiveTo investigate the longitudinal risk between periodontitis, cognitive impairment and dementia.MethodsWe examined the relationship between periodontitis and onset of mild cognitive impairment (MCI) and dementia over 15.6 years (SD 1.6) in older men from Northern Ireland enrolled in the PRIME-COG cohort, using logistic regression. We also assessed associations between exposure to periodontal pathogens and blood inflammatory markers.ResultsAmong 642 men, baseline periodontitis was not significantly associated with later onset of dementia and/or MCI (severe versus mild/none, OR 0.83, 95% CI 0.45–1.50, p = 0.923). However, having more teeth predicted lower risk (OR 0.95, 95% CI 0.91–0.99, p = 0.023). Dementia and/or MCI was associated with higher serum IL-6, IL-8, and IFN-γ at baseline, and IL-8 and TGF-β at follow-up. IgG levels to periodontal pathogens remained stable in men who developed dementia and/or MCI but declined in cognitively normal men. A positive correlation between IgG to periodontal pathogens and proinflammatory cytokines was observed in men who developed dementia and/or MCI.ConclusionsClinical periodontitis was not associated with dementia or MCI onset, but tooth retention was protective. Elevated inflammatory markers in affected men suggest systemic inflammation may contribute to cognitive decline. Larger, more diverse cohort studies are needed to clarify the role of periodontal disease in dementia and AD risk.<br/
Translating knowledge(s) across time and space: audiovisual translation of “Traditional Chinese medicine and culture” Open Course (a case study)
No full textThe audiovisual translation (AVT) of online courses plays a crucial role in the rapidly evolving global education landscape. This means that Massive Open Online Courses become massive translation sites, in which complex linguistic, cultural, and epistemological challenges are negotiated. Taking a cue from the EPISTRAN international research project, this article takes a close look at a hugely popular MOOC devoted to Traditional Chinese Medicine and Culture to identify both challenges as well as elements of good practice. One of the key findings is that integrating a translational perspective early into the design process, rather than viewing translation as an extra linguistic layer added at the end, helps minimise conceptual mismatches, maximise participant engagement, and encourage constant revision and updating of knowledge. MOOCs offered by world-renowned educational institutions to a broad range of multilingual and multicultural audiences powerfully showcase translation in its knowledge-making role
ATLAS photometry of interstellar object 3I/ATLAS
No full textWe present calibrated Asteroid Terrestrial-impact Last Alert System (ATLAS) photometry of the interstellar comet 3I/ATLAS (C/2025 N1) from March 28 through 2025 August 29, obtained with the five-site, robotic ATLAS network in the c (420–650 nm), o (560–820 nm), and Teide w (420–720 nm) bands. Stacked difference images yield reliable light curves measured in four fixed apertures that capture the evolving coma. We observe 3I/ATLAS transitioning in color from red (c − o) ≈ 0.7 before MJD 60860 to near-solar (c − o) ≈ 0.3 after MJD 60870, coincident with the appearance of a prominent antisolar tail. The absolute magnitude curve H(t) shows a slope break near MJD 60890 at r ∼ 3.3 au from −0.035 to −0.012 mag day−1, or in terms of coma cross section as a function of heliocentric distance, r−3.9 to r−1.1. We release the aperture photometry with geometry and uncertainties to enable cross-instrument synthesis of 3I/ATLAS activity and color evolution
Editorial for the thematic section: Towards a global anti colonial criminology of war, genocide and resistance
No full textEarly prediction of lithium-ion battery degradation with a generative pre-trained transformer
No full textThe early detection of degradation in lithium-ion batteries (LIBs) is crucial for effective predictive maintenance and recycling. However, accurately predicting the future degradation of LIBs in early stage is challenging due to the barely noticeable performance changes at initial charging cycles and the long-term nonlinear degradation pattern. In this work, we propose a two-stage early-stage degradation prediction method, BatteryGPT, which employs a Generative Pre-trained Transformer (GPT) to autoregressively predict the charging data of entire lifecycle and a state-of-health (SOH) estimator to correlates the predicted charging data with ageing features in LIBs. The validation demonstrates that BatteryGPT can predict the future LIB degradation with high accuracy using early charging data, before any capacity degradation is evident. Predicting with the first 30% of the battery lifetime, BatteryGPT significantly outperforms baselines, achieving a root mean square error (RMSE) of 0.213% for SOH variation prediction, and mean absolute percent errors (MAPE) of 2.30% and 1.18% for knee point and EOL predictions. Even predicting with the first 5% of lifetime charging data, BatteryGPT demonstrates strong early-stage prediction performance
Microplastic assessment approaches for African freshwater biota: a review
No full textMicroplastic pollution is a growing global concern with direct and indirect environmental health impacts. Africa hosts some of the most heavily polluted water bodies, exacerbated by limited management resources and research capacities. To evaluate the state–of–the–art in African freshwater microplastics approaches, we review studies that assessed pollution in freshwater organisms and appraise the field sampling and laboratory techniques used. Thirty–seven studies were included that analysed the status of microplastic concentration, ingestion, and abundance in African freshwater organisms. Of these, 11 studies conducted experimental work in laboratory settings, whereas the remainder were field–based. Studies were biased taxonomically and geographically, with 24 on fish, 10 on macroinvertebrates, and one each on birds and amphibians, and with studies predominantly in a few countries, mainly South Africa. Most of the studies were thus conducted in southern Africa, followed by east Africa, finding fibres to be the most dominant microplastic type, followed by fragments. Laboratory studies predominantly used pellets, polystyrene microbeads, polyethylene, polypropylene, polyvinyl chloride, nylon 66, and polyethylene terephthalate to determine their impact on organisms such as Clarias gariepinus, Oreochromis niloticus, Tilapia sparrmanii, Daphnia magna, Raphidocelis subcapitata and Tetrahymena thermophila. Microplastic extraction and separation from fish and aquatic macroinvertebrates are mostly done using potassium hydroxide (KOH), hydrogen peroxide (H2O2), nitric acid (HNO3) and sodium hydroxide (NaOH). Furthermore, instrumental analytical techniques for microplastics included the use of microscopes and Fourier–transform infrared (FT–IR) or attenuated total reflectance–Fourier transform infrared spectroscopy for polymer verification. Although Africa ranks highly in unmanaged plastic waste, studies on the prevalence of freshwater microplastics and their interactions with freshwater organisms in natural ecosystems remain scarce. Therefore, it is recommended that more studies are conducted to address the substantial gap, given the importance of freshwater biota in biomonitoring, especially in countries with a complete absence of studies on freshwater microplastic pollution