Browse Articles

Mantle melting and lithospheric structure beneath eastern Australia’s Cenozoic volcanoes from 3D magnetotellurics

Abstract One of the most remarkable features of the eastern Australian continent are Cenozoic age (65 Ma to present) volcanoes over 3,000 km span north-south, with no significant age progression, even though the continent has moved at a rate of up to 75 km/Ma in an NNE direction over much of this time. Three theorems have been advanced to explain age-independent volcanism: (1) decompression melting from the transition zone due to volatile content from subducted slab stagnation; (2) edge-driven convection at the margins of steps in lithospheric thickness that drive upwelling from volatile-rich mantle reservoirs; and (3) melting of low-viscosity pockets of sub-lithospheric mantle due to asthenospheric shear. In this paper we have undertaken a 3D inversion of magnetotelluric (MT) sites across the Tasmanide accretionary orogens in eastern Australia (~ 800 locations) to define the broad-scale resistivity of the lithosphere and asthenosphere. The upper mantle directly beneath the age-independent Cenozoic volcanoes has anomalously low-resistivity (~ 100 Ohm.m) below 125 km depth, compatible with dry lherzolite-harzburgite-wehrlite compositions at temperatures of ~ 1,400 °C. The resistivity model suggests that inland from the volcanos, there is a step-like increase in lithospheric thickness. In the lower crust, beneath volcanic centres a resistivity of ~ 50 Ohm.m is consistent with a hydrated clinopyroxene-orthopyroxene-plagioclase composition at ~ 900 °C. No additional conduction mechanisms (such as graphite, sulphides or partial melt) are required. Results suggest that decompression melting from the transition zone raises the geotherm to adiabatic below 125 km and efficiently removes volatiles to the crust over a wide area (hundreds of kilometres) of subducted slab. Edge-driven convention may also occur at the step in the lithosphere thickness, particularly for the New Volcanic Zone and the leucite Cosgrove Track volcanoes. However, surface volcanism occurs in a much narrower zone where the melt solidus is intersected at lower crustal depths.

The quantitative and qualitative histomorphological structure of human stapes footplate

Abstract This study analyzes the histomorphology of human stapes footplates, focusing on the footplate (FP), to enhance reconstructive otosurgery. Seven human stapes specimens obtained during pathological dissections were histologically processed. Tissue layer thicknesses (bone and cartilage) were measured at five points in longitudinal sections and three points in cross sections. Additional analyses of surrounding tissue area up to 100 μm from each point were conducted. A total of 1400 individual measurements were included in the analysis of the human FP, comprising 350 measurements each for cartilage and bone layer thickness, as well as the determined cartilage and bone areas. The FP consisted of a flat epithelial layer, a bone layer facing the tympanic cavity, and a cartilage layer. The central total thickness was 118.06 μm, increasing by 36% toward the periphery. Bone composition was 40% centrally and larger peripherally at 56%. Cross sections showed more homogeneous distribution, with a total thickness of 73.44 μm and 42% bone. This first detailed qualitative and quantitative topographical tissue analysis of the FP confirms a bilayered bone-cartilage structure with increasing bone thickness toward the periphery. The findings provide critical insights into prosthetic coupling sites and support the development of optimized reconstructive strategies in middle ear surgery.

Development of a homogenizer-disperser of liquid fodder for pigs

Beyond iron deficiency: A comprehensive national survey of anaemia etiology in Sri Lankan young adults

Representativeness of the Danish Blood Donor Study relative to the general population: a cross-sectional assessment

3D imaging contribution in pediatric surgical oncology: a multi-stakeholder assessment study

Visual guided AI color art image generation using enhanced GAN

Advice quality and source disclosure shape trust in AI-generated ethical advice

Abstract Can AI deliver ethical advice of expert quality? Will humans trust it? We address these questions using dilemmas published in the New York Times (NYT) column, The Ethicist, comparing humans’ perception of AI-generated advice (GPT-4) to that of the NYT expert. First, we investigated how useful AI-advice is perceived by diverse participants ( N  = 187), including laypeople, MBA students, and an expert panel of scholars and clergy. We find that people perceive the quality of AI-generated ethical advice to be on par with that of expert advice, with no significant difference in usefulness ratings between the two sources. When given a direct choice, 57% of participants preferred AI-generated advice. Building on these findings, we conducted a three-condition experiment ( N  = 642) investigating how much humans are willing to accept this advice. Our results reveal that before observing the advice, humans display a strong algorithm aversion in this context, with 72.6% of participants preferring to be advised ethically by humans. After being exposed to the quality of the AI-generated advice, however, algorithm aversion is reduced substantially to 53.2%. When hiding the source of the advice, algorithm aversion is further reduced to 46.3%. Taken together, our findings suggest that while humans initially exhibit strong resistance to AI-generated ethical advice, this aversion significantly diminishes when they experience the quality of AI guidance firsthand, indicating that trust in algorithmic ethical reasoning may be more malleable than previously assumed and could evolve as people gain direct exposure to AI’s capabilities in moral decision-making. Protocol registration The stage 1 protocol for this Registered Report was accepted in principle on 13/09/24. The protocol, as accepted by the journal, can be found at https://doi.org/10.17605/OSF.IO/6FPW7 .

A secure and explainable multimodal biometric system using trust adaptive fusion for face and fingerprint

Author Correction: Healthy forests safeguard traditional wild meat food systems in Amazonia

Data-driven classification of Escherichia coli using protein language model ascertains O-serotype determining genes

Abstract Serotyping of Escherichia coli is a critical tool for clinical diagnostics, epidemiology, and vaccine development. Traditional serotyping methods rely on antigen–antibody interactions or reference-based genomic sequence similarity tools that depend on direct matches to predefined serotype gene databases, making their performance highly sensitive to database completeness and limiting their ability to detect or generalize to novel, divergent, or recombinant variants. In this study, we introduce a data-driven approach using a Protein Language Model (PLM) to classify E. coli O serotypes. We applied the ESM-2 model to encode protein sequences into vector representations and trained a machine learning classifier to predict serotypes from genomic data. A dataset of 11,272 E. coli genomes was analyzed, revealing nine ML-prioritized markers— wcaM , wcaL , wcaK , wzzE , wzxC , wecC , glmM , garR , and hisD —that significantly contribute to O serotype classification. The classification model based on these genes outperformed traditional bioinformatics tools, achieving an accuracy of 93% using a Random Forest classifier. Notably, the proposed model exhibits high recall for low-frequency and underrepresented serotypes, leading to improved balanced performance across classes and contributing to the overall increase in classification accuracy. Our findings suggest that PLM-based analysis enhances serotype prediction, providing a scalable and efficient framework for high-throughput epidemiological surveillance and exploratory bacterial classification, complementing current diagnostic methods.

Predicting household cooking fuel choice in sub-Saharan Africa using supervised machine learning analysis of DHS data from 28 countries

Feasibility of short-term hospital mask demand forecasting using a backpropagation neural network under data scarcity

Beyond the forests: peatlands as overlooked carbon stores in coastal British Columbia

Abstract Peatlands are significant carbon stores, and yet their carbon stocks in coastal British Columbia, Canada, remain largely unquantified. We conducted a field assessment to estimate above- and belowground carbon stocks at six peatland sites across the coast of British Columbia. These values, together with data from the Canadian Peat Profile Database, were compared with regional aboveground carbon stock estimates of the upland forests. We found that coastal peatlands store approximately three to five times more carbon per area than adjacent temperate rainforests. Extrapolating these numbers to regional sums is hampered by lacking precise information about the peatland extent of the region. Assuming peatlands cover about 5% of coastal BC, they store at least 370 Mt C, which is about 20% of the upland forest C stock. These results underscore the importance of peatlands, and highlight a need for further assessment of peatlands in this region.

Green colloidal composites from Putranjiva roxburghii wall extract (PRWE) for the prevention of mild steel corrosion in an acidic medium of 1.0 M HCl

Replicated urban mosaics reveal trait- and species-specific shifts in carotenoid and structural plumage colouration of two passerines

Host preference and specialization in the genus Aphanomyces (Oomycetes) from molecular and interaction network insights

Abstract Aphanomyces (Saprolegniales, Oomycetes) includes some of the most economically and environmentally devastating pathogens of plants and freshwater animals. Despite research focused on its pathogenicity and dispersal, key biological questions, such as host range and specialization, remain poorly understood. In this study, we investigated the host preference and specialization within Aphanomyces . First, we delineated species boundaries employing delimitation algorithms based on 261 representative sequences of the nuclear ribosomal internal transcriber spacer (nrITS) from 261 samples of 20 described species and several unidentified taxa. Our results suggested that Aphanomyces diversity was previously underestimated, since we identified 14 putative new species. Furthermore, we compiled an interaction database of 1221 host records. Network analyses revealed Aphanomyces as a highly specialized group mainly targeting two clusters of hosts: freshwater animals or plants in wet terrestrial soils. In addition, pathogenic Aphanomyces species appeared to be highly specialized. This study represents the first investigation encompassing the full diversity of Aphanomyces species, not only economically relevant species. Our results set the basis to better understand the evolutionary history of host specialization of harmful oomycete pathogens.

Spiral phase infrared imaging with undetected photons using a visible wavelength spatial light modulator

Abstract Imaging with undetected photons utilises induced coherence between downconverted photon pairs in a nonlinear interferometer to record an image of an object using infrared probe photons whilst only detecting photons at an easier-to-detect visible wavelength that never interacts with the object. We show that the induced coherence between photon pairs also allows for manipulation of the Fourier components of infrared light from the object, by implementing phase masks on a spatial light modulator placed in the visible beam. By applying a spiral phase mask to the visible beam we demonstrate a well-known Fourier filtering technique, namely spiral phase-contrast imaging of an object placed in the infrared beam, giving omnidirectional edge enhancement of the image. This approach could also be applied to other Fourier filtering microscopy techniques, such as dark-field and phase-contrast microscopy using undetected photons.

Effects of emotional motivation and cognitive control on prospective memory aftereffects of completed intention

Service-oriented vulnerability assessment for the larger-scale high speed railway infrastructure network: a case in China

Abstract High-speed rail (HSR) vulnerability refers to the sensitivity of the infrastructure network to performance degradation under disruptions. Due to the increasing complexity of modern railway systems, topological analysis alone is no longer sufficient to capture their actual operational behavior. Recent studies have increasingly recognized the importance of integrating network functionality with topological structures when assessing vulnerability. This paper proposes a service-oriented vulnerability assessment framework that evaluates HSR vulnerability from the perspective of passenger travel service capacity under uncertain interruptions. A three-layer coupled network is constructed based on a bipartite graph, mapping passenger demand onto infrastructure via a functional layer to capture the coupling between passengers, trains, and tracks. The proposed framework integrates service-based vulnerability metrics, a novel passenger demand evaluation method, and realistic transfer strategies. A case study of China’s HSR network demonstrates the method’s effectiveness. Results show that the network generally exhibits low vulnerability due to strong connectivity. However, lines serving cities with high passenger volumes or involving long-distance transfers are more vulnerable under full-load conditions, where limited spare capacity may force passengers to choose alternative transport modes. These results provide meaningful insights for enhancing disaster prevention and emergency management in high-speed railway systems, emphasizing that the degradation of service capacity should also be regarded as a critical dimension when assessing structural vulnerability.