Browse Articles
Discover research articles across all indexed journals
Continuous processing of sustainable mixed-matrix carbon hollow fiber precursors for ethylene/ethane separation membranes
NLRP3 participates in IL-17 A-induced epithelial-mesenchymal transition in human nasal epithelial cells of chronic rhinosinusitis with nasal polyps
Deployable 3D architectures from wafer-fabricated precursors
Abstract We demonstrate that standard wafer fabrication can produce free-standing, mechanically stable, doubly-curved 3D structures with prescribed Gaussian curvature — a capability not previously achieved through semiconductor manufacturing. The stability of the deployed structures is realized through the bistable nature of their constituent auxetic unit cells. To impose prescribed Gaussian curvatures through deployment, we conformally flatten the target 3D mesh onto the 2D plane and locally tune the microstructure of each unit cell such that its second stable equilibrium occurs at the required isotropic expansion. The resulting precursor features a spatially heterogeneous tessellation. This generative method is validated on a spherical cap deployed from a flat disk through indentation, with deployment accuracy and structural stability confirmed numerically and experimentally. The method is further applied to a range of complex 3D shapes with both positive and negative curvatures. As a functional demonstration, paraboloidal reflectors with tunable focal lengths are fabricated and deployed, with reflected patterns agreeing with geometric optics predictions. This work establishes a route from flexible electronics towards deployable electronics, broadening the spectrum of realizable 3D semiconductor devices.
Life cycle assessment of renewable hydrogen and bioenergy pathways transitioning from conventional to sustainable power generation
Sharp structural variability of the Gorda slab imaged by a fiber array
Abstract Structural variability at the subduction interface imposes stress and strength heterogeneity that affects the behavior of megathrust earthquakes. Characterizing this variability can be challenging because the slab interface is often deep and seismically quiet. Seismic wavefields from intraslab earthquakes can contain high-frequency phase conversions from the megathrust fault that are delayed and distorted by interface topography and velocity heterogeneity. Distributed acoustic sensing (DAS) allows for long-term deployments of dense seismic arrays that can yield many observations of these converted phases at high spatial resolution over large areas. Here, we develop a technique to identify and enhance slab-converted phases in DAS data, and we pick the differential arrival times and relative polarities between the direct and converted phases at short wavelength along the fiber optic cable. We apply this framework to earthquake wavefields measured by a DAS array at the southern end of the Cascadia Subduction Zone, above the locked zone, which suggests kilometer-scale interface roughness and variations in crustal thickness and absolute depth of the Gorda slab. Converted phase wavefields also suggest sharp variability in the presence and position of fluids in the slab and forearc crust.
Application of multiscale token fusion and pruning in CNN–Transformer hybrids under low-data training for image recognition
Abstract In this paper, a hybrid convolutional neural network (CNN) and transformer architecture for image classification that explicitly exploits multiscale spatial representations while maintaining computational efficiency is proposed. A convolutional backbone is first used to extract hierarchical feature maps, which are subsequently tokenized and fused through a cross-scale token fusion (CSTF) mechanism. In addition, several token-level and CNN-level pruning strategies are evaluated to examine whether redundant spatial tokens or convolutional features can be removed without substantially degrading performance. Extensive experiments on Caltech-101 and Oxford-IIIT Pets under low-data training conditions show that the best proposed configurations are dataset-dependent: the single 14 $$\:\times\:14$$ scale achieves 70.28 $$\:\pm\:1.91$$ % accuracy on Caltech-101, while the single 7 $$\:\times\:$$ 7 scale achieves 28.35 $$\:\pm\:1.62$$ % accuracy on Oxford-IIIT Pets. Among the multi-scale fusion models, 7 $$\:\times\:$$ 7+14 $$\:\times\:$$ 14 performs best on Caltech-101 69.68 $$\:\pm\:$$ 1.77%, whereas 7 $$\:\times\:$$ 7+14 $$\:\times\:$$ 14+28 $$\:\times\:$$ 28 performs best on Oxford-IIIT Pets 27.57 $$\:\pm\:$$ 1.05%. CNN kernel pruning achieves the strongest pruning performance on both datasets, reaching 68.37 $$\:\pm\:$$ 1.06% on Caltech-101 and 28.15 $$\:\pm\:$$ 1.15% on Oxford-IIIT Pets. These results indicate that multi-scale token fusion can provide competitive performance, but careful scale selection is more important than simply increasing the number of spatial token scales.
Inflammatory biomarkers of asymptomatic and symptomatic tuberculosis
Abstract A large proportion of individuals with tuberculosis (TB) are asymptomatic. The biological and inflammatory underpinnings of asymptomatic TB are unknown and may differ from symptomatic TB. We characterise blood transcriptomic and proteomic profiles in South African community screening vs. health facility-based triage cohorts. Asymptomatic TB shares core transcriptomic and proteomic features with symptomatic TB, including upregulation of innate, interferon and inflammatory pathways and downregulation of T and B cell pathways. Integration of transcriptomic and proteomic data from asymptomatic TB individuals identifies two distinct sub-clusters characterized by higher or lower bacterial burden, blood IFN-γ responses, BMI, and chest radiographic abnormalities, suggesting different disease severity. We identify a new blood transcriptomic signature of asymptomatic TB. However, diagnostic performance of transcriptomic and proteomic markers is weaker for asymptomatic TB than symptomatic TB, suggesting that policy development for community-based, asymptomatic TB screening should not adopt biomarkers developed for symptomatic TB triage without further optimization.
Intravenous hydrogen-rich acetated Ringer’s solution attenuates liver injury in heatstroke rats through endothelial glycocalyx preservation
Abstract Heatstroke is a life-threatening systemic disorder characterized by hyperthermia, inflammatory activation, endothelial injury, and multiple organ dysfunction. The liver is particularly vulnerable, but effective post-onset therapeutic strategies remain limited. This study examined whether intravenous hydrogen-rich acetated Ringer’s solution (H-AR) attenuates liver injury after heatstroke onset in rats, in comparison with acetated Ringer’s solution alone (Control) and 2% hydrogen inhalation (HI). Liver injury was assessed 60 min after onset using histological scoring and liver enzyme measurements. Circulating markers of inflammation and endothelial injury, endothelial glycocalyx ultrastructure, and 24-h survival were also evaluated. Thermal exposure was comparable among the heatstroke groups. Both H-AR and HI significantly reduced histological liver injury scores compared with Control; H-AR showed significantly greater attenuation than HI and was the only intervention that significantly reduced alanine aminotransferase levels. Both hydrogen-based interventions suppressed high-mobility group box 1 and syndecan-1, preserved endothelial glycocalyx structure, and improved 24-h survival compared with Control. These findings suggest that post-onset intravenous H-AR attenuates heatstroke-associated liver injury, potentially through reduced inflammatory activation and endothelial glycocalyx preservation, and may offer advantages over hydrogen inhalation with respect to hepatoprotection.
Mechanosensory encoding of surface mechanics optimizes locomotion
Abstract Locomotion - whether walking, running, or crawling - depends on the precise coordination of forces between the body and its surroundings. Two critical factors in this process are the force that resists the relative motion between two bodies, and mechanosensation, the body’s ability to sense and respond to mechanical forces. Together, these processes enable efficient locomotion across diverse environments, yet how body-environment interaction forces shape neural activity in freely moving animals remains poorly understood. Here we show that the ‘gentle touch’ receptor neurons (TRNs) in the Caenorhabditis elegans body wall are sensitive to dynamic surface mechanics. Using a combination of calcium imaging and traction force microscopy in freely behaving animals informed by micromechanical stimulation, connectome-scale simulations, and optimal control theory, we identify friction force and crawling velocity as key determinants of mechanoreceptor activity. Mutations disrupting MEC-4 DEG/ENaC ion channel activity in body wall mechanoreceptors produce lethargic animals with impaired proprioceptive regulation, suggesting functional coupling between surface mechanoreceptors and proprioceptors. Together, our findings reveal that gentle ‘touch’ receptors encode body-environment interaction forces during movement to optimize locomotor energetics.
Integrated metabolomics and network pharmacology reveals that icariin antagonizes malignant phenotypes in triple-negative breast cancer via AKT1/SRC/NFKB1-mediated PI3K‒AKT pathway inhibition
Scaling and Population Loss in Mexican Urban Centres
Abstract Despite its pervasive implications, many cities worldwide continue to expand in a fragmented, horizontal manner. We analyse urban growth dynamics in 69 Mexican metropolitan areas from 1990 to 2020 using census data, developing a model of urban form change based on population size, density, and spatial configuration. We employ a radial probability density function and the urban expansion factor to create a framework for comparing urban expansion over time and across different regions. Over the past three decades, Mexico’s urban population has nearly doubled. However, populations have shifted outward, resulting in a decline of 2.5 million residents in central areas. Our analysis shows that distances from the city centre have increased by 28% on average, driven by population losses in central zones combined with growth in peripheral regions.