Tropical semi‑arid shelves commonly sustain shallow‑water carbonate factories that export bioclasts to adjacent coasts; however, their interactions with relict and modern siliciclastics remain under‑constrained. We investigate a mixed siliciclastic–carbonate system along the Ceará coast (Brazil) by integrating sedimentology, XRF geochemistry, and remote‑sensing mapping across 48 sediment samples spanning inner shelf to coastal environments (barriers, beaches, dunes, lake/lagoonal settings). Inner‑shelf substrates are bioclastic‑rich, sourced primarily from calcareous algae, benthic foraminifera, and molluscs, with mud‑rich seagrass meadows acting as sediment traps. Siliciclastic grains tend to dominate most coastal settings; however, the medium‑sand fractions in some beaches and barriers are bioclastic‑rich, especially where the shelf slope decreases (< 10 m water depth) near the Itapagé Inflexion. A gentle slope, high shallow-water carbonate production, alongshore drift, cross-shore exchange, aeolian sediment transport, and low siliciclastic input from fluvial sources is interpreted to favor accumulation of mixed siliciclastic-carbonates in this semi-arid coastal study area. These results highlight the importance of understanding local controlling factors when developing models of mixed siliciclastic–carbonate sedimentation on semi-arid tropical coasts, rather than relying on a universal model. Future work should quantify bioclastic production and coastal storage, to constrain sediment interaction between highstand coastal zones and the inner shelf.
Closed-form analytical solutions for displacement, strain, and stress serve as essential benchmarks for validating numerical methods. This work constructs complete function sets that generate two classes of strong solutions to the governing partial differential equations of two-dimensional beams. The boundary conditions are of Neumann type, prescribing displacement derivatives (strains) or equivalently stresses along all surfaces. The proposed framework is demonstrated on orthotropic and isotropic beams, effectively reproducing continuous and discontinuous surface stresses. The results provide a versatile set of benchmark solutions for assessing beam mechanics models.
Thin-shell wormholes built from effective black hole geometries are sensitive not only to the lapse function but also to the choice of areal radius. We construct a reflection-symmetric thin-shell wormhole from the positive-lapse sector of a polymer black hole surrounded by Kiselev-type quintessence and keep the nonareal angular function throughout the junction, stability, thermodynamic, and optical analyses. The Israel junction conditions give a negative surface energy density for every static throat on the positive branch, while the tangential null and intrinsic strong energy combinations are controlled by the local lapse slope. The radial dynamics is written as an effective-potential problem in which the nonareal sector produces a momentum-flux term and modifies the local stability criterion for surface equations of state with explicit radius dependence. For the sampled calibrated configurations, the linear barotropic and variable phantomlike closures remain locally unstable, whereas the variable Chaplygin gas admits finite linear radial stability windows. The same geometric correction also modifies the local first-law balance and shell entropy bookkeeping, while the optical analysis shows that cross-throat propagation generates additional inner image branches despite the wormhole and black hole geometries sharing the same exterior critical curve. These results identify how polymer corrections and a quintessence environment jointly reorganize the matter content, radial response, thermodynamic bookkeeping, and optical appearance of the resulting thin-shell wormhole.
Modified black-hole entropies can induce effective spacetime geometries and thereby provide a thermodynamic route for investigating thin-shell wormholes. In this work, we construct symmetric cut-and-paste wormholes from the generic entropic lapse function F_𝒮(r)=1-4πM/𝒮'(r) and formulate the Darmois–Israel junction conditions directly in terms of the lapse and of the entropy derivatives. We derive the surface stresses, shell energy-condition combinations, conservation equation, and radial effective potential, and then apply the formalism to the Bekenstein–Hawking, Barrow, Tsallis–Cirto, Rényi, Kaniadakis, logarithmic, loop-quantum-gravity-inspired, and exponential entropy prescriptions. The analysis shows that the symmetric construction requires negative surface energy density throughout every admissible positive-lapse domain, although entropy deformations can significantly modify the horizon structure, the allowed throat region, and the localization of the surface stresses. Within the parameter domains considered here, all examined constant-barotropic branches are linearly radially unstable, despite quantitative changes in their near-horizon scales. In contrast, a variable Chaplygin shell can support stable configurations, with the stability domains determined jointly by the entropic geometry, the throat radius, and the radial exponent of the shell equation of state. These results establish a unified framework for comparing entropy-induced black-hole geometries as thin-shell wormhole seeds and show that stability is governed not by the entropy deformation alone, but by its interplay with the dynamical response of the matter localized at the throat.
Multi-view data analysis seeks to integrate multiple representations of the same samples in order to recover a coherent low-dimensional structure. Classical approaches often rely on feature concatenation or explicit alignment assumptions, which become restrictive under heterogeneous geometries or nonlinear distortions. In this work, we propose two geometry-aware multi-view embedding strategies grounded in Gromov-Wasserstein (GW) optimal transport. The first, termed Mean-GWMDS, aggregates view-specific relational information by averaging distance matrices and applying GW-based multidimensional scaling to obtain a representative embedding. The second strategy, referred to as Multi-GWMDS, adopts a selection-based paradigm in which multiple geometry-consistent candidate embeddings are generated via GW-based alignment and a representative embedding is selected. Experiments on synthetic manifolds and real-world datasets show that the proposed methods effectively preserve intrinsic relational structure across views. These results highlight GW-based approaches as a flexible and principled framework for multi-view representation learning.
