Search Results (167)

With the growing demand for ecological monitoring and geological exploration, high-quality satellite remote-sensing imagery has become indispensable for accurate information extraction and automated analysis. However, haze reduces image contrast and sharpness, significantly impairing quality. Existing dehazing methods, primarily designed for natural images, struggle with remote-sensing images due to their complex imaging conditions and scale diversity. Given this, we propose a novel Multi-Scale Contextual Attention Generative Adversarial Network (MCA-GAN), specifically designed for satellite image dehazing. Our method integrates multi-scale feature extraction with global contextual guidance to enhance the network’s comprehension of complex remote-sensing scenes and its sensitivity to fine details. MCA-GAN incorporates two self-designed key modules: (1) a Multi-Scale Feature Aggregation Block, which employs multi-directional global pooling and multi-scale convolutional branches to bolster the model’s ability to capture land-cover details across varying spatial scales; (2) a Dynamic Contextual Attention Block, which uses a gated mechanism to fuse three-dimensional attention weights with contextual cues, thereby preserving global structural and chromatic consistency while retaining intricate local textures. Extensive qualitative and quantitative experiments on public benchmarks demonstrate that MCA-GAN outperforms other existing methods in both visual fidelity and objective metrics, offering a robust and practical solution for remote-sensing image dehazing. Full article

Atmospheric and oceanic turbulence can severely degrade the orbital angular momentum (OAM) mode purity of vortex beams in cross-media optical links. Here, we propose a hybrid correction framework that fuses multiscale phase-screen modeling with a lightweight U-Net predictor for phase-distortion—driven solely by measured optical intensity—and augments it with a feed-forward, Gaussian-reference subtraction scheme for iterative compensation. In our experiments, this approach boosts the l = 3 mode purity from 38.4% to 98.1%. Compared to the Gerchberg–Saxton algorithm, the Gaussian-reference feed-forward method achieves far lower computational complexity and greater robustness, making real-time phase recovery feasible for OAM-based communications over heterogeneous channels. Full article

Objectives: In this research study, we introduce a novel approach to develop an innovative nanocarrier system comprising gold nanoparticles (GNPs) loaded with doxorubicin (D) in combination with natural molecules, such as trans-resveratrol (R), piperine (P), and icariin (Ic), against human cervical cancer. The final objective is to improve the anticancer efficacy of doxorubicin on HeLa and CaSki cell lines. Methods: Resveratrol was also used for the synthesis of GNP_R1 nanoparticles. Multi-functional GNPs loaded with D, R, P, and Ic (e.g., GNP_R1@D/R/P/Ic) were successfully prepared and fully characterized by SPR, TEM, HR-TEM, XRD, AFM, DLS, and zeta potential. They were investigated for in vitro stability in various biological media. The cytotoxicity activity was tested on HeLa and CaSki cell lines, using the MTT assay, for their applications as anticancer agents. Results: Our results demonstrate that the novel multi-functional GNPs (such as GNP_R1@D/R and GNP_R1@D/R/P/Ic) can effectively target the cervical cancer cells, improving the bioavailability of therapeutic agents and enhancing their cytotoxicity against cervical cancer cells. In vitro assessments demonstrated that the multi-functional GNPs exhibited improved stability and potential anticancer efficacy on human cervical cancer cells. Conclusions: The described strategy connects the benefits of biomolecules with functional nanoparticles toward the development of various GNP_R1@D/R/P/Ic nanocarriers for their applications as anticancer agents against human cervical cancer. This study provides compelling evidence that the innovative nanoparticles can enhance the therapeutic efficacy of doxorubicin against cervical cancer and offer a more advantageous alternative compared to doxorubicin monotherapy. Full article

This study introduces an analytical framework that integrates the state-space method with generalized thermoelasticity theory to obtain exact solutions for the static and dynamic behaviors of laminated plates featuring imperfect interfaces and resting on a Winkler foundation. The model comprehensively accounts for the foundation-structure interaction, interfacial imperfection, and the coupling between the thermal and mechanical fields. A parametric analysis explores the impact of the dimensionless foundation coefficient, interface flexibility coefficient, and thermal conductivity on the static and dynamic behaviors of the laminated plates. The results indicate that a lower foundation stiffness results in higher sensitivity of structural deformation with respect to the foundation parameter. Furthermore, an increase in interfacial flexibility significantly reduces the global stiffness and induces discontinuities in the distribution of stress and temperature. Additionally, thermal conductivity governs the continuity of interfacial heat flux, while thermo-mechanical coupling amplifies the variations in specific field variables. The findings offer valuable insights into the design and reliability evaluation of composite structures operating in thermally coupled environments. Full article

This article explores the potentialities of “translanguages” as a lens for interpreting transnational women authors whose writing navigates multiple languages. By “translanguages”, we refer to the generation of a collage that results either from the writer’s alternation of various languages within the same work or from their concoction of a language of their own that reappropriates the contents and expressions of various source languages. We will illustrate our tenets by exploring case studies from Assia Djebar and Maxime Garcia Diaz. By resorting to feminist close-reading methodology, we intend to interrogate the possibilities of interpretation (and their limits) from a socially situated position. This, in turn, involves our approach to how the authors’ multiple languages interact and operate upon one another to create meaning and, last but not least, our analysis of the extent to which the transnational and translingual position of these authors shapes our own situated interpretations of the texts as readers. Full article

Few studies have examined Hybrid Aquatic–Aerial Vehicles (HAAVs), autonomous vehicles designed to operate in both air and water, especially those that are aircraft-launched and recovered, with a variable-sweep design to free dive into a body of water and breach under buoyant and propulsive force to re-achieve flight. The novel design research examines the viability of a recoverable sonar-search child aircraft for maritime patrol, one which can overcome the prohibitive sea state limitations of all current HAAV designs in the research literature. This paper reports on the analysis from computational fluid dynamic (CFD) simulations of such an HAAV diving into static seawater at low speeds due to the reverse thrust of two retractable electric-ducted fans (EDFs) and its subsequent breach back into flight initially using a fast buoyancy engine developed for deep-sea research vessels. The HAAV model entered the water column at speeds around 10 ms⁻¹ and exited at 5 ms⁻¹ under various buoyancy cases, normal to the surface. Results revealed that impact force magnitudes varied with entry speed and were more acute according to vehicle mass, while a sufficient portion of the fuselage was able to clear typical wave heights during its breach for its EDF propulsors and wings to protract unhindered. Examining the medium transition dynamics of such a novel HAAV has provided insight into the structural, propulsive, buoyancy, and control requirements for future conceptual design iterations. Research is now focused on validating these unperturbed CFD dive and breach cases with pool experiments before then parametrically and numerically examining the effects of realistic ocean sea states. Full article

Multi-functionality and high mission adaptability are important trends in the development of future aircrafts. Trans-domain aircraft, with their unique take-off and landing capabilities and cross-medium capability, have significant potential in the field of emergency rescue, marine monitoring and tourism. Trans-domain aircraft will meet various flight conditions in different domains. Therefore, the design of wing structures must consider the mechanical effects of different media on the aircraft. In the current study, a fishbone variable camber wing is proposed based on the concept of a camber morphing wing. The relationship between the actuation force and the trailing edge deflection is analyzed using the fluid–structure interaction. The flight performance of the flight conditions including cruise or climb underneath and cruise above the water can also be evaluated in the design iteration since the load-carrying capability can be satisfied and the structural deformation of the fluid loads and the actuators is taken into account. Finite element analysis is also employed for the structural verification. Finally, a structural model is manufactured, which is tested above and under water by measuring the trailing edge deflection using the digital image correlation technology. Full article

Wastewater involving nitrogen-containing emerging contaminants is always accompanied by ammonia nitrogen. In this study, the 254 nm UV light activating peroxymonosulfate (PMS) process was investigated based on its performance and mechanisms for the simultaneous removal of carbamazepine (CBZ) and ammonia nitrogen. The results showed that both CBZ and ammonia could be simultaneously removed from water by the UV/PMS process, which was mainly attributed to the oxidation of SO₄^•− and •OH, respectively. Solution pH did not significantly affect CBZ degradation, but was a crucial factor for the removal of ammonia, and only the alkaline condition was effective for ammonia removal. The steady-state concentration of SO₄^•− (4.37 × 10⁻¹¹ M) at pH 10.5 was determined as 32 times that of •OH (1.35 × 10⁻¹² M), which made CBZ more competitive than ammonia in competing for radicals and more adaptable to coexisting anions. An appropriate increase in PMS concentration and light intensity could improve the removal of ammonia more significantly than that of CBZ, but an over-intense reaction could accelerate the decrease in solution pH, resulting in a plateau in ammonia removal. Moreover, the formation of nitrate and nitrogen gas was the primary transformation route of ammonia in the UV/PMS process. With the optimum PMS concentration of 2 mM, about 50% of the total nitrogen could be removed. The results of this study may provide some insights into applying the UV/PMS process for the simultaneous removal of emerging contaminants and ammonia nitrogen. Full article

Mental health disorders represent a substantial global health concern, impacting millions and placing a significant burden on public health systems. Natural Language Processing (NLP) has emerged as a promising tool for analyzing large textual datasets to identify and predict mental health challenges. The aim of this scoping review is to identify the Arabic NLP techniques employed in mental health research, the specific mental health conditions addressed, and the effectiveness of these techniques in detecting and predicting such conditions. This scoping review was conducted according to the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) framework. Studies were included if they focused on the application of NLP techniques, addressed mental health issues (e.g., depression, anxiety, suicidal ideation) within Arabic text data, were published in peer-reviewed journals or conference proceedings, and were written in English or Arabic. The relevant literature was identified through a systematic search of four databases: PubMed, ScienceDirect, IEEE Xplore, and Google Scholar. The results of the included studies revealed a variety of NLP techniques used to address specific mental health issues among Arabic-speaking populations. Commonly utilized techniques included Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Recurrent Neural Network (RNN), and advanced transformer-based models such as AraBERT and MARBERT. The studies predominantly focused on detecting and predicting symptoms of depression and suicidality from Arabic social media data. The effectiveness of these techniques varied, with trans-former-based models like AraBERT and MARBERT demonstrating superior performance, achieving accuracy rates of up to 99.3% and 98.3%, respectively. Traditional machine learning models and RNNs also showed promise but generally lagged in accuracy and depth of insight compared to transformer models. This scoping review highlights the significant potential of NLP techniques, particularly advanced transformer-based models, in addressing mental health issues among Arabic-speaking populations. Ongoing research is essential to keep pace with the rapidly evolving field and to validate current findings. Full article

Accurate detection of underground grounding lines remains a significant technical challenge due to their deep burial and small cross-sectional dimensions, which cause signal scattering in heterogeneous soil media. This results in blurred features in GPR B-scan images, impeding reliable target identification. To address this limitation, we propose GPR-TSBiNet, an architecture incorporating two key model innovations. We introduce GPR-Transformer (GPR-Trans), a multi-branch backbone network specifically designed for GPR B-scan processing. In the neck stage, we develop the Spatial-Depth Converted Bidirectional Feature Pyramid Network (SC-BiFPN), which integrates SPD-ADown to mitigate feature loss caused by traditional pooling-based downsampling. We employ Shape-IoU as the loss function to enhance boundary detail preservation for small targets. Comparative experiments demonstrate that GPR-TSBiNet outperforms state-of-the-art (SOTA) models YOLOv11 and YOLOv10 in detection accuracy, achieving an AP0.5 improvement of 11.6% over YOLOv11X and 27.4% over YOLOv10X. Notably, the model improves small-target APsmall to 49.4 ± 0.7%, representing a 13.4% increase over the SOTA YOLOv11 model. Finally, real-world GPR validation experiments are conducted, confirming that GPR-TSBiNet provides a reliable solution for underground grounding line detection in GPR-based target recognition. Full article

This essay aims to examine the transformation of the traditional boundary between actantial roles inside fiction in literature and transmediality, to understand how this shift enables potential encounters between complex characters. This study focuses on contemporary complexity novels, where characters attempt to break free from their author-creators, as they offer a particularly compeling dynamic for investigation. It will examine this type of complex narration while also exploring the fluidity of contemporary storytelling in literature and transmediality, which introduces innovative narrative structures. Novels that reflect on the relationship between authorship and characters provide valuable insights from both a theoretical-literary and transmedia perspective, which deserve to be examined in light of the changes in the structure of contemporary narratives. Full article

Endometriosis is common and poses significant morbidity of lasting impact to young, pre-menopausal women, while ovarian cancer is a lethal gynecologic condition. Both conditions need better treatment. The human omentum is an apron of adipose tissue in the abdominopelvic cavity, the same space in which endometriosis and ovarian cancer manifest. We aim to determine molecular cues emitted by the omentum that aid the trans-coelomic spread of endometriosis and ovarian cancer in the abdomen–pelvic/peritoneal space. Endometriosis and ovarian cancer patients were prospectively recruited. Primary cell cultures of surgically-resected omentum, endometriosis and ovarian cancer were generated, and conditioned media (CM) from the omentum was derived. They were used for in vitro assays to evaluate the effect of the omentum on cell migration, angiogenesis and proliferation in endometriosis and ovarian cancer. Omental CM promoted cell migration in primary cultures of endometriosis and ovarian cancer. Omental CM contained high levels of HGF, SDF-1a, MCP-1, VEGF-A, IL-6 and IL-8. The observed cell migration was blocked by c-MET inhibition, suggesting that HGF/c-MET signaling mediates cell migration in endometriosis and ovarian cancer. Furthermore, PTTG1 was consistently upregulated in the migrated cells in both endometriosis and ovarian cancer. The omentum provides a favorable environment for trans-coelomic spread of endometriosis and ovarian cancer. HGF, c-MET and PTTG1 are potential therapeutic targets for inhibiting the abdomen–pelvic/peritoneal spread of endometriosis and ovarian cancer. Full article

In this study, the novel composite materials of activated carbon (AC) and persulfate (PS) doped by nitrogen (N) and sulfur (S) were successfully synthesized through one-step mechanical ball milling. Different from the previous liquid-phase activation process of PS, the direct in situ solid-phase activation of PS was achieved through the newly generated chemical bonds between AC and PS. The increased crystal surface exposure and highly electronegative atoms provided more reactive sites for the modified composites, enabling them to extract electrons from the pollutant. Compared to S doping, the N-doped composite exhibited a higher oxidative degradation ability, with a removal rate of 93.6% for tetracycline (TC, 40 mg/L) within 40 min. The interactions between AC and PS that occur in the interior of the composite avoid the limitations of mass transfer between the solid–liquid interface, thus expanding the pH application range of the catalytic reaction and minimizing the interference of other components in the solution. The synergistic effect between active oxygen species and electron transfer is the main mechanism for promoting pollutant degradation. This research puts forward a new insight into the activation approach of PS and proposes a feasible method for the advanced treatment of TC wastewater. Full article

Al₂O₃ with SiC, silver, and graphene nanoplatelets (GNPs) powder mixture was produced by ball milling using ethanol as dispersion media. The GNP-reinforced Al₂O₃-SiC-Ag ceramic–metal composites were densified by spark plasma sintering technology (SPS). A homogeneous dispersion of GNPs in Al₂O₃-SiC-Ag was observed from the sintered samples, and the GNPs were embedded between the grains, which resulted in increasing the contact area. The trans-granular mechanism of crack propagation becomes increasingly dominant by adding GNPs. The hardness reaches 27 GPa, as tested by the Vickers microhardness method, which reflects an increase of 11% compared to Ag-GNPs-free Al₂O₃-SiC. On the other hand, by adding Ag-GNP content, the improvement in density is limited. Wear mechanisms, as determined through ball-on-flat testing, including adhesion, abrasion, and microcracks, are observed and discussed. The composite demonstrated remarkable self-lubricating properties, exhibiting a lower coefficient of friction (COF) and wear rate in an air environment compared to monolithic Al₂O₃-SiC. This improvement is attributed to the formation of a self-lubricating film, enabled by the uniform distribution of Ag and GNPs within the Al₂O₃-SiC matrix. The findings of this study propose a novel material design approach for developing self-lubricating ceramic composites with hybrid solid lubricants. Full article

In this study, the design of an adaptive neural network-based fixed-time control system for a novel coaxial trans-domain hybrid aerial–underwater vehicle (HAUV) is investigated. A radial basis function neural network (RBFNN) approximation strategy-based adaptive fixed-time terminal sliding mode control (AFTSMC) scheme is proposed to solve the problems of the dynamic nonlinearity, model parameter perturbation, and multiple external disturbances of coaxial HAUV trans-media motion. A complete six-degrees-of-freedom model for a continuous water–air cross-domain model is first established based on the hyperbolic tangent transition function, and, subsequently, based on a basic framework of FTSMC, a fixed-time and fast-convergence controller is designed to track the target position and attitude signals. To reduce the dependence of the control scheme on precise model parameters, an RBFNN approximator is integrated into the sliding mode controller for the online model identification of the aggregate uncertainties of the coaxial HAUV, such as nonlinear unmodeled dynamics and external disturbances. At the same time, an adaptive technique is used to approximate the upper bound of the robust switching term gain in the controller, which further offsets the estimation error of the RBFNN and effectively attenuates the chattering effect. Based on Lyapunov stability theory, it is proven that the tracking error can converge in a fixed time. The effectiveness and superiority of the proposed control strategy are verified by several sets of simulation results obtained under typical working conditions. Full article