Abstract In the IoT era, wearable photodetectors play a crucial role in remote healthcare and environmental monitoring. Semiconductors are the most important component of these devices. Among them, ZnO is a potential candidate due to its high charge carrier mobility, mechanical stability, low cost, and non-toxicity. However, ZnO has a limited working range within the UV region. Here, the study introduces the development of an Ag/ZnO hybrid structure using an eco-friendly hydrothermal method for growing ZnO nanorods and producing Ag nanoparticles via green glucose reduction directly on a flexible substrate. When exposed to visible light (464 nm), the developed Ag/ZnO device...

Abstract Counterfactual explanations (CE) can make face classifiers more transparent, yet existing methods implicitly target a single attribute at a time, yield unnatural imagery, overly broad or off-target edits, and weak interpretability. We introduce a unified framework that (i) constrains edits with FacePart-based segmentation masks, (ii) performs localized blended latent diffusion on Stable Diffusion 2.1, (iii) re-ranks candidates via a semantic filter that combines CLIP with a trained classifier, and (iv) applies a controlled PGD adversarial step to expose decisive regions – jointly leveraging prompts, spatial masks, and classification gradients to steer generation while preserving identity. On CelebA-HQ with 40...

Abstract Hydrated vanadium pentoxide, V2O5·1.75H2O has emerged as a promising cathode material for multivalent ion batteries due to its tunable layered structure and enhanced ion transport properties. In this study, density functional theory (DFT) simulations are applied to investigate bilayer V2O5·nH2O material, focusing on how water content (n = 0, 1, 1.75, 2 and 2.25) influences its structural stability, electronic properties and ion intercalation behavior. Structural water forms hydrogen-bonded networks and pentameric clusters that expand the interlayer spacing, preserve [VO5] coordination, and create efficient diffusion pathways for Zn2+ and Mg2+ ions. Electronic structure analysis reveals that water intercalation narrows the band gap and...

Abstract Syntactic features such as dependency and constituency are well known to improve Semantic Role Labeling (SRL), yet existing syntax-aware SRL models remain largely opaque. Related explainable NLP methods focus primarily on token-level representations and do not quantify how such relations contribute to individual SRL predictions. This limitation is particularly concerning in high-stakes domains such as biomedicine, where interpretability is essential for building trust in NLP-assisted analysis. In this work, we propose a post-hoc explanation framework that targets pairwise syntactic relations and provides a quantitative characterization of their influence on SRL predictions, measuring both the magnitude and polarity of their...