Taiz University

Reducing catalyst material usage while maintaining high performance is critical for scalable green hydrogen production via electrolysis. In this work, low-loading alkaline hydrogen-evolution reaction (HER) cathodes are fabricated by direct current magnetron sputtering of Ni and Ni₄Mo, providing a one-step, solvent-free route to catalyst-coated substrates. By tuning sputter power and Ar pressure, the deposited layers are steered toward rough nanostructures with increased accessible surface area, which correlates with improved HER activity compared with denser reference films, as shown by three-electrode measurements. The sputtered Ni-Mo has the targeted Ni₄Mo composition and exhibits a nanocrystalline Ni-fcc-type structure rather than the equilibrium intermetallic phase. Process transfer from planar substrates to porous carbon paper yields catalyst loadings of 0.046-0.186 mg cm⁻² (Ni) and 0.053-0.318 mg cm⁻² (Ni4Mo). Three-electrode electrochemical benchmarking showed decreasing HER overpotential with increasing loading, reaching ~104 mV at 10 mA cm⁻² for a NiMo cathode with 0.21 mg/cm². Implemented in a PGM-free AEM electrolyzer, along with an uncatalyzed stainless steel anode, Ni4Mo outperforms Ni at high current densities, delivering 1.95 V at 1 A cm⁻² and 60 °C (1.88 V at 80 °C) and enabling a mass activity of ~4.7 A mg⁻¹ at 1.95 V. A 500 h steady-state durability experiment at 1 A cm⁻² demonstrates stable performance with a reduced degradation rate toward the end of the test.

Using relativized ordinal analysis, we give a proof-theoretic characterization of the provably total set-recursive-from-w functions of KPl and related theories. (c) 2026 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

This study investigates the role of the BNNC tip in determining hydrogen storage performance and presents novel insights into how tip geometry influences adsorption and spectroscopic signatures. A total of 96 BNNC configurations were evaluated using density functional theory at the wb97xd level with counterpoise corrections, Gibbs free energy, and Zero-point energy to obtain corrected hydrogen adsorption energetics. Notably, we demonstrate for the first time that IR spectra can distinguish between edge motifs, revealing how tip structure governs edge chemistry. In parallel, Raman spectra provide direct access to both hydrogenation sites and disclination angles, enabling simultaneous characterization of adsorption behavior and tip-induced topologies. The observed hydrogen adsorption preferences, together with the complementary IR and Raman fingerprints, underscore the potential of BNNCs as tunable hydrogen storage media for future energy applications.

Introduction: Injury to the inferior alveolar nerve is a potential complication during the removal of mandibular third molars, with a substantially increased risk when a direct anatomical relationship exists between the tooth roots and the mandibular canal. In such cases, coronectomy offers a surgical alternative that reduces the risk of nerve injury; however, the clinical relevance of postoperative root migration remains incompletely understood. Objective: This study analyzed the timing and extent of root migration after coronectomy, examined influencing factors, assessed radiological indications, and compared findings with existing literature. Method: This retrospective analysis was based on data from 73 coronectomies performed in 57 patients. During the study, panoramic X-ray images were examined with particular attention to radiological signs indicating an increased risk of inferior alveolar nerve injury, as well as combinations of these signs. The extent of root migration was determined using digital panoramic radiographs at follow-up examinations conducted at 1, 3, 6, 12, and 24 months. Additionally, the effects of age, anatomical factors related to impaction, tooth angulation, and the operator's level of professional experience were evaluated. Results: Root migration was detected in 90.4% of cases. Mean migration was 1.5 mm at 1 month, 2.4 mm at 3 months, 2.8 mm at 6 months, 3.2 mm at 12 months, and 3.5 mm at 24 months. The most pronounced migration occurred during the first 6 months postoperatively. A significant negative correlation was observed between patient age and the extent of migration. Horizontal, i.e., ramus space availability influenced migration, whereas tooth angulation and operator experience showed no significant effect. Conclusion: Coronectomy is an effective surgical option for patients at high risk of inferior alveolar nerve injury; nevertheless, the probability of subsequent intervention should be considered. With appropriate indication and follow-up, favorable long-term outcomes can be achieved. Orv Hetil. 2026; 167(12): 476-484.

In this paper, we introduce PASTA (Perceptual Assessment System for explanaTion of Artificial intelligence), a novel framework for a human-centric evaluation of XAI techniques in computer vision. Our first key contribution is a human evaluation of XAI explanations on four diverse datasets—COCO, Pascal Parts, Cats Dogs Cars, and MonumAI—which constitutes the first large-scale benchmark dataset for XAI, with annotations at both the image and concept levels. This dataset allows for robust evaluation and comparison across various XAI methods. Our second major contribution is a data-based metric for assessing the interpretability of explanations. It mimics human preferences, based on a database of human evaluations of explanations in the PASTA-dataset. With its dataset and metric, the PASTA framework provides consistent and reliable comparisons between XAI techniques, in a way that is scalable but still aligned with human evaluations. Additionally, our benchmark allows for comparisons between explanations across different modalities, an aspect previously unaddressed. Our findings indicate that humans tend to prefer saliency maps over other explanation types. Moreover, we provide evidence that human assessments show a low correlation with existing XAI metrics that are numerically simulated by probing the model.