We study the Temporal Exploration problem, where an agent must visit all vertices of a temporal graph while traversing at most one available edge per time step. Unlike static graphs, which can be explored in linear time, temporal constraints can substantially increase exploration time even when every snapshot of the graph is connected. To better understand the source of this complexity, we focus on a near-static setting and consider always-connected k-edge-deficient temporal graphs, in which each snapshot is connected and differs from a fixed underlying n-vertex graph by at most kedges. Although such graphs are structurally close to static graphs, they can still exhibit non-trivial temporal behavior. Prior work showed that these graphs can be explored in O(nk log n) time steps and established a lower bound of ohm(n log k), leaving open whether linear-time exploration in n is possible. We resolve this question by showing that any always-connected k-edge-deficient temporal graph admits an exploration schedule of length O(nk log k). Moreover, given such a temporal graph, the corresponding exploration schedule can be computed by a Las Vegas algorithm in expected polynomial time and, when k is constant, deterministically in polynomial time. The obtained bound is linear in the number of vertices up to a factor depending only on k, removes the extraneous logarithmic dependence on n, and is nearly optimal. In particular, for constant k, our result yields an order-optimal Theta(n) exploration time, showing that temporal exploration in this near-static regime essentially retains the linear-time character of static graph traversal. (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/).
Ammonia (NH3) is a promising green hydrogen carrier, and its synthesis under mild, distributed conditions has attracted increasing attention. Non-thermal plasma provides a potential route for ammonia synthesis by enabling nitrogen activation through electron-driven processes. This study investigates catalyst-free NH3 synthesis in a flowing water-electrode dielectric barrier discharge (DBD) reactor driven by alternating current (AC), unipolar pulse, and bipolar pulse. Electrical diagnostics and optical emission spectroscopy were used to examine how excitation mode affects discharge behavior, energy utilization, and nitrogen activation. Nanosecond pulsed excitation improved NH3 synthesis performance compared with AC excitation under the tested conditions. Unipolar pulsing was more favorable in the low specific energy input (SEI) regime, whereas bipolar pulsing maintained better performance at higher SEI, which was associated with discharge regulation induced by periodic field reversal. Optical emission analysis indicated that bipolar excitation showed a slightly higher mean effective reduced electric field, together with stronger N2+-related emission. These results suggest enhanced electron-impact excitation and ionization characteristics and highlight the role of excitation waveform in regulating discharge behavior and energy utilization in catalyst-free plasma-assisted ammonia synthesis.
Physics-Informed Neural Networks (PINNs) have emerged as a promising alternative for solving systems governed by partial differential equations (PDEs), such as the neutron diffusion equation. Here, conventional PINNs assume fixed PDE parameters, however, in reality, the material parameters inside a nuclear reactor core vary continuously. The variation renders the conventional fixed parameters PINNs unsuitable as the models must be retrained. To address this challenge, a parametric PINNs model is built so inferences can be made on various material properties without the need for retraining. This article aims to demonstrates the capabilities of PINNs in resolving the neutron diffusion equation with fixed parameters in both one-dimensional and two-dimensional geometries and compared to the reference finite difference solver. Then, the functionality of PINNs is extended by training the network across a range of material parameters pertaining to real physical changes in reactor conditions generated through OpenMC. The model is then verified against a reference solver on one-hundred random material properties within the OpenMC generated range, showing good agreement with the reference solution but with a vastly accelerated calculation routine.
Selective catalytic reduction technology using NH3 as a reducing agent is an effective method for abating the main air pollutants NOx from coal-fired industries, mobile exhausts, etc. However, suppressing the overoxidation of NH3 is a significant challenge. The over-oxidation of NH3 will generate NOx and N2O secondary pollutants, reducing the reduction efficiency. Achieving an optimal equilibrium between redox property and surface acidity is essential for the efficiency of NH3-SCR catalyst. Here, a Ru and H3PW12O40 (HPW) comodification method was employed to prepare the Ru-HPW/CeO2 catalyst by adjusting the redox property and acidity, achieving a significant leap in catalytic performance. Among the prepared catalysts, Ru-20HPW/ CeO2 demonstrated the most outstanding NOx removal efficiency, reaching over 80% NOx conversion at 200-350 degrees C. The characterization data indicate that the enhanced performance of Ru-20HPW/CeO2 is attributed to the equilibrium between its acidic properties and redox property. This originates from the presence of a large number of Br & Oslash;nsted acid sites that facilitate the adsorption of NH3, as well as an increased number of oxygen vacancies. This work provides a new strategy for constructing highly efficient and low-cost heterogeneous catalysts applied to environmental catalytic reactions.
The former CERN RD50 collaboration develops monolithic active pixel high voltage (HV) CMOS sensors for future colliders with the aim of high radiation tolerance, good time resolution, and high granularity pixel detectors. The most recent prototype, the RD50-MPW4, was produced by LFoundry in December 2023 using a 150 nm CMOS process. It features a matrix of 64x64 pixels with a 62 mu m pitch and employs a column-drain readout architecture. Compared to its predecessor, it now has separate analog and digital power domains and a new biasing scheme with a guard ring structure that supports bias voltages over 600 V. This contribution will discuss the design and latest results of the MPW4, where tests with unirradiated samples showed more than 99.9% efficiency, 16 mu m spatial resolution and 10 ns timing resolution. Efficiencies of over 99% were achieved for samples irradiated to fluences of 1 & times;1015 1 MeV neq/cm2. A 3D map of the charge collection efficiency from a measurement with two-photon absorption laser is presented that nicely outlines the depletion depth of this radiation hard, high granularity monolithic active pixel sensor.
