This article reports the measurement of the neutron background flux accidentally induced by the neutrino beam at the J-PARC facility in Japan. In particular, neutrino-nucleus neutral-current quasi-elastic (NCQE) scattering events, ν(ν̄)+N→ν(ν̄)+N′, can be obscured by a massive background of neutron-nucleus scattering events. The neutrons are produced within the materials (such as sand and concrete) located between the beam dump and the experimental area where the detectors are placed. We measured the accidental neutron events at the J-PARC neutrino facility using BGO and liquid scintillation detectors, with a plastic scintillation detector serving as an active veto counter. Based on a neutrino-mode data set of 2.972×1020 POT, we observed 88 neutron-induced recoil proton events within an electron-equivalent recoil energy range of 0.98–11.60 MeVee, selected via pulse-shape discrimination in the liquid scintillation detector. Accounting for the detection efficiency and resolution, and through comparison with simulations, the neutron flux was determined to be[1.45−0.24+0.22(stat.)±0.55(sys.)]×10−7cm−2s−1POT−1, assuming an exponential neutron energy spectrum. This result will contribute to the evaluation of neutron backgrounds for neutrino experiments at the J-PARC facility.
Declining system inertia necessitates quantifying intrinsic frequency support mechanisms. While load voltage dependency influences dynamics, its specific impacts on transient inertial and damping support remain under-quantified. This paper establishes an analytical framework to quantify voltage-dependent load contributions to the initial Rate of Change of Frequency (RoCoF) and frequency nadir. By employing a Center of Inertia (CoI) framework to mathematically isolate load voltage dependence from network oscillations, closed-form expressions are derived for two physical mechanisms. First, the instantaneous power reduction from the subtransient voltage dip functions as an equivalent inertia, proportional to the system’s base mechanical inertia and scaling linearly with grid impedance and load sensitivity. Second, load voltage sensitivity provides an effective damping torque that increases the damping ratio, suppressing the frequency nadir. Furthermore, the study reveals a critical trade-off with Automatic Voltage Regulators (AVR), where aggressive voltage recovery compromises this natural damping support. Time-domain simulations validate that voltage-dependent loads provide a self-regulating defense mechanism, particularly effective in weak grids.
Under regularity conditions and fixed strictly ordered scores, exact likelihood-ratio additivity for every positive table within the f-divergence ordinal quasi-symmetry family characterizes the Pearsonian model class. A common multiplier gives a remainder-free deviance allocation, whose identity extends to sampling zeros using likelihood suprema. In contrast, score-tilt invariance and global Fisher orthogonality characterize ordinary ordinal quasi-symmetry. We explain the asymptotic covariance structure, quantify relative nonadditivity, and compare published square contingency tables. Exactness alone guarantees neither better fit nor finite-sample calibration.
Flight delays impose substantial costs on airlines, airports, and passengers. While existing studies predominantly focus on predicting average delays, extreme delays cause disproportionate operational disruptions and passenger dissatisfaction. This study introduces a distributional sensitivity analysis framework to identify factors that specifically drive extreme flight delays. Using 2.08 million U.S. domestic flights from 2024, we employ quantile regression models combined with Global Distributional Importance and Tangent-SHAP to decompose factor contributions across the entire delay distribution. Our analysis reveals three distinct effect patterns: tail effects, exhibited by weather conditions and carrier service history, which disproportionately amplify extreme delays; location effects, exhibited by realized delay variables such as departure delay and late aircraft delay, which shift the entire distribution approximately uniformly; and center effects, exhibited by flight duration and distance, which primarily affect typical delays. The classification is supported by an extensive robustness suite covering estimator noise, quadrature design, train-test partitioning, and correlation-preserving perturbations. We identify 60 min of departure delay as a critical threshold (bootstrap 95% confidence interval 55-65 min), beyond which 67 percent of flights experience severe arrival delays exceeding 60 min. Summer months exhibit 2.04 times higher tail risk than fall. The estimated annual cost of delays exceeding 60 min is approximately 1.9 billion USD, with potential savings of approximately 1.0 billion USD through targeted interventions. These findings provide actionable insights for airlines and airports to prioritize interventions targeting extreme delay prevention rather than average delay reduction.
In a smoothly bounded domain Ω⊂ℝ^N (N∈ℕ), a no-flux initial-boundary value problem for the degenerate chemotaxis system with volume-filling effects, u_t = ∇· (D(u,v) ∇ u - h(u,v) ∇ v), v_t = Δv + g(u,v), x∈ Ω, t>0, is considered under the assumptions that D(1,s)=0 and that h(0,s)=h(1,s)=0. Here, initial data u_0 and v_0 have suitable regularity and satisfy 0≤ u_0≤ 1 and v_0≥ 0 with ∇ v_0 · ν|_∂ Ω = 0. It is proved that there exists a global weak solution such that 0≤ u≤ 1 and v≥ 0. Moreover, when D(r,s) = D(r) for all r∈[0,1] and s∈[0,∞) and additional conditions on D, h and g are assumed, uniqueness of global weak solutions with the mass conservation law ∫_Ωu(x,t) dx = ∫_Ωu_0(x) dx is shown. Also, a flat-hump-shaped stationary solution is constructed in the one-dimensional setting
