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Event and fault tree-based Bayesian network for probabilistic safety assessment of earthquake-induced fire and explosion hazard
No full textIn nuclear power plant engineering, probabilistic safety assessment (PSA) has been actively studied to evaluate risk due to earthquake events. Recently, the similar PSA framework has been proposed to calculate probability of shut-down of gas plants when earthquake occurred. However, in process plants, earthquakes can also trigger secondary hazards such as fires and explosions, which have been less addressed in seismic PSA despite their potentially catastrophic consequences. These cascading events would cause severe casualties, asset losses, and long-term health impacts by a leak of hazardous substances. To consider such multi-hazard impacts, i.e., earthquake-induced fires or explosions, this work proposes a Bayesian network (BN)-based framework, which is modelled by transforming from fault- and event-tree. For seismic risk, fault tree is constructed to represent the joint operation of constituting equipment, while the top event is defined as a shut-down by earthquake events. Then, the event tree is derived to represent an evolving process from release to final events (i.e., several types of fires and explosions). These constructed trees are transformed into BN, and this process can prevent causal errors when BN is modelled directly. By extending seismic PSA concepts with the traditional fire/explosion event-tree methodology in a unified BN framework, the intended contribution is to enable integrated multi-hazard risk assessment that can account for both seismic and post-seismic accident scenarios. The proposed framework is demonstrated by constructing BN model for earthquake-induced fire and explosion at a gas plant. Then, the inference of the BN model is presented. First, the risk of the multi-hazard on the system is quantified for different hazard levels of earthquake. Second, the contribution of each component to the system failure is evaluated with a retrofit strategy on crucial facilities. By analyzing various accident scenarios, it is showed that the proposed BN model can provide risk-informed decision-making for prioritizing repair and/or retrofitting of structures or equipment in the plant
Pursuing Coxeter theory for Kac-Moody affine Hecke algebras
Get PDFThe Kac-Moody affine Hecke algebra H was first constructed as the Iwahori-Hecke algebra of a p-adic Kac-Moody group by work of Braverman, Kazhdan, and Patnaik, and by work of Bardy-Panse, Gaussent, and Rousseau. Since H has a Bernstein presentation, for affine types it is a positive-level variation of Cherednik’s double affine Hecke algebra. Moreover, as H is realized as a convolution algebra, it has an additional “T-basis” corresponding to indicator functions of double cosets. For classical affine Hecke algebras, this T-basis reflects the Coxeter group structure of the affine Weyl group. In the Kac-Moody affine context, the indexing set WT for the T-basis is no longer a Coxeter group. Nonetheless, WT carries some Coxeter-like structures: a Bruhat order, a length function, and a notion of inversion sets. This paper contains the f irst steps toward a Coxeter theory for Kac-Moody affine Hecke algebras. We prove three results. The first is a construction of the length function via a representation of H. The second concerns the support of products in classical affine Hecke algebras. The third is a characterization of length deficits in the Kac-Moody affine setting via inversion sets. Using this characterization, we phrase our support theorem as a precise conjecture for Kac-Moody affine Hecke algebras. Lastly, we give a conjectural definition of a Kac-Moody affine Demazure product via the q = 0 specialization of H
Phenomenology and research in accounting (and related practices): a critical appreciation
No full textIn this chapter, we consider the philosophical and methodological character of phenomenology, delineating various types of phenomenology. We reflect on what it means to do a phenomenological study in accounting (and organization studies more generally), what is the potential of such study, and what has manifested in actual research. We seek to articulate ways forward in terms of the advancing of critical phenomenology for the analysis of accounting (and related practices)
Label-Free Glucose Sensing Using a High-Q Terahertz Metamaterial Absorber
No full textThis work presents a highly sensitive terahertz (THz) metamaterial absorber tailored for glucose detection in aqueous environments. The absorber features a multi-resonant structure with four distinct absorption peaks at 2.02, 4.41, 5.06, and 5.39 THz, achieving absorption efficiencies of 99.8%, 99.2%, 96.4%, and 95.2%, respectively. Among these, the 5.06 THz resonance exhibits the highest quality factor of 265, making it ideal for high-resolution sensing applications. To evaluate its biosensing performance, a 1 micrometer thick analyte layer was modeled with refractive index values ranging from 1.33 (pure water) to 1.45 (30% glucose solution). The resulting resonance shift yielded a sensitivity of 262.5 GHz/RIU and a figure of merit (FOM) of 7.17, demonstrating the absorber’s capability to detect subtle changes in glucose concentration. These results highlight the potential of the proposed design for non-invasive glucose monitoring and other biomedical sensing applications in the THz regime
Energy-Efficient Ultra-Reliable Low-Latency 6G Communication via Cooperative UAV–RIS-Assisted OTFS Networks and Hybrid PSO–DRL Optimisation
No full textUltra-reliable low-latency communication (URLLC) is a critical 6 G service, yet achieving <10 ms latency, ≥99.9% reliability, and energy efficiency remains challenging in dense, dynamic environments. This work proposes a UAV-RIS cooperative architecture combining mmWave UAV relays and reconfigurable intelligent surfaces to meet URLLC demands. The joint optimization of UAV trajectory, RIS phase shifts, and resource allocation is formulated as a mixed-integer nonlinear program and solved using a hybrid particle swarm optimization-deep reinforcement learning (PSO-DRL) approach, achieving sub-0.5s decision updates. Hardware-in-the-loop urban testbed experiments and Monte Carlo simulations show up to 35 % energy savings, 42 % latency reduction, and 99.9−99.95% reliability at high user densities (1,000UE/km2), outperforming ground-based baselines. These results validate the practicality and scalability of UAVRIS integration for real-time, energy-efficient 6G URLLC
Smoothed pseudo-population bootstrap methods with applications to finite population quantiles
No full textThis article introduces smoothed pseudo-population bootstrap methods for the purposes of mean-squared error estimation and for constructing confidence intervals for finite population quantiles. In an independent and identically distributed context, it has been shown that resampling from a smoothed estimate of the distribution function instead of the usual empirical distribution function can improve the convergence rate of the bootstrap mean-squared error estimator of a sample quantile. We extend the smoothed bootstrap to the survey sampling framework by implementing it in pseudo-population bootstrap methods for high entropy, single-stage survey designs, such as simple random sampling without replacement, Poisson sampling, and randomized systematic proportional-to-size sampling. Given a kernel function and a bandwidth, it consists of smoothing the pseudo-population from which bootstrap samples are drawn using the original sampling design. Given that the implementation of the proposed algorithms requires the specification of the bandwidth, we develop a plug-in selection method along with a grid search selection method based on a bootstrap estimate of the mean squared error. Simulation results suggest that the smoothed approach offers improved efficiency compared to the standard pseudo-population bootstrap for estimating the uncertainty of a quantile estimator, together with mixed results regarding confidence interval coverage
Regional anaesthetic block for lung resection surgery: the magic bullet we already use?
No full textLung resection surgery carries a high risk of postoperative and particularly pulmonary complications partly because of an exaggerated surgical stress response and associated inflammatory dysregulation. Intraoperative lidocaine administered i.v. or via paravertebral catheters reduces the incidence and severity of postoperative complications after minimally invasive lung resection surgery when compared with intraoperative remifentanil infusion. Lidocaine administration was also associated with a reduction in inflammatory biomarkers compared with remifentanil. Uncertainties remain regarding the relative clinical benefits of lidocaine vs other local anaesthetics, the impact of timing and mode of local anaesthetic administration, and the potential harms associated with remifentanil infusion in the absence of regional anaesthesia
Live-cell 3D-SIM of Rift Valley fever virus NSs filaments reveals a polygon web architecture
Get PDFA defining feature of Rift Valley fever virus (RVFV) is the incorporation of the NSs protein into large filamentous assemblies inside infected nuclei [R. Swanepoel, N. K. Blackburn, J. Gen. Virol. 34, 557–561 (1977).], as judged from fixed specimens. To gain insight into the 3D structure of NSs filaments within live-cell nuclei, we used genetic-code expansion (GCE) to incorporate trans-cyclooct-2 -en-L-lysine into the protein. This enabled site-specific fluorescent labeling with tetrazine dyes for live-cell structured illumination microscopy (SIM). Our superresolved images revealed the complete native architecture of NSs filaments as a micron-scale polygon web of fibers with discrete domain characteristics, overturning previous assumptions of simple linear filaments. Parallel experiments on fixed RVFV-infected cells confirmed that native NSs filaments also display this morphology. Overall, our 3D-SIM analysis reveals distinct structural plasticity within NSs filaments, establishing a quantitative structure–function relationship that support the importance of polygon organization for NSs filament function during RVFV infection
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