Abstract Large language models (LLMs) are evolving into engines for scientific discovery, yet the assumption that biological understanding requires domain-specific pre-training remains unchallenged. Here, we report that general-purpose LLMs possess an emergent capability for biological structural discovery. First, we demonstrate that a small-scale GPT-2, fine-tuned solely on English paraphrasing, achieves ~84% zero-shot accuracy in protein homology detection, where network-based interpretability confirms a deep structural isomorphism between human language and the language of life. Scaling to massive models (e.g., Qwen-3) reveals a phase transition, achieving near-perfect accuracy (~100%) on standard tasks while maintaining 75% precision on specially constructed remote homology datasets. Chain-of-Thought interpretability reveals that these models transcend simple sequence alignment, leveraging implicit structural knowledge to perform reasoning akin to "mental folding." We formalize this cross-modal universality through the BioPAWS benchmark. Our work establishes a minimalist paradigm for AI for Science, proving that abstract logical structures distilled from human language constitute a powerful cognitive prior for decoding the complex syntax of biology.
Modern LLM agents increasingly rely on dynamic structured generation, such as tool calling and response protocols. Unlike traditional structured generation with static structures, these workloads vary both across requests and within a request, posing new challenges to existing engines. We present XGrammar-2, a structured generation engine for dynamic agentic workloads. Our design is based on two key ideas: first-class support for tag-triggered structure switching, and fine-grained reuse across requests with different output structures. Concretely, XGrammar-2 introduces TagDispatch for dynamic structural dispatching and Cross-Grammar Cache for substructure-level cache reuse across grammars. It further improves efficiency with an Earley-based adaptive token mask cache, just-in-time compilation, and repetition state compression. Experiments show that XGrammar-2 achieves over 6x faster compilation than prior structured generation engines, and incurs near-zero end-to-end overhead in modern LLM serving systems.
In quantum field theory, the algebraic existence of a field does not guarantee the existence of a corresponding localized asymptotic particle state. This distinction is well established in the presence of infrared effects, long-range correlations, and environmental interactions, and becomes particularly relevant in supersymmetric theories, where fermionic and bosonic degrees of freedom are constrained at the algebraic level but need not share identical asymptotic behavior. In this work we introduce a minimal and predynamical localization criterion that distinguishes algebraically allowed degrees of freedom from those capable of forming stable, phasecoherent asymptotic states. The criterion is formulated in terms of long-time stability under slow structural fluctuations of an effective background, without modifying the underlying field equations or introducing new physical interactions. We show that fermionic and scalar fields respond qualitatively differently to such structural effects. While fermionic modes may retain asymptotic stability, scalar modes generically exhibit decoherence and damping, preventing their interpretation as localized one-particle states. This provides a conservative and model-independent perspective on how supersymmetric algebraic structures may coexist with an asymmetric observable particle spectrum. The analysis is intentionally non-constructive and does not rely on specific supersymmetrybreaking mechanisms, cosmological assumptions, or new dynamical ingredients. Rather, it clarifies localization as an independent structural requirement for particle existence within standard quantum field theory.
Dectot--Le Monnier de Gouville Esteban, Mohammad Hamdaqa, Moataz Chouchen
YARA has established itself as the de facto standard for "Detection as Code," enabling analysts and DevSecOps practitioners to define signatures for malware identification across the software supply chain. Despite its pervasive use, the open-source YARA ecosystem remains characterized by ad-hoc sharing and opaque quality. Practitioners currently rely on public repositories without empirical evidence regarding the ecosystem's structural characteristics, maintenance and diffusion dynamics, or operational reliability. We conducted a large-scale mixed-method study of 8.4 million rules mined from 1,853 GitHub repositories. Our pipeline integrates repository mining to map supply chain dynamics, static analysis to assess syntactic quality, and dynamic benchmarking against 4,026 malware and 2,000 goodware samples to measure operational effectiveness. We reveal a highly centralized structure where 10 authors drive 80% of rule adoption. The ecosystem functions as a "static supply chain": repositories show a median inactivity of 782 days and a median technical lag of 4.2 years. While static quality scores appear high (mean = 99.4/100), operational benchmarking uncovers significant noise (false positives) and low recall. Furthermore, coverage is heavily biased toward legacy threats (Ransomware), leaving modern initial access vectors (Loaders, Stealers) severely underrepresented. These findings expose a systemic "double penalty": defenders incur high performance overhead for decayed intelligence. We argue that public repositories function as raw data dumps rather than curated feeds, necessitating a paradigm shift from ad-hoc collection to rigorous rule engineering. We release our dataset and pipeline to support future data-driven curation tools.
Temporary support technology is used to support and stabilize the bridge structure, bear the bridge construction load, and ensure the stability and safety of the structure in the construction process. Different demolition sequences have a huge impact on the performance of the structure. In order to study the effect of the temporary support removal sequence on the mechanical performance of a composite beam bridge with corrugated steel webs (CSWs) in the construction stage, this article combined with a case study of a composite beam bridge with CSWs in Gansu Province, adopted finite element software to establish a spatial finite element model reflecting the whole construction process of a curved beam bridge with corrugated webs and selected three working conditions for comparative study. The effects of different removal sequences on the variation of vertical deflection, normal stress and shear stress of the section are analyzed. The results show that the section deformation is dominated by vertical flexural deformation, and the removal sequence of temporary supports has a great influence on the formation of the structural stiffness, in which the structural stiffness increase is the largest under operating Condition 3. When the temporary support is removed after the concrete strength of the bridge panel is formed, the vertical deflection of the beam body is the smallest. In addition, the beam section of the center span appears upward deflection. The normal stress value and stress gradient of the center span midspan section are the largest, while the stress gradient of the other sections is the smallest and the stress value is greatly reduced. The shear distribution ratio of each web plate under different operating conditions is basically the same, and the removal sequence of temporary supports has little influence on it. The study underscores the importance of construction sequence optimization for improving efficiency and sustainability in bridge engineering, contributing to the broader adoption of innovative materials and methods in sustainable infrastructure development.
Objective Most construction projects in offshore areas are affected by seawater corrosion and dynamic loads. Many of these projects have caused a series of accidents due to the corrosion of cement soil, such as the swelling and collapse of road bases and the cracking and destruction of foundations. From the perspective of dynamic load, cement soil is subjected to various stresses, including earthquakes, typhoons, vehicle-induced crushing, wave impacts, and other loads during construction and use, which inevitably aggravate the deterioration of the cement soil foundation.Methods In order to improve the mechanical properties of cement soil foundations in offshore areas, a coastal engineering clay from Guangzhou is selected to prepare nano–SiO<sub>2</sub>-improved cement soil specimens. The GDS true (dynamic) triaxial instrument is employed to conduct cyclic loading tests on the improved cement soil. The specimens are saturated in a vacuum using a saturator, placed in a seawater solution for corrosion after saturation, and then subjected to counterpressure saturation using the GDS true (dynamic) triaxial instrument. The peripheral pressure is set at 200 kPa, with a loading frequency of 1 Hz (sine wave), an initial axial force of 2 200 N, and a dynamic stress amplitude (<italic>σ</italic><sub>d</sub>) of 100, 200, 300, 400, 500, 600, 700, 800, 900, and 1 000 kPa. The specimens are loaded in ten stages and vibrated 10 times in each stage to investigate the effect of nano–SiO<sub>2</sub> on the mechanical properties of cement soil under corrosion conditions. To study the dynamic elastic modulus and damping characteristics of the improved cement soil under varying corrosion durations and concentrations, the changes in the dynamic elastic modulus of cement soil before and after improvement are compared. A dynamic elastic modulus ratio decay model is established, and the influence of changes in the damping ratio is analyzed.Results and Discussions The results showed that under the combined effects of cyclic loading and seawater corrosion, the dynamic elastic modulus of cement soil before and after nano–SiO<sub>2</sub> improvement decreased with increasing seawater concentration. When the dynamic strain (<italic>ε</italic><sub>d</sub>) was less than 0.3%, the rate of decrease of the dynamic elastic modulus was faster, whereas the decrease rate slowed when <italic>ε</italic><sub>d</sub> exceeded 0.3%. Under similar corrosive conditions, the dynamic elastic modulus of cement soil increased gradually with the rise in the corrosion time, but the growth rate decreased over time. The dynamic elastic modulus of nano–SiO<sub>2</sub>-improved cement soil was consistently greater than that of ordinary cement soil in all corrosion cycles. A good linear relationship was observed between the inverse of the dynamic elastic modulus and the dynamic strain of the cement soil when the Konder model was used. The maximum dynamic elastic modulus (<italic>E</italic><sub>d0</sub>) of nano–SiO<sub>2</sub>-modified cement soil was significantly higher than that of ordinary cement soil. The Darendeli model was utilized to analyze the dynamic elastic modulus of cement soil, and the decay model of the dynamic modulus ratio of cement soil before and after nano–SiO<sub>2</sub> improvement was obtained. This model better describes the variation in the dynamic elastic modulus of cement soil with dynamic strain under a corrosive environment. The hysteresis loop area (<italic>S</italic>) increases continuously with the increase in dynamic strain. The <italic>S</italic>–<italic>ε</italic><sub>d</sub> curve gradually moves downward with time and rises with the increase in sea salt concentration. Under the corrosion of seawater solutions with different concentrations, the damping ratio (<italic>λ</italic>) of cement soil before and after nano–SiO<sub>2</sub> modification increases with dynamic strain and gradually levels off, while the <italic>λ</italic>–<italic>ε</italic><sub>d</sub> curve shifts upward as the corrosion concentration increases. The overall trends of the <italic>S</italic>–<italic>ε</italic><sub>d</sub> and <italic>λ</italic>–<italic>ε</italic><sub>d</sub> curves for nano–SiO<sub>2</sub>-modified cement soil are slower than those for ordinary cement soil. For the same corrosion time, the hysteresis loop area (<italic>S</italic>) and damping ratio (<italic>λ</italic>) of nano–SiO<sub>2</sub>-modified cement soil are smaller than those of ordinary cement soil and increase with the increase in the concentration. After mixing an appropriate amount of nano–SiO<sub>2</sub> into the soil, nano–SiO<sub>2</sub> reacts with cement to generate cementitious substances that fill and refine some of the soil’s pores. This enhances the structural stability of the soil, increases the force between particles, improves load transfer efficiency, reduces energy loss during loading, and lowers energy consumption. A large quantity of cementitious substances is rapidly produced on the surface of soil particles. These substances, which appear as rods, bars, and spheres, increase with the concentration. Compared to ordinary hydraulic soil, the surface of soil particles rapidly produces a large number of gel-like substances in the form of rods, bars, and spheres that stack together to fill pores and particle gaps. This forms a dense spatial network, effectively enhancing the strength and structural stability of cement soil, reducing seawater erosion, improving corrosion resistance, and increasing resistance to the coupling effects of dynamic loading and seawater corrosion. Most current research on nano–SiO<sub>2</sub> cement soil focuses on its engineering properties under static load in ordinary environments, while studies on its dynamic properties in seawater corrosive environments remain limited.Conclusions This experiment investigates the effects of different seawater concentrations and corrosion durations on the kinetic properties of nano–SiO<sub>2</sub>-modified cement soil under the coupling of dynamic loading and seawater corrosion. It reveals the deterioration patterns of the mechanical properties of cement soil under these conditions and examines the improvement mechanism of nano–SiO<sub>2</sub>, providing a reference for future studies on cement soil base structures in coastal areas.
Tissue engineering (TE) aims to provide personalized solutions for tissue loss caused by trauma, tumors, or congenital defects. While traditional methods like autologous and homologous tissue transplants face challenges such as donor shortages and risk of donor site morbidity, TE provides a viable alternative using scaffolds, cells, and biologically active molecules. Textiles represent a promising scaffold option for both in-vitro and in-situ TE applications.Textile engineering is a broad field and can be divided into fiber-based textiles and yarn-based textiles. In fiber-based textiles the textile fabric is produced in the same step as the fibers (e.g. non-wovens, electrospun mats and 3D-printed). For yarn-based textiles, yarns are produced from fibers or filaments first and then, a textile fabric is produced (e.g. woven, weft-knitted, warp-knitted and braided fabrics).The selection of textile scaffold technology depends on the target tissue, mechanical requirements, and fabrication methods, with each approach offering distinct advantages. Braided scaffolds, with their high tensile strength, are ideal for load-bearing tissues like tendons and ligaments, while their ability to form stable hollow lumens makes them suitable for vascular applications. Weaving, weft-, and warp-knitting provide tunable structural properties, with warp-knitting offering the greatest design flexibility. Spacer fabrics enable complex 3D architecture, benefiting applications such as skin grafts and multilayered tissues. Electrospinning, though highly effective in mimicking the ECM, is structurally limited. The complex interactions between materials, fiber properties, and textile technologies allows for scaffolds with a wide range of morphological and mechanical characteristics (e.g., tensile strength of woven textiles ranging from 0.64 to 180.4 N/mm2). With in-depth knowledge, textiles can be tailored to obtain specific mechanical properties as accurately as possible and aid the formation of functional tissue. However, as textile structures inherently differ from biological tissues, careful optimization is required to enhance cell behavior, mechanical performance, and clinical applicability.This review is intended for TE experts interested in using textiles as scaffolds and provides a detailed analysis of the available options, their characteristics and known applications. For this, first the major fiber formation methods are introduced, then subsequent used automated textile technologies are presented, highlighting their strengths and limitations. Finally, we analyze how these textile and fiber structures are utilized in TE, organized by the use of textiles in TE across major organ systems, including the nervous, skin, cardiovascular, respiratory, urinary, digestive, and musculoskeletal systems.
Drains play an important role in seepage control in geotechnical engineering. The enormous number and one-dimensional (1D) geometry of drainage holes make their nature difficult to be accurately modeled in groundwater flow simulation. It has been well understood that drains function by presenting discharge boundaries, which can be characterized by water head, no-flux, unilateral or mixed water head-unilateral boundary condition. It has been found after years of practices that the flow simulation may become erroneous if the transitions among the drain boundary conditions are not properly considered. For this, a rigorous algorithm is proposed in this study to detect the onset of transitions among the water head, no-flux and mixed water head-unilateral boundary conditions for downwards-drilled drainage holes, which theoretically completes the description of drain boundary conditions. After verification against a numerical example, the proposed algorithm is applied to numerical modeling of groundwater flow through a gravity dam foundation. The simulation shows that for hundreds of downwards-drilled drainage holes used to be prescribed with water head boundary condition, 56% and 2% of them are transitioned to mixed water head-unilateral and no-flux boundary conditions, respectively. The phreatic surface around the drains will be overestimated by 25–33 m without the use of the mixed boundary condition. For the first time, this study underscores the importance of the mixed water head-unilateral boundary condition and the proposed transition algorithm in drain modeling, which may become more essential for simulation of transient flow because of groundwater dynamics.
Engineering geology. Rock mechanics. Soil mechanics. Underground construction
Kamal M. Hammad, Iuliia A. Sadykova, Eugene N. Prokopev
et al.
This study investigates spall damage and failure in Carbon Fiber-Reinforced Polymer (CFRP) pressure vessels under explosive internal loading using stimulated electric discharge. Analytical modeling, validation with published experimental data, and explicit numerical simulations were employed. A Coupled Eulerian–Lagrangian (CEL) framework in Abaqus/Explicit captured the dynamic-impact shock propagation, using continuum shell (SC8R) elements for the vessel, solid (C3D8R) for the PMMA insert, and Eulerian (EC3D8R) for copper-wire vapor. Intralaminar failure was modeled using the Hashin criterion, while interlaminar damage was captured using the energy-release-rate-tuned Virtual Crack Closure Technique (VCCT). Results demonstrated high-accuracy agreement with experiments in terms of free surface velocity and failure stresses, with minor discrepancies attributed to wire alignment, material model limitations, and wave reverberations. These findings highlight the reliability of the integrated modeling framework and support improved design and risk-mitigation strategies for composite pressure vessels, advancing safety and cost-efficiency through refined material characterization and structural assessment.
Mechanical engineering and machinery, Structural engineering (General)
Xabier Rey Barreiro, Nick Baberuxki, Meskerem Abebaw Mebratie
et al.
We discuss the use of symmetries for analysing the structural identifiability and observability of control systems. Special emphasis is put on the role of discrete symmetries, in contrast to the more commonly studied continuous or Lie symmetries. We argue that discrete symmetries are the origin of parameters which are structurally locally identifiable, but not globally. We exploit this fact to present a methodology for structural identifiability analysis that detects such parameters and characterizes the symmetries in which they are involved. We demonstrate the use of our methodology by applying it to four case studies.
Johan Cederbladh, Loek Cleophas, Eduard Kamburjan
et al.
With the current trend in Model-Based Systems Engineering towards Digital Engineering and early Validation & Verification, experiments are increasingly used to estimate system parameters and explore design decisions. Managing such experimental configuration metadata and results is of utmost importance in accelerating overall design effort. In particular, we observe it is important to 'intelligent-ly' reuse experiment-related data to save time and effort by not performing potentially superfluous, time-consuming, and resource-intensive experiments. In this work, we present a framework for managing experiments on digital and/or physical assets with a focus on case-based reasoning with domain knowledge to reuse experimental data efficiently by deciding whether an already-performed experiment (or associated answer) can be reused to answer a new (potentially different) question from the engineer/user without having to set up and perform a new experiment. We provide the general architecture for such an experiment manager and validate our approach using an industrial vehicular energy system-design case study.
This paper presents a proof of generic structural stability for Riemann solutions to $2 \times 2$ system of hyperbolic conservation laws in one spatial variable, without diffusive terms. This means that for almost every left and right state, shocks and rarefaction solutions of the same type are preserved via perturbations of the flux functions, the left state, and the right state. The main assumptions for this proof involve standard assumptions on strict hyperbolicity and genuine non-linearity, a technical assumption on directionality of rarefaction curves, and the regular manifold (submersion) assumption motivated by concepts in differential topology. We show that the structural stability of the Riemann solutions is related to the transversality of the Hugoniot loci and rarefaction curves in the state space. The regular manifold assumption is required to invoke a variant of a theorem from differential topology, Thom's parametric transversality theorem, to show the genericity of transversality of these curves. This in turn implies the genericity of structural stability. We then apply this theorem to two examples: the p-system and a $2 \times 2$ system governing the evolution of gravity-driven monodisperse particle-laden thin films. In particular, we illustrate how one can verify all the above assumptions for the former, and apply the theorem to different numerical and physical aspects of the system governing the latter.
Abstract Sequence-based maximum likelihood (ML) phylogenetics is a widely used method for inferring evolutionary relationships, which has illuminated the evolutionary histories of proteins and the organisms that harbour them. But modern implementations with sophisticated models of sequence evolution struggle to resolve deep evolutionary relationships, which can be obscured by excessive sequence divergence and substitution saturation. Structural phylogenetics has emerged as a promising alternative, because protein structure evolves much more slowly than protein sequences. Recent developments protein structure prediction using AI have made it possible to predict protein structures for entire protein families, and then to translate these structures into a sequence representation - the 3Di structural alphabet - that can in theory be directly fed into existing sequence based phylogenetic software. To unlock the full potential of this idea, however, requires the inference of a general substitution matrix for structural phylogenetics, which has so far been missing. Here we infer this matrix from large datasets of protein structures and show that it results in a better fit to empirical datasets that previous approaches. We then use this matrix to re-visit the question of the root of the tree of life. Using structural phylogenies of universal paralogs, we provide the first unambiguous evidence for a root between and archaea and bacteria. Finally, we discuss some practical and conceptual limitations of structural phylogenetics. Our 3Di substitution matrix provides a starting point for revisiting many deep phylogenetic problems that have so far been extremely difficult to solve.
In many countries, recent boosts in the construction and renovation sectors and energy efficiency directives are driving a growing interest in the built environment among designers and maintainers. In this context, customized software solutions tailored for Building Information Modelling (BIM) and Building Energy Modelling (BEM) are proving to be indispensable for optimizing operational efficiency within the Architecture, Engineering, Construction, Owner, and Operator (AECOO) sector and for facilitating the generation of buildings' Digital Twins (DTs). These DTs rely on accurate geometry and ancillary information (semantics, sensors, etc.) to define properties of single elements, enabling crucial simulations in structural conditions or energy needs. However, BIM and BEM model creation and their enrichment with semantic information are highly time-consuming and prone to manual errors. Hence, there is an increasing demand for automatic methods featuring a high level of geometric accuracy to reconstruct building elements, such as walls, floors, and openings captured via 3D reality-based surveying. This paper introduces an automated method for creating Boundary Representation (B-Rep) models from 3D surveying data for the generation of digital building replicas. The method is based on the detection and computation of topological elements from 3D reality-based point clouds. It proves valuable for architectural or design workflows and for conducting energy or quality system simulations.
Abstract Self-compacting concrete (SCC) is also seen as unsustainable since it uses a lot of natural resources. Recent researchers have focused on lowering construction costs and partially replacing cement with industrial waste. It is possible to effectively use various industrial wastes in concrete as cement or aggregates. Among these wastes, waste marble (WM) is a useful choice, and researchers have been interested in using WM in concrete for a couple of years. However, to pinpoint the advantages and recent advancements of research on WM as an ingredient of SCC, a comprehensive study is necessary. Therefore, the purpose of this study is to do a compressive evaluation of WM as an SCC ingredient. The review includes a general introduction to SCC and WM, the filling and passing capability of SCC, strength properties of SCC, durability, and microstructure analysis of SCC. According to the findings, WM improved the concrete strength and durability of SCC by up to 20% substitution due to micro-filling and pozzolanic reaction. Finally, the review also identifies research gaps for future investigations.
Systems of building construction. Including fireproof construction, concrete construction
XUE Song 1, 2, 3, YANG Zhibing 2, 3, CHEN Yifeng 2, 3, TONG Fuguo 1
An in-depth understanding of liquid flows through fracture intersections is important for predicting the seepage characteristics of fracture networks. The flow behavior of liquid at unsaturated intersections is closely related to the flow mode and geometric characteristics of fractures. A modeling study is given on the physical process of droplet splitting through unsaturated fracture intersections, which usually occurs under low flow rate and low saturation conditions. The effects of fracture apertures on droplet splitting behaviors are systematically investigated by varying the main channel width w1 and the branch width w2 of the fracture intersection. It is found that there are two droplet splitting patterns related to the droplet length: the flows dominated by the main channel and those dominated by the branch, which can be distinguished by the critical droplet length. This critical length is controlled by capillary force and permeability of channels, both varying with the channel widths. When the two controlling factors have opposite effects on the droplet splitting, the critical droplet length changes non-monotonously with w2. Conversely, the critical droplet length changes monotonously with w1. In addition, there is an optimal range for the width ratio w2/w1 to maximize the critical droplet length. This study provides theoretical support for predicting the seepage structure of fractured rocks under the conditions of low flow and low saturation.
Engineering geology. Rock mechanics. Soil mechanics. Underground construction
<p>The MethaneSAT satellite instrument and its aircraft precursor, MethaneAIR, are imaging spectrometers designed to measure methane concentrations with wide spatial coverage, fine spatial resolution, and high precision compared to currently deployed remote sensing instruments. At 12 960 m cruise altitude above ground (13 850 m above sea level), MethaneAIR datasets have a 4.5 km swath gridded to 10 m <span class="inline-formula">×</span> 10 m pixels with 17–20 ppb standard deviation on a flat scene. MethaneAIR was deployed in the summer of 2021 in the Permian Basin to test the accuracy of the retrieved methane concentrations and emission rates using the algorithms developed for MethaneSAT. We report here point source emissions obtained during a single-blind volume-controlled release experiment, using two methods. (1) The modified integrated mass enhancement (mIME) method estimates emission rates using the total mass enhancement of methane in an observed plume combined with winds obtained from Weather Research Forecast driven by High-Resolution Rapid Refresh meteorological data in Large Eddy Simulations mode (WRF-LES-HRRR). WRF-LES-HRRR simulates winds in stochastic eddy-scale (100–1000 m) variability, which is particularly important for low-wind conditions and informing the error budget. The mIME can estimate emission rates of plumes of any size that are detectable by MethaneAIR. (2) The divergence integral (DI) method applies Gauss's theorem to estimate the flux divergence fields through a series of closed surfaces enclosing the sources. The set of boxes grows from the upwind side of the plume through the core of each plume and downwind. No selection of inflow concentration, as used in the mIME, is required. The DI approach can efficiently determine fluxes from large sources and clusters of sources but cannot resolve small point emissions. These methods account for the effects of eddy-scale variation in different ways: the DI averages across many eddies, whereas the mIME re-samples many eddies from the LES simulation. The DI directly uses HRRR winds, while mIME uses WRF-LES-HRRR wind products. Emissions estimates from both the mIME and DI methods<span id="page5772"/> agreed closely with the single-blind volume-controlled experiments (<span class="inline-formula"><i>N</i></span> <span class="inline-formula">=</span> 21). The York regression between the estimated emissions and the released emissions has a slope of 0.96 [0.84, 1.08], <span class="inline-formula"><i>R</i></span> <span class="inline-formula">=</span> 0.83 and <span class="inline-formula"><i>N</i></span> <span class="inline-formula">=</span> 21, with 30 % mean percentage error for the whole dataset, which indicates that MethaneAIR can quantify point sources emitting more than 200 kg h<span class="inline-formula"><sup>−1</sup></span> for the mIME and 500 kg h<span class="inline-formula"><sup>−1</sup></span> for the DI method. The two methods also agreed on methane emission estimates from various uncontrolled sources in the Permian Basin. The experiment thus demonstrates the powerful potential of the MethaneAIR instrument and suggests that the quantification method should be transferable to MethaneSAT if it meets the design specifications.</p>
Performance-based engineering for natural hazards facilitates the design and appraisal of structures with rigorous evaluation of their uncertain structural behavior under potentially extreme stochastic loads expressed in terms of failure probabilities against stated criteria. As a result, efficient stochastic simulation schemes are central to computational frameworks that aim to estimate failure probabilities associated with multiple limit states using limited sample sets. In this work, a generalized stratified sampling scheme is proposed in which two phases of sampling are involved: the first is devoted to the generation of strata-wise samples and the estimation of strata probabilities whereas the second aims at the estimation of strata-wise failure probabilities. Phase-I sampling enables the selection of a generalized stratification variable (i.e., not necessarily belonging to the input set of random variables) for which the probability distribution is not known a priori. To improve the efficiency, Markov Chain Monte Carlo Phase-I sampling is proposed when Monte Carlo simulation is deemed infeasible and optimal Phase-II sampling is implemented based on user-specified target coefficients of variation for the limit states of interest. The expressions for these coefficients are derived with due regard to the sample correlations induced by the Markov chains and the uncertainty in the estimated strata probabilities. The proposed stochastic simulation scheme reaps the benefits of near-optimal stratified sampling for a broader choice of stratification variables in high-dimensional reliability problems with a mechanism to approximately control the accuracy of the failure probability estimators. The practicality of the scheme is demonstrated using two examples involving the estimation of failure probabilities associated with highly nonlinear responses induced by wind and seismic excitations.
The geometric trinity of gravity comprises three distinct formulations of general relativity: (i) the standard formulation describing gravity in terms of spacetime curvature, (ii) the teleparallel equivalent of general relativity describing gravity in terms of spacetime torsion, and (iii) the symmetric teleparallel equivalent of general relativity (STEGR) describing gravity in terms of spacetime non-metricity. In this article, we complete a geometric trinity of non-relativistic gravity, by (a) taking the non-relativistic limit of STEGR to determine its non-relativistic analogue, and (b) demonstrating that this non-metric theory is equivalent to the Newton--Cartan theory and its teleparallel equivalent, i.e., the curvature and the torsion based non-relativistic theories that are both geometrised versions of classical Newtonian gravity.