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At least 973 records · Page 54

Robust calibration of non-perturbative models with history matching

We apply, for the first time, Bayes Linear Emulation and History Matching to the calibration of non-perturbative models in Monte Carlo event generators. In contrast to the usual approach of "Monte Carlo tuning", History Matching does not result in best-fit plus ellipsoidal parameter uncertainty estimates but instead identifies all parameter space regions that are consistent with data. This approach leads to a systematic and robust quantification of parametric uncertainties in the models, especially in those challenging cases where different, possibly disjoint, regions of parameter space deliver similar results, which are usually not properly treated with current methodology. We highlight the power of this method with the hadronisation models available through Sherpa : the built-in cluster fragmentation Ahadic and string fragmentation through an interface to Pythia .

Iskauskas, Andrew [Durham U. (main)] (ORCID:000000↗

Robust Utility Maximization Under Convex Portfolio Constraints

We study a robust maximization problem from terminal wealth and consumption under a convex constraints on the portfolio. We state the existence and the uniqueness of the consumption–investment strategy by studying the associated quadratic backward stochastic differential equation. We characterize the optimal control by using the duality method and deriving a dynamic maximum principle.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robustness of Quadratic Hedging Strategies in Finance via Backward Stochastic Differential Equations with Jumps

We consider a backward stochastic differential equation with jumps (BSDEJ) which is driven by a Brownian motion and a Poisson random measure. We present two candidate-approximations to this BSDEJ and we prove that the solution of each candidate-approximation converges to the solution of the original BSDEJ in a space which we specify. We use this result to investigate in further detail the consequences of the choice of the model to (partial) hedging in incomplete markets in finance. As an application, we consider models in which the small variations in the price dynamics are modeled with a Poisson random measure with infinite activity and models in which these small variations are modeled with a Brownian motion or are cut off. Using the convergence results on BSDEJs, we show that quadratic hedging strategies are robust towards the approximation of the market prices and we derive an estimation of the model risk.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

In-depth understanding of molecular mechanisms of aldehyde toxicity to engineer robust Saccharomyces cerevisiae

Aldehydes are ubiquitous electrophilic compounds that ferment microorganisms including Saccharomyces cerevisiae encounter during the fermentation processes to produce food, fuels, chemicals, and pharmaceuticals. Aldehydes pose severe toxicity to the growth and metabolism of the S. cerevisiae through a variety of toxic molecular mechanisms, predominantly via damaging macromolecules and hampering the production of targeted compounds. Compounds with aldehyde functional groups are far more toxic to S. cerevisiae than all other functional classes, and toxic potency depends on physicochemical characteristics of aldehydes. The yeast synthetic biology community established a design–build–test–learn framework to develop S. cerevisiae cell factories to valorize the sustainable and renewable biomass, including the lignin-derived substrates. However, thermochemically pretreated biomass-derived substrate streams contain diverse aldehydes (e.g., glycolaldehyde and furfural), and biological conversions routes of lignocellulosic compounds consist of toxic aldehyde intermediates (e.g., formaldehyde and methylglyoxal), and some of the high-value targeted products have aldehyde functional group (e.g., vanillin and benzaldehyde). Numerous studies comprehensively characterized both single and additive effects of aldehyde toxicity via systems biology investigations, and novel molecular approaches have been discovered to overcome the aldehyde toxicity. Based on those novel approaches, researchers successfully developed synthetic yeast cell factories to convert lignocellulosic substrates to valuable products, including aldehyde compounds. Here, we highlight the salient relationship of physicochemical charac- teristics and molecular toxicity of aldehydes, the molecular detoxification and macromolecules protection mechanisms of aldehydes, and the advances of engineering robust S. cerevisiae against complex mixtures of aldehyde inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

Surface Remeshing with Robust High-Order Reconstruction

Remeshing is an important problem in variety of applications, such as finite element methods and geometry processing. Surface remeshing poses some unique challenges, as it must deliver not only good mesh quality but also good geometric accuracy. For applications such as finite elements with high-order elements (quadratic or cubic elements), the geometry must be preserved to high-order (third-order or higher) accuracy, since low-order accuracy may undermine the convergence of numerical computations. The problem is particularly challenging if the CAD model is not available for the underlying geometry, and is even more so if the surface meshes contain some inverted elements. We describe remeshing strategies that can simultaneously produce high-quality triangular meshes, untangling mildly folded triangles and preserve the geometry to high-order of accuracy. Our approach extends our earlier works on high-order surface reconstruction and mesh optimization by enhancing its robustness with a geometric limiter for under-resolved geometries. We also integrate high-order surface reconstruction with surface mesh adaptation techniques, which alter the number of triangles and nodes. We demonstrate the utilization of our method to meshes for high-order finite elements, biomedical image-based surface meshes, and complex interface meshes in fluid simulations.

Ray, Navamita↗

Robust late twenty-first century shift in the regional monsoons in RegCM-CORDEX simulations

Abstract We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25 km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability.

54 ENVIRONMENTAL SCIENCES↗

Towards understanding the robust strengthening of ENSO and more frequent extreme El Niño events in CMIP6 global warming simulations

The El Niño Southern Oscillation (ENSO) has profound impacts on weather patterns across the globe, yet there is no consensus on its response to global warming. Several modelling studies find a stronger ENSO in global warming scenarios, while other studies suggest ENSO weakening. Using a broad range of models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and four types of warming experiments, here we show that the majority of the models predict a stronger ENSO by century-end in Shared Social Pathway (SSP) experiments, and in idealized 1pctCO 2 and abrupt 4xCO 2 experiments. Several models, however, do predict no change or ENSO weakening, especially in the idealized experiments. Critically, the strongest forcing (abrupt-4xCO 2 ) does not induce the strongest ENSO response, while differences between the models are much greater than those between warming scenarios. For the long-term response (over 1000 years) the models disagree even on the sign of change. Furthermore, changes in ENSO sea surface temperature (SST) variability are only modestly correlated with the tropical Pacific mean state change. The highest correlation for ENSO SST amplitude is found with the mean zonal SST gradient in the SSP5-8.5 experiment (R = –0.58). In contrast, changes in ENSO rainfall variability correlate well with changes in the mean state, as well as with changes in ENSO SST variability. When evaluating the Bjerknes Stability Index for a subset of models, we find that it is not a reliable predictor of ENSO strengthening, as this index tends to predict greater stability with warming. We argue that the enhanced ENSO stability is offset by increases in atmospheric noise or/and potential nonlinear effects. However, a robust inter-model mechanism that can explain a stronger ENSO simulated with global warming is still lacking. Therefore, caution should be exercised when considering ENSO changes based on a single model or warming scenario.

54 ENVIRONMENTAL SCIENCES↗

Some Results of Multicriterial and Robust Optimization of Nuclear Power Systems Structure

The possibility of applying multicriterial and robust optimization methods as well as stochastic methods of determining the effect of uncertainties in the parameters of a system to structural optimization of nuclear power is discussed for the example of a hypothetical nuclear-power system consisting of thermal and fast reactors. It is shown that the optimal structures of nuclear power systems obtained by such methods are balanced in terms of conflicting criteria and technologically more diversified than those determined by single-criterion deterministic optimization. Cost-based innovative technologies, which can be adopted only by imposing additional external limitations in a single-criterion problem, appear in such structures. The examined methods make it possible to determine on a systematic basis the structures of nuclear power that are balanced in terms of a set of conflicting criteria, since factors having both positive and negative effects on the development of nuclear-power systems are included in the calculations, and to find economically efficient directions of structural changes in the system in order to improve stability and efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles instead of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.

97 MATHEMATICS AND COMPUTING↗

Robustness of Quantum Discord Between Two Noninteracting Qubits in Spin-Star Baths

We study the dynamics of quantum entanglement and discord between two noninteracting qubits, which couple with spin-star baths, obeying the XY Hamiltonian. We compare the dynamics of quantum discord with that of quantum entanglement. For the initial X-type state, in the common spin bath, the quantum discord is more robust than quantum entanglement. It is found that quantum discord of the two noninteracting qubits can be amplified, even in the regimes where entanglement suddenly disappears. This also points to a fact that the absence of entanglement does not necessarily indicate the absence of quantum correlations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Non-robust Phase Transitions in the Generalized Clock Model on Trees

Pemantle and Steif provided a sharp threshold for the existence of a robust phase transition (RPT) for the continuous rotator model and the Potts model in terms of the branching number and the second eigenvalue of the transfer matrix whose kernel describes the nearest neighbor interaction along the edges of the tree. Here a RPT is said to occur if an arbitrarily weak coupling with symmetry-breaking boundary conditions suffices to induce symmetry breaking in the bulk. They further showed that for the Potts model RPT occurs at a different threshold than PT (phase transition in the sense of multiple Gibbs measures), and conjectured that RPT and PT should occur at the same threshold in the continuous rotator model. We consider the class of four- and five-state rotation-invariant spin models with reflection symmetry on general trees which contains the Potts model and the clock model with scalarproduct-interaction as limiting cases. The clock model can be viewed as a particular discretization which is obtained from the classical rotator model with state space S{sup 1}. We analyze the transition between PT=RPT and PT≠RPT, in terms of the eigenvalues of the transfer matrix of the model at the critical threshold value for the existence of RPT. The transition between the two regimes depends sensitively on the third largest eigenvalue.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust perfluorinated porous organic networks: Succinct synthetic strategy and application in chlorofluorocarbons adsorption

Fluorinated porous organic networks (F-PONs) have demonstrated unique properties and applications, but approaches capable of affording F-PONs with high fluorine content and robust nanoporous architecture under metal-free and easy handling conditions are still rarely reported. Herein, using polydivinylbenzene (PDVB) as an easily available precursor, a novel and straightforward approach was developed to afford F-PONs via a dehydrative Friedel-Crafts reaction using perfluorinated benzylic alcohols as the cross-linking agent promoted by Brønsted acid (trifluoromethanesulfonic acid. Furthermore, the afforded material (F-PDVB) featured high fluorine content (22 at.%), large surface area (771 m 2 ∙g -1 ), and good chemical/thermal stability, rendering them as promising candidates for the adsorption of CO 2 , hydrocarbons, fluorocarbons, and chlorofluorocarbons, with weight capacities up to 520 wt% being achieved. This simple methodology can be extended to fabricate fluorinated hyper-crosslinked polymers (F-HCPs) from rigid aromatic monomers. The progress made in this work will open new opportunities to further expand the involvement of fluorinated materials in large scale applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time-consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data, whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types, and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗

A novel approach to robust H{sub ∞} integral control for TS fuzzy systems

In this paper, a novel approach to the robust H{sub ∞} integral control for TS fuzzy systems is considered. The control design concept can significantly improve the system stability for such a system. Based on the H{sub ∞} control theory and linear matrix inequality approach, a set of sufficient conditions guarantee the stability of the system and the H{sub ∞} performance. The proposed RHFI controllers are able to work well with the complex nonlinearity and can overcome the effect of approximate rules in the fuzzy system in case of parametric uncertainty existing in the system. This enables the fuzzy system to give appropriate responses with a fewer number of membership functions. Finally, the proposed RHFI controllers are verified through a simulation example, i.e., DFIG wind energy system. The simulated results show that the stability of the system is satisfied and the H{sub ∞} performance is achieved.

97 MATHEMATICS AND COMPUTING↗

Robust H{sub ∞} control for singular time-delay systems with saturating actuators via static output feedback

The problem of H{sub ∞} robust exponential stability and static output feedback stabilization of uncertain singular time-delay systems with saturating actuators are investigated. First, the delay-dependent condition is given to guarantee that the singular time-delay systems are not only exponential admissible, but also satisfies H{sub ∞} performance γ. Moreover, the estimation of stability region and the design method of H{sub ∞} static output feedback controller are given by solving a convex optimization problem. Some simulation examples are provided to demonstrate the merit of the proposed design methods.

97 MATHEMATICS AND COMPUTING↗

Robust and effective methodologies for cryopreservation and DNA extraction from anaerobic gut fungi

Cell storage and DNA isolation are essential to developing an expanded suite of microorganisms for biotechnology. However, many features of non-model microbes, such as an anaerobic lifestyle and rigid cell wall, present formidable challenges to creating strain repositories and extracting high quality genomic DNA. We establish accessible, high efficiency, and robust techniques to store lignocellulolytic anaerobic gut fungi long term without specialized equipment. Using glycerol as a cryoprotectant, gut fungal isolates were preserved for a minimum of 23 months at -80 °C. Unlike previously reported approaches, this improved protocol is non-toxic and rapid, with samples surviving twice as long with negligible growth impact. Genomic DNA extraction for these isolates was optimized to yield samples compatible with next generation sequencing platforms (e.g. Illumina, PacBio). Popular DNA isolation kits and precipitation protocols yielded preps that were unsuitable for sequencing due to carbohydrate contaminants from the chitin-rich cell wall and extensive energy reserves of gut fungi. To address this, we identified a proprietary method optimized for hardy plant samples that rapidly yielded DNA fragments in excess of 10 kb with minimal RNA, protein or carbohydrate contamination. Collectively, these techniques serve as fundamental tools to manipulate powerful biomass-degrading gut fungi and improve their accessibility among researchers.

59 BASIC BIOLOGICAL SCIENCES↗