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The classical Hastings–Powell model is well known to exhibit chaotic dynamics in a three-species food chain. Chaotic dynamics appear through period-doubling bifurcation of stable coexistence limit cycle around an unstable coexisting equilibrium point. A specific choice of parameter value leads to a situation, where the chaotic attractor disappears through a collision with an unstable limit cycle originated due to subcritical Hopf-bifurcation around the coexistence equilibrium. As a consequence, the top predator goes to extinction. The main objective of this work is to explore the structural sensitivity of this phenomenon by replacing the Holling-type II functional responses with Ivlev functional responses. In this work, we have shown the existence of two Hopf-bifurcation thresholds and numerically verified the existence of an unstable limit cycle. The model with Ivlev functional responses does not indicate any possibility of extinction of the top predator due to any collision of chaotic attractor with the unstable limit cycle for the chosen range of parameter values. Moreover, the model with Ivlev functional responses depicts an interesting scenario of bistable oscillatory coexistence. [ABSTRACT FROM AUTHOR]

Strong metal‐support interactions (SMSI) featuring the formation of encapsulation overlayer around metal nanoparticles has drawn much attention in heterogeneous catalysis. Recent years, various novel SMSI phenomena have been observed and the nature of SMSI also has been revealed with the improvement of characterization techniques. Understanding the SMSI effect could deepen the insight into the structure‐activity relationship of metal‐supported catalysts, and rationally guide the design of special metal‐interface sites to manipulate catalytic behavior in chemical reaction. In this review, the research progress of SMSI and its application in heterogeneous COx hydrogenation are briefly surveyed, with emphasis on the advanced characterization, manipulation strategy and specific role of SMSI in Fischer‐Tropsch synthesis process, CO2 methanation and Reverse Water Gas Shift reaction. The current challenges and perspectives for the development of SMSI are also discussed. [ABSTRACT FROM AUTHOR]

Linear stability analysis of the steady flow past elliptic cylinders of different aspect ratio (A r) has been conducted for the flow Reynolds number (R e) in the range 30–200. A new unstable mode, which we refer as tertiary wake mode, has been discovered. Two other unstable modes (the primary wake mode and the secondary wake mode), already reported in the literature, are also found. The critical R e for the onset of instability of these modes and the corresponding Strouhal number (S t) have been reported. Modes that have large growth rates tend to come close to the cylinder surface, and the extent to which they spread downstream in the wake is less compared to the weaker modes. The size of the vortical structures in a mode is inversely related to its S t. The change in the characteristics of these modes with respect to change in A r and R e , as well as their evolution leading to the fully developed flow, has been studied. Selective suppression of the unstable modes is effected using a slip-plate placed on the wake centerline. For R e = 150, it is shown that selective suppression of the unstable modes leads to different fully developed unsteady flows. [ABSTRACT FROM AUTHOR]

Biological systems are known to be inherently uncertain and complex, and it is often difficult to justify rigorously functional forms used in a mathematical model. Generally, one chooses some simple function having qualitatively correct behavior without concern for the precise choice of function; the assumption has been that qualitatively similar functions will produce qualitatively similar behavior from the model. However, it has been shown that, in some cases, the qualitative predictions from a model are sensitive to the particular functional form used; this property is known as structural sensitivity. A promising tool for quantification of structural sensitivity is the use of partially specified models, in which some number of functions in equations are not defined explicitly. However, in this approach we cannot rely on the traditional parameter-based framework, where all functional forms are well defined but contain parameters to be determined. The main difficulties are that, mathematically, we need to deal with an infinite-dimensional function space and that a well-defined measure on that space is needed. We propose a novel framework to reveal the structural sensitivity and quantify uncertainty in partially specified biological models based on ordinary differential equations backed up by empirical data. Our method uses path integration, previously introduced in theoretical physics. As an insightful example, we explore structural sensitivity of a well-known tritrophic food chain model in which the functional response of the predator is uncertain, using available experimental data on protozoan predation on bacteria. For the mentioned model, we compare the novel framework with the classical methods of parameter-based sensitivity analysis and demonstrate distinct outcomes for the two approaches. Finally, we discuss a further extension of the proposed framework. [ABSTRACT FROM AUTHOR]

The oxidative C-C cleavage of a C18 substrate is an important transformation in synthetic organic chemistry, facilitating the synthesis of valuable C8-C9 acids widely used in many industries. Through a comparative analysis of the catalytic and physicochemical properties of catalysts, comprising mono- (Pd or Au) and bimetallic (PdAu) nanoparticles deposited on oxides, oxyhydroxides and graphite-like carbon material Sibunit (Cp), it was shown that the efficiency of the catalyst in the oxidative cleavage of 9,10-dihydroxystearic acid relies on the nature of the active component, the support and the average size of metal nanoparticles (NPs). The dependency of 9,10-DSA conversion on the average size of metal NPs shows the structural sensitivity of the oxidative cleavage reaction. Notably, catalysts with an average size of gold particles less than 3 nm exhibit the highest activity. The nature of the active component and the support material are crucial factors determining the process selectivity. Among the catalysts studied, the most effective for the oxidative cleavage of 9,10-DSA is a material based on Au NPs deposited on Cp. [ABSTRACT FROM AUTHOR]

Inverse-designed devices with thousands of degrees of freedom could achieve high performance in compact footprints, but typically have complex structure topologies that contain many irregular and tiny features and sharp corners, which tend to lead to a poor robustness to fabrication errors. In order to effectively transform the structure of inverse-designed nanophotonic devices into simple structure topologies that have high robustness to fabrication errors without sacrificing device performance, in this paper, we propose a structure adjustment method that innovatively adjusts the structures of inverse-designed devices by introducing their structural sensitivity to the optical performance, extracting the device substructures with high sensitivity and eliminating those with low sensitivity, and, finally, transforming the device structures into simple structure topologies with high robustness and better performance. Two devices (90° crossing and T-junction) were designed and fabrication tolerance simulation was conducted to verify the method. The results show that the devices designed using the proposed method achieved better performance and were more robust to under/over-etched errors. [ABSTRACT FROM AUTHOR]

The oxidative C-C cleavage of a C18 substrate is an important transformation in synthetic organic chemistry, facilitating the synthesis of valuable C8-C9 acids widely used in many industries. Through a comparative analysis of the catalytic and physicochemical properties of catalysts, comprising mono- (Pd or Au) and bimetallic (PdAu) nanoparticles deposited on oxides, oxyhydroxides and graphite-like carbon material Sibunit (Cp), it was shown that the efficiency of the catalyst in the oxidative cleavage of 9,10-dihydroxystearic acid relies on the nature of the active component, the support and the average size of metal nanoparticles (NPs). The dependency of 9,10-DSA conversion on the average size of metal NPs shows the structural sensitivity of the oxidative cleavage reaction. Notably, catalysts with an average size of gold particles less than 3 nm exhibit the highest activity. The nature of the active component and the support material are crucial factors determining the process selectivity. Among the catalysts studied, the most effective for the oxidative cleavage of 9,10-DSA is a material based on Au NPs deposited on Cp.

A series of Pt/CeO2 catalysts with varied sizes of Pt domains are prepared and evaluated in propane total oxidation reaction, to investigate the structural sensitivity regarding the particle sizes and metal‐support interactions. Over Pt single atoms, clusters or nanoparticles (NP), the obtained similar turnover frequencies and apparent activation energies suggest the reaction is structure insensitive to the sizes of Pt domains. Nonetheless, detailed kinetic study reveals different adsorption behavior of reactants (C3H8 and O2) over these Pt species. Following a Langmuir‐Hinshelwood mechanism, C3H8 and O2 competitively adsorb on Pt surface. The adsorption of C3H8 and O2 on Pt single atom is much easier than on Pt nanoparticles due to its lower coordination. These findings provide experimental evidences for the reaction behavior of C3H8 oxidation over Pt/CeO2 catalysts, and lay a foundation for further understanding of the structure‐property relationship. [ABSTRACT FROM AUTHOR]

PtNiFe octahedra, nanocubes, polyhedra, and cuboctahedra were prepared using alkyl phosphonic acid and oleylamine as surfactant molecules. The synthesis route affords controlling PtNiFe nanostructures by changing the molar ratio of alkyl phosphonic acid/oleylamine (Rm). The different Rm values induce specific crystal facet–surfactant bindings on the growth seed, yielding the nanocrystals of various shapes. Both experimental and statistical results reveal that higher Rm results in the formation of shapes rich in {100} facets, such as nanocubes and cuboctahedra. On the contrary, lower Rm causes the formation of shapes rich in {111} facets, such as octahedra and polyhedra. The theoretical works determine a preferential adsorption of alkyl amine molecules on the PtNiFe(111) surface and conclude that the coverage area of the {111} facets plays the key to guide the final shapes of PtNiFe nanocrystals in the alkyl phosphonic acid/oleylamine synthetic system. Further, the electrochemical results clearly demonstrate the structure-dependent oxygen reduction reaction activities of PtNiFe nanocatalysts in different electrolytes (HClO4 and H2SO4), which is valuable for the PtNiFe nanocatalysts in fuel cells. [ABSTRACT FROM AUTHOR]

The quest for enhanced electrocatalysts can be boosted by descriptor‐based analyses. Because adsorption energies are the most common descriptors, electrocatalyst design is largely based on brute‐force routines that comb materials databases until an energetic criterion is verified. In this review, it is shown that an alternative is provided by generalized coordination numbers (denoted by CN¯$\overline {{\rm{CN}}} $ or GCN), an inexpensive geometric descriptor for strained and unstrained transition metals and some alloys. CN¯$\overline {{\rm{CN}}} $ captures trends in adsorption energies on both extended surfaces and nanoparticles and is used to elaborate structure‐sensitive electrocatalytic activity plots and selectivity maps. Importantly, CN¯$\overline {{\rm{CN}}} $ outlines the geometric configuration of the active sites, thereby enabling an atom‐by‐atom design, which is not possible using energetic descriptors. Specific examples for various adsorbates (e.g., *OH, *OOH, *CO, and *H), metals (e.g., Pt and Cu), and electrocatalytic reactions (e.g., O2 reduction, H2 evolution, CO oxidation, and reduction) are presented, and comparisons are made against other descriptors. [ABSTRACT FROM AUTHOR]

Inverse-designed devices with thousands of degrees of freedom could achieve high performance in compact footprints, but typically have complex structure topologies that contain many irregular and tiny features and sharp corners, which tend to lead to a poor robustness to fabrication errors. In order to effectively transform the structure of inverse-designed nanophotonic devices into simple structure topologies that have high robustness to fabrication errors without sacrificing device performance, in this paper, we propose a structure adjustment method that innovatively adjusts the structures of inverse-designed devices by introducing their structural sensitivity to the optical performance, extracting the device substructures with high sensitivity and eliminating those with low sensitivity, and, finally, transforming the device structures into simple structure topologies with high robustness and better performance. Two devices (90° crossing and T-junction) were designed and fabrication tolerance simulation was conducted to verify the method. The results show that the devices designed using the proposed method achieved better performance and were more robust to under/over-etched errors.

Structure–performance relationship is a complex issue in iron-catalyzed Fischer–Tropsch synthesis, and it is not easy to elucidate it by experimental investigations. First-principle calculation is a powerful method for explaining experimental results and guiding catalyst design. In this study, we investigated the reaction mechanisms of CH4 formation and C–C coupling on four χ-Fe5C2 surfaces and established the kinetic equations to compare the rates of CH4 formation and C1+C1 coupling reactions and determine the CH4/C2+ selectivity. The results show that the geometry of the χ-Fe5C2 surfaces has little effect on the formation rate of CH4; however, the C1+C1 coupling reactions are significantly affected by the surface geometry. The C1+C1 coupling reaction rates on the terraced-like (510) and (021) surfaces are much higher than those on the stepped-like (001) and (100) surfaces. Based on these results, we established a Brønsted–Evans–Polanyi (BEP) relationship between the effective barrier difference for CH4 formation and C1+C1 coupling (ΔEeff) and the adsorption energy of C+4H (ΔEC+4H) on χ-Fe5C2 surfaces. ΔEC+4H can be used as a descriptor for CH4/C2+ selectivity on different surfaces of χ-Fe5C2.

In mathematical ecology, it is often assumed that properties of a mathematical model are robust to specific parameterization of functional responses, in particular preserving the bifurcation structure of the system, as long as different functions are qualitatively similar. This intuitive assumption has been challenged recently (Fussmann & Blasius, 2005). Having considered the prey–predator system as a paradigm of nonlinear population dynamics, it has been shown that in fact both the bifurcation structure and the structure of the phase space can be rather different even when the component functions are apparently close to each other. However, these observations have so far been largely limited to nonspatial systems described by ODEs. In this paper, our main interest is to investigate whether such structural sensitivity occurs in spatially explicit models of population dynamics, in particular those that are described by PDEs. We consider a prey–predator model described by a system of two nonlinear reaction–diffusion–advection equations where the predation term is parameterized by three different yet numerically close functions. Using some analytical tools along with numerical simulations, we show that the properties of spatiotemporal dynamics are rather different between the three cases, so that patterns observed for one parameterization may not occur for the other two ones. • ODE-based population models are sensitive to nonlinear feedbacks parameterization. • Diffusion–reaction prey–predator model is studied analytically and numerically. • Pattern formation is sensitive to details of functional response parameterization. [ABSTRACT FROM AUTHOR]

This article introduces a novel method to calculate the structural sensitivity in non-linear flows. The method is completely data-driven and only uses direct solutions, avoiding the need to calculate the adjoint solution. Moreover, the method can be directly applied to calculate the structural sensitivity in three-dimensional flows. Depending on the nature and the complexity of the data analysed, the methodology presented to calculate this so-called non-linear structural sensitivity, uses dynamic mode decomposition (DMD) or higher order DMD to identify the global modes leading the flow dynamics. The performance of this novel technique has been tested in the two-dimensional wake of a circular cylinder at Reynolds number (Re) 50, 60, 85, 100, 130 and 160, the three-dimensional wake of a circular cylinder at Re = 280 and spanwise wavelength L z = 1.67 and 6.99, in a Food and Drug and Administration nozzle at Re = 800 and in two-concentric jets with similar velocity ratio at Re = 1500. The results have been compared with the structural sensitivity predicted by the linear theory, finding some similarities and discrepancies between both methods. Nevertheless, the highest structural sensitivity regions identified by this novel algorithm are in good agreement with the literature, where the flow instabilities have been controlled using different mechanisms of passive flow control located in the regions predicted by the non-linear structural sensitivity calculated in this article. [ABSTRACT FROM AUTHOR]

Density functional theory (DFT) has been established as a powerful research tool for heterogeneous catalysis research in obtaining key thermodynamic and/or kinetic parameters like adsorption energies, enthalpies of reaction, activation barriers, and rate constants. Understanding of density functional exchange-correlation approximations is essential to reveal the mechanism and performance of a catalyst. In the present work, we reported the influence of six exchange-correlation density functionals, including PBE, RPBE, BEEF+vdW, optB86b+vdW, SCAN, and SCAN+rVV10, on the adsorption energies, reaction energies and activation barriers of carbon hydrogenation and carbon-carbon couplings during the formation of methane and ethane over Ru(0001) and Ru(10 1 ¯ 1) surfaces. We found the calculated reaction energies are strongly dependent on exchange-correlation density functionals due to the difference in coordination number between reactants and products on surfaces. The deviation of the calculated elementary reaction energies can be accumulated to a large value for chemical reaction involving multiple steps and vary considerably with different exchange-correlation density functionals calculations. The different exchange-correlation density functionals are found to influence considerably the selectivity of Ru(0001) surface for methane, ethylene, and ethane formation determined by the adsorption energies of intermediates involved. However, the influence on the barriers of the elementary surface reactions and the structural sensitivity of Ru(0001) and Ru(10 1 ¯ 1) are modest. Our work highlights the limitation of exchange-correlation density functionals on computational catalysis and the importance of choosing a proper exchange-correlation density functional in correctly evaluating the activity and selectivity of a catalyst. [ABSTRACT FROM AUTHOR]

This study explored the effect of word knowledge facets (word-general and wordspecific knowledge) on second language (L2) Chinese lexical inference by highlighting the moderating effect of language proficiency level and learners' heritage status. L2 Chinese learners with a mixture of linguistic (low-intermediate and high-intermediate) and cultural (heritage and non-heritage) backgrounds completed a series of word-knowledge measurements as well as a lexical inferencing task. Through a moderated path model, the study demonstrated that word-general knowledge (morphological awareness) and word-specific knowledge (vocabulary knowledge) contributed to L2 Chinese lexical inference. In addition, the study underlined the moderating effect of heritage status on the correlation between word knowledge and lexical inference. Given the distinct patterns between heritage and non-heritage learners, morphological awareness may define the characteristics of reading profiles in the Chinese heritage learner population. [ABSTRACT FROM AUTHOR]

Abstract Background Prediction of the change in fold stability (ΔΔG) of a protein upon mutation is of major importance to protein engineering and screening of disease-causing variants. Many prediction methods can use 3D structural information to predict ΔΔG. While the performance of these methods has been extensively studied, a new problem has arisen due to the abundance of crystal structures: How precise are these methods in terms of structure input used, which structure should be used, and how much does it matter? Thus, there is a need to quantify the structural sensitivity of protein stability prediction methods. Results We computed the structural sensitivity of six widely-used prediction methods by use of saturated computational mutagenesis on a diverse set of 87 structures of 25 proteins. Our results show that structural sensitivity varies massively and surprisingly falls into two very distinct groups, with methods that take detailed account of the local environment showing a sensitivity of ~ 0.6 to 0.8 kcal/mol, whereas machine-learning methods display much lower sensitivity (~ 0.1 kcal/mol). We also observe that the precision correlates with the accuracy for mutation-type-balanced data sets but not generally reported accuracy of the methods, indicating the importance of mutation-type balance in both contexts. Conclusions The structural sensitivity of stability prediction methods varies greatly and is caused mainly by the models and less by the actual protein structural differences. As a new recommended standard, we therefore suggest that ΔΔG values are evaluated on three protein structures when available and the associated standard deviation reported, to emphasize not just the accuracy but also the precision of the method in a specific study. Our observation that machine-learning methods deemphasize structure may indicate that folded wild-type structures alone, without the folded mutant and unfolded structures, only add modest value for assessing protein stability effects, and that side-chain-sensitive methods overstate the significance of the folded wild-type structure.

The goal of this study was to analyze the structural sensitivity of a flexible pavement, whose asphalt layers underwent variations in its mechanical properties due to the asphalt binder content and the mix design method Marshall and Superpave. A variation of ±0.5% within the optimum asphalt binder contents was used (service tolerance) considering possible permissible variations in the asphalt binder content during the asphalt mixture manufacturing process. The values of resilient modulus and indirect tensile strength (Brazilian test) of the resulting asphalt mixtures were applied to the reference pavement structure analyzed by the me-PADS software. The results show that the variations in the asphalt binder content and the asphalt mixtures design method influence the mechanical properties and corresponding structural responses of the pavement investigated: the asphalt layers designed by the Marshall method presented greater sensitivity to the variation in asphalt binder content, which may constitute a technical differential of asphalt mixtures designed by the Superpave method.

Catalyst deactivation is one of the long-standing challenges in heterogeneous catalysis. Here, we found that the Ni/MgAl 2 O 4 catalyst shows an atmosphere-dependent deactivation behavior during dry reforming of methane (DRM) process, i.e., oxidation and redispersion of Ni near the inlet in an oxidizing atmosphere while coking and sintering of Ni near the outlet in a reducing atmosphere. These structural evolutions of the Ni species are revealed to be driven by the surface oxidation degree of the catalyst, such that it is reversible when the redox atmosphere changes. It inspired us to develop an alternating-feeding gas strategy that periodically changes the gas flow direction to balance the structural evolution of Ni species across catalyst bed through the spontaneous regeneration of deactivated sites, enabling a supra-stable DRM process. This study provides new insights into the catalyst deactivation for DRM process, while opens a new avenue to address catalyst deactivation in various redox-catalyzed processes. [Display omitted] • A local redox atmosphere-induced structural evolution of Ni/MgAl 2 O 4 was revealed. • Catalyst deactivation due to oxidation/redispersion of Ni particles was identified. • Reversible catalyst deactivation behaviors of Ni/MgAl 2 O 4 for DRM were summarized. • An alternating feeding strategy enabling a supra-stable DRM process was proposed. [ABSTRACT FROM AUTHOR]

[Display omitted] • DFT-based adsorption energies for C, CH x and COH on various transition metal sites. • The slopes of the scaling lines can be predicted based on electron-counting rules. • Anomalous structure dependence for the offsets of CH vs C and COH vs C. • COH hydrogenation to produce C is energy-intensive during CO 2 reduction to CH 4. The arduous modelling of reactions at heterogeneous catalysts is greatly simplified when adsorption-energy scaling relations between intermediates exist. Generally, the offset of these linear relations is structure-independent when the slope is unity and otherwise depends on the coordination number of the active sites. Here we examine the adsorption of *C, *CH, *CH 2 , *CH 3 and *COH on five different surface sites of nine transition metals to establish their structure-sensitive scaling relations. Interestingly, we show that the scaling relations of *C (valency 4) and C-containing species with valency 3 (*CH, *COH) have peculiar structure-independent offsets. These offsets stem from the analogous bonding of those species to the adsorption sites, in spite of their dissimilar valency. We show how this result implies that reaction pathways in catalysis involving *C, *CH and *COH, for instance CO 2 electroreduction to CH 4 , will usually have sizable thermodynamic limits imposed to their optimization. [ABSTRACT FROM AUTHOR]

According to the results of the study of activated red mud (ARM) and its copper-containing compositions, there is a relationship between the heat treatment conditions of compositions, the size of nanoparticles of the components, and catalytic activity in CO oxidation and steam reforming. It is shown that the introduction of CuO into the composition causes a decrease in the temperature of complete CO conversion in the oxidation reaction by 240-260°C. [ABSTRACT FROM AUTHOR]

Background: Prediction of the change in fold stability (ΔΔG) of a protein upon mutation is of major importance to protein engineering and screening of disease-causing variants. Many prediction methods can use 3D structural information to predict ΔΔG. While the performance of these methods has been extensively studied, a new problem has arisen due to the abundance of crystal structures: How precise are these methods in terms of structure input used, which structure should be used, and how much does it matter? Thus, there is a need to quantify the structural sensitivity of protein stability prediction methods. Results: We computed the structural sensitivity of six widely-used prediction methods by use of saturated computational mutagenesis on a diverse set of 87 structures of 25 proteins. Our results show that structural sensitivity varies massively and surprisingly falls into two very distinct groups, with methods that take detailed account of the local environment showing a sensitivity of ~ 0.6 to 0.8 kcal/mol, whereas machine-learning methods display much lower sensitivity (~ 0.1 kcal/mol). We also observe that the precision correlates with the accuracy for mutation-type-balanced data sets but not generally reported accuracy of the methods, indicating the importance of mutation-type balance in both contexts. Conclusions: The structural sensitivity of stability prediction methods varies greatly and is caused mainly by the models and less by the actual protein structural differences. As a new recommended standard, we therefore suggest that ΔΔG values are evaluated on three protein structures when available and the associated standard deviation reported, to emphasize not just the accuracy but also the precision of the method in a specific study. Our observation that machine-learning methods deemphasize structure may indicate that folded wild-type structures alone, without the folded mutant and unfolded structures, only add modest value for assessing protein stability effects, and that side-chain-sensitive methods overstate the significance of the folded wild-type structure. [ABSTRACT FROM AUTHOR]

The nanostructure of a semiconductor is a crucial parameter for efficient photocatalytic performance. Hereby, we have synthesized monoclinic bismuth vanadate (BiVO4) crystals with controlled ratio of {010} and {110} facets. The selective deposition of CuOx and CoOx over {010} and {110} facets has been performed using photo‐reduction and photo‐oxidation methods, respectively. It resulted in a highly efficient charge separation of photogenerated electrons and holes and enhancement of the photocatalytic reduction of CO2 by H2O into hydrocarbons, including CH4, C2H6 and C3H8. The controlled co‐catalyst deposition over different semiconductor facets provides a strategy for the synthesis of hydrocarbons from CO2 and H2O by efficient charge separation. [ABSTRACT FROM AUTHOR]

A honeycomb-type cable dome with two struts has the following characteristics: 1) honeycomb-shaped grids of random isosceles hexagon are adopted on upper chord ridge cables; 2) Fuller’s idea that tensegrity is an ocean of tensile cables and islands of compressed struts is discarded, so that two oblique struts are converged at both upper and lower chord nodes, instead of one vertical strut, which enlarge the upper chord grids and stabilize struts and the whole structure. Easy construction and combination of architectural and structural beauty are also achieved. A simplified calculation method of pretress distribution was proposed through nodal equilibrium equations. General calculation formulas of member forces at the prestress mode were given. Ninety examples of structural models were analyzed in order to show the magnitude and distribution features of member forces at the prestress mode. Parameter analysis showes that member forces are not sensitive to the rise-to-span ratio or whether an inner hoop is set, while the position of lower chord nodes is quite crucial. This study provided new ideas for structural selection, design and construction of cable domes. [ABSTRACT FROM AUTHOR]

An issue in mathematical modeling is that multiple models describe the same data based on different but all acceptable theoretical assumptions. To take this uncertainty in model construction into account, the classical parameter sensitivity analysis needs to be extended to consider alternative choices in model formulation. This is particularly important in population biology, where a single function often summarizes mechanisms from the physiological to the population level. Predictions based on population models were recently shown to be sometimes highly sensitive to the function that models predation. This so-called structural sensitivity extends the classical structural stability. It arises from differences between the bifurcation diagrams based on alternative model formulations. Here, we ask through an example of a predator-prey system that exhibits complex bifurcations (involving limit cycles and homoclinic orbits) how the qualitative changes in bifurcations occur during a small continuous switch between two acceptable model formulations. In this model, fixed parameter values are estimated from empirical data, free parameters allow one to explore a wide range of environmental conditions and species, and a remaining parameter makes a switch between two predation formulations. Thus, the change in model formulation becomes a parameter sensitivity problem that is studied by bifurcation analysis. A three-dimensional analysis revealed that most changes that occur with the change in formulation are related to a codimension-three degenerated Bogdanov--Takens bifurcation. Its canonical unfolding is derived, and its analysis highlights the differences in the phase portraits predicted with the two model formulations. Differences that are not related to this bifurcation are also discussed. The discussion ends with some perspectives toward the quantification of prediction uncertainty due to uncertainty in model structure in ecology, and possibly in other fields involving the modeling of complex systems. [ABSTRACT FROM AUTHOR]

The classic Rosenzweig–MacArthur predator–prey model has been shown to exhibit, like other coupled nonlinear ordinary differential equations (ODEs) from ecology, worrying sensitivity to model structure. This sensitivity manifests as markedly different community dynamics arising from saturating functional responses with nearly identical shapes but different mathematical expressions. Using a stochastic differential equation (SDE) version of the Rosenzweig–MacArthur model with the three functional responses considered by Fussmann & Blasius (2005), I show that such sensitivity seems to be solely a property of ODEs or stochastic systems with weak noise. SDEs with strong environmental noise have by contrast very similar fluctuations patterns, irrespective of the mathematical formula used. Although eigenvalues of linearized predator–prey models have been used as an argument for structural sensitivity, they can also be an argument against structural sensitivity. While the sign of the eigenvalues' real part is sensitive to model structure, its magnitude and the presence of imaginary parts are not, which suggests noise-driven oscillations for a broad range of carrying capacities. I then discuss multiple other ways to evaluate structural sensitivity in a stochastic setting, for predator–prey or other ecological systems. • Deterministic predator–prey models can show structural sensitivity to functional forms. • It has been shown using the eigenvalues of the Rosenzweig–MacArthur model. • But strong stochasticity and oscillatory transients combine into large-amplitude cycles. • Different mathematical forms of the functional response now yield similar dynamics. • Eigenvalues of the linearized model suggest already this stochastic robustness. [ABSTRACT FROM AUTHOR]

With the aim of providing a first step in the quest for a reduction of the aerodynamic drag on the rear-end of a car, we study the phenomena of separation and reattachment of an incompressible flow by focusing on a specific aerodynamic geometry, namely a backward-slanted step at 25 ∘ of inclination. The ensuing recirculation bubble provides the basis for an analytical and numerical investigation of streamwise-streak generation, lift-up effect, and turbulent-wake and Kelvin⁻Helmholtz instabilities. A linear stability analysis is performed, and an optimal control problem with a steady volumic forcing is tackled by means of a variational formulation, adjoint methods, penalization schemes, and an orthogonalization algorithm. Dealing with the transient growth of spanwise-periodic perturbations, and inspired by the need of physically-realizable disturbances, we finally provide a procedure attaining a kinetic-energy maximal gain on the order of 10 6 , with respect to the power introduced by the external forcing.

Electrocatalytic reduction of oxidized nitrogen compounds (NO x ) promises to help rebalance the nitrogen cycle. It is widely accepted that nitrate reduction to NH 4 + /NH 3 involves NO as an intermediate, and NO hydrogenation is the potential-limiting step of NO reduction. Whether *NO hydrogenates to *NHO or *NOH is still a matter of debate, which makes it difficult to optimize catalysts for NO x electroreduction. Here, " catalytic matrices " are used to swiftly extract features of active transition metal catalysts for NO electroreduction. The matrices show that active catalysts statistically stabilize *NHO over *NOH and have undercoordinated sites. Besides, square-symmetry active sites with Cu and other elements may prove active for NO electroreduction. Finally, multivariate regressions are able to reproduce the main features found by the matrices, which opens the door for more sophisticated machine-learning studies. In sum, catalytic matrices may ease the analysis of complex electrocatalytic reactions on multifaceted materials.

Numerous formulations with the same mathematical properties can be relevant to model a biological process. Different formulations can predict different model dynamics like equilibrium vs. oscillations even if they are quantitatively close (structural sensitivity). The question we address in this paper is: does the choice of a formulation affect predictions on the number of stable states? We focus on a predator–prey model with predator competition that exhibits multiple stable states. A bifurcation analysis is realized with respect to prey carrying capacity and species body mass ratio within range of values found in food web models. Bifurcation diagrams built for two type-II functional responses are different in two ways. First, the kind of stable state (equilibrium vs. oscillations) is different for 26.0–49.4% of the parameter values, depending on the parameter space investigated. Using generalized modelling, we highlight the role of functional response slope in this difference. Secondly, the number of stable states is higher with Ivlev's functional response for 0.1–14.3% of the parameter values. These two changes interact to create different model predictions if a parameter value or a state variable is altered. In these two examples of disturbance, Holling's disc equation predicts a higher system resilience. Indeed, Ivlev's functional response predicts that disturbance may trap the system into an alternative stable state that can be escaped from only by a larger alteration (hysteresis phenomena). Two questions arise from this work: (i) how much complex ecological models can be affected by this sensitivity to model formulation? and (ii) how to deal with these uncertainties in model predictions? [ABSTRACT FROM AUTHOR]

Structural sensitivity, namely the sensitivity of a model dynamics to slight changes in its mathematical formulation, has already been studied in some models with a small number of state variables. The aim of this study is to investigate the impact of structural sensitivity in a food web model. Especially, the importance of structural sensitivity is compared to that of trophic complexity (number of species, connectance), which is known to strongly influence food web dynamics. Food web structures are built using the niche model. Then food web dynamics are modeled using several type II functional responses parameterized to fit the same predation fluxes. Food web persistence was found to be mostly determined by trophic complexity. At the opposite, even if food web connectance promotes equilibrium dynamics, their occurrence is mainly driven by the choice of the functional response. These conclusions are robust to changes in some parameter values, the fitting method and some model assumptions. In a one-prey/one-predator system, it was shown that the possibility that multiple stable states coexist can be highly structural sensitive. Quantifying this type of uncertainty at the scale of ecosystem models will be both a natural extension to this work and a challenging issue. [ABSTRACT FROM AUTHOR]

This paper proposes a new power-constrained contrast enhancement algorithm for organic light-emitting diode displays that provides high perceptual image quality with low power consumption. Unlike existing methods, the proposed method can achieve the target power consumption (TPC) without iteration, while significantly alleviating overenhancement artifacts using global and local attributes compared to the benchmark methods. The proposed method consists of three steps. In the first step, mapping functions, which map the input intensity into the output intensity, are generated considering the TPC. In the second step, to properly alleviate the overenhancement artifacts, the proposed method adjusts the degree of contrast improvement in the mapping functions based on a global attribute that represents the contrast of the input image. Furthermore, the proposed method modifies the mapping functions using a local attribute, the spatial correlation between the input and output images, to alleviate the spatial distortion. Finally, using the modified mapping functions, the output image is generated to accurately meet the TPC. In the experiments, the proposed method increased the structural fidelity, enhancement performance measure, and sharpness by up to 13.1%, 65.7%, and 44.7% compared to the benchmark methods. Furthermore, it reduced the execution time by up to 28.1% and 91.6% compared to the benchmark methods and noniteratively met the TPC within an error rate of approximately 0.43%. [ABSTRACT FROM PUBLISHER]

Ethanol is a highly desirable product of the electrochemical reduction of CO and/or CO 2 on copper. Although ethanol and ethylene share common intermediates at the early stages of CO/CO 2 reduction to C 2 species on copper, the pathways bifurcate and most copper surfaces favor the formation of ethylene. We present here a combined experimental-computational study of the electroreduction of acetaldehyde to ethanol on Cu(1 1 1), Cu(1 0 0) and Cu(3 2 2). The experiments show structure-sensitive onset potentials for acetaldehyde reduction such that lower overpotentials are observed for more open facets ( η 3 2 2 < η 1 0 0 < η 1 1 1 ). Our DFT calculations show that the electrochemical reduction of acetaldehyde proceeds via a CH 3 CH 2 O* intermediate on the three electrodes at high *H coverage, and that the stability of this weakly bound intermediate determines the onset potential. Our results suggest that during the late stages of CO/CO 2 reduction to C 2 species on copper, ethanol formation has higher energetic barriers than ethylene formation, and hence the selectivity is inclined toward the latter. Importantly, our results suggest that the barriers for ethanol formation can be lowered by making use of its structure sensitivity. [ABSTRACT FROM AUTHOR]

In mathematical modelling, several different functional forms can often be used to fit a data set equally well, especially if the data is sparse. In such cases, these mathematically different but similar looking functional forms are typically considered interchangeable. Recent work, however, shows that similar functional responses may nonetheless result in significantly different bifurcation points for the Rosenzweig–MacArthur predator–prey system. Since the bifurcation behaviours include destabilizing oscillations, predicting the occurrence of such behaviours is clearly important. Ecologically, different bifurcation behaviours mean that different predictions may be obtained from the models. These predictions can range from stable coexistence to the extinction of both species, so obtaining more accurate predictions is also clearly important for conservationists. Mathematically, this difference in bifurcation structure given similar functional responses is called structural sensitivity. We extend the existing work to find that the Leslie–Gower–May predator–prey system is also structurally sensitive to the functional response. Using the Rosenzweig–MacArthur and Leslie–Gower–May models, we then aim to determine if there is some way to obtain a functional description of data so that different functional responses yield the same bifurcation structure, i.e., we aim to describe data such that our model is not structurally sensitive. We first add stochasticity to the functional responses and find that better similarity of the resulting bifurcation structures is achieved. Then, we analyse the functional responses using two different methods to determine which part of each function contributes most to the observed bifurcation behaviour. We find that prey densities around the coexistence steady state are most important in defining the functional response. Lastly, we propose a procedure for ecologists and mathematical modellers to increase the accuracy of model predictions in predator–prey systems. • Structurally sensitive models may lead to vastly different model predictions. • Bifurcation structures are studied for two models using three functional responses. • Fitting around the coexistence steady state decreases structural sensitivity. • We propose a method to improve model predictions in predator–prey systems. [ABSTRACT FROM AUTHOR]

The structural sensitivity shows where an instability of a fluid flow is most sensitive to changes in internal feedback mechanisms. It is formed from the overlap of the flow’s direct and adjoint global modes. These global modes are usually calculated with 2D or 3D global stability analyses, which can be very computationally expensive. For weakly non-parallel flows the direct global mode can also be calculated with a local stability analysis, which is orders of magnitude cheaper. In this theoretical paper we show that, if the direct global mode has been calculated with a local analysis, then the adjoint global mode follows at little extra cost. We also show that the maximum of the structural sensitivity is the location at which the local k + and k − branches have the same imaginary value. Finally, we use the local analysis to derive the structural sensitivity of two flows: a confined co-flow wake at Re = 400 , for which it works very well, and the flow behind a cylinder at Re = 50 , for which it works reasonably well. As expected, we find that the local analysis becomes less accurate when the flow becomes less parallel. [ABSTRACT FROM AUTHOR]

SUMMARY A discrete framework for computing the global stability and sensitivity analysis to external perturbations for any set of partial differential equations is presented. In particular, a complex-step approximation is used to achieve near analytical accuracy for the evaluation of the Jacobian matrix. Sensitivity maps for the sensitivity to base flow modifications and to a steady force are computed to identify regions of the flow field where an input could have a stabilising effect. Four test cases are presented: (1) an analytical test case to prove the theory of the discrete framework, (2) a lid-driven cavity at low Reynolds case to show the improved accuracy in the calculation of the eigenvalues when using the complex-step approximation, (3) the 2D flow past a circular cylinder at just below the critical Reynolds number used to validate the methodology, and finally, (4) the flow past an open cavity presented to give an example of the discrete method applied to a convectively unstable case. The latter three (2-4) of the aforementioned cases were solved with the 2D compressible Navier-Stokes equations using a Discontinuous Galerkin Spectral Element Method. Good agreement was obtained for the validation test case, (3), with appropriate results in the literature. Furthermore, it is shown that for the calculation of the direct and adjoint eigenmodes and their sensitivity maps to external perturbations, the use of complex variables is paramount for obtaining an accurate prediction. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

When we construct mathematical models to represent biological systems, there is always uncertainty with regards to the model specification-whether with respect to the parameters or to the formulation of model functions. Sometimes choosing two different functions with close shapes in a model can result in substantially different model predictions: a phenomenon known in the literature as structural sensitivity, which is a significant obstacle to improving the predictive power of biological models. In this paper, we revisit the general definition of structural sensitivity, compare several more specific definitions and discuss their usefulness for the construction and analysis of biological models. Then we propose a general approach to reveal structural sensitivity with regards to certain system properties, which considers infinite-dimensional neighbourhoods of the model functions: a far more powerful technique than the conventional approach of varying parameters for a fixed functional form. In particular, we suggest a rigorous method to unearth sensitivity with respect to the local stability of systems' equilibrium points. We present a method for specifying the neighbourhood of a general unknown function with $$n$$ inflection points in terms of a finite number of local function properties, and provide a rigorous proof of its completeness. Using this powerful result, we implement our method to explore sensitivity in several well-known multicomponent ecological models and demonstrate the existence of structural sensitivity in these models. Finally, we argue that structural sensitivity is an important intrinsic property of biological models, and a direct consequence of the complexity of the underlying real systems. [ABSTRACT FROM AUTHOR]