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Summary After any disaster, there is an immediate need to assess the integrity of local structures. When available, the displacement time history of a structure during the event can provide an invaluable source of triage assessment information. Although conventional sensors such as accelerometers readily provide this information, many structures are not instrumented and in these cases an alternative is needed. This paper presents such an alternative: a flexible, low‐cost, and target‐free approach to extracting motion time histories from video recordings of structures during an event. The approach is designed for scenarios where video recordings have inadvertently captured a dynamic event, with the goal of repurposing them for structural triage assessment through a combination of computer vision and signal processing techniques. A combination of parametric video stabilization, 3D denoising, and outlier robust camera motion estimation are employed to mitigate of the effects of camera motion and video encoding artifacts. The approach leverages the computer vision concept of optical flow to provide motion estimates, and 4 canonical optical flow algorithms are assessed as part of this study. The developed approach was validated on the records of the Network for Earthquake Simulation database. The overall findings indicate that the developed method is effective at reconstructing dynamic structural time histories, though the choice of optical flow algorithm plays a significant role in the overall performance. In particular, any employed optical flow algorithm must not overpenalize the high motion gradients that occur at the boundary of in‐motion buildings and the image background.

In condition monitoring of structures, acceleration time histories are usually recorded due to ease of instrumentation. In cases where the information about a displacement time history is required, the acceleration data needs to be integrated to obtain the velocity and then the velocity needs to be integrated to obtain the displacements. However, the numerical integration of the acceleration data usually introduces an unrealistic drift component to the velocity as well as displacement. This paper presents an eigenfunction method to derive velocity and displacement time histories from a given acceleration time history. The paper analyzes displacements in two case studies using the numerical integration as well as the proposed eigenfunction method. It is concluded that the eigenfunction method is a viable approach to derive the displacement information from the acceleration data.

Dissipative and unitary processes define the evolution of a many-body system. Their interplay gives rise to dynamical phase transitions and can lead to instabilities. In this study, we observe a nonstationary state of chiral nature in a synthetic many-body system with independently controllable unitary and dissipative couplings. Our experiment is based on a spinor Bose gas interacting with an optical resonator. Orthogonal quadratures of the resonator field coherently couple the Bose-Einstein condensate to two different atomic spatial modes, whereas the dispersive effect of the resonator losses mediates a dissipative coupling between these modes. In a regime of dominant dissipative coupling, we observe the chiral evolution and relate it to a positional instability.

Carbon dioxide electroreduction facilitates the sustainable synthesis of fuels and chemicals 1 . Although Cu enables CO 2 -to-multicarbon product (C 2+ ) conversion, the nature of the active sites under operating conditions remains elusive 2 . Importantly, identifying active sites of high-performance Cu nanocatalysts necessitates nanoscale, time-resolved operando techniques 3 – 5 . Here, we present a comprehensive investigation of the structural dynamics during the life cycle of Cu nanocatalysts. A 7 nm Cu nanoparticle ensemble evolves into metallic Cu nanograins during electrolysis before complete oxidation to single-crystal Cu 2 O nanocubes following post-electrolysis air exposure. Operando analytical and four-dimensional electrochemical liquid-cell scanning transmission electron microscopy shows the presence of metallic Cu nanograins under CO 2 reduction conditions. Correlated high-energy-resolution time-resolved X-ray spectroscopy suggests that metallic Cu, rich in nanograin boundaries, supports undercoordinated active sites for C–C coupling. Quantitative structure–activity correlation shows that a higher fraction of metallic Cu nanograins leads to higher C 2+ selectivity. A 7 nm Cu nanoparticle ensemble, with a unity fraction of active Cu nanograins, exhibits sixfold higher C 2+ selectivity than the 18 nm counterpart with one-third of active Cu nanograins. The correlation of multimodal operando techniques serves as a powerful platform to advance our fundamental understanding of the complex structural evolution of nanocatalysts under electrochemical conditions. By investigation of structural dynamics during the life cycle of Cu nanocatalysts, correlation of multimodal operando techniques was found to serve as a powerful platform to advance understanding of their complex structural evolution.

Background Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution. Results Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. Conclusions The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .

Single-atom catalysts offering intriguing activity and selectivity are subject of intense investigation. Understanding the nature of single-atom active site and its dynamics under working state are crucial to improving their catalytic performances. Here, we identify at atomic level a general evolution of single atom into a near-free state under electrocatalytic hydrogen evolution condition, via operando synchrotron X-ray absorption spectroscopy. We uncover that the single Pt atom tends to dynamically release from the nitrogen-carbon substrate, with the geometric structure less coordinated to support and electronic property closer to zero valence, during the reaction. Theoretical simulations support that the Pt sites with weakened Pt–support interaction and more 5 d density are the real active centers. The single-atom Pt catalyst exhibits very high hydrogen evolution activity with only 19 mV overpotential in 0.5 M H 2 SO 4 and 46 mV in 1.0 M NaOH at 10 mA cm −2 , and long-term durability in wide-pH electrolytes. Understanding the structural dynamics of single-atom site in electrochemical reactions is crucial for design of an efficient catalyst. Here, the authors develop highly active Pt single-atom electrocatalyst, and reveal the dynamic evolution of active sites by using operando synchrotron spectroscopy.

Snapshots of a phase transitionTime-resolved x-ray scattering can be used to investigate the dynamics of materials during the switch from one structural phase to another. So far, methods provide an ensemble average and may miss crucial aspects of the detailed mechanisms at play. Wall et al. used a total-scattering technique to probe the dynamics of the ultrafast insulator-to-metal transition of vanadium dioxide (VO2) (see the Perspective by Cavalleri). Femtosecond x-ray pulses provide access to the time- and momentum-resolved dynamics of the structural transition. Their results show that the photoinduced transition is of the order-disorder type, driven by an ultrafast change in the lattice potential that suddenly unlocks the vanadium atoms and yields large-amplitude uncorrelated motions, rather than occurring through a coherent displacive mechanism.Science, this issue p. 572; see also p. 525Many ultrafast solid phase transitions are treated as chemical reactions that transform the structures between two different unit cells along a reaction coordinate, but this neglects the role of disorder. Although ultrafast diffraction provides insights into atomic dynamics during such transformations, diffraction alone probes an averaged unit cell and is less sensitive to randomness in the transition pathway. Using total scattering of femtosecond x-ray pulses, we show that atomic disordering in photoexcited vanadium dioxide (VO2) is central to the transition mechanism and that, after photoexcitation, the system explores a large volume of phase space on a time scale comparable to that of a single phonon oscillation. These results overturn the current understanding of an archetypal ultrafast phase transition and provide new microscopic insights into rapid evolution toward equilibrium in photoexcited matter.

One of the key issues in supply chain sustainability is the efficient usage of the available resources. At the same time, proactive supply chain design with disruption risk considerations frequently leads to a network redundancy which implies some resource reservations in anticipation of possible disruptions.Even if resilient supply chain design has received much attention in literature, there is a research gap in designing both resilient and sustainable supply chains. This study contributes to closing the given gap by proposing a novel methodological approach to modelling network redundancy optimization. This allows for simultaneous computation of both optimal network redundancy and proactive contingency plans, considering both supply dynamics and structural disruption risks. The novelties of this study are the integration of sustainable resource utilization and SC resilience based on coordination of structure- and flow-oriented optimization. The model uncovers a practical approach to analyze and optimize supply chain redundancy by varying processing intensities of resource consumption in the network according to supply and structural dynamics. This makes it possible to explicitly include the dynamics of resource consumption for contingency plan realization in disruption scenarios.

Elementary processes associated with ionization of liquid water provide a framework for understanding radiation-matter interactions in chemistry and biology. Although numerous studies have been conducted on the dynamics of the hydrated electron, its partner arising from ionization of liquid water, H2O+, remains elusive. We used tunable femtosecond soft x-ray pulses from an x-ray free electron laser to reveal the dynamics of the valence hole created by strong-field ionization and to track the primary proton transfer reaction giving rise to the formation of OH. The isolated resonance associated with the valence hole (H2O+/OH) enabled straightforward detection. Molecular dynamics simulations revealed that the x-ray spectra are sensitive to structural dynamics at the ionization site. We found signatures of hydrated-electron dynamics in the x-ray spectrum.

The analysis of structural mobility in molecular dynamics plays a key role in data interpretation, particularly in the simulation of biomolecules. The most common mobility measures computed from simulations are the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuations (RMSF) of the structures. These are computed after the alignment of atomic coordinates in each trajectory step to a reference structure. This rigid-body alignment is not robust, in the sense that if a small portion of the structure is highly mobile, the RMSD and RMSF increase for all atoms, resulting possibly in poor quantification of the structural fluctuations and, often, to overlooking important fluctuations associated to biological function. The motivation of this work is to provide a robust measure of structural mobility that is practical, and easy to interpret. We propose a Low-Order-Value-Optimization (LOVO) strategy for the robust alignment of the least mobile substructures in a simulation. These substructures are automatically identified by the method. The algorithm consists of the iterative superposition of the fraction of structure displaying the smallest displacements. Therefore, the least mobile substructures are identified, providing a clearer picture of the overall structural fluctuations. Examples are given to illustrate the interpretative advantages of this strategy. The software for performing the alignments was named MDLovoFit and it is available as free-software at: http://leandro.iqm.unicamp.br/mdlovofit.