A deterministic approach for assessing tsunami-induced building damage through quantification of hydrodynamic forces

In certain coastal areas across the globe, tsunamis pose a great threat to buildings, infrastructure and people's lives. The prevailing approaches for assessing building damage are based on probabilistic analysis. This paper introduces a new deterministic approach to assess large-scale building damage through quantifying lateral loading on structures induced by tsunami waves. A depth-averaged hydrodynamic model is adopted to simulate tsunami propagation and inundation and calculate the induced pressures and forces on structures. The model solves the 2D nonlinear shallow water equations (SWEs) using a finite volume shock-capturing numerical scheme and is implemented on Graphics Processing Units (GPUs) to achieve high-performance computing for large-scale applications. A new model component is included to calculate pressures and forces using the predicted flow variables, i.e. water depth and velocities. The resulting maximum tsunami forces are combined with a lateral force resisting system on each building to estimate damage states. This new approach is developed by taking advantages of a similar damage assessment method and the corresponding coefficients for quantifying earthquake impact on buildings, due to the similarity between the horizontal force systems induced by tsunami waves and earthquake motions. After being successfully validated against three experimental cases related to flow hydrodynamics, pressures and forces, the model is used to simulate a hypothetical 1000-year tsunami event in the City of Seaside, Oregon, USA. The resulting damage states are then classified for each of the urban buildings in the area, taking into account different building types. The predicted results are consistent with those obtained using alternative approaches, confirming the potential of the proposed approach for practical engineering applications

Electron–Phonon Coupling in Suspended Graphene: Supercollisions by Ripples

Using electrical transport experiments and shot noise thermometry, we find strong evidence that “supercollision” scattering processes by flexural modes are the dominant electron–phonon energy transfer mechanism in high-quality, suspended graphene around room temperature. The power law dependence of the electron–phonon coupling changes from cubic to quintic with temperature. The change of the temperature exponent by two is reflected in the quadratic dependence on chemical potential, which is an inherent feature of two-phonon quantum processes

Appendix A. Descriptions and photographs of morphological characteristics of beach grasses and their typical foredune shape, taken from field data across the Pacific Northwest coastal foredunes (for Elymus mollis, Ammophila breviligulata, and Ammophila arenaria).

Descriptions and photographs of morphological characteristics of beach grasses and their typical foredune shape, taken from field data across the Pacific Northwest coastal foredunes (for Elymus mollis, Ammophila breviligulata, and Ammophila arenaria)

Appendix B. Additional information about the wind tunnel experimental design, including the tunnel diagram, and photographs of one replicate set of beach grass species and density experimental units.

Additional information about the wind tunnel experimental design, including the tunnel diagram, and photographs of one replicate set of beach grass species and density experimental units

Higher percentage of SARS-CoV-2 Spike-reactive memory B cells are detected in the extended booster group.

Percentage of Spike-reactive memory B cells were determined by flow cytometry. A) Example pre-bleed (baseline) PBMC staining for SARS-CoV-2 naïve individual. B) Example post 2nd vaccine PBMC staining for SARS-CoV-2 naïve individual. Example of full flow analysis shown if S1A Fig. C) Percentage Spike-reactive memory B cells at baseline and post 2nd vaccine were determined by flow cytometry. Previously infected individuals shown in red/grey. Extended and short interval groups shown with triangle and circle symbols, respectively. D’Agostino and Pearson tests were performed to determine normality. Based on this result, differences between groups were assessed using a Brown-Forsythe ANOVA test with Dunnett’s T3 multiple comparisons post hoc. ns P > 0.05, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001 and **** P ≤ 0.0001. D) Percentage of IgG, IgM or other Spike-reactive memory B cells for each vaccine group. E) Correlation between Spike IgG ED50 and percentage of Spike-reactive memory B cells. F) Correlation between ID50 against Wuhan-1 pseudotyped virus and percentage of Spike-reactive memory B cells. (Spearman’s correlation, r; a linear regression was used to calculate the goodness of fit, r2).</p

SARS-CoV-2 Spike-reactive memory B cells measured before and after vaccination.

A) Example FACS gating for pre-vaccination sample (baseline) and from post-vaccination sample (post 2nd) from SARS-CoV-2 naïve individual. B) Frequency of memory B cells in the total B cell population at baseline and post 2nd vaccine for matched donors. (TIF)</p

Neutralization against omicron sub-lineages following 3 vaccine doses and/or BA.1/BA.2 breakthrough infection.

Neutralization breadth and potency was measured against D614G, BA.1, BA.2 and BA.4/BA.5. Analysis of sera collected A) 3-weeks post 3rd BNT162b2 vaccine dose (post 3rd), B) 6-months post 3rd vaccine (6m-post 3rd) and C) following breakthrough infection (post-BTI) (presumed to be BA.1 or BA.2). D) Comparison of titres 3-weeks (post 3rd) and 6-months post 3rd boost (6m-post 3rd). E) Comparison of titres 3-weeks post 3rd boost (post 3rd) and following BTI (post-BTI). Samples from a single individual are joined. Short and long booster groups shown with circle and triangle symbols, respectively. Individuals infected with SARS-CoV-2 prior to vaccination are shaded grey. Based on this result, multiple Mann-Whitney tests or unpaired t tests using a two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli were employed to determine significance between groups. ns P > 0.05, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001 and **** P ≤ 0.0001.</p

Teaching open and reproducible scholarship: a critical review of the evidence base for current pedagogical methods and their outcomes

In recent years, the scientific community has called for improvements in the credibility, robustness and reproducibility of research, characterized by increased interest and promotion of open and transparent research practices. While progress has been positive, there is a lack of consideration about how this approach can be embedded into undergraduate and postgraduate research training. Specifically, a critical overview of the literature which investigates how integrating open and reproducible science may influence student outcomes is needed. In this paper, we provide the first critical review of literature surrounding the integration of open and reproducible scholarship into teaching and learning and its associated outcomes in students. Our review highlighted how embedding open and reproducible scholarship appears to be associated with (i) students' scientific literacies (i.e. students’ understanding of open research, consumption of science and the development of transferable skills); (ii) student engagement (i.e. motivation and engagement with learning, collaboration and engagement in open research) and (iii) students' attitudes towards science (i.e. trust in science and confidence in research findings). However, our review also identified a need for more robust and rigorous methods within pedagogical research, including more interventional and experimental evaluations of teaching practice. We discuss implications for teaching and learning scholarship.</p