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This paper presents a new fatigue damage detection and monitoring approach using a geometry-informed implementation of phase space warping (PSW). The proposed method is based on continuous-time PSW theory and geometric constructs, which clarifies the relationship between the deformation of the reconstructed phase flow and the underlying damage evolution. A discrete-time approximation to the continuous-time theory is established for practical applications. The practical geometry-informed PSW (GIPSW) algorithm is developed with integrated geometry-informed heuristics and global sensitivity analysis to monitor fatigue damage evolution accurately. The proposed method is validated through numerical experiments simulating nonlinear systems with varying fatigue damage dynamics, exhibiting distinct response complexities. The results show that the GIPSW improves the monitoring accuracy by at least 41.4% and can achieve maximally four-orders-of-magnitude-lower monitoring error compared with the conventional PSW algorithm. The GIPSW is also applied in physical experiments exploring raster-angle-affected fatigue damage dynamics in 3D-printed materials. The estimated hidden-fatigue damage-time history reveals distinct crack propagation rates differentiated by the raster angles and can be used for damage prognosis and modeling the fatigue mechanisms. The critical inflection points identified in the incremental damage-time histories detect the crack growth phase transitions as early as 0.17 of the total time to failure, which can be used for early damage awareness.

 

Abstract We conducted a mesocosm experiment to examine how ocean acidification (OA) affects communities of prokaryotes and eukaryotes growing on single‐use drinking bottles in subtropical eutrophic waters of the East China Sea. Based on 16S rDNA gene sequencing, simulated high CO 2 significantly altered the prokaryotic community, with the relative abundance of the phylum Planctomycetota increasing by 49%. Under high CO 2 , prokaryotes in the plastisphere had enhanced nitrogen dissimilation and ureolysis, raising the possibility that OA may modify nutrient cycling in subtropical eutrophic waters. The relative abundance of pathogenic and animal parasite bacteria also increased under simulated high CO 2 . Our results show that elevated CO 2 levels significantly affected several animal taxa based on 18S rDNA gene sequencing. For example, Mayorella amoebae were highly resistant, whereas Labyrinthula were sensitive to OA. Thus, OA may alter plastisphere food chains in subtropical eutrophic waters. 

Sickle cell disease is induced by a mutation that converts normal adult hemoglobin to sickle hemoglobin (HbS) and engenders intracellular polymerization of deoxy-HbS and erythrocyte sickling. Development of anti-sickling therapies requires quantitative understanding of HbS polymerization kinetics under organ-specific conditions, which are difficult to assess with existing experimental techniques. Thus, we developed a kinetic model based on the classical nucleation theory to examine the effectiveness of potential anti-sickling drug candidates. We validated this model by comparing its predictability against prior in vivo and in vitro experimental results. We used the model to quantify the efficacy of sickling inhibitors and obtain results consistent with recent screening assays. Global sensitivity analysis on the kinetic parameters in the model revealed that the solubility, nucleation rate prefactor, and oxygen affinity are quantities that dictate HbS polymerization. This finding provides quantitative guidelines for the discovery of intracellular processes to be targeted by sickling inhibitors.