Carrying the Longings

The objective of this paper is to reveal the origin and evolution of the work I have made, thereby establishing the foundation for my future practice. The core purpose of my work is to provoke introspection and to question, if not reverse, entrenched and stereotypical assumptions toward women. I derive inspiration from my confrontational relationship with my mother, who is a prominent female figure in my life. Our confrontations arise from our differing perspectives and beliefs regarding the roles and aspirations of women. These unpleasant confrontations are the origin of my practice, which is based on questioning assumptions and norms that affect my life. Ultimately, my work aims to build connections with those who have similar struggles to mine and advocate for women\u27s autonomy

Overturn of ilmenite‐bearing cumulates in a rheologically weak lunar mantle

©2019. American Geophysical UnionThe crystallization of the lunar magma ocean (LMO) determines the initial structure of the solid Moon. Near the end of the LMO crystallization, ilmenite‐bearing cumulates (IBC) form beneath the plagioclase crust. Being denser than the underlying mantle, IBC are prone to overturn, a hypothesis that explains several aspects of the Moon's evolution. Yet the formation of stagnant lid due to the temperature dependence of viscosity can easily prevent IBC from sinking. To infer the rheological conditions allowing IBC to sink, we calculated the LMO crystallization sequence and performed high‐resolution numerical simulations of the overturn dynamics. We assumed a diffusion creep rheology and tested the effects of reference viscosity, activation energy, and compositional viscosity contrast between IBC and mantle. The overturn strongly depends on reference viscosity and activation energy and is facilitated by a low IBC viscosity. For a reference viscosity of 1021 Pa s, characteristic of a dry rheology, IBC overturn cannot take place. For a reference viscosity of 1020 Pa s, the overturn is possible if the activation energy is a factor of 2–3 lower than the values typically assumed for dry olivine. These low activation energies suggest a role for dislocation creep. For lower‐reference viscosities associated with the presence of water or trapped melt, more than 95% IBC can sink regardless of the activation energy. Scaling laws for Rayleigh‐Taylor instability confirmed these results but also showed the need of numerical simulations to accurately quantify the overturn dynamics. Whenever IBC sink, the overturn occurs via small‐scale diapirs

Confounder Balancing in Adversarial Domain Adaptation for Pre-Trained Large Models Fine-Tuning

The excellent generalization, contextual learning, and emergence abilities in the pre-trained large models (PLMs) handle specific tasks without direct training data, making them the better foundation models in the adversarial domain adaptation (ADA) methods to transfer knowledge learned from the source domain to target domains. However, existing ADA methods fail to account for the confounder properly, which is the root cause of the source data distribution that differs from the target domains. This study proposes an adversarial domain adaptation with confounder balancing for PLMs fine-tuning (ADA-CBF). The ADA-CBF includes a PLM as the foundation model for a feature extractor, a domain classifier and a confounder classifier, and they are jointly trained with an adversarial loss. This loss is designed to improve the domain-invariant representation learning by diluting the discrimination in the domain classifier. At the same time, the adversarial loss also balances the confounder distribution among source and unmeasured domains in training. Compared to existing ADA methods, ADA-CBF can correctly identify confounders in domain-invariant features, thereby eliminating the confounder biases in the extracted features from PLMs. The confounder classifier in ADA-CBF is designed as a plug-and-play and can be applied in the confounder measurable, unmeasurable, or partially measurable environments. Empirical results on natural language processing and computer vision downstream tasks show that ADA-CBF outperforms the newest GPT-4, LLaMA2, ViT and ADA methods

Comparative analysis and characterization of the gut microbiota of four farmed snakes from southern China

Background The gut microbiota plays an important role in host immunity and metabolic homeostasis. Although analyses of gut microbiotas have been used to assess host health and foster disease prevention and treatment, no comparative comprehensive study, assessing gut microbiotas among several species of farmed snake, is yet available. In this study, we characterized and compared the gut microbiotas of four species of farmed snakes (Naja atra, Ptyas mucosa, Elaphe carinata, and Deinagkistrodon acutus) using high-throughput sequencing of the 16S rDNA gene in southern China and tested whether there was a relationship between gut microbiotal composition and host species. Results A total of 629 operational taxonomic units across 22 samples were detected. The five most abundant phyla were Bacteroidetes, Proteobacteria, Firmicutes, Fusobacteria, and Actinobacteria, while the five most abundant genera were Bacteroides, Cetobacterium, Clostridium, Plesiomonas, and Paeniclostridium. This was the first report of the dominance of Fusobacteria and Cetobacterium in the snake gut. Our phylogenetic analysis recovered a relatively close relationship between Fusobacteria and Bacteroidetes. Alpha diversity analysis indicated that species richness and diversity were highest in the gut microbiota of D. acutus and lowest in that of E. carinata. Significant differences in alpha diversity were detected among the four farmed snake species. The gut microbiotas of conspecifics were more similar to each other than to those of heterospecifics. Conclusion This study provides the first comparative study of gut microbiotas among several species of farmed snakes, and provides valuable data for the management of farmed snakes. In farmed snakes, host species affected the species composition and diversity of the gut microbiota

Integrating light-sheet imaging with virtual reality to recapitulate developmental cardiac mechanics

Currently, there is a limited ability to interactively study developmental cardiac mechanics and physiology. We therefore combined light-sheet fluorescence microscopy (LSFM) with virtual reality (VR) to provide a hybrid platform for 3D architecture and time-dependent cardiac contractile function characterization. By taking advantage of the rapid acquisition, high axial resolution, low phototoxicity, and high fidelity in 3D and 4D (3D spatial + 1D time or spectra), this VR-LSFM hybrid methodology enables interactive visualization and quantification otherwise not available by conventional methods, such as routine optical microscopes. We hereby demonstrate multiscale applicability of VR-LSFM to (a) interrogate skin fibroblasts interacting with a hyaluronic acid–based hydrogel, (b) navigate through the endocardial trabecular network during zebrafish development, and (c) localize gene therapy-mediated potassium channel expression in adult murine hearts. We further combined our batch intensity normalized segmentation algorithm with deformable image registration to interface a VR environment with imaging computation for the analysis of cardiac contraction. Thus, the VR-LSFM hybrid platform demonstrates an efficient and robust framework for creating a user-directed microenvironment in which we uncovered developmental cardiac mechanics and physiology with high spatiotemporal resolution

Numerical modeling on scratch and mar induced damages in polymeric systems

The barrel mar behavior, scratch induced delamination, and temperature-dependent scratch behavior were investigated in this dissertation via FEM modeling. The experimental tests were carried out according to ASTM/ISO standard to validate the FEM model. Three amorphous polymers PMMA, PC, and PS were employed to study the barrel mar behavior. By comparison to experimental results, the numerical analysis showed that the maximum plastic principal strain and total dissipated plastic energy can be considered for evaluating mar visibility resistance. Higher mar visibility resistance corresponds to lower maximum plastic principal strain and dissipated plastic energy values. Based on these two criteria, the parametric analysis shows that mar visibility resistance increases with lower modulus, higher yield stress, higher hardening slope, and lower softening slope. The FEA analysis to compare the delamination resistance of two semi-rigid PET-based laminates was conducted. The results show that the maximum principal stress distribution at the interface correlates well with the scratch-induced delamination behavior. A followed study was performed to validate the semi-quantitative FEM modeling approach with the double-layer epoxy-based polymeric coatings. The parametric yield stress study in both top and base layers revealed the delamination at the interface could initiate either from the scratch shoulder or behind the scratch tip. A FEM modeling methodology to quantitatively predict the temperature-dependent scratch behavior of amorphous polymers was proposed with the following theories. The Arruda-Boyce viscoplastic model is utilized to account for temperature and strain rate dependent strain-softening and strain-hardening behaviors. The post-yield behavior predicted in this model is calibrated using the yield point determined by the Richeton cooperative model. The pressure dependent Drucker-Prager model with calibrated post-yield experimental data at various strain rates is chosen as the plastic constitutive relationship of the polymeric systems for FEM simulation. Furthermore, temperature and pressure dependent frictional behavior is input into an ABAQUS contact model to simulate the variation of the adhesion coefficient of friction. The FEM simulation findings show a good agreement with the experimentally determined scratch depth and scratch coefficient of friction (SCOF) measured using the scratch test