Exploration of stable compounds, crystal structures, and superconductivity in the Be-H system

Using first-principles variable-composition evolutionary methodology, we explored the high-pressure structures of beryllium hydrides between 0 and 400 GPa. We found that BeH$_2$ remains the only stable compound in this pressure range. The pressure-induced transformations are predicted as $Ibam$ $\rightarrow$ $P\bar{3}m1$ $\rightarrow$ $R\bar{3}m$ $\rightarrow$ $Cmcm$ $\rightarrow$ $P4/nmm$, which occur at 24, 139, 204 and 349 GPa, respectively. $P\bar{3}m1$ and $R\bar{3}m$ structures are layered polytypes based on close packings of H atoms with Be atoms filling octahedral voids in alternating layers. $Cmcm$ and $P4/nmm$ structures have 3D-networks of strong bonds, but also feature rectanular and squre, respectively, layers of H atoms with short H-H distances. $P\bar{3}m1$ and $R\bar{3}m$ are semiconductors while $Cmcm$ and $P4/nmm$ are metallic. We have explored superconductivity of both metallic phases, and found large electron-phonon coupling parameters of $\lambda$=0.63 for $Cmcm$ (resulting in a $T_c$ of 32.1-44.1 K) at 250 GPa and $\lambda$=0.65 for $P4/nmm$ ($T_c$ = 46.1-62.4 K) at 400 GPa. The dependence of $T_c$ on pressure indicates that $T_c$ initially increases to a maximum of 45.1 K for $Cmcm$ at 275 GPa and 97.0 K for $P4/nmm$ at 365 GPa, and then decreases with increasing pressure for both phases

Multi-photon Nonlinear Fluorescence Emission in Upconversion Nanoparticles for Super-Resolution Imaging

University of Technology Sydney. Faculty of Science.Due to the unique optical properties gained by converting near-infrared light to shorter wavelength emissions, upconversion nanoparticles (UCNPs) have attracted considerable interest. Their superior features, including their multi-wavelength emissions, optical uniformity, background suppression, photostability and deep penetration depth through the tissue, make them extremely suitable for biological and biomedical applications. By taking advantage of their multi-photon nonlinear emissions in UNCPs, the goal of this thesis is to develop UCNPs-based super-resolution microscopy methods to address the challenges currently facing nanoscopy, for instance complexity, stability, limited penetration through the tissue and low throughput. The methods being investigated in this thesis make concrete the specific advantages in terms of image depth, speed, overall quality, and multiplexing potentials. To unlock a new mode of deep tissue super-resolution imaging, I first developed the near-infrared emission saturation (NIRES) nanoscopy by taking advantage of near-infrared-in and near-infrared-out optical nonlinear response curve from a single upconversion nanoparticle. This approach only requires two orders of magnitude that are lower than the excitation intensity, which is generally required for conventional multi-photon dyes. This work achieves a super-resolution of sub 50 nm, less than 1/20ᵗʰ of the excitation wavelength, and can image single UCNP through a 93 μm thick liver tissue. To improve the overall imaging quality and simplify the system setups, I further exploited the distinct nonlinear photon response curves from the two emission bands in UCNP, and explored an opportunity for a tightly focused doughnut excitation to generate distinct spectral dependent point speared functions (PSFs). With controllable PSFs from multi-channel emissions by the excitation power density, this work presents the possibility of achieving super-resolution imaging under saturated fluorescence excitation via PSF engineering. Moreover, I developed a multicolour Fourier fusion algorithm to enlarge the optical system's frequency shifting ability, and yield an enhanced imaging quality at a higher imaging speed. By realising the uniform and distinct nonlinear emission curves from different nanoparticles, this work posits a new optical encoding dimension for multiplexing imaging. Proposed here is a robust PSF engineering strategy to extract emitter properties. This work extends the multiplexing capacity of UCNPs and offers new opportunities for their applications. These methods are my contributions to the search for a stable, viable, and multifunctional optical imaging modality for the nanoscale context

On the Treves theorem for the AKNS equation

According to a theorem of Treves, the conserved functionals of the AKNS equation vanish on all pairs of formal Laurent series of a specified form, both of them with a pole of the first order. We propose a new and very simple proof for this statement, based on the theory of B\"acklund transformations; using the same method, we prove that the AKNS conserved functionals vanish on other pairs of Laurent series. The spirit is the same of our previous paper on the Treves theorem for the KdV, with some non trivial technical differences.Comment: LaTeX, 16 page

Self-evolving ghost imaging

Funding Australian Research Council (DE200100074, DP190101058); China Scholarship Council (201607950009, 201706020170); University of Technology Sydney. Acknowledgment We thank Prof. Fengli Gao from Jilin University for the helpful discussion about PGPeer reviewedPublisher PD

UMIFormer: Mining the Correlations between Similar Tokens for Multi-View 3D Reconstruction

In recent years, many video tasks have achieved breakthroughs by utilizing the vision transformer and establishing spatial-temporal decoupling for feature extraction. Although multi-view 3D reconstruction also faces multiple images as input, it cannot immediately inherit their success due to completely ambiguous associations between unstructured views. There is not usable prior relationship, which is similar to the temporally-coherence property in a video. To solve this problem, we propose a novel transformer network for Unstructured Multiple Images (UMIFormer). It exploits transformer blocks for decoupled intra-view encoding and designed blocks for token rectification that mine the correlation between similar tokens from different views to achieve decoupled inter-view encoding. Afterward, all tokens acquired from various branches are compressed into a fixed-size compact representation while preserving rich information for reconstruction by leveraging the similarities between tokens. We empirically demonstrate on ShapeNet and confirm that our decoupled learning method is adaptable for unstructured multiple images. Meanwhile, the experiments also verify our model outperforms existing SOTA methods by a large margin. Code will be available at https://github.com/GaryZhu1996/UMIFormer.Comment: Accepted by ICCV 202

Self-evolving ghost imaging

Ghost imaging can capture 2D images with a point detector instead of an array sensor. It therefore offers a solution to the challenge of building area format sensors in wavebands where such sensors are difficult and expensive to produce and opens up new imaging modalities due to high-performance single-pixel detectors. Traditionally, ghost imaging retrieves the image of an object offline, by correlating measured light intensities and applied illuminating patterns. Here we present a feedback-based approach for online updating of the imaging result that can bypass post-processing, termed self-evolving ghost imaging (SEGI). We introduce a genetic algorithm to optimize the illumination patterns in real-time to match the objects shape according to the measured total light intensity. We theoretically and experimentally demonstrate this concept for static and dynamic imaging. This method opens new perspectives for real-time ghost imaging in applications such as remote sensing (e.g. machine vision, LiDAR systems in autonomous vehicles) and biological imaging

High-resolution sea-level fluctuations during the Mid-Holocene in the Ningshao Coastal Plain region, eastern China

Sea level changes during the Mid-Holocene directly influenced the Neolithic culture in the Yangtze River Delta region (YRD). However, the high-resolution sea level change characteristics for this period remain unclear. In this study, we performed a high-resolution palynological analysis, including pollen, Dinoflagellate cysts, and Foraminiferal organic linings, using a high-resolution sediment core from Shanglin Lake, in the North of Ningshao Plain (the south of Hangzhou Bay). 11 accelerator mass spectrometry 14C(AMS) datings indicate the age of the sediments range from 8 cal ka B.P. to 5.6 cal ka B.P. The results show that during the Mid-Holocene, Shanglin Lake evolved from an estuary – subtidal lagoon – semi-enclosed bay – semi-enclosed lagoon – semi-enclosed bay – enclosed lagoon to a modern freshwater lake. There was a period of no, or minimal, eustatic sea-level rise between 7733 and 7585 cal yr B.P. The Mid-Holocene high sea level comes in 7253–7082 cal yr BP. Between 7000 cal yr BP and 5502 cal yr BP, the sea level is close to modern value. The sea level change during this period had a significant impact on the local Neolithic human activity

Canonical explicit B\"{a}cklund transformations with spectrality for constrained flows of soliton hierarchies

It is shown that explicit B\"{a}cklund transformations (BTs) for the high-order constrained flows of soliton hierarchy can be constructed via their Darboux transformations and Lax representation, and these BTs are canonical transformations including B\"{a}cklund parameter $\eta$ and possess a spectrality property with respect to $\eta$ and the 'conjugated' variable $\mu$ for which the pair $(\eta, \mu)$ lies on the spectral curve. As model we present the canonical explicit BTs with the spectrality for high-order constrained flows of the Kaup-Newell hierarchy and the KdV hierarchy.Comment: 21 pages, Latex, to be published in "PHYSICA A

Association between oxidative balance score and kidney stone in United States adults: analysis from NHANES 2007-2018

Purpose: To investigate the relationship between the Oxidative Balance Score (OBS) and kidney stone risk using NHANES 2007-2018 data, and to explore potential mechanisms and population-specific effects.Materials and methods: Data from the NHANES 2007-2018 were analyzed. OBS was calculated based on 16 dietary components and 4 lifestyle components. Multivariate logistic regression was employed to investigate the relationship between OBS and kidney stone. Further stratified analyses were conducted to examine the associations across different subgroups.Results: A total of 19,799 participants were included in the study. There was a consistent inverse association between OBS and the risk of kidney stones (OR = 0.97; 95% CI: 0.96–0.99). After dividing the participants into quartiles based on OBS, compared to the lowest quartile of OBS, the risk of kidney stones in the highest quartile of OBS was reduced by 33% (95% CI 0.50–0.89; p = 0.002). This association was consistent across both dietary and lifestyle OBS scores. The protective effect of OBS was notably pronounced among Non-Hispanic white and Other race groups, and among individuals with a higher level of education. However, the association was not significant among individuals with diabetes.Conclusion: A higher OBS, indicating a balance skewed towards antioxidants, is associated with a reduced risk of kidney stones, especially among specific population subgroups. These findings underscore the potential role of oxidative balance in kidney stone pathogenesis and highlight the importance of considering individual and population-specific factors in future research and preventive strategies