PPARγ2Pro12Ala Polymorphism and Human Health

The nuclear hormone receptor peroxisome proliferator activated receptor gamma (PPARγ) is an important transcription factor regulating adipocyte differentiation, lipid and glucose homeostasis, and insulin sensitivity. Numerous genetic mutations of PPARγ have been identified and these mutations positively or negatively regulate insulin sensitivity. Among these, a relatively common polymorphism of PPARγ, Pro12Ala of PPARγ2, the isoform expressed only in adipose tissue has been shown to be associated with lower body mass index, enhanced insulin sensitivity, and resistance to the risk of type 2 diabetes in human subjects carrying this mutation. Subsequent studies in different ethnic populations, however, have revealed conflicting results, suggesting a complex interaction between the PPARγ2 Pro12Ala polymorphism and environmental factors such as the ratio of dietary unsaturated fatty acids to saturated fatty acids and/or between the PPARγ2 Pro12Ala polymorphism and genetic factors such as polymorphic mutations in other genes. In addition, this polymorphic mutation in PPARγ2 is associated with other aspects of human diseases, including cancers, polycystic ovary syndrome, Alzheimer disease and aging. This review will highlight findings from recent studies

Shear Viscosity of Uniform Fermi Gases with Population Imbalance

The shear viscosity plays an important role in studies of transport phenomena in ultracold Fermi gases and serves as a diagnostic of various microscopic theories. Due to the complicated phase structures of population-imbalanced Fermi gases, past works mainly focus on unpolarized Fermi gases. Here we investigate the shear viscosity of homogeneous, population-imbalanced Fermi gases with tunable attractive interactions at finite temperatures by using a pairing fluctuation theory for thermodynamical quantities and a gauge-invariant linear response theory for transport coefficients. In the unitary and BEC regimes, the shear viscosity increases with the polarization because the excess majority fermions cause gapless excitations acting like a normal fluid. In the weak BEC regime the excess fermions also suppress the noncondensed pairs at low polarization, and we found a minimum in the ratio of shear viscosity and relaxation time. To help constrain the relaxation time from linear response theory, we derive an exact relation connecting some thermodynamic quantities and transport coefficients at the mean-field level for unitary Fermi superfluids with population imbalance. An approximate relation beyond mean-field theory is proposed and only exhibits mild deviations from numerical results.Comment: 11 pages, 4 figure

SAMFlow: Eliminating Any Fragmentation in Optical Flow with Segment Anything Model

Optical Flow Estimation aims to find the 2D dense motion field between two frames. Due to the limitation of model structures and training datasets, existing methods often rely too much on local clues and ignore the integrity of objects, resulting in fragmented motion estimation. Through theoretical analysis, we find the pre-trained large vision models are helpful in optical flow estimation, and we notice that the recently famous Segment Anything Model (SAM) demonstrates a strong ability to segment complete objects, which is suitable for solving the fragmentation problem. We thus propose a solution to embed the frozen SAM image encoder into FlowFormer to enhance object perception. To address the challenge of in-depth utilizing SAM in non-segmentation tasks like optical flow estimation, we propose an Optical Flow Task-Specific Adaption scheme, including a Context Fusion Module to fuse the SAM encoder with the optical flow context encoder, and a Context Adaption Module to adapt the SAM features for optical flow task with Learned Task-Specific Embedding. Our proposed SAMFlow model reaches 0.86/2.10 clean/final EPE and 3.55/12.32 EPE/F1-all on Sintel and KITTI-15 training set, surpassing Flowformer by 8.5%/9.9% and 13.2%/16.3%. Furthermore, our model achieves state-of-the-art performance on the Sintel and KITTI-15 benchmarks, ranking #1 among all two-frame methods on Sintel clean pass

Analytic formulas for the D-mode Robinson instability

The passive superconducting harmonic cavity (PSHC) scheme is adopted by several existing and future synchrotron light source storage rings, as it has a relatively smaller R/Q and a relatively larger quality factor (Q), which can effectively reduce the beam-loading effect and suppress the mode-one instability. Based on the mode-zero Robinson instability equation of uniformly filled rigid bunches and a search algorithm for minimum, we have revealed that the PSHC fundamental mode with a large loaded-Q possibly triggers the D-mode Robinson instability [T. He, et al., Mode-zero Robinson instability in the presence of passive superconducting harmonic cavities, PRAB 26, 064403 (2023)]. This D-mode Robinson instability is unique because it is anti-damped by the radiation-damping effect. In this paper, analytical formulas for the frequency and growth rate of the D-mode Robinson instability are derived with several appropriate approximations. These analytical formulas will facilitate analyzing and understanding the D-mode Robinson instability. Most importantly, useful formulas for the D-mode threshold detuning calculation have finally been found

Instruct-NeuralTalker: Editing Audio-Driven Talking Radiance Fields with Instructions

Recent neural talking radiance field methods have shown great success in photorealistic audio-driven talking face synthesis. In this paper, we propose a novel interactive framework that utilizes human instructions to edit such implicit neural representations to achieve real-time personalized talking face generation. Given a short speech video, we first build an efficient talking radiance field, and then apply the latest conditional diffusion model for image editing based on the given instructions and guiding implicit representation optimization towards the editing target. To ensure audio-lip synchronization during the editing process, we propose an iterative dataset updating strategy and utilize a lip-edge loss to constrain changes in the lip region. We also introduce a lightweight refinement network for complementing image details and achieving controllable detail generation in the final rendered image. Our method also enables real-time rendering at up to 30FPS on consumer hardware. Multiple metrics and user verification show that our approach provides a significant improvement in rendering quality compared to state-of-the-art methods.Comment: 11 pages, 8 figure

Bunch lengthening affected by the short-range effect of resonant modes in radio-frequency cavities

Longitudinal bunch lengthening via higher harmonic cavities is essential for the new state-of-the-art 4th generation of synchrotron light storage rings, as it can effectively improve the Touschek lifetime and mitigate the transverse emittance growth due to intrabeam scattering. In general, the optimum or near-optimum bunch lengthening condition is widely adopted for the double radio-frequency system. This paper reveals, under this optimum lengthening condition, that the short-range effect of resonant modes of the main and harmonic cavities has the potential to enhance or suppress the bunch lengthening significantly. Using the planned Hefei Advanced Light Facility storage ring as an example, it is particularly demonstrated that the short-range effects of the main and harmonic fundamental modes can dramatically degrade the bunch lengthening for the assumed case of high-charge bunches. This degradation of bunch lengthening is again presented with a realistic example of PETRA-IV that operated in timing mode with high bunch charge. It is found that there exists a setting of harmonic voltage and phase quite different from the conventional optimum lengthening setting, to get optimum bunch lengthening