999 research outputs found
PPARĪ³2Pro12Ala Polymorphism and Human Health
The nuclear hormone receptor peroxisome proliferator activated receptor gamma (PPARĪ³) is an important transcription factor regulating adipocyte differentiation, lipid and glucose homeostasis, and insulin sensitivity. Numerous genetic mutations of PPARĪ³ have been identified and these mutations positively or negatively regulate insulin sensitivity. Among these, a relatively common polymorphism of PPARĪ³, Pro12Ala of PPARĪ³2, 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 PPARĪ³2 Pro12Ala polymorphism and environmental factors such as the ratio of dietary unsaturated fatty acids to saturated fatty acids and/or between the PPARĪ³2 Pro12Ala polymorphism and genetic factors such as polymorphic mutations in other genes. In addition, this polymorphic mutation in PPARĪ³2 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
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