Transmission area and two-photon correlated imaging

The relationship between transmission area of an object imaged and the visibility of its image is investigated in a lensless system. We show that the changes of the visibility are quite different when the transmission area is varied by different manners. An increase of the transmission by adding the slit number leads to a decrease of the visibility. While, the change is adverse when the slit width is widened for a given distance between two slits.Comment: 10 pages, 4 figure

HCO3- transport through anoctamin/transmembrane protein ANO1/TMEM16A, in pancreatic acinar cells, regulates luminal pH

The identification of ANO1/TMEM16A as the likely calcium-dependent chloride channel of exocrine glands has led to a more detailed understanding of its biophysical properties. This includes a calcium-dependent change in channel selectivity and evidence that HCO3-permeability can be significant. Here we use freshly isolated pancreatic acini that preserve the luminal structure to measure intraluminal pH and test the idea that ANO1/TMEM16A contributes to luminal pH balance. Our data show that, under physiologically relevant stimulation with 10 pm cholesystokinin, the luminal acid load that results from the exocytic fusion of zymogen granules is significantly blunted by HCO3-buffer in comparison with HEPES, and that this is blocked by the specific TMEM16A inhibitor T16inh-A01. Furthermore, in a model of acute pancreatitis, we observed substantive luminal acidification and provide evidence that ANO1/TMEM16A acts to attenuate this pH shift. We conclude that ANO1/TMEM16A is a significant pathway in pancreatic acinar cells for HCO3-secretion into the lumen

Sub-wavelength Coherent Imaging of a Pure-Phase Object with Thermal Light

We report, for the first time, the observation of sub-wavelength coherent image of a pure phase object with thermal light,which represents an accurate Fourier transform. We demonstrate that ghost-imaging scheme (GI) retrieves amplitude transmittance knowledge of objects rather than the transmitted intensities as the HBT-type imaging scheme does.Comment: 5 pages, 4 figures; Any comments pls. contact: [email protected]

Placement Distance of Exit Advance Guide Sign on an Eight-Lane Expressway Considering Lane Changing Behaviour in China

The reasonable placement of the advance guide signs (AGSs) is important in improving driving efficiency and safety when exiting an expressway. By analysing the lane-changing process when approaching an exit on new two-way eight-lane expressways, we modified the tradi-tional AGS model lane-change distance formula. To this end, a field experiment was designed to explore the lane-change traversal time at the free flow condition (LOS 1). Considering the limitations of the experimental equip-ment, lane change distance at the worst levels of service was explored using VISSIM simulation. The results show that the eight-lane changing distance based on modified theoretical calculations, revealed a minor difference with VISSIM simulation in free flow condition. Further-more, placement distance at the worst levels of service are discussed. Then placement distance of all-level AGSs is recommended to be 3 km, 2 km, 1.2 km, and 0.8 km, considering the driver\u27s short-term memory attenuation calculation formula. Determining the two-way eight-lane AGS placement distance from the perspective of LOS can provide a basis on which to supplement the existing stan-dards and references for the AGS placement distance af-ter the expressway expansion in China

Combating Representation Learning Disparity with Geometric Harmonization

Self-supervised learning (SSL) as an effective paradigm of representation learning has achieved tremendous success on various curated datasets in diverse scenarios. Nevertheless, when facing the long-tailed distribution in real-world applications, it is still hard for existing methods to capture transferable and robust representation. Conventional SSL methods, pursuing sample-level uniformity, easily leads to representation learning disparity where head classes dominate the feature regime but tail classes passively collapse. To address this problem, we propose a novel Geometric Harmonization (GH) method to encourage category-level uniformity in representation learning, which is more benign to the minority and almost does not hurt the majority under long-tailed distribution. Specially, GH measures the population statistics of the embedding space on top of self-supervised learning, and then infer an fine-grained instance-wise calibration to constrain the space expansion of head classes and avoid the passive collapse of tail classes. Our proposal does not alter the setting of SSL and can be easily integrated into existing methods in a low-cost manner. Extensive results on a range of benchmark datasets show the effectiveness of GH with high tolerance to the distribution skewness. Our code is available at https://github.com/MediaBrain-SJTU/Geometric-Harmonization.Comment: Accepted to NeurIPS 2023 (spotlight