Photodarkening of amorphous selenium under high pressure

The photodarkening phenomena of amorphous Se have been studied by the optical absorption coefficient, sound velocity and attenuation measurements. The light illumination at low temperatures induces the photodarkening, and the photodarkened state is completely recovered by annealing near 306 K corresponding to the glass transition temperature. The photodarkening is enhanced by application of pressure. The sound velocity decreases and the sound attenuation increases by the illumination at low temperature. These suggest that a structural disorder increases in the photodarkened state. Three stages are observed for the recovery process of the photodarkened specimen. The photodarkening and the recovery process are discussed on the basis of VAP (valence alternative pair) model.<br /

A Study on the Elasto-plastical Constitutive Equation for Unsaturated Soil

In this paper, first, an elasto-plastic consitituve equation for unsaturated soil was developed by considering of the basically behavior of unsaturated soil. Second, the results of a number of triaxial test and a set of rigid foundation model tests were simulated by using this constitutive equation, the agreement between observed and computed results was satisfactory and confirms the possibilities of this constitutive equation

The dihydropyridine calcium channel blocker benidipine prevents lysophosphatidylcholine-induced endothelial dysfunction in rat aorta

<p>Abstract</p> <p>Background</p> <p>Lysophosphatidylcholine (LPC), an atherogenic component of oxidized low-density lipoprotein, has been shown to induce the attenuation of endothelium-dependent vascular relaxation. Although benidipine, a dihydropyridine-calcium channel blocker, is known to have endothelial protective effects, the effects of benidipine on LPC-induced endothelial dysfunction remain unknown. We examined the effects of benidipine on the impairment of endothelium-dependent relaxation induced by LPC.</p> <p>Methods</p> <p>Benidipine was administered orally to rats and aortas were then isolated. Aortic rings were treated with LPC and endothelial functions were then evaluated. Additionally, the effects of benidipine on intracellular calcium concentration ([Ca²⁺]_i) and membrane fluidity altered by LPC in primary cultured rat aortic endothelial cells were examined. [Ca²⁺]_iwas measured using the fluorescent calcium indicator fura-2. Membrane fluidity was monitored by measuring fluorescence recovery after photobleaching.</p> <p>Results</p> <p>Treatment with LPC impaired endothelial function. Benidipine prevents the impairment of relaxation induced by LPC. Acetylcholine elicited an increase in [Ca²⁺]_iin fura-2 loaded endothelial cells. The increase in [Ca²⁺]_iwas suppressed after exposure to LPC. Plasma membrane fluidity increased following incubation with LPC. Benidipine inhibited the LPC-induced increase in membrane fluidity and impairment of increase in [Ca²⁺]_i.</p> <p>Conclusion</p> <p>These results suggest that benidipine inhibited LPC-induced endothelial dysfunction by maintaining increase in [Ca²⁺]_i. Benidipine possesses membrane stabilization properties in LPC-treated endothelial cells. It is speculated that the preservation of membrane fluidity by benidipine may play a role in the retainment of calcium mobilization. The present findings may provide new insights into the endothelial protective effects of benidipine.</p

Scale dependant layer for self-supervised nuclei encoding

Recent developments in self-supervised learning give us the possibility to further reduce human intervention in multi-step pipelines where the focus evolves around particular objects of interest. In the present paper, the focus lays in the nuclei in histopathology images. In particular we aim at extracting cellular information in an unsupervised manner for a downstream task. As nuclei present themselves in a variety of sizes, we propose a new Scale-dependant convolutional layer to bypass scaling issues when resizing nuclei. On three nuclei datasets, we benchmark the following methods: handcrafted, pre-trained ResNet, supervised ResNet and self-supervised features. We show that the proposed convolution layer boosts performance and that this layer combined with Barlows-Twins allows for better nuclei encoding compared to the supervised paradigm in the low sample setting and outperforms all other proposed unsupervised methods. In addition, we extend the existing TNBC dataset to incorporate nuclei class annotation in order to enrich and publicly release a small sample setting dataset for nuclei segmentation and classification.Comment: 13 pages, 6 figures, 2 table