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Indium tin oxide (ITO) thin films have been deposited on (100) Si substrates by RF magnetron sputtering from a compact target (90% In2O3–10% SnO2 in weight) with 6 in. in diameter. In order to perform electromechanical characterizations of these films, strain gauges were fabricated. An experimental set-up based on bending beam theory was developed to determine the longitudinal piezoresistive coefficient (πl) of the strain gauges fabricated. It has been confirmed that electrical resistance of the strain gauges decreases with load increases which results a negative gauge factor. A model based on the activation energy was used to explain the origin of this negative signal. The influence of the temperature on piezoresistive properties of ITO films was also evaluated. [ABSTRACT FROM AUTHOR]

In the present work, the influence of different thermomechanical treatments in the final microstructure of a multiphase-steel (0.2%C–1.5%Mn–1.5%Si) through of morphological characterization of the transformation products was studied. The goal of this work was to investigate the volumetric fraction variation and phase distribution present in the microstructure. The steel was submitted to intercritic annealing treatment (α + γ) with and without previous reheating after the hot-rolling. The microstructure was observed by optical microscopy and mechanical properties were measured by Vickers microhardness. The results show a typical microstructure of multiphase steel (“dual-phase”) with increase of the martensite volumetric fraction and hardness values when the steel was submitted to intercritic annealing without reheating after the hot-rolling. [ABSTRACT FROM AUTHOR]

In the present work, the composition of H- 13 tool steel was modified with respect to the vanadium content to include an addition of niobium to obtain improved austenite grain size control without altering the tempering response of the steel. Optical metallography and transmission electron microscopy (TEM) observation of extraction replicas showed that the new steel had a smaller austenite grain size and a finer carbide size distribution than the vanadium steel, which indicates a higher potential toughness. [ABSTRACT FROM AUTHOR]

The occurrence of variant selection during the transformation of deformed austenite is examined, together with its effect on the product texture. A new prediction method is proposed based on the morphology of the austenite grains, on slip activity, and on the residual stresses remaining in the material after rolling. The aspect ratio of pancaked grains is demonstrated to play an important role in favoring selection of the transformed copper ({311}〈011〉 and {211}〈011〉) components. The extent of shear on active slip planes during prior rolling is shown to promote the formation of the transformed brass ({332}〈113〉 and {211}〈113〉) components. Finally, the residual stresses remaining in the material after rolling play an essential part by preventing growth of the {110}〈110〉 and {100}〈 uvw〉 orientations selected by the grain shape and slip activity rules. With the aid of these three variant selection criteria combined, it is possible to reproduce all the features of the transformation textures observed experimentally. The criteria also explain why the intensities of the transformed copper components are sensitive to the pancaking strain, while those of the transformed brass are a function of the cooling rate employed after hot rolling. [ABSTRACT FROM AUTHOR]

Cellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a substantial challenge. This heterogeneity often reflects variations in the chromatin structure, influenced by factors such as viral infections and cancer, which dramatically reshape the cellular landscape. To address the challenge of identifying distinct cell states, we developed artificial intelligence of the nucleus (AINU), a deep learning method that can identify specific nuclear signatures at the nanoscale resolution. AINU can distinguish different cell states based on the spatial arrangement of core histone H3, RNA polymerase II or DNA from super-resolution microscopy images. With only a small number of images as the training data, AINU correctly identifies human somatic cells, human-induced pluripotent stem cells, very early stage infected cells transduced with DNA herpes simplex virus type 1 and even cancer cells after appropriate retraining. Finally, using AI interpretability methods, we find that the RNA polymerase II localizations in the nucleoli aid in distinguishing human-induced pluripotent stem cells from their somatic cells. Overall, AINU coupled with super-resolution microscopy of nuclear structures provides a robust tool for the precise detection of cellular heterogeneity, with considerable potential for advancing diagnostics and therapies in regenerative medicine, virology and cancer biology., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2024.)