Abstract: The disclosure provides seals for devices that operate at elevated temperatures and have reactive metal vapors, such as lithium, sodium or magnesium. In some examples, such devices include energy storage devices that may be used within an electrical power grid or as part of a standalone system. The energy storage devices may be charged from an electricity production source for later discharge, such as when there is a demand for electrical energy consumption.

Abstract: The disclosure provides seals for devices that operate at elevated temperatures and have reactive metal vapors, such as lithium, sodium or magnesium. In some examples, such devices include energy storage devices that may be used within an electrical power grid or as part of a standalone system. The energy storage devices may be charged from an electricity production source for later discharge, such as when there is a demand for electrical energy consumption.

Abstract: The disclosure provides seals for devices that operate at elevated temperatures and have reactive metal vapors, such as lithium, sodium or magnesium. In some examples, such devices include energy storage devices that may be used within an electrical power grid or as part of a standalone system. The energy storage devices may be charged from an electricity production source for later discharge, such as when there is a demand for electrical energy consumption.

Abstract: The disclosure provides seals for devices that operate at elevated temperatures and have reactive metal vapors, such as lithium, sodium or magnesium. In some examples, such devices include energy storage devices that may be used within an electrical power grid or as part of a standalone system. The energy storage devices may be charged from an electricity production source for later discharge, such as when there is a demand for electrical energy consumption.

Abstract: A computer implemented image processing method is provided for identifying a tissue boundary of a tumor region of a tissue sample, the tissue sample containing non-tumor regions and at least one tumor region. The method includes obtaining an image of a tissue section of the tissue sample, identifying at least one image property of the image, and comparing the image property with classification data. The method further includes, based on the comparison, classifying a region of the image as a tumor region representing a tumor region in the tissue sample or a non-tumor region representing a non-tumor region in the tissue sample. If the region of the image is classified as a tumor region, the method includes identifying a boundary of the region of the image, and using the boundary to identify a tissue boundary of the tumor region of the tissue sample represented by the region of the image.

Abstract: The disclosure provides seals for devices that operate at elevated temperatures and have reactive metal vapors, such as lithium, sodium or magnesium. In some examples, such devices include energy storage devices that may be used within an electrical power grid or as part of a standalone system. The energy storage devices may be charged from an electricity production source for later discharge, such as when there is a demand for electrical energy consumption.

Abstract: A computer implemented method is provided for determining an amount of tumor cells in a tissue sample. The method includes obtaining first image data describing an image of a tissue sample at a first resolution, obtaining second image data describing the image at a second resolution, wherein the first resolution is lower than the second resolution, selecting a candidate tumor region from the second image data based on texture data determined from the first image data, identifying a tumor structure in the candidate region of the second image data, and determining a number of cells in the tumor structure based on its area and an estimate of tumor cell area to estimate an amount of tumor cells in the tissue sample.

Abstract: A computer implemented method is provided for determining an amount of tumor cells in a tissue sample. The method includes obtaining first image data describing an image of a tissue sample at a first resolution, obtaining second image data describing the image at a second resolution, wherein the first resolution is lower than the second resolution, selecting a candidate tumor region from the second image data based on texture data determined from the first image data, identifying a tumor structure in the candidate region of the second image data, and determining a number of cells in the tumor structure based on its area and an estimate of tumor cell area to estimate an amount of tumor cells in the tissue sample.

Abstract: A computer implemented image processing method is provided for identifying a tissue boundary of a tumour region of a tissue sample, the tissue sample containing non-tumour regions and at least one tumour region. The method includes obtaining an image of a tissue section of the tissue sample, identifying at least one image property of the image, and comparing the image property with classification data. The method further includes, based on the comparison, classifying a region of the image as a tumour region representing a tumour region in the tissue sample or a non-tumour region representing a non-tumour region in the tissue sample. If the region of the image is classified as a tumour region, the method includes identifying a boundary of the region of the image, and using the boundary to identify a tissue boundary of the tumour region of the tissue sample represented by the region of the image.