Abstract: A protected blood collection tube. The protected blood collection tube and sample includes a breakable inner container and an outer protective body. The inner container can receive a sample for applications such as biomedical, health care, dentistry, agricultural, industrial, and veterinary. The inner container can be received into the outer protective body for protection. A lid secures over the inner container forming a seal to prevent leakage and contamination of the sample or inner container contents. The outer protective body is breakage-resistant for protection if the protected blood collection tube is dropped.

Abstract: An apparatus with a corresponding method and computer program product are provided. The apparatus includes at least one processor; and at least one non-transitory memory including computer program code: wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform the steps (1600) of train or finetune at least one neural network (NN) based at least on a temporal persistence scope; and encode or decode one or more media frames elements based at least on the trained or finetuned at least one neural network. A further apparatus with a corresponding method and computer program product are provided.

Abstract: An example method includes: receiving an input extended block comprising an input block and input margins, wherein the input block is derived from an image or a video frame, and wherein the input block and the input margins are input to a filter, and wherein the input margins comprise pixels of the image or the video frame; filtering the input extended block to obtain a filtered extended block comprising a filtered block and filtered margins; receiving other blocks, wherein the other blocks are derived from the image or video frame, and wherein at least one pixel of the other blocks overlaps with at least one pixel of the filtered margins of the filtered extended block; and blending the filtered extended block with the other blocks, wherein an operation to blend the filtered extended block with the other blocks is applied to two or more overlapping pixels

Abstract: Various embodiments provide an apparatus, a method, and a computer program product. An example method includes determining one or more quantization parameters (quantizers) based at least on one or more of the following: a mean absolute value computed based on a set of parameters of a neural network comprising a parameter; a maximum absolute value computed based on a set of activations of the neural network comprising an activation; a number of parameters in the set of parameters of the neural network comprising the parameter; or a maximum absolute value computed based on an output value computed based on the parameter and the activation; and quantizing at least one of the parameter or the activation based at least on the one or more quantization parameters.

Abstract: Intra-prediction modes are defined in that, predictions obtained in accordance with those modes are based on a sum of a first component dependent on a set of reference samples and a second component not dependent on the reference samples.

Abstract: A device for protecting an inner container and the sample or contents in the inner container. The device for protecting an inner container and sample includes an inner container and an outer protective body. The inner container can receive a sample for applications such as biomedical, health care, dentistry, agricultural, industrial, and veterinary. The inner container can be received into the outer protective body for protection. A lid secures over the inner container forming a seal to prevent leakage and contamination of the sample or inner container contents. The outer protective body is breakage-resistant for protection if the apparatus is dropped.