Abstract: This application relates generally to automated systems and associated methods for identifying hematological abnormalities. An automated system can include at least one processor that, in operation, is configured to: receive, from a flow cytometer, a flow cytometry data matrix characterizing a tube that is associated with a sample; convert the flow cytometry data matrix into a high dimensional vector; produce a single sample high dimensional vector including a concatenation of multiple high dimensional vectors associated with the sample, wherein the multiple high dimensional vectors comprise the tube high dimensional vector; assemble a training data set including multiple sample high dimensional vectors; receive, from a datastore, outcome information including respective labels associated with each of the multiple sample high dimensional vectors; and train a classifier based on the training data set and the outcome information.

Abstract: Introduced here is an approach to improving the automatic identification of hematological malignancies by taking advantage of established databases through transfer learning. At a high level, this approach attempts to address the cross-domain gap by preserving knowledge of the source domain for better optimization of the target domain.

Abstract: Introduced here is an approach to improving the automatic identification of hematological diseases using computer-implemented models that are trained to rapidly distinguish between different collections of immunophenotypes that represent different disease types or disease states. Understanding the different patterns of immunophenotype collections contained in a given sample may permit a proposed diagnosis for a given hematological disease to be produced for the corresponding patient. For example, the proposed diagnoses may be output by a classification model based on the distribution of immunophenotypes across the given sample.

Abstract: Disclosed is a wig weave bundle formed by a first fake hair bundle and at least one second fake hair bundle. The first fake hair bundle has a multiple bundles of first fake hair strains braided into a braid which is disposed at an upper end of the first fake hair bundle, and the first fake hair strains dangle from the braid, and the braid is wound into a ring with a wearing part in the middle and provided for passing through a real hair bundle. The second fake hair bundle has one or more bundles of second fake hair strains, and a ring is connected to an upper end of the second fake hair bundle and connected to the brand of the first fake hair bundle, such that the second fake hair strains and first fake hair strains dangle from the braid altogether.

Abstract: The subject invention relates to two-stage inoculation and two-stage fermentation process which are performed by the inoculation time difference and staged fermentation. In the first stage, yeast, lactic acid bacteria and Acetobacter aceti are inoculated into a fermentation tank to perform primary fermentation to produce primary fermented material. In the second stage, yeast is added into the primary fermented material in a container to perform the secondary fermentation to produce secondary fermented material, and then the secondary fermented material is pasteurized to deactivate yeast, lactic acid bacteria and Acetobacter aceti in the container and stop fermentation reaction. Finally, the secondary fermented material is cooled to ambient temperature to prepare the kombucha fermented beverage preserving active fermentative bacteria and enzyme at ambient temperature. The invention is help to improve the preservation convenience of the kombucha fermented beverage and avoid excessive alcohol concentration.

Abstract: This application relates generally to a computer implemented method comprising: receiving a medical record data from a patient, wherein said record comprising a static attribute and a time dependent progression attribute; processing the time dependent progression attributes of medical record data using a trained neural network to into time-series representation, and converting the static attributes into static variables; combining the time-series representation and static variables to multiple vectors; providing a prognosis outcome by a trained classifier using said multiple vectors; wherein the neural network is trained by steps of (a) assembling a training data set comprising a retrospective collection of patients' medical record data wherein said record data comprising collected number of static attributes, time dependent progression attributes and patients' mortality and relapse outcomes; (b) processing the time dependent progression attributes of the training data set using a neural network to convert th

Abstract: Disclosed are a hairpiece, a hair extension structure, and a hair extension method that attaches a fake-hair bundle to a root position of a real-hair bundle to complete a hair extension. The hairpiece includes an inwardly folded fixing strip having fake-hair compositions with an upper end connected to the fake-hair bundle, and a thermosetting layer pre-combined with an inner side of the fixing strip. The hair extension structure has both fixing strip and thermosetting adhesive layer inwardly folded and the thermosetting adhesive layer covered and adhered onto both upper and lower sides of the real-hair bundle. The hair extension method includes measuring a user's head, preparing equal-division marks, grabbing the real-hair bundle according to the equal-division marks, covering and gluing the thermosetting adhesive layer of the hairpiece onto the real-hair bundle, and heating, melting, and solidifying the thermosetting adhesive layer to complete the hair extension structure of the hairpiece.

Abstract: This application relates generally to automated systems and methods for classifying subtypes of leukemia cells and other applications therefrom.

Abstract: This application relates generally to automated systems and methods to identify hematological abnormalities.

Abstract: A method for forming a damascene opening, wherein the method comprises steps as follows: Firstly, a semiconductor structure comprising an inter-metal dielectric (IMD), a first hard mask layer and a second hard mask layer stacked in sequence is provided, wherein the semiconductor structure has at least one trench extending downwards from the second hard mask layer to the IMD. A plasma treatment is then performed to modify a portion of the first hard mask layer exposed from the trench. Subsequently, a wet treatment is performed to remove the second hard mask layer and a portion of the first hard mask layer, wherein the plasma-modified portion of the first patterned hard mask layer has a first removing rate substantially less than a second removing rate of the second hard mask layer in the wet treatment.

Abstract: A method for determining an electrostatic force present in a flat object, includes: (a) positioning the object on a flat support; (b) providing a series of testing membranes which are substantially free of electrostatic charges and have different standarized weights; (c) placing on the surface of the object one of the testing membranes and turning the support to an inclined position relative to a horizontal plane; (d) repeating step (c) with the other ones of the testing membranes; (e) examining which one of the testing membranes slides relative to the object after the support is inclined, and determining the smallest weight among the standarized weights, that permits a sliding movement between the testing membranes and the object, and the largest weight among the standarized weights, that prevents the sliding movement; and (f) evaluating the electrostatic force as a function of the largest weight and the smallest weight. An apparatus for carrying out the process is also disclosed.