Abstract: This present invention systems and methods of accessing/monitoring the responsiveness of a breast cancer to a therapeutic compound.

Abstract: An eating utensil adapted for feeding infants includes an elongated handle, having a neck connected to a first end of the elongated handle; a feeding head secured to the neck, the feeding head having a soft outer shell; and a core composed of cotton and extending from the neck into an interior of the feeding head; the core maintains the shape of the feeding head; the soft outer shell provides a barrier between an infant's mouth and the core.

Abstract: Many network protocols, including certain Ethernet protocols, include specifications for multiplexing using of virtual lanes. Due to skews and/or other uncertainties associated with the process, packets from virtual lanes may arrive at the receiver out of order. The present disclosure discusses implementations of receivers that may use multiplexer based crossbars, such as Clos networks, to reorder the lanes. State-based controllers for the Clos networks and state-based methods to assign routes in are also discussed.

Abstract: Circuitry and methods for receiving data that may be compliant with a specific protocol is discussed. The described systems may be employed to implement a physical media access (PMA) sublayer and/or physical coding sublayer (PCS) for high-speed Ethernet protocols. Embodiments described herein may have reduced circuitry footprint that may be achieved by the use of a single recovered clock to drive the operations of PCS circuitry. Efficient use of components may also be achieved by the use of smaller-sized words for processing by the PCS circuitry. The circuitry may process the smaller-sized words by implementing pipelined circuitry. Implementations that employ programmable circuitry, hardened circuitry, or hybrid implementations are also discussed.

Abstract: Disclosed herein is a wireless power transmitting apparatus using an ultrasonic wave. The transmitting apparatus includes a communication interface configured to perform wireless communication with at least one receiving apparatus, a transducer configured to generate an ultrasonic signal and transmit the generated ultrasonic signal to the at least one receiving apparatus, and a processor configured, in response to a charging request being received from the at least one receiving apparatus via the communication interface, to identify a charging priority and direction of the at least one receiving apparatus, and to control the transducer to generate the ultrasonic signal for charging power of the at least one receiving apparatus and transmit the generated ultrasonic signal to the at least one receiving apparatus based on the charging priority and the direction.

Abstract: Systems and methods which utilize spread spectrum sensing on live circuits to obtain information regarding a circuit under test are provided. In some embodiments S/SSTDR testing may be utilized to obtain R, L, C and Z measurements from circuit components. In yet further embodiments, these measurements may be utilized to monitor the output of sensors on a circuit.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. In some embodiments, the morphometric information is based on image analysis of tissue subject to multiplex immunofluorescence and may include characteristic(s) of a minimum spanning tree (MST) and/or a fractal dimension observed in the images.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts risk of prostate cancer progression in a patient, where the model is based on features including one or more (e.g., all) of preoperative PSA, dominant Gleason Grade, Gleason Score, at least one of a measurement of expression of AR in epithelial and stromal nuclei and a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of average edge length in the minimum spanning tree (MST) of epithelial nuclei, and a morphometric measurement of area of non-lumen associated epithelial cells relative to total tumor area. In some embodiments, the morphometric information is based on image analysis of tissue subject to multiplex immunofluorescence and may include characteristic(s) of a minimum spanning tree (MST) and/or a fractal dimension observed in the images.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts whether a patient is likely to have a favorable pathological stage of prostate cancer, where the model is based on features including one or more (e.g., all) of preoperative PSA, Gleason Score, a measurement of expression of androgen receptor (AR) in epithelial and stromal nuclei and/or a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units, and a morphometric measurement of area of epithelial nuclei distributed away from gland units. In some embodiments, quantitative measurements of protein expression in cell lines are utilized to objectively assess assay (e.g.

Abstract: Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts whether a patient is likely to have a favorable pathological stage of prostate cancer, where the model is based on features including one or more (e.g., all) of preoperative PSA, Gleason Score, a measurement of expression of androgen receptor (AR) in epithelial and stromal nuclei and/or a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units, and a morphometric measurement of area of epithelial nuclei distributed away from gland units. In some embodiments, quantitative measurements of protein expression in cell lines are utilized to objectively assess assay (e.g.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.

Abstract: Embodiments of the disclosure provide a system and method of allocating a resource based on myriad input data. In some embodiments, the myriad input data include membership information, claims data, transactional data, etc. The myriad input data are sorted and organized in a meaningful association relationship before applied to a resource allocation modeling algorithm. The resource allocation modeling algorithm provides estimated resource necessary for the application chosen. For example, an insurance company may use membership information, claims data, transactional data, etc., to estimate how much reserves or funds it should hold to cover future claims within a certain timeframe.

Abstract: Systems and methods which utilize spread spectrum sensing on live circuits to obtain information regarding a circuit under test are provided. In some embodiments S/SSTDR testing may be utilized to obtain R, L, C and Z measurements from circuit components. In yet further embodiments, these measurements may be utilized to monitor the output of sensors on a circuit.

Abstract: Systems, methods and devices which utilize Spread Spectrum Time Domain Reflectometry (SSTDR) techniques to measure degradation of electronic components are provided. Such measurements may be implemented while the components “live” or otherwise functioning within an overall system. In one embodiment, monitoring a power converter in a high power system is accomplished. In this embodiment, degradation of components within the power converter (e.g. metal-oxide-semiconductor field-effect transistors (MOSFETs), capacitors, insulated-gate bipolar transistors (IGBTs), and the like) may be monitored by processing data from reflections of an SSTDR signal to determine changes in impedance, capacitance, or any other changes that may be characteristic of components degrading. For example, an aging MOSFET may experience an increase of drain to source resistance which adds additional resistance to a current path within a power converter.

Abstract: Systems and methods which utilize spread spectrum sensing on live circuits to obtain information regarding a circuit under test are provided. In some embodiments S/SSTDR testing may be utilized to obtain R, L, C and Z measurements from circuit components. In yet further embodiments, these measurements may be utilized to monitor the output of sensors on a circuit.

Abstract: An on-chip power converter and an on-chip switching power supply implemented using a film bulk acoustic resonator (FBAR) in place of an inductor. This MEMS device offers high inductance density and high Q factor. FBARs can be conveniently fabricated in a CMOS compatible process. FBARs also shows better EMI results than conventional inductors.

Abstract: In general, one aspect of the subject matter described in this specification can be embodied in methods for assessing risk associated with prostate cancer, the methods including the actions of receiving patient data, comparing, with a processor executing code, the patient data to one or more predictive models, the one or more predictive models comprising at least one of (a) a disease progression (DP) model, the DP model being configured to predicts a likelihood of developing significant disease progression, and (b) a favorable pathology (FP) model, the FP model being configured to predict a likelihood of having organ confined, low grade disease in a prostatectomy, and outputting one or more results of the comparison Other embodiments of the various aspects include corresponding systems, apparatus, and computer program products.

Abstract: Apparatus, methods, and computer-readable media are provided for segmentation, processing (e.g., preprocessing and/or postprocessing), and/or feature extraction from tissue images such as, for example, images of nuclei and/or cytoplasm. Tissue images processed by various embodiments described herein may be generated by Hematoxylin and Eosin (H&E) staining, immunofluorescence (IF) detection, immunohistochemistry (IHC), similar and/or related staining processes, and/or other processes. Predictive features described herein may be provided for use in, for example, one or more predictive models for treating, diagnosing, and/or predicting the occurrence (e.g., recurrence) of one or more medical conditions such as, for example, cancer or other types of disease.