Abstract: Polyurethane or polyisocyanate form stock and methods of manufacturing are described herein. The foam stock can include (a) a polyurethane or polyisocyanate formed by the reaction of (i) one or more isocyanates selected from the group consisting of diisocyanates, polyisocyanates, and mixtures thereof, and (ii) one or more polyols; and (b) a filler present in an amount from greater than 50% to 90% by weight, based on the total weight of the foam stock. The density of the foam stock can be from 10 lb/ft3 to 35 lb/ ft3. The flexural strength of the foam stock can be at least 100 psi. The resulting foam stock can be used to produce polyurethane or polyisocyanate foam to be used in composite panels.

Abstract: A method, computer system, and a computer program product for performing an interactive outcome analysis is provided. The present invention may include generating, by a computer, a first estimation outcome from a first plurality of input conditions. The present invention may include generating, by the computer, a parallel estimation outcome from a second plurality of input conditions, wherein at least one of said input conditions in said first plurality of input conditions is different from any of said second plurality of input conditions. The present invention may include selecting, by the computer, either said first or said parallel estimation outcome by analyzing said outcomes with one another and with a target goal outcome.

Abstract: A die casting method includes stirring an aluminum alloy liquid in a stirrer under an airtight vacuum condition. The stirrer includes an electromagnetic inductor and a stirring rod. The aluminum alloy liquid is simultaneously subjected to an electromagnetic stirring in a direction of a magnetic field generated by the electromagnetic inductor and a mechanical stirring under a rotation action of the stirring rod. The aluminum alloy liquid is stirred for 20-80 minutes until the aluminum alloy liquid becomes semisolid to obtain a semisolid aluminum alloy slurry. The method further includes injecting the semisolid aluminum alloy slurry into a filter die to perform die casting molding at an injection speed of 1.5-2.5 m/s, an injection specific pressure of 30-80 MPa, a pressurization pressure of 60-80 MPa, and a temperature of the filter die of 250-400° C., and maintaining pressure for 7-30 seconds to obtain the filtering cavity.

Abstract: Disclosed are PTHrP analogue formulations for transdermal delivery of a therapeutically effective amount of a PTHrP analogue, as well as transdermal patches prepared using these formulations, methods of preparing the disclosed formulations and patches, and methods of using these formulations and patches to treat osteoporosis, osteopenia, osteoarthritis, and/or bone fracture, improve bone mineral density (BMD), improve trabecular bone score (TBS), and treat, prevent, and/or reduce bone fractures.

Abstract: Compounds active on protein kinases are described, as well as methods of making and using such compounds to treat diseases and conditions associated with aberrant activity of protein kinases.

Abstract: A method and a system for generating a three-dimensional crown surface for replacing a missing tooth are disclosed. The method comprising: detecting the missing tooth from a digital three-dimensional representation of a mouth using a first artificial intelligence model; and using a second artificial intelligence model, generating a three-dimensional crown surface for replacing the missing tooth taking into account one or more of a dental preparation, margin line, occlusion, the gap between the preparation and adjacent and opposing teeth.

Abstract: In an approach for detecting web browsing subject-oriented event interactions and intelligently organizing web pages based on insights from important interactions for better exploration and efficient management, a processor extracts time series data associated with a plurality of web browsing events based on browsing historical actions of a user. A processor identifies the subject of each web browsing event. A processor determines major events based on the time series data and subjects of the plurality of web browsing events. A processor organizes the plurality of web browsing events based on subject hierarchy and timeline from the time series data. A processor highlights one or more uniform resource locators based on the subject hierarchy and timeline.

Abstract: A method of clustering data generated by an unknown model, the method including accessing the data, wherein the data includes a prediction target and a confidence, extracting a data group with high prediction confidence from the data, wherein the data group comprises a plurality of data cases, and where each of the data cases is described by a plurality of predictors, identifying high rank predictors of each the data cases in the data group, transforming the data group into a transformed data group including only the high rank predictors for each of the data cases, wherein the high rank predictors are ranked within each of the data cases included in the transformed data group, clustering the transformed data group to generate clusters, and profiling the clusters to extract an insight about the unknown model.

Abstract: An embodiment includes parsing conversation data to extract a message dataset and a user dataset. The embodiment classifies the message dataset into a category using machine learning processing and identifies the category as a top category based at least in part on an amount of the conversation data associated with the category. The embodiment generates impact data associated with the user dataset based on actions in the conversation data by the user. The embodiment generates role data associated with the user by applying a rule to the conversation data for the user. The embodiment generates key index data associated with the message dataset by identifying interactions with a message represented by the message dataset. The embodiment generates output data arranged according to a specified data format that is compatible with a user interface.

Abstract: Provided is a system for the prognostics of the chronic diseases after the medical examination based on the multi-label learning, including a data acquisition module, a data preprocessing module, a basic predicting model constructing module, and a local predicting module. The data acquisition module is configured to acquire physical examination data of a physical examination user. The basic predicting model constructing module is configured to construct a multi-label learning model for a physical examination scenario. The local predicting module includes a local model training unit and a predicting unit. The local model training unit adjusts the basic predicting model into a local predicting model, and solidifies the local predicting model into the local predicting module. The predicting unit outputs a predicted prognostic index for an occurrence of a plurality of chronic diseases, and finally acquires a future expected occurrence time of the chronic diseases.

Abstract: A coil structure includes a coil set including a first coil and a second coil. The first coil and the second coil are wound to form an annular area. A first end of the first coil and a first end of the second coil are close to an inner ring of the annular area. A second end of the first coil and a second end of the second coil are close to an outer ring of the annular area. The first end of the first coil is electrically connected to the first end of the second coil. A first projection-of the first coil on a plane perpendicular to an axial direction of the coil structure and a second projection of the second coil on the plane are mirror-symmetrical to each other.

Abstract: In an approach to efficient model adjustment utilizing a dual model system, one or more computer processors create a subset of a dataset utilizing a trained primary model; create a secondary model based on the created subset of the dataset; calculate a confidence of a case utilizing the trained primary model, wherein the confidence is a robustness indicator of a model indicating a capacity of the model to meet or exceed performance when applied to the dataset; responsive to the calculated confidence not exceeding a confidence threshold, generate a score of the case utilizing the created secondary model; responsive to an incorrect classification, update the created subset of the dataset with the case; retrain the secondary model utilizing the updated subset of the dataset.

Abstract: A computer-implemented method, system and computer program product for generating personalized recommendations to address a target problem. A machine learning prediction model directed to a target problem for an individual is built with historical data. After receiving data about the individual, a prediction for the individual is obtained in connection with the target problem by the built model using the received data about the individual. Key predictors (e.g., parameters) and their weight for the individual are generated using the prediction by an explanation model. Record(s) are identified from the historical data by performing similarity analysis of the historical data using the key predictors and their weight. Such records provide a population closely related to the individual with respect to the target problem. These records are then analyzed and recommendations are provided to a user to solve the target problem for the individual based on the analysis of the identified record(s).

Abstract: An approach is provided in which the approach captures a first user activity log of a first user accessing multiple systems and captures a set of second user activity logs of a set of second users accessing the multiple systems. The approach determines a set of system monitoring preferences based the first user activity log and the set of second user activity logs, and scores the multiple systems based on the set of system monitoring preferences. The approach generates a recommended system monitoring list based on the scored multiple systems, and transmits the recommended system monitoring list to the first user.

Abstract: An approach is provided in which the approach generates a parallel chart based on multiple records that includes a set of variable values corresponding to a set of variables. To generate the parallel chart, the approach arranges the set of variables on the parallel chart in a variable order based on at least one variable arrangement rule. The approach arranges an initial variable value order for each one of the set of variables, and computes a lucidity score based on the variable order and the initial variable value order of each of the set of variables. The lucidity score is a measurement of the clarity of the parallel chart. The approach adjusts the variable value order of at least one of the set of variables to increase the lucidity score and optimizes the clarity of the parallel chart based on the adjusted variable value order.

Abstract: Provided are a sulfonylbenzamide derivative and a conjugate thereof, a preparation method therefor, and the use thereof. In particular, provided is a sulfonylbenzamide derivative having a structure as represented by formula (D), a conjugate thereof, a preparation method therefor, a pharmaceutical composition containing same, and the use thereof in the preparation of a drug for treating cancers by means of receptor regulation. Each substituent in general formula (D) is as defined in the description.

Abstract: Devices, systems, and methods are provided for on-target rate optimization for video.

Abstract: A drowsy driving detection method comprises: acquiring a side face image of a currently seated driver collected by a camera module; performing face recognition on the side face image to obtain side face feature parameters, and determining, according to the side face feature parameters, whether an ID file corresponding to the currently seated driver exists in a driver ID library; and if yes, periodically acquiring a side face image of the driver in the current period collected by the camera module, obtaining eye movement feature parameters of the driver in the current period according to the side face image of the current period, and determining whether the driver is driving while drowsy according to a comparison result between the eye movement feature parameters of the current period and the normal eye movement feature parameters of the driver.

Abstract: Devices, systems, and methods are provided for on-target rate optimization for video.

Abstract: An embodiment includes detecting an interface element and an element attribute of the interface element in a series of views of a user interface, and then after an update of the user interface, detecting a candidate element and a candidate element attribute in a series of views of the updated user interface. The embodiment then determines that the updated user interface lacks any errors using a decision tree that includes comparisons of all interface elements of the user interface to corresponding candidate elements of the updated user interface. The embodiment then generates an optimized decision tree based at least in part on an analysis of the comparisons of the user interface to the updated user interface resulting in a condition that allows for the determining of a lack of errors based on comparisons of a subset of the interface elements to corresponding candidate elements.