Abstract: An assembly includes a base. The assembly includes an airbag supported by the base. The assembly includes an airbag guide supported by the base. The assembly includes a linchpin securing the airbag guide to the base. The linchpin includes a first marking and one of the base or the airbag guide includes a second marking, the first marking and the second marking align to collectively be a readable indicium.

Abstract: A vehicle seating assembly includes a seatback. The seatback includes a rear portion and a substantially horizontal strap including first and second ends fixed to the rear portion. The substantially horizontal strap further includes an intermediate attachment area fixed to the rear portion between the first and second ends.

Abstract: A predictive modeling method may include determining a time interval of time-series data; identifying one or more variables of the data as targets; determining a forecast range and a skip range associated with a prediction problem represented by the data; generating training data and testing data from the time-series data; fitting a predictive model to the training data; and testing the fitted model on the testing data. The forecast range may indicate a duration of a period for which values of the targets are to be predicted. The skip range may indicate a temporal lag between the time period corresponding to the data used to make predictions and the time period corresponding to the predictions. The skip range may separate input data subsets representing model inputs from subsets representing model outputs, and separate test data subsets representing model inputs from subsets representing validation data.

Abstract: A vehicle seating assembly includes a seatback. The seatback includes a rear portion and a substantially horizontal strap including first and second ends fixed to the rear portion. The substantially horizontal strap further includes an intermediate attachment area fixed to the rear portion between the first and second ends.

Abstract: A vehicle seating assembly includes a seatback. The seatback includes a rear portion and a substantially horizontal strap including first and second ends fixed to the rear portion. The substantially horizontal strap further includes an intermediate attachment area fixed to the rear portion between the first and second ends.

Abstract: A method for calibrating a CNC machine including providing instructions for machining a surface of a distortion-free object, selecting a true axis of movement of a toolhead of the machine using the instructions, instructing the toolhead to travel on an object to be machined along the true axis of movement, but where the toolhead actually travels along an actual axis that is deviated from the true axis as a result of the surface distortions on the object to be machined, selecting multiple points along the actual axis traveled by the toolhead on the object to be machined, comparing the distance of the multiple points along the actual axis from the true axis to determine offset amounts from the true axis corresponding to a lack of straightness of the object to be machined, and modifying the instructions to compensate for the offset amounts before uploading the instructions to a CNC controller.

Abstract: A method of making a seating assembly includes attaching an electronics module to a seat support structure. A cushion assembly is formed over the electronics module and secures the cushion assembly to an underlying seat support structure. Connecting features of the cushion assembly are flowed into securing channels of the seat support structure to form an interference fit. The cushion assembly and the underlying seat support structure are covered with a water barrier skin to form a watertight seating unit. A seating surface of the watertight seating unit is covered with a coverstock.

Abstract: A seat assembly includes a frame assembly have a seat portion and a seatback portion, wherein a seat member is supported on the seat portion of the frame assembly and a seatback is supported on the seatback portion of the frame assembly. Each of the seatback and the seat include a support portion supported on a carrier member, wherein the support portion and the carrier member are comprised of porous non-absorbent materials that are configured to allow water to drain therethrough. A cover member is comprised of a perforated fabric that is non-absorbent, and includes a first portion covering the seat member and a second portion covering the seatback.

Abstract: A seat assembly includes a frame assembly have a seat portion and a seatback portion, wherein a seat member is supported on the seat portion of the frame assembly and a seatback is supported on the seatback portion of the frame assembly. Each of the seatback and the seat include a support portion supported on a carrier member, wherein the support portion and the carrier member are comprised of porous non-absorbent materials that are configured to allow water to drain therethrough. A cover member is comprised of a perforated fabric that is non-absorbent, and includes a first portion covering the seat member and a second portion covering the seatback.

Abstract: A method for virtually calibrating a CNC machine including the steps of selecting a true axis of movement of a toolhead of the CNC machine, instructing the toolhead to travel along the true axis of movement, selecting multiple points along an actual axis traveled by the toolhead, comparing the distance of the multiple points along the actual axis from the true axis to determine offset amounts from the true axis corresponding to a lack of straightness, and modifying g-code instructions to compensate for the offset amounts before uploading the g-codes to a CNC controller.

Abstract: The present disclosure provides compounds that are Large Multifunctional Protease 7 (LMP7) inhibitors and are therefore useful for the treatment of diseases treatable by inhibition of LMP7. Also provided are pharmaceutical compositions containing such compounds and processes for preparing such compounds.

Abstract: A composition comprising a polypeptide ligated to an oligonucleotide through a sterol linker. A method of ligating a polypeptide to an oligonucleotide, comprising a polypeptide having a hedgehog steroyl transferse catalytic domain at the C-terminal of the polypeptide with an electrophilic residue, e.g., glycine, between polypeptide and the hedgehog steroyl transferse catalytic domain, and a steroylated oligonucleotide in solution, and permitting a reaction to cleave the hedgehog steroyl transferse catalytic domain from the polypeptide while ligating the steroylated oligonucleotide to the glycine at the C-terminal of the polypeptide. The oligonucleotide may be, for example, a therapeutic, diagnostic, or affinity ligand.

Abstract: The present disclosure is directed to certain inhibitors of RLK and ITK of formula (I), pharmaceutical compositions comprising such compounds, and method of treating diseases mediated by inhibition of RLK and ITK.

Abstract: A predictive modeling method may include obtaining a fitted, first-order predictive model configured to predict values of output variables based on values of first input variables; and performing a second-order modeling procedure on the fitted, first-order model, which may include: generating input data including observations including observed values of second input variables and predicted values of the output variables; generating training data and testing data from the input data; generating a fitted second-order model of the fitted first-order model by fitting a second-order model to the training data; and testing the fitted, second-order model of the first-order model on the testing data. Each observation of the input data may be generated by (1) obtaining observed values of the second input variables, and (2) applying the first-order predictive model to corresponding observed values of the first input variables to generate the predicted values of the output variables.

Abstract: A method for determining the predictive value of a feature may include: (a) performing predictive modeling procedures associated with respective predictive models, wherein performing each modeling procedure includes fitting the associated model to an initial dataset representing an initial prediction problem; (b) determining a first accuracy score of each of the fitted models, representing an accuracy with which the fitted model predicts an outcome of the initial prediction problem; (c) shuffling values of a feature across observations included in the initial dataset, thereby generating a modified dataset representing a modified prediction problem; (d) determining a second accuracy score of each of the fitted models, representing an accuracy with which the fitted model predicts an outcome of the modified prediction problem; and (e) determining a model-specific predictive value of the feature for each of the fitted models based on the first and second accuracy scores of the fitted model.

Abstract: A predictive modeling method may include determining a time interval of time-series data; identifying one or more variables of the data as targets; determining a forecast range and a skip range associated with a prediction problem represented by the data; generating training data and testing data from the time-series data; fitting a predictive model to the training data; and testing the fitted model on the testing data. The forecast range may indicate a duration of a period for which values of the targets are to be predicted. The skip range may indicate a temporal lag between the time period corresponding to the data used to make predictions and the time period corresponding to the predictions. The skip range may separate input data subsets representing model inputs from subsets representing model outputs, and separate test data subsets representing model inputs from subsets representing validation data.

Abstract: Systems and techniques for predictive data analytics are described. In a method for selecting a predictive model for a prediction problem, the suitabilities of predictive modeling procedures for the prediction problem may be determined based on characteristics of the prediction problem and/or on attributes of the respective modeling procedures. A subset of the predictive modeling procedures may be selected based on the determined suitabilities of the selected modeling procedures for the prediction problem. A resource allocation schedule allocating computational resources for execution of the selected modeling procedures may be generated, based on the determined suitabilities of the selected modeling procedures for the prediction problem. Results of the execution of the selected modeling procedures in accordance with the resource allocation schedule may be obtained. A predictive model for the prediction problem may be selected based on those results.

Abstract: Systems and techniques for predictive data analytics are described. In a method for selecting a predictive model for a prediction problem, the suitabilities of predictive modeling procedures for the prediction problem may be determined based on characteristics of the prediction problem and/or on attributes of the respective modeling procedures. A subset of the predictive modeling procedures may be selected based on the determined suitabilities of the selected modeling procedures for the prediction problem. A resource allocation schedule allocating computational resources for execution of the selected modeling procedures may be generated, based on the determined suitabilities of the selected modeling procedures for the prediction problem. Results of the execution of the selected modeling procedures in accordance with the resource allocation schedule may be obtained. A predictive model for the prediction problem may be selected based on those results.

Abstract: Systems and techniques for predictive data analytics are described. In a method for selecting a predictive model for a prediction problem, the suitabilities of predictive modeling procedures for the prediction problem may be determined based on characteristics of the prediction problem and/or on attributes of the respective modeling procedures. A subset of the predictive modeling procedures may be selected based on the determined suitabilities of the selected modeling procedures for the prediction problem. A resource allocation schedule allocating computational resources for execution of the selected modeling procedures may be generated, based on the determined suitabilities of the selected modeling procedures for the prediction problem. Results of the execution of the selected modeling procedures in accordance with the resource allocation schedule may be obtained. A predictive model for the prediction problem may be selected based on those results.

Abstract: The present disclosure is directed to certain inhibitors of kinases such as ITK, BLK, BMX, BTK, JAK3, TEC, TXK, HER2 (ERBB2), or HER4 (ERBB4), in particular ITK, pharmaceutical compositions comprising such compounds, and method of treating diseases mediated by such kinases.