Abstract: A lithium-ion battery separator includes a substrate defining inter-particle pores and a zeolite coating on a surface of the substrate. The zeolite coating includes zeolite particles. The zeolite particles are hydrophobic and have an average diameter smaller than an average pore size of inter-particle pores of the substrate, such that some of the zeolite particles are positioned in some of the inter-particle pores. The separator is non-flammable In a lithium-ion battery, the substrate is a first electrode, and a second electrode is in direct contact with the zeolite coating. The lithium-ion battery includes a non-flammable salt-concentrated electrolyte, and the zeolite coating has a high wettability for the electrolyte. The lithium-ion battery is non-flammable.

Abstract: A modular seat and method of assembling the same are provided. The modular seat includes a first seating component having one or more seating component attachment apertures. The modular seat also includes a first arm component having a first arm component shelf support configured to be received by one of the seating component attachment apertures. The modular seat may include one or more other components, such as attachment members, additional seating components, back support components, and/or additional arm components. A corresponding method of assembling a modular seat is also provided.

Abstract: A method for forming an amine-functionalized solid CO2 sorbent for carbon capture may include providing a support material and applying at least one cycle of molecular layer deposition (MLD) with an amine precursor onto the surface of the support material. An amine layer formed on the support material contains amine groups/amine-containing ligands to adsorb CO2 onto the support material in a low temperature operating window for adsorption and desorption without the loss of active sites.

Abstract: A modular seat and method of assembling the same are provided. The modular seat includes a first seating component having one or more seating component attachment apertures. The modular seat also includes a first arm component having a first arm component shelf support configured to be received by one of the seating component attachment apertures. The modular seat may include one or more other components, such as attachment members, additional seating components, back support components, and/or additional arm components. A corresponding method of assembling a modular seat is also provided.

Abstract: Fabricating a zeolite membrane on a substrate includes disposing first zeolite crystals on a substrate to yield a first layer on the substrate and disposing second zeolite crystals on the first layer to yield a second layer on the first layer, thereby yielding a membrane precursor. The membrane precursor is heated at a first temperature for a first length of time, and the temperature of the membrane precursor is increased or decreased from the first temperature to a second temperature. The membrane precursor is heated at the second temperature for a second length of time to yield the zeolite membrane. The second zeolite crystals have a smaller average diameter than the first zeolite crystals. The second temperature can exceed the first temperature or the first temperature can exceed the second temperature.

Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.

Abstract: A sensing film configured to detect an analyte gas includes a metal oxide thin film and noble metal nanoparticles disposed on the metal oxide thin film. The sensing film can be a compressed thin film of metal oxide nanostructures. Forming the sensing film includes dispersing the multiplicity of hydrophobic metal oxide nanostructures onto a surface of a layer of water to yield a thin film of the hydrophobic metal oxide nanostructures on the water. The hydrophobic metal oxide nanostructures have a common orientation with respect to the surface of the water. The thin film of the hydrophobic metal oxide nanostructures are compressed to yield a compressed thin film of the hydrophobic metal oxide nanostructures.

Abstract: A modular seat and method of assembling the same are provided. The modular seat includes a first seating component having one or more seating component attachment apertures. The modular seat also includes a first arm component having a first arm component shelf support configured to be received by one of the seating component attachment apertures. The modular seat may include one or more other components, such as attachment members, additional seating components, back support components, and/or additional arm components. A corresponding method of assembling a modular seat is also provided.

Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.

Abstract: An equine therapy boot that has an insulating shaft that can be securely fastened at multiple locations on an equine leg and hold a volume of therapeutic media to treat the equine hoof and leg is disclosed herein. The equine therapy boot includes a sole member, an internal securing mechanism, and an insulating shaft configured to retain therapeutic media. Advantageously, this equine therapy boot secures the horse's hoof to the sole member such that the insulating shaft is not displaced from the horse's hoof and leg during the treatment period. Also disclosed herein are methods of treating a diseased or injured horse's hoof and leg with the disclosed equine therapy boot.

Abstract: A data volume can be created on a network-accessible storage device in a data center for use by a virtual machine instance. More specifically, a management system of the data center may request storage servers to allocate space for the data volume. Prior to receiving confirmation that the data volume has been created, the management system may further request the storage servers to establish a lease that authorizes the virtual machine access to the data volume.

Abstract: Systems and methods for query term weighting are disclosed. A server receives a search query for employment candidates, the search query comprising a set of parameters, each parameter having a weight. The server generates, from a data repository storing records associated with professionals, a first set of search results based on the set of parameters and the weights of the parameters in the set. The server transmits the first set of search results. The server receives a response to search result(s) from the first set of search results, the search result(s) being associated with a set of factors, the response indicating a level of interest in the search result(s). The server adjusts the parameters in the set of parameters or adjusts the weights of the parameters based on the response to the search result(s). The server provides an output based on the adjusted parameters or the adjusted weights.

Abstract: In some examples, a merchant device at a point of sale (POS) location may present information to a merchant in a first language preferred by the merchant, and may present information to a buyer in a second language preferred by the buyer. The merchant device may switch between the different languages in response to detecting a change in the physical orientation of a display. For instance, in a first orientation in which the display is viewable from a merchant direction, the merchant device may present information in the language preferred by the merchant. When the orientation of the display is changed to a second orientation in which the display is viewable from a buyer direction, the merchant device may present information in the language indicated to be preferred by the buyer. Various techniques may be used for determining the preferred language of a particular buyer.

Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.

Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.

Abstract: Systems and methods for analyzing pipelined data are disclosed. In some examples, a server receives a transaction description requesting candidates for a given transaction. The server accesses first records representing parties that fully completed the given transaction and second records representing parties that were in a pipeline for completing the given transaction but did not fully complete the given transaction. The first records and the second records are stored at a data repository. The server generates a model for predicting whether an identified record represents a party likely to complete the given transaction. The model is generated based on at least the first records and the second records. The server orders a list of third records representing parties likely to complete the given transaction. The server provides an output representing the third records.

Abstract: A data volume can be created on a network-accessible storage device in a data center for use by a virtual machine instance. More specifically, a management system of the data center may request storage servers to allocate space for the data volume. Prior to receiving confirmation that the data volume has been created, the management system may further request the storage servers to establish a lease that authorizes the virtual machine access to the data volume.

Abstract: A data volume can be created on a network-accessible storage device in a data center for use by a virtual machine instance. More specifically, a management system of the data center may request storage servers to allocate space for the data volume. Prior to receiving confirmation that the data volume has been created, the management system may further request the storage servers to establish a lease that authorizes the virtual machine access to the data volume.

Abstract: Systems and methods for query term weighting are disclosed. A server receives a search query for employment candidates, the search query comprising a set of parameters, each parameter having a weight. The server generates, from a data repository storing records associated with professionals, a first set of search results based on the set of parameters and the weights of the parameters in the set. The server transmits the first set of search results. The server receives a response to search result(s) from the first set of search results, the search result(s) being associated with a set of factors, the response indicating a level of interest in the search result(s). The server adjusts the parameters in the set of parameters or adjusts the weights of the parameters based on the response to the search result(s). The server provides an output based on the adjusted parameters or the adjusted weights.

Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.