Abstract: Systems and methods described herein are optimized for cutting sealing elements on packages using optical radiation. Packages can pass through a cutting device that applies the optical radiation to damage, vaporize, or cut the sealing element (e.g., tape) on the package. The systems and methods control several aspects of the cutting process to adjust throughput, improve efficiency, and reduce line stoppages. Systems can include an in-feed conveyor that orients packages and rejects packages that are out of specification, which can lead to issues such as jamming or damage to the equipment. Systems can include a variable-speed cut conveyor controlled by a computing system to dynamically adjust the speed of packages based upon historical cut quality, environmental measurement data, and height data related to a vertical dimension of the package.

Abstract: Systems and methods described herein are optimized for cutting sealing elements on packages using optical radiation. Packages can pass through a cutting device that applies the optical radiation to damage, vaporize, or cut the sealing element (e.g., tape) on the package. The systems and methods control several aspects of the cutting process to adjust throughput, improve efficiency, and reduce line stoppages. Systems can include an in-feed conveyor that orients packages and rejects packages that are out of specification, which can lead to issues such as jamming or damage to the equipment. Systems can include a variable-speed cut conveyor controlled by a computing system to dynamically adjust the speed of packages based upon historical cut quality, environmental measurement data, and height data related to a vertical dimension of the package.

Abstract: A data security server system includes a first network proxy, a data classifier, an operation pipeline module, a vault database, security infrastructure, and second network proxy that function as secure data tunnel mechanisms through which network data containing sensitive information passes through. The data classifier identifies data payloads having data fields that require processing and routes these data payloads to an operation pipeline module which can redact, tokenize or otherwise process sensitive data before the data payload exits the system. The data classifier also reverses the process by identifying data payloads having redacted or tokenize data fields and restoring the sensitive data to these data fields.

Abstract: In some embodiments, user-selectable/connectable model representations may be provided via a user interface to facilitate artificial intelligence development. The model representations may comprises first and second machine learning model (ML) representations corresponding to first and second ML models, and non-ML model representations corresponding to non-ML models. Based on user input indicating selection of the first and second ML model representations and a non-ML model representation corresponding to a non-ML model, at least a portion of a software application may be generated such that the software application comprises (i) an instance of the first ML model, an instance of the second ML model, and an instance of the non-ML model and (ii) an input/output data path between the instance of the first ML model and at least one other instance, the at least one other instance comprising the instance of the second ML model or the instance of the non-ML model.

Abstract: Systems and methods described herein are optimized for cutting sealing elements on packages using optical radiation. Packages can pass through a cutting device that applies the optical radiation to damage, vaporize, or cut the sealing element (e.g., tape) on the package. The systems and methods control several aspects of the cutting process to adjust throughput, improve efficiency, and reduce line stoppages. Systems can include an in-feed conveyor that orients packages and rejects packages that are out of specification, which can lead to issues such as jamming or damage to the equipment. Systems can include a variable-speed cut conveyor controlled by a computing system to dynamically adjust the speed of packages based upon historical cut quality, environmental measurement data, and height data related to a vertical dimension of the package.

Abstract: The present disclosure relates to compositions comprising a range of ingredients suitable for use in adjusting and/or treating a companion animal such as a canid (e.g. a dog) or a feline (e.g. a cat) and their microbiomes, monitoring tools, and diagnostic methods for determining the health of a companion animal and their microbiome.

Abstract: In some embodiments, reduction of computational resource usage related to image labeling and/or segmentation may be facilitated. In some embodiments, a collection of images may be used to train one or more prediction models. Based on a presentation of an image on a user interface, an indication of a target quantity of superpixels for the image may be obtained. The image may be provided to a first prediction model to cause the prediction model to predict a quantity of superpixels for the image. The target quantity of superpixels may be provided to the first model to update the first model's configurations based on (i) the predicted quantity and (ii) the target quantity. A set of superpixels may be generated for the image based on the target quantity, and segmentation information related to the superpixels set may be provided to a second prediction model to update the second model's configurations.

Abstract: The present disclosure relates to compositions comprising a range of ingredients suitable for use in adjusting and/or treating a companion animal such as a canid (e.g. a dog) or a feline (e.g. a cat) and their microbiomes, monitoring tools, and diagnostic methods for determining the health of a companion animal and their microbiome.

Abstract: Systems and methods described herein are optimized for cutting sealing elements on packages using optical radiation. Packages can pass through a cutting device that applies the optical radiation to damage, vaporize, or cut the sealing element (e.g., tape) on the package. The systems and methods control several aspects of the cutting process to adjust throughput, improve efficiency, and reduce line stoppages. Systems can include an in-feed conveyor that orients packages and rejects packages that are out of specification, which can lead to issues such as jamming or damage to the equipment. Systems can include a variable-speed cut conveyor controlled by a computing system to dynamically adjust the speed of packages based upon historical cut quality, environmental measurement data, and height data related to a vertical dimension of the package.

Abstract: Methods for assessing the health of the microbiome and compositions and food products for improving intestinal health, treating intestinal dysbiosis, and/or treating an intestinal disorder in a companion animal, e.g., a dog are provided.

Abstract: Methods for assessing a canid's microbiome health are provided. The methods include, inter alia, detecting at least four bacterial taxa in a sample obtained from the canid.

Abstract: Methods for assessing a feline's microbiome health are provided. The methods include, inter alia, determining the health of a feline's microbiome comprising quantitation four or more bacterial species and determining the relative abundance of the four or more bacterial species by comparing the abundance with a control data set, wherein an increase or decrease in the abundance can be indicative of an unhealthy microbiome.

Abstract: Methods for assessing the microbiome of a feline are provided. The methods include, inter alia, detecting one or more bacterial species in a sample obtained from the feline, comparing the one or more bacterial species to a control data set, and determining the microbiome age.

Abstract: Methods for assessing the microbiome of a canid are provided. The methods include, inter alia, detecting one or more bacterial taxa in a sample obtained from the canid, correlating the one or more bacterial taxa to a control data set, and determining the microbiome biological age.

Abstract: A data security server system includes a first network proxy, a data classifier, an operation pipeline module, a vault database, security infrastructure, and second network proxy that function as secure data tunnel mechanisms through which network data containing sensitive information passes through. The data classifier identifies data payloads having data fields that require processing and routes these data payloads to an operation pipeline module which can redact, tokenize or otherwise process sensitive data before the data payload exits the system. The data classifier also reverses the process by identifying data payloads having redacted or tokenize data fields and restoring the sensitive data to these data fields.

Abstract: In certain implementations, a user request to add a new concept may be received. A set of media item recommendations may be caused to be loaded on a user interface for presentation to a user responsive to the user request to add the new concept. The media item recommendation set may include a set of recommendations loaded on an on-screen portion of the user interface and a set of recommendations loaded on an off-screen portion of the user interface. The on-screen user interface portion is visible to the user at a first time. The off-screen user interface portion is not being visible to the user at the first time. A user selection of one or more recommendations of the on-screen recommendation set is received. The off-screen recommendation set may be caused to be updated on the user interface during the presentation of the media item recommendation set based on the user recommendation selection.

Abstract: In some embodiments, reduction of computational resource usage related to image labeling and/or segmentation may be facilitated. In some embodiments, a collection of images may be used to train one or more prediction models. Based on a presentation of an image on a user interface, an indication of a target quantity of superpixels for the image may be obtained. The image may be provided to a first prediction model to cause the prediction model to predict a quantity of superpixels for the image. The target quantity of superpixels may be provided to the first model to update the first model's configurations based on (i) the predicted quantity and (ii) the target quantity. A set of superpixels may be generated for the image based on the target quantity, and segmentation information related to the superpixels set may be provided to a second prediction model to update the second model's configurations.

Abstract: In certain implementations, a user request to add a new concept may be received. A set of media item recommendations may be caused to be loaded on a user interface for presentation to a user responsive to the user request to add the new concept. The media item recommendation set may include a set of recommendations loaded on an on-screen portion of the user interface and a set of recommendations loaded on an off-screen portion of the user interface. The on-screen user interface portion is visible to the user at a first time. The off-screen user interface portion is not being visible to the user at the first time. A user selection of one or more recommendations of the on-screen recommendation set is received. The off-screen recommendation set may be caused to be updated on the user interface during the presentation of the media item recommendation set based on the user recommendation selection.

Abstract: In some embodiments, reduction of computational resource usage related to image labeling and/or segmentation may be facilitated. In some embodiments, a collection of images may be used to train one or more prediction models. Based on a presentation of an image on a user interface, an indication of a target quantity of superpixels for the image may be obtained. The image may be provided to a first prediction model to cause the prediction model to predict a quantity of superpixels for the image. The target quantity of superpixels may be provided to the first model to update the first model's configurations based on (i) the predicted quantity and (ii) the target quantity. A set of superpixels may be generated for the image based on the target quantity, and segmentation information related to the superpixels set may be provided to a second prediction model to update the second model's configurations.

Abstract: In some embodiments, reduction of computational resource usage related to image labeling and/or segmentation may be facilitated. In some embodiments, a collection of images may be used to train one or more prediction models. Based on a presentation of an image on a user interface, an indication of a target quantity of superpixels for the image may be obtained. The image may be provided to a first prediction model to cause the prediction model to predict a quantity of superpixels for the image. The target quantity of superpixels may be provided to the first model to update the first model's configurations based on (i) the predicted quantity and (ii) the target quantity. A set of superpixels may be generated for the image based on the target quantity, and segmentation information related to the superpixels set may be provided to a second prediction model to update the second model's configurations.