Abstract: Systems and methods are configured to perform prioritized processing of a plurality of processing objects under a time constraint. In various embodiments, a priority policy that includes deterministic prioritization rules, probabilistic prioritization rules, and a priority determination machine learning model is applied to the objects to determine high and low priority subsets. Here, the subsets are determined using the deterministic prioritization rules and a probabilistic ordering of the low priority subset is determined using the probabilistic prioritization rules and the priority determination machine learning model. In particular embodiments, the ordering is accomplished by determining a hybrid priority score for each object in the low priority subset based on a rule-based priority score and a machine-learning-based priority score.

Abstract: Systems and methods are configured to perform prioritized processing of a plurality of processing objects under a time constraint. In various embodiments, a priority policy that includes deterministic prioritization rules, probabilistic prioritization rules, and a priority determination machine learning model is applied to the objects to determine high and low priority subsets. Here, the subsets are determined using the deterministic prioritization rules and a probabilistic ordering of the low priority subset is determined using the probabilistic prioritization rules and the priority determination machine learning model. In particular embodiments, the ordering is accomplished by determining a hybrid priority score for each object in the low priority subset based on a rule-based priority score and a machine-learning-based priority score.

Abstract: Systems and methods are configured to perform prioritized processing of a plurality of processing objects under a time constraint. In various embodiments, a priority policy that includes deterministic prioritization rules, probabilistic prioritization rules, and a priority determination machine learning model is applied to the objects to determine high and low priority subsets. Here, the subsets are determined using the deterministic prioritization rules and a probabilistic ordering of the low priority subset is determined using the probabilistic prioritization rules and the priority determination machine learning model. In particular embodiments, the ordering is accomplished by determining a hybrid priority score for each object in the low priority subset based on a rule-based priority score and a machine-learning-based priority score.

Abstract: Systems and methods are configured to perform prioritized processing of a plurality of processing objects under a time constraint. In various embodiments, a priority policy that includes deterministic prioritization rules, probabilistic prioritization rules, and a priority determination machine learning model is applied to the objects to determine high and low priority subsets. Here, the subsets are determined using the deterministic prioritization rules and a probabilistic ordering of the low priority subset is determined using the probabilistic prioritization rules and the priority determination machine learning model. In particular embodiments, the ordering is accomplished by determining a hybrid priority score for each object in the low priority subset based on a rule-based priority score and a machine-learning-based priority score.

Abstract: Some system embodiments may include a flow monitor and a communication hub. The flow monitor may be configured to be mounted on a feed line. The flow monitor may include an accelerometer configured to detect vibration of the feed line. The communication hub may be configured to wirelessly communicate with the flow monitor, to receive accelerometer data from the flow monitor, and use the accelerometer data to communicate flow status information through a network to a user.

Abstract: ATR kinase is a key regulator of checkpoint responses to incompletely replicated and damaged DNA. Without this checkpoint, cells will enter mitosis prematurely, likely resulting in cell death. The invention provides methods and reagents to either block or activate the activation of the ATR kinase checkpoint, through, for example, either blocking or activating the expression of an ATR activator TopBP1. The invention also provides screening methods to identify additional ToBP1 inhibitors or activators that may be used to modulate the activity of the ATR checkpoint.

Abstract: ATR kinase is a key regulator of checkpoint responses to incompletely replicated and damaged DNA. Without this checkpoint, cells will enter mitosis prematurely, likely resulting in cell death. The invention provides methods and reagents to either block or activate the activation of the ATR kinase checkpoint, through, for example, either blocking or activating the expression of an ATR activator TopBP1. The invention also provides screening methods to identify additional ToBP1 inhibitors or activators that may be used to modulate the activity of the ATR checkpoint.

Abstract: ATR kinase is a key regulator of checkpoint responses to incompletely replicated and damaged DNA. Without this checkpoint, cells will enter mitosis prematurely, likely resulting in cell death. The invention provides methods and reagents to either block or activate the activation of the ATR kinase checkpoint, through, for example, either blocking or activating the expression of an ATR activator TopBP1. The invention also provides screening methods to identify additional ToBP1 inhibitors or activators that may be used to modulate the activity of the ATR checkpoint.

Abstract: The present invention provides compositions of ATR nucleic acids and proteins, as well as methods of using said compositions in screening assays. The invention further provides antibodies and transgenic animals based on the ATR compositions.

Abstract: The present invention provides compositions of ATR nucleic acids and proteins, as well as methods of using said compositions in screening assays. The invention further provides antibodies and transgenic animals based on the ATR compositions.

Abstract: Formaldehyde-free tissue preservative compositions are useful in the fields of mortuary science and histology. The compositions disinfect and preserve animal (including human) tissues and remains, yet avoid the use of formaldehyde and formalin--potentially hazardous materials that are undergoing increasing regulatory review. A trio of compositions for use in embalming human bodies is disclosed, as is a composition for use in histological preservation.