Abstract: The invention provides antibodies that specifically bind tau. The antibodies inhibit or delay tau-associated pathologies and associated symptomatic deterioration.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for monitoring and predicting various data related to an inventory. A data processing apparatus interacts with one or more business computers to obtain one of replenishment and consumption activity data related to an inventory. A model for variations in the inventory is created. The model is used to determine estimates of variation for one of currently planned replenishment activities and currently planned consumption activities. The estimates of variation are used to predict future inventory levels. A system including one or more agent computers is also described.

Abstract: An inventory agent operating on software includes instructions operable to cause a programmable processor to receive inventory data relating to stock in an inventory, apply the inventory data to a conditional probabilistic predictive statistical algorithm, calculate a predicted inventory level, and use the calculated predicted inventory level to determine whether to order additional stock for the inventory. The statistical algorithm uses a conditional probabilistic model to process the data. The inventory agent may be implemented in a supply chain management system.

Abstract: An inventory agent operating on software includes instructions operable to cause a programmable processor to receive inventory data relating to stock in an inventory. The inventory data includes planned inventory data and actual inventory data. The instructions are operable to cause the programmable processor to use the inventory data to calculate one or more correlations in errors between the planned inventory data and the actual inventory data, use the one or more correlations in errors to estimate a probability density for one or more errors, calculate a predicted inventory level, calculate a likely error of the predicted inventory level using the estimate of the probability density, and adjust the predicted inventory level with the likely error to estimate a likely actual inventory level. The inventory agent may be implemented in a supply chain management system.

Abstract: An inventory agent operating on software includes instructions operable to cause a programmable processor to receive inventory data relating to stock in an inventory. The inventory data includes planned inventory data and actual inventory data. The instructions are operable to cause the programmable processor to use the inventory data to calculate one or more correlations in errors between the planned inventory data and the actual inventory data, use the one or more correlations in errors to estimate a probability density for one or more errors, calculate a predicted inventory level, calculate a likely error of the predicted inventory level using the estimate of the probability density, and adjust the predicted inventory level with the likely error to estimate a likely actual inventory level. The inventory agent may be implemented in a supply chain management system.

Abstract: An inventory agent operating on software includes instructions operable to cause a programmable processor to receive inventory data relating to stock in an inventory, apply the inventory data to a conditional probabilistic predictive statistical algorithm, calculate a predicted inventory level, and use the calculated predicted inventory level to determine whether to order additional stock for the inventory. The statistical algorithm uses a conditional probabilistic model to process the data. The inventory agent may be implemented in a supply chain management system.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for monitoring and predicting various data related to an inventory. A data processing apparatus interacts with one or more business computers to obtain obtain one of replenishment and consumption activity data related to an inventory. A model for variations in the inventory is created. The model is used to determine estimates of variation for one of currently planned replenishment activities and currently planned consumption activities. The estimates of variation are used to predict future inventory levels. A system including one or more agent computers is also described.

Abstract: A method of calculating an order quantity for a product to maintain an inventory level at a future time includes determining an inventory sum and an inventory coefficient of the product over a previous time interval, determining a demand sum and a demand coefficient for the product over the previous time interval, determining an orders sum and an order coefficient for the product over the previous time interval, multiplying the inventory sum and the inventory coefficient to produce an inventory level, the demand sum and the demand coefficient to produce a demand level, and the orders sum and the order coefficient to produce an order level, and summing the inventory level, the demand level, and the order level to obtain the order quantity.