The Argument from Illusion and the Uniqueness Assumption

I argue that the mainstream formulation of the argument from illusion is invalid, and the Uniqueness Assumption which makes the argument valid is suspicious because the intuition of the assumption stems from common sense which is challenged by the argument from illusion. I show that even if sense data were admitted as objects in illusions, the subject can still perceive something real; she can perceive a composite. This means that the sense-datum account of illusion need not apply to perception

Spatial and temporal variation of north-west pacific tropical cyclone under the background of upper ocean warming

879-885Under the background of global warming, the activities of north-west pacific (NWP) tropical cyclones (TCs) are undergoing significant changes. The TC frequencies have been characterized by an initial slow increase followed by a rapid increase and then a decrease, the past 33 years. During the 21st century, the TC frequency of the NWP has clearly decreased. However, the three TC origin types in the NWP have experienced different types of changes. The TC frequencies of origin 1 (10°~22°N,110°~120°E) and origin 2 (8°~20°N,125°~145°E) are both increasing, but the TC frequency of origin 3 (5°~20°N,145°~155°E) is decreasing. Under the background of upper ocean warming, the average TC duration has shown a decreasing trend (-0.27d/10a), while the TC mean and maximum intensity has increased (0.93 m/s/10a and 1.57 m/s/10a, respectively). Therefore, the potential threats of TC activities to NWP coastal countries are likely to intensify. The changes in the thermal state of the upper ocean have many effects on TC activities. Sea surface temperature is not the main factor affecting the frequency of TCs. However, the response of TCs to the upper ocean heat content is obvious

Item recommendations for cache and synchronization of application stores

To reduce the latency of rendering the page of an app in an application store (e.g., that provides access to downloads of apps to a mobile device), the application store app periodically synchronizes with its backend and caches on the user mobile device app pages that a user is likely to visit. This disclosure uses deep learning models to predict the next N apps that a user is likely to visit based on permitted user activity signals, e.g., demographic information, historical visits to deep links associated with the app, etc