Abstract: Described are niclosamide analogue compounds, pharmaceutical compositions thereof, and method of using the corner pounds and compositions for treating a disease associated with dysregulation of the Wnt/Frizzled signaling pathway, such as cancer, fatty liver, antibiotic resistance, and viral infection. The disclosed compounds and compositions may also be used for modulating mitochondrial function and for treating certain non-cancer diseases and/or diorders, such as diabetes, fibrotic disease, primary sclerosing cholangitis.

Abstract: Embodiments of the disclosed technologies receive first event data associated with a first party application, receive second event data representing a click, in the first party application, on a link to a third party application, receive third event data from the third party application, convert the third event data to a label, map a compressed format of the labeled third event data to the first event data and the second event data to create multi-party attribution data, group multiple instances of the multi-party attribution data into a batch, add noise to the compressed format of the labeled third event data in the batch, and send the noisy batch to a second computing device. A debiasing algorithm can be applied to the noisy batch. The debiased noisy batch can be used to train at least one machine learning model.

Abstract: A rotor blade system. The rotor blade system includes a rotor and a plurality of blades coupled to the rotor. The plurality of blades are arranged in an airfoil distribution pattern. The airfoil distribution pattern includes one or more baseline blades and one or more intentionally mistuned blades including an intentional mistuning feature.

Abstract: Implementations of the present specification disclose methods, apparatuses, and devices for training an object detection system by using a gradient fine-tuning technique. In one aspect, the method includes: providing a training image as input to the object detection system; processing the training image by the object detection system; determining a gradient norm of each neural network layer based on object annotation data and the detection result corresponding to the training image; and updating, for each neural network layer, parameter values of the neural network layer based on an average of gradient norms and the gradient norm of the neural network layer.