Abstract: A fan and an electronic device are provided. The fan includes a hub, an outer frame surrounding the hub, and a plurality of blades connected between the hub and the outer frame. The outer frame includes a first side facing an air inlet of the fan, a second side facing an air outlet of the fan, and an inner wall between the first side and the second side. Each of the plurality of blades includes a first end connected to the hub and a second end connected to the outer frame. The second end includes a first region and a second region, the second region is connected to the inner wall. The first region extends from the second region and is disposed above the first side. A first notch is defined among the first regions of two adjacent blades and the first side.

Abstract: Examples of methods for thermal image determination are described. In some examples, a method may include determining, using a first machine learning model, a first thermal image of a first layer of additive manufacturing. In some examples, the method may include determining, using a second machine learning model, a second thermal image of a second layer based on a simulated thermal image. The second thermal image may have a second resolution that is greater than a first resolution of the simulated thermal image in some examples. In some examples, the method may include determining, using a third machine learning model, a third thermal image based on the first thermal image and the second thermal image.

Abstract: The present disclosure relates to methods of inhibiting vimentin activity, methods of screening for new vimentin inhibitors and uses of new vimentin inhibitors.

Abstract: Examples of the present disclosure relate to a method for processing three dimensional (3D) models. The method comprises categorizing the 3D models into geometrical characteristic categories, creating a geometrical template corresponding to each category, determining a label placement for each geometrical template, assigning a label to each 3D model based on the determined label placement and assigning a packing position to the 3D models based on their corresponding template. The method is such that some categories comprise more than one 3D model.

Abstract: In an example, a collection of compute resources corresponding to a class of devices is identified with a request and a synthesis routine is performed via a number of destinations corresponding to the class of devices. In an example, a type of compute resource to use with an operation of a request is determined, a device with the type of compute resource determined for the operation of the request is identified; the identified device performs the operation of the request within a bounds of a policy, and a result of the operation is communicated to a remote storage location.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions that when executed by the processor are to cause the processor to access a reduced resolution three-dimensional (3D) model file of an object to be built in a build bed of a 3D printing system, the reduced resolution 3D model file comprising a reduced resolution file of a first resolution 3D model file of the object. The instructions may also cause the processor to determine a packing arrangement for the object and a plurality of other objects to be built in the build bed through use of the reduced resolution 3D model file and output the determined packing arrangement for the 3D printing system to print the object and the other objects.

Abstract: Examples of methods for thermal image generation are described. In some examples, a method may include determining a score map based on first features from a model, a simulated thermal image at a first resolution, and second features of the simulated thermal image. In some examples, the method may include generating a thermal image at a second resolution based on the score map, the first features, and the second features, where the second resolution may be greater than the first resolution.

Abstract: Described herein are compounds that are inhibitors of p21-activated kinases (PAKS). In particular, the compounds described herein are demonstrated to be selective PAK4 inhibitors. The compounds described herein are also demonstrated to reduce the expression of key immune checkpoint molecules, such as PD-1 and CHEK2. Also described herein are pharmaceutical compositions containing such compounds, methods for using such compounds in the treatment of cancers, more specifically, the treatment of pancreatic and lung cancers, and to related uses.

Abstract: Examples of methods are described. In some examples, a method includes generating, using a first branch of a machine learning model, a first agent map based on a layer image. In some examples, the method includes generating, using a second branch of the machine learning model, a second agent map. In some examples, the first agent map and the second agent map indicate printing locations for different agents.

Abstract: Examples of methods for point cloud alignment are described herein. In some examples, a method includes orienting a model point cloud or a scanned point cloud based on a set of initial orientations. In some examples, the method includes determining, using a first portion of a machine learning model, first features of the model point cloud and second features of the scanned point cloud. In some examples, the method includes determining, using a second portion of the machine learning model, correspondence scores between the first features and the second features based on the set of initial orientations. In some examples, the method includes globally aligning the model point cloud and the scanned point cloud based on the correspondence scores.

Abstract: An example device includes: a memory storing instructions; and a processor connected to the memory. The instructions are to cause the processor to: receive predetermined locations of a fluidic input location and fluidic output locations at a three-dimensional (3D) object model; generate respective paths between the fluidic input and each of the fluidic outputs via associated portions of the 3D object model; replace the respective paths with respective hollow connectors that have respective fluidic resistance selected such that each of the fluidic outputs have a predetermined flow rate from the fluidic input to the fluid outputs; and store, at the memory, data indicative of locations and dimensions of the respective hollow connectors, relative to the fluidic input and the fluidic outputs, the data for use by a three-dimensional printer to print a part that includes the fluidic input, the fluidic outputs and the respective hollow connectors.

Abstract: Examples of methods are described herein. In some examples, a method includes determining a quantity of inner voxels in a canonical direction from each surface voxel of a set of surface voxels of a three-dimensional (3D) object model. In some examples, the method includes generating an encoded representation of the 3D object model, the encoded representation indicating a location of each surface voxel and the quantity of inner voxels for each surface voxel.

Abstract: Examples of methods are described. In some examples, a method may include printing a first solid material phase region. In some examples, the method may include printing a second solid material phase region distanced from the first solid material phase region. In some examples, the method may include printing a plurality of distanced beams, each having a thickness that is not more than one millimeter, to form a weak material phase region between the first solid material phase region and the second solid material phase region. In some examples, the weak material phase region has a volumetric density less than one.

Abstract: A disk-drive suspension includes a load beam, a flexure laid on top of the load beam, a first terminal provided on the flexure, and a first bump arranged on a top surface of the first terminal. The first terminal includes a narrow part having a first width in a first direction and including a center of the first terminal, and a wide part having a second width in the first direction greater than the first width. The wide part and the narrow part are arranged in a second direction intersecting the first direction. The first bump has, at the center, a first height from a bottom surface of the first terminal. The first height is greater than the first width.

Abstract: Examples of a thermal behavior prediction method are described herein. In some examples of the thermal behavior prediction method, a predicted heat map of a layer corresponding to a three-dimensional (3D) model is computed using at least one neural network. The predicted heat map is computed based on a contone map corresponding to the 3D model.

Abstract: Examples of methods for monitoring additive manufacturing by an electronic device are described herein. In some examples, a predicted thermal image is calculated for a layer. In some examples, a captured thermal image is obtained for the layer. In some examples, a risk score is calculated for the layer based on the predicted thermal image and the captured thermal image. In some examples, a mitigation operation is performed in response to determining that the risk score is outside of a threshold range.

Abstract: Examples of methods for predicting object deformations are described herein. In some examples, a method includes predicting a point cloud. In some examples, the predicted point cloud indicates a predicted object deformation. In some examples, the point cloud may be predicted using a machine learning model and edges determined from an input point cloud.

Abstract: Examples of methods for determining displacement maps are described herein. In some examples of the methods, a method includes determining a displacement map for a three-dimensional (3D) object model based on a compensated point cloud. In some examples, the method includes assembling the displacement map on the 3D object model for 3D manufacturing.

Abstract: Examples of methods are described. In some examples, a method includes determining, using a variational autoencoder model, a latent space representation. In some examples, the latent space representation is of object model data. In some examples, the method includes predicting manufacturing powder degradation. In some examples, predicting the manufacturing powder degradation is based on the latent space representation.