Abstract: A 3D integrated structure and a method for fabricating the structure. In the method, a first trimming process is performed in a peripheral region of a wafer stack to form a chamfered surface adjacent to and surrounding an active device region. As a result, a thickness of the wafer stack along the chamfered surface gradually decreases from an edge of the active device region outward. In this way, a photoresist layer can be subsequently easily applied to cover the junction of the active device region and the chamfered surface, without the formation of discontinuities there, which may affect the subsequent processes. Additionally, in the method, a second trimming process is performed at an edge of the peripheral region to form a clamping surface adjacent to and surrounding the chamfered surface. In this way, it is unnecessary to clamp the wafer stack at a top surface thereof.

Abstract: An optical assembly and a vehicle lamp are described. The optical assembly has a main exit direction, and includes a light source, a first light guide element and a second light guide element which are arranged in a superposed fashion in the main exit direction. The light source is allocated to the first light guide element, and the first light guide element has a first light in-coupling region and a first light out-coupling surface, the second light guide element has a second light in-coupling surface and a second light out-coupling surface, with the first light out-coupling surface facing the second light in-coupling surface. A light distribution structure is provided on at least a partial segment of at least one of the first light out-coupling surface and the second light in-coupling surface. The vehicle lamp includes the optical assembly described above.

Abstract: Systems and methods relating to improving the experience of gig-economy workers are disclosed, with particular reference to gig-economy work involving vehicle use. During or after performance of gig-economy work, data automatically collected may be used to generate and present recommendations or education points to gig-economy workers. Such recommendations may include targeted alerts to notify gig-economy workers of high-demand situations or to coordinate between gig-economy workers and gig-economy customers. Alerts may be generated based upon current excess demand for gig-economy services, as well as gig-economy worker availability and preferences. For example, alerts may be generated in response to detecting emergency conditions in an area in order to mobilize a large number of gig-economy transportation service providers.

Abstract: A computer-implemented method for determining a classification and/or regression result based on a provided input signal. The method includes: providing a first part, configured to denoise the provided input signal based on the input signal and a randomly drawn first value; randomly drawing a plurality of first values; determining, by the first part, a plurality of denoised signals, wherein denoised signals are each determined based on the provided input signal and a first value from the plurality of first values; determining, by a model, a plurality of predicted values based on the denoised values, wherein each predicted value characterizes a classification of a denoised signal or a regression results based on a denoised signal; providing an aggregated signal characterizing an aggregation of the predicted values, wherein the aggregated signal characterizes the classification and/or regression result determined by the method.

Abstract: Antibodies that bind SARS-CoV spike protein, SARS-CoV-2 spike protein, and methods of using same for treating or preventing conditions associated with SARS or COVID-19 and for detecting SARS-CoV or SARS-CoV-2.

Abstract: Computer-implemented method for training a machine learning system to denoise a provided input signal. The method includes: providing a first input signal and a first value to a first part of the machine learning system, wherein the first input signal characterizes a noisy signal; determining, by the first part, a first output signal for the first input signal and the first value; determining, by a second part of the machine learning system, a second value based on the first output signal, wherein the second value characterizes a probability of the first output signal to characterize a noisy signal; determining, by the second part, a third value based on a supplied second input signal, wherein the second input signal characterizes a non-noisy signal and wherein the third value characterizes a probability of the second input signal to characterize a non-noisy signal; training the machine learning system.

Abstract: A computer-implemented method for training an encoder. The encoder is configured for determining a latent representation of an image. Training the encoder includes: determining a latent representation and a noise image by providing a training image to the encoder, wherein the encoder is configured for determining a latent representation and a noise image for a provided image; masking out parts of the noise image, thereby determining a masked noise image; determining a predicted image by providing the latent representation and the masked noise image to a generator of a generative adversarial network; training the encoder by adapting parameters of the encoder based on a loss value, wherein the loss value characterizes a difference between the predicted image and the training image.

Abstract: A computer-implemented method of processing digital image data. The method includes: determining, by an encoder configured to map a first digital image to an extended latent space associated with a generator of a generative adversarial network, GAN, system, a noise prediction associated with the first digital image, determining, by the generator of the GAN system, at least one further digital image based on the noise prediction associated with the first digital image and a plurality of latent variables associated with the extended latent space.

Abstract: Compounds and pharmaceutical compositions that modulate kinase activity, including mutant EGFR and mutant HER2 kinase activity, and compounds, pharmaceutical compositions, and methods of treatment of diseases and conditions associated with kinase activity, including mutant EGFR and mutant HER2 activity, are described herein.

Abstract: Systems and methods relating to improving the experience of gig-economy workers are disclosed, with particular reference to gig-economy work involving vehicle use. During or after performance of gig-economy work, data automatically collected may be used to generate and present recommendations or education points to gig-economy workers. Such recommendations may include targeted alerts to notify gig-economy workers of high-demand situations or to coordinate between gig-economy workers and gig-economy customers. Alerts may be generated based upon current excess demand for gig-economy services, as well as gig-economy worker availability and preferences. For example, alerts may be generated in response to detecting emergency conditions in an area in order to mobilize a large number of gig-economy transportation service providers.

Abstract: The present disclosure pertains to techniques for reducing inaccuracies in context aware policies (CAP) with real-time feedforward validation in extended reality environments. In a particular aspect, a extended reality system is configured to author, by a user using the head-mounted device, a rule or policy or context aware policy (CAP) including one or more target actions and triggering context instances, capture, using one or more sensors, context history records for the user, render, by the head-mounted device, one or more validation scenes based on the rule or policy or CAP and the context history records, validate, by the user using the head-mounted device, the one or more validation scenes within an extended reality environment, and update, by the user using the head-mounted device, the rule or policy or CAP based on the validation.

Abstract: Features described herein generally relate to learning and recognizing object-centered routines. Particularly, object-centered routines can be learned and recognized by collecting data corresponding to a user. The data can include information representing interactions by the user with respect to objects in an environment. The routine can be learned by presenting a visual graph to the user. The user can define nodes associating an interaction with an object, specify a relationship between nodes, and arrange the nodes into segments. The visual graph can be stored, and a routine can be recognized based on the visual graph.

Abstract: Features described herein generally relate to generating and modifying policies with an artificial intelligence (AI) platform based on user activities. Particularly, data comprising characteristics of activities performed by a user in real-world and virtual environments is collected, a control structure is predicted based on the data and model parameters learned from historical policies, and a new policy is generated or a pre-existing policy is modified based on the control structure.

Abstract: The present disclosure relates to defining and modifying behavior in an extended reality environment. The systems and methods include capturing, using the one or more audio sensors, a natural language explanation of a rule or policy from the user, extracting features from the natural language explanation of the rule or policy, wherein the features include one or more conditions, one or more actions, and connections between the one or more events, conditions, and actions, predicting a control structure comprised of one or more conditional statements based on the extracted features and model parameters learned from historical rules or policies, and generating the rule or policy based on the control structure, wherein the rule or policy comprises the one or more conditional statements for executing the one or more actions based on evaluation of the one or more conditions.

Abstract: The present disclosure relates to refining context aware policies in extended reality systems. In one aspect, an extended reality system is provided that performs operations including: accessing data collected from user interactions while using a context aware policy in an extended reality environment, determining a support set and confidence score for the context aware policy based on the data, generating replacement policies for the context aware policy, determining a support set and confidence score for each of the replacement policies based on the data, identifying a replacement policy from the replacement policies as a replacement for the context aware policy based on the support sets and confidence scores, and updating one or more conditions or an action defined by the context aware policy with a modified version of the one or more conditions or the action defined by the replacement policy to generate an updated context aware policy.

Abstract: Features described herein generally relate to predicting policies with an artificial intelligence (AI) platform based on shared or similar interactions. Particularly, data that includes information about users and a corpus of policies is collected, embeddings are generated for the collected data, and policies are predicted based on the embeddings. The policies can be predicted based on content-based filtering, collaborative filtering, and/or game theory approaches.

Abstract: The present disclosure relates to systems and methods for defining and modifying behavior in an extended reality environment. The systems and methods include receiving a request to build or modify a rule or policy for a given user or activity, obtaining a template based on the user or the activity, displaying the template and tools for editing the template, receiving a modification to the template via the user interacting with the tools of the user interface, and modifying the template based on the modification to generate the rule or policy. The modification includes changing the initial value for the actions or the conditions of the template and saving the template as a separate instance representative of the rule or policy, and the rule or policy includes one or more conditional statements for executing one or more of the actions based on evaluation of one or more of the conditions.

Abstract: Therapy for influenza using a combination of a neuraminidase inhibitor, a macrolide antibiotic, and a non-steroidal anti-inflammatory drug has been found to provide improved clinical outcomes and reduced incidence of viral quasispecies compared to conventional treatment with neuraminidase inhibitors alone. Effective treatment schedules are also provided. The drug combination can be used in concert with a proton-pump inhibitor and/or an additional antibacterial antibiotic.

Abstract: A method for wafer etching in a deep silicon trench etching process includes the following steps: a. electrostatically absorbing a wafer using an electrostatic chuck, and stabilizing the atmosphere required by the process (S110); b. performing the sub-steps of a main process for the wafer, and the time for the sub-steps of the main process being shorter than the time required by the wafer main process; c. releasing the electrostatic adsorption of the electrostatic chuck on the wafer; d. determining whether the cumulative time of the sub-steps of the main process reaches a predetermined threshold or not, if so, performing the step e (S150), and if not, repeating the operations in the steps a to c (S140); and e. ending a wafer manufacturing process. The etching method avoids the wafer from continuous contact with the electrostatic chuck, reduces electrostatic accumulation on the surface of the wafer, and therefore solves the problem of resist reticulation on the surface of the wafer in the DSIE process.

Abstract: A critical dimension compensating method of a deep trench etching process includes: obtaining an etching critical dimension difference; compensating an masking layer layout for wafer etching according to a distance between an etching position and the center position of the wafer, and the etching critical dimension difference; and performing a deep trench etching to the wafer according to the compensated masking layer layout. The dimension of the etching patterns of the masking layer layout is compensated by using half of the critical dimension difference as the compensation value, such that the etch rate difference and the etching dimension difference caused by uneven distribution of the critical dimension at different wafer locations during the deep trench etching process are improved, thus greatly improving the uniformity of the critical dimension of the deep trench etching structure.