Abstract: One or more embodiments relate to a CEM having a hierarchical, interconnected, 3D network of thin, crumpled, graphene sheets, wherein the graphene sheets have irregularly shaped, micro-, macro- and meso-scale pore structures, where the CEM material has a BET SSA between approximately 1400 m2 g?1 and approximately 2200 m2 g?1, and where the CEM has a Raman ID/IG intensity ratio between approximately 0.05 to approximately 1.2, and a Raman I2D/IG intensity ratio between approximately 0.4 and approximately 0.8, and supercapacitors using the CEM as electrodes.

Abstract: One or more embodiments relate to a method for making carbon electrode material (CEM) having the steps: dispersing a carbon feedstock within a catalyst, thereby forming a mixture, wherein the catalyst is made up of particles; melting the carbon feedstock that is dispersed within the catalyst, thereby liquifying the carbon feedstock that coats catalyst particles and infiltrates spaces between the catalyst particles; carbonizing the melted carbon feedstock, thereby forming an interconnected 3D network of carbon nanosheets; converting the carbon nanosheets into graphene nanosheets; washing the graphene nanosheets, thereby forming the CEM; recovering and regenerating the catalyst. Further embodiments relate to repeating the method using recovered and regenerated catalyst.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: The disclosure relates to anti-cancer compounds derived from nuclear steroid receptor binders, to products containing the same, as well as to methods of their use and preparation.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting walking workouts. By accurately and promptly detecting the start of walking workouts activities and automatically distinguishing between walking workout and causal walking activities, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording walking workouts.

Abstract: Embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone. In some embodiments, a method comprises: detecting a crash event on a crash device; extracting multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features, wherein at least one multimodal feature is a rotation rate about a mean axis of rotation; and determining that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.

Abstract: Embodiments are disclosed for head dimension estimation for spatial audio applications. In an embodiment, a method comprises: obtaining, using one or more processors of an audio headset worn on a user's head, acceleration samples and rotation rate samples over a specified time window while the user rotates their head, the acceleration samples and rotation rate samples measured using motion sensors in the headset; determining a function that relates the acceleration samples to the rotation rate samples; comparing the function to a plurality of reference functions, where each reference function corresponds to a different head dimension in a nominal range of head dimensions; and estimating a dimension of the user's head based on the comparing.

Abstract: In an example method, a mobile device obtains sample data generated by one or more sensors over a period of time, where the one or more sensors are worn by a user. The mobile device determines that the user has fallen based on the sample data, and determines, based on the sample data, a severity of an injury suffered by the user. The mobile device generates one or more notifications based on the determination that the user has fallen and the determined severity of the injury.

Abstract: The invention relates to a diagnostic kit for multiple detection of 4 viruses of the Family Coronaviridae: HCoV, SARS-CoV, MERS-CoV and the SARS-CoV-2 viral strain that has caused a pandemic of the disease known as COVID-19. The kit uses a “One-Step” approach with quantitative gene amplification after backward transcription of the viral genome (rRT-PCR). In order to avoid potential false negatives, the invention contains a double control using Porcine Epidemic Diarrhoea Virus (PEDV-CoV) and Ribonuclease P (RNase P-RP).

Abstract: In an example method, a mobile device obtains sample data generated by one or more sensors over a period of time, where the one or more sensors are worn by a user. The mobile device determines that the user has fallen based on the sample data, and determines, based on the sample data, a severity of an injury suffered by the user. The mobile device generates one or more notifications based on the determination that the user has fallen and the determined severity of the injury.

Abstract: The present disclosure relates to methods and systems of determining swimming metrics of a user during a swimming session. The method can include receiving, by a processor circuit of a user device, motion information from one or more motion sensors of the user device; determining, by the processor circuit using the motion information, a first set of rotational data of the user device, wherein the first set of rotational data is expressed in a first frame of reference; converting, by the processor circuit, the first set of rotational data into a second set of rotational data, wherein the second set of rotational data is expressed in a second frame of reference; determining, by the processor circuit, one or more swimming metrics of the user; and outputting the one or more swimming metrics.

Abstract: A system may have electronic devices with wireless communications circuitry. Devices may transmit short-range wireless signals such as advertising packets. Each advertising packet may contain information on the motion context of the transmitting device. By comparing motion context information for received packets with local motion context information, an electronic device may analyze received signal strength indicator measurements with enhanced accuracy. Presence-in-vehicle state information and/or other device context may also be obtained from nearby devices by comparing local and received motion context.

Abstract: Example embodiments of the present disclosure relate to a solution for ph-AFQMC with direct product multi-Slater determinants trial. Multiple active spaces of a molecular system may be obtained and multiple coefficient tensors may be determined respectively. A composite coefficient tensor may be determined based on a tensor product of the multiple coefficient tensors of the multiple active spaces, and a trial wave function may be further determined based on the composite coefficient tensor and a cutoff value. As such, the multiple coefficient tensors for the multiple active spaces may be determined, thus the computation can be reduced. Additionally, since a cutoff value is used, the composite coefficient tensor is a sparse tensor and the number of Slater determinants may be reduced. Further, the determined trial wave function may be further used in a ph-AFQMC algorithm, and a balance between accuracy and efficiency may be achieved.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: One or more electronic device may use motion and/or activity sensors to estimate a user's 6 minute walking distance. In particular, because users typically walk at less than their maximum output and in imperfect conditions, control circuitry within the device(s) may rely on walks of shorter distances to estimate the 6 minute walking distance. For example, the control circuitry may gather activity information for the user, such as heart rate, calories burned, and step count, and analyze a distance component and a speed component for periods in which the user has walked. Individual 6 minute walk distance estimates may be generated based on each of the activity information, distance component, and speed component. The distance and speed estimates may be corrected for walking behaviors that deviate from an ideal testing environment, and may then be fused with the activity estimate to generate a final 6 minute walk distance estimate.

Abstract: In an example method, a mobile device obtains sample data generated by one or more sensors over a period of time, where the one or more sensors are worn by a user. The mobile device determines that the user has fallen based on the sample data, and determines, based on the sample data, a severity of an injury suffered by the user. The mobile device generates one or more notifications based on the determination that the user has fallen and the determined severity of the injury.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting cardio machine activities, estimating user direction of travel, and monitoring performance during cardio machine activities. By accurately and promptly detecting cardio machine activities and automatically distinguishing between activities performed on different types of cardio machines, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording activities on a wide variety of cardio machines. In various embodiments, cardio machine activity detection techniques may use magnetic field data from a magnetic field sensor to improve the accuracy of orientation data and device heading measurements used to detect the end of a cardio machine activity.

Abstract: Embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone). In some embodiments, a method comprises: detecting, with at least one processor, a crash event on a crash device; extracting, with the at least one processor, multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing, with the at least one processor, a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features; and determining, with the at least one processor, that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.

Abstract: Examples are disclosed related to forming solder joints between printed circuits by using radiant heat. One example provides a method of manufacturing an electronic device, the method comprising aligning a contact of a first printed circuit with a via of a second printed circuit. The method further comprises applying radiant heat via an infrared light source to a second surface of the second printed circuit, the radiant heat incident on the via to cause the via to conduct heat to solder located at an interface of the contact and the via, and after heating the solder to reflow, cooling the solder, thereby forming a solder joint between the contact of the first printed circuit and the via of the second printed circuit.