Abstract: An apparatus is provided which comprises a full adder including magnetoelectric material and spin orbit material. In some embodiments, the adder includes: a 3-bit carry generation structure and a multi-bit sum generation structure coupled to the 3-bit carry generation structure. In some embodiments, the 3-bit carry generation structure includes at least three cells comprising magnetoelectric material and spin orbit material, wherein the 3-bit carry generation structure is to perform a minority logic operation on first, second, and third inputs to generate a carry output. In some embodiments, the multi-bit sum generation structure includes at least four cells comprising magnetoelectric material and spin orbit material, wherein the multi-bit sum generation structure is to perform a minority logic operation on the first, second, and third inputs and the carry output to generate a sum output.

Abstract: An apparatus is provided which comprises one or more magnetoelectric spin orbit (MESO) minority gates with different peripheral complementary metal oxide semiconductor (CMOS) circuit techniques in the device layer including: (1) current mirroring, (2) complementary supply voltages, (3) asymmetrical transistor sizing, and (4) using transmission gates. These MESO minority gates use the multi-phase clock to prevent back propagation of current so that MESO gate can correctly process the input data.

Abstract: Embodiments include an embedded dynamic random access memory (DRAM) device, a method of forming an embedded DRAM device, and a memory device. An embedded DRAM device includes a dielectric having a logic area and a memory area, and a trace and a via disposed in the logic area of dielectric. The embedded DRAM device further includes ferroelectric capacitors disposed in the memory area of dielectric, where each ferroelectric capacitor includes a first electrode, a ferroelectric layer, and a second electrode, and where the ferroelectric layer surrounds the first electrode of each ferroelectric capacitor and extends along a top surface of the dielectric in the memory area. The embedded DRAM device includes an etch stop layer above the dielectric. The second etch stop in the logic area may have a z-height that is approximately equal to a z-height of a top surface of the second etch stop in the memory area.

Abstract: Embodiments include a memory array and a method of forming the memory array. A memory array includes a first dielectric over first metal traces, where first metal traces extend along a first direction, second metal traces on the first dielectric, where second metal traces extend along a second direction perpendicular to the first direction, and third metal traces on the second dielectric, where third metal traces extend along the first direction. The memory array includes a ferroelectric capacitor positioned in a trench having sidewalls and bottom surface, where the trench has a depth defined from a top surface of first metal trace to the top surface of third metal trace. The memory array further includes an insulating sidewall, a first electrode, a ferroelectric, and a second electrode disposed in the trench, where the trench has a rectangular cylinder shape defined by the first, second, and third metal traces.

Abstract: A privacy preserving sensor apparatus is described herein. The privacy preserving sensor apparatus includes a microphone that is configured to output a signal that is indicative of audio in an environment. The privacy preserving sensor apparatus further includes feature extraction circuitry integrated in the apparatus with the microphone, the feature extraction circuitry configured to extract features from the signal output by the microphone that are usable to detect occurrence of an event in the environment, wherein the signal output by the microphone is unable to be reconstructed based solely upon the features.

Abstract: A roller device, including a first tube having a first diameter, and a through-bore having a second diameter smaller than the first diameter, the through-bore extending through and concentric with the first tube, a first rod having a third diameter smaller than the second diameter, a first end, and a second end, where the second end of the first rod is operatively arranged to telescopingly engage with the through-bore of the first tube, a second rod having a fourth diameter equal to the third diameter, a first end and a second end, where the first end of the second rod is operatively arranged to telescopingly engage with the through-bore of the first tube, at least one roller arranged to rotate about the first tube, and a first handle fixedly secured to the first end of the first rod.

Abstract: The present disclosure relates to a tube management device for an infusion set that includes a holding member attachable to the patient and which defines a holding chamber for the tube. The tube may be engaged and disengaged with the device while the lube is operably connected to convey medication. The device may also allow a) the length of flexible tube controlled by the device and b) the position of the final exit of the tube from the holding member relative to the initial entry of the tube into the holding member to both be selectively adjusted. In some embodiments, tire holding chamber is defined by a plurality of channels which may be either non-intersecting or intersecting channels.

Abstract: An insulin infusion set (IIS) device with one or more features designed to achieve longevity in a patients continuous subcutaneous insulin infusion (CSII) site viability. One exemplary feature is an adsorbent material configured to adsorb phenolic excipients (e.g., m-cresol or other preservatives) from the insulin formulation. The adsorbent material may be positioned along a fluid pathway specifically designed to increase and/or extend exposure between the insulin formulation and the adsorbent material. Another exemplary feature is a medicament configured to reduce the patients inflammation or slow the progression of the patients inflammatory response. Yet another exemplary feature is a diffusive catheter configured to deliver the insulin formulation in a diffuse manner.

Abstract: In one embodiment, the present invention is directed to a system with multiple computing hosts each having a hypervisor to provide a virtual environment for the host and one or more containers each including a database instance and at least one database. These databases, and the database instance can be provided as a service to a user of a multi-tenant environment.

Abstract: Portable devices include environmental sensors that generate metrics about the environment (e.g., accelerometers detecting impulses and vibration, and GPS receivers detecting position and velocity). Such devices often use environmental metrics to extract user input directed at the device by the user, and status information about the device and the environment. Presented herein are techniques for using environmental metrics to infer physical activities performed by the user while attached to the device. For example, jogging may be inferred from regular, strong impulses and typical jogging speed; walking may be inferred from regular, weak impulses and typical walking speed; and riding in a vehicle may be inferred from low-level vibrations and high speed (optionally identifying the type of vehicle ridden by the user). Based on these inferences, the device may automatically present applications and/or or adjust user interfaces suitable for the user's physical activity, rather than responsive to user input.

Abstract: Technologies pertaining to calibration of filters of an audio system are described herein. A mobile computing device is configured to compute values for respective filters, such as equalizer filters, and transmit the values to a receiver device in the audio system. The receiver device causes audio to be emitted from a speaker based upon the values for the filters.

Abstract: A wrist-worn pressure sensing device includes a pressure sensor. The wrist-worn pressure sensing device also includes a first strap that sets the position of the pressure sensor on a wearer's wrist and a second strap that engages with the first strap to adjust the overall length of the strap without moving the set position of the pressure sensor on the wearer's wrist.

Abstract: In one embodiment, the present invention is directed to a system with multiple computing hosts each having a hypervisor to provide a virtual environment for the host and one or more containers each including a database instance and at least one database. These databases, and the database instance can be provided as a service to a user of a multi-tenant environment.

Abstract: Portable devices include environmental sensors that generate metrics about the environment (e.g., accelerometers detecting impulses and vibration, and GPS receivers detecting position and velocity). Such devices often use environmental metrics to extract user input directed at the device by the user, and status information about the device and the environment. Presented herein are techniques for using environmental metrics to infer physical activities performed by the user while attached to the device. For example, jogging may be inferred from regular, strong impulses and typical jogging speed; walking may be inferred from regular, weak impulses and typical walking speed; and riding in a vehicle may be inferred from low-level vibrations and high speed (optionally identifying the type of vehicle ridden by the user). Based on these inferences, the device may automatically present applications and/or or adjust user interfaces suitable for the user's physical activity, rather than responsive to user input.

Abstract: A privacy preserving sensor apparatus is described herein. The privacy preserving sensor apparatus includes a microphone that is configured to output a signal that is indicative of audio in an environment. The privacy preserving sensor apparatus further includes feature extraction circuitry integrated in the apparatus with the microphone, the feature extraction circuitry configured to extract features from the signal output by the microphone that are usable to detect occurrence of an event in the environment, wherein the signal output by the microphone is unable to be reconstructed based solely upon the features.

Abstract: A privacy preserving sensor apparatus is described herein. The privacy preserving sensor apparatus includes a microphone that is configured to output a signal that is indicative of audio in an environment. The privacy preserving sensor apparatus further includes feature extraction circuitry integrated in the apparatus with the microphone, the feature extraction circuitry configured to extract features from the signal output by the microphone that are usable to detect occurrence of an event in the environment, wherein the signal output by the microphone is unable to be reconstructed based solely upon the features.

Abstract: According to one embodiment of the present disclosure, a computing device is provided, comprising a processor configured to receive an input. The input includes a first pulse pressure signal obtained using a wearable tonometer affixed to a body of a user. The processor is further configured to apply a transfer function to the first pulse pressure signal, wherein the transfer function converts the first pulse pressure signal into a transformed pulse pressure signal. The transformed pulse pressure signal simulates a second pulse pressure signal of a handheld tonometer concurrently applied to the body of the user.

Abstract: A method for determining a risk of decompensated heart failure in a user includes receiving a first set of data that is fixed with respect to time. A machine-learning model generates one or more initial risk factors based on the first set of data. A second set of data for the user that dynamically updates over time is received from a wearable cardiovascular physiology monitor. The machine-learning model is used to generate dynamic data classifiers based on the one or more initial risk factors. Aggregate risk scores for the user are then indicated based on an evaluation of the second set of data against the dynamic data classifiers. In this way, static electronic medical records may be combined with dynamic, real-time data from wearable cardiovascular physiology monitors to provide an accurate and continuously updating risk of decompensated heart failure for a user.

Abstract: A “Food Logger” provides various approaches for learning or training one or more image-based models (referred to herein as “meal models”) of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with “meal features” that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Abstract: According to one aspect of the present disclosure, a method for estimating blood pressure is provided, comprising training a machine learning model on a cohort data set. The cohort data set may include subject-specific contextual data, time-varying features, and blood pressure measurements for a plurality of subjects. The method may include receiving contextual data for a specific subject, wherein the contextual data includes medical history data of the subject. The method may further include personalizing the machine learning model to the subject based on the contextual data. The method may include calibrating the machine learning model to the subject based on a set of time-varying features and blood pressure measurements of the subject. In addition, the method may include using the machine learning model and the time-varying features for the subject to generate a blood pressure estimate.