Abstract: Disclosed are techniques for training a position estimation module. In an aspect, a first network entity obtains a plurality of positioning measurements, obtains a plurality of positions of one or more user equipments (UEs), the plurality of positions determined based on the plurality of positioning measurements, stores the plurality of positioning measurements as a plurality of features and the plurality of positions as a plurality of labels corresponding to the plurality of features, and trains the position estimation module with the plurality of features and the plurality of labels to determine a position of a UE from positioning measurements taken by the UE.

Abstract: Disclosed are techniques for communication. In an aspect, a first network entity monitors performance of a machine learning positioning model based on one or more parameters, wherein the machine learning positioning model is used for positioning a user equipment (UE), and transmits, to a second network entity, a failure indication for the machine learning positioning model based on a number of failures of the machine learning positioning model satisfying a maximum number of failures before expiration of a failure timer.

Abstract: Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) obtains, during a positioning procedure with a location server, one or more positioning measurements of one or more positioning reference signal (PRS) resources transmitted by one or more network nodes, applies a machine learning model to at least the one or more positioning measurements to obtain one or more predicted future positioning measurements associated with the one or more network nodes, and transmits positioning information to the location server, wherein the positioning information comprises the one or more positioning measurements and the one or more predicted future positioning measurements, a current position of the UE determined based, at least in part, on the one or more positioning measurements and a predicted future position of the UE determined based, at least in part, on the one or more predicted future positioning measurements, or both.

Abstract: A method for optimizing cross Subscriber Identity Module (SIM) calling by a User Equipment (UE), comprising: detecting, by the UE, an event associated at the UE, and cross SIM calling is established at the UE; initiating, by the ePDG of the AP, an evolved Packet data gateway (ePDG) at a communication processor (CP) of the UE based on the call being established; and processing, by the CP of the UE, the cross SIM data packets using an IP security tunnel.

Abstract: In order to inhibit the growth of fungi, such as Cryptococcus neoformans, silver nanoparticles are synthesized and capped with an extract of Caralluma sinaica. The silver nanoparticles capped with the extract of Caralluma sinaica are made by adding the extract of Caralluma sinaica to an aqueous silver nitrate solution to reduce the silver nitrate and form a suspension of silver nanoparticles capped with the extract of Caralluma sinaica. The silver nanoparticles capped with the extract of Caralluma sinaica are removed from the suspension by centrifugation or the like. The silver nanoparticles capped with Caralluma sinaica extract exhibit strong antifungal activity. To treat a Cryptococcus neoformans infection, an effective dose of the silver nanoparticles capped with Caralluma sinaica extract may be administered to a patient in need thereof.

Abstract: Methods and apparatus for predicting wireless measurements based on virtual access points is described. In some embodiments, a location of a user equipment (UE) may be obtained, and given the location of the UE, an output may be generated using a machine learning model, the output including one or more predicted wireless measurements. The output may be indicative of a wireless channel in a multipath environment. In some variants, the machine learning model may have been trained by obtaining a training dataset including multipath components data and ground truth locations of a wireless device, and performing an optimization with respect to the multipath components data and the ground truth locations. In some implementations, a training output including a predicted multipath component may be produced during the training, and the optimization may include an iterative minimization of an error between at least the predicted multipath component and a labeled multipath component.

Abstract: A method for enhancing adhesion of a curable composition to a cement-based object includes applying a graphene oxide (GO) containing dispersion on a surface of the cement-based object thereby forming a GO-treated surface on the cement-based object. The method includes disposing the curable composition on the GO-treated surface of the cement-based object. The method includes curing the curable composition by heating thereby forming a GO interfacial layer and an epoxy resin layer. The GO interfacial layer is between the surface of the cement-based object and the epoxy resin layer. The curable composition includes an epoxy monomer and an amine curing agent. The GO interfacial layer has a thickness of from 0.1 to 10 nanometers (nm).

Abstract: Invention deals with a macular carotenoid formulation comprising Carotenoids, Lutein, Zeaxanthin, Meso Zeaxanthin, Beta Carotene, Alpha Carotene, Lycopene and Cryptoxanthin in a synergistic combination. The formulation helps in increasing macular pigment optical density (MPOD) related to prevention of age-related macular degeneration (ARMD). The formulation is used as a nutrient, nutraceutical or dietary supplement. The dietary supplement may be formulated as soft gel capsules, two-piece hard-shell capsules, liquid-fill capsules, tablets, effervescent granules, gummies, powder mixes, stick packs, beverages, emulsions, bakery products, dairy products, tinctures, oil suspensions, beadlets, powders, cold water-soluble powders, emulsions and granules or any combination thereof. The present invention can be used for the development of functional food, dietary plan and as a nutritional supplement.

Abstract: Disclosed are techniques for wireless signaling. In an aspect, a wireless sensing node receives a radio frequency for sensing (RF-S) configuration, performs one or more RF-S procedures based on the RF-S configuration, obtains sea state information based on the one or more RF-S procedures, and transmits the sea state information to a network component.

Abstract: A first sensing entity may receive, from a second sensing entity, a sensing information message that may include a first set of sensing attributes associated with a set of objects within an area associated with the first sensing entity. The first sensing entity may transmit a set of sensing signals at a target object. The first sensing entity may receive a set of reflected sensing signals based on the set of sensing signals and the target object. The first sensing entity may measure a second set of sensing attributes associated with the target object based on the set of reflected sensing signals and the first set of sensing attributes. The measured second set of sensing attributes may be more accurate than a set of sensing attributes that are not based on the first set of sensing attributes.

Abstract: The method of metered switching for a high-performance liquid chromatography (HPLC) sample injector is a method of controlled switching for a HPLC sample injector to control the amount of the sample being transferred to the HPLC separation column. In a load mode of the HPLC sample injector, a sample to be tested is injected therein until a sample loop is filled. The HPLC sample injector is switched into an injection mode such that a pressurized mobile phase pushes the sample through the sample loop and out of an outlet port. The HPLC sample injector is then switched back into the load mode at a selected time corresponding to a desired volume of the sample to be dispensed from the outlet port. The time-dependent correspondence between a flow rate of the pressurized mobile phase and the desired volume of the sample for the sample loop is already known.

Abstract: This disclosure provides systems, methods, and devices for wireless communication that support a sensing operation. In a first aspect, a method of wireless communication includes transmitting a configuration associated with a sensing operation. The method also includes receiving, from a network entity, a report based on the sensing operation performed by the network entity and that indicates an electromagnetic profile associated with an environment. Other aspects and features are also claimed and described.

Abstract: Apparatuses and methods for cell DRX impact reference signals for positioning and sensing are described. An apparatus is configured to receive, from a network entity, an UL reference signal configuration indication. The UL reference signal configuration associates a UL reference signal transmission occasions set with active/inactive DRX modes of a cell(s) associated with a UE. The apparatus is configured to provide, for a TRP(s) associated with the cell(s), and at the set of UL reference signal transmission occasions, an UL reference signal(s) during a portion of the active DRX mode based on the UL reference signal configuration. Another apparatus is configured to configure, for a UE, an UL reference signal configuration that associates UL reference signal transmission occasions with active/inactive DRX modes of a cell(s) associated with the UE. The apparatus is configured to provide, for the UE, the UL reference signal configuration.

Abstract: In one aspect, a UE receives, from a network entity, at least one of: (1) a first indication of a first mapping and a first list of indices for first location information, where the first location information is associated with a first set of network nodes and a first set of PRS resources and where the first mapping associates each index in the first list of indices with at least one PRS resource in the first set of PRS resources, or (2) a second indication of a previous implementation of the first mapping. The UE selects or configures at least one AI/ML positioning model based on at least one of the first indication or the second indication.

Abstract: Aspects presented herein may improve radio frequency (RF) sensing accuracy for an RF sensing node by enabling the RF sensing node to perform RF sensing using multiple antenna/antenna panels. In one aspect, a UE transmits, to a sensing entity, an indication of a capability to perform RF sensing using a set of antenna panels. The UE receives, from the sensing entity based on the indication, a configuration to perform an RF sensing operation using a subset of antenna panels in the set of antenna panels, where each antenna panel in the subset of antenna panels is configured to perform a corresponding RF sensing operation for each antenna panel. The UE performs, based on the configuration, the RF sensing operation via each antenna panel in the subset of antenna panels.

Abstract: A wireless device may receive a configuration for a measurement of a set of reference signals (RSs). The set of RSs may include a first subset of RSs and a second subset of RSs. The wireless device may receive the set of RSs from a network node. The first subset of RSs may be associated with a first transmission (Tx) power setting and the second subset of RSs may be associated with a second Tx power setting. The first Tx power setting may be different from the second Tx power setting. The wireless device may measure the set of RSs. The wireless device may output the measured set of RSs for a training of a positioning model. The wireless device may include a user equipment (UE) or a positioning reference unit (PRU).

Abstract: According to one aspect, a computer-implemented method can be used for producing an anomaly detection model. The method includes obtaining a learning data stream from a physical system, incrementally computing principal components of the learning data stream, performing orthonormalization of the principal components computed so as to obtain an orthonormal base representing the learning data stream, and producing the anomaly detection model including the orthonormal base and a detection threshold defined by a user. The anomaly detection model can then be applied to a physical system.

Abstract: A method implemented by computer for generating a model for anomaly detection in a system includes obtaining a learning data matrix corresponding to a normal operation of the system, decomposing the learning data matrix into singular values of the matrix of learning data, calculating a new base, defining a maximum Mahalanobis distance threshold representing a limit of the normal operation of the system, and defining an anomaly detection model from the new base and from the maximum Mahalanobis distance threshold.

Abstract: A user equipment (UE) may receive a configuration message including a configuration for a transmission of a set of positioning signals associated with a plurality of transmission (Tx) power settings. The set of positioning signals may include a first subset of positioning signals and a second subset of positioning signals. The UE may transmit the first subset of positioning signals using a first Tx power setting of the plurality of Tx power settings. The UE may transmit the second subset of positioning signals using a second Tx power setting of the plurality of Tx power settings.

Abstract: This disclosure provides systems, methods, and devices for wireless communication that support sensing assisted positioning. In a first aspect, a method of wireless communication includes receiving, from a first management function of a network, a first configuration that indicates a first parameter associated with a sensing operation operable to measure a characteristic of an object within an environment. The method also includes receiving, from a second management function of the network, a second configuration that indicates a second parameter associated with a positioning operation operable to identify a position of the object within the environment based on the characteristic The method further includes transmitting a sensing report based on the sensing operation and that indicates the characteristic, and transmitting a positioning report. Each of the positioning report and the sensing report indicating the position of the object within the environment.