Home treatment protocol for dentin hypersensitivity with hydroxyapatite-based biodynamic toothpaste and lactoferrin: a pilot study.

Background: In recent years, there has been a gradual increase in cases of dentin hypersensitivity, often related to gingival recession, enamel abrasion from brushing, and wear of root cementum. This condition can affect patients of all ages but is more common between 20 and 40 years of age, especially in females and individuals with periodontal disease. The study aimed to evaluate and compare the efficacy over time of a product for at-home treatment of dentin hypersensitivity.

Cardiac Time Intervals under Motion Using Bimodal Chest E-Tattoos and Multistage Processing.

Goal: We present a thin, soft, and chest conformable bimodal sensor, known as the chest e-tattoo, coupled with an advanced signal processing framework to accurately identify various cardiac events, and thereby extract cardiac time intervals even during body motion.

Methods: We built a wireless electronic tattoo that features synchronous electrocardiography (ECG) and seismocardiography (SCG). The SCG measures chest vibrations due to heartbeat, providing information on cardiovascular health that is complementary to the ECG.

Optimizing Sensor Placement for Temperature Mapping during Ablation Procedures.

Accurately mapping the temperature during ablation is crucial for improving clinical outcomes. While various sensor configurations have been suggested in the literature, depending on the sensors' type, number, and size, a comprehensive understanding of optimizing these parameters for precise temperature reconstruction is still lacking. This study addresses this gap by introducing a tool based on a theoretical model to optimize the placement of fiber Bragg grating sensors (FBG) within the organ undergoing ablation.

Noise cleaning the precision matrix of short time series.

We present a comparison between various algorithms of inference of covariance and precision matrices in small data sets of real vectors of the typical length and dimension of human brain activity time series retrieved by functional magnetic resonance imaging (fMRI). Assuming a Gaussian model underlying the neural activity, the problem consists of denoising the empirically observed matrices to obtain a better estimator of the (unknown) true precision and covariance matrices. We consider several standard noise-cleaning algorithms and compare them on two types of data sets.

On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications.

Developing radio access technologies that enable reliable and low-latency vehicular communications have become of the utmost importance with the rise of interest in autonomous vehicles. The Third Generation Partnership Project (3GPP) has developed Vehicle to Everything (V2X) specifications based on the 5G New Radio Air Interface (NR-V2X) to support connected and automated driving use cases, with strict requirements to fulfill the constantly evolving vehicular applications, communication, and service demands of connected vehicles, such as ultra-low latency and ultra-high reliability. This paper presents an analytical model for evaluating the performance of NR-V2X communications, with particular reference to the sensing-based semi-persistent scheduling operation defined in the NR-V2X Mode 2, in comparison with legacy sidelink V2X over LTE, specified as LTE-V2X Mode 4.