An Investigation into High-Accuracy and Energy-Efficient Novel Capacitive MEMS for Tire Pressure Sensor Application.

Tire pressure monitoring systems (TPMSs) are essential for maintaining driving safety by continuously monitoring critical tire parameters, such as pressure and temperature, in real time during vehicle operation. Among these parameters, tire pressure is the most significant, necessitating the use of highly precise, cost-effective, and energy-efficient sensing technologies. With the rapid advancements in micro-electro-mechanical system (MEMS) technology, modern automotive sensing and monitoring systems increasingly rely on MEMS sensors due to their compact size, low cost, and low power consumption.

Cell-type-specific regulators landscape and regulatory mechanisms underlying pyroptosis in uterine corpus endometrial carcinoma.

: Endometrial cancer (UCEC) has a significant detrimental effect on patient quality of life. Although pyroptosis-related genes have been reported to contribute to tumor pathogenesis, the specific mechanism of pyroptosis in patients with UCEC remains elusive. We provide an overview of the landscape of pyroptosis-related genes in UCEC tissues through single-cell RNA sequencing (scRNA-Seq) datasets from the tissues of UCEC of 6089 cells.

Three-dimensional spatial localization and volume estimation of prostate tumors using F-PSMA-1007 PET/CT versus multiparametric MRI.

Purpose: Fluorine-18 prostate-specific membrane antigen-1007 positron emission tomography/computed tomography (F-PSMA-1007 PET/CT) has been shown to be superior to multiparametric magnetic resonance imaging (MRI) for the locoregional staging of intermediate-risk and high-risk prostate tumors. This study aims to evaluate whether it is also superior in estimating tumor parameters, such as three-dimensional spatial localization and volume.

Methods: 134 participants underwent F-PSMA-1007 PET/CT and MRI prior to radical prostatectomy as part of the validating paired-cohort Next Generation Trial (NCT05141760).

Gunshots detection, identification, and classification: Applications to forensic science.

ce proliferation of audio sensors in surveillance, smartphones, and numerous devices has made gunshots-based event detection and forensic analysis critical for prompt police action and crime scene reconstruction. This paper initiates an analysis of the acoustic characteristics of gunshots and the variables affecting them, assessing their applicability and limitations in forensic science. It follows with a comprehensive review of existing literature on gunshots detection, identification, and classification technologies, detailing the critical components of machine learning applications, including dataset construction, feature extraction, and classifier selection.