Learning Informative Health Indicators Through Unsupervised Contrastive Learning

Condition monitoring is essential to operate industrial assets safely and efficiently. To achieve this goal, the development of robust health indicators has recently attracted significant attention. These indicators, which provide quantitative real-time insights into the health status of industrial assets over time, serve as valuable tools for fault detection and prognostics. In this study, we propose a novel and universal approach to learn health indicators based on unsupervised contrastive learning. Operational time acts as a proxy for the asset's degradation state, enabling the learning of a contrastive feature space that facilitates the construction of a health indicator by measuring the distance to the healthy condition. To highlight the universality of the proposed approach, we assess the proposed contrastive learning framework in two distinct tasks - wear assessment and fault detection - across two different case studies: a milling machines case study and a real condition monitoring case study of railway wheels from operating trains. First, we evaluate if the health indicator is able to learn the real health condition on a milling machine case study where the ground truth wear condition is continuously measured. Second, we apply the proposed method on a real case study of railway wheels where the ground truth health condition is not known. Here, we evaluate the suitability of the learned health indicator for fault detection of railway wheel defects. Our results demonstrate that the proposed approach is able to learn the ground truth health evolution of milling machines and the learned health indicator is suited for fault detection of railway wheels operated under various operating conditions by outperforming state-of-the-art methods. Further, we demonstrate that our proposed approach is universally applicable to different systems and different health conditions

Contractions, a risk for premature rupture of fetal membranes: A new protocol with cyclic biaxial tension

This study aims at investigating the effect of repeated mechanical loading on the rupture and deformation properties of fetal membranes. Ten membranes delivered by cesarean sections were tested using a custom-built inflation device which provides a multi-axial stress state. For each membrane, a group of samples was first cyclically stretched by application of pressure ranging between 10 and 40mmHg. After cycles, samples were subjected to inflation up to rupture. Differences between mechanical parameters from cycled and uncycled samples were analyzed. Ten cycles at 40% of mean critical membrane tension-representative of mean physiologic contractions-did not affect strength and stiffness of fetal membranes but reduced the work to rupture, thus indicating that contractions might increase the risk of premature rupture of the membrane. Cyclic testing demonstrated a large hysteresis loop and irreversible deformation on the first cycle, followed by rapid stabilization on subsequent cycles. In 80% of tests, amnion ruptured first and at the periphery of the sample, under uniaxial strain state. Chorion ruptured at higher deformation levels in the middle, under biaxial strain state

Prenatally engineered autologous amniotic fluid stem cell-based heart valves in the fetal circulation

Prenatal heart valve interventions aiming at the early and systematic correction of congenital cardiac malformations represent a promising treatment option in maternal-fetal care. However, definite fetal valve replacements require growing implants adaptive to fetal and postnatal development. The presented study investigates the fetal implantation of prenatally engineered living autologous cell-based heart valves. Autologous amniotic fluid cells (AFCs) were isolated from pregnant sheep between 122 and 128 days of gestation via transuterine sonographic sampling. Stented trileaflet heart valves were fabricated from biodegradable PGA-P4HB composite matrices (n = 9) and seeded with AFCs in vitro. Within the same intervention, tissue engineered heart valves (TEHVs) and unseeded controls were implanted orthotopically into the pulmonary position using an in-utero closed-heart hybrid approach. The transapical valve deployments were successful in all animals with acute survival of 77.8% of fetuses. TEHV in-vivo functionality was assessed using echocardiography as well as angiography. Fetuses were harvested up to 1 week after implantation representing a birth-relevant gestational age. TEHVs showed in vivo functionality with intact valvular integrity and absence of thrombus formation. The presented approach may serve as an experimental basis for future human prenatal cardiac interventions using fully biodegradable autologous cell-based living materials