The role of foam in improving the workability of sand : insights from DEM

Foam as a soil conditioner can transform the mechanical properties of the excavated natural muck and lubricate the interface between the cutting tools and muck, thus reducing the tools’ wear and promoting the efficiency of earth pressure balance (EPB) shield tunneling. This paper aims to explore the meso-mechanism of foam in improving the workability of sand by combining discrete element modeling (DEM) with experimental investigations of slump tests. A “sand-foam” mixture DEM model was generated by simplifying the sand grains and foam as individual particles with different properties. The particle-scale simulated parameters were calibrated based on a series of experimental observations. The effects of foam on the inter-particle contact distribution and the evolution of contact forces during the slumping process were investigated in detail through numerical modeling. It was found that injecting foam into sand specimens could increase the coordination number and the contact number around sand grains. Although the force transmission pattern changes from “sand-sand” into the coexistence of “sand-foam”, “sand-sand” and “foam-foam” contacts, the magnitude of contact forces transferred by foam particles is significantly lower than that by sand particles. The presence of foam reduces contact-scale frictional strength and thus reduces the stability of the microstructures of sand. In addition, the normal direction of inter-particle contact force deflects from the vertical to the horizontal and the magnitude of contact force decreases significantly with the influence of foam

Physics-informed neural network for fibre channel modelling in optical communication systems

Over 95% of the data traffic is carried over optical fibre communication links. The split-step Fourier method (SSFM) has been widely employed to model the evolution of optical signals along the fibre channels in optical communication systems. However, the split-step Fourier method requires very high computational resources, especially for ultra-long-haul and wideband communication systems. Meanwhile, deep learning techniques can be applied to investigate the evolution of optical signals along the fibre links, where the nonlinear Schrödinger equation (NLSE) can be solved directly using neural networks to avoid the huge complexity of the split-step Fourier simulations. In this work, we will discuss the application of neural networks in modelling the evolution of different types of optical pulses along fibre transmission channels

Metabolomic signature between diabetic and non-diabetic obese patients: A protocol for systematic review.

BackgroundType 2 diabetes mellitus (T2DM) is a chronic and progressive condition defined by hyperglycemia caused by abnormalities in insulin production, insulin receptor sensitivity, or both. Several studies have revealed that higher body mass index (BMI) is associated with increasing risk of developing diabetes. In this study, we perform a protocol for systematic review to explore metabolite biomarkers that could be used to identify T2DM in obese subjects.MethodsThe protocol of this review was registered in PROSPERO (CRD42023405518). Three databases, EMBASE, PubMed, and Web of Science were selected to collect potential literature from their inceptions to July December 2023. Data for collection will include title, authors, study subjects, publication date, sample size, detection and analytical platforms, participant characteristics, biological samples, confounding factors, methods of statistical analysis, the frequency and directions of changes in potential metabolic biomarkers, and major findings. Pathway analysis of differential metabolites will be performed with MetaboAnalyst 5.0 based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Human Metabolome Database.ResultsThe results of this systematic review will be published in a peer-reviewed journal.ConclusionThis systematic review will summarize the potential biomarkers and metabolic pathways to provide a new reference for the prevention and treatment of T2DM in obese subjects

The Effect of Smoking onmeibomian gland dysfunction (MGD) Parameters.

<p>The Effect of Smoking onmeibomian gland dysfunction (MGD) Parameters.</p

The Correlation between Smoking Index and MGD Parameters in the Smokers of both sexes.

<p>In the smokers with meibomian gland dysfunction (MGD), the smoking index was significantly correlated with the scores of lid margin abnormality (A) and meibum (B).</p

Research Progress on Metabolic Diseases in Rural Areas

Through the review of relevant literature in recent years, it is found that the incidence rate of metabolic diseases in rural areas is on the rise. The related factors that may cause diseases include diet structure, exercise habits, medical resources and other aspects. At the same time, there are some limitations in the intervention and treatment measures of this kind of disease. It is urgent to carry out in-depth exploration for the special conditions in rural areas. By reviewing the research progress related to metabolic diseases in rural areas, more new ideas are provided for the treatment and improvement of metabolic diseases in rural areas