EXPLORATION OF MICROPLASTIC FIBERS TRANSPORT DYNAMICS IN POROUS MEDIA USING A COMBINATION OF PHYSICAL EXPERIMENTS AND NUMERICAL SIMULATIONS

The existence of microplastics (MPs) in the environment has been a growing concern for two and a half decades, having now been found in remote areas, ocean sediment, deserts, and mountain peaks. MPs in the environment are a concern because they can impact soil properties and organisms. Research has determined that MPs can affect aquatic organisms in two forms: 1.) mechanical- MPs can attach to the body of the organism and impact their movement and 2.) chemical- the leaching of chemicals from the MPs can be absorbed by the organisms, both of these impact forms can lead organisms to experience inflammation, stress, death, and reproduction decline. The impact on human health is limited but assumed to see the same impacts as aquatic organisms. The largest MP type by mass found in the environment is microplastic fiber (MPF). Scientists understand where MPs come from and where they end up (large-scale movement), the missing aspect is how they move. This research gap is missing due to the transport mechanics occur at the pore scale which is difficult to capture. The mechanisms of MPFs transport have been proposed numerically but have not been validated. This research collected MPF transport data in a 2D laboratory model to understand the transport dynamics in porous media of three different lengths 0.3, 0.5, 0.8 cm and microbeads to act as a passive tracer, modeling MPF transport with existing simulation tools (ADE equation) and validate the only MPF distributed simulation model to date. Videos captured the trajectory of the fiber and beads, and the trajectory data was used to generate breakthrough curves. The experimental data found that fibers tumble/roll during their transport through the model, that fibers traveled much slower than expected, and longer fibers would travel slower. It was observed that fibers would have an abrupt change in velocity and became stuck then re-mobilized. This paper refers to this dynamic as “trapping”. Comparisons tothe ADE (i.e. advection-dispersion models) equation and the distributed simulation model (DSM) were unable to simulate MPF transport, which leads to the question of what dynamics are missing from the models. ADE simulation was unable to capture the correct shape of the curve, with particles arriving sooner than the experiments. The DSM can simulate the transport of beads but nothing else. This suggests that the missing dynamics result in a retention or trapping process, but the design of these experiments cannot determine the precise mechanism. However, two upscaled representations of the trapping process were able to significantly improve the agreement of the experimental and numerical results

Neural Radiance Fields: Past, Present, and Future

The various aspects like modeling and interpreting 3D environments and surroundings have enticed humans to progress their research in 3D Computer Vision, Computer Graphics, and Machine Learning. An attempt made by Mildenhall et al in their paper about NeRFs (Neural Radiance Fields) led to a boom in Computer Graphics, Robotics, Computer Vision, and the possible scope of High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D models have gained traction from res with more than 1000 preprints related to NeRFs published. This paper serves as a bridge for people starting to study these fields by building on the basics of Mathematics, Geometry, Computer Vision, and Computer Graphics to the difficulties encountered in Implicit Representations at the intersection of all these disciplines. This survey provides the history of rendering, Implicit Learning, and NeRFs, the progression of research on NeRFs, and the potential applications and implications of NeRFs in today's world. In doing so, this survey categorizes all the NeRF-related research in terms of the datasets used, objective functions, applications solved, and evaluation criteria for these applications.Comment: 413 pages, 9 figures, 277 citation

Intelligent Sensors for Human Motion Analysis

The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems

Micro/nano devices for blood analysis

[Excerpt] The development of microdevices for blood analysis is an interdisciplinary subject that demandsan integration of several research fields such as biotechnology, medicine, chemistry, informatics, optics,electronics, mechanics, and micro/nanotechnologies.Over the last few decades, there has been a notably fast development in the miniaturization ofmechanical microdevices, later known as microelectromechanical systems (MEMS), which combineelectrical and mechanical components at a microscale level. The integration of microflow and opticalcomponents in MEMS microdevices, as well as the development of micropumps and microvalves,have promoted the interest of several research fields dealing with fluid flow and transport phenomenahappening at microscale devices. [...

Automated processing of zebrafish imaging data: a survey

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines

Biomechanical Spectrum of Human Sport Performance

Writing or managing a scientific book, as it is known today, depends on a series of major activities, such as regrouping researchers, reviewing chapters, informing and exchanging with contributors, and at the very least, motivating them to achieve the objective of publication. The idea of this book arose from many years of work in biomechanics, health disease, and rehabilitation. Through exchanges with authors from several countries, we learned much from each other, and we decided with the publisher to transfer this knowledge to readers interested in the current understanding of the impact of biomechanics in the analysis of movement and its optimization. The main objective is to provide some interesting articles that show the scope of biomechanical analysis and technologies in human behavior tasks. Engineers, researchers, and students from biomedical engineering and health sciences, as well as industrial professionals, can benefit from this compendium of knowledge about biomechanics applied to the human body

Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data

This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and