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Plants are a vital component of human life on Earth; they provide us with food and essential nutrients as well as the oxygen we breathe. However, the science education community struggles to find ways to make plant processes less abstract and more understandable for learners. In this article we demonstrate how we make plant processes more understandable for learners by observing the behaviors of a specific plant structure, a stoma, which is a microscopic opening that plays a role in the movement of matter into and out of a plant. Recent research across plant-related science fields centers on plant stomata because they protect plants from various environmental strains, including attacks from pathogens. Translating this research into science classroom instruction has not occurred extensively. A key impediment is that few common methods to make stomata visible or demonstrate their dynamic nature to learners are available. The activities we share here make stomata visible utilizing a specific plant, Tradescantia zebrina, and common laboratory equipment. In the first activity, we share how to demonstrate stomata closing and opening by manipulating a combination of these environmental factors. In the second activity, we describe how to create a visual simulation of stomata response to attacks from microorganisms. 

Abstract Distributed acoustic sensing (DAS) is being explored in a variety of environments as a promising technology for the recording of seismic signals in dense array configurations. There is a particular interest for deploying DAS arrays on the ocean floor, presenting formidable challenges for conventional seismology. Taking advantage of the availability of a dark fiber on the Monterey Bay Accelerated Research System (MARS) 52 km offshore cable at Monterey Bay, California, in July 2022, we installed a DAS interrogator at the shore end of the cable with the intention of acquiring continuous data for a period of one year. Here, we describe the experiment and present examples of observations over the first six months of the deployment. 

This research paper will discuss the various technological innovations that have been developed within the past, are being developed in the present and will be developed in the future to bring progressive change within the healthcare industry. In particular, the way artificial intelligence and deep learning has brought about new methods for making task more efficient, less time consuming, and possibly more accurate. This study will discuss the different positive and negative effects of these technological methods to best see how artificial intelligence (AI) and deep learning is impacting the health industry in all areas. With supportive interviews from medical professionals, data scientist, and machine learning researchers, the analysis of real-world experiences and scenarios will provide more insight to what is beneficial or ineffective. The study utilizes extensive literary works to examine in detail the current AI and deep learning new approach to medicine, the risk and ethical concerns, the technological challenges from determining the best algorithms, and myths versus reality surrounded by this subject.