408 research outputs found

    Marine Toxins from Harmful Algae and Seafood Safety

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    The rapid expansion of aquaculture around the world is increasingly being impacted by toxins produced by harmful marine microalgae, which threaten the safety of seafood. In addition, ocean climate change is leading to changing patterns in the distribution of toxic dinoflagellates and diatoms which produce these toxins. New approaches are being developed to monitor for harmful species and the toxins they produce. This Special Issue covers pioneering research on harmful marine microalgae and their toxins, including the identification of species and toxins; the development of new chemical and biological techniques to identify and monitor species and toxins; the uptake of marine biotoxins in seafood and marine ecosystems; and the distribution and abundance of toxins, particularly in relation to climate change

    Tools for Quantifying Bacterial Motility Using Digital Holographic Microscopy as Applied to Studying the Simulated Microgravity Environment

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    Digital holographic microcopy (DHM) is a label-free technique that has gained attention in recent years as a tool for volumetric imaging. One application of DHM is for the study of microbial motility with the advantage being that organisms may freely move within their environment. Images created from DHM are in the form of holograms. Holograms are time recordings showing XY information with the Z information contained within. Z information can be retrieved from the holograms directly through a variety of numerical techniques or through reconstruction. Datasets generated from DHM are large and processing remains a challenging task. Here, we show how following reconstruction, the refocusing method can be used to locate particles manually through Z. We note the difference between the lateral and axial resolutions and show the impact of the point-spread functions on resolving data. We show that 2D tracking of organisms is generally sufficient for quantifying motility though specific applications such as surface behavior still require 3D information. With this understanding, we shift to studying the microgravity environment. The microgravity environment is the weightless environment of the space station. It is difficult to conduct experiments on the space station, so we simulate certain characteristics of that environment on Earth by using simulated microgravity devices. We review bacterial responses to microgravity and the simulated microgravity environment with an emphasis on motility and chemotaxis. Finally, we apply the techniques developed in this thesis to study the simulated microgravity environment by examining the motility and chemotaxis of Vibrio alginolyticus. We show that while there was little change in motility between simulated microgravity and normal gravity, there is a statistically significant difference in cloud sizes. Future work would involve comparing these responses with the actual microgravity environment

    2015 GREAT Day Program

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    SUNY Geneseo’s Ninth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1009/thumbnail.jp

    2023- The Twenty-seventh Annual Symposium of Student Scholars

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    The full program book from the Twenty-seventh Annual Symposium of Student Scholars, held on April 18-21, 2023. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1027/thumbnail.jp

    Colloids with perception-dependent motility: Dynamics and structure of rotating aggregates and directed swarms

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    In this thesis we focus on two-dimensional systems of colloids governed by Brownian dynamics that are able to sense their neighbors via a visual-type of perception, then they can switch their motility between passive and active depending on a given perception parameter. Our setup corresponds to experiments performed in Bechinger's lab in Konstanz University, where they have considered cases of quorum-sensing (isotropic perception) and visual-type of perception (anisotropic perception). Here we study the case when the perception is both anisotropic and also misaligned with respect to the self-propulsion orientation vector. The purpose of this thesis is to characterize the emergence of collective behaviors in this model, as well as the dynamics and structural changes of the system. We provide novel strategies where the interplay between perception and motility of the agents allows them to self-organize into rotating aggregates and directed swarms. Our study sheds light in the understanding of active automatons with adaptable collective states, and can be implemented for example in macroscopic swarms of robots, or microscopic colloids activated by light. In chapter 2 we introduce the ingredients necessary to perform particle-based numerical simulations, like the integration method, interaction forces, boundary conditions, and optimization techniques. We also briefly comment on the organization and design of the Brownian dynamics code we developed to obtain results shown in this thesis. In chapter 3, we consider systems of colloids with discontinuous motility and misaligned visual perception. We explain how this type of interaction generically leads to aggregation and rotation of cohesive structures. Then, we characterize the resulting dynamics for different system parameters. In chapter 4 we characterize different types of circular structures that emerge in this model, as a function of the perception threshold and misalignment angle. We also derive analytical expressions from conservation equations corresponding to a solid-body rotation of a continuum aggregate driven by activity at the interface. We find an agreement between theory and numerical results for the density, size, and angular velocity of the aggregates as a function of the system parameters. In chapter 5 we consider a binary mixture of particles with different misalignment angle. Under given conditions, we find the striking case where the system aggregates, self-sorts into species subdomains which counter-rotate leading to a self-propulsion of the overall system. We characterize this process by means of dynamic parameters and their averages in steady state. We find cases where the directed swarms can either dilute or remain robust, or where the aggregate is species homogeneous and its center of mass describes random motion. We also study the swarms shape and how it can change for varying misalignment angle. In chapter 6 we study cases when the mixture is non-equimolar. In this case the system self-organizes into swarms describing helical trajectories. We also show an example of an externally guided system, where we dynamically change the misalignment angle of the particles, leading to a swarm performing run-and-turn motion

    2020 GREAT Day Program

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    SUNY Geneseo’s Fourteenth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1014/thumbnail.jp

    Statistical Analysis of Self and Pairwise Interactions in Active Systems

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    Active systems often demonstrate impressive group level behaviors which appear coordinated, but are believed to arise only from individual-level interactions. To study the mathematics of these behavioral rules, we reduce such large group dynamics to the simplest cases of self interaction and pairwise interactions. In particular, we will only study passively gathered path data which is recorded without disrupting a system and therefore avoids introducing possible behavior influencing factors. We analyze emergent behaviors in two systems: transient self-trapping in a model of self-avoidant swimming droplets and leader-follower dynamics in experimental golden shiner duos. We compute several traditional path data analysis metrics including the mean square displacement and two point correlation function of both positional and velocity data to find that they are insufficient to describe the observed dynamics. To address this gap, we propose a use case for estimating the time delayed mutual information of random variables derived from path data; we argue that confined systems are a good candidate for our method since they are likely to reach a steady state. We adapt the sampling scheme of a k-nearest neighbors mutual information estimation method to compute the time delayed self mutual information of the path curvature of self-avoidant swimming droplets to study their self-interactions. We then use the same protocol to estimate the time delayed pairwise mutual information between angular positions of experimental golden shiner duos to study their pairwise interactions. We find that the decay of the mutual information of the path curvature of self-avoidant swimming droplets can be differentiated from other memoryless models with high path curvature. We also show that the decay timescale of the mutual information relates to the strength of the self-avoidant memory response of these droplets. In our experimental golden shiner path data, we find that peaks in the mutual information curves of the angular positions recover the reaction time or signaling timescale between fish when they are in a leader-follower configuration. Our method is entirely non-parametric and therefore very versatile; it should be applicable to any path-derived time series data that is either spatially confined or can be shown to sample from a stationary distribution.Doctor of Philosoph

    Investigating Eco-evolutionary Interactions between Hosts and Members of Their Gut Microbiota

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    Evolutionary and ecological interactions between hosts and their associated microbial communities, their microbiota, and between members of these communities are vital to understand. Microbial communities are widespread across diverse host taxa and hosts receive a variety of well-documented benefits from their microbial communities. Despite the importance of understanding eco-evolutionary dynamics for colonization outcomes and the benefits these communities provide to their hosts, our current knowledge in this area remains incomplete. For example, we do not know the full extent of coevolution and specific relationships between hosts and microbes, and between the microbes themselves, across host taxa. Questions remain about how host taxonomy, ecology and physiology, and other present microbes influence microbial community membership and function, host and microbe evolution, and specificity in colonization of hosts. I present several studies that aim to shed further light on these eco-evolutionary topics utilizing insect pollinators, with a particular focus on bumble bees, and their gut microbial communities

    CERNAS: Current Evolution and Research Novelty in Agricultural Sustainability

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    Climate changes pose overwhelming impacts on primary production and, consequently, on agricultural and animal farming. Additionally, at present, agriculture still depends strongly on fossil fuels both for energy and production factors ,such as synthetized inorganic fertilizers and harmful chemicals such as pesticides. The need to feed the growing world population poses many challenges. The need to reduce environmental impacts to a minimum, maintain healthy ecosystems, and improve soil microbiota are central to ensuring a promising future for coming generations. Livestock production under cover crop systems helps to alleviate compaction so that oxygen and water can sufficiently flow in the soil, add organic matter, and help hold soil in place, reducing crusting and protecting against erosion. The use of organic plant production practices allied to the control of substances used in agriculture also decisively contributes to alleviating the pressure on ecosystems. Some of the goals of this new decade are to use enhanced sustainable production methodologies to improve the input/output ratios of primary production, reduce environmental impacts, and rely on new innovative technologies. This reprint addresses original studies and reviews focused on the current evolution and research novelty in agricultural sustainability. New developments are discussed on issues related to quality of soil, natural fertilizers, or the sustainable use of land and water. Also, crop protection techniques are pivotal for sustainable food production under the challenges of the Sustainable Development Goals of the United Nations, allied to innovative weed control methodologies as a way to reduce the utilization of pesticides. The role of precision and smart agriculture is becoming more pertinent as communication technologies improve at a rapid rate. Waste management, reuse of agro-industrial residues, extension of shelf life, and use of new technologies are ways to reduce food waste, all contributing to higher sustainability in food supply chains, leading to a more rational use of natural resources. The unquestionable role of bees as pollinators and contributors to biodiversity is adjacent to characterizing beekeeping activities, which in turn contributes, together with the valorization of endemic varieties of plant foods, to the development of local communities. Finally, the short circuits and local food markets have a decisive role in the preservation and enhancement of rural economies.info:eu-repo/semantics/publishedVersio
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