Academic literature on the topic 'Biological feedback'

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Journal articles on the topic "Biological feedback"

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Karamzina, L. A., N. S. Mishchanchuk, and V. K. Rybalchenko. "Biological Feedback – Implemented Communication." Ukraïnsʹkij žurnal medicini, bìologìï ta sportu 3, no. 6 (2018): 288–92. http://dx.doi.org/10.26693/jmbs03.06.288.

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Ince, Laurence P. "A Textbook of Biological Feedback." American Journal of Psychotherapy 41, no. 2 (1987): 326–27. http://dx.doi.org/10.1176/appi.psychotherapy.1987.41.2.326.

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Søvik, Åste, Eirik Malinen, and Dag Rune Olsen. "Adapting Biological Feedback in Radiotherapy." Seminars in Radiation Oncology 20, no. 2 (2010): 138–46. http://dx.doi.org/10.1016/j.semradonc.2009.11.008.

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Stark, Lawrence, and Laurence R. Young. "DEFINING BIOLOGICAL FEEDBACK CONTROL SYSTEMS *." Annals of the New York Academy of Sciences 117, no. 1 (2006): 426–42. http://dx.doi.org/10.1111/j.1749-6632.1964.tb48200.x.

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El-Samad, Hana. "Biological feedback control—Respect the loops." Cell Systems 12, no. 6 (2021): 477–87. http://dx.doi.org/10.1016/j.cels.2021.05.004.

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Malinen, E., D. R. Olsen, and Å. Søvik. "176 ADAPTING BIOLOGICAL FEEDBACK IN RADIOTHERAPY." Radiotherapy and Oncology 102 (March 2012): S83. http://dx.doi.org/10.1016/s0167-8140(12)70147-0.

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Sokolov, A. V. "Medical training devices with biological feedback." Biomedical Engineering 29, no. 3 (1995): 116–18. http://dx.doi.org/10.1007/bf00560490.

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Vannahme, Christoph, Florian Maier-Flaig, Uli Lemmer, and Anders Kristensen. "Single-mode biological distributed feedback laser." Lab on a Chip 13, no. 14 (2013): 2675. http://dx.doi.org/10.1039/c3lc50140j.

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Voelkel, Susanne, and Luciane V. Mello. "Audio Feedback – Better Feedback?" Bioscience Education 22, no. 1 (2014): 16–30. http://dx.doi.org/10.11120/beej.2014.00022.

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Fnaiech, Mohamed Amine, Hazem Nounou, Mohamed Nounou, and Aniruddha Datta. "Intervention in Biological Phenomena via Feedback Linearization." Advances in Bioinformatics 2012 (November 6, 2012): 1–9. http://dx.doi.org/10.1155/2012/534810.

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The problems of modeling and intervention of biological phenomena have captured the interest of many researchers in the past few decades. The aim of the therapeutic intervention strategies is to move an undesirable state of a diseased network towards a more desirable one. Such an objective can be achieved by the application of drugs to act on some genes/metabolites that experience the undesirable behavior. For the purpose of design and analysis of intervention strategies, mathematical models that can capture the complex dynamics of the biological systems are needed. S-systems, which offer a go
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Dissertations / Theses on the topic "Biological feedback"

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Antonelli, Rita. "Robust output feedback regulation of a class of chemical and biological reactors." Thesis, Imperial College London, 2001. http://hdl.handle.net/10044/1/8156.

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Yazbek, John Elias. "Mitigating the effects of ribosome limitations on synthetic circuits via high-gain sRNA-mediated negative feedback." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99056.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Biological Engineering, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 85-88).<br>Resource limitations in bacterial cells can present significant hurdles that preclude correct synthetic circuit behavior. In a simple circuit with one constitutively expressed protein and one protein whose expression is inducible, it has been shown that inducing the expression of the second protein causes a significant decrease in the level of the first. In this thesis, we explore the possibility of re
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Sonntag, Sebastian [Verfasser], and Inga [Akademischer Betreuer] Hense. "Modeling biological-physical feedback mechanisms in marine systems / Sebastian Sonntag. Betreuer: Inga Hense." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2013. http://d-nb.info/1045023582/34.

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Bao, Yu. "Identification and Analysis of Critical Sites in RNA/Protein Sequences and Biological Networks." Kyoto University, 2018. http://hdl.handle.net/2433/235113.

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Morgan, Andrew T. "Encoding and decoding of cortical feedback to human early visual cortex." Thesis, University of Glasgow, 2018. http://theses.gla.ac.uk/30713/.

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Only 5% of excitatory input to primary visual cortical (V1) neurons corresponds to feedforward input from the retina, and only 20% of responses by these neurons can be explained by retinal input (Carandini, 2005; Muckli and Petro, 2013). Neuronal responses are therefore highly influenced by non-feedforward interactions, allowing the brain to combine external input from the retina with context and knowledge. This is accomplished by integrating feedforward input with signals from neurons processing higher-level or associative information. The signals transmitted from higher cortical areas to V1
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Ross, Kyla Turpin. "Quantitative Analysis of Feedback During Locomotion." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14110.

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It is known that muscles possess both intrinsic and reflexive responses to stretch, both of which have been studied extensively. While much is known about heterogenic and autogenic reflexes during XER, these have not been well characterized during locomotion. In this study, we mapped the distribution of autogenic and heterogenic feedback in hindlimb extensor muscles using muscle stretch in the spontaneously locomoting premammillary decerebrate cat. We used natural stimulation and compared stretch-evoked force responses obtained during locomotion with those obtained during XER. The goal was to
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Nguyen, Lan K. "Dynamical modelling of feedback gene regulatory networks." Diss., Lincoln University, 2009. http://hdl.handle.net/10182/1340.

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Living cells are made up of networks of interacting genes, proteins and other bio-molecules. Simple interactions between network components in forms of feedback regulations can lead to complex collective dynamics. A key task in cell biology is to gain a thorough understanding of the dynamics of intracellular systems and processes. In this thesis, a combined approach of mathematical modelling, computational simulation and analytical techniques, has been used to obtain a deeper insight into the dynamical aspects of a variety of feedback systems commonly encountered in cells. These systems range
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Moxley, Courtney. "Characterization of biotic and sodic lawns of the Kruger National Park using the framework of the positive feedback loop / Courtney Moxley." Bachelor's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/14020.

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The classical grazing lawn model is an intensely-grazed patch composed of short-statured, grazing-tolerant grass species. The formation and maintenance of these communities is controlled by positive feedbacks between grazers and the high-quality resource forage that the component grass species provide. Different nutrient cycling dynamics among the lawns identifies two discrete lawn types in the savanna: bioticallydriven lawns on nutrient-rich gabbroic soils and abiotically-driven lawns at sodic sites. We were interested in identifying whether the biotic and sodic lawns represented two distinct
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Krukauskas, Frank Krukauskas. "Using Auditory Feedback to Improve Striking for Mixed Martial Artists." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6529.

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The purpose of this study was to evaluate, auditory feedback as a training procedure to increase the effectiveness of throwing a "right cross.” Auditory feedback was evaluated in multiple baselines across behaviors design with 4 mixed martial arts students, two males and two females, 25-54 years old. The percentage of correct steps of the right crosses.” was stable .during baseline for all participants improved substantially following the introduction of the auditory feedback, and maintained at 90 percent or more for all participants during follow-up.
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Simoni, Mario F. "Synthesis and analysis of a physical model of biological rhythmic motor control with sensorimotor feedback." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/13284.

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Books on the topic "Biological feedback"

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Thomas, René. Biological feedback. CRC Press, 1990.

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Thomas, Rene, and Richard D'Ari. Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842.

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Declan, Bates, ed. Feedback control in systems biology. CRC Press, 2012.

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Lessard, Charles S. Basic feedback controls in biomedicine. Morgan & Claypool Publishers, 2009.

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M, Post W., and Travis C. C, eds. Positive feedback in natural systems. Springer-Verlag, 1986.

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Bose, Chinmoy K. Role of nonlinear dynamics in endocrine feedback. Nova Science Publishers, 2009.

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Association for Applied Psychophysiology and Biofeedback. Meeting. Roots to the future : proceedings. The Association, 1989.

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Iglesias, Pablo A., and Brian P. Ingalls. Control theory and systems biology. MIT Press, 2010.

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Kohl, Peter. Cardiac mechano-electric feedback and arrhythmias: From pipette to patient. W.B. Saunders, 2005.

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Peter, Kohl. Cardiac mechano-electric feedback and arrhythmias: From pipette to patient. Elsevier Saunders, 2005.

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Book chapters on the topic "Biological feedback"

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Thomas, René, and Richard D'Ari. "The Sos Response." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-23.

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Thomas, René, and Richard D'Ari. "Elements Of The Differential Description." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-8.

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Thomas, René, and Richard D'Ari. "On Determination And Differentiation." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-27.

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Thomas, René, and Richard D'Ari. "Characterizations Of Metal Ions In Biological Systems." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-3.

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Thomas, René, and Richard D'Ari. "Neuronal Networks." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-25.

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Thomas, René, and Richard D'Ari. "Positive Feedback Loops Generate Differentiation: Logical Description." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-16.

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Thomas, René, and Richard D'Ari. "Positive Feedback Loops Generate Differentiation: Differential Description." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-15.

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Thomas, René, and Richard D'Ari. "How Can A Transient Signal Switch A Function On Permanently?" In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-17.

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Thomas, René, and Richard D'Ari. "Many Steady States." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-18.

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Thomas, René, and Richard D'Ari. "Characterizations Of Metal Ions In Biological Systems." In Biological Feedback. CRC Press, 2024. http://dx.doi.org/10.1201/9781003574842-4.

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Conference papers on the topic "Biological feedback"

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Zhu, Mengjia, Oliver Pennington, Sam Kay, Amin Zarei, Michael Short, and Dongda Zhang. "Optimization-based operational space design for effective bioprocess performance under uncertainty." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.131628.

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Maintaining consistent product quality and yield in bioprocess operations is challenging due to uncertainties inherent in biological systems. Thus, robust strategies are essential to ensure key performance indicators (KPIs), such as product concentration and yield, are consistently met despite the uncertainties. Real-time feedback co Interntrol, though widely used, is often impractical due to its reliance on expensive sensors, rapid data processing, and high-speed control actions. This paper proposes a novel approach to address these challenges by identifying the operational space for control
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Kurgaev, Aleksandr F., and Oleksandr V. Palagin. "Rehabilitation According to the Biological Feedback." In 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2021. http://dx.doi.org/10.1109/idaacs53288.2021.9660953.

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Bearden, Alan J., Terrence L. Wong, and Michael P. O'Neill. "Biological imaging with laser-feedback microscopy (LFM)." In IS&T/SPIE's Symposium on Electronic Imaging: Science & Technology, edited by Tony Wilson and Carol J. Cogswell. SPIE, 1995. http://dx.doi.org/10.1117/12.205322.

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Higuchi, Keita, Michihiko Ueno, and Jun Rekimoto. "Scarecrow: Avatar Representation Using Biological Information Feedback." In 2014 IEEE International Conference on Internet of Things(iThings), and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing(CPSCom). IEEE, 2014. http://dx.doi.org/10.1109/ithings.2014.66.

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Seipel, Justin. "Emphasizing Mechanical Feedback in Bio-Inspired Design and Education." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-65587.

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Mechanical feedback in nature is a useful concept proposed by many researchers in different areas of biological research. The concept, at its core, is simply the idea that many mechanical processes in biology effectively act to assist in the self-stabilization of tasks, and therefore, serve functionally as a first level of feedback control. However, due to a conventional view of the nervous system as the ‘controller’ of the body, it has historically been assumed that the control of tasks does not critically depend on the self-stability properties of the mechanical (musculo-skeletal) system. Mo
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Shi, Fei, Peipei Zhou, and Ruiqi Wang. "Coupled positive feedback loops regulate the biological behavior." In 2012 IEEE 6th International Conference on Systems Biology (ISB). IEEE, 2012. http://dx.doi.org/10.1109/isb.2012.6314131.

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Efendiev, T. S., V. M. Katarkevich, and Anatoly N. Rubinov. "Picosecond distributed feedback dye laser for biological applications." In Laser Applications in Life Sciences: 5th International Conference, edited by Pavel A. Apanasevich, Nikolai I. Koroteev, Sergei G. Kruglik, and Victor N. Zadkov. SPIE, 1995. http://dx.doi.org/10.1117/12.197493.

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Sarma, Anish A., Jing Shuang Lisa Li, Josefin Stenberg, et al. "Internal Feedback in Biological Control: Architectures and Examples." In 2022 American Control Conference (ACC). IEEE, 2022. http://dx.doi.org/10.23919/acc53348.2022.9867859.

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Timmermann, Axel, and Fei-Fei Jin. "Biological feedback on El Nino and La Nina." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Zhaobo Sun, Fei-Fei Jin, and Toshiki Iwasaki. SPIE, 2003. http://dx.doi.org/10.1117/12.466361.

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Steel, Harrison, Aivar Sootla, Nicolas Delalez, and Antonis Papachristodoulou. "Mitigating Biological Signalling Cross-talk with Feedback Control." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8796251.

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Reports on the topic "Biological feedback"

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Suleimanova, G. P., and R. A. Grekhov. Clinical and psychological effectiveness of the method of biological feedback in patients with systemic scleroderma. ООО ИМА-Пресс, 2018. http://dx.doi.org/10.18411/1995-4484-2018-56-3(2)-76.

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Bogdanov, Sergey I. Electronic educational resource "Ambulance and emergency medical care for mental disorders and behavioral disorders at the prehospital stage". SIB-Expertise, 2024. http://dx.doi.org/10.12731/er0784.29012024.

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The Electronic educational resource (hereinafter referred to as EER) “Basic aspects of narcology” is designed for 36 training hours. This distance learning course aims to develop communicative competence, prepare for solving standard problems of professional activity using information resources, medical and biological terminology, and is also aimed at optimizing the educational process at the university, creating conditions for achieving the required level of modern education and comprehensive development of the personality of students . The EER was developed in accordance with the Federal Sta
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Bogdanov, Sergey I. Electronic educational resource "Basic aspects of narcology". SIB-Expertise, 2024. http://dx.doi.org/10.12731/er0783.29012024.

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The electronic educational resource (hereinafter referred to as EER) “Basic aspects of narcology” is designed for 36 training hours. This distance learning course aims to develop communicative competence, prepare for solving standard problems of professional activity using information resources, medical and biological terminology, and is also aimed at optimizing the educational process at the university, creating conditions for achieving the required level of modern education and comprehensive development of the personality of students . The EER was developed in accordance with the Federal Sta
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Galili, Gad, Harry J. Klee, and Asaph Aharoni. Elucidating the impact of enhanced conversion of primary to secondary metabolism on phenylpropanoids secondary metabolites associated with flavor, aroma and health in tomato fruits. United States Department of Agriculture, 2012. http://dx.doi.org/10.32747/2012.7597920.bard.

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• Targeted manipulating Phenylalanine (Phe) synthesis is one of the most powerful strategies to boost the biologically and economically important secondary metabolites, including phenylpropaniods, aromatic volatiles and specialized secondary metabolites. • Over-expression of the petunia MYB transcript factor, ODORANT1 (ODO1), results in significant alterations of the levels of specific phenylpropanoid compounds in plants. • Our previous studies indicated that ectopic expression of the feedback-insensitive AroG could break the bottleneck between primary and secondary metabolisms in tomato, ther
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Shahverdian, Scott, Derek Schook, Derek Schook, and Scott Shahverdian. Riverscape interpretation in Great Basin National Park: A geomorphic assessment of streams and riparian areas. National Park Service, 2025. https://doi.org/10.36967/2307540.

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Streams can be challenging systems to manage due to their dynamic nature and complex feedbacks between hydrologic, geomorphic, and biological processes that operate over a range of timescales. Stream-riparian ecosystems, also known as riverscapes or river corridors, are affected by events ranging from single storms to large-scale landscape disturbances such as wildfires and landslides. Understanding riverscape dynamics is necessary for identifying potential causes of their degradation, appropriate management actions, and potential restoration strategies. Developing appropriate expectations req
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Slaughter-Acey, Jaime, Kathryn Behrens, Amy M. Claussen, et al. Social and Structural Determinants of Maternal Morbidity and Mortality: An Evidence Map. Agency for Healthcare Research and Quality (AHRQ), 2023. http://dx.doi.org/10.23970/ahrqepccer264.

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Objective. The purpose was to review available evidence of risk factors associated with maternal morbidity and mortality in the United States during the prenatal and postpartum periods to inform a National Institutes of Health Pathways to Prevention Workshop: Identifying Risks and Interventions to Optimize Postpartum Health, held November 29–December 1, 2022. Data sources. We searched MEDLINE®, CINAHL®, and the Social Sciences Citation Index through November 2022. Review methods. We searched for observational studies examining exposures related to social and structural determinants of health a
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Innovative Solutions to Human-Wildlife Conflicts: National Wildlife Research Center Accomplishments, 2014. U.S. Department of Agriculture, Animal and Plant Health Inspection Service, 2015. http://dx.doi.org/10.32747/2015.7206799.aphis.

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The National Wildlife Research Center (NWRC) is the research arm of Wildlife Services (WS), a program within the U.S. Department of Agriculture’s (USDA) Animal and Plant Health Inspection Service (APHIS). NWRC’s researchers are dedicated to finding biologically sound, practical, and effective solutions to resolving wildlife damage management issues. They seek these solutions using a multiyear, multidisciplinary project management system. NWRC identifies and prioritizes projects based on feedback from WS program leaders, managers, and stakeholders concerning their most pressing wildlife damage
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Microbes in Models: Integrating Microbes into Earth System Models for Understanding Climate Change. American Society for Microbiology, 2023. http://dx.doi.org/10.1128/aamcol.jun.2023.

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Climate change is altering the planet and threatens humanity. Earth system models simulate the planet's physical, chemical, and biological processes to help scientists understand current environmental changes and make projections for Earth's future, which can inform society's responses to combat and mitigate climate change's negative effects. Climate change will fundamentally change life on Earth, including microorganisms. Microbes will also influence climate change by driving biogeochemical cycles through the consumption and production of greenhouse gasses. Thus, explicitly including microbia
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