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Добірка наукової літератури з теми "Biological framework"

Автор: Grafiati

Опубліковано: 11 березня 2023

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Статті в журналах з теми "Biological framework"

Sciberras, Josette, Raymond Zammit, and Patricia Vella Bonanno. "The European framework for intellectual property rights for biological medicines." Generics and Biosimilars Initiative Journal 10, no. 4 (December 15, 2021): 172–83. http://dx.doi.org/10.5639/gabij.2021.1004.022.

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Introduction: The Pharmaceutical Strategy for Europe (2020) proposes actions related to intellectual property (IP) rights as a means of ensuring patients’ access to medicines. This review aims to describe and discuss the European IP framework and its impact on accessibility of biological medicines and makes some recommendations. Methods: A non-systematic literature review on IP for biological medicines was conducted. Data on authorizations and patent and exclusivity expiry dates of biological medicines obtained from the European Medicines Agency’s (EMA) website and literature was analysed quantitatively and qualitatively. Results: The analysis showed that as at end July 2021, 1,238 medicines were authorized in Europe, of which 332 (26.8%) were biological medicines. There were only 55 biosimilars for 17 unique biologicals. There is an increasing trend in biological authorizations but signifi cant delays in submission of applications for marketing authorization of biosimilars, with no signifi cant diff erences in the time for assessment for marketing authorization between originator biologicals and biosimilars. For some of the more recent biosimilars, applications for authorization were submitted prior to patent and exclusivity expiry. COVID vaccines confi rmed the impact of knowledge transfer on accessibility, especially when linked to joint procurement. Discussion: IP protects originator products and impacts the development of biosimilars. Strategies to improve competition in the EU biological market are discussed. Pricing policies alone do not increase biosimilar uptake since patients are switched to second generation products. Evergreening strategies might be abusing the IP framework, and together with trade secrets and disproportionate prices compared to R & D and manufacturing costs lead to an imbalance between market access and innovation. Conclusion: The European Pharmaceutical Strategy should focus on IP initiatives that support earlier authorization of biosimilars of new biologicals. Recommendations include knowledge sharing, simplifi cation of the regulatory framework and transparency of prices and R & D costs.

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Belova, D. A. "Legal Framework for Reproductive Biological Material." Lex Russica, no. 7 (July 19, 2021): 111–21. http://dx.doi.org/10.17803/1729-5920.2021.176.7.111-121.

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The paper is devoted to the study of the legal nature of reproductive biological material and determination of the optimal legal regime of germ cells (oocytes, sperm) and tissues of human reproductive organs intended for reproduction purposes. It is noted that the reproductive biomaterial is not a thing, since it does not have the characteristics inherent in this legal category, and needs a special legal regime. The extension of the regime of ownership of the germ cells and tissues of human reproductive organs is unacceptable neither from the position of the current legislation, nor from the perspective of its development prospects. An analysis of the legal opportunities provided by the legislator in relation to reproductive biomaterial, as well as the procedure for their implementation, led to the conclusion that neither the persons from whom it comes, nor medical organizations can be recognized as its owners. The regime of property rights is not suitable for ensuring and protecting the interests of participants in public relations arising in connection with the use of reproductive biomaterial. It is proved that in relation to the germ cells and tissues of the reproductive organs, the interest of a person is not in acquiring actual and legal domination over them as such, but in acquiring or, on the contrary, not acquiring parental rights and obligations in relation to a child born as a result of their use. It is concluded that the designated interest should be mediated not by a real, but by a reproductive right.

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Gutschick, Vincent P., and Hormoz BassiriRad. "Biological Extreme Events: A Research Framework." Eos, Transactions American Geophysical Union 91, no. 9 (2010): 85. http://dx.doi.org/10.1029/2010eo090001.

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Song, Cheng Long, Chen Zou, Wen Ke Wang, and Si Kun Li. "An Integrated Framework for Biological Data Visualization." Advanced Materials Research 846-847 (November 2013): 1145–48. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1145.

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In the field of bioinformatics visualization, integrating software and data in different levels is the development trend. This paper presents an integration framework for biomolecular structure and genome sequences visualization. The framework can effectively support the data and software interoperability of biomolecular structure / genome sequences visualization. Based on the framework, we developed an integrated visualization system, which provides some new comprehensive visualization functions. Preliminary trial showed that the framework has a good prospect in the research of bioinformatics.

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M. Colombo, Rinaldo, and Elena Rossi. "A modeling framework for biological pest control." Mathematical Biosciences and Engineering 17, no. 2 (2020): 1413–27. http://dx.doi.org/10.3934/mbe.2020072.

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WEBB, BARBARA. "A FRAMEWORK FOR MODELS OF BIOLOGICAL BEHAVIOUR." International Journal of Neural Systems 09, no. 05 (October 1999): 375–81. http://dx.doi.org/10.1142/s0129065799000356.

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Modelling is most clearly understood as a adjunct in the process of deriving predictions from hypotheses. By representing a hypothesised mechanism in a model we hope by manipulating the model to understand the hypotheses' consequences. Eight dimensions on which models of biological behaviour can vary are described: the degree of realism with which they apply to biology; the level of biology they represent; the generality or range of systems the model is supposed to cover; the abstraction or amount of biological detail represented; the accuracy of representation of the mechanisms; the medium in which the model is built; the match of the model behaviour to biological behaviour; and the utility of the model in providing biological understanding and/or technical insight. It is hoped this framework will help to clarify debates over different approaches to modelling, particularly by pointing out how the above dimensions are relatively independent and should not be conflated.

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Horie, Ryota. "An optimization framework of biological dynamical systems." Journal of Theoretical Biology 253, no. 1 (July 2008): 45–54. http://dx.doi.org/10.1016/j.jtbi.2008.02.029.

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Maloney, Laurence T. "A mathematical framework for biological color vision." Behavioral and Brain Sciences 15, no. 1 (March 1992): 45–46. http://dx.doi.org/10.1017/s0140525x00067467.

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Schipper, Harvey, Eva A. Turley, and Michael Baum. "A new biological framework for cancer research." Lancet 348, no. 9035 (October 1996): 1149–51. http://dx.doi.org/10.1016/s0140-6736(96)06184-3.

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Blackburn, Tim M., Petr Pyšek, Sven Bacher, James T. Carlton, Richard P. Duncan, Vojtěch Jarošík, John R. U. Wilson, and David M. Richardson. "A proposed unified framework for biological invasions." Trends in Ecology & Evolution 26, no. 7 (July 2011): 333–39. http://dx.doi.org/10.1016/j.tree.2011.03.023.

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Дисертації з теми "Biological framework"

Tagger, B. "A framework for the management of changing biological experimentation." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/147616/.

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There is no point expending time and effort developing a model if it is based on data that is out of date. Many models require large amounts of data from a variety of heterogeneous sources. This data is subject to frequent and unannounced changes. It may only be possible to know that data has fallen out of date by reconstructing the model with the new data but this leads to further problems. How and when does the data change and when does the model need to be rebuilt? At best, the model will need to be continually rebuilt in a desperate attempt to remain current. At worst, the model will be producing erroneous results. The recent advent of automated and semi-automated data-processing and analysis tools in the biological sciences has brought about a rapid expansion of publicly available data. Many problems arise in the attempt to deal with this magnitude of data; some have received more attention than others. One significant problem is that data within these publicly available databases is subject to change in an unannounced and unpredictable manner. Large amounts of complex data from multiple, heterogeneous sources are obtained and integrated using a variety of tools. These data and tools are also subject to frequent change, much like the biological data. Reconciling these changes, coupled with the interdisciplinary nature of in silico biological experimentation, presents a significant problem. We present the ExperimentBuilder, an application that records both the current and previous states of an experimental environment. Both the data and metadata about an experiment are recorded. The current and previous versions of each of these experimental components are maintained within the ExperimentBuilder. When any one of these components change, the ExperimentBuilder estimates not only the impact within that specific experiment, but also traces the impact throughout the entire experimental environment. This is achieved with the use of keyword profiles, a heuristic tool for estimating the content of the experimental component. We can compare one experimental component to another regardless of their type and content and build a network of inter-component relationships for the entire environment. Ultimately, we can present the impact of an update as a complete cost to the entire environment in order to make an informed decision about whether to recalculate our results.

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Linsley, Drew. "A revised framework for human scene recognition." Thesis, Boston College, 2016. http://hdl.handle.net/2345/bc-ir:106986.

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Thesis advisor: Sean P. MacEvoy
For humans, healthy and productive living depends on navigating through the world and behaving appropriately along the way. But in order to do this, humans must first recognize their visual surroundings. The technical difficulty of this task is hard to comprehend: the number of possible scenes that can fall on the retina approaches infinity, and yet humans often effortlessly and rapidly recognize their surroundings. Understanding how humans accomplish this task has long been a goal of psychology and neuroscience, and more recently, has proven useful in inspiring and constraining the development of new algorithms for artificial intelligence (AI). In this thesis I begin by reviewing the current state of scene recognition research, drawing upon evidence from each of these areas, and discussing an unchallenged assumption in the literature: that scene recognition emerges from independently processing information about scenes’ local visual features (i.e. the kinds of objects they contain) and global visual features (i.e., spatial parameters. ). Over the course of several projects, I challenge this assumption with a new framework for scene recognition that indicates a crucial role for information sharing between these resources. Development and validation of this framework will expand our understanding of scene recognition in humans and provide new avenues for research by expanding these concepts to other domains spanning psychology, neuroscience, and AI
Thesis (PhD) — Boston College, 2016
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Psychology

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Keane, John F. "A framework for molecular signal processing and detection in biological cells /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/6126.

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Hwang, Daehee 1971. "A statistical framework for extraction of structured knowledge from biological/biotechnological systems." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/29603.

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Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2003.
Includes bibliographical references (leaves 203-215).
Despite enormous efforts to understand complex biological/biotechnological systems, a significant amount of knowledge has still remained unraveled. However, recent advances in high throughput technologies have offered new opportunities to understand these complex systems by providing us with huge amounts of data about these systems. Unlike traditional tools, these high throughput detection tools: (1) permit large-scale screening of formulations to find the optimal condition, and (2) provide us with a global scale of measurement for a given system. Thus, there has been a strong need for computational tools that effectively extract useful knowledge about systems behavior from the vast amount of data. This thesis presents a comprehensive set of computational tools that enables us to extract important information (called structured knowledge) from this huge amount of data to improve our understanding of biological and biotechnological systems. Then, in several case studies, this extracted knowledge is used to optimize these systems. These tools include: (1) optimal design of experiments (DOE) for efficient investigation of systems, and (2) various statistical methods for effective analyses of the data to capture all structured knowledge in the data. These tools have been applied to various biological and biotechnological systems for identification of: (1) discriminatory characteristics for several diseases from gene expression data to construct disease classifiers; (2) rules to improve plasma absorptions of drugs from high-throughput screening data; (3) binding rules of epitopes to MHC molecules from binding assay data to artificially activate immune responses involving these MHC molecules; (4) rules for pre-conditioning and plasma supplementation from metabolic profiling data to improve the bio-artificial liver (BAL) device;
(cont.) (5) rules to facilitate protein crystallizations from high-throughput screening data to find the optimal condition for crystallization; (6) a new clinical index from metabolic profiling through serum data to improve the diagnostic resolution of liver failure. The results from these applications demonstrate that the developed tools successfully extracted important information to understand systems behavior from various high-throughput data and suggested rules to improve systems performance. In the first case study, the statistical methods helped us identify a drug target for Multiple Scleroses disease through analyses of gene expression data and, then, facilitated finding a peptide drug to inhibit the drug target. In the fifth case study, the methodology enabled us to find large protein crystals for several test proteins difficult to crystallize. The rules identified from the other case studies are being validated for improvement of the systems behavior.
by Daehee Hwang.
Sc.D.

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Yates, Phillip. "An Inferential Framework for Network Hypothesis Tests: With Applications to Biological Networks." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2200.

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The analysis of weighted co-expression gene sets is gaining momentum in systems biology. In addition to substantial research directed toward inferring co-expression networks on the basis of microarray/high-throughput sequencing data, inferential methods are being developed to compare gene networks across one or more phenotypes. Common gene set hypothesis testing procedures are mostly confined to comparing average gene/node transcription levels between one or more groups and make limited use of additional network features, e.g., edges induced by significant partial correlations. Ignoring the gene set architecture disregards relevant network topological comparisons and can result in familiar n

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Alkhairy, Samiya Ashraf. "A modeling framework and toolset for simulation and characterization of the cochlea within the auditory system." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/67201.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 50-53).
Purpose: This research develops a modeling approach and an implementation toolset to simulate reticular lamina displacement in response to excitation at the ear canal and to characterize the cochlear system in the frequency domain. Scope The study develops existing physical models covering the outer, middle, and inner ears. The range of models are passive linear, active linear, and active nonlinear. These models are formulated as differential algebraic equations, and solved for impulse and tone excitations to determine responses. The solutions are mapped into tuning characteristics as a function of position within the cochlear partition. Objectives The central objective of simulation is to determine the characteristic frequency (CF)-space map, equivalent rectangular bandwidth (ERB), and sharpness of tuning (QERB) of the cochlea. The focus of this research is on getting accurate characteristics, with high time and space resolution. The study compares the simulation results to empirical measurements and to predictions of a model that utilizes filter theory and coherent reflection theory. Method We develop lumped and distributed physical models based on mechanical, acoustic, and electrical phenomena. The models are structured in the form of differential-algebraic equations (DAE), discretized in the space domain. This is in contrast to existing methods that solve a set of algebraic equations discretized in both space and time. The DAEs are solved using numerical differentiation formulas (NDFs) to compute the displacement of the reticular lamina and intermediate variables such as displacement of stapes in response to impulse and tone excitations at the ear canal. The inputs and outputs of the cochlear partition are utilized in determining its resonances and tuning characteristics. Transfer functions of the cochlear system with impulse excitation are calculated for passive and active linear models to determine resonance and tuning of the cochlear partition. Output characteristics are utilized for linear systems with tone excitation and for nonlinear models with stimuli of various amplitudes. Stability of the system is determined using generalized eigenvalues and the individual subsystems are stabilized based on their poles and zeros. Results The passive system has CF map ranging from 20 kHz at the base to 10 Hz at the apex of the cochlear partition, and has the strongest resonant frequency corresponding to that of the middle ear. The ERB is on the order of the CF, and the QERB is on the order of 1. The group delay decreases with CF which is in contradiction with findings from Stimulus Frequency Otoacoustic Emissions (SFOAE) experiments. The tuning characteristics of the middle ear correspond well to experimental observations. The stability of the system varies greatly with the choice of parameters, and number of space sections used for both the passive and active implementations. Implication Estimates of cochlear partition tuning based on solution of differential algebraic equations have better time and space resolution compared to existing methods that solve discretized set of equations. Domination of the resonance frequency of the reticular lamina by that of the middle ear rather than the resonant frequency of the cochlea at that position for the passive model is in contradiction with Bekesys measurements on human cadavers. Conclusion The methodology used in the thesis demonstrate the benefits of developing models and formulating the problem as differential-algebraic equations and solving it using the NDFs. Such an approach facilitates computation of responses and transfer functions simultaneously, studying stability of the system, and has good accuracy (controlled directly by error tolerance) and resolution.
by Samiya Ashraf Alkhairy.
M.Eng.

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De, Blocq Andrew Dirk. "Estimating spotted hyaena (Crocuta crocuta) population density using camera trap data in a spatially-explicit capture-recapture framework." Bachelor's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/13053.

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Includes bibliographical references.
Species-specific population data are important for the effective management and conservation of wildlife populations within protected areas. However such data are often logistically difficult and expensive to attain for species that are rare and have large ranges. Camera trap surveys provide a non-invasive, inexpensive and effective method for obtaining population level data on wildlife species. Provided that species can be individually identified, a photographic capture-recapture framework can be used to provide density estimates. Spatially-explicit capture-recapture (SECR) models have recently been developed, and are currently considered the most robust method for analysing capture-recapture data. Camera trap data sourced from a leopard survey performed in uMkhuze Game Reserve, KwaZulu-Natal, South Africa, was analysed using SPACECAP, a Bayesian inference-based SECR modelling program. Overall hyaena density for the reserve was estimated at 10.59 (sd=2.10) hyaenas/100 km2, which is comparable to estimates obtained using other methods for this reserve and some other protected areas in southern Africa. SECR methods are typically conservative in comparison to other methods of measuring large carnivore populations, which is somewhat supported by higher estimates in other nearby reserves. However, large gaps in time between studies and the variety of historical methods used confound comparisons between estimates. The findings from this study provide support for both camera trap surveys and SECR models in terms of deriving robust population data for spotted hyaenas and other individually recognisable species. Such data allows for studies on the drivers of population and distribution changes for such species in addition to temporal and spatial activity patterns and habitat preference for select species. The generation of accurate population data for ecologically important predators provides reserve managers with robust data upon which to make informed management decisions. This study shows that estimates for spotted hyaenas can be produced from an existing survey of leopards, which makes photographic capture-recapture methods a sensible and cost-effective option for the less charismatic species. The implementation of standardized and scientifically robust population estimation methods such as SECR using camera trap data would contribute appreciably to the conservation of important wildlife species and the ecological processes they support.

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Kalantari, John I. "A general purpose artificial intelligence framework for the analysis of complex biological systems." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5953.

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This thesis encompasses research on Artificial Intelligence in support of automating scientific discovery in the fields of biology and medicine. At the core of this research is the ongoing development of a general-purpose artificial intelligence framework emulating various facets of human-level intelligence necessary for building cross-domain knowledge that may lead to new insights and discoveries. To learn and build models in a data-driven manner, we develop a general-purpose learning framework called Syntactic Nonparametric Analysis of Complex Systems (SYNACX), which uses tools from Bayesian nonparametric inference to learn the statistical and syntactic properties of biological phenomena from sequence data. We show that the models learned by SYNACX offer performance comparable to that of standard neural network architectures. For complex biological systems or processes consisting of several heterogeneous components with spatio-temporal interdependencies across multiple scales, learning frameworks like SYNACX can become unwieldy due to the the resultant combinatorial complexity. Thus we also investigate ways to robustly reduce data dimensionality by introducing a new data abstraction. In particular, we extend traditional string and graph grammars in a new modeling formalism which we call Simplicial Grammar. This formalism integrates the topological properties of the simplicial complex with the expressive power of stochastic grammars in a computation abstraction with which we can decompose complex system behavior, into a finite set of modular grammar rules which parsimoniously describe the spatial/temporal structure and dynamics of patterns inferred from sequence data.

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Griesel, Gerhard. "Development and management framework for the Gouritz River Catchment." Pretoria : [s.n.], 2003. http://upetd.up.ac.za/thesis/available/etd-11202003-155742.

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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 systems in terms of the feedback responses among herbivores, decomposers and grass and decomposer community assemblages in a mesic savanna. We sampled these components of the abiotic and biotic template of five sodic and five biotic lawns in the Kruger National Park. We used Î² diversity in grass and dung beetle community assemblages among the lawns to identify whether sodic and biotic lawns were distinct for grass percent cover and dung beetle species abundance. Four and three categories of lawns were identified for these traits, respectively, and placed the lawns on a gradient from biotic-like to sodic-like with a range of intermediates. Soil Na content was higher among sodic lawns but these levels did not manifest themselves in the grass foliar Na content, as for biotic lawns. Herbivore utilization of the sodic lawns was higher than the biotic lawns. Biotic lawns showed no difference in herbivore metabolic biomass between the late-wet and early-mid dry season. We concluded that the systems of nutrient cycling and lawn maintenance are distinct between the biotic and sodic lawns, but that the lawns exist along a gradient in terms of their community characteristics and abiotic features. Efforts to classify grazing lawns will present benefits in improving our understanding of their dynamics and, resultantly, the management and conservation approaches that use them to control herbivore populations in African savanna ecosystems.

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Книги з теми "Biological framework"

Development, New Zealand Ministry of Economic. Bioprospecting: Harnessing benefits for New Zealand : a policy framework discussion. Wellington [N.Z.]: Ministry of Economic Development, 2007.

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(Ireland), Heritage Council. Towards a national framework for the management of biological data. Dublin: Heritage Council, 2002.

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Phantom menace or looming threat?: A new framework for assessing bioweapons threats. Baltimore: Johns Hopkins University Press, 2013.

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Barber, Ben. Building Illinois' biological memory: A framework for long-term ecosystem monitoring. Springfield, Ill: Illinois Dept. of Natural Resources, Energy and Environmental Assessment Division, 2000.

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Vladimir, Krever, World Wildlife Fund (U.S.), and Russia (Federation). Ministerstvo okhrany okruzhai͡u︡shcheĭ sredy i prirodnykh resursov., eds. Conserving Russia's biological diversity: An analytical framework and initial investment portfolio. Washington, D.C: World Wildlife Fund, 1994.

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National Research Council (U.S.). Board on Life Sciences. Reopening public facilities after a biological attack: A decision making framework. Washington, D.C: National Academies Press, 2005.

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Moshe, Shachak, ed. Biodiversity in drylands: Toward a unified framework. Oxford: Oxford University Press, 2005.

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Indian Institute of Management, Ahmedabad., ed. Empowering conservators of biodiversity and associated knowledge systems: An intellectual property based framework. Ahmedabad: Indian Institute of Management, 2002.

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Jenkins, Kurt Jeffrey. A framework for long-term ecological monitoring in Olympic National Park: Prototype for the Coniferous Forest Biome. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2003.

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Частини книг з теми "Biological framework"

Mabberley, D. J. "The Changing Biological Framework." In Tropical Rain Forest Ecology, 52–79. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3672-7_4.

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Mabberley, D. J. "The Changing Biological Framework." In Tropical Rain Forest Ecology, 52–79. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-3048-6_4.

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Kumar, Pramod, Vandana Mishra, and Subarna Roy. "Machine Learning Framework: Predicting Protein Structural Features." In Soft Computing for Biological Systems, 121–41. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7455-4_8.

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Loucks, Orie L. "Policy Framework Issues for Protecting Biological Diversity." In Air Pollution Effects on Biodiversity, 263–79. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3538-6_12.

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Possas, Arícia, Letícia Ungaretti Haberbeck, and Fernando Pérez-Rodríguez. "Food Risk Assessment Framework." In Risk Assessment Methods for Biological and Chemical Hazards in Food, 3–16. Boca Raton : CRC Press, 2021.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429083525-2.

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Moolgavkar, Suresh, and Georg Luebeck. "Multistage Carcinogenesis: A Unified Framework for Cancer Data Analysis." In Statistical Modeling for Biological Systems, 117–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34675-1_7.

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Uttley, Chris. "The Water Framework Directive and the Habitats and Birds Directives." In Biological Monitoring in Freshwater Habitats, 23–29. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9278-7_3.

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Hokkanen, Heikki M. T., Franz Bigler, Giovanni Burgio, Joop C. Van Lenteren, and Matt B. Thomas. "Ecological Risk Assessment Framework for Biological Control Agents." In Environmental Impacts of Microbial Insecticides, 1–14. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-1441-9_1.

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Badura, Jens, Broder Breckling, Thomas Potthast, and Jan Barkmann. "Conclusions: A Generalizing Framework for Biological Orientation Orientation." In Eco Targets, Goal Functions, and Orientors, 355–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58769-6_23.

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Crupi, Vincenzo. "Measures of Biological Diversity: Overview and Unified Framework." In History, Philosophy and Theory of the Life Sciences, 123–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10991-2_6.

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Тези доповідей конференцій з теми "Biological framework"

Krishnamoorthy, K., and T. Mathew. "217. Statistical Framework for Biological Monitoring." In AIHce 2006. AIHA, 2006. http://dx.doi.org/10.3320/1.2758928.

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Singh, Shivani. "An efficient framework for mining biological network." In 2015 International Conference on Advances in Computer Engineering and Applications (ICACEA). IEEE, 2015. http://dx.doi.org/10.1109/icacea.2015.7164735.

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Abdi, Afshin, Arash Einolghozati, and Faramarz Fekri. "Computing framework in biological cells via stochastic methods." In 2017 IEEE Information Theory Workshop (ITW). IEEE, 2017. http://dx.doi.org/10.1109/itw.2017.8278005.

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OKUMURA, TOSHIYUKI, SUSUMU DATE, YOICHI TAKENAKA, and HIDEO MATSUDA. "A FRAMEWORK FOR BIOLOGICAL ANALYSIS ON THE GRID." In Proceedings of the 2nd International Life Science Grid Workshop, LSGRID 2005. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772503_0007.

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"An improved stochastic modelling framework for biological networks." In 23rd International Congress on Modelling and Simulation (MODSIM2019). Modelling and Simulation Society of Australia and New Zealand, 2019. http://dx.doi.org/10.36334/modsim.2019.a1.altarawni.

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da Silva, Bruno S., Taua M. Cabreira, Bruno J. O. De Souza, Nicholas R. Matias, Ricardo A. O. Machado, Lucio Andre C. Jorge, and Paulo Roberto Ferreira. "Framework for Biological Control with Unmanned Aerial Vehicles." In 2022 Latin American Robotics Symposium (LARS), 2022 Brazilian Symposium on Robotics (SBR), and 2022 Workshop on Robotics in Education (WRE). IEEE, 2022. http://dx.doi.org/10.1109/lars/sbr/wre56824.2022.9995875.

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Amami, Maha, Rim Faiz, and Aymen Elkhlifi. "A framework for biological event extraction from text." In the 2nd International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2254129.2254193.

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Briscoe, Jayson, Leah Appelhans, Sean Smith, K. Westlake, Igal Brener, and Jeremy Wright. "Zirconium metal-organic framework functionalized plasmonic sensor." In Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XX, edited by Jason A. Guicheteau and Chris R. Howle. SPIE, 2019. http://dx.doi.org/10.1117/12.2519134.

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Petsios, Stefanos Konstantinos D., and Dimitrios I. Fotiadis. "A Computational Framework for the Analysis of Biological Models." In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4352488.

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"Inverse modeling of biological processes in sensitivity operator framework." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-666.

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Звіти організацій з теми "Biological framework"

Dzenitis, J. Acceptance Criteria Framework for Autonomous Biological Detectors. Office of Scientific and Technical Information (OSTI), December 2006. http://dx.doi.org/10.2172/902228.

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Shakya, B., E. Sharma, J. Gurung, and N. Chettri. The Landscape Approach in Biodiversity Conservation; A Regional Cooperation Framework for Implementation of the Convention on Biological Diversity in the Kangchenjunga Landscape. Kathmandu, Nepal: International Centre for Integrated Mountain Development (ICIMOD), 2007. http://dx.doi.org/10.53055/icimod.479.

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Seale, Maria, Natàlia Garcia-Reyero, R. Salter, and Alicia Ruvinsky. An epigenetic modeling approach for adaptive prognostics of engineered systems. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41282.

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Prognostics and health management (PHM) frameworks are widely used in engineered systems, such as manufacturing equipment, aircraft, and vehicles, to improve reliability, maintainability, and safety. Prognostic information for impending failures and remaining useful life is essential to inform decision-making by enabling cost versus risk estimates of maintenance actions. These estimates are generally provided by physics-based or data-driven models developed on historical information. Although current models provide some predictive capabilities, the ability to represent individualized dynamic factors that affect system health is limited. To address these shortcomings, we examine the biological phenomenon of epigenetics. Epigenetics provides insight into how environmental factors affect genetic expression in an organism, providing system health information that can be useful for predictions of future state. The means by which environmental factors influence epigenetic modifications leading to observable traits can be correlated to circumstances affecting system health. In this paper, we investigate the general parallels between the biological effects of epigenetic changes on cellular DNA to the influences leading to either system degradation and compromise, or improved system health. We also review a variety of epigenetic computational models and concepts, and present a general modeling framework to support adaptive system prognostics.

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Skalski, John R., and Roger F. Ngouenet. Monitoring and Evaluation of Smolt Migration in the Columbia Basin : Volume VII : Evaluation of the Compliance Testing Framework for RPA Improvement as Stated in the 2000 Federal Columbia River Power System (FCRPS) Biological Opinion. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/961873.

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Fleishman, Erica. Sixth Oregon climate assessment. Oregon Climate Change Research Institute, Oregon State University, 2023. http://dx.doi.org/10.5399/osu/1161.

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Consistent with its charge under Oregon House Bill 3543, the Oregon Climate Change Research Institute (OCCRI) conducts a biennial assessment of the state of climate change science, including biological, physical, and social science, as it relates to Oregon and the likely effects of climate change on Oregon. This sixth Oregon Climate Assessment builds on the previous assessments by continuing to evaluate past and projected future changes in Oregon’s climate and water supply. Like the fifth assessment, it is structured with the goal of supporting the state’s mitigation planning for natural hazards and implementation of the 2021 Oregon Climate Change Adaptation Framework.

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Dalton, Meghan M., and Erica Fleishman. Fifth Oregon climate assessment. Oregon Climate Change Research Institute, Oregon State University, 2021. http://dx.doi.org/10.5399/osu/1160.

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Consistent with its charge under Oregon House Bill 3543, the Oregon Climate Change Research Institute (OCCRI) conducts a biennial assessment of the state of climate change science, including biological, physical, and social science, as it relates to Oregon and the likely effects of climate change on Oregon. This fifth Oregon Climate Assessment builds on previous assessments (Dello and Mote 2010; Dalton et al. 2013, 2017; Mote et al. 2019) by continuing to evaluate past and projected future changes in Oregon’s climate and hydrology. This Assessment is structured with the goal of serving as a resource for the state’s mitigation planning for natural hazards and implementation of the 2021 Oregon Climate Change Adaptation Framework.

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Yurovskaya, M. V., and A. V. Yushmanova. Complex Investigations of the World Ocean. Proceedings of the VI Russian Scientific Conference of Young Scientists. Edited by D. A. Alekseev, A. Yu Andreeva, I. M. Anisimov, A. V. Bagaev, Yu S. Bayandina, E. M. Bezzubova, D. F. Budko, et al. Shirshov Institute Publishing House, April 2021. http://dx.doi.org/10.29006/978-5-6045110-3-9.

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The collection contains materials of the VI All-Russian Scientific Conference of Young Scientists "Complex Investigations of the World Ocean", dedicated to the discussion of the main scientific achievements of young specialists in the field of oceanology, modern methods and means of studying the World Ocean. Within the framework of the conference, issues of modern oceanology were considered in sections: ocean physics, ocean biology, ocean chemistry, marine geology, marine geophysics, marine ecology and environmental management, oceanological technology and instrumentation, as well as interdisciplinary physical and biological research of the ocean. Along with the coverage of the results obtained in the course of traditional oceanological expeditionary research, attention was paid to the development of modern methods of studying the ocean: numerical modeling and remote sensing methods of the Earth from space.

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Serre, Thomas, Lior Wolf, and Tomaso Poggio. A New Biologically Motivated Framework for Robust Object Recognition. Fort Belvoir, VA: Defense Technical Information Center, November 2004. http://dx.doi.org/10.21236/ada454724.

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Kapulnik, Yoram, and Donald A. Phillips. Isoflavonoid Regulation of Root Bacteria. United States Department of Agriculture, January 1996. http://dx.doi.org/10.32747/1996.7570561.bard.

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The overall objective of this project was to develop a conceptual framework for enhancing root colonization by beneficial bacteria. To accomplish this aim we tested the hypothesis that production and excretion of the plant phytoalexin medicarpin can be used for creation of a special niche along the legume roots, where beneficial microorganism, such as rhizobium, will have a selective advantage. On the Israeli side it was shown that higher medicarpin levels are exuded following the application of Rhizobium meliloti to the rhizosphere but the specific biochemical pathway governing medicarpin production was not induced significantly enough to support a constant production and excretion of this molecule to the rhizosphere. Furthermore, pathogenic bacteria and chemical elicitors were found to induce higher levels of this phytoalexin and it became important to test its natural abundance in field grown plants. On the US side, the occurrence of flavonoids and nucleosides in agricultural soils has been evaluated and biologically significant quantities of these molecules were identified. A more virulent Agrobacterium tumefaciens strain was isolated from alfalfa (Medicago sativa L.) which forms tumors on a wide range of plant species. This isolate contains genes that increase competitive colonization abilities on roots by reducing the accumulation of alfalfa isoflavonoids in the bacterial cells. Following gene tagging efforts the US lab found that mutation in the bacterial efflux pump operons of this isolate reduced its competitive abilities. This results support our original hypothesis that detoxification activity of isoflavenoids molecules, based on bacterial gene(s), is an important selection mechanism in the rhizosphere. In addition, we focused on biotin as a regulatory element in the rhizosphere to support growth of some rhizosphere microorganisms and designed a bacterial gene construct carrying the biotin-binding protein, streptavidin. Expressing this gene in tobacco roots did not affect the biotin level but its expression in alfalfa was lethal. In conclusion, the collaborative combination of basic and applied approaches toward the understanding of rhizosphere activity yielded new knowledge related to the colonization of roots by beneficial microorganisms in the presence of biological active molecules exuded from the plant roots.

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