MONOMIALS AND BASIN CYLINDERS FOR NETWORK DYNAMICS.
Ontology highlight
ABSTRACT:
SUBMITTER: Austin D
PROVIDER: S-EPMC4299671 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
MONOMIALS AND BASIN CYLINDERS FOR NETWORK DYNAMICS.
Austin Daniel D Dinwoodie Ian H IH
SIAM journal on applied dynamical systems 20150101 1
We describe methods to identify cylinder sets inside a basin of attraction for Boolean dynamics of biological networks. Such sets are used for designing regulatory interventions that make the system evolve towards a chosen attractor, for example initiating apoptosis in a cancer cell. We describe two algebraic methods for identifying cylinders inside a basin of attraction, one based on the Groebner fan that finds monomials that define cylinders and the other on primary decomposition. Both methods ...[more]
Similar Datasets
Project description:Basin stability (BS) is a universal concept for complex systems studies, which focuses on the volume of the basin of attraction instead of the traditional linearization-based approach. It has a lot of applications in real-world systems especially in dynamical systems with a phenomenon of multi-stability, which is even more ubiquitous in delayed dynamics such as the firing neurons, the climatological processes, and the power grids. Due to the infinite dimensional property of the space for the initial values, how to properly define the basin's volume for delayed dynamics remains a fundamental problem. We propose here a technique which projects the infinite dimensional initial state space to a finite-dimensional Euclidean space by expanding the initial function along with different orthogonal or nonorthogonal basis. A generalized concept of basin's volume in delayed dynamics and a highly practicable calculating algorithm with a cross-validation procedure are provided to numerically estimate the basin of attraction in delayed dynamics. We show potential applicabilities of this approach by applying it to study several representative systems of biological or/and physical significance, including the delayed Hopfield neuronal model with multistability and delayed complex networks with synchronization dynamics.
| S-EPMC4764917 | biostudies-literature
Project description:Shear-induced microstructures and their corresponding dynamic processes are investigated for phospholipid cylinders in aqueous solution by dissipative particle dynamic simulation. Various phospholipid cylinders with cross-sections, which are formed under shear-free flow, are selected to examine the effects of shear flow on their structures and dynamic processes. Shear flow induces the transition from cylinders into vesicles at weak rate and the transition into vesicle-lamella mixtures with increased shear rate and lamella structures at the strong shear rate. Then, the average radius of gyration and shape factors of the polymer chains in the dynamic processes are discussed in detail. Results show that shear flow causes the structure of the polymer chains to be elongated along the shear direction, and the configuration of the polymer chain can be rapidly transformed into an ellipsoid structure under strong shear.
| S-EPMC6817888 | biostudies-other
Project description:The realization of concurrently largely expandable and selectively rigid structures poses a fundamental challenge in modern engineering and materials research. Radially expanding structures in particular are known to require a high degree of deformability to achieve considerable dimension change, which restrains achievable stiffness in the direction of expanding motion. Mechanically hinged or plastically deformable wire-mesh structures and pressurized soft materials are known to achieve large expansion ratios, however often lack stiffness and require complex actuation. Cardiovascular or drug delivery implants are one example which can benefit from a largely expandable architecture that is simple in geometry and intrinsically stiff. Continuous shell cylinders offer a solution with these properties. However, no designs exist that achieve large expansion ratios in such shells when utilizing materials which can provide considerable stiffness. We introduce a new design paradigm for expanding continuous shells that overcomes intrinsic limitations such as poor deformability, insufficient stiffness and brittle behaviour by exploiting purely elastic deformation for self-expandable and ultra-thin polymer composite cylinders. By utilizing shell-foldability coupled with exploitation of elastic instabilities, we create continuous cylinders that can change their diameter by more than 2.5 times, which are stiff enough to stretch a confining vessel with their elastic energy. Based on folding experiments and analytical models we predict feasible radial expansion ratios, currently unmatched by comparable cylindrical structures. To emphasize the potential as a future concept for novel simple and durable expanding implants, we demonstrate the functionality on a to-scale prototype in packaging and expansion and predict feasible constellations of deployment environments.
| S-EPMC6828719 | biostudies-literature
Project description:If an object is very small in size compared with the wavelength of light, it does not scatter light efficiently. It is hence difficult to detect a very small object with light. We show using analytic theory as well as full wave numerical calculation that the effective polarizability of a small cylinder can be greatly enhanced by coupling it with a superlens type metamaterial slab. This kind of enhancement is not due to the individual resonance effect of the metamaterial slab, nor due to that of the object, but is caused by a collective resonant mode between the cylinder and the slab. We show that this type of particle-slab resonance which makes a small two-dimensional object much "brighter" is actually closely related to the reverse effect known in the literature as "cloaking by anomalous resonance" which can make a small cylinder undetectable. We also show that the enhancement of polarizability can lead to strongly enhanced electromagnetic forces that can be attractive or repulsive, depending on the material properties of the cylinder.
| S-EPMC4650704 | biostudies-literature
Project description:The optimal distribution of the reinforcing fibers for stiffening hollow cylindrical composites is explored using the linear elasticity theory. The spatial distribution of the vascular bundles in wild bamboo, a nature-designed functionally graded material, is the basis for the design. Our results suggest that wild bamboos maximize their flexural rigidity by optimally regulating the radial gradation of their vascular bundle distribution. This fact provides us with a plant-mimetic design principle that enables the realization of high-stiffness and lightweight cylindrical composites.
| S-EPMC5414991 | biostudies-literature
Project description:Natural and human disturbances have caused widespread regime shifts in shallow lakes of the lower Yangtze basin (LYB, China) resulting in a severe decline of ecosystem services. Improved understanding of the relationship between environmental forcing and ecosystem response, and the mechanisms behind regime shifts has significant implications for management. However, the patterns of these regime shifts and the underlying internal mechanisms are less known. In this study, two typical lakes (Chaohu and Zhangdu) from the LYB were selected to determine the trajectories of ecological regime shifts, both of which transitioned from vegetation- to plankton-dominated states several decades ago. Ecological trajectories since the 1900s in both lakes were reconstructed using palaeolimnological proxies, mainly diatom assemblages. Although results show that regime shifts occurred in both lakes in the 1970s and the 1950s, respectively, their inherent mechanisms were different. In Lake Zhangdu, altered hydrological conditions pushed the ecosystem across an ecological threshold, providing an example of a driver-mediated regime shift. In Lake Chaohu, ongoing nutrient loading influenced ecosystem processes and drove the lake to an alternative stable state, potentially presenting an example of a critical transition after a loss of resilience. This research indicates that palaeolimnological perspectives can provide insights into regime shift changes, as well as important information regarding which restoration methods should be tailored to individual lakes.
| S-EPMC6892519 | biostudies-literature
Project description:IntroductionRuminant production in the Black Sea basin (BSB) is critical for national economies and the subsistence of rural populations. Yet, zoonoses and transboundary animal diseases (TADs) are limiting and threatening the sector. To gain a more comprehensive understanding, this study characterizes key aspects of the ruminant sector in nine countries of the BSB, including Armenia, Azerbaijan, Belarus, Bulgaria, Georgia, Moldova, Romania, Türkiye, and Ukraine.MethodsWe selected six priority ruminant diseases (anthrax, brucellosis, Crimean Congo haemorrhagic fever (CCHF), foot-and-mouth disease (FMD), lumpy skin disease (LSD), and peste des petits ruminants (PPR)) that are present or threaten to emerge in the region. Standardized questionnaires were completed by a network of focal points and supplemented with external sources. We examined country and ruminant-specific data such as demographics, economic importance, and value chains in each country. For disease-specific data, we analysed the sanitary status, management strategies, and temporal trends of the selected diseases.Results and discussionThe shift from a centrally planned to a market economy, following the collapse of the Soviet Union, restructured the ruminant sector. This sector played a critical role in rural livelihoods within the BSB. Yet, it faced significant challenges such as the low sustainability of pastoralism, technological limitations, and unregistered farms. Additionally, ruminant health was hindered by informal animal trade as a result of economic factors, insufficient support for the development of formal trade, and socio-cultural drivers. In the Caucasus and Türkiye, where diseases were present, improvements to ruminant health were driven by access to trading opportunities. Conversely, European countries, mostly disease-free, prioritized preventing disease incursion to avoid a high economic burden. While international initiatives for disease management are underway in the BSB, there is still a need for more effective local resource allocation and international partnerships to strengthen veterinary health capacity, protect animal health and improve ruminant production.
| S-EPMC10557248 | biostudies-literature
Project description:Despite significant advances in characterizing the structural properties of complex networks, a mathematical framework that uncovers the universal properties of the interplay between the topology and the dynamics of complex systems continues to elude us. Here we develop a self-consistent theory of dynamical perturbations in complex systems, allowing us to systematically separate the contribution of the network topology and dynamics. The formalism covers a broad range of steady-state dynamical processes and offers testable predictions regarding the system's response to perturbations and the development of correlations. It predicts several distinct universality classes whose characteristics can be derived directly from the continuum equation governing the system's dynamics and which are validated on several canonical network-based dynamical systems, from biochemical dynamics to epidemic spreading. Finally, we collect experimental data pertaining to social and biological systems, demonstrating that we can accurately uncover their universality class even in the absence of an appropriate continuum theory that governs the system's dynamics.
| S-EPMC3852675 | biostudies-literature
Project description:To develop new magnetization-prepared imaging schemes based on a three-dimensional (3D) concentric cylinders trajectory.The 3D concentric cylinders trajectory, which is robust to off-resonance effects and timing delays while requiring fewer excitations than a comparable 3D Cartesian (3DFT) sequence, is used as the readout for magnetization-prepared sequences exploiting its inherently centric-ordered structure. Two applications: (i) T1 -weighted brain imaging with an inversion-recovery-prepared radiofrequency-spoiled gradient-echo (IR-SPGR) sequence, (ii) non-contrast-enhanced (NCE) peripheral angiography with a magnetization-prepared balanced steady-state free precession (bSSFP) sequence are presented to demonstrate the effectiveness of the proposed method. For peripheral angiography, the scan efficiency is further improved by interleaving different preparations at different rates and by carefully designing the sampling geometry for an efficient parallel imaging method.In vivo brain scans with an IR-SPGR sequence and lower extremity scans with a magnetization-prepared bSSFP sequence for NCE peripheral angiography both demonstrate that the proposed sequences with concentric cylinders effectively capture the transient magnetization-prepared contrast with faster scan times than a corresponding 3DFT sequence. The application of peripheral angiography also shows the feasibility of the proposed interleaving schemes and parallel imaging method.The 3D concentric cylinders trajectory is a robust and efficient readout that is well-suited for magnetization-prepared imaging.
| S-EPMC4056679 | biostudies-literature
Project description:Considerable attention has been given to deep-learning and machine-learning techniques in an effort to reduce the computational cost of computational fluid dynamics simulation. The present paper addresses the prediction of steady flows passing many fixed cylinders using a deep-learning model and investigates the accuracy of the predicted velocity field. The deep-learning model outputs the x- and y-components of the flow velocity field when the cylinder arrangement is input. The accuracy of the predicted velocity field is investigated, focusing on the velocity profile of the fluid flow and the fluid force acting on the cylinders. The present model accurately predicts the flow when the number of cylinders is equal to or close to that set in the training dataset. The extrapolation of the prediction to a smaller number of cylinders results in error, which can be interpreted as internal friction of the fluid. The results of the fluid force acting on the cylinders suggest that the present deep-learning model has good generalization performance for systems with a larger number of cylinders.
| S-EPMC8748461 | biostudies-literature