10,000 publications from this institution
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
The study of chemical reactions with oscillating kinetics has drawn increasing interest over the last few decades because it also contributes towards a deeper understanding of the complex phenomena of temporal and spatial organizations in biological systems. The Cellular Nonlinear Network (CNN) local activity principle introduced by Chua [1997, 2005] has provided a powerful tool for studying the emergence of complex patterns in a homogeneous lattice formed by coupled cells. Recently, Yang and Epstein proposed a reaction–diffusion Oregonator model with five variables for mimicking the Belousov–Zhabotinskii reaction. The Yang–Epstein model can generate oscillatory Turing patterns, including the twinkling eye, localized spiral and concentric wave structures. In this paper, we first propose a modified Yang–Epstein's Oregonator model by introducing a controller, and then map the revised Oregonator reaction–diffusion system into a reaction–diffusion Oregonator CNN. The Oregonator CNN has two cell equilibrium points Q 1 = (0, 0, 0, 0, 0) and Q 2 , representing the "original" equilibrium point and an additional equilibrium point, respectively. The bifurcation diagrams of the Oregonator CNN are calculated using the analytical criteria for local activity. The bifurcation diagrams of the Oregonator CNN at Q 1 have only locally active and unstable regions; and the ones at Q 2 have locally passive regions, locally active and unstable regions, and edge of chaos regions. The calculated results show that the parameter groups of the Oregonator CNN which generate complex patterns are located on the edge of chaos regions, or on locally active unstable regions near the edge of chaos boundary. Numerical simulations show also that the Oregonator CNNs can generate similar dynamics patterns if the parameter groups are selected the same as those of the Yang–Epstein model. In particular, the parameters of the Yang–Epstein model which exhibit twinkling-eye patterns, and pinwheel patterns are located on the edges of chaos regions near the boundaries of locally active unstable regions with respect to Q 2 . The parameters of the Yang–Epstein models which exhibit labyrinthine stripelike patterns are located on the locally active unstable regions near the boundaries of the edge of chaos regions with respect to Q 2 . However the parameter group of the Yang–Epstein model with isolated spiral patterns is in the locally passive region near the boundary with edge of chaos with respect to Q 2 , whose trajectories tend to the equilibrium point Q 2 . Choosing a kind of triggering initial conditions given in [Chua, 1997], and the parameters of the Oregonator equations with the twinkling-eye patterns, pinwheel patterns, labyrinthine stripelike patterns, and isolated spiral patterns, three kinds of new spiral waves generated by the Oregonator CNNs were observed by numerical simulations. They seem to be essentially different patterns to those generated by the Oregonator CNNs with initial conditions consisting of equilibrium points plus small random perturbations. Our results demonstrate once again Chua's assertion that a wide spectrum of complex behaviors may exist if the corresponding CNN cell parameters are chosen in or near the edge of chaos region.
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Insomnia is prevalent, causing severe distress and impairment. This review focuses on illuminating the puzzling finding that many insomnia patients misperceive their sleep. They overestimate their sleep onset latency (SOL) and underestimate their total sleep time (TST), relative to objective measures. This tendency is ubiquitous (although not universal). Resolving this puzzle has clinical, theoretical, and public health importance. There are implications for assessment, definition, and treatment. Moreover, solving the puzzle creates an opportunity for real-world applications of theories from clinical, perceptual, and social psychology as well as neuroscience. Herein we evaluate 13 possible resolutions to the puzzle. Specifically, we consider the possible contribution, to misperception, of (1) features inherent to the context of sleep (e.g., darkness); (2) the definition of sleep onset, which may lack sensitivity for insomnia patients; (3) insomnia being an exaggerated sleep complaint; (4) psychological distress causing magnification; (5) a deficit in time estimation ability; (6) sleep being misperceived as wake; (7) worry and selective attention toward sleep-related threats; (8) a memory bias influenced by current symptoms and emotions, a confirmation bias/belief bias, or a recall bias linked to the intensity/recency of symptoms; (9) heightened physiological arousal; (10) elevated cortical arousal; (11) the presence of brief awakenings; (12) a fault in neuronal circuitry; and (13) there being 2 insomnia subtypes (one with and one without misperception). The best supported resolutions were misperception of sleep as wake, worry, and brief awakenings. A deficit in time estimation ability was not supported. We conclude by proposing several integrative solutions.
Data-driven character animation based on motion capture can produce highly naturalistic behaviors and, when combined with physics simulation, can provide for natural procedural responses to physical perturbations, environmental changes, and morphological discrepancies. Motion capture remains the most popular source of motion data, but collecting mocap data typically requires heavily instrumented environments and actors. In this paper, we propose a method that enables physically simulated characters to learn skills from videos (SFV). Our approach, based on deep pose estimation and deep reinforcement learning, allows data-driven animation to leverage the abundance of publicly available video clips from the web, such as those from YouTube. This has the potential to enable fast and easy design of character controllers simply by querying for video recordings of the desired behavior. The resulting controllers are robust to perturbations, can be adapted to new settings, can perform basic object interactions, and can be retargeted to new morphologies via reinforcement learning. We further demonstrate that our method can predict potential human motions from still images, by forward simulation of learned controllers initialized from the observed pose. Our framework is able to learn a broad range of dynamic skills, including locomotion, acrobatics, and martial arts. (Video 1 )
To increase environmental health literacy (EHL) and leadership skills in Latino youth in Salinas, CA., we worked from 2012–2015 with 15 members of the CHAMACOS Youth Community Council (YCC), an outreach arm of a longitudinal study of impacts of environmental chemicals on children’s health. The YCC program provided hands-on research experiences related to Endocrine Disrupting Chemicals (EDCs) in cosmetics and their possible health effects. We use participatory research principles and Bloom’s Taxonomy of Educational Objectives to describe the development of EHC and leadership in the youth co-researchers. Using data from multiple qualitative sources, we explore the youths' engagement in a wide range of research and action processes. Promising outcomes, including perceptions of improved youth self-esteem, EHL, leadership, and career orientation are discussed, as are challenges, such as time constraints and high priority youth concerns not addressed by the study. Implications for other youth-engaged participatory science and leadership programs are presented.
Pore ‐ size ‐ specific functionalization is a novel approach that allowspreviously undreamed of control of the location of groups undergoing reaction in the surface modigication of preformedporous polymers. That sozespecific functionalization makes possible the simultaneous accommodation of seemingly incompatible requirements is demonstrated by the preparation of porous polyner beads with bimodal surface chemistry. Applications of this technique are foreseen in thechromatographic separation of complex miztures, sensors, catalyses, and eczyme immobilization.
