196,820 research outputs found
Statistical physics approaches to collective behavior in networks of neurons
No full textIn recent years, advances in experimental techniques have allowed for the first time simultaneous measurements of many interacting components in living systems at almost all scales, making now an exciting time to search for physical principles of collective behavior in living systems. This thesis focuses on statistical physics approaches to collective behavior in networks of interconnected neurons; both statistical inference methods driven by real data, and analytical methods probing the theory of emergent behavior, are discussed.
Chapter 3 is based on work with F. Randi, A. M. Leifer, and W. Bialek, where we constructed a joint probability model for the neural activity of the nematode, Caenorhabditis elegans. In particular, we extended the pairwise maximum entropy model, a statistical physics approach to consistently infer distributions from data that has successfully described the activity of networks with spiking neurons, to this very different system with neurons exhibiting graded potential. We discuss signatures of collective behavior found in the inferred models.
Chapter 4 is based on work with W. Bialek, where we examine the tuning condition for the connection matrix among neurons such that the resulting dynamics exhibit long time scales. Starting from the simplest case of random symmetric connections, we combine maximum entropy and random matrix theory methods to explore the constraints required from long time scales to become generic. We argue that a single long time scale can emerge generically from realistic constraints, but a full spectrum of slow modes requires more tuning
Application of wind generation capacity credits in the Great Britain and Irish systems
No full textPaper presented at Cigre 2010, 22nd to 27th August 2010, Paris, FranceThe concept of capacity credit is widely used to quantify the contribution of renewable
technologies to securing demand. This may be quantified in a number of ways; this paper
recommends the use of Effective Load Carrying Capability (ELCC, the additional demand
which the new generation can support without increasing system risk), with system risk being measured using Loss of Load Expectation (LOLE, this is calculated through direct use of historic time series for demand and wind load factor). The key benefit of this approach is that it automatically incorporates the available statistical information on the relationship between
wind availability and demand during the hours of very high demand which are most relevant
in assessing system adequacy risk. The underlying assumptions are discussed in detail, and a comparison is made with alternative calculation approaches; a theme running through the paper is the need to consider the assumptions carefully when presenting or interpreting risk
assessment results. A range of applications of capacity credits from Great Britain and Ireland are presented; this includes presentation of effective plant margin, ensuring that the optimal plant mix secures
peak demand in economic projection models, and the Irish capacity payments system.
Finally, new results comparing capacity credit results from the Great Britain and Irish systems using the same wind data are presented. This allows the various factors which influence capacity credit results to be identified clearly. It is well known that increasing the wind load factor or demand level typically increases the calculated capacity credit, while increasing the installed wind capacity typically decreases its capacity credit (as a percentage
of rated capacity). The new results also show that the width of the probability distribution for available conventional generating capacity, relative to the peak demand level, also has a strong influence on the results. This emphasises further that detailed understanding of risk model structures is vitally important in practical application.Science Foundation IrelandCharles Parsons Energy Research AwardsCharles Parson
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Constrained spectral clustering based methodology for intentional controlled islanding of large-scale power systems
No full textIntentional controlled islanding is an effective corrective approach to minimise the impact of cascading outages leading to large-area blackouts. This study proposes a novel methodology, based on `constrained spectral clustering', that is computationally very efficient and determines an islanding solution with minimal power flow disruption, while ensuring that each island contains only coherent generators. The proposed methodology also enables operators to constrain any branch, which must not be disconnected, to be excluded from the islanding solution. The methodology is tested using the dynamic models of the IEEE 39- and IEEE 118-bus test systems. Time-domain simulation results for different contingencies are used to demonstrate the effectiveness of the proposed methodology to minimise the impact of cascading outages leading to large-area blackouts. In addition, a realistically sized system (a reduced model of the Great Britain network with 815 buses) is used to evaluate the efficiency and accuracy of the methodology in large-scale networks. These simulations demonstrate that the author's methodology is more efficient, in a factor of approximately 10, and more accurate than another existing approach for minimal power flow disruption
Temporal precision of the encoding of motion information by visual interneurons
No full textWarzecha A-K, Kretzberg J, Egelhaaf M. Temporal precision of the encoding of motion information by visual interneurons. Current Biology. 1998;8(7):359-368.BACKGROUND:
There is much controversy about the timescale on which neurons process and transmit information. On the one hand, a vast amount of information can be processed by the nervous system if the precise timing of individual spikes on a millisecond timescale is important. On the other hand, neuronal responses to identical stimuli often vary considerably and stochastic response fluctuations can exceed the mean response amplitude. Here, we examined the timescale on which neural responses could be locked to visual motion stimuli.
RESULTS:
Spikes of motion-sensitive neurons in the visual system of the blowfly are time-locked to visual motion with a precision in the range of several tens of milliseconds. Nevertheless, different motion-sensitive neurons with largely overlapping receptive fields generate a large proportion of spikes almost synchronously. This precision is brought about by stochastic rather than by motion-induced membrane-potential fluctuations elicited by the common peripheral input. The stochastic membrane-potential fluctuations contain more power at frequencies above 30-40 Hz than the motion-induced potential changes. A model of spike generation indicates that such fast membrane-potential changes are a major determinant of the precise timing of spikes.
CONCLUSIONS:
The timing of spikes in neurons of the motion pathway of the blowfly is controlled on a millisecond timescale by fast membrane-potential fluctuations. Despite this precision, spikes do not lock to motion stimuli on this timescale because visual motion does not induce sufficiently rapid changes in the membrane potential
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
No full textHosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
Statistical mechanics for natural flocks of birds
No full textFlocking is a typical example of emergent collective behavior, where interactions between individuals produce collective patterns on the large scale. Here we show how a quantitative microscopic theory for directional ordering in a flock can be derived directly from field data. We construct the minimally structured (maximum entropy) model consistent with experimental correlations in large flocks of starlings. The maximum entropy model shows that local, pairwise interactions between birds are sufficient to correctly predict the propagation of order throughout entire flocks of starlings, with no free parameters. We also find that the number of interacting neighbors is independent of flock density, confirming that interactions are ruled by topological rather than metric distance. Finally, by comparing flocks of different sizes, the model correctly accounts for the observed scale invariance of long-range correlations among the fluctuations in flight direction.Flocking is a typical example of emergent collective behavior, where interactions between individuals produce collective patterns on the large scale. Here we show how a quantitative microscopic theory for directional ordering in a flock can be derived directly from field data. We construct the minimally structured (maximum entropy) model consistent with experimental correlations in large flocks of starlings. The maximum entropy model shows that local, pairwise interactions between birds are sufficient to correctly predict the propagation of order throughout entire flocks of starlings, with no free parameters. We also find that the number of interacting neighbors is independent of flock density, confirming that interactions are ruled by topological rather than metric distance. Finally, by comparing flocks of different sizes, the model correctly accounts for the observed scale invariance of long-range correlations among the fluctuations in flight direction
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