Exchange operator formalism for N-body spin models with near-neighbors interactions

We present a detailed analysis of the spin models with near-neighbors interactions constructed in our previous paper [Phys. Lett. B 605 (2005) 214] by a suitable generalization of the exchange operator formalism. We provide a complete description of a certain flag of finite-dimensional spaces of spin functions preserved by the Hamiltonian of each model. By explicitly diagonalizing the Hamiltonian in the latter spaces, we compute several infinite families of eigenfunctions of the above models in closed form in terms of generalized Laguerre and Jacobi polynomials.Comment: RevTeX, 31 pages, no figures; important additional conten

Hyperspectral Image Processing Using Locally Linear Embedding

We describe a method of processing hyperspectral images of natural scenes that uses a combination of k-means clustering and locally linear embedding (LLE). The primary goal is to assist anomaly detection by preserving spectral uniqueness among the pixels. In order to reduce redundancy among the pixels, adjacent pixels which are spectrally similar are grouped using the k-means clustering algorithm. Representative pixels from each cluster are chosen and passed to the LLE algorithm, where the high dimensional spectral vectors are encoded by a low dimensional mapping. Finally, monochromatic and tri-chromatic images are constructed from the k-means cluster assignments and LLE vector mappings. The method generates images where differences in the original spectra are reflected in differences in the output vector assignments. An additional benefit of mapping to a lower dimensional space is reduced data size. When spectral irregularities are added to a patch of the hyperspectral images, again the method successfully generated color assignments that detected the changes in the spectra

New Constraints on the Timing and Pattern of Deglaciation in the Húnaflói Bay Region of Northwest Iceland Using Cosmogenic 36CA Dating and Geomorphic Mapping

Understanding the evolution and timing of changes in ice sheet geometry and extent in Iceland during the Last Glacial Maximum (LGM) and subsequent deglaciation continues to stimulate much active research. Though many previous studies have advanced our knowledge of Icelandic ice sheet history preserved in marine and terrestrial settings (e.g., Andrews et al., 2000; Norðdahl et al., 2008), the timing of ice margin retreat remains largely unknown in several key regions. Recently published 36Cl surface exposure ages of bedrock surfaces and moraines in the West Fjords (Brynjólfsson et al., 2015) contribute important progress in establishing more precise age control of ice recession in northwest Iceland. In another recent study, the spatial pattern and style of deglaciation in northern Iceland have been revealed through geomorphic mapping and GIS analyses of glacial landforms (Principato et al., 2016). Additional insight comes from updated numerical modeling reconstructions, which now provide a series of glaciologically plausible Icelandic ice sheet configurations from the LGM through the last deglaciation (Patton et al., 2017). However, the optimization of ice sheet model simulations relies on critical comparisons with the available empirical record of glacial-geologic evidence and chronological control, which remains relatively limited and sparsely distributed throughout Iceland. Our investigation is motivated by the need for more accurate constraints on the deglacial history in northern Iceland, where dated terrestrial records of ice margin retreat are particularly scarce. (excerpt

A Computational Model of the Nucleus Accumbens: Network Properties and their Functional Implications

The Nucleus accumbens integrates convergent input from a number of limbic structures, and has been implicated in a variety of behavioral disorders including addiction and schizophrenia. The bistable membrane properties of the principal cell in the NAcb, the GABAergic medium spiny projection neuron (MSP), have been proposed to mediate afferent integration. To investigate how intrinsic properties may underlie this mechanism, we constructed a model of an MSP neuron in GENESIS, which preserves the main morphological features and relevant ionichynaptic currents. The model captures the major properties of in vivo neurons, including a non-linear response to the number of afferent inputs. In order to examine network properties of the NAcb and its response to varying patterns of afferent input, a 100- cell network with modifiable levels of gap junctions and GABAergic synaptic connectivity was constructed. Afferent inputs were modeled as Poisson-distributed spike trains. Addition of lateral inhibition in the network led to a decrease in spike output for cells receiving less synchronized input, suggesting that this may be a mechanism for increasing the signal to noise ratio. Dopaminergic modulation of the whole network led to a slight increase in overall synchronization, but did not further segregate cells that were already receiving synchronous input

Forward Analysis and Model Checking for Trace Bounded WSTS

We investigate a subclass of well-structured transition systems (WSTS), the bounded---in the sense of Ginsburg and Spanier (Trans. AMS 1964)---complete deterministic ones, which we claim provide an adequate basis for the study of forward analyses as developed by Finkel and Goubault-Larrecq (Logic. Meth. Comput. Sci. 2012). Indeed, we prove that, unlike other conditions considered previously for the termination of forward analysis, boundedness is decidable. Boundedness turns out to be a valuable restriction for WSTS verification, as we show that it further allows to decide all $\omega$-regular properties on the set of infinite traces of the system

Principal Component Analysis of Temporal and Spatial Information for Human Gait Recognition

Principal component analysis was applied to human gait patterns to investigate the role and relative importance of temporal versus spatial features. Datasets consisted of various limb and body angles sampled over increasingly long time intervals. We find that spatial and temporal cues may be useful for different aspects of recognition. Temporal cues contain information that can distinguish the phase of the gait cycle; spatial cues are useful for distinguishing running from walking. PCA and related techniques may be useful for identifying features used by the visual system for recognizing biological motion

Curvature Covariation as a Factor in Perceptual Salience

The salience of a contour depends upon several factors, including continuity, closure and curvature consistency. We analyze the statistics of curvature variation using a single image from Shimon Ullman’s [1] original work on contour salience. We develop a measure based on the arc length of a contour segment over which curvature variation remains within a constrained range. Locally, all contours in the image are similar with respect to curvature consistency. However, when the entire contour is considered, the most salient contours are found to have the most consistent curvatures. This finding reinforces Ullman’s point that salience is a global property of the object. We interpret these results in view of Rosenholtz’s [2] recent model of salience as a statistical measure of outliers from a population. In addition, we speculate on the visual cortical mechanisms in striate and extrastriate cortex required to carry out salience measurements on this class of images

Computational Modeling of Medium Spiny Projection Neurons in Nucleus Accumbens: Toward the Cellular Mechanisms of Afferent Stream Integration

The nucleus accumbens (Nacc) regulates the major feedback pathways linking prefrontal cortex, hippocampus, and amygdala. We describe simulations of a biophysical level model of a single medium spiny projection (MSP) neuron, the principle cell of the Nacc. The model suggests that the unusual bistable membrane potential of MSP cells arises from the interplay between two potassium currents, KIR and KA. We find that the transition from the membrane potential down state (~-85mV) to the upstate (~-60mV)requires a significant barrage of synchronized inputs, and that ongoing afferent stimulation is required to maintain the cell in the up state. The Nacc receives the densest dopaminergic innervation in the brain, and the model demonstrates, in agreement with recent experimental evidence, that dopamine acts to increase the energy barrier to membrane potential state transitions. Through its action on KIR and L-type Ca2+ channels, dopamine selectively lowers cell gain in the down state and increases it in the up state, a mechanism for context-dependent gain control. These findings suggest a mechanism of afferent pattern integration in the accumbens arising from transient synchronization among ensembles of MSP neurons. We attempt to relate these findings to possible origins of abnormalities of sensory gating in schizophrenia

The Role of NMDA Currents in State Transitions of the Nucleus Accumbens Medium Spiny Neuron

The nucleus accumbens (NAcb) integrates information from a wide range of glutamatergic afferent inputs, including the prefrontal cortex, hippocampus and amygdala. One of the glutamatergic receptors, the NMDA channel, has been implicated in the non-linearity of the current–voltage relationship in these cells under certain input conditions. In order to examine the relationship of the different glutamatergic receptors to the membrane response, we modeled the AMPA, GABAA and NMDA receptors in the medium spiny (MSP) cells and their afferent input. The model demonstrates that the NMDA current is capable of sustaining certain membrane states and contributes to the non-linearity of the membrane response to input

Personenmarken erfolgreich managen : ein markenpersönlichkeitsbasierter Steuerungsansatz

Personen, wie beispielsweise Sportler, Politiker, Künstler oder Manager, die ihre Leistungen und zunehmend auch sich selb st vermarkten, können als Marken verstanden werden. Ähnlich wie Gütermarken stehen auch Personenmarken immer häufiger vor der Herausforderung, durch eine erfolgreiche Differenzierung im Verdrängungswettbewerb zu bestehen. Trotz ihres enormen wirtschaftlichen Potenzials existiert für Personenmarken bislang kein systematischer Ansatz zur Differenzierung gegenüber der Konkurrenz und somit auch keine Grundlage für ihre effektive Vermarktung. Im vorliegenden Beitrag wird daher zunächst dargestellt, dass das Konzept der Marke auf Personen übertragen und der im Gütermarketing erfolgreich eingesetzte Differenzierungsansatz der Markenpersönlichkeit auch im Kontext von Personenmarken angewendet werden kann. In einem weiteren Schritt werden die im Rahmen einer empirischen Studie ermittelten Einflussfaktoren der Markenpersönlichkeit von Personenmarken vorgestellt und ihre Einsatzmöglichkeiten für ein effektives strategisches Management von Personenmarken beschrieben