Quantitative composition and distribution of the macrobenthic invertebrate fauna of the Continental Shelf ecosystems of the Northeastern United States

From the mid-1950's to the mid-1960's a series of quantitative surveys of the macrobenthic invertebrate fauna were conducted in the offshore New England region (Maine to Long Island, New York). The surveys were designed to 1) obtain measures of macrobenthic standing crop expressed in terms of density and biomass; 2) determine the taxonomic composition of the fauna (ca. 567 species); 3) map the general features of macrobenthic distribution; and 4) evaluate the fauna's relationships to water depth, bottom type, temperature range, and sediment organic carbon content. A total of 1,076 samples, ranging from 3 to 3,974 m in depth, were obtained and analyzed. The aggregate macrobenthic fauna consists of 44 major taxonomic groups (phyla, classes, orders). A striking fact is that only five of those groups (belonging to four phyla) account for over 80% of both total biomass and number of individuals of the macrobenthos. The five dominant groups are Bivalvia, Annelida, Amphipoda, Echninoidea, and Holothuroidea. Other salient features pertaining to the macrobenthos of the region are the following: substantial differences in quantity exist among different geographic subareas within the region, but with a general trend that both density and biomass increase from northeast to southwest; both density and biomass decrease with increasing depth; the composition of the bottom sediments significantly influences both the kind and quantity of macrobenthic invertebrates, the largest quantities of both measures of abundance occurring in the coarser grained sediments and diminishing with decreasing particle size; areas with marked seasonal changes in water temperature support an abundant and diverse fauna, whereas a uniform temperature regime is associated with a sparse, less diverse fauna; and no detectable trends are evident in the quantitative composition of the macrobenthos in relation to sediment organic carbon content. (PDF file contains 246 pages.

Collision geometry fluctuations and triangular flow in heavy-ion collisions

We introduce the concepts of participant triangularity and triangular flow in heavy-ion collisions, analogous to the definitions of participant eccentricity and elliptic flow. The participant triangularity characterizes the triangular anisotropy of the initial nuclear overlap geometry and arises from event-by-event fluctuations in the participant-nucleon collision points. In studies using a multi-phase transport model (AMPT), a triangular flow signal is observed that is proportional to the participant triangularity and corresponds to a large third Fourier coefficient in two-particle azimuthal correlation functions. Using two-particle azimuthal correlations at large pseudorapidity separations measured by the PHOBOS and STAR experiments, we show that this Fourier component is also present in data. Ratios of the second and third Fourier coefficients in data exhibit similar trends as a function of centrality and transverse momentum as in AMPT calculations. These findings suggest a significant contribution of triangular flow to the ridge and broad away-side features observed in data. Triangular flow provides a new handle on the initial collision geometry and collective expansion dynamics in heavy-ion collisions.Comment: 8 pages, 8 figures, correction after publication, Fig8b has been corrected: The pt selection in AMPT calculation has been changed to match the selection in STAR dat

Towards Efficient Maximum Likelihood Estimation of LPV-SS Models

How to efficiently identify multiple-input multiple-output (MIMO) linear parameter-varying (LPV) discrete-time state-space (SS) models with affine dependence on the scheduling variable still remains an open question, as identification methods proposed in the literature suffer heavily from the curse of dimensionality and/or depend on over-restrictive approximations of the measured signal behaviors. However, obtaining an SS model of the targeted system is crucial for many LPV control synthesis methods, as these synthesis tools are almost exclusively formulated for the aforementioned representation of the system dynamics. Therefore, in this paper, we tackle the problem by combining state-of-the-art LPV input-output (IO) identification methods with an LPV-IO to LPV-SS realization scheme and a maximum likelihood refinement step. The resulting modular LPV-SS identification approach achieves statical efficiency with a relatively low computational load. The method contains the following three steps: 1) estimation of the Markov coefficient sequence of the underlying system using correlation analysis or Bayesian impulse response estimation, then 2) LPV-SS realization of the estimated coefficients by using a basis reduced Ho-Kalman method, and 3) refinement of the LPV-SS model estimate from a maximum-likelihood point of view by a gradient-based or an expectation-maximization optimization methodology. The effectiveness of the full identification scheme is demonstrated by a Monte Carlo study where our proposed method is compared to existing schemes for identifying a MIMO LPV system

On the Physics of Size Selectivity

We demonstrate that two mechanisms used by biological ion channels to select particles by size are driven by entropy. With uncharged particles in an infinite cylinder, we show that a channel that attracts particles is small-particle selective and that a channel that repels water from the wall is large-particle selective. Comparing against extensive density-functional theory calculations of our model, we find that the main physics can be understood with surprisingly simple bulk models that neglect the confining geometry of the channel completely.Comment: 4 pages, 3 figures, Phys. Rev. Lett. (accepted

Density scaling in viscous liquids: From relaxation times to four-point susceptibilities

We present numerical calculations of a four-point dynamic susceptibility, chi_4(t), for the Kob-Andersen Lennard-Jones mixture as a function of temperature T and density rho. Over a relevant range of T and rho, the full t-dependence of chi_4(t) and thus the maximum in chi_4(t), which is proportional to the dynamic correlation volume, are invariant for state points for which the scaling variable rho^gamma/T is constant. The value of the material constant gamma is the same as that which superposes the relaxation time, tau, of the system versus rho^gamma/T. Thus, the dynamic correlation volume is directly related to tau for any thermodynamic condition in the regime where density scaling holds. Finally, we examine the conditions under which the density scaling properties are related to the existence of strong correlations between pressure and energy fluctuations.Comment: 5 pages, 4 figures, updated reference