Anisotropic constitutive modeling for nickel base single crystal superalloy Rene N4 at 982 C

A back stress/drag stress constitutive model based on a crystallographic approach to model single crystal anisotropy is presented. Experimental results demonstrated the need for the back stress variable in the inelastic flow equations. Experimental findings suggested that back stress is orientation dependent and controls both strain hardening and recovery characteristics. Due to the observed stable fatigue loops at 1800 F, drag stress is considered constant for this temperature. The constitutive model operated with constraints determined only from tensile data was extensively tested from simple tensile and fatigue to complicated strain hold tests. The model predicted very well under those conditions

Population Dynamics on Complex Food Webs

In this work we analyse the topological and dynamical properties of a simple model of complex food webs, namely the niche model. In order to underline competition among species, we introduce "prey" and "predators" weighted overlap graphs derived from the niche model and compare synthetic food webs with real data. Doing so, we find new tests for the goodness of synthetic food web models and indicate a possible direction of improvement for existing ones. We then exploit the weighted overlap graphs to define a competition kernel for Lotka-Volterra population dynamics and find that for such a model the stability of food webs decreases with its ecological complexity.Comment: 11 Pages, 5 Figures, styles enclosed in the submissio

Power-law distributions in empirical data

Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of power laws is complicated by the large fluctuations that occur in the tail of the distribution -- the part of the distribution representing large but rare events -- and by the difficulty of identifying the range over which power-law behavior holds. Commonly used methods for analyzing power-law data, such as least-squares fitting, can produce substantially inaccurate estimates of parameters for power-law distributions, and even in cases where such methods return accurate answers they are still unsatisfactory because they give no indication of whether the data obey a power law at all. Here we present a principled statistical framework for discerning and quantifying power-law behavior in empirical data. Our approach combines maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov statistic and likelihood ratios. We evaluate the effectiveness of the approach with tests on synthetic data and give critical comparisons to previous approaches. We also apply the proposed methods to twenty-four real-world data sets from a range of different disciplines, each of which has been conjectured to follow a power-law distribution. In some cases we find these conjectures to be consistent with the data while in others the power law is ruled out.Comment: 43 pages, 11 figures, 7 tables, 4 appendices; code available at http://www.santafe.edu/~aaronc/powerlaws

Condition numbers and scale free graphs

In this work we study the condition number of the least square matrix corresponding to scale free networks. We compute a theoretical lower bound of the condition number which proves that they are ill conditioned. Also, we analyze several matrices from networks generated with the linear preferential attachment model showing that it is very difficult to compute the power law exponent by the least square method due to the severe lost of accuracy expected from the corresponding condition numbers.Comment: Submitted to EP

The neurobiology of latent learning in the rat using salt appetite and its dissociation from conditioning /

The brain areas required for latent learning in the rat are not currently understood. Previous tasks used to assess latent learning, defined as the acquisition of neutral information that does not immediately influence behavior, have shared characteristics that prevented their use to determine the neurobiology of latent learning. This thesis describes a new task called the Latent Cue Preference (LCP) task, derived from the Conditioned Cue Preference (CCP) task that has been successfully used to determine the brain areas required for conditioning in the rat and other animals. In the LCP task, water deprived rats alternately drink a salt solution in one distinctive compartment of a CCP box apparatus and water in the other compartment over 8 days (training trials). They are then given a choice between the two compartments with no solutions present (preference test). The results of the behavioral experiments showed that this training results in two parallel forms of learning: (1) latent learning of an association between salt and salt-paired compartment cues, and (2) conditioning to water-paired compartment cues. Latent learning itself involved two components: (1) the latent association between salt and salt-paired cues, and (2) motivational information about salt deprivation used to retrieve the latent association, and used to compete with the conditioning to water-paired cues. In addition, the findings showed that latent learning and conditioning involve different neural circuits. Latent learning required an intact cortical-to-hippocampus circuit via the entorhinal cortex, while conditioning required an intact subcortical-to-hippocampus circuit via the fimbria-fornix. The acquisition and storage of the latent association depended on an intact entorhinal cortex/dorsal hippocampus circuit, while the use of motivational information to retrieve the association recruited the ventral hippocampus. Conditioning, on the other hand, required an intact fimbria-fornix, lateral amygdala, and hippocampus. These findings provide new knowledge to the field of learning and memory research, and allowed an update of the current Multiple Memory Systems model

Identifying "Useful" Fitness Models: Balancing the Benefits of Added Complexity with Realistic Data Requirements in Models of Individual Plant Fitness

Direct species interactions are commonly included in individual fitness models used for coexistence and local diversity modeling. Though widely considered important for such models, direct interactions alone are often insufficient for accurately predicting fitness, coexistence, or diversity outcomes. Incorporating higher-order interactions (HOIs) can lead to more accurate individual fitness models but also adds many model terms, which can quickly result in model overfitting. We explore approaches for balancing the trade-off between tractability and model accuracy that occurs when HOIs are added to individual fitness models. To do this, we compare models parameterized with data from annual plant communities in Australia and Spain, varying in the extent of information included about the focal and neighbor species. The best-performing models for both data sets were those that grouped neighbors based on origin status and life form, a grouping approach that reduced the number of model parameters substantially while retaining important ecological information about direct interactions and HOIs. Results suggest that the specific identity of focal or neighbor species is not necessary for building well-performing fitness models that include HOIs. In fact, grouping neighbors by even basic functional information seems sufficient to maximize model accuracy, an important outcome for the practical use of HOI-inclusive fitness models

Population genetics of seaside Sparrow (Ammodramus maritimus) subspecies along the gulf of Mexico.

Seaside Sparrows (Ammodramus maritimus) along the Gulf of Mexico are currently recognized as four subspecies, including taxa in Florida (A. m. juncicola and A. m. peninsulae) and southern Texas (Ammodramus m. sennetti), plus a widespread taxon between them (A. m. fisheri). We examined population genetic structure of this Gulf Coast clade using microsatellite and mtDNA data. Results of Bayesian analyses (Structure, GeneLand) of microsatellite data from nine locations do not entirely align with current subspecific taxonomy. Ammodramus m. sennetti from southern Texas is significantly differentiated from all other populations, but we found evidence of an admixture zone with A. m. fisheri near Corpus Christi. The two subspecies along the northern Gulf Coast of Florida are significantly differentiated from both A. m. sennetti and A. m. fisheri, but are not distinct from each other. We found a weak signal of isolation by distance within A. m. fisheri, indicating this population is not entirely panmictic throughout its range. Although continued conservation concern is warranted for all populations along the Gulf Coast, A. m. fisheri appears to be more secure than the far smaller populations in south Texas and the northern Florida Gulf Coast. In particular, the most genetically distinct populations, those in Texas south of Corpus Christi, occupy unique habitats within a very small geographic range

Ocean heat uptake and its consequences for the magnitude of sea level rise and climate change

Under increasing greenhouse gas concentrations, ocean heat uptake moderates the rate of climate change, and thermal expansion makes a substantial contribution to sea level rise. In this paper we quantify the differences in projections among atmosphere-ocean general circulation models of the Coupled Model Intercomparison Project in terms of transient climate response, ocean heat uptake efficiency and expansion efficiency of heat. The CMIP3 and CMIP5 ensembles have statistically indistinguishable distributions in these parameters. The ocean heat uptake efficiency varies by a factor of two across the models, explaining about 50% of the spread in ocean heat uptake in CMIP5 models with CO2 increasing at 1%/year. It correlates with the ocean global-mean vertical profiles both of temperature and of temperature change, and comparison with observations suggests the models may overestimate ocean heat uptake and underestimate surface warming, because their stratification is too weak. The models agree on the location of maxima of shallow ocean heat uptake (above 700 m) in the Southern Ocean and the North Atlantic, and on deep ocean heat uptake (below 2000 m) in areas of the Southern Ocean, in some places amounting to 40% of the top-to-bottom integral in the CMIP3 SRES A1B scenario. The Southern Ocean dominates global ocean heat uptake; consequently the eddy-induced thickness diffusivity parameter, which is particularly influential in the Southern Ocean, correlates with the ocean heat uptake efficiency. The thermal expansion produced by ocean heat uptake is 0.12 m YJ−1, with an uncertainty of about 10% (1 YJ = 1024 J)

Understanding Air Transportation Market Dynamics Using a Search Algorithm for Calibrating Travel Demand and Price

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS