A spatially and temporally explicit, individual-based, life-history and productivity modeling approach for aquatic species

EPA Science Inventory

Realized life history expression and productivity in aquatic species, and salmonid fishes in particular, is the result of multiple interacting factors including genetics, habitat, growth potential and condition, and the thermal regime individuals experience, both at critical stag...

HexSim: a modeling environment for ecology and conservation.

EPA Science Inventory

HexSim is a powerful and flexible new spatially-explicit, individual based modeling environment intended for use in ecology, conservation, genetics, epidemiology, toxicology, and other disciplines. We describe HexSim, illustrate past applications that contributed to our >10 year ...

Consumer-operated service program members' explanatory models of mental illness and recovery.

PubMed

Hoy, Janet M

2014-10-01

Incorporating individuals' understandings and explanations of mental illness into service delivery offers benefits relating to increased service relevance and meaning. Existing research delineates explanatory models of mental illness held by individuals in home, outpatient, and hospital-based contexts; research on models held by those in peer-support contexts is notably absent. In this article, I describe themes identified within and across explanatory models of mental illness and recovery held by mental health consumers (N = 24) at one peer center, referred to as a consumer-operated service center (COSP). Participants held explanatory models inclusive of both developmental stressors and biomedical causes, consistent with a stress-diathesis model (although no participant explicitly referenced such). Explicit incorporation of stress-diathesis constructs into programming at this COSP offers the potential of increasing service meaning and relevance. Identifying and incorporating shared meanings across individuals' understandings of mental illness likewise can increase relevance and meaning for particular subgroups of service users. © The Author(s) 2014.

Simple models for studying complex spatiotemporal patterns of animal behavior

NASA Astrophysics Data System (ADS)

Tyutyunov, Yuri V.; Titova, Lyudmila I.

2017-06-01

Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

The base rate principle and the fairness principle in social judgment

PubMed Central

Cao, Jack; Banaji, Mahzarin R.

2016-01-01

Meet Jonathan and Elizabeth. One person is a doctor and the other is a nurse. Who is the doctor? When nothing else is known, the base rate principle favors Jonathan to be the doctor and the fairness principle favors both individuals equally. However, when individuating facts reveal who is actually the doctor, base rates and fairness become irrelevant, as the facts make the correct answer clear. In three experiments, explicit and implicit beliefs were measured before and after individuating facts were learned. These facts were either stereotypic (e.g., Jonathan is the doctor, Elizabeth is the nurse) or counterstereotypic (e.g., Elizabeth is the doctor, Jonathan is the nurse). Results showed that before individuating facts were learned, explicit beliefs followed the fairness principle, whereas implicit beliefs followed the base rate principle. After individuating facts were learned, explicit beliefs correctly aligned with stereotypic and counterstereotypic facts. Implicit beliefs, however, were immune to counterstereotypic facts and continued to follow the base rate principle. Having established the robustness and generality of these results, a fourth experiment verified that gender stereotypes played a causal role: when both individuals were male, explicit and implicit beliefs alike correctly converged with individuating facts. Taken together, these experiments demonstrate that explicit beliefs uphold fairness and incorporate obvious and relevant facts, but implicit beliefs uphold base rates and appear relatively impervious to counterstereotypic facts. PMID:27325760

The base rate principle and the fairness principle in social judgment.

PubMed

Cao, Jack; Banaji, Mahzarin R

2016-07-05

Meet Jonathan and Elizabeth. One person is a doctor and the other is a nurse. Who is the doctor? When nothing else is known, the base rate principle favors Jonathan to be the doctor and the fairness principle favors both individuals equally. However, when individuating facts reveal who is actually the doctor, base rates and fairness become irrelevant, as the facts make the correct answer clear. In three experiments, explicit and implicit beliefs were measured before and after individuating facts were learned. These facts were either stereotypic (e.g., Jonathan is the doctor, Elizabeth is the nurse) or counterstereotypic (e.g., Elizabeth is the doctor, Jonathan is the nurse). Results showed that before individuating facts were learned, explicit beliefs followed the fairness principle, whereas implicit beliefs followed the base rate principle. After individuating facts were learned, explicit beliefs correctly aligned with stereotypic and counterstereotypic facts. Implicit beliefs, however, were immune to counterstereotypic facts and continued to follow the base rate principle. Having established the robustness and generality of these results, a fourth experiment verified that gender stereotypes played a causal role: when both individuals were male, explicit and implicit beliefs alike correctly converged with individuating facts. Taken together, these experiments demonstrate that explicit beliefs uphold fairness and incorporate obvious and relevant facts, but implicit beliefs uphold base rates and appear relatively impervious to counterstereotypic facts.

Measuring crown dynamics of longleaf pine in the sandhills of Eglin Air Force Base

Treesearch

Matt Anderson; Greg L. Somers; W. Rick Smith; Mickey Freeland; Donna Ruth

1998-01-01

The USDA Forest Service SRS, in cooperation with Auburn University, is developing an individual tree, spatially explicit, and btoiogicaily based growth model for natural iongieaf pine sands at Eglin Air Force Base in Florida. The goal of the growth model is to provide a tool for the land managers to compare silvicultural practices effects on the light and water...

Individual-Based Spatially-Explicit Model of an Herbivore and Its Resource: The Effect of Habitat Reduction and Fragmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T; Kercher, J

2002-06-17

We present an individual-based, spatially-explicit model of the dynamics of a small mammal and its resource. The life histories of each individual animal are modeled separately. The individuals can have the status of residents or wanderers and belong to behaviorally differing groups of juveniles or adults and males or females. Their territory defending and monogamous behavior is taken into consideration. The resource, green vegetation, grows depending on seasonal climatic characteristics and is diminished due to the herbivore's grazing. Other specifics such as a varying personal energetic level due to feeding and starvation of the individuals, mating preferences, avoidance of competitors,more » dispersal of juveniles, as a result of site overgrazing, etc. are included in the model. We determined model parameters from real data for the species Microtus ochrogaster (prairie vole). The simulations are done for a case of an enclosed habitat without predators or other species competitors. The goal of the study is to find the relation between size of habitat and population persistence. The experiments with the model show the populations go extinct due to severe overgrazing, but that the length of population persistence depends on the area of the habitat as well as on the presence of fragmentation. Additionally, the total population size of the vole population obtained during the simulations exhibits yearly fluctuations as well as multi-yearly peaks of fluctuations. This dynamics is similar to the one observed in prairie vole field studies.« less

Valence and arousal-based affective evaluations of foods.

PubMed

Woodward, Halley E; Treat, Teresa A; Cameron, C Daryl; Yegorova, Vitaliya

2017-01-01

We investigated the nutrient-specific and individual-specific validity of dual-process models of valenced and arousal-based affective evaluations of foods across the disordered eating spectrum. 283 undergraduate women provided implicit and explicit valence and arousal-based evaluations of 120 food photos with known nutritional information on structurally similar indirect and direct affect misattribution procedures (AMP; Payne et al., 2005, 2008), and completed questionnaires assessing body mass index (BMI), hunger, restriction, and binge eating. Nomothetically, added fat and added sugar enhance evaluations of foods. Idiographically, hunger and binge eating enhance activation, whereas BMI and restriction enhance pleasantness. Added fat is salient for women who are heavier, hungrier, or who restrict; added sugar is influential for less hungry women. Restriction relates only to valence, whereas binge eating relates only to arousal. Findings are similar across implicit and explicit affective evaluations, albeit stronger for explicit, providing modest support for dual-process models of affective evaluation of foods. Copyright © 2016 Elsevier Ltd. All rights reserved.

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

Individual-based modeling of ecological and evolutionary processes

USGS Publications Warehouse

DeAngelis, Donald L.; Mooij, Wolf M.

2005-01-01

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

The development of a spatially-explicit, individual-based, disease model for frogs and the chytrid fungus

EPA Science Inventory

Background / Question / Methods The fungal pathogen, Batrachochytrium dendrobatidis (BD), has been associated with amphibian population declines and even extinctions worldwide. Transmission of the fungus between amphibian hosts occurs via motile zoospores, which are produced on...

How big and how close? Habitat patch size and spacing to conserve a threatened species

Treesearch

Bruce G. Marcot; Martin G. Raphael; Nathan H. Schumaker; Beth Galleher

2013-01-01

We present results of a spatially explicit, individual-based stochastic dispersal model (HexSim) to evaluate effects of size and spacing of patches of habitat of Northern Spotted Owls (NSO; Strix occidentalis caurina) in Pacific Northwest, USA, to help advise recovery planning efforts. We modeled 31 artificial landscape scenarios representing...

Modeling the population-level effects of hypoxia on a coastal fish: implications of a spatially-explicit individual-based model

NASA Astrophysics Data System (ADS)

Rose, K.; Creekmore, S.; Thomas, P.; Craig, K.; Neilan, R.; Rahman, S.; Wang, L.; Justic, D.

2016-02-01

The northwestern Gulf of Mexico (USA) currently experiences a large hypoxic area ("dead zone") during the summer. The population-level effects of hypoxia on coastal fish are largely unknown. We developed a spatially-explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of individual Atlantic croaker could lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 x 800 spatial grid of 1 km2 cells for 140 years. Chlorophyll-a concentration and water temperature were specified daily for each grid cell. Dissolved oxygen (DO) was obtained from a 3-D water quality model for four years that differed in their severity of hypoxia. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and movement behavior was based on temperature preferences and avoidance of low DO. Hypoxia effects were imposed using exposure-effects sub-models that converted time-varying exposure to DO to reductions in growth and fecundity, and increases in mortality. Using sequences of mild, intermediate, and severe hypoxia years, the model predicted a 20% decrease in population abundance. Additional simulations were performed under the assumption that river-based nutrients loadings that lead to more hypoxia also lead to higher primary production and more food for croaker. Twenty-five percent and 50% nutrient reduction scenarios were simulated by adjusting the cholorphyll-a concentrations used as food proxy for the croaker. We then incrementally increased the DO concentrations to determine how much hypoxia would need to be reduced to offset the lower food production resulting from reduced nutrients. We discuss the generality of our results, the hidden effects of hypoxia on fish, and our overall strategy of combining laboratory and field studies with modeling to produce robust predictions of population responses to stressors under dynamic and multi-stressor conditions.

Moderating Effects of Mathematics Anxiety on the Effectiveness of Explicit Timing

ERIC Educational Resources Information Center

Grays, Sharnita D.; Rhymer, Katrina N.; Swartzmiller, Melissa D.

2017-01-01

Explicit timing is an empirically validated intervention to increase problem completion rates by exposing individuals to a stopwatch and explicitly telling them of the time limit for the assignment. Though explicit timing has proven to be effective for groups of students, some students may not respond well to explicit timing based on factors such…

Advanced hierarchical distance sampling

USGS Publications Warehouse

Royle, Andy

2016-01-01

In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

Towards collaborative filtering recommender systems for tailored health communications.

PubMed

Marlin, Benjamin M; Adams, Roy J; Sadasivam, Rajani; Houston, Thomas K

2013-01-01

The goal of computer tailored health communications (CTHC) is to promote healthy behaviors by sending messages tailored to individual patients. Current CTHC systems collect baseline patient "profiles" and then use expert-written, rule-based systems to target messages to subsets of patients. Our main interest in this work is the study of collaborative filtering-based CTHC systems that can learn to tailor future message selections to individual patients based explicit feedback about past message selections. This paper reports the results of a study designed to collect explicit feedback (ratings) regarding four aspects of messages from 100 subjects in the smoking cessation support domain. Our results show that most users have positive opinions of most messages and that the ratings for all four aspects of the messages are highly correlated with each other. Finally, we conduct a range of rating prediction experiments comparing several different model variations. Our results show that predicting future ratings based on each user's past ratings contributes the most to predictive accuracy.

Towards Collaborative Filtering Recommender Systems for Tailored Health Communications

PubMed Central

Marlin, Benjamin M.; Adams, Roy J.; Sadasivam, Rajani; Houston, Thomas K.

2013-01-01

The goal of computer tailored health communications (CTHC) is to promote healthy behaviors by sending messages tailored to individual patients. Current CTHC systems collect baseline patient “profiles” and then use expert-written, rule-based systems to target messages to subsets of patients. Our main interest in this work is the study of collaborative filtering-based CTHC systems that can learn to tailor future message selections to individual patients based explicit feedback about past message selections. This paper reports the results of a study designed to collect explicit feedback (ratings) regarding four aspects of messages from 100 subjects in the smoking cessation support domain. Our results show that most users have positive opinions of most messages and that the ratings for all four aspects of the messages are highly correlated with each other. Finally, we conduct a range of rating prediction experiments comparing several different model variations. Our results show that predicting future ratings based on each user’s past ratings contributes the most to predictive accuracy. PMID:24551430

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

NASA Astrophysics Data System (ADS)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

How big and how close? Habitat patch size and spacing to conserve a threatened species

EPA Science Inventory

We present results of a spatially-explicit, individual-based stochastic dispersal model (HexSim) to evaluate effects of size and spacing of patches of habitat of Northern Spotted Owls (NSO; Strix occidentalis caurina) in Pacific Northwest, USA, to help advise USDI Fish and Wildli...

Habitat restoration from an ecosystem goods and services perspective: Application of a spatially explicit individual-based model

EPA Science Inventory

Estuarine ecosystems provide many services to humans, but these ecosystems are also under pressure from human development, which has led to large investments in habitat protection and restoration. Restoration in estuaries is typically focused on emergent and submerged vegetation ...

HexSim: A flexible simulation model for forecasting wildlife responses to multiple interacting stressors

EPA Science Inventory

With SERDP funding, we have improved upon a popular life history simulator (PATCH), and in doing so produced a powerful new forecasting tool (HexSim). PATCH, our starting point, was spatially explicit and individual-based, and was useful for evaluating a range of terrestrial lif...

Simulating dispersal of reintroduced species within heterogeneous landscapes

Treesearch

Robert H. Gardner; Eric J. Gustafson

2004-01-01

This paper describes the development and application of a spatially explicit, individual based model of animal dispersal (J-walk) to determine the relative effects of landscape heterogeneity, prey availability, predation risk, and the energy requirements and behavior of dispersing organisms on dispersal success. Significant unknowns exist for the simulation of complex...

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies

USGS Publications Warehouse

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew

2010-01-01

We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

PubMed

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

2010-11-01

We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model designed for this study can be easily customized to study the disease spread dynamics of any other communicable disease by simply adjusting the modeled disease timeline and/or the infection model and modifying the transmission process. This type of simulations can help to improve comprehension of disease spread dynamics and to take better steps towards the prevention and control of an epidemic outbreak. PMID:19656403

An economic theory of cigarette addiction.

PubMed

Suranovic, S M; Goldfarb, R S; Leonard, T C

1999-01-01

In this paper we present a model in which individuals act in their own best interest, to explain many behaviors associated with cigarette addiction. There are two key features of the model. First, there is an explicit representation of the withdrawal effects experienced when smokers attempt to quit smoking. Second, there is explicit recognition that the negative effects of smoking generally appear late in an individual's life. Among the things we use the model to explain are: (1) how individuals can become trapped in their decision to smoke; (2) the conditions under which cold-turkey quitting and gradual quitting may occur; and (3) a reason for the existence of quit-smoking treatments.

Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

PubMed

Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

2009-08-31

Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future researchers.

Scale dependent inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...

HexSim: A flexible simulation model for forecasting wildlife responses to multiple interacting stressors - ESRP Meeting

EPA Science Inventory

With SERDP funding, we have improved upon a popular life history simulator (PATCH), and indoing so produced a powerful new forecasting tool (HexSim). PATCH, our starting point, was spatially explicit and individual-based, and was useful for evaluating a range of terrestrial life...

Settler Traditions of Place: Making Explicit the Epistemological Legacy of White Supremacy and Settler Colonialism for Place-Based Education

ERIC Educational Resources Information Center

Seawright, Gardner

2014-01-01

With the rise of place-based models of education, credence needs to be given to epistemological traditions that curate individual understandings of and relations to the social world (i.e., places). The epistemological traditions that have been shared across generations of North American settler colonialists are at the center of this article. The…

Bayesian inference in camera trapping studies for a class of spatial capture-recapture models

USGS Publications Warehouse

Royle, J. Andrew; Karanth, K. Ullas; Gopalaswamy, Arjun M.; Kumar, N. Samba

2009-01-01

We develop a class of models for inference about abundance or density using spatial capture-recapture data from studies based on camera trapping and related methods. The model is a hierarchical model composed of two components: a point process model describing the distribution of individuals in space (or their home range centers) and a model describing the observation of individuals in traps. We suppose that trap- and individual-specific capture probabilities are a function of distance between individual home range centers and trap locations. We show that the models can be regarded as generalized linear mixed models, where the individual home range centers are random effects. We adopt a Bayesian framework for inference under these models using a formulation based on data augmentation. We apply the models to camera trapping data on tigers from the Nagarahole Reserve, India, collected over 48 nights in 2006. For this study, 120 camera locations were used, but cameras were only operational at 30 locations during any given sample occasion. Movement of traps is common in many camera-trapping studies and represents an important feature of the observation model that we address explicitly in our application.

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

PubMed

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Modelling Hen Harrier Dynamics to Inform Human-Wildlife Conflict Resolution: A Spatially-Realistic, Individual-Based Approach

PubMed Central

Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860

Connecting micro dynamics and population distributions in system dynamics models

PubMed Central

Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

2014-01-01

Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842

Memory biases in remitted depression: the role of negative cognitions at explicit and automatic processing levels.

PubMed

Romero, Nuria; Sanchez, Alvaro; Vazquez, Carmelo

2014-03-01

Cognitive models propose that depression is caused by dysfunctional schemas that endure beyond the depressive episode, representing vulnerability factors for recurrence. However, research testing negative cognitions linked to dysfunctional schemas in formerly depressed individuals is still scarce. Furthermore, negative cognitions are presumed to be linked to biases in recalling negative self-referent information in formerly depressed individuals, but no studies have directly tested this association. In the present study, we evaluated differences between formerly and never-depressed individuals in several experimental indices of negative cognitions and their associations with the recall of emotional self-referent material. Formerly (n = 30) and never depressed individuals (n = 40) completed measures of explicit (i.e., scrambled sentence test) and automatic (i.e., lexical decision task) processing to evaluate negative cognitions. Furthermore participants completed a self-referent incidental recall task to evaluate memory biases. Formerly compared to never depressed individuals showed greater negative cognitions at both explicit and automatic levels of processing. Results also showed greater recall of negative self-referent information in formerly compared to never-depressed individuals. Finally, individual differences in negative cognitions at both explicit and automatic levels of processing predicted greater recall of negative self-referent material in formerly depressed individuals. Analyses of the relationship between explicit and automatic processing indices and memory biases were correlational and the majority of participants in both groups were women. Our findings provide evidence of negative cognitions in formerly depressed individuals at both automatic and explicit levels of processing that may confer a cognitive vulnerability to depression. Copyright © 2013 Elsevier Ltd. All rights reserved.

Integration of an Individual-Based Fish Bioenergetics Model into a Spatially Explicit Water Quality Model (CE-QUAL-ICM)

DTIC Science & Technology

2010-04-01

energy a fish can devote to growth being the difference between consumption in the form of food and the sum of life process expenditures , including...can incur an elemental deficit, and subsequently retain higher fractions of that element when it is in abun- dance to regain the target composition...Organic nitrogen and caloric content of detritus. Estuarine, Coastal, and Shelf Science 12: 39-47

A Geographically Explicit Genetic Model of Worldwide Human-Settlement History

PubMed Central

Liu, Hua; Prugnolle, Franck; Manica, Andrea; Balloux, François

2006-01-01

Currently available genetic and archaeological evidence is generally interpreted as supportive of a recent single origin of modern humans in East Africa. However, this is where the near consensus on human settlement history ends, and considerable uncertainty clouds any more detailed aspect of human colonization history. Here, we present a dynamic genetic model of human settlement history coupled with explicit geographical distances from East Africa, the likely origin of modern humans. We search for the best-supported parameter space by fitting our analytical prediction to genetic data that are based on 52 human populations analyzed at 783 autosomal microsatellite markers. This framework allows us to jointly estimate the key parameters of the expansion of modern humans. Our best estimates suggest an initial expansion of modern humans ∼56,000 years ago from a small founding population of ∼1,000 effective individuals. Our model further points to high growth rates in newly colonized habitats. The general fit of the model with the data is excellent. This suggests that coupling analytical genetic models with explicit demography and geography provides a powerful tool for making inferences on human-settlement history. PMID:16826514

The role of density-dependent individual growth in the persistence of freshwater salmonid populations.

PubMed

Vincenzi, Simone; Crivelli, Alain J; Jesensek, Dusan; De Leo, Giulio A

2008-06-01

Theoretical and empirical models of populations dynamics have paid little attention to the implications of density-dependent individual growth on the persistence and regulation of small freshwater salmonid populations. We have therefore designed a study aimed at testing our hypothesis that density-dependent individual growth is a process that enhances population recovery and reduces extinction risk in salmonid populations in a variable environment subject to disturbance events. This hypothesis was tested in two newly introduced marble trout (Salmo marmoratus) populations living in Slovenian streams (Zakojska and Gorska) subject to severe autumn floods. We developed a discrete-time stochastic individual-based model of population dynamics for each population with demographic parameters and compensatory responses tightly calibrated on data from individually tagged marble trout. The occurrence of severe flood events causing population collapses was explicitly accounted for in the model. We used the model in a population viability analysis setting to estimate the quasi-extinction risk and demographic indexes of the two marble trout populations when individual growth was density-dependent. We ran a set of simulations in which the effect of floods on population abundance was explicitly accounted for and another set of simulations in which flood events were not included in the model. These simulation results were compared with those of scenarios in which individual growth was modelled with density-independent Von Bertalanffy growth curves. Our results show how density-dependent individual growth may confer remarkable resilience to marble trout populations in case of major flood events. The resilience to flood events shown by the simulation results can be explained by the increase in size-dependent fecundity as a consequence of the drop in population size after a severe flood, which allows the population to quickly recover to the pre-event conditions. Our results suggest that density-dependent individual growth plays a potentially powerful role in the persistence of freshwater salmonids living in streams subject to recurrent yet unpredictable flood events.

Analyzing Variability in Landscape Nutrient Loading Using Spatially-Explicit Maps in the Great Lakes Basin

NASA Astrophysics Data System (ADS)

Hamlin, Q. F.; Kendall, A. D.; Martin, S. L.; Whitenack, H. D.; Roush, J. A.; Hannah, B. A.; Hyndman, D. W.

2017-12-01

Excessive loading of nitrogen and phosphorous to the landscape has caused biologically and economically damaging eutrophication and harmful algal blooms in the Great Lakes Basin (GLB) and across the world. We mapped source-specific loads of nitrogen and phosphorous to the landscape using broadly available data across the GLB. SENSMap (Spatially Explicit Nutrient Source Map) is a 30m resolution snapshot of nutrient loads ca. 2010. We use these maps to study variable nutrient loading and provide this information to watershed managers through NOAA's GLB Tipping Points Planner. SENSMap individually maps nutrient point sources and six non-point sources: 1) atmospheric deposition, 2) septic tanks, 3) non-agricultural chemical fertilizer, 4) agricultural chemical fertilizer, 5) manure, and 6) nitrogen fixation from legumes. To model source-specific loads at high resolution, SENSMap synthesizes a wide range of remotely sensed, surveyed, and tabular data. Using these spatially explicit nutrient loading maps, we can better calibrate local land use-based water quality models and provide insight to watershed managers on how to focus nutrient reduction strategies. Here we examine differences in dominant nutrient sources across the GLB, and how those sources vary by land use. SENSMap's high resolution, source-specific approach offers a different lens to understand nutrient loading than traditional semi-distributed or land use based models.

The mixed impact of medical school on medical students' implicit and explicit weight bias.

PubMed

Phelan, Sean M; Puhl, Rebecca M; Burke, Sara E; Hardeman, Rachel; Dovidio, John F; Nelson, David B; Przedworski, Julia; Burgess, Diana J; Perry, Sylvia; Yeazel, Mark W; van Ryn, Michelle

2015-10-01

Health care trainees demonstrate implicit (automatic, unconscious) and explicit (conscious) bias against people from stigmatised and marginalised social groups, which can negatively influence communication and decision making. Medical schools are well positioned to intervene and reduce bias in new physicians. This study was designed to assess medical school factors that influence change in implicit and explicit bias against individuals from one stigmatised group: people with obesity. This was a prospective cohort study of medical students enrolled at 49 US medical schools randomly selected from all US medical schools within the strata of public and private schools and region. Participants were 1795 medical students surveyed at the beginning of their first year and end of their fourth year. Web-based surveys included measures of weight bias, and medical school experiences and climate. Bias change was compared with changes in bias in the general public over the same period. Linear mixed models were used to assess the impact of curriculum, contact with people with obesity, and faculty role modelling on weight bias change. Increased implicit and explicit biases were associated with less positive contact with patients with obesity and more exposure to faculty role modelling of discriminatory behaviour or negative comments about patients with obesity. Increased implicit bias was associated with training in how to deal with difficult patients. On average, implicit weight bias decreased and explicit bias increased during medical school, over a period of time in which implicit weight bias in the general public increased and explicit bias remained stable. Medical schools may reduce students' weight biases by increasing positive contact between students and patients with obesity, eliminating unprofessional role modelling by faculty members and residents, and altering curricula focused on treating difficult patients. © 2015 John Wiley & Sons Ltd.

Visual sensory networks and effective information transfer in animal groups.

PubMed

Strandburg-Peshkin, Ariana; Twomey, Colin R; Bode, Nikolai W F; Kao, Albert B; Katz, Yael; Ioannou, Christos C; Rosenthal, Sara B; Torney, Colin J; Wu, Hai Shan; Levin, Simon A; Couzin, Iain D

2013-09-09

Social transmission of information is vital for many group-living animals, allowing coordination of motion and effective response to complex environments. Revealing the interaction networks underlying information flow within these groups is a central challenge. Previous work has modeled interactions between individuals based directly on their relative spatial positions: each individual is considered to interact with all neighbors within a fixed distance (metric range), a fixed number of nearest neighbors (topological range), a 'shell' of near neighbors (Voronoi range), or some combination (Figure 1A). However, conclusive evidence to support these assumptions is lacking. Here, we employ a novel approach that considers individual movement decisions to be based explicitly on the sensory information available to the organism. In other words, we consider that while spatial relations do inform interactions between individuals, they do so indirectly, through individuals' detection of sensory cues. We reconstruct computationally the visual field of each individual throughout experiments designed to investigate information propagation within fish schools (golden shiners, Notemigonus crysoleucas). Explicitly considering visual sensing allows us to more accurately predict the propagation of behavioral change in these groups during leadership events. Furthermore, we find that structural properties of visual interaction networks differ markedly from those of metric and topological counterparts, suggesting that previous assumptions may not appropriately reflect information flow in animal groups. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Built Environment and Health: Introducing Individual Space-Time Behavior

PubMed Central

Saarloos, Dick; Kim, Jae-Eun; Timmermans, Harry

2009-01-01

Many studies have examined the relationship between the built environment and health. Yet, the question of how and why the environment influences health behavior remains largely unexplored. As health promotion interventions work through the individuals in a targeted population, an explicit understanding of individual behavior is required to formulate and evaluate intervention strategies. Bringing in concepts from various fields, this paper proposes the use of an activity-based modeling approach for understanding and predicting, from the bottom up, how individuals interact with their environment and each other in space and time, and how their behaviors aggregate to population-level health outcomes. PMID:19578457

Models of social evolution: can we do better to predict 'who helps whom to achieve what'?

PubMed

Rodrigues, António M M; Kokko, Hanna

2016-02-05

Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking 'who helps whom to achieve what', from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. © 2016 The Author(s).

Models of social evolution: can we do better to predict ‘who helps whom to achieve what’?

PubMed Central

Rodrigues, António M. M.; Kokko, Hanna

2016-01-01

Models of social evolution and the evolution of helping have been classified in numerous ways. Two categorical differences have, however, escaped attention in the field. Models tend not to justify why they use a particular assumption structure about who helps whom: a large number of authors model peer-to-peer cooperation of essentially identical individuals, probably for reasons of mathematical convenience; others are inspired by particular cooperatively breeding species, and tend to assume unidirectional help where subordinates help a dominant breed more efficiently. Choices regarding what the help achieves (i.e. which life-history trait of the helped individual is improved) are similarly made without much comment: fecundity benefits are much more commonly modelled than survival enhancements, despite evidence that these may interact when the helped individual can perform life-history reallocations (load-lightening and related phenomena). We review our current theoretical understanding of effects revealed when explicitly asking ‘who helps whom to achieve what’, from models of mutual aid in partnerships to the very few models that explicitly contrast the strength of selection to help enhance another individual's fecundity or survival. As a result of idiosyncratic modelling choices in contemporary literature, including the varying degree to which demographic consequences are made explicit, there is surprisingly little agreement on what types of help are predicted to evolve most easily. We outline promising future directions to fill this gap. PMID:26729928

Designing a podiatry service to meet the needs of the population: a service simulation.

PubMed

Campbell, Jackie A

2007-02-01

A model of a podiatry service has been developed which takes into consideration the effect of changing access criteria, skill mix and staffing levels (among others) given fixed local staffing budgets and the foot-health characteristics of the local community. A spreadsheet-based deterministic model was chosen to allow maximum transparency of programming. This work models a podiatry service in England, but could be adapted for other settings and, with some modification, for other community-based services. This model enables individual services to see the effect on outcome parameters such as number of patients treated, number discharged and size of waiting lists of various service configurations, given their individual local data profile. The process of designing the model has also had spin-off benefits for the participants in making explicit many of the implicit rules used in managing their services.

Through the Immune Looking Glass: A Model for Brain Memory Strategies

PubMed Central

Sánchez-Ramón, Silvia; Faure, Florence

2016-01-01

The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust’s madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective. PMID:26869886

Molecular modelling of protein-protein/protein-solvent interactions

NASA Astrophysics Data System (ADS)

Luchko, Tyler

The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule destabilization. No conformational change was observed but a nucleotide dependent 'softening' of the interaction was found instead, suggesting that an entropic force in a microtubule configuration could be the mechanism of microtubule collapse. Finally, to overcome much of the computational costs associated with explicit soIvent calculations, a new combination of molecular dynamics with the 3D-reference interaction site model (3D-RISM) of solvation was integrated into the Amber molecular dynamics package. Our implementation of 3D-RISM shows excellent agreement with explicit solvent free energy calculations. Several optimisation techniques, including a new multiple time step method, provide a nearly 100 fold performance increase, giving similar computational performance to explicit solvent.

Calculation of Individual Tree Water Use in a Bornean Tropical Rain Forest Using Individual-Based Dynamic Vegetation Model SEIB-DGVM

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Saito, T.; Matsumoto, K.; Kume, T.; Nakagawa, M.; Sato, H.

2015-12-01

Bornean tropical rain forests are among the moistest biomes of the world with abundant rainfall throughout the year, and considered to be vulnerable to a change in the rainfall regime; e.g., high tree mortality was reported in such forests induced by a severe drought associated with the ENSO event in 1997-1998. In order to assess the effect (risk) of future climate change on eco-hydrology in such tropical rain forests, it is important to understand the water use of trees individually, because the vulnerability or mortality of trees against climate change can depend on the size of trees. Therefore, we refined the Spatially Explicit Individual-Based Dynamic Global Vegetation Model (SEIB-DGVM) so that the transpiration and its control by stomata are calculated for each individual tree. By using this model, we simulated the transpiration of each tree and its DBH-size dependency, and successfully reproduced the measured data of sap flow of trees and eddy covariance flux data obtained in a Bornean lowland tropical rain forest in Lambir Hills National Park, Sarawak, Malaysia.

Design and application of a technologically explicit hybrid energy-economy policy model with micro and macro economic dynamics

NASA Astrophysics Data System (ADS)

Bataille, Christopher G. F.

2005-11-01

Are further energy efficiency gains, or more recently greenhouse gas reductions, expensive or cheap? Analysts provide conflicting advice to policy makers based on divergent modelling perspectives, a 'top-down/bottom-up debate' in which economists use equation based models that equilibrate markets by maximizing consumer welfare, and technologists use technology simulation models that minimize the financial cost of providing energy services. This thesis summarizes a long term research project to find a middle ground between these two positions that is more useful to policy makers. Starting with the individual components of a behaviourally realistic and technologically explicit simulation model (ISTUM---Inter Sectoral Technology Use Model), or "hybrid", the individual sectors of the economy are linked using a framework of micro and macro economic feedbacks. These feedbacks are taken from the economic theory that informs the computable general equilibrium (CGE) family of models. Speaking in the languages of both economists and engineers, the resulting "physical" equilibrium model of Canada (CIMS---Canadian Integrated Modeling System), equilibrates energy and end-product markets, including imports and exports, for seven regions and 15 economic sectors, including primary industry, manufacturing, transportation, commerce, residences, governmental infrastructure and the energy supply sectors. Several different policy experiments demonstrate the value-added of the model and how its results compare to top-down and bottom-up practice. In general, the results show that technical adjustments make up about half the response to simulated energy policy, and macroeconomic demand adjustments the other half. Induced technical adjustments predominate with minor policies, while the importance of macroeconomic demand adjustment increases with the strength of the policy. Results are also shown for an experiment to derive estimates of future elasticity of substitution (ESUB) and autonomous energy efficiency indices (AEEI) from the model, parameters that could be used in long-run computable general equilibrium (CGE) analysis. The thesis concludes with a summary of the strengths and weakness of the new model as a policy tool, a work plan for its further improvement, and a discussion of the general potential for technologically explicit general equilibrium modelling.

Implementation science: a role for parallel dual processing models of reasoning?

PubMed Central

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-01-01

Background A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Discussion Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. Summary It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice. PMID:16725023

Implementation science: a role for parallel dual processing models of reasoning?

PubMed

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-05-25

A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice.

Modeling human mobility responses to the large-scale spreading of infectious diseases.

PubMed

Meloni, Sandro; Perra, Nicola; Arenas, Alex; Gómez, Sergio; Moreno, Yamir; Vespignani, Alessandro

2011-01-01

Current modeling of infectious diseases allows for the study of realistic scenarios that include population heterogeneity, social structures, and mobility processes down to the individual level. The advances in the realism of epidemic description call for the explicit modeling of individual behavioral responses to the presence of disease within modeling frameworks. Here we formulate and analyze a metapopulation model that incorporates several scenarios of self-initiated behavioral changes into the mobility patterns of individuals. We find that prevalence-based travel limitations do not alter the epidemic invasion threshold. Strikingly, we observe in both synthetic and data-driven numerical simulations that when travelers decide to avoid locations with high levels of prevalence, this self-initiated behavioral change may enhance disease spreading. Our results point out that the real-time availability of information on the disease and the ensuing behavioral changes in the population may produce a negative impact on disease containment and mitigation.

Epidemic spreading on random surfer networks with optimal interaction radius

NASA Astrophysics Data System (ADS)

Feng, Yun; Ding, Li; Hu, Ping

2018-03-01

In this paper, the optimal control problem of epidemic spreading on random surfer heterogeneous networks is considered. An epidemic spreading model is established according to the classification of individual's initial interaction radii. Then, a control strategy is proposed based on adjusting individual's interaction radii. The global stability of the disease free and endemic equilibrium of the model is investigated. We prove that an optimal solution exists for the optimal control problem and the explicit form of which is presented. Numerical simulations are conducted to verify the correctness of the theoretical results. It is proved that the optimal control strategy is effective to minimize the density of infected individuals and the cost associated with the adjustment of interaction radii.

Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

NASA Astrophysics Data System (ADS)

Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

2010-10-01

Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node Infestation Probabilities.

PubMed

Rincon, Diego F; Hoy, Casey W; Cañas, Luis A

2015-04-01

Most predator-prey models extrapolate functional responses from small-scale experiments assuming spatially uniform within-plant predator-prey interactions. However, some predators focus their search in certain plant regions, and herbivores tend to select leaves to balance their nutrient uptake and exposure to plant defenses. Individual-based models that account for heterogeneous within-plant predator-prey interactions can be used to scale-up functional responses, but they would require the generation of explicit prey spatial distributions within-plant architecture models. The silverleaf whitefly, Bemisia tabaci biotype B (Gennadius) (Hemiptera: Aleyrodidae), is a significant pest of tomato crops worldwide that exhibits highly aggregated populations at several spatial scales, including within the plant. As part of an analytical framework to understand predator-silverleaf whitefly interactions, the objective of this research was to develop an algorithm to generate explicit spatial counts of silverleaf whitefly nymphs within tomato plants. The algorithm requires the plant size and the number of silverleaf whitefly individuals to distribute as inputs, and includes models that describe infestation probabilities per leaf nodal position and the aggregation pattern of the silverleaf whitefly within tomato plants and leaves. The output is a simulated number of silverleaf whitefly individuals for each leaf and leaflet on one or more plants. Parameter estimation was performed using nymph counts per leaflet censused from 30 artificially infested tomato plants. Validation revealed a substantial agreement between algorithm outputs and independent data that included the distribution of counts of both eggs and nymphs. This algorithm can be used in simulation models that explore the effect of local heterogeneity on whitefly-predator dynamics. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A hybrid model for traffic flow and crowd dynamics with random individual properties.

PubMed

Schleper, Veronika

2015-04-01

Based on an established mathematical model for the behavior of large crowds, a new model is derived that is able to take into account the statistical variation of individual maximum walking speeds. The same model is shown to be valid also in traffic flow situations, where for instance the statistical variation of preferred maximum speeds can be considered. The model involves explicit bounds on the state variables, such that a special Riemann solver is derived that is proved to respect the state constraints. Some care is devoted to a valid construction of random initial data, necessary for the use of the new model. The article also includes a numerical method that is shown to respect the bounds on the state variables and illustrative numerical examples, explaining the properties of the new model in comparison with established models.

Agent-based modeling of malaria vectors: the importance of spatial simulation.

PubMed

Bomblies, Arne

2014-07-03

The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as "agents" in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important.

Modeling Wood Encroachment in Abandoned Grasslands in the Eifel National Park – Model Description and Testing

PubMed Central

Hudjetz, Silvana; Lennartz, Gottfried; Krämer, Klara; Roß-Nickoll, Martina; Gergs, André; Preuss, Thomas G.

2014-01-01

The degradation of natural and semi-natural landscapes has become a matter of global concern. In Germany, semi-natural grasslands belong to the most species-rich habitat types but have suffered heavily from changes in land use. After abandonment, the course of succession at a specific site is often difficult to predict because many processes interact. In order to support decision making when managing semi-natural grasslands in the Eifel National Park, we built the WoodS-Model (Woodland Succession Model). A multimodeling approach was used to integrate vegetation dynamics in both the herbaceous and shrub/tree layer. The cover of grasses and herbs was simulated in a compartment model, whereas bushes and trees were modelled in an individual-based manner. Both models worked and interacted in a spatially explicit, raster-based landscape. We present here the model description, parameterization and testing. We show highly detailed projections of the succession of a semi-natural grassland including the influence of initial vegetation composition, neighborhood interactions and ungulate browsing. We carefully weighted the single processes against each other and their relevance for landscape development under different scenarios, while explicitly considering specific site conditions. Model evaluation revealed that the model is able to emulate successional patterns as observed in the field as well as plausible results for different population densities of red deer. Important neighborhood interactions such as seed dispersal, the protection of seedlings from browsing ungulates by thorny bushes, and the inhibition of wood encroachment by the herbaceous layer, have been successfully reproduced. Therefore, not only a detailed model but also detailed initialization turned out to be important for spatially explicit projections of a given site. The advantage of the WoodS-Model is that it integrates these many mutually interacting processes of succession. PMID:25494057

INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

EPA Pesticide Factsheets

Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

Bee++: An Object-Oriented, Agent-Based Simulator for Honey Bee Colonies

PubMed Central

Betti, Matthew; LeClair, Josh; Wahl, Lindi M.; Zamir, Mair

2017-01-01

We present a model and associated simulation package (www.beeplusplus.ca) to capture the natural dynamics of a honey bee colony in a spatially-explicit landscape, with temporally-variable, weather-dependent parameters. The simulation tracks bees of different ages and castes, food stores within the colony, pollen and nectar sources and the spatial position of individual foragers outside the hive. We track explicitly the intake of pesticides in individual bees and their ability to metabolize these toxins, such that the impact of sub-lethal doses of pesticides can be explored. Moreover, pathogen populations (in particular, Nosema apis, Nosema cerenae and Varroa mites) have been included in the model and may be introduced at any time or location. The ability to study interactions among pesticides, climate, biodiversity and pathogens in this predictive framework should prove useful to a wide range of researchers studying honey bee populations. To this end, the simulation package is written in open source, object-oriented code (C++) and can be easily modified by the user. Here, we demonstrate the use of the model by exploring the effects of sub-lethal pesticide exposure on the flight behaviour of foragers. PMID:28287445

Landscape fragmentation and pollinator movement within agricultural environments: a modelling framework for exploring foraging and movement ecology

PubMed Central

2014-01-01

Pollinator decline has been linked to landscape change, through both habitat fragmentation and the loss of habitat suitable for the pollinators to live within. One method for exploring why landscape change should affect pollinator populations is to combine individual-level behavioural ecological techniques with larger-scale landscape ecology. A modelling framework is described that uses spatially-explicit individual-based models to explore the effects of individual behavioural rules within a landscape. The technique described gives a simple method for exploring the effects of the removal of wild corridors, and the creation of wild set-aside fields: interventions that are common to many national agricultural policies. The effects of these manipulations on central-place nesting pollinators are varied, and depend upon the behavioural rules that the pollinators are using to move through the environment. The value of this modelling framework is discussed, and future directions for exploration are identified. PMID:24795848

Landscape fragmentation and pollinator movement within agricultural environments: a modelling framework for exploring foraging and movement ecology.

PubMed

Rands, Sean A

2014-01-01

Pollinator decline has been linked to landscape change, through both habitat fragmentation and the loss of habitat suitable for the pollinators to live within. One method for exploring why landscape change should affect pollinator populations is to combine individual-level behavioural ecological techniques with larger-scale landscape ecology. A modelling framework is described that uses spatially-explicit individual-based models to explore the effects of individual behavioural rules within a landscape. The technique described gives a simple method for exploring the effects of the removal of wild corridors, and the creation of wild set-aside fields: interventions that are common to many national agricultural policies. The effects of these manipulations on central-place nesting pollinators are varied, and depend upon the behavioural rules that the pollinators are using to move through the environment. The value of this modelling framework is discussed, and future directions for exploration are identified.

Discovering latent commercial networks from online financial news articles

NASA Astrophysics Data System (ADS)

Xia, Yunqing; Su, Weifeng; Lau, Raymond Y. K.; Liu, Yi

2013-08-01

Unlike most online social networks where explicit links among individual users are defined, the relations among commercial entities (e.g. firms) may not be explicitly declared in commercial Web sites. One main contribution of this article is the development of a novel computational model for the discovery of the latent relations among commercial entities from online financial news. More specifically, a CRF model which can exploit both structural and contextual features is applied to commercial entity recognition. In addition, a point-wise mutual information (PMI)-based unsupervised learning method is developed for commercial relation identification. To evaluate the effectiveness of the proposed computational methods, a prototype system called CoNet has been developed. Based on the financial news articles crawled from Google finance, the CoNet system achieves average F-scores of 0.681 and 0.754 in commercial entity recognition and commercial relation identification, respectively. Our experimental results confirm that the proposed shallow natural language processing methods are effective for the discovery of latent commercial networks from online financial news.

A data management system for engineering and scientific computing

NASA Technical Reports Server (NTRS)

Elliot, L.; Kunii, H. S.; Browne, J. C.

1978-01-01

Data elements and relationship definition capabilities for this data management system are explicitly tailored to the needs of engineering and scientific computing. System design was based upon studies of data management problems currently being handled through explicit programming. The system-defined data element types include real scalar numbers, vectors, arrays and special classes of arrays such as sparse arrays and triangular arrays. The data model is hierarchical (tree structured). Multiple views of data are provided at two levels. Subschemas provide multiple structural views of the total data base and multiple mappings for individual record types are supported through the use of a REDEFINES capability. The data definition language and the data manipulation language are designed as extensions to FORTRAN. Examples of the coding of real problems taken from existing practice in the data definition language and the data manipulation language are given.

Interaction Effects between Exposure to Sexually Explicit Online Materials and Individual, Family, and Extrafamilial Factors on Hong Kong High School Students' Beliefs about Gender Role Equality and Body-Centered Sexuality

ERIC Educational Resources Information Center

To, Siu-ming; Kan, Siu-mee Iu; Ngai, Steven Sek-yum

2015-01-01

This study examined the interaction effects between Hong Kong adolescents' exposure to sexually explicit online materials (SEOM) and individual, family, peer, and cultural factors on their beliefs about gender role equality and body-centered sexuality. Based on a survey design with a sample of 503 high school students in Hong Kong, the results…

Opinion Dynamics with Disagreement and Modulated Information

NASA Astrophysics Data System (ADS)

Sîrbu, Alina; Loreto, Vittorio; Servedio, Vito D. P.; Tria, Francesca

2013-04-01

Opinion dynamics concerns social processes through which populations or groups of individuals agree or disagree on specific issues. As such, modelling opinion dynamics represents an important research area that has been progressively acquiring relevance in many different domains. Existing approaches have mostly represented opinions through discrete binary or continuous variables by exploring a whole panoply of cases: e.g. independence, noise, external effects, multiple issues. In most of these cases the crucial ingredient is an attractive dynamics through which similar or similar enough agents get closer. Only rarely the possibility of explicit disagreement has been taken into account (i.e., the possibility for a repulsive interaction among individuals' opinions), and mostly for discrete or 1-dimensional opinions, through the introduction of additional model parameters. Here we introduce a new model of opinion formation, which focuses on the interplay between the possibility of explicit disagreement, modulated in a self-consistent way by the existing opinions' overlaps between the interacting individuals, and the effect of external information on the system. Opinions are modelled as a vector of continuous variables related to multiple possible choices for an issue. Information can be modulated to account for promoting multiple possible choices. Numerical results show that extreme information results in segregation and has a limited effect on the population, while milder messages have better success and a cohesion effect. Additionally, the initial condition plays an important role, with the population forming one or multiple clusters based on the initial average similarity between individuals, with a transition point depending on the number of opinion choices.

A dual-route cascaded model of reading by deaf adults: evidence for grapheme to viseme conversion.

PubMed

Elliott, Eeva A; Braun, Mario; Kuhlmann, Michael; Jacobs, Arthur M

2012-01-01

There is an ongoing debate whether deaf individuals access phonology when reading, and if so, what impact the ability to access phonology might have on reading achievement. However, the debate so far has been theoretically unspecific on two accounts: (a) the phonological units deaf individuals may have of oral language have not been specified and (b) there seem to be no explicit cognitive models specifying how phonology and other factors operate in reading by deaf individuals. We propose that deaf individuals have representations of the sublexical structure of oral-aural language which are based on mouth shapes and that these sublexical units are activated during reading by deaf individuals. We specify the sublexical units of deaf German readers as 11 "visemes" and incorporate the viseme set into a working model of single-word reading by deaf adults based on the dual-route cascaded model of reading aloud by Coltheart, Rastle, Perry, Langdon, and Ziegler (2001. DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204-256. doi: 10.1037//0033-295x.108.1.204). We assessed the indirect route of this model by investigating the "pseudo-homoviseme" effect using a lexical decision task in deaf German reading adults. We found a main effect of pseudo-homovisemy, suggesting that at least some deaf individuals do automatically access sublexical structure during single-word reading.

Implicit and explicit self-esteem in currently depressed individuals with and without suicidal ideation.

PubMed

Franck, Erik; De Raedt, Rudi; Dereu, Mieke; Van den Abbeele, Dirk

2007-03-01

In the present study, we have further explored implicit self-esteem in currently depressed individuals. Since suicidal ideation is associated with lower self-esteem in depressed individuals, we measured both implicit and explicit self-esteem in a population of currently depressed (CD) individuals, with and without suicidal ideation (SI), and in a group of non-depressed controls (ND). The results indicate that only CD individuals with SI show a discrepancy between their implicit and explicit self-esteem: that is, they exhibit high implicit and low explicit self-esteem. CD individuals without SI exhibit both low implicit and low explicit self-esteem; and ND controls exhibit both normal implicit and normal explicit self-esteem. These results provide new insights in the study of implicit self-esteem and the combination of implicit and explicit self-esteem in depression.

Space-based Ornithology-Studying Bird Migration and Environmental Change in North America

NASA Technical Reports Server (NTRS)

Smith, James; Deppe, Jill

2008-01-01

Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. We have developed an individual-based, spatially explicit bird migration model that simulates the migration routes, timing and energy budgets of individual birds under dynamic weather and land surface conditions. Our model incorporates biophysical constraints, individual bird energy status, bird behavior, and flight aerodynamics. We model the speed, direction, and timing of individual birds moving through a user specified Lagrangian grid. The model incorporates environmental properties including wind speed and direction, topography, dynamic hydrologic properties of the landscape, and environmental suitability. The model is driven by important variables estimated from satellite observations of the land surface, by data assimilation products from weather and climate models, and biological field data. We illustrate the use of the model to study the impact of both short- and long-term environmental variatios, e.g. climate, drought, anthropogenic, on migration timing (phenology), spatial pattern, and fitness (survival and reproductive success). We present several theoretical simulations of the spring migration of Pectoral Sandpiper (Calidris melanotos) in North America with emphasis on the Central flyway from the Gulf of Mexico to Alaska.

Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

PubMed Central

2011-01-01

Background Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. Methods We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. Results The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. Conclusions We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficial. PMID:21554680

Power Analysis of Artificial Selection Experiments Using Efficient Whole Genome Simulation of Quantitative Traits

PubMed Central

Kessner, Darren; Novembre, John

2015-01-01

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50–100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates. PMID:25672748

Moderators of the Relationship between Implicit and Explicit Evaluation

PubMed Central

Nosek, Brian A.

2005-01-01

Automatic and controlled modes of evaluation sometimes provide conflicting reports of the quality of social objects. This paper presents evidence for four moderators of the relationship between automatic (implicit) and controlled (explicit) evaluations. Implicit and explicit preferences were measured for a variety of object pairs using a large sample. The average correlation was r = .36, and 52 of the 57 object pairs showed a significant positive correlation. Results of multilevel modeling analyses suggested that: (a) implicit and explicit preferences are related, (b) the relationship varies as a function of the objects assessed, and (c) at least four variables moderate the relationship – self-presentation, evaluative strength, dimensionality, and distinctiveness. The variables moderated implicit-explicit correspondence across individuals and accounted for much of the observed variation across content domains. The resulting model of the relationship between automatic and controlled evaluative processes is grounded in personal experience with the targets of evaluation. PMID:16316292

Characterizing Attention with Predictive Network Models.

PubMed

Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

2017-04-01

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

A new solution method for wheel/rail rolling contact.

PubMed

Yang, Jian; Song, Hua; Fu, Lihua; Wang, Meng; Li, Wei

2016-01-01

To solve the problem of wheel/rail rolling contact of nonlinear steady-state curving, a three-dimensional transient finite element (FE) model is developed by the explicit software ANSYS/LS-DYNA. To improve the solving speed and efficiency, an explicit-explicit order solution method is put forward based on analysis of the features of implicit and explicit algorithm. The solution method was first applied to calculate the pre-loading of wheel/rail rolling contact with explicit algorithm, and then the results became the initial conditions in solving the dynamic process of wheel/rail rolling contact with explicit algorithm as well. Simultaneously, the common implicit-explicit order solution method is used to solve the FE model. Results show that the explicit-explicit order solution method has faster operation speed and higher efficiency than the implicit-explicit order solution method while the solution accuracy is almost the same. Hence, the explicit-explicit order solution method is more suitable for the wheel/rail rolling contact model with large scale and high nonlinearity.

Towards automated assistance for operating home medical devices.

PubMed

Gao, Zan; Detyniecki, Marcin; Chen, Ming-Yu; Wu, Wen; Hauptmann, Alexander G; Wactlar, Howard D

2010-01-01

To detect errors when subjects operate a home medical device, we observe them with multiple cameras. We then perform action recognition with a robust approach to recognize action information based on explicitly encoding motion information. This algorithm detects interest points and encodes not only their local appearance but also explicitly models local motion. Our goal is to recognize individual human actions in the operations of a home medical device to see if the patient has correctly performed the required actions in the prescribed sequence. Using a specific infusion pump as a test case, requiring 22 operation steps from 6 action classes, our best classifier selects high likelihood action estimates from 4 available cameras, to obtain an average class recognition rate of 69%.

Implicit and explicit ethnocentrism: revisiting the ideologies of prejudice.

PubMed

Cunningham, William A; Nezlek, John B; Banaji, Mahzarin R

2004-10-01

Two studies investigated relationships among individual differences in implicit and explicit prejudice, right-wing ideology, and rigidity in thinking. The first study examined these relationships focusing on White Americans' prejudice toward Black Americans. The second study provided the first test of implicit ethnocentrism and its relationship to explicit ethnocentrism by studying the relationship between attitudes toward five social groups. Factor analyses found support for both implicit and explicit ethnocentrism. In both studies, mean explicit attitudes toward out groups were positive, whereas implicit attitudes were negative, suggesting that implicit and explicit prejudices are distinct; however, in both studies, implicit and explicit attitudes were related (r = .37, .47). Latent variable modeling indicates a simple structure within this ethnocentric system, with variables organized in order of specificity. These results lead to the conclusion that (a) implicit ethnocentrism exists and (b) it is related to and distinct from explicit ethnocentrism.

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

PubMed Central

Broekhuis, Femke; Gopalaswamy, Arjun M.

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

PubMed

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

An individual-based growth and competition model for coastal redwood forest restoration

USGS Publications Warehouse

van Mantgem, Phillip J.; Das, Adrian J.

2014-01-01

Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, Cheryl; Nisbet, Roger; Antczak, Philipp

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) thatmore » link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less

Making the Implicit Explicit: Supporting Teachers to Bridge Cultures

ERIC Educational Resources Information Center

Rothstein-Fisch, Carrie; Trumbull, Elise; Garcia, Sandra Gloria

2009-01-01

In this paper, we report the results of a longitudinal action research project in which elementary teachers used a cultural framework (individualism-collectivism) to understand differences between the culture of immigrant Latino families and the culture of U.S. schools. Making explicit the culture-based beliefs implicit in home and school…

Implicit Attitudes towards People with Intellectual Disabilities: Their Relationship with Explicit Attitudes, Social Distance, Emotions and Contact

PubMed Central

Wilson, Michelle Clare; Scior, Katrina

2015-01-01

Implicit attitude research has expanded rapidly over the last decade and is seen as very promising as it counters biases present in much attitude research such as social desirability. However, most research in the area of intellectual disabilities has focused on explicit attitudes alone. This study examined implicit attitudes to this population and also examined their association with emotional reactions and contact, which have previously been found to have a significant influence on attitudes and stigma. A web based survey consisting of a single target Implicit Association Test, measures of explicit attitudes, social distance, and emotional reactions towards and contact with individuals with intellectual disabilities was completed by 326 adult UK residents. Implicit attitudes were not significantly associated with explicit attitudes, social distance or emotional reactions. Instead there were small to moderate associations between emotional reactions and explicit attitudes and social distance. Implicit attitudes did not vary according to participants’ level of contact with individuals with intellectual disabilities, type of the contact relationship (voluntary versus involuntary), gender or educational attainment. In contrast, these participant characteristics did affect explicit attitudes and social distance. Implicit attitudes towards individuals with intellectual disabilities were somewhat negative and, unlike explicit attitudes and stigma, did not vary according to participant demographics or contact. As they may have a negative impact on the lives of people with intellectual disabilities, implicit attitudes merit increased attention in research and interventions in the intellectual disabilities field. PMID:26366575

Implicit Attitudes towards People with Intellectual Disabilities: Their Relationship with Explicit Attitudes, Social Distance, Emotions and Contact.

PubMed

Wilson, Michelle Clare; Scior, Katrina

2015-01-01

Implicit attitude research has expanded rapidly over the last decade and is seen as very promising as it counters biases present in much attitude research such as social desirability. However, most research in the area of intellectual disabilities has focused on explicit attitudes alone. This study examined implicit attitudes to this population and also examined their association with emotional reactions and contact, which have previously been found to have a significant influence on attitudes and stigma. A web based survey consisting of a single target Implicit Association Test, measures of explicit attitudes, social distance, and emotional reactions towards and contact with individuals with intellectual disabilities was completed by 326 adult UK residents. Implicit attitudes were not significantly associated with explicit attitudes, social distance or emotional reactions. Instead there were small to moderate associations between emotional reactions and explicit attitudes and social distance. Implicit attitudes did not vary according to participants' level of contact with individuals with intellectual disabilities, type of the contact relationship (voluntary versus involuntary), gender or educational attainment. In contrast, these participant characteristics did affect explicit attitudes and social distance. Implicit attitudes towards individuals with intellectual disabilities were somewhat negative and, unlike explicit attitudes and stigma, did not vary according to participant demographics or contact. As they may have a negative impact on the lives of people with intellectual disabilities, implicit attitudes merit increased attention in research and interventions in the intellectual disabilities field.

Explicit and implicit learning: The case of computer programming

NASA Astrophysics Data System (ADS)

Mancy, Rebecca

The central question of this thesis concerns the role of explicit and implicit learning in the acquisition of a complex skill, namely computer programming. This issue is explored with reference to information processing models of memory drawn from cognitive science. These models indicate that conscious information processing occurs in working memory where information is stored and manipulated online, but that this mode of processing shows serious limitations in terms of capacity or resources. Some information processing models also indicate information processing in the absence of conscious awareness through automation and implicit learning. It was hypothesised that students would demonstrate implicit and explicit knowledge and that both would contribute to their performance in programming. This hypothesis was investigated via two empirical studies. The first concentrated on temporary storage and online processing in working memory and the second on implicit and explicit knowledge. Storage and processing were tested using two tools: temporary storage capacity was measured using a digit span test; processing was investigated with a disembedding test. The results were used to calculate correlation coefficients with performance on programming examinations. Individual differences in temporary storage had only a small role in predicting programming performance and this factor was not a major determinant of success. Individual differences in disembedding were more strongly related to programming achievement. The second study used interviews to investigate the use of implicit and explicit knowledge. Data were analysed according to a grounded theory paradigm. The results indicated that students possessed implicit and explicit knowledge, but that the balance between the two varied between students and that the most successful students did not necessarily possess greater explicit knowledge. The ways in which students described their knowledge led to the development of a framework which extends beyond the implicit-explicit dichotomy to four descriptive categories of knowledge along this dimension. Overall, the results demonstrated that explicit and implicit knowledge both contribute to the acquisition ofprogramming skills. Suggestions are made for further research, and the results are discussed in the context of their implications for education.

Not explicit but implicit memory is influenced by individual perception style

PubMed Central

Tsushima, Yoshiaki

2018-01-01

Not only explicit but also implicit memory has considerable influence on our daily life. However, it is still unclear whether explicit and implicit memories are sensitive to individual differences. Here, we investigated how individual perception style (global or local) correlates with implicit and explicit memory. As a result, we found that not explicit but implicit memory was affected by the perception style: local perception style people more greatly used implicit memory than global perception style people. These results help us to make the new effective application adapting to individual perception style and understand some clinical symptoms such as autistic spectrum disorder. Furthermore, this finding might give us new insight of memory involving consciousness and unconsciousness as well as relationship between implicit/explicit memory and individual perception style. PMID:29370212

Not explicit but implicit memory is influenced by individual perception style.

PubMed

Hine, Kyoko; Tsushima, Yoshiaki

2018-01-01

Not only explicit but also implicit memory has considerable influence on our daily life. However, it is still unclear whether explicit and implicit memories are sensitive to individual differences. Here, we investigated how individual perception style (global or local) correlates with implicit and explicit memory. As a result, we found that not explicit but implicit memory was affected by the perception style: local perception style people more greatly used implicit memory than global perception style people. These results help us to make the new effective application adapting to individual perception style and understand some clinical symptoms such as autistic spectrum disorder. Furthermore, this finding might give us new insight of memory involving consciousness and unconsciousness as well as relationship between implicit/explicit memory and individual perception style.

Evolution of costly explicit memory and cumulative culture.

PubMed

Nakamaru, Mayuko

2016-06-21

Humans can acquire new information and modify it (cumulative culture) based on their learning and memory abilities, especially explicit memory, through the processes of encoding, consolidation, storage, and retrieval. Explicit memory is categorized into semantic and episodic memories. Animals have semantic memory, while episodic memory is unique to humans and essential for innovation and the evolution of culture. As both episodic and semantic memory are needed for innovation, the evolution of explicit memory influences the evolution of culture. However, previous theoretical studies have shown that environmental fluctuations influence the evolution of imitation (social learning) and innovation (individual learning) and assume that memory is not an evolutionary trait. If individuals can store and retrieve acquired information properly, they can modify it and innovate new information. Therefore, being able to store and retrieve information is essential from the perspective of cultural evolution. However, if both storage and retrieval were too costly, forgetting and relearning would have an advantage over storing and retrieving acquired information. In this study, using mathematical analysis and individual-based simulations, we investigate whether cumulative culture can promote the coevolution of costly memory and social and individual learning, assuming that cumulative culture improves the fitness of each individual. The conclusions are: (1) without cumulative culture, a social learning cost is essential for the evolution of storage-retrieval. Costly storage-retrieval can evolve with individual learning but costly social learning does not evolve. When low-cost social learning evolves, the repetition of forgetting and learning is favored more than the evolution of costly storage-retrieval, even though a cultural trait improves the fitness. (2) When cumulative culture exists and improves fitness, storage-retrieval can evolve with social and/or individual learning, which is not influenced by the degree of the social learning cost. Whether individuals socially learn a low level of culture from observing a high or the low level of culture influences the evolution of memory and learning, especially individual learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

DTIC Science & Technology

2015-08-01

21  Figure 4. Data-based proportion of DDD , DDE and DDT in total DDx in fish and sediment by... DDD dichlorodiphenyldichloroethane DDE dichlorodiphenyldichloroethylene DDT dichlorodiphenyltrichloroethane DoD Department of Defense ERM... DDD ) at the other site. The spatially-explicit model consistently predicts tissue concentrations that closely match both the average and the

A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.

2016-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

The importance of explicitly mapping instructional analogies in science education

NASA Astrophysics Data System (ADS)

Asay, Loretta Johnson

Analogies are ubiquitous during instruction in science classrooms, yet research about the effectiveness of using analogies has produced mixed results. An aspect seldom studied is a model of instruction when using analogies. The few existing models for instruction with analogies have not often been examined quantitatively. The Teaching With Analogies (TWA) model (Glynn, 1991) is one of the models frequently cited in the variety of research about analogies. The TWA model outlines steps for instruction, including the step of explicitly mapping the features of the source to the target. An experimental study was conducted to examine the effects of explicitly mapping the features of the source and target in an analogy during computer-based instruction about electrical circuits. Explicit mapping was compared to no mapping and to a control with no analogy. Participants were ninth- and tenth-grade biology students who were each randomly assigned to one of three conditions (no analogy module, analogy module, or explicitly mapped analogy module) for computer-based instruction. Subjects took a pre-test before the instruction, which was used to assign them to a level of previous knowledge about electrical circuits for analysis of any differential effects. After the instruction modules, students took a post-test about electrical circuits. Two weeks later, they took a delayed post-test. No advantage was found for explicitly mapping the analogy. Learning patterns were the same, regardless of the type of instruction. Those who knew the least about electrical circuits, based on the pre-test, made the most gains. After the two-week delay, this group maintained the largest amount of their gain. Implications exist for science education classrooms, as analogy use should be based on research about effective practices. Further studies are suggested to foster the building of research-based models for classroom instruction with analogies.

A Unified Framework for Monetary Theory and Policy Analysis.

ERIC Educational Resources Information Center

Lagos, Ricardo; Wright, Randall

2005-01-01

Search-theoretic models of monetary exchange are based on explicit descriptions of the frictions that make money essential. However, tractable versions of these models typically make strong assumptions that render them ill suited for monetary policy analysis. We propose a new framework, based on explicit micro foundations, within which macro…

Explicit and Implicit Stigma of Mental Illness as Predictors of the Recovery Attitudes of Assertive Community Treatment Practitioners.

PubMed

Stull, Laura G; McConnell, Haley; McGrew, John; Salyers, Michelle P

2017-01-01

While explicit negative stereotypes of mental illness are well established as barriers to recovery, implicit attitudes also may negatively impact outcomes. The current study is unique in its focus on both explicit and implicit stigma as predictors of recovery attitudes of mental health practitioners. Assertive Community Treatment practitioners (n = 154) from 55 teams completed online measures of stigma, recovery attitudes, and an Implicit Association Test (IAT). Three of four explicit stigma variables (perceptions of blameworthiness, helplessness, and dangerousness) and all three implicit stigma variables were associated with lower recovery attitudes. In a multivariate, hierarchical model, however, implicit stigma did not explain additional variance in recovery attitudes. In the overall model, perceptions of dangerousness and implicitly associating mental illness with "bad" were significant individual predictors of lower recovery attitudes. The current study demonstrates a need for interventions to lower explicit stigma, particularly perceptions of dangerousness, to increase mental health providers' expectations for recovery. The extent to which implicit and explicit stigma differentially predict outcomes, including recovery attitudes, needs further research.

Combining Model-driven and Schema-based Program Synthesis

NASA Technical Reports Server (NTRS)

Denney, Ewen; Whittle, John

2004-01-01

We describe ongoing work which aims to extend the schema-based program synthesis paradigm with explicit models. In this context, schemas can be considered as model-to-model transformations. The combination of schemas with explicit models offers a number of advantages, namely, that building synthesis systems becomes much easier since the models can be used in verification and in adaptation of the synthesis systems. We illustrate our approach using an example from signal processing.

Hierarchical models for estimating density from DNA mark-recapture studies

USGS Publications Warehouse

Gardner, B.; Royle, J. Andrew; Wegan, M.T.

2009-01-01

Genetic sampling is increasingly used as a tool by wildlife biologists and managers to estimate abundance and density of species. Typically, DNA is used to identify individuals captured in an array of traps ( e. g., baited hair snares) from which individual encounter histories are derived. Standard methods for estimating the size of a closed population can be applied to such data. However, due to the movement of individuals on and off the trapping array during sampling, the area over which individuals are exposed to trapping is unknown, and so obtaining unbiased estimates of density has proved difficult. We propose a hierarchical spatial capture-recapture model which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to (via movement) and detection by traps. Detection probability is modeled as a function of each individual's distance to the trap. We applied this model to a black bear (Ursus americanus) study conducted in 2006 using a hair-snare trap array in the Adirondack region of New York, USA. We estimated the density of bears to be 0.159 bears/km2, which is lower than the estimated density (0.410 bears/km2) based on standard closed population techniques. A Bayesian analysis of the model is fully implemented in the software program WinBUGS.

Building a Progressive-Situational Model of Post-Diagnosis Information Seeking for Parents of Individuals With Down Syndrome

PubMed Central

Gibson, Amelia N.

2016-01-01

This grounded theory study used in-depth, semi-structured interview to examine the information-seeking behaviors of 35 parents of children with Down syndrome. Emergent themes include a progressive pattern of behavior including information overload and avoidance, passive attention, and active information seeking; varying preferences between tacit and explicit information at different stages; and selection of information channels and sources that varied based on personal and situational constraints. Based on the findings, the author proposes a progressive model of health information seeking and a framework for using this model to collect data in practice. The author also discusses the practical and theoretical implications of a responsive, progressive approach to understanding parents’ health information–seeking behavior. PMID:28462351

Explicit continuous charge-based compact model for long channel heavily doped surrounding-gate MOSFETs incorporating interface traps and quantum effects

NASA Astrophysics Data System (ADS)

Hamzah, Afiq; Hamid, Fatimah A.; Ismail, Razali

2016-12-01

An explicit solution for long-channel surrounding-gate (SRG) MOSFETs is presented from intrinsic to heavily doped body including the effects of interface traps and fixed oxide charges. The solution is based on the core SRGMOSFETs model of the Unified Charge Control Model (UCCM) for heavily doped conditions. The UCCM model of highly doped SRGMOSFETs is derived to obtain the exact equivalent expression as in the undoped case. Taking advantage of the undoped explicit charge-based expression, the asymptotic limits for below threshold and above threshold have been redefined to include the effect of trap states for heavily doped cases. After solving the asymptotic limits, an explicit mobile charge expression is obtained which includes the trap state effects. The explicit mobile charge model shows very good agreement with respect to numerical simulation over practical terminal voltages, doping concentration, geometry effects, and trap state effects due to the fixed oxide charges and interface traps. Then, the drain current is obtained using the Pao-Sah's dual integral, which is expressed as a function of inversion charge densities at the source/drain ends. The drain current agreed well with the implicit solution and numerical simulation for all regions of operation without employing any empirical parameters. A comparison with previous explicit models has been conducted to verify the competency of the proposed model with the doping concentration of 1× {10}19 {{cm}}-3, as the proposed model has better advantages in terms of its simplicity and accuracy at a higher doping concentration.

A hierarchical model for spatial capture-recapture data

USGS Publications Warehouse

Royle, J. Andrew; Young, K.V.

2008-01-01

Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

Information of Complex Systems and Applications in Agent Based Modeling.

PubMed

Bao, Lei; Fritchman, Joseph C

2018-04-18

Information about a system's internal interactions is important to modeling the system's dynamics. This study examines the finer categories of the information definition and explores the features of a type of local information that describes the internal interactions of a system. Based on the results, a dual-space agent and information modeling framework (AIM) is developed by explicitly distinguishing an information space from the material space. The two spaces can evolve both independently and interactively. The dual-space framework can provide new analytic methods for agent based models (ABMs). Three examples are presented including money distribution, individual's economic evolution, and artificial stock market. The results are analyzed in the dual-space, which more clearly shows the interactions and evolutions within and between the information and material spaces. The outcomes demonstrate the wide-ranging applicability of using the dual-space AIMs to model and analyze a broad range of interactive and intelligent systems.

USING THE ECLPSS SOFTWARE ENVIRONMENT TO BUILD A SPATIALLY EXPLICIT COMPONENT-BASED MODEL OF OZONE EFFECTS ON FOREST ECOSYSTEMS. (R827958)

EPA Science Inventory

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ...

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

Mapping Thermal Habitat of Ectotherms Based on Behavioral Thermoregulation in a Controlled Thermal Environment

NASA Astrophysics Data System (ADS)

Fei, T.; Skidmore, A.; Liu, Y.

2012-07-01

Thermal environment is especially important to ectotherm because a lot of physiological functions rely on the body temperature such as thermoregulation. The so-called behavioural thermoregulation function made use of the heterogeneity of the thermal properties within an individual's habitat to sustain the animal's physiological processes. This function links the spatial utilization and distribution of individual ectotherm with the thermal properties of habitat (thermal habitat). In this study we modelled the relationship between the two by a spatial explicit model that simulates the movements of a lizard in a controlled environment. The model incorporates a lizard's transient body temperatures with a cellular automaton algorithm as a way to link the physiology knowledge of the animal with the spatial utilization of its microhabitat. On a larger spatial scale, 'thermal roughness' of the habitat was defined and used to predict the habitat occupancy of the target species. The results showed the habitat occupancy can be modelled by the cellular automaton based algorithm at a smaller scale, and can be modelled by the thermal roughness index at a larger scale.

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results from various remote sensing scenarios will also be presented.

Dealing with uncertainty in landscape genetic resistance models: a case of three co-occurring marsupials.

PubMed

Dudaniec, Rachael Y; Worthington Wilmer, Jessica; Hanson, Jeffrey O; Warren, Matthew; Bell, Sarah; Rhodes, Jonathan R

2016-01-01

Landscape genetics lacks explicit methods for dealing with the uncertainty in landscape resistance estimation, which is particularly problematic when sample sizes of individuals are small. Unless uncertainty can be quantified, valuable but small data sets may be rendered unusable for conservation purposes. We offer a method to quantify uncertainty in landscape resistance estimates using multimodel inference as an improvement over single model-based inference. We illustrate the approach empirically using co-occurring, woodland-preferring Australian marsupials within a common study area: two arboreal gliders (Petaurus breviceps, and Petaurus norfolcensis) and one ground-dwelling antechinus (Antechinus flavipes). First, we use maximum-likelihood and a bootstrap procedure to identify the best-supported isolation-by-resistance model out of 56 models defined by linear and non-linear resistance functions. We then quantify uncertainty in resistance estimates by examining parameter selection probabilities from the bootstrapped data. The selection probabilities provide estimates of uncertainty in the parameters that drive the relationships between landscape features and resistance. We then validate our method for quantifying uncertainty using simulated genetic and landscape data showing that for most parameter combinations it provides sensible estimates of uncertainty. We conclude that small data sets can be informative in landscape genetic analyses provided uncertainty can be explicitly quantified. Being explicit about uncertainty in landscape genetic models will make results more interpretable and useful for conservation decision-making, where dealing with uncertainty is critical. © 2015 John Wiley & Sons Ltd.

Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

NASA Astrophysics Data System (ADS)

Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

2016-02-01

Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

Direct versus Indirect Explicit Methods of Enhancing EFL Students' English Grammatical Competence: A Concept Checking-Based Consciousness-Raising Tasks Model

ERIC Educational Resources Information Center

Dang, Trang Thi Doan; Nguyen, Huong Thu

2013-01-01

Two approaches to grammar instruction are often discussed in the ESL literature: direct explicit grammar instruction (DEGI) (deduction) and indirect explicit grammar instruction (IEGI) (induction). This study aims to explore the effects of indirect explicit grammar instruction on EFL learners' mastery of English tenses. Ninety-four…

Estimating black bear density using DNA data from hair snares

USGS Publications Warehouse

Gardner, B.; Royle, J. Andrew; Wegan, M.T.; Rainbolt, R.E.; Curtis, P.D.

2010-01-01

DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capturerecapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km2. A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level. ?? The Wildlife Society.

Spatially explicit watershed modeling: tracking water, mercury and nitrogen in multiple systems under diverse conditions

EPA Science Inventory

Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...

Explicit and implicit cognition: a preliminary test of a dual-process theory of cognitive vulnerability to depression.

PubMed

Haeffel, Gerald J; Abramson, Lyn Y; Brazy, Paige C; Shah, James Y; Teachman, Bethany A; Nosek, Brian A

2007-06-01

Two studies were conducted to test a dual-process theory of cognitive vulnerability to depression. According to this theory, implicit and explicit cognitive processes have differential effects on depressive reactions to stressful life events. Implicit processes are hypothesized to be critical in determining an individual's immediate affective reaction to stress whereas explicit cognitions are thought to be more involved in long-term depressive reactions. Consistent with hypotheses, the results of study 1 (cross-sectional; N=237) showed that implicit, but not explicit, cognitions predicted immediate affective reactions to a lab stressor. Study 2 (longitudinal; N=251) also supported the dual-process model of cognitive vulnerability to depression. Results showed that both the implicit and explicit measures interacted with life stress to predict prospective changes in depressive symptoms, respectively. However, when both implicit and explicit predictors were entered into a regression equation simultaneously, only the explicit measure interacted with stress to remain a unique predictor of depressive symptoms over the five-week prospective interval.

Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

USGS Publications Warehouse

Wildhaber, Mark L.; Lamberson, Peter J.

2004-01-01

Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

Consequences of environmental and biological variances for range margins: a spatially explicit theoretical model

NASA Astrophysics Data System (ADS)

Malanson, G. P.; DeRose, R. J.; Bekker, M. F.

2016-12-01

The consequences of increasing climatic variance while including variability among individuals and populations are explored for range margins of species with a spatially explicit simulation. The model has a single environmental gradient and a single species then extended to two species. Species response to the environment is a Gaussian function with a peak of 1.0 at their peak fitness on the gradient. The variance in the environment is taken from the total variance in the tree ring series of 399 individuals of Pinus edulis in FIA plots in the western USA. The variability is increased by a multiplier of the standard deviation for various doubling times. The variance of individuals in the simulation is drawn from these same series. Inheritance of individual variability is based on the geographic locations of the individuals. The variance for P. edulis is recomputed as time-dependent conditional standard deviations using the GARCH procedure. Establishment and mortality are simulated in a Monte Carlo process with individual variance. Variance for P. edulis does not show a consistent pattern of heteroscedasticity. An obvious result is that increasing variance has deleterious effects on species persistence because extreme events that result in extinctions cannot be balanced by positive anomalies, but even less extreme negative events cannot be balanced by positive anomalies because of biological and spatial constraints. In the two species model the superior competitor is more affected by increasing climatic variance because its response function is steeper at the point of intersection with the other species and so the uncompensated effects of negative anomalies are greater for it. These theoretical results can guide the anticipated need to mitigate the effects of increasing climatic variability on P. edulis range margins. The trailing edge, here subject to increasing drought stress with increasing temperatures, will be more affected by negative anomalies.

Modular Cognitive-Behavioral Therapy for Childhood Anxiety Disorders. Guides to Individualized Evidence-Based Treatment Series

ERIC Educational Resources Information Center

Chorpita, Bruce F.

2006-01-01

This clinically wise and pragmatic book presents a systematic approach for treating any form of childhood anxiety using proven exposure-based techniques. What makes this rigorously tested modular treatment unique is that it is explicitly designed with flexibility and individualization in mind. Developed in a real-world, highly diverse community…

Making the most of sparse clinical data by using a predictive-model-based analysis, illustrated with a stavudine pharmacokinetic study.

PubMed

Zhang, L; Price, R; Aweeka, F; Bellibas, S E; Sheiner, L B

2001-02-01

A small-scale clinical investigation was done to quantify the penetration of stavudine (D4T) into cerebrospinal fluid (CSF). A model-based analysis estimates the steady-state ratio of AUCs of CSF and plasma concentrations (R(AUC)) to be 0.270, and the mean residence time of drug in the CSF to be 7.04 h. The analysis illustrates the advantages of a causal (scientific, predictive) model-based approach to analysis over a noncausal (empirical, descriptive) approach when the data, as here, demonstrate certain problematic features commonly encountered in clinical data, namely (i) few subjects, (ii) sparse sampling, (iii) repeated measures, (iv) imbalance, and (v) individual design variation. These features generally require special attention in data analysis. The causal-model-based analysis deals with features (i) and (ii), both of which reduce efficiency, by combining data from different studies and adding subject-matter prior information. It deals with features (iii)--(v), all of which prevent 'averaging' individual data points directly, first, by adjusting in the model for interindividual data differences due to design differences, secondly, by explicitly differentiating between interpatient, interoccasion, and measurement error variation, and lastly, by defining a scientifically meaningful estimand (R(AUC)) that is independent of design.

Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates

PubMed Central

Chambert, Thierry; Rotella, Jay J; Higgs, Megan D

2014-01-01

The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark–recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark–recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds. PMID:24834335

Continuum Fatigue Damage Modeling for Use in Life Extending Control

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.

1994-01-01

This paper develops a simplified continuum (continuous wrp to time, stress, etc.) fatigue damage model for use in Life Extending Controls (LEC) studies. The work is based on zero mean stress local strain cyclic damage modeling. New nonlinear explicit equation forms of cyclic damage in terms of stress amplitude are derived to facilitate the continuum modeling. Stress based continuum models are derived. Extension to plastic strain-strain rate models are also presented. Application of these models to LEC applications is considered. Progress toward a nonzero mean stress based continuum model is presented. Also, new nonlinear explicit equation forms in terms of stress amplitude are also derived for this case.

Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

PubMed Central

Dzialak, Matthew R.; Harju, Seth M.; Osborn, Robert G.; Wondzell, John J.; Hayden-Wing, Larry D.; Winstead, Jeffrey B.; Webb, Stephen L.

2011-01-01

Background Conserving animal populations in places where human activity is increasing is an ongoing challenge in many parts of the world. We investigated how human activity interacted with maternal status and individual variation in behavior to affect reliability of spatially-explicit models intended to guide conservation of critical ungulate calving resources. We studied Rocky Mountain elk (Cervus elaphus) that occupy a region where 2900 natural gas wells have been drilled. Methodology/Principal Findings We present novel applications of generalized additive modeling to predict maternal status based on movement, and of random-effects resource selection models to provide population and individual-based inference on the effects of maternal status and human activity. We used a 2×2 factorial design (treatment vs. control) that included elk that were either parturient or non-parturient and in areas either with or without industrial development. Generalized additive models predicted maternal status (parturiency) correctly 93% of the time based on movement. Human activity played a larger role than maternal status in shaping resource use; elk showed strong spatiotemporal patterns of selection or avoidance and marked individual variation in developed areas, but no such pattern in undeveloped areas. This difference had direct consequences for landscape-level conservation planning. When relative probability of use was calculated across the study area, there was disparity throughout 72–88% of the landscape in terms of where conservation intervention should be prioritized depending on whether models were based on behavior in developed areas or undeveloped areas. Model validation showed that models based on behavior in developed areas had poor predictive accuracy, whereas the model based on behavior in undeveloped areas had high predictive accuracy. Conclusions/Significance By directly testing for differences between developed and undeveloped areas, and by modeling resource selection in a random-effects framework that provided individual-based inference, we conclude that: 1) amplified selection or avoidance behavior and individual variation, as responses to increasing human activity, complicate conservation planning in multiple-use landscapes, and 2) resource selection behavior in places where human activity is predictable or less dynamic may provide a more reliable basis from which to prioritize conservation action. PMID:21297866

Explicit robust schemes for implementation of general principal value-based constitutive models

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement general hyperelastic constitutive models is addressed. To this end, special purpose functions are used to symbolically derive, evaluate, and automatically generate the associated FORTRAN code for the explicit forms of the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid for the entire deformation range. The analytical form of these explicit expressions is given here for the case in which the strain-energy potential is taken as a nonseparable polynomial function of the principle stretches.

Cryptography from noisy storage.

PubMed

Wehner, Stephanie; Schaffner, Christian; Terhal, Barbara M

2008-06-06

We show how to implement cryptographic primitives based on the realistic assumption that quantum storage of qubits is noisy. We thereby consider individual-storage attacks; i.e., the dishonest party attempts to store each incoming qubit separately. Our model is similar to the model of bounded-quantum storage; however, we consider an explicit noise model inspired by present-day technology. To illustrate the power of this new model, we show that a protocol for oblivious transfer is secure for any amount of quantum-storage noise, as long as honest players can perform perfect quantum operations. Our model also allows us to show the security of protocols that cope with noise in the operations of the honest players and achieve more advanced tasks such as secure identification.

An agent-based model driven by tropical rainfall to understand the spatio-temporal heterogeneity of a chikungunya outbreak.

PubMed

Dommar, Carlos J; Lowe, Rachel; Robinson, Marguerite; Rodó, Xavier

2014-01-01

Vector-borne diseases, such as dengue, malaria and chikungunya, are increasing across their traditional ranges and continuing to infiltrate new, previously unaffected, regions. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. We develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure vs. precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission. Copyright © 2013 Elsevier B.V. All rights reserved.

On the probability of extinction of the Haiti cholera epidemic

NASA Astrophysics Data System (ADS)

Bertuzzo, Enrico; Finger, Flavio; Mari, Lorenzo; Gatto, Marino; Rinaldo, Andrea

2014-05-01

Nearly 3 years after its appearance in Haiti, cholera has already exacted more than 8,200 deaths and 670,000 reported cases and it is feared to become endemic. However, no clear evidence of a stable environmental reservoir of pathogenic Vibrio cholerae, the infective agent of the disease, has emerged so far, suggesting that the transmission cycle of the disease is being maintained by bacteria freshly shed by infected individuals. Thus in principle cholera could possibly be eradicated from Haiti. Here, we develop a framework for the estimation of the probability of extinction of the epidemic based on current epidemiological dynamics and health-care practice. Cholera spreading is modelled by an individual-based spatially-explicit stochastic model that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. Our results indicate that the probability that the epidemic goes extinct before the end of 2016 is of the order of 1%. This low probability of extinction highlights the need for more targeted and effective interventions to possibly stop cholera in Haiti.

Bayesian methods to estimate urban growth potential

USGS Publications Warehouse

Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.

2017-01-01

Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.

Least-squares model-based halftoning

NASA Astrophysics Data System (ADS)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach permits the halftoner to be tuned to the individual printer, whose characteristics may vary considerably from those of other printers, for example, write-black vs. write-white laser printers.

Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, Robert M.

2008-01-01

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

A hierarchical model for estimating density in camera-trap studies

USGS Publications Warehouse

Royle, J. Andrew; Nichols, James D.; Karanth, K.Ullas; Gopalaswamy, Arjun M.

2009-01-01

Estimating animal density using capture–recapture data from arrays of detection devices such as camera traps has been problematic due to the movement of individuals and heterogeneity in capture probability among them induced by differential exposure to trapping.We develop a spatial capture–recapture model for estimating density from camera-trapping data which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to and detection by traps.We adopt a Bayesian approach to analysis of the hierarchical model using the technique of data augmentation.The model is applied to photographic capture–recapture data on tigers Panthera tigris in Nagarahole reserve, India. Using this model, we estimate the density of tigers to be 14·3 animals per 100 km2 during 2004.Synthesis and applications. Our modelling framework largely overcomes several weaknesses in conventional approaches to the estimation of animal density from trap arrays. It effectively deals with key problems such as individual heterogeneity in capture probabilities, movement of traps, presence of potential ‘holes’ in the array and ad hoc estimation of sample area. The formulation, thus, greatly enhances flexibility in the conduct of field surveys as well as in the analysis of data, from studies that may involve physical, photographic or DNA-based ‘captures’ of individual animals.

Persistence of Rift Valley fever virus in East Africa

NASA Astrophysics Data System (ADS)

Gachohi, J.; Hansen, F.; Bett, B.; Kitala, P.

2012-04-01

Rift Valley fever virus (RVFv) is a mosquito-borne pathogen of livestock, wildlife and humans that causes severe outbreaks in intervals of several years. One of the open questions is how the virus persists between outbreaks. We developed a spatially-explicit, individual-based simulation model of the RVFv transmission dynamics to investigate this question. The model, is based on livestock and mosquito population dynamics. Spatial aspects are explicitly represented by a set of grid cells that represent mosquito breeding sites. A grid cell measures 500 by 500m and the model considers a grid of 100 by 100 grid cells; the model thus operates on the regional scale of 2500km2. Livestock herds move between grid cells, and provide connectivity between the cells. The model is used to explore the spatio-temporal dynamics of RVFv persistence in absence of a wildlife reservoir in an east African semi-arid context. Specifically, the model assesses the importance of local virus persistence in mosquito breeding sites relative to global virus persistence mitigated by movement of hosts. Local persistence is determined by the length of time the virus remains in a mosquito breeding site once introduced. In the model, this is a function of the number of mosquitoes that emerge infected and their lifespan. Global persistence is determined by the level of connectivity between isolated grid cells. Our work gives insights into the ecological and epidemiological conditions under which RVFv persists. The implication for disease surveillance and management are discussed.

A conceptual care model for individualized care approach in cardiac rehabilitation--combining both illness representation and self-efficacy.

PubMed

Lau-Walker, Margaret

2006-02-01

This paper analyses the two prominent psychological theories of patient response--illness representation and self-efficacy--and explore the possibilities of the development of a conceptual individualized care model that would make use of both theories. Analysis of the literature established common themes that were used as the basis to form a conceptual framework intended to assist in the joint application of these theories to therapeutic settings. Both theories emphasize personal experience, pre-construction of self, individual response to illness and treatment, and that the patients' beliefs are more influential in their recovery than the severity of the illness. Where the theories are most divergent is their application to therapeutic interventions, which reflects the different sources of influence that each theory emphasizes. Based on their similarities and differences it is possible to integrate the two theories into a conceptual care model. The Interactive Care Model combines both theories of patient response and provides an explicit framework for further research into the design of effective therapeutic interventions in rehabilitation care.

The impact of resource dependence of the mechanisms of life on the spatial population dynamics of an in silico microbial community

NASA Astrophysics Data System (ADS)

Daly, Aisling J.; Baetens, Jan M.; De Baets, Bernard

2016-12-01

Biodiversity has a critical impact on ecosystem functionality and stability, and thus the current biodiversity crisis has motivated many studies of the mechanisms that sustain biodiversity, a notable example being non-transitive or cyclic competition. We therefore extend existing microscopic models of communities with cyclic competition by incorporating resource dependence in demographic processes, characteristics of natural systems often oversimplified or overlooked by modellers. The spatially explicit nature of our individual-based model of three interacting species results in the formation of stable spatial structures, which have significant effects on community functioning, in agreement with experimental observations of pattern formation in microbial communities.

Evaluation of Student Performance through a Multidimensional Finite Mixture IRT Model.

PubMed

Bacci, Silvia; Bartolucci, Francesco; Grilli, Leonardo; Rampichini, Carla

2017-01-01

In the Italian academic system, a student can enroll for an exam immediately after the end of the teaching period or can postpone it; in this second case the exam result is missing. We propose an approach for the evaluation of a student performance throughout the course of study, accounting also for nonattempted exams. The approach is based on an item response theory model that includes two discrete latent variables representing student performance and priority in selecting the exams to take. We explicitly account for nonignorable missing observations as the indicators of attempted exams also contribute to measure the performance (within-item multidimensionality). The model also allows for individual covariates in its structural part.

Green-Ampt approximations: A comprehensive analysis

NASA Astrophysics Data System (ADS)

Ali, Shakir; Islam, Adlul; Mishra, P. K.; Sikka, Alok K.

2016-04-01

Green-Ampt (GA) model and its modifications are widely used for simulating infiltration process. Several explicit approximate solutions to the implicit GA model have been developed with varying degree of accuracy. In this study, performance of nine explicit approximations to the GA model is compared with the implicit GA model using the published data for broad range of soil classes and infiltration time. The explicit GA models considered are Li et al. (1976) (LI), Stone et al. (1994) (ST), Salvucci and Entekhabi (1994) (SE), Parlange et al. (2002) (PA), Barry et al. (2005) (BA), Swamee et al. (2012) (SW), Ali et al. (2013) (AL), Almedeij and Esen (2014) (AE), and Vatankhah (2015) (VA). Six statistical indicators (e.g., percent relative error, maximum absolute percent relative error, average absolute percent relative errors, percent bias, index of agreement, and Nash-Sutcliffe efficiency) and relative computer computation time are used for assessing the model performance. Models are ranked based on the overall performance index (OPI). The BA model is found to be the most accurate followed by the PA and VA models for variety of soil classes and infiltration periods. The AE, SW, SE, and LI model also performed comparatively better. Based on the overall performance index, the explicit models are ranked as BA > PA > VA > LI > AE > SE > SW > ST > AL. Results of this study will be helpful in selection of accurate and simple explicit approximate GA models for solving variety of hydrological problems.

Exploring behavior of an unusual megaherbivore: A spatially explicit foraging model of the hippopotamus

USGS Publications Warehouse

Lewison, R.L.; Carter, J.

2004-01-01

Herbivore foraging theories have been developed for and tested on herbivores across a range of sizes. Due to logistical constraints, however, little research has focused on foraging behavior of megaherbivores. Here we present a research approach that explores megaherbivore foraging behavior, and assesses the applicability of foraging theories developed on smaller herbivores to megafauna. With simulation models as reference points for the analysis of empirical data, we investigate foraging strategies of the common hippopotamus (Hippopotamus amphibius). Using a spatially explicit individual based foraging model, we apply traditional herbivore foraging strategies to a model hippopotamus, compare model output, and then relate these results to field data from wild hippopotami. Hippopotami appear to employ foraging strategies that respond to vegetation characteristics, such as vegetation quality, as well as spatial reference information, namely distance to a water source. Model predictions, field observations, and comparisons of the two support that hippopotami generally conform to the central place foraging construct. These analyses point to the applicability of general herbivore foraging concepts to megaherbivores, but also point to important differences between hippopotami and other herbivores. Our synergistic approach of models as reference points for empirical data highlights a useful method of behavioral analysis for hard-to-study megafauna. ?? 2003 Elsevier B.V. All rights reserved.

Using implicit association tests for the assessment of implicit personality self-concepts of extraversion and neuroticism in schizophrenia.

PubMed

Suslow, Thomas; Lindner, Christian; Kugel, Harald; Egloff, Boris; Schmukle, Stefan C

2014-08-30

There is evidence from research based on self-report personality measures that schizophrenia patients tend to be lower in extraversion and higher in neuroticism than healthy individuals. Self-report personality measures assess aspects of the explicit self-concept. The Implicit Association Test (IAT) has been developed to assess aspects of implicit cognition such as implicit attitudes and implicit personality traits. The present study was conducted to investigate the applicability and reliability of the IAT in schizophrenia patients and test whether they differ from healthy individuals on implicitly measured extraversion and neuroticism. The IAT and the NEO-FFI were administered as implicit and explicit measures of extraversion and neuroticism to 34 schizophrenia patients and 45 healthy subjects. For all IAT scores satisfactory to good reliabilities were observed in the patient sample. In both study groups, IAT scores were not related to NEO-FFI scores. Schizophrenia patients were lower in implicit and explicit extraversion and higher in implicit and explicit neuroticism than healthy individuals. Our data show that the IAT can be reliably applied to schizophrenia patients and suggest that they differ from healthy individuals not only in their conscious representation but also in their implicit representation of the self with regard to neuroticism and extraversion-related characteristics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Implicit and explicit Theory of Mind reasoning in autism spectrum disorders: the impact of experience.

PubMed

Schuwerk, Tobias; Vuori, Maria; Sodian, Beate

2015-05-01

This study aimed to investigate the relationship between explicit and implicit forms of Theory of Mind reasoning and to test the influence of experience on implicit Theory of Mind reasoning in individuals with autism spectrum disorders and in neurotypical adults. Results from two standard explicit Theory of Mind tasks are mixed: Individuals with autism spectrum disorders did not differ from neurotypical adults in their performance in the Strange Stories Test, but scored significantly lower on the Reading the Mind in the Eyes Test. Furthermore, in an implicit false-belief task, individuals with autism spectrum disorders differed from neurotypical adults in false belief-congruent anticipatory looking. However, this group difference disappeared by (1) providing participants with the outcome of a false belief-based action and (2) subsequently repeating this test trial. Although the tendency to fixate the false belief-congruent location significantly increased from the first to the second test trial in individuals with autism spectrum disorders, it differed in neither test trial from chance. These findings support the notion of an implicit Theory of Mind deficit in autism spectrum disorders, but give rise to the idea that anticipatory looking behaviors in autism spectrum disorders may be affected by experience. Additionally, the pattern of results from implicit and explicit Theory of Mind measures supports the theory of two independent Theory of Mind reasoning systems. © The Author(s) 2014.

A Multi-Year Program Developing an Explicit Reflective Pedagogy for Teaching Pre-service Teachers the Nature of Science by Ostention

NASA Astrophysics Data System (ADS)

Smith, Mike U.; Scharmann, Lawrence

2008-02-01

This investigation delineates a multi-year action research agenda designed to develop an instructional model for teaching the nature of science (NOS) to preservice science teachers. Our past research strongly supports the use of explicit reflective instructional methods, which includes Thomas Kuhn’s notion of learning by ostention and treating science as a continuum (i.e., comparing fields of study to one another for relative placement as less to more scientific). Instruction based on conceptual change precepts, however, also exhibits promise. Thus, the investigators sought to ascertain the degree to which conceptual change took place among students (n = 15) participating in the NOS instructional model. Three case studies are presented to illustrate successful conceptual changes that took place as a result of the NOS instructional model. All three cases represent students who claim a very conservative Christian heritage and for whom evolution was not considered a legitimate scientific theory prior to participating in the NOS instructional model. All three case study individuals, along with their twelve classmates, placed evolution as most scientific when compared to intelligent design and a fictional field of study called “Umbrellaology.”

Group-based differences in anti-aging bias among medical students.

PubMed

Ruiz, Jorge G; Andrade, Allen D; Anam, Ramanakumar; Taldone, Sabrina; Karanam, Chandana; Hogue, Christie; Mintzer, Michael J

2015-01-01

Medical students (MS) may develop ageist attitudes early in their training that may predict their future avoidance of caring for the elderly. This study sought to determine MS' patterns of explicit and implicit anti-aging bias, intent to practice with older people and using the quad model, the role of gender, race, and motivation-based differences. One hundred and three MS completed an online survey that included explicit and implicit measures. Explicit measures revealed a moderately positive perception of older people. Female medical students and those high in internal motivation showed lower anti-aging bias, and both were more likely to intend to practice with older people. Although the implicit measure revealed more negativity toward the elderly than the explicit measures, there were no group differences. However, using the quad model the authors identified gender, race, and motivation-based differences in controlled and automatic processes involved in anti-aging bias.

The Construction of Visual-spatial Situation Models in Children's Reading and Their Relation to Reading Comprehension

PubMed Central

Barnes, Marcia A.; Raghubar, Kimberly P.; Faulkner, Heather; Denton, Carolyn A.

2014-01-01

Readers construct mental models of situations described by text to comprehend what they read, updating these situation models based on explicitly described and inferred information about causal, temporal, and spatial relations. Fluent adult readers update their situation models while reading narrative text based in part on spatial location information that is consistent with the perspective of the protagonist. The current study investigates whether children update spatial situation models in a similar way, whether there are age-related changes in children's formation of spatial situation models during reading, and whether measures of the ability to construct and update spatial situation models are predictive of reading comprehension. Typically-developing children from ages 9 through 16 years (n=81) were familiarized with a physical model of a marketplace. Then the model was covered, and children read stories that described the movement of a protagonist through the marketplace and were administered items requiring memory for both explicitly stated and inferred information about the character's movements. Accuracy of responses and response times were evaluated. Results indicated that: (a) location and object information during reading appeared to be activated and updated not simply from explicit text-based information but from a mental model of the real world situation described by the text; (b) this pattern showed no age-related differences; and (c) the ability to update the situation model of the text based on inferred information, but not explicitly stated information, was uniquely predictive of reading comprehension after accounting for word decoding. PMID:24315376

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

We present a study, based on simulations with SERDYCA, a spatially-explicit individual based model of rodent dynamics, on the connection between population persistence and the presence of inhomogeneities in the habitat. We are specifically interested on the effect that inhomogeneities that do not fragment the environment, have on population persistence. Our results suggest that a certain percentage of inhomogeneities can increase the average time to extinction of the population. Inhomogeneities decrease the population density and can increase the ratio of juveniles in the population thus providing a better chance for the population to restore itself after a severe period withmore » critically low population density. We call this the ''inhomogeneity localization effect''.« less

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Pursuing the method of multiple working hypotheses to understand differences in process-based snow models

NASA Astrophysics Data System (ADS)

Clark, Martyn; Essery, Richard

2017-04-01

When faced with the complex and interdisciplinary challenge of building process-based land models, different modelers make different decisions at different points in the model development process. These modeling decisions are generally based on several considerations, including fidelity (e.g., what approaches faithfully simulate observed processes), complexity (e.g., which processes should be represented explicitly), practicality (e.g., what is the computational cost of the model simulations; are there sufficient resources to implement the desired modeling concepts), and data availability (e.g., is there sufficient data to force and evaluate models). Consequently the research community, comprising modelers of diverse background, experience, and modeling philosophy, has amassed a wide range of models, which differ in almost every aspect of their conceptualization and implementation. Model comparison studies have been undertaken to explore model differences, but have not been able to meaningfully attribute inter-model differences in predictive ability to individual model components because there are often too many structural and implementation differences among the different models considered. As a consequence, model comparison studies to date have provided limited insight into the causes of differences in model behavior, and model development has often relied on the inspiration and experience of individual modelers rather than on a systematic analysis of model shortcomings. This presentation will summarize the use of "multiple-hypothesis" modeling frameworks to understand differences in process-based snow models. Multiple-hypothesis frameworks define a master modeling template, and include a a wide variety of process parameterizations and spatial configurations that are used in existing models. Such frameworks provide the capability to decompose complex models into the individual decisions that are made as part of model development, and evaluate each decision in isolation. It is hence possible to attribute differences in system-scale model predictions to individual modeling decisions, providing scope to mimic the behavior of existing models, understand why models differ, characterize model uncertainty, and identify productive pathways to model improvement. Results will be presented applying multiple hypothesis frameworks to snow model comparison projects, including PILPS, SnowMIP, and the upcoming ESM-SnowMIP project.

Image barcodes

NASA Astrophysics Data System (ADS)

Damera-Venkata, Niranjan; Yen, Jonathan

2003-01-01

A Visually significant two-dimensional barcode (VSB) developed by Shaked et. al. is a method used to design an information carrying two-dimensional barcode, which has the appearance of a given graphical entity such as a company logo. The encoding and decoding of information using the VSB, uses a base image with very few graylevels (typically only two). This typically requires the image histogram to be bi-modal. For continuous-tone images such as digital photographs of individuals, the representation of tone or "shades of gray" is not only important to obtain a pleasing rendition of the face, but in most cases, the VSB renders these images unrecognizable due to its inability to represent true gray-tone variations. This paper extends the concept of a VSB to an image bar code (IBC). We enable the encoding and subsequent decoding of information embedded in the hardcopy version of continuous-tone base-images such as those acquired with a digital camera. The encoding-decoding process is modeled by robust data transmission through a noisy print-scan channel that is explicitly modeled. The IBC supports a high information capacity that differentiates it from common hardcopy watermarks. The reason for the improved image quality over the VSB is a joint encoding/halftoning strategy based on a modified version of block error diffusion. Encoder stability, image quality vs. information capacity tradeoffs and decoding issues with and without explicit knowledge of the base-image are discussed.

The Things You Do: Internal Models of Others’ Expected Behaviour Guide Action Observation

PubMed Central

Schenke, Kimberley C.; Wyer, Natalie A.; Bach, Patric

2016-01-01

Predictions allow humans to manage uncertainties within social interactions. Here, we investigate how explicit and implicit person models–how different people behave in different situations–shape these predictions. In a novel action identification task, participants judged whether actors interacted with or withdrew from objects. In two experiments, we manipulated, unbeknownst to participants, the two actors action likelihoods across situations, such that one actor typically interacted with one object and withdrew from the other, while the other actor showed the opposite behaviour. In Experiment 2, participants additionally received explicit information about the two individuals that either matched or mismatched their actual behaviours. The data revealed direct but dissociable effects of both kinds of person information on action identification. Implicit action likelihoods affected response times, speeding up the identification of typical relative to atypical actions, irrespective of the explicit knowledge about the individual’s behaviour. Explicit person knowledge, in contrast, affected error rates, causing participants to respond according to expectations instead of observed behaviour, even when they were aware that the explicit information might not be valid. Together, the data show that internal models of others’ behaviour are routinely re-activated during action observation. They provide first evidence of a person-specific social anticipation system, which predicts forthcoming actions from both explicit information and an individuals’ prior behaviour in a situation. These data link action observation to recent models of predictive coding in the non-social domain where similar dissociations between implicit effects on stimulus identification and explicit behavioural wagers have been reported. PMID:27434265

Inequity aversion and the evolution of cooperation

NASA Astrophysics Data System (ADS)

Ahmed, Asrar; Karlapalem, Kamalakar

2014-02-01

Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These reciprocity based models assume agents recognize their partner and know their previous interactions, which requires advanced cognitive abilities. In this paper we are interested in developing a model that produces cooperation without requiring any explicit memory of previous game plays. Our model is based on the notion of inequity aversion, a concept introduced within behavioral economics, whereby individuals care about payoff equality in outcomes. Here we explore the effect of using income inequality to guide partner selection and interaction. We study our model by considering both the well-mixed and the spatially structured population and present the conditions under which cooperation becomes dominant. Our results support the hypothesis that inequity aversion promotes cooperative relationship among nonkin.

Inequity aversion and the evolution of cooperation.

PubMed

Ahmed, Asrar; Karlapalem, Kamalakar

2014-02-01

Evolution of cooperation is a widely studied problem in biology, social science, economics, and artificial intelligence. Most of the existing approaches that explain cooperation rely on some notion of direct or indirect reciprocity. These reciprocity based models assume agents recognize their partner and know their previous interactions, which requires advanced cognitive abilities. In this paper we are interested in developing a model that produces cooperation without requiring any explicit memory of previous game plays. Our model is based on the notion of inequity aversion, a concept introduced within behavioral economics, whereby individuals care about payoff equality in outcomes. Here we explore the effect of using income inequality to guide partner selection and interaction. We study our model by considering both the well-mixed and the spatially structured population and present the conditions under which cooperation becomes dominant. Our results support the hypothesis that inequity aversion promotes cooperative relationship among nonkin.

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

PubMed

Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

2016-07-15

We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

The Adolescent Mentalization-based Integrative Treatment (AMBIT) approach to outcome evaluation and manualization: adopting a learning organization approach.

PubMed

Fuggle, Peter; Bevington, Dickon; Cracknell, Liz; Hanley, James; Hare, Suzanne; Lincoln, John; Richardson, Garry; Stevens, Nina; Tovey, Heather; Zlotowitz, Sally

2015-07-01

AMBIT (Adolescent Mentalization-Based Integrative Treatment) is a developing team approach to working with hard-to-reach adolescents. The approach applies the principle of mentalization to relationships with clients, team relationships and working across agencies. It places a high priority on the need for locally developed evidence-based practice, and proposes that outcome evaluation needs to be explicitly linked with processes of team learning using a learning organization framework. A number of innovative methods of team learning are incorporated into the AMBIT approach, particularly a system of web-based wiki-formatted AMBIT manuals individualized for each participating team. The paper describes early development work of the model and illustrates ways of establishing explicit links between outcome evaluation, team learning and manualization by describing these methods as applied to two AMBIT-trained teams; one team working with young people on the edge of care (AMASS - the Adolescent Multi-Agency Support Service) and another working with substance use (CASUS - Child and Adolescent Substance Use Service in Cambridgeshire). Measurement of the primary outcomes for each team (which were generally very positive) facilitated team learning and adaptations of methods of practice that were consolidated through manualization. © The Author(s) 2014.

Stochastic modeling of soundtrack for efficient segmentation and indexing of video

NASA Astrophysics Data System (ADS)

Naphade, Milind R.; Huang, Thomas S.

1999-12-01

Tools for efficient and intelligent management of digital content are essential for digital video data management. An extremely challenging research area in this context is that of multimedia analysis and understanding. The capabilities of audio analysis in particular for video data management are yet to be fully exploited. We present a novel scheme for indexing and segmentation of video by analyzing the audio track. This analysis is then applied to the segmentation and indexing of movies. We build models for some interesting events in the motion picture soundtrack. The models built include music, human speech and silence. We propose the use of hidden Markov models to model the dynamics of the soundtrack and detect audio-events. Using these models we segment and index the soundtrack. A practical problem in motion picture soundtracks is that the audio in the track is of a composite nature. This corresponds to the mixing of sounds from different sources. Speech in foreground and music in background are common examples. The coexistence of multiple individual audio sources forces us to model such events explicitly. Experiments reveal that explicit modeling gives better result than modeling individual audio events separately.

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.

Explanatory models concerning the effects of small-area characteristics on individual health.

PubMed

Voigtländer, Sven; Vogt, Verena; Mielck, Andreas; Razum, Oliver

2014-06-01

Material and social living conditions at the small-area level are assumed to have an effect on individual health. We review existing explanatory models concerning the effects of small-area characteristics on health and describe the gaps future research should try to fill. Systematic literature search for, and analysis of, studies that propose an explanatory model of the relationship between small-area characteristics and health. Fourteen studies met our inclusion criteria. Using various theoretical approaches, almost all of the models are based on a three-tier structure linking social inequalities (posited at the macro-level), small-area characteristics (posited at the meso-level) and individual health (micro-level). No study explicitly defines the geographical borders of the small-area context. The health impact of the small-area characteristics is explained by specific pathways involving mediating factors (psychological, behavioural, biological). These pathways tend to be seen as uni-directional; often, causality is implied. They may be modified by individual factors. A number of issues need more attention in research on explanatory models concerning small-area effects on health. Among them are the (geographical) definition of the small-area context; the systematic description of pathways comprising small-area contextual as well as compositional factors; questions of direction of association and causality; and the integration of a time dimension.

Wildfire risk management on a landscape with public and private ownership: Who pays for protection?

Treesearch

Gwenlyn Busby; Heidi J. Albers

2010-01-01

Wildfire, like many natural hazards, affects large landscapes with many landowners and the risk individual owners face depends on both individual and collective protective actions. In this study, we develop a spatially explicit game theoretic model to examine the strategic interaction between landowners' hazard mitigation decisions on a landscape with public and...

A Behavioral Model of Landscape Change in the Amazon Basin: The Colonist Case

NASA Technical Reports Server (NTRS)

Walker, R. A.; Drzyzga, S. A.; Li, Y. L.; Wi, J. G.; Caldas, M.; Arima, E.; Vergara, D.

2004-01-01

This paper presents the prototype of a predictive model capable of describing both magnitudes of deforestation and its spatial articulation into patterns of forest fragmentation. In a departure from other landscape models, it establishes an explicit behavioral foundation for algorithm development, predicated on notions of the peasant economy and on household production theory. It takes a 'bottom-up' approach, generating the process of land-cover change occurring at lot level together with the geography of a transportation system to describe regional landscape change. In other words, it translates the decentralized decisions of individual households into a collective, spatial impact. In so doing, the model unites the richness of survey research on farm households with the analytical rigor of spatial analysis enabled by geographic information systems (GIs). The paper describes earlier efforts at spatial modeling, provides a critique of the so-called spatially explicit model, and elaborates a behavioral foundation by considering farm practices of colonists in the Amazon basin. It then uses, insight from the behavioral statement to motivate a GIs-based model architecture. The model is implemented for a long-standing colonization frontier in the eastern sector of the basin, along the Trans-Amazon Highway in the State of Para, Brazil. Results are subjected to both sensitivity analysis and error assessment, and suggestions are made about how the model could be improved.

Evolution of female multiple mating: A quantitative model of the “sexually selected sperm” hypothesis

PubMed Central

Bocedi, Greta; Reid, Jane M

2015-01-01

Explaining the evolution and maintenance of polyandry remains a key challenge in evolutionary ecology. One appealing explanation is the sexually selected sperm (SSS) hypothesis, which proposes that polyandry evolves due to indirect selection stemming from positive genetic covariance with male fertilization efficiency, and hence with a male's success in postcopulatory competition for paternity. However, the SSS hypothesis relies on verbal analogy with “sexy-son” models explaining coevolution of female preferences for male displays, and explicit models that validate the basic SSS principle are surprisingly lacking. We developed analogous genetically explicit individual-based models describing the SSS and “sexy-son” processes. We show that the analogy between the two is only partly valid, such that the genetic correlation arising between polyandry and fertilization efficiency is generally smaller than that arising between preference and display, resulting in less reliable coevolution. Importantly, indirect selection was too weak to cause polyandry to evolve in the presence of negative direct selection. Negatively biased mutations on fertilization efficiency did not generally rescue runaway evolution of polyandry unless realized fertilization was highly skewed toward a single male, and coevolution was even weaker given random mating order effects on fertilization. Our models suggest that the SSS process is, on its own, unlikely to generally explain the evolution of polyandry. PMID:25330405

Aggregate and Individual Replication Probability within an Explicit Model of the Research Process

ERIC Educational Resources Information Center

Miller, Jeff; Schwarz, Wolf

2011-01-01

We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostova, T; Carlsen, T

We present a study, based on simulations with SERDYCA, a spatially-explicit individual-based model of rodent dynamics, on the relation between population persistence and the presence of numerous isolated disturbances in the habitat. We are specifically interested in the effect of disturbances that do not fragment the environment on population persistence. Our results suggest that the presence of disturbances in the absence of fragmentation can actually increase the average time to extinction of the modeled population. The presence of disturbances decreases population density but can increase the chance for mating in monogamous species and consequently, the ratio of juveniles in themore » population. It thus provides a better chance for the population to restore itself after a severe period with critically low population density. We call this the ''disturbance-forced localization effect''.« less

Implicit but not explicit self-esteem predicts future depressive symptomatology.

PubMed

Franck, Erik; De Raedt, Rudi; De Houwer, Jan

2007-10-01

To date, research on the predictive validity of implicit self-esteem for depressive relapse is very sparse. In the present study, we assessed implicit self-esteem using the Name Letter Preference Task and explicit self-esteem using the Rosenberg self-esteem scale in a group of currently depressed patients, formerly depressed individuals, and never depressed controls. In addition, we examined the predictive validity of explicit, implicit, and the interaction of explicit and implicit self-esteem in predicting future symptoms of depression in formerly depressed individuals and never depressed controls. The results showed that currently depressed individuals reported a lower explicit self-esteem as compared to formerly depressed individuals and never depressed controls. In line with previous research, all groups showed a positive implicit self-esteem not different from each other. Furthermore, after controlling for initial depressive symptomatology, implicit but not explicit self-esteem significantly predicted depressive symptoms at six months follow-up. Although implicit self-esteem assessed with the Name Letter Preference Test was not different between formerly depressed individuals and never depressed controls, the findings suggest it is an interesting variable in the study of vulnerability for depression relapse.

A theory-informed approach to developing visually mediated interventions to change behaviour using an asthma and physical activity intervention exemplar.

PubMed

Murray, Jennifer; Williams, Brian; Hoskins, Gaylor; Skar, Silje; McGhee, John; Treweek, Shaun; Sniehotta, Falko F; Sheikh, Aziz; Brown, Gordon; Hagen, Suzanne; Cameron, Linda; Jones, Claire; Gauld, Dylan

2016-01-01

Visualisation techniques are used in a range of healthcare interventions. However, these frequently lack a coherent rationale or clear theoretical basis. This lack of definition and explicit targeting of the underlying mechanisms may impede the success of and evaluation of the intervention. We describe the theoretical development, deployment, and pilot evaluation, of a complex visually mediated behavioural intervention. The exemplar intervention focused on increasing physical activity among young people with asthma. We employed an explicit five-stage development model, which was actively supported by a consultative user group. The developmental stages involved establishing the theoretical basis, establishing a narrative structure, visual rendering, checking interpretation, and pilot testing. We conducted in-depth interviews and focus groups during early development and checking, followed by an online experiment for pilot testing. A total of 91 individuals, including young people with asthma, parents, teachers, and health professionals, were involved in development and testing. Our final intervention consisted of two components: (1) an interactive 3D computer animation to create intentions and (2) an action plan and volitional help sheet to promote the translation of intentions to behaviour. Theory was mediated throughout by visual and audio forms. The intervention was regarded as highly acceptable, engaging, and meaningful by all stakeholders. The perceived impact on asthma understanding and intentions was reported positively, with most individuals saying that the 3D computer animation had either clarified a range of issues or made them more real. Our five-stage model underpinned by extensive consultation worked well and is presented as a framework to support explicit decision-making for others developing theory informed visually mediated interventions. We have demonstrated the ability to develop theory-based visually mediated behavioural interventions. However, attention needs to be paid to the potential ambiguity associated with images and thus the concept of visual literacy among patients. Our revised model may be helpful as a guide to aid development, acceptability, and ultimately effectiveness.

What do we know about implicit false-belief tracking?

PubMed

Schneider, Dana; Slaughter, Virginia P; Dux, Paul E

2015-02-01

There is now considerable evidence that neurotypical individuals track the internal cognitions of others, even in the absence of instructions to do so. This finding has prompted the suggestion that humans possess an implicit mental state tracking system (implicit Theory of Mind, ToM) that exists alongside a system that allows the deliberate and explicit analysis of the mental states of others (explicit ToM). Here we evaluate the evidence for this hypothesis and assess the extent to which implicit and explicit ToM operations are distinct. We review evidence showing that adults can indeed engage in ToM processing even without being conscious of doing so. However, at the same time, there is evidence that explicit and implicit ToM operations share some functional features, including drawing on executive resources. Based on the available evidence, we propose that implicit and explicit ToM operations overlap and should only be considered partially distinct.

Detailed temporal structure of communication networks in groups of songbirds.

PubMed

Stowell, Dan; Gill, Lisa; Clayton, David

2016-06-01

Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch (Taeniopygia guttata) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that 'kernels' reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual. © 2016 The Authors.

An explicit asymptotic model for the surface wave in a viscoelastic half-space based on applying Rabotnov's fractional exponential integral operators

NASA Astrophysics Data System (ADS)

Wilde, M. V.; Sergeeva, N. V.

2018-05-01

An explicit asymptotic model extracting the contribution of a surface wave to the dynamic response of a viscoelastic half-space is derived. Fractional exponential Rabotnov's integral operators are used for describing of material properties. The model is derived by extracting the principal part of the poles corresponding to the surface waves after applying Laplace and Fourier transforms. The simplified equations for the originals are written by using power series expansions. Padè approximation is constructed to unite short-time and long-time models. The form of this approximation allows to formulate the explicit model using a fractional exponential Rabotnov's integral operator with parameters depending on the properties of surface wave. The applicability of derived models is studied by comparing with the exact solutions of a model problem. It is revealed that the model based on Padè approximation is highly effective for all the possible time domains.

Late positive potential to explicit sexual images associated with the number of sexual intercourse partners

PubMed Central

Steele, Vaughn R.; Staley, Cameron; Sabatinelli, Dean

2015-01-01

Risky sexual behaviors typically occur when a person is sexually motivated by potent, sexual reward cues. Yet, individual differences in sensitivity to sexual cues have not been examined with respect to sexual risk behaviors. A greater responsiveness to sexual cues might provide greater motivation for a person to act sexually; a lower responsiveness to sexual cues might lead a person to seek more intense, novel, possibly risky, sexual acts. In this study, event-related potentials were recorded in 64 men and women while they viewed a series of emotional, including explicit sexual, photographs. The motivational salience of the sexual cues was varied by including more and less explicit sexual images. Indeed, the more explicit sexual stimuli resulted in enhanced late positive potentials (LPP) relative to the less explicit sexual images. Participants with fewer sexual intercourse partners in the last year had reduced LPP amplitude to the less explicit sexual images than the more explicit sexual images, whereas participants with more partners responded similarly to the more and less explicit sexual images. This pattern of results is consistent with a greater responsivity model. Those who engage in more sexual behaviors consistent with risk are also more responsive to less explicit sexual cues. PMID:24526189

Modeling Task Switching without Switching Tasks: A Short-Term Priming Account of Explicitly Cued Performance

ERIC Educational Resources Information Center

Schneider, Darryl W.; Logan, Gordon D.

2005-01-01

Switch costs in task switching are commonly attributed to an executive control process of task-set reconfiguration, particularly in studies involving the explicit task-cuing procedure. The authors propose an alternative account of explicitly cued performance that is based on 2 mechanisms: priming of cue encoding from residual activation of cues in…

A Generic Individual-Based Spatially Explicit Model as a Novel Tool for Investigating Insect-Plant Interactions: A Case Study of the Behavioural Ecology of Frugivorous Tephritidae

PubMed Central

Wang, Ming; Cribb, Bronwen; Clarke, Anthony R.; Hanan, Jim

2016-01-01

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments. PMID:26999285

Bet-hedging as a complex interaction among developmental instability, environmental heterogeneity, dispersal, and life-history strategy.

PubMed

Scheiner, Samuel M

2014-02-01

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.

The role of movement restrictions and pre-emptive destruction in the emergency control strategy against CSF outbreaks in domestic pigs.

PubMed

Thulke, Hans-Hermann; Eisinger, Dirk; Beer, Martin

2011-04-01

Classical swine fever (CSF) outbreaks in domestic pig herds lead to the implementation of standard control measures according to legislative regulations. Ideal outbreak control entails the swift and efficient culling of all pigs on premises detected positive for CSF virus. Often all pig holdings around the detected cases are pre-emptively destroyed to exclude transmission into the neighbourhood. In addition to these measures, zones are defined in which surveillance and protection measures are intensified to prevent further distant disease spread. In particular, all movements are prohibited within standstill areas. Standstill also excludes the transport of fattened pigs to slaughter. Historical outbreaks provide evidence of the success of this control strategy. However, the extent to which the individual strategy elements contribute to this success is unknown. Therefore, we applied a spatially and temporally explicit epidemic model to the problem. Its rule-based formulation is tailored to a one-by-one model implementation of existing control concepts. Using a comparative model analysis the individual contributions of single measures to overall control success were revealed. From the results of the model we concluded that movement restrictions had the dominant impact on strategy performance suggesting a reversal of the current conceptual thinking. Additional measures such as pre-emptive culling only became relevant under imperfect compliance with movement restrictions. The importance of movement restrictions for the overall control success illustrates the need for explicit consideration of this measure when contingency strategies are being amended (e.g. emergency vaccination) and associated risks assessed. Copyright © 2011 Elsevier B.V. All rights reserved.

Investigating the predictive validity of implicit and explicit measures of motivation in problem-solving behavioural tasks.

PubMed

Keatley, David; Clarke, David D; Hagger, Martin S

2013-09-01

Research into the effects of individuals'autonomous motivation on behaviour has traditionally adopted explicit measures and self-reported outcome assessment. Recently, there has been increased interest in the effects of implicit motivational processes underlying behaviour from a self-determination theory (SDT) perspective. The aim of the present research was to provide support for the predictive validity of an implicit measure of autonomous motivation on behavioural persistence on two objectively measurable tasks. SDT and a dual-systems model were adopted as frameworks to explain the unique effects offered by explicit and implicit autonomous motivational constructs on behavioural persistence. In both studies, implicit autonomous motivation significantly predicted unique variance in time spent on each task. Several explicit measures of autonomous motivation also significantly predicted persistence. Results provide support for the proposed model and the inclusion of implicit measures in research on motivated behaviour. In addition, implicit measures of autonomous motivation appear to be better suited to explaining variance in behaviours that are more spontaneous or unplanned. Future implications for research examining implicit motivation from dual-systems models and SDT approaches are outlined. © 2012 The British Psychological Society.

A Watershed-based spatially-explicit demonstration of an Integrated Environmental Modeling Framework for Ecosystem Services in the Coal River Basin (WV, USA)

EPA Science Inventory

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quant...

Reduced cognitive capacity impairs the malleability of older adults' negative attitudes to stigmatized individuals.

PubMed

Krendl, Anne C

2018-05-21

Although engaging explicit regulatory strategies may reduce negative bias toward outgroup members, these strategies are cognitively demanding and thus may not be effective for older adults (OA) who have reduced cognitive resources. The current study therefore examines whether individual differences in cognitive capacity disrupt OA' ability to explicitly regulate their bias to stigmatized individuals. Young and OA were instructed to explicitly regulate their negative bias toward stigmatized individuals by using an explicit reappraisal strategy. Regulatory success was assessed as a function of age and individual differences in cognitive capacity (Experiment 1). In Experiment 2, the role of executive function in implementing cognitive reappraisal strategies was examined by using a divided attention manipulation. Results from Experiment 1 revealed that individual differences in OA' cognitive capacity disrupted their ability to regulate their negative emotional response to stigma. In Experiment 2, it was found that dividing attention in young adults (YA) significantly reduced their regulatory success as compared to YA' regulatory capacity in the full attention condition. As expected, dividing YA' attention made their performance similar to OA with relatively preserved cognitive capacity. Together, the results from this study demonstrated that individual differences in cognitive capacity predicted OA' ability to explicitly regulate their negative bias to a range of stigmatized individuals.

Achieving enlightenment: what do we know about the implicit learning system and its interaction with explicit knowledge?

PubMed

Vidoni, Eric D; Boyd, Lara A

2007-09-01

Two major memory and learning systems operate in the brain: one for facts and ideas (ie, the declarative or explicit system), one for habits and behaviors (ie, the procedural or implicit system). Broadly speaking these two memory systems can operate either in concert or entirely independently of one another during the performance and learning of skilled motor behaviors. This Special Issue article has two parts. In the first, we present a review of implicit motor skill learning that is largely centered on the interactions between declarative and procedural learning and memory. Because distinct neuroanatomical substrates support unique aspects of learning and memory and thus focal injury can cause impairments that are dependent on lesion location, we also broadly consider which brain regions mediate implicit and explicit learning and memory. In the second part of this article, the interactive nature of these two memory systems is illustrated by the presentation of new data that reveal that both learning implicitly and acquiring explicit knowledge through physical practice lead to motor sequence learning. In our new data, we discovered that for healthy individuals use of the implicit versus explicit memory system differently affected variability of performance during acquisition practice; variability was higher early in practice for the implicit group and later in practice for the acquired explicit group. Despite the difference in performance variability, by retention both groups demonstrated comparable change in tracking accuracy and thus, motor sequence learning. Clinicians should be aware of the potential effects of implicit and explicit interactions when designing rehabilitation interventions, particularly when delivering explicit instructions before task practice, working with individuals with focal brain damage, and/or adjusting therapeutic parameters based on acquisition performance variability.

Spatial capture-recapture models allowing Markovian transience or dispersal

USGS Publications Warehouse

Royle, J. Andrew; Fuller, Angela K.; Sutherland, Chris

2016-01-01

Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.

Emergent properties of climate-vegetation feedbacks in the North American Monsoon Macrosystem

NASA Astrophysics Data System (ADS)

Mathias, A.; Niu, G.; Zeng, X.

2012-12-01

The ability of ecosystems to adapt naturally to climate change and associated disturbances (e.g. wildfires, spread of invasive species) is greatly affected by the stability of feedback interactions between climate and vegetation. In order to study climate-vegetation interactions, such as CO2 and H2O exchange in the North American Monsoon System (NAMS), we plan to couple a community land surface model (NoahMP or CLM) used in regional climate models (WRF) with an individual based, spatially explicit vegetation model (ECOTONE). Individual based modeling makes it possible to link individual plant traits with properties of plant communities. Community properties, such as species composition and species distribution arise from dynamic interactions of individual plants with each other, and with their environment. Plants interact with each other through intra- and interspecific competition for resources (H2O, nitrogen), and the outcome of these interactions depends on the properties of the plant community and the environment itself. In turn, the environment is affected by the resulting change in community structure, which may have an impact on the drivers of climate change. First, we performed sensitivity tests of ECOTONE to assess its ability to reproduce vegetation distribution in the NAMS. We compared the land surface model and ECOTONE with regard to their capability to accurately simulate soil moisture, CO2 flux and above ground biomass. For evaluating the models we used the eddy-correlation sensible and latent heat fluxes, CO2 flux and observations of other climate and environmental variables (e.g. soil temperature and moisture) from the Santa Rita experimental range. The model intercomparison helped us understand the advantages and disadvantages of each model, providing us guidance for coupling the community land surface model (NoahMP or CLM) with ECOTONE.

Treatment algorithms and protocolized care.

PubMed

Morris, Alan H

2003-06-01

Excess information in complex ICU environments exceeds human decision-making limits and likely contributes to unnecessary variation in clinical care, increasing the likelihood of clinical errors. I reviewed recent critical care clinical trials searching for information about the impact of protocol use on clinically pertinent outcomes. Several recently published clinical trials illustrate the importance of distinguishing efficacy and effectiveness trials. One of these trials illustrates the danger of conducting effectiveness trials before the efficacy of an intervention is established. The trials also illustrate the importance of distinguishing guidelines and inadequately explicit protocols from adequately explicit protocols. Only adequately explicit protocols contain enough detail to lead different clinicians to the same decision when faced with the same clinical scenario. Differences between guidelines and protocols are important. Guidelines lack detail and provide general guidance that requires clinicians to fill in many gaps. Computerized or paper-based protocols are detailed and, when used for complex clinical ICU problems, can generate patient-specific, evidence-based therapy instructions that can be carried out by different clinicians with almost no interclinician variability. Individualization of patient therapy can be preserved by these protocols when they are driven by individual patient data. Explicit decision-support tools (eg, guidelines and protocols) have favorable effects on clinician and patient outcomes and can reduce the variation in clinical practice. Guidelines and protocols that aid ICU decision makers should be more widely distributed.

Evaluating Change in Behavioral Preferences: Multidimensional Scaling Single-Ideal Point Model

ERIC Educational Resources Information Center

Ding, Cody

2016-01-01

The purpose of the article is to propose a multidimensional scaling single-ideal point model as a method to evaluate changes in individuals' preferences under the explicit methodological framework of behavioral preference assessment. One example is used to illustrate the approach for a clear idea of what this approach can accomplish.

The effect of explicit financial incentives on physician behavior.

PubMed

Armour, B S; Pitts, M M; Maclean, R; Cangialose, C; Kishel, M; Imai, H; Etchason, J

2001-05-28

Managed care organizations use explicit financial incentives to influence physicians' use of resources. This has contributed to concerns regarding conflicts of interest for physicians and adverse effects on the quality of patient care. In light of recent publicized legislative and legal battles about this issue, we reviewed the literature and analyzed studies that examine the effect of these explicit financial incentives on the behavior of physicians. The method used to undertake the literature review followed the approach set forth in the Cochrane Collaboration handbook. Our literature review revealed a paucity of data on the effect of explicit financial incentives. Based on this limited evidence, explicit incentives that place individual physicians at financial risk appear to be effective in reducing physician resource use. However, the empirical evidence regarding the effectiveness of bonus payments on physician resource use is mixed. Similarly, our review revealed mixed effects of the influence of explicit financial incentives on the quality of patient care. The effect of explicit financial incentives on physician behavior is complicated by a lack of understanding of the incentive structure by the managed care organization and the physician. The lack of a universally acceptable definition of quality renders it important that future researchers identify the term explicitly.

En Route to Depression: Self-Esteem Discrepancies and Habitual Rumination.

PubMed

Phillips, Wendy J; Hine, Donald W

2016-02-01

Dual-process models of cognitive vulnerability to depression suggest that some individuals possess discrepant implicit and explicit self-views, such as high explicit and low implicit self-esteem (fragile self-esteem) or low explicit and high implicit self-esteem (damaged self-esteem). This study investigated whether individuals with discrepant self-esteem may employ depressive rumination in an effort to reduce discrepancy-related dissonance, and whether the relationship between self-esteem discrepancy and future depressive symptoms varies as a function of rumination tendencies. Hierarchical regressions examined whether self-esteem discrepancy was associated with rumination in an Australian undergraduate sample at Time 1 (N = 306; M(age) = 29.9), and whether rumination tendencies moderated the relationship between self-esteem discrepancy and depressive symptoms assessed 3 months later (n = 160). Damaged self-esteem was associated with rumination at Time 1. As hypothesized, rumination moderated the relationship between self-esteem discrepancy and depressive symptoms at Time 2, where fragile self-esteem and high rumination tendencies at Time 1 predicted the highest levels of subsequent dysphoria. Results are consistent with dual-process propositions that (a) explicit self-regulation strategies may be triggered when explicit and implicit self-beliefs are incongruent, and (b) rumination may increase the likelihood of depression by expending cognitive resources and/or amplifying negative implicit biases. © 2014 Wiley Periodicals, Inc.

Five challenges for spatial epidemic models

PubMed Central

Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter

2015-01-01

Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. PMID:25843387

Strategy evolution driven by switching probabilities in structured multi-agent systems

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Chen, Zengqiang; Li, Zhiqi

2017-10-01

Evolutionary mechanism driving the commonly seen cooperation among unrelated individuals is puzzling. Related models for evolutionary games on graphs traditionally assume that players imitate their successful neighbours with higher benefits. Notably, an implicit assumption here is that players are always able to acquire the required pay-off information. To relax this restrictive assumption, a contact-based model has been proposed, where switching probabilities between strategies drive the strategy evolution. However, the explicit and quantified relation between a player's switching probability for her strategies and the number of her neighbours remains unknown. This is especially a key point in heterogeneously structured system, where players may differ in the numbers of their neighbours. Focusing on this, here we present an augmented model by introducing an attenuation coefficient and evaluate its influence on the evolution dynamics. Results show that the individual influence on others is negatively correlated with the contact numbers specified by the network topologies. Results further provide the conditions under which the coexisting strategies can be calculated analytically.

On explicit algebraic stress models for complex turbulent flows

NASA Technical Reports Server (NTRS)

Gatski, T. B.; Speziale, C. G.

1992-01-01

Explicit algebraic stress models that are valid for three-dimensional turbulent flows in noninertial frames are systematically derived from a hierarchy of second-order closure models. This represents a generalization of the model derived by Pope who based his analysis on the Launder, Reece, and Rodi model restricted to two-dimensional turbulent flows in an inertial frame. The relationship between the new models and traditional algebraic stress models -- as well as anistropic eddy visosity models -- is theoretically established. The need for regularization is demonstrated in an effort to explain why traditional algebraic stress models have failed in complex flows. It is also shown that these explicit algebraic stress models can shed new light on what second-order closure models predict for the equilibrium states of homogeneous turbulent flows and can serve as a useful alternative in practical computations.

A Joint Gaussian Process Model for Active Visual Recognition with Expertise Estimation in Crowdsourcing

PubMed Central

Long, Chengjiang; Hua, Gang; Kapoor, Ashish

2015-01-01

We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations.

PubMed

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture.

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations

PubMed Central

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture. PMID:27003834

Compositional schedulability analysis of real-time actor-based systems.

PubMed

Jaghoori, Mohammad Mahdi; de Boer, Frank; Longuet, Delphine; Chothia, Tom; Sirjani, Marjan

2017-01-01

We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checker.

Land Use as a Driver of Patterns of Rodenticide Exposure in Modeled Kit Fox Populations

PubMed Central

Nogeire, Theresa M.; Lawler, Joshua J.; Schumaker, Nathan H.; Cypher, Brian L.; Phillips, Scott E.

2015-01-01

Although rodenticides are increasingly regulated, they nonetheless cause poisonings in many non-target wildlife species. Second-generation anticoagulant rodenticide use is common in agricultural and residential landscapes. Here, we use an individual-based population model to assess potential population-wide effects of rodenticide exposures on the endangered San Joaquin kit fox (Vulpes macrotis mutica). We estimate likelihood of rodenticide exposure across the species range for each land cover type based on a database of reported pesticide use and literature. Using a spatially-explicit population model, we find that 36% of modeled kit foxes are likely exposed, resulting in a 7-18% decline in the range-wide modeled kit fox population that can be linked to rodenticide use. Exposures of kit foxes in low-density developed areas accounted for 70% of the population-wide exposures to rodenticides. We conclude that exposures of non-target kit foxes could be greatly mitigated by reducing the use of second-generation anticoagulant rodenticides in low-density developed areas near vulnerable populations. PMID:26244655

Spatially explicit models, generalized reproduction numbers and the prediction of patterns of waterborne disease

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Gatto, M.; Mari, L.; Casagrandi, R.; Righetto, L.; Bertuzzo, E.; Rodriguez-Iturbe, I.

2012-12-01

Metacommunity and individual-based theoretical models are studied in the context of the spreading of infections of water-borne diseases along the ecological corridors defined by river basins and networks of human mobility. The overarching claim is that mathematical models can indeed provide predictive insight into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. To support the claim, we examine the ex-post reliability of published predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. For each modeled epidemic trajectory, it is assessed how well predictions reproduced the observed spatial and temporal features of the outbreak to date. The impact of different approaches is considered to the modeling of the spatial spread of V. cholera, the mechanics of cholera transmission and in accounting for the dynamics of susceptible and infected individuals within different local human communities. A generalized model for Haitian epidemic cholera and the related uncertainty is thus constructed and applied to the year-long dataset of reported cases now available. Specific emphasis will be dedicated to models of human mobility, a fundamental infection mechanism. Lessons learned and open issues are discussed and placed in perspective, supporting the conclusion that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control. Although explicit spatial modeling is made routinely possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here, we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0 explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Individualism in plant populations: using stochastic differential equations to model individual neighbourhood-dependent plant growth.

PubMed

Lv, Qiming; Schneider, Manuel K; Pitchford, Jonathan W

2008-08-01

We study individual plant growth and size hierarchy formation in an experimental population of Arabidopsis thaliana, within an integrated analysis that explicitly accounts for size-dependent growth, size- and space-dependent competition, and environmental stochasticity. It is shown that a Gompertz-type stochastic differential equation (SDE) model, involving asymmetric competition kernels and a stochastic term which decreases with the logarithm of plant weight, efficiently describes individual plant growth, competition, and variability in the studied population. The model is evaluated within a Bayesian framework and compared to its deterministic counterpart, and to several simplified stochastic models, using distributional validation. We show that stochasticity is an important determinant of size hierarchy and that SDE models outperform the deterministic model if and only if structural components of competition (asymmetry; size- and space-dependence) are accounted for. Implications of these results are discussed in the context of plant ecology and in more general modelling situations.

The Use of Modeling-Based Text to Improve Students' Modeling Competencies

ERIC Educational Resources Information Center

Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

2015-01-01

This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

Development of Social Anxiety: Social Interaction Predictors of Implicit and Explicit Fear of Negative Evaluation

PubMed Central

Allen, Joseph P.

2012-01-01

Little is known about how to predict which individuals with known temperament vulnerabilities will go on to develop social anxiety problems. Adolescents (N = 185) were followed from age 13 to 18 to evaluate psychosocial, prospective predictors of social anxiety symptoms and fears of negative evaluation (FNE), after accounting for pre-existing social withdrawal symptoms. Results from structural equation modeling suggest that lack of perceived social acceptance predicts subsequent explicit social anxiety and FNE, whereas the emotional intensity of close peer interactions predicts subsequent implicit FNE. Results are discussed in terms of the importance of peer interaction in the development of social anxiety, and the value of measuring both implicit and explicit FNE. PMID:17171538

Implicit and Explicit Theory of Mind Reasoning in Autism Spectrum Disorders: The Impact of Experience

ERIC Educational Resources Information Center

Schuwerk, Tobias; Vuori, Maria; Sodian, Beate

2015-01-01

This study aimed to investigate the relationship between explicit and implicit forms of Theory of Mind reasoning and to test the influence of experience on implicit Theory of Mind reasoning in individuals with autism spectrum disorders and in neurotypical adults. Results from two standard explicit Theory of Mind tasks are mixed: Individuals with…

Generalized Born Models of Macromolecular Solvation Effects

NASA Astrophysics Data System (ADS)

Bashford, Donald; Case, David A.

2000-10-01

It would often be useful in computer simulations to use a simple description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation, and approximations to such models that avoid the need to solve the Poisson equation are attractive because of their computational efficiency. Here we give an overview of one such approximation, the generalized Born model, which is simple and fast enough to be used for molecular dynamics simulations of proteins and nucleic acids. We discuss its strengths and weaknesses, both for its fidelity to the underlying continuum model and for its ability to replace explicit consideration of solvent molecules in macromolecular simulations. We focus particularly on versions of the generalized Born model that have a pair-wise analytical form, and therefore fit most naturally into conventional molecular mechanics calculations.

The origin of consistent protein structure refinement from structural averaging.

PubMed

Park, Hahnbeom; DiMaio, Frank; Baker, David

2015-06-02

Recent studies have shown that explicit solvent molecular dynamics (MD) simulation followed by structural averaging can consistently improve protein structure models. We find that improvement upon averaging is not limited to explicit water MD simulation, as consistent improvements are also observed for more efficient implicit solvent MD or Monte Carlo minimization simulations. To determine the origin of these improvements, we examine the changes in model accuracy brought about by averaging at the individual residue level. We find that the improvement in model quality from averaging results from the superposition of two effects: a dampening of deviations from the correct structure in the least well modeled regions, and a reinforcement of consistent movements towards the correct structure in better modeled regions. These observations are consistent with an energy landscape model in which the magnitude of the energy gradient toward the native structure decreases with increasing distance from the native state. Copyright © 2015 Elsevier Ltd. All rights reserved.

Merging information from multi-model flood projections in a hierarchical Bayesian framework

NASA Astrophysics Data System (ADS)

Le Vine, Nataliya

2016-04-01

Multi-model ensembles are becoming widely accepted for flood frequency change analysis. The use of multiple models results in large uncertainty around estimates of flood magnitudes, due to both uncertainty in model selection and natural variability of river flow. The challenge is therefore to extract the most meaningful signal from the multi-model predictions, accounting for both model quality and uncertainties in individual model estimates. The study demonstrates the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach facilitates explicit treatment of shared multi-model discrepancy as well as the probabilistic nature of the flood estimates, by treating the available models as a sample from a hypothetical complete (but unobserved) set of models. The advantages of the approach are: 1) to insure an adequate 'baseline' conditions with which to compare future changes; 2) to reduce flood estimate uncertainty; 3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; 4) to adjust multi-model consistency criteria when model biases are large; and 5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.

Incorporating pushing in exclusion-process models of cell migration.

PubMed

Yates, Christian A; Parker, Andrew; Baker, Ruth E

2015-05-01

The macroscale movement behavior of a wide range of isolated migrating cells has been well characterized experimentally. Recently, attention has turned to understanding the behavior of cells in crowded environments. In such scenarios it is possible for cells to interact, inducing neighboring cells to move in order to make room for their own movements or progeny. Although the behavior of interacting cells has been modeled extensively through volume-exclusion processes, few models, thus far, have explicitly accounted for the ability of cells to actively displace each other in order to create space for themselves. In this work we consider both on- and off-lattice volume-exclusion position-jump processes in which cells are explicitly allowed to induce movements in their near neighbors in order to create space for themselves to move or proliferate into. We refer to this behavior as pushing. From these simple individual-level representations we derive continuum partial differential equations for the average occupancy of the domain. We find that, for limited amounts of pushing, comparison between the averaged individual-level simulations and the population-level model is nearly as good as in the scenario without pushing. Interestingly, we find that, in the on-lattice case, the diffusion coefficient of the population-level model is increased by pushing, whereas, for the particular off-lattice model that we investigate, the diffusion coefficient is reduced. We conclude, therefore, that it is important to consider carefully the appropriate individual-level model to use when representing complex cell-cell interactions such as pushing.

On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation

PubMed Central

DiStefano, Joseph

2014-01-01

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p 1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I–O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and–importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It’s illustrated and validated here for models of moderate complexity, with and without initial conditions. Built-in examples include unidentifiable 2 to 4-compartment and HIV dynamics models. PMID:25350289

GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems.

PubMed

Sadowski, Krzysztof L; Thierens, Dirk; Bosman, Peter A N

2018-01-01

Learning and exploiting problem structure is one of the key challenges in optimization. This is especially important for black-box optimization (BBO) where prior structural knowledge of a problem is not available. Existing model-based Evolutionary Algorithms (EAs) are very efficient at learning structure in both the discrete, and in the continuous domain. In this article, discrete and continuous model-building mechanisms are integrated for the Mixed-Integer (MI) domain, comprising discrete and continuous variables. We revisit a recently introduced model-based evolutionary algorithm for the MI domain, the Genetic Algorithm for Model-Based mixed-Integer opTimization (GAMBIT). We extend GAMBIT with a parameterless scheme that allows for practical use of the algorithm without the need to explicitly specify any parameters. We furthermore contrast GAMBIT with other model-based alternatives. The ultimate goal of processing mixed dependences explicitly in GAMBIT is also addressed by introducing a new mechanism for the explicit exploitation of mixed dependences. We find that processing mixed dependences with this novel mechanism allows for more efficient optimization. We further contrast the parameterless GAMBIT with Mixed-Integer Evolution Strategies (MIES) and other state-of-the-art MI optimization algorithms from the General Algebraic Modeling System (GAMS) commercial algorithm suite on problems with and without constraints, and show that GAMBIT is capable of solving problems where variable dependences prevent many algorithms from successfully optimizing them.

Random close packing in protein cores

NASA Astrophysics Data System (ADS)

Gaines, Jennifer C.; Smith, W. Wendell; Regan, Lynne; O'Hern, Corey S.

2016-03-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈0.75 , a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈0.56 , which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

Random close packing in protein cores.

PubMed

Gaines, Jennifer C; Smith, W Wendell; Regan, Lynne; O'Hern, Corey S

2016-03-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈ 0.75, a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈ 0.56, which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

Measurement and description of underlying dimensions of comorbid mental disorders using Factor Mixture Models: results of the ESEMeD project.

PubMed

Almansa, Josué; Vermunt, Jeroen K; Forero, Carlos G; Vilagut, Gemma; De Graaf, Ron; De Girolamo, Giovanni; Alonso, Jordi

2011-06-01

Epidemiological studies on mental health and mental comorbidity are usually based on prevalences and correlations between disorders, or some other form of bivariate clustering of disorders. In this paper, we propose a Factor Mixture Model (FMM) methodology based on conceptual models aiming to measure and summarize distinctive disorder information in the internalizing and externalizing dimensions. This methodology includes explicit modelling of subpopulations with and without 12 month disorders ("ill" and "healthy") by means of latent classes, as well as assessment of model invariance and estimation of dimensional scores. We applied this methodology with an internalizing/externalizing two-factor model, to a representative sample gathered in the European Study of the Epidemiology of Mental Disorders (ESEMeD) study -- which includes 8796 individuals from six countries, and used the CIDI 3.0 instrument for disorder assessment. Results revealed that southern European countries have significantly higher mental health levels concerning internalizing/externalizing disorders than central countries; males suffered more externalizing disorders than women did, and conversely, internalizing disorders were more frequent in women. Differences in mental-health level between socio-demographic groups were due to different proportions of healthy and ill individuals and, noticeably, to the ameliorating influence of marital status on severity. An advantage of latent model-based scores is that the inclusion of additional mental-health dimensional information -- other than diagnostic data -- allows for greater precision within a target range of scores. Copyright © 2011 John Wiley & Sons, Ltd.

Mental Health Trainees' Explicit and Implicit Attitudes Toward Transracial Adoptive Families Headed by Lesbian, Gay, and Heterosexual Couples.

PubMed

Tan, Tony Xing; Jordan-Arthur, Brittany; Garafano, Jeffrey S; Curran, Laura

2017-01-01

We investigated 109 (79.8% female; 76% White, and 83.5% Heterosexual) mental health trainees' explicit and implicit attitudes toward heterosexual, lesbian, and gay White couples adopting and raising Black children. To determine explicit attitudes, we used a vignette depicting a Black child ready for adoption and three types of equally qualified White families who were headed by a heterosexual couple, gay couple, or lesbian couple. The trainees were asked to indicate which type of family they preferred to adopt the child. To determine implicit attitudes, we used the computer programed latency-based multifactor implicit association test (IAT) protocol. The IAT data were collected from each participant individually. Explicit data showed that over 80% of the participants indicated no strong preference in terms of which type of family should adopted the child. However, IAT data showed that the trainees implicitly preferred lesbian couples. Overall, the degree of congruence between explicit and implicit was very low. Implications for training were discussed.

Types of high self-esteem and prejudice: how implicit self-esteem relates to ethnic discrimination among high explicit self-esteem individuals.

PubMed

Jordan, Christian H; Spencer, Steven J; Zanna, Mark P

2005-05-01

There is increasing recognition that high self-esteem is heterogeneous. Recent research suggests that individuals who report having high self-esteem (i.e., have high explicit self-esteem) behave more defensively to the extent that they have relatively low implicit self-esteem. The current studies test whether individuals with high explicit self-esteem are more likely to discriminate ethnically, as a defensive technique, to the extent that they have relatively low implicit self-esteem. The results support this prediction. Among participants with high explicit self-esteem, all of whom were threatened by negative performance feedback, those with relatively low implicit self-esteem recommended a more severe punishment for a Native, but not a White, student who started a fist-fight. In Study 2, this pattern was not apparent for participants with relatively low explicit self-esteem.

Polarimetric ISAR: Simulation and image reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chambers, David H.

In polarimetric ISAR the illumination platform, typically airborne, carries a pair of antennas that are directed toward a fixed point on the surface as the platform moves. During platform motion, the antennas maintain their gaze on the point, creating an effective aperture for imaging any targets near that point. The interaction between the transmitted fields and targets (e.g. ships) is complicated since the targets are typically many wavelengths in size. Calculation of the field scattered from the target typically requires solving Maxwell’s equations on a large three-dimensional numerical grid. This is prohibitive to use in any real-world imaging algorithm, somore » the scattering process is typically simplified by assuming the target consists of a cloud of independent, non-interacting, scattering points (centers). Imaging algorithms based on this scattering model perform well in many applications. Since polarimetric radar is not very common, the scattering model is often derived for a scalar field (single polarization) where the individual scatterers are assumed to be small spheres. However, when polarization is important, we must generalize the model to explicitly account for the vector nature of the electromagnetic fields and its interaction with objects. In this note, we present a scattering model that explicitly includes the vector nature of the fields but retains the assumption that the individual scatterers are small. The response of the scatterers is described by electric and magnetic dipole moments induced by the incident fields. We show that the received voltages in the antennas are linearly related to the transmitting currents through a scattering impedance matrix that depends on the overall geometry of the problem and the nature of the scatterers.« less

Microphysical response of cloud droplets in a fluctuating updraft. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Harding, D. D.

1977-01-01

The effect of a fluctuating updraft upon a distribution of cloud droplets is examined. Computations are performed for fourteen vertical velocity patterns; each allows a closed parcel of cloud air to undergo downward as well as upward motion. Droplet solution and curvature effects are included. The classical equations for the growth rate of an individual droplet by vapor condensation relies on simplifying assumptions. Those assumptions are isolated and examined. A unique approach is presented in which all energy sources and sinks of a droplet may be considered and is termed the explicit model. It is speculated that the explicit model may enhance the growth of large droplets at greater heights. Such a model is beneficial to the studies of pollution scavenging and acid rain.

Asymmetric competition causes multimodal size distributions in spatially structured populations

PubMed Central

Velázquez, Jorge; Allen, Robert B.; Coomes, David A.; Eichhorn, Markus P.

2016-01-01

Plant sizes within populations often exhibit multimodal distributions, even when all individuals are the same age and have experienced identical conditions. To establish the causes of this, we created an individual-based model simulating the growth of trees in a spatially explicit framework, which was parametrized using data from a long-term study of forest stands in New Zealand. First, we demonstrate that asymmetric resource competition is a necessary condition for the formation of multimodal size distributions within cohorts. By contrast, the legacy of small-scale clustering during recruitment is transient and quickly overwhelmed by density-dependent mortality. Complex multi-layered size distributions are generated when established individuals are restricted in the spatial domain within which they can capture resources. The number of modes reveals the effective number of direct competitors, while the separation and spread of modes are influenced by distances among established individuals. Asymmetric competition within local neighbourhoods can therefore generate a range of complex size distributions within even-aged cohorts. PMID:26817778

Effects of individualized electrical impedance tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4-dimensional computed tomography in a porcine model

PubMed Central

Mudrak, Daniel; Kampusch, Stefan; Wielandner, Alice; Prosch, Helmut; Braun, Christina; Toemboel, Frédéric P. R.; Hofmanninger, Johannes; Kaniusas, Eugenijus

2017-01-01

Electrical impedance tomography (EIT) is a promising imaging technique for bedside monitoring of lung function. It is easily applicable, cheap and requires no ionizing radiation, but clinical interpretation of EIT-images is still not standardized. One of the reasons for this is the ill-posed nature of EIT, allowing a range of possible images to be produced–rather than a single explicit solution. Thus, to further advance the EIT technology for clinical application, thorough examinations of EIT-image reconstruction settings–i.e., mathematical parameters and addition of a priori (e.g., anatomical) information–is essential. In the present work, regional ventilation distribution profiles derived from different EIT finite-element reconstruction models and settings (for GREIT and Gauss Newton) were compared to regional aeration profiles assessed by the gold-standard of 4-dimensional computed tomography (4DCT) by calculating the root mean squared error (RMSE). Specifically, non-individualized reconstruction models (based on circular and averaged thoracic contours) and individualized reconstruction models (based on true thoracic contours) were compared. Our results suggest that GREIT with noise figure of 0.15 and non-uniform background works best for the assessment of regional ventilation distribution by EIT, as verified versus 4DCT. Furthermore, the RMSE of anteroposterior ventilation profiles decreased from 2.53±0.62% to 1.67±0.49% while correlation increased from 0.77 to 0.89 after embedding anatomical information into the reconstruction models. In conclusion, the present work reveals that anatomically enhanced EIT-image reconstruction is superior to non-individualized reconstruction models, but further investigations in humans, so as to standardize reconstruction settings, is warranted. PMID:28763474

Implicit and explicit self-esteem and their reciprocal relationship with symptoms of depression and social anxiety: a longitudinal study in adolescents.

PubMed

van Tuijl, Lonneke A; de Jong, Peter J; Sportel, B Esther; de Hullu, Eva; Nauta, Maaike H

2014-03-01

A negative self-view is a prominent factor in most cognitive vulnerability models of depression and anxiety. Recently, there has been increased attention to differentiate between the implicit (automatic) and the explicit (reflective) processing of self-related evaluations. This longitudinal study aimed to test the association between implicit and explicit self-esteem and symptoms of adolescent depression and social anxiety disorder. Two complementary models were tested: the vulnerability model and the scarring effect model. Participants were 1641 first and second year pupils of secondary schools in the Netherlands. The Rosenberg Self-Esteem Scale, self-esteem Implicit Association Test and Revised Child Anxiety and Depression Scale were completed to measure explicit self-esteem, implicit self-esteem and symptoms of social anxiety disorder (SAD) and major depressive disorder (MDD), respectively, at baseline and two-year follow-up. Explicit self-esteem at baseline was associated with symptoms of MDD and SAD at follow-up. Symptomatology at baseline was not associated with explicit self-esteem at follow-up. Implicit self-esteem was not associated with symptoms of MDD or SAD in either direction. We relied on self-report measures of MDD and SAD symptomatology. Also, findings are based on a non-clinical sample. Our findings support the vulnerability model, and not the scarring effect model. The implications of these findings suggest support of an explicit self-esteem intervention to prevent increases in MDD and SAD symptomatology in non-clinical adolescents. Copyright © 2013 Elsevier Ltd. All rights reserved.

Uncertainty in spatially explicit animal dispersal models

USGS Publications Warehouse

Mooij, Wolf M.; DeAngelis, Donald L.

2003-01-01

Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

Modeling error in assessment of mammographic image features for improved computer-aided mammography training: initial experience

NASA Astrophysics Data System (ADS)

Mazurowski, Maciej A.; Tourassi, Georgia D.

2011-03-01

In this study we investigate the hypothesis that there exist patterns in erroneous assessment of BI-RADS image features among radiology trainees when performing diagnostic interpretation of mammograms. We also investigate whether these error making patterns can be captured by individual user models. To test our hypothesis we propose a user modeling algorithm that uses the previous readings of a trainee to identify whether certain BI-RADS feature values (e.g. "spiculated" value for "margin" feature) are associated with higher than usual likelihood that the feature will be assessed incorrectly. In our experiments we used readings of 3 radiology residents and 7 breast imaging experts for 33 breast masses for the following BI-RADS features: parenchyma density, mass margin, mass shape and mass density. The expert readings were considered as the gold standard. Rule-based individual user models were developed and tested using the leave one-one-out crossvalidation scheme. Our experimental evaluation showed that the individual user models are accurate in identifying cases for which errors are more likely to be made. The user models captured regularities in error making for all 3 residents. This finding supports our hypothesis about existence of individual error making patterns in assessment of mammographic image features using the BI-RADS lexicon. Explicit user models identifying the weaknesses of each resident could be of great use when developing and adapting a personalized training plan to meet the resident's individual needs. Such approach fits well with the framework of adaptive computer-aided educational systems in mammography we have proposed before.

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theoretically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.

Biodiversity matters in feedbacks between climate change and air quality: a study using an individual-based model.

PubMed

Wang, Bin; Shuman, Jacquelyn; Shugart, Herman H; Lerdau, Manuel T

2018-03-30

Air quality is closely associated with climate change via the biosphere because plants release large quantities of volatile organic compounds (VOC) that mediate both gaseous pollutants and aerosol dynamics. Earlier studies, which considered only leaf physiology and simply scale up from leaf-level enhancements of emissions, suggest that climate warming enhances whole forest VOC emissions, and these increased VOC emissions aggravate ozone pollution and secondary organic aerosol formation. Using an individual-based forest VOC emissions model, UVAFME-VOC, that simulates system-level emissions by explicitly simulating forest community dynamics to the individual tree level, ecological competition among the individuals of differing size and age, and radiative transfer and leaf function through the canopy, we find that climate warming only sometimes stimulates isoprene emissions (the single largest source of non-methane hydrocarbon) in a southeastern U.S. forest. These complex patterns result from the combination of higher temperatures' stimulating emissions at the leaf level but decreasing the abundance of isoprene-emitting taxa at the community level by causing a decline in the abundance of isoprene-emitting species (Quercus spp.). This ecological effect eventually outweighs the physiological one, thus reducing overall emissions. Such reduced emissions have far-reaching implications for the climate-air-quality relationships that have been established on the paradigm of warming-enhancement VOC emissions from vegetation. This local scale modeling study suggests that community ecology rather than only individual physiology should be integrated into future studies of biosphere-climate-chemistry interactions. © 2018 by the Ecological Society of America.

Testing the role of reward and punishment sensitivity in avoidance behavior: a computational modeling approach

PubMed Central

Sheynin, Jony; Moustafa, Ahmed A.; Beck, Kevin D.; Servatius, Richard J.; Myers, Catherine E.

2015-01-01

Exaggerated avoidance behavior is a predominant symptom in all anxiety disorders and its degree often parallels the development and persistence of these conditions. Both human and non-human animal studies suggest that individual differences as well as various contextual cues may impact avoidance behavior. Specifically, we have recently shown that female sex and inhibited temperament, two anxiety vulnerability factors, are associated with greater duration and rate of the avoidance behavior, as demonstrated on a computer-based task closely related to common rodent avoidance paradigms. We have also demonstrated that avoidance is attenuated by the administration of explicit visual signals during “non-threat” periods (i.e., safety signals). Here, we use a reinforcement-learning network model to investigate the underlying mechanisms of these empirical findings, with a special focus on distinct reward and punishment sensitivities. Model simulations suggest that sex and inhibited temperament are associated with specific aspects of these sensitivities. Specifically, differences in relative sensitivity to reward and punishment might underlie the longer avoidance duration demonstrated by females, whereas higher sensitivity to punishment might underlie the higher avoidance rate demonstrated by inhibited individuals. Simulations also suggest that safety signals attenuate avoidance behavior by strengthening the competing approach response. Lastly, several predictions generated by the model suggest that extinction-based cognitive-behavioral therapies might benefit from the use of safety signals, especially if given to individuals with high reward sensitivity and during longer safe periods. Overall, this study is the first to suggest cognitive mechanisms underlying the greater avoidance behavior observed in healthy individuals with different anxiety vulnerabilities. PMID:25639540

Towards an explicit account of implicit learning.

PubMed

Forkstam, Christian; Petersson, Karl Magnus

2005-08-01

The human brain supports acquisition mechanisms that can extract structural regularities implicitly from experience without the induction of an explicit model. Reber defined the process by which an individual comes to respond appropriately to the statistical structure of the input ensemble as implicit learning. He argued that the capacity to generalize to new input is based on the acquisition of abstract representations that reflect underlying structural regularities in the acquisition input. We focus this review of the implicit learning literature on studies published during 2004 and 2005. We will not review studies of repetition priming ('implicit memory'). Instead we focus on two commonly used experimental paradigms: the serial reaction time task and artificial grammar learning. Previous comprehensive reviews can be found in Seger's 1994 article and the Handbook of Implicit Learning. Emerging themes include the interaction between implicit and explicit processes, the role of the medial temporal lobe, developmental aspects of implicit learning, age-dependence, the role of sleep and consolidation. The attempts to characterize the interaction between implicit and explicit learning are promising although not well understood. The same can be said about the role of sleep and consolidation. Despite the fact that lesion studies have relatively consistently suggested that the medial temporal lobe memory system is not necessary for implicit learning, a number of functional magnetic resonance studies have reported medial temporal lobe activation in implicit learning. This issue merits further research. Finally, the clinical relevance of implicit learning remains to be determined.

Developing and testing a global-scale regression model to quantify mean annual streamflow

NASA Astrophysics Data System (ADS)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Hendriks, A. Jan; Beusen, Arthur H. W.; Clavreul, Julie; King, Henry; Schipper, Aafke M.

2017-01-01

Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process-based global hydrological models.

Ensemble Simulations with Coupled Atmospheric Dynamic and Dispersion Models: Illustrating Uncertainties in Dosage Simulations.

NASA Astrophysics Data System (ADS)

Warner, Thomas T.; Sheu, Rong-Shyang; Bowers, James F.; Sykes, R. Ian; Dodd, Gregory C.; Henn, Douglas S.

2002-05-01

Ensemble simulations made using a coupled atmospheric dynamic model and a probabilistic Lagrangian puff dispersion model were employed in a forensic analysis of the transport and dispersion of a toxic gas that may have been released near Al Muthanna, Iraq, during the Gulf War. The ensemble study had two objectives, the first of which was to determine the sensitivity of the calculated dosage fields to the choices that must be made about the configuration of the atmospheric dynamic model. In this test, various choices were used for model physics representations and for the large-scale analyses that were used to construct the model initial and boundary conditions. The second study objective was to examine the dispersion model's ability to use ensemble inputs to predict dosage probability distributions. Here, the dispersion model was used with the ensemble mean fields from the individual atmospheric dynamic model runs, including the variability in the individual wind fields, to generate dosage probabilities. These are compared with the explicit dosage probabilities derived from the individual runs of the coupled modeling system. The results demonstrate that the specific choices made about the dynamic-model configuration and the large-scale analyses can have a large impact on the simulated dosages. For example, the area near the source that is exposed to a selected dosage threshold varies by up to a factor of 4 among members of the ensemble. The agreement between the explicit and ensemble dosage probabilities is relatively good for both low and high dosage levels. Although only one ensemble was considered in this study, the encouraging results suggest that a probabilistic dispersion model may be of value in quantifying the effects of uncertainties in a dynamic-model ensemble on dispersion model predictions of atmospheric transport and dispersion.

Five challenges for spatial epidemic models.

PubMed

Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter

2015-03-01

Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sattison, M.B.; Blackman, H.S.; Novack, S.D.

The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methods, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3)more » enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sattison, M.B.; Blackman, H.S.; Novack, S.D.

The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methodology, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3)more » enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements.« less

Quantum mechanical force field for hydrogen fluoride with explicit electronic polarization.

PubMed

Mazack, Michael J M; Gao, Jiali

2014-05-28

The explicit polarization (X-Pol) theory is a fragment-based quantum chemical method that explicitly models the internal electronic polarization and intermolecular interactions of a chemical system. X-Pol theory provides a framework to construct a quantum mechanical force field, which we have extended to liquid hydrogen fluoride (HF) in this work. The parameterization, called XPHF, is built upon the same formalism introduced for the XP3P model of liquid water, which is based on the polarized molecular orbital (PMO) semiempirical quantum chemistry method and the dipole-preserving polarization consistent point charge model. We introduce a fluorine parameter set for PMO, and find good agreement for various gas-phase results of small HF clusters compared to experiments and ab initio calculations at the M06-2X/MG3S level of theory. In addition, the XPHF model shows reasonable agreement with experiments for a variety of structural and thermodynamic properties in the liquid state, including radial distribution functions, interaction energies, diffusion coefficients, and densities at various state points.

Poisson point process modeling for polyphonic music transcription.

PubMed

Peeling, Paul; Li, Chung-fai; Godsill, Simon

2007-04-01

Peaks detected in the frequency domain spectrum of a musical chord are modeled as realizations of a nonhomogeneous Poisson point process. When several notes are superimposed to make a chord, the processes for individual notes combine to give another Poisson process, whose likelihood is easily computable. This avoids a data association step linking individual harmonics explicitly with detected peaks in the spectrum. The likelihood function is ideal for Bayesian inference about the unknown note frequencies in a chord. Here, maximum likelihood estimation of fundamental frequencies shows very promising performance on real polyphonic piano music recordings.

Linear mixed model for heritability estimation that explicitly addresses environmental variation.

PubMed

Heckerman, David; Gurdasani, Deepti; Kadie, Carl; Pomilla, Cristina; Carstensen, Tommy; Martin, Hilary; Ekoru, Kenneth; Nsubuga, Rebecca N; Ssenyomo, Gerald; Kamali, Anatoli; Kaleebu, Pontiano; Widmer, Christian; Sandhu, Manjinder S

2016-07-05

The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects-one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of "missing heritability" in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.

Spatial effects, sampling errors, and task specialization in the honey bee.

PubMed

Johnson, B R

2010-05-01

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists.

Spatially explicit models for inference about density in unmarked or partially marked populations

USGS Publications Warehouse

Chandler, Richard B.; Royle, J. Andrew

2013-01-01

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.

The scaling of geographic ranges: implications for species distribution models

USGS Publications Warehouse

Yackulic, Charles B.; Ginsberg, Joshua R.

2016-01-01

There is a need for timely science to inform policy and management decisions; however, we must also strive to provide predictions that best reflect our understanding of ecological systems. Species distributions evolve through time and reflect responses to environmental conditions that are mediated through individual and population processes. Species distribution models that reflect this understanding, and explicitly model dynamics, are likely to give more accurate predictions.

Visuomotor adaptation in head-mounted virtual reality versus conventional training

PubMed Central

Anglin, J. M.; Sugiyama, T.; Liew, S.-L.

2017-01-01

Immersive, head-mounted virtual reality (HMD-VR) provides a unique opportunity to understand how changes in sensory environments affect motor learning. However, potential differences in mechanisms of motor learning and adaptation in HMD-VR versus a conventional training (CT) environment have not been extensively explored. Here, we investigated whether adaptation on a visuomotor rotation task in HMD-VR yields similar adaptation effects in CT and whether these effects are achieved through similar mechanisms. Specifically, recent work has shown that visuomotor adaptation may occur via both an implicit, error-based internal model and a more cognitive, explicit strategic component. We sought to measure both overall adaptation and balance between implicit and explicit mechanisms in HMD-VR versus CT. Twenty-four healthy individuals were placed in either HMD-VR or CT and trained on an identical visuomotor adaptation task that measured both implicit and explicit components. Our results showed that the overall timecourse of adaption was similar in both HMD-VR and CT. However, HMD-VR participants utilized a greater cognitive strategy than CT, while CT participants engaged in greater implicit learning. These results suggest that while both conditions produce similar results in overall adaptation, the mechanisms by which visuomotor adaption occurs in HMD-VR appear to be more reliant on cognitive strategies. PMID:28374808

RY-Coding and Non-Homogeneous Models Can Ameliorate the Maximum-Likelihood Inferences From Nucleotide Sequence Data with Parallel Compositional Heterogeneity.

PubMed

Ishikawa, Sohta A; Inagaki, Yuji; Hashimoto, Tetsuo

2012-01-01

In phylogenetic analyses of nucleotide sequences, 'homogeneous' substitution models, which assume the stationarity of base composition across a tree, are widely used, albeit individual sequences may bear distinctive base frequencies. In the worst-case scenario, a homogeneous model-based analysis can yield an artifactual union of two distantly related sequences that achieved similar base frequencies in parallel. Such potential difficulty can be countered by two approaches, 'RY-coding' and 'non-homogeneous' models. The former approach converts four bases into purine and pyrimidine to normalize base frequencies across a tree, while the heterogeneity in base frequency is explicitly incorporated in the latter approach. The two approaches have been applied to real-world sequence data; however, their basic properties have not been fully examined by pioneering simulation studies. Here, we assessed the performances of the maximum-likelihood analyses incorporating RY-coding and a non-homogeneous model (RY-coding and non-homogeneous analyses) on simulated data with parallel convergence to similar base composition. Both RY-coding and non-homogeneous analyses showed superior performances compared with homogeneous model-based analyses. Curiously, the performance of RY-coding analysis appeared to be significantly affected by a setting of the substitution process for sequence simulation relative to that of non-homogeneous analysis. The performance of a non-homogeneous analysis was also validated by analyzing a real-world sequence data set with significant base heterogeneity.

Allowing macroalgae growth forms to emerge: Use of an agent-based model to understand the growth and spread of macroalgae in Florida coral reefs, with emphasis on Halimeda tuna

USGS Publications Warehouse

Yniguez, A.T.; McManus, J.W.; DeAngelis, D.L.

2008-01-01

The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an 'individual' being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns. ?? 2008 Elsevier B.V.

Assessment of the GECKO-A Modeling Tool and Simplified 3D Model Parameterizations for SOA Formation

NASA Astrophysics Data System (ADS)

Aumont, B.; Hodzic, A.; La, S.; Camredon, M.; Lannuque, V.; Lee-Taylor, J. M.; Madronich, S.

2014-12-01

Explicit chemical mechanisms aim to embody the current knowledge of the transformations occurring in the atmosphere during the oxidation of organic matter. These explicit mechanisms are therefore useful tools to explore the fate of organic matter during its tropospheric oxidation and examine how these chemical processes shape the composition and properties of the gaseous and the condensed phases. Furthermore, explicit mechanisms provide powerful benchmarks to design and assess simplified parameterizations to be included 3D model. Nevertheless, the explicit mechanism describing the oxidation of hydrocarbons with backbones larger than few carbon atoms involves millions of secondary organic compounds, far exceeding the size of chemical mechanisms that can be written manually. Data processing tools can however be designed to overcome these difficulties and automatically generate consistent and comprehensive chemical mechanisms on a systematic basis. The Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) has been developed for the automatic writing of explicit chemical schemes of organic species and their partitioning between the gas and condensed phases. GECKO-A can be viewed as an expert system that mimics the steps by which chemists might develop chemical schemes. GECKO-A generates chemical schemes according to a prescribed protocol assigning reaction pathways and kinetics data on the basis of experimental data and structure-activity relationships. In its current version, GECKO-A can generate the full atmospheric oxidation scheme for most linear, branched and cyclic precursors, including alkanes and alkenes up to C25. Assessments of the GECKO-A modeling tool based on chamber SOA observations will be presented. GECKO-A was recently used to design a parameterization for SOA formation based on a Volatility Basis Set (VBS) approach. First results will be presented.

Moving forward socio-economically focused models of deforestation.

PubMed

Dezécache, Camille; Salles, Jean-Michel; Vieilledent, Ghislain; Hérault, Bruno

2017-09-01

Whilst high-resolution spatial variables contribute to a good fit of spatially explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision-making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio-economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub-models of deforestation intensity based on socio-economic variables, we were able to create a map of predicted deforestation over the period 2001-2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approximately 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio-economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterization of socio-economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio-economic processes in the models. Whilst considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio-economic and political contexts influencing deforestation trends, this explicit characterization of the socio-economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects. © 2017 John Wiley & Sons Ltd.

Fast and accurate focusing analysis of large photon sieve using pinhole ring diffraction model.

PubMed

Liu, Tao; Zhang, Xin; Wang, Lingjie; Wu, Yanxiong; Zhang, Jizhen; Qu, Hemeng

2015-06-10

In this paper, we developed a pinhole ring diffraction model for the focusing analysis of a large photon sieve. Instead of analyzing individual pinholes, we discuss the focusing of all of the pinholes in a single ring. An explicit equation for the diffracted field of individual pinhole ring has been proposed. We investigated the validity range of this generalized model and analytically describe the sufficient conditions for the validity of this pinhole ring diffraction model. A practical example and investigation reveals the high accuracy of the pinhole ring diffraction model. This simulation method could be used for fast and accurate focusing analysis of a large photon sieve.

Explicit filtering in large eddy simulation using a discontinuous Galerkin method

NASA Astrophysics Data System (ADS)

Brazell, Matthew J.

The discontinuous Galerkin (DG) method is a formulation of the finite element method (FEM). DG provides the ability for a high order of accuracy in complex geometries, and allows for highly efficient parallelization algorithms. These attributes make the DG method attractive for solving the Navier-Stokes equations for large eddy simulation (LES). The main goal of this work is to investigate the feasibility of adopting an explicit filter in the numerical solution of the Navier-Stokes equations with DG. Explicit filtering has been shown to increase the numerical stability of under-resolved simulations and is needed for LES with dynamic sub-grid scale (SGS) models. The explicit filter takes advantage of DG's framework where the solution is approximated using a polyno- mial basis where the higher modes of the solution correspond to a higher order polynomial basis. By removing high order modes, the filtered solution contains low order frequency content much like an explicit low pass filter. The explicit filter implementation is tested on a simple 1-D solver with an initial condi- tion that has some similarity to turbulent flows. The explicit filter does restrict the resolution as well as remove accumulated energy in the higher modes from aliasing. However, the ex- plicit filter is unable to remove numerical errors causing numerical dissipation. A second test case solves the 3-D Navier-Stokes equations of the Taylor-Green vortex flow (TGV). The TGV is useful for SGS model testing because it is initially laminar and transitions into a fully turbulent flow. The SGS models investigated include the constant coefficient Smagorinsky model, dynamic Smagorinsky model, and dynamic Heinz model. The constant coefficient Smagorinsky model is over dissipative, this is generally not desirable however it does add stability. The dynamic Smagorinsky model generally performs better, especially during the laminar-turbulent transition region as expected. The dynamic Heinz model which is based on an improved model, handles the laminar-turbulent transition region well while also showing additional robustness.

Estimating carnivore community structures

PubMed Central

Jiménez, José; Nuñez-Arjona, Juan Carlos; Rueda, Carmen; González, Luis Mariano; García-Domínguez, Francisco; Muñoz-Igualada, Jaime; López-Bao, José Vicente

2017-01-01

Obtaining reliable estimates of the structure of carnivore communities is of paramount importance because of their ecological roles, ecosystem services and impact on biodiversity conservation, but they are still scarce. This information is key for carnivore management: to build support for and acceptance of management decisions and policies it is crucial that those decisions are based on robust and high quality information. Here, we combined camera and live-trapping surveys, as well as telemetry data, with spatially-explicit Bayesian models to show the usefulness of an integrated multi-method and multi-model approach to monitor carnivore community structures. Our methods account for imperfect detection and effectively deal with species with non-recognizable individuals. In our Mediterranean study system, the terrestrial carnivore community was dominated by red foxes (0.410 individuals/km2); Egyptian mongooses, feral cats and stone martens were similarly abundant (0.252, 0.249 and 0.240 individuals/km2, respectively), whereas badgers and common genets were the least common (0.130 and 0.087 individuals/km2, respectively). The precision of density estimates improved by incorporating multiple covariates, device operation, and accounting for the removal of individuals. The approach presented here has substantial implications for decision-making since it allows, for instance, the evaluation, in a standard and comparable way, of community responses to interventions. PMID:28120871

A watershed-based spatially-explicit demonstration of an integrated environmental modeling framework for ecosystem services in the Coal River Basin (WV, USA)

Treesearch

John M. Johnston; Mahion C. Barber; Kurt Wolfe; Mike Galvin; Mike Cyterski; Rajbir Parmar; Luis Suarez

2016-01-01

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, ...

From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality

PubMed Central

Kreft, Jan-Ulrich; Plugge, Caroline M.; Prats, Clara; Leveau, Johan H. J.; Zhang, Weiwen; Hellweger, Ferdi L.

2017-01-01

Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy. PMID:29230200

The relative effects of habitat loss and fragmentation on population genetic variation in the red-cockaded woodpecker (Picoides borealis).

PubMed

Bruggeman, Douglas J; Wiegand, Thorsten; Fernández, Néstor

2010-09-01

The relative influence of habitat loss, fragmentation and matrix heterogeneity on the viability of populations is a critical area of conservation research that remains unresolved. Using simulation modelling, we provide an analysis of the influence both patch size and patch isolation have on abundance, effective population size (N(e)) and F(ST). An individual-based, spatially explicit population model based on 15 years of field work on the red-cockaded woodpecker (Picoides borealis) was applied to different landscape configurations. The variation in landscape patterns was summarized using spatial statistics based on O-ring statistics. By regressing demographic and genetics attributes that emerged across the landscape treatments against proportion of total habitat and O-ring statistics, we show that O-ring statistics provide an explicit link between population processes, habitat area, and critical thresholds of fragmentation that affect those processes. Spatial distances among land cover classes that affect biological processes translated into critical scales at which the measures of landscape structure correlated best with genetic indices. Therefore our study infers pattern from process, which contrasts with past studies of landscape genetics. We found that population genetic structure was more strongly affected by fragmentation than population size, which suggests that examining only population size may limit recognition of fragmentation effects that erode genetic variation. If effective population size is used to set recovery goals for endangered species, then habitat fragmentation effects may be sufficiently strong to prevent evaluation of recovery based on the ratio of census:effective population size alone.

Assessing hypotheses about nesting site occupancy dynamics

USGS Publications Warehouse

Bled, Florent; Royle, J. Andrew; Cam, Emmanuelle

2011-01-01

Hypotheses about habitat selection developed in the evolutionary ecology framework assume that individuals, under some conditions, select breeding habitat based on expected fitness in different habitat. The relationship between habitat quality and fitness may be reflected by breeding success of individuals, which may in turn be used to assess habitat quality. Habitat quality may also be assessed via local density: if high-quality sites are preferentially used, high density may reflect high-quality habitat. Here we assessed whether site occupancy dynamics vary with site surrogates for habitat quality. We modeled nest site use probability in a seabird subcolony (the Black-legged Kittiwake, Rissa tridactyla) over a 20-year period. We estimated site persistence (an occupied site remains occupied from time t to t + 1) and colonization through two subprocesses: first colonization (site creation at the timescale of the study) and recolonization (a site is colonized again after being deserted). Our model explicitly incorporated site-specific and neighboring breeding success and conspecific density in the neighborhood. Our results provided evidence that reproductively "successful'' sites have a higher persistence probability than "unsuccessful'' ones. Analyses of site fidelity in marked birds and of survival probability showed that high site persistence predominantly reflects site fidelity, not immediate colonization by new owners after emigration or death of previous owners. There is a negative quadratic relationship between local density and persistence probability. First colonization probability decreases with density, whereas recolonization probability is constant. This highlights the importance of distinguishing initial colonization and recolonization to understand site occupancy. All dynamics varied positively with neighboring breeding success. We found evidence of a positive interaction between site-specific and neighboring breeding success. We addressed local population dynamics using a site occupancy approach integrating hypotheses developed in behavioral ecology to account for individual decisions. This allows development of models of population and metapopulation dynamics that explicitly incorporate ecological and evolutionary processes.

Spatial processes decouple management from objectives in a heterogeneous landscape: predator control as a case study.

PubMed

Mahoney, Peter J; Young, Julie K; Hersey, Kent R; Larsen, Randy T; McMillan, Brock R; Stoner, David C

2018-04-01

Predator control is often implemented with the intent of disrupting top-down regulation in sensitive prey populations. However, ambiguity surrounding the efficacy of predator management, as well as the strength of top-down effects of predators in general, is often exacerbated by the spatially implicit analytical approaches used in assessing data with explicit spatial structure. Here, we highlight the importance of considering spatial context in the case of a predator control study in south-central Utah. We assessed the spatial match between aerial removal risk in coyotes (Canis latrans) and mule deer (Odocoileus hemionus) resource selection during parturition using a spatially explicit, multi-level Bayesian model. With our model, we were able to evaluate spatial congruence between management action (i.e., coyote removal) and objective (i.e., parturient deer site selection) at two distinct scales: the level of the management unit and the individual coyote removal. In the case of the former, our results indicated substantial spatial heterogeneity in expected congruence between removal risk and parturient deer site selection across large areas, and is a reflection of logistical constraints acting on the management strategy and differences in space use between the two species. At the level of the individual removal, we demonstrated that the potential management benefits of a removed coyote were highly variable across all individuals removed and in many cases, spatially distinct from parturient deer resource selection. Our methods and results provide a means of evaluating where we might anticipate an impact of predator control, while emphasizing the need to weight individual removals based on spatial proximity to management objectives in any assessment of large-scale predator control. Although we highlight the importance of spatial context in assessments of predator control strategy, we believe our methods are readily generalizable in any management or large-scale experimental framework where spatial context is likely an important driver of outcomes. © 2018 by the Ecological Society of America.

Effects of Utterance Length on Lip Kinematics in Aphasia

ERIC Educational Resources Information Center

Bose, Arpita; van Lieshout, Pascal

2008-01-01

Most existing models of language production and speech motor control do not explicitly address how language requirements affect speech motor functions, as these domains are usually treated as separate and independent from one another. This investigation compared lip movements during bilabial closure between five individuals with mild aphasia and…

Algorithmic Modeling of Social Interactions Over Networks

DTIC Science & Technology

2015-10-10

reviewed by Pro- ceedings of the 9th International Conference on Web and Internet Eco- nomics: ( WINE 2013). • L.Coviello, Y. Sohn, A. Kramer, C. Marlow, M...explicit the benefits of the technology to a broad population. A subtle marketing campaign may communicate the technology’s individual-level value without

Evidence-based neurosurgery

PubMed Central

Esene, Ignatius N.; Baeesa, Saleh S.; Ammar, Ahmed

2016-01-01

Medical evidence is obtainable from approaches, which might be descriptive, analytic and integrative and ranked into levels of evidence, graded according to quality and summarized into strengths of recommendation. Sources of evidence range from expert opinions through well-randomized control trials to meta-analyses. The conscientious, explicit, and judicious use of current best evidence in making decisions related to the care of individual patients defines the concept of evidence-based neurosurgery (EBN). We reviewed reference books of clinical epidemiology, evidence-based practice and other previously related articles addressing principles of evidence-based practice in neurosurgery. Based on existing theories and models and our cumulative years of experience and expertise conducting research and promoting EBN, we have synthesized and presented a holistic overview of the concept of EBN. We have also underscored the importance of clinical research and its relationship to EBN. Useful electronic resources are provided. The concept of critical appraisal is introduced. PMID:27356649

Minimizing Erosion and Agro-Pollutants Transport from Furrow Irrigated Fields to the Nearby Water Body Using Spatially-Explicit Agent Based Model and Decision Optimization Platform

NASA Astrophysics Data System (ADS)

Ghoveisi, H.; Al Dughaishi, U.; Kiker, G.

2017-12-01

Maintaining water quality in agricultural watersheds is a worldwide challenge, especially where furrow irrigation is being practiced. The Yakima River Basin watershed in south central Washington State, (USA) is an example of these impacted areas with elevated load of sediments and other agricultural products due to runoff from furrow-irrigated fields. Within the Yakima basin, the Granger Drain watershed (area of 75 km2) is particularly challenged in this regard with more than 400 flood-irrigated individual parcels (area of 21 km2) growing a variety of crops from maize to grapes. Alternatives for improving water quality from furrow-irrigated parcels include vegetated filter strip (VFS) implementation, furrow water application efficiency, polyacrylamide (PAM) application and irrigation scheduling. These alternatives were simulated separately and in combinations to explore potential Best Management Practices (BMPs) for runoff-related-pollution reduction in a spatially explicit, agent based modeling system (QnD:GrangerDrain). Two regulatory scenarios were tested to BMP adoption within individual parcels. A blanket-style regulatory scenario simulated a total of 60 BMP combinations implemented in all 409 furrow-irrigated parcels. A second regulatory scenario simulated the BMPs in 119 furrow-irrigated parcels designated as "hotspots" based on a standard 12 Mg ha-1 seasonal sediment load. The simulated cumulative runoff and sediment loading from all BMP alternatives were ranked using Multiple Criteria Decision Analysis (MCDA), specifically the Stochastic Multi-Attribute Acceptability Analysis (SMAA) method. Several BMP combinations proved successful in reducing loads below a 25 NTU (91 mg L-1) regulatory sediment concentration. The QnD:GrangerDrain simulations and subsequent MCDA ranking revealed that the BMP combinations of 5 m-VFS and high furrow water efficiency were highly ranked alternatives for both the blanket and hotspot scenarios.

Hierarchical modeling of cluster size in wildlife surveys

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data

USGS Publications Warehouse

Dorazio, Robert M.

2013-01-01

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.

Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data.

PubMed

Dorazio, Robert M

2013-01-01

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar - and often identical - inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.

Enhancing community based health programs in Iran: a multi-objective location-allocation model.

PubMed

Khodaparasti, S; Maleki, H R; Jahedi, S; Bruni, M E; Beraldi, P

2017-12-01

Community Based Organizations (CBOs) are important health system stakeholders with the mission of addressing the social and economic needs of individuals and groups in a defined geographic area, usually no larger than a county. The access and success efforts of CBOs vary, depending on the integration between health care providers and CBOs but also in relation to the community participation level. To achieve widespread results, it is important to carefully design an efficient network which can serve as a bridge between the community and the health care system. This study addresses this challenge through a location-allocation model that deals with the hierarchical nature of the system explicitly. To reflect social welfare concerns of equity, local accessibility, and efficiency, we develop the model in a multi-objective framework, capturing the ambiguity in the decision makers' aspiration levels through a fuzzy goal programming approach. This study reports the findings for the real case of Shiraz city, Fars province, Iran, obtained by a thorough analysis of the results.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India.

PubMed

Sarkar, Mriganka Shekhar; Krishnamurthy, Ramesh; Johnson, Jeyaraj A; Sen, Subharanjan; Saha, Goutam Kumar

2017-01-01

Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals' ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger ( Panthera tigris ), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly's selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D 2 method and the Boyce index. There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models

NASA Astrophysics Data System (ADS)

Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea

2014-05-01

Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.

Monitoring gray wolf populations using multiple survey methods

USGS Publications Warehouse

Ausband, David E.; Rich, Lindsey N.; Glenn, Elizabeth M.; Mitchell, Michael S.; Zager, Pete; Miller, David A.W.; Waits, Lisette P.; Ackerman, Bruce B.; Mack, Curt M.

2013-01-01

The behavioral patterns and large territories of large carnivores make them challenging to monitor. Occupancy modeling provides a framework for monitoring population dynamics and distribution of territorial carnivores. We combined data from hunter surveys, howling and sign surveys conducted at predicted wolf rendezvous sites, and locations of radiocollared wolves to model occupancy and estimate the number of gray wolf (Canis lupus) packs and individuals in Idaho during 2009 and 2010. We explicitly accounted for potential misidentification of occupied cells (i.e., false positives) using an extension of the multi-state occupancy framework. We found agreement between model predictions and distribution and estimates of number of wolf packs and individual wolves reported by Idaho Department of Fish and Game and Nez Perce Tribe from intensive radiotelemetry-based monitoring. Estimates of individual wolves from occupancy models that excluded data from radiocollared wolves were within an average of 12.0% (SD = 6.0) of existing statewide minimum counts. Models using only hunter survey data generally estimated the lowest abundance, whereas models using all data generally provided the highest estimates of abundance, although only marginally higher. Precision across approaches ranged from 14% to 28% of mean estimates and models that used all data streams generally provided the most precise estimates. We demonstrated that an occupancy model based on different survey methods can yield estimates of the number and distribution of wolf packs and individual wolf abundance with reasonable measures of precision. Assumptions of the approach including that average territory size is known, average pack size is known, and territories do not overlap, must be evaluated periodically using independent field data to ensure occupancy estimates remain reliable. Use of multiple survey methods helps to ensure that occupancy estimates are robust to weaknesses or changes in any 1 survey method. Occupancy modeling may be useful for standardizing estimates across large landscapes, even if survey methods differ across regions, allowing for inferences about broad-scale population dynamics of wolves.

Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells.

PubMed

Macfarlane, Fiona R; Lorenzi, Tommaso; Chaplain, Mark A J

2018-06-01

A growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour-immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells.

Brain response to masked and unmasked facial emotions as a function of implicit and explicit personality self-concept of extraversion.

PubMed

Suslow, Thomas; Kugel, Harald; Lindner, Christian; Dannlowski, Udo; Egloff, Boris

2017-01-06

Extraversion-introversion is a personality dimension referring to individual differences in social behavior. In the past, neurobiological research on extraversion was almost entirely based upon questionnaires which inform about the explicit self-concept. Today, indirect measures are available that tap into the implicit self-concept of extraversion which is assumed to result from automatic processing functions. In our study, brain activation while viewing facial expression of affiliation relevant (i.e., happiness, and disgust) and irrelevant (i.e., fear) emotions was examined as a function of the implicit and explicit self-concept of extraversion and processing mode (automatic vs. controlled). 40 healthy volunteers watched blocks of masked and unmasked emotional faces while undergoing functional magnetic resonance imaging. The Implicit Association Test and the NEO Five-Factor Inventory were applied as implicit and explicit measures of extraversion which were uncorrelated in our sample. Implicit extraversion was found to be positively associated with neural response to masked happy faces in the thalamus and temporo-parietal regions and to masked disgust faces in cerebellar areas. Moreover, it was positively correlated with brain response to unmasked disgust faces in the amygdala and cortical areas. Explicit extraversion was not related to brain response to facial emotions when controlling trait anxiety. The implicit compared to the explicit self-concept of extraversion seems to be more strongly associated with brain activation not only during automatic but also during controlled processing of affiliation relevant facial emotions. Enhanced neural response to facial disgust could reflect high sensitivity to signals of interpersonal rejection in extraverts (i.e., individuals with affiliative tendencies). Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Modeling the growth of individuals in plant populations: local density variation in a strand population of Xanthium strumarium (Asteraceae).

PubMed

Weiner, J; Kinsman, S; Williams, S

1998-11-01

We studied the growth of individual Xanthium strumarium plants growing at four naturally occurring local densities on a beach in Maine: (1) isolated plants, (2) pairs of plants ≤1 cm apart, (3) four plants within 4 cm of each other, and (4) discrete dense clumps of 10-39 plants. A combination of nondestructive measurements every 2 wk and parallel calibration harvests provided very good estimates of the growth in aboveground biomass of over 400 individual plants over 8 wk and afforded the opportunity to fit explicit growth models to 293 of them. There was large individual variation in growth and resultant size within the population and within all densities. Local crowding played a role in determining plant size within the population: there were significant differences in final size between all densities except pairs and quadruples, which were almost identical. Overall, plants growing at higher densities were more variable in growth and final size than plants growing at lower densities, but this was due to increased variation among groups (greater variation in local density and/or greater environmental heterogeneity), not to increased variation within groups. Thus, there was no evidence of size asymmetric competition in this population. The growth of most plants was close to exponential over the study period, but half the plants were slightly better fit by a sigmoidal (logistic) model. The proportion of plants better fit by the logistic model increased with density and with initial plant size. The use of explicit growth models over several growth intervals to describe stand development can provide more biological content and more statistical power than "growth-size" methods that analyze growth intervals separately.

Analytical Modelling of the Spread of Disease in Confined and Crowded Spaces

NASA Astrophysics Data System (ADS)

Goscé, Lara; Barton, David A. W.; Johansson, Anders

2014-05-01

Since 1927 and until recently, most models describing the spread of disease have been of compartmental type, based on the assumption that populations are homogeneous and well-mixed. Recent models have utilised agent-based models and complex networks to explicitly study heterogeneous interaction patterns, but this leads to an increasing computational complexity. Compartmental models are appealing because of their simplicity, but their parameters, especially the transmission rate, are complex and depend on a number of factors, which makes it hard to predict how a change of a single environmental, demographic, or epidemiological factor will affect the population. Therefore, in this contribution we propose a middle ground, utilising crowd-behaviour research to improve compartmental models in crowded situations. We show how both the rate of infection as well as the walking speed depend on the local crowd density around an infected individual. The combined effect is that the rate of infection at a population scale has an analytically tractable non-linear dependency on crowd density. We model the spread of a hypothetical disease in a corridor and compare our new model with a typical compartmental model, which highlights the regime in which current models may not produce credible results.

Spatially Explicit Estimates of Suspended Sediment and Bedload Transport Rates for Western Oregon and Northwestern California

NASA Astrophysics Data System (ADS)

O'Connor, J. E.; Wise, D. R.; Mangano, J.; Jones, K.

2015-12-01

Empirical analyses of suspended sediment and bedload transport gives estimates of sediment flux for western Oregon and northwestern California. The estimates of both bedload and suspended load are from regression models relating measured annual sediment yield to geologic, physiographic, and climatic properties of contributing basins. The best models include generalized geology and either slope or precipitation. The best-fit suspended-sediment model is based on basin geology, precipitation, and area of recent wildfire. It explains 65% of the variance for 68 suspended sediment measurement sites within the model area. Predicted suspended sediment yields range from no yield from the High Cascades geologic province to 200 tonnes/ km2-yr in the northern Oregon Coast Range and 1000 tonnes/km2-yr in recently burned areas of the northern Klamath terrain. Bed-material yield is similarly estimated from a regression model based on 22 sites of measured bed-material transport, mostly from reservoir accumulation analyses but also from several bedload measurement programs. The resulting best-fit regression is based on basin slope and the presence/absence of the Klamath geologic terrane. For the Klamath terrane, bed-material yield is twice that of the other geologic provinces. This model explains more than 80% of the variance of the better-quality measurements. Predicted bed-material yields range up to 350 tonnes/ km2-yr in steep areas of the Klamath terrane. Applying these regressions to small individual watersheds (mean size; 66 km2 for bed-material; 3 km2 for suspended sediment) and cumulating totals down the hydrologic network (but also decreasing the bed-material flux by experimentally determined attrition rates) gives spatially explicit estimates of both bed-material and suspended sediment flux. This enables assessment of several management issues, including the effects of dams on bedload transport, instream gravel mining, habitat formation processes, and water-quality. The combined fluxes can also be compared to long-term rock uplift and cosmogenically determined landscape erosion rates.

Explicit and implicit reinforcement learning across the psychosis spectrum.

PubMed

Barch, Deanna M; Carter, Cameron S; Gold, James M; Johnson, Sheri L; Kring, Ann M; MacDonald, Angus W; Pizzagalli, Diego A; Ragland, J Daniel; Silverstein, Steven M; Strauss, Milton E

2017-07-01

Motivational and hedonic impairments are core features of a variety of types of psychopathology. An important aspect of motivational function is reinforcement learning (RL), including implicit (i.e., outside of conscious awareness) and explicit (i.e., including explicit representations about potential reward associations) learning, as well as both positive reinforcement (learning about actions that lead to reward) and punishment (learning to avoid actions that lead to loss). Here we present data from paradigms designed to assess both positive and negative components of both implicit and explicit RL, examine performance on each of these tasks among individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis, and examine their relative relationships to specific symptom domains transdiagnostically. None of the diagnostic groups differed significantly from controls on the implicit RL tasks in either bias toward a rewarded response or bias away from a punished response. However, on the explicit RL task, both the individuals with schizophrenia and schizoaffective disorder performed significantly worse than controls, but the individuals with bipolar did not. Worse performance on the explicit RL task, but not the implicit RL task, was related to worse motivation and pleasure symptoms across all diagnostic categories. Performance on explicit RL, but not implicit RL, was related to working memory, which accounted for some of the diagnostic group differences. However, working memory did not account for the relationship of explicit RL to motivation and pleasure symptoms. These findings suggest transdiagnostic relationships across the spectrum of psychotic disorders between motivation and pleasure impairments and explicit RL. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Simple model of epidemics with pathogen mutation.

PubMed

Girvan, Michelle; Callaway, Duncan S; Newman, M E J; Strogatz, Steven H

2002-03-01

We study how the interplay between the memory immune response and pathogen mutation affects epidemic dynamics in two related models. The first explicitly models pathogen mutation and individual memory immune responses, with contacted individuals becoming infected only if they are exposed to strains that are significantly different from other strains in their memory repertoire. The second model is a reduction of the first to a system of difference equations. In this case, individuals spend a fixed amount of time in a generalized immune class. In both models, we observe four fundamentally different types of behavior, depending on parameters: (1) pathogen extinction due to lack of contact between individuals; (2) endemic infection; (3) periodic epidemic outbreaks; and (4) one or more outbreaks followed by extinction of the epidemic due to extremely low minima in the oscillations. We analyze both models to determine the location of each transition. Our main result is that pathogens in highly connected populations must mutate rapidly in order to remain viable.

Self-Love or Other-Love? Explicit Other-Preference but Implicit Self-Preference

PubMed Central

Gebauer, Jochen E.; Göritz, Anja S.; Hofmann, Wilhelm; Sedikides, Constantine

2012-01-01

Do humans prefer the self even over their favorite other person? This question has pervaded philosophy and social-behavioral sciences. Psychology’s distinction between explicit and implicit preferences calls for a two-tiered solution. Our evolutionarily-based Dissociative Self-Preference Model offers two hypotheses. Other-preferences prevail at an explicit level, because they convey caring for others, which strengthens interpersonal bonds–a major evolutionary advantage. Self-preferences, however, prevail at an implicit level, because they facilitate self-serving automatic behavior, which favors the self in life-or-die situations–also a major evolutionary advantage. We examined the data of 1,519 participants, who completed an explicit measure and one of five implicit measures of preferences for self versus favorite other. The results were consistent with the Dissociative Self-Preference Model. Explicitly, participants preferred their favorite other over the self. Implicitly, however, they preferred the self over their favorite other (be it their child, romantic partner, or best friend). Results are discussed in relation to evolutionary theorizing on self-deception. PMID:22848605

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André

2009-04-01

SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.

Default contagion risks in Russian interbank market

NASA Astrophysics Data System (ADS)

Leonidov, A. V.; Rumyantsev, E. L.

2016-06-01

Systemic risks of default contagion in the Russian interbank market are investigated. The analysis is based on considering the bow-tie structure of the weighted oriented graph describing the structure of the interbank loans. A probabilistic model of interbank contagion explicitly taking into account the empirical bow-tie structure reflecting functionality of the corresponding nodes (borrowers, lenders, borrowers and lenders simultaneously), degree distributions and disassortativity of the interbank network under consideration based on empirical data is developed. The characteristics of contagion-related systemic risk calculated with this model are shown to be in agreement with those of explicit stress tests.

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Beyond the Sponge Model: Encouraging Students' Questioning Skills in Abnormal Psychology.

ERIC Educational Resources Information Center

Keeley, Stuart M.; Ali, Rahan; Gebing, Tracy

1998-01-01

Argues that educators should provide students with explicit training in asking critical questions. Describes a training strategy taught in abnormal psychology courses at Bowling Green State University (Ohio). Based on a pre- and post-test, results support the promise of using explicit questioning training in promoting the evaluative aspects of…

Fully implicit Particle-in-cell algorithms for multiscale plasma simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chacon, Luis

The outline of the paper is as follows: Particle-in-cell (PIC) methods for fully ionized collisionless plasmas, explicit vs. implicit PIC, 1D ES implicit PIC (charge and energy conservation, moment-based acceleration), and generalization to Multi-D EM PIC: Vlasov-Darwin model (review and motivation for Darwin model, conservation properties (energy, charge, and canonical momenta), and numerical benchmarks). The author demonstrates a fully implicit, fully nonlinear, multidimensional PIC formulation that features exact local charge conservation (via a novel particle mover strategy), exact global energy conservation (no particle self-heating or self-cooling), adaptive particle orbit integrator to control errors in momentum conservation, and canonical momenta (EM-PICmore » only, reduced dimensionality). The approach is free of numerical instabilities: ω peΔt >> 1, and Δx >> λ D. It requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant CPU gains (vs explicit PIC) have been demonstrated. The method has much potential for efficiency gains vs. explicit in long-time-scale applications. Moment-based acceleration is effective in minimizing N FE, leading to an optimal algorithm.« less

A surface-potential-based drain current compact model for a-InGaZnO thin-film transistors in Non-Degenerate conduction regime

NASA Astrophysics Data System (ADS)

Yu, Fei; Ma, Xiaoyu; Deng, Wanling; Liou, Juin J.; Huang, Junkai

2017-11-01

A physics-based drain current compact model for amorphous InGaZnO (a-InGaZnO) thin-film transistors (TFTs) is proposed. As a key feature, the surface potential model accounts for both exponential tail and deep trap densities of states, which are essential to describe a-InGaZnO TFT electrical characteristics. The surface potential is solved explicitly without the process of amendment and suitable for circuit simulations. Furthermore, based on the surface potential, an explicit closed-form expression of the drain current is developed. For the cases of the different operational voltages, surface potential and drain current are verified by numerical results and experimental data, respectively. As a result, our model can predict DC characteristics of a-InGaZnO TFTs.

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E

2017-07-01

We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.

A second generation distributed point polarizable water model.

PubMed

Kumar, Revati; Wang, Fang-Fang; Jenness, Glen R; Jordan, Kenneth D

2010-01-07

A distributed point polarizable model (DPP2) for water, with explicit terms for charge penetration, induction, and charge transfer, is introduced. The DPP2 model accurately describes the interaction energies in small and large water clusters and also gives an average internal energy per molecule and radial distribution functions of liquid water in good agreement with experiment. A key to the success of the model is its accurate description of the individual terms in the n-body expansion of the interaction energies.

Multi-model predictive control based on LMI: from the adaptation of the state-space model to the analytic description of the control law

NASA Astrophysics Data System (ADS)

Falugi, P.; Olaru, S.; Dumur, D.

2010-08-01

This article proposes an explicit robust predictive control solution based on linear matrix inequalities (LMIs). The considered predictive control strategy uses different local descriptions of the system dynamics and uncertainties and thus allows the handling of less conservative input constraints. The computed control law guarantees constraint satisfaction and asymptotic stability. The technique is effective for a class of nonlinear systems embedded into polytopic models. A detailed discussion of the procedures which adapt the partition of the state space is presented. For the practical implementation the construction of suitable (explicit) descriptions of the control law are described upon concrete algorithms.

Structure and dynamics of human vimentin intermediate filament dimer and tetramer in explicit and implicit solvent models.

PubMed

Qin, Zhao; Buehler, Markus J

2011-01-01

Intermediate filaments, in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, and play an important role in mechanotransduction as well as in providing mechanical stability to cells at large stretch. The molecular structures, mechanical and dynamical properties of the intermediate filament basic building blocks, the dimer and the tetramer, however, have remained elusive due to persistent experimental challenges owing to the large size and fibrillar geometry of this protein. We have recently reported an atomistic-level model of the human vimentin dimer and tetramer, obtained through a bottom-up approach based on structural optimization via molecular simulation based on an implicit solvent model (Qin et al. in PLoS ONE 2009 4(10):e7294, 9). Here we present extensive simulations and structural analyses of the model based on ultra large-scale atomistic-level simulations in an explicit solvent model, with system sizes exceeding 500,000 atoms and simulations carried out at 20 ns time-scales. We report a detailed comparison of the structural and dynamical behavior of this large biomolecular model with implicit and explicit solvent models. Our simulations confirm the stability of the molecular model and provide insight into the dynamical properties of the dimer and tetramer. Specifically, our simulations reveal a heterogeneous distribution of the bending stiffness along the molecular axis with the formation of rather soft and highly flexible hinge-like regions defined by non-alpha-helical linker domains. We report a comparison of Ramachandran maps and the solvent accessible surface area between implicit and explicit solvent models, and compute the persistence length of the dimer and tetramer structure of vimentin intermediate filaments for various subdomains of the protein. Our simulations provide detailed insight into the dynamical properties of the vimentin dimer and tetramer intermediate filament building blocks, which may guide the development of novel coarse-grained models of intermediate filaments, and could also help in understanding assembly mechanisms.

Incorporating lower grade toxicity information into dose finding designs

PubMed Central

Iasonos, Alexia; Zohar, Sarah; O’Quigley, John

2012-01-01

Background Toxicity grades underlie the definition of a dose limiting toxicity (DLT) but in the majority of phase I designs, the information contained in the individual grades is not used. Some authors have argued that it may be more appropriate to consider a polytomous rather than dichotomous response. Purpose We investigate whether the added information on individual grades can improve the operating characteristics of the Continual Reassessment Method (CRM). Methods We compare the original CRM design for a binary response with two stage CRM designs which make di erent use of lower-grade toxicity information via simulations. Specifically we study; a two-stage design that utilizes lower-grade toxicities in the first stage only, during the initial non model-based escalation, and two-stage designs where lower grades are used throughout the trial via explicit models. We postulate a model relating the rates of lower grade toxicities to the rate of DLTs, or assume the relative rates of low to high grade toxicities is unknown. The designs were compared in terms of accuracy, patient allocation and precision. Results Significant gains can be achieved when using grades in the first stage of a two-stage design. Otherwise, only modest improvements are seen when the information on grades is exploited via the use of explicit models, where the parameters are known precisely. CRM with some use of grade information, increases the number of patients treated at the MTD by approximately 5%. The additional information from lower grades can lead to a small increase in the precision of our estimate of the MTD. Limitations Our comparisons are not exhaustive and it would be worth studying other models and situations. Conclusions Although, the gains in performance were not as great as we had hoped, we observed no cases where the performance of CRM was poorer. Our recommendation is that investigators might consider using graded toxicities at the design stage. PMID:21835856

UManSysProp: An online and open-source facility for molecular property prediction and atmospheric aerosol calculations

NASA Astrophysics Data System (ADS)

Topping, David; Barley, Mark; McFiggans, Gordon; Aumont, Bernard

2016-04-01

The many thousands of individual aerosol components ensure that explicit manual calculation of properties that influence their environmental impacts is laborious and time-consuming. The emergence of explicit automatic mechanism generation techniques, including up to many millions of individual gas phase products as aerosol precursors, renders manual calculations impossible and automation is necessary. It can be difficult to establish what factors are responsible for the outcome of a model prediction. This is particularly true when the number of components might be high in, for example, SOA mass partitioning simulations. It then becomes difficult for others in the community to assess the results presented. This might be complicated by the need to include pure component vapour pressures or activity coefficient predictions for a wide range of highly multifunctional compounds. It isn't clear to what extent replication of results is ever achieved for a range of aerosol simulations. Whilst this might also be an issue with results from instrumentation, the development of community driven software at least enables modellers to tackle this problem directly. Here we describe the development and application of a new web based facility, UManSysProp, to tackle such issues. Current facilities include: pure component vapour pressures, critical properties and sub-cooled densities of organic molecules; activity coefficient predictions for mixed inorganic-organic liquid systems; hygroscopic growth factors and CCN activation potential of mixed inorganic/organic aerosol particles with associated Kappa-Kohler values; absorptive partitioning calculations with/without a treatment of non-ideality. The website can be found here: http://umansysprop.seaes.manchester.ac.uk/

Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families

PubMed Central

Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert

2016-01-01

In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes. PMID:27402363

Attitudes toward Overweight Individuals among Fitness Center Employees: An Examination of Contextual Effects

ERIC Educational Resources Information Center

Dimmock, James A.; Hallett, Bree E.; Grove, J. Robert

2009-01-01

Our study assessed implicit and explicit evaluations of overweight individuals among a sample of fitness center employees (N = 70). Participants completed a general demographics questionnaire and an explicit, self-report Antifat Attitudes Test (AFAT). Participants also completed two Implicit Association Tests (IATs) to measure implicit attitudes…

Relative complexation energies for Li(+) ion in solution: molecular level solvation versus polarizable continuum model study.

PubMed

Eilmes, Andrzej; Kubisiak, Piotr

2010-01-21

Relative complexation energies for the lithium cation in acetonitrile and diethyl ether have been studied. Quantum-chemical calculations explicitly describing the solvation of Li(+) have been performed based on structures obtained from molecular dynamics simulations. The effect of an increasing number of solvent molecules beyond the first solvation shell has been found to consist in reduction of the differences in complexation energies for different coordination numbers. Explicit-solvation data have served as a benchmark to the results of polarizable continuum model (PCM) calculations. It has been demonstrated that the PCM approach can yield relative complexation energies comparable to the predictions based on molecular-level solvation, but at significantly lower computational cost. The best agreement between the explicit-solvation and the PCM results has been obtained when the van der Waals surface was adopted to build the molecular cavity.

Self-Regulation and Implicit Attitudes Toward Physical Activity Influence Exercise Behavior.

PubMed

Padin, Avelina C; Emery, Charles F; Vasey, Michael; Kiecolt-Glaser, Janice K

2017-08-01

Dual-process models of health behavior posit that implicit and explicit attitudes independently drive healthy behaviors. Prior evidence indicates that implicit attitudes may be related to weekly physical activity (PA) levels, but the extent to which self-regulation attenuates this link remains unknown. This study examined the associations between implicit attitudes and self-reported PA during leisure time among 150 highly active young adults and evaluated the extent to which effortful control (one aspect of self-regulation) moderated this relationship. Results indicated that implicit attitudes toward exercise were unrelated to average workout length among individuals with higher effortful control. However, those with lower effortful control and more negative implicit attitudes reported shorter average exercise sessions compared with those with more positive attitudes. Implicit and explicit attitudes were unrelated to total weekly PA. A combination of poorer self-regulation and negative implicit attitudes may leave individuals vulnerable to mental and physical health consequences of low PA.

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - SEEM

DTIC Science & Technology

2015-06-01

hazard quotient HSI Habitat Suitability Index LOAEL lowest observed adverse effect level mg/kg milligrams per kilogram NOAEL no observed adverse... effect level NPL National Priorities List PRR Patuxent Research Refuge QA quality assurance QC quality control ACRONYMS AND...mean and maximum) for each individual for the exposure period; EHQs are then compiled to arrive at a modeled population— effects curve. Figure 1

Improvement, Verification, and Refinement of Spatially Explicit Exposure Models in Risk Assessment - SEEM Demonstration

DTIC Science & Technology

2015-06-01

hazard quotient HSI Habitat Suitability Index LOAEL lowest observed adverse effect level mg/kg milligrams per kilogram NOAEL no observed adverse... effect level NPL National Priorities List PRR Patuxent Research Refuge QA quality assurance QC quality control ACRONYMS AND...mean and maximum) for each individual for the exposure period; EHQs are then compiled to arrive at a modeled population— effects curve. Figure 1

How cognitive heuristics can explain social interactions in spatial movement.

PubMed

Seitz, Michael J; Bode, Nikolai W F; Köster, Gerta

2016-08-01

The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. © 2016 The Author(s).

How cognitive heuristics can explain social interactions in spatial movement

PubMed Central

Köster, Gerta

2016-01-01

The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as ‘stop if another step would lead to a collision’ or ‘follow the person in front’. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. PMID:27581483

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Effects of reducing attentional resources on implicit and explicit memory after severe traumatic brain injury.

PubMed

Watt, S; Shores, E A; Kinoshita, S

1999-07-01

Implicit and explicit memory were examined in individuals with severe traumatic brain injury (TBI) under conditions of full and divided attention. Participants included 12 individuals with severe TBI and 12 matched controls. In Experiment 1, participants carried out an implicit test of word-stem completion and an explicit test of cued recall. Results demonstrated that TBI participants exhibited impaired explicit memory but preserved implicit memory. In Experiment 2, a significant reduction in the explicit memory performance of both TBI and control participants, as well as a significant decrease in the implicit memory performance of TBI participants, was achieved by reducing attentional resources at encoding. These results indicated that performance on an implicit task of word-stem completion may require the availability of additional attentional resources that are not preserved after severe TBI.

The Application of FIA-based Data to Wildlife Habitat Modeling: A Comparative Study

Treesearch

Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Randall J. Schultz

2005-01-01

We evaluated the capability of two types of models, one based on spatially explicit variables derived from FIA data and one using so-called traditional habitat evaluation methods, for predicting the presence of cavity-nesting bird habitat in Fishlake National Forest, Utah. Both models performed equally well, in measures of predictive accuracy, with the FIA-based model...

Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases

NASA Astrophysics Data System (ADS)

Belik, Vitaly; Geisel, Theo; Brockmann, Dirk

2011-08-01

We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.

Change-in-ratio estimators for populations with more than two subclasses

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.

1991-01-01

Change-in-ratio methods have been developed to estimate the size of populations with two or three population subclasses. Most of these methods require the often unreasonable assumption of equal sampling probabilities for individuals in all subclasses. This paper presents new models based on the weaker assumption that ratios of sampling probabilities are constant over time for populations with three or more subclasses. Estimation under these models requires that a value be assumed for one of these ratios when there are two samples. Explicit expressions are given for the maximum likelihood estimators under models for two samples with three or more subclasses and for three samples with two subclasses. A numerical method using readily available statistical software is described for obtaining the estimators and their standard errors under all of the models. Likelihood ratio tests that can be used in model selection are discussed. Emphasis is on the two-sample, three-subclass models for which Monte-Carlo simulation results and an illustrative example are presented.

Mate-sampling costs and sexy sons.

PubMed

Kokko, H; Booksmythe, I; Jennions, M D

2015-01-01

Costly female mating preferences for purely Fisherian male traits (i.e. sexual ornaments that are genetically uncorrelated with inherent viability) are not expected to persist at equilibrium. The indirect benefit of producing 'sexy sons' (Fisher process) disappears: in some models, the male trait becomes fixed; in others, a range of male trait values persist, but a larger trait confers no net fitness advantage because it lowers survival. Insufficient indirect selection to counter the direct cost of producing fewer offspring means that preferences are lost. The only well-cited exception assumes biased mutation on male traits. The above findings generally assume constant direct selection against female preferences (i.e. fixed costs). We show that if mate-sampling costs are instead derived based on an explicit account of how females acquire mates, an initially costly mating preference can coevolve with a male trait so that both persist in the presence or absence of biased mutation. Our models predict that empirically detecting selection at equilibrium will be difficult, even if selection was responsible for the location of the current equilibrium. In general, it appears useful to integrate mate sampling theory with models of genetic consequences of mating preferences: being explicit about the process by which individuals select mates can alter equilibria. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Implicit affectivity in patients with borderline personality disorder.

PubMed

Dukalski, Bibiana; Quirin, Markus; Kersting, Anette; Suslow, Thomas; Donges, Uta-Susan

2017-01-01

It has been argued that borderline personality disorder (BPD) is related to an enhanced affective reactivity. According to findings from research based on self-report, individuals with BPD develop and feel more negative and less positive affect than healthy individuals. Implicit affectivity, which can be measured using indirect assessment methods, relates to processes of the impulsive, intuitive system. In the present study, implicit and explicit affectivity was examined in patients suffering from BPD compared to healthy persons. Thirty-five women with BPD and 35 healthy women participated in the study. Implicit affectivity was assessed using the Implicit Positive and Negative Affect Test (IPANAT). Measures of explicit state and trait affectivity were also administered. BPD women had lower explicit positive state and trait affect scores and higher negative state and trait affect scores than healthy women. They had also lower implicit positive affect but they did not differ from healthy women regarding implicit negative affect. Total number of comorbid disorders was correlated with both implicit positive and implicit negative affect. According to our data, BPD patients exhibit reduced implicit positive affect as well as reduced explicit positive affect compared to healthy persons. According to our IPANAT data, BPD patients are characterized by a normal disposition to develop negative affective reactions which is in line with a number of findings from psycho-physiological research on BPD. Self-reports of negative affectivity in BPD could be biased by negative distortion.

Balancing Management and Leadership in Complex Health Systems Comment on "Management Matters: A Leverage Point for Health Systems Strengthening in Global Health".

PubMed

Kwamie, Aku

2015-08-14

Health systems, particularly those in low- and middle-income countries (LMICs), need stronger management and leadership capacities. Management and leadership are not synonymous, yet should be considered together as there can be too much of one and not enough of the other. In complex adaptive health systems, the multiple interactions and relationships between people and elements of the system mean that management and leadership, so often treated as domains of the individual, are additionally systemic phenomena, emerging from these relational interactions. This brief commentary notes some significant implications for how we can support capacity strengthening interventions for complex management and leadership. These would necessarily move away from competency-based models focused on training for individuals, and would rather encompass longer-term initiatives explicitly focused on systemic goals of accountability, innovation, and learning. © 2015 by Kerman University of Medical Sciences.

Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

PubMed Central

Zhu, Shanjiang; Levinson, David

2015-01-01

Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756

sGD: software for estimating spatially explicit indices of genetic diversity.

PubMed

Shirk, A J; Cushman, S A

2011-09-01

Anthropogenic landscape changes have greatly reduced the population size, range and migration rates of many terrestrial species. The small local effective population size of remnant populations favours loss of genetic diversity leading to reduced fitness and adaptive potential, and thus ultimately greater extinction risk. Accurately quantifying genetic diversity is therefore crucial to assessing the viability of small populations. Diversity indices are typically calculated from the multilocus genotypes of all individuals sampled within discretely defined habitat patches or larger regional extents. Importantly, discrete population approaches do not capture the clinal nature of populations genetically isolated by distance or landscape resistance. Here, we introduce spatial Genetic Diversity (sGD), a new spatially explicit tool to estimate genetic diversity based on grouping individuals into potentially overlapping genetic neighbourhoods that match the population structure, whether discrete or clinal. We compared the estimates and patterns of genetic diversity using patch or regional sampling and sGD on both simulated and empirical populations. When the population did not meet the assumptions of an island model, we found that patch and regional sampling generally overestimated local heterozygosity, inbreeding and allelic diversity. Moreover, sGD revealed fine-scale spatial heterogeneity in genetic diversity that was not evident with patch or regional sampling. These advantages should provide a more robust means to evaluate the potential for genetic factors to influence the viability of clinal populations and guide appropriate conservation plans. © 2011 Blackwell Publishing Ltd.

Discriminative analysis of lip motion features for speaker identification and speech-reading.

PubMed

Cetingül, H Ertan; Yemez, Yücel; Erzin, Engin; Tekalp, A Murat

2006-10-01

There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application.

Child abuse and negative explicit and automatic self-associations: the cognitive scars of emotional maltreatment.

PubMed

van Harmelen, Anne-Laura; de Jong, Peter J; Glashouwer, Klaske A; Spinhoven, Philip; Penninx, Brenda W J H; Elzinga, Bernet M

2010-06-01

Individuals reporting Childhood Abuse (CA) (i.e., emotional neglect, emotional-, physical- and sexual-abuse) are marked by increased explicit (i.e. self-reported) negative self-associations, and an increased risk to develop depression or anxiety disorders. Automatic self-associations might play an important role in the development and maintenance of affective disorders after exposure to CA, since automatic associations are assumed to be involved in uncontrolled (spontaneous) affective behavior. This study examined whether individuals reporting a history of CA show stronger automatic (and explicit) self-depression and/or self-anxiety associations than individuals who report no CA in a large cohort study (Netherlands Study of Depression and Anxiety (NESDA), n = 2981). The Implicit Association Test (IAT) was utilized to assess automatic self-depression and self-anxiety associations. We found that CA was associated with enhanced automatic (and explicit) self-depression and self-anxiety associations. Additionally, when compared to physical- and sexual-abuse, Childhood Emotional Maltreatment (CEM; emotional abuse and emotional neglect) had the strongest link with enhanced automatic (and explicit) self-depression and self-anxiety associations. In addition, automatic and explicit negative self-associations partially mediated the association between CEM and depressive or anxious symptomatology. Implications regarding the importance of CA, and CEM in particular will be discussed. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

PubMed

Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin

2017-09-01

N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

Getting the biggest birch for the bang: restoring and expanding upland birchwoods in the Scottish Highlands by managing red deer

PubMed Central

Tanentzap, Andrew J; Zou, James; Coomes, David A

2013-01-01

High deer populations threaten the conservation value of woodlands and grasslands, but predicting the success of deer culling, in terms of allowing vegetation to recover, is difficult. Numerical simulation modeling is one approach to gain insight into the outcomes of management scenarios. We develop a spatially explicit model to predict the responses of Betula spp. to red deer (Cervus elaphus) and land management in the Scottish Highlands. Our model integrates a Bayesian stochastic stage-based matrix model within the framework of a widely used individual-based forest simulation model, using data collected along spatial and temporal gradients in deer browsing. By initializing our model with the historical spatial locations of trees, we find that densities of juvenile trees (<3 m tall) predicted after 9–13 years closely match counts observed in the field. This is among the first tests of the accuracy of a dynamical simulation model for predicting the responses of tree regeneration to herbivores. We then test the relative importance of deer browsing, ground cover vegetation, and seed availability in facilitating landscape-level birch regeneration using simulations in which we varied these three variables. We find that deer primarily control transitions of birch to taller (>3 m) height tiers over 30 years, but regeneration also requires suitable ground cover for seedling establishment. Densities of adult seed sources did not influence regeneration, nor did an active management scenario where we altered the spatial configuration of adults by creating “woodland islets”. Our results show that managers interested in maximizing tree regeneration cannot simply reduce deer densities but must also improve ground cover for seedling establishment, and the model we develop now enables managers to quantify explicitly how much both these factors need to be altered. More broadly, our findings emphasize the need for land managers to consider the impacts of large herbivores rather than their densities. PMID:23919137

Alpha 94: Literacy and Cultural Development Strategies in Rural Areas.

ERIC Educational Resources Information Center

Hautecoeur, Jean-Paul, Ed.

This book compiles 21 action research articles from 12 countries that describe community-based initiatives in adult literacy education in peripheral rural areas. These initiatives represent dynamic experiments in cultural action that explicitly link individual basic education and a collective change in the conditions of local life. The reports…

The kinetics of heterogeneous nucleation and growth: an approach based on a grain explicit model

NASA Astrophysics Data System (ADS)

Rouet-Leduc, B.; Maillet, J.-B.; Denoual, C.

2014-04-01

A model for phase transitions initiated on grain boundaries is proposed and tested against numerical simulations: this approach, based on a grain explicit model, allows us to consider the granular structure, resulting in accurate predictions for a wide span of nucleation processes. Comparisons are made with classical models of homogeneous (JMAK: Johnson and Mehl 1939 Trans. Am. Inst. Min. Eng. 135 416; Avrami 1939 J. Chem. Phys. 7 1103; Kolmogorov 1937 Bull. Acad. Sci. USSR, Mat. Ser. 1 335) as well as heterogeneous (Cahn 1996 Thermodynamics and Kinetics of Phase Transformations Im et al (Pittsburgh: Materials Research Society)) nucleation. A transition scale based on material properties is proposed, allowing us to discriminate between random and site-saturated regimes. Finally, we discuss the relationship between an Avrami-type exponent and the transition regime, establishing conditions for its extraction from experiments.

Alternative modeling methods for plasma-based Rf ion sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veitzer, Seth A., E-mail: veitzer@txcorp.com; Kundrapu, Madhusudhan, E-mail: madhusnk@txcorp.com; Stoltz, Peter H., E-mail: phstoltz@txcorp.com

Rf-driven ion sources for accelerators and many industrial applications benefit from detailed numerical modeling and simulation of plasma characteristics. For instance, modeling of the Spallation Neutron Source (SNS) internal antenna H{sup −} source has indicated that a large plasma velocity is induced near bends in the antenna where structural failures are often observed. This could lead to improved designs and ion source performance based on simulation and modeling. However, there are significant separations of time and spatial scales inherent to Rf-driven plasma ion sources, which makes it difficult to model ion sources with explicit, kinetic Particle-In-Cell (PIC) simulation codes. Inmore » particular, if both electron and ion motions are to be explicitly modeled, then the simulation time step must be very small, and total simulation times must be large enough to capture the evolution of the plasma ions, as well as extending over many Rf periods. Additional physics processes such as plasma chemistry and surface effects such as secondary electron emission increase the computational requirements in such a way that even fully parallel explicit PIC models cannot be used. One alternative method is to develop fluid-based codes coupled with electromagnetics in order to model ion sources. Time-domain fluid models can simulate plasma evolution, plasma chemistry, and surface physics models with reasonable computational resources by not explicitly resolving electron motions, which thereby leads to an increase in the time step. This is achieved by solving fluid motions coupled with electromagnetics using reduced-physics models, such as single-temperature magnetohydrodynamics (MHD), extended, gas dynamic, and Hall MHD, and two-fluid MHD models. We show recent results on modeling the internal antenna H{sup −} ion source for the SNS at Oak Ridge National Laboratory using the fluid plasma modeling code USim. We compare demonstrate plasma temperature equilibration in two-temperature MHD models for the SNS source and present simulation results demonstrating plasma evolution over many Rf periods for different plasma temperatures. We perform the calculations in parallel, on unstructured meshes, using finite-volume solvers in order to obtain results in reasonable time.« less

Alternative modeling methods for plasma-based Rf ion sources.

PubMed

Veitzer, Seth A; Kundrapu, Madhusudhan; Stoltz, Peter H; Beckwith, Kristian R C

2016-02-01

Rf-driven ion sources for accelerators and many industrial applications benefit from detailed numerical modeling and simulation of plasma characteristics. For instance, modeling of the Spallation Neutron Source (SNS) internal antenna H(-) source has indicated that a large plasma velocity is induced near bends in the antenna where structural failures are often observed. This could lead to improved designs and ion source performance based on simulation and modeling. However, there are significant separations of time and spatial scales inherent to Rf-driven plasma ion sources, which makes it difficult to model ion sources with explicit, kinetic Particle-In-Cell (PIC) simulation codes. In particular, if both electron and ion motions are to be explicitly modeled, then the simulation time step must be very small, and total simulation times must be large enough to capture the evolution of the plasma ions, as well as extending over many Rf periods. Additional physics processes such as plasma chemistry and surface effects such as secondary electron emission increase the computational requirements in such a way that even fully parallel explicit PIC models cannot be used. One alternative method is to develop fluid-based codes coupled with electromagnetics in order to model ion sources. Time-domain fluid models can simulate plasma evolution, plasma chemistry, and surface physics models with reasonable computational resources by not explicitly resolving electron motions, which thereby leads to an increase in the time step. This is achieved by solving fluid motions coupled with electromagnetics using reduced-physics models, such as single-temperature magnetohydrodynamics (MHD), extended, gas dynamic, and Hall MHD, and two-fluid MHD models. We show recent results on modeling the internal antenna H(-) ion source for the SNS at Oak Ridge National Laboratory using the fluid plasma modeling code USim. We compare demonstrate plasma temperature equilibration in two-temperature MHD models for the SNS source and present simulation results demonstrating plasma evolution over many Rf periods for different plasma temperatures. We perform the calculations in parallel, on unstructured meshes, using finite-volume solvers in order to obtain results in reasonable time.

Toward an Optimal Pedagogy for Teamwork.

PubMed

Earnest, Mark A; Williams, Jason; Aagaard, Eva M

2017-10-01

Teamwork and collaboration are increasingly listed as core competencies for undergraduate health professions education. Despite the clear mandate for teamwork training, the optimal method for providing that training is much less certain. In this Perspective, the authors propose a three-level classification of pedagogical approaches to teamwork training based on the presence of two key learning factors: interdependent work and explicit training in teamwork. In this classification framework, level 1-minimal team learning-is where learners work in small groups but neither of the key learning factors is present. Level 2-implicit team learning-engages learners in interdependent learning activities but does not include an explicit focus on teamwork. Level 3-explicit team learning-creates environments where teams work interdependently toward common goals and are given explicit instruction and practice in teamwork. The authors provide examples that demonstrate each level. They then propose that the third level of team learning, explicit team learning, represents a best practice approach in teaching teamwork, highlighting their experience with an explicit team learning course at the University of Colorado Anschutz Medical Campus. Finally, they discuss several challenges to implementing explicit team-learning-based curricula: the lack of a common teamwork model on which to anchor such a curriculum; the question of whether the knowledge, skills, and attitudes acquired during training would be transferable to the authentic clinical environment; and effectively evaluating the impact of explicit team learning.

Testing the Use of Implicit Solvent in the Molecular Dynamics Modelling of DNA Flexibility

NASA Astrophysics Data System (ADS)

Mitchell, J.; Harris, S.

DNA flexibility controls packaging, looping and in some cases sequence specific protein binding. Molecular dynamics simulations carried out with a computationally efficient implicit solvent model are potentially a powerful tool for studying larger DNA molecules than can be currently simulated when water and counterions are represented explicitly. In this work we compare DNA flexibility at the base pair step level modelled using an implicit solvent model to that previously determined from explicit solvent simulations and database analysis. Although much of the sequence dependent behaviour is preserved in implicit solvent, the DNA is considerably more flexible when the approximate model is used. In addition we test the ability of the implicit solvent to model stress induced DNA disruptions by simulating a series of DNA minicircle topoisomers which vary in size and superhelical density. When compared with previously run explicit solvent simulations, we find that while the levels of DNA denaturation are similar using both computational methodologies, the specific structural form of the disruptions is different.

Moran model as a dynamical process on networks and its implications for neutral speciation.

PubMed

de Aguiar, Marcus A M; Bar-Yam, Yaneer

2011-09-01

In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.

Moran model as a dynamical process on networks and its implications for neutral speciation

NASA Astrophysics Data System (ADS)

de Aguiar, Marcus A. M.; Bar-Yam, Yaneer

2011-03-01

In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.

Background-Error Correlation Model Based on the Implicit Solution of a Diffusion Equation

DTIC Science & Technology

2010-01-01

1 Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation Matthew J. Carrier* and Hans Ngodock...4. TITLE AND SUBTITLE Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation 5a. CONTRACT NUMBER 5b. GRANT...2001), which sought to model error correlations based on the explicit solution of a generalized diffusion equation. The implicit solution is

EXPLICIT: a feasibility study of remote expert elicitation in health technology assessment.

PubMed

Grigore, Bogdan; Peters, Jaime; Hyde, Christopher; Stein, Ken

2017-09-04

Expert opinion is often sought to complement available information needed to inform model-based economic evaluations in health technology assessments. In this context, we define expert elicitation as the process of encoding expert opinion on a quantity of interest, together with associated uncertainty, as a probability distribution. When availability for face-to-face expert elicitation with a facilitator is limited, elicitation can be conducted remotely, overcoming challenges of finding an appropriate time to meet the expert and allowing access to experts situated too far away for practical face-to-face sessions. However, distance elicitation is associated with reduced response rates and limited assistance for the expert during the elicitation session. The aim of this study was to inform the development of a remote elicitation tool by exploring the influence of mode of elicitation on elicited beliefs. An Excel-based tool (EXPLICIT) was developed to assist the elicitation session, including the preparation of the expert and recording of their responses. General practitioners (GPs) were invited to provide expert opinion about population alcohol consumption behaviours. They were randomised to complete the elicitation by either a face-to-face meeting or email. EXPLICIT was used in the elicitation sessions for both arms. Fifteen GPs completed the elicitation session. Those conducted by email were longer than the face-to-face sessions (13 min 30 s vs 10 min 26 s, p = 0.1) and the email-elicited estimates contained less uncertainty. However, the resulting aggregated distributions were comparable. EXPLICIT was useful in both facilitating the elicitation task and in obtaining expert opinion from experts via email. The findings support the opinion that remote, self-administered elicitation is a viable approach within the constraints of HTA to inform policy making, although poor response rates may be observed and additional time for individual sessions may be required.

Evaluating the effect of salinity on a simulated American Crocodile (Crocodylus acutus) population with applications to conservation and Everglades restoration

USGS Publications Warehouse

Richards, Paul M.; Mooij, Wolf M.; DeAngelis, Donald L.

2004-01-01

Everglades restoration will alter the hydrology of South Florida, affecting both water depth and salinity levels in the southern fringes of the Everglades, the habitat of the endangered American crocodile (Crocodylus acutus). A key question is what the effects of these hydrologic changes will be on the crocodile population. Reliable predictions of the viability of endangered species under a variety of management scenarios are of vital importance in conservation ecology. Juvenile American crocodiles are thought to be sensitive to high salinity levels, suffering reduced mass, and potentially reduced survivorship and recruitment. This could negatively impact the population recovery. We addressed the management issue of how the crocodile population will respond to alterations in hydrology with a spatially explicit individual-based model. The model is designed to relate water levels, salinities, and dominant vegetation to crocodile distribution, abundance, population growth, individual growth, survival, nesting effort, and nesting success. Our analysis shows that Everglades restoration, through its effects on water flow to estuaries, may benefit crocodile populations if increased freshwater flow reduces the chance that regional salinity levels exceed levels where small individuals lose mass. In addition, we conclude that conservation priority should be placed on reducing anthropogenic sources of mortality on large individuals, such as road mortality. Finally, research should focus on estimates of annual survivorship for large individuals.

Constant pH Molecular Dynamics of Proteins in Explicit Solvent with Proton Tautomerism

PubMed Central

Goh, Garrett B.; Hulbert, Benjamin S.; Zhou, Huiqing; Brooks, Charles L.

2015-01-01

pH is a ubiquitous regulator of biological activity, including protein-folding, protein-protein interactions and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH-dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi-site λ-dynamics (CPHMDMSλD). In the CPHMDMSλD framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi-site λ-dynamics, and designed novel biasing potentials to ensure that the physical end-states are predominantly sampled. We show that explicit solvent CPHMDMSλD simulations model realistic pH-dependent properties of proteins such as the Hen-Egg White Lysozyme (HEWL), binding domain of 2-oxoglutarate dehydrogenase (BBL) and N-terminal domain of ribosomal L9 (NTL9), and the pKa predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 pKa units. With the recent development of the explicit solvent CPHMDMSλD framework for nucleic acids, accurate modeling of pH-dependent properties of both major class of biomolecules – proteins and nucleic acids is now possible. PMID:24375620

Thinking Styles in Implicit and Explicit Learning

ERIC Educational Resources Information Center

Xie, Qiuzhi; Gao, Xiangping; King, Ronnel B.

2013-01-01

This study investigated whether individual differences in thinking styles influence explicit and implicit learning. Eighty-seven university students in China participated in this study. Results indicated that performance in the explicit learning condition was positively associated with Type I thinking styles (i.e. legislative and liberal styles)…

When cognition kicks in: working memory and speech understanding in noise.

PubMed

Rönnberg, Jerker; Rudner, Mary; Lunner, Thomas; Zekveld, Adriana A

2010-01-01

Perceptual load and cognitive load can be separately manipulated and dissociated in their effects on speech understanding in noise. The Ease of Language Understanding model assumes a theoretical position where perceptual task characteristics interact with the individual's implicit capacities to extract the phonological elements of speech. Phonological precision and speed of lexical access are important determinants for listening in adverse conditions. If there are mismatches between the phonological elements perceived and phonological representations in long-term memory, explicit working memory (WM)-related capacities will be continually invoked to reconstruct and infer the contents of the ongoing discourse. Whether this induces a high cognitive load or not will in turn depend on the individual's storage and processing capacities in WM. Data suggest that modulated noise maskers may serve as triggers for speech maskers and therefore induce a WM, explicit mode of processing. Individuals with high WM capacity benefit more than low WM-capacity individuals from fast amplitude compression at low or negative input speech-to-noise ratios. The general conclusion is that there is an overarching interaction between the focal purpose of processing in the primary listening task and the extent to which a secondary, distracting task taps into these processes.

"What is relevant in a text document?": An interpretable machine learning approach

PubMed Central

Arras, Leila; Horn, Franziska; Montavon, Grégoire; Müller, Klaus-Robert

2017-01-01

Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML) models have been trained to automatically map documents to these abstract concepts, allowing to annotate very large text collections, more than could be processed by a human in a lifetime. Besides predicting the text’s category very accurately, it is also highly desirable to understand how and why the categorization process takes place. In this paper, we demonstrate that such understanding can be achieved by tracing the classification decision back to individual words using layer-wise relevance propagation (LRP), a recently developed technique for explaining predictions of complex non-linear classifiers. We train two word-based ML models, a convolutional neural network (CNN) and a bag-of-words SVM classifier, on a topic categorization task and adapt the LRP method to decompose the predictions of these models onto words. Resulting scores indicate how much individual words contribute to the overall classification decision. This enables one to distill relevant information from text documents without an explicit semantic information extraction step. We further use the word-wise relevance scores for generating novel vector-based document representations which capture semantic information. Based on these document vectors, we introduce a measure of model explanatory power and show that, although the SVM and CNN models perform similarly in terms of classification accuracy, the latter exhibits a higher level of explainability which makes it more comprehensible for humans and potentially more useful for other applications. PMID:28800619

An explicitly solvated full atomistic model of the cardiac thin filament and application on the calcium binding affinity effects from familial hypertrophic cardiomyopathy linked mutations

NASA Astrophysics Data System (ADS)

Williams, Michael; Schwartz, Steven

2015-03-01

The previous version of our cardiac thin filament (CTF) model consisted of the troponin complex (cTn), two coiled-coil dimers of tropomyosin (Tm), and 29 actin units. We now present the newest revision of the model to include explicit solvation. The model was developed to continue our study of genetic mutations in the CTF proteins which are linked to familial hypertrophic cardiomyopathies. Binding of calcium to the cTnC subunit causes subtle conformational changes to propagate through the cTnC to the cTnI subunit which then detaches from actin. Conformational changes propagate through to the cTnT subunit, which allows Tm to move into the open position along actin, leading to muscle contraction. Calcium disassociation allows for the reverse to occur, which results in muscle relaxation. The inclusion of explicit TIP3 water solvation allows for the model to get better individual local solvent to protein interactions; which are important when observing the N-lobe calcium binding pocket of the cTnC. We are able to compare in silica and in vitro experimental results to better understand the physiological effects from mutants, such as the R92L/W and F110V/I of the cTnT, on the calcium binding affinity compared to the wild type.

Consolidated Bibliography--Unclassified Technical Reports, Special Reports, and Technical Notes: FY 1974 through FY 1981.

DTIC Science & Technology

1982-02-01

methodological and design inadequacies. The purposes of this study were to design and test a methodological model and to provide an objective assessment of ICR...provide an alternative to the purchase of special training equipments. Models of the Learner in Computer-assisted Instruction. TR 76-23. December 1975...3. D. Fletcher. lAD-A020 725) The adaptability of computer-assisted instruction to individuals should be en- hanced by the use of explicit models of

Model for the orientational ordering of the plant microtubule cortical array

NASA Astrophysics Data System (ADS)

Hawkins, Rhoda J.; Tindemans, Simon H.; Mulder, Bela M.

2010-07-01

The plant microtubule cortical array is a striking feature of all growing plant cells. It consists of a more or less homogeneously distributed array of highly aligned microtubules connected to the inner side of the plasma membrane and oriented transversely to the cell growth axis. Here, we formulate a continuum model to describe the origin of orientational order in such confined arrays of dynamical microtubules. The model is based on recent experimental observations that show that a growing cortical microtubule can interact through angle dependent collisions with pre-existing microtubules that can lead either to co-alignment of the growth, retraction through catastrophe induction or crossing over the encountered microtubule. We identify a single control parameter, which is fully determined by the nucleation rate and intrinsic dynamics of individual microtubules. We solve the model analytically in the stationary isotropic phase, discuss the limits of stability of this isotropic phase, and explicitly solve for the ordered stationary states in a simplified version of the model.

Nemo: an evolutionary and population genetics programming framework.

PubMed

Guillaume, Frédéric; Rougemont, Jacques

2006-10-15

Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.

On the Takayanagi principle for the shape memory effect and thermomechanical behaviors in polymers with multi-phases

NASA Astrophysics Data System (ADS)

Lu, Haibao; Yu, Kai; Huang, Wei Min; Leng, Jinsong

2016-12-01

We present an explicit model to study the mechanics and physics of the shape memory effect (SME) in polymers based on the Takayanagi principle. The molecular structural characteristics and elastic behavior of shape memory polymers (SMPs) with multi-phases are investigated in terms of the thermomechanical properties of the individual components, of which the contributions are combined by using Takayanagi’s series-parallel model and parallel-series model, respectively. After that, Boltzmann superposition principle is employed to couple the multi-SME, elastic modulus parameter (E) and temperature parameter (T) in SMPs. Furthermore, the extended Takayanagi model is proposed to separate the plasticizing effect and physical swelling effect on the thermo-/chemo-responsive SME in polymers and then compared with the available experimental data reported in the literature. This study is expected to provide a powerful simulation tool for modeling and experimental substantiation of the mechanics and working mechanism of SME in polymers.

Interspecific variation in growth responses to climate and competition of five eastern tree species.

PubMed

Rollinson, Christine R; Kaye, Margot W; Canham, Charles D

2016-04-01

Climate and competition are often presented from two opposing views of the dominant driver of individual tree growth and species distribution in temperate forests, such as those in the eastern United States. Previous studies have provided abundant evidence indicating that both factors influence tree growth, and we argue that these effects are not independent of one another and rather that interactions between climate, competition, and size best describe tree growth. To illustrate this point, we describe the growth responses of five common eastern tree species to interacting effects of temperature, precipitation, competition, and individual size using maximum likelihood estimation. Models that explicitly include interactions among these four factors explained over half of the variance in annual growth for four out of five species using annual climate. Expanding temperature and precipitation analyses to include seasonal interactions resulted in slightly improved models with a mean R2 of 0.61 (SD 0.10). Growth responses to individual factors as well their interactions varied greatly among species. For example, growth sensitivity to temperature for Quercus rubra increased with maximum annual precipitation, but other species showed no change in sensitivity or slightly reduced annual growth. Our results also indicate that three-way interactions among individual stem size, competition, and temperature may determine which of the five co-occurring species in our study could have the highest growth rate in a given year. Continued consideration and quantification of interactions among climate, competition, and individual-based characteristics are likely to increase understanding of key biological processes such as tree growth. Greater parameterization of interactions between traditionally segregated factors such as climate and competition may also help build a framework to reconcile drivers of individual-based processes such as growth with larger-scale patterns of species distribution.

Using Multiple Lenses to Examine the Development of Beginning Biology Teachers' Pedagogical Content Knowledge for Teaching Natural Selection Simulations

NASA Astrophysics Data System (ADS)

Sickel, Aaron J.; Friedrichsen, Patricia

2018-02-01

Pedagogical content knowledge (PCK) has become a useful construct to examine science teacher learning. Yet, researchers conceptualize PCK development in different ways. The purpose of this longitudinal study was to use three analytic lenses to understand the development of three beginning biology teachers' PCK for teaching natural selection simulations. We observed three early-career biology teachers as they taught natural selection in their respective school contexts over two consecutive years. Data consisted of six interviews with each participant. Using the PCK model developed by Magnusson et al. (1999), we examined topic-specific PCK development utilizing three different lenses: (1) expansion of knowledge within an individual knowledge base, (2) integration of knowledge across knowledge bases, and (3) knowledge that explicitly addressed core concepts of natural selection. We found commonalities across the participants, yet each lens was also useful to understand the influence of different factors (e.g., orientation, subject matter preparation, and the idiosyncratic nature of teacher knowledge) on PCK development. This multi-angle approach provides implications for considering the quality of beginning science teachers' knowledge and future research on PCK development. We conclude with an argument that explicitly communicating lenses used to understand PCK development will help the research community compare analytic approaches and better understand the nature of science teacher learning.

Spin-orbit splitted excited states using explicitly-correlated equation-of-motion coupled-cluster singles and doubles eigenvectors

NASA Astrophysics Data System (ADS)

Bokhan, Denis; Trubnikov, Dmitrii N.; Perera, Ajith; Bartlett, Rodney J.

2018-04-01

An explicitly-correlated method of calculation of excited states with spin-orbit couplings, has been formulated and implemented. Developed approach utilizes left and right eigenvectors of equation-of-motion coupled-cluster model, which is based on the linearly approximated explicitly correlated coupled-cluster singles and doubles [CCSD(F12)] method. The spin-orbit interactions are introduced by using the spin-orbit mean field (SOMF) approximation of the Breit-Pauli Hamiltonian. Numerical tests for several atoms and molecules show good agreement between explicitly-correlated results and the corresponding values, calculated in complete basis set limit (CBS); the highly-accurate excitation energies can be obtained already at triple- ζ level.

Culture, morality and individual differences: comparability and incomparability across species.

PubMed

Saucier, Gerard

2018-04-19

Major routes to identifying individual differences (in diverse species) include studies of behaviour patterns as represented in language and neurophysiology. But results from these approaches appear not to converge on some major dimensions. Identifying dimensions of human variation least applicable to non-human species may help to partition human-specific individual differences of recent evolutionary origin from those shared across species. Human culture includes learned, enforced social-norm systems that are symbolically reinforced and referenced in displays signalling adherence. At a key juncture in human evolution bullying aggression and deception-based cheating apparently became censured in the language of a moral community, enabling mutual observation coordinated in gossip, associated with external sanctions. That still-conserved cultural paradigm moralistically regulates selfish advantage-taking, with shared semantics and explicit rules. Ethics and moral codes remain critical and universal components of human culture and have a stronger imprint in language than most aspects of the currently popular Big-Five taxonomy, a model that sets out five major lines of individual-differences variation in human personality. In other species (e.g. chimpanzees), human observers might see apparent individual differences in morality-relevant traits, but not because the animals have human-analogue sanctioning systems. Removing the moral dimension of personality and other human-specific manifestations (e.g. religion) may aid in identifying those other bases of individual differences more ubiquitous across species.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

PubMed

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

GPGPU-based explicit finite element computations for applications in biomechanics: the performance of material models, element technologies, and hardware generations.

PubMed

Strbac, V; Pierce, D M; Vander Sloten, J; Famaey, N

2017-12-01

Finite element (FE) simulations are increasingly valuable in assessing and improving the performance of biomedical devices and procedures. Due to high computational demands such simulations may become difficult or even infeasible, especially when considering nearly incompressible and anisotropic material models prevalent in analyses of soft tissues. Implementations of GPGPU-based explicit FEs predominantly cover isotropic materials, e.g. the neo-Hookean model. To elucidate the computational expense of anisotropic materials, we implement the Gasser-Ogden-Holzapfel dispersed, fiber-reinforced model and compare solution times against the neo-Hookean model. Implementations of GPGPU-based explicit FEs conventionally rely on single-point (under) integration. To elucidate the expense of full and selective-reduced integration (more reliable) we implement both and compare corresponding solution times against those generated using underintegration. To better understand the advancement of hardware, we compare results generated using representative Nvidia GPGPUs from three recent generations: Fermi (C2075), Kepler (K20c), and Maxwell (GTX980). We explore scaling by solving the same boundary value problem (an extension-inflation test on a segment of human aorta) with progressively larger FE meshes. Our results demonstrate substantial improvements in simulation speeds relative to two benchmark FE codes (up to 300[Formula: see text] while maintaining accuracy), and thus open many avenues to novel applications in biomechanics and medicine.

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India

PubMed Central

Sarkar, Mriganka Shekhar; Johnson, Jeyaraj A.; Sen, Subharanjan

2017-01-01

Background Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals’ ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger (Panthera tigris), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. Methods We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly’s selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D2 method and the Boyce index. Results There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Discussion Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve. PMID:29114438

On the Leaky Math Pipeline: Comparing Implicit Math-Gender Stereotypes and Math Withdrawal in Female and Male Children and Adolescents

ERIC Educational Resources Information Center

Steffens, Melanie C.; Jelenec, Petra; Noack, Peter

2010-01-01

Many models assume that habitual human behavior is guided by spontaneous, automatic, or implicit processes rather than by deliberate, rule-based, or explicit processes. Thus, math-ability self-concepts and math performance could be related to implicit math-gender stereotypes in addition to explicit stereotypes. Two studies assessed at what age…

Using group model building to understand factors that influence childhood obesity in an urban environment.

PubMed

Nelson, David A; Simenz, Christopher J; OʼConnor, Sarah P; Greer, Yvonne D; Bachrach, Ann L; Shields, Tony; Fuller, Brett A; Horrigan, Katie; Pritchard, Kathleen; Springer, Judy B; Meurer, John R

2015-01-01

Despite increased attention, conventional views of obesity are based upon individual behaviors, and children and parents living with obesity are assumed to be the primary problem solvers. Instead of focusing exclusively on individual reduction behaviors for childhood obesity, greater focus should be placed on better understanding existing community systems and their effects on obesity. The Milwaukee Childhood Obesity Prevention Project is a community-based coalition established to develop policy and environmental change strategies to impact childhood obesity in Milwaukee, Wisconsin. The coalition conducted a Group Model Building exercise to better understand root causes of childhood obesity in its community. Group Model Building is a process by which a group systematically engages in model construction to better understand the systems that are in place. It helps participants make their mental models explicit through a careful and consistent process to test assumptions. This process has 3 main components: (1) assembling a team of participants; (2) conducting a behavior-over-time graphs exercise; and (3) drawing the causal loop diagram exercise. The behavior-over-time graph portion produced 61 graphs in 10 categories. The causal loop diagram yielded 5 major themes and 7 subthemes. Factors that influence childhood obesity are varied, and it is important to recognize that no single solution exists. The perspectives from this exercise provided a means to create a process for dialogue and commitment by stakeholders and partnerships to build capacity for change within the community.

Probability based models for estimation of wildfire risk

Treesearch

Haiganoush Preisler; D. R. Brillinger; R. E. Burgan; John Benoit

2004-01-01

We present a probability-based model for estimating fire risk. Risk is defined using three probabilities: the probability of fire occurrence; the conditional probability of a large fire given ignition; and the unconditional probability of a large fire. The model is based on grouped data at the 1 km²-day cell level. We fit a spatially and temporally explicit non-...

A model for the perception of environmental sound based on notice-events.

PubMed

De Coensel, Bert; Botteldooren, Dick; De Muer, Tom; Berglund, Birgitta; Nilsson, Mats E; Lercher, Peter

2009-08-01

An approach is proposed to shed light on the mechanisms underlying human perception of environmental sound that intrudes in everyday living. Most research on exposure-effect relationships aims at relating overall effects to overall exposure indicators in an epidemiological fashion, without including available knowledge on the possible underlying mechanisms. Here, it is proposed to start from available knowledge on audition and perception to construct a computational framework for the effect of environmental sound on individuals. Obviously, at the individual level additional mechanisms (inter-sensory, attentional, cognitive, emotional) play a role in the perception of environmental sound. As a first step, current knowledge is made explicit by building a model mimicking some aspects of human auditory perception. This model is grounded in the hypothesis that long-term perception of environmental sound is determined primarily by short notice-events. The applicability of the notice-event model is illustrated by simulating a synthetic population exposed to typical Flemish environmental noise. From these simulation results, it is demonstrated that the notice-event model is able to mimic the differences between the annoyance caused by road traffic noise exposure and railway traffic noise exposure that are also observed empirically in other studies and thus could provide an explanation for these differences.

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Population density estimated from locations of individuals on a passive detector array

USGS Publications Warehouse

Efford, Murray G.; Dawson, Deanna K.; Borchers, David L.

2009-01-01

The density of a closed population of animals occupying stable home ranges may be estimated from detections of individuals on an array of detectors, using newly developed methods for spatially explicit capture–recapture. Likelihood-based methods provide estimates for data from multi-catch traps or from devices that record presence without restricting animal movement ("proximity" detectors such as camera traps and hair snags). As originally proposed, these methods require multiple sampling intervals. We show that equally precise and unbiased estimates may be obtained from a single sampling interval, using only the spatial pattern of detections. This considerably extends the range of possible applications, and we illustrate the potential by estimating density from simulated detections of bird vocalizations on a microphone array. Acoustic detection can be defined as occurring when received signal strength exceeds a threshold. We suggest detection models for binary acoustic data, and for continuous data comprising measurements of all signals above the threshold. While binary data are often sufficient for density estimation, modeling signal strength improves precision when the microphone array is small.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina.

PubMed

Flores, Celina E; Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species' distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina

PubMed Central

Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species’ distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns. PMID:29782523

Derivation of an Explicit Form of the Percolation-Based Effective-Medium Approximation for Thermal Conductivity of Partially Saturated Soils

NASA Astrophysics Data System (ADS)

Sadeghi, Morteza; Ghanbarian, Behzad; Horton, Robert

2018-02-01

Thermal conductivity is an essential component in multiphysics models and coupled simulation of heat transfer, fluid flow, and solute transport in porous media. In the literature, various empirical, semiempirical, and physical models were developed for thermal conductivity and its estimation in partially saturated soils. Recently, Ghanbarian and Daigle (GD) proposed a theoretical model, using the percolation-based effective-medium approximation, whose parameters are physically meaningful. The original GD model implicitly formulates thermal conductivity λ as a function of volumetric water content θ. For the sake of computational efficiency in numerical calculations, in this study, we derive an explicit λ(θ) form of the GD model. We also demonstrate that some well-known empirical models, e.g., Chung-Horton, widely applied in the HYDRUS model, as well as mixing models are special cases of the GD model under specific circumstances. Comparison with experiments indicates that the GD model can accurately estimate soil thermal conductivity.

First Gridded Spatial Field Reconstructions of Snow from Tree Rings

NASA Astrophysics Data System (ADS)

Coulthard, B. L.; Anchukaitis, K. J.; Pederson, G. T.; Alder, J. R.; Hostetler, S. W.; Gray, S. T.

2017-12-01

Western North America's mountain snowpacks provide critical water resources for human populations and ecosystems. Warmer temperatures and changing precipitation patterns will increasingly alter the quantity, extent, and persistence of snow in coming decades. A comprehensive understanding of the causes and range of long-term variability in this system is required for forecasting future anomalies, but snowpack observations are limited and sparse. While individual tree ring-based annual snowpack reconstructions have been developed for specific regions and mountain ranges, we present here the first collection of spatially-explicit gridded field reconstructions of seasonal snowpack within the American Rocky Mountains. Capitalizing on a new western North American snow-sensitive network of over 700 tree-ring chronologies, as well as recent advances in PRISM-based snow modeling, our gridded reconstructions offer a full space-time characterization of snow and associated water resource fluctuations over several centuries. The quality of reconstructions is evaluated against existing observations, proxy-records, and an independently-developed first-order monthly snow model.

Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

NASA Astrophysics Data System (ADS)

He, Hongxing; Meyer, Astrid; Jansson, Per-Erik; Svensson, Magnus; Rütting, Tobias; Klemedtsson, Leif

2018-02-01

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models.

In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period.

The nonlim approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.

Bayesian analysis of multi-state data with individual covariates for estimating genetic effects on demography

USGS Publications Warehouse

Converse, Sarah J.; Royle, J. Andrew; Urbanek, Richard P.

2012-01-01

Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.

Dynamic Impact Tolerance of Shuttle RCC Leading Edge Panels using LS-DYNA

NASA Technical Reports Server (NTRS)

Fasanella, Edwin; Jackson, Karen E.; Lyle, Karen H.; Jones, Lisa E.; Hardy, Robin C.; Spellman, Regina L.; Carney, Kelly S.; Melis, Matthew E.; Stockwell, Alan E.

2008-01-01

This paper describes a research program conducted to enable accurate prediction of the impact tolerance of the shuttle Orbiter leading-edge wing panels using 'physics-based- codes such as LS-DYNA, a nonlinear, explicit transient dynamic finite element code. The shuttle leading-edge panels are constructed of Reinforced-Carbon-Carbon (RCC) composite material, which issued because of its thermal properties to protect the shuttle during re-entry into the Earth's atmosphere. Accurate predictions of impact damage from insulating foam and other debris strikes that occur during launch required materials characterization of expected debris, including strain-rate effects. First, analytical models of individual foam and RCC materials were validated. Next, analytical models of individual foam cylinders impacting 6-in. x 6-in. RCC flat plates were developed and validated. LS-DYNA pre-test models of the RCC flat plate specimens established the impact velocity of the test for three damage levels: no-detectable damage, non-destructive evaluation (NDE) detectable damage, or visible damage such as a through crack or hole. Finally, the threshold of impact damage for RCC on representative Orbiter wing panels was predicted for both a small through crack and for NDE-detectable damage.

The explicit and implicit dance in psychoanalytic change.

PubMed

Fosshage, James L

2004-02-01

How the implicit/non-declarative and explicit/declarative cognitive domains interact is centrally important in the consideration of effecting change within the psychoanalytic arena. Stern et al. (1998) declare that long-lasting change occurs in the domain of implicit relational knowledge. In the view of this author, the implicit and explicit domains are intricately intertwined in an interactive dance within a psychoanalytic process. The author views that a spirit of inquiry (Lichtenberg, Lachmann & Fosshage 2002) serves as the foundation of the psychoanalytic process. Analyst and patient strive to explore, understand and communicate and, thereby, create a 'spirit' of interaction that contributes, through gradual incremental learning, to new implicit relational knowledge. This spirit, as part of the implicit relational interaction, is a cornerstone of the analytic relationship. The 'inquiry' more directly brings explicit/declarative processing to the foreground in the joint attempt to explore and understand. The spirit of inquiry in the psychoanalytic arena highlights both the autobiographical scenarios of the explicit memory system and the mental models of the implicit memory system as each contributes to a sense of self, other, and self with other. This process facilitates the extrication and suspension of the old models, so that new models based on current relational experience can be gradually integrated into both memory systems for lasting change.

On the solution of evolution equations based on multigrid and explicit iterative methods

NASA Astrophysics Data System (ADS)

Zhukov, V. T.; Novikova, N. D.; Feodoritova, O. B.

2015-08-01

Two schemes for solving initial-boundary value problems for three-dimensional parabolic equations are studied. One is implicit and is solved using the multigrid method, while the other is explicit iterative and is based on optimal properties of the Chebyshev polynomials. In the explicit iterative scheme, the number of iteration steps and the iteration parameters are chosen as based on the approximation and stability conditions, rather than on the optimization of iteration convergence to the solution of the implicit scheme. The features of the multigrid scheme include the implementation of the intergrid transfer operators for the case of discontinuous coefficients in the equation and the adaptation of the smoothing procedure to the spectrum of the difference operators. The results produced by these schemes as applied to model problems with anisotropic discontinuous coefficients are compared.

Reducing obesity prejudice in medical education.

PubMed

Matharu, Kabir; Shapiro, Johanna F; Hammer, Rachel R; Kravitz, R L; Wilson, Machelle D; Fitzgerald, Faith T

2014-01-01

Healthcare worker attitudes toward obese individuals facilitate discrimination and contribute to poor health outcomes. Previous studies have demonstrated medical student bias toward obese individuals, but few have examined effects of the educational environment on these prejudicial beliefs. We sought to determine whether an innovative educational intervention (reading a play about obesity) could diminish obesity prejudice relative to a standard medical lecture. We conducted a randomized, controlled trial enrolling medical students (n = 129) from three universities. Students were assigned to play-reading or a standard lecture. Explicit attitudes and implicit bias toward obese individuals were assessed prior to intervention and after four months. At baseline, students demonstrated moderate explicit and implicit bias toward obese people despite high scores on empathy. Students randomized to the play-reading group had significantly decreased explicit fat bias (P = 0.01) at follow-up, while students in the lecture group showed increased endorsement of a prescriptive model of care at the expense of a patient-centered approach (P = 0.03). There was a significant increase in empathy for those in both the theater (P = 0.007) and lecture group (P = 0.02). The intervention had no significant effect on implicit bias or regard for obesity as a civil rights issue. Dramatic reading may be superior to traditional medical lectures for showcasing patient rights and preferences. The present study demonstrates for the first time that play-reading diminishes conscious obesity bias. Further research should determine whether nontraditional methods of instruction promote improved understanding of and care for obese patients.

Explicit Pharmacokinetic Modeling: Tools for Documentation, Verification, and Portability

EPA Science Inventory

Quantitative estimates of tissue dosimetry of environmental chemicals due to multiple exposure pathways require the use of complex mathematical models, such as physiologically-based pharmacokinetic (PBPK) models. The process of translating the abstract mathematics of a PBPK mode...

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

How to Analyze Interpersonal and Individual Effects in Peer-Tutored Reading Intervention

ERIC Educational Resources Information Center

Müller, Bettina; Richter, Tobias; Križan, Ana; Hecht, Teresa; Ennemoser, Marco

2016-01-01

Reading strategy interventions relying upon peer tutoring are a common way to foster poor readers' comprehension skills. Those interventions are based on the assumption that tutees benefit from the (higher) reading skills of their tutors. However, this interpersonal effect has not yet been tested explicitly because the effectiveness of peer…

Teaching Scientists to Communicate: Evidence-based assessment for undergraduate science education

NASA Astrophysics Data System (ADS)

Mercer-Mapstone, Lucy; Kuchel, Louise

2015-07-01

Communication skills are one of five nationally recognised learning outcomes for an Australian Bachelor of Science (BSc) degree. Previous evidence indicates that communication skills taught in Australian undergraduate science degrees are not developed sufficiently to meet the requirements of the modern-day workplace-a problem faced in the UK and USA also. Curriculum development in this area, however, hinges on first evaluating how communication skills are taught currently as a base from which to make effective changes. This study aimed to quantify the current standard of communication education within BSc degrees at Australian research-intensive universities. A detailed evidential baseline for not only what but also how communication skills are being taught was established. We quantified which communication skills were taught and assessed explicitly, implicitly, or were absent in a range of undergraduate science assessment tasks (n = 35) from four research-intensive Australian universities. Results indicate that 10 of the 12 core science communication skills used for evaluation were absent from more than 50% of assessment tasks and 77.14% of all assessment tasks taught less than 5 core communication skills explicitly. The design of assessment tasks significantly affected whether communication skills were taught explicitly. Prominent trends were that communication skills in tasks aimed at non-scientific audiences were taught more explicitly than in tasks aimed at scientific audiences, and the majority of group and multimedia tasks taught communication elements more explicitly than individual, or written and oral tasks. Implications for science communication in the BSc and further research are discussed.

Estimating the population density of the Asian tapir (Tapirus indicus) in a selectively logged forest in Peninsular Malaysia.

PubMed

Rayan, D Mark; Mohamad, Shariff Wan; Dorward, Leejiah; Aziz, Sheema Abdul; Clements, Gopalasamy Reuben; Christopher, Wong Chai Thiam; Traeholt, Carl; Magintan, David

2012-12-01

The endangered Asian tapir (Tapirus indicus) is threatened by large-scale habitat loss, forest fragmentation and increased hunting pressure. Conservation planning for this species, however, is hampered by a severe paucity of information on its ecology and population status. We present the first Asian tapir population density estimate from a camera trapping study targeting tigers in a selectively logged forest within Peninsular Malaysia using a spatially explicit capture-recapture maximum likelihood based framework. With a trap effort of 2496 nights, 17 individuals were identified corresponding to a density (standard error) estimate of 9.49 (2.55) adult tapirs/100 km(2) . Although our results include several caveats, we believe that our density estimate still serves as an important baseline to facilitate the monitoring of tapir population trends in Peninsular Malaysia. Our study also highlights the potential of extracting vital ecological and population information for other cryptic individually identifiable animals from tiger-centric studies, especially with the use of a spatially explicit capture-recapture maximum likelihood based framework. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

Breeding success of a marine central place forager in the context of climate change: A modeling approach.

PubMed

Massardier-Galatà, Lauriane; Morinay, Jennifer; Bailleul, Frédéric; Wajnberg, Eric; Guinet, Christophe; Coquillard, Patrick

2017-01-01

In response to climate warming, a southward shift in productive frontal systems serving as the main foraging sites for many top predator species is likely to occur in Subantarctic areas. Central place foragers, such as seabirds and pinnipeds, are thus likely to cope with an increase in the distance between foraging locations and their land-based breeding colonies. Understanding how central place foragers should modify their foraging behavior in response to changes in prey accessibility appears crucial. A spatially explicit individual-based simulation model (Marine Central Place Forager Simulator (MarCPFS)), including bio-energetic components, was built to evaluate effects of possible changes in prey resources accessibility on individual performances and breeding success. The study was calibrated on a particular example: the Antarctic fur seal (Arctocephalus gazella), which alternates between oceanic areas in which females feed and the land-based colony in which they suckle their young over a 120 days rearing period. Our model shows the importance of the distance covered to feed and prey aggregation which appeared to be key factors to which animals are highly sensitive. Memorization and learning abilities also appear to be essential breeding success traits. Females were found to be most successful for intermediate levels of prey aggregation and short distance to the resource, resulting in optimal female body length. Increased distance to resources due to climate warming should hinder pups' growth and survival while female body length should increase.

Breeding success of a marine central place forager in the context of climate change: A modeling approach

PubMed Central

Massardier-Galatà, Lauriane; Morinay, Jennifer; Bailleul, Frédéric; Wajnberg, Eric; Guinet, Christophe; Coquillard, Patrick

2017-01-01

In response to climate warming, a southward shift in productive frontal systems serving as the main foraging sites for many top predator species is likely to occur in Subantarctic areas. Central place foragers, such as seabirds and pinnipeds, are thus likely to cope with an increase in the distance between foraging locations and their land-based breeding colonies. Understanding how central place foragers should modify their foraging behavior in response to changes in prey accessibility appears crucial. A spatially explicit individual-based simulation model (Marine Central Place Forager Simulator (MarCPFS)), including bio-energetic components, was built to evaluate effects of possible changes in prey resources accessibility on individual performances and breeding success. The study was calibrated on a particular example: the Antarctic fur seal (Arctocephalus gazella), which alternates between oceanic areas in which females feed and the land-based colony in which they suckle their young over a 120 days rearing period. Our model shows the importance of the distance covered to feed and prey aggregation which appeared to be key factors to which animals are highly sensitive. Memorization and learning abilities also appear to be essential breeding success traits. Females were found to be most successful for intermediate levels of prey aggregation and short distance to the resource, resulting in optimal female body length. Increased distance to resources due to climate warming should hinder pups’ growth and survival while female body length should increase. PMID:28355282

Do Contact and Empathy Mitigate Bias Against Gay and Lesbian People Among Heterosexual First-Year Medical Students? A Report From the Medical Student CHANGE Study.

PubMed

Burke, Sara E; Dovidio, John F; Przedworski, Julia M; Hardeman, Rachel R; Perry, Sylvia P; Phelan, Sean M; Nelson, David B; Burgess, Diana J; Yeazel, Mark W; van Ryn, Michelle

2015-05-01

A recent Institute of Medicine report concluded that lesbian and gay individuals face discrimination from health care providers and called for research on provider attitudes. Medical school is a critical juncture for improving future providers' treatment of sexual minorities. This study examined both explicit bias and implicit bias against lesbian women and gay men among first-year medical students, focusing on two predictors of such bias, contact and empathy. This study included the 4,441 heterosexual first-year medical students who participated in the baseline survey of the Medical Student Cognitive Habits and Growth Evaluation Study, which employed a stratified random sample of 49 U.S. medical schools in fall 2010. The researchers measured explicit attitudes toward gay and lesbian people using feeling thermometer self-assessments, implicit attitudes using the Implicit Association Test, amount and favorability of contact using self-report items, and empathy using subscales of the Interpersonal Reactivity Index. Nearly half (45.79%; 956/2,088) of respondents with complete data on both bias measures expressed at least some explicit bias, and most (81.51%; 1,702/2,088) exhibited at least some implicit bias against gay and lesbian individuals. Both amount and favorability of contact predicted positive implicit and explicit attitudes. Both cognitive and emotional empathy predicted positive explicit attitudes, but not implicit attitudes. The prevalence of negative attitudes presents an important challenge for medical education, highlighting the need for more research on possible causes of bias. Findings on contact and empathy point to possible curriculum-based interventions aimed at ensuring high-quality care for sexual minorities.

An efficient hydro-mechanical model for coupled multi-porosity and discrete fracture porous media

NASA Astrophysics Data System (ADS)

Yan, Xia; Huang, Zhaoqin; Yao, Jun; Li, Yang; Fan, Dongyan; Zhang, Kai

2018-02-01

In this paper, a numerical model is developed for coupled analysis of deforming fractured porous media with multiscale fractures. In this model, the macro-fractures are modeled explicitly by the embedded discrete fracture model, and the supporting effects of fluid and fillings in these fractures are represented explicitly in the geomechanics model. On the other hand, matrix and micro-fractures are modeled by a multi-porosity model, which aims to accurately describe the transient matrix-fracture fluid exchange process. A stabilized extended finite element method scheme is developed based on the polynomial pressure projection technique to address the displacement oscillation along macro-fracture boundaries. After that, the mixed space discretization and modified fixed stress sequential implicit methods based on non-matching grids are applied to solve the coupling model. Finally, we demonstrate the accuracy and application of the proposed method to capture the coupled hydro-mechanical impacts of multiscale fractures on fractured porous media.

Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model

NASA Astrophysics Data System (ADS)

Verburg, Peter H.; Soepboer, Welmoed; Veldkamp, A.; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S. A.

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Modeling the spatial dynamics of regional land use: the CLUE-S model.

PubMed

Verburg, Peter H; Soepboer, Welmoed; Veldkamp, A; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S A

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Polyelectrolyte properties of single stranded DNA measured using SAXS and single molecule FRET: beyond the wormlike chain model

PubMed Central

Meisburger, Steve P.; Sutton, Julie L.; Chen, Huimin; Pabit, Suzette A.; Kirmizialtin, Serdal; Elber, Ron; Pollack, Lois

2013-01-01

Nucleic acids are highly charged polyelectrolytes that interact strongly with salt ions. Rigid, base-paired regions are successfully described with worm like chain models, but non base-paired single stranded regions have fundamentally different polymer properties because of their greater flexibility. Recently, attention has turned to single stranded nucleic acids due to the growing recognition of their biological importance, as well as the availability of sophisticated experimental techniques sensitive to the conformation of individual molecules. We investigate polyelectrolyte properties of poly(dT), an important and widely studied model system for flexible single stranded nucleic acids, in physiologically important mixed mono- and di-valent salt. We report measurements of the form factor and interparticle interactions using SAXS, end to end distances using smFRET, and number of excess ions using ASAXS. We present a coarse-grained model that accounts for flexibility, excluded volume, and electrostatic interactions in these systems. Predictions of the model are validated against experiment. We also discuss the state of all-atom, explicit solvent Molecular Dynamics simulations of poly(dT), the next step in understanding the complexities of ion interactions with these highly charged and flexible polymers. PMID:23606337

An equilibrium-point model for fast, single-joint movement: I. Emergence of strategy-dependent EMG patterns.

PubMed

Latash, M L; Gottlieb, G L

1991-09-01

We describe a model for the regulation of fast, single-joint movements, based on the equilibrium-point hypothesis. Limb movement follows constant rate shifts of independently regulated neuromuscular variables. The independently regulated variables are tentatively identified as thresholds of a length sensitive reflex for each of the participating muscles. We use the model to predict EMG patterns associated with changes in the conditions of movement execution, specifically, changes in movement times, velocities, amplitudes, and moments of limb inertia. The approach provides a theoretical neural framework for the dual-strategy hypothesis, which considers certain movements to be results of one of two basic, speed-sensitive or speed-insensitive strategies. This model is advanced as an alternative to pattern-imposing models based on explicit regulation of timing and amplitudes of signals that are explicitly manifest in the EMG patterns.

Modeling mechanical inhomogeneities in small populations of proliferating monolayers and spheroids.

PubMed

Lejeune, Emma; Linder, Christian

2018-06-01

Understanding the mechanical behavior of multicellular monolayers and spheroids is fundamental to tissue culture, organism development, and the early stages of tumor growth. Proliferating cells in monolayers and spheroids experience mechanical forces as they grow and divide and local inhomogeneities in the mechanical microenvironment can cause individual cells within the multicellular system to grow and divide at different rates. This differential growth, combined with cell division and reorganization, leads to residual stress. Multiple different modeling approaches have been taken to understand and predict the residual stresses that arise in growing multicellular systems, particularly tumor spheroids. Here, we show that by using a mechanically robust agent-based model constructed with the peridynamic framework, we gain a better understanding of residual stresses in multicellular systems as they grow from a single cell. In particular, we focus on small populations of cells (1-100 s) where population behavior is highly stochastic and prior investigation has been limited. We compare the average strain energy density of cells in monolayers and spheroids using different growth and division rules and find that, on average, cells in spheroids have a higher strain energy density than cells in monolayers. We also find that cells in the interior of a growing spheroid are, on average, in compression. Finally, we demonstrate the importance of accounting for stochastic fluctuations in the mechanical environment, particularly when the cellular response to mechanical cues is nonlinear. The results presented here serve as a starting point for both further investigation with agent-based models, and for the incorporation of major findings from agent-based models into continuum scale models when explicit representation of individual cells is not computationally feasible.

The convergent and concurrent validity of trait-based prototype assessment of personality disorder categories in homeless persons.

PubMed

Samuel, Douglas B; Connolly, Adrian J; Ball, Samuel A

2012-09-01

The DSM-5 proposal indicates that personality disorders (PDs) be defined as collections of maladaptive traits but does not provide a specific diagnostic method. However, researchers have previously suggested that PD constructs can be assessed by comparing individuals' trait profiles with those prototypic of PDs and evidence from the five-factor model (FFM) suggests that these prototype matching scores converge moderately with traditional PD instruments. The current study investigates the convergence of FFM PD prototypes with interview-assigned PD diagnoses in a sample of 99 homeless individuals. This sample had very high rates of PDs, which extends previous research on samples with more modest prevalence rates. Results indicated that diagnostic agreement between these methods was generally low but consistent with the agreement previously observed between explicit PD measures. Furthermore, trait-based and diagnostic interview scores evinced similar relationships with clinically important indicators such as abuse history and past suicide attempts. These findings demonstrate the validity of prototype methods and suggest their consideration for assessing trait-defined PD types within DSM-5.

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

PubMed Central

Marai, G. Elisabeta

2018-01-01

Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage—and its evaluation—of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature. PMID:28866550

All-Atom Polarizable Force Field for DNA Based on the Classical Drude Oscillator Model

PubMed Central

Savelyev, Alexey; MacKerell, Alexander D.

2014-01-01

Presented is a first generation atomistic force field for DNA in which electronic polarization is modeled based on the classical Drude oscillator formalism. The DNA model is based on parameters for small molecules representative of nucleic acids, including alkanes, ethers, dimethylphosphate, and the nucleic acid bases and empirical adjustment of key dihedral parameters associated with the phosphodiester backbone, glycosidic linkages and sugar moiety of DNA. Our optimization strategy is based on achieving a compromise between satisfying the properties of the underlying model compounds in the gas phase targeting QM data and reproducing a number of experimental properties of DNA duplexes in the condensed phase. The resulting Drude force field yields stable DNA duplexes on the 100 ns time scale and satisfactorily reproduces (1) the equilibrium between A and B forms of DNA and (2) transitions between the BI and BII sub-states of B form DNA. Consistency with the gas phase QM data for the model compounds is significantly better for the Drude model as compared to the CHARMM36 additive force field, which is suggested to be due to the improved response of the model to changes in the environment associated with the explicit inclusion of polarizability. Analysis of dipole moments associated with the nucleic acid bases shows the Drude model to have significantly larger values than those present in CHARMM36, with the dipoles of individual bases undergoing significant variations during the MD simulations. Additionally, the dipole moment of water was observed to be perturbed in the grooves of DNA. PMID:24752978

Comparing implicit and explicit semantic access of direct and indirect word pairs in schizophrenia to evaluate models of semantic memory.

PubMed

Neill, Erica; Rossell, Susan Lee

2013-02-28

Semantic memory deficits in schizophrenia (SZ) are profound, yet there is no research comparing implicit and explicit semantic processing in the same participant sample. In the current study, both implicit and explicit priming are investigated using direct (LION-TIGER) and indirect (LION-STRIPES; where tiger is not displayed) stimuli comparing SZ to healthy controls. Based on a substantive review (Rossell and Stefanovic, 2007) and meta-analysis (Pomarol-Clotet et al., 2008), it was predicted that SZ would be associated with increased indirect priming implicitly. Further, it was predicted that SZ would be associated with abnormal indirect priming explicitly, replicating earlier work (Assaf et al., 2006). No specific hypotheses were made for implicit direct priming due to the heterogeneity of the literature. It was hypothesised that explicit direct priming would be intact based on the structured nature of this task. The pattern of results suggests (1) intact reaction time (RT) and error performance implicitly in the face of abnormal direct priming and (2) impaired RT and error performance explicitly. This pattern confirms general findings regarding implicit/explicit memory impairments in SZ whilst highlighting the unique pattern of performance specific to semantic priming. Finally, priming performance is discussed in relation to thought disorder and length of illness. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism.

PubMed

Goh, Garrett B; Hulbert, Benjamin S; Zhou, Huiqing; Brooks, Charles L

2014-07-01

pH is a ubiquitous regulator of biological activity, including protein-folding, protein-protein interactions, and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH-dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi-site λ-dynamics (CPHMD(MSλD)). In the CPHMD(MSλD) framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi-site λ-dynamics, and designed novel biasing potentials to ensure that the physical end-states are predominantly sampled. We show that explicit solvent CPHMD(MSλD) simulations model realistic pH-dependent properties of proteins such as the Hen-Egg White Lysozyme (HEWL), binding domain of 2-oxoglutarate dehydrogenase (BBL) and N-terminal domain of ribosomal protein L9 (NTL9), and the pKa predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 pKa units. With the recent development of the explicit solvent CPHMD(MSλD) framework for nucleic acids, accurate modeling of pH-dependent properties of both major class of biomolecules-proteins and nucleic acids is now possible. © 2013 Wiley Periodicals, Inc.

Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: placing back-calculations in a formal statistical framework.

PubMed

Jones, Hayley E; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J; Baker, David R; Ades, A E

2014-07-15

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these 'back-calculations', the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. Copyright © 2014. Published by Elsevier B.V.

Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: Placing back-calculations in a formal statistical framework

PubMed Central

Jones, Hayley E.; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J.; Baker, David R.; Ades, A.E.

2014-01-01

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these ‘back-calculations’, the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. PMID:24636801

Using eye movements as an index of implicit face recognition in autism spectrum disorder.

PubMed

Hedley, Darren; Young, Robyn; Brewer, Neil

2012-10-01

Individuals with an autism spectrum disorder (ASD) typically show impairment on face recognition tasks. Performance has usually been assessed using overt, explicit recognition tasks. Here, a complementary method involving eye tracking was used to examine implicit face recognition in participants with ASD and in an intelligence quotient-matched non-ASD control group. Differences in eye movement indices between target and foil faces were used as an indicator of implicit face recognition. Explicit face recognition was assessed using old-new discrimination and reaction time measures. Stimuli were faces of studied (target) or unfamiliar (foil) persons. Target images at test were either identical to the images presented at study or altered by changing the lighting, pose, or by masking with visual noise. Participants with ASD performed worse than controls on the explicit recognition task. Eye movement-based measures, however, indicated that implicit recognition may not be affected to the same degree as explicit recognition. Autism Res 2012, 5: 363-379. © 2012 International Society for Autism Research, Wiley Periodicals, Inc. © 2012 International Society for Autism Research, Wiley Periodicals, Inc.

Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling.

PubMed

Garcia, Leandro M T; Diez Roux, Ana V; Martins, André C R; Yang, Yong; Florindo, Alex A

2017-08-22

Despite the increasing body of evidences on the factors influencing leisure-time physical activity, our understanding of the mechanisms and interactions that lead to the formation and evolution of population patterns is still limited. Moreover, most frameworks in this field fail to capture dynamic processes. Our aim was to create a dynamic conceptual model depicting the interaction between key psychological attributes of individuals and main aspects of the built and social environments in which they live. This conceptual model will inform and support the development of an agent-based model aimed to explore how population patterns of LTPA in adults may emerge from the dynamic interplay between psychological traits and built and social environments. We integrated existing theories and models as well as available empirical data (both from literature reviews), and expert opinions (based on a systematic expert assessment of an intermediary version of the model). The model explicitly presents intention as the proximal determinant of leisure-time physical activity, a relationship dynamically moderated by the built environment (access, quality, and available activities) - with the strength of the moderation varying as a function of the person's intention- and influenced both by the social environment (proximal network's and community's behavior) and the person's behavior. Our conceptual model is well supported by evidence and experts' opinions and will inform the design of our agent-based model, as well as data collection and analysis of future investigations on population patterns of leisure-time physical activity among adults.

Climate-driven mathematical models to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

NASA Astrophysics Data System (ADS)

Dommar, Carlos J.; Robinson, Marguerite; Lowe, Rachel; Conan, Anne; Buchy, Philippe; Tarantola, Arnaud; Rodó, Xavier

2014-05-01

The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments. The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure versus precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission. Our results highlight the urgent need to establish adequate monitoring and mosquito control programs in vulnerable countries. These models can help to inform public health officials on both the impact and potential spatial expansion of vector-borne diseases through both urban and rural regions under the influence of dynamic climatic conditions. Given the climate sensitivity of vector-borne diseases, such as chikungunya, it is important to link the monitoring of meteorological conditions to public health surveillance and control.

Ecological forestry in an uneven-aged, late-successional forest: Simulated effects of contrasting treatments on structure and yield

Treesearch

Jacob J. Hanson; Craig G. Lorimer; Corey R. Halpin; Brian J. Palik

2012-01-01

Ecological forestry practices are designed to retain species and structural features important for maintaining ecosystem function but which may be deficient in conventionally managed stands. We used the spatially-explicit, individual tree model CANOPY to assess tradeoffs in enhanced ecological attributes vs. reductions in timber yield for a wide variety of treatments...

Teaching the Repeated Prisoner's Dilemma with a Non-Computerised Adaptation of Axelrod's Tournament

ERIC Educational Resources Information Center

Dennis, Catherine

2015-01-01

Darwin's theory of evolution is explicitly competitive, yet co-operation between individuals is a common phenomenon. The Prisoner's Dilemma model is central to the teaching of the evolution of co-operation. The best-known explorations of the Prisoner's Dilemma are the tournaments run by Robert Axelrod in the 1980s. Aimed at students of biological…

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

PubMed Central

Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r = 0.7033, MCCB social cognition r = 0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r = 0.7785, PANSS negative r = 0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. PMID:27177764

There is more than one way to model an elephant. Experiment-driven modeling of the actin cytoskeleton.

PubMed

Ditlev, Jonathon A; Mayer, Bruce J; Loew, Leslie M

2013-02-05

Mathematical modeling has established its value for investigating the interplay of biochemical and mechanical mechanisms underlying actin-based motility. Because of the complex nature of actin dynamics and its regulation, many of these models are phenomenological or conceptual, providing a general understanding of the physics at play. But the wealth of carefully measured kinetic data on the interactions of many of the players in actin biochemistry cries out for the creation of more detailed and accurate models that could permit investigators to dissect interdependent roles of individual molecular components. Moreover, no human mind can assimilate all of the mechanisms underlying complex protein networks; so an additional benefit of a detailed kinetic model is that the numerous binding proteins, signaling mechanisms, and biochemical reactions can be computationally organized in a fully explicit, accessible, visualizable, and reusable structure. In this review, we will focus on how comprehensive and adaptable modeling allows investigators to explain experimental observations and develop testable hypotheses on the intracellular dynamics of the actin cytoskeleton. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

There is More Than One Way to Model an Elephant. Experiment-Driven Modeling of the Actin Cytoskeleton

PubMed Central

Ditlev, Jonathon A.; Mayer, Bruce J.; Loew, Leslie M.

2013-01-01

Mathematical modeling has established its value for investigating the interplay of biochemical and mechanical mechanisms underlying actin-based motility. Because of the complex nature of actin dynamics and its regulation, many of these models are phenomenological or conceptual, providing a general understanding of the physics at play. But the wealth of carefully measured kinetic data on the interactions of many of the players in actin biochemistry cries out for the creation of more detailed and accurate models that could permit investigators to dissect interdependent roles of individual molecular components. Moreover, no human mind can assimilate all of the mechanisms underlying complex protein networks; so an additional benefit of a detailed kinetic model is that the numerous binding proteins, signaling mechanisms, and biochemical reactions can be computationally organized in a fully explicit, accessible, visualizable, and reusable structure. In this review, we will focus on how comprehensive and adaptable modeling allows investigators to explain experimental observations and develop testable hypotheses on the intracellular dynamics of the actin cytoskeleton. PMID:23442903

Dynamics of a Chlorophyll Dimer in Collective and Local Thermal Environments

DOE PAGES

Merkli, M.; Berman, Gennady Petrovich; Sayre, Richard Thomas; ...

2016-01-30

Here we present a theoretical analysis of exciton transfer and decoherence effects in a photosynthetic dimer interacting with collective (correlated) and local (uncorrelated) protein-solvent environments. Our approach is based on the framework of the spin-boson model. We derive explicitly the thermal relaxation and decoherence rates of the exciton transfer process, valid for arbitrary temperatures and for arbitrary (in particular, large) interaction constants between the dimer and the environments. We establish a generalization of the Marcus formula, giving reaction rates for dimer levels possibly individually and asymmetrically coupled to environments. We identify rigorously parameter regimes for the validity of the generalizedmore » Marcus formula. The existence of long living quantum coherences at ambient temperatures emerges naturally from our approach.« less

Do more intelligent brains retain heightened plasticity for longer in development? A computational investigation.

PubMed

Thomas, Michael S C

2016-06-01

Twin studies indicate that the heritability of general cognitive ability - the genetic contribution to individual differences - increases with age. Brant et al. (2013) reported that this increase in heritability occurs earlier in development for low ability children than high ability children. Allied with structural brain imaging results that indicate faster thickening and thinning of cortex for high ability children (Shaw et al., 2006), Brant and colleagues argued higher cognitive ability represents an extended sensitive period for brain development. However, they admitted no coherent mechanistic account can currently reconcile the key empirical data. Here, computational methods are employed to demonstrate the empirical data can be reconciled without recourse to variations in sensitive periods. These methods utilized population-based artificial neural network models of cognitive development. In the model, ability-related variations stemmed from the timing of the increases in the non-linearity of computational processes, causing dizygotic twins to diverge in their behavior. These occurred in a population where: (a) ability was determined by the combined small contributions of many neurocomputational factors, and (b) individual differences in ability were largely genetically constrained. The model's explanation of developmental increases in heritability contrasts with proposals that these increases represent emerging gene-environment correlations (Haworth et al., 2010). The article advocates simulating inherited individual differences within an explicitly developmental framework. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Beta Regression Finite Mixture Models of Polarization and Priming

ERIC Educational Resources Information Center

Smithson, Michael; Merkle, Edgar C.; Verkuilen, Jay

2011-01-01

This paper describes the application of finite-mixture general linear models based on the beta distribution to modeling response styles, polarization, anchoring, and priming effects in probability judgments. These models, in turn, enhance our capacity for explicitly testing models and theories regarding the aforementioned phenomena. The mixture…

Modeling emerald ash borer spread in Ohio and Michigan

Treesearch

Anantha Prasad; Louis Iverson; Matthew Peters; Jonathan Bossenbroek; Davis Sydnor; Mark Schwartz

2008-01-01

Our group has been modelling the spread of emerald ash borer (EAB) in Ohio using a spatially explicit cell-based model that takes into account the insect's flight characteristics (Insect Flight Model) as well as external factors that enable the insects to travel passively (Insect Ride Model).

Genotype calling from next-generation sequencing data using haplotype information of reads

PubMed Central

Zhi, Degui; Wu, Jihua; Liu, Nianjun; Zhang, Kui

2012-01-01

Motivation: Low coverage sequencing provides an economic strategy for whole genome sequencing. When sequencing a set of individuals, genotype calling can be challenging due to low sequencing coverage. Linkage disequilibrium (LD) based refinement of genotyping calling is essential to improve the accuracy. Current LD-based methods use read counts or genotype likelihoods at individual potential polymorphic sites (PPSs). Reads that span multiple PPSs (jumping reads) can provide additional haplotype information overlooked by current methods. Results: In this article, we introduce a new Hidden Markov Model (HMM)-based method that can take into account jumping reads information across adjacent PPSs and implement it in the HapSeq program. Our method extends the HMM in Thunder and explicitly models jumping reads information as emission probabilities conditional on the states of adjacent PPSs. Our simulation results show that, compared to Thunder, HapSeq reduces the genotyping error rate by 30%, from 0.86% to 0.60%. The results from the 1000 Genomes Project show that HapSeq reduces the genotyping error rate by 12 and 9%, from 2.24% and 2.76% to 1.97% and 2.50% for individuals with European and African ancestry, respectively. We expect our program can improve genotyping qualities of the large number of ongoing and planned whole genome sequencing projects. Contact: dzhi@ms.soph.uab.edu; kzhang@ms.soph.uab.edu Availability: The software package HapSeq and its manual can be found and downloaded at www.ssg.uab.edu/hapseq/. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22285565

An ethical justification for the Chronic Care Model (CCM)

PubMed Central

Oprea, Liviu; Braunack‐Mayer, Annette; Rogers, Wendy A.; Stocks, Nigel

2009-01-01

Abstract Background:  Chronic diseases are major causes of morbidity and mortality in developed countries. Their effects can be mitigated by high quality evidence‐based care, but this is not the norm in most systems. The Chronic Care Model (CCM) is an evidence‐based policy response to this practice gap, which uses multiple strategies to promote the quality of chronic care. Objective:  To review CCM with an ethical lens. Methods:  We reviewed the published empirical and non‐empirical articles of CCM to analyse the ethical underpinnings of this model. Results and conclusions:  We argue that its principal ethical value lies in the institutional cooperation it builds between the stakeholders involved in health care services. First, we briefly describe CCM and argue that the pathways through which it aims to improve patients’ health outcomes are not made explicit. Second, we argue that the potential of CCM to be more beneficent, compared with traditional health care systems, depends on its capacity to promote mutual trust between health care providers and patients. There is no evidence to date that the implementation of CCM enhances mutual trust between health care professionals and patients. Third, we argue that CCM seeks to enhance human agency, allowing increased expression of individual autonomy and increased respect for individuals thereby expanding human freedom and avoiding social discrimination. However, we review the communication patterns that characterize the model of doctor–patient relationship promoted by this model and argue that these communication patterns raise ethical concerns that may prevent the model from reaching its expected outcomes. PMID:19906213

Principles of Cancer Screening: Lessons from History and Study Design Issues

PubMed Central

Croswell, Jennifer M.; Ransohoff, David F.; Kramer, Barnett S.

2010-01-01

Early detection of cancer has held great promise and intuitive appeal in the medical community for well over a century. Its history developed in tandem with that of the periodic health examination, in which any deviations—subtle or glaring--from a clearly demarcated “normal” were to be rooted out, given the underlying hypothesis that diseases develop along progressive linear paths of increasing abnormalities. This model of disease development drove the logical deduction that early detection—by “breaking the chain” of cancer development--must be of benefit to affected individuals. In the latter half of the 20th century, researchers and guidelines organizations began to explicitly challenge the core assumptions underpinning many clinical practices. A move away from intuitive thinking began with the development of evidence-based medicine. One key method developed to explicitly quantify the overall risk-benefit profile of a given procedure was the analytic framework. The shift away from pure deductive reasoning and reliance on personal observation was driven, in part, by a rising awareness of critical biases in cancer screening that can mislead clinicians, including healthy volunteer bias, length-biased sampling, lead-time bias, and overdiagnosis. A new focus on the net balance of both benefits and harms when determining the overall worth of an intervention also arose: it was recognized that the potential downsides of early detection were frequently overlooked or discounted because screening is performed on basically healthy persons and initially involves relatively noninvasive methods. Although still inconsistently applied to early detection programs, policies, and belief systems in the United States, an evidence-based approach is essential to counteract the misleading—even potentially harmful--allure of intuition and individual observation. PMID:20709205

Principles of cancer screening: lessons from history and study design issues.

PubMed

Croswell, Jennifer M; Ransohoff, David F; Kramer, Barnett S

2010-06-01

Early detection of cancer has held great promise and intuitive appeal in the medical community for well over a century. Its history developed in tandem with that of the periodic health examination, in which any deviations--subtle or glaring--from a clearly demarcated "normal" were to be rooted out, given the underlying hypothesis that diseases develop along progressive linear paths of increasing abnormalities. This model of disease development drove the logical deduction that early detection, by "breaking the chain" of cancer development, must be of benefit to affected individuals. In the latter half of the 20th century, researchers and guidelines organizations began to explicitly challenge the core assumptions underpinning many clinical practices. A move away from intuitive thinking began with the development of evidence-based medicine. One key method developed to explicitly quantify the overall risk-benefit profile of a given procedure was the analytic framework. The shift away from pure deductive reasoning and reliance on personal observation was driven, in part, by a rising awareness of critical biases in cancer screening that can mislead clinicians, including healthy volunteer bias, length-biased sampling, lead-time bias, and overdiagnosis. A new focus on the net balance of both benefits and harms when determining the overall worth of an intervention also arose: it was recognized that the potential downsides of early detection were frequently overlooked or discounted because screening is performed on basically healthy persons and initially involves relatively noninvasive methods. Although still inconsistently applied to early detection programs, policies, and belief systems in the United States, an evidence-based approach is essential to counteract the misleading--even potentially harmful--allure of intuition and individual observation. Published by Elsevier Inc.

Dynamics of prey moving through a predator field: a model of migrating juvenile salmon

USGS Publications Warehouse

Petersen, J.H.; DeAngelis, D.L.

2000-01-01

The migration of a patch of prey through a field of relatively stationary predators is a situation that occurs frequently in nature. Making quantitative predictions concerning such phenomena may be difficult, however, because factors such as the number of the prey in the patch, the spatial length and velocity of the patch, and the feeding rate and satiation of the predators all interact in a complex way. However, such problems are of great practical importance in many management situations; e.g., calculating the mortality of juvenile salmon (smolts) swimming down a river or reservoir containing many predators. Salmon smolts often move downstream in patches short compared with the length of the reservoir. To take into account the spatial dependence of the interaction, we used a spatially-explicit, individual-based modeling approach. We found that the mortality of prey depends strongly on the number of prey in the patch, the downstream velocity of prey in the patch, and the dispersion or spread of the patch in size through time. Some counterintuitive phenomena are predicted, such as predators downstrean capturing more prey per predator than those upstream, even though the number of prey may be greatly depleted by the time the prey patch reaches the downstream predators. Individual-based models may be necessary for complex spatial situations, such as salmonid migration, where processes such as schooling occur at fine scales and affect system predictions. We compare some results to predictions from other salmonid models. (C) 2000 Elsevier Science Inc.

Performing the unexplainable: Implicit task performance reveals individually reliable sequence learning without explicit knowledge

PubMed Central

Sanchez, Daniel J.; Gobel, Eric W.; Reber, Paul J.

2015-01-01

Memory-impaired patients express intact implicit perceptual–motor sequence learning, but it has been difficult to obtain a similarly clear dissociation in healthy participants. When explicit memory is intact, participants acquire some explicit knowledge and performance improvements from implicit learning may be subtle. Therefore, it is difficult to determine whether performance exceeds what could be expected on the basis of the concomitant explicit knowledge. Using a challenging new sequence-learning task, robust implicit learning was found in healthy participants with virtually no associated explicit knowledge. Participants trained on a repeating sequence that was selected randomly from a set of five. On a performance test of all five sequences, performance was best on the trained sequence, and two-thirds of the participants exhibited individually reliable improvement (by chi-square analysis). Participants could not reliably indicate which sequence had been trained by either recognition or recall. Only by expressing their knowledge via performance were participants able to indicate which sequence they had learned. PMID:21169570

Knowledge representation to support reasoning based on multiple models

NASA Technical Reports Server (NTRS)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

An explicit three-dimensional nonhydrostatic numerical simulation of a tropical cyclone

NASA Technical Reports Server (NTRS)

Tripoli, G. J.

1992-01-01

A nonhydrostatic numerical simulation of a tropical cyclone is performed with explicit representation of cumulus on a meso-beta scale grid and for a brief period on a meso-gamma scale grid. Individual cumulus plumes are represented by a combination of explicit resolution and a 1.5 level closure predicting turbulent kinetic energy (TKE).

Chimpanzees and the mathematics of battle.

PubMed

Wilson, Michael L; Britton, Nicholas F; Franks, Nigel R

2002-06-07

Recent experiments have demonstrated the importance of numerical assessment in animal contests. Nevertheless, few attempts have been made to model explicitly the relationship between the relative number of combatants on each side and the costs and benefits of entering a contest. One framework that may be especially suitable for making such explicit predictions is Lanchester's theory of combat, which has proved useful for understanding combat strategies in humans and several species of ants. We show, with data from a recent series of playback experiments, that a model derived from Lanchester's 'square law' predicts willingness to enter intergroup contests in wild chimpanzees (Pan troglodytes). Furthermore, the model predicts that, in contests with multiple individuals on each side, chimpanzees in this population should be willing to enter a contest only if they outnumber the opposing side by a factor of 1.5. We evaluate these results for intergroup encounters in chimpanzees and also discuss potential applications of Lanchester's square and linear laws for understanding combat strategies in other species.

Chimpanzees and the mathematics of battle.

PubMed Central

Wilson, Michael L; Britton, Nicholas F; Franks, Nigel R

2002-01-01

Recent experiments have demonstrated the importance of numerical assessment in animal contests. Nevertheless, few attempts have been made to model explicitly the relationship between the relative number of combatants on each side and the costs and benefits of entering a contest. One framework that may be especially suitable for making such explicit predictions is Lanchester's theory of combat, which has proved useful for understanding combat strategies in humans and several species of ants. We show, with data from a recent series of playback experiments, that a model derived from Lanchester's 'square law' predicts willingness to enter intergroup contests in wild chimpanzees (Pan troglodytes). Furthermore, the model predicts that, in contests with multiple individuals on each side, chimpanzees in this population should be willing to enter a contest only if they outnumber the opposing side by a factor of 1.5. We evaluate these results for intergroup encounters in chimpanzees and also discuss potential applications of Lanchester's square and linear laws for understanding combat strategies in other species. PMID:12061952

Parental autonomy support and discrepancies between implicit and explicit sexual identities: dynamics of self-acceptance and defense.

PubMed

Weinstein, Netta; Ryan, William S; Dehaan, Cody R; Przybylski, Andrew K; Legate, Nicole; Ryan, Richard M

2012-04-01

When individuals grow up with autonomy-thwarting parents, they may be prevented from exploring internally endorsed values and identities and as a result shut out aspects of the self perceived to be unacceptable. Given the stigmatization of homosexuality, individuals perceiving low autonomy support from parents may be especially motivated to conceal same-sex sexual attraction, leading to defensive processes such as reaction formation. Four studies tested a model wherein perceived parental autonomy support is associated with lower discrepancies between self-reported sexual orientation and implicit sexual orientation (assessed with a reaction time task). These indices interacted to predict anti-gay responding indicative of reaction formation. Studies 2-4 showed that an implicit/explicit discrepancy was particularly pronounced in participants who experienced their fathers as both low in autonomy support and homophobic, though results were inconsistent for mothers. Findings of Study 3 suggested contingent self-esteem as a link between parenting styles and discrepancies in sexual orientation measures. (c) 2012 APA, all rights reserved.

Traveltime-based descriptions of transport and mixing in heterogeneous domains

NASA Astrophysics Data System (ADS)

Luo, Jian; Cirpka, Olaf A.

2008-09-01

Modeling mixing-controlled reactive transport using traditional spatial discretization of the domain requires identifying the spatial distributions of hydraulic and reactive parameters including mixing-related quantities such as dispersivities and kinetic mass transfer coefficients. In most applications, breakthrough curves (BTCs) of conservative and reactive compounds are measured at only a few locations and spatially explicit models are calibrated by matching these BTCs. A common difficulty in such applications is that the individual BTCs differ too strongly to justify the assumption of spatial homogeneity, whereas the number of observation points is too small to identify the spatial distribution of the decisive parameters. The key objective of the current study is to characterize physical transport by the analysis of conservative tracer BTCs and predict the macroscopic BTCs of compounds that react upon mixing from the interpretation of conservative tracer BTCs and reactive parameters determined in the laboratory. We do this in the framework of traveltime-based transport models which do not require spatially explicit, costly aquifer characterization. By considering BTCs of a conservative tracer measured on different scales, one can distinguish between mixing, which is a prerequisite for reactions, and spreading, which per se does not foster reactions. In the traveltime-based framework, the BTC of a solute crossing an observation plane, or ending in a well, is interpreted as the weighted average of concentrations in an ensemble of non-interacting streamtubes, each of which is characterized by a distinct traveltime value. Mixing is described by longitudinal dispersion and/or kinetic mass transfer along individual streamtubes, whereas spreading is characterized by the distribution of traveltimes, which also determines the weights associated with each stream tube. Key issues in using the traveltime-based framework include the description of mixing mechanisms and the estimation of the traveltime distribution. In this work, we account for both apparent longitudinal dispersion and kinetic mass transfer as mixing mechanisms, thus generalizing the stochastic-convective model with or without inter-phase mass transfer and the advective-dispersive streamtube model. We present a nonparametric approach of determining the traveltime distribution, given a BTC integrated over an observation plane and estimated mixing parameters. The latter approach is superior to fitting parametric models in cases wherein the true traveltime distribution exhibits multiple peaks or long tails. It is demonstrated that there is freedom for the combinations of mixing parameters and traveltime distributions to fit conservative BTCs and describe the tailing. A reactive transport case of a dual Michaelis-Menten problem demonstrates that the reactive mixing introduced by local dispersion and mass transfer may be described by apparent mean mass transfer with coefficients evaluated by local BTCs.

Observational learning by individuals with autism: a review of teaching strategies.

PubMed

Plavnick, Joshua B; Hume, Kara A

2014-05-01

Observational learning is the process used to explain the acquisition of novel behaviors or performance of previously acquired behaviors under novel conditions after observing the behavior of another person and the consequences that follow the behavior. Many learners with autism do not attend to environmental stimuli at a level sufficient to learn a range of prosocial behaviors through observation of others. Modeling, group or dyadic instruction, and explicit observation training can improve the extent to which individuals with autism learn through observation. This article reviews previous research that involved observational learning by individuals with autism and outlines future research that could benefit instructional practices.

Drinkers’ memory bias for alcohol picture cues in explicit and implicit memory tasks

PubMed Central

Nguyen-Louie, Tam T.; Buckman, Jennifer F.; Ray, Suchismita

2016-01-01

Background Alcohol cues can bias attention and elicit emotional reactions, especially in drinkers. Yet, little is known about how alcohol cues affect explicit and implicit memory processes, and how memory for alcohol cues is affected by acute alcohol intoxication. Methods Young adult participants (N=161) were randomly assigned to alcohol, placebo, or control beverage conditions. Following beverage consumption, they were shown neutral, emotional and alcohol-related pictures cues. Participants then completed free recall and repetition priming tasks to test explicit and implicit memory, respectively, for picture cues. Average blood alcohol concentration for the alcohol group was 74 ± 13 mg/dl when memory testing began. Two mixed linear model analyses were conducted to examine the effects of beverage condition, picture cue type, and their interaction on explicit and implicit memory. Results Picture cue type and beverage condition each significantly affected explicit recall of picture cues, whereas only picture cue type significantly influenced repetition priming. Individuals in the alcohol condition recalled significantly fewer pictures than those in other conditions, regardless of cue type. Both free recall and repetition priming were greater for emotional and alcohol-related cues compared to neutral picture cues. No interaction effects were detected. Conclusions Young adult drinkers showed enhanced explicit and implicit memory processing of alcohol cues compared to emotionally neutral cues. This enhanced processing for alcohol cues was on par with that seen for positive emotional cues. Acute alcohol intoxication did not alter this preferential memory processing for alcohol cues over neutral cues. PMID:26811126

Decision support systems in health economics.

PubMed

Quaglini, S; Dazzi, L; Stefanelli, M; Barosi, G; Marchetti, M

1999-08-01

This article describes a system addressed to different health care professionals for building, using, and sharing decision support systems for resource allocation. The system deals with selected areas, namely the choice of diagnostic tests, the therapy planning, and the instrumentation purchase. Decision support is based on decision-analytic models, incorporating an explicit knowledge representation of both the medical domain knowledge and the economic evaluation theory. Application models are built on top of meta-models, that are used as guidelines for making explicit both the cost and effectiveness components. This approach improves the transparency and soundness of the collaborative decision-making process and facilitates the result interpretation.

The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

NASA Astrophysics Data System (ADS)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

A Model-Based Approach to Infer Shifts in Regional Fire Regimes Over Time Using Sediment Charcoal Records

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; Hooten, M.; Higuera, P. E.; Marlon, J. R.; McLachlan, J. S.; Kelly, R.

2016-12-01

Sediment charcoal records are used in paleoecological analyses to identify individual local fire events and to estimate fire frequency and regional biomass burned at centennial to millenial time scales. Methods to identify local fire events based on sediment charcoal records have been well developed over the past 30 years, however, an integrated statistical framework for fire identification is still lacking. We build upon existing paleoecological methods to develop a hierarchical Bayesian point process model for local fire identification and estimation of fire return intervals. The model is unique in that it combines sediment charcoal records from multiple lakes across a region in a spatially-explicit fashion leading to estimation of a joint, regional fire return interval in addition to lake-specific local fire frequencies. Further, the model estimates a joint regional charcoal deposition rate free from the effects of local fires that can be used as a measure of regional biomass burned over time. Finally, the hierarchical Bayesian approach allows for tractable error propagation such that estimates of fire return intervals reflect the full range of uncertainty in sediment charcoal records. Specific sources of uncertainty addressed include sediment age models, the separation of local versus regional charcoal sources, and generation of a composite charcoal record The model is applied to sediment charcoal records from a dense network of lakes in the Yukon Flats region of Alaska. The multivariate joint modeling approach results in improved estimates of regional charcoal deposition with reduced uncertainty in the identification of individual fire events and local fire return intervals compared to individual lake approaches. Modeled individual-lake fire return intervals range from 100 to 500 years with a regional interval of roughly 200 years. Regional charcoal deposition to the network of lakes is correlated up to 50 kilometers. Finally, the joint regional charcoal deposition rate exhibits changes over time coincident with major climatic and vegetation shifts over the past 10,000 years. Ongoing work will use the regional charcoal deposition rate to estimate changes in biomass burned as a function of climate variability and regional vegetation pattern.

An example of population-level risk assessments for small mammals using individual-based population models.

PubMed

Schmitt, Walter; Auteri, Domenica; Bastiansen, Finn; Ebeling, Markus; Liu, Chun; Luttik, Robert; Mastitsky, Sergey; Nacci, Diane; Topping, Chris; Wang, Magnus

2016-01-01

This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. © 2015 SETAC.

Computational neuroanatomy: ontology-based representation of neural components and connectivity

PubMed Central

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-01-01

Background A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future. PMID:19208191

Epideictic Discourse as a Bridge to Argumentation: A Rhetorically Based Strategy for Teaching the Arts of Persuasion.

ERIC Educational Resources Information Center

Ryan, Pat

Epideictic rhetoric, expression of praise or blame, animates much communication, from gossip to sermons, from commercial ads to love letters. Even when writing for purposes other than to judge, writers often frame their talk with implicit or explicit expressions of praise for individuals or groups or ideas considered "good." Epideictic…

Do male and female black-backed woodpeckers respond differently to gaps in habitat?

Treesearch

Jennifer Pierson; Fred W. Allendorf; Vicki Saab; Pierre Drapeau; Michael K. Schwartz

2010-01-01

We used population- and individual-based genetic approaches to assess barriers to movement in black-backed woodpeckers (Picoides arcticus), a fire-specialist that mainly occupies the boreal forest in North America. We tested if male and female woodpeckers exhibited the same movement patterns using both spatially implicit and explicit genetic analyses to define...

Chapter 6: Temperature

USGS Publications Warehouse

Jones, Leslie A.; Muhlfeld, Clint C.; Hauer, F. Richard; F. Richard Hauer,; Lamberti, G.A.

2017-01-01

Stream temperature has direct and indirect effects on stream ecology and is critical in determining both abiotic and biotic system responses across a hierarchy of spatial and temporal scales. Temperature variation is primarily driven by solar radiation, while landscape topography, geology, and stream reach scale ecosystem processes contribute to local variability. Spatiotemporal heterogeneity in freshwater ecosystems influences habitat distributions, physiological functions, and phenology of all aquatic organisms. In this chapter we provide an overview of methods for monitoring stream temperature, characterization of thermal profiles, and modeling approaches to stream temperature prediction. Recent advances in temperature monitoring allow for more comprehensive studies of the underlying processes influencing annual variation of temperatures and how thermal variability may impact aquatic organisms at individual, population, and community based scales. Likewise, the development of spatially explicit predictive models provide a framework for simulating natural and anthropogenic effects on thermal regimes which is integral for sustainable management of freshwater systems.

Implicit and explicit host effects on excitons in pentacene derivatives.

PubMed

Charlton, R J; Fogarty, R M; Bogatko, S; Zuehlsdorff, T J; Hine, N D M; Heeney, M; Horsfield, A P; Haynes, P D

2018-03-14

An ab initio study of the effects of implicit and explicit hosts on the excited state properties of pentacene and its nitrogen-based derivatives has been performed using ground state density functional theory (DFT), time-dependent DFT, and ΔSCF. We observe a significant solvatochromic redshift in the excitation energy of the lowest singlet state (S 1 ) of pentacene from inclusion in a p-terphenyl host compared to vacuum; for an explicit host consisting of six nearest neighbour p-terphenyls, we obtain a redshift of 65 meV while a conductor-like polarisable continuum model (CPCM) yields a 78 meV redshift. Comparison is made between the excitonic properties of pentacene and four of its nitrogen-based analogs, 1,8-, 2,9-, 5,12-, and 6,13-diazapentacene with the latter found to be the most distinct due to local distortions in the ground state electronic structure. We observe that a CPCM is insufficient to fully understand the impact of the host due to the presence of a mild charge-transfer (CT) coupling between the chromophore and neighbouring p-terphenyls, a phenomenon which can only be captured using an explicit model. The strength of this CT interaction increases as the nitrogens are brought closer to the central acene ring of pentacene.

Implicit and explicit host effects on excitons in pentacene derivatives

NASA Astrophysics Data System (ADS)

Charlton, R. J.; Fogarty, R. M.; Bogatko, S.; Zuehlsdorff, T. J.; Hine, N. D. M.; Heeney, M.; Horsfield, A. P.; Haynes, P. D.

2018-03-01

An ab initio study of the effects of implicit and explicit hosts on the excited state properties of pentacene and its nitrogen-based derivatives has been performed using ground state density functional theory (DFT), time-dependent DFT, and ΔSCF. We observe a significant solvatochromic redshift in the excitation energy of the lowest singlet state (S1) of pentacene from inclusion in a p-terphenyl host compared to vacuum; for an explicit host consisting of six nearest neighbour p-terphenyls, we obtain a redshift of 65 meV while a conductor-like polarisable continuum model (CPCM) yields a 78 meV redshift. Comparison is made between the excitonic properties of pentacene and four of its nitrogen-based analogs, 1,8-, 2,9-, 5,12-, and 6,13-diazapentacene with the latter found to be the most distinct due to local distortions in the ground state electronic structure. We observe that a CPCM is insufficient to fully understand the impact of the host due to the presence of a mild charge-transfer (CT) coupling between the chromophore and neighbouring p-terphenyls, a phenomenon which can only be captured using an explicit model. The strength of this CT interaction increases as the nitrogens are brought closer to the central acene ring of pentacene.

Frequency response function-based explicit framework for dynamic identification in human-structure systems

NASA Astrophysics Data System (ADS)

Wei, Xiaojun; Živanović, Stana

2018-05-01

The aim of this paper is to propose a novel theoretical framework for dynamic identification in a structure occupied by a single human. The framework enables the prediction of the dynamics of the human-structure system from the known properties of the individual system components, the identification of human body dynamics from the known dynamics of the empty structure and the human-structure system and the identification of the properties of the structure from the known dynamics of the human and the human-structure system. The novelty of the proposed framework is the provision of closed-form solutions in terms of frequency response functions obtained by curve fitting measured data. The advantages of the framework over existing methods are that there is neither need for nonlinear optimisation nor need for spatial/modal models of the empty structure and the human-structure system. In addition, the second-order perturbation method is employed to quantify the effect of uncertainties in human body dynamics on the dynamic identification of the empty structure and the human-structure system. The explicit formulation makes the method computationally efficient and straightforward to use. A series of numerical examples and experiments are provided to illustrate the working of the method.

First Prismatic Building Model Reconstruction from Tomosar Point Clouds

NASA Astrophysics Data System (ADS)

Sun, Y.; Shahzad, M.; Zhu, X.

2016-06-01

This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

Relevance of behavioral and social models to the study of consumer energy decision making and behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burns, B.A.

This report reviews social and behavioral science models and techniques for their possible use in understanding and predicting consumer energy decision making and behaviors. A number of models and techniques have been developed that address different aspects of the decision process, use different theoretical bases and approaches, and have been aimed at different audiences. Three major areas of discussion were selected: (1) models of adaptation to social change, (2) decision making and choice, and (3) diffusion of innovation. Within these three areas, the contributions of psychologists, sociologists, economists, marketing researchers, and others were reviewed. Five primary components of the modelsmore » were identified and compared. The components are: (1) situational characteristics, (2) product characteristics, (3) individual characteristics, (4) social influences, and (5) the interaction or decision rules. The explicit use of behavioral and social science models in energy decision-making and behavior studies has been limited. Examples are given of a small number of energy studies which applied and tested existing models in studying the adoption of energy conservation behaviors and technologies, and solar technology.« less

Combining information from multiple flood projections in a hierarchical Bayesian framework

NASA Astrophysics Data System (ADS)

Le Vine, Nataliya

2016-04-01

This study demonstrates, in the context of flood frequency analysis, the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach explicitly accommodates shared multimodel discrepancy as well as the probabilistic nature of the flood estimates, and treats the available models as a sample from a hypothetical complete (but unobserved) set of models. The methodology is applied to flood estimates from multiple hydrological projections (the Future Flows Hydrology data set) for 135 catchments in the UK. The advantages of the approach are shown to be: (1) to ensure adequate "baseline" with which to compare future changes; (2) to reduce flood estimate uncertainty; (3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; (4) to diminish the importance of model consistency when model biases are large; and (5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.

Explicit and implicit motor learning in children with unilateral cerebral palsy.

PubMed

van der Kamp, John; Steenbergen, Bert; Masters, Rich S W

2017-07-30

The current study aimed to investigate the capacity for explicit and implicit learning in children with unilateral cerebral palsy. Children with left and right unilateral cerebral palsy and typically developing children shuffled disks toward a target. A prism-adaptation design was implemented, consisting of pre-exposure, prism exposure, and post-exposure phases. Half of the participants were instructed about the function of the prism glasses, while the other half were not. For each trial, the distance between the target and the shuffled disk was determined. Explicit learning was indicated by the rate of adaptation during the prism exposure phase, whereas implicit learning was indicated by the magnitude of the negative after-effect at the start of the post-exposure phase. Results No significant effects were revealed between typically developing participants and participants with unilateral cerebral palsy. Comparison of participants with left and right unilateral cerebral palsy demonstrated that participants with right unilateral cerebral palsy had a significantly lower rate of adaptation than participants with left unilateral cerebral palsy, but only when no instructions were provided. The magnitude of the negative after-effects did not differ significantly between participants with right and left unilateral cerebral palsy. The capacity for explicit motor learning is reduced among individuals with right unilateral cerebral palsy when accumulation of declarative knowledge is unguided (i.e., discovery learning). In contrast, the capacity for implicit learning appears to remain intact among individuals with left as well as right unilateral cerebral palsy. Implications for rehabilitation Implicit motor learning interventions are recommended for individuals with cerebral palsy, particularly for individuals with right unilateral cerebral palsy Explicit motor learning interventions for individual with cerebral palsy - if used - best consist of singular verbal instruction.

A work-centered cognitively based architecture for decision support: the work-centered infomediary layer (WIL) model

NASA Astrophysics Data System (ADS)

Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge

2003-09-01

Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.

Analytical validation of an explicit finite element model of a rolling element bearing with a localised line spall

NASA Astrophysics Data System (ADS)

Singh, Sarabjeet; Howard, Carl Q.; Hansen, Colin H.; Köpke, Uwe G.

2018-03-01

In this paper, numerically modelled vibration response of a rolling element bearing with a localised outer raceway line spall is presented. The results were obtained from a finite element (FE) model of the defective bearing solved using an explicit dynamics FE software package, LS-DYNA. Time domain vibration signals of the bearing obtained directly from the FE modelling were processed further to estimate time-frequency and frequency domain results, such as spectrogram and power spectrum, using standard signal processing techniques pertinent to the vibration-based monitoring of rolling element bearings. A logical approach to analyses of the numerically modelled results was developed with an aim to presenting the analytical validation of the modelled results. While the time and frequency domain analyses of the results show that the FE model generates accurate bearing kinematics and defect frequencies, the time-frequency analysis highlights the simulation of distinct low- and high-frequency characteristic vibration signals associated with the unloading and reloading of the rolling elements as they move in and out of the defect, respectively. Favourable agreement of the numerical and analytical results demonstrates the validation of the results from the explicit FE modelling of the bearing.

Who Shall Not Be Treated: Public Attitudes on Setting Health Care Priorities by Person-Based Criteria in 28 Nations.

PubMed

Rogge, Jana; Kittel, Bernhard

2016-01-01

The principle of distributing health care according to medical need is being challenged by increasing costs. As a result, many countries have initiated a debate on the introduction of explicit priority regulations based on medical, economic and person-based criteria, or have already established such regulations. Previous research on individual attitudes towards setting health care priorities based on medical and economic criteria has revealed consistent results, whereas studies on the use of person-based criteria have generated controversial findings. This paper examines citizens' attitudes towards three person-based priority criteria, patients' smoking habits, age and being the parent of a young child. Using data from the ISSP Health Module (2011) in 28 countries, logistic regression analysis demonstrates that self-interest as well as socio-demographic predictors significantly influence respondents' attitudes towards the use of person-based criteria for health care prioritization. This study contributes to resolving the controversial findings on person-based criteria by using a larger country sample and by controlling for country-level differences with fixed effects models.

Role of Spontaneous Brain Activity in Explicit and Implicit Aspects of Cognitive Flexibility under Socially Conflicting Situations: A Resting-state fMRI Study using Fractional Amplitude of Low-frequency Fluctuations.

PubMed

Fujino, Junya; Tei, Shisei; Jankowski, Kathryn F; Kawada, Ryosaku; Murai, Toshiya; Takahashi, Hidehiko

2017-12-26

We are constantly exposed to socially conflicting situations in everyday life, and cognitive flexibility is essential for adaptively coping with such difficulties. Flexible goal choice and pursuit are not exclusively conscious, and therefore cognitive flexibility involves both explicit and implicit forms of processing. However, it is unclear how individual differences in explicit and implicit aspects of flexibility are associated with neural activity in a resting state. Here, we measured intrinsic fractional amplitude of low-frequency fluctuations (fALFF) by resting-state functional magnetic resonance imaging (RS-fMRI) as an indicator of regional brain spontaneous activity, together with explicit and implicit aspects of cognitive flexibility using the Cognitive Flexibility Scale (CFS) and Implicit Association Test (IAT). Consistent with the dual processing theory, there was a strong association between explicit aspects of flexibility (CFS score) and "rationalism" thinking style and between implicit aspects (IAT effect) and "experientialism." The level of explicit flexibility was also correlated with fALFF values in the left lateral prefrontal cortex, whereas the level of implicit flexibility was correlated with fALFF values in the right cerebellum. Furthermore, the fALFF values in both regions predicted individual preference for flexible decision-making strategy in a vignettes simulation task. These results add to our understanding of the neural mechanisms underlying flexible decision-making for solving social conflicts. More generally, our findings highlight the utility of RS-fMRI combined with both explicit and implicit psychometric measures for better understanding individual differences in social cognition. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Ethical Justification for Conducting Public Health Surveillance Without Patient Consent

PubMed Central

Heilig, Charles M.; White, Angela

2012-01-01

Public health surveillance by necessity occurs without explicit patient consent. There is strong legal and scientific support for maintaining name-based reporting of infectious diseases and other types of public health surveillance. We present conditions under which surveillance without explicit patient consent is ethically justifiable using principles of contemporary clinical and public health ethics. Overriding individual autonomy must be justified in terms of the obligation of public health to improve population health, reduce inequities, attend to the health of vulnerable and systematically disadvantaged persons, and prevent harm. In addition, data elements collected without consent must represent the minimal necessary interference, lead to effective public health action, and be maintained securely. PMID:22095338

Exploring component-based approaches in forest landscape modeling

Treesearch

H. S. He; D. R. Larsen; D. J. Mladenoff

2002-01-01

Forest management issues are increasingly required to be addressed in a spatial context, which has led to the development of spatially explicit forest landscape models. The numerous processes, complex spatial interactions, and diverse applications in spatial modeling make the development of forest landscape models difficult for any single research group. New...

Toward a Predictive Model of Arctic Coastal Retreat in a Warming Climate, Beaufort Sea, Alaska

DTIC Science & Technology

2011-09-30

level by waves and surge and tide. Melt rate is governed by an empirically based iceberg melting algorithm that includes explicitly the roles of wave...Thermal erosion of a permafrost coastline: Improving process-based models using time-lapse photography, Arctic Alpine Antarctic Research 43(3): 474

Estimating abundance of mountain lions from unstructured spatial sampling

USGS Publications Warehouse

Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; Mckelvey, Kevin S.

2012-01-01

Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional mark–recapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capture–recapture data have produced methods estimating abundance and density of animals from spatially explicit capture–recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture–recapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908 km2) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100 km2 (95% Cl 2.3–5.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% Cl 3.1–11.0) under the full model (including effects of distance, sex, survey effort, and distance x sex on detection probability). These numbers translate to a total estimate of 293 mountain lions (95% Cl 182–451) to 529 (95% Cl 245–870) within the Blackfoot drainage. Results from the distance model are similar to previous estimates of 3.6 mountain lions/100 km2 for the study area; however, results from all other models indicated greater numbers of mountain lions. Our results indicate that unstructured spatial sampling combined with spatial capture–recapture analysis can be an effective method for estimating large carnivore densities.

Are the benefits of autonomy satisfaction and the costs of autonomy frustration dependent on individuals' autonomy strength?

PubMed

Van Assche, Jasper; van der Kaap-Deeder, Jolene; Audenaert, Elien; De Schryver, Maarten; Vansteenkiste, Maarten

2018-01-29

From a self-determination theory perspective, individuals are assumed to benefit and suffer from, respectively, the satisfaction and frustration of the psychological need for autonomy, even if they score low on autonomy strength. Yet, previous studies on need strength are scarce, operationalized need strength differently, and produced inconsistent findings. In two studies among 224 South African adults (M age  = 24.13, SD = 4.25; 54.0% male) and 156 Belgian prisoners (M age  = 38.60, SD = 11.68; 88.5% male), we investigated the moderating role of autonomy valuation and desire in the relations of autonomy satisfaction and frustration with a variety of well-being and ill-being indicators. Study 1 provided some evidence for the moderating role of mostly explicit autonomy desire (rather than explicit autonomy valuation). In Study 2, neither explicit nor implicit autonomy desire played a consistent moderating role. Overall, these findings are congruent with a moderate (albeit not with a strong) interpretation of the universality claim made within self-determination theory, provide initial evidence for a differentiation between deficit-based and growth-oriented interpersonal differences in need strength, and indicate that the potential moderating role of need strength deserves continued attention before any firm conclusions can be drawn. © 2018 Wiley Periodicals, Inc.

Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS

NASA Astrophysics Data System (ADS)

Peck, Myron A.; Arvanitidis, Christos; Butenschön, Momme; Canu, Donata Melaku; Chatzinikolaou, Eva; Cucco, Andrea; Domenici, Paolo; Fernandes, Jose A.; Gasche, Loic; Huebert, Klaus B.; Hufnagl, Marc; Jones, Miranda C.; Kempf, Alexander; Keyl, Friedemann; Maar, Marie; Mahévas, Stéphanie; Marchal, Paul; Nicolas, Delphine; Pinnegar, John K.; Rivot, Etienne; Rochette, Sébastien; Sell, Anne F.; Sinerchia, Matteo; Solidoro, Cosimo; Somerfield, Paul J.; Teal, Lorna R.; Travers-Trolet, Morgan; van de Wolfshaar, Karen E.

2018-02-01

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Teacher challenges, perceptions, and use of science models in middle school classrooms about climate, weather, and energy concepts

NASA Astrophysics Data System (ADS)

Yarker, Morgan Brown

Research suggests that scientific models and modeling should be topics covered in K-12 classrooms as part of a comprehensive science curriculum. It is especially important when talking about topics in weather and climate, where computer and forecast models are the center of attention. There are several approaches to model based inquiry, but it can be argued, theoretically, that science models can be effectively implemented into any approach to inquiry if they are utilized appropriately. Yet, it remains to be explored how science models are actually implemented in classrooms. This study qualitatively looks at three middle school science teachers' use of science models with various approaches to inquiry during their weather and climate units. Results indicate that the teacher who used the most elements of inquiry used models in a way that aligned best with the theoretical framework than the teachers who used fewer elements of inquiry. The theoretical framework compares an approach to argument-based inquiry to model-based inquiry, which argues that the approaches are essentially identical, so teachers who use inquiry should be able to apply model-based inquiry using the same approach. However, none of the teachers in this study had a complete understanding of the role models play in authentic science inquiry, therefore students were not explicitly exposed to the ideas that models can be used to make predictions about, and are representations of, a natural phenomenon. Rather, models were explicitly used to explain concepts to students or have students explain concepts to the teacher or to each other. Additionally, models were used as a focal point for conversation between students, usually as they were creating, modifying, or using models. Teachers were not observed asking students to evaluate models. Since science models are an important aspect of understanding science, it is important that teachers not only know how to implement models into an inquiry environment, but also understand the characteristics of science models so that they can explicitly teach the concept of modeling to students. This study suggests that better pre-service and in-service teacher education is needed to prepare students to teach about science models effectively.

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

A Robotic Coach Architecture for Elder Care (ROCARE) Based on Multi-user Engagement Models

PubMed Central

Fan, Jing; Bian, Dayi; Zheng, Zhi; Beuscher, Linda; Newhouse, Paul A.; Mion, Lorraine C.; Sarkar, Nilanjan

2017-01-01

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment. PMID:28113672

On the evolution of primitive genetic codes.

PubMed

Weberndorfer, Günter; Hofacker, Ivo L; Stadler, Peter F

2003-10-01

The primordial genetic code probably has been a drastically simplified ancestor of the canonical code that is used by contemporary cells. In order to understand how the present-day code came about we first need to explain how the language of the building plan can change without destroying the encoded information. In this work we introduce a minimal organism model that is based on biophysically reasonable descriptions of RNA and protein, namely secondary structure folding and knowledge based potentials. The evolution of a population of such organism under competition for a common resource is simulated explicitly at the level of individual replication events. Starting with very simple codes, and hence greatly reduced amino acid alphabets, we observe a diversification of the codes in most simulation runs. The driving force behind this effect is the possibility to produce fitter proteins when the repertoire of amino acids is enlarged.

A Robotic Coach Architecture for Elder Care (ROCARE) Based on Multi-User Engagement Models.

PubMed

Fan, Jing; Bian, Dayi; Zheng, Zhi; Beuscher, Linda; Newhouse, Paul A; Mion, Lorraine C; Sarkar, Nilanjan

2017-08-01

The aging population with its concomitant medical conditions, physical and cognitive impairments, at a time of strained resources, establishes the urgent need to explore advanced technologies that may enhance function and quality of life. Recently, robotic technology, especially socially assistive robotics has been investigated to address the physical, cognitive, and social needs of older adults. Most system to date have predominantly focused on one-on-one human robot interaction (HRI). In this paper, we present a multi-user engagement-based robotic coach system architecture (ROCARE). ROCARE is capable of administering both one-on-one and multi-user HRI, providing implicit and explicit channels of communication, and individualized activity management for long-term engagement. Two preliminary feasibility studies, a one-on-one interaction and a triadic interaction with two humans and a robot, were conducted and the results indicated potential usefulness and acceptance by older adults, with and without cognitive impairment.

Child Speech, Language and Communication Need Re-Examined in a Public Health Context: A New Direction for the Speech and Language Therapy Profession

ERIC Educational Resources Information Center

Law, James; Reilly, Sheena; Snow, Pamela C.

2013-01-01

Background: Historically speech and language therapy services for children have been framed within a rehabilitative framework with explicit assumptions made about providing therapy to individuals. While this is clearly important in many cases, we argue that this model needs revisiting for a number of reasons. First, our understanding of the nature…

Spatially explicit shallow landslide susceptibility mapping over large areas

USGS Publications Warehouse

Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

Genomic Prediction Accounting for Residual Heteroskedasticity

PubMed Central

Ou, Zhining; Tempelman, Robert J.; Steibel, Juan P.; Ernst, Catherine W.; Bates, Ronald O.; Bello, Nora M.

2015-01-01

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. PMID:26564950

Using effort information with change-in-ratio data for population estimation

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.

1995-01-01

Most change-in-ratio (CIR) methods for estimating fish and wildlife population sizes have been based only on assumptions about how encounter probabilities vary among population subclasses. When information on sampling effort is available, it is also possible to derive CIR estimators based on assumptions about how encounter probabilities vary over time. This paper presents a generalization of previous CIR models that allows explicit consideration of a range of assumptions about the variation of encounter probabilities among subclasses and over time. Explicit estimators are derived under this model for specific sets of assumptions about the encounter probabilities. Numerical methods are presented for obtaining estimators under the full range of possible assumptions. Likelihood ratio tests for these assumptions are described. Emphasis is on obtaining estimators based on assumptions about variation of encounter probabilities over time.

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum

PubMed Central

Ito, Makoto; Doya, Kenji

2015-01-01

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the “win-stay, lose-switch” strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum. PMID:26529522

Schizophrenia: Do Sense Perceptions Correlate with Episodic Activity, as Indians Know Kokopelli/Pele Matches with Mother Earth's Electromagnetic Field Activity, EMF?

NASA Astrophysics Data System (ADS)

McCulley, Aspen; Pawa Matagamon, Sagamo; McLeod, David Matthew

2007-10-01

Certain Indian cognomens seem to indicate an environmental awareness of an electromagnetic wrath some traditional cultures are careful to acknowledge and accommodate. These include Pele/Kokopelli, Keitan, and Hobomock, that have carried explicit information our cultures have been cognizant of Mother Earth's not-always-benign influences. Let's consider schizophrenia, with or without a viral cofactor, and Kokopelli/Pele. She/he may be explicitly referenced as a hunch-backed, flute-playing individual, dancing-around in correlation with Earth's electromagnetic activities. Depending on the specific version and its details, individuals, particularly children, are admonished to avoid certain areas. Of especial importance and relevance may be cultural awareness that individuals, whom another type of culture has discriminated against, despite no a priori guilt, are explicitly absolved of culpability by the blanket statement that The Great Spirit is implicated in their behavior. Of course, this provides information of a religious sort, possibly corroborated by a currently prominent individual.

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient.

PubMed

Fyllas, Nikolaos M; Bentley, Lisa Patrick; Shenkin, Alexander; Asner, Gregory P; Atkin, Owen K; Díaz, Sandra; Enquist, Brian J; Farfan-Rios, William; Gloor, Emanuel; Guerrieri, Rossella; Huasco, Walter Huaraca; Ishida, Yoko; Martin, Roberta E; Meir, Patrick; Phillips, Oliver; Salinas, Norma; Silman, Miles; Weerasinghe, Lasantha K; Zaragoza-Castells, Joana; Malhi, Yadvinder

2017-06-01

One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale. © 2017 John Wiley & Sons Ltd/CNRS.

Using Hydrologic Modeling to Screen Potential Environmental Management Methods for Malaria Vector Control in Niger

NASA Astrophysics Data System (ADS)

Gianotti, R. L.; Bomblies, A.; Eltahir, E. A.

2008-12-01

This study describes the use of HYDREMATS, a physically-based distributed hydrology model, to investigate environmental management methods for malaria vector control in the Sahelian village of Banizoumbou, Niger. The model operates at fine spatial and temporal scales to enable explicit simulation of individual pool dynamics and isolation of mosquito breeding habitats. The results showed that leveling of topographic depressions where temporary breeding habitats form during the rainy season could reduce the persistence time of a pool to less than the time needed for establishment of mosquito breeding, approximately 7 days. Increasing the surface soil permeability by ploughing could also reduce the persistence time of a pool but this technique was not as effective as leveling. Therefore it is considered that leveling should be the preferred of the two options where possible. This investigation demonstrates that management methods that modify the hydrologic environment have significant potential to contribute to malaria vector control and human health improvement in Sahelian Africa.

Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.

PubMed

Kong, Ru; Li, Jingwei; Orban, Csaba; Sabuncu, Mert R; Liu, Hesheng; Schaefer, Alexander; Sun, Nanbo; Zuo, Xi-Nian; Holmes, Avram J; Eickhoff, Simon B; Yeo, B T Thomas

2018-06-06

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data.

PubMed

Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C

2013-05-30

ImmunoPrecipitation (IP) efficiencies may vary largely between different antibodies and between repeated experiments with the same antibody. These differences have a large impact on the quality of ChIP-seq data: a more efficient experiment will necessarily lead to a higher signal to background ratio, and therefore to an apparent larger number of enriched regions, compared to a less efficient experiment. In this paper, we show how IP efficiencies can be explicitly accounted for in the joint statistical modelling of ChIP-seq data. We fit a latent mixture model to eight experiments on two proteins, from two laboratories where different antibodies are used for the two proteins. We use the model parameters to estimate the efficiencies of individual experiments, and find that these are clearly different for the different laboratories, and amongst technical replicates from the same lab. When we account for ChIP efficiency, we find more regions bound in the more efficient experiments than in the less efficient ones, at the same false discovery rate. A priori knowledge of the same number of binding sites across experiments can also be included in the model for a more robust detection of differentially bound regions among two different proteins. We propose a statistical model for the detection of enriched and differentially bound regions from multiple ChIP-seq data sets. The framework that we present accounts explicitly for IP efficiencies in ChIP-seq data, and allows to model jointly, rather than individually, replicates and experiments from different proteins, leading to more robust biological conclusions.

High School Students' Meta-Modeling Knowledge

NASA Astrophysics Data System (ADS)

Fortus, David; Shwartz, Yael; Rosenfeld, Sherman

2016-12-01

Modeling is a core scientific practice. This study probed the meta-modeling knowledge (MMK) of high school students who study science but had not had any explicit prior exposure to modeling as part of their formal schooling. Our goals were to (A) evaluate the degree to which MMK is dependent on content knowledge and (B) assess whether the upper levels of the modeling learning progression defined by Schwarz et al. (2009) are attainable by Israeli K-12 students. Nine Israeli high school students studying physics, chemistry, biology, or general science were interviewed individually, once using a context related to the science subject that they were learning and once using an unfamiliar context. All the interviewees displayed MMK superior to that of elementary and middle school students, despite the lack of formal instruction on the practice. Their MMK was independent of content area, but their ability to engage in the practice of modeling was content dependent. This study indicates that, given proper support, the upper levels of the learning progression described by Schwarz et al. (2009) may be attainable by K-12 science students. The value of explicitly focusing on MMK as a learning goal in science education is considered.

Does spatial variation in environmental conditions affect recruitment? A study using a 3-D model of Peruvian anchovy

NASA Astrophysics Data System (ADS)

Xu, Yi; Rose, Kenneth A.; Chai, Fei; Chavez, Francisco P.; Ayón, Patricia

2015-11-01

We used a 3-dimensional individual-based model (3-D IBM) of Peruvian anchovy to examine how spatial variation in environmental conditions affects larval and juvenile growth and survival, and recruitment. Temperature, velocity, and phytoplankton and zooplankton concentrations generated from a coupled hydrodynamic Nutrients-Phytoplankton-Zooplankton-Detritus (NPZD) model, mapped to a three dimensional rectangular grid, were used to simulate anchovy populations. The IBM simulated individuals as they progressed from eggs to recruitment at 10 cm. Eggs and yolk-sac larvae were followed hourly through the processes of development, mortality, and movement (advection), and larvae and juveniles were followed daily through the processes of growth, mortality, and movement (advection plus behavior). A bioenergetics model was used to grow larvae and juveniles. The NPZD model provided prey fields which influence both food consumption rate as well as behavior mediated movement with individuals going to grids cells having optimal growth conditions. We compared predicted recruitment for monthly cohorts for 1990 through 2004 between the full 3-D IBM and a point (0-D) model that used spatially-averaged environmental conditions. The 3-D and 0-D versions generated similar interannual patterns in monthly recruitment for 1991-2004, with the 3-D results yielding consistently higher survivorship. Both versions successfully captured the very poor recruitment during the 1997-1998 El Niño event. Higher recruitment in the 3-D simulations was due to higher survival during the larval stage resulting from individuals searching for more favorable temperatures that lead to faster growth rates. The strong effect of temperature was because both model versions provided saturating food conditions for larval and juvenile anchovies. We conclude with a discussion of how explicit treatment of spatial variation affected simulated recruitment, other examples of fisheries modeling analyses that have used a similar approach to assess the influence of spatial variation, and areas for further model development.

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species

PubMed Central

Geary, Matthew; Fielding, Alan H.; McGowan, Philip J. K.; Marsden, Stuart J.

2015-01-01

Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years) scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5–30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and ‘increased grazing’ (the opposite conversion) the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the ‘reduced grazing’ scenario were nonlinear. ‘Scenario-led’ landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse. PMID:26569604

Modelling the nonlinear behaviour of an underplatform damper test rig for turbine applications

NASA Astrophysics Data System (ADS)

Pesaresi, L.; Salles, L.; Jones, A.; Green, J. S.; Schwingshackl, C. W.

2017-02-01

Underplatform dampers (UPD) are commonly used in aircraft engines to mitigate the risk of high-cycle fatigue failure of turbine blades. The energy dissipated at the friction contact interface of the damper reduces the vibration amplitude significantly, and the couplings of the blades can also lead to significant shifts of the resonance frequencies of the bladed disk. The highly nonlinear behaviour of bladed discs constrained by UPDs requires an advanced modelling approach to ensure that the correct damper geometry is selected during the design of the turbine, and that no unexpected resonance frequencies and amplitudes will occur in operation. Approaches based on an explicit model of the damper in combination with multi-harmonic balance solvers have emerged as a promising way to predict the nonlinear behaviour of UPDs correctly, however rigorous experimental validations are required before approaches of this type can be used with confidence. In this study, a nonlinear analysis based on an updated explicit damper model having different levels of detail is performed, and the results are evaluated against a newly-developed UPD test rig. Detailed linear finite element models are used as input for the nonlinear analysis, allowing the inclusion of damper flexibility and inertia effects. The nonlinear friction interface between the blades and the damper is described with a dense grid of 3D friction contact elements which allow accurate capturing of the underlying nonlinear mechanism that drives the global nonlinear behaviour. The introduced explicit damper model showed a great dependence on the correct contact pressure distribution. The use of an accurate, measurement based, distribution, better matched the nonlinear dynamic behaviour of the test rig. Good agreement with the measured frequency response data could only be reached when the zero harmonic term (constant term) was included in the multi-harmonic expansion of the nonlinear problem, highlighting its importance when the contact interface experiences large normal load variation. The resulting numerical damper kinematics with strong translational and rotational motion, and the global blades frequency response were fully validated experimentally, showing the accuracy of the suggested high detailed explicit UPD modelling approach.

Money Walks: Implicit Mobility Behavior and Financial Well-Being.

PubMed

Singh, Vivek Kumar; Bozkaya, Burcin; Pentland, Alex

2015-01-01

Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting "big data," present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal "foraging" behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models.

Money Walks: Implicit Mobility Behavior and Financial Well-Being

PubMed Central

Singh, Vivek Kumar; Bozkaya, Burcin; Pentland, Alex

2015-01-01

Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting “big data,” present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal “foraging” behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models. PMID:26317339

Using climate information to understand the spatio-temporal heterogeneity of a chikungunya outbreak in the presence of widespread asymptomatic infection

NASA Astrophysics Data System (ADS)

Dommar, C. J.; Lowe, R.; Robinson, M.; Rodó, X.

2013-12-01

The emergence and persistence of human pathogens in the environment represents a constant threat to society, with global implications for human health, economies and ecosystems. Of particular concern are vector-borne diseases, such as dengue, malaria and chikungunya, which are increasing across their traditional ranges and continuing to infiltrate new regions. This unprecedented situation has been partly attributed to the increase in global temperatures in recent decades which has allowed non-native mosquito species to invade and successfully colonise previously inhospitable environments The spatio-temporal evolution of these diseases is determined by the interaction of the host and vector, which is strongly dependent on social structures and mobility patterns. In turn, vector populations are thought to be driven by external environmental variables, such as precipitation and temperature. Furthermore, the ability of asymptomatic individuals to successfully transmit the infection and evade control measures can undermine public health interventions. We employed a stochastic model, which explicitly included asymptomatic and undocumented laboratory confirmed cases, and applied it to a documented outbreak in Cambodia in 2012 (Trapeang Roka village, Kampong Speu Province). The resulting estimate of the reproduction number was considerably higher than values obtained for previous outbreaks and highlights the importance of asymptomatic transmission. Subsequently, we develop an agent-based model (ABM), in which each individual is explicitly represented and vector populations are linked to precipitation estimates in a tropical setting. The model is implemented on both scale-free and regular networks. The spatio-temporal transmission of chikungunya is analysed and the presence of asymptomatic silent spreaders within the population is investigated in the context of implementing travel restrictions during an outbreak. Preventing the movement of symptomatic individuals alone is found to be an insufficient mechanism to halt the spread of the disease, which can be readily carried to neighbouring nodes via sub-clinical individuals. Furthermore, the impact of topology structure versus precipitation levels is assessed and precipitation is found to be the dominant factor driving spatio-temporal transmission. Our results highlight the urgent need to establish adequate monitoring and mosquito control programs in vulnerable countries. These models can help to inform public health officials on both the impact and potential spatial expansion of vector-borne diseases through both urban and rural regions under the influence of dynamic climatic conditions. Given the climate sensitivity of vector-borne diseases, such as chikungunya, it is important to link the monitoring of meteorological conditions to public health surveillance and control.

Project-Based Teaching: Helping Students Make Project Connections

NASA Astrophysics Data System (ADS)

Johnson, Heather Jo Pusich

Project-based curriculum materials are designed to support students in engaging with scientific content and practices in meaningful ways, with the goal of improving students' science learning. However, students need to understand the connections between what they are doing on a day-to-day basis with respect to the goals of the overall project for students to get the motivational and cognitive benefits of a project-based approach. In this dissertation, I looked at the challenges that four ninth grade science teachers faced as they helped students to make these connections using a project-based environmental science curriculum. The analysis revealed that in general when the curriculum materials made connections explicit, teachers were better able to articulate the relationship between the lesson and the project during enactment. However, whether the connections were explicit or implicit in the materials, enactments of the same lesson across teachers revealed that teachers leveraged different aspects of the project context in different ways depending on their knowledge, beliefs, and goals about project-based teaching. The quantitative analysis of student data indicated that when teacher enactments supported project goals explicitly, students made stronger connections between a lesson and the project goal. Therefore, a teacher's ability to make clear connections during classroom instruction is essential. Furthermore, when students made connections between each lesson and the larger project goals their attitudes toward the lesson were more positive and they performed better on the final assessment. These findings suggest that connections between individual lessons and the goals of the project are critical to the effectiveness of project-based learning. This study highlights that while some teachers were able to forge these connections successfully as a result of leveraging cognitive resources, teachers' beliefs, knowledge and goals about project-based teaching are variable. As such, teachers adopting project-based curriculum materials need more support - through educative curriculum materials, coaching, or ongoing professional development - to help them support project connections consistently and explicitly in their teaching practice.

Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process.

PubMed

Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang

2014-10-01

Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Slip Continuity in Explicit Crystal Plasticity Simulations Using Nonlocal Continuum and Semi-discrete Approaches

DTIC Science & Technology

2013-01-01

Based Micropolar Single Crystal Plasticity: Comparison of Multi - and Single Criterion Theories. J. Mech. Phys. Solids 2011, 59, 398–422. ALE3D ...element boundaries in a multi -step constitutive evaluation (Becker, 2011). The results showed the desired effects of smoothing the deformation field...Implementation The model was implemented in the large-scale parallel, explicit finite element code ALE3D (2012). The crystal plasticity

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Personalized State-space Modeling of Glucose Dynamics for Type 1 Diabetes Using Continuously Monitored Glucose, Insulin Dose, and Meal Intake: An Extended Kalman Filter Approach.

PubMed

Wang, Qian; Molenaar, Peter; Harsh, Saurabh; Freeman, Kenneth; Xie, Jinyu; Gold, Carol; Rovine, Mike; Ulbrecht, Jan

2014-03-01

An essential component of any artificial pancreas is on the prediction of blood glucose levels as a function of exogenous and endogenous perturbations such as insulin dose, meal intake, and physical activity and emotional tone under natural living conditions. In this article, we present a new data-driven state-space dynamic model with time-varying coefficients that are used to explicitly quantify the time-varying patient-specific effects of insulin dose and meal intake on blood glucose fluctuations. Using the 3-variate time series of glucose level, insulin dose, and meal intake of an individual type 1 diabetic subject, we apply an extended Kalman filter (EKF) to estimate time-varying coefficients of the patient-specific state-space model. We evaluate our empirical modeling using (1) the FDA-approved UVa/Padova simulator with 30 virtual patients and (2) clinical data of 5 type 1 diabetic patients under natural living conditions. Compared to a forgetting-factor-based recursive ARX model of the same order, the EKF model predictions have higher fit, and significantly better temporal gain and J index and thus are superior in early detection of upward and downward trends in glucose. The EKF based state-space model developed in this article is particularly suitable for model-based state-feedback control designs since the Kalman filter estimates the state variable of the glucose dynamics based on the measured glucose time series. In addition, since the model parameters are estimated in real time, this model is also suitable for adaptive control. © 2014 Diabetes Technology Society.

In search of a health education model: teachers' conceptions in four Mediterranean countries.

PubMed

Caussidier, Claude; El Hage, Fadi; Munoz, François; Remki, Latifa; Larribi, Rym; Khzami, Salah-Eddine; Berger, Dominique; de Carvalho, Graça S; Favre, Daniel

2011-12-01

School programs are defined to promote the health of the pupils and to develop their competencies so that they can adopt behaviors favorable to their health. With the European project FP6 Biohead-Citizen (2004-2007), we analyzed the conceptions of teachers as regards health education, in France, Lebanon, Morocco and Tunisia, in reference to the biomedical model and the social health model. These four countries were selected because their school curricula represented different models of health education. Lebanon and Tunisia addressed health education with the biomedical model. In Morocco, the curriculum was also primarily based on the biomedical model and enclosed a few instructions issued from the social health model. In France, the health education curriculum declared an approach based on the health promotion model. Our study was based on multivariate statistical analyses of questionnaires filled out by 2537 in-service and pre-service teachers. Our analysis showed that the conceptions of the teachers concerning health education were not structured and related to a specific model. We also found that the dominating factors of influence on the choices expressed with regards to health education were, among different sociocultural variables, the religion, the home country, and, to a lesser extent, the level of training. Thus, the conceptions of the teachers were not integrated into comprehensive approaches but related to individual characteristics. Consequently health education implementation would require thorough training for pre-service and in-service teachers and should also explicitly take into account their conceptions and values.

Transient analysis of a thermal storage unit involving a phase change material

NASA Technical Reports Server (NTRS)

Griggs, E. I.; Pitts, D. R.; Humphries, W. R.

1974-01-01

The transient response of a single cell of a typical phase change material type thermal capacitor has been modeled using numerical conductive heat transfer techniques. The cell consists of a base plate, an insulated top, and two vertical walls (fins) forming a two-dimensional cavity filled with a phase change material. Both explicit and implicit numerical formulations are outlined. A mixed explicit-implicit scheme which treats the fin implicity while treating the phase change material explicitly is discussed. A band algorithmic scheme is used to reduce computer storage requirements for the implicit approach while retaining a relatively fine grid. All formulations are presented in dimensionless form thereby enabling application to geometrically similar problems. Typical parametric results are graphically presented for the case of melting with constant heat input to the base of the cell.

Content relatedness in the social web based on social explicit semantic analysis

NASA Astrophysics Data System (ADS)

Ntalianis, Klimis; Otterbacher, Jahna; Mastorakis, Nikolaos

2017-06-01

In this paper a novel content relatedness algorithm for social media content is proposed, based on the Explicit Semantic Analysis (ESA) technique. The proposed scheme takes into consideration social interactions. In particular starting from the vector space representation model, similarity is expressed by a summation of term weight products. In this paper, term weights are estimated by a social computing method, where the strength of each term is calculated by the attention the terms receives. For this reason each post is split into two parts, title and comments area, while attention is defined by the number of social interactions such as likes and shares. The overall approach is named Social Explicit Semantic Analysis. Experimental results on real data show the advantages and limitations of the proposed approach, while an initial comparison between ESA and S-ESA is very promising.

Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

PubMed Central

Schur, Nadine; Hürlimann, Eveline; Garba, Amadou; Traoré, Mamadou S.; Ndir, Omar; Ratard, Raoult C.; Tchuem Tchuenté, Louis-Albert; Kristensen, Thomas K.; Utzinger, Jürg; Vounatsou, Penelope

2011-01-01

Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs. PMID:21695107

DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

EPA Science Inventory

An explicit dynamic water-quality modeling algorithm is developed for tracking dissolved substances in water-distribution networks. The algorithm is based on a mass-balance relation within pipes that considers both advective transport and reaction kinetics. Complete mixing of m...

Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study.

PubMed

Phelan, Sean M; Dovidio, John F; Puhl, Rebecca M; Burgess, Diana J; Nelson, David B; Yeazel, Mark W; Hardeman, Rachel; Perry, Sylvia; van Ryn, Michelle

2014-04-01

To examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students. A web-based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti-fat attitudes test. A majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non-Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice. Implicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact. Copyright © 2013 The Obesity Society.

Strengthening Ties: The Case for Building a Social Policy Centered on Families

ERIC Educational Resources Information Center

Longman, Phillip; Mundy, Liza; Black, Rachel; Bornfreund, Laura; Byrum, Greta; Cramer, Reid; Gangadharan, Seeta Peña; Guernsey, Lisa; Lieberman, Abbie; Lynn, Barry; McCarthy, Mary Alice

2015-01-01

Most of the social and economic policies in the U.S. do not explicitly address or take into account the growing importance of families as sources of human capital and determinants of individual success. Even the small subsets of programs that we conventionally frame as part of "family policy" are often based on long-defunct assumptions…

Explicit formulation of second and third order optical nonlinearity in the FDTD framework

NASA Astrophysics Data System (ADS)

Varin, Charles; Emms, Rhys; Bart, Graeme; Fennel, Thomas; Brabec, Thomas

2018-01-01

The finite-difference time-domain (FDTD) method is a flexible and powerful technique for rigorously solving Maxwell's equations. However, three-dimensional optical nonlinearity in current commercial and research FDTD softwares requires solving iteratively an implicit form of Maxwell's equations over the entire numerical space and at each time step. Reaching numerical convergence demands significant computational resources and practical implementation often requires major modifications to the core FDTD engine. In this paper, we present an explicit method to include second and third order optical nonlinearity in the FDTD framework based on a nonlinear generalization of the Lorentz dispersion model. A formal derivation of the nonlinear Lorentz dispersion equation is equally provided, starting from the quantum mechanical equations describing nonlinear optics in the two-level approximation. With the proposed approach, numerical integration of optical nonlinearity and dispersion in FDTD is intuitive, transparent, and fully explicit. A strong-field formulation is also proposed, which opens an interesting avenue for FDTD-based modelling of the extreme nonlinear optics phenomena involved in laser filamentation and femtosecond micromachining of dielectrics.

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

PubMed Central

McClelland, Amanda; Zelner, Jon; Streftaris, George; Funk, Sebastian; Metcalf, Jessica; Dalziel, Benjamin D.; Grenfell, Bryan T.

2017-01-01

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging. PMID:29084216

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission-With an application to the 2014-2015 West Africa Ebola outbreak.

PubMed

Lau, Max S Y; Gibson, Gavin J; Adrakey, Hola; McClelland, Amanda; Riley, Steven; Zelner, Jon; Streftaris, George; Funk, Sebastian; Metcalf, Jessica; Dalziel, Benjamin D; Grenfell, Bryan T

2017-10-01

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging.

Validity for an integrated laboratory analogue of sexual aggression and bystander intervention.

PubMed

Parrott, Dominic J; Tharp, Andra Teten; Swartout, Kevin M; Miller, Cameron A; Hall, Gordon C Nagayama; George, William H

2012-01-01

This study sought to develop and validate an integrated laboratory paradigm of sexual aggression and bystander intervention. Participants were a diverse community sample (54% African American) of heterosexual males (N = 156) between 21 and 35 years of age who were recruited to complete the study with a male friend and an ostensibly single, heterosexual female who reported a strong dislike of sexual content in the media. Participants viewed a sexually explicit or nonsexually explicit film clip as part of contrived media rating task and made individual choices of which film clip to show the female confederate. Immediately thereafter, participants were required to reach consensus on a group decision of which film clip to show the female confederate. Subjecting a target to an unwanted experience with a sexual connotation was operationalized as selection of the sexually explicit video, whereas successful bystander intervention was operationalized as the event of one partner individually selecting the sexually explicit video but then selecting the nonsexually explicit video for the group choice. Results demonstrated that a 1-year history of sexual aggression and endorsement of pertinent misogynistic attitudes significantly predicted selection of the sexually-explicit video. In addition, bystander efficacy significantly predicted men's successful prevention of their male peer's intent to show the female confederate a sexually explicit video. Discussion focused on how these data inform future research and bystander intervention programming for sexual aggression. © 2012 Wiley Periodicals, Inc.

Efficient Translation of LTL Formulae into Buchi Automata

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Lerda, Flavio

2001-01-01

Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

Place-based and data-rich citizen science as a precursor for conservation action.

PubMed

Haywood, Benjamin K; Parrish, Julia K; Dolliver, Jane

2016-06-01

Environmental education strategies have customarily placed substantial focus on enhancing ecological knowledge and literacy with the hope that, upon discovering relevant facts and concepts, participants will be better equipped to process and dissect environmental issues and, therefore, make more informed decisions. The assumption is that informed citizens will become active citizens--enthusiastically lobbying for, and participating in, conservation-oriented action. We surveyed and interviewed and used performance data from 432 participants in the Coastal Observation and Seabird Survey Team (COASST), a scientifically rigorous citizen science program, to explore measurable change in and links between understanding and action. We found that participation in rigorous citizen science was associated with significant increases in participant knowledge and skills; a greater connection to place and, secondarily, to community; and an increasing awareness of the relative impact of anthropogenic activities on local ecosystems specifically through increasing scientific understanding of the ecosystem and factors affecting it. Our results suggest that a place-based, data-rich experience linked explicitly to local, regional, and global issues can lead to measurable change in individual and collective action, expressed in our case study principally through participation in citizen science and community action and communication of program results to personal acquaintances and elected officials. We propose the following tenets of conservation literacy based on emergent themes and the connections between them explicit in our data: place-based learning creates personal meaning making; individual experience nested within collective (i.e., program-wide) experience facilitates an understanding of the ecosystem process and function at local and regional scales; and science-based meaning making creates informed concern (i.e., the ability to discern both natural and anthropogenic forcing), which allows individuals to develop a personalized prioritization schema and engage in conservation action. © 2016 Society for Conservation Biology.

Enhancing Pre-Service Physics Teachers' Perceived Self-Efficacy of Argumentation-Based Pedagogy through Modelling and Mastery Experiences

ERIC Educational Resources Information Center

Ogan-Bekiroglu, Feral; Aydeniz, Mehmet

2013-01-01

This study explored the impact of explicit instruction on argumentation-based pedagogy, coupled with modelling and hands-on learning activities on pre-service physics teachers' perceived self-efficacy to teach science through argumentation. Participants consisted of 24 pre-service physics teachers attending an established teacher education program…

Decision making under explicit risk is impaired in individuals with human immunodeficiency virus (HIV).

PubMed

Fujiwara, Esther; Tomlinson, Sara E; Purdon, Scot E; Gill, M John; Power, Christopher

2015-01-01

Human immunodeficiency virus (HIV) can affect the frontal-striatal brain regions, which are known to subserve decision-making functions. Previous studies have reported impaired decision making among HIV+ individuals using the Iowa Gambling Task, a task that assesses decision making under ambiguity. Previous study populations often had significant comorbidities such as past or present substance use disorders and/or hepatitis C virus coinfection, complicating conclusions about the unique contributions of HIV-infection to decision making. Decision making under explicit risk has very rarely been examined in HIV+ individuals and was tested here using the Game of Dice Task (GDT). We examined decision making under explicit risk in the GDT in 20 HIV+ individuals without substance use disorder or HCV coinfection, including a demographically matched healthy control group (n = 20). Groups were characterized on a standard neuropsychological test battery. For the HIV+ group, several disease-related parameters (viral load, current and nadir CD4 T-cell count) were included. Analyses focused on the GDT and spanned between-group (t-tests; analysis of covariance, ANCOVA) as well as within-group comparisons (Pearson/Spearman correlations). HIV+ individuals were impaired in the GDT, compared to healthy controls (p = .02). Their decision-making impairments were characterized by less advantageous choices and more random choice strategies, especially towards the end of the task. Deficits in the GDT in the HIV+ group were related to executive dysfunctions, slowed processing/motor speed, and current immune system status (CD4+ T-cell levels, ps < .05). Decision making under explicit risk in the GDT can occur in HIV-infected individuals without comorbidities. The correlational patterns may point to underlying fronto-subcortical dysfunctions in HIV+ individuals. The GDT provides a useful measure to assess risky decision making in this population and should be tested in larger studies.

Learning to Mean in Spanish Writing: A Case Study of a Genre-Based Pedagogy for Standards-Based Writing Instruction

ERIC Educational Resources Information Center

Troyan, Francis J.

2016-01-01

This case study reports the results of a genre-based approach, which was used to explicitly teach the touristic landmark description to fourth-grade students of Spanish as a foreign language. The instructional model and unit of instruction were informed by the pedagogies of the Sydney School of Linguistics and an instructional model for…

Explicit and implicit springback simulation in sheet metal forming using fully coupled ductile damage and distortional hardening model

NASA Astrophysics Data System (ADS)

Yetna n'jock, M.; Houssem, B.; Labergere, C.; Saanouni, K.; Zhenming, Y.

2018-05-01

The springback is an important phenomenon which accompanies the forming of metallic sheets especially for high strength materials. A quantitative prediction of springback becomes very important for newly developed material with high mechanical characteristics. In this work, a numerical methodology is developed to quantify this undesirable phenomenon. This methodoly is based on the use of both explicit and implicit finite element solvers of Abaqus®. The most important ingredient of this methodology consists on the use of highly predictive mechanical model. A thermodynamically-consistent, non-associative and fully anisotropic elastoplastic constitutive model strongly coupled with isotropic ductile damage and accounting for distortional hardening is then used. An algorithm for local integration of the complete set of the constitutive equations is developed. This algorithm considers the rotated frame formulation (RFF) to ensure the incremental objectivity of the model in the framework of finite strains. This algorithm is implemented in both explicit (Abaqus/Explicit®) and implicit (Abaqus/Standard®) solvers of Abaqus® through the users routine VUMAT and UMAT respectively. The implicit solver of Abaqus® has been used to study spingback as it is generally a quasi-static unloading. In order to compare the methods `efficiency, the explicit method (Dynamic Relaxation Method) proposed by Rayleigh has been also used for springback prediction. The results obtained within U draw/bending benchmark are studied, discussed and compared with experimental results as reference. Finally, the purpose of this work is to evaluate the reliability of different methods predict efficiently springback in sheet metal forming.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, Erin L.; Gedy, Bradley C.; Oyler-McCance, Sara J.; Garey, Andrew L.; Emel, Sarah L.; Mumma, Matthew; Wagner, Helene H.; Fortin, Marie-Josée; Cushman, Samuel A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

USGS Publications Warehouse

Landguth, E.L.; Fedy, B.C.; Oyler-McCance, S.J.; Garey, A.L.; Emel, S.L.; Mumma, M.; Wagner, H.H.; Fortin, M.-J.; Cushman, S.A.

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation-by-distance, isolation-by-barrier, and isolation-by-landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non-equilibrium conditions after introduction of isolation-by-landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals. ?? 2011 Blackwell Publishing Ltd.

Explicitly represented polygon wall boundary model for the explicit MPS method

NASA Astrophysics Data System (ADS)

Mitsume, Naoto; Yoshimura, Shinobu; Murotani, Kohei; Yamada, Tomonori

2015-05-01

This study presents an accurate and robust boundary model, the explicitly represented polygon (ERP) wall boundary model, to treat arbitrarily shaped wall boundaries in the explicit moving particle simulation (E-MPS) method, which is a mesh-free particle method for strong form partial differential equations. The ERP model expresses wall boundaries as polygons, which are explicitly represented without using the distance function. These are derived so that for viscous fluids, and with less computational cost, they satisfy the Neumann boundary condition for the pressure and the slip/no-slip condition on the wall surface. The proposed model is verified and validated by comparing computed results with the theoretical solution, results obtained by other models, and experimental results. Two simulations with complex boundary movements are conducted to demonstrate the applicability of the E-MPS method to the ERP model.

Rapid race perception despite individuation and accuracy goals.

PubMed

Kubota, Jennifer T; Ito, Tiffany

2017-08-01

Perceivers rapidly process social category information and form stereotypic impressions of unfamiliar others. However, a goal to individuate a target or to accurately predict their behavior can result in individuated impressions. It is unknown how the combination of both accuracy and individuation goals affects perceptual category processing. To explore this, participants were given both the goal to individuate targets and accurately predict behavior. We then recorded event-related brain potentials while participants viewed photos of black and white males along with four pieces of individuating information in the form of descriptions of past behavior. Even with explicit individuation and accuracy task goals, participants rapidly differentiated targets by race within 200 ms. Importantly, this rapid categorical processing did not influence behavioral outcomes as participants made individuated predictions. These findings indicate that individuals engage in category processing even when provided with individuation and accuracy goals, but that this processing does not necessarily result in category-based judgments.

Landscape modeling for Everglades ecosystem restoration

USGS Publications Warehouse

DeAngelis, D.L.; Gross, L.J.; Huston, M.A.; Wolff, W.F.; Fleming, D.M.; Comiskey, E.J.; Sylvester, S.M.

1998-01-01

A major environmental restoration effort is under way that will affect the Everglades and its neighboring ecosystems in southern Florida. Ecosystem and population-level modeling is being used to help in the planning and evaluation of this restoration. The specific objective of one of these modeling approaches, the Across Trophic Level System Simulation (ATLSS), is to predict the responses of a suite of higher trophic level species to several proposed alterations in Everglades hydrology. These include several species of wading birds, the snail kite, Cape Sable seaside sparrow, Florida panther, white-tailed deer, American alligator, and American crocodile. ATLSS is an ecosystem landscape-modeling approach and uses Geographic Information System (GIS) vegetation data and existing hydrology models for South Florida to provide the basic landscape for these species. A method of pseudotopography provides estimates of water depths through time at 28 ?? 28-m resolution across the landscape of southern Florida. Hydrologic model output drives models of habitat and prey availability for the higher trophic level species. Spatially explicit, individual-based computer models simulate these species. ATLSS simulations can compare the landscape dynamic spatial pattern of the species resulting from different proposed water management strategies. Here we compare the predicted effects of one possible change in water management in South Florida with the base case of no change. Preliminary model results predict substantial differences between these alternatives in some biotic spatial patterns. ?? 1998 Springer-Verlag.

Supporting inquiry learning by promoting normative understanding of multivariable causality

NASA Astrophysics Data System (ADS)

Keselman, Alla

2003-11-01

Early adolescents may lack the cognitive and metacognitive skills necessary for effective inquiry learning. In particular, they are likely to have a nonnormative mental model of multivariable causality in which effects of individual variables are neither additive nor consistent. Described here is a software-based intervention designed to facilitate students' metalevel and performance-level inquiry skills by enhancing their understanding of multivariable causality. Relative to an exploration-only group, sixth graders who practiced predicting an outcome (earthquake risk) based on multiple factors demonstrated increased attention to evidence, improved metalevel appreciation of effective strategies, and a trend toward consistent use of a controlled comparison strategy. Sixth graders who also received explicit instruction in making predictions based on multiple factors showed additional improvement in their ability to compare multiple instances as a basis for inferences and constructed the most accurate knowledge of the system. Gains were maintained in transfer tasks. The cognitive skills and metalevel understanding examined here are essential to inquiry learning.

Drinkers' memory bias for alcohol picture cues in explicit and implicit memory tasks.

PubMed

Nguyen-Louie, Tam T; Buckman, Jennifer F; Ray, Suchismita; Bates, Marsha E

2016-03-01

Alcohol cues can bias attention and elicit emotional reactions, especially in drinkers. Yet, little is known about how alcohol cues affect explicit and implicit memory processes, and how memory for alcohol cues is affected by acute alcohol intoxication. Young adult participants (N=161) were randomly assigned to alcohol, placebo, or control beverage conditions. Following beverage consumption, they were shown neutral, emotional and alcohol-related pictures cues. Participants then completed free recall and repetition priming tasks to test explicit and implicit memory, respectively, for picture cues. Average blood alcohol concentration for the alcohol group was 74±13mg/dl when memory testing began. Two mixed linear model analyses were conducted to examine the effects of beverage condition, picture cue type, and their interaction on explicit and implicit memory. Picture cue type and beverage condition each significantly affected explicit recall of picture cues, whereas only picture cue type significantly influenced repetition priming. Individuals in the alcohol condition recalled significantly fewer pictures than those in other conditions, regardless of cue type. Both free recall and repetition priming were greater for emotional and alcohol-related cues compared to neutral picture cues. No interaction effects were detected. Young adult drinkers showed enhanced explicit and implicit memory processing of alcohol cues compared to emotionally neutral cues. This enhanced processing for alcohol cues was on par with that seen for positive emotional cues. Acute alcohol intoxication did not alter this preferential memory processing for alcohol cues over neutral cues. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Using genetic data to estimate diffusion rates in heterogeneous landscapes.

PubMed

Roques, L; Walker, E; Franck, P; Soubeyrand, S; Klein, E K

2016-08-01

Having a precise knowledge of the dispersal ability of a population in a heterogeneous environment is of critical importance in agroecology and conservation biology as it can provide management tools to limit the effects of pests or to increase the survival of endangered species. In this paper, we propose a mechanistic-statistical method to estimate space-dependent diffusion parameters of spatially-explicit models based on stochastic differential equations, using genetic data. Dividing the total population into subpopulations corresponding to different habitat patches with known allele frequencies, the expected proportions of individuals from each subpopulation at each position is computed by solving a system of reaction-diffusion equations. Modelling the capture and genotyping of the individuals with a statistical approach, we derive a numerically tractable formula for the likelihood function associated with the diffusion parameters. In a simulated environment made of three types of regions, each associated with a different diffusion coefficient, we successfully estimate the diffusion parameters with a maximum-likelihood approach. Although higher genetic differentiation among subpopulations leads to more accurate estimations, once a certain level of differentiation has been reached, the finite size of the genotyped population becomes the limiting factor for accurate estimation.

Modeling fuels and fire effects in 3D: Model description and applications

Treesearch

Francois Pimont; Russell Parsons; Eric Rigolot; Francois de Coligny; Jean-Luc Dupuy; Philippe Dreyfus; Rodman R. Linn

2016-01-01

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose.We present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates...

Alaska at the Crossroads of Migration: Space Based Ornithology

NASA Technical Reports Server (NTRS)

Deppe, Jill; Wessels, Konrad; Smith, James A.

2007-01-01

Understanding bird migration on a global scale is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Revolutionary advances in remote sensing now provide us with near real-time measurements of atmospheric and land surface conditions at high spatial resolution over entire continents. We use spatially-explicit, individual based bird migration models driven by numerical weather prediction models of atmospheric conditions, dynamic habitat suitability maps derived from remotely sensed land surface conditions, biophysiological models, and biological field data to simulate migration routes, timing, energy budgets, and survival of individual birds and populations. Long-distance migratory birds travel annually between breeding grounds in Alaska and wintering grounds in Latin Amierica. Approximately 25% of these species are potential vectors of Avian Influenza. Alaska is at the crossroads of Asian and New World migratory flyways and is likely to be a point of introduction of Asian H5N1 AI into the western hemisphere. If/when an infected bird is detected, a pressing question will be where was this bird several days ago, and where is it likely to go after it was released from the survey site? Answers to such questions will increase effectiveness of AI surveillance and mitigation measures. From a conservation perspective, Alaska's diverse landscape provides breeding sites for many migrants, and climatic and land surface changes along migratory flyways in the western hemisphere may reduce bird survival and physical condition upon arrival at Alaskan breeding territories, success and migrant populations.

SIR model on a dynamical network and the endemic state of an infectious disease

NASA Astrophysics Data System (ADS)

Dottori, M.; Fabricius, G.

2015-09-01

In this work we performed a numerical study of an epidemic model that mimics the endemic state of whooping cough in the pre-vaccine era. We considered a stochastic SIR model on dynamical networks that involve local and global contacts among individuals and analysed the influence of the network properties on the characterization of the quasi-stationary state. We computed probability density functions (PDF) for infected fraction of individuals and found that they are well fitted by gamma functions, excepted the tails of the distributions that are q-exponentials. We also computed the fluctuation power spectra of infective time series for different networks. We found that network effects can be partially absorbed by rescaling the rate of infective contacts of the model. An explicit relation between the effective transmission rate of the disease and the correlation of susceptible individuals with their infective nearest neighbours was obtained. This relation quantifies the known screening of infective individuals observed in these networks. We finally discuss the goodness and limitations of the SIR model with homogeneous mixing and parameters taken from epidemiological data to describe the dynamic behaviour observed in the networks studied.

Deciphering the crowd: modeling and identification of pedestrian group motion.

PubMed

Yücel, Zeynep; Zanlungo, Francesco; Ikeda, Tetsushi; Miyashita, Takahiro; Hagita, Norihiro

2013-01-14

Associating attributes to pedestrians in a crowd is relevant for various areas like surveillance, customer profiling and service providing. The attributes of interest greatly depend on the application domain and might involve such social relations as friends or family as well as the hierarchy of the group including the leader or subordinates. Nevertheless, the complex social setting inherently complicates this task. We attack this problem by exploiting the small group structures in the crowd. The relations among individuals and their peers within a social group are reliable indicators of social attributes. To that end, this paper identifies social groups based on explicit motion models integrated through a hypothesis testing scheme. We develop two models relating positional and directional relations. A pair of pedestrians is identified as belonging to the same group or not by utilizing the two models in parallel, which defines a compound hypothesis testing scheme. By testing the proposed approach on three datasets with different environmental properties and group characteristics, it is demonstrated that we achieve an identification accuracy of 87% to 99%. The contribution of this study lies in its definition of positional and directional relation models, its description of compound evaluations, and the resolution of ambiguities with our proposed uncertainty measure based on the local and global indicators of group relation.

Deciphering the Crowd: Modeling and Identification of Pedestrian Group Motion

PubMed Central

Yücel, Zeynep; Zanlungo, Francesco; Ikeda, Tetsushi; Miyashita, Takahiro; Hagita, Norihiro

2013-01-01

Associating attributes to pedestrians in a crowd is relevant for various areas like surveillance, customer profiling and service providing. The attributes of interest greatly depend on the application domain and might involve such social relations as friends or family as well as the hierarchy of the group including the leader or subordinates. Nevertheless, the complex social setting inherently complicates this task. We attack this problem by exploiting the small group structures in the crowd. The relations among individuals and their peers within a social group are reliable indicators of social attributes. To that end, this paper identifies social groups based on explicit motion models integrated through a hypothesis testing scheme. We develop two models relating positional and directional relations. A pair of pedestrians is identified as belonging to the same group or not by utilizing the two models in parallel, which defines a compound hypothesis testing scheme. By testing the proposed approach on three datasets with different environmental properties and group characteristics, it is demonstrated that we achieve an identification accuracy of 87% to 99%. The contribution of this study lies in its definition of positional and directional relation models, its description of compound evaluations, and the resolution of ambiguities with our proposed uncertainty measure based on the local and global indicators of group relation. PMID:23344382

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions Based on a Bank of Norm-Inequality-Constrained Epoch-State Filters

NASA Technical Reports Server (NTRS)

Carpenter, J. R.; Markley, F. L.; Alfriend, K. T.; Wright, C.; Arcido, J.

2011-01-01

Sequential probability ratio tests explicitly allow decision makers to incorporate false alarm and missed detection risks, and are potentially less sensitive to modeling errors than a procedure that relies solely on a probability of collision threshold. Recent work on constrained Kalman filtering has suggested an approach to formulating such a test for collision avoidance maneuver decisions: a filter bank with two norm-inequality-constrained epoch-state extended Kalman filters. One filter models 1he null hypothesis 1ha1 the miss distance is inside the combined hard body radius at the predicted time of closest approach, and one filter models the alternative hypothesis. The epoch-state filter developed for this method explicitly accounts for any process noise present in the system. The method appears to work well using a realistic example based on an upcoming highly-elliptical orbit formation flying mission.

The discrepancy between implicit and explicit attitudes in predicting disinhibited eating.

PubMed

Goldstein, Stephanie P; Forman, Evan M; Meiran, Nachshon; Herbert, James D; Juarascio, Adrienne S; Butryn, Meghan L

2014-01-01

Disinhibited eating (i.e., the tendency to overeat, despite intentions not to do so, in the presence of palatable foods or other cues such as emotional stress) is strongly linked with obesity and appears to be associated with both implicit (automatic) and explicit (deliberative) food attitudes. Prior research suggests that a large discrepancy between implicit and explicit food attitudes may contribute to greater levels of disinhibited eating; however this theory has not been directly tested. The current study examined whether the discrepancy between implicit and explicit attitudes towards chocolate could predict both lab-based and self-reported disinhibited eating of chocolate. Results revealed that, whereas neither implicit nor explicit attitudes alone predicted disinhibited eating, absolute attitude discrepancy positively predicted chocolate consumption. Impulsivity moderated this effect, such that discrepancy was less predictive of disinhibited eating for those who exhibited lower levels of impulsivity. The results align with the meta-cognitive model to indicate that attitude discrepancy may be involved in overeating. © 2013.

A dependency-based modelling mechanism for problem solving

NASA Technical Reports Server (NTRS)

London, P.

1978-01-01

The paper develops a technique of dependency net modeling which relies on an explicit representation of justifications for beliefs held by the problem solver. Using these justifications, the modeling mechanism is able to determine the relevant lines of inference to pursue during problem solving. Three particular problem-solving difficulties which may be handled by the dependency-based technique are discussed: (1) subgoal violation detection, (2) description binding, and (3) maintaining a consistent world model.

Scales and erosion

USDA-ARS?s Scientific Manuscript database

There is a need to develop scale explicit understanding of erosion to overcome existing conceptual and methodological flaws in our modelling methods currently applied to understand the process of erosion, transport and deposition at the catchment scale. These models need to be based on a sound under...

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT: A GIS-BASED HYDROLOGIC MODELING TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extens...

Enhanced Estimation of Terrestrial Loadings for TMDLs: Normalization Approach

USDA-ARS?s Scientific Manuscript database

TMDL implementation plans to remediate pathogen-impaired streams are usually based on deterministic terrestrial fate and transport (DTFT) models. A novel protocol is proposed that can effectively, efficiently, and explicitly capture the predictive uncertainty of DTFT models used to establish terres...

Decoding leaf hydraulics with a spatially explicit model: principles of venation architecture and implications for its evolution.

PubMed

McKown, Athena D; Cochard, Hervé; Sack, Lawren

2010-04-01

Leaf venation architecture is tremendously diverse across plant species. Understanding the hydraulic functions of given venation traits can clarify the organization of the vascular system and its adaptation to environment. Using a spatially explicit model (the program K_leaf), we subjected realistic simulated leaves to modifications and calculated the impacts on xylem and leaf hydraulic conductance (K(x) and K(leaf), respectively), important traits in determining photosynthesis and growth. We tested the sensitivity of leaves to altered vein order conductivities (1) in the absence or (2) presence of hierarchical vein architecture, (3) to major vein tapering, and (4) to modification of vein densities (length/leaf area). The K(x) and K(leaf) increased with individual vein order conductivities and densities; for hierarchical venation systems, the greatest impact was from increases in vein conductivity for lower vein orders and increases in density for higher vein orders. Individual vein order conductivities were colimiting of K(x) and K(leaf), as were their densities, but the effects of vein conductivities and densities were orthogonal. Both vein hierarchy and vein tapering increased K(x) relative to xylem construction cost. These results highlight the important consequences of venation traits for the economics, ecology, and evolution of plant transport capacity.

Implicit and Explicit Sexual Attitudes: How Are They Related to Sexual Desire and Sexual Satisfaction in Men and Women?

PubMed

Dosch, Alessandra; Belayachi, Sanaâ; Van der Linden, Martial

2016-01-01

This article examines individual variability in sexual desire and sexual satisfaction by exploring the relation between these sexual aspects and sexual attitudes (implicit and explicit) and by taking gender into account, as this has been shown to be an influential factor. A total of 28 men and 33 women living in heterosexual relationships completed questionnaires assessing sexual desire (dyadic, solitary), sexual satisfaction, and explicit sexual attitudes. An adapted version of the Affect Misattribution Procedure was used to assess implicit sexual attitudes. Results showed higher levels of dyadic and solitary sexual desire in men than in women. No gender differences were found regarding sexual satisfaction or sexual attitudes. High dyadic sexual desire was associated with positive implicit and explicit sexual attitudes, regardless of gender. However, solitary sexual desire was significantly higher in men than women and was associated, in women only, with positive implicit sexual attitudes, suggesting that solitary sexual desire may fulfill different functions in men and women. Finally, sexual satisfaction depended on the combination of explicit and implicit sexual attitudes in both men and women. This study highlights the importance of considering both implicit and explicit sexual attitudes to better understand the mechanisms underlying individual variability in sexual desire and satisfaction.

Components of Implicit Stigma against Mental Illness among Chinese Students

PubMed Central

Wang, Xiaogang; Huang, Xiting; Jackson, Todd; Chen, Ruijun

2012-01-01

Although some research has examined negative automatic aspects of attitudes toward mental illness via relatively indirect measures among Western samples, it is unclear whether negative attitudes can be automatically activated in individuals from non-Western countries. This study attempted to validate results from Western samples with Chinese college students. We first examined the three-component model of implicit stigma (negative cognition, negative affect, and discriminatory tendencies) toward mental illness with the Single Category Implicit Association Test (SC-IAT). We also explored the relationship between explicit and implicit stigma among 56 Chinese university college students. In the three separate SC-IATs and the combined SC-IAT, automatic associations between mental illness and negative descriptors were stronger relative to those with positive descriptors and the implicit effect of cognitive and affective SC-IATs were significant. Explicit and implicit measures of stigma toward mental illness were unrelated. In our sample, women's overall attitudes toward mental illness were more negative than men's were, but no gender differences were found for explicit measures. These findings suggested that implicit stigma toward mental illness exists in Chinese students, and provide some support for the three-component model of implicit stigma toward mental illness. Future studies that focus on automatic components of stigmatization and stigma-reduction in China are warranted. PMID:23029366

A Knowledge Navigation Method for the Domain of Customers' Services of Mobile Communication Corporations in China

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

Rapidly increasing amount of mobile phone users and types of services leads to a great accumulation of complaining information. How to use this information to enhance the quality of customers' services is a big issue at present. To handle this kind of problem, the paper presents an approach to construct a domain knowledge map for navigating the explicit and tacit knowledge in two ways: building the Topic Map-based explicit knowledge navigation model, which includes domain TM construction, a semantic topic expansion algorithm and VSM-based similarity calculation; building Social Network Analysis-based tacit knowledge navigation model, which includes a multi-relational expert navigation algorithm and the criterions to evaluate the performance of expert networks. In doing so, both the customer managers and operators in call centers can find the appropriate knowledge and experts quickly and exactly. The experimental results show that the above method is very powerful for knowledge navigation.

Predicting the evolution of large cholera outbreaks: lessons learnt from the Haiti case study

NASA Astrophysics Data System (ADS)

Bertuzzo, Enrico; Mari, Lorenzo; Righetto, Lorenzo; Knox, Allyn; Finger, Flavio; Casagrandi, Renato; Gatto, Marino; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2013-04-01

Mathematical models can provide key insights into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and possibly anticipating the impact of alternative interventions. Spatially explicit models of waterborne disease are made routinely possible by widespread data mapping of hydrology, road network, population distribution, and sanitation. Here, we study the ex-post reliability of predictions of the ongoing Haiti cholera outbreak. Our model consists of a set of dynamical equations (SIR-like, i.e. subdivided into the compartments of Susceptible, Infected and Recovered individuals) describing a connected network of human communities where the infection results from the exposure to excess concentrations of pathogens in the water, which are, in turn, driven by hydrologic transport through waterways and by mobility of susceptible and infected individuals. Following the evidence of a clear correlation between rainfall events and cholera resurgence, we test a new mechanism explicitly accounting for rainfall as a driver of enhanced disease transmission by washout of open-air defecation sites or cesspool overflows. A general model for Haitian epidemic cholera and the related uncertainty is thus proposed and applied to the dataset of reported cases now available. The model allows us to draw predictions on longer-term epidemic cholera in Haiti from multi-season Monte Carlo runs, carried out up to January 2014 by using a multivariate Poisson rainfall generator, with parameters varying in space and time. Lessons learned and open issues are discussed and placed in perspective. We conclude that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control.

Explicit ions/implicit water generalized Born model for nucleic acids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tolokh, Igor S.; Thomas, Dennis G.; Onufriev, Alexey V.

Ion atmosphere around highly charged nucleic acid molecules plays a significant role in their dynamics, structure and interactions. Here we utilized the implicit solvent framework to develop a model for the explicit treatment of ions interacting with nucleic acid molecules. The proposed explicit ions/implicit water model is based on a significantly modified generalized Born (GB) model, and utilizes a non-standard approach to defining the solute/solvent dielectric boundary. Specifically, the model includes modifications to the GB interaction terms for the case of multiple interacting solutes – disconnected dielectric boundary around the solute-ion or ion-ion pairs. Fully analytical description of all energymore » components for charge-charge interactions is provided. The effectiveness of the approach is demonstrated by calculating the potential of mean force (PMF) for Na+-Cl− ion pair and by carrying out a set of Monte Carlo (MC) simulations of mono- and trivalent ions interacting with DNA and RNA duplexes. The monovalent (Na+) and trivalent (CoHex3+) counterion distributions predicted by the model are in close quantitative agreement with all-atom explicit water molecular dynamics simulations used as reference. Expressed in the units of energy, the maximum deviations of local ion concentrations from the reference are within kBT. The proposed explicit ions/implicit water GB model is able to resolve subtle features and differences of CoHex distributions around DNA and RNA duplexes. These features include preferential CoHex binding inside the major groove of RNA duplex, in contrast to CoHex biding at the "external" surface of the sugar-phosphate backbone of DNA duplex; these differences in the counterion binding patters were shown earlier to be responsible for the observed drastic differences in condensation propensities between short DNA and RNA duplexes. MC simulations of CoHex ions interacting with homopolymeric poly(dA·dT) DNA duplex with modified (de-methylated) and native Thymine bases are used to explore the physics behind CoHex-Thymine interactions. The simulations suggest that the ion desolvation penalty due to proximity to the low dielectric volume of the methyl group can contribute significantly to CoHex-Thymine interactions. Compared to the steric repulsion between the ion and the methyl group, the desolvation penalty interaction has a longer range, and may be important to consider in the context of methylation effects on DNA condensation.« less

Explicit ions/implicit water generalized Born model for nucleic acids

NASA Astrophysics Data System (ADS)

Tolokh, Igor S.; Thomas, Dennis G.; Onufriev, Alexey V.

2018-05-01

The ion atmosphere around highly charged nucleic acid molecules plays a significant role in their dynamics, structure, and interactions. Here we utilized the implicit solvent framework to develop a model for the explicit treatment of ions interacting with nucleic acid molecules. The proposed explicit ions/implicit water model is based on a significantly modified generalized Born (GB) model and utilizes a non-standard approach to define the solute/solvent dielectric boundary. Specifically, the model includes modifications to the GB interaction terms for the case of multiple interacting solutes—disconnected dielectric boundary around the solute-ion or ion-ion pairs. A fully analytical description of all energy components for charge-charge interactions is provided. The effectiveness of the approach is demonstrated by calculating the potential of mean force for Na+-Cl- ion pair and by carrying out a set of Monte Carlo (MC) simulations of mono- and trivalent ions interacting with DNA and RNA duplexes. The monovalent (Na+) and trivalent (CoHex3+) counterion distributions predicted by the model are in close quantitative agreement with all-atom explicit water molecular dynamics simulations used as reference. Expressed in the units of energy, the maximum deviations of local ion concentrations from the reference are within kBT. The proposed explicit ions/implicit water GB model is able to resolve subtle features and differences of CoHex distributions around DNA and RNA duplexes. These features include preferential CoHex binding inside the major groove of the RNA duplex, in contrast to CoHex biding at the "external" surface of the sugar-phosphate backbone of the DNA duplex; these differences in the counterion binding patters were earlier shown to be responsible for the observed drastic differences in condensation propensities between short DNA and RNA duplexes. MC simulations of CoHex ions interacting with the homopolymeric poly(dA.dT) DNA duplex with modified (de-methylated) and native thymine bases are used to explore the physics behind CoHex-thymine interactions. The simulations suggest that the ion desolvation penalty due to proximity to the low dielectric volume of the methyl group can contribute significantly to CoHex-thymine interactions. Compared to the steric repulsion between the ion and the methyl group, the desolvation penalty interaction has a longer range and may be important to consider in the context of methylation effects on DNA condensation.

Structuring the collaboration of science and service in pursuit of a shared vision.

PubMed

Chorpita, Bruce F; Daleiden, Eric L

2014-01-01

The enduring needs of our society highlight the importance of a shared vision to improve human functioning and yield better lives for families and communities. Science offers a powerful strategy for managing the inevitable uncertainty in pursuit of these goals. This article presents ideas and examples of methods that could preserve the strengths of the two major paradigms in children's mental health, evidence-based treatments and individualized care models, but that also have the potential to extend their applicability and impact. As exemplified in some of the articles throughout this issue, new models to connect science and service will likely emerge from novel consideration of better ways to structure and inform collaboration within mental health systems. We contend that the future models for effective systems will involve increased attention to (a) client and provider developmental pathways, (b) explicit frameworks for coordinating people and the knowledge and other resources they use, and (c) a balance of evidence-based planning and informed adaptation. We encourage the diverse community of scientists, providers, and administrators in our field to come together to enhance our collective wisdom through consideration of and reflection on these concepts and their illustrations.

The good, the bad and the ugly of marine reserves for fishery yields

PubMed Central

De Leo, Giulio A.; Micheli, Fiorenza

2015-01-01

Marine reserves (MRs) are used worldwide as a means of conserving biodiversity and protecting depleted populations. Despite major investments in MRs, their environmental and social benefits have proven difficult to demonstrate and are still debated. Clear expectations of the possible outcomes of MR establishment are needed to guide and strengthen empirical assessments. Previous models show that reserve establishment in overcapitalized, quota-based fisheries can reduce both catch and population abundance, thereby negating fisheries and even conservation benefits. By using a stage-structured, spatially explicit stochastic model, we show that catches under quota-based fisheries that include a network of MRs can exceed maximum sustainable yield (MSY) under conventional quota management if reserves provide protection to old, large spawners that disproportionally contribute to recruitment outside the reserves. Modelling results predict that the net fishery benefit of MRs is lost when gains in fecundity of old, large individuals are small, is highest in the case of sedentary adults with high larval dispersal, and decreases with adult mobility. We also show that environmental variability may mask fishery benefits of reserve implementation and that MRs may buffer against collapse when sustainable catch quotas are exceeded owing to stock overestimation or systematic overfishing. PMID:26460129

An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

NASA Astrophysics Data System (ADS)

Hu, Xiaolin; Puddy, Richard W.

This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

Evaluating impacts of fire management strategies on native and invasive plants using an individual-based model

NASA Astrophysics Data System (ADS)

Gangur, Alexander N.; Fill, Jennifer M.; Northfield, Tobin D.; van de Wiel, Marco

2017-04-01

The capacity for species to coexist and potentially exclude one another can broadly be attributed to drivers that influence fitness differences (such as competitive ability) and niche differences (such as environmental change). These drivers, and thus the determinants of coexistence they influence, can interact and fluctuate both spatially and temporally. Understanding the spatiotemporal variation in niche and fitness differences in systems prone to fluctuating drivers, such as fire, can help to inform the management of invasive species. In the Cape floristic region of South Africa, invasive Pinus pinaster seedlings are strong competitors in the post-burn environment of the fire-driven Fynbos vegetation. In this, system native Protea spp. are especially vulnerable to unseasonal burns, but seasonal prescribed (Summer) burns are thought to present a high safety risk. Together, these issues have limited the appeal of prescribed burn management as an alternative to costly manual eradication of P. pinaster. Using a spatially-explicit field-of-neighbourhood individual-based model, we represent the drivers of spatiotemporal variation in niche differences (driven by fire regimes) and fitness differences (driven by competitive ability). In doing so, we evaluate optimal fire management strategies to a) control invasive P. pinaster in the Cape floristic region of South Africa, while b) minimizing deleterious effects of management on native Protea spp. The scarcity of appropriate data for model calibration has been problematic for models in invasion biology, but we use recent advances in Approximate Bayesian Computing techniques to overcome this limitation. We present early conclusions on the viability of prescribed burn management to control P. pinaster in South Africa.

The Importance of Explicitly Representing Soil Carbon with Depth over the Permafrost Region in Earth System Models: Implications for Atmospheric Carbon Dynamics at Multiple Temporal Scales between 1960 and 2300.

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2014-12-01

We conducted an assessment of changes in permafrost area and carbon storage simulated by process-based models between 1960 and 2300. The models participating in this comparison were those that had joined the model integration team of the Vulnerability of Permafrost Carbon Research Coordination Network (see http://www.biology.ufl.edu/permafrostcarbon/). Each of the models in this comparison conducted simulations over the permafrost land region in the Northern Hemisphere driven by CCSM4-simulated climate for RCP 4.5 and 8.5 scenarios. Among the models, the area of permafrost (defined as the area for which active layer thickness was less than 3 m) ranged between 13.2 and 20.0 million km2. Between 1960 and 2300, models indicated the loss of permafrost area between 5.1 to 6.0 million km2 for RCP 4.5 and between 7.1 and 15.2 million km2 for RCP 8.5. Among the models, the density of soil carbon storage in 1960 ranged between 13 and 42 thousand g C m-2; models that explicitly represented carbon with depth had estimates greater than 27 thousand g C m-2. For the RCP 4.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 32 Pg C to gains of 58 Pg C, in which models that explicitly represent soil carbon with depth simulated losses or lower gains of soil carbon in comparison with those that did not. For the RCP 8.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 642 Pg C to gains of 66 Pg C, in which those models that represent soil carbon explicitly with depth all simulated losses, while those that do not all simulated gains. These results indicate that there are substantial differences in responses of carbon dynamics between model that do and do not explicitly represent soil carbon with depth in the permafrost region. We present analyses of the implications of the differences for atmospheric carbon dynamics at multiple temporal scales between 1960 and 2300.

Teachers' Perceptions of Strategy Based Reading Instruction for Reading Comprehension

ERIC Educational Resources Information Center

Gibson, Katherine D.

2009-01-01

Strategy based reading instruction helps teachers differentiate the teaching of reading. It also supports many types of readers by explicitly teaching and modeling reading comprehension strategies. The purpose of this study is to explore the effectiveness of strategy based reading instruction for improving student reading comprehension. …