A model of the pelagic ecossystem in the eastern tropical Pacific Ocean

English: Recent calls for a more holistic approach to fisheries management have motivated development of trophic mass-balance models of ecosystems that underlie fisheries production. We developed a model hypothesis of the pelagic ecosystem in the eastern tropical Pacific Ocean (ETP) to gain insight into the relationships among the various species in the system and to explore the ecological implications of alternative methods of harvesting tunas. We represented the biomasses of and fluxes between the principal elements in the ecosystem with Ecopath, and examined the ecosystem's dynamic, time-series behavior with Ecosim. We parameterized the model for 38 species or groups of species, and described the sources, justifications, assumptions, and revisions of our estimates of the various parameters, diet relations, fisheries landings, and fisheries discards in the model. We conducted sensitivity analyses with an intermediate version of the model, for both the Ecopath mass-balance and the dynamic trajectories predicted by Ecosim. The analysis showed that changes in the basic parameters for two components at middle trophic levels, Cephalopods and Auxis spp., exert the greatest influence on the system. When the Cephalopod Q/B and Auxis spp. P/B were altered from their initial values and the model was rebalanced, the trends of the biomass trajectories predicted by Ecosim were not sensitive, but the scaling was sensitive for several components. We described the review process the model was subjected to, which included reviews by the IATTC Purse-seine Bycatch Working Group and by a working group supported by the National Center for Ecological Analysis and Synthesis. We fitted the model to historical time series of catches per unit of effort and mortality rates for yellowfin and bigeye tunas in simulations that incorporated historical fishing effort and a climate driver to represent the effect of El Niño-Southern Oscillation-scale variation on the system. The model was designed to evaluate the possible ecological implications of fishing for tunas in various ways. We recognize that a model cannot possibly represent all the complexity of a pelagic ocean ecosystem, but we believe that the ETP model provides insight into the structure and function of the pelagic ETP. Spanish: Llamamientos recientes hacia un enfoque más holístico al ordenamiento de la pesca han motivado el desarrollo de modelos tróficos de balance de masas de los ecosistemas que sostienen la producción pesquera. Desarrollamos una hipótesis modelo del ecosistema pelágico en el Océano Pacífico oriental tropical (POT) con miras a mejorar los conocimientos de las relaciones entre las distintas especies en el sistema y explorar las implicaciones ecológicas de métodos alternativos de capturar atunes. Con Ecopath representamos las biomasas de los elementos principales en el ecosistema, y los flujos entre los mismos, y con Ecosim examinamos el comportamiento dinámico del ecosistema con el tiempo. Parametrizamos el modelo para 38 especies o grupos de especies (denominados “componentes” del modelo), y describimos las fuentes, justificaciones, supuestos, y revisiones de nuestras estimaciones de los distintos parámetros, relaciones basadas en dieta, capturas retenidas de las pesquerías, y descartes de las mismas en el modelo. Realizamos análisis de sensibilidad con una versión intermedia del modelo, para el balance de masas de Ecopath y las trayectorias dinámicas predichas por Ecosim también. El análisis demostró que cambios en los parámetros básicos para dos componentes en niveles tróficos medianos, Cefalópodos y Auxis spp., ejercieron la mayor influencia sobre el sistema. Cuando se alteraron el Q/B de los Cefalópodos y el P/B de los Auxis spp. de sus valores iniciales y se balanceó el modelo de nuevo, las tendencias de las trayectorias de la biomasa predichas por Ecosim no fueron sensibles, pero la escala fue sensible para varios componentes. Describimos el proceso de revisión al que fue sujeto el modelo, inclusive revisiones por el Grupo de Trabajo sobre Captura Incidental de la CIAT y un grupo de trabajo apoyado por el Centro Nacional para Síntesis y Análisis Ecológicos. Ajustamos el modelo a series de tiempo históricas de capturas por unidad de esfuerzo y tasas de mortalidad de atunes aleta amarilla y patudo en simulaciones que incorporaron esfuerzo de pesca histórico e impulsos climáticos para representar el efecto de variaciones a escala de El Niño-Oscilación del Sur sobre el sistema. El modelo fue diseñado para evaluar las posibles implicaciones ecológicas de la pesca atunera de varias formas. Reconocemos la imposibilidad de que el modelo represente toda la complejidad de un ecosistema oceánico pelágico, pero creemos que el modelo del POT mejora los conocimientos de la estructura y función del POT pelágico.

A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example

We present a method to integrate environmental time series into stock assessment models and to test the significance of correlations between population processes and the environmental time series. Parameters that relate the environmental time series to population processes are included in the stock assessment model, and likelihood ratio tests are used to determine if the parameters improve the fit to the data significantly. Two approaches are considered to integrate the environmental relationship. In the environmental model, the population dynamics process (e.g. recruitment) is proportional to the environmental variable, whereas in the environmental model with process error it is proportional to the environmental variable, but the model allows an additional temporal variation (process error) constrained by a log-normal distribution. The methods are tested by using simulation analysis and compared to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. In the traditional method, the estimates of recruitment were provided by a model that allowed the recruitment only to have a temporal variation constrained by a log-normal distribution. We illustrate the methods by applying them to test the statistical significance of the correlation between sea-surface temperature (SST) and recruitment to the snapper (Pagrus auratus) stock in the Hauraki Gulf–Bay of Plenty, New Zealand. Simulation analyses indicated that the integrated approach with additional process error is superior to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. The results suggest that, for the snapper stock, recruitment is positively correlated with SST at the time of spawning.

Modified Kanerva model. Results for real time word recognition

This paper describes results obtained using the modified Kanerva model to perform word recognition in continuous speech after being trained on the multi-speaker Alvey 'Hotel' speech corpus. Theoretical discoveries have recently enabled us to increase the speed of execution of part of the model by two orders of magnitude over that previously reported by Prager & Fallside. The memory required for the operation of the model has been similarly reduced. The recognition accuracy reaches 95% without syntactic constraints when tested on different data from seven trained speakers. Real time simulation of a model with 9,734 active units is now possible in both training and recognition modes using the Alvey PARSIFAL transputer array. The modified Kanerva model is a static network consisting of a fixed nonlinear mapping (location matching) followed by a single layer of conventional adaptive links. A section of preprocessed speech is transformed by the non-linear mapping to a high dimensional representation. From this intermediate representation a simple linear mapping is able to perform complex pattern discrimination to form the output, indicating the nature of the speech features present in the input window.

Validation of a lattice Boltzmann model for gas-solid reactions with experiments

A lattice Boltzmann method is used to model gas-solid reactions where the composition of both the gas and solid phase changes with time, while the boundary between phases remains fixed. The flow of the bulk gas phase is treated using a multiple relaxation time MRT D3Q19 model; the dilute reactant is treated as a passive scalar using a single relaxation time BGK D3Q7 model with distinct inter- and intraparticle diffusivities. A first-order reaction is incorporated by modifying the method of Sullivan et al. [13] to include the conversion of a solid reactant. The detailed computational model is able to capture the multiscale physics encountered in reactor systems. Specifically, the model reproduced steady state analytical solutions for the reaction of a porous catalyst sphere (pore scale) and empirical solutions for mass transfer to the surface of a sphere at Re=10 (particle scale). Excellent quantitative agreement between the model and experiments for the transient reduction of a single, porous sphere of Fe 2O 3 to Fe 3O 4 in CO at 1023K and 10 5Pa is demonstrated. Model solutions for the reduction of a packed bed of Fe 2O 3 (reactor scale) at identical conditions approached those of experiments after 25 s, but required prohibitively long processor times. The presented lattice Boltzmann model resolved successfully mass transport at the pore, particle and reactor scales and highlights the relevance of LB methods for modelling convection, diffusion and reaction physics. © 2012 Elsevier Inc.

Production planning of multi-stage multi-option seru production systems with sustainable measures

With the concerns over climate change and the escalation in worldwide population, sustainable development attracts more and more attention of academia, policy makers, and businesses in countries. Sustainable manufacturing is an inextricable measure to achieve sustainable development since manufacturing is one of the main energy consumers and greenhouse gas contributors. In the previous researches on production planning of manufacturing systems, environmental factor was rarely considered. This paper investigates the production planning problem under the performance measures of economy and environment with respect to seru production systems, a new manufacturing system praised as Double E (ecology and economy) in Japanese manufacturing industries. We propose a mathematical model with two objectives minimizing carbon dioxide emission and makespan for processing all product types by a seru production system. To solve this mathematical model, we develop an algorithm based on the non-dominated sorting genetic algorithm II. The computation results and analysis of three numeral examples confirm the effectiveness of our proposed algorithm. © 2014 Elsevier Ltd. All rights reserved.

A Neural Network Model of Speech Acquisition and Motor Equivalent Speech Production

This article describes a neural network model that addresses the acquisition of speaking skills by infants and subsequent motor equivalent production of speech sounds. The model learns two mappings during a babbling phase. A phonetic-to-orosensory mapping specifies a vocal tract target for each speech sound; these targets take the form of convex regions in orosensory coordinates defining the shape of the vocal tract. The babbling process wherein these convex region targets are formed explains how an infant can learn phoneme-specific and language-specific limits on acceptable variability of articulator movements. The model also learns an orosensory-to-articulatory mapping wherein cells coding desired movement directions in orosensory space learn articulator movements that achieve these orosensory movement directions. The resulting mapping provides a natural explanation for the formation of coordinative structures. This mapping also makes efficient use of redundancy in the articulator system, thereby providing the model with motor equivalent capabilities. Simulations verify the model's ability to compensate for constraints or perturbations applied to the articulators automatically and without new learning and to explain contextual variability seen in human speech production.

Differential and numerical models of hysteretic systems with stochastic and deterministic inputs

Many deterministic models with hysteresis have been developed in the areas of economics, finance, terrestrial hydrology and biology. These models lack any stochastic element which can often have a strong effect in these areas. In this work stochastically driven closed loop systems with hysteresis type memory are studied. This type of system is presented as a possible stochastic counterpart to deterministic models in the areas of economics, finance, terrestrial hydrology and biology. Some price dynamics models are presented as a motivation for the development of this type of model. Numerical schemes for solving this class of stochastic differential equation are developed in order to examine the prototype models presented. As a means of further testing the developed numerical schemes, numerical examination is made of the behaviour near equilibrium of coupled ordinary differential equations where the time derivative of the Preisach operator is included in one of the equations. A model of two phenotype bacteria is also presented. This model is examined to explore memory effects and related hysteresis effects in the area of biology. The memory effects found in this model are similar to that found in the non-ideal relay. This non-ideal relay type behaviour is used to model a colony of bacteria with multiple switching thresholds. This model contains a Preisach type memory with a variable Preisach weight function. Shown numerically for this multi-threshold model is a pattern formation for the distribution of the phenotypes among the available thresholds.

Prediction in dynamic models with time-dependent conditional variances

This paper considers forecasting the conditional mean and variance from a single-equation dynamic model with autocorrelated disturbances following an ARMA process, and innovations with time-dependent conditional heteroskedasticity as represented by a linear GARCH process. Expressions for the minimum MSE predictor and the conditional MSE are presented. We also derive the formula for all the theoretical moments of the prediction error distribution from a general dynamic model with GARCH(1, 1) innovations. These results are then used in the construction of ex ante prediction confidence intervals by means of the Cornish-Fisher asymptotic expansion. An empirical example relating to the uncertainty of the expected depreciation of foreign exchange rates illustrates the usefulness of the results. © 1992.

Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

Telescoping is not time compression: a model of the dating of autobiographical events.

A model of telescoping is proposed that assumes no systematic errors in dating. Rather, the overestimation of recent occurrences of events is based on the combination of three factors: (1) Retention is greater for recent events; (2) errors in dating, though unbiased, increase linearly with the time since the dated event; and (3) intrusions often occur from events outside the period being asked about, but such intrusions do not come from events that have not yet occurred. In Experiment 1, we found that recall for colloquia fell markedly over a 2-year interval, the magnitude of errors in psychologists' dating of the colloquia increased at a rate of .4 days per day of delay, and the direction of the dating error was toward the middle of the interval. In Experiment 2, the model used the retention function and dating errors from the first study to predict the distribution of the actual dates of colloquia recalled as being within a 5-month period. In Experiment 3, the findings of the first study were replicated with colloquia given by, instead of for, the subjects.

Communication system model for information rate evaluation of differential detection over time-varying channels

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.

Speech Recognition with unknown partial feature corruption - a review of the union model

This paper provides a summary of our studies on robust speech recognition based on a new statistical approach – the probabilistic union model. We consider speech recognition given that part of the acoustic features may be corrupted by noise. The union model is a method for basing the recognition on the clean part of the features, thereby reducing the effect of the noise on recognition. To this end, the union model is similar to the missing feature method. However, the two methods achieve this end through different routes. The missing feature method usually requires the identity of the noisy data for noise removal, while the union model combines the local features based on the union of random events, to reduce the dependence of the model on information about the noise. We previously investigated the applications of the union model to speech recognition involving unknown partial corruption in frequency band, in time duration, and in feature streams. Additionally, a combination of the union model with conventional noise-reduction techniques was studied, as a means of dealing with a mixture of known or trainable noise and unknown unexpected noise. In this paper, a unified review, in the context of dealing with unknown partial feature corruption, is provided into each of these applications, giving the appropriate theory and implementation algorithms, along with an experimental evaluation.

Scaling in the time-dependent failure of a fiber bundle with local load sharing

We study the scaling behaviors of a time-dependent fiber-bundle model with local load sharing. Upon approaching the complete failure of the bundle, the breaking rate of fibers diverges according to r(t)proportional to(T-f-t)(-xi) where T-f is the lifetime of the bundle and xi approximate to 1.0 is a universal scaling exponent. The average lifetime of the bundle [T-f] scales with the system size as N-delta, where delta depends on the distribution of individual fiber as well as the breakdown rule. [S1063-651X(99)13902-3].

Immune reactions to Bacteroides fragilis populations with three different types of capsule in a model of infection

The survival and growth of populations of the obligately anaerobic pathogenic bacterium Bacteroides fragilis enriched for large capsules (LCs), small capsules (SCs) or an electron-dense layer (EDL; non-capsulate by light microscopy) were examined in a mouse model of infection over a minimum period of 20 d. Chambers which allowed the influx of leukocytes, but not the efflux of bacteria, were implanted in the mouse peritoneal cavity. The LC and EDL populations consistently attained viable cell densities of the order of 10(8)-10(9) c.f.u. ml-1 within 24 h, whereas the SC population did not. However, after 3 d, all three bacterial populations maintained total viable numbers of 10(8)-10(9) c.f.u. ml-1 within the chambers. LC expression was selected against within 24 h in the model, the populations becoming non-capsulate by light microscopy, whereas in the SC population expression of the SC was retained by approximately 90% of the population. The EDL population remained non-capsulate by light microscopy throughout. Lymphocytes infiltrated the chambers to an equal extent for all three B. fragilis populations and at approximately 1000 times higher concentration than chambers which contained only quarter-strength Ringer's solution. The presence of neutrophils within the chambers did not cause a decrease in the total viable bacterial count. Each population elicited antibodies specific for outer-membrane proteins and polysaccharide, as detected by immunoblotting, which cross-reacted with the other populations. Differences were observed in the immunogenicity of the outer-membrane proteins within the three populations. Neutrophils were initially the predominant cell type in the chambers, but as the total leukocyte count increased with incubation time, neutrophils were outnumbered by other leukocytes.(ABSTRACT TRUNCATED AT 250 WORDS)

Spindle assembly checkpoint protein expression correlates with cellular proliferation and shorter time to recurrence in ovarian cancer.

Ovarian carcinoma (OC) is the most lethal of the gynecological malignancies, often presenting at an advanced stage. Treatment is hampered by high levels of drug resistance. The taxanes are microtubule stabilizing agents, used as first-line agents in the treatment of OC that exert their apoptotic effects through the spindle assembly checkpoint. BUB1-related protein kinase (BUBR1) and mitotic arrest deficient 2 (MAD2), essential spindle assembly checkpoint components, play a key role in response to taxanes. BUBR1, MAD2, and Ki-67 were assessed on an OC tissue microarray platform representing 72 OC tumors of varying histologic subtypes. Sixty-one of these patients received paclitaxel and platinum agents combined; 11 received platinum alone. Overall survival was available for all 72 patients, whereas recurrence-free survival (RFS) was available for 66 patients. Increased BUBR1 expression was seen in serous carcinomas, compared with other histologies (P = .03). Increased BUBR1 was significantly associated with tumors of advanced stage (P = .05). Increased MAD2 and BUBR1 expression also correlated with increased cellular proliferation (P < .0002 and P = .02, respectively). Reduced MAD2 nuclear intensity was associated with a shorter RFS (P = .03), in ovarian tumors of differing histologic subtype (n = 66). In this subgroup, for those women who received paclitaxel and platinum agents combined (n = 57), reduced MAD2 intensity also identified women with a shorter RFS (P < .007). For the entire cohort of patients, irrespective of histologic subtype or treatment, MAD2 nuclear intensity retained independent significance in a multivariate model, with tumors showing reduced nuclear MAD2 intensity identifying patients with a poorer RFS (P = .05).