Mathematical programming model for heat exchanger design through optimization of partial objectives

Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature.

Les pratiques d’intervention policières auprès des personnes en crise ou atteintes de troubles mentaux : le cas des agents de réponse en intervention de crise du Service de police de la Ville de Montréal

Cette recherche porte sur les pratiques d’intervention des agents de réponse en intervention de crise (RIC), de leur partenaire fixe et des agents en attente de la formation du Service de police de la Ville de Montréal (SPVM) auprès des personnes en crise ou atteintes de troubles mentaux. Les agents RIC sont des patrouilleurs de première ligne qui ont reçu une formation complète sur les principes d’intervention en contexte de crise ou de santé mentale. Ce modèle de réponse spécialisée est une solution proactive qui a pour but d’améliorer l’action policière en situation de crise et de veiller à une meilleure prise en charge de ces personnes par les ressources institutionnelles. La désinstitutionnalisation des soins et des services psychiatriques a eu pour effet une augmentation du nombre de personnes atteintes de troubles mentaux dans la communauté. Par conséquent, cet accroissement a engendré des rapports plus fréquents entre les services policiers et cette clientèle. Les interventions en contexte de crise ou de santé mentale sont particulières et complexes, de même qu’elles requièrent un niveau supérieur de compréhension des crises humaines. Les autorités policières ont admis que ces interventions représentent une part significative de leur travail et que la formation policière traditionnelle ne les prépare pas suffisamment pour intervenir adéquatement auprès de cette population. En réponse à ces considérations et dans l’objectif d’améliorer leur capacité d’agir, les forces policières se sont dotées de modèles de réponse policière spécialisée en intervention de crise. L’approche la plus répandue est l’équipe d’intervention de crise (« crisis intervention team » ou « CIT »), aussi appelée le modèle de Memphis. Il existe plusieurs variantes de ce modèle, mais les composantes principales, c’est-à-dire la formation avancée et la consolidation d’un partenariat avec le système de santé demeurent dans l’ensemble de ces structures. L’objectif de cette recherche consiste à sonder les perceptions des agents RIC, de leur partenaire fixe et des agents en attente de la formation afin de comprendre et de contraster leurs visions et leurs pratiques d’intervention en contexte de crise ou de santé mentale. Chaque groupe a apporté des précisions intéressantes. Nous avons conduit 12 entrevues qualitatives avec des policiers du SPVM. De façon générale, les participants rapportent que leurs pratiques d’intervention auprès des personnes en crise ou atteintes de troubles mentaux sont davantage ancrées dans une perspective de relation d’aide. Ils mentionnent également que la communication, l’écoute et la confiance doivent être privilégiées avant tout autre stratégie dans les situations qui les permettent et que la force doit être employée seulement lorsqu’elle est nécessaire, c’est-à-dire lorsque leur sécurité ou celle d’autrui est en péril ou lorsque la communication n’est pas possible. Puis, ils admettent que le recours à l’expertise des intervenants en santé mentale permet une analyse plus approfondie de la situation et de l’état mental de la personne visée par l’intervention. D’autre part, en ce qui concerne les limites de la formation policière traditionnelle, les candidats ont soulevé qu’il y a un manque de connaissances en matière de santé mentale ainsi qu’une difficulté associée à l’évaluation de l’état de la personne et du besoin de transport ont été soulevés. Sur le plan des apprentissages, les agents RIC disent avoir une compréhension plus globale de la problématique de santé mentale, de meilleures habiletés communicationnelles, une analyse plus approfondie de la situation, de plus grandes connaissances juridiques, une compréhension du fonctionnement des services hospitaliers ainsi qu’une appréciation particulière pour le partage de savoirs et les principes d’endiguement. Ils font part également de l’importance des rapports pour documenter l’évolution de l’état mental d’une personne et ils ajoutent que la dimension temporelle joue un rôle clé dans la résolution définitive de la problématique. Au sujet des partenaires, ils évoquent des retombées similaires. Toutefois, à la suite de la formation, ils reconnaissent davantage l’importance de leur rôle dans la sécurité de leur partenaire et ils y accordent dorénavant une attention marquée lors de ces interventions. Enfin, les agents non formés formulent des attentes relatives au développement d’outils et de compétences, ce qui leur sera rendu dans la formation RIC. Globalement, les agents RIC et les partenaires interviewés ont modifié leurs pratiques pour les arrimer avec la philosophie des interventions en contexte de crise ou de santé mentale. Ils ont également davantage confiance en leurs capacités et habiletés d’intervention auprès des personnes en crise ou atteintes de troubles mentaux grâce aux connaissances acquises dans la formation.

Les pratiques d’intervention policières auprès des personnes en crise ou atteintes de troubles mentaux : le cas des agents de réponse en intervention de crise du Service de police de la Ville de Montréal

Cette recherche porte sur les pratiques d’intervention des agents de réponse en intervention de crise (RIC), de leur partenaire fixe et des agents en attente de la formation du Service de police de la Ville de Montréal (SPVM) auprès des personnes en crise ou atteintes de troubles mentaux. Les agents RIC sont des patrouilleurs de première ligne qui ont reçu une formation complète sur les principes d’intervention en contexte de crise ou de santé mentale. Ce modèle de réponse spécialisée est une solution proactive qui a pour but d’améliorer l’action policière en situation de crise et de veiller à une meilleure prise en charge de ces personnes par les ressources institutionnelles. La désinstitutionnalisation des soins et des services psychiatriques a eu pour effet une augmentation du nombre de personnes atteintes de troubles mentaux dans la communauté. Par conséquent, cet accroissement a engendré des rapports plus fréquents entre les services policiers et cette clientèle. Les interventions en contexte de crise ou de santé mentale sont particulières et complexes, de même qu’elles requièrent un niveau supérieur de compréhension des crises humaines. Les autorités policières ont admis que ces interventions représentent une part significative de leur travail et que la formation policière traditionnelle ne les prépare pas suffisamment pour intervenir adéquatement auprès de cette population. En réponse à ces considérations et dans l’objectif d’améliorer leur capacité d’agir, les forces policières se sont dotées de modèles de réponse policière spécialisée en intervention de crise. L’approche la plus répandue est l’équipe d’intervention de crise (« crisis intervention team » ou « CIT »), aussi appelée le modèle de Memphis. Il existe plusieurs variantes de ce modèle, mais les composantes principales, c’est-à-dire la formation avancée et la consolidation d’un partenariat avec le système de santé demeurent dans l’ensemble de ces structures. L’objectif de cette recherche consiste à sonder les perceptions des agents RIC, de leur partenaire fixe et des agents en attente de la formation afin de comprendre et de contraster leurs visions et leurs pratiques d’intervention en contexte de crise ou de santé mentale. Chaque groupe a apporté des précisions intéressantes. Nous avons conduit 12 entrevues qualitatives avec des policiers du SPVM. De façon générale, les participants rapportent que leurs pratiques d’intervention auprès des personnes en crise ou atteintes de troubles mentaux sont davantage ancrées dans une perspective de relation d’aide. Ils mentionnent également que la communication, l’écoute et la confiance doivent être privilégiées avant tout autre stratégie dans les situations qui les permettent et que la force doit être employée seulement lorsqu’elle est nécessaire, c’est-à-dire lorsque leur sécurité ou celle d’autrui est en péril ou lorsque la communication n’est pas possible. Puis, ils admettent que le recours à l’expertise des intervenants en santé mentale permet une analyse plus approfondie de la situation et de l’état mental de la personne visée par l’intervention. D’autre part, en ce qui concerne les limites de la formation policière traditionnelle, les candidats ont soulevé qu’il y a un manque de connaissances en matière de santé mentale ainsi qu’une difficulté associée à l’évaluation de l’état de la personne et du besoin de transport ont été soulevés. Sur le plan des apprentissages, les agents RIC disent avoir une compréhension plus globale de la problématique de santé mentale, de meilleures habiletés communicationnelles, une analyse plus approfondie de la situation, de plus grandes connaissances juridiques, une compréhension du fonctionnement des services hospitaliers ainsi qu’une appréciation particulière pour le partage de savoirs et les principes d’endiguement. Ils font part également de l’importance des rapports pour documenter l’évolution de l’état mental d’une personne et ils ajoutent que la dimension temporelle joue un rôle clé dans la résolution définitive de la problématique. Au sujet des partenaires, ils évoquent des retombées similaires. Toutefois, à la suite de la formation, ils reconnaissent davantage l’importance de leur rôle dans la sécurité de leur partenaire et ils y accordent dorénavant une attention marquée lors de ces interventions. Enfin, les agents non formés formulent des attentes relatives au développement d’outils et de compétences, ce qui leur sera rendu dans la formation RIC. Globalement, les agents RIC et les partenaires interviewés ont modifié leurs pratiques pour les arrimer avec la philosophie des interventions en contexte de crise ou de santé mentale. Ils ont également davantage confiance en leurs capacités et habiletés d’intervention auprès des personnes en crise ou atteintes de troubles mentaux grâce aux connaissances acquises dans la formation.

A generative probabilistic oriented wavelet model for texture segmentation

This Letter addresses image segmentation via a generative model approach. A Bayesian network (BNT) in the space of dyadic wavelet transform coefficients is introduced to model texture images. The model is similar to a Hidden Markov model (HMM), but with non-stationary transitive conditional probability distributions. It is composed of discrete hidden variables and observable Gaussian outputs for wavelet coefficients. In particular, the Gabor wavelet transform is considered. The introduced model is compared with the simplest joint Gaussian probabilistic model for Gabor wavelet coefficients for several textures from the Brodatz album [1]. The comparison is based on cross-validation and includes probabilistic model ensembles instead of single models. In addition, the robustness of the models to cope with additive Gaussian noise is investigated. We further study the feasibility of the introduced generative model for image segmentation in the novelty detection framework [2]. Two examples are considered: (i) sea surface pollution detection from intensity images and (ii) image segmentation of the still images with varying illumination across the scene.

A systems model for community injury prevention

The purpose of this study was to develop, explicate, and validate a comprehensive model in order to more effectively assess community injury prevention needs, plan and target efforts, identify potential interventions, and provide a framework for an outcome-based evaluation of the effectiveness of interventions. A systems model approach was developed to conceptualize the major components of inputs, efforts, outcomes and feedback within a community setting. Profiling of multiple data sources demonstrated a community feedback mechanism that increased awareness of priority issues and elicited support from traditional as well as non-traditional injury prevention partners. Injury countermeasures including education, enforcement, engineering, and economic incentives were presented for their potential synergistic effect impacting on knowledge, attitudes, or behaviors of a targeted population. Levels of outcome data were classified into ultimate, intermediate and immediate indicators to assist with determining the effectiveness of intervention efforts. A collaboration between business and health care was successful in achieving data access and use of an emergency department level of injury data for monitoring of the impact of community interventions. Evaluation of injury events and preventive efforts within the context of a dynamic community systems environment was applied to a study community with examples detailing actual profiling and trending of injuries. The resulting model of community injury prevention was validated using a community focus group, community injury prevention coordinators, and injury prevention national experts. ^

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Self-tuning algorithm for dsp-based motion control in cnc applications

This thesis describes the development of an adaptive control algorithm for Computerized Numerical Control (CNC) machines implemented in a multi-axis motion control board based on the TMS320C31 DSP chip. The adaptive process involves two stages: Plant Modeling and Inverse Control Application. The first stage builds a non-recursive model of the CNC system (plant) using the Least-Mean-Square (LMS) algorithm. The second stage consists of the definition of a recursive structure (the controller) that implements an inverse model of the plant by using the coefficients of the model in an algorithm called Forward-Time Calculation (FTC). In this way, when the inverse controller is implemented in series with the plant, it will pre-compensate for the modification that the original plant introduces in the input signal. The performance of this solution was verified at three different levels: Software simulation, implementation in a set of isolated motor-encoder pairs and implementation in a real CNC machine. The use of the adaptive inverse controller effectively improved the step response of the system in all three levels. In the simulation, an ideal response was obtained. In the motor-encoder test, the rise time was reduced by as much as 80%, without overshoot, in some cases. Even with the larger mass of the actual CNC machine, decrease of the rise time and elimination of the overshoot were obtained in most cases. These results lead to the conclusion that the adaptive inverse controller is a viable approach to position control in CNC machinery.

Efficient Computation of Electromagnetic Waves in Hydrocarbon Exploration Using the Improved Numerical Mode Matching (NMM) Method

In this study, we developed and improved the numerical mode matching (NMM) method which has previously been shown to be a fast and robust semi-analytical solver to investigate the propagation of electromagnetic (EM) waves in an isotropic layered medium. The applicable models, such as cylindrical waveguide, optical fiber, and borehole with earth geological formation, are generally modeled as an axisymmetric structure which is an orthogonal-plano-cylindrically layered (OPCL) medium consisting of materials stratified planarly and layered concentrically in the orthogonal directions.

In this report, several important improvements have been made to extend applications of this efficient solver to the anisotropic OCPL medium. The formulas for anisotropic media with three different diagonal elements in the cylindrical coordinate system are deduced to expand its application to more general materials. The perfectly matched layer (PML) is incorporated along the radial direction as an absorbing boundary condition (ABC) to make the NMM method more accurate and efficient for wave diffusion problems in unbounded media and applicable to scattering problems with lossless media. We manipulate the weak form of Maxwell's equations and impose the correct boundary conditions at the cylindrical axis to solve the singularity problem which is ignored by all previous researchers. The spectral element method (SEM) is introduced to more efficiently compute the eigenmodes of higher accuracy with less unknowns, achieving a faster mode matching procedure between different horizontal layers. We also prove the relationship of the field between opposite mode indices for different types of excitations, which can reduce the computational time by half. The formulas for computing EM fields excited by an electric or magnetic dipole located at any position with an arbitrary orientation are deduced. And the excitation are generalized to line and surface current sources which can extend the application of NMM to the simulations of controlled source electromagnetic techniques. Numerical simulations have demonstrated the efficiency and accuracy of this method.

Finally, the improved numerical mode matching (NMM) method is introduced to efficiently compute the electromagnetic response of the induction tool from orthogonal transverse hydraulic fractures in open or cased boreholes in hydrocarbon exploration. The hydraulic fracture is modeled as a slim circular disk which is symmetric with respect to the borehole axis and filled with electrically conductive or magnetic proppant. The NMM solver is first validated by comparing the normalized secondary field with experimental measurements and a commercial software. Then we analyze quantitatively the induction response sensitivity of the fracture with different parameters, such as length, conductivity and permeability of the filled proppant, to evaluate the effectiveness of the induction logging tool for fracture detection and mapping. Casings with different thicknesses, conductivities and permeabilities are modeled together with the fractures in boreholes to investigate their effects for fracture detection. It reveals that the normalized secondary field will not be weakened at low frequencies, ensuring the induction tool is still applicable for fracture detection, though the attenuation of electromagnetic field through the casing is significant. A hybrid approach combining the NMM method and BCGS-FFT solver based integral equation has been proposed to efficiently simulate the open or cased borehole with tilted fractures which is a non-axisymmetric model.

States' Responding Behavior in Conflict: Asymmetric Response and Strategic Conflict Avoidance

State responses to external threats and aggression are studied with focus on two different rationales: (1) to make credible deterrent threats to avoid being exploited, and (2) to minimize the risk of escalation to unwanted war. Given external aggression, the target state's responding behavior has three possibilities: concession (under-response), reciprocation, and escalation. This study focuses on the first two possibilities and investigates how the strategic nature of crisis interaction can explain the intentional choice of concession or avoidance of retaliation. I build a two-level bargaining model that accounts for the domestic bargaining situation between the leader and the challenger for each state. The model's equilibrium shows that the responding behavior is determined not only by inter-state level variables (e.g. balance of power between two states, or cost of war that each state is supposed to pay), but also the domestic variables of both states. Next, the strategic interaction is rationally explained by the model: as the responding state believes that the initiating state has strong domestic challenges and, hence, the aggression is believed to be initiated for domestic political purposes (a rally-around-the-flag effect), the response tends to decrease. The concession is also predicted if the target state leader has strong bargaining power against her domestic challengers \emph{and} she believes that the initiating leader suffers from weak domestic standing. To test the model's prediction, I conduct a lab experiment and case studies. The experimental result shows that under an incentivized bargaining situation, individual actors are observed to react to hostile action as the model predicts: if the opponent is believed to suffer from internally driven difficulties, the subject will not punish hostile behavior of the other player as severely as she would without such a belief. The experiment also provides supporting evidence for the choice of concession: when the player finds herself in a favorable situation while the other has disadvantages, the player is more likely to make concessions in the controlled dictator game. Two cases are examined to discuss how the model can explain the choice of either reciprocation or concession. From personal interviews and fieldwork in South Korea, I find that South Korea's reciprocating behavior during the 2010 Yeonpyeong Island incident is explained by a combination of `low domestic power of initiating leader (Kim Jong-il)' and `low domestic power of responding leader (Lee Myung-bak).' On the other hand, the case of EC-121 is understood as a non-response or concession outcome. Declassified documents show that Nixon and his key advisors interpreted the attack as a result of North Korea's domestic political instabilities (low domestic power of initiating leader) and that Nixon did not have difficulties at domestic politics during the first few months of his presidency (high domestic power of responding leader).

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as f-test is performed during each node’s split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Polytomous item response theory models

Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

Odorant-induced currents in intact patches from rat olfactory receptor neurons: Theory and experiment

Odorant-induced currents in mammalian olfactory receptor neurons have proved difficult to obtain reliably using conventional whole-cell recording. By using a mathematical model of the electrical circuit of the patch and rest-of-cell, we demonstrate how cell-attached patch measurements can be used to quantitatively analyze responses to odorants or a high (100 mM) K+ solution. High K+ induced an immediate current flux from cell to pipette, which was modeled as a depolarization of similar to 52 mV, close to that expected from the Nernst equation (56 mV), and no change in the patch conductance. By contrast, a cocktail of cAMP-stimulating odorants induced a current flux from pipette into cell following a significant (4-10 s) delay. This was modeled as an average patch conductance increase of 36 pS and a depolarization of 13 mV, Odorant-induced single channels had a conductance of 16 pS. In cells bathed with no Mg2+ and 0.25 mM Ca2+, odorants induced a current flow from cell to pipette, which was modeled as a patch conductance increase of similar to 115 pS and depolarization of similar to 32 mV, All these results are consistent with cAMP-gated cation channels dominating the odorant response, This approach, which provides useful estimates of odorant-induced voltage and conductance changes, is applicable to similar measurements in any small cells.

Factors affecting hematopoietic progenitor cell mobilization: An analysis of 307 patients

We reviewed the data of 307 patients treated with autologous bone marrow transplantation with the aim to identify factors associated with poor hematopoietic stern cell (HSC) mobilization after administration of cyclophosphamide and granulocyte-colony stimulating factor. Success in mobilization was defined when >= 2.0 x 10(6) CD34+ cells/kg weight could be collected with <= 3 leukapheresis procedures. Success was observed in 260 patients (84.7%) and nonsuccess in 47 patients (15.3%). According to the stepwise regression model: diagnosis, chemotherapy load, treatment with mitoxantrone and platelet count before mobilization were found to be independent predictive factors for HSC mobilization. These results could help in the previous recognition of patients at risk for non response to mobilization and allow to plan an alternative protocol for this group of patients. (C) 2008 Elsevier Ltd. All rights reserved.

Spectral linewidth narrowing by a narrow bandwidth squeezed vacuum in a cavity

The fluorescence spectrum of a strongly driven two-level atom located inside an optical cavity damped by a narrow-bandwidth squeezed vacuum is studied. We use a dressed atom model approach, first applied to squeezed vacuum problems by Yeoman and Barnett, to derive the master equation of the system and discuss the role of the cavity and the squeezed vacuum in the narrowing of the spectral lines and the population trapping effect. We find that in the presence of a single-mode cavity the effect of squeezing on the fluorescence spectrum is more evident in the linewidths of the Rabi sidebands rather than in the linewidth of the central component. Even in the absence of squeezing, the cavity can reduce the linewidth of the central component almost to zero, whereas the Rabi sidebands can be narrowed only to some finite value. In the presence of a two-mode cavity and a two-mode squeezed vacuum the signature of squeezing is evident in the linewidths of all spectral lines. We also establish that the narrowing of the spectral lines is very sensitive to the detuning of the driving field from the atomic resonance. Moreover, we find that the population trapping effect, predicted for the broadband squeezed vacuum case, may appear in a narrow-bandwidth case only if the input squeezed modes are perfectly matched to the cavity modes and if there is non-zero squeezing at the Rabi sidebands.

Detecting environmental impacts on metapopulations of mound spring invertebrates - Assessing an incidence function model

We use a stochastic patch occupancy model of invertebrates in the Mound Springs ecosystem of South Australia to assess the ability of incidence function models to detect environmental impacts on metapopulations. We assume that the probability of colonisation decreases with increasing isolation and the probability of extinction is constant across spring vents. We run the models to quasi-equilibrium, and then impose an impact by increasing the local extinction probability. We sample the output at various times pre- and postimpact, and examine the probability of detecting a significant change in population parameters. The incidence function model approach turns out to have little power to detect environmental impacts on metapopulations with small numbers of patches. (C) 2001 Elsevier Science Ltd. All rights reserved.