The role of lower partial moments in stochastic modeling

Lower partial moments plays an important role in the analysis of risks and in income/poverty studies. In the present paper, we further investigate its importance in stochastic modeling and prove some characterization theorems arising out of it. We also identify its relationships with other important applied models such as weighted and equilibrium models. Finally, some applications of lower partial moments in poverty studies are also examined

Modeling the Transport Sector: The Role of Existing Fuel Taxes in Climate Policy

Existing fuel taxes play a major role in determining the welfare effects of exempting the transportation sector from measures to control greenhouse gases. To study this phenomenon we modify the MIT Emissions Prediction and Policy Analysis (EPPA) model to disaggregate the household transportation sector. This improvement requires an extension of the GTAP data set that underlies the model. The revised and extended facility is then used to compare economic costs of cap-and-trade systems differentiated by sector, focusing on two regions: the USA where the fuel taxes are low, and Europe where the fuel taxes are high. We find that the interplay between carbon policies and pre-existing taxes leads to different results in these regions: in the USA exemption of transport from such a system would increase the welfare cost of achieving a national emissions target, while in Europe such exemptions will correct pre-existing distortions and reduce the cost.

Modeling chemotaxis reveals the role of reversed phosphotransfer and a bi-functional kinase-phosphatase

Understanding how multiple signals are integrated in living cells to produce a balanced response is a major challenge in biology. Two-component signal transduction pathways, such as bacterial chemotaxis, comprise histidine protein kinases (HPKs) and response regulators (RRs). These are used to sense and respond to changes in the environment. Rhodobacter sphaeroides has a complex chemosensory network with two signaling clusters, each containing a HPK, CheA. Here we demonstrate, using a mathematical model, how the outputs of the two signaling clusters may be integrated. We use our mathematical model supported by experimental data to predict that: (1) the main RR controlling flagellar rotation, CheY6, aided by its specific phosphatase, the bifunctional kinase CheA3, acts as a phosphate sink for the other RRs; and (2) a phosphorelay pathway involving CheB2 connects the cytoplasmic cluster kinase CheA3 with the polar localised kinase CheA2, and allows CheA3-P to phosphorylate non-cognate chemotaxis RRs. These two mechanisms enable the bifunctional kinase/phosphatase activity of CheA3 to integrate and tune the sensory output of each signaling cluster to produce a balanced response. The signal integration mechanisms identified here may be widely used by other bacteria, since like R. sphaeroides, over 50% of chemotactic bacteria have multiple cheA homologues and need to integrate signals from different sources.

Mathematical Modeling to Investigate Antiarrhythmic Drug Side Effects: Rate-Dependence Role in Ionic Currents and Action Potentials Shape in the O’Hara Model

Sudden cardiac death due to ventricular arrhythmia is one of the leading causes of mortality in the world. In the last decades, it has proven that anti-arrhythmic drugs, which prolong the refractory period by means of prolongation of the cardiac action potential duration (APD), play a good role in preventing of relevant human arrhythmias. However, it has long been observed that the “class III antiarrhythmic effect” diminish at faster heart rates and that this phenomenon represent a big weakness, since it is the precise situation when arrhythmias are most prone to occur. It is well known that mathematical modeling is a useful tool for investigating cardiac cell behavior. In the last 60 years, a multitude of cardiac models has been created; from the pioneering work of Hodgkin and Huxley (1952), who first described the ionic currents of the squid giant axon quantitatively, mathematical modeling has made great strides. The O’Hara model, that I employed in this research work, is one of the modern computational models of ventricular myocyte, a new generation began in 1991 with ventricular cell model by Noble et al. Successful of these models is that you can generate novel predictions, suggest experiments and provide a quantitative understanding of underlying mechanism. Obviously, the drawback is that they remain simple models, they don’t represent the real system. The overall goal of this research is to give an additional tool, through mathematical modeling, to understand the behavior of the main ionic currents involved during the action potential (AP), especially underlining the differences between slower and faster heart rates. In particular to evaluate the rate-dependence role on the action potential duration, to implement a new method for interpreting ionic currents behavior after a perturbation effect and to verify the validity of the work proposed by Antonio Zaza using an injected current as a perturbing effect.

Modeling the marine aragonite cycle: changes under rising carbon dioxide and its role in shallow water CaCO3 dissolution

The marine aragonite cycle has been included in the global biogeochemical model PISCES to study the role of aragonite in shallow water CaCO3 dissolution. Aragonite production is parameterized as a function of mesozooplankton biomass and aragonite saturation state of ambient waters. Observation-based estimates of marine carbonate production and dissolution are well reproduced by the model and about 60% of the combined CaCO3 water column dissolution from aragonite and calcite is simulated above 2000 m. In contrast, a calcite-only version yields a much smaller fraction. This suggests that the aragonite cycle should be included in models for a realistic representation of CaCO3 dissolution and alkalinity. For the SRES A2 CO2 scenario, production rates of aragonite are projected to notably decrease after 2050. By the end of this century, global aragonite production is reduced by 29% and total CaCO3 production by 19% relative to pre-industrial. Geographically, the effect from increasing atmospheric CO2, and the subsequent reduction in saturation state, is largest in the subpolar and polar areas where the modeled aragonite production is projected to decrease by 65% until 2100.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Modeling the role of fixational eye movements in real-world scenes

Our eyes never remain still. Even when we stare at a fixed point, small involuntary movements take place in our eyes in an imperceptible manner. Researchers agree on the presence of three main contributions to eye movements when we fix the gaze: microsaccades, drifts and tremor. These small movements carry the image across the retina stimulating the photoreceptors and thus avoiding fading. Nowadays it is commonly accepted that these movements can improve the discrimination performance of the retina. In this paper, several retina models with and without fixational eye movements were implemented by mean of RetinaStudio tool to test the feasibility of these models to be incorporated in future neuroprostheses. For this purpose each retina model has been stimulated with natural scene images in two experiments. Results are discussed from the point of view of a neuroprosthesis development.

Modeling the relationships between adult attachment patterns and borderline personality disorder: The role of impulsivity and aggressiveness

To obtain a better understanding of the associations among Borderline Personality Disorder (BPD), adult attachment patterns, impulsivity, and aggressiveness, we tested four competing models of these relationships: a) BPD is associated with the personality traits of impulsivity and aggressiveness, but adult attachment patterns predict neither BPD nor impulsive/aggressive features; b) adult attachment patterns are significant predictors of BPD but not of impulsive/aggressive traits, although these traits correlate with BPD; c) adult attachment patterns are significant predictors of impulsive and aggressive traits, which in turn predict BPD; and d) adult attachment patterns significantly predict both BPD and impulsive/aggressive traits. We assessed 466 consecutively admitted outpatients using the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (V. 2.0), the Attachment Style Questionnaire, the Barratt Impulsiveness Scale-11, and the Aggression Questionnaire. Maximum likelihood structural equation modeling of the covariance matrix showed that model (c) was the best fitting model (chi(2) (21) = 31.67, p >.05, RMSEA = .023, test of close fit p >.85). This result indicates that adult attachment patterns act indirectly as risk factors for BPD because of their relationships with aggressive/impulsive personality traits.

Modeling the role of investigator bias, interrogation techniques, and suspect decision -making on the likelihood of confession

The purpose of the current study was to attempt to model various cognitive and social processes that are believed to lead to false confessions. More specifically, this study manipulated the variables of experimenter expectancy, guilt-innocence of the suspect, and interrogation techniques using the Russano et al. (2005) paradigm. The primary measure of interest was the likelihood of the participant signing the confession statement. By manipulating experimenter expectancy, the current study sought to further explore the social interactions that may occur in the interrogation room. In addition, in past experiments, the interrogator has typically been restricted to the use of one or two interrogation techniques. In the present study, interrogators were permitted to select from 15 different interrogation techniques when attempting to solicit a confession from participants. ^ Consistent with Rusanno et al. (2005), guilty participants (94%) were more likely to confess to the act of cheating than innocent participants (31%). The variable of experimenter expectancy did not effect confessions rates, length of interrogation, or the type of interrogation techniques used. Path analysis revealed feelings of pressure and the weighing of consequences on the part of the participant were associated with the signing of the confession statement. The findings suggest the guilt/innocence of the participant, the participant's perceptions of the interrogation situation, and length of interrogation play a pivotal role in the signing of the confession statement. Further examination of these variables may provide researchers with a better understanding of the relationship between interrogations and confessions. ^

Idealized modeling of the role of stability and shear on mesoscale gravity wave evolution

Mesoscale Gravity Waves (MGWs) are large pressure perturbations that form in the presence of a stable layer at the surface either behind Mesoscale Convective Systems (MCSs) in summer or over warm frontal surfaces behind elevated convection in winter. MGWs are associated with damaging winds, moderate to heavy precipitation, and occasional heat bursts at the surface. The forcing mechanism for MGWs in this study is hypothesized to be evaporative cooling occurring behind a convective line. This evaporatively-cooled air generates a downdraft that then depresses the surface-based stable layer and causes pressure decreases, strong wind speeds and MGW genesis. Using the Weather Research and Forecast Model (WRF) version 3.0, evaporative cooling is simulated using an imposed cold thermal. Sensitivity studies examine the response of MGW structure to different thermal and shear profiles where the strength and depth of the inversion are varied, as well as the amount of wind shear. MGWs are characterized in terms of response variables, such as wind speed perturbations (U'), temperature perturbations (T'), pressure perturbations (P'), potential temperature perturbations (Θ'), and the correlation coefficient (R) between U' and P'. Regime Diagrams portray the response of MGW to the above variables in order to better understand the formation, causes, and intensity of MGWs. The results of this study indicate that shallow, weak surface layers coupled with deep, neutral layers above favor the formation of waves of elevation. Conversely, deep strong surface layers coupled with deep, neutral layers above favor the formation of waves of depression. This is also the type of atmospheric setup that tends to produce substantial surface heating at the surface.

Modeling Two-Oscillator Circadian Systems Entrained by Two Environmental Cycles

Several experimental studies have altered the phase relationship between photic and non-photic environmental, 24 h cycles (zeitgebers) in order to assess their role in the synchronization of circadian rhythms. To assist in the interpretation of the complex activity patterns that emerge from these ""conflicting zeitgeber'' protocols, we present computer simulations of coupled circadian oscillators forced by two independent zeitgebers. This circadian system configuration was first employed by Pittendrigh and Bruce (1959), to model their studies of the light and temperature entrainment of the eclosion oscillator in Drosophila. Whereas most of the recent experiments have restricted conflicting zeitgeber experiments to two experimental conditions, by comparing circadian oscillator phases under two distinct phase relationships between zeitgebers (usually 0 and 12 h), Pittendrigh and Bruce compared eclosion phase under 12 distinct phase relationships, spanning the 24 h interval. Our simulations using non-linear differential equations replicated complex non-linear phenomena, such as ""phase jumps'' and sudden switches in zeitgeber preferences, which had previously been difficult to interpret. Our simulations reveal that these phenomena generally arise when inter-oscillator coupling is high in relation to the zeitgeber strength. Manipulations in the structural symmetry of the model indicated that these results can be expected to apply to a wide range of system configurations. Finally, our studies recommend the use of the complete protocol employed by Pittendrigh and Bruce, because different system configurations can generate similar results when a ""conflicting zeitgeber experiment'' incorporates only two phase relationships between zeitgebers.