Richard M. Salter

Tactics and Strategies for Managing Ebola Outbreaks and the Salience of Immunization

We present a stochastic transmission chain simulation model for Ebola viral disease (EVD) in West Africa, with the salutary result that the virus may be more controllable than previously suspected. The ongoing tactics to detect cases as rapidly as possible and isolate individuals as safely as practicable is essential to saving lives in the current outbreaks in Guinea, Liberia, and Sierra Leone. Equally important are educational campaigns that reduce contact rates between susceptible and infectious individuals in the community once an outbreak occurs. However, due to the relatively low R 0 of Ebola (around 1.5 to 2.5 next generation cases are produced per current generation case in naïve populations), rapid isolation of infectious individuals proves to be highly efficacious in containing outbreaks in new areas, while vaccination programs, even with low efficacy vaccines, can be decisive in curbing future outbreaks in areas where the Ebola virus is maintained in reservoir populations.

Modeling neural networks in scheme

A system for simulating neural networks has been written in the LISP dialect, Scheme, using an object-oriented style of program ming, rather than the standard numerical techniques used in previous studies. Each node in the Scheme network represents either a neuron or a functional group of neurons, and can pass messages which trigger computations and actions in other nodes. The Scheme modeling approach overcomes two major problems inherent to the standard numerical approach. First, it provides a flexible environment for systematically studying the effects of perturbing a networks structure, response, or updating param eters. In fact, the Scheme system can recreate any previously studied neural network. Second, it allows the construction of hierarchical networks with several interacting levels. This system can handle hierarchical organization in a natural way, because a single node in a Scheme network can contain a model of an entire lower level of neural processing. The implementation of neural networks with hierarchical structure is significant because recent biological data suggests that this is the architecture which supports human cognition.

Sympatric speciation in structureless environments

BackgroundDarwin and the architects of the Modern Synthesis found sympatric speciation difficult to explain and suggested it is unlikely to occur. Increasingly, evidence over the past few decades suggest that sympatric speciation can occur under ecological conditions that require at most intraspecific competition for a structured resource. Here we used an individual-based population model with variable foraging strategies to study the evolution of mating behavior among foraging strategy types. Initially, individuals were placed at random on a structureless resource landscape, with subsequent spatial variation induced through foraging activity itself. The fitness of individuals was determined by their biomass at the end of each generational cycle. The model incorporates three diallelic, codominant foraging strategy genes, and one mate-choice or m-trait (i.e. incipient magic trait) gene, where the latter is inactive when random mating is assumed.ResultsUnder non-random mating, the m-trait gene promotes increasing levels of either disassortative or assortative mating when the frequency of m respectively increases or decreases from 0.5. Our evolutionary simulations demonstrate that, under initial random mating conditions, an activated m-trait gene evolves to promote assortative mating because the system, in trying to fit a multipeak adaptive landscape, causes heterozygous individuals to be less fit than homozygous individuals.ConclusionOur results extend our theoretical understanding that sympatric speciation can evolve under nicheless or gradientless resource conditions: i.e. the underlying resource is monomorphic and initially spatially homogeneous. Further the simplicity and generality of our model suggests that sympatric speciation may be more likely than previously thought to occur in mobile, sexually-reproducing organisms.

Panmictic and Clonal Evolution on a Single Patchy Resource Produces Polymorphic Foraging Guilds

We develop a stochastic, agent-based model to study how genetic traits and experiential changes in the state of agents and available resources influence individuals’ foraging and movement behaviors. These behaviors are manifest as decisions on when to stay and exploit a current resource patch or move to a particular neighboring patch, based on information of the resource qualities of the patches and the anticipated level of intraspecific competition within patches. We use a genetic algorithm approach and an individual’s biomass as a fitness surrogate to explore the foraging strategy diversity of evolving guilds under clonal versus hermaphroditic sexual reproduction. We first present the resource exploitation processes, movement on cellular arrays, and genetic algorithm components of the model. We then discuss their implementation on the Nova software platform. This platform seamlessly combines the dynamical systems modeling of consumer-resource interactions with agent-based modeling of individuals moving over a landscapes, using an architecture that lays transparent the following four hierarchical simulation levels: 1.) within-patch consumer-resource dynamics, 2.) within-generation movement and competition mitigation processes, 3.) across-generation evolutionary processes, and 4.) multiple runs to generate the statistics needed for comparative analyses. The focus of our analysis is on the question of how the biomass production efficiency and the diversity of guilds of foraging strategy types, exploiting resources over a patchy landscape, evolve under clonal versus random hermaphroditic sexual reproduction. Our results indicate greater biomass production efficiency under clonal reproduction only at higher population densities, and demonstrate that polymorphisms evolve and are maintained under random mating systems. The latter result questions the notion that some type of associative mating structure is needed to maintain genetic polymorphisms among individuals exploiting a common patchy resource on an otherwise spatially homogeneous landscape.

New models for the CS1 course: what are they and are they leading to the same place?

Owens: The first course in Computer Science has been beset by several diverse approaches in the past few years. This panel proposal suggests that a reasonable way to discuss these different models is to have a representative from each of several positions describe the first course at his/her school and then speculate on where the students will be at the end of the third year in the program. Each panelist will discuss core topics covered. This panel is not intended to be a debate as to the one best way to do things, but is intended to reassure the Computer Science community that there are many paths to a solid CS foundation.

Using nova to construct agent-based models for epidemiological teaching and research

Epidemic modeling is dominated by systems models - so-called SIR models - that describe the spatio-temporal and network dynamics of disease outbreaks. Reed-Frost, discrete-time, stochastic transmission-chain models have also been important; but, increasingly, epidemiological modelers are turning to agent-based (ABM) approaches that permit the inclusion of individual-specific characters, which may relate to the genetics of hosts or pathogens, host exposure histories, co-infections or other general health correlates. Here we introduce Nova, a graphically driven computational modeling platform for creating and running both dynamical systems and ABM models that have application both in teaching and research. Because Nova is based on the JavaScript language, all Nova models are easily transformed into Nova Online web apps. In the teaching arena, our presentation features our “SIR circle games”; in the research arena we discuss the application of Nova to modeling outbreaks of Ebola and measles.

Illustrating CPU design concepts with DLSim 3

DLSim, a GUI-based digital logic simulation program developed by Richard Salter at Oberlin College, has been used for class demonstrations and homework exercises in the Computer Organization course at Oberlin for over ten years. Until recently its use has been limited to the component of the course dealing with low-level logic design using gates and flip-flops. A new version, DLSim 3, extends those capabilities through the use of Java plug-ins, making it possible to use the software for digital design at higher levels of abstraction. With DLSim 3, we are able to present the many levels of circuit design in a single environment, from low level combinational and sequential circuits through models of complete CPUs. The purpose of this paper is to give an introduction to DLSim 3 and to describe how we have used it in the classroom, focusing particularly on CPU design.

New models for the CS1 course: a fifteen year retrospective

The year was 1994; the place, Phoenix Arizona. A panel session moderated by Barbara Boucher Owens entitled New Models for the CS1 Course: What Are They and Are They Leading to the Same Place? [1] took place before a packed audience at SIGCSE ’94. At the time, the World Wide Web was just over the horizon, and disk drives held at most a few hundred megabytes. The most popular language for CS1 was Pascal. At the SIGCSE’94 panel we heard about four diverse approaches to introductory computer science: the “breadthfirst” approach, which includes discrete mathematics, logic and problem solving; the “object-oriented” approach, which introduces objects from the beginning; the“formal”approach, which mandates correctness proofs; and the “Scheme” approach, which focuses on abstraction. For SIGCSE’09 three of the four panelists from the ’94 panel have returned to update the discussion. Joining this group is a younger faculty member who, as a student in the 1990’s, was directly affected by the teaching philosophies of the time. The veteran panelists will comment on how their approaches have evolved over the years. Have the expectations of today’s student population forced these educators to adjust their philosophies, or have they been able to adapt their core beliefs to the current environment? Looking ahead, the most important question remains, how does one craft a CS1 curriculum that can appeal to a wide audience and best prepare students for the road ahead.

Using SCHEME in the introductory computer science curriculum (abstract)

Panelists will discuss the various aspects of using the SCHEME programming language as a tool for the instruction of computer science concepts in an introductory computer science course. This approach has been used both experimentally and on a regular basis at institutions in the United States and Europe focusing on the technologies for coping with the complexity of organization of large-scale software systems, as a reflection of general principles of software design. The course develops three basic means for decomposing difficult problems: building abstraction hierarchies, establishing conventional interfaces, and moving to new levels of linguistic description. There is significant laboratory work completed in the course using the SCHEME dialect of the programming ltiguage LISP, including such topics as modeling physical phenomena, event-based simulation, interpreters and compilers, and logic programming. The goal of the course is not to teach a programming language, but rather to explore important general principles of programming style using a number of the novel features of SCHEME.

Modeling epidemics: A primer and Numerus Model Builder implementation

Epidemiological models are dominated by compartmental models, of which SIR formulations are the most commonly used. These formulations can be continuous or discrete (in either the state-variable values or time), deterministic or stochastic, or spatially homogeneous or heterogeneous, the latter often embracing a network formulation. Here we review the continuous and discrete deterministic and discrete stochastic formulations of the SIR dynamical systems models, and we outline how they can be easily and rapidly constructed using Numerus Model Builder, a graphically-driven coding platform. We also demonstrate how to extend these models to a metapopulation setting using NMB network and mapping tools.