A Perturbation Scheme for Spherical Arrangements with Application to Molecular Modeling

We describe a software package for computing and manipulating the subdivision of a sphere by a collection of (not necessarily great) circles and for computing the boundary surface of the union of spheres. We present problems that arise in the implementation of the software and the solutions that we have found for them. At the core of the paper is a novel perturbation scheme to overcome degeneracies and precision problems in computing spherical arrangements while using floating point arithmetic. The scheme is relatively simple, it balances between the efficiency of computation and the magnitude of the perturbation, and it performs well in practice. In one O(n) time pass through the data, it perturbs the inputs necessary to insure no potential degeneracies and then passes the perturbed inputs on to the geometric algorithm. We report and discuss experimental results. Our package is a major component in a larger package aimed to support geometric queries on molecular models; it is currently employed by chemists working in "rational drug design." The spherical subdivisions are used to construct a geometric model of a molecule where each sphere represents an atom. We also give an overview of the molecular modeling package and detail additional features and implementation issues.

Revised Report on the Algorithmic Language Scheme

Data and procedures and the values they amass, Higher-order functions to combine and mix and match, Objects with their local state, the message they pass, A property, a package, the control of point for a catch- In the Lambda Order they are all first-class. One thing to name them all, one things to define them, one thing to place them in environments and bind them, in the Lambda Order they are all first-class. Keywords: Scheme, Lisp, functional programming, computer languages.

On the Dirichlet Prior and Bayesian Regularization

A common objective in learning a model from data is to recover its network structure, while the model parameters are of minor interest. For example, we may wish to recover regulatory networks from high-throughput data sources. In this paper we examine how Bayesian regularization using a Dirichlet prior over the model parameters affects the learned model structure in a domain with discrete variables. Surprisingly, a weak prior in the sense of smaller equivalent sample size leads to a strong regularization of the model structure (sparse graph) given a sufficiently large data set. In particular, the empty graph is obtained in the limit of a vanishing strength of prior belief. This is diametrically opposite to what one may expect in this limit, namely the complete graph from an (unregularized) maximum likelihood estimate. Since the prior affects the parameters as expected, the prior strength balances a "trade-off" between regularizing the parameters or the structure of the model. We demonstrate the benefits of optimizing this trade-off in the sense of predictive accuracy.

MIT Scheme Reference Manual

MIT Scheme is an implementation of the Scheme programming language that runs on many popular workstations. The MIT Scheme Reference Manual describes the special forms, procedures, and datatypes provided by the implementation for use by application programmers.

RABBIT: A Compiler for SCHEME

We have developed a compiler for the lexically-scoped dialect of LISP known as SCHEME. The compiler knows relatively little about specific data manipulation primitives such as arithmetic operators, but concentrates on general issues of environment and control. Rather than having specialized knowledge about a large variety of control and environment constructs, the compiler handles only a small basis set which reflects the semantics of lambda-calculus. All of the traditional imperative constructs, such as sequencing, assignment, looping, GOTO, as well as many standard LISP constructs such as AND, OR, and COND, are expressed in macros in terms of the applicative basis set. A small number of optimization techniques, coupled with the treatment of function calls as GOTO statements, serve to produce code as good as that produced by more traditional compilers. The macro approach enables speedy implementation of new constructs as desired without sacrificing efficiency in the generated code. A fair amount of analysis is devoted to determining whether environments may be stack-allocated or must be heap-allocated. Heap-allocated environments are necessary in general because SCHEME (unlike Algol 60 and Algol 68, for example) allows procedures with free lexically scoped variables to be returned as the values of other procedures; the Algol stack-allocation environment strategy does not suffice. The methods used here indicate that a heap-allocating generalization of the "display" technique leads to an efficient implementation of such "upward funargs". Moreover, compile-time optimization and analysis can eliminate many "funargs" entirely, and so far fewer environment structures need be allocated at run time than might be expected. A subset of SCHEME (rather than triples, for example) serves as the representation intermediate between the optimized SCHEME code and the final output code; code is expressed in this subset in the so-called continuation-passing style. As a subset of SCHEME, it enjoys the same theoretical properties; one could even apply the same optimizer used on the input code to the intermediate code. However, the subset is so chosen that all temporary quantities are made manifest as variables, and no control stack is needed to evaluate it. As a result, this apparently applicative representation admits an imperative interpretation which permits easy transcription to final imperative machine code. These qualities suggest that an applicative language like SCHEME is a better candidate for an UNCOL than the more imperative candidates proposed to date.

Explicit representation of subgrid heterogeneity in a GCM land-surface scheme

Essery, R L H, Best, M J, Betts, R A, Cox, P M & Taylor, C M, Explicit representation of subgrid heterogeneity in a GCM land-surface scheme. Journal of Hydrometeorology 4, pp 530-543 (2003).

A Fully Distributed Location Management Scheme for Large PCS

In [previous papers] we presented the design, specification and proof of correctness of a fully distributed location management scheme for PCS networks and argued that fully replicating location information is both appropriate and efficient for small PCS networks. In this paper, we analyze the performance of this scheme. Then, we extend the scheme in a hierarchical environment so as to scale to large PCS networks. Through extensive numerical results, we show the superiority of our scheme compared to the current IS-41 standard.

Analysis of an asymptotic preserving scheme for linear kinetic equations in the diffusion limit

We present a mathematical analysis of the asymptotic preserving scheme proposed in [M. Lemou and L. Mieussens, SIAM J. Sci. Comput., 31 (2008), pp. 334-368] for linear transport equations in kinetic and diffusive regimes. We prove that the scheme is uniformly stable and accurate with respect to the mean free path of the particles. This property is satisfied under an explicitly given CFL condition. This condition tends to a parabolic CFL condition for small mean free paths and is close to a convection CFL condition for large mean free paths. Our analysis is based on very simple energy estimates. © 2010 Society for Industrial and Applied Mathematics.

An energy-efficient data delivery scheme for delay-sensitive traffic in wireless sensor networks

We propose a novel data-delivery method for delay-sensitive traffic that significantly reduces the energy consumption in wireless sensor networks without reducing the number of packets that meet end-to-end real-time deadlines. The proposed method, referred to as SensiQoS, leverages the spatial and temporal correlation between the data generated by events in a sensor network and realizes energy savings through application-specific in-network aggregation of the data. SensiQoS maximizes energy savings by adaptively waiting for packets from upstream nodes to perform in-network processing without missing the real-time deadline for the data packets. SensiQoS is a distributed packet scheduling scheme, where nodes make localized decisions on when to schedule a packet for transmission to meet its end-to-end real-time deadline and to which neighbor they should forward the packet to save energy. We also present a localized algorithm for nodes to adapt to network traffic to maximize energy savings in the network. Simulation results show that SensiQoS improves the energy savings in sensor networks where events are sensed by multiple nodes, and spatial and/or temporal correlation exists among the data packets. Energy savings due to SensiQoS increase with increase in the density of the sensor nodes and the size of the sensed events. © 2010 Harshavardhan Sabbineni and Krishnendu Chakrabarty.

Accessibility, availability and affordability of anti-malarials in a rural district in Kenya after implementation of a national subsidy scheme.

BACKGROUND: Poor access to prompt and effective treatment for malaria contributes to high mortality and severe morbidity. In Kenya, it is estimated that only 12% of children receive anti-malarials for their fever within 24 hours. The first point of care for many fevers is a local medicine retailer, such as a pharmacy or chemist. The role of the medicine retailer as an important distribution point for malaria medicines has been recognized and several different strategies have been used to improve the services that these retailers provide. Despite these efforts, many mothers still purchase ineffective drugs because they are less expensive than effective artemisinin combination therapy (ACT). One strategy that is being piloted in several countries is an international subsidy targeted at anti-malarials supplied through the retail sector. The goal of this strategy is to make ACT as affordable as ineffective alternatives. The programme, called the Affordable Medicines Facility - malaria was rolled out in Kenya in August 2010. METHODS: In December 2010, the affordability and accessibility of malaria medicines in a rural district in Kenya were evaluated using a complete census of all public and private facilities, chemists, pharmacists, and other malaria medicine retailers within the Webuye Demographic Surveillance Area. Availability, types, and prices of anti-malarials were assessed. There are 13 public or mission facilities and 97 medicine retailers (registered and unregistered). RESULTS: The average distance from a home to the nearest public health facility is 2 km, but the average distance to the nearest medicine retailer is half that. Quinine is the most frequently stocked anti-malarial (61% of retailers). More medicine retailers stocked sulphadoxine-pyramethamine (SP; 57%) than ACT (44%). Eleven percent of retailers stocked AMFm subsidized artemether-lumefantrine (AL). No retailers had chloroquine in stock and only five were selling artemisinin monotherapy. The mean price of any brand of AL, the recommended first-line drug in Kenya, was $2.7 USD. Brands purchased under the AMFm programme cost 40% less than non-AMFm brands. Artemisinin monotherapies cost on average more than twice as much as AMFm-brand AL. SP cost only $0.5, a fraction of the price of ACT. CONCLUSIONS: AMFm-subsidized anti-malarials are considerably less expensive than unsubsidized AL, but the price difference between effective and ineffective therapies is still large.

Regularization of an iterative algorithm for the extrapolation of bandlimited signals

info:eu-repo/semantics/published

On the regularization of linear inverse problems in Fourier optics

info:eu-repo/semantics/published

Ill-Posedness, Regularization and Number of Degrees of Freedom

info:eu-repo/semantics/published

Linear inverse problems with discrete data: II. Stability and regularization

For pt.I. see ibid. vol.1, p.301 (1985). In the first part of this work a general definition of an inverse problem with discrete data has been given and an analysis in terms of singular systems has been performed. The problem of the numerical stability of the solution, which in that paper was only briefly discussed, is the main topic of this second part. When the condition number of the problem is too large, a small error on the data can produce an extremely large error on the generalised solution, which therefore has no physical meaning. The authors review most of the methods which have been developed for overcoming this difficulty, including numerical filtering, Tikhonov regularisation, iterative methods, the Backus-Gilbert method and so on. Regularisation methods for the stable approximation of generalised solutions obtained through minimisation of suitable seminorms (C-generalised solutions), such as the method of Phillips (1962), are also considered.