Explicit Analytical Expression for a Lanchester Attrition-Rate Coefficient for Bonder and Farrell’s m-Period Target-Engagement Policy

Canonical Methods in the Solution of Variable-Coefficient Lanchester-Type Equations of Modern Warfare

This paper develops a mathematical theory for solving determin-istic, Lanchester-type, 'square-law' attrition equations for combat between two homogeneous forces with temporal variations in fire effec-tivenesses (as expressed b y the Lanchester attrition-rate coefficients). It gives a general form for expressing the solution of such variable-coefficient combat attrition equations in terms of La...

Stochastic Attrition Models of Lanchester Type

Attrition Modeling in the Presence of Decoys: An Operations-other-than-War Motivation

Under various operational conditions, in particular in operations other than war (OOTW) or peacekeeping, an intervening force, here Blue, must occasionally engage in attrition warfare with an opposing force, here Red, that is intermingled with noncombatants. Desirably, Red armed actives are targeted, and not the unarmed noncombatants. This article describes some simple Lanchesterian attrition m...

From Craft to Reflective Art and Science; Comment on “Metrics and Evaluation Tools for Patient Engagement in Healthcare Organization- and System-Level Decision-Making: A Systematic Review”

Patient engagement practices are increasingly incorporated in health research, governance, and care. More recently, a large number of evaluation tools and metrics have been developed to support engagement evaluation. This growing interest in evaluation reflects a maturation of the patient engagement field, moving from a “craft” to a reflective “art and science,” with more explicit expected bene...

O-3: Drug Repositioning by Merging Gene Expression Data Analysis and Cheminformatics Target Prediction Approaches

The transcriptional responses of drug treatments combined with a protein target prediction algorithm was utilised to associate compounds to biological genomic space. This enabled us to predict efficacy of compounds in cMap and LINCS against 181 databases of diseases extracted from GEO. 18/30 of top drugs predicted for leukemia (e.g. Leflunomide and Etoposide) and breast cancer (e.g. Tamoxifen a...