Comparison of dimensional accuracies of stereolithography and powder binder printing

This paper presents a comparative experimental investigation of the dimensional accuracies of two widely used rapid prototyping (RP) processes: stereolithography (SLA) and powder binder printing (PBP). Four replicates of a purpose-designed component using each RP process were fabricated, and the measurements of the internal and external features of all surfaces were performed using a general-purpose coordinate measurement machine. The results showed that in both cases, the main cause of dimensional variations was the volumetric change inherent in the process. The precision of SLA was far better than that of PBP. The dimensional accuracy of SLA was better in the z direction, whereas PBP produced better dimensional accuracy in the x–y plane. In both RP processes, the height error consisted of two components: constant error and cumulative error. The constant error component was equal to the datum surface error. SLA yielded an average datum surface error that was 68 % higher than in PBP. The height error of SLA improved with the increase in nominal height, whereas it deteriorated in PBP

Modular Composition of Gene Transcription Networks

Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.United States. Air Force Office of Scientific Research (FA9550-12-1-0129