Search for: All records

We study notions of generic and coarse computability in the context of computable structure theory. Our notions are stratified by the Σβ hierarchy. We focus on linear orderings. We show that at the Σ1 level, all linear orderings have both generically and coarsely computable copies. This behavior changes abruptly at higher levels; we show that at the Σα+2 level for any α ∈ ωCK 1 the set of linear orderings with generically or coarsely computable copies is Σ1 1-complete and therefore maximally complicated. This development is new even in the general analysis of generic and coarse computability of countable structures. In the process of proving these results, we introduce new tools for understanding generically and coarsely computable structures. We are able to give a purely structural statement that is equivalent to having a generically computable copy and show that every relational structure with only finitely many relations has coarsely and generically computable copies at the lowest level of the hierarchy. 

Abstract Given a countable structure, the Scott complexity measures the difficulty of characterizing the structure up to isomorphism. In this paper, we consider the Scott complexity of linear orders. For any limit ordinal , we construct a linear order whose Scott complexity is . This completes the classification of the possible Scott sentence complexities of linear orderings. Previously, there was only one known construction of any structure (of any signature) with Scott complexity , and our construction gives new examples, for example, rigid structures, of this complexity. Moreover, we can construct the linear orders so that not only does have Scott complexity , but there are continuum‐many structures and all such structures also have Scott complexity . In contrast, we demonstrate that there is no structure (of any signature) with Scott complexity that is only ‐equivalent to structures with Scott complexity . Our construction is based on functions that are almost periodic but not periodic, such as those arising from shifts of the ‐adic valuations. 

Prymnesium parvumare harmful haptophyte algae that cause massive environmental fish kills. Their polyketide polyether toxins, the prymnesins, are among the largest nonpolymeric compounds in nature and have biosynthetic origins that have remained enigmatic for more than 40 years. In this work, we report the “PKZILLAs,” massiveP. parvumpolyketide synthase (PKS) genes that have evaded previous detection. PKZILLA-1 and -2 encode giant protein products of 4.7 and 3.2 megadaltons that have 140 and 99 enzyme domains. Their predicted polyene product matches the proposed pre-prymnesin precursor of the 90-carbon–backbone A-type prymnesins. We further characterize the variant PKZILLA-B1, which is responsible for the shorter B-type analog prymnesin-B1, fromP. parvumRCC3426 and thus establish a general model of haptophyte polyether biosynthetic logic. This work expands expectations of genetic and enzymatic size limits in biology. 

Soft actuators have been studied and analyzed as a new solution for soft robotic technologies. These types of actuators have many advantages due to their predictable deformations and their ease of control, enabling them to hold and move delicate objects performing complex movements in confined spaces. Soft actuators can be made using different manufacturing processes, but the most common is mold casting. However, this manufacturing process involves several steps, increasing the manufacturing time and hindering changes in the design. This paper presents a novel design of a 3D printed soft pneumatic actuator based on additive manufacturing, achieving design versatility and performance. The produced actuator has seven segments that can be individually controlled. The actuators were made using fused deposition modeling (FDM) technology in one continuous process and without support material. The mechanical performance of the soft actuators was demonstrated, analyzing the deformation in the z-axis based on input pressure. 

Dielectric electroactive polymers (DEAPs) represent a subclass of smart materials that are capable of converting between electrical and mechanical energy. These materials can be used as energy harvesters, sensors, and actuators. However, current production and testing of these devices is limited and requires multiple step processes for fabrication. This paper presents an alternate production method via 3D printing using Thermoplastic Polyurethane (TPU) as a dielectric elastomer. This study provides electromechanical characterization of flexible dielectric films produced by additive manufacturing and demonstrates their use as DEAP actuators. The dielectric material characterization of TPU includes: measurement of the dielectric constant, percentage radial elongation, tensile properties, pre-strain effects on actuation, surface topography, and measured actuation under high voltage. The results demonstrated a high dielectric constant and ideal elongation performance for this material, making the material suitable for use as a DEAP actuator. In addition, it was experimentally determined that the tensile properties of the material depend on the printing angle and thickness of the samples thereby making these properties controllable using 3D printing. Using surface topography, it was possible to analyze how the printing path, affects the roughness of the films and consequently affects the voltage breakdown of the structure and creates preferential deformation directions. Actuators produced with concentric circle paths produced an area expansion of 4.73% uniformly in all directions. Actuators produced with line paths produced an area expansion of 5.71% in the direction where the printed lines are parallel to the deformation direction, and 4.91% in the direction where the printed lines are perpendicular to the deformation direction. 

Dielectric electroactive polymers are materials capable of mechanically adjusting their volume in response to an electrical stimulus. However, currently these materials require multi-step manufacturing processes which are not additive. This paper presents a novel 3D printed flexible dielectric material and characterizes its use as a dielectric electroactive polymer (DEAP) actuator. The 3D printed material was characterized electrically and mechanically and its functionality as a dielectric electroactive polymer actuator was demonstrated. The flexible 3-D printed material demonstrated a high dielectric constant and ideal stress-strain performance in tensile testing making the 3-D printed material ideal for use as a DEAP actuator. The tensile stress- strain properties were measured on samples printed under three different conditions (three printing angles 0°, 45° and 90°). The results demonstrated the flexible material presents different responses depending on the printing angle. Based on these results, it was possible to determine that the active structure needs low pre-strain to perform a visible contractive displacement when voltage is applied to the electrodes. The actuator produced an area expansion of 5.48% in response to a 4.3 kV applied voltage, with an initial pre-strain of 63.21% applied to the dielectric material. 

One way that researchers can test whether they understand a biological system is to see if they can accurately recreate it as a computer model. The more they learn about living things, the more the researchers can improve their models and the closer the models become to simulating the original. In this approach, it is best to start by trying to model a simple system. Biologists have previously succeeded in creating ‘minimal bacterial cells’. These synthetic cells contain fewer genes than almost all other living things and they are believed to be among the simplest possible forms of life that can grow on their own. The minimal cells can produce all the chemicals that they need to survive – in other words, they have a metabolism. Accurately recreating one of these cells in a computer is a key first step towards simulating a complete living system. Breuer et al. have developed a computer model to simulate the network of the biochemical reactions going on inside a minimal cell with just 493 genes. By altering the parameters of their model and comparing the results to experimental data, Breuer et al. explored the accuracy of their model. Overall, the model reproduces experimental results, but it is not yet perfect. The differences between the model and the experiments suggest new questions and tests that could advance our understanding of biology. In particular, Breuer et al. identified 30 genes that are essential for life in these cells but that currently have no known purpose. Continuing to develop and expand models like these to reproduce more complex living systems provides a tool to test current knowledge of biology. These models may become so advanced that they could predict how living things will respond to changing situations. This would allow scientists to test ideas sooner and make much faster progress in understanding life on Earth. Ultimately, these models could one day help to accelerate medical and industrial processes to save lives and enhance productivity.