Reachability in Restricted Chemical Reaction Networks

The popularity of molecular computation has given rise to several models of abstraction, one of the more recent ones being Chemical Reaction Networks (CRNs). These are equivalent to other popular computational models, such as Vector Addition Systems and Petri-Nets, and restricted versions are equivalent to Population Protocols. This paper continues the work on core reachability questions related to Chemical Reaction Networks; given two configurations, can one reach the other according to the system\u27s rules? With no restrictions, reachability was recently shown to be Ackermann-complete, this resolving a decades-old problem.Here, we fully characterize monotone reachability problems based on various restrictions such as the rule size, the number of rules that may create a species (k-source) or consume a species (k-consuming), the volume, and whether the rules have an acyclic production order (feed-forward). We show PSPACE-completeness of reachability with only bimolecular reactions with two-source and two-consuming rules. This proves hardness of reachability in Population Protocols, which was unknown. Further, this shows reachability in CRNs is PSPACE-complete with size-2 rules, which was previously only known with size-5 rules. This is achieved using techniques within the motion planning framework.We provide many important results for feed-forward CRNs where rules are single-source or single-consuming. We show that reachability is solvable in polynomial time if the system does not contain special void or autogenesis rules. We then fully characterize all systems of this type and show that if you allow void/autogenesis rules, or have more than one source and one consuming, the problems become NP-complete. Finally, we show several interesting special cases of CRNs based on these restrictions or slight relaxations and note future significant open questions related to this taxonomy

Covert Computation in the Abstract Tile-Assembly Model

There have been many advances in molecular computation that offer benefits such as targeted drug delivery, nanoscale mapping, and improved classification of nanoscale organisms. This power led to recent work exploring privacy in the computation, specifically, covert computation in self-assembling circuits. Here, we prove several important results related to the concept of a hidden computation in the most well-known model of self-assembly, the Abstract Tile-Assembly Model (aTAM). We show that in 2D, surprisingly, the model is capable of covert computation, but only with an exponential-sized assembly. We also show that the model is capable of covert computation with polynomial-sized assemblies with only one step in the third dimension (just-barely 3D). Finally, we investigate types of functions that can be covertly computed as members of P/Poly

Reachability in Restricted Chemical Reaction Networks

The popularity of molecular computation has given rise to several models of abstraction, one of the more recent ones being Chemical Reaction Networks (CRNs). These are equivalent to other popular computational models, such as Vector Addition Systems and Petri-Nets, and restricted versions are equivalent to Population Protocols. This paper continues the work on core reachability questions related to Chemical Reaction Networks; given two configurations, can one reach the other according to the system's rules? With no restrictions, reachability was recently shown to be Ackermann-complete, this resolving a decades-old problem. Here, we fully characterize monotone reachability problems based on various restrictions such as the rule size, the number of rules that may create a species (k-source) or consume a species (k-consuming), the volume, and whether the rules have an acyclic production order (feed-forward). We show PSPACE-completeness of reachability with only bimolecular reactions with two-source and two-consuming rules. This proves hardness of reachability in Population Protocols, which was unknown. Further, this shows reachability in CRNs is PSPACE-complete with size-2 rules, which was previously only known with size-5 rules. This is achieved using techniques within the motion planning framework. We provide many important results for feed-forward CRNs where rules are single-source or single-consuming. We show that reachability is solvable in polynomial time if the system does not contain special void or autogenesis rules. We then fully characterize all systems of this type and show that if you allow void/autogenesis rules, or have more than one source and one consuming, the problems become NP-complete. Finally, we show several interesting special cases of CRNs based on these restrictions or slight relaxations and note future significant open questions related to this taxonomy.Comment: This research was supported in part by National Science Foundation Grant CCF-181760

Design of Launch Vehicle Flight Control Systems Using Ascent Vehicle Stability Analysis Tool

A launch vehicle represents a complicated flex-body structural environment for flight control system design. The Ascent-vehicle Stability Analysis Tool (ASAT) is developed to address the complicity in design and analysis of a launch vehicle. The design objective for the flight control system of a launch vehicle is to best follow guidance commands while robustly maintaining system stability. A constrained optimization approach takes the advantage of modern computational control techniques to simultaneously design multiple control systems in compliance with required design specs. "Tower Clearance" and "Load Relief" designs have been achieved for liftoff and max dynamic pressure flight regions, respectively, in the presence of large wind disturbances. The robustness of the flight control system designs has been verified in the frequency domain Monte Carlo analysis using ASAT

Salmonella Typhimurium and Multidirectional Communication in the Gut

The mammalian digestive tract is home to trillions of microbes, including bacteria, archaea, protozoa, fungi and viruses. In monogastric mammals the stomach and small intestine harbor diverse bacterial populations but are typically less populated than the colon. The gut bacterial community (microbiota hereafter) varies widely among different host species and individuals within a species. It is influenced by season of the year, age of the host, stress and disease. Ideally, the host and microbiota benefit each other. The host provides nutrients to the microbiota and the microbiota assists the host with digestion and nutrient metabolism. The resident microbiota competes with pathogens for space and nutrients and, through this competition, protects the host in a phenomenon called colonization resistance. The microbiota participates in development of the host immune system, particularly regulation of autoimmunity and mucosal immune response. The microbiota also shapes gut-brain communication and host responses to stress; and, indeed, the microbiota is a newly recognized endocrine organ within mammalian hosts.Salmonella enterica serovar Typhimurium (S. Typhimurium hereafter) is a food-borne pathogen which adapts to and alters the gastrointestinal (GI) environment. In the GI tract, S. Typhimurium competes with the microbiota for nutrients and overcomes colonization resistance to establish infection. To do this, S. Typhimurium uses multiple defense mechanisms to resist environmental stressors, like the acidic pH of the stomach, and virulence mechanisms which allow it to invade the intestinal epithelium and disseminate throughout the host. To coordinate gene expression and disrupt signaling within the microbiota and between host and microbiota, S. Typhimurium employs its own chemical signaling and may regulate host hormone metabolism.This review will discuss the multidirectional interaction between S. Typhimurium, host and microbiota as well as mechanisms that allow S. Typhimurium to succeed in the gut

Building Squares with Optimal State Complexity in Restricted Active Self-Assembly

Tile Automata is a recently defined model of self-assembly that borrows many concepts from cellular automata to create active self-assembling systems where changes may be occurring within an assembly without requiring attachment. This model has been shown to be powerful, but many fundamental questions have yet to be explored. Here, we study the state complexity of assembling n × n squares in seeded Tile Automata systems where growth starts from a seed and tiles may attach one at a time, similar to the abstract Tile Assembly Model. We provide optimal bounds for three classes of seeded Tile Automata systems (all without detachment), which vary in the amount of complexity allowed in the transition rules. We show that, in general, seeded Tile Automata systems require Θ(log^{1/4} n) states. For Single-Transition systems, where only one state may change in a transition rule, we show a bound of Θ(log^{1/3} n), and for deterministic systems, where each pair of states may only have one associated transition rule, a bound of Θ(({log n}/{log log n})^{1/2})

Building Squares with Optimal State Complexity in Restricted Active Self-Assembly

Tile Automata is a recently defined model of self-assembly that borrows many concepts from cellular automata to create active self-assembling systems where changes may be occurring within an assembly without requiring attachment. This model has been shown to be powerful, but many fundamental questions have yet to be explored. Here, we study the state complexity of assembling $n \times n$ squares in seeded Tile Automata systems where growth starts from a seed and tiles may attach one at a time, similar to the abstract Tile Assembly Model. We provide optimal bounds for three classes of seeded Tile Automata systems (all without detachment), which vary in the amount of complexity allowed in the transition rules. We show that, in general, seeded Tile Automata systems require $\Theta{(\log^{\frac{1}{4}} n)}$ states. For single-transition systems, where only one state may change in a transition rule, we show a bound of $\Theta{(\log^{\frac{1}{3}} n)}$, and for deterministic systems, where each pair of states may only have one associated transition rule, a bound of $\Theta( (\frac{\log n}{\log \log n})^\frac{1}{2} )$.Comment: An earlier version was published in the 2022 Symposium on Algorithmic Foundations of Dynamic Networks (SAND

Ares I Flight Control System Design

The Ares I launch vehicle represents a challenging flex-body structural environment for flight control system design. This paper presents a design methodology for employing numerical optimization to develop the Ares I flight control system. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Under the assumption that the Ares I time-varying dynamics and control system can be frozen over a short period of time, the flight controllers are designed to stabilize all selected frozen-time launch control systems in the presence of parametric uncertainty. Flex filters in the flight control system are designed to minimize the flex components in the error signals before they are sent to the attitude controller. To ensure adequate response to guidance command, step response specifications are introduced as constraints in the optimization problem. Imposing these constraints minimizes performance degradation caused by the addition of the flex filters. The first stage bending filter design achieves stability by adding lag to the first structural frequency to phase stabilize the first flex mode while gain stabilizing the higher modes. The upper stage bending filter design gain stabilizes all the flex bending modes. The flight control system designs provided here have been demonstrated to provide stable first and second stage control systems in both Draper Ares Stability Analysis Tool (ASAT) and the MSFC 6DOF nonlinear time domain simulation

Building Squares with Optimal State Complexity in Restricted Active Self-Assembly

Tile Automata is a recently defined model of self-assembly that borrows many concepts from cellular automata to create active self-assembling systems where changes may be occurring within an assembly without requiring attachment. This model has been shown to be powerful, but many fundamental questions have yet to be explored. Here, we study the state complexity of assembling n × n squares in seeded Tile Automata systems where growth starts from a seed and tiles may attach one at a time, similar to the abstract Tile Assembly Model. We provide optimal bounds for three classes of seeded Tile Automata systems (all without detachment), which vary in the amount of complexity allowed in the transition rules. We show that, in general, seeded Tile Automata systems require Θ(log^{1/4} n) states. For Single-Transition systems, where only one state may change in a transition rule, we show a bound of Θ(log^{1/3} n), and for deterministic systems, where each pair of states may only have one associated transition rule, a bound of Θ(({log n}/{log log n})^{1/2})

PDiscoNet: Semantically consistent part discovery for fine-grained recognition

Fine-grained classification often requires recognizing specific object parts, such as beak shape and wing patterns for birds. Encouraging a fine-grained classification model to first detect such parts and then using them to infer the class could help us gauge whether the model is indeed looking at the right details better than with interpretability methods that provide a single attribution map. We propose PDiscoNet to discover object parts by using only image-level class labels along with priors encouraging the parts to be: discriminative, compact, distinct from each other, equivariant to rigid transforms, and active in at least some of the images. In addition to using the appropriate losses to encode these priors, we propose to use part-dropout, where full part feature vectors are dropped at once to prevent a single part from dominating in the classification, and part feature vector modulation, which makes the information coming from each part distinct from the perspective of the classifier. Our results on CUB, CelebA, and PartImageNet show that the proposed method provides substantially better part discovery performance than previous methods while not requiring any additional hyper-parameter tuning and without penalizing the classification performance. The code is available at https://github.com/robertdvdk/part_detection.Comment: 9 pages, 8 figures, ICC