Despite marine sciences’ turn towards big data over the last decades, only a very small portion of the world’s oceans today are sufficiently understood. Their modeling requires constant research and development of new ocean technologies, a highly competitive field usually conducted by corporate industries or public research institutions. In this case, an ocean robotics engineer and a media theorist met over the summer of 2019 in Santa Barbara to explore and reflect on alternative approaches in the design process of oceanographic data engineering and the role that media theory could play in it. They built and deployed a GPS trackable floating device that provided some _in situ_ data from the Santa Barbara Channel, and posed many open questions. The field report speaks of obstacles and failures, as well as surprising results and insights in the design process. Video available at: https://vimeo.com/527395527

Hefring Engineering has created OceanScout, a new underwater glider designed for compactness, simplicity and affordability. The vehicle is optimized for shelf & upper ocean measurements, low personnel requirements, long duration deployments, and scalable multi-vehicle operations. Affordability will facilitate adoption by new glider users, and scalability will enable established groups to deploy greater numbers of vehicles. This paper provides a review of the design and capabilities of the prototype OceanScout glider.

We discuss the design of a fault-detection system for an unmanned underwater vehicle (UUV) actuator and present the results of in-water testing. We first discuss the design of the system, then its integration onto the UUV, the in-water testing sequence, and finally the analysis of the test results –- missed detection and false-alarm rate. This system serves as a platform for UUV fault detection and isolation research, enabling the development of system requirements, and providing the opportunity to compare the merits of the centralized vs decentralized fault-detection design approaches.

Telescope networks are gaining traction due to their promise of higher resource utilization than single telescopes and as enablers of novel astronomical observation modes. However, as telescope network sizes increase, the possibility of scheduling them completely or even semi-manually disappears. In an earlier paper, a step towards software telescope scheduling was made with the specification of the Reservation formalism, through the use of which astronomers can express their complex observation needs and preferences. In this paper we build on that work. We present a solution to the discretized version of the problem of scheduling a telescope network. We derive a solvable integer linear programming (ILP) model based on the Reservation formalism. We show computational results verifying its correctness, and confirm that our Gurobi-based implementation can address problems of realistic size. Finally, we extend the ILP model to also handle the novel observation requests that can be specified using the more advanced Compound Reservation formalism.

Las Cumbres Observatory Global Telescope (LCOGT) is developing a worldwide network of fully robotic optical telescopes dedicated to time-domain astronomy. Observatory automation, longitudinal spacing of the sites, and a centralised network scheduler enable a range of observing modes impossible with traditional manual observing from a single location. We discuss the design goals of the LCOGT network scheduler, and in particular examine the unique network characteristics we seek to exploit for novel observing. We present an analysis of the key design trade-offs informing the scheduling architecture and data model, with special emphasis on both the unusual capabilities we have implemented, and some of the limitations of our approach. Finally, we describe some of the lessons we have learnt as we have moved from the beta test phase into full operational deployment in 2014.

Scheduling of university and institutional telescopes is typically performed manually, and astronomers are used to interacting with a human to explain their requirements for resources and time. Las Cumbres Observatory Global Telescope (LCOGT) is deploying a worldwide network of robotic telescopes. At LCOGT manual scheduling is infeasible due to: 1) the number of resources and observations that must be scheduled, 2) the scheduling-time dependencies that arise when concurrent or consecutive access to telescopes is required, and 3) the need to rapidly re-calculate the schedule to accommodate near-real-time requests from high priority observing programmes (e.g. transient followup programmes), and changing resource availability due to weather and other reasons. In this paper we develop a formalism capable of expressing the complex requirements and preferences of astronomers concerning resource and time allocation on a telescope network, and formulate the offline telescope network scheduling problem as the problem of choosing and scheduling (i.e. assigning concrete start and end times to) a maximum priority, non-overlapping subset of an input list of requests.

Cellular functions in biological organisms are comprised of the complex interactions of many molecular species: proteins, DNA and mRNA molecules, hormones, etc. Recent experimental developments in molecular biology have enabled researchers to characterize many of the biochemical pathways involved in these functions, and enormous amounts of data are currently available. However, despite this wealth of data, we still lack a sufficient understanding as to how cellular mechanisms combine to form the observable properties of cellular behavior. Key obstacles that restrict this understanding are the inherently complex and stochastic properties of cellular systems. Not only must we overcome the complex many-body nature of the interactions between the cellular components, but we are also we are faced with an additional difficulty, stemming from the stochastic, nonequilibrium nature of chemical reactions. The 3 Workshop on Stochasticity in Biochemical Reaction Networks was held to discuss recent progress on the role of intrinsic stochasticity in many-body biochemical networks. 1 Overview of the Field Cells in biological organisms are subject to vast amounts of random variation, which can cause isogenic cells to respond differently. There are many factors that may contribute to this phenotypical diversity. The simplest of these include fluctuations in environmental conditions such as nutrients, heat, radiation, etc. But even in homogenous environments, diversity can arise from the rare and discrete nature of chemical interactions within a cell. In general, molecules that are present in smaller numbers are prone to a greater extent of variable response, as single molecule events take on greater relative importance. In particular, since cells contain only one or two copies of many important genes, these cells can express vastly different behaviors when these genes become active (on) or inactive (off). Switching times from on to off and back are controlled by an uncountable number of random or chaotic events as the many cellular constituents move and interact within the cell. Effectively, genes can be (de)activated simply due to chance reactions with gene regulatory molecules. In turn, these regulatory molecules undergo their own complicated set of events, including degradation, dimerization, folding, etc. Any of these events may assist or impede a chemical’s reaction with a corresponding regulatory site of a given gene. As alluded to above, gene regulation is particularly prone to stochastic fluctuations due their extremely small population numbers. The variability in gene regulation subsequently affects the downstream regulation of other processes [30, 10, 55, 22, 41, 11, 25]. This variability is often deleterious to the organism’s survival, and biology has developed many mechanisms to suppress this variability, such as negative feedback or auto-regulation [2, 9, 38], which can reduce fluctuations for a given mean expression level. As

We examine various algebraic/combinatorial properties of Low-Density Parity-Check codes as predictors for the performance of the sum-product algorithm on the AWGN channel in the error floor region. We consider three families of check matrices, two algebraically constructed and one sampled from an ensemble, expurgated to remove short cycles. The three families have similar properties, all are (3; 6)-regular, have girth 8, and have code length roughly 280. The best predictors are small trapping sets, and the predictive value is much higher for the algebraically constructed families than the random ones.

Studies in adults with rheumatoid arthritis reported low serum ghrelin that increased following anti–tumor necrosis factor (TNF) infusion. Data on juvenile idiopathic arthritis (JIA) are lacking. The aim of this pilot study was to explore serum ghrelin levels in patients with JIA and the possible association with anti-TNF treatment, disease activity, and nutritional status. Fifty-two patients with JIA (14/52 on anti-TNF treatment) were studied. Juvenile idiopathic arthritis was inactive in 3 of 14 anti-TNF–treated patients and in 11 of 38 non–anti-TNF-treated patients. The nutritional status, energy intake/requirements, appetite, and fasting serum ghrelin levels were assessed. Ghrelin control values were obtained from 50 individuals with minor illness matched for age, sex, and body mass index. Ghrelin levels in patients with JIA were significantly lower than in controls (P < .001, confidence interval [CI] = −101 to −331). Analysis according to anti-TNF treatment and disease activity showed that ghrelin levels were comparable to control values only in 3 patients with anti-TNF–induced remission. Ghrelin in non–anti-TNF-treated patients in remission was low. Multiple regression analysis showed that disease activity (P = .002, CI = −84.16 to −20.01) and anti-TNF treatment (P = .003, CI = −82.51 to −18.33) were significant independent predictors of ghrelin after adjusting for other potential confounders. Ghrelin did not correlate with nutritional status, energy balance, and appetite. Serum ghrelin is low in patients with JIA and is restored to values similar to those in controls following anti-TNF–induced remission. Our study provides evidence that TNF blockade is independently associated with serum ghrelin, which possibly contributes to anti-TNF–induced remission. These preliminary results could form the basis for future research.

We present a driver program for performing replica-exchange molecular dynamics simulations with the TINKER package. Parallelization is based on the Message Passing Interface, with every replica assigned to a separate process. The algorithm is not communication intensive, which makes the program suitable for running even on loosely Coupled cluster systems. Particular attention is paid to the practical aspects of analyzing the program Output.Program summaryProgram title: TiReXCatalogue identifier: AEEK_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEEK_v1-0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qLib.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 43 385No. of bytes in distributed program, including test data, etc.: 502 262Distribution format: tar.gzProgramming language: Fortran 90/95Computer: Most UNIX machinesOperating system: LinuxHas the code been vectorized or parallelized?: parallelized with MPIClassification: 16.13External routines: TINKER version 4.2 or 5.0, built as a libraryNature of problem: Replica-exchange molecular dynamics.Solution method: Each replica is assigned to a separate process; temperatures are swapped between replicas at regular time intervals.Running time: The sample run may take up to a few minutes. (C) 2009 Elsevier B.V. All rights reserved.

The stochastic simulation algorithm (SSA) is widely used in the discrete stochastic simulation of chemical kinetics. The propensity functions which play a central role in this algorithm have been derived under the point-molecule assumption, i.e., that the total volume of the molecules is negligible compared to the volume of the container. It has been shown analytically that for a one-dimensional system and the A+A reaction, when the point-molecule assumption is relaxed, the propensity function need only be adjusted by replacing the total volume of the system with the free volume of the system. In this paper we investigate via numerical simulations the impact of relaxing the point-molecule assumption in two dimensions. We find that the distribution of times to the first collision is close to exponential in most cases, so that the formalism of the propensity function is still applicable. In addition, we find that the area excluded by the molecules in two dimensions is usually higher than their close-packed area, requiring a larger correction to the propensity function than just the replacement of the total volume by the free volume.

The Inhomogeneous Stochastic Simulation Algorithm (ISSA) is a variant of the stochastic simulation algorithm in which the spatially inhomogeneous volume of the system is divided into homogeneous subvolumes, and the chemical reactions in those subvolumes are augmented by diffusive transfers of molecules between adjacent subvolumes. The ISSA can be prohibitively slow when the system is such that diffusive transfers occur much more frequently than chemical reactions. In this paper we present the Multinomial Simulation Algorithm (MSA), which is designed to, on the one hand, outperform the ISSA when diffusive transfer events outnumber reaction events, and on the other, to handle small reactant populations with greater accuracy than deterministic-stochastic hybrid algorithms. The MSA treats reactions in the usual ISSA fashion, but uses appropriately conditioned binomial random variables for representing the net numbers of molecules diffusing from any given subvolume to a neighbor within a prescribed distance. Simulation results illustrate the benefits of the algorithm.

This thesis is concerned with studying what happens when space must be taken into account in discrete stochastic simulation of chemical kinetics. The Stochastic Simulation Algorithm of Gillespie, which is the simulation technique of choice for mesoscopic stochastic chemical kinetics, is rigorously applicable to systems of point molecules which are well-stirred. The former condition means that the molecules must occupy volume negligible compared to the total volume of the system. The latter condition means that the distribution of the molecules' positions in space must be uniformly random.The SSA has been steadily gaining ground as a method of simulating intracellular kinetics. However, one or both of the conditions which make it rigorously applicable are frequently not met in that biological context. In the first section of this thesis we present our results regarding relaxing the point molecule condition. We find that, even when molecules are allowed to exclude substantial volume, the distribution of inter-collision times is still close to exponential, making the SSA still applicable once appropriate propensity functions are chosen. In the second section of the thesis we concern ourselves with relaxing the well-stirred condition. The Inhomogeneous SSA is applicable in that situation, but it may not be a realistic choice because of its computational cost. We present the Multinomial Simulation Algorithm for stochastic reaction-diffusion, which interlaces approximate stochastic diffusion with reactions simulated according to the SSA.

SummarySelf-assembling peptides can serve as building blocks for novel biomaterials. Replica exchange molecular dynamics simulations are a powerful means to probe the conformational space of these peptides. We discuss the theoretical foundations of this enhanced sampling method and its use in biomolecular simulations. We then apply this method to determine the monomeric conformations of the Alzheimer amyloid-β(, , , , , , , , , , , , , , , , ) peptide that can serve as initiation sites for aggregation.

Self-assembling peptides can serve as building blocks for novel biomaterials. Replica exchange molecular dynamics simulations are a powerful means to probe the conformational space of these peptides. We discuss the theoretical foundations of this enhanced sampling method and its use in biomolecular simulations. We then apply this method to determine the monomeric conformations of the Alzheimer amyloid-beta(12-28) peptide that can serve as initiation sites for aggregation.

This paper is aimed at understanding what happens to the propensity functions (rates) of bimolecular chemical reactions when the volume occupied by the reactant molecules is not negligible compared to the containing volume of the system. For simplicity our analysis focuses on a one-dimensional gas of N hard-rod molecules, each of length l. Assuming these molecules are distributed randomly and uniformly inside the real interval [0,L] in a nonoverlapping way, and that they have Maxwellian distributed velocities, the authors derive an expression for the probability that two rods will collide in the next infinitesimal time dt. This probability controls the rate of any chemical reaction whose occurrence is initiated by such a collision. The result turns out to be a simple generalization of the well-known result for the point molecule case l=0: the system volume L in the formula for the propensity function in the point molecule case gets replaced by the "free volume" L-Nl. They confirm the result in a series of one-dimensional molecular dynamics simulations. Some possible wider implications of this result are discussed.

The BvgAS two-component system controls virulence in the human respiratory pathogen Bordetella pertussis, the etiological agent of whooping cough. BvgAS is unlike orthodox two-component signal transduction systems in that it employs a four step phosphorelay from the sensor protein BvgS to the response regulator BvgA, instead of the more common two step phosphotransfer. Further, B. pertussis displays at least three distinct phenotypic phases, each characterized by maximal expression of some genes and minimal expression of others. In vitro experiments are modeled by ordinary differential equations of chemical kinetics in order to obtain kinetic parameter estimates. Completed versions of the model are then simulated using deterministic (ODE), stochastic (Gillespie's algorithm) or multiscale (tau leaping, slow-scale SSA or hybrid) chemical kinetics algorithms, depending on what is appropriate. Preliminary results indicate that the full complexity of the three phenotypic phases of B. pertussis cannot be achieved without incorporating the phosphorelay (i.e. by simple two-step phosphotransfer) or BvgAS autoregulation in the model

: Bacteria sense and respond to environmental stimuli using pairs of proteins called two-component systems. These are composed of a histidine kinase sensor protein, which autophosphorylates in the presence of the signal being sensed, and a response regulator protein, which is typically involved in binding DNA and controlling gene transcription. The information that a signal is being sensed is relayed from the sensor to the response regulator via a phosphotransfer step. A more sophisticated variant of the two-component system, the phosphorelay, contains two additional signaling domains and two additional phosphotransfer steps. The BvgAS phosphorelay controls virulence in the Bordetella family of respiratory pathogens. Bordetella pertussis is the strictly human-adapted etiological agent of whooping cough, and causes acute infections. Bordetella bronchiseptica causes chronic respiratory infections in a variety of four-legged mammals. BvgAS employs a four step His-Asp-His-Asp phosphorelay from the sensor protein BvgS to the response regulator BvgA. We have developed a family of computational models and simulations of the BvgAS signal transduction and gene expression pathway, which we use to explore both quantitative and qualitative questions. The ultimate goal is to unravel how the phosphorelay works and what are its advantages over the more simple two-component systems.