A type system for components

In modern distributed systems, dynamic reconfiguration, i.e., changing at runtime the communication pattern of a program, is chal- lenging. Generally, it is difficult to guarantee that such modifications will not disrupt ongoing computations. In a previous paper, a solution to this problem was proposed by extending the object-oriented language ABS with a component model allowing the programmer to: i) perform up- dates on objects by means of communication ports and their rebinding; and ii) precisely specify when such updates can safely occur in an object by means of critical sections. However, improper rebind operations could still occur and lead to runtime errors. The present paper introduces a type system for this component model that extends the ABS type system with the notion of ports and a precise analysis that statically enforces that no object will attempt illegal rebinding

Biomarkers in emergency medicine

Researchers navigate the ocean of biomarkers searching for proper targets and optimal utilization of them. Emergency medicine builds up the front line to maximize the utility of clinically validated biomarkers and is the cutting edge field to test the applicability of promising biomarkers emerging from thorough translational researches. The role of biomarkers in clinical decision making would be of greater significance for identification, risk stratification, monitoring, and prognostication of the patients in the critical- and acute-care settings. No doubt basic research to explore novel biomarkers in relation to the pathogenesis is as important as its clinical counterpart. This special issue includes five selected research papers that cover a variety of biomarker- and disease-related topics

Syntactic Markovian Bisimulation for Chemical Reaction Networks

In chemical reaction networks (CRNs) with stochastic semantics based on continuous-time Markov chains (CTMCs), the typically large populations of species cause combinatorially large state spaces. This makes the analysis very difficult in practice and represents the major bottleneck for the applicability of minimization techniques based, for instance, on lumpability. In this paper we present syntactic Markovian bisimulation (SMB), a notion of bisimulation developed in the Larsen-Skou style of probabilistic bisimulation, defined over the structure of a CRN rather than over its underlying CTMC. SMB identifies a lumpable partition of the CTMC state space a priori, in the sense that it is an equivalence relation over species implying that two CTMC states are lumpable when they are invariant with respect to the total population of species within the same equivalence class. We develop an efficient partition-refinement algorithm which computes the largest SMB of a CRN in polynomial time in the number of species and reactions. We also provide an algorithm for obtaining a quotient network from an SMB that induces the lumped CTMC directly, thus avoiding the generation of the state space of the original CRN altogether. In practice, we show that SMB allows significant reductions in a number of models from the literature. Finally, we study SMB with respect to the deterministic semantics of CRNs based on ordinary differential equations (ODEs), where each equation gives the time-course evolution of the concentration of a species. SMB implies forward CRN bisimulation, a recently developed behavioral notion of equivalence for the ODE semantics, in an analogous sense: it yields a smaller ODE system that keeps track of the sums of the solutions for equivalent species.Comment: Extended version (with proofs), of the corresponding paper published at KimFest 2017 (http://kimfest.cs.aau.dk/

Experimental Biological Protocols with Formal Semantics

Both experimental and computational biology is becoming increasingly automated. Laboratory experiments are now performed automatically on high-throughput machinery, while computational models are synthesized or inferred automatically from data. However, integration between automated tasks in the process of biological discovery is still lacking, largely due to incompatible or missing formal representations. While theories are expressed formally as computational models, existing languages for encoding and automating experimental protocols often lack formal semantics. This makes it challenging to extract novel understanding by identifying when theory and experimental evidence disagree due to errors in the models or the protocols used to validate them. To address this, we formalize the syntax of a core protocol language, which provides a unified description for the models of biochemical systems being experimented on, together with the discrete events representing the liquid-handling steps of biological protocols. We present both a deterministic and a stochastic semantics to this language, both defined in terms of hybrid processes. In particular, the stochastic semantics captures uncertainties in equipment tolerances, making it a suitable tool for both experimental and computational biologists. We illustrate how the proposed protocol language can be used for automated verification and synthesis of laboratory experiments on case studies from the fields of chemistry and molecular programming

Process algebra modelling styles for biomolecular processes

We investigate how biomolecular processes are modelled in process algebras, focussing on chemical reactions. We consider various modelling styles and how design decisions made in the definition of the process algebra have an impact on how a modelling style can be applied. Our goal is to highlight the often implicit choices that modellers make in choosing a formalism, and illustrate, through the use of examples, how this can affect expressability as well as the type and complexity of the analysis that can be performed

Computational Modeling for the Activation Cycle of G-proteins by G-protein-coupled Receptors

In this paper, we survey five different computational modeling methods. For comparison, we use the activation cycle of G-proteins that regulate cellular signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving example. Starting from an existing Ordinary Differential Equations (ODEs) model, we implement the G-protein cycle in the stochastic Pi-calculus using SPiM, as Petri-nets using Cell Illustrator, in the Kappa Language using Cellucidate, and in Bio-PEPA using the Bio-PEPA eclipse plug in. We also provide a high-level notation to abstract away from communication primitives that may be unfamiliar to the average biologist, and we show how to translate high-level programs into stochastic Pi-calculus processes and chemical reactions.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

A Photometric Investigation of the GRB970228 Afterglow and the Associated Nebulosity

We carefully analyze the WFPC2 and STIS images of GRB970228. We measure magnitudes for the GRB970228 point source component in the WFPC2 images of $V=26.20^{+0.14}_{-0.13}$, $I_c=23.94^{+0.10}_{-0.09}$ and $V=26.52^{+0.16}_{-0.18}$, $I_c=24.31^{+0.15}_{-0.11}$ on March 26 and April 7, respectively; and $R_c=27.09^{+0.14}_{-0.14}$ on September 4 in the STIS image. For the extended component, we measure magnitudes of $R_c=25.48^{+0.22}_{-0.20}$ in the combined WFPC2 images and $R_c=25.54^{+0.33}_{-0.22}$ in the STIS image, which are consistent with no variation. This value is fainter than previously reported (Galama et al. 98) and modifies the previously assumed magnitudes for the optical transient when it faded to a level where the extended source component contribution was not negligible, alleviating the discrepancy to a power-law temporal behavior. We also measure a color of $V_{606}-I_{814}=-0.18^{+0.51}_{-0.61}$ for the extended source component. Taking into account the extinction measured in this field (Castander & Lamb 1998), this color implies that the extended source is most likely a galaxy with ongoing star formation.Comment: 21 pages, including 8 figures. Submitted to Ap

Design and analysis of DNA strand displacement devices using probabilistic model checking

Designing correct, robust DNA devices is difficult because of the many possibilities for unwanted interference between molecules in the system. DNA strand displacement has been proposed as a design paradigm for DNA devices, and the DNA strand displacement (DSD) programming language has been developed as a means of formally programming and analysing these devices to check for unwanted interference. We demonstrate, for the first time, the use of probabilistic verification techniques to analyse the correctness, reliability and performance of DNA devices during the design phase. We use the probabilistic model checker prism, in combination with the DSD language, to design and debug DNA strand displacement components and to investigate their kinetics. We show how our techniques can be used to identify design flaws and to evaluate the merits of contrasting design decisions, even on devices comprising relatively few inputs. We then demonstrate the use of these components to construct a DNA strand displacement device for approximate majority voting. Finally, we discuss some of the challenges and possible directions for applying these methods to more complex designs

The importance of root interactions in field bean/triticale intercrops

To highlight the contribution of belowground interactions to biomass and N and P yields, field bean and triticale were grown in a P-poor soil as sole crops and as replacement intercrops at two N levels. The shoots were always in contact, while the roots of adjacent rows were free to interact or were completely separated. This allowed simultaneous testing the intraspecific and interspecific competition between rows, which to our knowledge has not been studied before. Root biomass, distribution in soil, morphometry, and functional traits were determined, together with the nodule number and biomass. The Land Equivalent Ratio for shoot biomass and N and P yield were higher than 1 when roots were in contact, and markedly lower when they were separated. This demonstrates the positive contribution of root interactions, which in field bean, consisted of increased root elongation without changes in biomass and nutrient status; in triticale, of increased N and P uptake eciency and reduced biomass partitioning to roots. The soil-plant processes underlying intercrop advantage led to complementarity in N sources with low N inputs and facilitated N and P uptake with high N inputs, which demonstrates that intercropping could be profitable in both low and high input agriculture

Biochar impact on the estimation of the colorimetric-based enzymatic assays of soil

This study was carried out in order to assess the influence of biochar applications on the estimation of colorimetric-based enzymatic assays and to verify the effectiveness of the most common methods. Since most methods used to determine enzymatic activities in the soil are based on colorimetry, biochar may absorb substrates and/ or coloured products thereby distorting the analytical result. Biochar was added to two soils, with different textures and cation exchangeable capacities, at a rate of 2% (w/w), and seven enzyme activities were determined following standard methods. The biochar amendment lowered the spectrophotometer reading of the activity of FDAase and dehydrogenase in the sandy soil. In the three enzymatic activities based on p-nitrophenol production (β-glucosidase, phosphatase and arylsulphatase), the addition of biochar did not change the enzyme assays. The biochar led to an overestimation in terms of the protease and urease activities in the sandy soil. In the clay loamy soil, biochar did not change the response of any of the enzyme activities tested. A biochar dose of up to 2% only guarantees the effectiveness of the most common spectrophotometric methods for not excessively sandy soils