58 research outputs found
Digital control of force microscope cantilevers using a field programmable gate array
This report describes a cantilever controller for magnetic resonance force
microscopy (MRFM) based on a field programmable gate array (FPGA), along with
the hardware and software used to integrate the controller into an experiment.
The controller is assembled from a low-cost commercially available software
defined radio (SDR) device and libraries of open-source software. The
controller includes a digital filter comprising two cascaded second-order
sections ("biquads"), which together can implement transfer functions for
optimal cantilever controllers. An appendix in this report shows how to
calculate filter coefficients for an optimal controller from measured
cantilever characteristics. The controller also includes an input multiplexer
and adder used in calibration protocols. Filter coefficients and multiplexer
settings can be set and adjusted by control software while an experiment is
running. The input is sampled at 64 MHz; the sampling frequency in the filters
can be divided down under software control to achieve a good match with filter
characterisics. Data reported here were sampled at 500 kHz, chosen for acoustic
cantilevers with resonant frequencies near 8 kHz. Inputs are digitized with 12
bits resolution, outputs with 14 bits. The experiment software is organized as
a client and server to make it easy to adapt the controller to different
experiments. The server encapusulates the details of controller hardware
organization, connection technology, filter architecture, and number
representation. The same server could be used in any experiment, while a
different client encodes the particulars of each experiment.Comment: submitted to Review of Scientific Instrument
Applying SMT Solvers to the Test Template Framework
The Test Template Framework (TTF) is a model-based testing method for the Z
notation. In the TTF, test cases are generated from test specifications, which
are predicates written in Z. In turn, the Z notation is based on first-order
logic with equality and Zermelo-Fraenkel set theory. In this way, a test case
is a witness satisfying a formula in that theory. Satisfiability Modulo Theory
(SMT) solvers are software tools that decide the satisfiability of arbitrary
formulas in a large number of built-in logical theories and their combination.
In this paper, we present the first results of applying two SMT solvers, Yices
and CVC3, as the engines to find test cases from TTF's test specifications. In
doing so, shallow embeddings of a significant portion of the Z notation into
the input languages of Yices and CVC3 are provided, given that they do not
directly support Zermelo-Fraenkel set theory as defined in Z. Finally, the
results of applying these embeddings to a number of test specifications of
eight cases studies are analysed.Comment: In Proceedings MBT 2012, arXiv:1202.582
A clinically relevant sheep model of orthotopic heart transplantation 24 h after donor brainstem death
BACKGROUND: Heart transplantation (HTx) from brainstem dead (BSD) donors is the gold-standard therapy for severe/end-stage cardiac disease, but is limited by a global donor heart shortage. Consequently, innovative solutions to increase donor heart availability and utilisation are rapidly expanding. Clinically relevant preclinical models are essential for evaluating interventions for human translation, yet few exist that accurately mimic all key HTx components, incorporating injuries beginning in the donor, through to the recipient. To enable future assessment of novel perfusion technologies in our research program, we thus aimed to develop a clinically relevant sheep model of HTx following 24 h of donor BSD. METHODS: BSD donors (vs. sham neurological injury, 4/group) were hemodynamically supported and monitored for 24 h, followed by heart preservation with cold static storage. Bicaval orthotopic HTx was performed in matched recipients, who were weaned from cardiopulmonary bypass (CPB), and monitored for 6 h. Donor and recipient blood were assayed for inflammatory and cardiac injury markers, and cardiac function was assessed using echocardiography. Repeated measurements between the two different groups during the study observation period were assessed by mixed ANOVA for repeated measures. RESULTS: Brainstem death caused an immediate catecholaminergic hemodynamic response (mean arterial pressure, p = 0.09), systemic inflammation (IL-6 - p = 0.025, IL-8 - p = 0.002) and cardiac injury (cardiac troponin I, p = 0.048), requiring vasopressor support (vasopressor dependency index, VDI, p = 0.023), with normalisation of biomarkers and physiology over 24 h. All hearts were weaned from CPB and monitored for 6 h post-HTx, except one (sham) recipient that died 2 h post-HTx. Hemodynamic (VDI - p = 0.592, heart rate - p = 0.747) and metabolic (blood lactate, p = 0.546) parameters post-HTx were comparable between groups, despite the observed physiological perturbations that occurred during donor BSD. All p values denote interaction among groups and time in the ANOVA for repeated measures. CONCLUSIONS: We have successfully developed an ovine HTx model following 24 h of donor BSD. After 6 h of critical care management post-HTx, there were no differences between groups, despite evident hemodynamic perturbations, systemic inflammation, and cardiac injury observed during donor BSD. This preclinical model provides a platform for critical assessment of injury development pre- and post-HTx, and novel therapeutic evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40635-021-00425-4
Minimum Information About a Simulation Experiment (MIASE)
The original publication is available at www.ploscompbiol.orgReproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes.The discussions that led to the definition of MIASE benefited from the support of a Japan Partnering Award by the UK Biotechnology and Biological Sciences Research Council. DW was supported by the Marie Curie program and by the German Research Association (DFG Research Training School ‘‘dIEM oSiRiS’’ 1387/1). This publication is based on work (EJC) supported in part by Award No KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). FTB acknowledges support by the NIH (grant 1R01GM081070- 01). JC is supported by the European Commission, DG Information Society, through the Seventh Framework Programme of Information and Communication Technologies, under the VPH NoE project (grant number 223920). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Publishers versio
BioSimulators: a central registry of simulation engines and services for recommending specific tools
Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations
Act now against new NHS competition regulations: an open letter to the BMA and the Academy of Medical Royal Colleges calls on them to make a joint public statement of opposition to the amended section 75 regulations.
Practical recipes for the model order reduction, dynamical simulation, and compressive sampling of large-scale open quantum systems
This article presents numerical recipes for simulating high-temperature and
non-equilibrium quantum spin systems that are continuously measured and
controlled. The notion of a spin system is broadly conceived, in order to
encompass macroscopic test masses as the limiting case of large-j spins. The
simulation technique has three stages: first the deliberate introduction of
noise into the simulation, then the conversion of that noise into an equivalent
continuous measurement and control process, and finally, projection of the
trajectory onto a state-space manifold having reduced dimensionality and
possessing a Kahler potential of multi-linear form. The resulting simulation
formalism is used to construct a positive P-representation for the thermal
density matrix. Single-spin detection by magnetic resonance force microscopy
(MRFM) is simulated, and the data statistics are shown to be those of a random
telegraph signal with additive white noise. Larger-scale spin-dust models are
simulated, having no spatial symmetry and no spatial ordering; the
high-fidelity projection of numerically computed quantum trajectories onto
low-dimensionality Kahler state-space manifolds is demonstrated. The
reconstruction of quantum trajectories from sparse random projections is
demonstrated, the onset of Donoho-Stodden breakdown at the Candes-Tao sparsity
limit is observed, a deterministic construction for sampling matrices is given,
and methods for quantum state optimization by Dantzig selection are given.Comment: 104 pages, 13 figures, 2 table
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