The effect of small-amplitude time-dependent changes to the surface morphology of a sphere

Typical approaches to manipulation of flow separation employ passive means or active techniques such as blowing and suction or plasma acceleration. Here it is demonstrated that the flow can be significantly altered by making small changes to the shape of the surface. A proof of concept experiment is performed using a very simple time-dependent perturbation to the surface of a sphere: a roughness element of 1% of the sphere diameter is moved azimuthally around a sphere surface upstream of the uncontrolled laminar separation point, with a rotational frequency as large as the vortex shedding frequency. A key finding is that the non-dimensional time to observe a large effect on the lateral force due to the perturbation produced in the sphere boundary layers as the roughness moves along the surface is ˆt =tU_(∞)/D ≈4. This slow development allows the moving element to produce a tripped boundary layer over an extended region. It is shown that a lateral force can be produced that is as large as the drag. In addition, simultaneous particle image velocimetry and force measurements reveal that a pair of counter-rotating helical vortices are produced in the wake, which have a significant effect on the forces and greatly increase the Reynolds stresses in the wake. The relatively large perturbation to the flow-field produced by the small surface disturbance permits the construction of a phase-averaged, three-dimensional (two-velocity component) wake structure from measurements in the streamwise/radial plane. The vortical structure arising due to the roughness element has implications for flow over a sphere with a nominally smooth surface or distributed roughness. In addition, it is shown that oscillating the roughness element, or shaping its trajectory, can produce a mean lateral force

Computer Architectures to Close the Loop in Real-time Optimization

© 2015 IEEE.Many modern control, automation, signal processing and machine learning applications rely on solving a sequence of optimization problems, which are updated with measurements of a real system that evolves in time. The solutions of each of these optimization problems are then used to make decisions, which may be followed by changing some parameters of the physical system, thereby resulting in a feedback loop between the computing and the physical system. Real-time optimization is not the same as fast optimization, due to the fact that the computation is affected by an uncertain system that evolves in time. The suitability of a design should therefore not be judged from the optimality of a single optimization problem, but based on the evolution of the entire cyber-physical system. The algorithms and hardware used for solving a single optimization problem in the office might therefore be far from ideal when solving a sequence of real-time optimization problems. Instead of there being a single, optimal design, one has to trade-off a number of objectives, including performance, robustness, energy usage, size and cost. We therefore provide here a tutorial introduction to some of the questions and implementation issues that arise in real-time optimization applications. We will concentrate on some of the decisions that have to be made when designing the computing architecture and algorithm and argue that the choice of one informs the other

Small RNA-based antiviral defense in the phytopathogenic fungus Colletotrichum higginsianum

Even though the fungal kingdom contains more than 3 million species, little is known about the biological roles of RNA silencing in fungi. The Colletotrichum genus comprises fungal species that are pathogenic for a wide range of crop species worldwide. To investigate the role of RNA silencing in the ascomycete fungus Colletotrichum higginsianum, knock-out mutants affecting genes for three RNA-dependent RNA polymerase (RDR), two Dicer-like (DCL), and two Argonaute (AGO) proteins were generated by targeted gene replacement. No effects were observed on vegetative growth for any mutant strain when grown on complex or minimal media. However, Δdcl1, Δdcl1Δdcl2 double mutant, and Δago1 strains showed severe defects in conidiation and conidia morphology. Total RNA transcripts and small RNA populations were analyzed in parental and mutant strains. The greatest effects on both RNA populations was observed in the Δdcl1, Δdcl1Δdcl2, and Δago1 strains, in which a previously uncharacterized dsRNA mycovirus [termed Colletotrichum higginsianum non-segmented dsRNA virus 1 (ChNRV1)] was derepressed. Phylogenetic analyses clearly showed a close relationship between ChNRV1 and members of the segmented Partitiviridae family, despite the non-segmented nature of the genome. Immunoprecipitation of small RNAs associated with AGO1 showed abundant loading of 5'U-containing viral siRNA. C. higginsianum parental and Δdcl1 mutant strains cured of ChNRV1 revealed that the conidiation and spore morphology defects were primarily caused by ChNRV1. Based on these results, RNA silencing involving ChDCL1 and ChAGO1 in C. higginsianum is proposed to function as an antiviral mechanism

Nonlinear predictive control on a heterogeneous computing platform

Nonlinear Model Predictive Control (NMPC) is an advanced control technique that often relies on computationally demanding optimization and integration algorithms. This paper proposes and investigates a heterogeneous hardware implementation of an NMPC controller based on an interior point algorithm. The proposed implementation provides flexibility of splitting the workload between a general-purpose CPU with a fixed architecture and a field-programmable gate array (FPGA) to trade off contradicting design objectives, namely performance and computational resource usage. A new way of exploiting the structure of the Karush-Kuhn-Tucker (KKT) matrix yields significant memory savings, which is crucial for reconfigurable hardware. For the considered case study, a 10x memory savings compared to existing approaches and a 10x speedup over a software implementation are reported. The proposed implementation can be tested from Matlab using a new release of the Protoip software tool, which is another contribution of the paper. Protoip abstracts many low-level details of heterogeneous hardware programming and allows quick prototyping and processor-in-the-loop verification of heterogeneous hardware implementations

Influence of 16S rRNA Hypervariable Region on Estimates of Bacterial Diversity and Community Composition in Seawater and Marine Sediment

To assess the influence of 16S ribosomal RNA (rRNA) tag choice on estimates of microbial diversity and/or community composition in seawater and marine sediment, we examined bacterial diversity and community composition from a site in the Central North Atlantic and a site in the Equatorial Pacific. For each site, we analyzed samples from four zones in the water column, a seafloor sediment sample, and two subseafloor sediment horizons (with stratigraphic ages of 1.5 and 5.5 million years old). We amplified both the V4 and V6 hypervariable regions of the 16S rRNA gene and clustered the sequences into operational taxonomic units (OTUs) of 97% similarity to analyze for diversity and community composition. OTU richness is much higher with the V6 tag than with the V4 tag, and subsequently OTU-level community composition is quite different between the two tags. Vertical patterns of relative diversity are broadly the same for both tags, with maximum taxonomic richness in seafloor sediment and lowest richness in subseafloor sediment at both geographic locations. Genetic dissimilarity between sample locations is also broadly the same for both tags. Community composition is very similar for both tags at the class level, but very different at the level of 97% similar OTUs. Class-level diversity and community composition of water-column samples are very similar at each water depth between the Atlantic and Pacific. However, sediment communities differ greatly from the Atlantic site to the Pacific site. Finally, for relative patterns of diversity and class-level community composition, deep sequencing and shallow sequencing provide similar results

Software and hardware code generation for predictive control using splitting methods

This paper presents SPLIT, a C code generation tool for Model Predictive Control (MPC) based on operator splitting methods. In contrast to existing code generation packages, SPLIT is capable of generating both software and hardware-oriented C code to allow quick prototyping of optimization algorithms on conventional CPUs and field-programmable gate arrays (FPGAs). A Matlab interface is provided for compatibility with existing commercial and open-source software packages. A numerical study compares software, hardware and heterogeneous implementations of splitting methods and investigates MPC design trade-offs. For the considered testcases the reported speedup of hardware implementations over software realizations is 3x to 11x

High-level synthesis using the Julia language

The growing proliferation of FPGAs and High-level Synthesis (HLS) tools has led to a large interest in designing hardware accelerators for complex operations and algorithms. However, existing HLS toolflows typically require a significant amount of user knowledge or training to be effective in both industrial and research applications. In this paper, we propose using the Julia language as the basis for an HLS tool. The Julia HLS tool aims to decrease the barrier to entry for hardware acceleration by taking advantage of the readability of the Julia language and by allowing the use of the existing large library of standard mathematical functions written in Julia. We present a prototype Julia HLS tool, written in Julia, that transforms Julia code to VHDL. We highlight how features of Julia and its compiler simplified the creation of this tool, and we discuss potential directions for future work

Preparation of multiplexed small RNA libraries from plants

[EN] High-throughput sequencing is a powerful tool for exploring small RNA populations in plants. The ever-increasing output from an Illumina Sequencing System allows for multiplexing multiple samples while still obtaining sufficient data for small RNA discovery and characterization. Here we describe a protocol for generating multiplexed small RNA libraries for sequencing up to 12 samples in one lane of an Illumina HiSeq System single-end, 50 base pair run. RNA ligases are used to add the 3¿ and 5¿ adaptors to purified small RNAs; ligation products that lack a small RNA molecule (adaptor-adaptor products) are intentionally depleted. After cDNA synthesis, a linear PCR step amplifies the DNA fragments. The 3¿ PCR primers used here include unique 6- nucleotide sequences to allow for multiplexing up to 12 samples.The original version of this protocol was described in Carbonell et al. (2012). The updated version of the protocol was described in Carbonell et al. (2014). This work was supported by grants from the National Science Foundation (MCB-0956526, MCB-1231726) and National Institutes of Health (AI043288)Gilbert, KB.; Fahlgren, N.; Kasschau, KD.; Chapman, EJ.; Carrington, JC.; Carbonell, A. (2014). Preparation of multiplexed small RNA libraries from plants. Bio-protocol. 4(21):1-17. https://doi.org/10.21769/BioProtoc.1275S11742