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Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies

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BIOINFORMATICS 2016年第9期32卷 1316-1322页

作者： Wang, Xiaowei Washington Univ Sch Med Dept Radiat Oncol St Louis MO 63108 USA

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes targeted by miRNAs. Currently, most researchers rely on computational programs to initially identify target candidates for subsequent validation. Although considerable progress has been made in recent years for computational target prediction, there is still significant room for algorithmic improvement. Results: Here, we present an improved target prediction algorithm, which was developed by modeling high-throughput profiling data from recent CLIPL (crosslinking and immunoprecipitation followed by RNA ligation) sequencing studies. In these CLIPL-seq studies, the RNA sequences in each miRNA-target pair were covalently linked and unambiguously determined experimentally. By analyzing the CLIPL data, many known and novel features relevant to target recognition were identified and then used to build a computational model for target prediction. Comparative analysis showed that the new algorithm had improved performance over existing algorithms when applied to independent experimental data.

关键词： MICRORNA computer simulation computer algorithms COMPARATIVE studies FORECASTING

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Disturbance rejection of real power flow by grid-tied inverter

Disturbance rejection of real power flow by grid-tied invert...

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American Control Conference

作者： Xin Zhao Benjamin T. Gwynn Raymond A. de Callafon William Torre Dept. of Mechanical and Aerospace Engineering and the Sychrophasor Grid Monitoring and Automation (SyGMA) laboratory at the University of California San Diego Center for Energy Research University of California San Diego

ISBN: (纸本)9781509045839

High penetration of distributed and renewable power generation systems challenges the conventional paradigm of stabilizing power systems with the standard rotational inertia used in power generation. To improve the stability of a power system, advanced disturbance rejection control techniques can be used to provide damping and power disturbance mitigation. An approach for three-phase (real) power disturbance mitigation using real-time feedback control is outlined in this paper. The control algorithm for power disturbance rejection is formulated via the internal model principle, computed via minimum variance control and designed to operate with a commercial grid-tied inverter. The end result is a real-time controlled inverter that is able to reduce power disturbances created by unanticipated load changes in an electrical grid. An experimental setup is used to validate the proposed control algorithm through on/off switching of a dynamic load and the results illustrate the feasibility of the proposed controller for real-time mitigation of power flow oscillations.

关键词： Power Disturbances Disturbance rejection Power flow computer algorithms Inventors power systems Power system stability real-time feedback control Internal model principle Variance Power production dynamic loading

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The Minimum Step Linkage Algorithm and Cumulative Cost Model for Time-Dependent Shortest Paths

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TRANSACTIONS IN GIS 2016年第6期20卷 962-975页

作者： Indriasari, Vini Dean, Denis Univ Texas Dallas Geog & Geospatial Informat Sci Dallas TX USA

Real-word road networks are typically time-dependent, but research on time-dependent shortest paths (TDSPs) is not as rich as that on static shortest paths (SSPs). For large networks, some speed-up techniques are usually applied to compute SSPs. Unfortunately, many of these techniques are impractical for TDSPs, especially the techniques requiring a precomputation because the number of time instances may be incredibly large or even infinite. Therefore, this study introduced a new TDSP technique that is able to overcome the issue of infinite time instances by utilizing network geometry alone for the pre-computation, namely the Minimum Step Linkage (MSL) algorithm. It works with a data model called Cumulative Cost Model (CCM). The theoretical concepts of the new data model and algorithm are described, and its performances were tested and compared with existing algorithms through a series of simulations.

关键词： NAVIGATION MATHEMATICAL models computer algorithms DATA modeling computer simulation MATRICES REAL-time computing

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Resilient Consensus for Time-Varying Networks of Dynamic Agents

Resilient Consensus for Time-Varying Networks of Dynamic Age...

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American Control Conference

作者： David Saldana Amanda Prorok Shreyas Sundaram Mario F. M. Campos Vijay Kumar University of Pennsylvania Purdue University Universidade Federal de Minas Gerais

ISBN: (纸本)9781509045839

We consider networks of dynamic agents that execute cooperative, distributed control algorithms in order to coordinate themselves and to collectively achieve goals. The agents rely on consensus algorithms that are based on local interactions with their nearest neighbors in the communication graph. However, such systems are not robust to one or more malicious agents and there are no performance guarantees when one or more agents do not cooperate. Recent results in network science deal with this problem by requiring specific graph topological properties. Nevertheless, the required network topologies imply high connectivity levels, which may be difficult to achieve in systems that exhibit time-varying communication graphs. In this paper, we propose an approach that provides resilience for networks of dynamic agents whose communication graphs are time-varying. We show that in the case where the required connectivity constraints cannot be satisfied at all times, we can resort to a consensus protocol that guarantees resilience when the union of communication graphs over a bounded period of time satisfies certain robustness properties. We propose a control policy to attain resilient behavior in the context of perimeter surveillance with a team of robots. We provide simulations that support our theoretical analyses.

关键词： Time varying networks Agents control strategy Resilience computer algorithms Communication Research Network topology Nearest neighbor Network

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Reducing Controller Updates Via Event-Triggered Model Predictive Control In An Embedded Artificial Pancreas

Reducing Controller Updates Via Event-Triggered Model Predic...

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American Control Conference

作者： Ankush Chakrabarty Stamatina Zavitsanou Francis J. Doyle Eyal Dassau Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA 02138 USA

ISBN: (纸本)9781509045839

An essential component in the design of a wearable or implantable artificial pancreas is a low-power, embedded control algorithm capable of tight glucose regulation in people with Type 1 Diabetes Mellitus (T1DM). In this paper, physiological insights into glucose management are leveraged to formulate a safety-constrained, event-triggered model predictive control (MPC) algorithm customized to reduce the number of controller updates, leading to reduced processor runtime and lowered energy expenditure. The proposed event-triggered MPC is deployed on a wearable (65 mm × 30 mm × 5 mm) embedded prototyping platform running a single core 1 GHz 32-bit ARM11 processor. The efficiency of the proposed method is verified in a hardware-in-the-loop simulation study with ten subjects simulated in-silico using the United States Food and Drug Administration (US FDA) accepted UVA/Padova Metabolic Simulator. The controller is challenged with large, unannounced meals and sudden hypoglycemia. Empirical studies reveal that the proposed event-triggered MPC remains idle for 50% of the time in closed-loop, while maintaining 32 (out of 53) hours in the clinically accepted safe glucose region (70-180 mg/dL), compared to 35.5 hours for its time-triggered counterpart, with reduced time in hypoglycemia. Thus, the proposed strategy significantly reduces the number of controller updates required, without compromising safety in glycemic regulation.

关键词： Event trigger component design Artificial Pancreas Wearable Controllers Model predictive control Predictive control computer algorithms In Silico

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Remaining useful life estimation of Lithium-ion batteries based on thermal dynamics

Remaining useful life estimation of Lithium-ion batteries ba...

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American Control Conference

作者： Dong Zhang Satadru Dey Hector E. Perez Scott J. Moura Energy Controls and Applications Lab (eCAL) in Civil and Environmental Engineering University of California Berkeley 94720 USA

ISBN: (纸本)9781509045839

Longevity remains one of the key issues for Lithium-ion (Li-ion) battery technology. On-board Intelligent Battery Management Systems (BMS) implement health-conscious control algorithms in order to increase battery lifetime while maintaining the performance. For such algorithms, the information on Remaining Useful Life (RUL) of the battery is crucial for optimizing the battery performance and ensuring minimal degradation. However, accurate prediction of RUL remains one of the most challenging tasks until this date. In this paper, we present an online RUL estimation scheme for Li-ion batteries, which is designed from a thermal perspective. The key novelty lies in (i) leveraging thermal dynamics to predict RUL and, (ii) developing a hierarchical estimation algorithm with provable convergence properties. The algorithm consists of three stages working in cascade. The first two stages estimate the core temperature, State-of-Charge (SOC) and battery capacity based on a combination of thermal and Coulombic SOC model. The third stage receives this capacity information and in turn identifies a capacity fade aging model. Finally, we estimate the RUL by predicting the battery capacity fade over the cycles utilizing the identified aging model. A combination of sliding mode observers and nonlinear least-squares algorithm is utilized for designing the estimators. Simulation results illustrate the performance of the proposed RUL estimation scheme.

关键词： lithium ion battery Life estimation remaining service life Battery Capacity computer algorithms Batteries Thermal double-stage Battery Life algorithms

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Sliding mode control algorithms for wheel slip control of road vehicles

Sliding mode control algorithms for wheel slip control of ro...

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American Control Conference

作者： Gian Paolo Incremona Enrico Regolin Alessio Mosca Antonella Ferrara Dipartimento di Ingegneria Industriale e dell'Informazione University of Pavia

ISBN: (纸本)9781509045839

Sliding mode control approaches are presented in this paper for the wheel slip control of road vehicles. The major design requirement for the controllers is to make the wheel slip ratio follow a desired value, while guaranteeing that the sliding mode control is stabilizing. Its robustness in front of matched and unmatched uncertainties and data transmission delays is assessed in simulation. In the present paper different algorithms of first and second order type and integral or non integral nature are discussed. Simulation results are reported and analyzed, putting into evidence the superior performance, in the considered automotive context, of the integral sliding mode control.

关键词： Variable structure systems road vehicles Wheel slip slip control Land transportation SLIP RATIO Design Requirements computer algorithms

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Mosquito-inspired swarming for decentralized pursuit with autonomous vehicles

Mosquito-inspired swarming for decentralized pursuit with au...

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American Control Conference

作者： Daigo Shishika Derek A. Paley Department of Aerospace Engineering University of Maryland Aerospace Engineering Education in the Department of Aerospace Engineering and the Institute for Systems Research University of Maryland

ISBN: (纸本)9781509045839

Inspired by the swarming behavior of male mosquitoes that aggregate to attract and subsequently pursue a female mosquito, we study how oscillatory motion in autonomous swarming vehicles helps the success of target capture. We consider the scenario in which multiple guardians with limited perceptual range are deployed to protect an area from an aerial intruder. The intruder becomes a target once it enters the perceptual range of a guardian and, when a guardian becomes a pursuer, it speeds up and chases the target. We focus on the strategy in the swarming phase, when the intruder has not yet been perceived by any of the guardians. In the parameter space consisting of the intruder's speed and guardians' ability (i.e., maximum acceleration and perceptual range) we identify necessary and sufficient conditions for target capture. We further compare circular and radial swarming motion and its effect on successful target capture. For the application to autonomous aerial vehicles, we propose a control algorithm that achieves swarming motion while also avoiding collisions. The theoretical results are demonstrated by experiments with a swarm of quadrotors.

关键词： Legal Guardians TARGET ACQUISITION Autonomous Vehicles Intruder Swarming Targets parameter space methods computer algorithms Swarming behavior maximum acceleration oscillating movements dike swarms

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Robust point-to-point control with velocity limitation

Robust point-to-point control with velocity limitation

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International Conference on Process Control (PC)

作者： Ján Kardoš Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovak Republic

ISBN: (纸本)9781538640128

In this contribution, the original modification of a special kind of robust point-to-point (fixed target) motion control with the intentional limitation of maximal velocity is presented. Theoretical background of the provided control algorithm is given by the variable structure control theory yielding the fast and accurate time sub-optimal control. This ensures the desired quality and integrity of the motion control despite the presence of significant parametric and signal disturbances. Simulation results show the reliability of the presented control method.

关键词： motion control optimal control robust control variable structure systems Motor Control Variable structure systems Robust control Optimal control point-to-point control Control Methods Variable structure control computer algorithms

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Time-average constraints in stochastic Model Predictive Control

Time-average constraints in stochastic Model Predictive Cont...

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American Control Conference

作者： James Fleming Mark Cannon the Engineering Science Unit University of Southampton S017 1BJ UK the Department of Engineering Science University of Oxford OX1 3PJ UK

ISBN: (纸本)9781509045839

This paper presents two alternatives to using chance constraints in stochastic MPC, motivated by the observation that many stochastic constrained control algorithms aim to impose a bound on the time-average of constraint violations. We consider imposing a robust constraint on the time-average of constraint violations over a finite period. By allowing the controller to respond to the effects of past violations, two algorithms are presented that solve this problem, both requiring a single convex optimization after a preprocessing step. Stochastic MPC formulations that 'remember' previous violations and react accordingly were given previously in [1], [2], but in those works the focus was on asymptotic guarantees on the average number of violations. In contrast we give stronger robust bounds on the violation permissible in any time period of a specified length. The method is also applied to a bound on the sum of convex loss functions of the amount of constraint violation, thus allowing controllers to place greater importance on avoiding large violations.

关键词： amount constraint violation average time Constraint computer algorithms Predictive control Maximum Allowable Concentration Stochastic models Bound Stochastic

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