Interior Loops Research Articles

Periodic orbits of the perturbed relative motion

This paper presents a novel dynamical system for the perturbed relative motion of deputy satellite. The governing equations are derived in the LVLH frame under the second zonal harmonic coefficient effect of the Earth on both chief and deputy satellites. An extended numerical analysis on the deputy satellite motion is performed, where the initial state vector of deputy satellite and eccentricity of chief satellite are used as initial conditions for finding its own periodic orbits. The interior loops of periodic orbits are obtained using numerical integrator RKEOM. Such orbits are analysed for different parameters and their stability are also discussed, where these orbits have considerable importance in the resonance analysis of motion The second zonal harmonic coefficient effect on the periodicity, initial position, initial true anomaly is studied, alongside exploring these orbits with one, two and three loops. Furthermore, a single variable nonlinear regression model is developed to predict initial true anomaly using eccentricity of chief satellite’s orbit.

RNA Secondary Structures with Given Motif Specification: Combinatorics and Algorithms.

The study of native motifs of RNA secondary structures helps us better understand the formation and eventually the functions of these molecules. Commonly known structural motifs include helices, hairpin loops, bulges, interior loops, exterior loops and multiloops. However, enumerative results and generating algorithms taking into account the joint distribution of these motifs are sparse. In this paper, we present progress on deriving such distributions employing a tree-bijection of RNA secondary structures obtained by Schmitt and Waterman and a novel rake decomposition of plane trees. The key feature of the latter is that the derived components encode motifs of the RNA secondary structures without pseudoknots associated with the plane trees very well. As an application, we present an algorithm (RakeSamp) generating uniformly random secondary structures without pseudoknots that satisfy fine motif specifications on the length and degree of various types of loops as well as helices.

Kalman filter and classical Preisach hysteresis model applied to the state of charge battery estimation

The goal of this work is first to include a hysteresis model in the classical equivalent circuit model (ECM) for a battery system and then to improve the estimation of the state of charge (SoC) by applying the Extended Kalman Filter (EKF). The hysteretic behavior of the open circuit voltage (OCV) is modelled with the classical Preisach model used for magnetic materials. The construction of the Preisach operator is made by means of the Everett function identified from experimental data which only involve the charging curves of the battery. Thus, a significant reduction in the time necessary to obtain the measurements is achieved. The model is assessed with some laboratory experiments performed on a lithium-ion battery and the results show that with this procedure hysteresis is very well reproduced, even when interior loops are present. In addition, the use of the EKF allows us to eliminate the measurements noise and ensure the accuracy of SoC estimation. The high computational efficiency and precision of the method, joined to the limited computational resources needed for the numerical implementation, make it particularly suitable for real-time embedded battery management system (BMS) applications. In addition, the proposed methodology is well-adapted to any battery type, independently of the SoC-OCV profile of the hysteresis cycle.

Fast terminal sliding mode control design for position control of induction motors using adaptive quantum neural networks

In this work, an efficient robust control scheme is proposed for position control of induction motors based on field-oriented control (FOC). The proposed control scheme consists of three interior loops. In the outer loop, the central controller based on the nonsingular fast terminal sliding mode control (NFTSM) is designed. The objective of this loop is to provide the required stator current in the q-axis for regulating the electromagnetic torque. In the inner loops, two fractional-order PI (FOPI) controllers are designed to provide the stator voltages. Besides, since induction motors have a complex mathematical model, time-varying dynamics, and non-linear structure, to deal with these challenges in the controller design, the quantum neural network (QNN) is presented with a novel framework and employed to estimate the lumped uncertainties. This makes the main contribution of the paper. In addition, to further improve system performance, the parameters of the FOPI controllers are tuned by employing the artificial bee colony (ABC) optimization algorithm. The stability of the proposed control approach is proved by Lyapunov’s stability theory. According to the results of the comparative simulation, the superiority of this approach is confirmed.

Competition-Enhanced Ligand Selection to Screen for DNA Aptamers for Spherical Gold Nanoparticles.

The Competition-Enhanced Ligand Selection (CompELS) approach was used to identify aptamer candidates for spherical gold nanoparticles (AuNPs). This approach differs from conventional Systematic Evolution of Ligands by EXponential enrichment (SELEX)-based aptamer screening by eliminating repeated elution and polymerase chain reaction (PCR) amplification steps of bound candidate sequences between each selection round to continually enrich the candidate aptamer pool with oligonucleotides remaining from an earlier SELEX selection round. Instead, a new pool of unenriched oligonucleotides is added during each CompELS selection round to compete with existing target-bound oligonucleotides species for target binding sites. In this study, 24 aptamer candidates for AuNPs were identified using the CompELS approach and then compared to reveal similarities in their primary structures and their predicted secondary structures. No strong patterns in individual base identities (position-dependent) nor in segments of consecutive bases (independent of position) prevailed among the identified sequences. Motifs in predicted secondary structures, on the other hand, were shared among otherwise unrelated aptamer sequences. These motifs were revealed using a systematic classification and enumeration of distinct secondary structure elements, namely, hairpins, duplexes, single-stranded segments, interior loops, bulges, and multibranched loops.

Robust force and displacement control of an active landing gear for vibration reduction at touchdown and during taxiing

In this paper, a new approach is proposed to control the dynamic response of a landing gear system subjected to runway force, both on heavy landing conditions and at the taxiing process. The mathematical model of the system is used in a way that covers nonlinear dynamics characteristics of landing gear and nonlinear/nonaffine property of the external actuator. The operation of the landing gear system and its components are described briefly. The desired control system includes two different interior loops for displacement and force control. The inner loop determines the actuator force and the outer loop performs the displacement control. A lumped uncertainty is considered in both displacement and force control loops that represent uncertainties including parametric errors, measurement noises, unmodeled dynamics, disturbance due to runway excitation, and other disturbances. The direct method of Lyapunov is utilized for asymptotic stability analysis of the robust nonlinear control system (RNCS). This system is simulated in MATLAB software and the performance of the proposed controller is analyzed exactly. Besides, the results are compared with a passive system and conventional PID control. The comparison indicates that RNCS works better and more precisely. This method can reduce vibrations at touchdown and taxiing and effectively overcome uncertainty and provide well aircraft handling by decreasing the changes in tire force.

A novel riboswitch classification based on imbalanced sequences achieved by machine learning.

Riboswitch, a part of regulatory mRNA (50–250nt in length), has two main classes: aptamer and expression platform. One of the main challenges raised during the classification of riboswitch is imbalanced data. That is a circumstance in which the records of a sequences of one group are very small compared to the others. Such circumstances lead classifier to ignore minority group and emphasize on majority ones, which results in a skewed classification. We considered sixteen riboswitch families, to be in accord with recent riboswitch classification work, that contain imbalanced sequences. The sequences were split into training and test set using a newly developed pipeline. From 5460 k-mers (k value 1 to 6) produced, 156 features were calculated based on CfsSubsetEval and BestFirst function found in WEKA 3.8. Statistically tested result was significantly difference between balanced and imbalanced sequences (p < 0.05). Besides, each algorithm also showed a significant difference in sensitivity, specificity, accuracy, and macro F-score when used in both groups (p < 0.05). Several k-mers clustered from heat map were discovered to have biological functions and motifs at the different positions like interior loops, terminal loops and helices. They were validated to have a biological function and some are riboswitch motifs. The analysis has discovered the importance of solving the challenges of majority bias analysis and overfitting. Presented results were generalized evaluation of both balanced and imbalanced models, which implies their ability of classifying, to classify novel riboswitches. The Python source code is available at https://github.com/Seasonsling/riboswitch.

Impedance fuzzy control of an active aircraft landing gear system

In this paper, a new approach is proposed to control the dynamic behavior of a landing gear system for providing the passenger comfort and aircraft handling subject to the runway disturbances. The proposed control system includes three interior loops. The inner loop is responsible for controlling actuator force by a PI controller, the middle loop controls the body position by a PD-like fuzzy controller and the outer loop is the impedance control loop. The novelty of control system is the use of impedance rule in determining the reference body position. The impedance rule has been considered as a linear second order system that is able to provide a suitable trade-off between two objectives: passenger comfort and aircraft handling. The impedance control provides a suitable dynamic behavior for the landing gear in wide range of runway conditions including a bumpy or flat ground. Performance of the control system is evaluated and compared with passive system using computer simulation. The results illustrate that impedance control is successful in decreasing the vibrations and improving both passenger comfort and aircraft handling.

An effective sequence structure representation for long non-coding RNA identification and cancer association using machine learning methods

The invent of high-throughput technologies and consequent developments in Bioinformatics research unveiled many important non-coding transcript molecules such as Long non-coding RNAs (lncRNAs). The available studies confirmed that lncRNAs play important genetic and epigenetic roles in higher-order species like the human and their differential expressions leads to complex diseases like cancer. Even though there are arrays of studies and related tools for the analysis, less conserved patterns in the sequences and intractable structural properties challenge the understanding of varying functionalities of lncRNAs. For the better approximation of these characteristics, higher quality feature representation is required. This paper proposes an extended hybrid sequence-structure feature set for machine learning based lncRNA analysis. Here, the sequence features are derived from various frequencies of k -mer patterns, GC content and molecular weight. The structure representations consider the context of different secondary structure elements which include stems, interior loops, multi-loops and hairpin loops. These features are used for the classification of lncRNA/mRNA and cancerous/non-cancerous lncRNAs. The classifications use machine learning algorithms such as LDA based topic model, Random Forest, SVM and Naïve Bayes. The results show that the proposed feature set is effective in classifying lncRNAs and provide a direction towards the analysis of the role of secondary structure elements in cancer-related lncRNAs.

Direct adaptive fuzzy control of flexible-joint robots including actuator dynamics using particle swarm optimization

In this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. The design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a PID control law. One novelty of this paper is the use of a PSO algorithm for optimizing the control design parameters to achieve a desired performance. It is worthy of note that to form control law by considering practical considerations just the available feedbacks are used. It is beneficial for industrial applications wherethe real-time computation is costly. The proposed control approach has a fast response with a good tracking performance under the well-behaved control efforts. The stability is guaranteed in the presence of both structured and unstructured uncertainties. As a result, all system states are remained bounded. Simulation results on a two-link flexible-joint robot show the efficiency of the proposed scheme.

Using in-cell SHAPE-Seq and simulations to probe structure-function design principles of RNA transcriptional regulators.

Antisense RNA-mediated transcriptional regulators are powerful tools for controlling gene expression and creating synthetic gene networks. RNA transcriptional repressors derived from natural mechanisms called attenuators are particularly versatile, though their mechanistic complexity has made them difficult to engineer. Here we identify a new structure–function design principle for attenuators that enables the forward engineering of new RNA transcriptional repressors. Using in-cell SHAPE-Seq to characterize the structures of attenuator variants within Escherichia coli, we show that attenuator hairpins that facilitate interaction with antisense RNAs require interior loops for proper function. Molecular dynamics simulations of these attenuator variants suggest these interior loops impart structural flexibility. We further observe hairpin flexibility in the cellular structures of natural RNA mechanisms that use antisense RNA interactions to repress translation, confirming earlier results from in vitro studies. Finally, we design new transcriptional attenuators in silico using an interior loop as a structural requirement and show that they function as desired in vivo. This work establishes interior loops as an important structural element for designing synthetic RNA gene regulators. We anticipate that the coupling of experimental measurement of cellular RNA structure and function with computational modeling will enable rapid discovery of structure–function design principles for a diverse array of natural and synthetic RNA regulators.

Adaptive type-2 fuzzy estimation of uncertainties in the control of electrically driven flexible-joint robots

This paper presents a novel decentralized tracking control system of electrically driven flexible-joint robots by adaptive type-2 fuzzy estimation and compensation of uncertainties. Owing to using voltage control strategy, the proposed control approach has important advantages over the torque control approaches in terms of being free from manipulator dynamics, computationally simple and decoupled. The design includes two interior loops: the inner loop controls the motor position while the outer loop controls the joint angle of the robot. An adaptive proportional–integral–derivative controller governs the outer loop, whereas a robust nonlinear controller supported by estimation of uncertainty is employed for the inner loop. More specifically, the main contribution of the paper arises from this fact that the proposed control method uses the interval Type-2 Fuzzy Logic systems for estimation of uncertainty. This is the main difference between this paper and those published in literature. One advantage of the proposed approach is that it uses available feedbacks as an important advantage from a practical point of view. The method is verified by stability analysis and its effectiveness is demonstrated by simulations. The direct method of Lyapunov is utilized for stability analysis of the proposed approach. The case of study is the tracking control of a three-joint articulated flexible-joint robot driven by permanent magnet DC motors. Simulation results show the superior robustness of the type-2 fuzzy system to Type-1 fuzzy system.

Combinatorics of RNA Secondary Structures with Base Triples.

The structure of RNA has been the subject of intense research over the last decades due to its importance for the correct functioning of RNA molecules in biological processes. Hence, a large number of models for RNA folding and corresponding algorithms for structure prediction have been developed. However, previous models often only consider base pairs, although every base is capable of up to three edge-to-edge interactions with other bases. Recently, Höner zu Siederdissen et al. presented an extended model of RNA secondary structure, including base triples together with a folding algorithm-the first thermodynamics-based algorithm that allows the prediction of secondary structures with base triples. In this article, we investigate the search space processed by this new algorithm, that is, the combinatorics of extended RNA secondary structures with base triples. We present generalized definitions for structural motifs like hairpins, stems, bulges, or interior loops occurring in structures with base triples. Furthermore, we prove precise asymptotic results for the number of different structures (size of search space) and expectations for various parameters associated with structural motifs (typical shape of folding). Our analysis shows that the asymptotic number of secondary structures of size n increases exponentially to [Formula: see text] compared to the classic model by Stein and Waterman for which [Formula: see text] structures exist. A comparison with the classic model reveals large deviations in the expected structural appearance, too. The inclusion of base triples constitutes a significant refinement of the combinatorial model of RNA secondary structure, which, by our findings, is quantitatively characterized. Our results are of special theoretical interest, because a closer look at the numbers involved suggests that extended RNA secondary structures constitute a new combinatorial class not bijective with any other combinatorial objects studied so far.

Interval type-2 fuzzy-neural network indirect adaptive sliding mode control for an active suspension system

This paper presents a novel interval type-2 fuzzy-neural network indirect adaptive sliding mode control (SMC) approach (T2FNNAS) for a suspension system including actuator dynamics. It is equipped with a novel moving sliding surface in which the slope and intercept of sliding surface are simultaneity adjusted by adaptive interval T2FNN to improve controller robustness against system uncertainties and unknown disturbances. As a result, the drawbacks of the conventional SMC, such as chattering effect and a required priori knowledge of the bounds of uncertainties, are removed. Based on the Lyapunov synthesis approach, the free parameters of the adaptive FNN are tuned on-line. One advantage of the proposed approach is that, by incorporating the Lyapunov design approach and SMC method into the adaptive fuzzy-neural control scheme to derive the control law, the proposed approach not only assures closed-loop stability but also achieves a good performance for the overall system. Another advantage of the proposed method is that to relax the requirement for the bound of approximation error, and an estimation mechanism is also employed to observe the bound of it real time. Design of the control system consists of two interior loops. The inner loop is a force control of the hydraulic actuator, while the outer loop is position controller that use T2FNNAS. Finally, a comparison between the proposed approach and a robust model reference adaptive control approach is provided. Simulation results confirm that the proposed approach effectively improves both the passenger comfort and the ride quality of the car.

Adaptive impedance control of a hydraulic suspension system using particle swarm optimisation

This paper presents a novel active control approach for a hydraulic suspension system subject to road disturbances. A novel impedance model is used as a model reference in a particular robust adaptive control which is applied for the first time to the hydraulic suspension system. A scheme is introduced for selecting the impedance parameters. The impedance model prescribes a desired behaviour of the active suspension system in a wide range of different road conditions. Moreover, performance of the control system is improved by applying a particle swarm optimisation algorithm for optimising control design parameters. Design of the control system consists of two interior loops. The inner loop is a force control of the hydraulic actuator, while the outer loop is a robust model reference adaptive control (MRAC). This type of MRAC has been applied for uncertain linear systems. As another novelty, despite nonlinearity of the hydraulic actuator, the suspension system and the force loop together are presented as an uncertain linear system to the MRAC. The proposed control method is simulated on a quarter-car model. Simulation results show effectiveness of the method.

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.

Large-scale analysis of structural, sequence and thermodynamic characteristics of A-to-I RNA editing sites in human Alu repeats

BackgroundAlu repeats in the human transcriptome undergo massive adenosine to inosine RNA editing. This process is selective, as editing efficiency varies greatly among different adenosines. Several studies have identified weak sequence motifs characterizing the editing sites, but these alone do not account for the large diversity observed.ResultsHere we build a dataset of 29,971 editing sites and use it to characterize editing preferences. We focus on structural aspects, studying the double-stranded RNA structure of the Alu repeats, and show the editing frequency of a given site to depend strongly on the micro-structure it resides in. Surprisingly, we find that interior loops, and especially the nucleotides at their edges, are more likely to be edited than helices. In addition, the sequence motifs characterizing editing sites vary with the micro-structure. Finally, we show that thermodynamic stability of the site is important for its editing.ConclusionsAnalysis of a large dataset of editing events reveals more information on sequence and structural motifs characterizing the A-to-I editing process

Impedance control of an active suspension system

A novel control system is developed to control dynamic behavior of a vehicle subject to road disturbances. The novelty of this paper is to apply the impedance control on an active vehicle suspension system operated by a hydraulic actuator. A relation between the passenger comfort and vehicle handling is derived using the impedance parameters. The impedance control law is simple, free of model and can be applied for a broad range of road conditions including a flat road. Impedance control is achieved through two interior loops which are force control of the actuator by feedback linearization and fuzzy control loop to track a desired body displacement provided by the impedance rule. The system stability is analyzed. A quarter-car model of suspension system and a nonlinear model of hydraulic actuator are used to simulate the control system.

Molecular basis of gene regulation by the THI‐box riboswitch

Riboswitches are genetic control elements located mainly within the 5' untranslated regions of messenger RNAs. These RNA elements undergo conformational changes that modulate gene expression upon binding of regulatory signals including vitamins, amino acids, nucleobases and uncharged tRNA. The thiamin pyrophosphate (TPP)-binding riboswitch (THI-box) is found in all three kingdoms of life and can regulate gene expression at the levels of premature termination of transcription, initiation of translation and mRNA splicing. The THI-box is composed of two parallel stacked helices bound by another helix in a three-way junction. We performed an in vivo expression analysis of mutants with substitutions in conserved bases located at the interior and terminal loops of the Escherichia coli thiM THI-box, which is translationally regulated, and observed two different phenotypic classes. One class exhibited high expression during growth in the presence or absence of thiamin, while the second class exhibited low expression regardless of the presence of thiamin. Accessibility of the Shine-Dalgarno region of the RNA following the addition of TPP was monitored by means of an oligonucleotide-dependent RNase H cleavage assay, and binding of 30S ribosomal subunits. These studies showed that high- and low-expression mutant RNAs are locked in the non-repressive and repressive conformations respectively.

Kinetics of Internal-Loop Formation in Polypeptide Chains: A Simulation Study

The speed of simple diffusional motions, such as the formation of loops in the polypeptide chain, places one physical limit on the speed of protein folding. Many experimental studies have explored the kinetics of formation of end-to-end loops in polypeptide chains; however, protein folding more often requires the formation of contacts between interior points on the chain. One expects that, for loops of fixed contour length, interior loops will form more slowly than end-to-end loops, owing to the additional excluded volume associated with the “tails”. We estimate the magnitude of this effect by generating ensembles of randomly coiled, freely jointed chains, and then using the theory of Szabo, Schulten, and Schulten to calculate the corresponding contact formation rates for these ensembles. Adding just a few residues, to convert an end-to-end loop to an internal loop, sharply decreases the contact rate. Surprisingly, the relative change in rate increases for a longer loop; sufficiently long tails, however, actually reverse the effect and accelerate loop formation slightly. Our results show that excluded volume effects in real, full-length polypeptides may cause the rates of loop formation during folding to depart significantly from the values derived from recent loop-formation experiments on short peptides.