CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data.

Transcriptomic analysis across species is increasingly used to reveal conserved gene regulations which implicate crucial regulators. Cross-species analysis of single-cell RNA sequencing (scRNA-seq) data provides new opportunities to identify the cellular and molecular conservations, especially for cell types and cell type-specific gene regulations. However, few methods have been developed to analyze cross-species scRNA-seq data to uncover both molecular and cellular conservations. Here, we built a tool called CACIMAR, which can perform cross-species analysis of cell identities, markers, regulations, and interactions using scRNA-seq profiles. Based on the weighted sum models of the conserved features, we developed different conservation scores to measure the conservation of cell types, regulatory networks, and intercellular interactions. Using publicly available scRNA-seq data on retinal regeneration in mice, zebrafish, and chick, we demonstrated four main functions of CACIMAR. First, CACIMAR allows to identify conserved cell types even in evolutionarily distant species. Second, the tool facilitates the identification of evolutionarily conserved or species-specific marker genes. Third, CACIMAR enables the identification of conserved intracellular regulations, including cell type-specific regulatory subnetworks and regulators. Lastly, CACIMAR provides a unique feature for identifying conserved intercellular interactions. Overall, CACIMAR facilitates the identification of evolutionarily conserved cell types, marker genes, intracellular regulations, and intercellular interactions, providing insights into the cellular and molecular mechanisms of species evolution.

IReNA: Integrated regulatory network analysis of single-cell transcriptomes and chromatin accessibility profiles.

Recently, single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) have been developed to separately measure transcriptomes and chromatin accessibility profiles at the single-cell resolution. However, few methods can reliably integrate these data to perform regulatory network analysis. Here, we developed integrated regulatory network analysis (IReNA) for network inference through the integrated analysis of scRNA-seq and scATAC-seq data, network modularization, transcription factor enrichment, and construction of simplified intermodular regulatory networks. Using public datasets, we showed that integrated network analysis of scRNA-seq data with scATAC-seq data is more precise to identify known regulators than scRNA-seq data analysis alone. Moreover, IReNA outperformed currently available methods in identifying known regulators. IReNA facilitates the systems-level understanding of biological regulatory mechanisms and is available at https://github.com/jiang-junyao/IReNA.

Comparative Analysis of the Chloroplast Genome of Cardamine hupingshanensis and Phylogenetic Study of Cardamine.

Cardamine hupingshanensis (K. M. Liu, L. B. Chen, H. F. Bai and L. H. Liu) is a perennial herbal species endemic to China with narrow distribution. It is known as an important plant for investigating the metabolism of selenium in plants because of its ability to accumulate selenium. However, the phylogenetic position of this particular species in Cardamine remains unclear. In this study, we reported the chloroplast genome (cp genome) for the species C. hupingshanensis and analyzed its position within Cardamine. The cp genome of C. hupingshanensis is 155,226 bp in length and exhibits a typical quadripartite structure: one large single copy region (LSC, 84,287 bp), one small single copy region (17,943 bp) and a pair of inverted repeat regions (IRs, 26,498 bp). Guanine-Cytosine (GC) content makes up 36.3% of the total content. The cp genome contains 111 unique genes, including 78 protein-coding genes, 29 tRNA genes and 4 rRNA genes. A total of 115 simple sequences repeats (SSRs) and 49 long repeats were identified in the genome. Comparative analyses among 17 Cardamine species identified the five most variable regions (trnH-GUG-psbA, ndhK-ndhC, trnW-CCA-trnP-UGG, rps11-rpl36 and rpl32-trnL-UAG), which could be used as molecular markers for the classification and phylogenetic analyses of various Cardamine species. Phylogenetic analyses based on 79 protein coding genes revealed that the species C. hupingshanensis is more closely related to the species C. circaeoides. This relationship is supported by their shared morphological characteristics.

The complete chloroplast genome of Strobilanthes biocullata (Acanthaceae).

Strobilanthes biocullata is a plietesial species endemic to China. The complete chloroplast genome (cp genome) of S. biocullata was sequenced for the first time. The cp genome of S. biocullata is 144,012 bp in length. It consists of a large single copy (LSC) region (91,628 bp) and a small single copy (SSC) region (17,666 bp), which are separated by two inverted repeats (IRs, 34,718 bp). It contains 114 unique genes, including 80 protein-coding genes, 30 tRNA genes, and four rRNA genes. The overall GC content is 38.2%. Phylogenetic analysis of 13 species has been conducted. This newly sequenced cp genome will be useful to further genetic diversity, phylogeny, and genomic studies of the genus Strobilanthes.

Trajectory Generation by Chance-Constrained Nonlinear MPC With Probabilistic Prediction.

Continued great efforts have been dedicated toward high-quality trajectory generation based on optimization methods; however, most of them do not suitably and effectively consider the situation with moving obstacles; and more particularly, the future position of these moving obstacles in the presence of uncertainty within some possible prescribed prediction horizon. To cater to this rather major shortcoming, this work shows how a variational Bayesian Gaussian mixture model (vBGMM) framework can be employed to predict the future trajectory of moving obstacles; and then with this methodology, a trajectory generation framework is proposed which will efficiently and effectively address trajectory generation in the presence of moving obstacles, and incorporate the presence of uncertainty within a prediction horizon. In this work, the full predictive conditional probability density function (PDF) with mean and covariance is obtained and, thus, a future trajectory with uncertainty is formulated as a collision region represented by a confidence ellipsoid. To avoid the collision region, chance constraints are imposed to restrict the collision probability, and subsequently, a nonlinear model predictive control problem is constructed with these chance constraints. It is shown that the proposed approach is able to predict the future position of the moving obstacles effectively; and, thus, based on the environmental information of the probabilistic prediction, it is also shown that the timing of collision avoidance can be earlier than the method without prediction. The tracking error and distance to obstacles of the trajectory with prediction are smaller compared with the method without prediction.

Comparative analysis of chloroplast genomes for five Dicliptera species (Acanthaceae): molecular structure, phylogenetic relationships, and adaptive evolution.

The genus Dicliptera (Justicieae, Acanthaceae) consists of approximately 150 species distributed throughout the tropical and subtropical regions of the world. Newly obtained chloroplast genomes (cp genomes) are reported for five species of Dilciptera (D. acuminata, D. peruviana, D. montana, D. ruiziana and D. mucronata) in this study. These cp genomes have circular structures of 150,689-150,811 bp and exhibit quadripartite organizations made up of a large single copy region (LSC, 82,796-82,919 bp), a small single copy region (SSC, 17,084-17,092 bp), and a pair of inverted repeat regions (IRs, 25,401-25,408 bp). Guanine-Cytosine (GC) content makes up 37.9%-38.0% of the total content. The complete cp genomes contain 114 unique genes, including 80 protein-coding genes, 30 transfer RNA (tRNA) genes, and four ribosomal RNA (rRNA) genes. Comparative analyses of nucleotide variability (Pi) reveal the five most variable regions (trnY-GUA-trnE-UUC, trnG-GCC, psbZ-trnG-GCC, petN-psbM, and rps4-trnL-UUA), which may be used as molecular markers in future taxonomic identification and phylogenetic analyses of Dicliptera. A total of 55-58 simple sequence repeats (SSRs) and 229 long repeats were identified in the cp genomes of the five Dicliptera species. Phylogenetic analysis identified a close relationship between D. ruiziana and D. montana, followed by D. acuminata, D. peruviana, and D. mucronata. Evolutionary analysis of orthologous protein-coding genes within the family Acanthaceae revealed only one gene, ycf15, to be under positive selection, which may contribute to future studies of its adaptive evolution. The completed genomes are useful for future research on species identification, phylogenetic relationships, and the adaptive evolution of the Dicliptera species.

The complete chloroplast genome of Rungia pectinata (Acanthaceae).

Rungia pectinata is an important traditional Chinese herbal medicine from the family Acanthaceae. The complete chloroplast genome (cp genome) of the genus Rungia was sequenced for the first time. The cp genome of R. pectinata was 149,627 bp in length. It was consisted of a large single copy (LSC) region (81,976 bp) and a small single copy (SSC) region (16,626 bp), which were separated by two inverted repeats (IRs, 25,511 bp). This plastome contained 114 unique genes, including 80 protein-coding genes, 30 tRNA genes, and four rRNA genes. The overall GC content was 38.0%. Phylogenetic analysis of nine species in Acanthaceae was also conducted. This newly sequenced cp genome will be useful to further evolutionary studies, phylogenetic studies, and pharmacognostic identification in the genus Rungia.

Force estimation and failure detection based on disturbance observer for an ear surgical device.

The disturbance observer is one of the useful tools for estimating the contact force between the subject body and the environment in robotic and mechatronic systems. This paper introduced a novel automatic office-based ear surgical device for the treatment of Otitis Media with Effusion (OME) under the guidance of force sensing information. Since the force sensing information must be reliable so as to ensure the safety of the device, a contact force estimation method based on the disturbance observer is proposed. The system model is built and a control strategy is proposed and developed. In the control strategy, a composite motion controller for an ultrasonic motor (USM) stage is presented, and then the design and the stability analysis of an advanced disturbance observer is given. Furthermore, a contact estimator and a failure detector, aiming to enhance the safety and reliability enhancement, are designed. Finally, the proposed control strategy is studied with both simulation and experiment. The experimental results show that the advanced disturbance observer can estimate the actual contact force correctly and precisely, and the disturbance observer based force estimation and failure detection method is feasible which can be used in force sensing, contact detection and fault diagnosis.

A novel compact compliant actuator design for rehabilitation robots.

Rehabilitation robots have direct physical interaction with human body. Ideally, actuators for rehabilitation robots should be compliant, force controllable, and back drivable due to safety and control considerations. Various designs of Series Elastic Actuators (SEA) have been developed for these applications. However, current SEA designs face a common performance limitation due to the compromise on the spring stiffness selection. This paper presents a novel compact compliant force control actuator design for portable rehabilitation robots to overcome the performance limitations in current SEAs. Our design consists of a servomotor, a ball screw, a torsional spring between the motor and the ball screw, and a set of translational springs between the ball screw nut and the external load. The soft translational springs are used to handle the low force operation and reduce output impedance, stiction, and external shock load. The torsional spring, being in the high speed range, has high effective stiffness and improves the system bandwidth in large force operation when the translational springs are fully compressed. This design is also more compact due to the smaller size of the springs. We explain the construction and the working principle of our new design, followed by the dynamic modeling and analysis of the actuator. We also show the preliminary testing results of a prototype actuator designed for a lower limb exoskeleton for gait rehabilitation.

SVD-based Preisach hysteresis identification and composite control of piezo actuators.

In this paper, the singular value decomposition (SVD) based identification and compensation of the hysteretic phenomenon in piezo actuators are addressed using a Preisach model. First, this paper presents an SVD-based least squares algorithm and a revision approach of the identification through updating the SVD. With the identified parameters and a log of the memory curve, a Preisach-based inversion compensator is constructed which is complemented with a feedback controller to address the inevitable and residual modeling errors. Experimental results are furnished for both the identification and compensation approaches. The Preisach-based feedforward controller significantly improves the tracking performance and reduces the root-mean-square (RMS) tracking error of a PID controller by 76.7% and 89% at 1 Hz and 25 Hz, respectively. With the proposed composite controller, the percent-RMS errors at 1 Hz and 25 Hz are reduced to 0.035% and 0.31%, respectively.

Optimization of a reversible hood for protecting a pedestrian's head during car collisions.

This study evaluated and optimized the performance of a reversible hood (RH) for the prevention of the head injuries of an adult pedestrian from car collisions. The FE model of a production car front was introduced and validated. The baseline RH was developed from the original hood in the validated car front model. In order to evaluate the protective performance of the baseline RH, the FE models of an adult headform and a 50th percentile human head were used in parallel to impact the baseline RH. Based on the evaluation, the response surface method was applied to optimize the RH in terms of the material stiffness, lifting speed, and lifted height. Finally, the headform model and the human head model were again used to evaluate the protective performance of the optimized RH. It was found that the lifted baseline RH can obviously reduce the impact responses of the headform model and the human head model by comparing with the retracted and lifting baseline RH. When the optimized RH was lifted, the HIC values of the headform model and the human head model were further reduced to much lower than 1000. The risk of pedestrian head injuries can be prevented as required by EEVC WG17.

Microdispensing system via the contacting method.

This paper presents the development of a microdispensing system based on a contacting method, with an aim to lowering production and maintenance cost. The liquid, to be dispensed, is brought into contact with the work piece, thus dispensing a droplet by making use of the adhesion force between the liquid and the work piece. A piezoelectric actuator is employed as the drive for the system to achieve high precision. The control of the system is accomplished with a PID controller; controlling the dispensing process and trajectory tracking.

Decoupled tracking and thermal monitoring of non-stationary targets.

Fault diagnosis and predictive maintenance address pertinent economic issues relating to production systems as an efficient technique can continuously monitor key health parameters and trigger alerts when critical changes in these variables are detected, before they lead to system failures and production shutdowns. In this paper, we present a decoupled tracking and thermal monitoring system which can be used on non-stationary targets of closed systems such as machine tools. There are three main contributions from the paper. First, a vision component is developed to track moving targets under a monitor. Image processing techniques are used to resolve the target location to be tracked. Thus, the system is decoupled and applicable to closed systems without the need for a physical integration. Second, an infrared temperature sensor with a built-in laser for locating the measurement spot is deployed for non-contact temperature measurement of the moving target. Third, a predictive motion control system holds the thermal sensor and follows the moving target efficiently to enable continuous temperature measurement and monitoring.

Fault detection and diagnosis based on modeling and estimation methods.

This paper investigates the problem of fault detection and diagnosis in a class of nonlinear systems with modeling uncertainties. A nonlinear observer is first designed for monitoring fault. Radial basis function (RBF) neural network is used in this observer to approximate the unknown nonlinear dynamics. When a fault occurs, another RBF is triggered to capture the nonlinear characteristics of the fault function. The fault model obtained by the second neural network (NN) can be used for identifying the failure mode by comparing it with any known failure modes. Finally, a simulation example is presented to illustrate the effectiveness of the proposed scheme.

Geometrical error compensation of machines with significant random errors.

In this paper, we present a new statistical approach towards soft geometrical error compensation of machines with significant errors. The approach, based on an analysis of the probability of the random error recurring, can reduce the adverse influence of random errors on the compensation of systematic errors. The proposed methodology is made up of three steps. First, error classes are defined from the error bands obtained from calibration. Second, the probability of the magnitude of random error belonging to each of these classes is computed based on the density of the data set within the class. Based on these probabilities, the most probable systematic part of the error measurement can be statistically deduced. Finally, the geometrical error compensation is carried out based on this value. Experimental results are provided for the linear error compensation of a single-axis piezo-ceramic motion system.