Adaptive Neuro-fuzzy Inference System Trained for Sizing Semi-elliptical Notches Scanned by Eddy Currents.

The present study explores the capability of COMSOL Multiphysics, as a finite element modelling (FEM) tool, to model the interaction between a split-D differential surface eddy current (ECT) probe and semi-elliptical surface electrical discharge machined (EDM) notches. The effect of the small probe's lift-off and tilt on its signal is investigated through modelling and subsequently, the simulation outcomes are validated using the probe's impedance measurements. In the next stage, an adaptive neuro-fuzzy inference system (ANFIS) is designed to take the signal features as inputs and consequently, provide the length of the scanned notch as the system's output. The system is trained by extracted features of thirty model-generated signals obtained from scanning of the same number of semi-elliptical notches by means of the split-D probe. The trained ANFIS is tested afterwards using the measured signals of 3 calibration EDM notches together with 5 model-based ones. A very low average estimation error is observed with regard to the length estimation of the test notches and the accuracy of the length estimation is found to be quite reasonable.

Characterisation of the bacterial community structures in the intestine of Lampetra morii.

The metagenomic analysis and 16S rDNA sequencing method were used to investigate the bacterial community in the intestines of Lampetra morii. The bacterial community structure in L. morii intestine was relatively simple. Eight different operational taxonomic units were observed. Chitinophagaceae_unclassified (26.5 %) and Aeromonas spp. (69.6 %) were detected as dominant members at the genus level. The non-dominant genera were as follows: Acinetobacter spp. (1.4 %), Candidatus Bacilloplasma (2.5 %), Enterobacteria spp. (1.5 %), Shewanella spp. (0.04 %), Vibrio spp. (0.09 %), and Yersinia spp. (1.8 %). The Shannon-Wiener (H) and Simpson (1-D) indexes were 0.782339 and 0.5546, respectively. The rarefaction curve representing the bacterial community richness and Shannon-Wiener curve representing the bacterial community diversity reached asymptote, which indicated that the sequence depth were sufficient to represent the majority of species richness and bacterial community diversity. The number of Aeromonas in lamprey intestine was two times higher after stimulation by lipopolysaccharide than PBS. This study provides data for understanding the bacterial community harboured in lamprey intestines and exploring potential key intestinal symbiotic bacteria essential for the L. morii immune response.

A study of two confined electrons using the Woods-Saxon potential.

In this paper, we studied two electrons confined in a quantum dot with the Woods-Saxon potential by using the method of numerical diagonalization of the Hamiltonian matrix within the effective-mass approximation. The great advantage of our methodology is that it enables confinement regimes by varying two parameters in the model potential. A ground-state behavior (singlet [Formula: see text] triplet state transitions) as a function of the strength of a magnetic field has been investigated. We found that the confinement barrier size and the barrier inclination of a Woods-Saxon potential are important for the singlet-triplet oscillation of a two-electron quantum dot. Based on the computed energies and wavefunctions, the linear and nonlinear optical absorption coefficients have been examined between the (1)S state (L = 0) and the (1)P state (L = 1). The results are presented as a function of the incident photon energy for the different values of the barrier size and height. It is found that the optical properties of the two-electron system in a quantum dot are strongly affected by the barrier height and size.

Green's function method applied to the paramagnetic properties of R(1-x)X(x)MnO(3).

The magnetic properties of the isotropic manganites R(1-x)X(x)MnO(3) are studied in the paramagnetic regime using the Green's function method. The Curie-Weiss and critical temperatures, Θ and T(c), are obtained within the random phase approximation, as well as the high-temperature susceptibility. Our results are in agreement with other theoretical and experimental results.

Operation of the Collaborative Composite Manufacturing (CCM) System.

The automated tape placement and the automated fiber placement (AFP) machines provide a safer working environment and reduce the labor intensity of workers than the traditional manual fiber placement does. Thus, the production accuracy, repeatability and efficiency of composite manufacturing are significantly improved. However, the current AFP systems can only produce the composite components with large open surface or simple revolution parts, which cannot meet the growing interest in small complex or closed structures from industry. In this research, by employing a 1-degree of freedom (DoF) rotational stage, a 6-RSS parallel robot, and a 6-DoF serial robot, the dexterity of the AFP system can be significantly improved for manufacturing complex composite parts. The rotational stage mounted on the parallel robot is utilized to hold the mandrel and the serial robot carries the placement head to mimic two human hands that have enough dexterity to lay the fiber to the mandrel with complex contour. Although the CCM system increases the flexibility of composite manufacturing, it is quite time-consuming or even impossible to generate the feasible off-line path, which ensures uniform lay-up of subsequent fibers considering the constraints like singularities, collisions between the fiber placement head and mandrel, smooth fiber direction change and keeping the fiber placement head along the norm of the part's surface, etc. Moreover, due to the existing positioning error of the robots, the on-line path correction is needed. Therefore, the on-line pose correction algorithm is proposed to correct the paths of both parallel and serial robots, and to keep the relative path between the two robots unchanged through the visual feedback when the constraint or singularity problems in the off-line path planning occur. The experimental results demonstrate the designed CCM system can fulfill the movement needed for manufacturing a composite structure with Y-shape.

Diurnal Rhythms Spatially and Temporally Organize Autophagy.

Circadian rhythms are a hallmark of physiology, but how such daily rhythms organize cellular catabolism is poorly understood. Here, we used proteomics to map daily oscillations in autophagic flux in mouse liver and related these rhythms to proteasome activity. We also explored how systemic inflammation affects the temporal structure of autophagy. Our data identified a globally harmonized rhythm for basal macroautophagy, chaperone-mediated autophagy, and proteasomal activity, which concentrates liver proteolysis during the daytime. Basal autophagy rhythms could be resolved into two antiphase clusters that were distinguished by the subcellular location of targeted proteins. Inflammation induced by lipopolysaccharide reprogrammed autophagic flux away from a temporal pattern that favors cytosolic targets and toward the turnover of mitochondrial targets. Our data detail how daily biological rhythms connect the temporal, spatial, and metabolic aspects of protein catabolism.

Effect of combined ursodeoxycholic acid and glucocorticoid on the outcome of Kasai procedure: A systematic review and meta-analysis.

INTRODUCTION: Multiple studies have investigated the effect of ursodeoxycholic acid (UDCA) or glucocorticoid (GC) on the outcome of the hepatoportoenterostomy (Kasai procedure) in patients with biliary atresia (BA). However, the combined effect of these drugs (UDCA + GC) is little understood. METHODS: This meta-analysis specifically evaluated the effect of UDCA + GC after the Kasai procedure in patients with BA. A comprehensive literature search was conducted for all relevant articles in the electronic databases Medline, PubMed, Cochrane, Excerpta Medica Database (EMBASE), China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database on Disc (CBM-disc), and Vendor Information Pages (VIP). RESULTS: Eight studies with BA patients were finally included in our meta-analysis. The 8 identified studies consisted of 3 case-control, 3 cohort, and 2 randomized controlled trials (RCTs) with overall 530 subjects (144, 152, and 234 subjects, respectively). Among them, 312 patients were treated with UDCA + GC, while 218 received placebo or other intervention. The meta-analysis indicated that groups that received UDCA + GC had significantly lower rates of postoperative jaundice relative to the controls (pooled, odds ratio [OR] = 2.41; 95% confidence interval [CI] 1.44-4.04; Z = 3.34; P = .0008), while rates of cholangitis were similar (pooled, OR = 0.87; 95% CI 0.43-1.74; Z = 0.40; P = .69). CONCLUSIONS: Combined UDCA and GC intervention was superior to that of the control in accelerating the clearance of serum bilirubin in patients with BA after the Kasai procedure. However, this conclusion requires further confirmation using RCTs of high methodological quality.

Identification and Control for Singularly Perturbed Systems Using Multitime-Scale Neural Networks.

Many well-established singular perturbation theories for singularly perturbed systems require the full knowledge of system model parameters. In order to obtain an accurate and faithful model, a new identification scheme for singularly perturbed nonlinear system using multitime-scale recurrent high-order neural networks (NNs) is proposed in this paper. Inspired by the optimal bounded ellipsoid algorithm, which is originally designed for discrete-time systems, a novel weight updating law is developed for continuous-time NNs identification process. Compared with other widely used gradient-descent updating algorithms, this new method can achieve faster convergence, due to its adaptively adjusted learning rate. Based on the identification results, a control scheme using singular perturbation theories is developed. By using singular perturbation methods, the system order is reduced, and the controller structure is simplified. The closed-loop stability is analyzed and the convergence of system states is guaranteed. The effectiveness of the identification and the control scheme is demonstrated by simulation results.

Bacterial community composition in the gut content of Lampetra japonica revealed by 16S rRNA gene pyrosequencing.

The composition of the bacterial communities in the hindgut contents of Lampetrs japonica was surveyed by Illumina MiSeq of the 16S rRNA gene. An average of 32385 optimized reads was obtained from three samples. The rarefaction curve based on the operational taxonomic units tended to approach the asymptote. The rank abundance curve representing the species richness and evenness was calculated. The composition of microbe in six classification levels was also analyzed. Top 20 members in genera level were displayed as the classification tree. The abundance of microorganisms in different individuals was displayed as the pie charts at the branch nodes in the classification tree. The differences of top 50 genera in abundance between individuals of lamprey are displayed as a heatmap. The pairwise comparison of bacterial taxa abundance revealed that there are no significant differences of gut microbiota between three individuals of lamprey at a given rarefied depth. Also, the gut microbiota derived from L. japonica displays little similarity with other aquatic organism of Vertebrata after UPGMA analysis. The metabolic function of the bacterial communities was predicted through KEGG analysis. This study represents the first analysis of the bacterial community composition in the gut content of L. japonica. The investigation of the gut microbiota associated with L. japonica will broaden our understanding of this unique organism.

A novel sliding-mode control of induction motor using space vector modulation technique.

This paper presents a novel sliding-mode control method for torque control of induction motors. The control principle is based on sliding-mode control combined with space vector modulation technique. The sliding-mode control contributes to the robustness of induction motor drives, and the space vector modulation improves the torque, flux, and current steady-state performance by reducing the ripple. The Lyapunov direct method is used to ensure the reaching and sustaining of sliding mode and stability of the control system. The performance of the proposed system is compared with those of conventional sliding-mode controller and classical PI controller. Finally, computer simulation results show that the proposed control scheme provides robust dynamic characteristics with low torque ripple.

Nonlinear systems identification and control via dynamic multitime scales neural networks.

This paper deals with the adaptive nonlinear identification and trajectory tracking via dynamic multilayer neural network (NN) with different timescales. Two NN identifiers are proposed for nonlinear systems identification via dynamic NNs with different timescales including both fast and slow phenomenon. The first NN identifier uses the output signals from the actual system for the system identification. In the second NN identifier, all the output signals from nonlinear system are replaced with the state variables of the NNs. The online identification algorithms for both NN identifier parameters are proposed using Lyapunov function and singularly perturbed techniques. With the identified NN models, two indirect adaptive NN controllers for the nonlinear systems containing slow and fast dynamic processes are developed. For both developed adaptive NN controllers, the trajectory errors are analyzed and the stability of the systems is proved. Simulation results show that the controller based on the second identifier has better performance than that of the first identifier.

Sliding mode fault tolerant control dealing with modeling uncertainties and actuator faults.

In this paper, two sliding mode control algorithms are developed for nonlinear systems with both modeling uncertainties and actuator faults. The first algorithm is developed under an assumption that the uncertainty bounds are known. Different design parameters are utilized to deal with modeling uncertainties and actuator faults, respectively. The second algorithm is an adaptive version of the first one, which is developed to accommodate uncertainties and faults without utilizing exact bounds information. The stability of the overall control systems is proved by using a Lyapunov function. The effectiveness of the developed algorithms have been verified on a nonlinear longitudinal model of Boeing 747-100/200.

Nonlinear optical properties in a nanoring: quantum size and magnetic field effect.

We have studied the nonlinear optical absorption and the nonlinear optical rectification of an exciton in a nanoring in the presence of magnetic flux. The calculation results show that one can control the properties of nonlinear optical absorption and nonlinear optical rectification of a nanoring by tuning the outer and inner radius. Moreover, we find that the nonlinear optical properties of a nanoring can be modulated by the magnetic flux through the nanoring.