DNA sequences classification and computation scheme based on the symmetry principle

The DNA sequences containing multifarious novel symmetrical structure frequently play crucial role in how genomes work. Here we present a new scheme for understanding the structural features and potential mathematical rules of symmetrical DNA sequences using a method containing stepwise classification and recursive computation. By defining the symmetry of DNA sequences, we classify all sequences and conclude a series of recursive equations for computing the quantity of all classes of sequences existing theoretically; moreover, the symmetries of the typical sequences at different levels are analyzed. The classification and quantitative relation demonstrate that DNA sequences have recursive and nested properties. The scheme may help us better discuss the formation and the growth mechanism of DNA sequences because it has a capability of educing the information about structure and quantity of longer sequences according to that of shorter sequences by some recursive rules. Our scheme may provide a new stepping stone to the theoretical characterization, as well as structural analysis, of DNA sequences

Active-disturbance rejection control based on a novel sliding mode observer for PMSM speed and rotor position

A novel sliding mode observer (SMO) is presented for sensorless control of permanent magnet synchronous machines (PMSM). Compared to conventional sliding mode observers, the sigmoid function is used to weaken chattering problem; Kalman filter is substituted for conventional low-pass filters. Asymptotical stability is analyzed by Lyapunov stability theory. The active-disturbance rejection control (ADRC) speed regulator is designed with a given speed and estimated speed by novel sliding mode observer as inputs and iq* as output. The effect of load in speed loop is regarded as an external disturbance in the ADRC regulator. The disturbance is observed and compensated by ADRC, which leads to good dynamic and static performance and robust to load. Experimental results are provided to verify the feasibility and effectiveness of the proposed method

4-Amino-1-(2-benzoyl-1-phenyl­eth­yl)-3-phenyl-1H-1,2,4-triazol-5(4H)-thione

In the title compound, C23H20N4OS, the two phenyl rings of the diphenyl­propanone fragment form a dihedral angle of 86.8 (1)°, and the third phenyl ring attached to the triazole ring is twisted from the latter at 40.1 (1)°. In the crystal, mol­ecules are paired into centrosymmetric dimers via pairs of inter­molecular N—H⋯O and N—H⋯S hydrogen bonds

On Weak Exponential Expansiveness of Evolution Families in Banach Spaces

The aim of this paper is to give several characterizations for the property of weak exponential expansiveness for evolution families in Banach spaces. Variants for weak exponential expansiveness of some well-known results in stability theory (Datko (1973), Rolewicz (1986), Ichikawa (1984), and Megan et al. (2003)) are obtained

On Nonuniform Polynomial Trichotomy of Linear Discrete-Time Systems in Banach Spaces

We study two nonuniform polynomial trichotomy concepts for linear discrete-time systems in Banach spaces. Our main objective is to give summation property for nonuniform polynomial trichotomies. As for applications we obtain characterization of these concepts in terms of Lyapunov functions

Using corneal topography design personalized cataract surgery programs

AIM:To investigate how to design personalized cataract surgery programs to achieve surgical correction of preoperative corneal astigmatism with surgical astigmatism under the guidance of corneal topography, improve postoperative visual quality and reduce the cost of treatment. <p>METHODS: Totally 202 cases(226 eyes)cataract patients were divided into randomized treatment group and individualized treatment group. According to the method and location of the incision, randomized treatment group were divided into 8 groups. Surgical astigmatism after different incision were calculated with the use of preoperative and postoperative corneal astigmatism through vector analysis method. Individualized treatment groups were designed personably for surgical method with reference of every surgically induced astigmatism, the surgical method chooses the type of surgical incision based on close link between preoperative corneal astigmatism and surgically induced astigmatism, and the incision was located in the steep meridian. The postoperative corneal astigmatism of individualized treatment group was observed. <p>RESULTS: Postoperative corneal astigmatism of individualized treatment group were lower than that of 3.0mm clear corneal tunnel incision in the randomized treatment group, there were statistically significance difference, while with 3.0mm sclera tunnel incision group there were no statistically significance difference. After 55.8% of patients with the use of individualized surgical plan could undergo the operation of extracapsular cataract extraction with relatively low cost and rigid intraocular lens implantation, the per capita cost of treatment could be reduced. <p>CONCLUSION: Personalized cataract surgery programs are designed to achieve surgical correction of preoperative corneal astigmatism under the use of corneal topography, improve postoperative visual quality and reduce the cost of treatment

Learning to Generate SAR Images with Adversarial Autoencoder

Deep learning-based synthetic aperture radar (SAR) target recognition often suffers from sparsely distributed training samples and rapid angular variations due to scattering scintillation. Thus, data-driven SAR target recognition is considered a typical few-shot learning (FSL) task. This paper first reviews the key issues of FSL and provides a definition of the FSL task. A novel adversarial autoencoder (AAE) is then proposed as a SAR representation and generation network. It consists of a generator network that decodes target knowledge to SAR images and an adversarial discriminator network that not only learns to discriminate “fake” generated images from real ones but also encodes the input SAR image back to a target knowledge. The discriminator employs progressively expanding convolution layers and a corresponding layer-by-layer training strategy. It uses two cyclic loss functions to enforce consistency between the inputs and outputs. Moreover, rotated cropping is introduced as a mechanism to address the challenge of representing the target orientation. The MSTAR 7-target dataset is used to evaluate the AAE’s performance, and the results demonstrate its ability to generate SAR images with aspect angular diversity. Using only 90 training samples with at least 25 degrees of orientation interval, the trained AAE is able to generate the remaining 1,748 samples of other orientation angles with an unprecedented level of fidelity. Thus, it can be used for data augmentation in SAR target recognition FSL tasks. Our experimental results show that the AAE could boost the test accuracy by 5.77%