Control strategy of central pattern generator gait movement under condition of attention selection

As a typical rhythmic movement, human being＇s rhythmic gait movement can be generated by a central pattern generator （CPG） located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being＇s motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.

Real-time generation of circular patterns in electron beam lithography

Electron beam lithography(EBL)involves the transfer of a pattern onto the surface of a substrate byfirst scanning a thin layer of organicfilm(called resist)on the surface by a tightly focused and precisely controlled electron beam(exposure)and then selectively removing the exposed or nonexposed regions of the resist in a solvent(developing).It is widely used for fabrication of integrated cir-cuits,mask manufacturing,photoelectric device processing,and otherfields.The key to drawing circular patterns by EBL is the graphics production and control.In an EBL system,an embedded processor calculates and generates the trajectory coordinates for movement of the electron beam,and outputs the corresponding voltage signal through a digital-to-analog converter(DAC)to control a deflector that changes the position of the electron beam.Through this procedure,it is possible to guarantee the accuracy and real-time con-trol of electron beam scanning deflection.Existing EBL systems mostly use the method of polygonal approximation to expose circles.A circle is divided into several polygons,and the smaller the segmentation,the higher is the precision of the splicing circle.However,owing to the need to generate and scan each polygon separately,an increase in the number of segments will lead to a decrease in the overall lithography speed.In this paper,based on Bresenham’s circle algorithm and exploiting the capabilities of afield-programmable gate array and DAC,an improved real-time circle-producing algorithm is designed for EBL.The algorithm can directly generate cir-cular graphics coordinates such as those for a single circle,solid circle,solid ring,or concentric ring,and is able to effectively realizes deflection and scanning of the electron beam for circular graphics lithography.Compared with the polygonal approximation method,the improved algorithm exhibits improved precision and speed.At the same time,the point generation strategy is optimized to solve the blank pixel and pseudo-pixel problems that arise with Bresenham’s circle algorithm.A complete electron beam deflection system is established to carry out lithography experiments,the results of which show that the error between the exposure results and the preset pat-terns is at the nanometer level,indicating that the improved algorithm meets the requirements for real-time control and high precision of EBL.

Monoaminergic and catecholaminergic activation of the central pattern generator for locomotion following spinal cord injury Innovative therapeutic approaches

The development of secondary health complications following spinal cord injury has been increasingly recognized by healthcare professionals as a major concern. These problems most specifically affect complete or near-complete spinal cord injury patients （e.g., those with minimal mobility）, who are not typically rehabilitated with treadmill training approaches, because motor control and leg movements are largely impaired. However, recent pharmaceutical advances in central pattern generator activation may provide new therapeutic hopes for these spinal cord injury patients. This article provides a comprehensive overview, for the non-specialist, of the most recent advances in this field.

Arm motion control model based on central pattern generator

According to the theory of Matsuoka neural oscillators and with the con- sideration of the fact that the human upper arm mainly consists of six muscles, a new kind of central pattern generator （CPG） neural network consisting of six neurons is pro- posed to regulate the contraction of the upper arm muscles. To verify effectiveness of the proposed CPG network, an arm motion control model based on the CPG is established. By adjusting the CPG parameters, we obtain the neural responses of the network, the angles of joint and hand of the model with MATLAB. The simulation results agree with the results of crank rotation experiments designed by Ohta et al., showing that the arm motion control model based on a CPG network is reasonable and effective.

Study on dynamics of central pattern generator for a quadrupedal robot

Based on Matsuoka＇s central pattern generator （CPG） model and taking quadruped as an example, the dynamics of CPG model was investigated through the single-parameter-analysis method and the numerical simulation technique. Simulation results indicate that the CPG model exhibits complex dynamics, while each parameter has specifically definitive influence trends on the CPG output. These conclusions were applied to control a quadrupedal robot to walk in different gaits, clear obstacle, and walk up- and down-slope successfully.

Preparation and Optical Patterning of Organic-Inorganic Hybrid Color-Filter Films Using Latent Pigments by Utilizing Photo-Acid-Generator and Microwave Irradiation

Preparation and photo-patterning characteristics of organic-inorganic hybrid thin film containing latent pigment by using photo-acid-generator (PAG) and microwave irradiation have been investigated. The acrylic thin film modified with methoxysilane containing PAG was formed on a glass substrate and irradiated with ultraviolet rays to promote sol-gel reaction by catalytic action of acid which was generated from PAG. And then the film was hardened with microwave irradiation, yielding organic-inorganic hybrid polymer film having hardness, highly transparency and strong adhesion with a glass substrate. Since this reaction only occurred in the optically (UV) irradiated regions, by exploiting the difference between the adhesivenesses of these regions photo-irradiated through photomask with a glass substrate, it was possible to form a patterned film with pitch of 100 to 50 μm by a simple lift-off method. A pigment-containing film using latent pigments (with subtractive three primary colors of coloring materials) and a patterned film were prepared, and it was possible to make these films multi-colored by varying the mixing ratio of the pigments. This multi-colored film-preparation method is effective for simply and efficiently forming a color-filter film by applying optical and microwave irradiation.

Central pattern generation underlying Limulus rhythmic behavior patterns

Many behavioral activities of the horseshoe crab Limulus are rhythmic, and most of these are produced in large part by central pattern generators within the CNS. The chain of opisthosomal （‘abdominal＇） ganglia controls gill movements of ventilation and gill cleaning, and the prosomal ring of fused ganglia （brain and segmental ‘thoracic＇ ganglia） controls generation of feeding and locomotor movements of the legs. Both the opisthosomal CNS and the prosomal CNS can generate behaviorally ap- propriate patterns of motor output in isolation, without movements or sensory input. Preparations of the isolated opisthosomal CNS generate rhythmic output patterns of motor activity characterized as fictive ventilatory and gill cleaning rhythms. Moreover, CNS preparations also express longer-term patterns, such as intermittent ventilation or sequential bouts of ventilation and gill cleaning. Such longer-term patterns are commonly observed in intact animals. The isolated prosomal CNS does not spontaneously generate the activity patterns characteristic of walking, swimming, and feeding. However, perfusion of octopamine in the isolated prosomal CNS activates central pattern generators underlying rhythmic chewing movements, and injection of octopamine into in- tact Limulus promotes the chewing pattern of feeding, whether or not food is presented. Our understanding of the ability of neu-romodulators such as octopamine to elicit or alter central motor programs may help to clarify the central neural circuits of pattern generation that oroduce and coordinate these rhythmic behaviors

Analysis on General-Particular Pattern of an Invitation to Exhibitors

An Invitation to exhibitors is one of the typical exhibition documents.The General-Particular pattern is the common text pattern found in invitations to exhibitors.This paper is an analysis on its way of organization and expression from the perspective of text macro structure and aims at summarizing its general laws and features to master the essence of other exhibition documents.

Study on Test Compaction in High-Level Automatic Test Pattern Generation (ATPG) Platform

Advancements in semiconductor technology are making gate-level test generation more challenging. This is because a large amount of detailed structural information must be processed in the search process of automatic test pattern generation (ATPG). In addition, ATPG needs to deal with new defects caused by process variation when IC is shrinking. To reduce the computation effort of ATPG, test generation could be started earlier at higher abstraction level, which is in line with top-down design methodology that has become more popular nowadays. In this research, we employ Chen’s high-level fault model in the high-level ATPG. Besides shorter ATPG time as shown in many previous works, our study showed that high-level ATPG also contributes to test compaction. This is because most of the high-level faults correlate with the gate-level collapsed faults especially at input/output of the modules in a circuit. The high-level ATPG prototype used in our work is mainly composed by constraint-driven test generation engine and fault simulation engine. Experimental result showed that more reduced/compact test set can be generated from the high-level ATPG.

From furnace up to freezer:Elevational patterns of plant diversity in Mount Palvar,a semi-arid Irano-Turanian mountain range of southwest Asia

Much of the world's biodiversity lies in heterogeneous mountain areas with their diverse environments.As an example,Iranian montane ranges are highly diverse,particularly in the Irano-Turanian phytogeographical region.Understanding plant diversity patterns with increasing elevation is of high significance,not least for conservation planning.We studied the pattern of species richness,Shannon diversity,endemic richness,endemics ratio,and richness of life forms along a 3900 m elevational transect in Mount Palvar,overlooking the Lut Desert in Southeast Iran.We also analyzed the effect of environmental variables on species turnover along the vertical gradient.A total of 120 vegetation plots(10 m×10 m)were sampled along the elevational transect containing species and environmental data.To discover plant diversity pattern along the elevational gradient,generalized additive model(GAM)was used.Non-metric multidimensional scaling(NMDS)was applied for illustrating the correlation between species composition and environmental variables.We found hump-shaped pattern for species richness,Shannon diversity,endemic richness,and species richness of different life forms,but a monotonic increasing pattern for ratio of endemic species from low to high elevations.Our study confirms the humped pattern of species richness peaking at intermediate elevations along a complete elevational gradient in a semi-arid mountain.The monotonic increase of endemics ratio with elevation in our area as a case study is consistent with global increase of endemism with elevation.According to our results,temperature and precipitation are two important climatic variables that drive elevational plant diversity,particularly in seasonally dry areas.Our study suggests that effective conservation and management are needed for this low latitude mountain area along with calling for long-term monitoring for species redistribution.

Enhancing SAT-Based Test Pattern Generation

This paper presents modeling tools based on Boolean satisfiability (SAT) to solve problems of test generation for combinational circuits. It exploits an added layer to maintain circuit-related information and value justification relations to a generic SAT algorithm. It dovetails binary decision graphs (BDD) and SAT techniques to improve the efficiency of automatic test pattern generation (ATPG). More specifically, it first exploits inexpensive reconvergent fanout analysis of circuit to gather information on the local signal correlation by using BDD learning, then uses the above learned information to restrict and focus the overall search space of SAT-based ATPG. Its learning technique is effective and lightweight. The experimental results demonstrate the effectiveness of the approach.

The generalized Chapman-Richards function and applications to tree and stand growth

The generalized Chapman-Richards model was derived from the Chapman-Richards function in which parameters h, k and m were unconstrained. Based on the structure of solutions and biological interpretations, the model could be classified into eight cases (three categories) at all and among them only 4 kinds of cases are suitable in forestry that represent four typical growth patterns of trees and stands. For each of 4 equations, the model properties and biological interpretations for parameters were discussed in detail. The generalized Chapman-Richards model was capable of describing a wide range of growth curves that was asymptotic or nonasymptotic, with or without inflection point. In order to illustrate the versatility of the model, it was fitted to a group of data sets concerning the DBH growth of cryptomeria plantations with 4 initial densities and the DBH and height growth of natural Korean pine tree. Comparing the generalized Chapman-Richards function and the Schnute model, it was found that the parameters and expressions of the two models were interchangeable in theory, and the fitting results were explicitly identical in empirical applications.

Likelihood and Quadratic Distance Methods for the Generalized Asymmetric Laplace Distribution for Financial Data

Maximum likelihood (ML) estimation for the generalized asymmetric Laplace (GAL) distribution also known as Variance gamma using simplex direct search algorithms is investigated. In this paper, we use numerical direct search techniques for maximizing the log-likelihood to obtain ML estimators instead of using the traditional EM algorithm. The density function of the GAL is only continuous but not differentiable with respect to the parameters and the appearance of the Bessel function in the density make it difficult to obtain the asymptotic covariance matrix for the entire GAL family. Using M-estimation theory, the properties of the ML estimators are investigated in this paper. The ML estimators are shown to be consistent for the GAL family and their asymptotic normality can only be guaranteed for the asymmetric Laplace (AL) family. The asymptotic covariance matrix is obtained for the AL family and it completes the results obtained previously in the literature. For the general GAL model, alternative methods of inferences based on quadratic distances (QD) are proposed. The QD methods appear to be overall more efficient than likelihood methods infinite samples using sample sizes n ≤5000 and the range of parameters often encountered for financial data. The proposed methods only require that the moment generating function of the parametric model exists and has a closed form expression and can be used for other models.

Pattern formation in mutation of “Game of Life”

This paper presents pattern formation in generalized cellular automata (GCA) by varying parameters of classic “game of life”. Different dynamic behaviors are classified. The influence of remembrance of dynamic behavior of GCA is also studied. Experiments show the emergence of the self-organizing patterns that is analogous with life forms at the edge of chaos, which consist of certain nontrivial structure and go through periods of growth, maturity and death. We describe these experiments and discuss their potential as alternative way for creating artificial life and generative art, and as a new method for pattern genesis.

Management of erectile dysfunction: barriers faced by general practitioners

Aim: To explore the barriers faced by general practitioners (GPs) in the management of patients with erectile dysfunction (ED). Methods: This was a qualitative analysis of focus group discussions and in-depth inter views involving 28 Malaysian GPs. Results: GPs' perception of ED being not a serious condition was a major determinant of their prescribing practice. Doctor's age (younger), gender (female), short consultation time and lack of experience were cited as barriers. The GPs' prescribing habits were heavily influenced by the feedback from the first few patients under treatment, the uncertainty of etiology of ED without proper assessment and the profit margin with bulk purchase. Other barriers include Patients' coexisting medical conditions, older age, lower socio-economic status, unrealistic expectations and inappropriate use of the anti-impoteneet drugs. Cardiovascular side effects and cost were two most important drug barriers. Conclusion: The factors influencing the management of ED among the general practitioners were multiple and complex. An adequate understanding of how these factors (doctors, patients and drugs) interact can assist in the formulation and implementation of strategies that encourage GPs to identify and manage ED patients.

Modelling of thrust generated by oscillation caudal fin of underwater bionic robot

A simplified model of the thrust force is proposed based on a caudal fin oscillation of an underwater bionic robot. The caudal fin oscillation is generalized by cen- tral pattern generators （CPGs）. In this model, the drag coefficient and lift coefficient are the two critical parameters which are obtained by the digital particle image velocimetry （DPIV） and the force transducer experiment. Numerical simulation and physical experi- ments have been performed to verify this dynamic model.

Kernel Generalized Noise Clustering Algorithm

To deal with the nonlinear separable problem, the generalized noise clustering （GNC） algorithm is extended to a kernel generalized noise clustering （KGNC） model. Different from the fuzzy c-means （FCM） model and the GNC model which are based on Euclidean distance, the presented model is based on kernel-induced distance by using kernel method. By kernel method the input data are nonlinearly and implicitly mapped into a high-dimensional feature space, where the nonlinear pattern appears linear and the GNC algorithm is performed. It is unnecessary to calculate in high-dimensional feature space because the kernel function can do it just in input space. The effectiveness of the proposed algorithm is verified by experiments on three data sets. It is concluded that the KGNC algorithm has better clustering accuracy than FCM and GNC in clustering data sets containing noisy data.

Predicate Oriented Pattern Analysis for Biomedical Knowledge Discovery

In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF, OWL). With the increasing number of semi-structured data coming into the biomedical community, data integration and knowledge discovery from heterogeneous domains become important research problem. In the application level, detection of related concepts among medical ontologies is an important goal of life science research. It is more crucial to figure out how different concepts are related within a single ontology or across multiple ontologies by analysing predicates in different knowledge bases. However, the world today is one of information explosion, and it is extremely difficult for biomedical researchers to find existing or potential predicates to perform linking among cross domain concepts without any support from schema pattern analysis. Therefore, there is a need for a mechanism to do predicate oriented pattern analysis to partition heterogeneous ontologies into closer small topics and do query generation to discover cross domain knowledge from each topic. In this paper, we present such a model that predicates oriented pattern analysis based on their close relationship and generates a similarity matrix. Based on this similarity matrix, we apply an innovated unsupervised learning algorithm to partition large data sets into smaller and closer topics and generate meaningful queries to fully discover knowledge over a set of interlinked data sources. We have implemented a prototype system named BmQGen and evaluate the proposed model with colorectal surgical cohort from the Mayo Clinic.

A Sketch-Based Generation Model for Diverse Ceramic Tile Images Using Generative Adversarial Network

Ceramic tiles are one of the most indispensable materials for interior decoration.The ceramic patterns can’t match the design requirements in terms of diversity and interactivity due to their natural textures.In this paper,we propose a sketch-based generation method for generating diverse ceramic tile images based on a hand-drawn sketches using Generative Adversarial Network(GAN).The generated tile images can be tailored to meet the specific needs of the user for the tile textures.The proposed method consists of four steps.Firstly,a dataset of ceramic tile images with diverse distributions is created and then pre-trained based on GAN.Secondly,for each ceramic tile image in the dataset,the corresponding sketch image is generated and then the mapping relationship between the images is trained based on a sketch extraction network using ResNet Block and jump connection to improve the quality of the generated sketches.Thirdly,the sketch style is redefined according to the characteristics of the ceramic tile images and then double cross-domain adversarial loss functions are employed to guide the ceramic tile generation network for fitting in the direction of the sketch style and to improve the training speed.Finally,we apply hidden space perturbation and interpolation for further enriching the output textures style and satisfying the concept of“one style with multiple faces”.We conduct the training process of the proposed generation network on 2583 ceramic tile images dataset.To measure the generative diversity and quality,we use Frechet Inception Distance(FID)and Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)metrics.The experimental results prove that the proposed model greatly enhances the generation results of the ceramic tile images,with FID of 32.47 and BRISQUE of 28.44.

氦气资源形成地质条件、成因机理与富集规律

借鉴含油气系统思路及方法,基于典型富氦气田解剖,并利用地球化学成藏方法技术,研究天然气中氦气资源形成的地质条件、成因机理与富集规律。结果表明:①氦气“生-运-聚”机理与天然气有显著差异性,氦气主要为基底富U、Th元素缓慢α衰变或深部壳幔氦释放,沿岩石圈复合输导体系运移至天然气成藏系统,依附适宜载体气聚集成藏。②氦运移输导主要受“岩石圈断裂、基底断裂、沉积层断裂、有效输导层”复合输导体系控制,基于地下流体中“氦-气-水”相平衡及相-势耦合综合分析,提出氦气运聚过程中具有“水溶相、气溶相、游离相”3种主要赋存状态,存在氦气“集流、渗流、扩散”3种运移方式。③富氦气藏形成和氦气富集通常受控于“优质氦源、高效输导、适宜载体”3大主控要素,具有“脱溶汇聚、浮力驱动、压差驱替”3种聚集成藏动力类型,已发现富氦气藏具有相对“近氦源、邻断裂、低势区、高部位”的分布规律和成藏模式。④氦气富集区勘探和评价需要依托天然气兼探/并探,在评价落实氦气“源-运-聚”要素与天然气“生-储-盖”条件耦合匹配性、局部相对低势高部位有利圈闭载体气区的基础上,综合评价优选“通源连圈、低势高位、气氦适配”的有利氦气富集区。