New taxa, names, and combinations in Saxifraga (Saxifragaceae) for the Flora of China

The following new species, new variety, new name, and four new combinations are published for the forthcoming account of Saxifraga L. in the Flora of China, Volume 8: S. epiphylla Gornall & H. Ohba, sp. nov., S. gemmigera Engler var. gemmuligera (Engler) J. T. Pan & Gornall, comb. nov., S. heterotricha Marquand & Airy-Shaw var. anadena (H. Smith) J. T. Pan & Gornall, comb. et stat, nov., S. hypericoides Franchet var. aurantiascens (Engler & Irmscher) J. T. Pan & Gornall, comb. nov., S. hypericoides var. rockii (Mattfeld) J. T. Pan & Gornall, comb. et stat. nov., S. sinomontana J. T. Pan & Gornall, nom. nov., and S. sinomontana var. amabilis H. Smith ex J. T. Pan, var. nov. In addition, the names S. mengtzeana Engler & Irmscher and S. mengtzeana var. cordatifolia Engler & Irmscher are lectotypified here.

基于循环抑制CPG模型控制的蛇形机器人三维运动

具有三维运动能力和独特的节律运动方式,使生物蛇能在复杂的地形环境中生存.大多数动物节律运动是由中央模式发生器(Centralpatterngenerator,CPG)控制的.以此为理论依据,首次以循环抑制建模机理构建蛇形机器人组合关节运动控制的CPG模型.证明该模型是节律输出型CPG中微分方程维数最少的.采用单向激励方式连接该类CPG构建蛇形机器人三维运动神经网络控制体系,给出该CPG网络产生振荡输出的必要条件.应用蛇形机器人动力学模型仿真得到控制三维运动的CPG神经网络参数,利用该CPG网络的输出使“勘查者”成功实现三维运动.该结果为建立未探明的生物蛇神经网络模型提供了一种全新的方法.

基于循环抑制CPG模型的蛇形机器人控制器

依据生物利用中央模式发生器(Central pattern generator,CPG)的自激行为产生有节律的协调运动适应多种环境,基于循环抑制CPG建模理论设计了蛇形机器人CPG控制器模型,分析了单个神经元、循环抑制CPG以及该控制器模型的稳定性,并把该控制器应用到一个结合蛇形机器人“勘查者-Ⅰ”动力学特性的仿真模型,得到了实现蜿蜒运动的CPG控制器参数,进而研究了调节S波个数、身体构形曲率、蜿蜒运动速度以及运动轨迹曲率的CPG控制器参数设定策略。此外,“勘查者-Ⅰ”应用该CPG控制器的输出成功实现了蜿蜒运动。该研究结果为设计人工CPG控制器提供了一个可行的方法。

网络遥操作机器人的任务产生方法研究

为了解决网络遥操作中操作者误操作问题,给出了一种在非结构环境下遥操作机器人的模糊控制方法,介绍了一种网络遥操作机器人控制系统结构,对任务产生器进行了设计,并以网络遥操作机械手抓取物品为例,通过实验验证了所设计方法的合理性。

可重构机器人体系结构及模块化控制系统的实现

本文提出了一种适用于新型可重构星球机器人的模块化控制系统,根据机构和运动特性,基于CAN总线和分布式控制器技术,将系统结构和功能分解成不同模块由各自的控制器独立执行,建立具有任务层和运动层的分层次控制结构,实现了组合式规划、分布式控制的混合式控制方法。本文设计了两种不同的控制器,并采用PPG脉冲宽度调节方法实现了对在机器人上使用的R/C电机的标定和控制。通过在子机器人原理样机上进行实验,验证了这套控制系统和控制体系结构的可行性。

基于智能可重构装配线制造系统的产品装配序列规划研究

研究了基于智能装配单元的可重构装配线制造系统环境中的产品装配建模方法与装配序列表达机制,提出由产品层次装配模型与生产线装配工艺齿状结构描述相结合的重构装配线装配序列规划与表达方法。

基于循环抑制CPG的蛇形机器人运动控制方法

蛇具有细长无肢的身体、独特的半球形关节，使其可在神经系统控制下完成与环境相适应的多种节律运动。模仿蛇的运动机理和行为方式而设计的蛇形机器人克服了轮腿式机器人的缺点，增加了机器人的运动方式，扩大了机器人的应用范围。但应用传统的控制策略实现蛇形机器人运动控制遇到了很难克服的问题。随着社会经济与科技的发展，研究人员把从蛇运动神经系统研究中得到的启示应用到蛇形机器人上，希望不仅可以解决其运动控制问题，更能在构型、步态及控制机制上皆可展示蛇的特征。 生物学家已经证明动物的节律运动是其低级神经中枢的自激行为，是由中枢模式发生器(Central Pattern Generator，CPG)控制的。中枢模式发生器是一种能够在缺乏有规律的感知和中枢控制输入的情况下，产生有节奏模式输出的神经网络。 本文以国家自然科学基金课题《基于CPG的蛇形机器人控制方法研究》和国家“863”高技术计划资助项目《具有环境适应能力的蛇形机器人的研究》为依托，突破以相互抑制机理研究CPG的传统观点，首次创新性地提出应用循环抑制(Cyclic Inhibition, CI)机理来研究蛇形机器人的CPG建模与实现问题。本研究涵概了神经元模型的特性分析、蛇形机器人关节循环抑制CPG建模理论、蛇形机器人循环抑制CPG神经网络稳定性分析以及典型步态的生成方法、循环抑制CPG神经网络控制蛇形机器人蜿蜒运动参数设定策略、应用动力学仿真和实验对该CPG控制方法有效性的验证。 首先，本文介绍了两个用于CPG建模研究的蛇形机器人“勘查者”和“勘查者-I”。给出各自机械系统、控制系统的构成和动力学仿真平台。 其次，详细分析了神经元以及传统的相互抑制(Mutual Inhibition, MI)CPG的特性。从工程角度首次创新性地应用循环抑制建模理论构建了蛇形机器人CPG模型，并对其稳定性进行了深入的分析。首次证明持续型神经元构成的单向循环抑制(Unilateral Cyclic Inhibition, UCI) CPG是能产生振荡输出CPG中微分方程数量最少的，而且其产生振荡输出的机理完全不同于传统的相互抑制CPG。其不需要具备调整功能，只需要神经元之间强的单向循环抑制连接。 第三，首次应用单向激励连接循环抑制CPG构成蛇形机器人神经网络系统。分析了其稳定性，给出其产生振荡输出的条件。通过仿真和实验验证了循环抑制CPG神经网络实现典型步态(蜿蜒运动、伸缩运动和侧向运动)的有效性。首次应用双向循环抑制(Bidirectional Cyclic Inhibition, BCI)CPG神经网络在不同高级控制神经元命令激活下的输出实现蛇形机器人典型运动步态之间的转换。为蛇节律运动生成机制建模提供了新方法。 最后，从实时性、控制方便性等工程应用的角度，对单向循环抑制CPG神经网络实现蛇形机器人蜿蜒运动控制进行了深入的分析。给出了S-波形、幅值、运动速度和运动轨迹曲率的参数设定策略。该系统应用首CPG自激励权重调解成功解决了传统CPG控制系统中CPG的个数比蛇形机器人关节数多一个的问题，并用其实现了一种独特的转弯控制策略。 综上，为蛇形机器人运动控制提供了全新的方法。

归因任务中预期强度水平对结果评价的影响

Previous researches has shown that two components of the event- related brain potential, the feedback negativity (FRN) and P300, are related to outcome evaluation. So far, the nature of the outcome evaluation reflected by FRN and the significance of P300 remains unknown. Some studies found that the process of outcome evaluation may be related to the expectation, and the FRN may be affected by the intensity levels of the expectation for the outcome. To address these issues, the present study will start on two aspects: (1)This study required 39 participants to make attribution about their performance during a task, the aim was to assess the levels of the expectations for the outcome under four conditions in the attribution task. The main finding is that, the expectations for monetary reward under four conditions are scaled. (2)Based on the results of the first study, this study also required 16 participants to make attribution about their performance during a task. A functional dissociation was observed, with the FRN affected by the intensity levels of the expectation for the outcome, while the P300 sensitive to the degree of emotion the participants experienced. Dipole source location analysis showed that the most likely neural generator of FRN and P300 is the cingulate cortex, suggesting that FRN might reflect cognitive conflict when the actual outcome is different from the expectation, and P300 is related to the emotion processing of outcome stimuli. These results suggest that there is a functional dissociation between FRN and P300.

Principles, Opportunism and Seeing in Design: A Computational Approach

This thesis introduces elements of a theory of design activity and a computational framework for developing design systems. The theory stresses the opportunistic nature of designing and the complementary roles of focus and distraction, the interdependence of evaluation and generation, the multiplicity of ways of seeing over the history of a design session versus the exclusivity of a given way of seeing over an arbitrarily short period, and the incommensurability of criteria used to evaluate a design. The thesis argues for a principle based rather than rule based approach to designing documents. The Discursive Generator is presented as a computational framework for implementing specific design systems, and a simple system for arranging blocks according to a set of formal principles is developed by way of illustration. Both shape grammars and constraint based systems are used to contrast current trends in design automation with the discursive approach advocated in the thesis. The Discursive Generator is shown to have some important properties lacking in other types of systems, such as dynamism, robustness and the ability to deal with partial designs. When studied in terms of a search metaphor, the Discursive Generator is shown to exhibit behavior which is radically different from some traditional search techniques, and to avoid some of the well-known difficulties associated with them.

Combining Associational and Causal Reasoning to Solve Interpretation and Planning Problems

This report describes a paradigm for combining associational and causal reasoning to achieve efficient and robust problem-solving behavior. The Generate, Test and Debug (GTD) paradigm generates initial hypotheses using associational (heuristic) rules. The tester verifies hypotheses, supplying the debugger with causal explanations for bugs found if the test fails. The debugger uses domain-independent causal reasoning techniques to repair hypotheses, analyzing domain models and the causal explanations produced by the tester to determine how to replace faulty assumptions made by the generator. We analyze the strengths and weaknesses of associational and causal reasoning techniques, and present a theory of debugging plans and interpretations. The GTD paradigm has been implemented and tested in the domains of geologic interpretation, the blocks world, and Tower of Hanoi problems.

Prevalence of Asthma Symptoms and Associated Factors in Schoolchildren from Brazilian Amazon Islands

Objectives. To determine the prevalence of asthma symptoms among schoolchildren living on two different Brazilian Amazon islands and to identify the risk factors related to this condition. Methods. A cross-sectional study of 400 schoolchildren (5-8 years old) using written questionnaires produced by the International Study of Asthma and Allergies in Childhood, a skin prick test (allergic sensitization), and a stool examination (for helminthic infection). Nonparametric tests were carried out, and the risk factors were identified by logistic regression. Results. the prevalence of active asthma symptoms was markedly higher in children living on Outeiro Island (OI) than those living on Comb Island (CBI) (30.5% and 16.5%, respectively). the logistic regression identified several risk factors of asthma symptoms on CBI: parental history of asthma, night coughing in the past year, and currently have a cat. On OI, the major risk factors were parental history of asthma, personal history of eczema, having two or more older siblings, and night coughing in the past year. the risk factors in common on both the islands were night coughing in the past year and parental history of asthma. Conclusions. the prevalence of asthma symptoms was higher in those with a lifestyle closer to that observed in urban areas (i.e., better sanitation and hygiene), reinforcing the protective effect of a rural environment. Different risk factors were associated with asthma symptoms in schoolchildren living on OI and on CBI. This fact may reflect the environmental individuality and particularities of each island.

A hyper-heuristic ensemble method for static job-shop scheduling.

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyperheuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

A hybrid power system for remote areas in Jordan

This paper presents a techno-economic assessment for a unique Isolated Hybrid Power System (IHPS) design for remote areas isolated from the grid which also has the capability of being operated as a smart μ-grid. The share of renewable energy sources in resource poor developing countries is low. In these countries an increase in the share of alternative energy (wind, water and sun) delivered with inexpensive operationally robust generation and delivery systems is seen to the way forward. In our design also incorporates a novel storage system to increase the effectiveness of the Isolated IHPSs previously reported in the literature. The configuration reported is a system consisting of, the wind and sun powered generation complemented with batteries, fuel cell unit and a diesel generator. The modelling design and simulations were based on Simulations conducted using MATLAB/SIMULINK, and HOMER Energy Planning and Design software tools. The design and simulation of a new storage approach incorporating Hydrogen Peroxide (H2O2) fuel cell (increasing the efficiency of the fuel cell from 35% to 65%) and a single board computer (Raspberry Pi) used for the energy management and control the system are the novel features of our design. The novel control strategy implemented also includes a synchronization capability that facilitates IHPS to IHPS or IHPS to Main-Grid connection. In the paper after briefly but comprehensively detailing the design and simulations we will present the results on which we conclude that smart independent systems that can utilize indigenous renewable energy with a capability of being able to synchronize with the grid or each other are the most optimal way of electrifying resource poor developing countries in a sustainable way with minimum impact on the environment and also achieve reductions in Green House Gases.

A genetic algorithm based economic dispatch (GAED) with environmental constraint optimisation

The role of renewable energy in power systems is becoming more significant due to the increasing cost of fossil fuels and climate change concerns. However, the inclusion of Renewable Energy Generators (REG), such as wind power, has created additional problems for power system operators due to the variability and lower predictability of output of most REGs, with the Economic Dispatch (ED) problem being particularly difficult to resolve. In previous papers we had reported on the inclusion of wind power in the ED calculations. The simulation had been performed using a system model with wind power as an intermittent source, and the results of the simulation have been compared to that of the Direct Search Method (DSM) for similar cases. In this paper we report on our continuing investigations into using Genetic Algorithms (GA) for ED for an independent power system with a significant amount of wind energy in its generator portfolio. The results demonstrate, in line with previous reports in the literature, the effectiveness of GA when measured against a benchmark technique such as DSM.

Resíduos de medicamentos

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas