Tank cultivation of the red alga Palmaria palmata: Effects of intermittent light on growth rate, yield and growth kinetics

Tank cultivation of marine macroalgae involves air-agitation of the algal biomass and intermittent light conditions, i.e. periodic, short light exposure of the thalli in the range of 10 s at the water surface followed by plunging to low light or darkness at the tank bottom and recirculation back to the surface in the range of 1-2 min. Open questions relate to effects of surface irradiance on growth rate and yield in such tumble cultures and the possibility of chronic photoinhibition in full sunlight. A specially constructed shallow-depth tank combined with a dark tank allowed fast circulation times of approximately 5 s, at a density of 4.2 kg fresh weight (FW) m(-2) s(-1). Growth rate and yield of the red alga Palmaria palmata increased over a wide range of irradiances, with no signs of chronic photoinhibition, up to a growth-saturating irradiance of approximately 1600 mumol m(-2) s(-1) in yellowish light supplied by a sodium high pressure lamp at 16 h light per day. Maximum growth rate ranged at 12% FW d(-1), and maximum yield at 609 g FW m(-2) d(-1). This shows that high growth rates of individual thalli may be reached in a dense tumble culture, if high surface irradiances and short circulation times are supplied. Another aspect of intermittent light relates to possible changes of basic growth kinetics, as compared to continuous light. For this purpose on-line measurements of growth rate were performed with a daily light reduction by 50% in light-dark cycles of 1, 2 or 3 min duration during the daily light period. Growth rates at 10degreesC and 50 mumol photon m(-2) s- 1 dropped in all three intermittent light regimes during both the main light and dark periods and reached with all three periodicities approximately 50% of the control, with no apparent changes in basic growth kinetics, as compared to continuous light.

智能机器人基于作业子空间划分的自学习自适应控制方法

现有的机器人自适应控制基本上都是在建立机器人线性化的动力学模型的基础上,采用某种显式或隐式参数辨识的方法,在线地修正控制作用.本文针对机器人运动和动力学参数变化的固有特点,提出一种完全不同的自学习自适应方法.这种方法基于智能机器人分级系统中的两级结构,并且在空间域里而不是在时间域里处理机器人参数的变化.把机器人的作业空间划分成子空间,其中包括重力载荷的作用,每个子空间对应一组控制器.规划的轨迹映射到作业空间形成子空间序列.用自学习方法选择与这个序列对应的最佳控制器序列.该方法算法简单,计算量小.避开了通常的自适应方法遇到的一系列困难问题.

Cognitive control of movement via the cerebellar-recipient thalamus.

The cognitive control of behavior was long considered to be centralized in cerebral cortex. More recently, subcortical structures such as cerebellum and basal ganglia have been implicated in cognitive functions as well. The fact that subcortico-cortical circuits for the control of movement involve the thalamus prompts the notion that activity in movement-related thalamus may also reflect elements of cognitive behavior. Yet this hypothesis has rarely been investigated. Using the pathways linking cerebellum to cerebral cortex via the thalamus as a template, we review evidence that the motor thalamus, together with movement-related central thalamus have the requisite connectivity and activity to mediate cognitive aspects of movement control.

Development of Illusory contour perception in infants

We investigated whether infants from 8 ^ 22 weeks of age were sensitive to the illusory contour created by aligned line terminators. Previous reports of illusory-contour detection in infants under 4 months old could be due to infants' preference for the presence of terminators rather than their configuration. We generated preferential-looking stimuli containing sinusoidal lines whose oscillating, abutting terminators give a strong illusory contour in adult perception. Our experiments demonstrated a preference in infants 8 weeks old and above for an oscillating illusory contour compared with a stimulus containing equal terminator density and movement. Control experiments excluded local line density, or attention to alignment in general, as the basis for this result. In the youngest age group (8 ^ 10 weeks) stimulus velocity appears to be critical in determining the visibility of illusory contours, which is consistent with other data on motion processing at this age. We conclude that, by 2 months of age, the infant's visual system contains the nonlinear mechanisms necessary to extract an illusory contour from aligned terminators.

PLS modelling and fault detection on the Tennessee Eastman benchmark

This paper describes the application of multivariate regression techniques to the Tennessee Eastman benchmark process for modelling and fault detection. Two methods are applied : linear partial least squares, and a nonlinear variant of this procedure using a radial basis function inner relation. The performance of the RBF networks is enhanced through the use of a recently developed training algorithm which uses quasi-Newton optimization to ensure an efficient and parsimonious network; details of this algorithm can be found in this paper. The PLS and PLS/RBF methods are then used to create on-line inferential models of delayed process measurements. As these measurements relate to the final product composition, these models suggest that on-line statistical quality control analysis should be possible for this plant. The generation of `soft sensors' for these measurements has the further effect of introducing a redundant element into the system, redundancy which can then be used to generate a fault detection and isolation scheme for these sensors. This is achieved by arranging the sensors and models in a manner comparable to the dedicated estimator scheme of Clarke et al. 1975, IEEE Trans. Pero. Elect. Sys., AES-14R, 465-473. The effectiveness of this scheme is demonstrated on a series of simulated sensor and process faults, with full detection and isolation shown to be possible for sensor malfunctions, and detection feasible in the case of process faults. Suggestions for enhancing the diagnostic capacity in the latter case are covered towards the end of the paper.

Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland

During the last 50 years, agricultural intensification has caused many wild plant and animal species to go extinct regionally or nationally and has profoundly changed the functioning of agro-ecosystems. Agricultural intensification has many components, such as loss of landscape elements, enlarged farm and field sizes and larger inputs of fertilizer and pesticides. However, very little is known about the relative contribution of these variables to the large-scale negative effects on biodiversity. In this study, we disentangled the impacts of various components of agricultural intensification on species diversity of wild plants, carabids and ground-nesting farmland birds and on the biological control of aphids.

An ultra-short-term wind power prediction method using “offline classification and optimization, online model matching” based on time series features

The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS), and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application, the pattern of the last short WPTS is recognized, then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations.

A Microgrid Testbed for Interdisciplinary Research on Cyber-Secure Industrial Control in Power Systems

This paper describes a smart grid test bed comprising embedded generation, phasor measurement units (PMUs), and supporting ICT components and infrastructure. The test bed enables the development of a use case focused on a synchronous islanding scenario, where the embedded generation becomes islanded from the mains supply. Due to the provisioned control components, control strategy, and best-practice ICT support infrastructure, the islanded portion of the grid is able to continue to operate in a secure and dependable manner.

DACA: architecture to implement dynamic access control mechanisms on business tier components

Access control is a software engineering challenge in database applications. Currently, there is no satisfactory solution to dynamically implement evolving fine-grained access control mechanisms (FGACM) on business tiers of relational database applications. To tackle this access control gap, we propose an architecture, herein referred to as Dynamic Access Control Architecture (DACA). DACA allows FGACM to be dynamically built and updated at runtime in accordance with the established fine-grained access control policies (FGACP). DACA explores and makes use of Call Level Interfaces (CLI) features to implement FGACM on business tiers. Among the features, we emphasize their performance and their multiple access modes to data residing on relational databases. The different access modes of CLI are wrapped by typed objects driven by FGACM, which are built and updated at runtime. Programmers prescind of traditional access modes of CLI and start using the ones dynamically implemented and updated. DACA comprises three main components: Policy Server (repository of metadata for FGACM), Dynamic Access Control Component (DACC) (business tier component responsible for implementing FGACM) and Policy Manager (broker between DACC and Policy Server). Unlike current approaches, DACA is not dependent on any particular access control model or on any access control policy, this way promoting its applicability to a wide range of different situations. In order to validate DACA, a solution based on Java, Java Database Connectivity (JDBC) and SQL Server was devised and implemented. Two evaluations were carried out. The first one evaluates DACA capability to implement and update FGACM dynamically, at runtime, and, the second one assesses DACA performance against a standard use of JDBC without any FGACM. The collected results show that DACA is an effective approach for implementing evolving FGACM on business tiers based on Call Level Interfaces, in this case JDBC.

Special section on intelligent control systems and signal processing

The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

Learning control systems

Novel method of controller (PID) autotuning, involving neural networks and genetic algorithms: to employ neural networks to map the identification measures and controller parameters to objective functions, adapt these models on-line; to employ the genetic algorithm to perform on-line minimization.

Role of plasmodium translationally repressed gene products in malaria transmission

Tese de doutoramento, Ciências Biomédicas (Microbiologia e Parasitologia), Universidade de Lisboa, Faculdade de Medicina, 2015

Fractional order control on a wind turbine benchmark

This paper is about a hierarchical structure with an event-based supervisor in a higher level and a fractional-order proportional integral (FOPI) in a lower level applied to a wind turbine. The event-based supervisor analyzes the operation conditions to determine the state of the wind turbine. This controller operate in the full load region and the main objective is to capture maximum power generation while ensuring the performance and reliability required for a wind turbine to be integrated into an electric grid. The main contribution focus on the use of fractional-order proportional integral controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. Comparisons between fractional-order pitch control and a default proportional integral pitch controller applied to a wind turbine benchmark are given and simulation results by Matlab/Simulink are shown in order to prove the effectiveness of the proposed approach.

The influence of use additives on nitrous oxide emission during swine slurry composting.

use of additives (Mg/P and nitrification inhibitor dicyandiamide - DCD), on nitrous oxide emission during swine slurry composting. The experiment was run in duplicate; the gas was monitored for 30 days in different treatments (control, DCD, Mg/P and DCD + Mg/P). Nitrous oxide emissions rate (mg of N2O-N.day-1) and the accumulated emissions were calculated to compare the treatments. Results has shown that emissions of N-N2O were reduced by approximately 70, 46 and 96% through the additions of DCD, MgCl2.6H2O + H3PO4 and both additives, respectively, compared to the control. Keywords Composting; swine slurry; additives; nitrous