Inducible system in human hepatoma cell lines for hepatitis C virus production

We cloned the complete complementary DNA of an isolate of the hepatitis C virus, HCV-S1, into a tetra cycline-inducible expression vector and stably transfected it into two human hepatoma cell lines, Huh7 and HepG2. Twenty-six Huh7 and two HepG2-positive clones were obtained after preliminary screening. Two Huh7 (SH-7 and -9) and one HepG2 (G-19) clones were chosen for further characterisation. Expression of HCV proteins in these cells accumulated from 6 In to 4 days posttreatment. Full-length viral plus-strand RNA was detected by Northern analyses. Using RT-PCR and ribonuclease protection assay, we also detected the synthesis of minus-strand HCV RNA. Plus- and minus-strand viral RNA was still detected after treatment with actinomycin D. Indirect immunofluorescence staining with anti-E2, NS4B, and NS5A revealed that these proteins were mostly localised to the endoplasmic reticulum (ER). Culture media from tet-induced SH-9 cells was separated on sucrose density gradients and analysed for the presence of HCV RNA. Viral RNA levels peaked at two separate ranges, one with a buoyant density of 1.08 g/ml and another from 1.17 to 1.39 g/ml. Electron microscopy demonstrated the presence of subviral-like particles (approximately 20-25 nm in diameter) in the cytoplasm of SH-9 and G-19 cells, which were positively labelled by anti-HCV core antibodies. Anti-E2 antibodies strongly labelled cytoplasmic vesicular structures and some viral-like particles. Complete viral particles of about 50 nm which reacted with anti-E2 antibodies were observed in the culture media of tet-induced SH-9 cells following negative staining. Supernatant from tet-treated SH-9 cells was found to infect naive Huh7 and stable Huh7-human CD81 cells. (C) 2002 Elsevier Science (USA).

In vitro growth and leaf anatomy of Cattleya walkeriana (Gardner, 1839) grown in natural ventilation system

Natural ventilation system facilitates gaseous exchanges in in vitro plants promoting changes in the leaf tissue, which can be evaluated through the leaf anatomy, and it allows a cultivation closer to the photoautrophic micropropagation. The objective of this work was to evaluate the effects on in vitro growth and on the leaf anatomy of Cattleya walkeriana grown in natural and conventional ventilation system with different concentrations of sucrose (0; 15; 30 and 45 L-1) combined with different cultivation systems (conventional micropropagation and natural ventilation system). The culture medium was composed of MS salts, solidified with 7 g L-1 of agar and pH adjusted to 5.8. Forty milliliters of culture medium were distributed in 250 mL flasks, autoclaved at 120 ºC for 20 minutes. The greater plant growth, as well as the greater thickness of the mesophyll was observed with the use of 20 g L-1 sucrose in natural ventilation system. Plants grown in natural ventilation system showed a thicker leaf mesophyll, which is directly related to photoautotrophic crops. The natural ventilation system induced more elliptical stomata and probably more functional formats.

Gradual correction of phosphorus availability in the no-tillage system

ABSTRACT In areas cultivated under no-tillage system, the availability of phosphorus (P) can be raised by means of the gradual corrective fertilization, applying phosphorus into sowing furrows at doses higher than those required by the crops. The objective of this work was to establish the amount of P to be applied in soybean crop to increase content of P to pre-established values at the depth of 0.0 to 0.10 m. An experiment was carried out on a clayey Haplorthox soil with a randomized block experimental design distributed in split-split plot, with four replications. Two soybean crop systems (single or intercropped with Panicum maximum Jaca cv. Aruana) were evaluated in the plots. In addition, it was evaluated four P levels (0, 60, 120 and 180 kg ha-1 P2O5) applied in the first year in the split plots; and four P levels (0, 30, 60 and 90 kg ha-1 P2O5) applied in the two subsequent crops in the split-split plot. Contents of P were extracted by Mehlich-1 and Anion Exchange Resin methods from soil samples collected in the split-split plot. It was found that it is necessary to apply 19.4 or 11.1 kg ha-1 of P2O5, via triple superphosphate as source, to increase 1 mg dm-3 of P extracted by Mehlich-1 or Resin, respectively, in the 0.0 to 0.10 m layer of depth. The soil drain P character decreases as the amount of this nutrient supplied in the previous crops is increased.

Residential energy resources management by a SCADA system in case of excess wind generation

The end consumers in a smart grid context are seen as active players. The distributed generation resources applied in smart home system as a micro and small-scale systems can be wind generation, photovoltaic and combine heat and power facility. The paper addresses the management of domestic consumer resources, i.e. wind generation, solar photovoltaic, combined heat and power, electric vehicle with gridable capability and loads, in a SCADA system with intelligent methodology to support the user decision in real time. The main goal is to obtain the better management of excess wind generation that may arise in consumer’s distributed generation resources. The optimization methodology is performed in a SCADA House Intelligent Management context and the results are analyzed to validate the SCADA system.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

A multi-agent system for the support of producer coalition formation in electricity markets

All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. To get negotiation power and advantages of scale economy, distributed producers can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multitechnology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the development of a multi-agent market simulator – MASCEM – able to study alternative coalitions of distributed producers in order to identify promising Virtual Power Producers in an electricity market.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

MASDScheGATS: a prototype system for dynamic scheduling

A manufacturing system has a natural dynamic nature observed through several kinds of random occurrences and perturbations on working conditions and requirements over time. For this kind of environment it is important the ability to efficient and effectively adapt, on a continuous basis, existing schedules according to the referred disturbances, keeping performance levels. The application of Meta-Heuristics and Multi-Agent Systems to the resolution of this class of real world scheduling problems seems really promising. This paper presents a prototype for MASDScheGATS (Multi-Agent System for Distributed Manufacturing Scheduling with Genetic Algorithms and Tabu Search).

Towards the wide implementation of standards IEC 61968/70 (CIM) and IEC 61850 in the distribution system (CIGRÉ C6-105_2010)

Currently, power systems (PS) already accommodate a substantial penetration of distributed generation (DG) and operate in competitive environments. In the future, as the result of the liberalisation and political regulations, PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage and provide market agents to ensure a flexible and secure operation. This cannot be done with the traditional PS operational tools used today like the quite restricted information systems Supervisory Control and Data Acquisition (SCADA) [1]. The trend to use the local generation in the active operation of the power system requires new solutions for data management system. The relevant standards have been developed separately in the last few years so there is a need to unify them in order to receive a common and interoperable solution. For the distribution operation the CIM models described in the IEC 61968/70 are especially relevant. In Europe dispersed and renewable energy resources (D&RER) are mostly operated without remote control mechanisms and feed the maximal amount of available power into the grid. To improve the network operation performance the idea of virtual power plants (VPP) will become a reality. In the future power generation of D&RER will be scheduled with a high accuracy. In order to realize VPP decentralized energy management, communication facilities are needed that have standardized interfaces and protocols. IEC 61850 is suitable to serve as a general standard for all communication tasks in power systems [2]. The paper deals with international activities and experiences in the implementation of a new data management and communication concept in the distribution system. The difficulties in the coordination of the inconsistent developed in parallel communication and data management standards - are first addressed in the paper. The upcoming unification work taking into account the growing role of D&RER in the PS is shown. It is possible to overcome the lag in current practical experiences using new tools for creating and maintenance the CIM data and simulation of the IEC 61850 protocol – the prototype of which is presented in the paper –. The origin and the accuracy of the data requirements depend on the data use (e.g. operation or planning) so some remarks concerning the definition of the digital interface incorporated in the merging unit idea from the power utility point of view are presented in the paper too. To summarize some required future work has been identified.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

Distributed Model Predictive Control for Housing with Hourly Auction of Available Energy

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

From simulation to statistical analysis: timeliness assessment of ethernet/IP-based distributed systems

A number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor distributed real-time applications. Full-duplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional Fieldbus networks? Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. In the past few years, it is particularly significant the considerable amount of work that has been devoted to the timing analysis of Ethernet-based technologies. It happens, however, that the majority of those works are restricted to the analysis of sub-sets of the overall computing and communication system, thus without addressing timeliness at a holistic level. To this end, we are addressing a few inter-linked research topics with the purpose of setting a framework for the development of tools suitable to extract temporal properties of Commercial-Off-The-Shelf (COTS) Ethernet-based factory-floor distributed systems. This framework is being applied to a specific COTS technology, Ethernet/IP. In this paper, we reason about the modelling and simulation of Ethernet/IP-based systems, and on the use of statistical analysis techniques to provide usable results. Discrete event simulation models of a distributed system can be a powerful tool for the timeliness evaluation of the overall system, but particular care must be taken with the results provided by traditional statistical analysis techniques.