Practical Quality Control: Comparision of Methods on the Quantification of Stationary Phases in Paper and Thin-Layer Chromatographic Systems

Introduction: Paper and thin layer chromatography methods are frequently used in Classic Nuclear Medicine for the determination of radiochemical purity (RCP) on radiopharmaceutical preparations. An aliquot of the radiopharmaceutical to be tested is spotted at the origin of a chromatographic strip (stationary phase), which in turn is placed in a chromatographic chamber in order to separate and quantify radiochemical species present in the radiopharmaceutical preparation. There are several methods for the RCP measurement, based on the use of equipment as dose calibrators, well scintillation counters, radiochromatografic scanners and gamma cameras. The purpose of this study was to compare these quantification methods for the determination of RCP. Material and Methods: 99mTc-Tetrofosmin and 99mTc-HDP are the radiopharmaceuticals chosen to serve as the basis for this study. For the determination of RCP of 99mTc-Tetrofosmin we used ITLC-SG (2.5 x 10 cm) and 2-butanone (99mTc-tetrofosmin Rf = 0.55, 99mTcO4- Rf = 1.0, other labeled impurities 99mTc-RH RF = 0.0). For the determination of RCP of 99mTc-HDP, Whatman 31ET and acetone was used (99mTc-HDP Rf = 0.0, 99mTcO4- Rf = 1.0, other labeled impurities RF = 0.0). After the development of the solvent front, the strips were allowed to dry and then imaged on the gamma camera (256x256 matrix; zoom 2; LEHR parallel-hole collimator; 5-minute image) and on the radiochromatogram scanner. Then, strips were cut in Rf 0.8 in the case of 99mTc-tetrofosmin and Rf 0.5 in the case of 99mTc-HDP. The resultant pieces were smashed in an assay tube (to minimize the effect of counting geometry) and counted in the dose calibrator and in the well scintillation counter (during 1 minute). The RCP was calculated using the formula: % 99mTc-Complex = [(99mTc-Complex) / (Total amount of 99mTc-labeled species)] x 100. Statistical analysis was done using the test of hypotheses for the difference between means in independent samples. Results:The gamma camera based method demonstrated higher operator-dependency (especially concerning the drawing of the ROIs) and the measures obtained using the dose calibrator are very sensitive to the amount of activity spotted in the chromatographic strip, so the use of a minimum of 3.7 MBq activity is essential to minimize quantification errors. Radiochromatographic scanner and well scintillation counter showed concordant results and demonstrated the higher level of precision. Conclusions: Radiochromatographic scanners and well scintillation counters based methods demonstrate to be the most accurate and less operator-dependant methods.

Utilização de algoritmos de processamento e análise de imagem na avaliação do dano em placas compósitas

PTDC/EME–TME/66207/2006 e POSC/EEA-SRI/55386/2004

Contexts-management strategy in considering the security in urban computing based on urban design

Urban Computing (UrC) provides users with the situation-proper information by considering context of users, devices, and social and physical environment in urban life. With social network services, UrC makes it possible for people with common interests to organize a virtual-society through exchange of context information among them. In these cases, people and personal devices are vulnerable to fake and misleading context information which is transferred from unauthorized and unauthenticated servers by attackers. So called smart devices which run automatically on some context events are more vulnerable if they are not prepared for attacks. In this paper, we illustrate some UrC service scenarios, and show important context information, possible threats, protection method, and secure context management for people.

Knowledge management systems and intellectual capital measurement in portuguese organizations: a case study

This paper presents the results of an exploratory study on knowledge management in Portuguese organizations. The study was based on a survey sent to one hundred of the main Portuguese organizations, in order to know their current practices relating knowledge management systems (KMS) usage and intellectual capital (IC) measurement. With this study, we attempted to understand what are the main tools used to support KM processes and activities in the organizations, and what metrics are pointed by organizations to measure their knowledge assets.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Cooperative scheduling system with emergent swarm based behavior

This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective – global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.

Agent-based simulation of electronic marketplaces with decision support

This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Bid definition method for electricity markets based on an adaptive multiagent system

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.

Case-based reasoning for self-optimizing behavior

In this paper we present a Self-Optimizing module, inspired on Autonomic Computing, acquiring a scheduling system with the ability to automatically select a Meta-heuristic to use in the optimization process, so as its parameterization. Case-based Reasoning was used so the system may be able of learning from the acquired experience, in the resolution of similar problems. From the obtained results we conclude about the benefit of its use.

Man-tailored biomimetic sensor of molecularly imprinted materials for the potentiometric measurement of oxytetracycline

A novel biomimetic sensor for the potentiometric transduction of oxytetracycline is presented. The artificial host was imprinted in methacrylic acid and/or acrylamide based polymers. Different amounts of molecularly imprinted and non-imprinted polymers were dispersed in different plasticizing solvents and entrapped in a poly(vinyl chloride) matrix. Only molecularly imprinted based sensors allowed a potentiometric transduction, suggesting the existence of host–guest interactions. These sensors exhibited a near-Nernstian response in steady state evaluations; slopes and detection limits ranged 42–63 mV/decade and 2.5–31.3 µg/mL, respectively. Sensors were independent from the pH of test solutions within 2–5. Good selectivity was observed towards glycine, ciprofloxacin, creatinine, acid nalidixic, sulfadiazine, cysteine, hydroxylamine and lactose. In flowing media, the biomimetic sensors presented good reproducibility (RSD of ±0.7%), fast response, good sensitivity (65 mV/decade), wide linear range (5.0×10−5 to 1.0×10−2 mol/L), low detection limit (19.8 µg/mL), and a stable baseline for a 5×10−3M citrate buffer (pH 2.5) carrier. The sensors were successfully applied to the analysis of drugs and urine. This work confirms the possibility of using molecularly imprinted polymers as ionophores for organic ion recognition in potentiometric transduction.

A study on security grade assignment model for mobile users in urban computing

The relation between the information/knowledge expression and the physical expression can be involved as one of items for an ambient intelligent computing [2],[3]. Moreover, because there are so many contexts around user/spaces during a user movement, all appplcation which are using AmI for users are based on the relation between user devices and environments. In these situations, it is possible that the AmI may output the wrong result from unreliable contexts by attackers. Recently, establishing a server have been utilizes, so finding secure contexts and make contexts of higher security level for save communication have been given importance. Attackers try to put their devices on the expected path of all users in order to obtain users informationillegally or they may try to broadcast their SPAMS to users. This paper is an extensionof [11] which studies the Security Grade Assignment Model (SGAM) to set Cyber-Society Organization (CSO).

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.

A survey of techniques and technologies for web-based real-time interactive rendering

When exploring a virtual environment, realism depends mainly on two factors: realistic images and real-time feedback (motions, behaviour etc.). In this context, photo realism and physical validity of computer generated images required by emerging applications, such as advanced e-commerce, still impose major challenges in the area of rendering research whereas the complexity of lighting phenomena further requires powerful and predictable computing if time constraints must be attained. In this technical report we address the state-of-the-art on rendering, trying to put the focus on approaches, techniques and technologies that might enable real-time interactive web-based clientserver rendering systems. The focus is on the end-systems and not the networking technologies used to interconnect client(s) and server(s).