Análise histomorfológica de dentes decíduos de cães com rizogênese incompleta, após biopulpectomia e obturação dos canais radiculares com hidróxido de cálcio em diferentes veículos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Endodontics pastes formulated with copaiba oil: action on oral microbiota and dentin bridge formation in dogs

This study analysed the effect of pastes formulated with calcium hydroxide P.A. and different vehicles (saline solution - paste A and Copaifera langsdorffii Desfon oil - paste B) on oral microorganisms and dentin bridge formation in dogs. The antimicrobial action of the pastes and their components was analysed by the minimum inhibitory concentration in agar gel technique. The components were diluted and tested on fifteen standard strains of microorganisms associated with endodontic diseases. The microorganisms were cultivated and after incubation data was analysed using One-Way ANOVA and Turkey's test (P≤0.05). Four superior incisors of ten animals were used to evaluate dentin bridge formation. Two incisors were capped with paste A (GA) and two with paste B (GB). After 90 days, the teeth were extracted for histological analysis and the degree of dentin bridge formation evaluated. Data was analysed by the Kruskal-Wallis test (P<0.05). The pastes and their components were classified in the following decreasing order of antimicrobial action: calcium hydroxide P.A., paste A, paste B and Copaifera langsdorffii Desfon oil. Calcium hydroxide P.A. showed significantly higher antimicrobial action than the pastes or their vehicles. No significant difference was observed between the two pastes in dentin bridge formation. Based on the microorganisms studied, it can be concluded that the pastes analysed showed similar antimicrobial potential but differed significantly from their individual components. No significant difference was observed in dentin bridge formation between the different pastes tested.

The Use of Nanotechnology in Cosmetic Formulations: The Influence of Vehicle in the Vitamin A Skin Penetration

Despite the efficacy of topical retinoic acid, skin reactions have limited its acceptance by patients. Other retinoids, like Retinyl Palmitate (RP), are considerably less irritating, but they are also less effective. In order to enhance the performance of retinoids, in this work RP has been added to cosmetic formulations such as nanoemulsions, which can provide better penetration of this active substance. Because the vehicle can directly influence the skin penetration and the effectiveness of RP, two skin care products containing 5000 UI RP have been developed and investigated, namely a nanoemulsifying system and a classic gel cream. In vitro penetration tests were conducted by using Franz diffusion cells and placing porcine ear skin and iso-propanol in the receptor compartment. The RP concentration in the skin layers was analyzed by high performance liquid chromatography, and a Zeta-Sizer system was employed for measurement of the the particle size distribution. The penetration tests revealed a large difference between the vehicles in terms of the RP concentrations in each skin layer. The classic gel cream furnished better RP penetration in both the stratum corneum and the epidermis without stratum corneum + dermis, as compared to the self-nanoemulsifying system. The two vehicles displayed the same particle size (between 100 and 200 nm). Better understanding of RP skin delivery using different vehicles has been acquired, and the importance of evaluating the efficacy of nanocosmetics. Results from the present study should also contribute to the assessment of commercial self-nanoemulsifying systems with potential application in the facile production of nanoemulsions.

Desarrollo preliminar de descriptores para el análisis sensorial de ajos desecados y liofilizados

El polvo de ajo (Allium sativum L.) es una alternativa para conservar en el tiempo sus propiedades sensoriales y prolongar su vida útil como alimento procesado. En la actualidad, no existe una definición clara de las propiedades sensoriales que caracterizan el ajo ni de las técnicas más adecuadas para su análisis. Los objetivos del presente trabajo fueron estudiar diferentes vehículos y determinar el más apropiado para el análisis sensorial del polvo de ajo, y generar y definir los descriptores para las propiedades sensoriales de olor y flavor de diferentes cultivares deshidratados a través de dos métodos: en estufa a 50°C y por liofilización a -50°C, bajo vacío. Se pretende contribuir a la caracterización de este producto aportando un vocabulario específico y sus definiciones, como así también una metodología sensorial propia. Ocho evaluadores, seleccionados y entrenados de acuerdo con las normas internacionales y con experiencia en análisis sensorial, probaron diferentes vehículos y una vez determinado el más adecuado, desarrollaron el lenguaje descriptivo para los ajos desecados y liofilizados seleccionando por consenso los descriptores que mejor caracterizaban las cultivares, y se definió cada término. Se generaron 31 descriptores simples. Si bien, algunos de los descriptores coincidieron con los publicados en la guía ASTM DS 66 (1996) para ajos frescos, con esta investigación se aportó un amplio número de términos nuevos para la descripción del olor y el flavor de los ajos desecados y liofilizados, los cuales contribuyen a una mejor caracterización sensorial de este producto.

On-line learning of a fuzzy controller for a precise vehicle cruise control system

Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight). This work presents a method to on-line evolve a fuzzy controller for commanding vehicles? pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller?s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data. Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.

3D models created from ROV videos and their corresponding subtransect dimensions

Underwater video transects have become a common tool for quantitative analysis of the seafloor. However a major difficulty remains in the accurate determination of the area surveyed as underwater navigation can be unreliable and image scaling does not always compensate for distortions due to perspective and topography. Depending on the camera set-up and available instruments, different methods of surface measurement are applied, which make it difficult to compare data obtained by different vehicles. 3-D modelling of the seafloor based on 2-D video data and a reference scale can be used to compute subtransect dimensions. Focussing on the length of the subtransect, the data obtained from 3-D models created with the software PhotoModeler Scanner are compared with those determined from underwater acoustic positioning (ultra short baseline, USBL) and bottom tracking (Doppler velocity log, DVL). 3-D model building and scaling was successfully conducted on all three tested set-ups and the distortion of the reference scales due to substrate roughness was identified as the main source of imprecision. Acoustic positioning was generally inaccurate and bottom tracking unreliable on rough terrain. Subtransect lengths assessed with PhotoModeler were on average 20% longer than those derived from acoustic positioning due to the higher spatial resolution and the inclusion of slope. On a high relief wall bottom tracking and 3-D modelling yielded similar results. At present, 3-D modelling is the most powerful, albeit the most time-consuming, method for accurate determination of video subtransect dimensions.

Long term individual load forecast under different electrical vehicles uptake scenarios

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

Modification of composition of a nanoemulsion with different cholesteryl ester molecular species: Effects on stability, peroxidation, and cell uptake

Purpose: Use of lipid nanoemulsions as carriers of drugs for therapeutic or diagnostic purposes has been increasingly studied. Here, it was tested whether modifications of core particle constitution could affect the characteristics and biologic properties of lipid nanoemulsions. Methods: Three nanoemulsions were prepared using cholesteryl oleate, cholesteryl stearate, or cholesteryl linoleate as main core constituents. Particle size, stability, pH, peroxidation of the nanoemulsions, and cell survival and uptake by different cell lines were evaluated. Results: It was shown that cholesteryl stearate nanoemulsions had the greatest particle size and all three nanoemulsions were stable during the 237-day observation period. The pH of the three nanoemulsion preparations tended to decrease over time, but the decrease in pH of cholesteryl stearate was smaller than that of cholesteryl oleate and cholesteryl linoleate. Lipoperoxidation was greater in cholesteryl linoleate than in cholesteryl oleate and cholesteryl stearate. After four hours' incubation of human umbilical vein endothelial cells (HUVEC) with nanoemulsions, peroxidation was minimal in the presence of cholesteryl oleate and more pronounced with cholesteryl linoleate and cholesteryl stearate. In contrast, macrophage incubates showed the highest peroxidation rates with cholesteryl oleate. Cholesteryl linoleate induced the highest cell peroxidation rates, except in macrophages. Uptake of cholesteryl oleate nanoemulsion by HUVEC and fibroblasts was greater than that of cholesteryl linoleate and cholesteryl stearate. Uptake of the three nanoemulsions by monocytes was equal. Uptake of cholesteryl oleate and cholesteryl linoleate by macrophages was negligible, but macrophage uptake of cholesteryl stearate was higher. In H292 tumor cells, cholesteryl oleate showed the highest uptakes. HUVEC showed higher survival rates when incubated with cholesteryl stearate and smaller survival with cholesteryl linoleate. H292 survival was greater with cholesteryl stearate. Conclusion: Although all three nanoemulsion types were stable for a long period, considerable differences were observed in size, oxidation status, and cell survival and nanoemulsion uptake in all tested cell lines. Those differences may be helpful in protocol planning and interpretation of data from experiments with lipid nanoemulsions.

Evaluation of pH and Calcium Ion Release of Calcium Hydroxide Pastes Containing Different Substances

Introduction: The objective of this study was to evaluate the pH and calcium ion release of calcium hydroxide pastes associated with different substances. Methods: Forty acrylic teeth with simulated root canals were divided into 4 groups according to the substance associated to the calcium hydroxide paste: chlorhexidine (CHX) in 2 formulations (1% solution and 2% gel), Casearia sylvestris Sw extract, and propylene glycol (control). The teeth with pastes and sealed coronal accesses were immersed in 10 mL deionized water. After 10 minutes, 24 hours, 48 hours, and 7, 15, and 30 days, the teeth were removed to another container, and the liquid was analyzed. Calcium ion release was measured by atomic absorption spectrophotometry, and pH readings were made with a pH meter. Data were analyzed statistically by analysis of variance and Tukey test (alpha = 0.05). Results: Calcium analysis revealed significant differences (P < .05) for 1% CHX solution and 2% CHX gel at 10 minutes. After 24 hours, 2% CHX gel x Control and 2% CHX gel x 1% CHX solution differed significantly (P < .05). After 48 hours, there were significant differences (P < .05) for 2% CHX gel x Control and Extract x Control. No differences (P > .05) were observed among groups in the other periods. Regarding the pH, there were significant differences (P < .05) for 2% CHX gel x Control and 2% CHX gel x 1% CHX solution after 48 hours and for 2% CHX gel x Control after 15 days. In the other periods, no differences (P > .05) were observed among groups. Conclusions: All pastes behaved similarly in terms of pH and calcium ion release in the studied periods. (J Endod 2009;35:1274-1277)

Probing the effect of vehicles on topical delivery: Understanding the basic relationship between solvent and solute penetration using silicone membranes

Purpose. In the present study we examined the relationship between solvent uptake into a model membrane (silicone) with the physical properties of the solvents (e.g., solubility parameter, melting point, molecular weight) and its potential predictability. We then assessed the subsequent topical penetration and retention kinetics of hydrocortisone from various solvents to define whether modifications to either solute diffusivity or partitioning were dominant in increasing permeability through solvent-modified membranes. Methods. Membrane sorption of solvents was determined from weight differences following immersion in individual solvents, corrected for differences in density. Permeability and retention kinetics of H-3-hydrocortisone, applied as saturated solutions in the various solvents, were determined over 48 h in horizontal Franz-type glass diffusion cells. Results. Solvent sorption into the membrane could be related to differences in solubility parameters, MW and hydrogen bonding (r(2) = 0.76). The actual and predicted volume of solvent sorbed into the membrane was also found to be linearly related to Log hydrocortisone flux, with changes in both diffusivity and partitioning of hydrocortisone observed for the different solvent vehicles. Conclusions. A simple structure-based predictive model can be applied to the sorption of solvents into silicone membranes. Changes in solute diffusivity and partitioning appeared to contribute to the increased hydrocortisone flux observed with the various solvent vehicles. The application of this predictive model to the more complex skin membrane remains to be determined.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

A general overview on hybrid and electric vehicles

The economical and environment impacts of fossil energies increased the interest for hybrid, battery and fuel-cell electric vehicles. Several demanding engineering challenges must be faced, motivated by different physical domains integration. This paper aims to present an overview on hybrid (HEV) and electric vehicles (EV) basic structures and features. In addition, it will try to point out some of the most relevant challenges to overcome for HEV and EV may be a solid option for the mobility issue. New developments in energy storage devices and energy management systems (EMS) are crucial to achieve this goal.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.