Sodium bicarbonate solution as an anti-erosive agent against simulated endogenous erosion

This study investigated whether sodium bicarbonate solution, applied on enamel previously exposed to a simulated intrinsic acid, can control dental erosion. Volunteers wore palatal devices containing enamel slabs, which were exposed twice daily extra-orally to hydrochloric acid (0.01 M, pH 2) for 2 min. Immediately afterwards, the palatal devices were re-inserted in the mouth and volunteers rinsed their oral cavity with a sodium bicarbonate solution or deionized water for 60 s. After the washout period, the palatal devices were refilled with a new set of specimens and participants were crossed over to receive the alternate rinse solution. The surface loss and surface microhardness (SMH) of specimens were assessed. The surface loss of eroded enamel rinsed with a sodium bicarbonate solution was significantly lower than the surface loss of eroded enamel rinsed with deionized water. There were no differences between treatments with sodium bicarbonate and deionized water for SMH measurements. Regardless of the solution used as an oral rinse, eroded enamel showed lower SMH than uneroded specimens. Rinsing with a sodium bicarbonate solution after simulated endogenous erosive challenge controlled enamel surface loss but did not alter the microhardness.

Effect of simulated masticatory loading on the retention of stud attachments for implant overdentures

P>This study assessed the effect of simulated mastication on the retention of two stud attachment systems for 2-implants overdentures. Sixteen specimens, each simulating an edentulous ridge with implants and an overdenture were divided into two groups, according to the attachment system: Group I (Nobel Biocare ball-socket attachments) and Group II (Locator attachments). Retention forces were measured before and after 400 000 simulated masticatory loads in a customised device. Data were compared by two-way anova followed by Bonferroni test (alpha = 0 center dot 05). Group I presented significantly lower retention forces (Newtons) than Group II at baseline (10 center dot 6 +/- 3 center dot 6 and 66 center dot 4 +/- 16 center dot 0, respectively). However, differences were not significant after 400 000 loads (7 center dot 9 +/- 4 center dot 3 and 21 center dot 6 +/- 17 center dot 0). The number of cycles did not influence the measurements in Group I, whereas a non-linear descending curve was found for Group II. It was concluded that simulated mastication resulted in minor changes for the ball attachment tested. Nevertheless, it reduced the retention of Locator attachments to 40% of the baseline values, what suggests that mastication is a major factor associated with maintenance needs for this system.

A simulated annealing algorithm for finding consensus sequences

Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules. Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing. Unlike the conventional approach of finding a consensus sequence by first forming a multiple sequence alignment, this algorithm searches for a sequence that minimises the sum of pairwise distances to each of the input sequences. The resulting consensus sequence can then be used to induce a multiple sequence alignment. The time required by the algorithm scales linearly with the number of input sequences and quadratically with the length of the consensus sequence. We present results demonstrating the high quality of the consensus sequences and alignments produced by the new algorithm. For comparison, we also present similar results obtained using ClustalW. The new algorithm outperforms ClustalW in many cases.

Amylases in enzyme detergents and their effects on a simulated long-life dairy dessert

Enzyme detergents used in the food industry contain proteinase as the major enzyme but amylase may be present, either by design or inadvertently. Three commercial enzyme detergents and 3 enzyme preparations used in detergents were assayed for alpha-amylase activity by the Ceralpha method using the Megazyme kits. The amylase activities of the detergents varied from 3.2x 10(-6) to 32x 10(-6) mumoles ml(-1) h(-1) while the enzyme preparations had much higher activities ranging from 0.05 to 8.06 mumoles ml(-1) h(-1). When added aseptically to a simulated dairy dessert (2% starch solution) and stored for 42 days, the enzyme detergents caused an increase in viscosity; enzyme preparations at low concentrations caused an initial increase in viscosity followed by a decrease; and enzyme preparations at high concentrations caused an immediate decrease in viscosity. The increase in viscosity corresponded to formation of a distinct network of starch granules while the decrease in viscosity was characterised by a marked decrease in size of the granules and little or no network of granules. Decreases in viscosity corresponded to increases in reducing sugars but samples which increased in viscosity showed no measurable reducing sugars. The amylase activity in all sources was destroyed by heating at 75degreesC for 15 min at pH 1.8.

Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation

The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08º and 1.4º, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

Robosonic: Randomness-Based Manipulation of Sounds Assisted by Robots

In this text, we intend to explore the possibilities of sound manipulation in a context of augmented reality (AR) through the use of robots. We use the random behaviour of robots in a limited space for the real-time modulation of two sound characteristics: amplitude and frequency. We add the possibility of interaction with these robots, providing the user the opportunity to manipulate the physical interface by placing markers in the action space, which alter the behaviour of the robots and, consequently, the audible result produced. We intend to demonstrate through the agents, programming of random processes and direct manipulation of this application, that it is possible to generate empathy in interaction and obtain specific audible results, which would be difficult to otherwise reproduce due to the infinite loops that the interaction promotes.

Robosonic: Manipulação de Sons Aleatória Assistida por Robots

Neste texto, pretendemos explorar as possibilidades de manipulação de sons num contexto de realidade aumentada (AR) através da utilização de robots. Utilizamos o comportamento aleatório dos robots, num espaço circunscrito para a modulação em tempo real de duas características do som: a amplitude e a frequência. Acrescentamos a possibilidade de interacção com estes robots dando a oportunidade ao utilizador de manipular a interface física, colocando markers no espaço de acção que alterem o comportamento dos robots e, por conseguinte, o resultado sonoro produzido. Pretendemos demonstrar que através de agentes, programação de aleatórios e manipulação directa desta aplicação, se pode gerar empatia na interacção e atingir resultados sonoros específicos, difíceis de reproduzir de outra forma devido aos ciclos infinitos que a interacção promove.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

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 simulator 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 is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive 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 an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

Study of the influence of count’s number in myocardium in the determination of reproducible functional parameters in Gated-SPECT studies simulated with GATE

Myocardial Perfusion Gated Single Photon Emission Tomography (Gated-SPET) imaging is used for the combined evaluation of myocardial perfusion and left ventricular (LV) function. But standard protocols of the Gated-SPECT studies require long acquisition times for each study. It is therefore important to reduce as much as possible the total duration of image acquisition. However, it is known that this reduction leads to decrease on counts statistics per projection and raises doubts about the validity of the functional parameters determined by Gated-SPECT. Considering that, it’s difficult to carry out this analysis in real patients. For ethical, logistical and economical matters, simulated studies could be required for this analysis. Objective: Evaluate the influence of the total number of counts acquired from myocardium, in the calculation of myocardial functional parameters (LVEF – left ventricular ejection fraction, EDV – end-diastolic volume, ESV – end-sistolic volume) using routine software procedures.

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE

A literature review on the optimization of legged robots

Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes.