Using asymmetric keys in a certified trust model for multiagent systems

We present a contribution based on encryption to the model for the certification of trust in multiagent systems. The originality of the proposal remains in the use of asymmetric keys that allow the local storage of testimonies with the service agents that were assessed. The aim is to raise the level of efficiency that client agents have when contracting specialized service agents. To reach this objective we make three hypotheses: (i) client agents are able to measure and inform the quality of a service they receive from a service agent; (ii) distributed certificate control is possible if every service agent stores the certificates it receives from its client agents and, (iii) the content of a certificate can be considered safe as long as the public and private keys used to encrypt the certificate remain safe. This approach reduces some weak points of trust models that rely on the direct interaction between service and client agents (direct trust) or those that rely on testimony obtained from client agents (propagated trust). Simulation showed that encrypted certificates of trust improved the efficiency of client agents when choosing their service provider agents. The reason seems to be that the reputation of a given service provider agent is based on the reputation it has among the totality of client agents that used its services.     

Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi’s orthogonal arrays

This work presents a study on the applicability of radial base function (RBF) neural networks for prediction of Roughness Average (R_a) in the turning process of SAE 52100 hardened steel, with the use of Taguchi’s orthogonal arrays as a tool to design parameters of the network. Experiments were conducted with training sets of different sizes to make possible to compare the performance of the best network obtained from each experiment. The following design factors were considered: (i) number of radial units, (ii) algorithm for selection of radial centers and (iii) algorithm for selection of the spread factor of the radial function. Artificial neural networks (ANN) models obtained proved capable to predict surface roughness in accurate, precise and affordable way. Results pointed significant factors for network design have significant influence on network performance for the task proposed. The work concludes that the design of experiments (DOE) methodology constitutes a better approach to the design of RBF networks for roughness prediction than the most common trial and error approach.     

Effect of passive ultrassonic instrumentation as a final irrigation protocol on debris and smear layer removal—a sem analysis

This study sought to evaluate the efficacy of passive ultrasonic irrigation (PUI) on removing the smear layer and debris from root dentin using scanning electron microscopy (SEM). Twenty‐five bovine incisors were manually prepared and divided into three groups according to the final irrigation protocol: EDTA, final irrigation with 12 mL of 17% EDTA for 3 minutes followed by 5 mL of 2.5% NaOCl; EDTA/PUI, final flush with 4 mL of 17% EDTA and PUI for 30 seconds. These procedures were repeated three times to standardize the volume of the irrigant. Control group, after preparation, the specimens were irrigated only with 17 mL of 2.5% NaOCl. The roots were fractured and analyzed using SEM. The intragroup analysis revealed that the EDTA/PUI protocol removed a higher amount of debris at the cervical third (P = 0.03). The intergroup analysis revealed that EDTA/PUI presented the lowest amount of debris at the cervical third (P = 0.007). Smear layer scores were higher in the control group compared with the EDTA and EDTA/PUI groups, but only at the cervical third (P = 0.02). None of the final irrigant protocols completely removed the smear layer and debris. EDTA/PUI only improved the removal of debris at the cervical third. Microsc. Res. Tech. 76:496–502, 2013. © 2013 Wiley Periodicals, Inc.     

Molecular Mechanism of Action of 2‐Ferrocenyl‐1,1‐diphenylbut‐1‐ene on HL‐60 Leukemia Cells

The aim of this work was to investigate the mechanism of action of 2‐ferrocenyl‐1,1‐diphenylbut‐1‐ene ( 1 ) on HL‐60 human leukemia cells. While inactive against noncancerous cells, 1 provoked a concentration‐dependent decrease in viable tumor cells, primarily via apoptosis, as evidenced by analysis of cell morphology, activation of caspases 3 and 7, increased DNA fragmentation, and externalization of phosphatidylserine. Necrosis was observed only at the highest tested concentration (4 μM ). Compound 1 interfered with the cell cycle, causing an accumulation of cells in the G₁/G₀ phase. Interaction of 1 with dsDNA and ssDNA was observed by differential pulse voltammetry and confirmed by hyperchromicity in the UV/Vis spectra of dsDNA, with an interaction constant of 2×10⁴ M ^?1. Both the organic analogue 1,1,2‐triphenylbut‐1‐ene ( 2 ) and ferrocene were inactive against cancer and noncancer cell lines and did not react with DNA. These results reinforce the idea that the hybrid strategy of conjugating ferrocene to the structure of tamoxifen derivatives is advantageous in finding new substances with antineoplastic activity.     

Marine shrimp fisheries research—a mismatch on spatial and thematic needs

Scientometrics - Marine shrimp fishing is an economic activity of global importance due to its high profitability, but it also presents several environmental and socioeconomic problems. In a...     

Eggshells as agro-industrial waste substitute for CaCO3 in glass foams: A study on obtaining lower thermal conductivity

In this work, discarded glass bottles (GB) and eggshells (ES) were used to produce foam glass designed for thermal insulation. The literature on the thermal conductivity of foam glasses produced with eggshells is sparse. This material was used as pore-forming agent at 3% and 5% weight fractions to obtain a foam glass with low thermal conductivity. Homogenized powders were uniaxially pressed, and the compacts were fired at three temperatures (800, 850, and 900°C). Raw materials were characterized by chemical analysis and particle size distribution. The foam glasses were characterized by their porosity, phases, compressive strength, and thermal conductivity. The best insulating properties were obtained for the composition containing 5 wt% ES fired at 800°C. This sample displayed a porosity of 91.4% while its thermal conductivity was of 0.037 W/m.K, with a compressive strength of 1.12 ± 0.38 MPa. Crystalline phases were observed in samples fired at 850 and 900°C as a result of the devitrification process. The final properties of the materials are comparable to those of commercial foam glasses obtained from non-renewable, more expensive raw materials, a great indicator that the studied compositions could be used as an environmentally friendly substitute.     

ELA—A new Approach for Learning Agents

In this paper we discuss a new incremental learning approach used to implement adaptive behavior in autonomous agents. Adaptive agents must increase their performance based on experience using some learning approach. Often, incremental learning techniques like memory-based reasoning (MBR) are used. However, traditional MBR algorithms require an adequate (generally complex) measure of similarity, need much data and spend much time for computing similarities between examples. Such problems are unacceptable for autonomous agents that live in very dynamic environments, because they have little time to make decisions. Our approach does not use similarity measures between examples, classifies examples very fast and can compact data. We represent data as a concept graph (CG), each node representing a partition of the data. We propose an algorithm that uses the partitions to classify new examples. We compare our results with other techniques and conclude that the method performs quite well. Finally, we apply the approach to an application of adaptive agents for personalizing web search.This research was funded by Région Picardie in France. We thank Emerson Paraiso and Cesar Tacla for comments and time spent with the discussions.     

Listeria monocytogenes: Occurrence in beef and identification of the main contamination points in processing plants

This study aimed to establish the occurrence of Listeria spp., especially L. monocytogenes and its main serotypes, in beef and processing plants. A total of 443 samples were obtained from equipment, installations and products from 11 meat processing establishments from Paraná state, Brazil. All samples were analyzed using USDA methodology for Listeria spp. detection, followed by species identification. The occurrence of Listeria spp. in the samples was 38.1% of which 51.4% were from equipment, 35.4% from installations and 30.2% from products. The identified species were: L. monocytogenes (12.6%), L. innocua (78.4%), L. seeligeri (1.2%), L. welshimeri (7.2%) and L. grayi (0.6%). The identified serotypes of L. monocytogenes were 1/2a and 4b. The results demonstrate the significance of equipment and installations as sources of contamination by Listeria spp. and L. monocytogenes in the processing of beef and meat products.