Bond strength of artificial teeth attached to a microwave-polymerized denture base resin after immersion in disinfectant solutions

To evaluate the bond strength between two types of acrylic resin teeth and a microwave denture base resin after immersion in disinfectant solutions for 180 days. Eighty specimens made of acrylic resin teeth (Biotone and Biotone IPN) attached to a microwave polymerized denture base resin (Nature-Cryl MC) were divided into eight groups (n = 10) according to the treatment (distilled water-control, 2% chlorhexidine digluconate, 1% sodium hypochlorite and sodium perborate solution-Corega Tabs). The shear strength tests (MPa) were carried out using a universal testing machine with a 0.5 mm/min speed. Data analysis was performed using ANOVA and multiple comparison Student-Newman-Keuls post hoc test (α = 0.05). Biotone IPN showed similar results among the groups (distilled water, 8.25 ± 1.81 MPa; chlorhexidine, 7.81 ± 3.34 MPa; hypochlorite, 7.75 ± 3.72 MPa; and Corega Tabs, 7.58 ± 2.27 MPa, whereas Biotone showed significantly lower shear bond strength values for the groups immersed in Corega Tabs (5.25 ± 3.27 MPa) and chlorhexidine (6.08 ± 2.35 MPa). Soaking the dentures in 1% sodium hypochlorite could be recommended as a disinfectant solution for dentures fabricated with conventional acrylic resin denture teeth and microwave denture base resin. For dentures fabricated with IPN teeth and microwave denture base resin, all the soaking solutions evaluated in this study could be suggested to denture wearers.

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Effects of two estradiol esters (benzoate and cypionate) on the induction of synchronized ovulations in Bos indicus cows submitted to a timed artificial insemination protocol

The effects of estradiol benzoate (EB) and estradiol cypionate (EC) on induction of ovulation after a synchronized LH surge and on fertility of Bos indicus females submitted to timed AI (TAI) were evaluated. In Experiment 1, ovariectomized Nelore heifers were used to evaluate the effect of EB (n = 5) and EC (n = 5) on the circulating LH profile. The LH surge timing (19.6 and 50.5 h; P = 0.001), magnitude (20.5 and 9.4 ng/mL; P = 0.005), duration (8.6 and 16.5 h; P = 0.001), and area under the LH curve (158.6 and 339.4 ng/mL; P = 0.01) differed between the EB and EC treatments, respectively. In Experiment 2 (follicular responses; n = 60) and 3 (pregnancy per AI; P/AI; n = 953) suckled Bos indicus beef cows submitted to an estradiol/progesterone-based synchronization protocol were assigned to receive one of two treatments to induce synchronized ovulation: 1 mg of EB im 24 h after progesterone (P4) device removal or 1 mg of EC im at P4 device removal. There was no difference (P > 0.05) between EB and EC treatments on follicular responses (maximum diameter of the ovulatory follicle, 13.1 vs. 13.9 mm; interval from progesterone device removal to ovulation, 70.2 vs. 68.5 h; and ovulation rate, 77.8 vs. 82.8%, respectively). In addition, P/AI was similar (P < 0.22) between the cows treated with EB (57.5%; 277/482) and EC (61.8%; 291/471). In conclusion, despite pharmacologic differences, both esters of estradiol administered either at P4 device removal (EC) or 24 h later (EB) were effective in inducing an LH surge which resulted in synchronized ovulations and similar P/AI in suckled Bos indicus beef cows submitted to TAI. (C) 2012 Elsevier Inc. All rights reserved.

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Sensitivity of Eisenia andrei (Annelida, Oligochaeta) to a commercial formulation of abamectin in avoidance tests with artificial substrate and natural soil under tropical conditions

Obtaining ecotoxicological data on pesticides in tropical regions is imperative for performing more realistic risk analysis, and avoidance tests have been proposed as a useful, fast and cost-effective tool. Therefore, the present study aimed to evaluate the avoidance behavior of Eisenia andrei to a formulated product, Vertimec(A (R)) 18 EC (a.i abamectin), in tests performed on a reference tropical artificial soil (TAS), to derive ecotoxicological data on tropical conditions, and a natural soil (NS), simulating crop field conditions. In TAS tests an adaptation of the substrate recommended by OECD and ISO protocols was used, with residues of coconut fiber as a source of organic matter. Concentrations of the pesticide on TAS test ranged from 0 to 7 mg abamectin/kg (dry weight-d.w.). In NS tests, earthworms were exposed to samples of soils sprayed in situ with: 0.9 L of Vertimec(A (R)) 18 EC/ha (RD); twice as much this dosage (2RD); and distilled water (Control), respectively, and to 2RD: control dilutions (12.5, 25, 50, 75%). All tests were performed under 25 +/- A 2A degrees C, to simulate tropical conditions, and a 12hL:12hD photoperiod. The organisms avoided contaminated TAS for an EC50,48h = 3.918 mg/kg soil d.w., LOEC = 1.75 mg/kg soil d.w. and NOEC = 0.85 mg/kg soil d.w. No significant avoidance response occurred for any NS test. Abamectin concentrations in NS were rather lower than EC50, 48h and LOEC determined in TAS tests. The results obtained contribute to overcome a lack of ecotoxicological data on pesticides under tropical conditions, but more tests with different soil invertebrates are needed to improve pesticides risk analysis.

A New Control Architecture for Robust Controllers in Rear Electric Traction Passenger HEVs

It is well known that control systems are the core of electronic differential systems (EDSs) in electric vehicles (EVs)/hybrid HEVs (HEVs). However, conventional closed-loop control architectures do not completely match the needed ability to reject noises/disturbances, especially regarding the input acceleration signal incoming from the driver's commands, which makes the EDS (in this case) ineffective. Due to this, in this paper, a novel EDS control architecture is proposed to offer a new approach for the traction system that can be used with a great variety of controllers (e. g., classic, artificial intelligence (AI)-based, and modern/robust theory). In addition to this, a modified proportional-integral derivative (PID) controller, an AI-based neuro-fuzzy controller, and a robust optimal H-infinity controller were designed and evaluated to observe and evaluate the versatility of the novel architecture. Kinematic and dynamic models of the vehicle are briefly introduced. Then, simulated and experimental results were presented and discussed. A Hybrid Electric Vehicle in Low Scale (HELVIS)-Sim simulation environment was employed to the preliminary analysis of the proposed EDS architecture. Later, the EDS itself was embedded in a dSpace 1103 high-performance interface board so that real-time control of the rear wheels of the HELVIS platform was successfully achieved.

Xylitol concentrations in artificial saliva after application of different xylitol dental varnishes

Objective: The present study analyzed xylitol concentrations in artificial saliva over time after application of varnishes containing 10% and 20% xylitol. Material and Methods: Fifteen bovine enamel specimens (8x4 mm) were randomly allocated to 3 groups (n=5/group), according to the type of varnish used: 10% xylitol, 20% xylitol and no xylitol (control). After varnish application (4 mg), specimens were immersed in vials containing 500 mu L of artificial saliva. Saliva samples were collected in different times (1, 8, 12, 16, 24, 48 and 72 h) and xylitol concentrations were analyzed. Data were assessed by two-way repeated-measures ANOVA (p<0.05). Results: Colorimetric analysis was not able to detect xylitol in saliva samples of the control group. Salivary xylitol concentrations were significantly higher up to 8 h after application of the 20% xylitol varnish. Thereafter, the 10% xylitol varnish released larger amounts of that polyol in artificial saliva. Conclusions: Despite the results in short-term, sustained xylitol releases could be obtained when the 10% xylitol varnish was used. These varnishes seem to be viable alternatives to increase salivary xylitol levels, and therefore, should be clinically tested to confirm their effectiveness.

Artificial and natural radioactivity in edible mushrooms from Sao Paulo, Brazil

Environmental biomonitoring has demonstrated that organisms such as crustaceans, fish and mushrooms are useful to evaluate and monitor both ecosystem contamination and quality. Particularly, some mushroom species have a high capacity to retain radionuclides and some toxic elements from the soil and the air. The potential of mushrooms to accumulate radionuclides in their fruit-bodies has been well documented. However, there are no studies that determine natural and artificial radionuclide composition in edible mushrooms, in Brazil. Artificial (Cs-137) and natural radioactivity (K-40. Ra-226. Ra-228) were determined in 17 mushroom samples from 3 commercialized edible mushroom species. The edible mushrooms collected were Agaricus sp., Pleurotus sp. and Lentinula sp. species. The activity measurements were carried out by gamma spectrometry. The levels of Cs-137 varied from 1.45 +/- 0.04 to 10.6 +/- 0.3 Bq kg(-1), K-40 levels varied from 461 +/- 2 to 1535 +/- 10 Bq kg(-1), Ra-226 levels varied from 14 +/- 3 to 66 +/- 12 Bq kg(-1) and Ra-228 levels varied from 6.2 +/- 0.2 to 54.2 +/- 1.7 Bq kg(-1). Cs-137 levels in Brazilian mushrooms are in accordance with the radioactive fallout in the Southern Hemisphere. The artificial and natural activities determined in this study were found to be below the maximum permissible levels as established by national legislation. Thus, these mushroom species can be normally consumed by the population without any apparent risks to human health.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

Detorque evaluation of dental abutment screws after immersion in a fluoridated artificial saliva solution

Purpose: Implant-abutment connections still present failures in the oral cavity due to the loosening of mechanical integrity by detorque and corrosion of the abutment screws. The objective of this study was to evaluate the detorque of dental abutment screws before and after immersion in fluoridated solutions. Materials and Methods: Five commercial implant-abutment assemblies were assessed in this investigation: (C) Conex˜aoR , (E) EmfilsR , (I) INPR , (S) SINR , and (T) Titanium FixR . The implants were embedded in an acrylic resin and then placed in a holding device. The abutments were first connected to the implants and torqued to 20Ncmusing a handheld torque meter. The detorque values of the abutments were evaluated after 10 minutes. After applying a second torque of 20 Ncm, implant-abutment assemblies were withdrawn every 3 hours for 12 hours in a fluoridated solution over a period of 90 days. After that period, detorque of the abutments was examined. Scanning electronicmicroscopy (SEM) associated to energy dispersive spectroscopy (EDS) was applied to inspect the surfaces of abutments. Results: Detorque values of systems C, E, and I immersed in the fluoridated solution were significantly higher than those of the initial detorque. ANOVA demonstrated no significant differences in detorque values between designs S and T. Signs of localized corrosion could not be detected by SEM although chemical analysis by EDS showed the presence of elements involved in corrosive processes. Conclusion: An increase of detorque values recorded on abutments after immersion in fluoridated artificial saliva solutions was noticed in this study. Regarding chemical analysis, such an increase of detorque can result from a corrosion layer formed between metallic surfaces at static contact in the implant-abutment joint during immersion in the fluoridated solutions.

Different protocols to produce artificial dentine carious lesions in vitro and in situ: hardness and mineral content correlation

This study compared dentine demineralization induced by in vitro and in situ models, and correlated dentine surface hardness (SH), cross-sectional hardness (CSH) and mineral content by transverse microradiography (TMR). Bovine dentine specimens (n = 15/group) were demineralized in vitro with the following: MC gel (6% carboxymethylcellulose gel and 0.1 m lactic acid, pH 5.0, 14 days); buffer I (0.05 m acetic acid solution with calcium, phosphate and fluoride, pH 4.5, 7 days); buffer II (0.05 m acetic acid solution with calcium and phosphate, pH 5.0, 7 days), and TEMDP (0.05 m lactic acid with calcium, phosphate and tetraethyl methyl diphosphonate, pH 5.0, 7 days). In an in situ study, 11 volunteers wore palatal appliances containing 2 bovine dentine specimens, protected with a plastic mesh to allow biofilm development. The volunteers dripped a 20% sucrose solution on each specimen 4 times a day for 14 days. In vitro and in situ lesions were analyzed using TMR and statistically compared by ANOVA. TMR and CSH/SH were submitted to regression and correlation analysis (p < 0.05). The in situ model produced a deep lesion with a high R value, but with a thin surface layer. Regarding the in vitro models, MC gel produced only a shallow lesion, while buffers I and II as well as TEMDP induced a pronounced subsurface lesion with deep demineralization. The relationship between CSH and TMR was weak and not linear. The artificial dentine carious lesions induced by the different models differed significantly, which in turn might influence further de- and remineralization processes. Hardness analysis should not be interpreted with respect to dentine mineral loss

Movement of Heterorhabditis amazonensis and Steinernema arenarium in search of corn fall armyworm larvae in artificial conditions

Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae) is considered to be the main pest of maize crops in Brazil. Entomopathogenic nematodes (EPN) may be used to control this pest and exhibit different, unique abilities to search for their hosts. The movement of EPN in relation to S. frugiperda was evaluated. To test for horizontal movement, a styrofoam enclosure filled with sand was divided into segments, nematodes were placed at the entrance to the enclosure and a larva was placed at the end of each division. The same approach was used to evaluate vertical movement; however, PVC pipes were used in this case. In general, the mortality was inversely proportional to the initial distance between host and nematodes. In the vertical displacement test, both nematodes were able to kill the larvae up to a distance of 25 cm. Therefore, the infective juveniles of H. amazonensis and S. arenarium can search out, infect and kill larvae of S. frugiperda at distances of up to 60 cm and 25 cm of horizontal and vertical displacement, respectively.