EIS study of Ti-23Ta alloy in artificial saliva

Although titanium and Ti-6Al-4V alloy have been widely used as dental materials, possible undesirable effects such as cytotoxic reactions and neurological disorder due to metal release led to the development of more corrosion resistant and V and Al free titanium alloys, containing Nb, Zr, Mo and Ta atoxic elements. Fluoride containing products used in the prevention of plaque formation and dental caries can affect the stability of the passive oxide films formed on the Ti alloys. In this work, the corrosion behaviour of the new Ti-23Ta alloy has been evaluated in artificial saliva of different pH and fluoride concentration using electrochemical impedance spectroscopy. Electrochemical impedance spectroscopy study showed that the oxide film formed on the alloy in artificial saliva consists of an inner compact film and an outer porous layer. The corrosion resistance of Ti-23Ta alloy which is reduced by increasing F concentration or decreasing pH is related to the resistance of the inner compact layer. The presence of fluoride and low pH of the saliva enhance the porosity of the oxide film and its dissolution.

Artificial Pinning Center Studies in BI2212 Tapes and Bulks With Zirconium Oxide Inclusion

Zirconium oxide inclusion in Bi2212 superconducting tapes and bulks was studied as possible artificial pinning centers (APC). In order to analyze the zirconium oxide APC addition in Bi2212 samples, magnetization measurements were performed in bulks and transport properties measurements were performed on tapes. In magnetization measurements, the critical current densities are proportional to the width of the magnetization loop at each applied magnetic field. Addition of ZrO(2) in Bi2212 superconductors broadened the magnetization loop and enhanced the critical current densities at 4.2 K in bulks, as a clear indication that ZrO(2) addition improved the pinning and acted as APCs. In contrast, the transport critical current densities decreased in tapes.

Sites of Defoliation by Atta sexdens rubropilosa (Hymenoptera, Formicidae) in Artificial Plants

This study aimed to achieve a better understanding about the foraging behavior of leaf-cutter ant (Atta sexdens rubropilosa Forel) workers with respect to defoliation sites in plants. To accomplish that, artificial plants 70 cm in height were prepared and divided into four levels (heights), having natural plant leaves attached to them. Evaluations during the bioassays included the number of leaves dropped by the ants, as well as the percentage of plant mass removed. In all replicates, it became evident that the most exploited plant site is the apical region, which significantly differed from other plant levels.

A demonstration of artificial dissipation effects in some finite volume solution methods for the Navier-Stokes equations

The artificial dissipation effects in some solutions obtained with a Navier-Stokes flow solver are demonstrated. The solvers were used to calculate the flow of an artificially dissipative fluid, which is a fluid having dissipative properties which arise entirely from the solution method itself. This was done by setting the viscosity and heat conduction coefficients in the Navier-Stokes solvers to zero everywhere inside the flow, while at the same time applying the usual no-slip and thermal conducting boundary conditions at solid boundaries. An artificially dissipative flow solution is found where the dissipation depends entirely on the solver itself. If the difference between the solutions obtained with the viscosity and thermal conductivity set to zero and their correct values is small, it is clear that the artificial dissipation is dominating and the solutions are unreliable.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Equine chorionic gonadotropin and gonadotropin-releasing hormone enhance fertility in a norgestomet-based, timed artificial insemination protocol in suckled Nelore (Bos indicus) cows

Two experiments were conducted to investigate the effects of equine chorionic gonadotropin (eCG) at progestin removal and gonadotropin-releasing hormone (GnRH) at timed artificial insemination (TA!) on ovarian follicular dynamics (Experiment 1) and pregnancy rates (Experiment 2) in suckled Nelore (Bos indicus) cows. Both experiments were 2 x 2 factorials (eCG or No eCG, and GnRH or No GnRH), with identical treatments. In Experiment 1, 50 anestrous cows, 134.5 +/- 2.3 d postpartum, received a 3 mg norgestomet ear implant se, plus 3 mg norgestomet and 5 mg estradiol valerate im on Day 0. The implant was removed on Day 9, with TAI 54 h later. Cows received 400 IU eCG or no further treatment on Day 9 and GnRH (100 mu g gonadorelin) or no further treatment at TAI. Treatment with eCG increased the growth rate of the largest follicle from Days 9 to 11 (means +/- SEM, 1.53 +/- 0.1 vs. 0.48 +/- 0.1 mm/d; P < 0.0001), its diameter on Day 11(11.4 +/- 0.6 vs. 9.3 +/- 0.7 mm; P = 0.03), as well as ovulation rate (80.8% vs. 50.0%, P = 0.02), whereas GnRH improved the synchrony of ovulation (72.0 +/- 1.1 VS. 71.1 +/- 2.0 h). In Experiment 2 (n = 599 cows, 40 to 120 d postpartum), pregnancy rates differed (P = 0.004) among groups (27.6%, 40.1%, 47.7%, and 55.7% for Control. GnRH, eCG, and eCG + GnRH groups). Both eCG and GnRH improved pregnancy rates (51.7% vs. 318%, P = 0.002; and 48.0% vs 37.6%, P = 0.02, respectively), although their effects were not additive (no significant interaction). In conclusion, eCG at norgestomet implant removal increased the growth rate of the largest follicle (LF) from implant removal to TAI, the diameter of the LF at TAI, and rates of ovulation and pregnancy rates. Furthermore, GnRH at TAI improved the synchrony of ovulations and pregnancy rates in postpartum Nelore cows treated with a norgestomet-based TAI protocol. (C) 2010 Elsevier Inc. All rights reserved.

Color stability of silorane-based composites submitted to accelerated artificial ageing-An in situ study

Objectives: To assess the in situ color stability, surface and the tooth/restoration interface degradation of a silorane-based composite (P90, 3M ESPE) after accelerated artificial ageing (AAA), in comparison with other dimethacrylate monomer-based composites (Z250/Z350, 3M ESPE and Esthet-X, Dentsply). Methods: Class V cavities (25 mm(2) x 2 mmdeep) were prepared in 48 bovine incisors, which were randomly allocated into 4 groups of 12 specimens each, according to the type of restorative material used. After polishing, 10 specimens were submitted to initial color readings (Easyshade, Vita) and 2 to analysis by scanning electronic microscopy (SEM). Afterwards, the teeth were submitted to AAA for 384 h, which corresponds to 1 year of clinical use, after which new color readings and microscopic images were obtained. The values obtained for the color analysis were submitted to statistical analysis (1-way ANOVA, Tukey, p < 0.05). Results: With regard to color stability, it was verified that all the composites showed color alteration above the clinically acceptable levels (Delta E >= 3.3), and that the silorane-based composite showed higher Delta E (18.6), with a statistically significant difference in comparison with the other composites (p < 0.05). The SEM images showed small alterations for the dimethacrylate-based composites after AAA and extensive degradation for the silorane-based composite with a rupture at the interface between the matrix/particle. Conclusion: It may be concluded that the silorane-based composite underwent greater alteration with regard to color stability and greater surface and tooth/restoration interface degradation after AAA. (C) 2011 Elsevier Ltd. All rights reserved.

A bacterial artificial chromosome library of Lotus japonicus constructed in an Agrobacterium tumefaciens-transformable vector

We constructed a BAC library of the model legume Lotus japonicus with a 6-to 7-fold genome coverage. We used vector PCLD04541, which allows direct plant transformation by BACs. The average insert size is 94 kb. Clones were stable in Escherichia coli and Agrobacterium tumefaciens.

Axon navigation in the mammalian primary olfactory pathway: Where to next?

The process of establishing long-range neuronal connections can be divided into at least three discrete steps. First, axons need to be stimulated to grow and this growth must be towards appropriate targets. Second, after arriving at their target, axons need to be directed to their topographically appropriate position and in some cases, such as in cortical structures, they must grow radially to reach the correct laminar layer Third, axons then arborize and form synaptic connections with only a defined subpopulation of potential post-synaptic partners. Attempts to understand these mechanisms in the visual system have been ongoing since pioneer studies in the 1940s highlighted the specificity of neuronal connections in the retino-tectal pathway. These classical systems-based approaches culminated in the 1990s with the discovery that Eph-ephrin repulsive interactions were involved in topographical mapping. In marked contrast, it was the cloning of the odorant receptor family that quickly led to a better understanding of axon targeting in the olfactory system. The last 10 years have seen the olfactory pathway rise in prominence as a model system for axon guidance. Once considered to be experimentally intractable, it is now providing a wealth of information on all aspects of axon guidance and targeting with implications not only for our understanding of these mechanisms in the olfactory system but also in other regions of the nervous system.

Use of confocal microscopy to follow the development of penetrative hyphae during growth of Rhizopus oligosporus in an artificial solid-state fermentation system

Two methods were compared for determining the concentration of penetrative biomass during growth of Rhizopus oligosporus on an artificial solid substrate consisting of an inert gel and starch as the sole source of carbon and energy. The first method was based on the use of a hand microtome to make sections of approximately 0.2- to 0.4-mm thickness parallel to the substrate surface and the determination of the glucosamine content in each slice. Use of glucosamine measurements to estimate biomass concentrations was shown to be problematic due to the large variations in glucosamine content with mycelial age. The second method was a novel method based on the use of confocal scanning laser microscopy to estimate the fractional volume occupied by the biomass. Although it is not simple to translate fractional volumes into dry weights of hyphae due to the lack of experimentally determined conversion factors, measurement of the fractional volumes in themselves is useful for characterizing fungal penetration into the substrate. Growth of penetrative biomass in the artificial model substrate showed two forms of growth with an indistinct mass in the region close to the substrate surface and a few hyphae penetrating perpendicularly to the surface in regions further away from the substrate surface. The biomass profiles against depth obtained from the confocal microscopy showed two linear regions on log-linear plots, which are possibly related to different oxygen availability at different depths within the substrate. Confocal microscopy has the potential to be a powerful tool in the investigation of fungal growth mechanisms in solid-state fermentation. (C) 2003 Wiley Periodicals, Inc.

Preliminary clinical trial in percutaneous nephrolithotomy using a real-time navigation system for percutaneous kidney access

Background: Precise needle puncture of renal calyces is a challenging and essential step for successful percutaneous nephrolithotomy. This work tests and evaluates, through a clinical trial, a real-time navigation system to plan and guide percutaneous kidney puncture. Methods: A novel system, entitled i3DPuncture, was developed to aid surgeons in establishing the desired puncture site and the best virtual puncture trajectory, by gathering and processing data from a tracked needle with optical passive markers. In order to navigate and superimpose the needle to a preoperative volume, the patient, 3D image data and tracker system were previously registered intraoperatively using seven points that were strategically chosen based on rigid bone structures and nearby kidney area. In addition, relevant anatomical structures for surgical navigation were automatically segmented using a multi-organ segmentation algorithm that clusters volumes based on statistical properties and minimum description length criterion. For each cluster, a rendering transfer function enhanced the visualization of different organs and surrounding tissues. Results: One puncture attempt was sufficient to achieve a successful kidney puncture. The puncture took 265 seconds, and 32 seconds were necessary to plan the puncture trajectory. The virtual puncture path was followed correctively until the needle tip reached the desired kidney calyceal. Conclusions: This new solution provided spatial information regarding the needle inside the body and the possibility to visualize surrounding organs. It may offer a promising and innovative solution for percutaneous punctures.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.