Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Electrochemical impedance spectroscopy investigation of the electrochemical behaviour of copper coated with artificial patina layers and submitted to wet and dry cycles

Due to rain events historical monuments exposed to the atmosphere are frequently submitted to wet and dry cycles. During drying periods wetness is maintained in some confined regions and the corrosion product layer, generally denominated patinas, builds up and gets thicker. The aim of this study is to use electrochemical impedance spectroscopy (EIS) to investigate the electrochemical behaviour of pure copper coated with two artificial patina layers and submitted either to continuous or to intermittent immersion tests, this latter aiming to simulate wet and dry cycles. The experiments were performed in 0.1 mol dm(-3) NaCl solution and in artificial rainwater containing the most significant pollutants of the city of Sao Paulo. The results of the continuous immersion tests in the NaCl solution have shown that the coated samples behave like a porous electrode with finite pore length. On the other hand, in the intermittent tests a porous electrode response with semi-infinite pore length can be developed. The results were interpreted based on the model of de Levie and a critical comparison with previous interpretations reported in the literature for similar systems is presented. (C) 2011 Elsevier Ltd. All rights reserved.

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.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Operational regimes for a simplified one-step artificial chaperone refolding method

The artificial chaperone method for protein refolding developed by Rozema et al. (Rozema, D.; Gellman, S. H. J. Am. Chem. Soc. 1995, 117 (8), 2373-2374) involves the sequential dilution of denatured protein into a buffer containing detergent (cetyltrimethylammonium bromide, CTAB) and then into a refolding buffer containing cyclodextrin WD). In this paper a simplified one-step artificial chaperone method is reported, whereby CTAB is added directly to the denatured solution, which is then diluted directly into a refolding buffer containing P-cyclodextrin (P-CD). This new method can be applied at high protein concentrations, resulting in smaller processing volumes and a more concentrated protein solution following refolding. The increase in achievable protein concentration results from the enhanced solubility of CTAB at elevated temperatures in concentrated denaturant. The refolding yields obtained for the new method were significantly higher than for control experiments lacking additives and were comparable to the yields obtained with the classical two-step approach. A study of the effect of beta-CD and CTAB concentrations on refolding yield suggested two operational regimes: slow stripping ( beta-CDXTABsimilar to1), most suited for higher protein concentrations, and fast stripping (beta-CD/CTABsimilar to2.7), best suited for lower protein concentrations. An increased chaotrope concentration resulted in higher refolding yields and an enlarged operational regime.

Brood production increases when artificial heating is provided to colonies of stingless bees

Although stingless bees are capable of maintaining their nest temperature within certain limits, brood production of several species declines or even completely stops during periods of low ambient temperature. In the present study, we investigated whether the brood production of the meliponine species Nannotrigona testaceicornis can be artificially increased through heating the colonies during the cold season. For this, we monitored the rate of brood cell production of seven hives in intervals of 24 hours under two different experimental conditions: 1. without; and 2. with heating. Each treatment (first with and subsequently without heating) lasted for nine consecutive days. The ambient temperature (TA) during both experimental periods was very similar (TA(WITH) = 16.1 degrees C; TA(WITHOUT) = 16.3 degrees C). On average, the colonies built 3.6 brood cells per day without and 15.8 brood cells per day with artificial heating (Wilcoxon Rank Sum test: T = 10, Z = 4, P < 0.001). In both treatments, the rate of brood cell production increased with increasing environmental temperature (Spearman Rank Correlation: R(WITH) = 0.71, P = 0.02; R(WITHOUT) = 0.66, P = 0.05). We concluded that artificial heating during cold periods increased the brood cell production in N. testaceicornis Our results indicate that the use of heaters for stingless bee hives during periods of low ambient temperature may be helpful for stingless beekeeping.

A prospective study evaluating the efficacy of the artificial sphincter AMS 800 for the treatment of postradical prostatectomy urinary incontinence and the correlation between preoperative urodynamic and surgical outcomes

OBJECTIVES We have evaluated prospectively the long-term efficacy of the artificial urinary sphincter (AUS) AMS 800 for the treatment postradical prostatectomy urinary incontinence (PRPUI) patients. We also evaluated the correlation between preoperative urodynamic findings and surgical outcomes. METHODS From May 1997 to April 2003, 40 consecutive patients with PRPUI caused by intrinsic sphincter deficiency (ISD) were treated with the AMS 800. Mean age was 68.3 +/- 6.3 years. Continence status was evaluated on the basis of pad count, impact of urinary incontinence on the quality of life, complications, and surgical revisions. Preoperative urodynamic findings were correlated with surgical outcomes. RESULTS Follow-up ranged from 27 to 132 months (mean = 53.4 +/- 21.4 months). There was a significant reduction in pad count from 4.0 +/- 0.9 to 0.62 +/- 1.07 diapers per day (P <0.001) leading to continence in 90%. There was a significant reduction on the impact of incontinence decreasing from 5.0 +/- 0.7 to 1.4 +/- 0.93 (P <0.001) in a visual analogue scale (VAS). Surgical revision rate was 20%. Preoperative urodynamics was useful to identify sphincter deficiency. Except by a tendency of worse results in patients with reduced bladder compliance (RBC), other urodynamic parameters did not correlate with a worse surgical outcome. CONCLUSIONS The AMS 800 offers good long-term continence to most PRPUI patients. Preoperative findings like detrusor hyperactivity (DH), impaired detrusor contraction (IDC), low Valsalva leak point pressure, bladder outlet obstruction (BOO), and mild RBC were not associated with worse surgical outcomes.

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.