Cluster analysis and artificial neural network on the superovulatory response prediction in mice

Complex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.

Fault location in underground systems using artificial neural networks and PSCAD/EMTDC

The need for high reliability and environmental concerns are making the underground networks the most appropriate choice of energy distribution. However, like any other system, underground distribution systems are not free of failures. In this context, this work presents an approach to study underground systems using computational tools by integrating the software PSCAD/EMTDC with artificial neural networks to assist fault location in power distribution systems. Targeted benefits include greater accuracy and reduced repair time. The results presented here shows the feasibility of the proposed approach. © 2012 IEEE.

Identification of steel bars immersed in reinforced concrete based on experimental results of eddy current testing and artificial neural network analysis

This paper presents an experimental research on the use of eddy current testing (ECT) and artificial neural networks (ANNs) in order to identify the gauge and position of steel bars immersed in concrete structures. The paper presents details of the ECT probe and concrete specimens constructed for the tests, and a study about the influence of the concrete on the values of measured voltages. After this, new measurements were done with a greater number of specimens, simulating a field condition and the results were used to generate training and validation vectors for multilayer perceptron ANNs. The results show a high percentage of correct identification with respect to both, the gauge of the bar and of the thickness of the concrete cover. © 2013 Copyright Taylor and Francis Group, LLC.

Chlorophyll a spatial inference using artificial neural network from multispectral images and in situ measurements

Considering the importance of monitoring the water quality parameters, remote sensing is a practicable alternative to limnological variables detection, which interacts with electromagnetic radiation, called optically active components (OAC). Among these, the phytoplankton pigment chlorophyll a is the most representative pigment of photosynthetic activity in all classes of algae. In this sense, this work aims to develop a method of spatial inference of chlorophyll a concentration using Artificial Neural Networks (ANN). To achieve this purpose, a multispectral image and fluorometric measurements were used as input data. The multispectral image was processed and the net training and validation dataset were carefully chosen. From this, the neural net architecture and its parameters were defined to model the variable of interest. In the end of training phase, the trained network was applied to the image and a qualitative analysis was done. Thus, it was noticed that the integration of fluorometric and multispectral data provided good results in the chlorophyll a inference, when combined in a structure of artificial neural networks.

Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98 fb-1 of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (EÌ̧T>40 GeV) and total hadronic transverse energy (HT>120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified models. © 2013 CERN.

Onboard and real-time artificial satellite orbit determination using GPS

An algorithm for real-time and onboard orbit determination applying the Extended Kalman Filter (EKF) method is developed. Aiming at a very simple and still fairly accurate orbit determination, an analysis is performed to ascertain an adequacy of modeling complexity versus accuracy. The minimum set of to-be-estimated states to reach the level of accuracy of tens of meters is found to have at least the position, velocity, and user clock offset components. The dynamical model is assessed through several tests, covering force model, numerical integration scheme and step size, and simplified variational equations. The measurement model includes only relevant effects to the order of meters. The EKF method is chosen to be the simplest real-time estimation algorithm with adequate tuning of its parameters. In the developed procedure, the obtained position and velocity errors along a day vary from 15 to 20 m and from 0.014 to 0.018 m/s, respectively, with standard deviation from 6 to 10 m and from 0.006 to 0.008 m/s, respectively, with the SA either on or off. The results, as well as analysis of the final adopted models used, are presented in this work. © 2013 Ana Paula Marins Chiaradia et al.

Timing of prostaglandin F2α treatment in an estrogen-based protocol for timed artificial insemination or timed embryo transfer in lactating dairy cows

Objectives were to investigate progesterone concentrations and fertility comparing 2 different intervals from PGF2α treatment and induced ovulation in an estrogen-based ovulation synchronization protocol for timed artificial insemination (TAI) or timed embryo transfer (TET) in lactating dairy cows. A total of 1,058 lactating Holstein cows [primiparous (n=371) and multiparous (n=687)], yielding 34.1±0.33 kg of milk/d at various days in milk were randomly assigned to receive treatment with PGF2α on either d 7 or 8 of the following protocol: d 0: 2mg of estradiol benzoate + controlled internal drug release device; d 8: controlled internal drug release device removal + 1.0mg of estradiol cypionate; d 10: TAI or d 17: TET. Only cows with a corpus luteum at d 17 received an embryo and all cows received GnRH at TET. Pregnancy diagnoses were performed by detection (transrectal ultrasonography) of an embryo on d 28 or a fetus on d 60. Fertility [pregnancy per artificial insemination (P/AI) or pregnancy per embryo transfer (P/ET)] was affected by breeding technique (AI vs. ET) and time of PGF2α treatment (d 7 vs. 8) at the 28-d pregnancy diagnosis for TAI [32.9% (238) vs. 20.6% (168)] and TET cows [47% (243) vs. 40.7% (244)] and at the 60-d pregnancy diagnosis for TAI [30% (238) vs. 19.2% (168)] and TET cows [37.9% (243) vs. 33.5% (244)]. The progesterone (P4) concentration at d 10 altered fertility in TAI cows, with higher P/AI in cows with P4 concentration <0.1 ng/mL compared with cows with P4 concentration ≥0.1 ng/mL, and in ET cows, with higher P/ET in cows with P4 concentration <0.22 ng/mL compared with cows with P4 concentration ≥0.22 ng/mL. Prostaglandin F2α treatment at d 7 increased the percentage of cows with P4 <0.1 ng/mL on d 10 [39.4 (85) vs. 23.2 (54)]. Reducing the period between PGF2α and TAI from 72 to 48h in dairy cows resulted in a clear reduction in fertility in cows bred by TAI and a subtle negative effect in cows that received TET. The earlier PGF2α treatment benefits are most likely mediated through gamete transport, fertilization, or early embryo development and a more subtle effect of earlier PGF2α treatment that may be mediated through changes in the uterine or hormonal environment that manifests itself after ET on d 7. © 2013 American Dairy Science Association.

Effects of artificial substrate and night-time aeration on the water quality in Macrobrachium amazonicum (Heller 1862) pond culture

The effects of artificial substrate and night-time aeration on the culture of Macrobrachium amazonicum were evaluated in 12 ponds stocked with 45 prawns m-2. A completely randomized design in 2 × 2 factorial scheme with three replicates was used. The combination of factors resulted in four treatments: with substrate and aeration (SA), with substrate and without aeration (SWA), without substrate and with aeration (WSA) and without substrate and aeration (WSWA). The presence of substrate in SA and SWA treatments reduced suspended particles (seston) by ~17.3% and P-orthophosphate by ~50%. The use of aerator (WSA and SA treatments) significantly (P < 0.05) increased the concentration of dissolved oxygen, suspended particles and nutrients in the pond water. These results indicate that the effect of substrate on turbidity and total suspended solids (TSS) values is opposite to the effect of the aerator. The aerators in semi-intensive grow-out M. amazonicum farming lower water quality because they increased the amount of detritus and nutrients in the pond water. On the other hand, the use of artificial substrate reduces turbidity values, chlorophyll a, TSS and P-orthophosphate concentrations. Therefore, the combination of substrate addition and night-time aeration is not interesting because they have opposite effects. © 2013 John Wiley & Sons Ltd.

Artificial neural network model of discharge lamps in the power quality context

This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

Genotoxicological assessment of two reactive dyes extracted from cotton fibres using artificial sweat

Human eyes have a remarkable ability to recognize hundreds of colour shades, which has stimulated the use of colorants, especially for clothing, but toxicological studies have shown that some textile dyes can be hazardous to human health. Under conditions of intense perspiration, dyes can migrate from coloured clothes and penetrate into human skin. Garments made from cotton fabrics are the most common clothing in tropical countries, due to their high temperatures. Aiming to identify safe textile dyes for dyeing cotton fabrics, the genotoxicity [in vitro Comet assay with normal human dermal fibroblasts (NHDF), Tail Intensity] and mutagenicity [Salmonella/microsome preincubation assay (30 min), tester strains TA98, TA100, YG1041 and YG1042] of Reactive Blue 2 (RB2, CAS No. 12236-82-7, C.I. 61211) and Reactive Green 19 (RG19, CAS No. 61931-49-5, C.I. 205075) were evaluated both in the formulated form and as extracted from cotton fibres using different artificial sweats. Both the dyes could migrate from cotton fibres to sweat solutions, the sweat composition and pH being important factors during this extraction. However, the dye sweat solutions showed no genotoxic/mutagenic effects, whereas a weak mutagenic potential was detected by the Ames test for both dyes in their formulated form. These findings emphasize the relevance of textile dyes assessment under conditions that more closely resemble human exposure, in order to recognize any hazard. © 2013 Elsevier Ltd. All rights reserved.

Influence of artificial aging in marginal adaptation of mixed class V cavities

The aim of this study was to investigate whether the artificial aging by thermal cycling had influenced the marginal adaptation of class V restorations with/without chlorhexidine application in the bond process. Twelve intact human third molars were used. Class V cavity preparations were performed on the buccal surface and the teeth received 35% phosphoric acid-etching procedure (Ultradent Products Inc., South Jordan, Utah, USA). Subsequently, the samples were divided in two groups: Untreated acid-etched dentin and chlorhexidine application as an adjunct in the bond process. The adhesive Single Bond 2 (3M ESPE, St. Paul, MN, USA) was used after 2% chlorhexidine application, and the restorations were performed with FiltekTM Z350 XT (3M ESPE) composite resin. The specimens were submitted to artificial aging by thermal cycling with 3,000 cycles. Analyzes were performed on scanning electron microscopy using replicas of marginal adaptation in percentage of continuous margin before and after the artificial aging. The data were analyzed by paired test and the results showed statistically significant differences in the percentage of continuous margin with/without chlorhexidine treatment before and after thermal cycling. This study concluded that the artificial aging by thermal cycling influenced the marginal adaptation of mixed class V composite restorations.

Timed artificial insemination programs during the summer in lactating dairy cows: Comparison of the 5-d Cosynch protocol with an estrogen/progesterone-based protocol

The objective of this study was to compare a GnRH-based to an estrogen/progesterone (E2/P4)-based protocol for estrous cycle synchronization and fixed timed artificial insemination (TAI), both designed for synchronization of ovulation and to reduce the period from follicular emergence until ovulation in cows with a synchronized follicular wave. A total of 1,190 lactating Holstein cows (primiparous: n = 685 and multiparous: n = 505) yielding 26.5 ± 0.30 kg of milk/d at 177 ± 5.02 d in milk were randomly assigned to receive one of the following programs: 5-d Cosynch protocol [d -8: controlled internal drug release (CIDR) + GnRH; d -3: CIDR removal + PGF2α; d -2: PGF2α; d 0: TAI + GnRH] or E2/P4 protocol (d -10: CIDR + estradiol benzoate; d -3: PGF2α; d -2: CIDR removal + estradiol cypionate; d 0: TAI). Rectal temperature and circulating progesterone (P4) were measured on d -3, -2, 0 (TAI), and 7. The estrous cycle was considered to be synchronized when P4 was ≥1.0 ng/mL on d 7 in cows that had luteolysis (P4 ≤0.4 ng/mL on d 0). To evaluate the effects of heat stress, cows were classified by number of heat stress events: 0, 1, and 2-or-more measurements of elevated body temperature (≥39.1°C). Pregnancy success (pregnancy per artificial insemination, P/AI) was determined at d 32 and 60 after TAI. The cows in the 5-d Cosynch protocol had increased circulating P4 at the time of PGF2α injection (2.66 ± 0.13 vs. 1.66 ± 0.13 ng/mL). The cows in the E2/P4 protocol were more likely to be detected in estrus (62.8 vs. 43.4%) compared with the cows in the 5-d Cosynch protocol, and expression of estrus improved P/AI in both treatments. The cows in the 5-d Cosynch protocol had greater percentage of synchronized estrous cycle (78.2%), compared with cows in the E2/P4 protocol (70.7%). On d 60, the E2/P4 protocol tended to improve P/AI (20.7 vs. 16.7%) and reduced pregnancy loss from 32 to 60 d (11.0 vs. 19.6%), compared with the 5-d Cosynch protocol. In cows with their estrous cycle synchronized, the E2/P4 protocol had greater P/AI (25.6 vs. 17.7%) on d 60 and lower pregnancy loss from 32 to 60 d (6.7 vs. 21.7%) compared with cows in the 5-d Cosynch protocol. Follicle diameter affected pregnancy loss from 32 to 60 d only in the cows in the 5-d Cosynch protocol, with smaller follicles resulting in greater pregnancy loss. Pregnancy per AI at d 60 was different between protocols in the cows with 2 or more measurements of heat stress (5-d Cosynch = 12.2% vs. E2/P4 = 22.8%), but not in the cows without or with 1 heat stress measurement. In conclusion, the 5-d Cosynch protocol apparently produced better estrous cycle synchronization than the E2/P4 protocol but did not improve P/AI. The potential explanation for these results is that increased E2 concentrations during the periovulatory period can improve pregnancy success and pregnancy maintenance, and this effect appears to be greatest in heat-stressed cows when circulating E2 may be reduced. © 2013 American Dairy Science Association.