Determinação de sacarose no xarope artificial de groselha por medidas de viscosidade: uma abordagem interdisciplinar

The development of the National Curriculum Parameters for High School (PCN) is established from a logic in which the disciplines are integrated and coordinated in order to promote interdisciplinarity. However, there are few didactic-pedagogic activities that enable teachers in practice to reach this goal. In this paper, we propose an experimental activity to be used with High School students, addressing the concept of viscosity from an interdisciplinary perspective between the disciplines of Physics and Chemistry. For that purpose, flow times of sucrose solutions of different concentrations will be measured in a glass Ford and these data will be used to construct a calibration curve, which will be used to determine the concentration of sucrose in artificial flavor syrup of gooseberry.

Recycling leather waste: preparing and studying on the microstructure, mechanical, and rheological properties of leather waste/rubber composite

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Artificial neural networks applied to bandsawing process control

In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.

Caracterização espacial e epidemiológica da ocorrência de infecção por agentes de enfermidades transmissíveis em carnívoros selvagens e domésticos de uma área de Mata Atlântica e de floresta artificial no estado do Paraná

Pós-graduação em Medicina Veterinária - FCAV

Estratégias para aumento da concentração de progesterona durante o desenvolvimento do folículo ovulatório em vacas holandesas em lactação submetidas à inseminação artificial em tempo fixo

Pós-graduação em Zootecnia - FMVZ

Análise da influência de variantes do método de solução de escoamentos utilizando os métodos de elementos finitos com compressibilidade artificial e pseudo-características

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influência de aspectos técnicos e anatômicos nos índices de fertilidade baseado no desempenho da inseminação artificial

The aim of this work was to examine both the influence of anatomical and technical aspects on fertility rate of sheep based on the performance of transcervical artificial insemination (TCAI). Transcervical artificial insemination was performed with traction of the cervix in 122 ewes using frozen semen from 11 rams, both Santa Ines breed. The data collected were: type of external cervical opening (CO) (P - papilla; FL - flap; DB - duckbill, S - spiral; RO - rosette), duration of cervical manipulation (2-3, 4-5 and 6-7 minutes), degree of difficulty in cervical transposition (low, moderate, high) and presumed semen deposition site (SC - superficial cervical; DC - deep cervical; IU - intrauterine). The influence of these variables on pregnancy rate was evaluated. Cervical opening type and duration of cervical manipulation had no influence (p>0.05) on fertility. The degree of difficulty in cervical manipulation influenced (p<0.05) pregnancy rate, since insemination classified as low grade had 52% of pregnancy, while those classified as high recorded only 20%. The presumed site of semen deposition influenced significantly (p<0.05) fertility. Pregnancy rates of deposition at each site were: UI – 45.8%, DC – 25.7%; SC – 15.4%. As expected, deeper depositions resulted in higher fertility. In conclusion, the performance of TCAI did not depend on the anatomical classification of external cervical opening of ewe and the duration of cervical manipulation within the range tested (2-7 minutes). The TCAI may have higher fertility rates if difficulties in the application were reduced and the semen deposition was deeper.

Efeito do período pós-parto sobre a taxa de prenhez de vacas de corte submetidas à IATF (Inseminação Artificial em Tempo Fixo)

This work aimed to evaluate the influence of postpartum period (precocious - of 28 to 44 days and late - of 45 to 90 days) on the bovine pregnancy rate using fixed-time AI. For that, 678 cows were divided in two groups: precocious group (G-P, n=151) and late group (G-T, n=527). The animals received CIDR® + 2 mL of estradiol benzoate (BE) in the day zero (D0). After eight days (D8) the dispositive was removed and both groups received 2.5mL PGF2α, concurrent with PGF2α injection, they received either 1.5mL of eCG or temporary calf removal (RTB). In the next day (D9), the cows received 1 mL de BE and 24 hours later, the fixed-time AI was performed with Nelore bovine semen. The calves were returned to their mothers. The pregnancy rate was not different between the groups (p>0.05), G-P=40% and G-T=48%. The results indicate that females with less than 45 days of postpartum are able to hormone protocol of fixed-time IA.

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.

Perda de matéria seca em grãos de milho submetidos a sistemas de secagem natural e artificial.

The permanence of the corn grain in the field, after physiological maturity, is an important cause of crop losses, both in quantitative and qualitative aspect. By ceasing the supply of assimilated substances to grains, due to physiological maturity, the synthesis reactions are overcome by breathing, responsible for the maintenance of the living tissues of the grains, which occur at the expense of reserves accumulated during grain formation. In addition, there are losses from fungus and insects attack due to adverse weather conditions. Technological advances in recent decades, the develop of grain dryers with different capacities and efficiencies, has led to the early withdrawal of the product from the field, still damp, reducing spoilage. Moreover, the use of artificial drying systems can represent a significant cost to the producer. Thus, the present work aimed to study the effect of natural and artificial methods of drying on maize dry matter losses, for Botucatu, city of Sao Paulo state, Brazil. The cornfield production was conducted at the Experimental Farm “Lageado” and the experimental treatments were conducted in the Laboratory of Agricultural Products Processing, in the Department of Rural Engineering, where the drying systems were tested. The treatments were: shade (control), artificial with heated air, artificial unheated air and, drying attached to the plant. The following analyzes for quality monitoring were performed: weight test, thousand-grain weight test and, grain dry weight. The results showed significant loss in quality of drying beans attached to the plant, by assessing the dry matter loss and by the variation of the grain weight. The weight test showed that the worst performance was the artificial with heated air treatment. We used mathematical modeling techniques to describe the dry matter loss and adjusted the mathematical model to the experimental data analyzed. From the experimental data obtained during drying the grain attached to the plant, it was still possible to fit a regression model that estimates the loss of grain dry matter under the climate from Botucatu during the 2011/2012 harvest period.

Artificial Equations, Artificial Distinctions: Language that Poisons the Waters of Ethnic Relations

“It is my contention at this point that when race relations on campuses get better, it is in spite of, not because of, the proliferation of jargon-based rhetoric about diversity.”

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.

Effect of nAellore cows ciclicity on conception and pregnant rates after synchronization protocols for fixed timed artificial insemination

Palhano H.B., Jesus V.L.T., Abidu-Figueiredo M., Baldrighi J.M. & Mello M.R.B. [Effect of nAellore cows ciclicity on conception and pregnant rates after synchronization protocols for fixed timed artificial insemination]. Efeito da ciclicidade de vacas Nelore sobre as taxas de concepcao e de prenhez apos protocolos de sincronizacao para inseminacao artificial em tempo fixo. Revista Brasileira de Medicina Veterinaria, 34(1):63-68, 2012. Departamento de Biologia Animal, Universidade Federal Rural do Rio de Janeiro, BR 465 km 7, Seropedica, RJ 23890-000, Brasil. Email: hbpalhano@gmail.com The present study evaluated the effect on conception and pregnancy rates of Nellore cows selected for Fixed Timed Artificial Insemination (FTAI) program, submitted to four synchronization protocols. Four hundred and ninety lactating females were used and assigned to eight groups: I-OvSynch, n=68, with selection of cycling cows; II-OvSynch + progesterone (P-4), n=67, after selection of non-cycling animals; III-OvSynch, without selection, n=68; IV-OvSynch + P-4, without selection, n=67; V-Co-Synch, n=55, with selection of cycling cows; VI-Co-Synch + P-4, n=55, with selection non-cycling cows; VII- Co-Synch without selection, n=55; VIII- Co-Synch + P-4, without selection, n=55. The conception and pregnancy rates were, respectively, 45.6%, 27.9% and 82.4%, 48.5% for groups I and III; 61.2%, 37.3% and 85.1%, 58.2% for groups II and IV; 43.6%, 25.5% and 80%, 41.8% for groups V and VII; 52.7%, 32.7% and 83.6%, 50.9% for groups VI and VIII. When compared these rates, the results after chi-square test showed significant difference (P < 0.05) among protocols with or without selection. There was no significant difference (P > 0.05) between OvSynch and Co-Synch protocols, with or without P-4 and with selection, considering Co-Synch a viable option for optimization of FTAI. In conclusion, the selection of cows before FTAI program contributed significantly to improve the conception and pregnancy rates.