PBL and B-Learning for Civil Engineering Students in a Transportation Course

The results of a pedagogical strategy implemented at the University of Sao Paulo at Sao Carlos are presented and discussed. The initiative was conducted in a transportation course offered to Civil Engineering students. The approach is a combination of problem-based learning and project-based learning (PBL) and blended-learning (B-learning). Starting in 2006, a different problem was introduced every year. From 2009 on, however, the problem-based learning concept was expanded to project-based learning. The performance of the students was analyzed using the following elements: (1) grades in course activities; (2) answers from a questionnaire designed for course evaluation; and (3) cognitive maps made to assess the effects of PBL through the comparison of the responses provided by the students involved and those not involved in the experiment. The results showed positive aspects of the method, such as a strong involvement of several students with the subject. A gradual increase in the average scores obtained by the students in the project activities (from 6.77 in 2006 to 8.24 in 2009) was concomitant with a better evaluation of these activities and of the course as a whole (90 and 97% of options "Good" or "Very good" in 2009, respectively). A growing interest in the field of transportation engineering as an alternative for further studies was also noticed. DOI: 10.1061/(ASCE)EI.1943-5541.0000115. (C) 2012 American Society of Civil Engineers.

Performance tests of two small trigeneration pilot plants

Trigeneration systems have been used with advantage in the last years in distributed electricity generation systems as a function of a growth of natural gas pipeline network distribution system, tax incentives, and energy regulation policies. Typically, a trigeneration system is used to produce electrical power simultaneously with supplying heating and cooling load by recovering the combustion products thermal power content that otherwise would be driven to atmosphere. Concerning that, two small scale trigeneration plants have been tested for overall efficiency evaluation and operational comparison. The first system is based on a 30 kW (ISO) natural gas powered microturbine, and the second one uses a 26 kW natural gas powered internal combustion engine coupled to an electrical generator as a prime mover. The stack gases from both machines were directed to a 17.6 kW ammonia-water absorption refrigeration chiller for producing chilled water first and next to a water heat recovery boiler in order to produce hot water. Experimental results are presented along with relevant system operational parameters for appropriate operation including natural gas consumption, net electrical and thermal power production, i.e., hot and cold water production rates, primary energy saving index, and the energy utilization factor over total and partial electrical load operational conditions. (c) 2011 Elsevier Ltd. All rights reserved.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Comparative performance evaluation of hepatitis C virus genotyping based on the 5' untranslated region versus partial sequencing of the NS5B region of brazilian patients with chronic hepatitis C

Background Genotyping of hepatitis C virus (HCV) has become an essential tool for prognosis and prediction of treatment duration. The aim of this study was to compare two HCV genotyping methods: reverse hybridization line probe assay (LiPA v.1) and partial sequencing of the NS5B region. Methods Plasma of 171 patients with chronic hepatitis C were screened using both a commercial method (LiPA HCV Versant, Siemens, Tarrytown, NY, USA) and different primers targeting the NS5B region for PCR amplification and sequencing analysis. Results Comparison of the HCV genotyping methods showed no difference in the classification at the genotype level. However, a total of 82/171 samples (47.9%) including misclassification, non-subtypable, discrepant and inconclusive results were not classified by LiPA at the subtype level but could be discriminated by NS5B sequencing. Of these samples, 34 samples of genotype 1a and 6 samples of genotype 1b were classified at the subtype level using sequencing of NS5B. Conclusions Sequence analysis of NS5B for genotyping HCV provides precise genotype and subtype identification and an accurate epidemiological representation of circulating viral strains.

Evaluation of the performance of a castor-oil based formulation in limiting pesticide residues in strawberry crops

A study was made to evaluate the effect of a castor oil-based detergent on strawberry crops treated with different classes of pesticides, namely deltamethrin, folpet, tebuconazole, abamectin and mancozeb, in a controlled environment. Experimental crops of greenhouse strawberries were cultivated in five different ways with control groups using pesticides and castor oil-based detergent. The results showed that the group 2, which was treated with castor oil-based detergent, presented the lowest amount of pesticide residues and the highest quality of fruit produced.

Performance of six diagnostic tests to screen for Chagas disease in blood banks and prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening based on the analysis of epidemiological variables

OBJECTIVE: The frequent occurrence of inconclusive serology in blood banks and the absence of a gold standard test for Chagas'disease led us to examine the efficacy of the blood culture test and five commercial tests (ELISA, IIF, HAI, c-ELISA, rec-ELISA) used in screening blood donors for Chagas disease, as well as to investigate the prevalence of Trypanosoma cruzi infection among donors with inconclusive serology screening in respect to some epidemiological variables. METHODS: To obtain estimates of interest we considered a Bayesian latent class model with inclusion of covariates from the logit link. RESULTS: A better performance was observed with some categories of epidemiological variables. In addition, all pairs of tests (excluding the blood culture test) presented as good alternatives for both screening (sensitivity > 99.96% in parallel testing) and for confirmation (specificity > 99.93% in serial testing) of Chagas disease. The prevalence of 13.30% observed in the stratum of donors with inconclusive serology, means that probably most of these are non-reactive serology. In addition, depending on the level of specific epidemiological variables, the absence of infection can be predicted with a probability of 100% in this group from the pairs of tests using parallel testing. CONCLUSION: The epidemiological variables can lead to improved test results and thus assist in the clarification of inconclusive serology screening results. Moreover, all combinations of pairs using the five commercial tests are good alternatives to confirm results.

Reliability-based design optimization strategies based on FORM: a review

In deterministic optimization, the uncertainties of the structural system (i.e. dimension, model, material, loads, etc) are not explicitly taken into account. Hence, resulting optimal solutions may lead to reduced reliability levels. The objective of reliability based design optimization (RBDO) is to optimize structures guaranteeing that a minimum level of reliability, chosen a priori by the designer, is maintained. Since reliability analysis using the First Order Reliability Method (FORM) is an optimization procedure itself, RBDO (in its classical version) is a double-loop strategy: the reliability analysis (inner loop) and the structural optimization (outer loop). The coupling of these two loops leads to very high computational costs. To reduce the computational burden of RBDO based on FORM, several authors propose decoupling the structural optimization and the reliability analysis. These procedures may be divided in two groups: (i) serial single loop methods and (ii) unilevel methods. The basic idea of serial single loop methods is to decouple the two loops and solve them sequentially, until some convergence criterion is achieved. On the other hand, uni-level methods employ different strategies to obtain a single loop of optimization to solve the RBDO problem. This paper presents a review of such RBDO strategies. A comparison of the performance (computational cost) of the main strategies is presented for several variants of two benchmark problems from the literature and for a structure modeled using the finite element method.

Flexural strengthening of reinforced concrete beams with carbon fibers reinforced polymer (CFRP) sheet bonded to a transition layer of high performance cement-based composite

Resistance to corrosion, high tensile strength, low weight, easiness and rapidity of application, are characteristics that have contributed to the spread of the strengthening technique characterized by bonding of carbon fibers reinforced polymer (CFRP). This research aimed to develop an innovate strengthening method for RC beams, based on a high performance cement-based composite of steel fibers (macro + microfibers) to be applied as a transition layer. The purpose of this transition layer is better control the cracking of concrete and detain or even avoid premature debonding of strengthening. A preliminary study in short beams molded with steel fibers and strengthened with CFRP sheet, was carried out where was verified that the conception of the transition layer is valid. Tests were developed to get a cement-based composite with adequate characteristics to constitute the layer transition. Results showed the possibility to develop a high performance material with a pseudo strain-hardening behavior, high strength and fracture toughness. The application of the strengthening on the transition layer surface had significantly to improve the performance levels of the strengthened beam. It summary, it was proven the efficiency of the new strengthening technique, and much information can be used as criteria of projects for repaired and strengthened structures.