Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Evaluation of phenotypic stability of resistance to Phytophthora spp. in cacao clones

Resistance of fourteen Theobroma cacao clones to Phytophthora spp. was evaluated using stem inoculations on grafted seedlings. Concepts of phenotypic stability were used to interpret the results and to express horizontality of the resistance. The linear regression coefficient 'b', the determination coefficient (R²) and average lesion size were used to determine the level of horizontal resistance, the phenotypic stability and the predictability of all clones. The results indicated that clones P 7 and MA 15 present highest levels of horizontal resistance and stability, but with moderate predictability. Clones CAS 1 and CEPEC 13 were classified as those with high horizontal resistance, stability and predictability, while clones PA 30, UF 650 and SIAL 88 and EET 59 showed intermediate resistance and stability and high predictability. Clones SPA 17, OC 61, PA 150, SIAL 505, ICS 1 and R 41 presented high susceptibility and intermediate or low stability and moderate or high predictability.

Determination of Alkalinity and dissociation constants of high salinity waters: use of F5BC titration function

Measurements of parameters expressed in terms of carbonic species such as Alkalinity and Acidity of saline waters do not analyze the influence of external parameters to the titration such as Total free and associated Carbonic Species Concentration, activity coefficient, ion pairing formation and Residual Liquid Junction Potential in pH measurements. This paper shows the development of F5BC titration function based on the titrations developed by Gran (1952) for the carbonate system of natural waters. For practical use, samples of saline waters from Pocinhos reservoir in Paraiba were submitted to titration and linear regression analysis. Results showed that F5BC involves F1x and F2x Gran functions determination, respectively, for Alkalinity and Acidity calculations without knowing "a priori" the endpoint of the titration. F5BC also allows the determination of the First and Second Apparent Dissociation Constant of the carbonate system of saline and high ionic strength waters.

Guava fruit loss caused by rust

The aim of this paper was to estimate the loss caused by rust (Puccinia psidii) to 'Paluma' guava production in orchards located in Rio de Janeiro State. The disease intensity on the reproductive organs of plants was observed during two chemical control experiments carried out in 2003 and 2004. The loss was estimated based on simple linear regression and the production reduction (fruit number and weight ha-1) on the incidence of diseased buds and fruits. In the first experiment, no relationship was established between incidence of diseased buds and loss since there was a delay in spraying and the incidence of buds showing rust was high (mean of 47%) at the beginning of flowering. In the second experiment (2003-2004), spraying occurred at the beginning of the epidemics and there was a linear relationship between incidence of diseased buds and loss, justifying fungicide intervention at this stage. For the fruiting stage, a significant relationship was found between incidence of diseased fruits and loss in both experiments. In the absence of chemical control, rust reduced fruit production by around 90%.

Problems and potentialities of e-Learning for regular undergraduate courses in emergency medicine

BACKGROUND: E-learning techniques are spreading at great speed in medicine, raising concerns about the impact of adopting them. Websites especially designed to host courses are becoming more common. There is a lack of evidence that these systems could enhance student knowledge acquisition. GOAL: To evaluate the impact of using dedicated-website tools over cognition of medical students exposed to a first-aid course. METHODS: Prospective study of 184 medical students exposed to a twenty-hour first-aid course. We generated a dedicated-website with several sections (lectures, additional reading material, video and multiple choice exercises). We constructed variables expressing the student's access to each section. The evaluation was composed of fifty multiple-choice tests, based on clinical problems. We used multiple linear regression to adjust for potential confounders. RESULTS: There was no association of website intensity of exposure and the outcome - beta-coeficient 0.27 (95%CI - 0.454 - 1.004). These findings were not altered after adjustment for potential confounders - 0.165 (95%CI -0.628 - 0.960). CONCLUSION: A dedicated website with passive and active capabilities for aiding in person learning had not shown association with a better outcome.

Spatio-temporal modelling of the duration of the cotton cycle in the State Of Goiás, Brazil

The objective of this work was to develop and validate a mathematical model to estimate the duration of cotton (Gossypium hirsutum L. r. latifolium hutch) cycle in the State of Goiás, Brazil, by applying the method of growing degree-days (GD), and considering, simultaneously, its time-space variation. The model was developed as a linear combination of elevation, latitude, longitude, and Fourier series of time variation. The model parameters were adjusted by using multiple-linear regression to the observed GD accumulated with air temperature in the range of 15°C to 40°C. The minimum and maximum temperature records used to calculate the GD were obtained from 21 meteorological stations, considering data varying from 8 to 20 years of observation. The coefficient of determination, resulting from the comparison between the estimated and calculated GD along the year was 0.84. Model validation was done by comparing estimated and measured crop cycle in the period from cotton germination to the stage when 90 percent of bolls were opened in commercial crop fields. Comparative results showed that the model performed very well, as indicated by the Pearson correlation coefficient of 0.90 and Willmott agreement index of 0.94, resulting in a performance index of 0.85.

Determination of the influence of the variation of reducing and non-reducing sugars on coffee quality with use of artificial neural network

The present study aimed at evaluating the use of Artificial Neural Network to correlate the values resulting from chemical analyses of samples of coffee with the values of their sensory analyses. The coffee samples used were from the Coffea arabica L., cultivars Acaiá do Cerrado, Topázio, Acaiá 474-19 and Bourbon, collected in the southern region of the state of Minas Gerais. The chemical analyses were carried out for reducing and non-reducing sugars. The quality of the beverage was evaluated by sensory analysis. The Artificial Neural Network method used values from chemical analyses as input variables and values from sensory analysis as output values. The multiple linear regression of sensory analysis values, according to the values from chemical analyses, presented a determination coefficient of 0.3106, while the Artificial Neural Network achieved a level of 80.00% of success in the classification of values from the sensory analysis.

Evaluation of empirical methods to estimate reference evapotranspiration in Uberaba, State of Minas Gerais, Brazil

Evapotranspiration is the process of water loss of vegetated soil due to evaporation and transpiration, and it may be estimated by various empirical methods. This study had the objective to carry out the evaluation of the performance of the following methods: Blaney-Criddle, Jensen-Haise, Linacre, Solar Radiation, Hargreaves-Samani, Makkink, Thornthwaite, Camargo, Priestley-Taylor and Original Penman in the estimation of the potential evapotranspiration when compared to the Penman-Monteith standard method (FAO56) to the climatic conditions of Uberaba, state of Minas Gerais, Brazil. A set of 21 years monthly data (1990 to 2010) was used, working with the climatic elements: temperature, relative humidity, wind speed and insolation. The empirical methods to estimate reference evapotranspiration were compared with the standard method using linear regression, simple statistical analysis, Willmott agreement index (d) and performance index (c). The methods Makkink and Camargo showed the best performance, with "c" values ​​of 0.75 and 0.66, respectively. The Hargreaves-Samani method presented a better linear relation with the standard method, with a correlation coefficient (r) of 0.88.

Validation study of an overall radiation balance estimation method under Ponta Grossa (PR) Brazil weather conditions

Radiation balance is the fraction of incident solar radiation upon earth surface which is available to be used in several natural processes, such as biological metabolism, water loss by vegetated surfaces, variation of temperature in farming systems and organic decomposition. The present study aimed to assess and validate the performance of two estimation models for Rn in Ponta Grossa city, Paraná State, Brazil. To this end, during the period of 04/01/2008 to 04/30/2011, from radiometric data collected by an automatic weather station set at the Experimental Station, of the State University of Ponta Grossa. We performed a linear regression study by confrontation between measurements made through radiometric balance and Rn estimates obtained from Brunt classical method, and the proposed method. Both models showed excellent performance and were confirmed by the statistical parameters applied. However, the alternative method has the advantage of requiring only global solar radiation values, temperature, and relative humidity.

The use of ALOS/PALSAR data for estimating sugarcane productivity

Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.

Predictors of fluid intravasation during operative hysteroscopy: a preplanned prospective observational study with 200 cases

PURPOSE: To verify the predictors of intravasation rate during hysteroscopy.METHODS: Prospective observational study (Canadian Task Force classification II-1). All cases (n=200 women; 22 to 86 years old) were treated in an operating room setting. Considering respective bag overfill to calculate water balance, we tested two multiple linear regression models: one for total intravasation (mL) and the other for absorption rate (mL.min-1). The predictors tested (independent variables) were energy (mono/bipolar), tube patency (with/without tubal ligation), hysterometry (cm), age≤50 years, body surface area (m2), surgical complexity (with/without myomectomy) and duration (min).RESULTS: Mean intravasation was significantly higher when myomectomy was performed (442±616 versus 223±332 mL; p<0.01). In the proposed multiple linear regression models for total intravasation (adjusted R2=0.44; p<0.01), the only significant predictors were myomectomy and duration (p<0.01).In the proposed model for intravasation rate (R2=0.39; p<0.01), only myomectomy and hysterometry were significant predictors (p=0.02 and p<0.01, respectively).CONCLUSIONS: Not only myomectomy but also hysterometry were significant predictors of intravasation rate during operative hysteroscopy.

Metabolism and gene polymorphisms of the folate pathway in Brazilian women with history of recurrent abortion

PURPOSE: To investigate the association between polymorphisms in genes that encode enzymes involved in folate- and vitamin B12-dependent homocysteine metabolism and recurrent spontaneous abortion (RSA).METHODS: We investigated the C677T and A1298C polymorphisms of the methylenetetrahydrofalate reductase gene (MTHFR), the A2756G polymorphism of the methionine synthase gene (MS) and the 844ins68 insertion of the cystathionine beta synthetase gene (CBS). The PCR technique followed by RFLP was used to assess the polymorphisms; the serum levels of homocysteine, vitamin B12 and folate were investigated by chemiluminescence. The EPI Info Software version 6.04 was used for statistical analysis. Parametric variables were compared by Student's t-test and nonparametric variables by the Wilcoxon rank sum test.RESULTS: The frequencies of gene polymorphisms in 89 women with a history of idiopathic recurrent miscarriage and 150 controls were 19.1 and 19.6% for the C677T, insertion, 20.8 and 26% for the A1298C insertion, 14.2 and 21.9% for the A2756G insertion, and 16.4 and 18% for the 844ins68 insertion, respectively. There were no significant differences between case and control groups in any of the gene polymorphisms investigated. However, the frequency of the 844ins68 insertion in the CBS gene was higher among women with a history of loss during the third trimester of pregnancy (p=0.003). Serum homocysteine, vitamin B12 and folate levels id not differ between the polymorphisms studied in the case and control groups. However, linear regression analysis showed a dependence of serum folate levels on the maintenance of tHcy levels.CONCLUSION: The investigated gene polymorphisms and serum homocysteine, vitamin B12 and folate levels were not associated with idiopathic recurrent miscarriage in the present study. Further investigations are needed in order to confirm the role of the CBS 844ins68 insertion in recurrent miscarriage.

Factors associated with postpartum weight retention in a Brazilian cohort

PURPOSE: To identify the factors associated with weight retention after pregnancy.METHODS: A cohort study was performed with 145 women receiving maternity care at a hospital in Caxias do Sul, Rio Grande do Sul, Brazil, aged 19 to 45 years, between weeks 38 and 42 of pregnancy. The patients were evaluated at one month, three months, and six months after delivery. Student's t-test or one-way analysis of variance (ANOVA) was used to compare groups, as indicated; correlations were assessed with Pearson's and Spearman's tests, as indicated; to identify and evaluate confounders independently associated with total weight loss, a multivariate linear regression analysis was performed and statistical significance was set at p≤0.05.RESULTS: There was a significant positive association between total weight gain - and a negative association with physical exercise during pregnancy - with total weight loss. Higher parity, inter-pregnancy interval, calorie intake, pre-pregnancy body mass index (BMI), weight gain related to pre-pregnancy BMI, presence and severity of depression, and lack of exclusive breastfeeding were directly associated with lower weight loss. Among nominal variables, level of education and marital status were significantly associated with total weight loss.CONCLUSION: In the present study, lower weight retention in the postpartum period was associated with higher educational attainment and with being married. Normal or below-normal pre-pregnancy BMI, physical activity and adequate weight gain during pregnancy, lower parity, exclusive breastfeeding for a longer period, appropriate or low calorie intake, and absence of depression were also determinants of reduced weight retention.