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Copyright of Brazilian Journal of Production Engineering / Revista Brasileira de Engenharia de Produção is the property of Brazilian Journal of Production Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Exacta is the property of Exacta - Engenharia de Producao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article focuses on the episode of a southern swell in the Canary Islands from August 9 to 16, 2023. It examines the socioeconomic effects, characterization, and behavior of the waves, analyzing their origins, impacts, and predictive models. It mentions that the study reveals the significant impact of such events on the southern coasts of the Canary Islands, detailing their origins, characteristics, and predictive patterns.

ABSTRACT Top-quality pellets can significantly increase density and durability of agricultural residues, reducing logistic costs. However, these pellets depend on numerous parameters, including feedstock properties and production conditions. To ensure high-quality pellets, a single-factor experiment and the response surface methodology were used to investigate the effects of particle size, moisture content, molding pressure, pelleting time, ultrasonic power, and interaction effects between variables on density and durability of pellets for ultrasonic vibration-assisted pelleting of corn stover. The response surface models between variables and response were established. The results showed that all variables affect the density and durability of pellets. An optimal condition for density and durability was obtained, and a further experiment was conducted to validate the values. The results suggested that desirability (0.999) under optimal conditions confirmed the validation of models. The optimal combination of process parameters included particle size of 1.5 mm, moisture content of 10 %, molding pressure of 379 kPa, pelleting time of 80 s, ultrasonic power of 250 W, with values of 1,381.14 kg m–3 and 97.58 % for density and durability of pellets, respectively.

The objective of this study is to carry out a comparative analysis with the application of two models, the Autoregressive Integrated Moving Average (ARIMA) and the Vectorial Autoregression (VAR), in the sponsoring companies of the Entidades Fechadas de Previdência Complementar, listed in Brasil, Bolsa, Balcão (B3). Through a quasi-experimental action, two models were utilized, the Autoregressive Integrated Moving Average (ARIMA) and the Vector Autoregression model (ARV). Based on the predictive results of these models, it was possible to identify that the data run by the ARIMA method did not present a good fit, it was possible to conclude that the model created by ARV was more robust in predicting future situations of the analyzed companies, and that, decisions based on predictive models, pointed to the need to anticipate decisions on the discount rate, the inflation rate, the rate of salary increase and on the guaranteeing assets. [ABSTRACT FROM AUTHOR]

ABSTRACT Due to the conditions in which traditional sheep production systems operate, the evaluation of animal growth from live weight (LW) is limited by the high cost of the livestock scale as well as the sophisticated maintenance required. In this scenario, in recent years, biometric measurements have been investigated as an accurate indirect method to predict the LW of farm animals. Therefore, the present study was undertaken to examine different models for predicting the body weight of growing lambs using the body volume (BV) formula. Body volume, heart girth (HG) and body length (BL) data of 290 lambs aged between two and eight months were recorded. Body volume was calculated from HG and BL data using a formula that calculates the volume of a cylinder. The estimation of LW from the BV formula was achieved through regression equations using three mathematical models (linear, quadratic and exponential). The mean values of LW, HG, BL and BV of the lambs were 29.12±12.04kg, 70.00±11.69cm, 38.40±6.43cm and 23.93±9.90dm3, respectively. The correlation coefficient between LW and BV was r = 0.96 (P

The use of machine learning approaches in sports has been grown in the last decade. Sports analytics, outcome match results, and possible player’s injury are examples of machine learning applications. Accordingly, this work aims to use machine learning techniques to build models to predict FutSal National League (LNF) results (win/loss/draw) based on data collected in the first half of a match. To accomplish that, we extract the data from the LNF website, and, based on the data, we propose six new features using the concept of team strength. The data correspond to the 2016 to 2019 seasons. The models are built usimg machine learning approaches, and they are validated through an accuracy metric. We build ten models, and the predictions are organized as follows: the individual performance of each model and a voting approach (committee) based on the majority of the predicted results. The results show that the individual models get better performance when predicting a single result (e.g., home win) with 95% accuracy. On the other hand, the committee gets a better performance regarding the overall results. The win, loss, and draw results reach almost 79% accuracy.

This paper investigates the phenomenon of judicial reorganization in Brazil between the years 2013 to 2018, identifying key factors that explain the process of judicial reorganization. Specifically, this research answers to the following question: for the Brazilian case, what are the relevant variables to forecast judicial reorganization? Thus, it seeks to put down an existing gap, since no work has been found in the literature dealing with the forecast of judicial reorganization in Brazil. This research is justified by the following factors: relevance and growth of judicial reorganization, seen from the perspective of the Brazilian reorganization law; the scarce empirical literature that deals with judicial reorganization in Brazil; the importance of the existence of quantitative models that explain with high precision the judicial reorganization of companies in Brazil. This research advances the frontier on judicial recovery in Brazil and increases the empirical knowledge about the applicability of Brazilian Law 11.101/2005. To answer the question above, two predictive models were developed, comparing them, a Cox model and a logistic model. The results show the use and effectiveness of both methods, although highlights the superiority of the logistic model as the predictive method of judicial reorganization in Brazil, based in indicators of liquidity, profitability, indebtedness and rotativity. [ABSTRACT FROM AUTHOR]

Mango production presents challenges, such as the maturation of the mango branches, which, combined with good nutrition and biochemicals involved in this process, such as carbohydrate and starch favor the development of the plant. Therefore, the use of non-destructive, fast techniques to determine the levels of these components in the plant, such as spectroscopy, can optimize the analysis of these components. Therefore, this work aimed to develop predictive models for determination of starch and carbohydrate contents in "Palmer" mango leaves using vis-nir spectroscopy subjected to different potassium sources. The work was carried out in the region of San Francisco Valley, using the following steps: (1) leaf sampling; (2) spectral analysis; (3) lab determination of carbohydrate and starch contents; and (4) development of predictive regression and classification models. The predictive regression models used were Principal Components Regression (PCR) and Partial Least Squares Regression (PLSR). Supervised discriminant models were also developed to classify mango leaves according to different potassium sources used, using linear discriminant analysis (LDA). Vis-NIR spectroscopy showed low values for the non-destructive evaluation of "Palmer" mango leaves using PCR and PLSR for carbohydrate and starch prediction with R2 of 0.58 lower than the models considered excellent (R² >0.90); The development of classification models did not allow the discrimination of different sources of potassium in "Palmer" mango leaves with an accuracy of 64.2%. [ABSTRACT FROM AUTHOR]

Objective: To map care technologies capable of subsidizing safety in the stages of the organ transplantation process. Methods: Scope review developed in five stages through searches in six databases, between October and November 2020. Results: Among the selected publications, 2020 was the year with the highest number of studies (25.92%), the PubMed database had the largest selection of articles (37.03%) and the country with the largest number of publications was the United States (51.85%). As for the care technologies identified, 77.77% were light-hard and 22.22% were hard. Regarding the type of technology, 51.85% are digital, 22.22% machines / equipment, 14.81% predictive models and others related to protocol and robotic technology (11.11%). Conclusion: In relation to the potential of the technologies, they provide monitoring, data tracking, health education, permanent education, rapid and effective communication of organs, as well as quality in the stages of the transplant and safety processes. The impact of this study is the visualization of the panorama of technological development in health in the context of organ transplants, highlighting the areas that are being studied and the problems in this context that are being solved through health technologies. [ABSTRACT FROM AUTHOR]

We present a review of how Type Ia Supernovae (SN Ia) are used in cosmology to estimate cosmological models parameters. In particular, we discuss how they helped with the paradigm shift observed at the turn of the last century to this one: the Universe is in an accelerated expansion rate. For this, we will discuss how to delimit cosmological parameters, especially the deceleration parameter, with the definition of a type of distance in cosmology, which is calculated knowing the luminosity of astrophysical objects. We developed a software to be used with this article by teachers in their classes or orientations, as well as by students in their individual studies. The SimECosmo, acronym for Simulador para o Ensino de Cosmologia, has a user interface and allows the visualization of how cosmological parameters affect model predictions, comparing with SN Ia data from the Union 2.1 and Pantheon Sample compilations. [ABSTRACT FROM AUTHOR]

Objective: To build an evaluation predictive model of time between Human Immunodeficiency Virus diagnosis and first hospitalization. Methods: An epidemiological, descriptive, and retrospective study, with a sample of 200 medical records of people with Acquired Immunodeficiency Syndrome, monitored in a specialized service. Survival analysis was performed using the Kaplan-Meier estimator, the Weibull parametric model, and the Cox semi-parametric model. Results: There were significant differences in time between diagnosis and hospitalization regarding age, sexual orientation, therapy discontinuation records, and the number of medical and multidisciplinary consultations. The Weibull model presented the record of therapy discontinuity as a significant co-variable. In the Cox model, the occupation, alcohol and psychotropic use, T-CD4+ lymphocyte count, viral load, and psychiatric history variables were significant to explain the risk of hospitalization. Conclusion: It was possible to identify the risk and protection factors for the outcome hospitalization. The models also pointed out factors that influence the time between human immunodeficiency virus diagnosis and first hospitalization, and enabled an enriching discussion about the intrinsic aspects of health care for people living with the virus and the disease. [ABSTRACT FROM AUTHOR]

ABSTRACT Mapping the chemical attributes of the soil on a large scale can result in gains when planning the use and occupation of the land. There are different techniques available for this purpose, whose performance should be tested for different types of landscapes. The aim of this study was to spatialize chemical attributes of the soil, comparing eight methods of prediction. Forty morphometric attributes, generated from a digital elevation model, were used as independent variables, in addition to geophysical data, images from the Landsat 8 satellite and the NDVI. All possible combinations between the satellite bands were calculated, generating 28 new variables. Combinations between the Th, U and K bands obtained from the geophysical data were also calculated, generating a further three variables. The final variables to be calculated were the distances between the four points of the edges of the basin (d1, d2, d3 and d4). The dependent variables for the model were Al, Ca, Fe, K, Mg, Na, Si, Ti, Cr, Cu, Mn, Ni, P, Pb, V, Zn, Zr, S and Cl. A total of 200 soil samples were used, which were collected from 100 points at two depths (0-10 and 10-30 cm); the total elements were determined using an X-ray fluorescence analyzer. The Random Forest algorithm proved to be superior to the others in predicting the chemical attributes of the soil at both depths, and is suitable for predicting soil attributes in the study region. Spatial variables are essential, and should be considered when modelling chemical elements in the soil. Using the methods under test, it is possible to predict elements with R2 values ranging from 0.32 to 0.62.

Predictive modeling for customer churn classification is a common practice among companies from different sectors, however even though it is a widely explored subject, choosing a suitable classifier may be a difficult task, given the particularities of each company and the variety of available algorithms. Therefore, the purpose of this article is to choice of an algorithm for customer churn predictive modeling in a Brazilian startup. The decision-making process used the SAPEVO-M method to obtain the weights of criteria and to define an interpretability measure for the evaluated algorithms, and the VIKOR method was used to evaluate the alternatives. After applying the methods, the classifiers trained with SVM (radial kernel) and Logistic Regression algorithms were considered the most suitable for the business model of the company in question. [ABSTRACT FROM AUTHOR]

Knowledge of techniques to obtain information on the future production trend is essential for rural managers. Therefore, the purpose of this work was to make predictions. For that, time series models implemented in free software R of Brazilian corn production for the 2017/2018, 2018/2019 and 2019/2020 harvests were used. ARIMA (Autoregressive Integrated Moving Average) and ETS (Error, Trend, Seasonal - Error, Trend, Seasonal) methodologies were applied. Both models proved to be suitable. The model that presented the best forecast results was ARIMA, whose mean absolute percentage error of the predictions was less than that presented in the ETS model, when compared with the data reserved for verifying the predictive efficiency of the adjusted models. The results demonstrate the applicability of prediction models and computational tools that are easy to use. Such techniques aim to contribute to the decision-making and planning process by the rural manager, who has seen the corn crop in recent years, present production records and be one of the main cultivars that contributes to the Brazilian economy. [ABSTRACT FROM AUTHOR]

A study of correlations was conducted to determine the main morphometric measurements of the carcass that influence the determination of the commercial cuts from the forequarter and hindquarter in Nellore heifers. Eighty-one Nellore heifers, randomly chosen form a commercial herd, were slaughtered according to the actual regulation. The animal's body weight was measured before the slaughter. After the slaughtering, the hot and cold carcasses were determined and then divided into half-carcasses and weighed after cooling. The morphometric measurements evaluated were the internal carcass length, width, perimeter and depth of leg, chest depth, ribeye area, and subcutaneous fat thickness. The half-carcasses were divided into forequarter and hindquarter to establish the commercial meat cuts. The data were analysed using Pearson's correlation (p<0,05), followed by the development of multiple linear equations using the stepwise method. The highest positive correlations (> 0.60) were found in the variable weight, as the best correlation between the cuts of the forequarter and hindquarter was with the half carcass weight. The variables related to length, width, depth, and perimeter presented low to moderate correlations (<0.40) as the ribeye area showed a moderate and positive correlation (<0.40), yet the subcutaneous fat thickness did not correlate with the commercial meat cuts. The weight of the half carcass was the first variable that participated in the multiple linear regression model for the forequarter and hindquarte, and the other tested variables did not show a high increase in the prediction model. The observed and predicted values were calculated and compared, and they were broadly similar, thus showing the high prediction of the regression equations, and it can be well applied to estimate the cuts of the forequarter and hindquarter. The most important variable to predict the commercial cuts of Nellore heifers was the half-carcass weight. [ABSTRACT FROM AUTHOR]

This article describes a pilot study that analyzes a predictive model for hospitalizations of children and adolescents with respiratory diseases secondary to infection. The study was conducted at the Lauro Wanderley University Hospital in Paraíba, between September 2023 and February 2024. Adapted questionnaires from the Functional Status Scale were used to collect personal and clinical information from 15 children. The majority of participants were female and had no comorbidities. Respiratory and motor physiotherapy was the most common treatment, and most participants had good mental state and functionality. [Extracted from the article]

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Business & Projects / Revista de Gestão e Projetos is the property of Revista de Gestao e Projetos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ABSTRACT The objective of this work was to use biometric measurements to predict carcass characteristics of lambs of the Morada Nova breed. We used 48 lambs with mean initial body weight (BW) of 15.0±0.04 kg and slaughter body weight (SBW) of 26.37±2.43 kg. The animals were weighed weekly and underwent a period of adaptation of 15 days before slaughter. The biometric measurements were obtained the day before slaughter, comprising body length, withers height, rump height, thigh length, breast width, rump width, thigh perimeter, rump perimeter, thorax perimeter, leg length, and body condition score. Additional measurements included slaughter BW and empty BW (EBW). The data recorded at slaughter comprised the weights of the viscera, carcass, and internal fat and offal. The in vivo measurements of body length were present in most of the equations for predicting the SBW, EBW, hot carcass weight (HCW), and cold carcass weight (CCW). The SBW and EBW presented a variation of approximately 9%. The variables that evaluated the carcass, HCW, and CCW demonstrated less data variation than SBW and EBW, which was probably because these measurements were obtained following evisceration and skinning, thus removing factors of more significant variation in vivo . The prediction models found in the present study varied with an R² of 0.49-0.93, indicating high levels of variation. In sum, biometric measurements can be used to predict the carcass characteristics of Morada Nova lambs with different body conditions.

Copyright of Revista Psicologia. Organizacoes e Trabalho is the property of Sociedade Brasileira de Psicologia Organizacional e do Trabalho and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work is based on a bibliometric review aiming to provide an overview of the use of geotechnology applied to plan and management in medium-sized cities, as outlining the main trends and gaps, Scopus was selected as the key database for this study, considering its global use in the academic setting. The researched key terms appear only in 2007, evidencing the lack of papers about medium cities in highperformance journals. It was highlighted predictive models of urban sprawl and assessment of the ecological safety level of cities. Major innovations have adopted multiple satellite data sources, programming validation and optimization routines of image classifying algorithms, as well as the increment of semi-automated open and open-source processing chains. Given the various applications derived from geotechnologies, the adoption of these tools by municipal secretariats is essential to replace the archaic or inefficient territorial planning and management. [ABSTRACT FROM AUTHOR]

Copyright of Computing & System Journal (C&S) / Revista de Sistemas e Computação (RSC) is the property of FACS Servicos Educacionais S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista de Contabilidade e Organizações is the property of Revista de Contabilidade e Organizacoes and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Relações Internacionais is the property of Relacoes Internacionais and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of JBES: Brazilian Journal of Health Economics / Jornal Brasileiro de Economia da Saúde is the property of JBES: Brazilian Journal of Health Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study characterized the thermal environment and assessed the physiological aspects of acclimatization of Sindhi and Guzerat heifers in a tropical environment (Brazil) under shade. Eight Sindhi and eight Guzerat purebred heifers (Bos indicus) had their physiological traits measured twice a day (9:00 a.m. and 2:00 p.m.). Environmental data during the experimental period were collected at two-hour intervals between 5:00 a.m. and 5:00 p.m. The temperature-humidity (THI) and the black globe temperature-humidity (BGHI) indices were calculated, and surface temperature (St), respiratory rate (Rr), and rectal temperature (Rt) were collected, being used to estimate heat loss by cutaneous (Ec) and respiratory (Er) evaporation. In the warmer parts of the day (1:00 and 3:00 p.m.), the THI and BGHI reached values of 80.26 and 81.25, respectively. There was no significant difference in rectal temperatures between the breeds, but higher values were observed in the afternoon. Heat transfer by cutaneous evaporation reached 118.71±12.91 W.m-2 and 103.43±6.82 W.m-2 at 2:00 p.m. for the Sindhi and Guzerat heifers, respectively. Under these conditions (air temperature was between 29 and 30°C), 84% of the total latent heat loss in Sindhi and Guzerat heifers was represented by Ec. It can be concluded that Sindhi and Guzerat heifers can maintain homeothermy with minimal thermoregulatory effort under shade conditions in a tropical environment.

A comparison between the rolling loads calculated through the theoretical models of Sims, Orowan-Pascoe and Ekelund is performed in order to verify the performance of the models compared to the real values recorded during the processing of plain carbon-manganese steels and niobium steels during the finish rolling in the hot strip mill. To determine the hot deformation resistance, the equations of Shida, Poliak & Siciliano, Siciliano, Marini & Bruna, Siciliano, Leduc & Hensger, Misaka and Siciliano & Jonas are used. In the direct comparison between the calculated values and the actual values the best level of precision is obtained when the load prediction models are combined with the Shida equation, respectively Sims, Orowan-Pascoe and Ekelund. In order to better adjust calculated loads to the reality of the industrial process, adjustment factors are proposed for each of the seven stands of the finishing mill. With the application of the adjustment factors, the load prediction equations presented global mean errors in the finishing mill, varying between 4.3 and 5.6% for C-Mn steels and 4.6 and 6.3% for niobium steels. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Agricultura Irrigada - RBAI is the property of Revista Brasileira de Agricultura Irrigada - RBAI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: to trace epidemiological profile of HIV / AIDS in Montes Claros, Minas Gerais and analyze the trend line of growth of the disease. Method: it is an epidemiological, cross-sectional, descriptive-analytical study with a quantitative approach. The data were collected through DATASUS, SINAN and SIM, referring to the period between 1986 and 2016. The analysis of the predictive model was by Simple Linear Regression, for which the validation assumptions were met. Results: since the first diagnosis notified in 1986, there was a great spread of the disease, totaling 523 confirmed cases. The distribution was 59.8% (313) for men; 31.9% (167) in the 30-39-year age group; 33.7% (176) in brown-skinned; and 48.4% (256) of heterosexual sexual contact exposure. Mortality corresponds to 71.9% (23) of males; 43.8% (14) in the age range of 30-39 years. The trend curve of the epidemic denotes a progressive increase in incidence according to the function of -2227.779 + 1.122* (year). Conclusion: the data show that the HIV / AIDS epidemic is still expanding. However, since its onset, the sociodemographic profile of the disease assumes a changing character, which requires constant vigilance for adequacy of control policies. [ABSTRACT FROM AUTHOR]

This article describes the development of prediction equations for disability status in patients with multiple sclerosis (MS). The Expanded Disability Status Scale (EDSS) is commonly used to track the progression of disability in MS patients, but it requires a detailed neurological examination performed by a trained clinician. The aim of this study was to develop a prediction equation for disability status in MS patients using simple tests of bodily function and activity commonly used in physiotherapy practice. Functional mobility was identified as the most significant predictor of disability level, and two models of disability prediction equations in MS were generated. [Extracted from the article]

La erosión eólica potencial del suelo (EEP) es un dato básico utilizado en varios modelos de predicción para calcular la erosión eólica de suelos agrícolas. El objetivo de este estudio fue cuantificar la EEP de un Haplustol y un Ustipsammente de la Región Semiárida Pampeana (RSP) y compararla con las predicciones del modelo Ecuación de Erosión Eólica en Español (EWEQ), realizadas con diferentes factores climáticos (C). Se efectuaron mediciones de EEP a campo durante un año en ambos suelos, mantenidos sin cobertura y con mínima rugosidad. Los resultados indicaron que la EEP medida a campo fue mayor en el Ustipsammente (270 Mg ha-1 año-1) que en el Haplustol (40 Mg ha-1 año -1 ), con una reducción en el espesor del horizonte de 21,3 y 3,1 mm, respectivamente. La erosión del Ustipsammente fue dos veces mayor en primavera-verano que en otoño-invierno. Este efecto no se observó en el Haplustol, debido a su menor desecamiento y mayores contenidos de humedad luego de las lluvias. La erosión del Haplustol, por desecarse más lentamente luego de una lluvia, fue más condicionada por las precipitaciones que la del Ustipsammente. Un 40% de la erosión de ambos suelos fue definida por la duración de las tormentas. Las tasas de erosión (EEP por unidad de tiempo, Qt) se correlacionaron positivamente con la velocidad promedio del viento (V), ajustando a una función polinómica en ambos suelos. A la misma V, Qt fue siempre mayor en el Ustipsammente. La EEP calculada con la EWEQ, utilizando el factor C correspondiente al año de muestreo (30,3), fue la más semejante a la erosión medida a campo, aunque el modelo la subestimó en un 43% en el Haplustol y en un 18% en el Ustipsammente. La EWEQ deberá ofrecer al usuario distintos factores C para poder predecir EEP en escenarios climáticos variables.The potential wind erosion of a soil (EEP) is a basic data for predicting wind erosion of agricultural soils in most wind erosion prediction models. The objective of this study was to compare the predicted EEP of two soils by means of the Spanish Version of the Wind Erosion Equation (EWEQ), with field-measured EEP in a semiarid environment of Argentina, loaded with different climatic C factors. Wind erosion measurements were carried out along one year in a Typic Ustipsammment and an Entic Haplustoll, both maintained bare and flat along the sampling period. Results indicated that EEP was higher in the Ustipsamment (270 Mg ha-1 yr-1) than in the Haplustoll (40 Mg ha-1 yr-1). These amounts represented 21,3 and 3,1 mm losses of the topsoil. Wind erosion of the Ustipsamment was twice in Spring-Summer than in Autumn-Winter. This effect was not observed in the Haplustoll, due to a slower drying rate after a rainfall event, which maintained the soil surface moist during a longer period of time. Storm duration explained 40% of the wind erosion variability in both soils. Wind erosion rates (Qt, EEP per unit time) correlated positively with the mean wind speed in both soils. At similar wind speeds, Qt was always higher in the Typic Ustipsamment. The EEP calculated with a C factor corresponding to the sampling period (30,3) was the most similar to field measurements, but EWEQ underestimated wind erosion by 43% for the Haplustoll and by 18% for the Ustipsamment. The EWEQ model should include different climatic C factors in order to offer the user the prediction of wind erosion under variable climatic scenarios.

Este trabalho foi realizado com o objetivo de avaliar o modelo Cornell Net Carbohydrate and Protein System (CNCPS), versão 5.0, na predição do consumo de matéria seca de vacas da raça Holandesa, lactantes, em pastagem de capim coast-cross suplementada com silagem de milho e concentrado (3 ou 6 kg/vaca.dia). Foram realizados seis ensaios experimentais, cada um com 12 vacas. Em três das avaliações, os animais receberam, além do concentrado, 17 kg de silagem de milho/dia (base natural). As coletas de forragem selecionada na pastagem para análise da composição química foram realizadas por uma vaca com fístula esofágica. A estimativa do consumo voluntário foi realizada com sesquióxido de cromo (Cr2O3), administrado em doses de 5 g, duas vezes ao dia. Foram fornecidos ao programa dados (inputs) referentes aos animais (peso vivo corporal, escore corporal, idade, produção e composição do leite e tipo racial), ao ambiente (temperatura, umidade relativa do ar e manejo) e à composição do alimento em cada período experimental. Os valores preditos pelo CNCPS para a ingestão voluntária de matéria seca foram próximos àqueles estimados, havendo pequena tendência do modelo em subestimar o valor determinado com o indicador.The aim of this work was to evaluate the ability of the Cornell Net Carbohydrate and Protein System (CNCPS) version 5.0 to estimate the dry matter intake (DMI) of grazing lactating Holstein cows, grazing coast-cross pasture supplemented with corn silage and concentrate (3 or 6 kg/cow/day). Six experiments were carried out, with 12 cows each. The cows were fed 17 kg/cow/day of corn ensilage in three experiments. The chemical composition of extrusa samples of forage was determined, obtained using an esophageous fistulated cow. The intake estimates were obtained using 5 g of chromium oxide (Cr2O3) methodology supplied two times a day. Data corresponding to animals (body weight, age, milk yield and composition and racial type), environment (temperature, air relative humidity and management condition) and the feed chemical composition in each experimental period were provided to the program. The DMI values predicted by the CNCPS model were close to those obtained by the chromium oxide methodology.

The study of soil property relationships is of great importance in agronomy aiming for a rational management of environmental resources and an improvement of agricultural productivity. Studies of this kind are traditionally performed using static regression models, which do not take into account the involved spatial structure. This work has the objective of evaluating the relation between a time-consuming and "expensive" variable (like soil total nitrogen) and other simple, easier to measure variables (as for instance, soil organic carbon, pH, etc.). Two important classes of models (linear state-space and neural networks) are used for prediction and compared with standard uni- and multivariate regression models, used as reference. For an oat crop cultivated area, situated in Jaguariuna, SP, Brazil (22º41' S, 47º00' W) soil samples of a Typic Haplustox were collected from the plow layer at points spaced 2 m apart along a 194 m spatial transect. Recurrent neural networks and standard state-space models had a better predictive performance of soil total nitrogen as compared to the standard regression models. Among the standard regression models the Vector Auto-Regression model had a better predictive performance for soil total nitrogen.O estudo da relação entre as propriedades do solo é de grande importância na área agronômica objetivando um manejo racional dos recursos naturais do meio ambiente e um aumento na produtividade agrícola. Tradicionalmente este estudo tem sido realizado usando modelos de regressão estática os quais não levam em consideração a estrutura espacial envolvida. Este trabalho teve o objetivo de avaliar a relação entre uma variável de determinação mais cara e demorada (por exemplo, nitrogênio total do solo) e outras de mais barata e rápida determinação (p.e., carbono orgânico do solo, pH, etc.). Duas importantes classes de modelos (espaço de estados linear e redes neurais) são usadas para predição e comparadas aos modelos de regressão uni- e multivariados aqui usados como referência. Para tal, em uma área experimental cultivada com aveia, situada em Jaguariúna, SP (22º41' S e 47º00' W), amostras de um solo classificado como Latossolo foram coletadas na camada arável ao longo de uma transeção espacial de 194 m, eqüidistantes de 2 m. Os modelos de rede neural recorrente e de espaço de estados padrão tiveram uma melhor performance preditiva da variável nitrogênio total do solo quando comparados aos modelos de regressão padrão. Entre os modelos de regressão padrão o Autoregressivo Vetorial teve um melhor desempenho preditivo da variável nitrogênio total do solo.

The aim of the present study was to verify the relation between migraine and stress, and to identify the best predictor model for migraine, considering personal and environment variables. Migraine was identified applying the Test of the Brazilian Headache Society to 75 women without psychiatric history. Stress was identified by the Stress Symptom for Adults Inventory. Simultaneously, life events, socioeconomic level, and sample characteristics were assessed. According to the results, 55% of women presented migraine and 59% showed stress. The prediction model revealed that the presence of stress was the only predictor of the presence of migraine in women. These findings suggest an association between migraine and stress, which should be considered in the health assistance of women. [ABSTRACT FROM AUTHOR]

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Bankruptcy prediction may have great utility to financial and nonfinancial institutions with regard to take in advance the best possible decisions regarding loans or investments. In specific literature, many bankruptcy prediction models have made use of data mining. The preprocessing step is important to select good quality data for use in mining operations. Still, although the selection of attributes can be very beneficial to pre-select representative data to improve the forecast performance end, it is not known which method is the best selection. This work has as main objective to compare two approaches for evaluating subsets of attributes: Filter and Wrapper. Despite being based on data mining techniques and widely used in the step of feature selection in bankruptcy prediction models, these techniques are rarely used to treat data from financial statements of Brazilian companies. Therefore the empirical basis of this study consists of a sample of Brazilian industrial and commercial enterprises, collecting data for the period 2004 to 2011. The results indicated that, in this sample, the filter approach was more efficient, providing better classification results both for logistic regression (91,80%) and for neural networks (93,98%). It was shown also the importance of making explicit the evaluation stage of the selection of attributes for achieving better results in applications of data mining techniques to predict insolvency. A specific conclusion about the advantages of the filter approach shows that it may be preferred to assess the attributes that will make predictive models. [ABSTRACT FROM AUTHOR]

This study presents as objective to establish the causal relationships between culture and organizational strategies adopted by the Higher Education Institutions (HEIs) of the Rio Grande do Norte state. It was a study of the explanatory type, predominantly quantitative with the thirty-one institutions. The data were treated by means of a predictive model of canonical correlation. The results indicated the existence of an entrepreneurial cultural style and a prospective strategic outlook as the predominant type. The canonical correlation results indicated a strong relationship between the variables, so that it was possible to identify that the 77.88% linear variation of the compound (organizational strategy) of the first function was influenced by the variation of another compound (organizational culture) that make it up. Finally, it can be concluded that this study confirms the relationship between the styles of organizational culture types and organizational strategies of the HEIs. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work aimed to model and forecast the average daily concentration of inhalable particulate matter (PM10) using the SARIMAX model, in the Greater Vit�ria Region (RGV), ES, Brazil, for the period from January 1st, 2008 to December 31th, 2018. For this, time series of PM10 concentration and meteorological parameters wind speed (V), relative humidity (U), precipitation (PP), temperature (T), solar radiation (I) and atmospheric pressure (P) were considered. These parameters were obtained from the State Environmental Institute (IEMA), being chosen the Laranjeiras, Carapina, Jardim Camburi, Enseada do Su�, Vit�ria (Centro), Ibes and Vila Capixaba stations to the study of prediction and forecasting. According to performance indicators, SARIMAX models, for most seasons, have been presented as good models for making predictions and forecasts of air quality in the localities. Regarding the prediction of regular air quality events, in general, the SARIMAX models stood out when compared to the SARIMA and ARMA models. Among the meteorological variables evaluated, V, U, PP and T stand out as predictor variables of PM10 concentrations and assumed a decisive role in improving the performance of the prediction models. [ABSTRACT FROM AUTHOR]