Estimating mortality in laying hens as the environmental temperature increases

Layer mortality due to heat stress is an important economic loss for the producer. The aim of this study was to determine the mortality pattern of layers reared in the region of Bastos, SP, Brazil, according to external environment and bird age. Data mining technique were used based on monthly mortality records of hens in production, 135 poultry houses, from January 2004 to August 2008. The external environment was characterized according maximum and minimum temperatures, obtained monthly at the meteorological station CATI in the city of Tupa, SP, Brazil. Mortality was classified as normal (<= 1.2%) or high (> 1.2%), considering the mortality limits mentioned in literature. Data mining technique produced a decision tree with nine levels and 23 leaves, with 62.6% of overall accuracy. The hit rate for the High class was 64.1% and 59.9% for Normal class. The decision tree allowed finding a pattern in the mortality data, generating a model for estimating mortality based on the thermal environment and bird age.

Uma aplicação de análise de decisão com o método AHP Processo de hierarquia analítica: um estudo sobre adoção de Sistema eletrônico de cobrança no Transporte público urbano

This thesis carries through an application of Analysis of Multicriterion Decision with use of the method of Analytical Hierarchy Process (AHP) in the problematic one of taking of decision of the adoption of electronic collecting in the system of urban transport in the country, a subject that has been controversial. A modeling of criteria and alternatives is carried through and applied a questionnaire based on method AHP the excellent actors in the system of urban transport - Leading of the Managing Agency Public Municipal theatre of Urban Transports, Controller of Company of Bus, Controller of Labor union, Controller of Union of Companies, Communitarian Leader. The considered alternatives were: the maintenance of the current state with collectors, the implementation of electronic collection without collectors, and the implementation of electronic collection with collectors. The used criteria were: job, impact in the fare, control of the system, easiness of use, information. The study was carried through in the city of Natal, RN, where if the adoption of electronic collection argues and where this implementation in some bus lines between Natal and Parnamirim exists, city that integrates the region of the great Natal. The main results of the method evidence in a dimension, the viability of use of method AHP with questionnaire by means of validation of the judgments with analysis of variance beyond proper the normal mechanisms of analysis of consistency to the method, and in another one, the contribution of the analysis boarding multicriterion to become the judgments more clearly. The main results of the analysis help to show that although to models of criteria and distinct judgments of the actors, the method evidenced that it has inclination the adoption of the electronic collection on the current situation, even so with divergences between the maintenance or not of the collector. The research points to the possibility of accomplishment of the application of the AHP in successive rounds of judgments

Potential tuberculostatic agents. Topliss application on benzoic acid [(5-nitro-thiophen-2-yl)-methylene]-hydrazide series

Nitroaromatic compounds such as nifuroxazide are used in many human enteropathogenic bacteria infections without causing an increase in the plasmidial antibiotic resistance of the aerobic Gram-negative intestinal Enterobacteriaceae. For these reasons, these compounds have been synthesized using the rational approach of Topliss' decision tree. Generally. this approach allows us to obtain the most active derivative from the series in a few steps. These compounds were tested against Mycobacterium tuberculosis in vitro and the most active of the series identified. A new lead for potential tuberculostatic activity has been predicted and will be used in further QSAR studies. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Cost-benefit of hospitalization compared with outpatient care for pregnant women with pregestational and gestational diabetes or with mild hyperglycemia, in Brazil

CONTEXTO E OBJETIVO: Gestações complicadas pelo diabetes estão associadas com aumento de complicações maternas e neonatais. Os custos hospitalares aumentam de acordo com a assistência prestada. O objetivo foi calcular o custo-benefício e a taxa de rentabilidade social da hospitalização comparada ao atendimento ambulatorial em gestantes com diabetes ou com hiperglicemia leve. DESENHO do ESTUDO: Estudo prospectivo, observacional, quantitativo, realizado em hospital universitário, sendo incluídas todas as gestantes com diabetes pregestacional e gestacional ou com hiperglicemia leve que não desenvolveram intercorrências clínicas na gestação e que tiveram parto no Hospital das Clínicas, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista (HC-FMB-Unesp). MÉTODOS: Trinta gestantes tratadas com dieta foram acompanhadas em ambulatório e 20 tratadas com dieta e insulina foram abordadas com hospitalizações curtas e frequentes. Foram obtidos custos diretos (pessoal, material e exames) e indiretos (despesas gerais) a partir de dados contidos no prontuário e no sistema de custo por absorção do hospital e posteriormente calculado o custo-benefício. RESULTADOS: O sucesso do tratamento das gestantes diabéticas evitou o gasto de US$ 1.517,97 e US$ 1.127,43 para pacientes hospitalizadas e ambulatoriais, respectivamente. O custo-benefício da atenção hospitalizada foi US$ 143.719,16 e ambulatorial, US$ 253.267,22, com rentabilidade social 1,87 e 5,35 respectivamente. CONCLUSÃO: A análise árvore de decisão confirma que o sucesso dos tratamentos elimina custos no hospital. A relação custo-benefício indicou que o tratamento ambulatorial é economicamente mais vantajoso do que a hospitalização. A rentabilidade social de ambos os tratamentos foi maior que 1, indicando que ambos os tipos de atendimento à gestante diabética têm benefício positivo.

Estudo de caso de dois acidentes do trabalho investigados com o método de árvore de causas

São apresentados dois acidentes do trabalho típicos, ocorridos em empresa de grande porte, investigados com o Método de Árvore de Causas ­ ADC, método que permite identificar o papel desempenhado por fatores gerenciais e de organização do trabalho no desencadeamento desses fenômenos. Os casos apresentados revelam a participação, na gênese dos acidentes, de fatores como designação temporária e improvisada de trabalhadores para funções e postos de trabalho, execução de tarefas deixadas à iniciativa e ao arbítrio dos trabalhadores, falta de ferramentas e de materiais apropriados à execução de tarefas e falhas na circulação de informações, entre outros. São também analisadas as indicações para o uso do método, suas potencialidades em termos de prevenção, bem como as implicações decorrentes de dificuldades de aplicação, de necessidades de treinamento e reciclagens e do dispêndio elevado de tempo para investigação de cada acidente.

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

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

A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data

Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.

Modelling an expert GIS system based on knowledge to evaluate oil spill environmental sensitivity

Oil spills cause great damage to coastal habitats, especially when rapid and suitable response measures are not taken. Establishing high priority areas is fundamental for the operation of response teams. Under this context and considering the need for keeping all geographical information up-to-date for emergencial use, the present study proposes employing a decision tree coupled with a knowledge-based approach using GIS to assign oil sensitivity indices to Brazilian coastal habitats. The modelled system works based on rules set by the official standards of Brazilian Federal Environment Organ. We tested it on one of the littoral regions of Brazil where transportation of petroleum is most intense: the coast of the municipalities of Sao Sebastiao and Caraguatatuba in the northern littoral of São Paulo state, Brazil. The system automatically ranked the littoral sensitivity index of the study area habitats according to geographical conditions during summer and winter; since index ranks of some habitats varied between these seasons because of sediment alterations. The obtained results illustrate the great potential of the proposed system in generating ESI maps and in aiding response teams during emergency operations. (C) 2009 Elsevier Ltd. All rights reserved.

Anthropotechnological analysis of industrial accidents in Brazil

The Brazilian Ministry of Labour has been attempting to modify the norms used to analyse industrial accidents in the country. For this purpose, in 1994 it tried to make compulsory use of the causal tree approach to accident analysis, an approach developed in France during the 1970s,without having previously determined whether it is suitable for use under the industrial safety conditions that prevail in most Brazilian firms. In addition, apposition from Brazilian employers has blocked the proposed changes to the norms. The present study employed anthropotechnology to analyse experimental application of the causal tree method to work-related accidents in industrial firms in the region of Botucatu, São Paulo. Three work-related accidents were examined in three industrial firms representative of local, national and multinational companies. on the basis of the accidents analysed in this study, the rationale for the use of the causal tree method in Brazil can be summarized for each type of firm as follows:the method is redundant if there is a predominance of the type of risk whose elimination or neutralization requires adoption of conventional industrial safety measures (firm representative of local enterprises); the method is worth while if the company's specific technical risks have already largely been eliminated (firm representative of national enterprises); and the method is particularly appropriate if the firm has a good safety record and the causes of accidents are primarily related to industrial organization and management (multinational enterprise).

Diagnostic de securite d'une entreprise bresilienne a partir de l'analyse des accidents du travail par la methode de l'arbre des causes

We present here the results of a study of 21 work-related accidents that occurred in a Brazilian manufacturing company. The aim was to assess the safety level of the company to improve its work accident prevention policy. In the last 6 months of 1992 and 1993, all accidents resulting in 15 days' absence from work, reported for social security purposes, were analyzed using the INRS causal tree method (ADC) and a questionnaire completed on site. Potential risk factors for accidents were identified based on the specific factors highlighted by the ADC. More universal trees were also compiled for the safety assessment. Three hundred and thirty specific accident factors were recorded (man of 15.71 per accident). This is consistent with there being multiple causes of accidents rather than the assertion of Brazilian business safety departments that accidents are due to 'dangerous' or 'unsafe' behavior. Introducing the idea of culpability into accidents prevents the implementation of an appropriate information feedback process, essential for effective prevention. However, the large number of accidents related to 'material' (78%) and 'environment' (70%) indicates that working conditions are poor. This shows that the technical risks, mostly due to unsafe machinery and equipment are not being dealt with. Seventy-five potential accident factors were identified. Of these, 35% were 'organizational', a high proportion for the company studied. Improvisation occurs at all levels, particularly at the organizational level. This is, thus a major determinant for entire series of, if not most, accident situations. The poor condition of equipment also plays a major role in accidents. The effects of poor equipment on safety exacerbate the organizational shortcomings. The company's safety intervention policy should improve the management of human resources (rules designating particular workers for particular workstations; instructions for the safe operation of machines and equipment; training of operators, etc.) and introduce programs to detect risks and to improve the safety of machines and equipment. We also recommend the establishment of a program to follow the results of any preventive measures adopted.

Diagnostic de sécurité d’une entreprise brésilienne à partir de l’analyse des accidents du travail par la méthode de l’arbre des causes

We present here the results of a study of 21 work-related accidents that occurred in a Brazilian manufacturing company. The aim was to assess the safety level of the company to improve its work accident prevention policy. In the last 6 months of 1992 and 1993, all accidents resulting in 15 days' absence from work, reported for social security purposes, were analyzed using the INRS causal tree method (ADC) and a questionnaire completed on site. Potential risk factors for accidents were identified based on the specific factors highlighted by the ADC. More universal trees were also compiled for the safety assessment. Three hundred and thirty specific accident factors were recorded (mean of 15.71 per accident). This is consistent with there being multiple causes of accidents rather than the assertion of Brazilian business safety departments that accidents are due to dangerous or unsafe behavior. Introducing the idea of culpability into accidents prevents the implementation of an appropriate information feedback process, essential for effective prevention. However, the large number of accidents related to material (78%) and environment (70%) indicates that working conditions are poor. This shows that the technical risks, mostly due to unsafe machinery and equipment are not being dealt with. Seventy-five potential accident factors were identified. Of these, 35% were organizational, a high proportion for the company studied. Improvisation occurs at all levels, particularly at the organizational level. This is thus a major determinant for entire series of, if not most, accident situations. The poor condition of equipment also plays a major role in accidents. The effects of poor equipment on safety exacerbate the organizational shortcomings. The company's safety intervention policy should improve the management of human resources (rules designating particular workers for particular workstations; instructions for the safe operation of machines and equipment; training of operators, etc.) and introduce programs to detect risks and to improve the safety of machines and equipment. We also recommend the establishment of a program to follow the results of any preventive measures adopted.

Measuring the efficiency of outsourcing: An illustrative case study from the aerospace industry

Outsourcing is related to the action which an organization deals with its suppliers through a kind of business contract where a specific activity or service has been hired to be made. The outsourcing of some activities has become a common practice in the industry, nowadays. It reduces costs, significantly, in the production process and, at the same time, adds some values to the business organization. However it is necessary to measure the performance of these activities. Data Envelopment Analysis (DEA) is a non-parametric method useful to measure comparative performance. It has a wide range of applications measuring comparative efficiency. The Analytic Hierarchy Process (AHP) is a multiple criteria decision-making method that uses hierarchic structures to represent a decision problem and then develops priorities for the alternatives based on the decision-maker's judgments. This paper presents an integrated application based on DEA and AHP to evaluate the efficiency of subcontracted companies in a Brazilian aerospace factory. © 2007 Springer-Verlag London Limited.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.