The oil and gas industry worldwide is experiencing problems of vandalism and mechanical deterioration due to corrosion in its various pipeline transport systems, a drop in the price of hydrocarbons ...due to the COVID-19, limitation of maintenance processes. This article provides a contribution original to the knowledge and management of a pipeline transportation system (PTS), without an immediate high impact that would help reduce property loss due to corrosion, through the development of intelligent evaluation models that combine field data, laboratory, and cognitive knowledge in a case study in Mexico. The research is divided into Part 1: modeling, a Fuzzy expert system (FES) unified the knowledge of corrosion specialists and mechanical integrity studies (MIS) and identified evolutionary corrosion patterns with reliability of 0.9029. An artificial neural network (ANN) supported by statistics and metallography establishes test reliability of 0.9556 and determines the corrosion inhibition capacity (C) of Mexican hydrocarbon mixtures based on their properties compared to carbon steel. Part 2: analysis of the operational and economic risk of the PTS under corrosive effects, using Monte Carlo simulation (MCS) estimates various financial scenarios considering corrosive profiles of soils, supply, demand, and inflation.
•A fuzzy expert system to assess the nephropathy control is proposed.•The success rate of the fuzzy expert system is 93.33%.•The use of this system allows reduce the lack of control and wrong ...treatments.•The system would be useful if it is adapted to the diagnosis of other pathologies.•Recognition of predictor variables of lack of control avoid irreversible damage in kidneys.
Diabetic nephropathy is a life-threatening complication if not controlled properly. Early detection and effective control prevent its progression. In this study, the development of a Fuzzy Expert System (FES) is proposed to help doctors assess the nephropathy control in patients with Type 2 Diabetes Mellitus (T2DM). The study is based on a FES that was developed with the use of Clinical Practice Guidelines (CPG), data bases and the expertise of a team of doctors. It considers the use of input variables such as Glomerular Filtration Rate (GFR), serum creatinine, blood glucose, Type 2 Diabetes Mellitus Age (T2DMA), uric acid, hypertension and dyslipidemia. All these factors, give an efficient nephropathy control assessment. Sixty tests were performed using the expertise of a team of doctors, the expected results were compared with those estimated by the FES (using the same cases), and it was observed that the FES succeeds in up to 93.33% of the cases. The response surface analysis shows that GFR, serum creatinine and hypertension have a greater impact in the nephropathy control. This system supports the doctors in nephropathy control, but it does not estimate the renal failure stages. Nephropathy control is a clinical problem that includes uncertainty and inaccuracy, so the use of a FES is recommended to overcome this problem, since fuzzy systems help to assess the inherent uncertainty degree.
Nowadays, a large part of daily activities is associated with the use of fossil fuels. Therefore, the excessive exploitation and related pollution have led to the search for alternatives. A current ...alternative to replace them is production of biofuels. They are produced in facilities called biorefineries which are ecodesigned. The ecodesign in biorefineries is a multicriteria issue encountering various criteria. In this context, the aim of this study is the assessment of various biorefinery ecodesign alternatives for the selection of the optimal pathway to produce biodiesel as an alternative to fossil fuels. A multicriteria decision-making methodological framework is proposed and applied to two case studies with three scenarios each. Decision support techniques show that the best ecodesign alternative for the first case study is a biorefinery of four platforms to produce biodiesel, glycerin, potassium phosphate, heat and energy, bio-oil, and bio-carbon from jatropha biomass, while in case two the selection is not conclusive which is attributable to subjectivity. This framework addresses the issue presented by biorefineries looking for sustainability but also for other industries looking for application on their process design. Incorporating sustainable considerations into biorefinery process design as well as assessing them through different criteria to choose the optimal configuration is the main issue faced by decision makers and stakeholders.
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El objetivo de este trabajo es desarrollar una herramienta de soporte a la decisión clínica para evaluar el resultado de la interacción de los medicamentos utilizados para tratar el SARS- CoV-2 y la ...coadministración de medicamentos para tratar comorbilidades. Se utilizan redes neuronales (RNs) para realizar la predicción de los resultados de la interacción de medicamentos. El modelo ha sido desarrollado utilizando una red neuronal artificial del tipo PNN (Red neuronal probabilística) /GRNN (Red neuronal de regresión general). Una vez que la red neuronal artificial fue entrenada, probada y validada, se obtuvo un coeficiente de determinación del 82.79%, con lo que se pueden tener predicciones buenas y rápidas para conocer el resultado de la interacción de medicamentos específicos para el SARS- CoV-2 con otros fármacos para tratar diferentes enfermedades. Para el entrenamiento de la RN se utilizó una base de datos, considerando nueve fármacos para tratar el SARS- CoV-2 y 10 categorías de medicamentos para tratar otros tipos de padecimientos. En la literatura existen estudios que demuestran la importancia de la correcta coadministración de medicamentos. Sin embargo, no existen, actualmente, herramientas que integren el uso de redes neuronales y el nuevo conocimiento obtenido de las respuestas ante las interacciones entre fármacos, que pueden ser utilizados de primera mano por los especialistas en el tratamiento disminuyendo con el riego de dicha interacción. Por ello, este trabajo pretende abordar esta brecha en el conocimiento. Este sistema puede ser utilizado como una herramienta de apoyo a la decisión, para evaluar y seleccionar entre el mejor tratamiento a utilizar en un paciente con SARS- CoV-2, y evitar complicaciones por la interacción negativa que puede provocar con otros medicamentos.
The cane sugar industry in Mexico depends heavily on the supply of energy, fossil fuels and material resources for its proper operation. The overuse of these resources plus the technical and ...technological deficiency causes severe environmental consequences. This scientific work aims to analyze the environmental damage attributable to cane sugar production following the life cycle assessment (LCA) methodology. System boundaries include sugarcane growing and harvesting, sugarcane transportation, sugar milling and electricity cogeneration from bagasse. The associated emissions were acquired from the SimaPro-Ecoinvent database, the Roundtable on Sustainable Biofuels (RSB) and the Agroscope Reckenholz-Tänikon Research Station (ART). The life cycle impact assessment (LCIA) was carried out by SimaPro 8.3.0 software and the characterization method used was IMPACT 2002+. The results show that sugarcane growing and harvesting stage provides the most harmful environmental impacts (52%) followed by electricity cogeneration (25.7%), sugarcane transportation (12.1%) and finally, sugar milling (10.2%). Regarding the environmental contributions at the endpoint categories, the highest percentage of impacts is found in the Human health category (53%), followed by Climate change (21%), Ecosystem quality (16%) and Resources (10%). The LCA in cane sugar production can support the decision-making process to deal with this environmental problem.
Sugarcane cultivation requires correct fertilizer rates. However, when nutrients are not available, or there is over-fertilization, the yields are significantly reduced and the environmental burden ...increase. In this study, it is proposed a decision support system (DSS) for the correct NPK (nitrogen, phosphorus and potassium) fertilization. The DSS consists of two fuzzy models; the edaphic condition model (EDC-M) and the NPK fertilization model (NPK-M). The DSS using parameters from soil analysis and is based on the experience of two groups of experts to avoid the bias to the reality of a single group of professionals. The results of the DSS are compared with the results of soil analysis and those of the group of experts. One hundred and sixty tests were developed in the NPK-M. The N rate shows R
2
=0.981 for the DSS and R
2
=0.963 for soil analyzes. The P rate shows R
2
=0.9702 for the DSS and R
2
=0.9183 for the soil analyzes. The K rate shows R
2
=0.9691 for the DSS and R
2
=0.9663 for the soil analyzes. Environmental results indicate that the estimated rates with the DSS do reduce the environmental impact on the tests performed.
