Tool selection is relevant because a wide variety of materials exhibit different machinability behaviors. Tool life during manufacturing is commonly associated with productivity. Insert developers have been using coatings on cutting tools to enhance their performance, with chemical vapor deposition (CVD) and physical vapor deposition (PVD) being the two most used techniques. This study analyzed the cutting tool wear mechanism by machining AISI D2 steel using two different inserts of TiAlN/TiN PVD and TiCN/Al₂O₃ CVD as layers deposited on a carbide substrate. The two inserts were tested at three different cutting speeds, namely, low, medium, and high; these values were below the data suggested by the supplier catalog. The flank wear and rake face were analyzed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectrometry (EDX). The adhesion material, edge deformation, and abrasion were the main wear mechanisms before catastrophic damage occurred at the three different cutting speeds in the PVD cutting tool. Nevertheless, increasing the cutting speed reduced the tool life from 84% to 61% at high values compared to the medium values of PVD and CVD, respectively, where the medium value resulted in a balance between the material removal rate and tool life. The wear mechanism of the CVD tool was BUE and chipping; nevertheless, its craters were larger than those of the PVD. Compared to those configured for PVD, the CVD insert demonstrated the ability to machine D2 steel at twice the cutting speed with a workpiece surface roughness of 0.3 µm, in contrast to a variation of 0.6 to 0.15 µm with the PVD tool.

Computational sciences have been highlighted in the application to any area with good results. One of the primary interests of humanity is water quality because it is a vital resource for the existence of living beings. This research applies a data mining model based on CRISP-DM methodology built to classify water contamination in lotic systems in Puebla City, located in the center of Mexico. The classification was carried out through physicochemical parameters using a water quality evaluation model based on the amount of dissolved oxygen percentage (%DO). Results demonstrate that the application of decision trees and K-NN algorithms, using chemical parameters, are effective in determining the presence of contamination in lotic water bodies and represent a novel way to evaluate water quality in the water system along rivers in Puebla, Mexico.

Las redes sociales son uno de los medios de comunicación política más importantes, a través de ellas se publican y generan opiniones de una gran variedad de temas, por esta razón, son un medio excelente para realizar análisis y comprender sucesos. En este trabajo se realizó un análisis de sentimientos de publicaciones de X/Twitter sobre las elecciones de candidatos presidenciales de México en 2024 utilizando la clasificación de polaridad de sentimientos para medir el posicionamiento de los participantes. Se utilizó una metodología basada en KDD y se analizaron 151 821 publicaciones sobre cuatro aspirantes a candidatos a la presidencia de México del partido MORENA. Los resultados mostraron que los candidatos mejor posicionados en la elección son aquellos que obtuvieron la mayor cantidad de publicaciones con polaridad positiva, aunque el aspirante ganador no coincidió con el mayor porcentaje de polaridades positivas. Este resultado indica que es necesario incluir otras variables además de la polaridad para hacer una predicción más exacta de los ganadores de las contiendas políticas.