There is an increasing need to establish reliable safety controls in the food industry and to protect public health. Consequently, there are numerous efforts to develop sensitive, robust, and selective analytical strategies. As regulatory requirements for food and the concentration for target biomarkers in clinical analysis evolve, the food and health sectors are showing a growing interest in developing non-destructive, rapid, on-site, and environmentally safe methodologies. One alternative that meets the conditions is non-destructive spectroscopic sensors, such as those based on vibrational spectroscopy (Raman, surface-enhanced Raman—SERS, mid- and near-infrared spectroscopy, and hyperspectral imaging built on those techniques). The use of vibrational spectroscopy in food safety and health applications is expanding rapidly, moving beyond the laboratory bench to include on-the-go and in-line deployment. The dominant trends include the following: (1) the miniaturisation and portability of instruments; (2) surface-enhanced Raman spectroscopy (SERS) and nanostructured substrates for the detection of trace contaminants; (3) hyperspectral imaging (HSI) and deep learning for the spatial screening of quality and contamination; (4) the stronger integration of chemometrics and machine learning for robust classification and quantification; (5) growing attention to calibration transfer, validation, and regulatory readiness. These advances will bring together a variety of tools to create a real-time decision-making system that will address the issue in question. This article review aims to highlight the trends in vibrational spectroscopy tools for health and food safety control, with a particular focus on handheld and miniaturised instruments.

There is an increasing need to establish reliable safety controls in the food industry and protect public health. Consequently, there are numerous efforts to develop sensitive, robust and selective analytical strategies. As regulatory requirements for food and the concentration or target bi-omarkers in clinical analysis evolve, the food and health sectors are showing a growing interest in developing non-destructive, rapid, on-site and environmentally safe methodologies. One alternative that meets the conditions is non-destructive spectroscopic sensors, such as those based on vibrational spectroscopy (Raman, surface-enhanced Raman — SERS, mid- and near-infrared spectroscopy, and hyperspectral imaging built on those techniques). The use of vibrational spectroscopy in food safety and health applications is expanding rapidly, moving beyond the laboratory bench to include on-the-go and in-line deployment. The dominant trends are: (1) the min-iaturization and portability of instruments; (2) surface-enhanced Raman spectroscopy (SERS) and nanostructured substrates for the detection of trace contaminants; (3) hyperspectral imaging (HSI) and deep learning for the spatially screening of quality and contamination; (4) the stronger in-tegration of chemometrics and machine learning for robust classification and quantification; (5) growing attention to calibration transfer, validation, and regulatory readiness. These advances will bring together a variety of tools to create a real-time decision-making system that will address the issue in question. This article review aims to highlight trends in vibrational spectroscopy tools for health and food safety control, with a particular focus on handheld and miniaturised instruments.

La energía mecánica necesaria para mover un vehículo se emplea en obtener un trabajo útil (aceleración y ascenso de pendientes en el trayecto) y en vencer resistencias al avance de diferente naturaleza. Estas incluyen resistencias aerodinámicas, resistencias asociadas a la rodadura en los neumáticos, resistencias asociadas la deriva y deslizamiento lateral y longitudinal en el neumático y pérdidas asociadas a toda la cadena cinemática del vehículo, desde el motor a las ruedas. Mejorar la eficiencia energética mecánica de un vehículo implica actuar sobre alguno de los factores que suponen resistencias al avance. Entre las estrategias que favorecen esta mejora se encuentran el diseño de vehículos con bajos coeficientes de arrastre aerodinámico, áreas frontales reducidas, el uso de lubricantes de altas prestaciones y neumáticos con baja resistencia a la rodadura. Parte de las pérdidas energéticas en el neumático están relacionadas con el deslizamiento longitudinal y la deriva lateral de este. En este contexto, un aspecto menos estudiado que impacta sobre el rendimiento del vehículo está relacionado con el control del par entregado a los neumáticos, especialmente durante el paso por curva. Este factor es particularmente relevante en vehículos que permiten gestionar de forma independiente el par aplicado a cada rueda de un eje motriz. En este trabajo se presenta un modelo que permite determinar las pérdidas mecánicas en el vehículo en función de la velocidad, el radio de curvatura y el reparto de par entre ruedas motrices. Para ello se ha empleado el software de simulación Adams Car. Además de evaluar las pérdidas energéticas, se ha analizado la estabilidad del vehículo con el objetivo de garantizar que no se comprometa su comportamiento dinámico. Los resultados obtenidos muestran como un adecuado reparto del par entre las ruedas puede conseguir reducir las pérdidas energéticas asociadas al neumático, incrementando así la eficiencia energética del vehículo en comparación con los sistemas convencionales de tracción, que entregan el mismo par a ambas ruedas de un mismo eje motriz.