Automatic parameter tuning for functional regionalization methods

The methods used to define functional regions for public statistics and policy purposes need to establish several parameter values. This is typically achieved using expert knowledge based on qualitative judgements and lengthy consultations with local stakeholders. We propose to support this process by using an optimization algorithm to calibrate any regionalization method by identifying the parameter values that produce the best regionalization for a given quantitative indicator. The approach is exemplified by using a grid search and a genetic algorithm to configure the official methods employed in the UK and Sweden for the definition of their respective official concepts of local labour markets.     

Recent advances in γ‐aminobutyric acid (GABA) properties in pulses: an overview

Beans, peas, and lentils are all types of pulses that are extensively used as foods around the world due to their beneficial effects on human health including their low glycaemic index, cholesterol lowering effects, ability to decrease the risk of heart diseases and their protective effects against some cancers. These health benefits are a result of their components such as bioactive proteins, dietary fibre, slowly digested starches, minerals and vitamins, and bioactive compounds. Among these bioactive compounds, γ‐aminobutyric acid (GABA), a non‐proteinogenic amino acid with numerous reported health benefits (e.g. anti‐diabetic and hypotensive effects, depression and anxiety reduction) is of particular interest. GABA is primarily synthesised in plant tissues by the decarboxylation of l ‐glutamic acid in the presence of glutamate decarboxylase (GAD). It is widely reported that during various processes including enzymatic treatment, gaseous treatment (e.g. with carbon dioxide), and fermentation (with lactic acid bacteria), GABA content increases in the plant matrix. The objective of this review paper is to highlight the current state of knowledge on the occurrence of GABA in pulses with special focus on mechanisms by which GABA levels are increased and the analytical extraction and estimation methods for this bioactive phytochemical. © 2017 Society of Chemical Industry     

Infantry mobility hybrid electric vehicle performance analysis and design

Optimal energy flux analysis and design of a power plant for infantry mobility hybrid diesel-electric vehicle is dealt with in this paper. Control strategy management and propulsion system sizing is done on the basis of minimizing total fuel consumption. A quasi-static system model has allowed analyzing the most restrictive operations; moreover the simulation has been used in expected real driving cycles in order to check the performance in typical mission.     

Advanced DNA- and Protein-based Methods for the Detection and Investigation of Food Allergens

Currently, food allergies are an important health concern worldwide. The presence of undeclared allergenic ingredients or the presence of traces of allergens due to contamination during food processing poses a great health risk to sensitized individuals. Therefore, reliable analytical methods are required to detect and identify allergenic ingredients in food products. The present review addresses the recent developments regarding the application of DNA- and protein-based methods for the detection of allergenic ingredients in foods. The fitness-for-purpose of reviewed methodology will be discussed, and future trends will be highlighted. Special attention will be given to the evaluation of the potential of newly developed and promising technologies that can improve the detection and identification of allergenic ingredients in foods, such as the use of biosensors and/or nanomaterials to improve detection limits, specificity, ease of use, or to reduce the time of analysis. Such rapid food allergen test methods are required to facilitate the reliable detection of allergenic ingredients by control laboratories, to give the food industry the means to easily determine whether its product has been subjected to cross-contamination and, simultaneously, to identify how and when this cross-contamination occurred.     

Automated Systems Based on Machine Vision for Inspecting Citrus Fruits from the Field to Postharvest—a Review

Computer vision systems are becoming a scientific but also a commercial tool for food quality assessment. In the field, these systems can be used to predict yield, as well as for robotic harvesting or the early detection of potentially dangerous diseases. In postharvest handling, it is mostly used for the automated inspection of the external quality of the fruits and for sorting them into commercial categories at very high speed. More recently, the use of hyperspectral imaging is allowing the detection of not only defects in the skin of the fruits but also their association to certain diseases of particular importance. In the research works that use this technology, wavelengths that play a significant role in detecting some of these dangerous diseases are found, leading to the development of multispectral imaging systems that can be used in industry. This article reviews recent works that use colour and non-standard computer vision systems for the automated inspection of citrus. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of internal and external features of these fruits. Particular attention is paid to inspection for the early detection of some dangerous diseases like citrus canker, black spot, decay or citrus Huanglongbing.