Optimal synthesis of thermally coupled distillation sequences using a novel MILP approach

This paper introduces a novel MILP approach for the design of distillation columns sequences of zeotropic mixtures that explicitly include from conventional to fully thermally coupled sequences and divided wall columns with a single wall. The model is based on the use of two superstructure levels. In the upper level a superstructure that includes all the basic sequences of separation tasks is postulated. The lower level is an extended tree that explicitly includes different thermal states and compositions of the feed to a given separation task. In that way, it is possible to a priori optimize all the possible separation tasks involved in the superstructure. A set of logical relationships relates the feasible sequences with the optimized tasks in the extended tree resulting in a MILP to select the optimal sequence. The performance of the model in terms of robustness and computational time is illustrated with several examples.

Disposable electrochromic polyaniline sensor based on a redox response using a conventional camera: A first approach to handheld analysis

We present a disposable optical sensor for Ascorbic Acid (AA). It uses a polyaniline based electrochromic sensing film that undergoes a color change when exposed to solutions of ascorbic acid at pH 3.0. The color is monitored by a conventional digital camera working with the hue (H) color coordinate. The electrochromic film was deposited on an Indium Tin Oxide (ITO) electrode by cyclic voltammetry and then characterized by atomic force microscopy, electrochemical and spectroscopic techniques. An estimation of the initial rate of H, as ΔH/Δt, is used as the analytical parameter and resulted in the following logarithmic relationship: ΔH/Δt = 0.029 log[AA] + 0.14, with a limit of detection of 17 μM. The relative standard deviation when using the same membrane 5 times was 7.4% for the blank, and 2.6% (for n = 3) on exposure to ascorbic acid in 160 μM concentration. The sensor is disposable and its applicability to pharmaceutical analysis was demonstrated. This configuration can be extended for future handheld configurations.

Estimation of Key Dates and Stages in Rice Crops Using Dual-Polarization SAR Time Series and a Particle Filtering Approach

Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique.

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.