The Effect of Food Type (Fish Nuggets or French Fries) on Oil Blend Degradation during Repeated Frying

Abstract: Oil that is reused multiple times for deep frying goes through changes in chemical composition and physical characteristics, affecting the quality of the fried foods. In this study, the effect of the food type (fish nuggets or French fries) on the degradation of an oil blend during the deep‐fat frying of each food at 180°C during 12 days was determined, and the characteristics of the fried products were evaluated. The degradation of oil during repeated use was relatively faster when fish nuggets were fried than when French fries were fried, as higher values of total polar compounds were obtained. Practical Application: The results are useful for producers of French fries and fish nuggets, such as restaurants or fast foods sellers, providing them with practical guidelines within the permitted values established by the regulatory authorities. The studied foods have high economic importance and are different in their composition. Under the studied conditions, the tested oil blend may be used during 4 d (4 h per day) with a daily replenishment, without discarding the oil when frying fish nuggets, and must be discarded after 8 d when French fries are processed. This suggestion allows preparing safe fried foods for consumers.     

Sequential processing of quantitative phase images for the study of cell behaviour in real‐time digital holographic microscopy

Transmitted light holographic microscopy is particularly used for quantitative phase imaging of transparent microscopic objects such as living cells. The study of the cell is based on extraction of the dynamic data on cell behaviour from the time‐lapse sequence of the phase images. However, the phase images are affected by the phase aberrations that make the analysis particularly difficult. This is because the phase deformation is prone to change during long‐term experiments. Here, we present a novel algorithm for sequential processing of living cells phase images in a time‐lapse sequence. The algorithm compensates for the deformation of a phase image using weighted least‐squares surface fitting. Moreover, it identifies and segments the individual cells in the phase image. All these procedures are performed automatically and applied immediately after obtaining every single phase image. This property of the algorithm is important for real‐time cell quantitative phase imaging and instantaneous control of the course of the experiment by playback of the recorded sequence up to actual time. Such operator's intervention is a forerunner of process automation derived from image analysis. The efficiency of the propounded algorithm is demonstrated on images of rat fibrosarcoma cells using an off‐axis holographic microscope.     

A DNA Methyltransferase Modulator Inspired by Peyssonenyne Natural Product Structures

A novel epigenetic modulator that displays a DNMT1 inhibition and DNMT3A activation profile was characterized (compound 8 ). This compound is a derivative of palmitic acid that incorporates the putative reactive functional group (diynone) of the peyssonenyne natural products. Other analogues containing the diynone or an acetoxyenediyne did not show the same biological profile. In U937 human leukemia cells, diynone 8 induced cell differentiation and apoptosis, which correlated with the expression of Fas protein. Very surprisingly, diynone 8 was toxic to normal human fibroblasts (BJ) and mouse embryo fibroblasts (MEF), but not to immortalized human fibroblasts (BJEL); this unique effect was not observed with the classical DNMT inhibitor 5‐azacytidine. Therefore, compound 8 interferes in a very specific manner with signaling pathways, the activities of which differ between normal and immortalized cell types. This toxicity is reminiscent of the effects of Dnmt1 ablation on mouse fibroblasts. In fact, some of the genes deregulated by the loss of Dnmt1 are similarly deregulated by 8 , but not by the DNMT inhibitor SGI‐1027.     

Effects of Catalyst Activity Profiles on the Operating Conditions of an Industrial Polymerization Reactor

The aim of this paper is to analyze how different catalyst activity profiles influence the operating strategies of industrial polymerization reactors. Since the catalyst activity profiles may change considerably in the range of the residence-time of the reactor, the properties of the produced polymer powder are the averages of ones produced by catalyst particles with various activities. Hence, the residence-time distribution of the polymer phase has an effect on the product properties as well. Based on these phenomena a new method is proposed to transform information from laboratory reactor into a form which can be used to estimate the operation condition of industrial reactor. The whole approach is demonstrated in case of the production of high-density polyethylene.     

Advanced Adaptive Sonar for Mapping Applications

An advanced adaptive sonar module is described, capable of being configured to different circumstances and distances according to reflectors found in the environment. Thanks to the sensory distribution, it is possible to identify three basic types of reflector (planes, edges and corners). Furthermore, a heuristic map of the environment is built. The proposed methods have been computationally optimized, and implemented in a real-time system based on a Field-Programmable Gate Array (FPGA) and a Digital Signal Processor (DSP). Results have been obtained in the detection, classification and mapping of obstacles; and finally testing has been carried out on a commercial vehicle.     

A new algorithm to compute conjectured supply function equilibrium in electricity markets

Several types of market equilibria approaches, such as Cournot, Conjectural Variation (CVE), Supply Function (SFE) or Conjectured Supply Function (CSFE) have been used to model electricity markets for the medium and long term. Among them, CSFE has been proposed as a generalization of the classic Cournot. It computes the equilibrium considering the reaction of the competitors against changes in their strategy, combining several characteristics of both CVE and SFE. Unlike linear SFE approaches, strategies are linearized only at the equilibrium point, using their first-order Taylor approximation. But to solve CSFE, the slope or the intercept of the linear approximations must be given, which has been proved to be very restrictive.This paper proposes a new algorithm to compute CSFE. Unlike previous approaches, the main contribution is that the competitors’ strategies for each generator are initially unknown (both slope and intercept) and endogenously computed by this new iterative algorithm.To show the applicability of the proposed approach, it has been applied to several case examples where its qualitative behavior has been analyzed in detail.