Prediction of Flooding in Packed Liquid-Liquid and High-Pressure Extraction Columns Using a Gaussian Process

Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely.     

Cold plasma for the disinfection of industrial food-contact surfaces: An overview of current status and opportunities

Food safety is the primary goal for food and drink manufacturers. Cleaning and disinfection practices applied to the processing environment are vital to maintain this safety; yet, current approaches can incur costly downtime and the potential for microorganisms to grow and establish, if not effectively removed. For that reason, manufacturers are seeking nonthermal, online, and continuous disinfection processes to control the microbial levels within the processing environment. One such emerging technique, with great potential, is cold atmospheric pressure plasma (CAP). This review presents the latest advances and challenges associated with CAP-based technologies for the decontamination of surfaces and equipment found within the food-processing environment. It provides a detailed overview of the technology and a comprehensive analysis of the many CAP-based antimicrobial studies on food-contact surfaces and materials. As CAP is considered an emerging technique, many of the recent studies are still in the preliminary stages, with results obtained under widely different conditions. This lack of cohesive information and an inability to directly compare CAP systems has greatly impeded technological development. The review further explores the challenge of scaling CAP technology to meet industry needs, considering aspects such as regulatory constraints, environmental credentials, and cost of use. Finally, a discussion is presented on the future outlook for CAP technology in this area, identifying key challenges that must be addressed to promote industry uptake.     

Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles

Hydrograph clustering helps to identify dynamic patterns within aquifers systems, an important foundation of characterizing groundwater systems and their influences, which is necessary to effectively manage groundwater resources. We develope an unsupervised modeling approach to characterize and cluster hydrographs on regional scale according to their dynamics. We apply feature-based clustering to improve the exploitation of heterogeneous datasets, explore the usefulness of existing features and propose new features specifically useful to describe groundwater hydrographs. The clustering itself is based on a powerful combination of Self-Organizing Maps with a modified DS2L-Algorithm, which automatically derives the cluster number but also allows to influence the level of detail of the clustering. We further develop a framework that combines these methods with ensemble modeling, internal cluster validation indices, resampling and consensus voting to finally obtain a robust clustering result and remove arbitrariness from the feature selection process. Further we propose a measure to sort hydrographs within clusters, useful for both interpretability and visualization. We test the framework with weekly data from the Upper Rhine Graben System, using more than 1800 hydrographs from a period of 30 years (1986-2016). The results show that our approach is adaptively capable of identifying homogeneous groups of hydrograph dynamics. The resulting clusters show both spatially known and unknown patterns, some of which correspond clearly to external controlling factors, such as intensive groundwater management in the northern part of the test area. This framework is easily transferable to other regions and, by adapting the describing features, also to other time series-clustering applications.

     

Endometriosis detection and localization in laparoscopic gynecology

Multimedia Tools and Applications - Endometriosis is a common gynecologic condition typically treated via laparoscopic surgery. Its visual versatility makes it hard to identify for non-specialized...     

Anisotropy Effects in the Shape-Memory Performance of Polymer Foams

Isotropic and anisotropic shape-memory polymer foams are prepared by supercritical carbon dioxide foaming from a multiblock copolymer (PDLCL) consisting of poly(ω-pentadecalactone) and poly(ε-caprolactone) segments. Analysis by micro-computed tomography reveals for the anisotropic PDLCL foam cells a high shape anisotropy ratio of R = 1.72 ± 0.62 with a corresponding Young's compression moduli ratio between longitudinal and transversal direction of 4.3. The experimental compression data in the linear elastic range can be well described by the anisotropic open foam model of Gibson and Ashby. A micro-morphological analysis for single pores using scanning electron microscopy images permits the correlation between the macroscopic stress-compression behavior and microscale structural changes.     

Model-driven engineering for mobile robotic systems: a systematic mapping study

Software and Systems Modeling - Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of...     

Fabrication of Anticounterfeiting Nanocomposites with Multiple Security Features via Integration of a Photoresponsive Polymer and Upconverting Nanoparticles

Anticounterfeiting materials are used to distinguish real banknotes, products, and documents from counterfeits, fakes, or unauthorized replicas. However, conventional anticounterfeiting materials generally exhibit a single anticounterfeiting function, resulting in a low level of security. Herein, a novel anticounterfeiting nanocomposite is demonstrated with numerous prominent security features. The nanocomposite is fabricated by doping upconverting nanoparticles (UCNPs) in a photoresponsive azobenzene-containing polymer (azopolymer). Because of the cis–trans photoisomerization of the azopolymer, the nanocomposite exhibits photoinduced reversible color changes suitable for anticounterfeiting applications. Additionally, the hard nanocomposite can be converted to a rubber-like soft solid by light irradiation. Imprinted microstructures are fabricated on the photosoftened nanocomposite, which result in photonic colors. Moreover, polarization-dependent structures are fabricated on the nanocomposite via photoinduced orientation for encryption. Importantly, UCNPs in the nanocomposite emit visible light upon excitation by near-infrared light, enabling the observation of various anticounterfeiting structures with high contrast. An advantage of the anticounterfeiting nanocomposite is that the security features can be observed by the naked eye for quick discrimination and can be analyzed using laboratory equipment for higher accuracy. The anticounterfeiting nanocomposite is easily processed on paper, glass, and plastic, which demonstrates its potential anticounterfeiting functions for banknotes, wines, and medicines.     

Two Methods,One Goal: Structural Differences between Cocrystallization and Crystal Soaking to Discover Ligand Binding Poses

In lead optimization, protein crystallography is an indispensable tool to analyze drug binding. Binding modes and non-covalent interaction inventories are essential to design follow-up synthesis candidates. Two protocols are commonly applied to produce protein–ligand complexes: cocrystallization and soaking. Because of its time and cost effectiveness, soaking is the more popular method. Taking eight ligand hinge binders of protein kinase A, we demonstrate that cocrystallization is superior. Particularly for flexible proteins, such as kinases, and larger ligands cocrystallization captures more reliable the correct binding pose and induced protein adaptations. The geometrical discrepancies between soaking and cocrystallization appear smaller for fragment-sized ligands. For larger flexible ligands that trigger conformational changes of the protein, soaking can be misleading and underestimates the number of possible polar interactions due to inadequate, highly impaired positions of protein amino-acid side and main chain atoms. Thus, if applicable cocrystallization should be the gold standard to study protein–ligand complexes.     

Density of solutions of formaldehyde in water and alcohols

Formaldehyde is an important chemical that is mostly handled in aqueous solutions, which generally also contain methanol; furthermore, also solutions of formaldehyde in other alcohols are used. The density of these solutions is an important thermophysical property. The available models of the density of formaldehyde-containing solutions, however, all have shortcomings, such as a poor accuracy or a limited range of applicability. Therefore, in the present work, a new model of the density in systems of the type (formaldehyde + water + alcohol) was developed. The alcohols that are presently included in the new model are methanol, 1-propanol, and isoprenol; an extension to other alcohols is straightforward. The model was developed using literature data and extensive new density data measured in this work covering binary, ternary, and quarternary solutions of formaldehyde in water, methanol, 1-propanol, and isoprenol at temperatures of $283-333$ K and formaldehyde concentrations of 0.06 − 0.30 g g⁻¹.     

A visible-light and infrared video database for performance evaluation of video/image fusion methods

Multidimensional Systems and Signal Processing - In general, the fusion of visible-light and infrared images produces a composite representation where both data are pictured in a single image. The...