Effects of Combined High Hydrostatic Pressure and Dense Phase Carbon Dioxide on the Activity,Structure and Size of Polyphenoloxidase

High hydrostatic pressure (HHP) may activate undesirable enzymes such as polyphenoloxidase (PPO). Carbon dioxide (CO₂) addition to HHP could increase enzyme inactivation. We investigated the inactivation of combined HHP and dense phase carbon dioxide process on activity, secondary conformation and size of pure PPO from mushroom. Solutions (2.35μM, in phosphate buffer pH 6.8) were treated with HHP alone (HHP), or 3.6% w/w of CO₂ was injected into the package (HHP+CO₂). Treatment conditions were 600 MPa, 20 °C, for 1, 3, 5, 7, and 9 min. HHP+CO₂ treatment significantly decreased residual enzyme activity (REA) to 30% to 12% after 1 to 9 min, respectively, whereas only HHP had no significant effect. Both HHP and HHP+CO₂ treatments caused changes in secondary conformations, however HHP+CO₂ changes were more extensive. Alpha‐helix fractions were reduced by 32% and 41%, while β sheet, turn and unordered increased by 63% and 213%, 100% and 71%, and 118% and 82% for HHP and HHP+CO₂, respectively after 9 min. The protein size in HHP+CO₂ samples was 5‐ to 6‐fold larger than that of Control and HHP treatment, and this increase was inversely correlated with REA. The best inactivation kinetics of HHP+CO₂ model was the 2‐fractional model with 2 simultaneous 1st‐order steps, contributing 70% and 30% to original enzyme activity, with k_labile = 12.15 min^?1 and k_stable = 0.07 min^?1, respectively. No recovery in activity, secondary conformation and size in all samples were observed after 1‐mo storage. Addition of CO₂ in HHP treatment can improve enzyme inactivation, and therefore product shelf‐life and quality.     

Damage identification by response surface based model updating using D-optimal design

Statistical tools, as well as mathematical ones, have been widely adopted and their performance has been shown in different engineering problems where randomicity usually exists. In the realm of engineering, merging statistical analysis into structural evaluation and assessment will be a tendency in the future. As a combination of mathematical and statistical techniques, response surface methodology has been successfully applied to design optimization, response prediction and model validation. This methodology provides explicit functions to represent the relationships between the inputs and outputs of a physical system, which is also a desirable advantage in damage identification. However, so far little research has been carried out in applying the response surface methodology to structural damage identification. This paper presents a damage identification method achieved by response surface based model updating using D-optimal designs. Compared with some common designs constructing response surfaces, D-optimal designs generally require a minimum number of numerical samples and this merit is quite desirable when analysts cannot obtain enough samples. In this study, firstly D-optimal designs are used to establish response surface models for screening out non-significant updating parameters and then first-order response surface models are constructed to substitute for finite element models in predicting the dynamic responses of an intact or damaged physical system. Three case studies of a numerical beam, a tested reinforced concrete frame and a tested full-scale bridge have been used to verify the proposed method. Physical properties such as Young’s modulus and section inertias were chosen as the input features and modal frequency was the only response feature. It has been observed that the proposed method gives enough accuracy in damage prediction of not only the numerical but also the real-world structures with single and multiple damage scenarios, and the first-order response surface models based on the D-optimal criterion are adequate for such damage identification purposes.     

Effect of Tissue Disruption by Different Methods Followed by Incubation with Hydrolyzing Enzymes on the Production of Vanillin from Tongan Vanilla Beans

Vanilla is one of the most popular and valuable flavorings worldwide. Natural vanilla is extracted from the cured vanilla pods of Vanilla planifolia. The main aromatic compound in vanilla is vanillin, a phenolic aldehyde, which is produced by enzymatic hydrolysis of glucovanillin during the curing process. Although the amount of glucovanillin in the uncured green bean is present at the level of 10–15%, only an average of about 2% vanillin yield results from the traditional curing process. Therefore, the aim of the experiment was to increase the vanillin yield by obtaining the maximum conversion of glucovanillin. This was obtained by the addition of exogenous cellulase, pectinase, and beta glucosidase enzymes and cellular-damaging techniques on green Tongan vanilla beans to enhance the interaction between glucovanallin substrate and enzymes and successfully achieved vanillin production ranging from 4.25 to 7.00% on a dry weight basis. These techniques may be further refined and translated into industrial curing practices for improvement of natural vanillin yield from vanilla beans.     

Bioactivation and irreversible binding of the cognition activator tacrine using human and rat liver microsomal preparations. Species difference

Tacrine's [1,2,3,4-tetrahydro-9-acridinamine monohydrochloride monohydrate, (THA)] metabolic fate was examined using human and rat liver microsomal preparations. Following 1-hr incubations with human microsomes, [14C]THA (0.4 microM) was extensively metabolized to 1-hydroxyTHA with trace amounts of 2-, 4-, and 7-hydroxyTHA also produced. Poor recovery of radioactivity in the postreaction incubates suggested association of THA-derived radioactivity with precipitated microsomal protein. After exhaustive extraction, 0.034, 0.145, 0.126, and 0.012 nmol eq bound/mg protein/60 min of THA-derived radioactivity was bound to human liver preparations H109, H111, H116, and H118, respectively. Preparations H109 and H118 were lower in P4501A2 content and catalytic activity as compared with preparations H111 and H116. Incubations of equimolar [14C]1-hydroxyTHA with human liver microsomes also resulted in binding to protein, although to a lesser extent than observed with THA. [14C]THA (0.4 microM) was incubated for 1 hr with rat liver microsomes (1 microM P-450) prepared from noninduced (N), phenobarbital (PB), isoniazid (I), and 3-methylcholanthrene (3-MC)-pretreated animals. In all incubations, 1-hydroxyTHA was the major biotransformation product detected. After exhaustive extraction, 0.048, 0.054, 0.049, and 0.153 nmol eq/mg protein/60 min of THA-derived radioactivity was bound to microsomal protein from N, PB, I, and 3-MC pretreated rats. Increased binding with 3-MC induced rat liver preparations suggests the involvement of the P-450 1A subfamily in THA bioactivation. Glutathione (5 mM) coincubation inhibited the irreversible binding of THA-derived radioactivity in both human and 3-MC-induced rat liver preparations, whereas human epoxide hydrase (100 micrograms/incubate) had a relative minor effect. A mechanism is proposed involving a putative quinone methide(s) intermediate in the bioactivation and irreversible binding of THA. A species difference in THA-derived irreversible binding exists between human and noninduced rat liver microsomes, suggesting that the rat is a poor model for studying the underlying mechanism(s) of THA-induced elevations in liver marker enzymes found in clinical investigations.     

Cutting to the chase with warm-start contextual bandits

Knowledge and Information Systems - Multi-armed bandits achieve excellent long-term performance in practice and sublinear cumulative regret in theory. However, a real-world limitation of bandit...     

Tailoring 3D Printed Micro-Structured Carbons for Adsorption

The manufacture of tailored carbon-based adsorbent structures with exceptionally low-pressure drops and improved kinetics using stereolithographic 3D printing is presented. Adsorbent structures are printed from commercial resins with square, circular, and hexagonal cross-sectional microchannels. These structures can reduce energy use by 50–95% compared to conventional carbon-packed beds. The activated 3D printed carbon achieves Brunauer–Emmett–Teller surface areas over 1000 m² g⁻¹ and shows outstanding butane adsorption capacities, over twice the capacity of a commercial carbon and a comparable capacity to phenolic-based carbons. The structures also show excellent uptakes of cyclohexane, up to 0.62 g g⁻¹ in a saturated feed. The introduction of complex axial geometries including spirals and chevrons enable superior adsorption kinetics and premature breakthrough of contaminants at high gas flow rates. These results demonstrate the success of intelligent manufacturing of low-pressure drop, high-capacity micro-structured adsorbents, allowing for the development of gas separation technologies for applications such as greenhouse gas removal and respiratory protection.     

Neural network-based optical flow versus traditional optical flow techniques with thermal aerial imaging in real-world settings

The study explores the feasibility of optical flow-based neural network from real-world thermal aerial imagery. While traditional optical flow techniques have shown adequate performance, sparse techniques do not work well during cold-soaked low-contrast conditions, and dense algorithms are more accurate in low-contrast conditions but suffer from the aperture problem in some scenes. On the other hand, optical flow from convolutional neural networks has demonstrated good performance with strong generalization from several synthetic public data set benchmarks. Ground truth was generated from real-world thermal data estimated with traditional dense optical flow techniques. The state-of-the-art Recurrent All-Pairs Field Transform for the Optical Flow model was trained with both color synthetic data and the captured real-world thermal data across various thermal contrast conditions. The results showed strong performance of the deep-learning network against established sparse and dense optical flow techniques in various environments and weather conditions, at the cost of higher computational demand.