Development of a water-in-oil-in-water multiple emulsion system integrating biomimetic aqueous-core lipid nanodroplets for protein entity stabilization. Part II: process and product characterization

The aqueous-core enclosed in lipid nanoballoons integrating multiple emulsions of the type water-in-oil-in-water mimic, at least in theory, the environment within viable cells, thus being suitable for housing hydrophilic protein entities such as bioactive proteins, peptides and bacteriophage particles. This study reports a complete physicochemical characterization of optimized biomimetic aqueous-core lipid nanoballoons housing hydrophilic (BSA) protein entities, evolved from a statistical 2³×3¹ factorial design study (three variables at two levels and one variable at three levels) that was the subject of the first paper of a series of three, aiming at complete stabilization of the three-dimensional structure of protein entities attempted via housing the said molecular entities within biomimetic aqueous-core lipid nanoballoons integrating a multiple (W/O/W) emulsion. The statistical factorial design followed led to the production of an optimum W/O/W multiple emulsion possessing quite homogeneous particles with an average hydrodynamic size of (186.2?±?2.6) nm and average Zeta potential of (?36.5?±?0.9) mV, and exhibiting a polydispersity index of 0.206?±?0.014. Additionally, the results obtained for the diffusion coefficient of the lipid nanoballoons integrating the optimized W/O/W multiple emulsion were comparable and of the same order of magnitude (10^?12 m² s^?1) as those published by other authors since, typically, diffusion coefficients for molecules range from 10^?10 to 10^?7 m² s^?1, but diffusion coefficients for nanoparticles are typically of the order of magnitude of 10^?12 m² s^?1.     

Correct behavior identification system in a Tagged World

This paper presents a system that is able to process the information provided by a Tagged World to identify user’s behavior and to produce alarms in dangerous situations. The system inputs are signals from sensors, which are used to recognize correct behavior (action sequences) by Inductive Learning, using Data Mining techniques. The inference engine is a reasoning device that is implemented by means of Regular Grammars. It permits us to control user’s behavior. As output, the system produces and sends alarms when a user action sequence is wrong, indicating the erroneous actions, forgotten future, and so on. To test our system, the Tagged World is supposed to be at a house, where we have used RFID technology to control the objects inside it.     

Retrofit of RC hollow piers with CFRP sheets

Hollow bridge piers, particularly those built before the seventies, often have insufficient shear capacity due to inadequate transverse reinforcement details. Therefore, special attention must be given to this very important aspect when reinforced concrete (RC) piers with hollow sections are analysed and retrofitted. This paper covers the experimental analysis of retrofit solutions using CFRP sheets along the piers’ entire height to prevent shear failure. Experimental cyclic tests were carried out to evaluate the shear retrofit strategy efficiency on a set of RC piers with square hollow sections. This work also covers the study of design procedures for CFRP shear retrofitting and the evaluation of the associated ductility capacity improvement. The various transverse reinforcement detailing scenarios were assessed to determine their shear-failure prevention efficiency. The corresponding cyclic response behavior was also evaluated. The most relevant experimental information is presented in the paper, such as the evolution of the outer damage pattern. Finally, shear retrofit solutions, with a 40% increase over the maximum flexural force, show that this strategy is adequate to allow satisfactory ductility behavior.     

Efficient driver drowsiness detection at moderate levels of drowsiness

Previous research on driver drowsiness detection has focused primarily on lane deviation metrics and high levels of fatigue. The present research sought to develop a method for detecting driver drowsiness at more moderate levels of fatigue, well before accident risk is imminent. Eighty-seven different driver drowsiness detection metrics proposed in the literature were evaluated in two simulated shift work studies with high-fidelity simulator driving in a controlled laboratory environment. Twenty-nine participants were subjected to a night shift condition, which resulted in moderate levels of fatigue; 12 participants were in a day shift condition, which served as control. Ten simulated work days in the study design each included four 30-min driving sessions, during which participants drove a standardized scenario of rural highways. Ten straight and uneventful road segments in each driving session were designated to extract the 87 different driving metrics being evaluated. The dimensionality of the overall data set across all participants, all driving sessions and all road segments was reduced with principal component analysis, which revealed that there were two dominant dimensions: measures of steering wheel variability and measures of lateral lane position variability. The latter correlated most with an independent measure of fatigue, namely performance on a psychomotor vigilance test administered prior to each drive. We replicated our findings across eight curved road segments used for validation in each driving session. Furthermore, we showed that lateral lane position variability could be derived from measured changes in steering wheel angle through a transfer function, reflecting how steering wheel movements change vehicle heading in accordance with the forces acting on the vehicle and the road. This is important given that traditional video-based lane tracking technology is prone to data loss when lane markers are missing, when weather conditions are bad, or in darkness. Our research findings indicated that steering wheel variability provides a basis for developing a cost-effective and easy-to-install alternative technology for in-vehicle driver drowsiness detection at moderate levels of fatigue.     

Morphology and Stability of Edible Lycopene-Containing Micro- and Nanocapsules Produced Through Electrospraying and Spray Drying

Food and Bioprocess Technology - In this work, lycopene was encapsulated through electrospraying and spray drying (using a microporous membrane cap) within different edible biopolymeric matrices....     

Automatic bearing fault diagnosis based on one-class ν-SVM

Rolling-element bearings are among the most used elements in industrial machinery, thus an early detection of a defect in these components is necessary to avoid major machine failures. Vibration analysis is a widely used condition monitoring technique for high-speed rotating machinery. Using the information contained in the vibration signals, an automatic method for bearing fault detection and diagnosis is presented in this work. Initially, a one-class ν-SVM is used to discriminate between normal and faulty conditions. In order to build a model of normal operation regime, only data extracted under normal conditions is used. Band-pass filters and Hilbert Transform are then used sequentially to obtain the envelope spectrum of the original raw signal that will finally be used to identify the location of the problem. In order to check the performance of the method, two different data sets are used: (a) real data from a laboratory test-to-failure experiment and (b) data obtained from a fault-seeded bearing test. The results showed that the method was able not only to detect the failure in an incipient stage but also to identify the location of the defect and qualitatively assess its evolution over time.     

Ontologies versus relational databases: are they so different? A comparison

Two main data models are currently used for representing knowledge and information in computer systems. Database models, especially relational databases, have been the leader in last few decades, enabling information to be efficiently stored and queried. On the other hand, ontologies have appeared as an alternative to databases in applications that require a more ‘enriched’ meaning. However, there is controversy regarding the best information modeling technique, as both models present similar characteristics. In this paper, we present a review of how ontologies and databases are related, of what their main differences are and of the mechanisms used to communicate with each other.     

A new biobased plasticizer for poly(vinyl chloride) based on epoxidized cottonseed oil

The use of epoxidized cottonseed oil as plasticizer for poly(vinyl chloride) was studied. The plasticizer content was set to 70 phr and the optimum isothermal curing conditions were studied in the temperature range comprised between 160 and 220 °C with varying curing times in the 7.5–17.5 min range. The influence of the curing conditions on overall performance of cured plastisols was followed by the evolution of mechanical properties (tensile tests with measurements of tensile strength, elongation at break, and modulus), change in color, surface changes of fractured samples by scanning electron microscopy (SEM), thermal transitions by differential scanning calorimetry, and migration in n‐hexane. The optimum mechanical features of cured plastisols are obtained for curing temperatures in the 190–220 °C range. For these curing conditions, fractography analysis by SEM gives evidences of full curing process as no PVC particles and free plasticizer can be found. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43642.     

Protein breakdown during the preparation of frozen batter-coated squid rings

The objective of this paper was to study the main chemical and microstructural changes in squid proteins during processing as a frozen batter-coated product using different coatings. Protein bands of the squid and of the batters used for coating were studied using SDS-PAGE. It is concluded that it is not only the proteins of the layer of batter, which are directly exposed both to the frying oil and to freezing temperatures, that deteriorate during the preparation process, the protein fraction of the squid substrate, mainly the myofibrillar proteins, is also degraded. At a microstructural level, big voids are generated during freezing as a consequence of the packing of the fibres, although the size of these voids decreases after final frying. After this step of the process, the central sarcoplasm is still visible but has been altered by coagulation of the sarcoplasmic proteins and the sarcolemma is observed to be separate from the myofibrillar package.