Performance Evaluation of a Zero-Fouling Reciprocating Scraped-Surface Heat Exchanger

An innovative self-cleaning shell-and-tube heat exchanger is presented. Inside each interior tube (through which the product flows) a scraping rod is fitted. This rod moves in reciprocal manner and the scraping elements mounted on the rod fully clean the tube wall surface. Additionally, the macroscopic displacements of the flow, induced by the insert device motion, promote high flow mixing. Consequently, tube-side heat transfer coefficients are enhanced. Thermal-hydraulic and scraping power measurements are performed in laminar regime for motionless and dynamic conditions. An extended performance evaluation criterion is proposed, in order to balance the augmentation of heat transfer and the increased power consumption (pumping and scraping power) of the device. This study allows stating guidelines for the operation of the device, concluding that the performance of the heat exchanger is irrespective of the velocity ratio. The scraper can be used intermittently, or at the minimum scraping frequency that ensures fouling mitigation.     

Effect of Temperature on the Viscosity of Honey

Influence of temperature on the viscosity of honeys was analysed in the present work. The viscosity value decreased with the increase of temperature. The effect caused by temperature in the range studied was more important in the low range of temperature, whereas at high temperature, the viscosity showed less variation. Water activity and glass transition temperature was determined to relate these characteristics. Four experimental viscosity models were checked using the experimental data to correlate the influence of temperature upon honey viscosity.     

Carob Fruit Polyphenols Reduce Tocopherol Loss,Triacylglycerol Polymerization and Oxidation in Heated Sunflower Oil

Heated oils may contain potentially toxic altered compounds. A denatured carob fiber, very rich in non-extractable tannins (Exxenterol^®), exhibits antioxidant activities in in vitro experiments. The present study was designed to evaluate in sunflower oil (SO) heated to frying temperature, the protective effect on oil thermal oxidation and polymerization of adding 10 mg Exxenterol/kg oil (SO-10) and 50 mg Exxenterol/kg oil (SO-50). After 2, 8 and 16 h at 180 °C, SO displayed a relevant increase in triacylglycerol-derived polar material (PM) and polymer contents and a decrease in α-tocopherol concentrations. Thermal oxidation changes were significantly checked in SO-50 throughout the 16-h heating, while SO-10 only displayed protection from thermal oxidation during the first 2 h of heating. Oil frying-life was doubled because formation of PM and polymers was inhibited by more than 50%. Results clearly show that this non-extractable tannin-rich fiber can be successfully employed as an additive to significantly prolong sunflower oil frying-life, and thus decrease the potential toxicity of the heated oil.     

Investigation of RuO2-SnO2 thin film formation by thermogravimetry-mass spectrometry and infrared emission spectroscopy

The thermal evolution process of RuO₂-SnO₂/Ti mixed oxide thin films of varying noble metal content has been investigated by thermogravimetry-mass spectrometry and Fourier transform infrared emission spectroscopy. The gel-like films prepared from aqueous solutions of the precursor salts Sn(OH)₂(CH₃COO)_2−xCl_x and Ru(OH)Cl₃ on titanium metal support were heated in an atmosphere containing 20% O₂ and 80% Ar up to 873 K.Chlorine evolution takes place in a single stage process between 573 and 773 K, while the decomposition of organic species like various types of carbonyls, carbonates and carboxylates occurs in two main stages between 423 and 773 K. The combustion temperature of the organic species formed decreases with the increase of the ruthenium content, indicating the catalytic effect of the noble metal. The secondary processes can significantly influence the morphology and electrochemical properties of the films when used as anodes in electrochemical processes.     

Monitoring particle adsorption by use of laser reflectometry near the critical angle

We investigate the use of laser reflectometry near the critical angle to monitor particle adsorption onto a flat glass surface. Experimental results show that positive particles are adsorbed onto the glass surface and that their adsorption kinetics depend strongly on the volume fraction occupied by the particles in suspension but not appreciably on the particle size. The reflectance near the critical angle is dominated by the particles on the surface, with the contribution of the particles in suspension being very low. We compare the reflectance change near the critical angle with the change in reflectance near the Brewster angle when particles are adsorbed onto the glass surface. We find that reflectometry near the critical angle is 3000 times more sensitive than it is near the Brewster angle. Some optical images are presented to validate our results.     

Time estimation during prolonged sleep deprivation and its relation to activation measures

This is the first study to analyze variations in time estimation during 60 h of sleep deprivation and the relation between time estimation performance and the activation measures of skin resistance level, body temperature, and Stanford Sleepiness Scale (SSS) scores. Among 30 healthy participants 18 to 24 years of age, for a 10-s interval using the production method, we found a lengthening in time estimations that was modulated by circadian oscillations. No differences in gender were found in the time estimation task during sleep deprivation. The variations in time estimation correlated significantly with body temperature, skin resistance level, and SSS throughout the sleep deprivation period. When body temperature is elevated, indicating a high level of activation, the interval tends to be underestimated, and vice versa. When the skin resistance level or SSS is elevated (low activation), time estimation is lengthened, and vice versa. This lengthening is important because many everyday situations involve duration estimation under moderate to severe sleep loss. Actual or potential applications of this research include transportation systems, emergency response work, sporting activities, and industrial settings in which accuracy in anticipation or coincidence timing is important for safety or efficiency.     

Evolution of the thymus size in response to physiological and random events throughout life

During embryogenesis and in the early stages of life, the thymus is a crucial organ for the generation of the T cell repertoire. T cells are generated from hematopoietic stem cells already differentiated to precursor T cells in the bone marrow. These cells enter the thymus guided by chemotactic factors secreted by this organ. The complex maturation process takes place that ensures self-tolerance and homeostasis. Thymocytes that show autoreactivity do not leave the thymus, but rather die by apoptosis. The final percentage of mature T cells that survive to migrate from the thymus to the periphery is very low: at most 5%, under optimal conditions. The highest migration occurs in childhood and adulthood, at least in mice and humans; however, it declines throughout life and is minimal in the elderly. Under normal circumstances, the thymus commences involution soon after birth, and this involution correlates with the capacity to export mature T cells to the periphery. Hormones, cytokines, and neurotransmitters all play a role in this age-associated process, but the reasons for and mechanisms of this involution remain unknown. Apart from physiological conditions that change throughout life and govern age-related thymus evolution, random states and events provoked by intrinsic or extrinsic factors can induce either thymus involution, as in reversible transient thymic hypoplasias, or thymic hyperplasias. The age-associated involution, unlike transient involutions, follows a regular pattern for all individuals, though there are clear differences between the sexes. Nevertheless, even the age-associated involution seems to be reversible, raising the possibility of therapeutic strategies aimed at enhancing thymus function in the elderly.     

A COMPLEX CASE-BASED ADVISOR

The complexity of current organization systems, and the increase in the importance of the realization of internal controls in firms, make it necessary to construct models that automate and facilitate the work of auditors. A tool for the decision support process has been developed. The objective of the system is to facilitate the process of internal auditing in small and medium-sized enterprises. The system analyzes the data that characterizes each one of the activities carried out by the firm, then determines the state of each activity, calculates the associated risk, detects the erroneous processes, and generates recommendations to improve these processes. The developed model is composed of two case-based reasoning systems. One is used to identify the activities that may be improved and the other to determine how the activities could be improved. Each of the two subsystems use a different problem-solving method in each of the steps of the reasoning cycle. The system has been tested in 22 small and medium-sized companies in the textile sector, located in the northwest of Spain during the last 38 months and the obtained results are very encouraging.     

A Variational Approach to Video Registration with Subspace Constraints

This paper addresses the problem of non-rigid video registration, or the computation of optical flow from a reference frame to each of the subsequent images in a sequence, when the camera views deformable objects. We exploit the high correlation between 2D trajectories of different points on the same non-rigid surface by assuming that the displacement of any point throughout the sequence can be expressed in a compact way as a linear combination of a low-rank motion basis. This subspace constraint effectively acts as a trajectory regularization term leading to temporally consistent optical flow. We formulate it as a robust soft constraint within a variational framework by penalizing flow fields that lie outside the low-rank manifold. The resulting energy functional can be decoupled into the optimization of the brightness constancy and spatial regularization terms, leading to an efficient optimization scheme. Additionally, we propose a novel optimization scheme for the case of vector valued images, based on the dualization of the data term. This allows us to extend our approach to deal with colour images which results in significant improvements on the registration results. Finally, we provide a new benchmark dataset, based on motion capture data of a flag waving in the wind, with dense ground truth optical flow for evaluation of multi-frame optical flow algorithms for non-rigid surfaces. Our experiments show that our proposed approach outperforms state of the art optical flow and dense non-rigid registration algorithms.     

Detecting malicious tweets in trending topics using a statistical analysis of language

Twitter spam detection is a recent area of research in which most previous works had focused on the identification of malicious user accounts and honeypot-based approaches. However, in this paper we present a methodology based on two new aspects: the detection of spam tweets in isolation and without previous information of the user; and the application of a statistical analysis of language to detect spam in trending topics. Trending topics capture the emerging Internet trends and topics of discussion that are in everybody’s lips. This growing microblogging phenomenon therefore allows spammers to disseminate malicious tweets quickly and massively. In this paper we present the first work that tries to detect spam tweets in real time using language as the primary tool. We first collected and labeled a large dataset with 34 K trending topics and 20 million tweets. Then, we have proposed a reduced set of features hardly manipulated by spammers. In addition, we have developed a machine learning system with some orthogonal features that can be combined with other sets of features with the aim of analyzing emergent characteristics of spam in social networks. We have also conducted an extensive evaluation process that has allowed us to show how our system is able to obtain an F-measure at the same level as the best state-of-the-art systems based on the detection of spam accounts. Thus, our system can be applied to Twitter spam detection in trending topics in real time due mainly to the analysis of tweets instead of user accounts.