Modelling of low temperature wine-making,using immobilized cells

A new biocatalyst was prepared by immobilization of Saccharomyces cerevisiae AXAZ-1 yeast cells on whole corn grains. This biocatalyst was used for 30 repeated batch fermentations of glucose and grape musts at various temperatures. The biocatalyst retained its operational stability for a long period and it proved able to produce dry wines of fine clarity, even at extremely low temperatures (5 °C). The produced wines were analyzed for volatile byproducts by GC and GC–MS. The results showed an increase in the number and amount of esters produced when immobilized cells were used. In addition, an increase in the percentages of esters and a decrease in those of alcohols with the decrease of fermentation temperature were observed. Finally a model, appropriate for describing sugar consumption and the simultaneous ethanol formation by immobilized cells, was proposed. The results of this model fit almost perfectly with the experimental data.     

Classifying RFID attacks and defenses

RFID (Radio Frequency Identification) systems are one of the most pervasive computing technologies with technical potential and profitable opportunities in a diverse area of applications. Among their advantages is included their low cost and their broad applicability. However, they also present a number of inherent vulnerabilities. This paper develops a structural methodology for risks that RFID networks face by developing a classification of RFID attacks, presenting their important features, and discussing possible countermeasures. The goal of the paper is to categorize the existing weaknesses of RFID communication so that a better understanding of RFID attacks can be achieved and subsequently more efficient and effective algorithms, techniques and procedures to combat these attacks may be developed.     

Assessing allergenicity of different tomato ecotypes by using pooled sera of allergic subjects: identification of the main allergens

An evaluation of the potential allergenicity of different tomato ecotypes is reported. Twelve tomato ecotypes were assessed through a proteomic approach, using pools of sera of allergic patients from two different regions (Emilia Romagna in Northern Italy and Campania in Southern Italy), in order to identify the major allergens and evaluate differences in IgE binding properties of the tomato cultivars. Pooled sera of allergic people from Emilia Romagna showed as the main allergen a suberization-associated anionic peroxidase, whereas pooled sera of allergic patients from Campania were mostly reactive to profilin. The two proteins were identified through a proteomic approach based on the use of high-resolution mass spectrometric techniques. Quite interestingly, in some cases, several ecotypes showed a less reactivity toward patients?? sera than other, potentially indicating the possibility to identify ipoallergenic varieties. Anyway, the allergenic pattern response to tomatoes was serum-specific, indicating that the allergenic properties of different tomato ecotypes are defined by the specific proteins to which the patient is sensitized, a strong indication that ipoallergenicity of the different ecotypes is possible, but mostly related to the individual susceptibility.     

A distributed task planning system for computer-integrated manufacturing systems

A formal mathematical framework for a distributed task planning method suitable for computerintegrated manufacturing systems is proposed. All pertinent algorithms are derived. A detailed timing analysis associated with primitive actions and activities (complex tasks) execution is presented. A formal language is designed for event tracking and error specification. Based on the derived language, an error recovery mechanism (automaton) is proposed. A case study demonstrates the applicability of the presented method with and without error occurrences.Dr Kokinaki is currently Science and Engineering Research Centre, De Montfort University, UK.     

Olive oil waste treatment: a comparative and critical presentation of methods, advantages & disadvantages

Since olive oil industries were considered responsible for a great amount of pollution there has been a strong need for optimization of olive oil waste treatment systems. The currently employed systems are numerous and fall in the following large categories; bioremediation (ex-situ, in-situ), thermal processes (incineration, pyrolysis, gasification), evaporation, membrance processes, electrolysis, ozonation, digestion, coagulation/flocculation/precipitation, and distillation. Both advantages and disadvantages in conjunction with respective methodology and explicit flow diagrams were presented per waste treatment method. Furthermore, most recent studies were reported and more than twenty-five figures showing mainly the effectiveness of the current waste treatment methods versus time or temperature were displayed. The comparative presentation of the various olive oil waste treatment methodologies showed that though bioremediation stands for the most enviromentally friendly technique, its required longer treatment time in conjuction with its weakness to deal with elemental contaminants makes imperative the employment of a second alternative technique which could either be a membrance process (low energy cost, reliability, reduced capital cost) or a coagulation/flocculation method because of its low cost and high effectiveness. Biogas production appears to be another promising and energy effective waste treatment method. On the other hand, methods like distillation and ozonation (high cost) and electrolysis (experimental level) are unlikely to dominate this field unless their high cost is substantially reduced in the near future.     

An insulin infusion advisory system based on autotuning nonlinear model-predictive control

This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.     

Customer engagement and performance in social media: a managerial perspective

Electronic Markets - The topic of customer engagement via social media is receiving increasing consideration in the literature. Previously, scholars’ use of the notion and dimensionality of...     

Salinity Stress Alters the Secondary Metabolic Profile of M. sativa,M. arborea and Their Hybrid (Alborea)

Increased soil salinity, and therefore accumulation of ions, is one of the major abiotic stresses of cultivated plants that negatively affect their growth and yield. Among Medicago species, only Medicago truncatula, which is a model plant, has been extensively studied, while research regarding salinity responses of two important forage legumes of Medicago sativa (M. sativa) and Medicago arborea (M. arborea) has been limited. In the present work, differences between M. arborea, M. sativa and their hybrid Alborea were studied regarding growth parameters and metabolomic responses. The entries were subjected to three different treatments: (1) no NaCl application (control plants), (2) continuous application of 100 mM NaCl (acute stress) and (3) gradual application of NaCl at concentrations of 50-75-150 mM by increasing NaCl concentration every 10 days. According to the results, M. arborea maintained steady growth in all three treatments and appeared to be more resistant to salinity. Furthermore, results clearly demonstrated that M. arborea presented a different metabolic profile from that of M. sativa and their hybrid. In general, it was found that under acute and gradual stress, M. sativa overexpressed saponins in the shoots while M. arborea overexpressed saponins in the roots, which is the part of the plant where most of the saponins are produced and overexpressed. Alborea did not perform well, as more metabolites were downregulated than upregulated when subjected to salinity stress. Finally, saponins and hydroxycinnamic acids were key players of increased salinity tolerance.     

Investigation on modeling parameters of concrete beams reinforced with basalt FRP bars

Fiber-reinforced polymer (FRP) bars are widely used as internal reinforcement replacing the conventional steel bars to prevent from corrosion. Among the different types of FRP bars, basalt FRP (BFRP) bars have been used in different structural applications and, herein, three already tested concrete beams reinforced with BFRP bars are analyzed using three-dimensional (3-D) finite element analysis (FEA). The beams were tested in four-point bending. In the FEA the behavior of concrete is simulated using the “Concrete-Damaged Plasticity” model offered in ABAQUS software. The research presented here presents a calibrated model for nonlinear FEA of BFRP concrete beams to predict their response considering both the accuracy and the computational efficiency. The calibration process showed that the concrete model should be regularized using a mesh-dependent characteristic length and material-dependent post-yield fracture and crushing energies to provide accurate mesh-size independent results. FEA results were compared to the test results with regard to failure load and crack patterns. Both the test results and the numerical results were compared to the design predictions of ACI 440.1R-15 and CSA S806-12, where CSA S806-12 seems to overestimate the shear strength for two beams.