Capability of the rosemary (Rosmarinus officinalis) extract on the oxidative stability of cooked sea bream (Sparus aurata) during frozen storage

The effects of rosemary extract addition on oxidative stability of cooked sea bream during frozen storage period were investigated. Sea bream fillets were fried, oven baked and grilled. Three groups with rosemary extract were also cooked by the same methods and cooked samples (with and without rosemary extract) were stored in ?18?°C for 4?months. After cooking procedures, the FFA formation was quite similar in fresh-raw and fried sea bream fillets, but significantly increased oven baked (0.31?C0.33% oleic acid) and grilled fillets (0.39?C0.40% oleic acid). The highest value of PV was also obtained from grilled fillets (1.18?C1.58?meq/kg). However, TBA values (1.92?mg MA/kg for fresh-raw fillet) did not increase in sea bream fillets after the frying and grilling procedure except oven baking without rosemary extract (2.41?mg MA/kg). A considerable increase in the FFA, PV and TBA was observed in all cooked groups during frozen storage period. The treated samples with rosemary extract generally showed slower PV and TBA formation than those of the untreated samples. However, the additions of rosemary extract have positive effect on sensory quality of baked sea bream.     

Efficiency of Gold Nano Particles on the Autoxidized Soybean Oil Polymer: Fractionation and Structural Analysis

Polyunsaturated plant oils have gained great interest as monomers to produce biodegradable polymers obtained from renewable resources due to the limited existing sources of petroleum oil and environmental issues. Soybean oil was autoxidized by exposure to atomospheric oxygen at room temperature with or without the presence of gold nanoparticles (Au NPs) 5–41 days. When the autoxidation process was catalyzed with Au NPs, the molecular weight of the oxidized oil was increased in 5 days. In contrast to this, without Au NPs, the oxidized oil was still a fluidized liquid. Autoxidized soybean oil polymer in toluene solution with gold NP showed a surface plasmon resonance at λ_max = 540 nm in a UV–VIS spectrometer and a fluorescence emission spectrum at λ_max = 450 nm, when it was irradiated at λ_max = 390 nm. The higher molecular weight of the polymeric oils was successively fractionated by the extraction from the solvent‐non‐solvent mixture CHCl₃/petroleum ether with the volume ratio of 5:15. Three polymeric oils fractions with different molecular weight (ca 1000, 4000, and 40,000 g/mol) were obtained. GC–MS analysis, ¹H‐NMR and GPC techniques were used in the structural analysis of the fractionated polymeric oils.     

Flashing point compressibility of geothermal fluids with low CO2 content and its use in estimating reservoir volume

In this study, the bubble point pressure effect or, as it is more commonly known, the flashing point effect of CO₂ on geothermal fluids is shown, and the compressibility of the geothermal fluids containing low concentrations of dissolved CO₂ at the flashing point is formulated for isoenthalpic phase change. The compressibility, termed the isoenthalpic flashing point compressibility, can be calculated with well-known parameters. New, easy-to-use graphs are presented to estimate the compressibility for such systems. Correction for ionic strength of the geothermal brine is also considered. The practical use of the compressibility is illustrated to estimate the fluid content of a geothermal reservoir. A material balance method incorporating the isoenthalpic flashing point compressibility in geothermal modeling is investigated. The material balance method presented in the paper is of primary importance in the evaluation of geothermal reservoirs since both the areal extent and the vertical thickness can not be accurately determined, particularly in the initial development stages of the reservoirs. Applications of the method to geothermal fields are discussed.     

High-Performance Liquid Chromatography Analysis and Assessment of Benzoic Acid in Yogurt, Ayran, and Cheese in Turkey

Among food sources, particular attention is paid to milk and dairy products, due to its nutritional importance. Benzoic acid is extensively used in the preservation of foods. A reliable method for the determination of benzoic acid in some dairy products, such as yogurt, ayran, and cheese using high-performance liquid chromatography and UV detection was validated. The peak of benzoic acid was measured at a wavelenght of 226 nm. Samples were purchased from supermarkets in Turkey in the period 2009–2010. All dairy product samples were produced from cow’s milk. The levels of benzoic acid in cheese, yogurt, and ayran samples were in the range of 3.17 to 56.77 mg kg⁻¹, 8.94 to 28.30 mg kg⁻¹, and 1.54 to 16.57 mg L⁻¹, respectively. The results show that benzoic acid widely occurs in milk products in Turkey at the low levels.     

Communication Scheduling and Remote Estimation With Adversarial Intervention

We study a communication scheduling and remote estimation problem within a worst-case scenario that involves a strategic adversary. Specially, a remote sensing system consisting of a sensor, an encoder and a decoder is configured to observe, transmit, and recover a discrete time stochastic process. At each time step, the sensor makes an observation on the state variable of the stochastic process. The sensor is constrained by the number of transmissions over the time horizon, and thus it needs to decide whether to transmit its observation or not after making each measurement. If the sensor decides to transmit, it sends the observation to the encoder, who then encodes and transmits the observation to the decoder. Otherwise, the sensor and the encoder maintain silence. The decoder is required to generate a real-time estimate on the state variable. The sensor, the encoder, and the decoder collaborate to minimize the sum of the communication cost for the sensor, the encoding cost for the encoder, and the estimation error for the decoder. There is also a jammer interfering with the communication between the encoder and the decoder, by injecting an additive channel noise to the communication channel. The jammer is charged for the jamming power and is rewarded for the estimation error generated by the decoder, and it aims to minimize its net cost. We consider a feedback Stackelberg game with the sensor, the encoder, and the decoder as the composite leader, and the jammer as the follower. Under some technical assumptions, we obtain a feedback Stackelberg solution, which is threshold based for the scheduler, and piecewise affine for the encoder and the decoder. We also generate numerical results to demonstrate the performance of the remote sensing system under the feedback Stackelberg solution.      

Multi-machine earliness and tardiness scheduling problem: an interconnected neural network approach

This paper addresses the problem of scheduling a set of independent jobs with sequence-dependent setups and distinct due dates on non-uniform multi-machines to minimize the total weighted earliness and tardiness, and explores the use of artificial neural networks as a valid alternative to the traditional scheduling approaches. The objective is to propose a dynamical gradient neural network, which employs a penalty function approach with time varying coefficients for the solution of the problem which is known to be NP-hard. After the appropriate energy function was constructed, the dynamics are defined by steepest gradient descent on the energy function. The proposed neural network system is composed of two maximum neural networks, three piecewise linear and one log-sigmoid network all of which interact with each other. The motivation for using maximum networks is to reduce the network complexity and to obtain a simplified energy function. To overcome the tradeoff problem encountered in using the penalty function approach, a time varying penalty coefficient methodology is proposed to be used during simulation experiments. Simulation results of the proposed approach on a scheduling problem indicate that the proposed coupled network yields an optimal solution which makes it attractive for applications of larger sized problems.     

An investigation on renewable energy education at the university level in Turkey

In the present study, to discover how teaching of renewable energy sources in Turkey is carried out at the university level, a questionnaire was developed and applied at different universities in Turkey. The analyses conducted on the data obtained from the questionnaire revealed that education about geothermal, solar and wind energy is given at master’s level, other renewable energy sources are taught at the undergraduate level within the curriculum of some engineering courses. The teaching performed about renewable energy sources is in Turkish and at encyclopedic level. As preparing and obtaining the required materials are costly, some problems are encountered in the teaching of renewable sources. In Turkish universities, no degree about renewable energy sources is granted. Hence, the country must make use of the people having engineering degree to capitalize on its renewable energy sources. As there is no program specializing on providing training about the renewable energy sources, it seems to be difficult to find experts about this issue. The current state of renewable energy sources education seems to be inadequate and it should be expanded and strengthened.     

Electrochemical treatment of deproteinated whey wastewater and optimization of treatment conditions with response surface methodology

Electrochemical treatment of deproteinated whey wastewater produced during cheese manufacture was studied as an alternative treatment method for the first time in literature. Through the preliminary batch runs, appropriate electrode material was determined as iron due to high removal efficiency of chemical oxygen demand (COD), and turbidity. The electrochemical treatment conditions were optimized through response surface methodology (RSM), where applied voltage was kept in the range, electrolyte concentration was minimized, waste concentration and COD removal percent were maximized at 25 degrees C. Optimum conditions at 25 degrees C were estimated through RSM as 11.29 V applied voltage, 100% waste concentration (containing 40 g/L lactose) and 19.87 g/L electrolyte concentration to achieve 29.27% COD removal. However, highest COD removal through the set of runs was found as 53.32% within 8h. These results reveal the applicability of electrochemical treatment to the deproteinated whey wastewater as an alternative advanced wastewater treatment method.