Characterization of liver oils from three species of sharks collected in Tunisian coasts: In vitro digestibility by pancreatic lipase

The increase in world fish lipid request has made necessary the search for new fish species rich in polyunsaturated fatty acid (PUFA) that could be used as raw material for oil production. In this study, liver oils from the deep‐sea sharks Mustelus mustelus, Squalus acanthias, and Rhinobatos cemiculus were extracted and analyzed to describe their lipids characteristics. Lipid contents of shark livers ranged from 64.245 to 69.57%. Among minerals, potassium and sodium were the most abundant while unsaturated fatty acids (FAs) were dominant exceeding 55% of the total FAs. Omega‐3 PUFA (ω‐3 PUFA) profiles exhibited a dominance of eicosapentaenoic acid and docosahexaenoic acid. This study suggests that shark livers, actually considered as waste, may be an attractive source of ω‐3 PUFAs and a good source of carotenoids and phenolic compounds.

Practical applications

The production of EPA and DHA concentrates from residual sources of marine oils has unexplored potential of use in food industry and oil‐based nutraceutical production for obtaining health benefits can be achieved. The economic activities of fish residues can reduce inappropriate excessive fishing, reducing imports of fish oils while contributing to the ecosystem balance.     

FIVE-SPOT INJECTION/PRODUCTION WELL LOCATION DESIGN BASED ON FRACTURE GEOMETRICAL CHARACTERISTICS IN HEAVY OIL FRACTURED RESERVOIRS DURING MISCIBLE DISPLACEMENT: AN EXPERIMENTAL APPROACH

Mapping fracture characteristics by using seismic acquisition and processing is important not only to identify sweet spots, but also to optimize production, especially for unconventional heavy oil reservoirs. In this experimental work we used five-spot micromodels initially saturated with heavy oil to find the optimum well locations during first-contact miscible displacement. The experiments were performed at a fixed injection rate on fractured micromodels with various patterns. The optimum location for injection/production wells was found in the pattern where fractures make an angle of 45° with the mean flow direction. Moreover, oil recovery was increased with the density, length, level of scattering, and discontinuity of fractures. The analysis of the experimentally measured recovery curve revealed that there are three distinct stages for each displacement. The efficiency of the first stage was found to be dominated by dispersion and diffusion. However, the recovery of the second stage was significantly affected by the fracture orientation. The displacement efficiency of the third stage was controlled by solvent dispersion, which is at maximum for the pattern with higher density, length, scattering, and discontinuity of fractures. Saturation monitoring showed that the fracture geometrical characteristics strongly affected the splitting, spreading, and shielding of the produced fingers and solvent front shape and consequently affected the recovery factor. As a result, five-spot micromodels can be used to investigate the optimum location of injection/production wells during miscible displacements in fractured heavy oil reservoirs.     

Application of adaptive strategy for supply chain agent

Information Systems and e-Business Management - With the tremendous increase in the globalization of trade the corresponding supply chains supporting the manufacture, distribution and supply of...     

Aflatoxins: Occurrence in red chilli and control by gamma irradiation

Chilli is one of the valuable spices commercialised globally, added as condiments in various cuisines and is easily susceptible to aflatoxin contamination (produced mainly by Aspergillus flavus) during pre- and post-harvesting stages. The important factors such as temperature, moisture content and humidity affect the growth of fungi producing aflatoxins. Chillies contaminated with aflatoxins could be carcinogenic and thus can pose a threat to the general population leading to the loss of international trade market. Therefore, to overcome this problem, there is a need for some effective and novel technologies such as gamma irradiation. Gamma irradiation minimises the toxicological effects of aflatoxins by inhibiting the growth as well as the proliferation of Aspergillus species. In this work, the natural occurrence of aflatoxins including the contribution of gamma irradiation on either eliminating or controlling the aflatoxins in red chilli is reviewed.     

Accuracy assessment and trend analysis of MODIS-derived data on snow-covered areas in the Sutlej basin,Western Himalayas

Snow is important for hydrological studies and is a variable very sensitive to climatic variations. In the present study, the variability of snow-covered areas (SCAs) obtained through Moderate Resolution Imaging Spectroradiometer (MODIS) snow data products was analysed using the Mann–Kendall test and Sen’s slope estimator in the Sutlej basin, Western Himalayas, India. However, due to the limitations of long time-series snow cover data, the study has been carried out for a time period from 2000 to 2009. Before trend analysis, the estimated SCA was validated using the ground-based snowfall data. A simple linear regression test was applied to analyse the relationship between the variation in SCA and snowfall. The relationship between the mean annual snowfall and SCA indicated a highly significant correlation (R² = 0.95). In order to have a better insight into the relationship, the regression test was also carried out for six elevation zones. The coefficient of determination (R²) varied from 0.78 at the 1500–2000 m asl zone to 0.96 at the 3000–3500 m asl zone. The trend analysis indicated reduction in SCA with significant negative behaviour for annual, winter, and post-monsoon seasons and for November and December months. The negative trend was observed for an elevation of <2500 m asl in the basin. Moreover, during the same period (2000–2009), the temperature (T_max and T_min) increased while there was a decrease in snowfall. The trend analysis of temperature from 1984 to 2009 revealed positive trends with significant trend in T_min as determined by using the Mann–Kendall statistical test. The reduction in SCA was, therefore, attributed to the increasing trends in temperature, particularly T_min, associated with reduction in snowfall. These SCA variations have significant implications for water resources managers in the area as some of these observed trends, if continue, may result in changes in hydrological/ecological balance of the Sutlej basin.     

Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To address SDN’s current and future challenges, there is a need to know how artificial intelligence (AI) optimization techniques can efficiently balance the load. This study aims to explore two artificial intelligence optimization techniques, namely Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO), used for load balancing in SDN. Further, we identified that a modification to the existing optimization technique could improve the performance by using a reliable link and node to form the path to reach the target node and improve load balancing. Finally, we propose a conceptual framework for SDN futurology by evaluating node and link reliability, which can balance the load efficiently and improve QoS in SDN.     

N4SID and MOESP algorithms to highlight the ill-conditioning into subspace identification

In this paper,an analysis for ill conditioning problem in subspace identifcation method is provided.The subspace identifcation technique presents a satisfactory robustness in the parameter estimation of process model which performs control.As a frst step,the main geometric and mathematical tools used in subspace identifcation are briefly presented.In the second step,the problem of analyzing ill-conditioning matrices in the subspace identifcation method is considered.To illustrate this situation,a simulation study of an example is introduced to show the ill-conditioning in subspace identifcation.Algorithms numerical subspace state space system identifcation(N4SID)and multivariable output error state space model identifcation(MOESP)are considered to study,the parameters estimation while using the induction motor model,in simulation(Matlab environment).Finally,we show the inadequacy of the oblique projection and validate the efectiveness of the orthogonal projection approach which is needed in ill-conditioning;a real application dealing with induction motor parameters estimation has been experimented.The obtained results proved that the algorithm based on orthogonal projection MOESP,overcomes the situation of ill-conditioning in the Hankel s block,and thereby improving the estimation of parameters.     

Low-Complexity Selected Mapping Scheme Using a Bank of Butterfly Circuits in Orthogonal Frequency Division Multiplexing Systems

Selected mapping schemes (SLMs) have gained popularity to improve the peak-to-average power ratio (PAPR) reduction performance. Even so, the computational load increases greatly owing to the many inverse fast Fourier transforms (IFFTs) in conventional SLM (CSLM) and to overcome this disadvantage, several low-complexity schemes are in vogue. This paper proposes two \(\frac{N}{2}\)-point IFFTs, where N is the number of subcarriers in OFDM, and a bank of butterfly circuits (BFCs) to replace multiple IFFTs in the CSLM. The output sequence of the two \(\frac{N}{2}\)-point IFFTs are simultaneously sent to a bank of M-BFCs to generate a set of M statistically independent candidate signals, including the original OFDM signal. The parameters of the first BFC, which generates the original OFDM signal, are derived. To simplify the complexity, constraints are imposed on the selection of parameters of the remaining M ? 1 BFCs. The results indicate that the proposed SLM (PSLM), when compared with the CSLM, achieves an appreciable computational complexity reduction gain with the loss of a slight PAPR reduction performance.     

Modeling of Compositional Grading and Plus Fraction Properties Changes with Depth in Petroleum Reservoirs

Abstract

In this work we use a nonisothermal model to predict compositional variation in a petroleum fluid column; at the same time, a nonisothermal model will be used to predict change of plus fraction molecular weight (and as a result all other its properties) with depth. We will investigate the effect of several factors as mode of characterization, binary interaction coefficients, volume shifts, and near-criticality on the change of physical properties, including bubble point pressure, solution gas–oil ratio, and oil formation volume factor. A computer program will be used to predict the location of the gas–oil contact and we will show how neglecting compositional grading (CG) can lead to serious errors in the calculated initial oil in place.     

Influence of geological setting of islands and significance of reefs for tsunami wave impact on the Atoll Islands, Maldives

This paper discusses the influence of the geological setting of islands and reefs in the Maldives on the impact of the 26 December 2004 Indian Ocean Tsunami. Geological and geomorphological data (including orientation, location, size, ellipticity, reef-island distance, proportion of reef area to island area) were collected for completely flooded and <25% flooded islands. The results show that although the different parameters may interact to reduce or magnify the impact, the reef-island distance is the most important factor. The critical minimum distance between the reef and the island shoreline required for the wave to set up is estimated as 89 m on the eastern and 140 m on the western sides of the island, respectively. Circular islands with short reef-island distance and small percent of reef area seem to be safer in the context of tsunami. The result of this study can be applied to identify islands that are naturally protected/resilient against natural disasters such as tsunami and those where the hazard is greatest.