Chemical composition and nutritional quality of tehineh (sesame butter)

The chemical composition and nutritional quality of tehineh, a paste of dehulled roasted sesame seeds, from Saudi Arabia and other countries, were studied. Results showed 24.7% protein, 58.9% fat, 2.3% fiber, 3.0% ash and <1.0% moisture. The tehineh contained relatively high amounts (mg/100 g) of P (692), Mg (362), Fe (7.19), Cu (1.96), Mn (1.46) and Zn (7.82) and low amounts of Ca (61) and Se (0.05). Gas-liquid chromatography (GLC) analysis of the oil revealed percentages of 42.4 for oleic, 39.7 for linoleic, 9.8 for palmitic and 6.4 for stearic acid. Lysine was the only limiting amino acid with a chemical score of 64, while the sulphur-containing amino acids (methionine + cystine) and tryptophan were present in amounts exceeding the requirement of the FAO/WHO (1973) reference protein. The in vitro protein digestibility (IVPD) value of 83.3% and the calculated protein efficiency ratio (C-PER), 2.14, were slightly higher than those of sesame seeds and both values were lower than the IVPD and C-PER of 90.0% and 2.50, respectively, for ANRC casein.     

Nitrogen management in reservoir catchments through constructed wetland systems.

In this study, nitrogen removal was investigated in pilot-scale subsurface flow (SSF) and in free water surface flow (FWS) constructed wetlands installed in the campus of TUBITAK-Marmara Research Center, Gebze, near Istanbul, Turkey. The main purposes of this study are to apply constructed wetlands for the protection of water reservoirs and to reuse wastewater. Experiments were carried out at continuous flow reactors. The effects of the type of plants on the removal were investigated by using emergent (Canna, Cyperus, Typhia spp., Phragmites spp., Juncus, Poaceae, Paspalum and Iris.), submerged (Elodea, Egeria) and floating (Pistia, Salvina and Lemna) marsh plants at different conditions. During the study period HLRs were 30, 50, 70, 80 and 120 L m(2)d(-1) respectively. The average annual NH4-N, NO(3)-N, organic N and TN treatment efficiencies in SSF and FWS wetlands are 81% and 68%, 37% and 49%, 75% and 68%, 47% and 53%, respectively. Nitrification, denitrification and ammonification rate constant (k20) values in SSF and FNS systems have been found as 0.898 d(-1) and 0.541 d(-1), 0.488 d(-1) and 0.502 d(-1), 0.986 d(-1) and 0.908 respectively. Two types of the models (first-order plug flow and multiple regression) were tried to estimate the system performances.     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

Bioprinting a cell-laden matrix for bone regeneration: A focused review

Although many efforts have been made to regenerate the bone lesions, existing challenges can be mitigated through the development of tissue engineering scaffolds. However, the weak control on the microstructure of constructs, limitation in preparation of patient-specific and multilayered scaffolds, restriction in the fabrication of cell-laden matrixes, and challenges in preserving the drug/growth factors' efficacy in conventional methods have led to the development of bioprinting technology for regeneration of bone defects. So in this review, conventional 3D printers are classified, then the priority of the different types of bioprinting technologies for the preparation of the cell/growth factor-laden matrixes are focused. Besides, the bio-ink compositions, including polymeric/hybrid hydrogels and cell-based bio-inks are classified according to fundamental and recent studies. Herein, different effective parameters, such as viscosity, rheological properties, cross-linking methods, biodegradation biocompatibility, are considered. Finally, different types of cells and growth factors that can encapsulate in the bio-inks to promote bone repair are discussed, and both in vitro and in vivo achievement are considered. This review provides current and future perspectives of cell-laden bioprinting technologies. The restrictions and challenges are identified, and proper strategies for the development of cell-laden matrixes and high-performance printable bio-inks are proposed.     

A cross-layer approach for partition detection at overlay layer for structured P2P in MANETs

Due to limited radio range and mobility of nodes in mobile ad hoc networks (MANETs), the network partitioning and merging could occur frequently. When structured peer-to-peer (P2P) overlays are running over MANETs, then network partition in the physical network can also cause network partition at the overlay layer. Existing approaches for structured P2P overlay over MANETs do not detect network partition at the overlay layer. This paper proposes a cross-layer approach to detect network partition at the overlay layer for structured P2P overlay over MANETs. Simulation results show that the proposed approach is highly effective and efficient in terms of routing overhead, success ratio and false-negative ratio.     

AN INTERACTIVE SEARCH ASSISTANT ARCHITECTURE BASED ON INTRINSIC QUERY STREAM CHARACTERISTICS

Search engine query log mining has evolved over time to more like data stream mining due to the endless and continuous sequence of queries known as query stream. In this paper, we propose an online frequent sequence discovery (OFSD) algorithm to extract frequent phrases from within query streams, based on a new frequency rate metric, which is suitable for query stream mining. OFSD is an online, single pass, and real-time frequent sequence miner appropriate for data streams. The frequent phrases extracted by the OFSD algorithm are used to guide novice Web search engine users to complete their search queries more efficiently. YourEye, our online phrase recommender is then introduced. The advantages of YourEye compared with Google Suggest, a service powered by Google for phrase suggestion, is also described. Various characteristics of two specific Web search engine query logs are analyzed and then the query logs are used to evaluate YourEye. The experimental results confirm the significant benefit of monitoring frequent phrases within the queries instead of the whole queries because none-separable items. The number of the monitored elements substantially decreases, which results in smaller memory consumption as well as better performance. Re-ranking the retrieved pages based on past users clicks for each frequent phrase extracted by OFSD is also introduced. The preliminary results show the advantages of the proposed method compared to the similar work reported in Smyth et al.     

UML-CI: A reference model for profiling critical infrastructure systems

The study of critical infrastructure systems organization and behavior has drawn great attention in the recent years. This is in part due to their great influence on the ordinary life of every citizen. In this paper, we study critical infrastructures’ characteristics and propose a reference model based on the Unified Modeling Language (UML). This reference model attempts to provide suitable means for the task of modeling an infrastructure system through offering five major metamodels. We introduce each of these metamodels and explain how it is possible to integrate them into a unique representation to characterize various aspects of an infrastructure system. Based on the metamodels of UML-CI, infrastructure system knowledge bases can be built to aid the process of infrastructure system modeling, profiling, and management.     

On-line neuro-expert monitoring system for Borssele Nuclear Power Plant

A new method for an on-line monitoring system for the nuclear power plants has been developed utilizing the neural networks and the expert system. The integration of them is expected to enhance a substantial potential of the functionality as operators support.

The recurrent neural network and the feed-forward neural network with adaptive learning are selected for the plant modeling and anomaly detection because of the high capability of modeling for dynamic behavior. The expert system is used as a decision agent, which works on the information space of both the neural networks and the human operators. The information of other sensory signals is also fed to the expert system, together with the outputs that the neural networks generate from the measured plant signals. The expert system can treat almost all known correlation between plant status patterns and operation modes as a priori set of rules.

From the off-line test at Borssele Nuclear Power Plant (PWR 480 MWe) in the Netherlands, it was shown that the neuro-expert system successfully monitored the plant status. The expert system worked satisfactorily in diagnosing the system status by using the outputs of the neural networks and a priori knowledge base from the PWR simulator. The electric power coefficient is simultaneously monitored from the measured reactive and active electric power signals.     

Nano levels detection of beryllium by a novel beryllium PVC-based membrane sensor based on 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy

A novel poly(vinyl chloride)-based 2,3,5,6,8,9-hexahydro-1,4,7,10-benzotetra oxacyclododecine-12-carbaldehyde-12-(2,4-dinitrophenyl)hy (PBC) with sodium tetraphenyl borate (NaTPB) as an anion excluder, benzyl acetate (BA), acetophenon (AP) and o-nitrophenyloctyl ether (NPOE) as plasticizing solvent mediators was prepared and investigated as a beryllium selective sensor. The best performance was observed with the membrane having the PVC–NaTPB–NPOE–PBC composition 30%:3%:62%:5%, which worked well over a very wide concentration range (1.0×10⁻⁷ M to 1.0×10⁻¹ M). The sensor exhibits a Nernstian slope of 29.9 mV per decade of Be²⁺ activity. The detection limit of the sensor is 7.0×10⁻⁸ M (630 ppt). The proposed electrode shows excellent discriminating ability toward Be²⁺ ion with regard to alkali, alkaline earth, transition and heavy metal ions. It was successfully applied to the determination of beryllium in a mineral sample.     

Cylindrical functionally graded shell model based on the first order shear deformation nonlocal strain gradient elasticity theory

Microsystem Technologies - In this article, a cylindrical functionally graded shell model is developed in the framework of nonlocal strain gradient theory for the first time. For this purpose, the...