Effect of fortification with asparagus powder on the qualitative properties of processed cheese

The qualitative properties of processed cheese (PC) fortified with different levels of asparagus powder (AP) (0.5%, 1% and 1.5% wt/wt) were evaluated during storage. AP decreased the pH and lipolysis indexes and increased the phenolic content, antioxidant activity and proteolysis of the processed cheeses. AP made the structure of the cheese more elastic, increased the rigidity and decreased the spreadability compared with the control sample, which corresponded to the results obtained using dynamic oscillatory rheometry. The results showed that AP as a rich source of bioactive components could be used for the fortification of processed cheeses.     

A comparative study of two approaches for supporting optimal network location queries

Given a set S of sites and a set O of weighted objects, an optimal location query finds the location(s) where introducing a new site maximizes the total weight of the objects that are closer to the new site than to any other site. With such a query, for instance, a franchise corporation (e.g., McDonald’s) can find a location to open a new store such that the number of potential store customers (i.e., people living close to the store) is maximized. Optimal location queries are computationally complex to compute and require efficient solutions that scale with large datasets. Previously, two specific approaches have been proposed for efficient computation of optimal location queries. However, they both assume p-norm distance (namely, L₁ and L₂/Euclidean); hence, they are not applicable where sites and objects are located on spatial networks. In this article, we focus on optimal network location (ONL) queries, i.e., optimal location queries in which objects and sites reside on a spatial network. We introduce two complementary approaches, namely EONL (short for Expansion-based ONL) and BONL (short for Bound-based ONL), which enable efficient computation of ONL queries with datasets of uniform and skewed distributions, respectively. Moreover, with an extensive experimental study we verify and compare the efficiency of our proposed approaches with real world datasets, and we demonstrate the importance of considering network distance (rather than p-norm distance) with ONL queries.     

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.     

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.     

An Approach to Synthesize Thick α- and γ-Al2O3 Coatings by High-Speed Physical Vapor Deposition

Crystalline α- and γ-Al₂O₃ exhibit in many applications high wear resistance, chemical resistance, and hot hardness, making them interesting materials for production engineering. To synthesize α-Al₂O₃ with high coating thickness of s ≥ 10 μm, chemical vapor deposition at temperatures T > 1000 °C is well established. However, there are almost no studies dealing with the synthesis of thick α-Al₂O₃ by physical vapor deposition (PVD) at high temperatures T > 700 °C. High-temperature deposition of thick coatings can be realized by means of the dense hollow cathode plasma, combined with the transport function of the plasma gas in high-speed (HS) PVD. Herein, crystalline α- and γ-Al₂O₃ films are deposited on cemented carbides at substrate temperatures T _s ≈ 570 °C and T _s ≈ 780 °C by HS-PVD. These coatings exhibit a thickness up to s = 20 μm. Moreover, phase analysis presents α-phases in coatings synthesized at substrate temperature of T _s ≈ 780 °C with significant higher hardness than films by T _s ≈ 570 °C. These release the potential of HS-PVD to synthesize α-Al₂O₃ coatings with high thickness. Thereby, a higher thickness of these coatings is beneficial for the wear protection of turning and die casting tools.     

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.     

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.     

Preparation and study of a thermo-responsive membrane using binary liquid crystal mixtures of cholesteryl cetyl ether and cholesteryl oleyl carbonate

A facile method for the synthesis of thermotropic liquid crystalline cholesteryl cetyl ether (CCE) was carried out from cholesterol and cetyl alcohol using montmorillonite K-10 as an acid catalyst. The aim of this study was to investigate the use of liquid crystalline blends of CCE and cholesteryl oleyl carbonate (COC) with appropriate crystal to smectic phase temperature (T _c?Cs) just above body temperature as a temperature-modulated drug permeation system. Using 30/70?mol ratio of COC/CCE, a mixture of desirable phase transition temperature was obtained. The phase transition behavior of COC/CCE binary liquid crystalline mixture was established by differential scanning calorimetry and polarizing optical microsopy. The COC/CCE-embedded cellulose nitrate membrane was used by an in vitro drug penetration studies. Paracetamol and mesalazine were chosen as hydrophobic and hydrophilic drug models, respectively. Paracetamol permeability through the membrane was higher at temperatures above the phase transition of liquid crystal (LC) blends (39?°C) than its permeability below the phase transition temperature of liquid crystal blends (30?°C). The drug penetration through LC-embedded cellulose membrane was influenced by the pore size of the membrane and therefore the adsorbed amount of LC. There was no penetration of mesalazine through that membrane presumably, due to the differences in hydrophilicity of LC-embedded membrane and permeated drug.     

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...     

Fabrication and characterization of highly efficient three component CuBTC/graphene oxide/PSF membrane for gas separation application

Metal organic frameworks (MOFs) with marvelous properties have aroused enormous attention for different application especially gas adsorption and separation. In this regard, fabrication of MOF hybrids with carbon based materials is new strategy to upgrade MOF performance. In this study CuBTC (Copper benzene-1,3,5-tricarboxylic acid)/graphene oxide (GO) composite was synthesized and characterized by BET, SEM, TGA, XRD and FT-IR techniques. Then CuBTC and CuBTC/GO composite were incorporated into polysulfone (PSF) polymer to construct mixed matrix membranes (MMMs). The obtained membranes were characterized by SEM, TGA, XRD and tensile tests and their gas permeability was measured. The results were compared to those of CuBTC/PSF MMMs. It was revealed that CuBTC/GO composite as filler showed superior performance relative to CuBTC. For instance, 15 wt% loading of CuBTC/GO in PSF represented outstanding gas separation behavior while the same loading of CuBTC in PSF deteriorated performance of MMM. Well particle dispersion and favorable polymer-filler interaction were responsible for such observed difference. A high H₂/CH₄ and H₂/N₂ selectivity of 80.03 and 70.46 were recorded for CuBTC/GO in PSF (15 wt%) compared to 44.56 and 40.92 for CuBTC in PSF (15 wt%).