钛沉积工艺制备TiN/cBN和TiC/金钢石涂层颗粒(英文)

用钛熔盐沉积及热处理工艺分别制备碳化钛涂覆的立方碳化硼颗粒(TiN/cBN)及碳化钛涂覆的金刚石颗粒(TiC/金刚石)。将cBN或金刚石颗粒分别与钛粉和KCl、NaCl和K2TiF6熔盐混合。将所得混合物在Ar气氛中加热至900°C,然后在H2气氛中于1000°C进行热处理。采用扫描电镜、X射线衍射和聚焦离子束技术对所制得颗粒进行表征。结果表明:cBN和金刚石颗粒表面已覆盖了纳米钛层。对Ti/cBN和TiC/金刚石涂层颗粒进行热处理后,颗粒表面沉积的Ti层与cBN和金刚石颗粒发生了原位化学反应,分别转化为钛化合物TiN和TiC。     

VWF,Platelets and the Antiphospholipid Syndrome

The antiphospholipid syndrome (APS) is characterized by thrombosis and/or pregnancy morbidity with the persistent presence of antiphospholipid antibodies (aPLs). Laboratory criteria for the classification of APS include the detection of lupus anticoagulant (LAC), anti-cardiolipin (aCL) antibodies and anti-β2glycoprotein I (aβ2GPI) antibodies. Clinical criteria for the classification of thrombotic APS include venous and arterial thrombosis, along with microvascular thrombosis. Several aPLs, including LAC, aβ2GPI and anti-phosphatidylserine/prothrombin antibodies (aPS/PT) have been associated with arterial thrombosis. The Von Willebrand Factor (VWF) plays an important role in arterial thrombosis by mediating platelet adhesion and aggregation. Studies have shown that aPLs antibodies present in APS patients are able to increase the risk of arterial thrombosis by upregulating the plasma levels of active VWF and by promoting platelet activation. Inflammatory reactions induced by APS may also provide a suitable condition for arterial thrombosis, mostly ischemic stroke and myocardial infarction. The presence of other cardiovascular risk factors can enhance the effect of aPLs and increase the risk for thrombosis even more. These factors should therefore be taken into account when investigating APS-related arterial thrombosis. Nevertheless, the exact mechanism by which aPLs can cause thrombosis remains to be elucidated.     

ARTIFICIAL INTELLIGENCE(AI)-DRIVEN SPECTRUM MANAGEMENT

Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle(UAV)communication to smart cognitive networks and massive Internet of Things(IoT)systems.Enabling these emerging applications over the fifth generation(5G)of wireless cellular systems requires meeting numerous challenges pertaining to spectrum sharing and management.In fact,most 5G applications will be highly reliant on intelligent spectrum management techniques,which should adapt to dynamic network environments while also guaranteeing high reliability and high quality-of-experience(QoE).     

Mechanically Fastened FRP-Strengthened Two-Way Concrete Slabs with and without Cutouts

The feasibility of strengthening concrete slabs in flexure, with and without cutouts, using the mechanically fastened (MF) FRP technique is investigated. Two series of large-scale reinforced concrete slabs are tested. The first series is comprised of five slabs without a cutout, and measuring 2,600×2,600×120?mm; the second series consists of four slabs of the same dimensions with a central cutout measuring 800×800?mm. The mechanically fastened system is found to be a valid alternative to the externally bonded system resulting in a rapid, economic, and effective strengthening technique for two-way concrete slabs. The increases in ultimate capacities of the MF FRP-strengthened slabs range between 30 and 70% over those of the unstrengthened specimens. In addition, finite-element modeling of MF FRP-strengthened slabs is introduced in this study. The interfacial behavior between the MF FRPs and the concrete substrate is accounted for by using appropriate interfacial models. Very good agreement is obtained between the test results and the numerical predictions.     

Prevalence and survival of Campylobacter in Egyptian dairy products

Campylobacter is a leading foodborne pathogen that poses an interesting paradox of being frequently transmitted by foodstuffs, yet showing sensitivity to food preservation procedures. In the present study, 227 samples of milk and dairy products were randomly collected and examined for the presence of Campylobacter spp. Samples were collected from the Egyptian area Abou-Homos, where the pathogen had been previously shown to be a major causative agent of intestinal disease. Potential Campylobacter isolates were speciated using a multiplex PCR assay targeting the housekeeping gene lpxA. Only raw milk and fresh Domiati cheese samples were found to contain Campylobacter jejuni at low incidence rates. Using a selected C. jejuni isolate recovered in this study, it was shown that the pathogen maintained its viability in Domiati cheese more than in yoghurt, yet it survived in both products more than expected. This suggests that this foodborne strain of C. jejuni may develop adaptive strategies that aid survival under food preservation conditions, which contradicts with what is known about this pathogen as a stress-sensitive organism.     

A Multi-objective Optimization for Sizing and Placement of Voltage-controlled Distributed Generation Using Supervised Big Bang–Big Crunch Method

Abstract—This article presents an efficient multi-objective optimization approach based on the supervised big bang–big crunch method for optimal planning of dispatchable distributed generator. The proposed approach aims to enhance the system performance indices by optimal sizing and placement of distributed generators connected to balanced/unbalanced distribution networks. The distributed generation units in the proposed algorithms are modeled as a voltage-controlled node with the flexibility to be converted to a constant power node in the case of reactive power limit violation. The proposed algorithm is implemented in the MATLAB (The MathWorks, Natick, Massachusetts, USA) environment, and the simulation studies are performed on IEEE 69-bus and IEEE 123-node distribution test systems. Validation of the proposed method is done by comparing the results with published results obtained from other competing methods, and the consequent discussions prove the effectiveness of the proposed approach.     

Crude Wax Extracted from Rice Bran Oil Improves Oleogel Properties and Oxidative Stability

Crude wax extracted from rice bran oil (RBO) is used to improve the oleogel properties and oxidative stability of RBO. The effect of crude rice bran wax (CrBW) on the formation characteristics and oxidative stability of oleogels is discussed. The results show that oleogels can be formed with 7.0 wt% CrBW at 20 °C. As the concentration of CrBW increases from 7.0 to 11.0 wt%, the hardness and solid fat content (SFC) of the oleogels increase significantly, and the oleogels are primarily β' crystals. Moreover, oleogel crystals formed with 5 and 7 wt% CrBW are flocculent; when the amount included is 9%, the oleogel crystals are transformed into long dendrites, and the density rises. After 90 days of storage at 20 °C, the peroxide value of oleogels formed with 9.0 wt% CrBW slowly rises from 3.21 to 6.52 mmol kg⁻¹. Practical Applications: Oleogels prepared here by CrBW and RBO are an innovative structural lipid without trans fats. Useful information on the rich fats and nutrients in CrBW is provided, which reduces the production cost and improves the industrial production capacity.     

Log-based mining techniques applied to Web service composition reengineering

Web service compositions are becoming more and more complex, involving numerous interacting ad-hoc services. These services are often implemented as business processes themselves. By analysing such complex web service compositions one is able to better understand, control and eventually re-design them. Our contribution to this problem is a mining algorithm, based on a statistical technique to discover composite web service patterns from execution logs. Our approach is characterised by a “local” pattern’s discovery that covers partial results through a dynamic programming algorithm. Those locally discovered patterns are then composed iteratively until the composite Web service is discovered. The analysis of the disparities between the discovered model and the initial ad-hoc composite model (delta-analysis) enables initial design gaps to be detected and thus to re-engineer the initial Web service composition.     

Deep multilayer multiple kernel learning

Multiple kernel learning (MKL) approach has been proposed for kernel methods and has shown high performance for solving some real-world applications. It consists on learning the optimal kernel from one layer of multiple predefined kernels. Unfortunately, this approach is not rich enough to solve relatively complex problems. With the emergence and the success of the deep learning concept, multilayer of multiple kernel learning (MLMKL) methods were inspired by the idea of deep architecture. They are introduced in order to improve the conventional MKL methods. Such architectures tend to learn deep kernel machines by exploring the combinations of multiple kernels in a multilayer structure. However, existing MLMKL methods often have trouble with the optimization of the network for two or more layers. Additionally, they do not always outperform the simplest method of combining multiple kernels (i.e., MKL). In order to improve the effectiveness of MKL approaches, we introduce, in this paper, a novel backpropagation MLMKL framework. Specifically, we propose to optimize the network over an adaptive backpropagation algorithm. We use the gradient ascent method instead of dual objective function, or the estimation of the leave-one-out error. We test our proposed method through a large set of experiments on a variety of benchmark data sets. We have successfully optimized the system over many layers. Empirical results over an extensive set of experiments show that our algorithm achieves high performance compared to the traditional MKL approach and existing MLMKL methods.