Pack Cementation Coatings for High-Temperature Oxidation Resistance of AISI 304 Stainless Steel

Aluminum and titanium are deposited on the surface of steel by the pack cementation method to improve its hot-corrosion and high-temperature oxidation resistance. In this research, coatings of aluminum and titanium and a two-step coating of aluminum and titanium were applied on an AISI 304 stainless steel substrate. The coating layers were examined by carrying out scanning electron microscopy (SEM) and x-ray diffraction (XRD). The SEM results showed that the aluminized coating consisted of two layers with a thickness of 450???m each, the titanized coating consisted of two layers with a thickness of 100???m each, and the two-step coatings of Al and Ti consisted of three layers with a thickness of 200???m each. The XRD investigation of the coatings showed that the aluminized coating consisted of Al₂O₃, AlCr₂, FeAl, and Fe₃Al phases; the titanized layers contained TiO₂, Ni₃Ti, FeNi, and Fe₂TiO₅ phases; and the two-step coating contained AlNi, Ti₃Al, and FeAl phases. The uncoated and coated specimens were subjected to isothermal oxidation at 1050?°C for 100?h. The oxidation results revealed that the application of a coating layer increased the oxidation resistance of the coated AISI 304 samples as opposed to the uncoated ones.     

Harnessing Normal and Engineered Mesenchymal Stem Cells Derived Exosomes for Cancer Therapy: Opportunity and Challenges

There remains a vital necessity for new therapeutic approaches to combat metastatic cancers, which cause globally over 8 million deaths per year. Mesenchymal stem cells (MSCs) display aptitude as new therapeutic choices for cancer treatment. Exosomes, the most important mediator of MSCs, regulate tumor progression. The potential of harnessing exosomes from MSCs (MSCs-Exo) in cancer therapy is now being documented. MSCs-Exo can promote tumor progression by affecting tumor growth, metastasis, immunity, angiogenesis, and drug resistance. However, contradictory evidence has suggested that MSCs-Exo suppress tumors through several mechanisms. Therefore, the exact association between MSCs-Exo and tumors remains controversial. Accordingly, the applications of MSCs-Exo as novel drug delivery systems and standalone therapeutics are being extensively explored. In addition, engineering MSCs-Exo for targeting tumor cells has opened a new avenue for improving the efficiency of antitumor therapy. However, effective implementation in the clinical trials will need the establishment of standards for MSCs-Exo isolation and characterization as well as loading and engineering methods. The studies outlined in this review highlight the pivotal roles of MSCs-Exo in tumor progression and the promising potential of MSCs-Exo as therapeutic drug delivery vehicles for cancer treatment.     

Polyphenol-rich seaweed (Eucheuma cottonii) extract suppresses breast tumour via hormone modulation and apoptosis induction

The edible red seaweed Eucheuma cottonii is abundantly cultivated for carrageenan production. This study investigated the effects of dietary E. cottonii polyphenol-rich extract (ECME) on breast cancer. In vitro assays showed that ECME was antiproliferative against oestrogen-dependent MCF-7 and oestrogen-independent MB-MDA-231 human breast-cancer cells (IC₅₀ values of 20 and 42 μg/ml, respectively) but was non-toxic to normal cell lines. The ECME (150 and 300 mg/kg BW) was fed to female rats and, after 4 weeks, rat mammary tumour was induced using LA7 cells (inoculated subcutaneously). The ECME inhibited tumour development and erythrocyte lipid peroxidation in the cancer-induced rats, dose-dependently. It showed anti-oestrogenic effects on the rat estrous cycle and serum hormone levels. Electron microscopy and histopathology observations confirmed apoptosis in the rat mammary tumours. The polyphenol-rich ECME was tumour-suppressive via apoptosis induction, downregulating the endogenous oestrogen biosynthesis, and improving antioxidative status in the rats.     

A Novel Alternative Method for Modeling the Effects of Air Temperature and Slice Thickness on Quality and Drying Kinetics of Tomato Slices: Superposition Technique

The effect of air temperature (AT) and slice thickness (ST) on the quality and drying kinetics of tomato slices were studied. The drying period of tomato slices to reach the moisture content of 15% (wb) ranged from 2.6 to 18.7 h. The water diffusivity, activation energy, and resistance to diffusion ranged from 1.4 × 10^?10 to 2.8 × 10^?9 m²/s, 21.25 to 23.4 kJ/mol, and from 939 to 4590 m² s/kg, respectively. Drying had a significant effect on ascorbic acid, soluble solid, acidity, and pH (P = 0.01). The ascorbic acid degradation was greatly influenced by ST. The results show that time-temperature superposition technique (TTST) was very efficient in the modeling of the drying process. The proposed TTST provides a novel alternative in curve-fitting exercise of drying data. Neural networks also showed favorable performance in estimating the drying functions.     

The Addiction-Stroop test: Theoretical considerations and procedural recommendations.

Decisions about using addictive substances are influenced by distractions by addiction-related stimuli, of which the user might be unaware. The addiction-Stroop task is a paradigm used to assess this distraction. The empirical evidence for the addiction-Stroop effect is critically reviewed, and meta-analyses of alcohol-related and smoking-related studies are presented. Studies finding the strongest effects were those in which participants had strong current concerns about an addictive substance or such concerns were highlighted through experimental manipulations, especially those depriving participants of the substance. Theories to account for addiction-related attentional bias are discussed, of which the motivational theory of current concerns appears to provide the most complete account of the phenomenon. Recommendations are made for maximizing the precision of the addiction-Stroop test in future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Rapid activation of protein C by factor Xa and thrombin in the presence of polyanionic compounds

A recent study indicated that negatively charged substances such as heparin and dextran sulfate accelerate thrombin activation of coagulation factor XI by a template mechanism. Because the serine proteinase of the natural anticoagulant pathway, activated protein C, can bind heparin, it was reasonable to think that these compounds may also bind protein C (PC) and accelerate its activation by thrombin or other heparin binding plasma serine proteinases by a similar mechanism. To test this, PC activation by thrombin and factor Xa (fXa) was studied in the presence of these polysaccharides. With thrombin in the absence of thrombomodulin (TM), these polysaccharides markedly reduced the Km for PC and Gla-domainless PC (GDPC) activation in the presence of Ca2+. With TM containing chondroitin sulfate, heparin did not influence PC activation by thrombin, but with TM lacking chondroitin sulfate, the characteristic high-affinity PC interaction at low Ca2+ (approximately 50 to 100 micromol/L) was largely eliminated by heparin. In EDTA, heparin enhanced thrombin activation of GDPC by reducing the Km, but it inhibited PC activation by increasing the Km. PC activation in EDTA was insensitive to the presence of heparin if the exosite 2 mutant, R93,97,101A thrombin, was used for activation. These results suggest that, when the Gla-domain of PC is not fully stabilized by Ca2+, it interacts with the anion binding exosite 2 of thrombin and that heparin binding to this site prevents this interaction. Additional studies indicated that, in the presence of phospholipid vesicles, heparin and dextran sulfate dramatically accelerate PC activation by fXa by also reducing the Km. Interestingly, on phospholipids containing 40% phosphatidylethanolamine, the activation rate of near physiological PC concentrations ( approximately 80 nmol/L) by fXa in the presence of dextran sulfate was nearly comparable to that observed by the thrombin-TM complex. The biochemical and potential therapeutical ramifications of these findings are discussed.     

Investigating the effect of nanoparticles on the rutting behaviour of hot-mix asphalt

Rutting is considered as one of the major damages in asphalt mixtures. In this study, different types of nanoparticles such as TiO₂, Al₂O₃, Fe₂O₃ and ZnO in different percentages were added to the base asphalt binder in order to decrease the rutting potential of hot-mix asphalt (HMA). In the first step, asphalt binder tests for characteristics such as penetration grade, ductility, softening point and viscosity were performed on the asphalt binder modified by the nanoparticles. Then, after preparing HMA samples, the static creep test was done at two stress levels at a specific temperature. Results of this study showed that using the nanoparticles improved the behavioural properties of the asphalt binder and decreased rutting in asphalt mix samples. Furthermore, scanning electron microscope images taken from the asphalt binder samples modified by the nanoparticles demonstrated that these nanoparticles were properly distributed in the asphalt binder space and had a positive effect on the rutting performance of the asphalt mixes.     

A NEW DISTRIBUTED JOB SCHEDULING ALGORITHM FOR GRID SYSTEMS

Job scheduling is one of the key issues in the design of grid environments. The performance of the grid system severely degrades if a method does not exist to efficiently schedule the user jobs. In this article, a fully distributed, learning automata–based job scheduling algorithm is proposed for grid environments. The proposed method is composed of two types of procedures: in the first, a procedure is run at the grid nodes and in the second, the procedure is run at the schedulers. The proposed algorithm synchronizes the performance of the schedulers by the learning automata that select their actions using the pseudo-random number generators with the same seed. In this method, the grid computational capacity that is allocated to each scheduler is proportional to its workload. To show the efficiency of the proposed method, several simulation experiments were conducted under different grid scenarios. The obtained results show that the proposed algorithm outperforms several well-known methods in terms of makespan, flow time, and load balancing.     

Using class-based feature selection for the classification of hyperspectral data

The rapid advances in hyperspectral sensing technology have made it possible to collect remote-sensing data in hundreds of bands. However, the data-analysis methods that have been successfully applied to multispectral data are often limited in achieving satisfactory results for hyperspectral data. The major problem is the high dimensionality, which deteriorates the classification due to the Hughes Phenomenon. In order to avoid this problem, a large number of algorithms have been proposed, so far, for feature reduction. Based on the concept of multiple classifiers, we propose a new schema for the feature selection procedure. In this framework, instead of using feature selection for whole classes, we adopt feature selection for each class separately. Thus different subsets of features are selected at the first step. Once the feature subsets are selected, a Bayesian classifier is trained on each of these feature subsets. Finally, a combination mechanism is used to combine the outputs of these classifiers. Experiments are carried out on an Airborne Visible/Infrared Imaging Spectroradiometer (AVIRIS) data set. Encouraging results have been obtained in terms of classification accuracy, suggesting the effectiveness of the proposed algorithms.     

Robustification of input redundant feedback systems using robust actuator weighting in the control allocation problem

In this article, a new methodology for robust actuator weighting in the control allocation (CA) problem of input redundant feedback systems is addressed. The methodology is based on the control structural properties of the plant which were previously used for control configuration selection. Robust performance (RP) measures including H _∞ norm and structured singular value of the closed-loop system are used in this article. The capability of the approach is proven with application to lateral dynamics control of the vehicle over-actuated with front and rear steering systems. Employing the RP measures, it is concluded that the vehicle feedback control with front steering angles gives superior RP properties in comparison with the feedback loop of the rear steering angles. Based on these results, the penalty weightings in the cost function of the CA unit are determined. Simulation results based on nonlinear seven degrees of freedom vehicle handling model show that the selection of penalty weightings in the CA unit based on the RP properties of the control inputs (front and rear steering angles) improves the RP of the closed-loop.