Effects of bovine serum albumin on the corrosion behaviour of AISI 316L, Co–28Cr–6Mo, and Ti–6Al–4V alloys in phosphate buffered saline solutions

The corrosion behaviour of AISI 316L, wrought Co–28Cr–6Mo and Ti–6Al–4V was studied in aerated solutions of phosphate buffered saline (PBS) at various concentrations of bovine serum albumin (BSA) at 37 °C. Open circuit potential, potentiodynamic polarization, linear polarization resistance (LPR) and electrochemical impedance spectroscopy (EIS) experiments along with X-ray photoelectron spectroscopy (XPS) on Co–28Cr–6Mo oxide layer were conducted to study the interaction of BSA and passive layers and to measure the corrosion rates. Ti–6Al–4V alloy had the lowest corrosion rate and the highest breakdown potential. It was shown that BSA has enhanced the alloy passive film stability at higher concentrations.     

Investigation of chitosan‐g‐PEG grafted nanoparticles as a half‐life enhancer carrier for tissue plasminogen activator delivery

Tissue plasminogen activator (tPA) a thrombolytic agent is commonly used for digesting the blood clot. tPA half‐life is low (4–6 min) and its administration needs a prolonged continuous infusion. Improving tPA half‐life could reduce enzyme dosage and enhance patient compliance. Nano‐carries could be used as delivery systems for the protection of enzymes physically, enhancing half‐life and increasing the stability of them. In this study, chitosan (CS) and polyethylene glycol (PEG) were used for the preparation of CS‐g‐PEG/tPA nanoparticles (NPs) via the ion gelation method. Particles’ size and loading capacity were optimised by central composite design. Then, NPs cytotoxicity, release profile, enzyme activity and in vivo half‐life and coagulation time were investigated. The results showed that NPs does not have significant cytotoxicity. Release study revealed that a burst effect happened in the first 5 min and resulted in releasing 30% of tPA. Loading tPA in NPs could decrease 25% of its activity but the half‐life of it increases in comparison to free tPA in vivo. Also, blood coagulation time has significantly affected (p ‐value = 0.041) by encapsulated tPA in comparison to free tPA. So, CS‐g‐PEG/tPA could increase enzyme half‐life during the time and could be used as a non‐toxic candidate delivery system for tPA.Inspec keywords: drug delivery systems, nanofabrication, drugs, nanomedicine, coagulation, biomedical materials, cellular biophysics, enzymes, biochemistry, toxicology, molecular biophysics, biological tissues, blood, nanoparticles, polymersOther keywords: chitosan‐g‐PEG grafted nanoparticles, half‐life enhancer carrier, tissue plasminogen activator delivery, tPA half‐life, prolonged continuous infusion, enzyme dosage, polyethylene glycol, cytotoxicity, enzyme activity, encapsulated tPA, enzyme half‐life, blood coagulation, time 5.0 min     

Putative mechanism for anticancer properties of Ag–PP (NPs) extract

One of the most important challenges in treating cancer is the invasion and the angiogenesis of cancer cells. The synthesis of green nanoparticles (NPs) and their use in therapeutic fields is one of the most effective methods with minimal side effects in cancer treatment. In this study, cytotoxic and anti‐angiogenic effects of silver NPs (AgNPs) coated with palm pollen extract [Ag–PP(NPs)] were evaluated. For this purpose, the cells were treated with NPs and then were subjected to trypan blue testing (48 h). Then, the cancer invasion was evaluated by the scratch procedure and the expressions of the vascular endothelial growth factor (VEGF) and its receptor (VEGF‐R) genes were estimated using real‐time PCR assay. Also, the angiogenesis effect of the NPs was investigated with chick chorioallantoic membrane (CAM) assay. The Ag–PP(NPs) induced cytotoxicity on MCF7 cells. The findings also showed that Ag–PP(NPs) inhibit invasive cancer cells and reduce the expression of VEGF and VEGF‐R and significantly reduced the number and vessels lengths and the lengths and weights of the embryos in CAM assay. Ag–PP(NPs) with the induction of cytotoxic effects, metastatic inhibition and anti‐angiogenesis properties should be considered as an appropriate option for treatment of cancerInspec keywords: nanomedicine, genetics, cellular biophysics, toxicology, patient treatment, silver, cancer, biochemistry, biomedical materials, nanoparticles, nanofabrication, membranesOther keywords: minimal side effects, cancer treatment, silver NPs, cancer invasion, vascular endothelial growth factor, receptor genes, VEGF‐R, real‐time polymerase chain reaction assay, angiogenesis effect, chick chorioallantoic membrane assay, MCF7 cells, invasive cancer cells, cytotoxic effects, putative mechanism, anticancer properties, antiangiogenic effects, antiangiogenesis properties, Ag–PP‐induced cytotoxicity, metastatic inhibition, palm pollen extraction, trypan blue testing, time 48.0 hour, Ag     

Structural performance assessment of GFRP elastic gridshells by machine learning interpretability methods

The prediction of structural performance plays a significant role in damage assessment of glass fiber reinforcement polymer (GFRP) elastic gridshell structures. Machine learning (ML) approaches are implemented in this study, to predict maximum stress and displacement of GFRP elastic gridshell structures. Several ML algorithms, including linear regression (LR), ridge regression (RR), support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), category boosting (CatBoost), and light gradient boosting machine (LightGBM), are implemented in this study. Output features of structural performance considered in this study are the maximum stress as f₁(x) and the maximum displacement to self-weight ratio as f₂(x). A comparative study is conducted and the Catboost model presents the highest prediction accuracy. Finally, interpretable ML approaches, including shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions. SHAP is employed to describe the importance of each variable to structural performance both locally and globally. The results of sensitivity analysis (SA), feature importance of the CatBoost model and SHAP approach indicate the same parameters as the most significant variables for f₁(x) and f₂(x).     

Synthesis, characterization and application of allyl phenol modified amberlite XAD-4 resin for preconcentration and determination of copper in water samples

A new chelating resin was prepared by coupling Amberlite XAD-4 with phenol through an azo spacer, then modified by allyl bromide and characterized (by elemental analysis and IR) and studied for preconcentration of Cu(II) using flame atomic absorption spectrometry (FAAS) for metal monitoring. The optimum pH value for sorption of the above mentioned metal ion was 4.5. The resin was subjected to chemical evaluation through batch binding and column chromatography of Cu(II). The chelating resin can be reused for 15 cycles of sorption-desorption without any significant change in sorption capacity. A recovery of 98% was obtained for the metal ion with 0.5 M HNO₃ as eluting agent. The equilibrium adsorption data of Cu(II) on modified resin were analyzed by Langmuir, Freundlich and Temkin models. Based on equilibrium adsorption data the Langmuir, Freundlich and Temkin constants were determined to be 0.061, 0.193 and 0.045 at pH 4.5 and 25 °C. The method was applied for the copper determination from industrial waste water sample.     

Properties of waste‐poly(ethylene terephthalate)/acrylonitrile butadiene styrene blends compatibilized with maleated acrylonitrile butadiene styrene

Waste poly(ethylene terephthalate) (W‐PET)/acrylonitrile‐butadiene‐styrene (ABS) blends were prepared with a variety of compositions at several rotor speeds in an internal mixer, replacing ABS with different maleated ABS (ABS‐g‐MA) samples in compatibilized blends. A Box–Behnken model for three variables, with three levels, was chosen for the experimental design. ABS‐g‐MA‐based samples exhibited finer particles with a more uniform particle size distribution than ABS‐based ones, as a consequence of the compatibilizing process. Rheological results implied a greater elastic nature for compatibilized blends which increased in the presence of more ABS content; the same trend was observed for complex viscosity. With increasing ABS‐g‐MA or MA concentration, more shear thinning behavior was observed similar to that of ABS; whereas the uncompatibilized blends showed Newtonian behavior like that of W‐PET. The observed shifting in T_gW‐PET and T_gABS obtained from dynamic mechanical thermal analysis confirmed the good compatibility in W‐PET/ABS‐g‐MA blends in contrast with that in ordinary W‐PET/ABS blends. The mechanical properties were measured and modeled versus the various factors considered in a response surface methodology. The experimental data found a good fit with the obtained equation models. The mechanical properties of the compatibilized blends showed a large positive deviation from the mixing rule, while the uncompatibilized samples had lower properties, even compared to those predicted by the mixing rule. J. VINYL ADDIT. TECHNOL., 2010. © 2010 Society of Plastics Engineers     

Surface defect detection in tiling Industries using digital image processing methods: Analysis and evaluation

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated.     

Generation of entangled coherent-squeezed states: their entanglement and nonclassical properties

In this paper, after a brief review on the coherent states and squeezed states, we introduce two classes of entangled coherent-squeezed states. Next, in order to generate the introduced entangled states, we present a theoretical scheme based on the resonant atom-field interaction. In the proposed model, a \(\varLambda \)-type three-level atom interacts with a two-mode quantized field in the presence of two strong classical fields. Then, we study the amount of entanglement of the generated entangled states using the concurrence and linear entropy. Moreover, we evaluate a few of their nonclassical properties such as photon statistics, second-order correlation function, and quadrature squeezing and establish their nonclassicality features.     

A segmentation approach for file broadcast scheduling

We study the broadcast scheduling problem in which clients send their requests to a server in order to receive some files available on the server. The server may be scheduled in a way that several requests are satisfied in one broadcast. When files are transmitted over computer networks, broadcasting the files by fragmenting them provides flexibility in broadcast scheduling that allows the optimization of per user response time. The broadcast scheduling algorithm, then, is in charge of determining the number of segments of each file and their order of transmission in each round of transmission. In this paper, we obtain a closed form approximation formula which approximates the optimal number of segments for each file, aiming at minimizing the total response time of requests. The obtained formula is a function of different parameters including those of underlying network as well as those of requests arrived at the server. Based on the obtained approximation formula we propose an algorithm for file broadcast scheduling which leads to total response time which closely conforms to the optimum one. We use extensive simulation and numerical study in order to evaluate the proposed algorithm which reveals high accuracy of obtained analytical approximation. We also investigate the impact of various headers that different network protocols add to each file segment. Our segmentation approach is examined for scenarios with different file sizes at the range of 100 KB to 1 GB. Our results show that for this range of file sizes the segmentation approach shows on average 13% tolerance from that of optimum in terms of total response time and the accuracy of the proposed approach is growing by increasing file size. Besides, using proposed segmentation in this work leads to a high Goodput of the scheduling algorithm.     

Mechanism study of silver nanoparticle production using Neurospora intermedia

Elucidation of the molecular mechanism of silver nanoparticle (AgNP) synthesis is necessary to control nanoparticle size, shape, and monodispersity. In this study, the mechanism of AgNP formation by Neurospora intermedia was investigated. The higher production rate of AgNP formation using a culture supernatant heat‐treated at 100° and 121°C relative to that with an un‐treated culture supernatant indicated that the native form of the molecular species is not essential. The effect of the protein molecular weight (MW) on the nanoparticle size distribution and average size was studied by means of ultraviolet–visible spectroscopy and dynamic light scattering. Using un‐treated and concentrated cell‐free filtrate passed through 10 and 20 kDa cut‐off filters led to the production of AgNPs with average sizes of 25, 30, and 34 nm, respectively. Also, using the permeate fraction of cell‐free filtrate passed through a 100 kDa cut‐off filter led to the formation of the smallest nanoparticles with the narrowest size distribution (average size of 16 nm and polydispersity index of 0.18). Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis of the fungal extracellular proteins showed two notable bands with the MWs of 15 and 23 kDa that are involved in the reduction and stabilisation of the nanoparticles, respectively.Inspec keywords: silver, nanoparticles, nanofabrication, proteins, molecular weight, ultraviolet spectra, visible spectra, cellular biophysics, electrophoresis, molecular biophysicsOther keywords: Neurospora intermedia, molecular mechanism, silver nanoparticle synthesis, nanoparticle shape, nanoparticle monodispersity, AgNP formation, untreated culture supernatant, molecular species, protein molecular weight, MW, nanoparticle size distribution, ultraviolet‐visible spectroscopy, dynamic light scattering, untreated cell‐free filtrate, concentrated cell‐free filtrate, cut‐off filters, permeate fraction, polydispersity index, Sodium dodecyl sulphate polyacrylamide gel electrophoresis analysis, fungal extracellular proteins, nanoparticle reduction, nanoparticle stabilisation, temperature 100 degC, temperature 121 degC, size 25 nm, size 30 nm, size 34 nm, size 16 nm, Ag