Effect of transition metal doping on the sintering and electrochemical properties of GDC buffer layer in SOFCs

A dense Ce_0.9Gd_0.1O_2−d (GDC) interlayer is an essential component of the SOFCs to inhibit interfacial elemental diffusion between zirconia-based electrolytes (eg YSZ) and cathodes. However, the characteristic high sintering temperature of GDC (>1400°C) makes it challenging to fabricate an effective highly dense interlayer owing to the formation of more resistive (Zr,Ce)O₂ interfacial solid solutions with YSZ at those temperatures. To fabricate a useful GDC interlayer, we studied the influence of transition metal (TM) (Co, Cu, Fe, Mn, & Zn) doping on the sintering and electrochemical properties of GDC. Dilatometry data showed dramatic drops in the necking and final sintering temperatures for the TM-doped GDCs, improving the densification of the GDC in the order of Fe > Co > Mn > Cu > Zn. However, the electrochemical impedance data showed that among various transition metal dopants, Mn doping resulted in the best electrochemical properties. Anode supported SOFCs with Mn-doped, nano, and commercial-micron GDC interlayers were compared with regard to their performance and stability levels. Although all of the SOFCs showed stable performance, the SOFC with the Mn-doped GDC interlayer showed the highest power density of 1.14 W cm⁻² at 750°C. Hence, Mn-doped GDC is suggested for application as an effective diffusion barrier layer in SOFCs.     

Microfluidic Tumor-on-a-Chip Model to Study Tumor Metabolic Vulnerability

Tumor-specific metabolic adaptations offer an interesting therapeutic opportunity to selectively destroy cancer cells. However, solid tumors also present gradients of nutrients and waste products across the tumor mass, forcing tumor cells to adapt their metabolism depending on nutrient availability in the surrounding microenvironment. Thus, solid tumors display a heterogenous metabolic phenotype across the tumor mass, which complicates the design of effective therapies that target all the tumor populations present. In this work, we used a microfluidic device to study tumor metabolic vulnerability to several metabolic inhibitors. The microdevice included a central chamber to culture tumor cells in a three-dimensional (3D) matrix, and a lumen in one of the chamber flanks. This design created an asymmetric nutrient distribution across the central chamber, generating gradients of cell viability. The results revealed that tumor cells located in a nutrient-enriched environment showed low to no sensitivity to metabolic inhibitors targeting glycolysis, fatty acid oxidation, or oxidative phosphorylation. Conversely, when cell density inside of the model was increased, compromising nutrient supply, the addition of these metabolic inhibitors disrupted cellular redox balance and led to tumor cell death.     

Magnetic Properties and Microstructural Modifications of Sm-Co-Hf Alloy Ribbons by B Addition

Journal of Superconductivity and Novel Magnetism - Microstructure optimization is highly desirable for improving the magnetic properties of permanent magnetic materials. To optimize the...     

Ag–Sr doped mesoporous bioactive glass nanoparticles loaded chitosan/gelatin coating for orthopedic implants

In this study, we investigated surface and biological properties of Ag–Sr-doped mesoporous bioactive glass nanoparticle (Ag–Sr MBGN) loaded chitosan/gelatin coatings deposited by electrophoretic deposition (EPD) on 316L stainless steel. The EPD parameters, that is, deposition time, applied voltage, and distance between the electrodes was optimized by the Taguchi design of experiment (DoE) approach. Scanning electron microscopy (SEM) images illustrated the spherical morphology of the synthesized Ag–Sr MBGNs with the mean particle size of 160 ± 20 nm. Energy-dispersive X-ray (EDX) spectroscopy results confirmed the presence of Ag and Sr in the synthesized MBGNs. Optimum EPD parameters determined by DoE approach were 5 g/L of Ag–Sr MBGNs, deposition time of 5 min, and applied voltage of 30 V. SEM images confirmed that the coatings were fairly homogenous. Fourier-transform infrared spectroscopy and EDX results confirmed the presence of chitosan, gelatin, and Ag–Sr MBGNs in the coatings. Chitosan/gelatin/Ag–Sr MBGN composite coatings exhibited suitable wettability for the protein attachment and proliferation of osteoblast cells. The composite coatings exhibited suitable adhesion strength with the substrate. The coatings developed HA crystals upon immersion in simulated body fluid. The results of the turbidity test confirmed that the coatings are antibacterial to the Escherichia coli cells.     

Optimal Automatic Generation Control of Asynchronous Power Systems Using Output Feedback Control Strategy with Dynamic Participation of Wind Turbines

Abstract—This article presents the design of optimal output feedback automatic generation control regulators for an interconnected power system with dynamic participation of doubly fed induction generator based wind turbines. The power systems consist of plants with hydro-thermal turbines and are interconnected via parallel AC/DC links. Efforts have been made to propose optimal automatic generation control regulators based on feedback of output state variables, which are easily accessible and available for the measurement. The designed optimal output feedback automatic generation control regulators are implemented, and the system dynamic responses for various system states are obtained considering 1% load perturbation in one of the areas. The dynamic performance is compared with that obtained with optimal automatic generation control regulators designed using full state vector feedback. The pattern of closed-loop eigenvalues is also determined to test the system stability.     

Facile Synthesis of Ferrocene-Based Polyamides and Their Organic Analogues Terpolyamides: Influence of Aliphatic and Aromatic Sequences on Physico-Chemical Characteristics

Efforts have been devoted to synthesize and characterize processable polymers with desired properties. Herein, four different series of aromatic and aliphatic terpolyamides were prepared via solution phase polycondensation of 4,4′-oxydianiline and hexamethylenediamine (HMDA) with various diacids chlorides (isophthalyol dichloride, terepthalyol dichloride, 1, 1′-ferrocene dicarboxylic acid chloride and trans-azobenzene-4, 4′-dicarbonyl chloride). The structural, morphological and physico-chemical nature of as prepared polymers was explored by Fourier-transform infrared spectroscopy, scanning electron microscopy, thermal analysis (TGA and DSC), and wide-angle x-ray diffraction. Moreover, an aliphatic diamine was incorporated in varying concentration as a flexible methylene spacer and the effect of its concentration on the properties of polyamides was also studied. Changes in various physico-chemical properties such as solubility, inherent viscosity, surface morphology and flame retarding behaviour were investigated. Marked difference in morphology and solubility was observed with the change in the ratio of segments in the chain. Inherent viscosities of polymers ranged from 1.8052–1.6274 dl/g indicating reasonably moderate molecular weights. Interestingly, ferrocene based aromatic polymers were more thermally stable (T_g 260 °C, T_i 310 °C, T_h 525 °C, T_f 720 °C, for PF₀), and also found to exhibit best flame retarding behavior (limiting oxygen index value for PF₀is LOI 33.15%).

     

Silicon Application Enhances the Photosynthetic Pigments and Phenolic/Flavonoid Content by Modulating the Phenylpropanoid Pathway in Common Buckwheat under Aluminium Stress

Silicon - Silicon (Si) is very effective in the amelioration of heavy metal (HM) stress in different crop plants. This investigation was conducted to assess the protective role of Si in modulating...     

A Novel Sprague-Dawley Rat Model Presents Improved NASH/NAFLD Symptoms with PEG Coated Vitexin Liposomes

Chronic liver disease (CLD) is a global threat to the human population, with manifestations resulting from alcohol-related liver disease (ALD) and non-alcohol fatty liver disease (NAFLD). NAFLD, if not treated, may progress to non-alcoholic steatohepatitis (NASH). Furthermore, inflammation leads to liver fibrosis, cirrhosis, and hepatocellular carcinoma. Vitexin, a natural flavonoid, has been recently reported for inhibiting NAFLD. It is a lipogenesis inhibitor and activates lipolysis and fatty acid oxidation. In addition, owing to its antioxidant properties, it appeared as a hepatoprotective candidate. However, it exhibits low bioavailability and low efficacy due to its hydrophobic nature. A novel rat model for liver cirrhosis was developed by CCL4/Urethane co-administration. Vitexin encapsulated liposomes were synthesized by the ‘thin-film hydration’ method. Polyethylene glycol (PEG) was coated on liposomes to enhance stability and stealth effect. The diseased rats were then treated with vitexin and PEGylated vitexin liposomes, administered intravenously and orally. Results ascertained the liposomal encapsulation of vitexin and subsequent PEG coating to be a substantial strategy for treating liver cirrhosis through oral drug delivery.     

Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear

Malaria is a serious worldwide disease, caused by a bite of a female Anopheles mosquito. The parasite transferred into complex life round in which it is grown and reproduces into the human body. The detection and recognition of Plasmodium species are possible and efficient through a process called staining (Giemsa). The staining process slightly colorizes the red blood cells (RBCs) but highlights Plasmodium parasites, white blood cells and artifacts. Giemsa stains nuclei, chromatin in blue tone and RBCs in pink color. It has been reported in numerous studies that manual microscopy is not a trustworthy screening technique when performed by nonexperts. Malaria parasites host in RBCs when it enters the bloodstream. This paper presents segmentation of Plasmodium parasite from the thin blood smear points on region growing and dynamic convolution based filtering algorithm. After segmentation, malaria parasite classified into four Plasmodium species: Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, and Plasmodium malaria. The random forest and K‐nearest neighbor are used for classification base on local binary pattern and hue saturation value features. The sensitivity for malaria parasitemia (MP) is 96.75% on training and testing of the proposed approach while specificity is 94.59%. Beside these, the comparisons of the two features are added to the proposed work for classification having sensitivity is 83.60% while having specificity is 94.90% through random forest classifier based on local binary pattern feature.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.