Biopreservative technologies of food: an alternative to chemical preservation and recent developments

Food Science and Biotechnology - Despite centuries of developing strategies to prevent food-associated illnesses, food safety remains a significant concern, even with multiple technological...     

Mangiferin Inhibits Apoptosis in Doxorubicin-Induced Vascular Endothelial Cells via the Nrf2 Signaling Pathway

Doxorubicin increases endothelial permeability, hence increasing cardiomyocytes’ exposure to doxorubicin (DOX) and exposing myocytes to more immediate damage. Reactive oxygen species are major effector molecules of doxorubicin’s activity. Mangiferin (MGN) is a xanthone derivative that consists of C-glucosylxanthone with additional antioxidant properties. This particular study assessed the effects of MGN on DOX-induced cytotoxicity in human umbilical vein endothelial cells’ (HUVECs’) signaling networks. Mechanistically, MGN dramatically elevated Nrf2 expression at both the messenger RNA and protein levels through the upregulation of the PI3K/AKT pathway, leading to an increase in Nrf2-downstream genes. Cell apoptosis was assessed with a caspase-3 activity assay, transferase-mediated dUTP-fluorescein nick end labeling (TUNEL) staining was performed to assess DNA fragmentation, and protein expression was determined by Western blot analysis. DOX markedly increased the generation of reactive oxygen species, PARP, caspase-3, and TUNEL-positive cell numbers, but reduced the expression of Bcl-2 and antioxidants’ intracellular concentrations. These were effectively antagonized with MGN (20 μM), which led to HUVECs being protected against DOX-induced apoptosis, partly through the PI3K/AKT-mediated NRF2/HO-1 signaling pathway, which could theoretically protect the vessels from severe DOX toxicity.     

Solar hydrogen generation from organic substance using earth abundant CuS–NiO heterojunction semiconductor photocatalyst

This work explores the critical role of NiO co-catalyst assembled on the surface of a CuS primary photocatalyst which effectively improves interface properties and enhances solar-to-hydrogen production by prolonging lifetime of photo-excitons generated at the CuS surface. The nanoscale CuS/NiO heterojunction is formulated using hydrothermal and wet impregnation methods. The resultant CuS/NiO composite shows optical absorbance between 380 and 780 nm region. The type-II energetic structure formed at CuS/NiO heterojunction facilitates rapid charge separation and as a result, the CuS/NiO composite exhibits 13 folds higher photocatalytic water splitting performance than CuO and NiO. The champion CuO/NiO photocatalyst is first identified by screening the catalysts using a preliminary water splitting test reaction under natural Sunlight irradiation. After the optimization of the catalyst, it was further explored for enhanced photocatalytic hydrogen production using different organic substances dispersed in water (alcohols, amine and organic acids). The champion CuS/NiO catalyst (CPN-2) exhibited the photocatalytic hydrogen production rate of 52.3 mmol h^?1.g^?1_cat in the presence of lactic acid-based aqueous electrolyte and, it is superior than hydrogen production rate obtained in the presence of other organic substances (triethanolamine, glycerol, ethylene glycol, methanol) tested under identical experimental conditions. These results indicate that the energetic structure of CuS/NiO photocatalyst is favorable for photocatalytic oxidation or reforming of lactic acid. The oxidation of lactic acid contributes both protons and electrons for enhanced hydrogen generation as well as protects CuS from photocorrosion. The modification of surface property and energetic structure of CuS photocatalyst by the NiO co-catalyst improves photogenerated charge carrier separation and in turn enhances the solar-to-hydrogen generation efficiency. The recyclability tests showed the potential of CPN-2 photocatalyst for prolonged photocatalytic hydrogen production while continuous supply of lactic acid feedstock is available.     

Sensitivity-based conceptual design and tolerance allocation using the continuous ants colony algorithm (CACO)

In an assembly, there are two ways to control the deviation of critical dimensions. One is by keeping the deviation of the critical dimension small by tightening manufacturing tolerances and controlling aging and environmental effects. This approach is traditional and expensive, as it requires tighter manufacturing tolerances and protection from aging and the environment. The second is by moving the nominal values of the non-critical dimensions to a less sensitive portion. This approach is very helpful in improving the quality with no additional cost. One can analyze any number of designs very early in the concept development stage of a project. After the concept design the cost-based optimal tolerances for the corresponding dimensions are allocated. The continuous ants colony algorithm, a kind of meta-heuristic approach, is used as an optimization tool for minimizing the critical dimension deviation and allocating the cost- based optimal tolerances.     

Thermal transport properties of carbon-assisted phase change nanocomposite

Abstract

In this study, stability, density, rheology, and thermal conductivity of the Multi-wall carbon nanotubes (MWCNTs) based PCM nanocomposites were experimentally investigated. The PCM OM08 has been selected for the air-conditioning application with a phase change temperature of 8–10?°C. PCM nanocomposites (without surfactant) in various concentrations namely 0.05, 0.1, 0.3 and 0.5?vol. % were prepared using a typical two-step method and high homogenous stability is achieved using a mechanical mixing technique (ultra-sonication). The density of PCM nanocomposites was measured using two different types of standard volumetric flask approach and the experimental values confirmed good conformity with the Pak and Cho mixing theory. The highest thermal conductivity augmentation of 24.03%and 64.04% were achieved in liquid and solid states, respectively, with 0.5?vol. % of MWCNT. While, the addition of MWCNT resulted in a changeover of Newtonian to Non-Newtonian behaviors at a low shear rate, and the dynamic viscosity enhancement was increased by 130% with 0.5?vol. % of MWCNT. Further, the results were compared with existing correlations and it was found that the experimental values were in line with existing correlations.     

Influence of different conducting substrates on magnetic properties of electrodeposited Ni–Fe thin films

Electrodeposition of Ni–Fe soft magnetic alloy on copper and stainless steel substrates was performed in chloride bath. The deposition parameters such as current density, pH, temperature and deposition time have been investigated. From the investigation the optimized deposition parameters were current density 3.5 mA/cm², pH 3, temperature 30 °C and deposition time 15 min. The Ni–Fe magnetic alloys deposited on copper and stainless steel substrates under optimized deposition parameters are subjected to various characterizations. The structural and surface morphology of the Ni–Fe films were detected by using X-ray diffractogram (XRD) and scanning electron microscope (SEM) respectively. The constituents in the films were determined by energy dispersive X-ray spectroscopy (EDAX) technique. The magnetic properties such as the coercivity (H_c) and saturation magnetization of the films were studied with the help of vibrating sample magnetometer (VSM). From the magnetic studies it is concluded that the grain size are create a considerable impact on magnetic behavior of the films on both the substrates. The films prepared on stainless steel substrate of 0.1 M concentration at optimized deposition parameters exhibits higher coercivity (5010 Oe) which seems to be ideal for magnetic sensor applications.     

Region based coronary artery segmentation using modified Frangi's vesselness measure

Recent research suggests that the cardiovascular diseases (CVDs), seem to be the foremost cause of mortality among the world populace. Three dimensional (3D) imaging modality such as computed tomography angiography(CTA) is a standard noninvasive imaging modality which has great potentials for the visualization of heart and coronary arteries. This article presents a fully automated method for coronary artery extraction using modified Frangi's vesselness measure and region based segmentation. In this article, grayness and gradient based measures are used while computing Frangi's vesselness measure to improve the extraction of coronary arteries. The obtained vesselness measures are utilized for automatically computing the location of ostia. The locations of ostia are then used as starting seed points in region growing segmentation to extract coronary arteries. Three major coronary arteries, namely the left anterior descending artery (LAD), left circumflex artery (LCX) and right coronary artery (RCA) are segmented using the proposed method and the centerlines are extracted for the main coronary branches. The performance of the proposed method is evaluated using 12 3D CCTA data set. The experimental results reveal that during the calculation of modified Frangi's vesselness measure the proposed method gives improved results. The qualitative results obtained during the segmentation stage are also convincing. The average segmentation accuracy and overlap measure of the proposed method are 97.4% and 77.86%, respectively. Hence, the proposed automated approach can detect and extract coronary arteries in CCTA images with high performance.     

Efficient Resource Allocation in Fog Computing Using QTCS Model

Infrastructure of fog is a complex system due to the large number of heterogeneous resources that need to be shared. The embedded devices deployed with the Internet of Things (IoT) technology have increased since the past few years, and these devices generate huge amount of data. The devices in IoT can be remotely connected and might be placed in different locations which add to the network delay. Real time applications require high bandwidth with reduced latency to ensure Quality of Service (QoS). To achieve this, fog computing plays a vital role in processing the request locally with the nearest available resources by reduced latency. One of the major issues to focus on in a fog service is managing and allocating resources. Queuing theory is one of the most popular mechanisms for task allocation. In this work, an efficient model is designed to improve QoS with the efficacy of resource allocation based on a Queuing Theory based Cuckoo Search (QTCS) model which will optimize the overall resource management process.     

Hydrothermally synthesized ZnO and Z-rGO nanorods: Effect of post-annealing temperature and rGO incorporation on hydrogen sensing

Journal of Materials Science: Materials in Electronics - In this work, hydrogen-sensing characteristics of zinc oxide nanorods and reduced graphene oxide-incorporated zinc oxide nanorods are...     

Scalable Lanthanum Titanate (La2Ti2O7) nanostructures as UV photodetectors

Thermally and chemically stable perovskite-like layer structures have attracted extensively in the field of energy and environmental applications. In this study, La₂Ti₂O₇ was synthesized by the solvothermal method at 180 °C. This method provides high pure and homogeneously dispersed nanorods of orthorhombic phase having length of 250 nm and width of 70 nm. Even though this is a low-temperature synthesis method, it yields high crystalline nature after calcination. The novelty of this work is its synthesis methodology by the solvothermal route to achieve lower weight loss of La₂Ti₂O₇. Furthermore, they exhibit narrow absorption in the UV-region from 200 to 350 nm, makes it possible to fabricate it as UV photodetector at ambient condition. In presence of UV illumination at 390 nm, it shows sharp photocurrent response with the decay time of 1.7 s.