Egg white proteins and β-cyclodextrin: effective cryoprotectant mixture against oxidative changes in the myofibrillar proteins of Culter alburnus

The effect of egg white protein (EWP) and β-cyclodextrin (β-CD) mixture was analysed on the myofibrillar proteins (MP) of Culter alburnus during a frozen storage at −18 °C for 60 days. Different proportions of EWP:β-CD mixture (0%, 2%, 4% and 6%) were added into MP to analyse their effect against oxidative changes. During the study, sulphydryl contents and Ca-ATPase activity (0.297 to 0.136 mmol g⁻¹) decreased. Moreover, protein denaturation also prompted the surface hydrophobicity (11.47 to 32.06 μg) and carbonyls (26.36 to 49 mg.28 nmol mg⁻¹) of control MP. A significant decline was observed in emulsifying properties. Besides, EWP:β-CD showed remarkable stability against oxidative changes, by significantly reducing the carbonyls (26.26 to 37.69 nmol mg⁻¹) and surface hydrophobicity (11.51 to 20.31 μg) and also the decline of Ca-ATPase activity (0.29 to 0.19 mmol g⁻¹). It can be concluded that EWP:β-CD (6%) is an efficient approach against oxidative changes in MP from Culter alburnus.     

Intelligent Transmission Control for Efficient Operations in SDN

Although the Software-Defined Network (SDN) is a well-controlled and efficient network but the complexity of open flow switches in SDN causes multiple issues. Many solutions have been proposed so far for the prevention of errors and mistakes in it but yet, there is still no smooth transmission of pockets from source to destination specifically when irregular movements follow the destination host in SDN, the errors include packet loss, data compromise etc. The accuracy of packets received at their desired destination is possible if networks for pockets and hosts are monitored instead of analysis of network snapshot statistically for the state, as these approaches with open flow switches, discover bugs after their occurrence. This article proposes a design to achieve the said objective by defining the Intelligent Transmission Control Layer (ITCL) layer. It monitors all the connections of end hosts at their specific locations and performs necessary settlements when the connection state changes for one or multiple hosts. The layer informs the controller regarding any state change at one period and controller collects information of end nodes reported via ITCL. Then, updates flow tables accordingly to accommodate a location-change scenario with a route-change policy. ICTL is organized on prototype-based implementation using the popular POX platform. In this paper, it has been discovered that ITCL produces efficient performance in the trafficking of packets and controlling different states of SDN for errors and packet loss.     

Numerical investigation on optimization of thermal analysis due to immersion of hybrid nanostructures in a fluid of shear dependent viscosity using the finite element method

This article considers the dispersion of hybrid and mono nanoparticles in a fluid with viscosity (Williamson) dependent on shear rate, over a heated surface moving with nonuniform velocity and exposed to a magnetic field in the presence of an applied current. Extensive modeling leads to complex coupled mathematical models that are solved numerically via the finite element method (FEM). Convergent simulations are run to investigate the role of parameters on the dynamics of flow fields. The magnetic field intensity plays a role in controlling the magnetohydrodynamic boundary layer thickness (BLT) and thermal radiation controls the thickness of thermal boundary layers (TBL). However, the magnetic field intensity is responsible for an increase in BLT. In contrast to this, thermal radiation plays a role in controlling the thickness of the TBL. The impact of shear rate dependent viscosity on velocity is remarkable for both fluids. The motion of both of the fluids slows down when viscosity varies as a function of shear rate. Viscosity depending on the shear rate has a significant impact on wall shear stress. It is observed from simulations that wall shear increases when the parameters appearing in the model for shear rate dependent viscosity are increased. However, this increase in wall shear stress associated with a hybrid nanofluid is greater than the increase in wall shear stress associated with a mono nanofluid.     

New insights into the crystallization process of sol-gel–derived 45S5 bioactive glass

In this work the influence of thermal treatment conditions on crystallization of a sol-gel-derived 45S5 bioactive glass was evaluated using DSC, XRD, TEM, EDX, and X-ray nanocomputed tomography (nano-CT). Temperature and time of the thermal treatment strongly influence the composition of the crystalline phases. At the onset of the glass transition temperature (600°C), combeite crystallizes as the main phase along with a calcium silicate-phosphate phase, which decomposes into rhenanite from 2 hours of thermal treatment at this temperature. At the crystallization temperature (700°C), combeite remains as the main crystalline phase. Additionally, Na₂Ca₂Si₂O₇ crystalline phase is formed. Our results provide a basic platform for tailoring the crystalline phases by controlling the nucleation and growth of crystalline phases via thermal treatments. Different morphologies (round particles, stacked layers, toothpick-like, and long features) were discerned by TEM as a function of temperature and time of treatment. It is the first time that bioactive glass is investigated by nano-CT at laboratory scale. This novel technique enables the 3D visualization of features in the nanometer range, giving clear information about the volumetric distribution of phases in the sample.     

SPION@APTES@FA-PEG@Usnic Acid Bionanodrug for Cancer Therapy

In this work, we aimed to develop stable usnic acid (UA)-conjugated superparamagnetic iron oxide nanoparticles (SPIONs) as a potential drug carrier for in vitro analysis of MCF-7 (breast cancer cell line), HeLa (cervix cancer cell line), L929 (mouse fibroblast cell line), U87 (glioblastoma cell line, brain cancer), and A549 (human lung cancer cell line) cell lines. SPIONs were synthesized via the polyol method and functionalized with APTES using the Stöber method. Carboxylated polyethylene glycol (PEG-COOH), folic acid (FA), and carboxylated luteolin (CL) were conjugated on the surface via a carboxylic/amine group using the nanoprecipitation method, respectively. X-ray powder diffraction analysis confirmed the purity of the product with crystallite size of around 11 nm. Fourier-transformed infrared spectrophotometer (FT-IR) analyses explained the conjugation of all functional groups to the surface of SPIONs. The percentages of inorganic and organic content in the products were investigated via thermal gravimetric analyzer (TGA). For morphological analysis, a transmission electron microscope (TEM) was used. The superparamagnetic property of the product was also confirmed by vibrating sample magnetometer (VSM).     

Convolutional Neural Network for Histopathological Osteosarcoma Image Classification

Osteosarcoma is one of the most widespread causes of bone cancer globally and has a high mortality rate. Early diagnosis may increase the chances of treatment and survival however the process is time-consuming (reliability and complexity involved to extract the hand-crafted features) and largely depends on pathologists’ experience. Convolutional Neural Network (CNN—an end-to-end model) is known to be an alternative to overcome the aforesaid problems. Therefore, this work proposes a compact CNN architecture that has been rigorously explored on a Small Osteosarcoma histology Image Dataaseet (a high-class imbalanced dataset). Though, during training, class-imbalanced data can negatively affect the performance of CNN. Therefore, an oversampling technique has been proposed to overcome the aforesaid issue and improve generalization performance. In this process, a hierarchical CNN model is designed, in which the former model is non-regularized (due to dense architecture) and the later one is regularized, specifically designed for small histopathology images. Moreover, the regularized model is integrated with CNN’s basic architecture to reduce overfitting. Experimental results demonstrate that oversampling might be an effective way to address the imbalanced class problem during training. The training and testing accuracies of the non-regularized CNN model are 98% & 78% with an imbalanced dataset and 96% & 81% with a balanced dataset, respectively. The regularized CNN model training and testing accuracies are 84% & 75% for an imbalanced dataset and 87% & 86% for a balanced dataset.     

A Secure Communication Protocol for Unmanned Aerial Vehicles

Mavlink is a lightweight and most widely used open-source communication protocol used for Unmanned Aerial Vehicles. Multiple UAVs and autopilot systems support it, and it provides bi-directional communication between the UAV and Ground Control Station. The communications contain critical information about the UAV status and basic control commands sent from GCS to UAV and UAV to GCS. In order to increase the transfer speed and efficiency, the Mavlink does not encrypt the messages. As a result, the protocol is vulnerable to various security attacks such as Eavesdropping, GPS Spoofing, and DDoS. In this study, we tackle the problem and secure the Mavlink communication protocol. By leveraging the Mavlink packet’s vulnerabilities, this research work introduces an experiment in which, first, the Mavlink packets are compromised in terms of security requirements based on our threat model. The results show that the protocol is insecure and the attacks carried out are successful. To overcome Mavlink security, an additional security layer is added to encrypt and secure the protocol. An encryption technique is proposed that makes the communication between the UAV and GCS secure. The results show that the Mavlink packets are encrypted using our technique without affecting the performance and efficiency. The results are validated in terms of transfer speed, performance, and efficiency compared to the literature solutions such as MAVSec and benchmarked with the original Mavlink protocol. Our achieved results have significant improvement over the literature and Mavlink in terms of security.     

Local-Tetra-Patterns for Face Recognition Encoded on Spatial Pyramid Matching

Face recognition is a big challenge in the research field with a lot of problems like misalignment, illumination changes, pose variations, occlusion, and expressions. Providing a single solution to solve all these problems at a time is a challenging task. We have put some effort to provide a solution to solving all these issues by introducing a face recognition model based on local tetra patterns and spatial pyramid matching. The technique is based on a procedure where the input image is passed through an algorithm that extracts local features by using spatial pyramid matching and max-pooling. Finally, the input image is recognized using a robust kernel representation method using extracted features. The qualitative and quantitative analysis of the proposed method is carried on benchmark image datasets. Experimental results showed that the proposed method performs better in terms of standard performance evaluation parameters as compared to state-of-the-art methods on AR, ORL, LFW, and FERET face recognition datasets.     

An efficient double exponentially weighted moving average Benjamini‐Hochberg control chart to control false discovery rate

A control chart based on double exponentially weighted moving average and Benjamini‐Hochberg multiple testing procedure is proposed that controls the false discovery rate (FDR). The proposed control chart is based on probabilities (or P values) to accept or reject the null hypothesis of the underlying process is in control. To make a decision, instead of using only the current probability, previous “m” probabilities are considered. The performance of the control chart is evaluated in terms of average run length (ARL) using Monte Carlo simulations. Procedure for estimation of parameters used in the control chart is also discussed. The proposed control chart is compared with previous control charts and found to be more efficient in controlling the false discovery rate.