Screening of anionic-modified polymers in terms of stability,disintegration, and swelling behavior

This study aimed to screen the stability, disintegration, and swelling behavior of chemically modified anionic polymers. Investigated polymers were well-known and widely used staples of the pharmaceutical and medical field, namely, alginate (AL), carboxymethyl cellulose (CMC), polycarbophil (PC), and hyaluronic acid (HA). On the basis of amide bond formation between the carboxylic acid moieties of anionic polymers and the primary amino group of the modification ligand cysteine (CYS), the modified polymers were obtained. Unmodified polymers served as controls throughout all studies. With the Ellman’s assay, modification degrees were determined of synthesized polymeric excipients. Stability assay in terms of erosion study at physiological conditions were performed. Moreover, water uptake of compressed polymeric discs were evaluated and further disintegration studies according to the USP were carried out to define the potential ranking. Results ranking figured out PCCYS?>?CMCCYS?>?HACYS?>?ALCYS in terms of water uptake capacity compared to respective controls. Cell viability assays on Caco-2 cell line as well as on RPMI 2650 (ATTC CCL30) proved modification not being harmful to those. Due to the results of this study, an intense screening of prominent anionic polymer derivate was performed in order to help the pharmaceutical research for the best choice of polymeric excipients for developments of controlled drug release systems.     

Fractional Order Nonlinear Bone Remodeling Dynamics Using the Supervised Neural Network

This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and unstable fluctuation through the MBD. Untreated myeloma causes by increasing the OC and reducing the osteoblasts, resulting in net bone waste the tumor growth. The solutions of the FOMM will be provided by using the stochastic framework based on the Levenberg-Marquardt backpropagation (LVMBP) neural networks (NN), i.e., LVMBPNN. The mathematical performances of three variations of the fractional-order derivative based on the nonlinear disease model using the LVMPNN. The static structural performances are 82% for investigation and 9% for both learning and certification. The performances of the LVMBPNN are authenticated by using the results of the Adams-Bashforth-Moulton mechanism. To accomplish the capability, steadiness, accuracy, and ability of the LVMBPNN, the performances of the error histograms (EHs), mean square error (MSE), recurrence, and state transitions (STs) will be provided.     

WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance. To implement WiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator. The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30% and enhances the throughput by 20%–50%, hence maintaining user fairness and accommodating more wireless devices and traffic load in the network, when compared to traditional client-driven (CD) approach and state of the art Wi-Balance approach.     

Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and beef with different concentrations (10%–50% v/v). Principal component analysis (PCA) and partial least square (PLS) were used to develop a calibration model at 800–3500 cm⁻¹. Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken, lamb, and beef samples. The corresponding FTIR peaks for the lard have been observed at 1159.6, 1743.4, 2853.1, and 2922.5 cm⁻¹, which differentiate chicken, lamb, and beef samples. The wavenumbers offer the highest determination coefficient R² value of 0.846 and lowest root mean square error of calibration (RMSEC) and root mean square error prediction (RMSEP) with an accuracy of 84.6%. Even the tiniest fat adulteration up to 10% can be reliably discovered using this methodology.     

Dynamic S-Box Generation Using Novel Chaotic Map with Nonlinearity Tweaking

A substitution box (S-Box) is a crucial component of contemporary cryptosystems that provide data protection in block ciphers. At the moment, chaotic maps are being created and extensively used to generate these S-Boxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts. In this paper, the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach. The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their working makes both of these dynamic in nature. The tweak approach employs cubic polynomials while permuting the values of an initial S-Box to enhance its cryptographic fort. Values of the parameters are provided using the cipher key and a small variation in values of these parameters results in a completely different unique S-Box. Comparative analysis and exploration confirmed that the projected chaotic map exhibits a significant amount of chaotic complexity. The security assessment in terms of bijectivity, nonlinearity, bits independence, strict avalanche, linear approximation probability, and differential probability criteria are utilized to critically investigate the effectiveness of the proposed S-Box against several assaults. The proposed S-Box’s cryptographic performance is comparable to those of recently projected S-Boxes for its adaption in real-world security applications. The comparative scrutiny pacifies the genuine potential of the proposed S-Box in terms of its applicability for data security.     

Topological Characterization of Book Graph and Stacked Book Graph

Degree based topological indices are being widely used in computer-aided modeling, structural activity relations, and drug designing to predict the underlying topological properties of networks and graphs. In this work, we compute the certain important degree based topological indices like Randic index, sum connectivity index, ABC index, ABC₄ index, GA index and GA₅ index of Book graph B_n and Stacked book graph B_m,n. The results are analyzed by using edge partition, and the general formulas are derived for the above-mentioned families of graphs.     

Recent progress in the modification of carbon materials and their application in composites for electromagnetic interference shielding

With the development in the modern technologies such as telecommunication instruments and scientific electronic devices, large amount of the electromagnetic radiations are produced, which lead to harmful effect on the highly sensitive electronic devices as well as on the health of human beings. To minimize the effect of electromagnetic radiations produced by different technologies, more efficient shielding materials are required which must be cost-effective, lightweight and good corrosion resistive. In this review, we focused on the shielding materials based on composites of carbon nanotubes and graphene. The typical surface modification of carbon nanotubes and graphene to optimize their interactions with polymers matrix has also summarized. It was found that the composites based on these carbon fillers were more efficient for electromagnetic interference shielding due to their unique properties (i.e., superior electrical, mechanical and thermal) together with lightweight, easy processing. Hence, the carbon nanotubes and graphene-based composites are excellent shielding materials against the electromagnetic radiations.     

Structural,Electrical and Dielectric Properties of Hexa-ferrite-Polyaniline Nano-composites

Ferrite-polyaniline (PANI) composites were prepared by in situ polymerization of polyaniline with the general formula (1 ? x) ferrite + (x) PANI where x = 0, 0.25, 0.5, 0.75, 1. The samples were characterized by XRD, SEM, electrical resistivity, and dielectric measurements. X-ray diffraction reveals single phase formation of CaBaCo₂Al_0.5Fe_11.5O₂₂ Y-type ferrite, whereas polyaniline exhibits an amorphous nature. At room temperature, the resistivity of nano-composites increases with the increase of ferrite filler contents from 3.17 × 10⁴ to 3.19 × 10⁷ Ω cm. Real and imaginary parts of the complex permittivity of the PANI-ferrite composites follow the Maxwell-Wagner model. Based on the Jonscher Law, the AC conductivity of PANI-ferrite composites experiences an increase with the increase in frequency. The exponent calculated from AC conductivity reveals that the hopping is the likely conduction mechanism. The activation energy obtained from temperature-dependent measurements is consistent with room temperature resistivity. Due to the light weight, low cost and flexibility of design, the ferrite-polymer composites are considered useful for microwave devices.     

Large scale synthesis of single-crystal and polycrystalline boron nitride nanosheets

Boron nitride nanosheets (BNNSs) have an identical crystal structure and similar lattice parameter to those of graphene sheets. However, growing quality BNNSs consisting of only several atomic layers remains a challenge. Here, we report on the synthesis of BNNSs at a temperature of 350 °C using a CO₂ pulsed laser plasma deposition (CO₂-PLD) technique by irradiating a pyrolytic hexagonal boron nitride (h-BN) target. The deposition was performed either in vacuum at a pressure of 0.2 Pa, for which we obtained polycrystalline BN, or in hydrogen (H₂) atmosphere at a pressure of 26 Pa for which we obtained single-crystal BNNSs. The presence of H₂ seems to minimize the side effects of sputtering and the material shows higher purity and better crystallinity. High resolution transmission electron microscopy (HRTEM) showed the sheets to be mostly defect-free and to have the characteristic honeycomb structure of six-membered B₃-N₃ hexagon. HRTEM, electron diffraction, X-ray diffraction, Raman scattering, and Fourier transform infrared spectroscopy clearly identified h-BN.     

A new nonparametric double exponentially weighted moving average control chart

There are many practical situations where the underlying distribution of the quality characteristic either deviates from normality or it is unknown. In such cases, practitioners often make use of the nonparametric control charts. In this paper, a new nonparametric double exponentially weighted moving average control chart on the basis of the signed-rank statistic is proposed for monitoring the process location. Monte Carlo simulations are carried out to obtain the run length characteristics of the proposed chart. The performance comparison of the proposed chart with the existing parametric and nonparametric control charts is made by using various performance metrics of the run length distribution. The comparison showed the superiority of the suggested chart over its existing parametric and nonparametric counterparts. An illustrative example for the practical implementation of the proposed chart is also provided by using the industrial data set.