Deformation due to expanding ring load in modified couple stress thermoelastic diffusion in time and frequency domain

The two-dimensional problem of expanding ring load in a modified couple stress theory of thermoelastic diffusion with heat sources in time and frequency domains is investigated. The mathematical formulation prepared for thermoelastic diffusion solids with one and two relaxation times using Laplace and Hankel transforms. The displacements, stress components, temperature change, and chemical potential are obtained in a transformed domain. Numerical computation is performed for these quantities and the resulting quantities are shown graphically for the time and frequency domains. Comparisons are made with the results predicted by the two theories and different values of time and frequency. Particular cases of interest are also deduced.     

BAGEL: A non-ignorable missing value estimation method for mixed attribute datasets

Surveys are mainly conducted to obtain valuable information on some criteria from a specified population. But, the survey results often become biased due to non-response of the subjects under study for highly significant attributes. Such non-ignorable missingness need to be treated and the actual values should be retrieved. Many methods have already been proposed for handling missing values in either discrete or continuous attributes. But, there exists a large gap in handling non-ignorable missing values in datasets with mixed attributes. With the intent of addressing this gap, this paper proposes a methodology called as Bayesian Genetic Algorithm (BAGEL) with hybridized Bayesian and Genetic Algorithm principles. In BAGEL, the initial population is generated using Bayesian model and fitness values of the chromosomes are evaluated using Bayesian principles. BAGEL is implemented in real datasets for imputing both discrete and continuous missing values and the imputation accuracy is observed. The experimental results show the superior performance of BAGEL than other standard imputation techniques. Statistical tests conducted to validate the experimental results also prove that BAGEL outperforms at all missing rates from 5% to 50%.     

Synthesis,defect characterization and photocatalytic degradation efficiency of Tb doped CuO nanoparticles

Monoclinic undoped and Tb doped CuO are prepared by solution combustion method and annealed at different temperatures. The effect of annealing and doping on their structural and optical properties of CuO are examined using XRD, FTIR and DRS. The surface and lattice defects in CuO and Tb doped CuO is analyzed qualitatively and quantitatively using positron lifetime and Doppler broadening spectroscopy. The average positron lifetime and electron momentum (energy) S parameter increases owing to the number of vacancies in the CuO lattice upon doping and decreases with increasing temperature. The migration of vacancies from grain to grain boundary region is observed at 600 °C annealed samples. At 800 °C, the overall behavior of lifetime value denotes that the vacancy type defect is recovered, cluster vacancy and microvoids exists with reducing size. The photocatalytic performance of undoped and Tb doped CuO on degradation of methylene blue (MB) and methyl orange (MO) is investigated under visible light for two different lamp power and dye concentration. The influence of annealing temperature and dopant ion on the efficiency is also elaborated. Enhanced photocatalytic efficiency in Tb doped CuO is observed upon annealing. X-ray photoelectron spectroscopy (XPS) result indicates that the valence states of Cu, O and Tb ions exist at the surface of the particles. Brunauer–Emmett–Teller N₂ adsorption–desorption analyses were employed to characterize specific surface area and porosity of Tb doped CuO. The doped CuO with pore size of about ～34 nm have a surface area of 16–28 m²/g. The surface area effect plays an important role in the enhanced catalytic performance on Tb doped catalysts.     

Biogenic synthesis,characterisation and antifungal activity of gum kondagogu‐silver nano bio composite construct: assessment of its mode of action

The biogenic synthesis of silver nanoparticles was achieved by using gum kondagogu (Cochlospermum gossypium), a natural biopolymer (Gk‐AgNPs). Synthesised nanoparticles were characterised by using UV–visible spectroscopy, inductively coupled plasma‐atomic emission spectrometer, X‐ray diffraction, transmission electron microscope techniques. The silver nano particle size determined was found to be 3.6 ± 2.2 nm. The synthesised Gk‐AgNPs showed antifungal activity and exhibited minimum inhibitory concentration and minimal fungicidal concentration values ranging from 3.5 to 6.5 µg mL⁻¹ against Aspergillus parasiticus (NRRL‐2999) and Aspergillus flavus (NRRL‐6513). Scanning electron microscopy–energy dispersive spectroscopy analysis revealed morphological changes including deformation, shrunken and ruptured mycelium of the fungi. At the biochemical level, the mode of action revealed that there was an elevated level of reactive oxygen species, lipid peroxidation, superoxide dismutase, and catalase enzyme activity. Increased oxidative stress led to increased outer membrane damage, which was confirmed by the entry of N ‐phenyl naphthylamine to the phospholipid layer of outer membrane and higher levels of K⁺ release from the fungi treated with Gk‐AgNPs. This study explores the possible application of biogenic silver nanoparticles produced from gum kondagogu as potent antifungal agents. The potent antifungal activity of Gk‐AgNPs gives scope for its relevance in biomedical application and as a seed dressing material.Inspec keywords: antibacterial activity, nanocomposites, silver, nanofabrication, nanoparticles, biomedical materials, polymers, visible spectra, ultraviolet spectra, atomic emission spectroscopy, X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, microorganisms, X‐ray chemical analysis, enzymes, lipid bilayers, biomembranes, biomechanics, nanomedicineOther keywords: antifungal activity, gum kondagogu‐silver nanobiocomposite, Cochlospermum gossypium, natural biopolymer, UV‐visible spectroscopy, inductively coupled plasma‐atomic emission spectrometer, X‐ray diffraction, transmission electron microscope, fungicidal concentration, Aspergillus parasiticus, Aspergillus flavus, scanning electron microscopy, SEM‐energy dispersive spectroscopy, fungi deformation, ruptured mycelium, reactive oxygen species, lipid peroxidation, superoxide dismutase, catalase enzyme activity, oxidative stress, membrane damage, N‐phenyl naphthylamine, phospholipid layer, potassium ion release, biogenic silver nanoparticle, antifungal agent, seed dressing material, Ag     

Evaluation of potential anti‐cancer activity of cationic liposomal nanoformulated Lycopodium clavatum in colon cancer cells

Research dealing with early diagnosis and efficient treatment in colon cancer to improve patient''s survival is still under investigation. Chemotherapeutic agent result in high systemic toxicity due to their non‐specific actions on DNA repair and/or cell replication. Traditional medicine such as Lycopodium clavatum (LC) has been claimed to have therapeutic potentials against cancer. The present study focuses on targeted drug delivery of cationic liposomal nanoformulated LC (CL‐LC) in colon cancer cells (HCT15) and comparing the efficacy with an anti‐colon cancer drug, 7‐ethyl‐10‐hydroxy‐camptothecin (SN38) along with its nanoformulated form (CL‐SN38). The colloidal suspension of LC was made using thin film hydration method. The drugs were characterised using ultraviolet, dynamic light scattering, scanning electron microscopy, energy, dispersive X‐ray spectroscopy. In vitro drug release showed kinetics of 49 and 89% of SN38 and LC, whereas CL‐SN38 and CL‐LC showed 73 and 74% of sustained drug release, respectively. Studies on morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis of Bcl‐2, Bax, p53 by real‐time polymerase chain reaction and western blot analysis of Bad and p53 protein were performed. Nanoformulated LC significantly inhibited growth and increased the apoptosis of colon cancer cells indicating its potential anti‐cancer activity against colon cancer cells.Inspec keywords: cancer, biological organs, cellular biophysics, drug delivery systems, drugs, nanomedicine, genetics, DNA, molecular biophysics, biochemistry, lipid bilayers, toxicology, suspensions, colloids, light scattering, X‐ray chemical analysis, solvation, enzymes, nanostructured materialsOther keywords: energy dispersive X‐ray spectroscopy, in vitro drug release, morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis, Bcl‐2, Bax, real‐time polymerase chain reaction, western blot analysis, Bad protein, p53 protein, scanning electron microscopy, dynamic light scattering, ultraviolet scattering, thin film hydration method, colloidal suspension, nanoformulated form CL‐SN38, 7‐ethyl‐10‐hydroxy‐camptothecin, anticolon cancer drug, colon cancer cells HCT15, cationic liposomal nanoformulated LC, targeted drug delivery, therapeutic potentials, Lycopodium clavatum, traditional medicines, cell replication, DNA repair, nonspecific actions, high systemic toxicity, chemotherapeutic agents, patient survival, colon cancer treatment, colon cancer diagnosis, CL‐LC, potential anticancer activity     

Multiple metastatic infections in a hemodialysis patient with untunneled internal jugular catheter

We present an end‐stage renal disease patient on dialysis with fever. The primary source was right internal jugular vein catheter which had metastatic infections in the body probably via an arteriovenous communication in a cavity in left lung. Patient had right psoas muscle abscess and a left kidney abscess. An ¹⁸F‐fluorodeoxyglucose‐positron emission spectroscopy scan was done to find out left kidney abscess. A search of literature did not reveal many patients of psoas abscess secondary to infection of hemodialysis access.     

An improved algorithm for connectivity analysis of distribution networks

In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks.     

Detection and Classification of Diabetic Retinopathy Using DCNN and BSN Models

Diabetes is associated with many complications that could lead to death. Diabetic retinopathy, a complication of diabetes, is difficult to diagnose and may lead to vision loss. Visual identification of micro features in fundus images for the diagnosis of DR is a complex and challenging task for clinicians. Because clinical testing involves complex procedures and is time-consuming, an automated system would help ophthalmologists to detect DR and administer treatment in a timely manner so that blindness can be avoided. Previous research works have focused on image processing algorithms, or neural networks, or signal processing techniques alone to detect diabetic retinopathy. Therefore, we aimed to develop a novel integrated approach to increase the accuracy of detection. This approach utilized both convolutional neural networks and signal processing techniques. In this proposed method, the biological electro retinogram (ERG) sensor network (BSN) and deep convolution neural network (DCNN) were developed to detect and classify DR. In the BSN system, electrodes were used to record ERG signal, which was pre-processed to be noise-free. Processing was performed in the frequency domain by the application of fast Fourier transform (FFT) and mel frequency cepstral coefficients (MFCCs) were extracted. Artificial neural network (ANN) classifier was used to classify the signals of eyes with DR and normal eye. Additionally, fundus images were captured using a fundus camera, and these were used as the input for DCNN-based analysis. The DCNN consisted of many layers to facilitate the extraction of features and classification of fundus images into normal images, non-proliferative DR (NPDR) or early-stage DR images, and proliferative DR (PDR) or advanced-stage DR images. Furthermore, it classified NPDR according to microaneurysms, hemorrhages, cotton wool spots, and exudates, and the presence of new blood vessels indicated PDR. The accuracy, sensitivity, and specificity of the ANN classifier were found to be 94%, 95%, and 93%, respectively. Both the accuracy rate and sensitivity rate of the DCNN classifier was 96.5% for the images acquired from various hospitals as well as databases. A comparison between the accuracy rates of BSN and DCNN approaches showed that DCNN with fundus images decreased the error rate to 4%.     

Biological decolourization of C.I. Direct Black 38 by E. gallinarum

In the present study, an Enterococcus gallinarum strain was isolated from effluent treatment plant of a textile industry based on its ability to decolourize C.I. Direct Black 38 (DB38), a benzidine-based azo dye. Effects of dye concentration and medium composition on dye decolourization were studied. The strain was found to decolourize DB38 even under aerobic conditions. Kinetics of DB38 decolourization was also examined, and V(max) and K(s) of decolourization were found to be higher in Luria broth (12.8 mg l(-1)h(-1) and 490.6 mg l(-1)) than in minimal medium (4.09 mg l(-1)h(-1) and 161.84 mg l(-1)). However, decolourization rate/biomass was found to be higher in minimal medium than in Luria broth, indicating greater decolourization efficiency of biomass in the former. The study also revealed biodegradation of DB38 to benzidine and its further deamination to 4-aminobiphenyl (4-ABP) by the culture. Ammonia released during this process was used as nitrogen source for growth of the culture.     

Effect of simultaneous double doping in Ba and Ti sites on dielectric and ferroelectric properties of sol–gel synthesized nano-BaTiO<Subscript>3</Subscript>

Lead free (Ba_(1−3x)Nd_(2x))(Ti_(1−y)Zr_y)O₃ (x = 0, 0.025, y = 0, 0.025, 0.05) ceramics were prepared successfully using sol–gel method. The effect of Nd, Zr content on dielectric and polarisation properties of BaTiO₃ were studied using dielectric and hysteresis measurements. SEM analysis proved that the particle size of compounds as prepared were in the order of 30–60 nm. The ferroelectric phase transition from tetragonal to cubic phase was observed around 130 °C for pure BaTiO₃. With the addition of Nd (2.5 mol%) and increasing content of Zr (2.5 and 5 mol%), it was observed that transition temperature (T_c) shifts to lower temperatures (70–50 °C), but didn’t show any relaxor behaviour. Dielectric measurements showed an increase in the values at room temperature in all the doped samples. The synthesized ceramics exhibited typical P–E hysteresis loops at room temperature accompanied by saturation polarisation (P_s) and remanent polarisation (P_r). Behaviour of polarisation phenomena in these compounds showed interesting results with increasing temperature.