Evaluation of antifungal effect of iron‐oxide nanoparticles against different Candida species

Iron‐oxide nanoparticles (IONPs) have been widely favoured due to their biodegradable, low cytotoxic effects and having reactive surface which can be altered with biocompatible coatings. Considering various medical applications of IONPs, the authors were encouraged to study whether IONPs could be effective against fungal infections caused by Candida species. In this study, IONPs were characterised by scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectroscopy and vibrating sample magnetometer. The goal of this study was to evaluate the antifungal activity of IONPs against different Candida spp. compared with fluconazole (FLC). IONPs were spherical with the size of 30–40 nm. The minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) values of IONPs ranged from 62.5 to 500 µg/ml and 500 to 1000 μg/ml, respectively. The MIC and MFC of FLC were in range of 16–128 μg/ml and 64–512 μg/ml, respectively. The growth inhibition value indicated that Candida tropicalis, Candida albicans and Candida glabrata spp. were most susceptible to IONPs. The finding showed that the IONPs possessed antifungal potential against pathogenic Candida spp. and could inhibit the growth of all the tested Candida spp. Further studies, both in vitro and in vivo (including susceptibility, toxicity, Probability of kill (PK) and efficacy studies) are needed to determine whether IONPs are suitable for medicinal purposes.Inspec keywords: iron compounds, nanoparticles, nanomedicine, biomedical materials, microorganisms, cellular biophysics, toxicology, drugs, scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectraOther keywords: antifungal effect, iron‐oxide nanoparticles, Candida species, biodegradable effects, cytotoxic effects, reactive surface, biocompatible coatings, medical applications, IONP, fungal infections, Candidiasis, immunocompromised hosts, antifungal drugs, resistant organisms, antifungal properties, side effects, chemical drugs, scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectroscopy, vibrating sample magnetometer, antifungal activity, disc diffusion, broth microdilution, minimal inhibitory concentration, minimum fungicidal concentration, Candida tropicalis, Candida Albicans, Candida glabrata, antifungal potential, Fe₃ O₄      

Conditional mean- and median-based cumulative sum control charts for Weibull data

This article deals with the monitoring of censored data using the cumulative sum (CUSUM) control charts for Weibull lifetimes under type-I censoring. To develop an efficient CUSUM structure for censored data, we use the conditional expected value (CEV) and conditional median (CM) approaches. In particular, we focus on the detection of shifts in the mean of Weibull lifetimes assuming censored data. In addition to fixed/known parameter values, the effect of estimation is assessed on the detection power of control charts. The performance of the proposed charts is evaluated by the average run length (ARL). Furthermore, the ARL performance of CUSUM charts is compared with CEV- and CM-based exponentially weighted moving average (EWMA) control charts. Besides an extensive simulation study, the significance of the current work is illustrated by a data set on the response time of a thermostat experiment.     

3D Semantic Deep Learning Networks for Leukemia Detection

White blood cells (WBCs) are a vital part of the immune system that protect the body from different types of bacteria and viruses. Abnormal cell growth destroys the body’s immune system, and computerized methods play a vital role in detecting abnormalities at the initial stage. In this research, a deep learning technique is proposed for the detection of leukemia. The proposed methodology consists of three phases. Phase I uses an open neural network exchange (ONNX) and YOLOv2 to localize WBCs. The localized images are passed to Phase II, in which 3D-segmentation is performed using deeplabv3 as a base network of the pre-trained Xception model. The segmented images are used in Phase III, in which features are extracted using the darknet-53 model and optimized using Bhattacharyya separately criteria to classify WBCs. The proposed methodology is validated on three publically available benchmark datasets, namely ALL-IDB1, ALL-IDB2, and LISC, in terms of different metrics, such as precision, accuracy, sensitivity, and dice scores. The results of the proposed method are comparable to those of recent existing methodologies, thus proving its effectiveness.     

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.     

Exhaust emission profiling of fatty acid methyl esters and NOx control studies using selective synthetic and natural additives

Clean Technologies and Environmental Policy - The present study was focused on the optimized biodiesel production using Moringa oleifera (M. oleifera) and rice bran oils, characterization, and...     

On increasing the sensitivity of moving average control chart using auxiliary variable

In the statistical process control, the most useful tool to monitor the manufacturing processes in the industries is the control chart. Quality practitioners always desire the charting structure that identifies sustainable changes in the monitoring processes. The sensitivity of the control chart is improved when additional correlated auxiliary information about the study variable is introduced. The regression estimate in the form of auxiliary and supporting variables presents an unbiased and efficient statistic of the mean of the process variable. In this study, auxiliary information-based moving average (AB-MA) control chart is designed for efficient monitoring of shifts in the process location parameter. The performance of the AB-MA control chart is evaluated and compared with existing charts using average run length and other run length characteristics. The comparison reveals that the AB-MA control chart outperforms the competitors in detecting the small and medium changes in the process location parameter. The application of the proposal is also provided to implement it in real situation.     

Structure Preserving Algorithm for Fractional Order Mathematical Model of COVID-19

In this article, a brief biological structure and some basic properties of COVID-19 are described. A classical integer order model is modified and converted into a fractional order model with as order of the fractional derivative. Moreover, a valued structure preserving the numerical design, coined as Grunwald–Letnikov non-standard finite difference scheme, is developed for the fractional COVID-19 model. Taking into account the importance of the positivity and boundedness of the state variables, some productive results have been proved to ensure these essential features. Stability of the model at a corona free and a corona existing equilibrium points is investigated on the basis of Eigen values. The Routh–Hurwitz criterion is applied for the local stability analysis. An appropriate example with fitted and estimated set of parametric values is presented for the simulations. Graphical solutions are displayed for the chosen values of (fractional order of the derivatives). The role of quarantined policy is also determined gradually to highlight its significance and relevancy in controlling infectious diseases. In the end, outcomes of the study are presented.     

Bright,dark and dark-singular soliton solutions of nonlinear Schrödinger's equation with spatio-temporal dispersion

This article presents an analytical study of the propagation of solitons through optical fibres. We consider a nonlinear Schrödinger equation with spatio-temporal dispersion and quadratic–cubic nonlinearity. Jacobi elliptic functions are used as an ansatz to extract optical dark and bright solitons as well as Jacobi elliptic solutions. The extended direct algebraic method gives dark and dark-singular soliton solutions. The constraint conditions which guarantee the existence of soliton solutions are listed.     

Biofilm reduction,cell proliferation,anthelmintic and cytotoxicity effect of green synthesised silver nanoparticle using Artemisia vulgaris extract

Infectious diseases are caused by etiological agents. Nanotechnology has been used to minimise the effect of clinical pathogens which have resistance to antibiotics. In current research synthesis, characterisation and biological activities of green synthesised nanoparticles using Artemisia vulgaris extract have been done. The characterisation of AgNPs was carried out using Fourier transform infrared spectroscopy, UV‐Vis spectrophotometry, and scanning electron microscopy. Anti‐biofilm, cell viability, antibacterial, brine shrimp lethality, and deoxyribonucleic acid protection effects have been screened. UV‐Vis spectra showed the absorption peak of synthesised nanoparticles at 400 nm. FT‐IR indicated the involvement of the functional group in the preparation of AgNPs. SEM showed the spherical shape of AgNPs with 30 nm diameter. Biological screening results revealed the antibacterial effect against clinical bacterial pathogens. Biofilm reduction and cell viability assay also supported the antibacterial effect. Cytotoxicity effect was recorded as 100% at 200 μg/ml through brine shrimp lethality assay. Protein kinase inhibition zones recorded for AgNPs (16 mm bald) compared with A. vulgaris extract (11 mm bald). It has been concluded that green synthesised AgNPs are more effective against infectious pathogens and could be used as a potential source for therapeutic drugs.Inspec keywords: cellular biophysics, toxicology, silver, nanoparticles, nanomedicine, diseases, microorganisms, ultraviolet spectra, visible spectra, Fourier transform infrared spectra, enzymes, molecular biophysicsOther keywords: biofilm reduction, cell proliferation, anthelmintic effect, cytotoxicity effect, green synthesised silver nanoparticle, Artemisia vulgaris extract, infectious diseases, aetiological agents, Fourier transform infrared spectroscopy, UV‐Vis spectrophotometry, scanning electron microscopy, SEM, antibiofilm, cell viability, brine shrimp lethality, deoxyribonucleic acid protection effects, AgNP, cytotoxicity, protein kinase inhibition zones, therapeutic drugs     

Heat transfer analysis of Walters’-B fluid with Newtonian heating through an oscillating vertical plate by using fractional Caputo–Fabrizio derivatives

Mechanics of Time-Dependent Materials - This paper presents a study of Walters’-B fluid with Caputo–Fabrizio fractional derivatives through an infinitely long oscillating vertical plate...