Vels University

Simulated systems are used for modelling and analysis of systems for which an analytical solution is either not accessible or difficult to achieve. Simulation is a highly flexible and adaptable discipline within computer science. Because it is simpler than conventional approaches, which are often challenging, simulation is also chosen as a method of system analysis. Because of this, simulation is an area with extensive application and demand, making it interesting and beneficial to have a chapter dedicated to researching simulation with a case study of modelling a Queuing system.

clinical trials.Communicated by Ramaswamy H. Sarma.

A new method of graphene oxide (GO) synthesis via single-step reforming of sugarcane bagasse agricultural waste by oxidation under muffled atmosphere conditions is reported. The strong and sharp X-ray diffraction peak at 2θ = 11.6° corresponds to an interlayer distance of 0.788 nm (d002) for the AB stacked GOs. High-resolution transmission electron microscopy (HRTEM) and selected-area electron diffraction (SAED) confirm the formation of the GO layer structure and the hexagonal framework. This is a promising method for fast and effective synthesis of GO from sugarcane bagasse intended for a variety of energy and environmental applications.

INTRODUCTION: Image segmentation in medical physics plays a vital role in image analysis to identify the affected tumour. The process of subdividing an image into its constituent parts that are homogeneous in feature is called Image segmentation, and this process concedes to extract some useful information. Numerous image segmentation techniques have been developed, and these techniques conquer different restrictions on conventional medical segmentation techniques. This paper presents a review of medical image segmentation techniques and statistical mechanics based on the novel method named as Lattice Boltzmann method (LBM). The beauty of LBM is to augment the computational speed in the process of medical image segmentation with an accuracy and specificity of more than 95% compared to traditional methods. As there is not much information on LBM in medical physics, it is intended to present a review of the research progress of LBM.OBJECTIVE: As there is no review paper on the research progress of the LB method, this paper presents a review with an objective to give some thought regarding the different segmentation for medical image and novel LB method to advance interest for future investigation and exploration in medical image segmentation.METHODS: This paper in attendance a short review of medical image segmentation techniques based on Thresholding, Region-based, Clustering, Edge detection, Model-based and the novel method Lattice Boltzmann method (LBM).CONCLUSION: In this paper, we outlined various segmentation techniques applied to medical images, emphasize that none of these problem areas has been acceptably settled, and all of the algorithms depicted are available for broad improvement. Since LBM has the benefits of speed and adaptability of modelling to guarantee excellent image processing quality with a reasonable amount of computer resources, we predict that this method will become a new research hotspot in image processing.

The aim of the study is to prepare aqueous dispersions of lipid nanoparticles--flurbiprofen solid lipid nanoparticles (FLUSLN) and flurbiprofen nanostructured lipid carriers (FLUNLC) by hot homogenization followed by sonication technique and then incorporated into the freshly prepared hydrogels for transdermal delivery. They are characterized for particle size, for all the formulations, more than 50% of the particles were below 300 nm after 90 days of storage at RT. DSC analyses were performed to characterize the state of drug and lipid modification. Shape and surface morphology were determined by TEM which revealed fairly spherical shape of the formulations. Further they were evaluated for in vitro drug release characteristics, rheological behaviour, pharmacokinetic and pharmacodynamic studies. The pharmacokinetics of flurbiprofen in rats following application of SLN gel (A1) and NLC gel (B1) for 24 h were evaluated. The Cmax of the B1 formulation was 38.67 +/- 2.77 microg/ml, which was significantly higher than the A1 formulation (Cmax = 21.79 +/- 2.96 microg/ml). The Cmax and AUC of the B1 formulation were 1.8 and 2.5 times higher than the A1 gel formulation respectively. The bioavailability of flurbiprofen with reference to oral administration was found to increase by 4.4 times when gel formulations were applied. Anti-inflammatory effect in the Carrageenan-induced paw edema in rat was significantly higher for B1 and A1 formulation than the orally administered flurbiprofen. Both the SLN and NLC dispersions and gels enriched with SLN and NLC possessed a sustained drug release over period of 24 h but the sustained effect was more pronounced with the SLN and NLC gel.

Exosomes are the phospholipid-membrane-bound subpopulation of extracellular vesicles derived from the plasma membrane. The main activity of exosomes is cellular communication. In cancer, exosomes play an important rolefrom two distinct perspectives, one related to carcinogenesis and the other as theragnostic and drug delivery tools. The outer phospholipid membrane of Exosome improves drug targeting efficiency. . Some of the vital features of exosomes such as biocompatibility, low toxicity, and low immunogenicity make it a more exciting drug delivery system. Exosome-based drug delivery is a new innovative approach to cancer treatment. Exosome-associated biomarker analysis heralded a new era of cancer diagnostics in a more specific way. This Review focuses on exosome biogenesis, sources, isolation, interrelationship with cancer and exosome-related cancer biomarkers, drug loading methods, exosome-based biomolecule delivery, advances and limitations of exosome-based drug delivery, and exosome-based drug delivery in clinical settings studies. The exosome-based understanding of cancer will change the diagnostic and therapeutic approach in the future.

The advent of the "Green Revolution" was a great success in significantly increasing crop productivity. However, it involved high ecological costs in terms of excessive use of synthetic agrochemicals, raising concerns about agricultural sustainability. Indiscriminate use of synthetic pesticides resulted in environmental degradation, the development of pest resistance, and possible dangers to a variety of nontarget species (including plants, animals, and humans). Thus, a sustainable approach necessitates the exploration of viable ecofriendly alternatives. Plant-based biopesticides are attracting considerable attention in this context due to their target specificity, ecofriendliness, biodegradability, and safety for humans and other life forms. Among all the relevant biopesticides, plant essential oils (PEOs) or their active components are being widely explored against weeds, pests, and microorganisms. This review aims to collate the information related to the expansion and advancement in research and technology on the applications of PEOs as biopesticides. An insight into the mechanism of action of PEO-based bioherbicides, bioinsecticides, and biofungicides is also provided. With the aid of bibliometric analysis, it was found that ~75% of the documents on PEOs having biopesticidal potential were published in the last five years, with an annual growth rate of 20.51% and a citation per document of 20.91. Research on the biopesticidal properties of PEOs is receiving adequate attention from European (Italy and Spain), Asian (China, India, Iran, and Saudi Arabia), and American (Argentina, Brazil, and the United States of America) nations. Despite the increasing biopesticidal applications of PEOs and their widespread acceptance by governments, they face many challenges due to their inherent nature (lipophilicity and high volatility), production costs, and manufacturing constraints. To overcome these limitations, the incorporation of emerging innovations like the nanoencapsulation of PEOs, bioinformatics, and RNA-Seq in biopesticide development has been proposed. With these novel technological interventions, PEO-based biopesticides have the potential to be used for sustainable pest management in the future.

A new sequence of pyrazole derivatives (1-6) was synthesized from condensation technique under utilizing ultrasound irradiation. Synthesized compounds were characterized from IR, (1)H NMR, (13)C NMR, Mass and elemental analysis. Synthesized compounds (1-6) were screened for antimicrobial activity. Among the compounds 3 (MIC: 0.25 μg/mL) was exceedingly antibacterially active against gram negative bacteria of Escherichia coli and compound 4 (MIC: 0.25 μg/mL) was highly active against gram positive bacteria of Streptococcus epidermidis compared with standard Ciprofloxacin. Compound 2 (MIC: 1 μg/mL) was highly antifungal active against Aspergillus niger proportionate to Clotrimazole. Synthesized compounds (1-6) were screened for anti-inflammatory activity and the compound 2-((5-hydroxy-3-methyl-1H-pyrazol-4-yl)(4-nitrophenyl)methyl)hydrazinecarboxamide (4) was better activity against anti-inflammatory when compared with standard drugs (Diclofenac sodium). Compounds (2, 3 and 4) are the most important molecules and hence the need to develop new drugs of antibacterial, antifungal and anti-inflammatory agents.

Eucalyptus globules belonging to the Myrtaceae family was explored for the synthesis of zinc oxide nanoparticles and for biological applications. The aqueous extract of the synthesized zinc nanoparticles (ZnNPs) was characterized using UV-visible spectrophotometer, FTIR, SEM and TEM. The aqueous broth was observed to be an efficient reducing agent, leading to the rapid formation of ZnNPs of varied shapes with sizes ranging between 52–70 nm. In addition, antifungal activity of the biosynthesized ZnNPs was evaluated against major phytopathogens of apple orchards. At 100 ppm of ZnNPs, the fungal growth inhibition rate was found to be 76.7% for Alternaria mali, followed by 65.4 and 55.2% inhibition rate for Botryosphaeria dothidea and Diplodia seriata, respectively. The microscopic observations of the treated fungal plates revealed that ZnNPs damages the topography of the fungal hyphal layers leading to a reduced contraction of hyphae. This considerable fungicidal property of ZnNPs against phytopathogenic fungi can have a tremendous impact on exploitation of ZnNPs for fungal pest management and ensure protection in fruit crops.

The purpose of this research was to investigate novel particulate carrier systems such as solid lipid nanoparticles (SLN) and nanostructured lipid carrier (NLC) for transdermal delivery of nitrendipine (NDP). For this investigation, four different gel-forming agents were selected for hydrogel preparation. Aqueous dispersions of lipid nanoparticles made from trimyristin (TM) were prepared by hot homogenization technique followed by sonication and then incorporated into the freshly prepared hydrogels. The particle size was analyzed by photon correlation spectroscopy (PCS) using Malvern zetasizer, which shows that for all the tested formulations, more than 50% of the particles were below 250 nm after 90 days of storage at room temperature. DSC analysis was performed to characterize the state of drug and lipid modification. Shape and surface morphology were determined by scanning electron microscope (SEM) and transmission electron microscope (TEM), which revealed fairly spherical shape of the formulations. The antihypertensive activity of the gels in comparison with that of oral NDP was studied using desoxy corticosterone acetate (DOCA)-induced hypertensive rats. It was observed that both carbopol SLN (A1) and carbopol NLC (B1) gels significantly controlled hypertension from the first hour (p < .05). The developed gels increased the efficacy of NDP for the therapy of hypertension. Both the SLN and NLC dispersions and the gels enriched with SLN and NLC possessed a sustained drug release over a period of 24 h, but the sustained effect was more pronounced with the SLN and the NLC gel formulations. Further, they were evaluated for zeta potential, entrapment efficiency, in vitro release, ex vivo permeation, and skin irritation studies.

Abstract The green methodologies of nanoparticles with plant extracts have received an increase of interest. Copper oxide nanoparticles (CuO NPs) have been utilized in a many of applications in the last few decades. The current study presents the synthesis of CuO NPs with aqueous extract of Morinda citrifolia as a stabilizing agent. The leaf extract of Morinda citrifolia was mixed with a solution of copper sulphate (CuSO 4 ·5H 2 O) and sodium hydroxide as a catalyst. UV–visible spectroscopy, FTIR, XRD, SEM, TEM, and EDAX analysis were performed to study the synthesized CuO NPs. Particle size distribution of the synthesized CuO NPs have been measured with dynamic light scattering. The CuO NPs synthesized were highly stable, sphere-like, and have size of particles from 20 to 50 nm. Furthermore, as-formed CuO NPs shown strong antibacterial activity against the Gram-positive bacteria ( Bacillus subtilis, and Staphylococcus aureus ), and Gram-negative bacteria ( Escherichia coli ). CuO NPs revealed a similar trend was analysed for antifungal activity. The zone of inhibition for the fungi evaluated for Aspergillus flavus (13.0 ± 1.1), Aspergillus niger (14.3 ± 0.7), and Penicillium frequentans (16.8 ± 1.4). According to the results of this investigation, green synthesized CuO NPs with Morinda citrifolia leaf extract may be used in biomedicine as a replacement agent for biological applications.

Nanotechnology is a science of producing and utilizing nanosized particles that are measured in nanometers. The unique size-dependent properties make the nanoparticles superior and indispensable as they show unusual physical, chemical, and properties such as conductivity, heat transfer, melting temperature, optical properties, and magnetization. Taking the advantages of these singular properties in order to develop new products is the main purpose of nanotechnology, and that is why it is regarded as "the next industrial revolution." Although nanotechnology is quite a recent discipline, there have already high number of publications which discuss this topic. However, the safety of nanomaterials is of high priority. Whereas toxicity focuses on human beings and aims at protecting individuals, ecotoxicity looks at various trophic organism levels and intend to protect populations and ecosystems. Ecotoxicity includes natural uptake mechanisms and the influence of environmental factors on bioavailability (and thereby on toxicity). The present paper focuses on the ecotoxic effects and mechanisms of nanomaterials on microorganisms, plants, and other organisms including humans.

A Wireless Sensor Network (WSN) aided by the Internet of Things (IoT) is a collaborative system of WSN systems and IoT networks are work to exchange, gather, and handle data. The primary objective of this collaboration is to enhance data analysis and automation to facilitate improved decision-making. Securing IoT with the assistance of WSN necessitates the implementation of protective measures to confirm the safety and reliability of the interconnected WSN and IoT components. This research significantly advances the current state of the art in IoT and WSN security by synergistically harnessing the potential of machine learning and the Firefly Algorithm. The contributions of this work are twofold: firstly, the proposed FA-ML technique exhibits an exceptional capability to enhance intrusion detection accuracy within the WSN-IoT landscape. Secondly, the amalgamation of the Firefly Algorithm and machine learning introduces a novel dimension to the domain of security-oriented optimization techniques. The implications of this research resonate across various sectors, ranging from critical infrastructure protection to industrial automation and beyond, where safeguarding the integrity of interconnected systems are of paramount importance. The amalgamation of cutting-edge machine learning and bio-inspired algorithms marks a pivotal step forward in crafting robust and intelligent security measures for the evolving landscape of IoT-driven technologies. For intrusion detection in the WSN-IoT, the FA-ML method employs a support vector machine (SVM) machine model for classification with parameter tuning accomplished using a Grey Wolf Optimizer (GWO) algorithm. The experimental evaluation is simulated using NSL-KDD Dataset, revealing the remarkable enhancement of the FA-ML technique, achieving a maximum accuracy of 99.34%. In comparison, the KNN-PSO and XGBoost models achieved lower accuracies of 96.42% and 95.36%, respectively. The findings validate the potential of the FA-ML technique as an active security solution for WSN-IoT systems, harnessing the power of machine learning and the Firefly Algorithm to bolster intrusion detection capabilities.

This study aims to optimize the input parameters such as mass fraction and particle size of SiC along with depth of cut, feed and cutting speed in the milling of Al5059/SiC/MoS2. The hybrid metal matrix composites are generally fabricated by reinforcing of different sizes (10, 20, 40 μm) of SiC with aluminium at a different levels (5%,10% &15%) whereas the MoS2 addition is fixed as 2%. The effect of each control factor on response variables are analyzed through Taguchi S/N ratio method. Also, the most significant method for prediction of response parameters is satisfied by ANN model than the regression model. Analysis of variance (ANOVA) results envisage that mass fraction of SiC, feed rate is the most domineering factor on response variable.

The strategy of World Health Organization is to develop efficient and inexpensive vaccine against various infectious diseases amongst children's population. Vaccination is considered as the most cost effective health intervention known to public. Since 90 years various substances have been added in vaccine formulation but still alum is considered as the safest adjuvant for human use licensed by United States Food and Drug Administration. MF 59 and ASO4 are the adjuvants were developed recently and approved for human use. Due to poor adjuvancity, conventional vaccines require multiple recall injection at approximately time intervals to attain optimal immune response. For past approximately two decades the vaccine research has been focused towards the alternation of alum type of adjuvant in order to increase the immunogenicity. The development of new vaccines, is more efficacious or easier to deliver, or both have become an area of research that can certainly benefit from controlled release technology. Especially, the conversion of multiple administration vaccine into single administration vaccine may represent an improved advancement towards the betterment of human health care and welfare. Biodegradable polymer microparticles have been evaluated for delivering antigens in native form, sustained release keeping in mind the safety aspects. In this article we review the overall concept of adjuvants in vaccine technology with special focus towards the prospects of controlled release antigens.

Nitrogen-doped carbon dot decorated zinc oxide nanoparticles (N-CDs@ZnO composite) were successfully fabricated by an economical wet-impregnation method and used as a photocatalyst for the degradation of aqueous methylene blue (MB) dye under UV-light at room temperature. The chemical composition and morphological features of the prepared N-CDs@ZnO composite were characterized by attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and field emission scanning electron microscopy (FESEM). The photodegradation capability of the N-CDs@ZnO composite was compared with that of bare ZnO nanoparticles, under identical experimental conditions. The results show that the N-CDs@ZnO composite exhibits notably higher photocatalytic activity (degradation efficiency over 99%, 60 min) compared to bare ZnO nanoparticles (75%, 60 min) towards the degradation of MB under UV-light irradiation. Besides, the degradation obeyed the pseudo-first-order kinetics model with a photocatalytic rate constant (k) of 0.0557 min-1, which was ∼2.3 times higher than that of bare ZnO nanoparticles (0.0240 min-1). The crucial roles of N-CDs in the enhancement of the photocatalytic activity of the N-CDs@ZnO composite arise because the N-CDs can efficiently absorb UV-light and trap electrons, thus hindering the recombination of the photo-generated electron-hole pairs and also suppressing the photocorrosion of the ZnO nanoparticles in the N-CDs@ZnO composite. The N-CDs@ZnO composite not only showed good photocatalytic activity but also had good stability since the photocatalytic activity did not significantly decrease after three cycling tests. The present study shows that the N-CDs@ZnO composite can be considered as an ideal photocatalyst in the field of dye degradation. Overall, the present approach obeys green chemistry principles with the simple construction of the N-CDs@ZnO composite and the composite holds promise for the development of efficient photocatalytic systems.

Lean manufacturing initiative is being followed by various organizations in the recent years which mainly focuses on improving the efficiency of operations by eliminating and reducing wastes. This paper aimed to explain the implementation of lean manufacturing techniques in the crankshaft manufacturing system at an automotive manufacturing plant located in south India.. A multi criteria decision making model, analytical hierarchy process is applied to analyze the decision making process in the manufacturing system. The objective of the case industry was to increase the export sales. Lean manufacturing system was selected to meet the company“s quality, cost and delivery targets. Crankshaft was manufactured in a single piece flow system with the low cost machines developed indigenously and the results are that the crankshafts have passed the testing, validation and approval by the customer to produce any variant in the company. After implementing lean manufacturing system, the manufacturing lead time reduced by forty percent, defects were reduced, higher process capability achieved, quick response to the customer demand in small lots were achieved.

The present work is planned to investigate the fundamental properties of the novel plant fiber extracted from the bark of Acacia nilotica L. tree. The various chemical compositions of the Acacia nilotica L. fiber (ANF) such as cellulose (56.46 wt. %), hemicelluloses (14.14 wt. %), lignin (8.33 wt. %) and ash content (4.95 wt. %) were identified through the chemical analysis. The maximum degradation temperature of ANF (339°C) was determined by the thermogravimetric analysis. The crystallinity index (44.82%) and crystalline size (3.21 nm) of the ANF were calculated by the X-ray diffraction analysis. The surface topography of ANF was estimated through the atomic force microscope. The density of ANF was identified as a value of 1165 kg/m3 which is comparatively lower than the other renowned fibers such as Acacia leucophloea (1385 kg/m3) and Jute (1460 kg/m3); this would be confirmed with all above characterization results that is an appropriate material to fabricate the green composites.

In recent era, the creation of electronic contraptions is expanding step by step, which leads to tremendous electronic waste. This is the condition drives as a result of the current individuals expecting new innovation in a brief time. This circumstance makes the manufacturers in a circumstance to create the new item in a brief time, so the current items need to either be disposed or dismantled. In this circumstance the manufactures wanted to re-manufacture the end-of-life (E-O-L) items to meet the component necessity in the new items production. In this sense in our previous work we exhibited a methodology to choose the optimal number of take back product, so that the aggregate expense needed for the reverse logistic (RL) can be lessened. In this paper, we exhibited a novel methodology for the RL operation of E-O-L items, in view of an optimal scheduling algorithm. In the previous work we have located the optimal number of take back E-O-L products for the disassembly-to-order (D-T-O), and this paper displayed the procedure to legitimately schedule the machines to disassemble the products, so that the aggregate time as well as the total cost needed for the RL operation can be diminished. In the proposed structure artificial bee colony (ABC) algorithm is utilized. The proposed framework drives the preferred performance over the existing scheduling algorithms.

Image processing is a technique which is used to derive information from the images. Segmentation is a section of image processing for the separation or segregation of information from the required target region of the image. There are different techniques used for segmentation of pixels of interest from the image. Active contour is one of the active models in segmentation techniques, which makes use of the energy constraints and forces in the image for separation of region of interest. Active contour defines a separate boundary or curvature for the regions of target object for segmentation. The contour depends on various constraints based on which they are classified into different types such as gradient vector flow, balloon and geometric models. Active contour models are used in various image processing applications specifically in medical image processing. In medical imaging, active contours are used in segmentation of regions from different medical images such as brain CT images, MRI images of different organs, cardiac images and different images of regions in the human body. Active contours can also be used in motion tracking and stereo tracking. Thus, the active contour segmentation is used for the separation of pixels of interest for different image processing.