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AbstractHere, a simple, one step, lucrative and green synthesis of Cassia fistulaleaf extract inspired antibacterial silver nanoparticles (CF-SNPs) was provided. Characterization of these CF-SNPs were achieved by using various spectroscopic techniques for instance Ultraviolet Visible (UV-Vis) Spectroscopy, Fourier-Transform Infrared (FTIR) Spectroscopy, Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM) and Energy Dispersive X-ray (EDX). The effective antibacterial action of the CF-SNPs was checked against Escherichia coli(E. Coli) DH5-Alpha where MIC was 1.6 nM. Anticancer dynamism of the CF-SNPs was also tested in opposition to skin melanoma, A375 cell lines in which 4.4 nM was IC50. The binding proneness of HSA towards CF-SNPs was investigated by means of UV-Vis Spectroscopy, Fluorescence Spectroscopy, Time Resolved Fluorescence Spectroscopy, Circular Dichroism (CD) Spectroscopy, Dynamic Light Scattering, and Isothermal Titration Colorimetry (ITC). CD spectroscopy established minor secondary structural exchange of HSA in HSA-CF-SNPs complex. ITC and Time Resolved Fluorescence Spectroscopy verified the static type quenching mechanism involved in HSA-CF-SNPs complex. The binding constant was 3.45 × 108M−1at 298.15K from ITC study. The thermodynamic parameters showed that the interaction was occurred spontaneously by the hydrophilic forces and hydrogen bonding.Communicated by Ramaswamy H. Sarma

Mobile banking is promoted as a powerful channel for reaching out to the masses for their banking needs, yet its adoption remains slow. Existing studies identify perceived safety, perceived ease of use, perceived usefulness, financial literacy, and demographic characteristics as key determinants of mobile banking adoption. However, given the low financial literacy of rural adults, handholding, defined as the provision of support to adopt mobile banking, could be an important component of ‘facilitating conditions’ as recognised under the UTAUT framework. To empirically examine this relationship, partial least square structural equation modelling (PLS-SEM) was employed using data from a primary survey conducted in eight villages in West Bengal, India. After controlling for all the variables traditionally identified, the findings confirm the role of handholding, both institutional and informal, in catalysing the transition to mobile banking in rural areas. Focussing on tech-savvy youngsters during financial literacy programmes may help in increasing the migration to mobile banking through the informal handholding channel.

Memristors that mimic brain functions are crucial for energy-efficient neuromorphic devices. Ion channels that emulate biological synapses are still in the early stages of development, especially the tunability of memory states. Here, we demonstrate that cations such as K+, Na+, Ca2+, and Al3+intercalated in the interlayer spaces of vermiculite result in highly confined channels of size 3–5 Å. They host exotic memristor properties through ion exchange dynamics, even at high salt concentrations of 1 M. The bipolar memristor characteristics observed are tunable with frequency, geometric asymmetry, ion concentration, and intercalants. Notably, we observe polarization-flipping memristor behavior in two cases: one with Al3+ions and another with devices having a geometric asymmetry ratio greater than 15. This inversion is attributed to the overscreening of counterions due to their accumulation at the channel entrance. Our results suggest that ion exchange dynamics, ion–ion interactions, and ion accumulation/depletion mechanisms, particularly with multivalent ions, can be harnessed to develop advanced memristor devices.

We describe the 18F-fluorodeoxyglucose positron emission tomography/contrast enhanced computed tomography (FDG PET/CECT) images of a 63-year-old male who complained of back pain and was suspected of multiple myeloma based on magnetic resonance imaging. PET/CECT suggested the FDG avid lesion involving prostate, accompanied by multiple lytic skeletal lesions with no evidence to suggest other possible primary site. A bone marrow biopsy suggested a metastatic adenocarcinoma of primary prostatic origin. Post anti-androgen therapy follow-up FDG PET/CT revealed reductions in the metabolic activities and soft tissue components of most of the metastatic skeletal lesions. These images highlight the possible indication of FDG PET/CT in evaluation of prostatic malignancy in era of 68Ga-PSMA. Keywords: Anti androgen therapy, FDG petct, lytic skeletal metastases, Prostate carcinoma, Author(s): Shantanu Pande (corresponding author) [1]; Nihit Mhatre [2]; Ipsita Dhal [3] INTRODUCTION Fluorodeoxyglucose (FDG) is a glucose analog, and most tumors demonstrate increased glucose metabolism because of upregulation of [...]

Climate change, land degradation, and limited land and water resources have challenged our ability to meet the food demand of a rapidly growing population. To tackle this challenge, modern agricultural systems are relying on new technologies like the Internet of Things (IoT) to improve agricultural productivity and resource use efficiency. Although IoT has gained considerable attention in the last few years, the key concepts of IoT and their applicability across different domains of agriculture are still new to many researchers, practitioners, managers, and policymakers. In this paper, we provide a comprehensive review of the use of different IoT platforms, wireless sensor networks, and other associated technologies like remote sensing, cloud computing, and big data analytics in digital agriculture. The review also explores the use of communication technologies, microcontrollers, and machine learning in smart irrigation and decision support systems. The necessity of interoperability (data transfer and communication without human interference) among devices is discussed in detail with regard to facilitating and exchanging agricultural data more effectively. The discussion also includes opportunities and challenges in standardizing IoT; developing energy‐efficient and affordable technologies; and improving data collection, transfer, storage, processing, security, anonymity, and privacy. This paper further calls for collaborative research in sensor and communication technologies in the agricultural sector. Different platforms, sensors, and structures of IoT in digital agriculture were reviewed.The application of IoT in data management, interoperability, and precision farming was reviewed.Potential of IoT to improve agricultural quality and productivity was highlighted.Challenges and opportunities of IoT in digital agriculture were discussed.

In this study, an improved version of aquila optimizer (AO) known as EHAOMPA has been developed by using the marine predators algorithm (MPA). MPA is a recent and well-behaved optimizer with a unique memory saving and fish aggregating devices mechanism. At the same time, it suffers from various defects such as inadequate global search, sluggish convergence, and stagnation of local optima. However, AO has contented robust global exploration capability, fast convergence speed, and high search efficiency. Thus, the proposed EHAOMPA aims to complement the shortcomings of AO and MPA while bringing new features. Specifically, the representative-based hunting technique is incorporated into the exploration stage to enhance population diversity. At the same time, random opposition-based learning is introduced into the exploitation stage to prevent the optimizer from sticking to local optima. This study tests the performance of EHAOMPA’s on 23 standard mathematical benchmark functions, 29 complex test functions from the CEC2017 test suite, six constrained industrial engineering design problems, and a convolutional neural network hyperparameter (CNN-hyperparameter) optimization for Corona Virus Disease 19 (COVID-19) computed tomography-image detection problem. EHAOMPA is compared with four existing optimization algorithm types, achieving the best performance on both numerical and practical issues. Compared with other methods, the test function results demonstrate that EHAOMPA exhibits a more potent global search capability, a higher convergence rate, increased accuracy, and an improved ability to avoid local optima. The excellent experimental results in practical problems indicate that the developed EHAOMPA has great potential in solving real-world optimization problems. The combination of multiple strategies can effectively improve the performance of the algorithm. The source code of the EHAOMPA is publicly available at https://github.com/WangShuang92/EHAOMPA.Graphical Abstract

The field of ‘women in science’ in India is evolving with policies that could support ending gender discrimination in the practice and culture of science. Gender inclusivity in science is a complex phenomenon, and it differs in forms and scale across institutions. This complexity has invoked feminist scholars, governments, and organisations to critically engage with issues of gender inequities in science. This article, based on a sample study, seeks to understand the idea of gender inclusivity in science, and the discrimination and marginalisation women scientists face, while exploring how they negotiate institutional spaces and address specific and unique challenges in their everyday reality.

Although there is no dearth of international and national level studies that have investigated the effects of clean energy for gender empowerment, until now no study has attempted to capture [...]

Carbon monoxide (CO) is one of the most poisonous gases present in the atmosphere. It also called the silent killer of twenty-first century. CO is produced into the environment by incomplete combustion of carbon containing compounds. It causes lots of people die every year including the firefighters. The main aim of this work to find out the literature study of standard respiratory escape masks for ambient temperature CO oxidation purposes. The research under concern is applicable for developing respiratory protection systems for military, mining, and space devices. There are many catalysts which are active for this process under different conditions. Among these catalysts, the hopcalite (CuMnOx) is one of the best-known catalysts for low-temperature CO oxidation. It is a low-cost, easily available, and highly stable catalyst. The hopcalite catalyst is active for a longer time and would be tolerant of moisture and impurities in reacting gases. The catalyst surface and reacting gases forever play a key role in catalytic reactions. Hopcalite is an ideal catalyst for use in next-generation respiratory protection devices. Although there are numerous research papers present on this topic until now no one review are present for demanding this issue. So there is a space in this area; it has been made an attempt to seal this hole by this review. Graphical abstractSummary• To develop a standard fire escape masks for protection of respiratory systems in military, mining, and firefighting, etc.

The hopcalite (CuMnOx) catalyst is a well-known catalyst for CO oxidation at a low temperature and it is synthesized by the co-precipitation method with different types of precursors. Activity of the CuMnOx catalysts for CO oxidation is strongly dependent upon the combination of precursors, ranking in order {Mn(Ac)2+ Cu(NO3)2} > {Mn(Ac)2+ Cu(Ac)2} > {Mn(NO3)2+ Cu(NO3)2} > {Mn(NO3)2+ Cu(AC)2}. All the precursors were precipitated by KMnO4solution and the precursors mostly comprised of MnO2, Mn2O3and CuO phases. Keeping the same precipitant while changing the precursors caused a change in the lattice oxygen mobility which influenced the CO oxidation activity. The calcination strategy of the precursors has great influence on the activity of resulting catalysts. The reactive calcination (RC) conditions produce multifarious phenomena of CO oxidation and the precursor decomposition in a single-step process. The activity order of the catalysts for CO oxidation was as follows: reactive calcination (RC) > flowing air > stagnant air. Therefore, we recommended that the RC route was the more appropriate calcination route for the production of highly active CuMnOx catalysts. All the catalysts were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, Brunauer–Emmett–Teller analysis, X-ray photoelectron spectroscopy and scanning electron microscopy technique. The influence of precursors on the structural properties and the catalytic activity of co-precipitation derived binary CuMnOx catalysts for CO oxidation has been investigated.

Exosomes have emerged as a promising tool for the delivery of drugs and genetic materials, owing to their biocompatibility and non-immunogenic nature. However, challenges persist in achieving successful oral delivery due to their susceptibility to degradation in the harsh gastrointestinal (GI) environment and impeded transport across the mucus-epithelium barrier. To overcome these challenges, we have developed high-purity bovine milk exosomes (mExo) as a scalable and efficient oral drug delivery system, which can be customized by incorporating hydrophilic and zwitterionic motifs on their surface. In our study, we observed significantly improved transport rates by 2.5–4.5-fold in native porcine intestinal mucus after the introduction of hydrophilic and zwitterionic surface modifications, as demonstrated by transwell setup and fluorescence recovery after photobleaching (FRAP) analysis. Remarkably, mExo functionalized by a block peptide (BP), consisting of cationic and anionic amino acids arranged in blocks at the two ends, demonstrated superior tolerability in the acidic gastric environment (with a protein recovery rate of 84.8 ± 7.7%) and exhibited a 2.5-fold increase in uptake by intestinal epithelial cells. Furthermore, both mExo and mExo-BP demonstrated successful intracellular delivery of functional siRNA, resulting in up to 65% suppression of the target green fluorescence protein (GFP) gene expression at a low dose of siRNA (5 pmol) without causing significant toxicity. These findings highlight the immense potential of modifying mExo with hydrophilic and zwitterionic motifs for effective oral delivery of siRNA therapies.

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The study focuses on the in vitro and in vivo evaluation of the developed gentamicin sulphate (GS)-loaded poly lactic-co-glycolic acid (PLGA) nanoparticle (PNP)-based pullulan film (PNP-F). Sterilization being an essential pre-requisite for the dosage form was carried out using ethylene oxide. Post-sterilization, PNP-F was evaluated for mechanical properties, percentage drug loading, antimicrobial effectiveness study, test for sterility and in vitro dissolution study using Strat-M® membrane. In vitro dissolution study revealed that GS gradually released from PNP-F and the highest cumulative percentage drug release was found to be 86.76 ± 0.03% at 192 h. Wound healing assay was performed to study the effect of PNP-F over migratory potential of dermal fibroblast cells (NIH-3T3) in the presence of micro-organisms, Pseudomonas aeruginosa(PA) and Staphylococcus aureus(SA). PNP-F inhibited the growth of PA and SA, allowing the growth of fibroblast cells indicating its suitability for application. In vivo study of surgical site was performed by superficial incision model in Wistar rats. Measurement of in vivo incision healing confirmed faster wound healing in the incision which received PNP-F compared to marketed cream containing GS.

The noble metal catalysts are most commonly considered to be used in an automobile as a catalytic converter. Palladium (Pd) is a highly active catalyst for carbon monoxide (CO) oxidation in platinum group metals. It is very active for low-temperature CO oxidation if dispersed on suitable metal oxides and composite oxides. The oxidized Pd metal nanocatalyst has been applied more actively than the completely reduced particles. The performance of Pd oxide nanocatalysts strongly depends upon the surface structure, number of active sites and various Pd–O interactions. Palladium is an ideal catalyst not only for the automobile industry through cross-coupling reactions but also for low-temperature catalytic oxidation of CO. The Pd metal is more resistant for sulfur and potassium poisoning, and they are chemically sensitive and degraded rapidly in the presence of fuel impurities. The higher activity of Pd nanocatalyst was attributed to the small particle size and higher dispersion over Pd support. The chemisorptions of CO on Pd catalysts were studied in this review. The results obtained from this study will provide the scientific basis for the future design of Pd-based oxidation catalysts.

An autonomous Vehicle to Vehicle (V2V) communication mode, which allows V2V communication in out of eNB (Evolved Node B) coverage areas, has been recently introduced into the Long Term Evolution (LTE) standard. Recent research has studied the performance of this LTE V2V autonomous mode for an urban intersection use case, where non-line-of-sight (NLOS) communication links are present and it is observed that the overall message transmission performance in LTE V2V is found to degrade drastically in NLOS link conditions. To improve the performance, a vehicle-assisted relaying strategy was proposed. In this scheme, at each time instance, distance of each vehicle from intersection point is computed. Then the vehicle close to the intersection point is nominated as relaying vehicle and will rebroadcast the BSMs (Basic Safety Message) in a selective manner. However, security aspects while relaying the BSM is not being addressed in the suggested model. We cannot reject the possibility that a vehicle can be malicious. A malicious vehicle can manipulate its distance from the intersection point, thereby nominating itself as the relaying vehicle with malicious motives such as to use extra infrastructural faciltiy, curiosity in the messages sent by other vehicles, etc. This work proposes a secure algorithm for finding the most appropriate relaying vehicle to address this security vulnerability so that a vehicle can no longer falsify its location information.

This study discusses the insights derived from a primary survey conducted in urban centres in the Indian state of Odisha located in the eastern region of India, which is generally perceived as less developed than other regions of the country. There is evidence that Odisha is catching up with the digital revolution, and the survey reveals significant achievements in terms of people’s general awareness of various digital payment systems and access to smartphones. The use of digital payments has increased with increasing education and income levels, and the proportion of cash transactions has declined post-COVID-19. Major barriers to the wider adoption of digital payments in the state include network issues such as poor internet connectivity, low internet speed and lack of acceptability. The empirical findings of this study establish that receiving incomes into bank accounts instead of in cash increases the affinity towards paying digitally.

A simple electrochemical technique was employed to synthesize nanocorn electrolytic manganese dioxide (MnO2) (EMD) in the presence of the structure-directing agent poly(vinylpyrrolidone) (PVP) at the optimum concentration in an aqueous acidic manganese sulfate bath. X-ray diffraction and scanning electron microscopy analyses confirmed the formation of γ-manganese dioxide with nanocorn-shaped crystals at the optimum concentration – namely, 20 mg/l PVP. The finely ground material was successfully employed in the removal of the toxic dyes Chicago sky blue (CSB) and malachite green (MG) from aqueous solution. Various process parameters such as different adsorbents, adsorbent dose, contact time, initial dye concentration and pH were varied and optimized for both dyes. It was found that EMD20PVPshowed 99.61% adsorption efficiency at an optimum dose of 0.04 g/20 ml of the 100 mg/l CSB dye solution at room temperature within 20 min. However, the same EMD20PVPsample showed 99.5% adsorption efficiency at an optimum dose of 0.07 g/20 ml of the 100 mg/l MG dye solution at room temperature within 120 min. From the adsorption kinetics study, it was concluded that the adsorption process follows pseudo-second-order kinetics and the adsorption isotherm confirms that the reaction follows Langmuir adsorption for both dyes.

AbstractGeopolymers are comparatively new generation of construction materials made from industrial by-products and supplemental cementitious materials (SCM) with high silica and alumina content. Currently, the demand for SCM has enlarged significantly based on global climate change action plans, so its use through the geopolymerisation process has attracted the attention of researchers from all over the world. This article focuses on the main mechanisms of construction and demolition (C&D) waste on the resulting physical, mechanical and durability properties of geopolymer concrete (GPC) on fresh and hardened state. This article deals with the partial substitution of coarse aggregates (CA) by C&D waste on GPC. The partial replacement of CA was carried out in five proportions, that is, 0%, 10%, 20%, 30% and 40%, and every sample was analysed to determine the slump cone, the compressive strength, flexural strength and splitting tensile strength for 7 and 28 d. It is observed that the percentage variation of C&D waste influences the hardening properties of GPC. The analysis of Finite element (FE) is taken by using FE software ANSYS.

Flake-shaped franklinite (ZnFe2O4) nanoparticles were successfully prepared by using the co-precipitation method. The phase and crystallinity of the synthesised franklinite nanoparticles were studied by X-ray diffraction. The scanning electron microscopy results revealed that the flake-shaped entities were formed in combination with rod-shaped nanomaterial. The band gap of the synthesised franklinite nanoparticles was found to be ∼2.14 eV by ultraviolet–visible diffuse reflectance spectroscopy measurements, indicating that this material absorbs visible light (λmax= 579.37 nm). The ferrite nanoparticles were successfully employed as a photocatalytic material for the degradation of the dye malachite green in an aqueous medium with ∼99% efficiency under visible light irradiation.

3D printing has been recognized to be such a game-changer in manufacturing that it has now permeated virtually every aspect of the industry, including mould and die casting. A thorough examination of 3D printing's past, present and future in the business is provided here. Casting procedures may be enhanced or drastically altered by 3D printing. The design of goods, assemblies, and parts will be transformed by 3D printing, which is more than just a manufacturing technology. With the aid of 3D printing, sand casting is a technique that can make complex components out of almost any metal alloy at a reasonable cost. Using this integration, producers may build massive components in the least amount of time. It has also established a distinctive place in other casting elements; Examples include the ceramic shell, sand mould sand core, and wax pattern, we'll learn more about sand casting and 3D printing this week.

In the current study, finger millets (Eleusine coracana) served as the raw material to assess the impacts of malting and Lactiplantibacillus plantarum-mediated fermentation. Post-fermentation analysis revealed a substantial elevation in the concentration of 5-methyltetrahdrofolate (5-MTHF) (bioactive form of folate) in the fermented samples, UM-F (unmalted and fermented) and M-F (malted and fermented) with 137.28 and 147.84 μg/100g, respectively. Furthermore, malting followed by fermentation collectively reduced the spiked pesticides, lindane, and chlorpyrifos from the original concentration of 330.83 ppb and 295.12 ppb in the UM-UF (unmalted and unfermented) samples to 44.44 ppb (86.53% decrease) and 12.13 ppb (95.88% decrease), respectively. In silicoinvestigation envisaged the role of two enzymes, alcohol dehydrogenase and alkaline phosphatase of L. plantarumin the disintegration of lindane and chlorpyrifos, respectively which was subsequently validated by quantifying the enzymes in the fermentation medium (alkaline phosphatase obtained in M-F was 1.60 U/mL and the alcohol dehydrogenase produced was 44.02 U/mg protein). Biochemical analyses, thermal gravimetric analysis, infrared spectroscopy, and X-ray diffraction studies reported significant transformations among the samples, UM-UF, UM-F, M-UF (malted and unfermented millet), and M-F, which indicates the role of malting and fermentation and the enzymes involved in the processes.

Partitional clustering techniques such as K-Means (KM), Fuzzy C-Means (FCM), and Rough K-Means (RKM) are very simple and effective techniques for image segmentation. But, because their initial cluster centers are randomly determined, it is often seen that certain clusters converge to local optima. In addition to that, pathology image segmentation is also problematic due to uneven lighting, stain, and camera settings during the microscopic image capturing process. Therefore, this study proposes an Improved Slime Mould Algorithm (ISMA) based on opposition based learning and differential evolution’s mutation strategy to perform illumination-free White Blood Cell (WBC) segmentation. The ISMA helps to overcome the local optima trapping problem of the partitional clustering techniques to some extent. This paper also performs a depth analysis by considering only color components of many well-known color spaces for clustering to find the effect of illumination over color pathology image clustering. Numerical and visual results encourage the utilization of illumination-free or color component-based clustering approaches for image segmentation. ISMA-KM and “ab” color channels of CIELab color space provide best results with above-99% accuracy for only nucleus segmentation. Whereas, for entire WBC segmentation, ISMA-KM and the “CbCr” color component of YCbCr color space provide the best results with an accuracy of above 99%. Furthermore, ISMA-KM and ISMA-RKM have the lowest and highest execution times, respectively. On the other hand, ISMA provides competitive outcomes over CEC2019 benchmark test functions compared to recent well-established and efficient Nature-Inspired Optimization Algorithms (NIOAs).

With emergence of smart city concept, intelligent transportation becomes one of its key enablers, with navigation as an indispensable component. Vehicular ad hoc network (VANET) based systems emerge to provide navigation services to vehicle users, which is characterized by employing Roadside Units (RSUs) to collect road condition information from nearby vehicles. The querying vehicle exploits the information retrieved through the RSUs to determine an optimal route. We focus on addressing two key issues in such system. First, while querying, the destination of the vehicle user should not be leaked to the queried RSU and trusted authority (TA), which is likely to be misused. Second, the navigation process should be independent of participation of the centralized TA, which can be a single point of failure. To address these issues, this article proposes a security and privacy preserved intelligent vehicle navigation system, adopting a distributed approach, to retrieve navigation without revealing the destination. The security of the system has been thoroughly evaluated using an adversary model, BAN Logic and AVISPA tool. In addition, the performance of the proposed system has been evaluated, and compared with the existing systems. The comparison illustrates that the proposed system is computationally efficient than the existing systems.

Combining Data Envelopment Analysis and dynamic panel data methods, we find that adoption of digital payment technologies by Indian banks has helped enhance their cost efficiency. Instead of directly reducing the inputs used in intermediation, the gain in efficiency may be on account of cheaper availability of such inputs when banks go digital. These gains may stem from assimilation into the entire digital payments ecosystem, as opposed to piecemeal adoption of technology. We find both cost and technical efficiencies exhibiting persistence. Banks’ relative asset holdings in the industry, non-performing assets, cost of deposits and returns on advances and equity are other important variables that drive cost efficiency.

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2–4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein–Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

In the advent of increased transportation systems, the importance and growth of heavy vehicle movements and their applications play a significant role. The transportation sector involving heavy vehicles needs appropriate components for systematic movements. With the prominence of components utilised in heavy vehicle systems and power train mechanism, this paper develops novel variants of multi-level inverters for effective functioning of the vehicular system. Along with the classic multi-level inverter (MLI), new variants – modified multi-level inverter and reduced switch multi-level inverter are designed with complete operation based on their switching states and are implemented for a nine level output voltage module. The proposed inverter models for the heavy vehicle system is tested and validated based on the total harmonic distortion (THD). For each level and their switching states, THD is evaluated and the inverter performance is proved for its superiority for heavy vehicle system and their applicability in power train applications.

Biologic aggressiveness of OSCC (Oral Cavity Squamous Cell Carcinoma), has intrigued research in various prognosticating histopathological markers over past few decades. DOI (Depth of Invasion) is one such histopathological factor which affects outcomes and was included in the AJCC 8th edition TNM staging. Pattern of Invasion (POI) has been widely reported as an adverse prognostic factor associated with higher locoregional failure and poor prognosis. However, these factors are not utilized for treatment decision making and for outcome assessment.

In this work, we have established a simple, efficient, non-toxic, cost-effective and completely green strategy to synthesize carbon dots (CDs) using Mucuna pruriens(alkushi) seeds. Synthesized CDs through facile one-pot hydrothermal route has a spherical shape with an average diameter of 4.02 nm. Surface analysis of these CDs was performed utilizing XPS, FTIR, and zeta potential measurement, confirming the presence of –OH, -NH2, and –COOH groups. The obtained CDs exhibit excellent photostability, high quantum yield and possess outstanding water solubility. Moreover, these CDs provide high response for detection of Au3+ions through fluorescence quenching with a noticeable change in colour of the solution (colorimetric). The LOD was calculated to be 51.20 nM using 3σ/k rule. The mechanism of sensing was established through FTIR, florescence lifetime, UV and Isothermal Titration Calorimetry (ITC). These experiments indicate that a ground state complex formed between CDs and Au3+ions and subsequent reduction to Au0. The specificity towards Au3+ions was tested against different interfering ions and was implemented to analysis the real sample. The synthesized CDs have also the potential to be applied in temperature sensing application. The cytotoxicity and biocompatibility were evaluated against prostate cancer cell line (PC3cell) and a human lung fibroblast cell line (WI38 cell). Finally, Non-cytotoxic CDs were applied for live cell imaging and in vitrosensing of Au3+ions.

Purpose: Smooth and autonomous navigation of mobile robot in a cluttered environment is the main purpose of proposed technique. That includes localization and path planning of mobile robot. These are important aspects of the mobile robot during autonomous navigation in any workspace. Navigation of mobile robots includes reaching the target from the start point by avoiding obstacles in a static or dynamic environment. Several techniques have already been proposed by the researchers concerning navigational problems of the mobile robot still no one confirms the navigating path is optimal. Design/methodology/approach: Therefore, the modified grey wolf optimization (GWO) controller is designed for autonomous navigation, which is one of the intelligent techniques for autonomous navigation of wheeled mobile robot (WMR). GWO is a nature-inspired algorithm, which mainly mimics the social hierarchy and hunting behavior of wolf in nature. It is modified to define the optimal positions and better control over the robot. The motion from the source to target in the highly cluttered environment by negotiating obstacles. The controller is authenticated by the approach of V-REP simulation software platform coupled with real-time experiment in the laboratory by using Khepera-III robot. Findings: During experiments, it is observed that the proposed technique is much efficient in motion control and path planning as the robot reaches its target position without any collision during its movement. Further the simulation through V-REP and real-time experimental results are recorded and compared against each corresponding results, and it can be seen that the results have good agreement as the deviation in the results is approximately 5% which is an acceptable range of deviation in motion planning. Both the results such as path length and time taken to reach the target is recorded and shown in respective tables. Originality/value: After literature survey, it may be said that most of the approach is implemented on either mathematical convergence or in mobile robot, but real-time experimental authentication is not obtained. With a lack of clear evidence regarding use of MGWO (modified grey wolf optimization) controller for navigation of mobile robots in both the environment, such as in simulation platform and real-time experimental platforms, this work would serve as a guiding link for use of similar approaches in other forms of robots.

Multi-label Text Classification (MTC) is a challenging task in Natural Language Processing (NLP). The goal of the MTC task is to label a document with a set of labels. By incorporating various term weighting schemes in MTC, high dimensional feature space has been generated; due to that, multi-label learning algorithms face substantial problems in performing MTC tasks. To deal with these issues, Feature Selection (FS) approaches are effective solutions. This paper proposes a Lightweight Term-weighting FS (LwTwFS) approach based on a modified Chi-square (CHI) filter-based FS method to deal with this issue. The modified CHI approach works for Inter-Class Concentration (ICC) and Intra-Class Dispersion (ICD), and its strength has been increased by adding positive and negative correlations. A novel modified equation has been introduced to distribute the features among the categories (i.e., here, multi-label) in the corpus. The proposed modified CHI-based FS approach works on the term weighting-based Feature Extraction (FE) approach. Multi-Layer Perceptron (MLP) has been used in the classification phase due to the adaptive learning property, which refers to learning how to do tasks based on data provided during training or prior experience. We have used two publicly available multi-label corpora for experimental verification: the Arxiv Academic Paper Dataset (AAPD) and the Reuters Corpus Volume I (RCVI-V2). According to the results, in terms of performance, the LwTwFS methodology combined with the MLP classifier surpasses other combinations in terms of Jaccard Score (JS), Hamming Loss (HL), Ranking Loss (RL), Precision (Pr), Recall (Re), and F-micro and F-macro. For the AAPD corpus, the LwTwFS method achieves the best JS, HL, RL, Pr, F-micro, and F-macro values, which are 0.9636, 0.0121, 0.0303, 0.9636, 0.9882, and 0.9894. For the RCVI-V2 corpus, the LwTwFS method achieves the best JS, Pr, Re, F-micro, and F-macro values of 1.0000, and HL, RL values of 0.0000. Empirical results on widely used two benchmark multi-label text corpus show that LwTwFS achieves competitive performance, especially when labels are limited.

Cuckoo Search (CS) algorithm is a nature-inspired optimization algorithm (NIOA) with less control parameters that is stable, versatile, and easy to implement. CS has good global search capabilities, but it is prone to local optima problems. As a result, it may be possible to improve the classic CS algorithm's optimization capability. Centered on fuzzy set theory, this paper introduces an improved CS version. The population of solutions has been divided into two fuzzy sets, and each solution is assigned to one of the sets based on its fitness. The fuzzy collection centroids, global best solution advice, and Lévy distribution dependent mutation are all used to boost the population's solutions. With well-accepted objective functions such as Otsu inter class variance and Kapur's entropy, the experimental analysis has been conducted on the CEC-2014 test suite and image multi-level thresholding domain. The proposed fuzzy cuckoo search (FCS) algorithm is compared to the classical CS, PSO, FA, SMA, and BA algorithm and provides satisfactory results.

Breast histopathology image segmentation is a complex task due to indiscernibly correlated and noisy regions of interest. Breast histopathological images are composed of different types of cells. Some of these cells can be harmful for humans due to the presence of cancer. Under such circumstances, many segmentation techniques for automatic detection of cancer cells have been proposed considering clustering schemes. However, such clustering methodologies are sensitive to initial cluster centers, which promote false-positive solutions. This paper presents the use of the Whale Optimization Algorithm (WOA) for proper clustering segmentation of breast histopathological images to overcome clustering issues. Also, a rigorous comparative study is conducted among the proposed approach and several state-of-art Nature-Inspired Optimization Algorithms (NIOAs) and traditional clustering techniques. The numerical results indicate that the proposed approach outperforms the other utilized clustering methods in terms of precision, robustness, and quality of the segmented outputs.

AbstractCalcium Dependent Protein Kinases are found in the Apicomplexan, algae, and plants; however, they are not reported in vertebrates and are regarded as excellent drug targets for pharmaceutical interventions. Calcium Dependent Protein Kinases of Cryptosporidiumare probably involved in the regulation of invasion and egress process during the infection of the host cells. The previous study reported that after the Calcium Dependent Protein Kinase 1 gene, Calcium Dependent Protein Kinase 6 of Cryptosporidium parvumis expressed in all stages of the parasite (merozoites/schizonts as well as sexual stages) at a comparable level and makes it as a valid drug target. In this study, an attempt is made to address the similarity in sequences and phylogenetic study of Calcium Dependent Protein Kinase 6 (CDPK6) among Calcium Dependent Protein Kinases of Apicomplexans. Further, the three-dimensional structure determination of CDPK6 of C. parvumwas performed through a molecular modeling approach followed by virtual screening of small-molecule inhibitors from different datasets. The best inhibitor from Tres Cantos Antimalarial Set with ID 11730 reported a binding affinity of −8.2 kcal/mol against CDPK6 of C. parvum. Furthermore, the reliability of the binding mode of the inhibitor is validated through a complex molecular dynamics simulation study for a time interval of 100 ns. The simulation study advocates that the inhibitor Tres Cantos Antimalarial Set_11730 formed a stable interaction with the predicted active site residues and can be considered for industrial pharmaceutical research in future.Communicated by Ramaswamy H. Sarma

Bacillus cereusis a spore-forming bacterial species that has some pathogenic strains responsible for several human diseases. The present study was aimed to characterize a pathogenic strain of B. cereusWBI3 isolated from pond water of rural Tinna village area of West Bengal and its control by plant products. Out of the four screened bacterial isolates, WBI3 was found to possess haemolytic character. The bacterial strain WBI3 was gram-positive, spore forming, rod-shaped, motile bacterium, positive for catalase, oxidase, methyl red and nitrate reduction test and negative for indole, urease, citrate and Voges–Proskauer test. Bacterial isolate WBI3 was capable of producing amylase, lipase and gelatinase enzymes and was able to ferment trehalose, dextrose, fructose and salicin. Among twenty standard antibiotics, the bacterium was sensitive to seventeen antibiotics but resistant to three antibiotics. Morphological, biochemical and molecular analyses of the bacterial strain WBI3 indicated that it was a haemolytic and penicillin-resistant strain of B. cereus. Among six tested plant extracts, aqueous and alcoholic (methanolic and ethanolic) extracts of Acacia niloticashowed significant antibacterial activity against B. cereusWBI3 and inhibition zone diameters were 21.66 ± 1.52 mm, 25.33 ± 0.57 mm and 22.33 ± 1.52 mm, respectively. Further studies are needed to identify the bioactive compounds which have an antagonistic role against this pathogenic strain, so that a formulation can be made which would help to control the bacterial strain in the water bodies and spreading of diseases caused by this strain.

Microstructures of additively manufactured (AM) materials are highly heterogeneous, periodic, and hierarchical at various length scales, leading to complex mechanical response. In this study, nanoindentation trend analysis combined with machine learning (ML) was used to unravel the hierarchical and heterogeneous microstructures and associated multiscale mechanical responses in a laser-directed energy deposited low-alloy martensitic steel. At length scale encompassing several melt pools, periodic hardness fluctuations were attributed to variation in strain accommodation and phase transformation during primary solidification and thermal reheat cycles between the melt pools. The observed trends were a net balance between dislocation accumulation due to volume contraction during liquid to austenite solidification, and relaxation due to subsequent solid-state martensitic transformation during cooling. The hardness trends within a single melt pool (250–300 µm) were ascribed to cooling rate variations which manifests in form of changes in primary dendritic arm spacing. The inter-dendritic regions enriched with Cr and Mo demonstrated higher elastic modulus and hardness. In microstructural scale, variation in pop-in behavior in the nanoindentation load-displacement (P-h) curves was correlated to local microstructural heterogeneity in the indenter-material interaction volume (dendritic segregation + martensite matrix) using various ML-based classification techniques: decision tree, support vector machine and neural network. It classified the indentations into three broad categories: first set showing only one pop-in lying within the segregation channel with 10,000

13,000 N/m with multiple popins lied on the matrix-segrgeation interface. This novel multimodal structure-property correlative framework, integrating nanoindentation trend analysis with ML, provides a high-throughput approach to unravel the complex mechanical behavior of AM materials across multiple length scales, representing a key advancement in the field.

This study presents a novel approach utilizing solvothermal techniques to synthesize zeolitic imidazolate framework (ZIF‐4) particles. Various properties of the ZIF‐4 particles are investigated to shed light on the structural and morphological characteristics. These ZIF‐4 particles act as a positive triboelectric layer in the fabrication of a triboelectric nanogenerator (TENG) designed for powering electronic devices. The solvothermal‐assisted synthesis ensures the controlled and efficient production of ZIF‐4, optimizing its characteristics for enhanced performance in the TENG. The generated TENG, based on ZIF‐4 particles, determines promising capabilities in converting mechanical energy into electrical power. The highest power of TENG is obtained to be 18 μW at a load resistance of 50 MΩ. This work contributes major insights to the search for sustainable and effective power solutions for electronic gadgets. It emphasizes the potential of ZIF‐4 as a crucial triboelectric material, demonstrating its importance in the advancement of TENGs. A zeolitic imidazolate framework‐4 (ZIF‐4) is developed through a novel method utilizing a stovetop kitchen pressure cooker for triboelectric nanogenerator (TENG).

Variation of microbial diversity in landfill associated geoenvironments with differential exposure to extremophilic conditions.Distribution of genes encoding PET and PHA degrading enzymes and the taxonomy their corresponding hosts.Characterization of geoenvironment in which the plastic degrading microorganisms thrive.Presence of monotypic oceanic genus Plesiocystis in landfill environment.

Purpose: This study aims to modify a nature-based numerical method named the invasive weed optimization (IWO) method for mobile robot path planning in various complex environments. Design/methodology/approach: The existing IWO method is quick in converging to a feasible solution but in a complex environment; it takes more time as well as computational resources. So, in this paper, the computational part of this artificial intelligence technique is modified with the help of recently developed evolution algorithms like particle swarm optimization, genetic algorithm, etc. Some conditional logic statements were used while doing sensor-based mapping for exploring complex paths. Implementation of sensor-based exploration, mathematical IWO method and prioritizing them for better efficiency made this modified IWO method take complex dynamic decisions. Findings: The proposed modified IWO is better for dynamic obstacle avoidance and navigating a long complex map. The deviation of results in simulation and experiments is less than 5.5%, which validates a good agreement between simulation and real-time testing platforms. Originality/value: As per a deep literature review, it has found that the proposed approach has not been implemented on the Khepera-III robot for smooth motion planning. Here a dynamic obstacle mapping feature is implemented. A method to selectively distribute seeds instead of a random normal distribution is also implemented in this work. The modified version of IWO is coded in MATLAB and simulated through V-Rep simulation software. The integration of sensors was done through logical conditioning. The simulation results are validated using real-time experiments.

Effective rock phosphate (RP) solubilization by Bacillus thuringenesis P0B11, Lysinobaccillus fusiformisP0B28, and Aspergillus aculeatus P0F3isolated from Mahanadi estuary of Odisha, India.First report of RP solubilization by L. fusiformisP0B28.First report of in vitro stearic acid production during RP solubilization.Organic acids were the major mechanism for RP solubilization and responsible for morphological and mineralogical changes confirmed by SEM, XRD and FTIR, respectively.

As a gut-restricted, nonabsorbed therapy, polymeric bile acid sequestrants (BAS) play an important role in managing hyperlipidemia and hyperglycemia. Similarly, nonabsorbable sequestrants of dietary phosphate have been used for the management of hyperphosphatemia in end-stage renal disease. To evaluate the potential utility of such polymer sequestrants to treat type 2 diabetes (T2D) and its associated renal and cardiovascular complications, we synthesized a novel polymeric sequestrant, SAR442357, possessing optimized bile acid (BA) and phosphate sequestration characteristics. Long-term treatment of T2D obese cZucker fatty/Spontaneously hypertensive heart failure F1 hybrid (ZSF1) with SAR442357 resulted in enhanced sequestration of BAs and phosphate in the gut, improved glycemic control, lowering of serum cholesterol, and attenuation of diabetic kidney disease (DKD) progression. In comparison, colesevelam, a BAS with poor phosphate binding properties, did not prevent DKD progression, whereas losartan, an angiotensin II receptor blocker that is widely used to treat DKD, showed no effect on hyperglycemia. Analysis of hepatic gene expression levels of the animals treated with SAR442357 revealed upregulation of genes responsible for the biosynthesis of cholesterol and BAs, providing clear evidence of target engagement and mode of action of the new sequestrant. Additional hepatic gene expression pathway changes were indicative of an interruption of the enterohepatic BA cycle. Histopathological analysis of ZSF1 rat kidneys treated with SAR442357 further supported its nephroprotective properties. Collectively, these findings reveal the pharmacological benefit of simultaneous sequestration of BAs and phosphate in treating T2D and its associated comorbidities and cardiovascular complications.

Bovine milk-derived exosomes have recently emerged as a promising nano-vehicle for the encapsulation and delivery of macromolecular biotherapeutics. Here we engineer high purity bovine milk exosomes (mExo) with modular surface tunability for oral delivery of small interfering RNA (siRNA). We utilize a low-cost enrichment method combining casein chelation with differential ultracentrifugation followed by size exclusion chromatography, yielding mExo of high concentration and purity. Using in vitromodels, we demonstrate that negatively charged hydrophobic mExos can penetrate multiple biological barriers to oral drug delivery. A hydrophilic polyethylene glycol (PEG) coating was introduced on the mExo surface viapassive, stable hydrophobic insertion of a conjugated lipid tail, which significantly reduced mExo degradation in acidic gastric environment and enhanced their permeability through mucin by over 3× compared to unmodified mExo. Both mExo and PEG-mExo exhibited high uptake by intestinal epithelial cells and mediated functional intracellular delivery of siRNA, thereby suppressing the expression of the target green fluorescence protein (GFP) gene by up to 70%. We also show that cationic chemical transfection is significantly more efficient in loading siRNA into mExo than electroporation. The simplicity of isolating high purity mExo in high concentrations and equipping them with tunable surface properties, demonstrated here, paves way for the development of mExo as an effective, scalable platform technology for oral drug delivery of siRNA.

The application of iron (Fe) or nickel (Ni) doping over hopcalite (CuMnOx) catalyst highly effects on their structural properties and catalytic performance for ambient conditions carbon monoxide (CO) oxidation have been investigated. The NiO and Fe2O3phases are easily isolated over the CuMnOx catalyst. The (Fe or Ni) doping was done in the range of (0.5–5 wt%) in CuMnOx catalyst. The better catalytic activity was observed at 3.50 wt% of Fe, and 4.0 wt% of Ni loading in CuMnOx catalyst was separately found. However, the catalytic performance of CuMnOx catalyst was also depended on the promoters’ percentages rate. The smaller percentages of promoters carry out superior result than the higher ones. The size of catalytic material was also decreases, and specific surface area was also increased; therefore, the formation of active sites for CO conversion improved highly. The calcination strategies (reactive calcinations and traditional calcinations) highly affect on the performance of final catalysts. The reactive calcinations prepared catalysts that show the most excellent catalytic performances for CO conversion as compared to the other ones. The activity of catalysts was also matched with their characterization results.

High nitrogen (N) rate often leads to low yield of rice due to lodging and mutual shading. This study was conducted to ascertain whether silicon (Si) could enhance yield response of rice to higher N rate by enhancing rigidity of plant parts and improving photosynthesis. The effects of Si and N on crop growth, photosynthesis, N use efficiencies and yield of rice were investigated during wet season (June to November) in sub‐humid tropical region of India. An increasing trend in crop growth rate with Si at all levels of N was observed. Silicon reduced the flag leaf angle making the leaf more upright and enhanced flag leaf N content. Leaf chlorophyll concentration and single leaf photosynthesis rate were higher with Si compared to without Si at flowering stage. Both N and Si significantly affected panicle number and grain filling. Application of 200 kg SiO2ha−1and 100 kg N ha−1produced the highest number of panicle per square meter, filled grain per panicle and yield. Significant yield increases ranging from 8.2–16.9% were observed with Si compared to without Si. Both N and Si treatments had significant effects on N uptake and N use efficiency. Agronomic N use efficiency and N recovery efficiency were higher with Si compared to without Si. The highest physiological N use efficiency was recorded with 200 kg SiO2ha−1and 80 kg N ha−1. Silicon may enhance yield response of rice to higher N rate by improving source (photosynthetic) capacity and sink (reproductive organ) strength.

Contemporary states act as facilitators and this facilitation can be result oriented and successful only when effective governance is ensured. In the era of globalisation, greater emphasis is being laid today on good governance because of the critical link between the state and the global community. The nation states need to reinvent themselves and reframe their development strategy, which requires a thorough revision of their existing approach to international relations and internal governance. As a part of the ongoing administrative reform process, e-governance envisages a structural change in the bureaucracy and is perceived as a key to a more flexible and proactive governance in tune with the concerns of citizen-friendly administration.The present article explores the challenges and prospects of e-governance and tries to delve into the complex socio-cultural dynamics alongside political-bureaucratic initiatives that are crucial factors for the successful transition from traditional governance to the electronic governance. It attempts to situate the ongoing Digital India Mission in the larger context of good governance by examining the case study of the Indian Province of Odisha, where a silent but stunning revolution is taking shape.