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Enterococcus species and their probiotic potential: Current status and future prospects
Probiotics are described as live microbes that, once consumed in sufficient quantities, provide a health advantage to the host. A rising number of research works have verified the health benefits of probiotics. Enterococci are common bacteria that may be found almost anywhere. For their opportunistic pathogenicity, Enterococci have been associated with numerous nosocomial infections resulting from resistance to antibiotics and the existence of other virulence factors, notably the development of vancomycin-resistant Enterococci. However, some Enterococcal strains such as E. faecium and E. faecalis strains are being utilized as probiotics and are widely marketed, usually in the form of pharmaceutical solutions. Enterococcus spp. based probiotics are used to treat irritable bowel syndrome, infectious diarrhea, and antibiotic-associated diarrhea, along with decreasing cholesterol levels and enhancing host immunity. To be used as probiotics in the future, Enterococcal strains must be properly defined and thoroughly evaluated in terms of safety and can be beneficial. Here, in this work, we have reviewed various aspects of Enterococcus spp. pertaining to its possibility of being utilized as a probiotic strain. 2023 Krishna, et al. -
Bismuth (III) oxide decorated graphene oxide filled epoxy nanocomposites: thermo-mechanical and photon attenuation properties
In this study, bismuth (III) oxide (Bi2O3) decorated graphene oxide (GO) nanocomposites were employed as novel radioprotective fillers in the epoxy matrix. Decoration of GO with Bi2O3 would transform it as carrier for Bi2O3 particles, thereby enhancing the thermo-mechanical and radiation shielding properties of the epoxy composites through effective filler distribution. Structural and compositional studies confirmed the successful decoration of Bi2O3 on the surface of GO. Thereupon, epoxy composites containing decorated fillers at different loadings (5, 10 and 15 wt%) were synthesized using solution casting technique. The correlation between surface decoration and filler loading was systematically examined as function of thermo-mechanical, viscoelastic and radiation shielding properties of the composites. These nanocomposites displayed good thermal resistance (~ 450 C), high glass transition temperature (~ 136 C), elastic modulus (~ 4.36 GPa) and storage modulus, thereby confirming the improved dispersion and better interfacial adhesion in the composites. The formation of continuous filler network across epoxy matrix formed by decorated fillers significantly improved X-ray and ?-ray shielding properties of epoxy composites in the wide energy range of medical interest (301332 keV). Shielding efficiency of these lowly loaded BGO/epoxy composites were comparable with the composites containing Bi2O3 nanoparticles alone and highly loaded microcomposites. 2022 Japan Society for Composite Materials, Korean Society for Composite Materials and Informa UK Limited, trading as Taylor & Francis Group. -
Broadband Spectral Properties of MAXI J1348-630 using AstroSat Observations
We present broadband X-ray spectral analysis of the black hole X-ray binary MAXI J1348-630, performed using five AstroSat observations. The source was in the soft spectral state for the first three observations and in the hard state for the last two. The three soft state spectra were modeled using a relativistic thin accretion disk with reflection features and thermal Comptonization. Joint fitting of the soft state spectra constrained the spin parameter of the black hole a * > 0.97 and the disk inclination angle i = 32.9 ? 0.6 + 4.1 degrees. The bright and faint hard states had bolometric flux a factor of ?6 and ?10 less than that of the soft state respectively. Their spectra were fitted using the same model except that the inner disk radius was not assumed to be at the last stable orbit. However, the estimated values do not indicate large truncation radii and the inferred accretion rate in the disk was an order of magnitude lower than that of the soft state. Along with earlier reported temporal analysis, AstroSat data provide a comprehensive picture of the evolution of the source. 2022. National Astronomical Observatories, CAS and IOP Publishing Ltd. -
A Novel Generative Adversarial Network-Based Approach for Automated Brain Tumour Segmentation
Background: Medical image segmentation is more complicated and demanding than ordinary image segmentation due to the density of medical pictures. A brain tumour is the most common cause of high mortality. Objectives: Extraction of tumorous cells is particularly difficult due to the differences between tumorous and non-tumorous cells. In ordinary convolutional neural networks, local background information is restricted. As a result, previous deep learning algorithms in medical imaging have struggled to detect anomalies in diverse cells. Methods: As a solution to this challenge, a deep convolutional generative adversarial network for tumour segmentation from brain Magnetic resonance Imaging (MRI) images is proposed. A generator and a discriminator are the two networks that make up the proposed model. This network focuses on tumour localisation, noise-related issues, and social class disparities. Results: Dice Score Coefficient (DSC), Peak Signal to Noise Ratio (PSNR), and Structural Index Similarity (SSIM) are all generally 0.894, 62.084 dB, and 0.88912, respectively. The models accuracy has improved to 97 percent, and its loss has reduced to 0.012. Conclusions: Experiments reveal that the proposed approach may successfully segment tumorous and benign tissues. As a result, a novel brain tumour segmentation approach has been created. 2023 by the authors. -
The use of self-protective measures to prevent COVID-19 spread: an application of the health belief model
This study uses a health belief model to examine the preventive behavioral orientation or self-protective measures adopted by people in the face of the current COVID-19 pandemic. A total of 603 participants were selected from the city of Bangalore, India. The data was collected through an online survey with participants age varying between 17 and 54 and mean as 23 years (SD = 4.32). The findings revealed that perceived barrier has significant negative impact, while perceived threat, perceived consequences, perceived benefits, community and individual self-efficacy, and general health cues have a positive influence on an individuals intention to follow self-protective measures against COVID-19. Based on the constructs of the health belief model, this study proposes multiple health-related interventions to reduce the spread of COVID-19. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Encapsulated 3converter for power loss minimization in a grid-connected system
A newly designed DCAC three phase bidirectional converter (DATBC) with an encapsulated DCDC converter (EDC) for the energy storage system (ESD) is analysed and investigated in this research paper. By using encapsulated or embedded or hidden DCDC converter a stable and constant DC bus is developed between the encapsulated DCDC converter and DCAC three phase bidirectional converter. The proposed converter is entirely different from the traditional dual-stage DCAC converter, because it takes less than 20% of power used for the DCAC conversion process. So, this reduced power consumption increases efficiency to a considerable value. A new control technique for zero sequence has been adopted components are inserted in the modulating signal based on carrier pulse width modulation (CPWM). Working principle, implementation and characteristics of the DCAC three phase bidirectional converter are analysed. Effectiveness and feasibility of the developed converter are examined with a proto-type model. 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Solute-solvent interaction and DFT studies on bromonaphthofuran 1,3,4-oxadiazole fluorophores for optoelectronic applications
In the present work, computational and experimental studies were carried out to explore the photophysical properties of bromonaphthofuran substituted 1,3,4-oxadiazole derivatives for optoelectronic applications. Density functional theory (DFT) was used to demonstrate the electronic and optical properties of the synthesised molecules. The theoretical ground state dipole moments of the fluorophores in gas and solvent environments were also computed using Gaussian 09W software. Further, the HOMO-LUMO energies of the fluorophores determined using DFT agree well with the experimental values. Molecular electrostatic potential 3D plots were used to identify the sites which are electrophilic and nucleophilic in nature. Dipole moment of both the fluorophores in ground and excited states were determined experimentally. The excited state dipole moments being higher than that of the ground state shows the redistribution of electron densities in the excited state than in the ground state in both the fluorophores. The solute-solvent interactions, both specific and non-specific, were assessed using Catalan parameters. Further, the nature of chemical reactivity was determined based on global descriptors. The photophysical properties of the fluorophores studied suggest their potential use as promising candidates for organic light emitting diode (OLED), solar cell and chemosensor applications. 2022 Elsevier Inc. -
Measuring Financial Inclusion in India: An Approach
In light of the COVID-19-induced financial crisis, the need for robust financial services and networks has become more apparent than ever, which necessitated the accurate measurement of the breadth of financial inclusion in India. First, the study conducted a detailed critical review of the current indices and their construction methodology. Then, we created a financial inclusion index for India by accounting for the flaws existing in the current indices. The primary contribution of this study to the existing literature is the new approach it proposed for the assignment of weights in the financial inclusion index. Based on this new financial inclusion index, the study concluded that Indias Southern states and union territories showed better financial inclusion. In contrast, the traditionally backward BIMARU states of Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh, and a few of the North Eastern states of India, lagged. The study also provided a refined and inclusive definition of financial inclusion based on its new approach to index creation. 2023, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
In silico studies of viral protein inhibitors of Marburg virus using phytochemicals from Andrographis paniculata
The Marburg virus is a causative agent of Marburg hemorrhagic fever, which was discovered in Marburg, Germany, in 1967. It is a highly contagious and fatal disease transmitted by body fluids. The reservoir host is African fruit bats. Currently, there is no vaccine available to control this disease. Medicinal plants possess many phytochemicals of great therapeutic value. Many have antiviral properties and have been identified as promising drug molecules against various viral diseases proven with an in silico approach. The current research uses the in silico approach to identify the phyto-derived drugs from Andrographis paniculata to treat the Marburg virus. Twenty-four bioactive molecules from the A. paniculata plant were investigated against the targets VP35 and VP40 of Marburg viral proteins using the AutoDock Vina 1.1.2 tool. Out of 24 compounds, Andrographidine C, Andrographidine A, Andrographolactone, and 7-O-methylwogonin showed best docking scores for the target VP40 dimer while Bisandrographolide A, Luteolin Andrographolide, and Andrographiside showed best docking scores with VP35 protein. To determine the druglikeness, pharmacokinetic and pharmacodynamic properties and toxicity for each targets highest docking score compound was assessed using the Swiss absorption, distribution, metabolism, and excretion (ADME) and pkCSM tool. Andrographidine C and Andrographolide performed well in all the parameters of ADME and toxicity. These compounds are recommended as effective inhibitors of VP35 and VP40 of Marburg virus and potential antiviral drugs to treat the hemorrhagic disease. Furthermore, in vitro and in vivo studies can be used to examine the effectiveness and mode of action against the proteins of the Marburg virus. 2023 R. Hariprasath et al -
Banana peels as a cost effective substrate for fungal chitosan synthesis: optimisation and characterisation
Massive accumulation of unprocessed banana peels enthralls sustainable issues as they are eventually dumped as landfills leading to emission of obnoxious gasses. To avoid these persisting challenges the present study shims lights on chitosan production from the characterised fungal strain using banana peel hydrolysate as an effective medium. Substantial amount of carbohydrate in banana peels serves as a potential solution for fungal chitosan production in a view to attain a circular bioeconomy and repurposed for synthesis of beneficial products in a cost effective manner. Presence of fermentable sugars in banana peels qualifies them as a feasible substrate which could be exploited for scaling up of fungal chitosan synthesis. Screened isolate was subjected to statistical optimisation using formulated medium to elucidate the influential factors that had significant effect on chitosan production. The harvested chitosan biomass was characterised through standardised techniques and evaluated for further studies. Statistical optimisation reveals that ammonium nitrate (5 g/L), pH (6) and incubation time (144 hrs) were the three PBD variables that had a greater influence on fungal chitosan yield. The validated developed model exhibited maximum yield of 200 mg/L, a 4.4 fold increase than unoptimised medium (45 mg/L). These findings emphasise the fermentative synthesis of chitosan through valorisation of banana peel prop up a complementary approach in concomitant with preserving renewable resources and bioproduct formation. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Mediating role of self-concept on character strengths and well-being among adolescents with specific learning disorder in India
Background: Adolescents with Specific Learning Disorder (SLD) are at higher risk of academic underachievement, stigmatization, and mental health issues. However, the complete elimination of disorder-related deficits and external challenges is an impracticable solution for enhancing their well-being. Aim: The study adopts a strength-based approach to understand the role of an innate factor, i.e., self-concept, in the association between character strengths and well-being of adolescents with SLD. Methods: A correlational research design following a mediation analysis was adopted to examine the association between the study variables on a sample of 115 adolescents with SLD from India. Results: Self-concept functioned as a partial mediator between the life-satisfaction construct of well-being and six character strengths: Appreciation of beauty and excellence, Perseverance, Judgment, Leadership, Perspective, and Zest. Gender differences were identified with regard to the study variables. Conclusions and implications: Self-concept of adolescents with SLD could partly contribute to enhanced character strengths awareness to protect well-being. Further, the crucial role of internal factors like self-concept and character strengths in improving the well-being of this population was highlighted. Thereby encouraging future research on SLD to adopt approaches that focus on innate strengths rather than deficits and external sources of well-being. 2022 Elsevier Ltd -
Machine LearningEnabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data
Abstract: An increasingly large dataset of pharmaceuticsdisciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robustdata on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset (http://www.models.life.ku.dk/Tablets) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. Highlights: We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation Model extension from lab-scale to pilot-scale successfully demonstrated Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s). -
Examining the Relationship between Academic Expectations and Suicidal Ideation among College Students in India Using the Interpersonal Theory of Suicide
Objective: As the second most populous country in the world, India accounts for over 20% of the global suicide deaths. Notably, young adults make up 38% of those who die by suicide in India. Yet, the literature on factors associated with suicide within this age group in India is limited. The Interpersonal Theory of Suicide (IPTS) posits thwarted belongingness and perceived burdensomeness as constructs that heighten the risk for suicide. Testing mechanisms that may mediate the relationship between common stressors for young adults in India, such as academic expectations, and suicidal ideation are important to better understand factors contributing to suicide risk within this country. Method: Indian college students (N = 432, M age = 19.41, 73.1% male) completed questionnaires on academic expectations, thwarted belongingness, perceived burdensomeness, collectivism, and suicidal ideation. Results: Current suicidal ideation was endorsed at a rate of 38%. Academic expectancy from the self, perceived burdensomeness, and thwarted belongingness was significantly associated with suicidal ideation. The only significantly mediated pathway was academic expectancy from others to suicidal ideation through perceived burdensomeness. Collectivism was not a significant moderator in the model. Discussion: The sample endorsed high rates of suicidal ideation, highlighting the need for culturally appropriate interventions. Thwarted belongingness, perceived burdensomeness, and academic expectations from oneself may be relevant treatment targets for reducing suicidal ideation among college students in India.HIGHLIGHTS Over one-third of Indian university students endorsed suicidal ideation. Suicidal ideation related to ones own more than others academic expectations. Results offer support for the Interpersonal Theory of Suicide within this context. 2022 International Academy for Suicide Research. -
Impact of helpful reviews on customer purchase intention with special reference to mobile phone reviews
Technological advances in the digital space have provided renewed impetus to businesses. Costly, labor-intensive marketing campaigns have been replaced by digital marketing. However, along with benefits, the increasing sophistication and exponential growth of e-commerce businesses have also introduced new challenges. The large number of similar product offerings and the high volume of reviews have created a technology-induced hurdle for consumers that can impair their thought processes. Often, users will only scan the top few reviews to arrive at a decision. In the current setup, older reviews that accumulate votes over time are found at the top of the helpful review list, in contrast to fresh entrants. The current study proposes placing reviews in appropriate positions in the helpful review list using statistical and scientifically derived helpfulness scores. The study utilized a sample of consumer goods (specifically, mobile phones) and re-ranked reviews based on their expected score. Amazon.in provided the initial review dataset. Random Forest and gradient-boosting regression techniques were used to predict review helpfulness. An Elaboration Likelihood Model was used to explore the impact of central and peripheral cues on review helpfulness. The gradient-boosting regression was the best-performing method of predicting review helpfulness, and the reviews were re-ranked. The re-ranked reviews were tested for helpfulness vis-a-vis the initial ranking of reviews using the survey method. The result indicated that the proposed re-ranking of reviews was more helpful to end users and helped mitigate uncertainty in decisions. The study utilized the Information Acceptance Model to assess the influence of electronic word of mouth on purchase intention. 2023 Conscientia Beam. All Rights Reserved. -
Fault diagnosis in a five-level multilevel inverter using an artificial neural network approach
Introduction. Cascaded H-bridge multilevel inverters (CHB-MLI) are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of CHB-MLI. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of 5 level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation experiment for the modulation index value of 0.85, one second open and short circuit faults are created for the place of faulty switch. Fault is identified automatically by means of artificial neural network (ANN) technique using sinusoidal pulse width modulation based on distorted total harmonic distortion (THD) and managed by its own. The novelty of the proposed work consists of a fast Fourier transform (FFT) and ANN to identify faulty switch. Purpose. The proposed architecture is to identify faulty switch during open and short failures, which has to be reduced THD and make the system in reliable operation. Methods. The proposed topology is to be design and evaluate using MATLAB/Simulink platform. Results. Using the FFT and ANN approaches, the normal and faulty conditions of the MLI are explored, and the faulty switch is detected based on voltage changing patterns in the output. Practical value. The proposed topology has been very supportive for implementing non-conventional energy sources based multilevel inverter, which is connected to large demand in grid. References 22, tables 2, figures 17. E. Parimalasundar, R. Senthil Kumar, V.S. Chandrika, K. Suresh. -
Multiway Relay Based Framework for Network Coding in Multi-Hop WSNs
In todays information technology (IT) world, the multi-hop wireless sensor networks (MHWSNs) are considered the building block for the Internet of Things (IoT) enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service (QoS) in a stipulated time slot to end-user over the Internet. Smart city (SC) is an example of one such application which can automate a group of civil services like automatic control of traffic lights, weather prediction, surveillance, etc., in our daily life. These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput, energy efficiency, and end-to-end delay, wherein low latency is considered a challenging issue in next-generation networks (NGN). This paper introduces a single and parallels stable server queuing model with a multi-class of packets and native and coded packet flow to illustrate the simple chain topology and complex multiway relay (MWR) node with specific neighbor topology. Further, for improving data transmission capacity in MHWSNs, an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node. Finally, the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets. The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results. 2023 Tech Science Press. All rights reserved. -
IoT enabled lung cancer detection and routing algorithm using CBSOA-based ShCNN
The Internet of Things (IoT) has tremendously spread worldwide, and it influenced the world through easy connectivity, interoperability, and interconnectivity using IoT devices. Numerous techniques have been developed using IoT-enabled health care systems for cancer detection, but some limitations exist in transmitting the health data to the cloud. The limitations can be accomplished using the proposed chronological-based social optimization algorithm (CBSOA) that effectively transmits the patient's health data using IoT network, thereby detecting lung cancer in an effective way. Initially, nodes in the IoT network are simulated such that patient's health data are collected, and for transmission of such data, routing is performed in order to transmit the health data from source to destination through a gateway based on cloud service using CBSOA. The fitness is newly modeled by assuming the factors like energy, distance, trust, delay, and link quality. Finally, lung cancer detection is carried out at the destination point. At the destination point, the acquired input data is fed to preprocessing phase to make the data acceptable for further mechanism using data normalization. Once the feature selection is done using Canberra distance, then the lung cancer detection is performed using shepard convolutional neural network (ShCNN). The process of routing as well as training of ShCNN is performed using the CBSOA algorithm, which is devised by the inclusion of the chronological concept into the social optimization algorithm. The proposed approach has achieved a maximum accuracy of 0.940, maximum sensitivity of 0.941, maximum specificity of 0.928, and minimum energy of 0.452. 2022 John Wiley & Sons Ltd. -
A STUDY OF AN UNDIRECTED GRAPH ON A FINITE SUBSET OF NATURAL NUMBERS
Let Gn = (V, E) be an undirected simple graph, whose vertex set comprises of the natural numbers which are less than n but not relatively prime to n and two distinct vertices u, v ? V are adjacent if and only if gcd(u, v) > 1. Connectedness, completeness, minimum degree, maximum degree, independence number, domination number and Eulerian property of the graph Gn are studied in this paper. 2022, RAMANUJAN SOCIETY OF MATHEMATICS AND MATHEMATICAL SCIENCES. All rights reserved. -
Spectral characteristics of the black hole binary 4U 1957+115: a multi mission perspective
We report spectral analysis of the persistent black hole X-ray binary, 4U 1957+115, using AstroSat, Swift, and NuSTAR observations carried out between 2016 and 2019. Modelling with a disc emission, thermal Comptonization, and blurred reflection components revealed that the source was in the high-soft state with the disc flux ?87 per cent of the total and high-energy photon index ?2.6. There is an evidence that either the inner disc radius varied by ?25 per cent or the colour hardening factor changed by ?12 per cent. The values of the inner disc radius imply that for a non-spinning black hole, the black hole mass is < 7 M ? and the source is located > 30 kpc away. On the other hand, a rapidly spinning black hole would be consistent with the more plausible black hole mass of < 10 M ? and a source distance of ?10 kpc. Fixing the distance to 10 kpc and using a relativistic accretion disc model, constrained the black hole mass to 6 M? and inclination angle to 72. A positive correlation is detected between the accretion rate and inner radii or equivalently between the accretion rate and colour factor. 2022 The Author(s). -
Integrated Effect of Flow Field Misalignment and Gas Diffusion Layer Compression/Intrusion on High Temperature - Polymer Electrolyte Membrane Fuel Cell Performance
Misalignment in the flow field plates of High-Temperature Polymer Electrolyte Membrane Fuel Cell (HT-PEMFC) due to manufacturing tolerances, assembly process, or unavoidable vibration during the cell operation is contemplated its performance and durability. This study investigates the effect of flow field plate misalignment and its concomitant impact with varying the clamping pressures on HT-PEMFC operation. The study considers six degrees of cathode flow field misalignment, varying from 0% to 100% with respect to the anode flow field. Clamping pressures ranging from 1 to 2 MPa are applied to the various cases of misalignment to study their effect on GDL deformation and intrusion into the channels. The structural analysis shows that as the misalignment increases from 0 to 100%, the GDL compression increases from 26.72% to 37.75% for 1 MPa, 40.07% to 56.63% for 1.5 MPa, and 53.43% to 75.51% for 2 MPa, owing to the increase in compression approximately by 41% from their base cases and it is also crucial to note that GDL compression exaggerates at higher clamping pressures. The misalignment results in the sagging of Membrane Electrode Assembly (MEA), and the amplitude of wave nature is proportional to the degree of misalignment and clamping pressure, indicating the misalignment is the sole factor for structural changes. As a result, considerable variance in current distribution and average value is observed, i.e., at operating voltage 0.5 V, the current density drops from 4472.7 to 4264.4, 4420.7 to 4211.8, and 4374.1 to 4161.3 A m?2 from cases 1 to 6 for clamping pressures 1, 1.5, and 2 MPa, respectively, resulting in a 4.7% loss in performance. According to the observations, a misalignment of 60% is tolerable, with minimal performance loss and negligible non-uniformity in cell distributions. 2022 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited.