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Assessment of SERVQUAL Model in Hospitals Located in Tier II Cities of India
Service quality, being an assessment of services offered to a customer or the extent to which the services offered meets customers expectations, plays a significant role in healthcare industry. Patients pay hefty prices for the services they avail from specialty hospitals and they demand quality services. Hospitals have a larger challenge in delivering these services effectively to the patients. The current study helps us understand the role of information systems in service delivery process. Most of the hospitals have adopted healthcare information systems due to the benefit it provides. The study attempts to analyze the impact of information systems on service quality in the hospitals which are located in Tier II cities. The popular SERVQUAL model is adopted for this purpose. Patients who visit the hospitals were part of the respondent group. Gap score is found in order to observe the expected and actual experience of the patients based on five dimensions. 2018, 2018 Indian Institute of Health Management Research. -
Facile fabrication of mesh-free, GO-reinforced ZrO2-based separators for advanced alkaline water electrolysis
Alkaline Water Electrolysis (AWE) is a promising method for sustainable hydrogen production due to its maturity and use of non-noble metal catalysts. A key challenge lies in developing cost-effective, durable, and scalable separators that ensure ionic conduction and separation between the electrodes. This study presents a mesh-free composite separator composed of zirconia nanoparticles (ZrO2 NPs), polysulfone (PSU), and graphene oxide (GO), eliminating the need for expensive polyphenylene sulphide (PPS) mesh and its hazardous hydrophilic surface treatments. GO was incorporated as a multifunctional additive to enhance mechanical strength, hydrophilicity, and dispersion of ZrO2 NPs. Separators were fabricated with varying compositions of ZrO2 NPs, PSU, and GO, and tested in a zero-gap titanium-based electrolyser using nickel foam electrodes and 30?wt% potassium hydroxide (KOH) electrolyte. Amongst them, the Sep72/25/3 separator (72?wt% ZrO2, 25?wt% PSU, 3?wt% GO) showed a low area-specific resistance (ASR) of 298?m? cm2 at room temperature (RT). It also exhibited excellent wettability with a reduced contact angle of 23 after 24?h conditioning in 30?wt% KOH, along with a notable improvement in tensile strength, from 1.75?MPa (without GO) to 3.26?MPa, validating the reinforcing role of GO. The results demonstrate a simple and scalable route for fabricating mesh-free separators that strike an optimal balance between ionic resistance, mechanical strength, and wettability, thereby offering a cost-effective alternative for next-generation advanced alkaline water electrolysis (AAWE) systems. The Korean Ceramic Society 2025. -
Investigation of thermal performance of moving concave parabolic porous fin wetted by water based MoS2 nanofluid using Homotopy Perturbation Method
Recent advancements in nanotechnology have led to significant improvements in the design, manufacturing, and thermal efficiency of engineering systems. Nanofluids, when combined with extended surfaces, enhance heat transfer performance, helping to prevent overheating while also offering improved stability, durability, and adaptability across various environmental conditions. This research focuses on the thermal response of a moving porous fin featuring a concave parabolic profile, immersed in a nanofluid composed of water as the base fluid and molybdenum disulfide (MoS2) nanoparticles. The governing nonlinear nanofluid model is nondimensionalized, and thermal characteristics such as temperature profiles, heat transfer rates, efficiency, and fin effectiveness are obtained using the Homotopy Perturbation Method (HPM). The effects of important dimensionless parameters on thermal profiles are examined through graphical illustrations. The results demonstrate that temperature rises with increases in the Peclet number and thermal conductivity, whereas it decreases as porosity, radiation, convection, and emissivity parameters increase. Furthermore, the inclusion of MoS2 nanofluid leads to an average heat transfer enhancement of approximately 3.84% compared to conventional fluids under radiative conditions. 2025 -
Numerical study on magnetohydrodynamics micropolar Carreau nanofluid with Brownian motion and thermophoresis effect
The current work explores the investigation of the influence of nonlinear thermal radiation on unsteady, magnetohydrodynamics boundary layer flow of micropolar Carreau nanofluid past a stretching sheet. Viscous dissipation, internal heating, Brownian motion, heat source/sink, thermophoresis, chemical reaction, and Joule heating effects are considered in the study. To analyze the model, the governing partial differential equations are rephrased and written in the non-dimensional form with the relevant dimensionless quantities. To obtain the solutions, the nonlinear non-dimensional governing equations are numerically solved using finite difference approximation. The impact of every significant flow parameter on fluid motion, micro-rotation, temperature, concentration, surface drag, heat, and mass transfer rates are presented through plotted graphs and tables. It is noted from the study that the fluid flow and angular motion increase, whereas the temperature declines with higher values of the micropolar constant. Further, it is noticed that thermal distribution is a rising function of radiation parameter, and due to the nonlinear thermal radiation effect, there is an increase of 4.903% in temperature distribution when compared to linear thermal radiation. To support the validity of the solutions, a comparison was made with notable results from the existing literature for the specific case of this study. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Extractive Text Summarization Using Sentence Ranking
Automatic Text summarization is the technique to identify the most useful and necessary information in a text. It has two approaches 1)Abstractive text summarization and 2)Extractive text summarization. An extractive text summarization means an important information or sentence are extracted from the given text file or original document. In this paper, a novel statistical method to perform an extractive text summarization on single document is demonstrated. The method extraction of sentences, which gives the idea of the input text in a short form, is presented. Sentences are ranked by assigning weights and they are ranked based on their weights. Highly ranked sentences are extracted from the input document so it extracts important sentences which directs to a high-quality summary of the input document and store summary as audio. 2019 IEEE. -
Abusive Words Detection on Reddit Comments Using Machine Learning Algorithms
Utilization of artificial intelligence contributes to the efficient examination of emotions, resulting in valuable insights into the psychological condition of users on a large scale. In this research endeavor, sentiment analysis is conducted on a dataset from Reddit, which was obtained through Kaggle. The feedback in this collection of data was divided into downbeat, neutral, and upbeat sentiments. Various machine learning techniques, like Random Forest, Extreme Gradient Boosting Classifier (XGB), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and Convolutional Neural Network (CNN), were detected and examined to assess their effectiveness in sentiment classification. The review of these techniques comprised performance criteria such as F1 Score, accuracy, precision, and recall. Additionally, confusion matrices were utilized to assess the algorithms' proficiency in identifying abusive language. The investigation's conclusions indicate that, when it comes to sentiment analysis, the random forest method performs better than any other strategy, with a maximum accuracy of 0.99 that is on par with the CNN model's accuracy of 0.98. Moreover, random forest proves to be the most effective algorithm in recognizing negative comments and abusive language. This study underscores the significance of employing machine learning algorithms in sentiment analysis, content moderation, social media monitoring, and customer feedback analysis, emphasizing their role in enhancing automated systems that aim to comprehend user sentiments in online discussions. 2024 IEEE. -
The Road to Reducing Vehicle CO2 Emissions: A Comprehensive Data Analysis
In recent years, the influence of carbon dioxide (CO2) releases on the environment have become a major concern. Vehicles are one of the major sources of CO2 emissions, and their contribution to climate change cannot be ignored. This research paper aims to investigate the CO2 emissions of vehicles and compare them with different types of engines, fuel types, and vehicle models. The study was carried out by gathering information about the CO2 emissions of vehicles from the official open data website of the Canadian government. Data from a 7-year period are included in the dataset, which is a compiled version. There is a total of 220 cases and 9 variables. The data is analyzed using statistical methods and tests to identify the significant differences in CO2 emissions among different Car Models. The results indicate that vehicles with diesel engines emit higher levels of CO2 compared to those with gasoline engines. Electric vehicles, on the other hand, have zero CO2 emissions, making them the most environmentally friendly option. Furthermore, the study found that the CO2 emissions of vehicles vary depending on the type of fuel used. The study also reveals that the CO2 emissions of vehicles depend on the model and age of the vehicle. Newer models tend to emit lower levels of CO2 compared to older models. In conclusion, this study provides valuable insights into the CO2 emissions of Cars and highlights the need to adopt cleaner and more sustainable transportation options. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Electrospun nanofibers of 2D Cr2CTx MXene embedded in PVA for efficient electrocatalytic water splitting
The usage of transition metal carbide-based electrocatalysts has proven to be an efficient and effective strategy for enhancing the kinetics of water splitting reactions encompassing the generation of hydrogen (hydrogen evolution reaction, HER) and oxygen (oxygen evolution reaction, OER). In this investigation, we have prepared a composite material by integrating Cr2CTx MXene (derived from Cr2AlC MAX phase) and polyvinyl alcohol (PVA) through electrospinning technique. Carbonization of the MXene-PVA nanofibers resulted in the formation of Cr2CTx/carbon nanofiber (Cr2CTx/CNF) that exhibits high porosity, stability, surface area, and electrocatalytic activity. Systematic examination and optimization for the electrocatalytic water splitting reaction reveales outstanding performance, characterized by substantially lower overpotentials of 265 mV and 250 mV at the constant current density of 10 mA cm?2 with lower Tafel slope values of 85 mV dec?1 and 52 mV dec?1 for HER and OER, respectively. Moreover, this work presents a novel strategy for fabricating non-precious electrocatalyst Cr2CTx/CNF through a cost-effective and straightforward electrospinning and carbonization process, advancing electrocatalytic water splitting applications, especially for oxygen evolution reactions. 2024 The Royal Society of Chemistry. -
Critical Analysis of MoS2-Based Systems for Textile Wastewater Treatment
Indiscriminate discharge of toxic organic contaminant-laden wastewater into water bodies is one of the major issues posing a risk to the environment in general and aquatic living systems in particular. Widely used textile dyes are ubiquitous in the effluents emanating from industries. Photocatalysts, due to their efficiency and eco-friendliness, can be effectively used to remove pollutant dyes from the water bodies. Molybdenum disulfide (MoS2), an emerging co-catalyst, has high photocatalytic activity, strong absorptivity, non-toxicity, and low cost; with a graphene-like structure, it offers functional features similar to graphene: high charge carrier transfer, strong wear resistance, and good mechanical strength. However, in aspects such as cost, abundance, versatile morphologies, and tunable band gap with efficient visible light absorption properties, MoS2 scores over graphene. The present chapter discusses the recent advances in nanostructured MoS2 materials for applications in environmental remediation. Special emphasis has been paid to MoS2 and MoS2-based systems for the photocatalytic degradation of various organic contaminants such as malachite green, methyl orange, rhodamine B, and methylene blue that find extensive use in the textile industry. As a result, MoS2 systems play an essential role in nanocomposites, especially in speeding up photo-induced electron transport and lowering electron recombination rates, making them desirable photocatalysts for the degradation of pollutants. The chapter focuses on addressing SDG 3 (Good Health and Wellbeing), SDG 6 (Clean Water and Sanitation), SDG 7 (Clean and Affordable Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), SDG 14 (Life Below Water), and SDG 15 (Life on Land). 2025 Moharana Choudhury, Ankur Rajpal, Srijan Goswami, Arghya Chakravorty and Vimala Raghavan. -
Sustainable Peanut Shell-Derived Carbon Dots for Fluorescent Sensing of Pb2+ Ions
Lead (Pb), a chemical element, is highly toxic even at low doses and can cause permanent harm with immediate life-threatening consequences upon short-term exposure. Its toxicity poses a significant risk, particularly to young children, leading to lifelong severe health issues. Detecting lead is crucial, and there is increasing interest in adopting eco-friendly approaches, such as utilizing carbon dots (CDs) derived from biomass. In our present study, we have synthesized CDs from peanut shells (PNS) through a straightforward pyrolysis process and employed various techniques to characterize these PNS-based CDs. Our findings reveal that these CDs emit fluorescence at 455 and 574nm when excited at 285nm, particularly in the presence of nanomolar Pb2+ ions. Notably, these PNS-derived CDs (PNS-CDs) demonstrate remarkable sensitivity and selectivity for detecting Pb2+ ions. A limit of detection (LOD) of 16.59nM was determined for the sensor, corresponding to a linear concentration range of 16.622.2nM. This study proposes a novel and simple one-pot pyrolysis method to synthesize CDs from PNS for the rapid testing of lead contamination in the environment, which holds great promise for sensor applications. 2025 Wiley-VCH GmbH. -
Unveiling the supercapacitive behavior of electrospun Cr2CTx/carbon nanofiber membrane
A novel electrospinning-based strategy was employed to fabricate Cr2CTx/carbon nanofibers using Cr2CTx MXene and polyvinyl alcohol (PVA) as precursors. This approach enables the formation of porous, conductive composite MXene layers dispersed in carbon nanofibers. The resulting material exhibited notable supercapacitive performance, delivering 338.8 F g?1 capacitance, 67.7 Wh kg?1 energy, and 1998 W kg?1 power density. This journal is The Royal Society of Chemistry, 2025 -
Exploring pseudocapacitive performance in Cr2CTx/NiFe2O4 composites: experimental insights
The growing demand for sustainable and efficient energy storage systems has driven the development of advanced, durable, and cost-effective materials. This study introduces heterostructures of 2D Cr2CTx MXene and NiFe2O4, leveraging their synergistic properties, such as high conductivity, surface termination groups (-OH, -O, and -F), tunable surface chemistry, and rich redox activity. Comprehensive structural and morphological characterization confirms the enhanced functionality of Cr2CTx/NiFe2O4, which exhibits a remarkable specific capacitance of 1719.5 F g?1 with 88% retention over 5000 cycles in a three-electrode system. Additionally, the asymmetric supercapacitor device demonstrates a specific capacitance of 486.66 F g?1, an energy density of 97.66 W h kg?1, and a power density of 1203.95 W kg?1, retaining 94% of its capacitance after 5000 cycles. A plausible charge transfer mechanism in the composite is discussed, providing new insights into the synergistic Cr2CTx/NiFe2O4 heterostructures as high-performance materials for energy storage applications. 2025 The Royal Society of Chemistry. -
Cr2MoAlC2 MAX phase and its derivative Cr2MoC2Tx MXene for supercapacitors and electrocatalytic water splitting
The expanding research on 2D MXenes has enabled new strategies to engineer material properties via structural design. While bimetallic or double transition metal (DTM) MXenes have continued to gain attention since their emergence in 2015, their versatile structure and exceptional physicochemical properties have inspired wide exploration. This study reports the synthesis of the Cr2MoAlC2 MAX phase and its derivative Cr2MoC2Tx MXene (Tx = F/OH/O), leveraging the synergistic incorporation of Cr and Mo as dual transition metals. The structural, thermal, chemical, and surface morphology characteristics were analyzed using various techniques. Cr2MoC2Tx MXene exhibits superior pseudocapacitance performance as an electrode material, achieving a specific capacitance of 1350 F g?1 at 1 A g?1 with 84% retention over 5000 cycles. In a two-electrode asymmetric device, Cr2MoC2Tx MXene delivers a specific capacitance of 438.3 F g?1 at 1 A g?1, an energy density of ?87.66 Wh kg?1, and a power density of 1200 W kg?1. Additionally, Cr2MoC2Tx MXene demonstrates excellent electrocatalytic activity for water splitting applications, with overpotentials of 186 mV for the hydrogen evolution reaction (HER) and 280 mV for the oxygen evolution reaction (OER), at 10 mA cm?2. This dual functionality, driven by the synergistic interaction between Cr and Mo, establishes Cr2MoC2Tx MXene as a promising material for both energy storage and hydrogen production, positioning it as a competitive candidate among state-of-the-art materials. Furthermore, this research aligns with the United Nations Sustainable Development Goal (SDG) 7, contributing to the advancement of high-performance electrode materials for next-generation electrochemical applications. This journal is The Royal Society of Chemistry, 2026. -
Geographies of Gender and Leadership: Regional Inequalities and Women in Omans Oil & Gas Sector
Introduction / Main Objective: This research explores Omani women's spatial and cultural barriers to leadership in the Oil & Gas industry. It looks at geographic location and regional differences and how these affect women's access to and experience of leadership. Background of the Problem: While significant advancements have been made in women's participation in the labor force in Oman, spatial disparities still exist whereby women in urban areas have more chances of leadership compared to women in rural or rural-remote towns. Cultural expectations and infrastructural constraints add to these geographical disparities. Novelty: This study innovatively combines a geographic perspective in gender and leadership research in Oman's Oil & Gas sector with an emphasis on regional disparities influencing women's career development. Research Methods: A qualitative method involving questionnaires was conducted among thirty women managers within various regions of Oman. Responses were processed to determine spatially connected obstacles and coping mechanisms. Findings: Women in urban areas like Muscat enjoy better access to education, professional networks, and organizational support, while women in rural areas are confronted by cultural conservatism, poor infrastructure, and lower promotion opportunities. There was an urban-rural leadership training and family support divide. Conclusion: Geography profoundly influences women's leadership paths in Oman's Oil & Gas industry. For policies to enhance gender equity, leadership development policy needs to take regional disparities into consideration and adapt interventions to local contexts. 2025, Green Publication. All rights reserved. -
The Role Of Leadership Behaviour On Team Success In Omani Healthcare: A Mediation Analysis In Diverse Clinical Settings
This study investigates the mediating role of leadership behavior in enhancing team processes and overall team success within the healthcare sector in Oman. Drawing upon the Leading Diversity (LeaD) model, the research conceptualizes the dynamics between leadership behavior, team process effectiveness, and team success in healthcare teams. A structured survey was administered to 25 team leaders representing hospitals and primary care centers across Oman, capturing perspectives on leadership competencies, team collaboration, and outcomes. Using Confirmatory Factor Analysis (CFA), the findings reveal that task-based leadership behavior partially mediates the relationship between effective team processes and team success. This indicates that while structured team processes are essential, their effectiveness is significantly enhanced when complemented by proactive, goal-oriented leadership. The study reinforces the critical role of leadership in navigating cultural and professional diversity among healthcare professionalsincluding physicians, nurses, technicians, and administrators. In Omans evolving healthcare landscape, characterized by modernization, resource pressures, and rising patient expectations, effective leadership is shown to improve patient care, reduce clinical errors, and enhance staff morale and communication. While the study accounts for potential social desirability and common method bias, measures were taken to minimize these effects. The application of the LeaD model in a healthcare context marks a novel contribution to leadership and healthcare management literature, emphasizing that inclusive, adaptive leadership is not only beneficial but necessary for delivering high-quality healthcare in multicultural environments. 2025, Green Publication. All rights reserved. -
The Role Of Leadership Behaviour On Team Success In Omani Healthcare: A Mediation Analysis In Diverse Clinical Settings
This study investigates the mediating role of leadership behavior in enhancing team processes and overall team success within the healthcare sector in Oman. Drawing upon the Leading Diversity (LeaD) model, the research conceptualizes the dynamics between leadership behavior, team process effectiveness, and team success in healthcare teams. A structured survey was administered to 25 team leaders representing hospitals and primary care centers across Oman, capturing perspectives on leadership competencies, team collaboration, and outcomes. Using Confirmatory Factor Analysis (CFA), the findings reveal that task-based leadership behavior partially mediates the relationship between effective team processes and team success. This indicates that while structured team processes are essential, their effectiveness is significantly enhanced when complemented by proactive, goal-oriented leadership. The study reinforces the critical role of leadership in navigating cultural and professional diversity among healthcare professionalsincluding physicians, nurses, technicians, and administrators. In Omans evolving healthcare landscape, characterized by modernization, resource pressures, and rising patient expectations, effective leadership is shown to improve patient care, reduce clinical errors, and enhance staff morale and communication. While the study accounts for potential social desirability and common method bias, measures were taken to minimize these effects. The application of the LeaD model in a healthcare context marks a novel contribution to leadership and healthcare management literature, emphasizing that inclusive, adaptive leadership is not only beneficial but necessary for delivering high-quality healthcare in multicultural environments. 2025, Green Publication. All rights reserved. -
CNN-Bidirectional LSTM based Approach for Financial Fraud Detection and Prevention System
Detecting fraudulent activity has become a pressing issue in the ever-expanding realm of financial services, which is vital to ensuring a positive ecosystem for everyone involved. Traditional approaches to fraud detection typically rely on rule-based algorithms or manually pick a subset of attributes to perform prediction. Yet, users have complex interactions and always display a wealth of information when using financial services. These data provide a sizable Multiview network that is underutilized by standard approaches. The proposed method solves this problem by first cleaning and normalizing the data, then using Kernel principal component analysis to extract features, and finally using these features to train a model with CNN-BiLS TM, a neural network architecture that combines the best parts of the Bidirectional Long Short-Term Memory (BiLS TM) network and the Convolution Neural Network (CNN). BiLSTM makes better use of how text fits into time by looking at both the historical context and the context of what came after. 2023 IEEE. -
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Interpreting the Evidence on Life Cycle to Improve Educational Outcomes of Students Based on Generalized ARC-GRU Approach
Research on the effects of teachers' fatigue on students' learning has been significantly less common than research on the effects of teachers' fatigue on teachers' own performance. Therefore, the purpose of this research is to see if teachers' emotional weariness has any bearing on their students' performance in the classroom. Consideration is given to a student's grades and their impressions of whether or not the system receive assistance from teachers, as well as to the student's general outlook on school, confidence in their own abilities, and faith in the availability of faculty support. Data preparation, feature extraction, and model training are the first steps in the proposed approach. Indicators of the quality of the education being provided are eliminated (by outlier removal and feature scaling). k-mean clustering approach is a technique of clustering which is commonly used in feature extraction. Following feature extraction, GARCH-GRU models are trained. The proposed approach is superior to two popular alternatives, ARCH and GRU. Using the provided method, the system were able to achieve a maximum accuracy of 97.07%. 2024 IEEE. -
Sociocentric and Cosmocentric Coping: Cultural Logics of Parenting During Crisis in Low-Resource Indian Families
Coping with crisis is a culturally situated process shaped by models of self, morality, and notions of good life rather than by individual stress regulation alone. Drawing on cultural psychology frameworks, this study examines how parents of young children in low-resource settings coped with adversity situated within the context of COVID-19 pandemic. Using a constructivist qualitative design, in-depth interviews were conducted with 16 parents of children under six years of age belonging from economically marginalized communities living in urban Delhi, India. Data were analyzed through Reflexive Thematic Analysis, guided by Kirmayers (2007) model of Cultural Configurations of the Self. These narratives illustrate how coping emerged as a moral, relational, and faith-based practice under conditions of adversity and uncertainty. Sociocentric coping reflects a relational orientation in which well-being is understood as collective, caregiving is regarded as morally central, and emotional regulation is oriented toward preserving family harmony. Cosmocentric coping reflects an orientation toward higher-order forces through which uncertainty is accepted, distress is externalized, and endurance cultivated. The study challenges individualistic models of coping and highlights how care, endurance, and meaning-making are collectively organized in contexts of structural vulnerability. The paper extends theoretical understanding of coping with crisis and calls for a contextually grounded model of parental coping. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.