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Mindfully fashioned: Sustaining style through product value retention
In the ever-evolving landscape of fashion industry, the pursuit of sustainability and mindful consumption has emerged as an imperative. This study presents an innovative and integrated framework that amalgamates the Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) approach. This comprehensive framework explores the dynamic interplay between Sustainable Mindfulness (SM), Product Value Retention (PVR), Brand Loyalty (BL) and Circular Practices (CP) in the fashion domain. The study underscores Theory of Planned Behavior (TPB) as the theoretical foundation, shedding light on how attitudes, subjective norms, and perceived behavioral control shape SM and, subsequently, PVR. This study explores into the multidimensional aspects of sustainable fashion, enabling a holistic understanding of the nuanced relationships between PVR strategies, and sustainable consumption attitudes. The study sets the stage for a more harmonious coexistence between style and sustainability, charting a course for the fashion industry that values mindfulness, longevity, and environmental responsibility. The findings offer actionable insights for fashion managers, emphasizing strategic approaches to enhance sustainability, consumer awareness, and circular initiatives in the industry. This study not only advances theoretical discourse but also offers actionable insights for fashion brands and policymakers aiming to foster SM among diverse consumer segments. It sets the stage for a more harmonious coexistence between style and sustainability, charting a course for the fashion industry that values mindfulness, longevity, and environmental responsibility. 2024 Elsevier Ltd -
Electrochemical sensing of vitamin B6 using platinum nanoparticles decorated poly(2-aminothiazole)
Vitamin B6 (Vit B6), also known as pyridoxine, is pivotal in fundamental physiological and metabolic processes within the body. Insufficient levels of this essential nutrient may contribute to various health complications. We introduce an electrochemical sensor designed to determine Vit B6 levels precisely. This sensor is constructed through a two-step process: first, by modifying a bare carbon fiber paper electrode (CFP) with poly(2-aminothiazole) (PAT), and second, by electrodepositing platinum nanoparticles onto the modified electrode surface, giving the final working electrode- Pt/PAT/CFP. Electrochemical impedance spectroscopy (EIS) and Cyclic voltammetry (CV) were utilized to examine the electrochemical characteristics of the developed sensor. The characterization of the sensor was done through a range of analytical techniques, including X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and optical profilometric studies. Furthermore, we optimized the sensor's performance by assessing the impact of pH, scan rates, and analyte concentrations. The sensor showed a wide linear dynamic range of 5.0 nM80 M and a low detection limit of 0.054 M. We have successfully quantified Vit B6 levels in tablet formulations and dried palm date fruits. The outcomes of this study hold the promise of substantial progress in Vit B6 quantification, with far-reaching implications across pharmaceuticals, healthcare, and nutritional science. 2024 Elsevier B.V. -
Training in Cultural Competence for Mental Health Care: A Mixed-Methods Study of Students, Faculty, and Practitioners from India and USA
Although the need to train clinicians to provide effective mental health care to individuals from diverse backgrounds has been recognized worldwide, a bulk of what we know about training in cultural competence (CC) is based on research conducted in the United States. Research on CC in mental health training from different world populations is needed due to the context-dependent nature of CC. Focusing on India and USA, two diverse countries that provide complementary contexts to examine CC, we explored graduate students, practicing clinicians, and faculty members perspectives regarding CCtraining they received/provided and future training needs using mixed-methods. The data were collected using focus groups (n = 25 groups total: 15 in India, 11 in USA), and a survey (n = 800: 450 in India, 350 in USA). Our data highlight the salient social identities in these countries, and the corresponding constituents of CC training. Participants in India described a practical emphasis to their CC training (e.g., learning about CC through life experiences and clinical practice experiences) more so than through coursework, whereas participants in USA described varying levels of courseworkrelated toCC along with practice. Participants in both countries considered enormity of CC as a challenge, while those in the US also identified CC training limited to a white, straight, male perspective, hesitancy in engaging with diversity topics, and limited time and competence of the faculty. Strengths of CC training in India and USA are mutually informative in generating recommendations for enhancing the training in both countries. The Author(s) 2024. -
One-pot hydrothermal synthesis of 3D garland BiOI, spherical ZnO, and CNFs onto Ni foam: Supercapacitor performance with enhanced electrochemical properties
This study reported one-pot hydrothermal synthesis of 3D garland BiOI, spherical ZnO, and carbon nanofibers (CNFs) onto Ni foam substrate with improved supercapacitor performance and enhanced electrochemical properties. The synthesized nanocomposites exhibited high specific capacitance (SC) of 1073 g?1 at a current density of 1 A/g and excellent cycling stability with 88.6% retention of original capacity after 5000 cycles in 2M KOH aqueous solution. The findings highlight the potential of 3D materials for use as electrode materials in advanced supercapacitor applications due to their high energy storage capabilities. 2024 Elsevier Ltd -
Comprehensive evaluation and performance analysis of machine learning in heart disease prediction
Heart disease is a leading cause of mortality on a global scale. Accurately predicting cardiovascular disease poses a significant challenge within clinical data analysis. The present study introduces a prediction model that utilizes various combinations of information and employs multiple established classification approaches. The proposed technique combines the genetic algorithm (GA) and the recursive feature elimination method (RFEM) to select relevant features, thus enhancing the models robustness. Techniques like the under sampling clustering oversampling method (USCOM) address the issue of data imbalance, thereby improving the models predictive capabilities. The classification challenge employs a multilayer deep convolutional neural network (MLDCNN), trained using the adaptive elephant herd optimization method (AEHOM). The proposed machine learning-based heart disease prediction method (ML-HDPM) demonstrates outstanding performance across various crucial evaluation parameters, as indicated by its comprehensive assessment. During the training process, the ML-HDPM model exhibits a high level of performance, achieving an accuracy rate of 95.5% and a precision rate of 94.8%. The systems sensitivity (recall) performs with a high accuracy rate of 96.2%, while the F-score highlights its well-balanced performance, measuring 91.5%. It is worth noting that the specificity of ML-HDPM is recorded at a remarkable 89.7%. The findings underscore the potential of ML-HDPM to transform the prediction of heart disease and aid healthcare practitioners in providing precise diagnoses, exerting a substantial influence on patient care outcomes. The Author(s) 2024. -
Seasonal study on the Aquatic and Terrestrial Habitat of Edayar region, Ernakulam, Kerala, India
This study examines the plant diversity and physicochemical characteristics of both aquatic and terrestrial ecosystems in the industrialized region of Edayar, Kadungalloor, Ernakulam, Kerala, India. The research is conducted seasonally, encompassing the four seasons of Kerala: southwest monsoon, northeast monsoon, winter season and summer season. Edayar is home to approximately 400 industries. The main objective of this study is to assess the plant diversity with a specific focus on herb and macrophyte diversity, in the Edayar region, along with analyzing the physicochemical properties of soil and water. Random sampling using quadrat techniques is employed to collect data on species diversity. Diversity indices, such as the Simpson Index and Shannon-Wiener index are utilized to analyze the recorded species diversity. Scoparia dulcis L. among herb species and Eichhornia crassipes (Mart.) Solms among macrophytes were found dominating in all the seasons. The results for the physico-chemical analysis of water and soil were found approaching the threshold of standard limits.The findings provide valuable insights into plant diversity and ecological dynamics of the Edayar region, which have been significantly impacted by industrial activities. The outcomes serve as a basis for the development and implementation of effective conservation and management strategies to mitigate potential ecological risks associated with industrial activities in the region. 2024 World Researchers Associations. All rights reserved. -
Lignin nanoparticles from Ayurvedic industry spent materials: Applications in Pickering emulsions for curcumin and vitamin D3 encapsulation
Lignin nanoparticles (LNP), extracted from spent materials of Dashamoola Arishta (Ayurvedic formulation), shared a molecular weight of 14.42 kDa with commercial lignin. Processed into LNPs (496.43 0.54 nm) via planetary ball milling, they demonstrated stability at pH 8.0 with a zeta potential of ?32 0.27 mV. Operating as Pickering particles, LNP encapsulated curcumin and vitamin D3 in sunflower oil, forming LnE + Cu + vD3 nanoemulsions (particle size: 347.40 0.71 nm, zeta potential: ?42.27 0.72 mV) with high encapsulation efficiencies (curcumin: 87.95 0.21%, vitamin D3: 72.66 0.11%). The LnE + Cu + vD3 emulsion exhibited stability without phase separation over 90 days at room (27 2 C) and refrigeration (4 1 C) temperatures. Remarkably, LnE + Cu + vD3 exhibited reduced toxicity, causing 29.32% and 34.99% cell death in L6 and RAW264.7 cells respectively, at the highest concentration (50 ?g/mL). This underscores the potential valorization of Ayurvedic industry spent materials for diverse industrial applications. 2024 Elsevier Ltd -
APPLICATION OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL INDUSTRY
Artificial Technology is the blockbuster technology today. Pharmaceutical industry is no exception to the technology onslaught. Pharmaceutical industry adapting to the Artificial Intelligence (AI) to improve the overall performance of the industry processes, through improved efficiency in the operations and reduced lead time in the drug discovery. This is done through AIs ability of scanning huge data to speed up the drug discovery stage by identifying prospective drug candidates through technology like Structure-Based Virtual Screening (SBVS) and Fragment-Based Drug Discovery (FBDD). A nascent drug approach called as drug repurposing is very prospective through AI, and AI makes it possible to integrate nanotechnology, targeted drug development and personalised treatment based on genetic and proteomic data. AI has huge applications in the very important drug development stage of clinical trials. Selection of suitable participants, predicting drug responses will have huge cost reduction with the AI technology. In addition to drug trials, AI is transforming the pharmaceutical marketing process. Personalised communication, predictive sales forecasting, automated content generation and sentiment analysis are some of the possible as of now. These applications make the companies offer tailor made marketing strategies specific to physicians and patients and monitor the brand reputation and bring efficiency in the supply chain. Albeit the potential benefits, adoption of AI fully in the pharmaceutical industry has its own challenges. In the areas of data privacy, regulatory compliance and ethics related to drug testing, AI could face serious challenges. As the technology evolves, AI will have its impact on the pharmaceutical industry offering huge growth opportunities. India could emerge as a potential superpower in the pharmaceutical industry if AI is properly harnessed for industry growth. India can be the pharmacy for the entire world in the coming days if industry finds a way to utilize AI properly. 2024, Indian Pharmaceutical Association. All rights reserved. -
Simultaneous X-Ray and Optical Polarization Observations of the Blazar Mrk 421
We present near-simultaneous X-ray and optical polarization measurements in the high synchrotron peaked (HSP) blazar Mrk 421. The X-ray polarimetric observations were carried out using Imaging X-ray Polarimetry Explorer (IXPE) on 2023 December 6. During IXPE observations, we also carried out optical polarimetric observations using 104 cm Sampurnanand telescope at Nainital and multiband optical imaging observations using 2 m Himalayan Chandra Telescope at Hanle. From model-independent analysis of IXPE data, we detected X-ray polarization with degree of polarization (?X) of 8.5% 0.5% and an electric vector position angle (?X) of 10.6 1.7 in the 2?8 keV band. From optical polarimetry on 2023 December 6, in B, V, and R bands, we found values of ?B = 4.27% 0.32%, ?V = 3.57% 0.31%, and ?R = 3.13% 0.25%. The value of ?B is greater than that observed at longer optical wavelengths, with the degree of polarization suggesting an energy-dependent trend, gradually decreasing from higher to lower energies. This is consistent with that seen in other HSP blazars and favors a stratified emission region encompassing a shock front. The emission happening in the vicinity of the shock front will be more polarized due to the ordered magnetic field resulting from shock compression. The X-ray emission, involving high-energy electrons, originates closer to the shock front than the optical emission. The difference in the spatial extension could plausibly account for the observed variation in polarization between X-ray and optical wavelengths. This hypothesis is further supported by the broadband spectral energy distribution modeling of the X-ray and optical data. 2024. The Author(s). Published by the American Astronomical Society. -
Eco-Conscious Silver Nanoparticles via Quassia indica: Characterization and Multifaceted Applications
This research work explores the green synthesis of silver nanoparticles using Quassia indica (QI-Ag NPs), a natural plant extract, as a stabilizing and reducing agent. The synthesized QI-Ag NPs were characterized using various analytical techniques, including UV-Visible spectroscopy, X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), Transmission Electron Microscopy (HR-TEM) and Selected Area Electron Diffraction (SAED). The UV-Visible analysis revealed a characteristic peak at 430 nm, indicating the successful formation of AgNPs. XRD analysis unveiled the crystalline nature of the nanoparticles, with four distinctive peaks corresponding to the silver crystallographic planes. SEM and EDX provided insights into the morphology and chemical composition of the QI-AgNPs. Moreover, TEM and SAED elucidated the structural attributes and crystallinity of the nanoparticles. The Ag NPs exhibited a spherical structure and crystalline nature, as supported by both SAED and XRD findings. The zeta potential of QI-Ag NPs exhibited a value of-24.2 mV. The synthesized QI-Ag NPs were evaluated for their photocatalytic potential, demonstrating a remarkable 97% degradation of Crystal Violet dye. Furthermore, comprehensive studies encompassing antioxidant, antimicrobial and cytotoxicity assessments were conducted, showcasing the multifaceted applications of these nanoparticles. This research underscores the promising potential of Q. indica-mediated silver nanoparticles as environmentally benign and versatile nanomaterials. 2024 World Scientific Publishing Company. -
ANALYSIS, ASSESSMENT, AND MANAGEMENT OF ENVIRONMENTAL AIR POLLUTION USING ENVIRONMENTAL ENGINEERING IN DEVELOPING COUNTRIES
Recent studies underscore the value of contemporary technology and gas emissions mitigation while overlooking the necessity of optimal fuel in Developing Countries (DC). DC's historical economic expansion has significantly depended on fossil fuels, resulting in severe environmental air pollution (EAP) challenges. The separation of economic progress from pollution has been the central emphasis in advancing environmental civilization in emerging countries. This study presents an analysis, assessment, and management of EAP using environmental engineering (EE) in DC. This work has examined the evolution of EAP regulations in DC, emphasizing a strategic shift from emission regulation to Air Quality Management (AQM). The regulation of Sulfur dioxide (SO2) emissions addressed the worsening of acid rain in DC. Since 2015, regulatory measures across several sources and industries have aimed to decrease the total amount of Fine Particulate Matter (FPM2.5), signifying a shift towards an AQM-focused policy. Escalating ozone (O3) pollution necessitates integrated management measures for O3 and FPM2.5, focusing on their intricate photochemical reactions. Significant enhancement of AQM in DC, as a crucial metric for the efficacy of sustainable economic development, necessitates the profound carbon reduction of the DC's energy infrastructure and the establishment of more integrated strategies to tackle EAP and climate change in DC concurrently. 2024, Rotherham Academic Press Ltd. All rights reserved. -
Tuning the electronic dimensionality and bandgap in Cs2AgBiX6 (X = Br, Cl) for photovoltaic applications: a DFT-1/2 study of cation disorder
Nontoxic, stable, and experimentally realized lead-free halide double perovskites, Cs2AgBiX6 (X = Br, Cl), attracted much attention for solar cell applications. However, their reduced electronic dimensionality and indirect (wide) bandgap, limiting solar energy absorption efficiency, are not mostly suitable. To address such issues, we employ the computationally efficient DFT-1/2 + SOC method to study the electronic structure of cation-ordered and cation-disordered materials comparatively. Our study explores the impact of cation disorder in tuning the electronic dimensionality, demonstrating how the disorder effect reduces bandgaps, increases solar energy absorption, enhances band dispersion, and decreases carrier effective masses for better photovoltaic performance. We observe an evolution of the electronic dimensionality in the disordered systems, influencing the carrier effective masses and absorption properties. Fractional (and non-integer) electronic dimensionality appears to be an essential concept in understanding the optoelectronic properties. The direct bandgap, high absorption in the desired energy range, and mostly lower effective masses of the disordered systems make them suitable for solar cell applications. 2024 The Royal Society of Chemistry. -
Evaluating the effect of different ligands on the supercapacitance and hydrogen evolution reaction studies of Zn-Co MOF
Metal-Organic Frameworks (MOFs) have recently attracted a lot of interest because of their potential uses in energy storage and catalysis. In this study, we investigate the impact of various ligands on the electrochemical performance of Zn-Co MOFs for both energy storage and hydrogen evolution reaction (HER) studies. Specifically, Zn-Co MOFs are synthesized using different ligands, and their structural and electrochemical properties are characterized by a range of analytical techniques. 2,5-dihydroxybenzoic acid (DBA) and benzene-1,2,4,5-tetracarboxylic acid (BTC) are employed due to their distinct structural features and potential effects on MOF performance. Subsequently, electrochemical studies are conducted to assess the supercapattery performance and HER activity of these MOFs. The specific capacitance and overpotential value at 10 mA/cm2 of Zn-Co/DBA MOF is observed to be 1775.3 F/g and 186 mV, whereas that of Zn-Co/BTC MOF is found to be 136.6 F/g and 279 mV. The MOF synthesis using DBA as a ligand is more effective for energy-related applications. This study aims to report a multifunctional MOF composite for energy and environmental applications with better efficiency than other reported systems. Our findings provide insights into how the choice of ligand influences the structural properties and electrochemical behavior of Zn-Co MOFs, shedding light on the potential of these MOFs as versatile materials for energy storage and HER applications. 2024 Elsevier B.V. -
Na+ doped CuO: A new paradigm electrode material for high performance supercapacitors
This study investigates the influence of sodium doping on the properties of cupric oxide (CuO) thin films synthesized via spray pyrolysis. Comprehensive characterization was conducted using X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDAX), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FESEM), Raman spectroscopy, Hall effect measurements, and electrochemical studies. All films exhibited p-type conductivity, with an optical band gap variation from 1.53 to 1.73 eV. XRD analysis confirmed the dominance of monoclinic CuO, with minor phases of Cu2O and Cu4O3. EDAX and XPS verified the incorporation of Cu, O, and Na elements. FESEM revealed a densely packed morphology with uniform particle distribution and rough surfaces in the electrically optimized film. The Raman spectra of doped samples showed increased intensity and sharpness, attributed to Na + ion-induced polarizability enhancement. Hall effect measurements indicated a tenfold decrease in carrier concentration and a more than tenfold increase in mobility upon sodium doping. Films doped with 4 at.% sodium exhibited the lowest resistivity. Additionally, Na doping enhanced the electrochemical performance of CuO. These findings demonstrate that sodium doping significantly enhances the electrical, optical and electrochemical properties of CuO thin films, making them suitable for applications in optoelectronic devices and supercapacitors. 2024 Elsevier Ltd and Techna Group S.r.l. -
Deciphering the properties of UV upturn galaxies in the Virgo cluster
The UV upturn refers to the increase in UV flux at wavelengths shorter than 3000 observed in quiescent early-type galaxies (ETGs), which still remains a puzzle. In this study, we aim to identify ETGs showing the UV upturn phenomenon within the Virgo galaxy cluster. We utilized a colourcolour diagram to identify all potential possible UV upturn galaxies. The spectral energy distributions (SED) of these galaxies were then analysed using the CIGALE software; we confirmed the presence of UV upturn in galaxies within the Virgo cluster. We found that the SED fitting method is the best tool to visualize and confirm the UV upturn phenomenon in ETGs. Our findings reveal that the population distributions regarding stellar mass and star formation rate properties are similar between UV upturn and red sequence galaxies. We suggest that the UV contribution originates from old stellar populations and can be modelled effectively without a burst model. Moreover, by estimating the temperature of the stellar population responsible for the UV emission, we determined it to be 13 000 K to 18 000 K. These temperature estimates support the notion that the UV upturn likely arises from the contribution of low mass evolved stellar populations (extreme horizontal branch stars). Furthermore, the Mg2 index, a metallicity indicator, in the confirmed upturn galaxies shows higher strength and follows a similar trend to previous studies. This study sheds light on the nature of UV upturn galaxies within the Virgo cluster and provides evidence that low-mass evolved stellar populations are the possible mechanisms driving the UV upturn phenomenon. 2024 The Author(s). -
Magnetic field and light dependant supercapacitor behaviours of Mn3O4-rGO hybrid nanocomposites
Recently, hybrid nanostructures have been very promising candidates for energy generation and storage applications in nanotechnology. Here, Manganese Oxide (Mn3O4) decorated reduced graphene oxide (rGO) nanosheets hybrid composite was synthesised in chemical methods. The hybrid nanocomposite shows supercapacitance performance under a magnetic field and light irradiation. The magnetoelectrochemistry behaviour of the material was studied by varying external magnetic fields and the charge storage behaviours depending on the magnetic field. Additionally, the charge storage behaviour also changes under visible light irradiation. Interestingly, 82% enhancement is obtained under visible light. Therefore the present work gives a new pathway to understand the charge storage behaviour under light and magnetic fields. Qatar University and Springer Nature Switzerland AG 2024. -
Environmental degradation in geopolitical risk and uncertainty contexts for India: A comparison of ecological footprint, CO2 emissions, and load capacity factor
This study assesses the role of geopolitical risk and uncertainty in the degradation of the environment by forming the functions for ecological footprint, CO2 emissions, and load capacity factor for the period 19902019 in India. Besides, the specified function endogenizes economic growth, renewable energy consumption, and natural resource rent as the additional covariates. The use of the autoregressive distributed lag model (ARDL) confirms the long-run relationship between study variables. Further, the dynamic simulations of the autoregressive distributed lag model (DYNARDL) outcomes show that geopolitical risk improves the quality of the environment by reducing the ecological footprint and CO2 emissions. However, it degrades the environment by reducing the load capacity factor. Furthermore, the uncertainty improves the environmental quality by reducing the CO2 emissions and ecological footprint, but the reduced load capacity factor due to uncertainty implies the degradation of environmental quality in India. Given these findings, the study proposes different environmental conservation policies. 2023 Elsevier Ltd -
Detection of high-frequency pulsation in WR135: Investigation of stellar wind dynamics
We report the detection of high-frequency pulsations in WR 135 from short-cadence (10 minute) optical photometric and spectroscopic time series surveys. The harmonics up to the sixth order are detected from the integrated photometric flux variations, while the comparatively weaker eighth harmonic is detected from the strengths of the emission lines. We investigate the driving source of the stratified winds of WR 135 using the radiative transfer modeling code, CMFGEN, and find the physical conditions that can explain the propagation of such pulsations. From our study, we find that the optically thick subsonic layers of the atmosphere are close to the Eddington limit and are launched by the Fe opacity. The outer optically thin supersonic winds (Tross = 0.1 0.01) are launched by the He II and C IV opacities. The stratified winds above the sonic point undergo velocity perturbation that can lead to clumps. In the optically thin supersonic winds, dense clumps of smaller size (fVFF = 0.27 0.3, where fVFF is the volume filling factor) pulsate with higher-order harmonics. The larger clumps (fVFF = 0.2) oscillate with lower-order harmonics of the pulsation and affect the overall wind variability. 2024. The Author(s). -
Pure and suggestive impulse buying in mobile shopping app: shopping pattern of young consumers
Purpose: This study differentiates pure impulse buying behaviour from suggestive impulse buying behaviour in using mobile shopping applications (apps). This study aims to assess the moderating effects of instant discount and cashback promotional offers along with the mediating effects of impulse buying intention (IBI) and user satisfaction (US), using the app stimuli (performance expectancy, effort expectancy, layout, atmosphere, privacy and security). Design/methodology/approach: The study was done in three stages: analysis of variance, followed by structural equation modelling (SEM) and paired t-tests. Findings: The results showed that instant discounts and cashback offers are different from each other for the mediating variable IBI. The SEM results for pure impulse buying showed that, except for layout, the remaining variables have a positive relationship with IBI. For suggestive impulse buying, effort expectancy and layout were significantly related to both the mediating variables. Finally, pure and suggestive impulse buying behaviour showed significant differences. Originality/value: Previous studies have looked into impulse buying in its generic sense and not through the types of impulse buying they were measuring. As impulse buying behaviour is a predominant theme for discussion today, marketing professionals and researchers must comprehend the impact of app stimuli in the context of select types of impulse buying behaviour. 2024, Emerald Publishing Limited. -
A homotopy-based computational scheme for two-dimensional fractional cable equation
In this paper, we examine the time-dependent two-dimensional cable equation of fractional order in terms of the Caputo fractional derivative. This cable equation plays a vital role in diverse areas of electrophysiology and modeling neuronal dynamics. This paper conveys a precise semi-analytical method called the q-homotopy analysis transform method to solve the fractional cable equation. The proposed method is based on the conjunction of the q-homotopy analysis method and Laplace transform. We explained the uniqueness of the solution produced by the suggested method with the help of Banach's fixed-point theory. The results obtained through the considered method are in the form of a series solution, and they converge rapidly. The obtained outcomes were in good agreement with the exact solution and are discussed through the 3D plots and graphs that express the physical representation of the considered equation. It shows that the proposed technique used here is reliable, well-organized and effective in analyzing the considered non-homogeneous fractional differential equations arising in various branches of science and engineering. 2024 World Scientific Publishing Company.