Innovative Approach Research Articles

Practical Development of Artistic and Creative Activity of Students: from Work Experience

Introduction. In this study, the author addresses the problem of the development of modern innovative educational technologies in the context of artistic and creative activity. The purpose of the study is to reveal the features of the implementation of modern innovative pedagogical approaches in pedagogical artistic and creative practice. Methodology. Artistic and creative activity is studied from the perspective of a personal activity approach as a leading type of pedagogical activity. From the point of view of the competence approach, the main competencies of students are determined within the framework of continuous multi-level specialized education (artistic, aesthetic and socio-pedagogical). The Childrenʼs Academy of Artistic Creativity and Design became a research site. Results. The study shows that the project method is currently in demand in the context of the development of modern innovative educational technologies. The importance for pedagogical artistic and creative practice is particularly noted. It is shown that during the implementation of the project, the student acquires certain artistic and creative competencies necessary for further training in professional artistic and creative activities. Conclusion. In conclusion, the main aspects of the application of the project method in pedagogical artistic and creative practice are shown.

Suppression of Sugarcane Red Rot Disease through Its Rhizospheric Mycoflora

Red rot disease of sugarcane is so devastating in nature that it has been referred to as “cancer of sugarcane”. The sugar industry in India suffered losses more than 500 million US dollars every year due to red rot. So, there is a need to look over the management and control of the disease. Biological control method is an alternative method of chemical pesticides which are an innovative, cost effective and eco-friendly approach. Soil samples were collected from sugarcane rhizosphere of four different varieties viz., CoPk 05191 and CoLk 94184 (resistant to red rot) and CoJ 64 and Co 1148 (susceptible to red rot) planted at ICAR-Indian Institute of Sugarcane Research, Lucknow experimental farm. The samples were subjected for the isolation of rhizospheric mycoflora on Potato Dextrose Agar media and antagonistic activities of the isolates were tested against red rot pathogens (Cf 07, Cf 08 and Cf 09). Isolates showing more than 50 % inhibition with all the three pathotypes (Cf 07, Cf 08 and Cf 09) were selected for further study. Among the twelve selected isolates used for field experiment for the management of red rot, isolate T16 was found to be highly effective. The suppression of red rot offered by rhizospheric isolates is probably due to induced systemic resistance in sugarcane plants or by the enzymatic action of metabolites produced by the rhizospheric mycoflora. The different levels of red rot infected seed cane viz., 5%, 10%, 15%, 20%, 25%, 30%, 35% and 40% were treated with MHAT and planted along with healthy seed canes, infected seed canes, as a control to work out the losses caused by different level of red rot seed infection. The result revealed that a yield loss was recorded with the infected seed. The losses were directly proportionate with the level of red rot infected seed.

Smart Solutions for Diet-Related Disease Management: Connected Care, Remote Health Monitoring Systems, and Integrated Insights for Advanced Evaluation

The prevalence of diet-related diseases underscores the imperative for innovative management approaches. The deployment of smart solutions signifies a paradigmatic evolution, capitalising on advanced technologies to enhance precision and efficacy. This paper aims to present and explore smart solutions for the management of diet-related diseases, focusing on leveraging advanced technologies, such as connected care, the Internet of Medical Things (IoMT), and remote health monitoring systems (RHMS), to address the rising prevalence of diet-related diseases. This transformative approach is exemplified in case studies focusing on tailored RHMS capabilities. This paper aims to showcase the potential of three RHMS in introducing a novel evaluation method and their customisation for proactive management of conditions influenced by dietary habits. The RO-SmartAgeing System uniquely addresses age-related aspects, providing an integrated approach that considers the long-term impact of dietary choices on ageing, marking an advanced perspective in healthcare. The NeuroPredict Platform, leveraging complex neuroinformatics, enhances the understanding of connections between brain health, nutrition, and overall well-being, contributing novel insights to healthcare assessments. Focused on liver health monitoring, the HepatoConect system delivers real-time data for personalized dietary recommendations, offering a distinctive approach to disease management. By integrating cutting-edge technologies, these smart solutions transcend traditional healthcare boundaries.

Unraveling the Neo-Sûfī Paradigm: An Analysis of Dr. Fazlûr Raḥmān's Theoretical Insights and Concepts

This research focuses on Dr. Fazlûr Raḥmān's Neo-Sûfī paradigm, a contemporary departure from traditional perspectives on Sûfīsm aimed at addressing global challenges. The study traces Raḥmān's academic journey from British India, highlighting his influential work advocating for a reevaluation of conventional Islāmic thought in the face of technological advancements and cultural shifts. Through an extensive literature review, the research contextualises the historical development of Sûfīsm, scrutinises traditional views, and assesses modern challenges to Sûfī thought, offering a critical examination of Raḥmān's contributions, particularly the Neo-Sûfī paradigm. The study's theoretical framework is grounded in Raḥmān's innovative approach deeply rooted in Islāmic philosophy and theology. Raḥmān reimagines traditional Sûfī concepts to address contemporary challenges while preserving ties to Islāmic heritage. Drawing insights from scholars like William C. Chittick and Seyyed Hossein Nasr, the research employs an interdisciplinary methodology based on primary sources to analyse the Neo-Sûfī paradigm comprehensively. It aims to position Raḥmān's ideas within the broader context of Islāmic thought, enriching the understanding of the intricate relationship between Sûfīsm, tradition, and modernity. Exploring the evolution of Sûfīsm within the Neo-Sûfī paradigm, the research underscores its adaptability to contemporary challenges, spiritual dimensions, and contributions to social cohesion. It investigates how Raḥmān reconciles tradition and modernity, assessing the compatibility of Sûfī thought with contemporary philosophical currents. The study discusses the implications of the Neo-Sûfī paradigm, including its role in interfaith dialogue, contributions to contemporary Islāmic thought, and policy recommendations. Despite acknowledging limitations, the research concludes that Dr. Fazlûr Raḥmān's Neo-Sûfī paradigm provides a dynamic response to modern challenges, harmoniously integrating tradition and modernity. Its implications extend beyond individual spiritual practice to interfaith dialogue, societal cohesion, and policy recommendations, presenting Raḥmān's paradigm as a valuable source of wisdom in navigating contemporary complexities within the ongoing discourse on Islāmic thought.

Green Ostrich fat waste extracts as a novel potential inhibitor to sustainable corrosion of steel in acidic environments: Electrochemical and DFT evaluation

The shift from traditional chemical corrosion inhibitors to green alternatives, focusing on plant extracts (GCIs), addresses environmental concerns in line with sustainable development goals. An innovative approach explores animal-derived extracts for eco-friendly corrosion inhibition, addressing environmental issues associated with conventional chemical inhibitors. Ostrich Oil, renowned for its nutritional, cosmetic, and pharmaceutical properties, is examined as a potential green corrosion inhibitor for C38 steel in 1 M hydrochloric. Extracted and characterized through GC-FID, Ostrich Oil exhibits corrosion protection analyzed via impedance spectroscopy, potentiodynamic polarization, and gravimetric methods. Complementary SEM and metallurgical microscopy with EDS offer surface insights. DFT and MD simulations explore the relationship between electronic properties and inhibition efficiency. Results show Ostrich Oil's significant corrosion inhibition (up to 94%), attributed to chemical adsorption of fatty compounds. The corrosion mechanism is influenced by Oil extract adsorption, increasing double electrochemical layer resistance. Gas chromatography identifies main compounds, and quantum chemical calculations highlight its reactivity. This research underscores the potential of animal-derived extracts, exemplified by Ostrich Oil, as effective and environmentally friendly corrosion inhibitors, contributing to sustainable corrosion protection practices.

Blockchain-based Decentralized Reward Sharing: The Case of Mining Pools

We introduce a reciprocity protocol , an innovative approach to coordinating and sharing rewards in blockchains. Inherently decentralized and implementable, it puts emphasis on incentives rather than forcing specific sharing rules from the outset. Analyzing the non-cooperative game the protocol induces, we identify a robust, strict, and Pareto-dominant symmetric equilibrium. In it, even self-centered participants show extensive systemic reciprocity. Thus, despite a setting that is generally unfavorable to reciprocal behavior, the protocol enables users to build trust between themselves by taking on a role akin to a social contract.

Optimizing Pneumonia Diagnosis Using RCGAN-CTL: A Strategy for Small or Limited Imaging Datasets

In response to the urgent need for efficient pneumonia diagnosis—a significant health challenge that has been intensified during the COVID-19 era—this study introduces the RCGAN-CTL model. This innovative approach combines a coupled generative adversarial network (GAN) with relativistic and conditional discriminators to optimize performance in contexts with limited data resources. It significantly enhances the efficacy of small or incomplete datasets through the integration of synthetic images generated by an advanced RCGAN. Rigorous evaluations using a wide range of lung X-ray images validate the model’s effectiveness. In binary classification tasks that differentiate between normal and pneumonia cases, RCGAN-CTL demonstrates exceptional accuracy, exceeding 99%, with an area under the curve (AUC) of around 95%. Its capabilities extend to a complex triple classification task, accurately distinguishing between normal, viral pneumonia, and bacterial pneumonia, with precision scores of 89.9%, 95.5%, and 90.5%, respectively. A notable improvement in sensitivity further evidences the model’s robustness. Comprehensive validation underscores RCGAN-CTL’s superior accuracy and reliability in both binary and triple classification scenarios. This advancement is pivotal for enhancing deep learning applications in medical diagnostics, presenting a significant tool in addressing the challenges of pneumonia diagnosis, a key concern in contemporary healthcare.

Numerical simulations and mathematical models in laser welding: a review based on physics and heat source models

The dominant phenomenon in laser welding processes is heat transfer by conduction, making it crucial to gain insights into energy distribution within the heat-affected region, including the melt pool. Thermal analysis enables the description of thermo-mechanical, metallurgical aspects, and also addresses studies related to fluid flow and energy transfer. As research in welding processes has advanced, these models have evolved. This is why it is now efficient to use computational modeling techniques as it allows us to analyze the behavior of laser welding during the process. This underlines the importance of this work which has carried out an exhaustive theoretical literature review with the objective of classifying and describing the numerical simulations of laser welding based on the physics involved. In that sense, the mathematical models and strategies used in laser welding are explored in a general way. Therefore, two types of laser welding by conduction and deep penetration are defined from this point and they are categorized according to the phenomena involved in Model Heat Conduction and Model Integral Multiphysics. This comprehensive review article serves as a valuable resource for higher education students by providing a structured and detailed exploration of laser welding and its mathematical modeling. By classifying and describing numerical simulations based on the physics involved, it offers a framework for students to understand the complexities of this field. Additionally, this innovative approach to organizing and presenting research contributes to educational innovation by facilitating a more efficient and effective learning experience, helping students acquire the knowledge and research skills necessary for advancements in the laser welding domain.

Nanotopology-Enabled On-Site Pathogen Detection for Managing Atopic Dermatitis.

Atopic dermatitis (AD), a prevalent skin condition often complicated by microbial infection, poses a significant challenge in identifying the responsible pathogen for its effective management. However, a reliable, safe tool for pinpointing the source of these infections remains elusive. In this study, a novel on-site pathogen detection that combines chemically functionalized nanotopology with genetic analysis is proposed to capture and analyze pathogens closely associated with severe atopic dermatitis. The chemically functionalized nanotopology features a 3D hierarchical nanopillar array (HNA) with a functional polymer coating, tailored to isolate target pathogens from infected skin. This innovative nanotopology demonstrates superior pathogenic capture efficiency, favorable entrapment patterns, and non-cytotoxicity. An HNA-assembled stick is utilized to directly retrieve bacteria from infected skin samples, followed by extraction-free quantitative loop-mediated isothermal amplification (direct qLAMP) for validation. To mimic human skin conditions, porcine skin is employed to successfully capture Staphylococcus aureus, a common bacterium exacerbating AD cases. The on-site detection method exhibits an impressive detection limit of 103 cells mL-1. The HNA-assembled stick represents a promising tool for on-site detection of bacteria associated with atopic dermatitis. This innovative approach enables to deepen the understanding of AD pathogenesis and open avenues for more effective management strategies for chronic skin conditions.

Sensor Technologies for Hydraulic Valve and System Performance Monitoring: Challenges and Perspectives

AbstractHydraulic fluid power systems are essential for a range of engineering applications such as transportation, heavy industry, and robotics. The scale of the industry is such that hydraulic pumps are estimated to account for 15% of all the energy consumption in the European Union and yet the average efficiency of fluid power systems is only 22%. The digitalization of hydraulic systems offers significant advantages in terms of energy efficiency, performance, reduced maintenance, and automation. However, this requires advances in the integration of smart sensing technologies to provide real‐time feedback on the operation and health of hydraulic components. This review details developing trends in hydraulic fluid power research and provides an overview of progress related to the digitalization of these systems and their integration within an Industry 4.0 framework. The fundamentals of relevant sensor technologies and innovative approaches for integrating sensors into hydraulics systems are discussed. Methods to deliver power to the sensors and associated electronics through harvested pressure ripples are also reviewed. An outlook with respect to future directions in this field is given, including an assessment of the potential for exploiting advanced manufacturing technologies, in particular additive manufacturing, to facilitate successful sensor integration into hydraulic fluid power systems.

External Wall Systems in Passive House Standard: Material, Thermal and Environmental LCA Analysis

The construction sector, a significant consumer of energy, possesses the potential to realize substantial environmental and economic advantages through the adoption of innovative technologies and design approaches. Notably, the Passive House standard, exemplified by energy-efficient single-family homes, emerges as a prominent solution. This study analyzes five external wall systems across multiple stages: (i) a literature review and examination of external wall techniques within the passive standard, utilizing the Passive House Database; (ii) a material and technological assessment of three wood-based and two masonry constructions; (iii) an in-depth thermal performance analysis of selected external partitions; and (iv) a Life Cycle Assessment (LCA) of the external wall systems. Our findings indicate that among the single-family homes built to the passive standard, 50.94% utilized timber constructions, while 34.21% employed masonry. Thermal analysis revealed that the masonry wall, EW-M-01, exhibited superior thermal efficiency with a heat transfer coefficient (U-value) of 0.0889 W/m2K. Meanwhile, the wooden wall, EW-T-01, led its category with a U-value of 0.1000 W/m2K. The LCA highlighted that the wooden wall EW-T-02 presented the lowest integrated non-renewable energy demand (PENTR) at 425.70 MJ/kg and the most favorable Global Warming Potential (GWP), with a reduction of 55.51 kg CO2e. Conversely, the masonry wall EW-M-01 recorded the highest energy demand and CO2e emissions, at 780.96 MJ/kg and 90.59 kg CO2e, respectively. Water consumption was lowest for the EW-T-02 wooden wall (0.08 m3) and highest for the EW-M-02 masonry wall (0.19 m3). Conclusively, our analysis of passive house external walls demonstrates that wood-based systems offer superior performance in terms of materials, thermal efficiency, and LCA indicators, positioning them as the preferred option for sustainable passive construction.

Coupling electrocatalytic CO2 reduction with glucose oxidation for concurrent production of formate with high efficiency

Electrocatalytic reduction of CO2 (CO2ER) coupled with the oxygen evolution reaction (OER) is an energy-intensive process that generates low-value oxygen, limiting its industrial application. To overcome this limitation, here we report a membrane electrode assembly (MEA) system that combines CO2ER with glucose electrooxidation (GEOR) to simultaneously produce formate using bismuth subcarbonate and carbon nanotube hybrid (BOC-CNT) and nickel cobalt oxide decorated on carbon fiber paper (NCO-CFP) as the cathode and anode catalysts, respectively. The BOC-CNT catalyst showed excellent electrocatalytic performance for CO2ER to formate, affording a high FEHCOO- of 97.9 % with current density of 360 mA cm−2 at −0.77 V vs. RHE (-580 mV overpotential), and the NCO-CFP catalyst achieved GEOR at 0.99 V (vs. RHE) with FEHCOO- >98 %. The coupled CO2ER//GEOR MEA exhibits a low onset cell voltage of 1.20 V and reaches ultrahigh apparent Faraday efficiency of formate (>190 %) in a wide range from 1.8 to 2.4 V, achieving ∼ 33.3 % energy savings compared to CO2ER//OER with a high formate yield of 0.92 mol g-1h−1 at 100 mA cm−2. Besides, all generated formate can be collected from the electrolyte on the anode side due to the spontaneous migration of formate under electric field, thus reducing cross-contamination from CO2 and alkaline electrolytes. In addition, the coupled CO2ER//GEOR system exhibited good electrocatalytic stability for at least 32 h. This strategy provides an innovative and promising approach for the co-electrolytic transformation of biomass derivatives and CO2 to formate.

Microclimate-Monitoring: Examining the Indoor Environment of Greek Museums and Historical Buildings in the Face of Climate Change

The preservation of cultural artifacts within museums and historical buildings requires control of microclimatic conditions, and the constantly evolving climate certainly poses a challenge to maintaining recommended conditions. Focused on the Archaeological Museum of Delphi and the Church of Acheiropoietos in Greece, our study evaluates the hygrothermal behavior of these buildings with a specific emphasis on the preservation of cultural heritage objects hosted there. An innovative approach to the real-time analysis of data is utilized, aiming to achieve a timely detection of extreme temperature and humidity levels. A one-year monitoring campaign was carried out to achieve a detailed assessment of the indoor climate in selected museums and historical buildings in Greece. The monitoring campaign was performed using dataloggers that were set to measure and record temperature (T) and relative humidity (RH) values hourly. The results allowed for the detection of extreme temperature and relative humidity values, pinpointing the time period that requires more attention. The museum’s heating, ventilation, and air conditioning (HVAC) systems provide temperature control for visitor comfort, but the temperature still rises in summer, highlighting the impact of external climate factors. The church’s lack of HVAC systems widens the temperature range compared to the museum, but significant hourly fluctuations are not observed, underlining the building’s high thermal mass and inertia. Both buildings demonstrate a significant response to changes in outdoor temperature, emphasizing the need for future adaptation to climate change. The HMRhs and PRD indices indicate minimal microclimate risk in both buildings for temperature and RH, reducing the probability of material damage. The church’s slightly higher HMRhs index values, attributed to relative humidity, increases susceptibility due to sensitive materials. Overall, the study highlights the importance of managing microclimatic conditions in historical buildings and proposes careful adaptations for the protection of cultural heritage.

Stay Alert: Drowsiness Detection with IoT Technology

The "Drowsiness Detection using IoT with Eye Blink Sensor and Buzzer" project aims to address the critical issue of driver fatigue and drowsiness, a major cause of road accidents. Leveraging Internet of Things (IoT) technologies and a combination of eye blink sensors and a buzzer, this system provides a real-time solution for monitoring and alerting drivers when signs of drowsiness are detected. The project focuses on enhancing road safety by preventing accidents caused by driver fatigue Drowsiness detection is a critical aspect of ensuring safety, particularly in domains such as transportation where fatigue-related accidents pose significant risks. In recent years, the proliferation of Internet of Things (IoT) devices has enabled innovative approaches to drowsiness detection systems. This abstract outlines a novel framework for drowsiness detection utilizing IoT technologies. Our proposed system integrates various sensors, including facial recognition cameras, heart rate monitors, and accelerometers, into a networked IoT infrastructure. These sensors continuously monitor key physiological and behavioral indicators associated with drowsiness, such as eye movement patterns, blink frequency, heart rate variability, and head position changes.

Supply Chain as a Service (SCaaS) in Apparel Industry

Supply Chain as a Service (SCaaS) represents an innovative approach for businesses to outsource various aspects of their supply chain, including manufacturing, procurement, warehousing, quality assurance, and logistics. Within the apparel industry, the supply chain encompasses five key categories: design, textile manufacturing, apparel manufacturing, distribution, and end-user purchase. Due to its consumer-centric nature, the apparel supply chain experiences fluctuating demand, posing challenges for effective management. Small apparel businesses often struggle with planning and implementing efficient supply chain strategies, resulting in significant losses, wasted labor, and missed deadlines. This paper proposes the implementation of SCaaS as a tailored solution for apparel units. The primary aim is to offer comprehensive end-to-end management services, ranging from strategic planning to product delivery. By leveraging SCaaS, companies can optimize their time allocation, focusing on customer interactions and the innovation of new products. This approach streamlines operations, enhances efficiency, and mitigates the risks associated with supply chain management, ultimately enabling apparel businesses to better adapt to market dynamics and meet consumer demands effectively.

Lopinavir enhances anoikis by remodeling autophagy in a circRNA-dependent manner

ABSTRACT Macroautophagy/autophagy-mediated anoikis resistance is crucial for tumor metastasis. As a key autophagy-related protein, ATG4B has been demonstrated to be a prospective anti-tumor target. However, the existing ATG4B inhibitors are still far from clinical application, especially for tumor metastasis. In this study, we identified a novel circRNA, circSPECC1, that interacted with ATG4B. CircSPECC1 facilitated liquid-liquid phase separation of ATG4B, which boosted the ubiquitination and degradation of ATG4B in gastric cancer (GC) cells. Thus, pharmacological addition of circSPECC1 may serve as an innovative approach to suppress autophagy by targeting ATG4B. Specifically, the circSPECC1 underwent significant m6A modification in GC cells and was subsequently recognized and suppressed by the m6A reader protein ELAVL1/HuR. The activation of the ELAVL1-circSPECC1-ATG4B pathway was demonstrated to mediate anoikis resistance in GC cells. Moreover, we also verified that the above pathway was closely related to metastasis in tissues from GC patients. Furthermore, we determined that the FDA-approved compound lopinavir efficiently enhanced anoikis and prevented metastasis by eliminating repression of ELAVL1 on circSPECC1. In summary, this study provides novel insights into ATG4B-mediated autophagy and introduces a viable clinical inhibitor of autophagy, which may be beneficial for the treatment of GC with metastasis.

Islamic Education Perspective of Mahmud Yunus

The thinking of Islamic education in the perspective of Mahmud Yunus is a holistic and innovative approach that emphasizes the integration between Islamic teachings and modern knowledge, character building, inclusivity, and the use of participating teaching methods. The contribution of Mahmud Yunus' thought in the field of Islamic education has not only had an impact at the conceptual level, but also seen in its implementation in modern pesantren educational institutions in Indonesia. Many of the holistic and innovative principles he proposes have been applied successfully, helping to shape Islamic education that fits the demands of the times and the needs of the Indonesian people. The goal of Islamic education is to create Muslim individuals who are strong in faith, have noble character, are knowledgeable, and have practical world skills. Mahmud Yunus also championed an Islamic education curriculum that unites religious knowledge and general science, as well as integrated Arabic language teaching. His thinking influenced modern pesantren educational institutions in Indonesia in developing holistic and modern Islamic education in Indonesia.

Innovative FOCUS: A Program to Foster Creativity and Innovation in the Context of Education for Sustainability

This study is based on the urgent need to adapt education systems to meet the challenges of the 21st century. It examines the implementation of the “Innovative FOCUS” program at the secondary school level to promote creative problem-solving skills in the sustainability context. The Innovative FOCUS program employs a two-stage approach, integrating flexibility, originality, creative personality development, and strategic planning. It includes in-service teacher training and a challenge-based learning framework in which students engage in real-world sustainability projects. The program’s effectiveness was evaluated through teacher and student feedback focusing on the development of prototypes addressing sustainability challenges. The implementation of the InFOCUS program in 19 secondary schools demonstrated significant effectiveness. Teachers indicated that the program’s tools were effective in promoting students’ creativity and problem-solving skills. Of the 64 student teams, 62 successfully developed innovative prototypes, reflecting an improved capacity for innovative thinking and underlining the practical impact of the program. The Innovative FOCUS program effectively integrates sustainability education with creative and critical thinking skills. It demonstrates the potential of challenge-based learning in transforming students’ approaches to real-world problems, aligning education with 21st-century sustainability goals. The program’s success highlights the importance of such innovative approaches in contemporary education systems.

Le facteur de croissance des nerfs (NGF) dans l’hypertension pulmonaire (HTP)

Pulmonary hypertension (PH) is the main pathology in lung circulation, characterized by increased pressure in pulmonary arteries and ultimately resulting in right heart failure with potentially fatal outcomes. Given the current lack of available curative treatments, it is of paramount importance to identify novel therapeutic targets. Due to its involvement in pulmonary arterial remodeling, hyperreactivity, and inflammation, our explorations have focused on the nerve growth factor (NGF), offering promising avenues for innovative therapeutic approaches.

Innovative stochastic finite difference approach for modelling unsteady non-Newtonian mixed convective fluid flow with variable thermal conductivity and mass diffusivity

A novel stochastic numerical scheme is introduced to solve stochastic differential equations. The development of the scheme is based on two different parts. One part finds the solution for the deterministic equation, and the second part is the numerical approximation for the integral part of the Wiener process term in the stochastic partial differential equation. The scheme’s stability and consistency in the mean square sense are also ensured. Additionally, a respective mathematical model of the boundary layer flow of Casson fluid on a flat and oscillatory plate is formulated. Wiener process terms perturb the model to be studied. This scheme will be solved in contexts including deterministic and stochastic. The influence of different parameters on velocity, temperature, and concentration profiles is demonstrated in various graphical representations. The main objective of this study is to present a reliable numerical approach that surpasses the limitations of traditional numerical methods to analyze non-Newtonian mixed convective fluid flows with varying transport parameters. Our objective is to demonstrate the capabilities of the new stochastic finite difference scheme in enhancing our comprehension of stochastic fluid flow phenomena. This will be achieved by comprehensively examining its mathematical foundations and computer execution. Our objective is to develop a revolutionary method that will serve as a valuable resource for scientists and engineers studying the modeling and understanding of stochastic unstable non-Newtonian mixed convective fluid flow. This method will address the challenges posed by the fluid’s changing thermal conductivity and mass diffusivity.