Blueprint For Research Research Articles

Team science in interdisciplinary health professions education research: a multi-institutional case study.

The interdisciplinary nature of health professions education requires exploration of problems by interdisciplinary research teams. Drawing on the Dynamics of Cross-disciplinary Research Development conceptual framework, this study explores the processes and experiences of an interdisciplinary research team, identifying elements of successful collaboration. Case study data were collected from a team of nine researchers from six universities. Data included meeting minutes and researcher reflections. Researcher reflection and meeting minute themes converged within the framework constructs: Contexts and inputs, social learning processes, social capital outcomes, and knowledge and human capital outcomes. This study provides a blueprint for interdisciplinary researchers indicating that successful collaboration starts with transparent, distributed leadership. The convergence of data illustrates how social learning processes, social capital outcomes, and knowledge and human capital outcomes facilitate research team outcomes.

Major components of RNAi gene families in Oryza sativa cultivar Kitaake: In-silico discovery and characterization

BackgroundThe Oryza sativa cultivar Kitaake is a promising new model rice for research due to its short life cycle (9 weeks), adaptability to greenhouse conditions, readily accepts foreign genes, and its complete genome sequence is accessible, providing a valuable blueprint for researchers. However, its major RNA interference (RNAi) gene families (DCLs, AGOs, RDRs) have not yet been studied. These gene families influence target-specific protein-coding gene expression and biotic and abiotic stresses, regulating plant growth and development. ObjectivesThis study aims to identify and characterize RNAi gene families from the Kitaake rice. MethodsThis study has been designed by in-silico analysis to explore major RNAi genes highlighting their molecular functions, phylogenetic groups, regulatory factors, and other vital characteristics of Kitaake rice corresponding to OsRNAi genes. ResultsThis study has identified 10 DCLs, 21 AGOs, and 7 RDRs as major RNAi proteins of Kitaake rice corresponding to OsRNAi by BLASTP search. Domain analysis has been revealed the RNase III, PAZ, and Piwi domains are related to gene silencing processes. According to synteny study, Kitaake and rice have the most homology in 33 RNAi gene pairs, suggesting they share a chromosomal order and similar functions. The majority of OsKRNAi proteins have been located in the nucleus and chloroplast, which are related to gene silencing. Gene silencing and ribonuclease III activity are key terms from gene ontology (GO) analysis, which is part of the gene silencing process. Gene regulatory analysis has identified some important transcription factors including ERE, which participates in DNA binding and microRNAs (miRNAs) including 'Osa-MIR168' improves rice resistance to blast disease. The investigation of cis-acting regulatory elements in OsKRNAi genes has shown various crucial components, including MBS, W-box, LTR, ABRE, ARE that are linked with the different stresses. Genes (such as OsKAGO1d) were found to be overexpressed in target of rapamycin (TOR), increasing susceptibility to pathogens. ConclusionThe findings of this study may be useful resources for further experimental investigation on the improvement of Kitaake rice crop against different stresses.

Knowledge‐Based Deep Learning to Predict Vegetation Carbon, Nitrogen and Phosphorus Densities in China’s Shrublands

AbstractAccurate estimations of carbon (C), nitrogen (N), and phosphorus (P) densities in shrublands are pivotal for assessing terrestrial ecosystem carbon sequestration. Combining in‐situ investigations and machine learning facilitates large‐scale patterns mapping, however, which often overlooks underlying ecological regulations. Here we utilize data from 1,122 survey plots across China's shrublands and develop a novel knowledge‐based deep learning framework that integrates a structural equation model (SEM) to elucidate mechanisms and construct an artificial neural network (ANN) based on these causal relationships. Results show that biomass allocation to different organs follows allometric regulations and that N and P concentrations maintain a degree of stoichiometric homeostasis following biological stoichiometry theory. This insight guides the construction of our ANN, which outperforms both SEM and other prevalent machine learning methods. By leveraging ecological theories to inform model construction, our framework not only enhances prediction accuracy and explainability but also provides a methodological blueprint for ecological research.

Advancements in Cooperative Mobile Robots Control Strategies for Large-Scale Material Transport

This paper explores groundbreaking advancements in control strategies for cooperative mobile robots used in large-scale material transport, a critical aspect of modern industrial, manufacturing, logistics, and construction sectors. It delves into the development of sophisticated systems that enable seamless coordination among multiple mobile robot systems. The research presents a novel hierarchical finite state automaton for dynamic mission adaptation and a null space-based control scheme for precise task execution and enhanced system resilience. The introduction of Mecanum wheels facilitates flexible movement and manipulation of materials, thereby increasing operational efficiency and safety. Cutting-edge sensory technology, including LiDAR, and the implementation of the Robot Operating System are highlighted for their roles in enhancing autonomous navigation and intelligent operation. Additionally, the paper discusses the impact of centralized and decentralized control methods in ensuring safe, cooperative object transport. The findings contribute to the vision of Industry 4.0 by promoting the integration of automation and robotic cooperation in complex environments and present a foundational blueprint for further research. Challenges for future work such as scalability, communication efficiency, collision avoidance, and energy efficiency are also considered, underscoring the need for ongoing development of robust and scalable robotic systems to address modern transport challenges.

Exploring Chinese Characteristics in Science Fiction Films: A Case Study of 'Wandering Earth'

Chinese science fiction films were first created in the 1930s, but few outstanding works appeared until the beginning of the 21st century. With the appearance of Wandering Earth in the 2019 Spring Festival, Chinese science fiction films entered a new stage of development.This paper, using the 'Wandering Earth' series as a blueprint for research, first summarizes the development of Chinese science fiction films. Secondly, it focuses on analyzing why 'Wandering Earth' can be considered a genuinely Chinese hard science fiction film.Finally, through the analysis of the Wandering Earth series, we will summarise the future creative direction of Chinese sci-fi films and the experience that can be learnt from it, so as to accumulate creative experience for building domestic sci-fi film IP in the future.

Theory-Guided Multiclass Text Classification in Online Academic Discussions

ABSTRACT Machine learning (ML) and deep learning (DL) provide significant opportunities to enhance our understanding of idea generation in asynchronous online discussions (AODs). Drawing on the interaction analysis model (IAM) as our theoretical framework, we built one baseline ML and three DL systems to automate message classification when assessing collaborative knowledge construction depth in academic AODs. The viability of these systems was demonstrated via four offerings of a traditional online course. We achieved 79% as the highest overall accuracy score across all phases of the IAM. To the best of our knowledge, this study is the first to classify AOD messages across all IAM phases. We contribute to the theory by updating the IAM to better explain how to promote deeper interactions in AODs. Additionally, we provide a methodological blueprint for future research where classifying text is crucial.

Wealth in Water: A Blueprint for Sustainable Global Ocean Research

Pushing forward with leveraging water resources, promoting international cooperation, and ensuring transparency in deep-sea mining operations. There is also a concern about where to discharge the toxins of unpurified water. Artificial Intelligence has created a dominance in the applications field with a totally automated system. Out of a thorough analysis completed with indicators, satellite radar, and A Journals, there are 30 years of research and 8 years of monitored testing to achieve accuracy and relevance. The patents in place are, Oceanic Mining System (4446636), Flexible Solar Skin in Combination with an Airplane (4768738), Cargo Torpedo (4421050), Oceanic seaplow system (4398362), and previous articles like “Is Extracting Lithium and deep-sea mining more sustainable?”, “AI as a Means of Water Purification Protection”, “Global Water Distribution”, and “Can Deep Sea Water be Processed into Potable Water and Distributed into the Middle East’? To report some ballpark numbers on the proposal and how we would navigate these projects, there will be an exact location of where the plant will be built as well as a water/salinity report of the water being treated. There are still issues with analyzing the cost of desalination compared to other alternatives. Deep Sea Water proves to be a higher quality water and the investment is well worth it. The surveys lean toward clients preferring the International Standards Operating Procedure. All recipients agree there should be a sense of urgency on water shortages. Currently, AI has proven to be a vital asset in eliminating biases and expenses.

Untangling the Paradoxical Relationship Between Religion and Business: A Systematic Literature Review of Chief Executive Officer (CEO) Religiosity Research

Despite numerous chief executive officers (CEOs) citing their religious convictions as the primary guiding framework for their decision-making, leadership behavior, business philosophy, and motivation to contribute to society, the impact of CEOs’ religious convictions is relatively limited in the business literature. However, the widespread yet potentially ambiguous impact of CEO religiosity, encompassing both a CEO’s religious denomination and level of religiosity, on individual, organizational, economical, and societal levels remains a neglected area of research. This gap is attributed to challenges in conceptualizing and measuring this multifaceted construct, with existing research scattered and predominantly confined to the ethics domain. Notably, this oversight is significant given the pivotal role that CEOs, as primary decision-makers, play in organizational dynamics. This article aims to address this gap by conducting a systematic literature review of 50 articles focused on CEO religiosity, seeking to enhance the understanding of personal religion in the business world. Through an analysis of publication trends, methodological approaches, theoretical frameworks, and empirical findings, the review not only offers insights for future research and theorizing but also proposes a conceptual framework for understanding and advancing CEO religiosity research. Additionally, this review identifies specific areas warranting further investigation, thereby highlighting existing research gaps and providing explicit starting points for future research. Through these contributions, this article provides a blueprint for future research on CEO religiosity and holds significant implications for management practice.

Analyzing the Spiritual Connotation of Japanese Pop Culture from the Course of Modernization Based on Contemporary Japanese Writers

The development of pop culture in Japan has long historical roots. Since its post-war modernization, Japan has successfully transformed itself from an old culture-importing country to a culture-exporting country. The article focuses on a number of epochal points since Japan's post-war renaissance, analyzing a number of representative Japanese authors and their works from 1945 to the present, and understanding the birth and spread of Japanese popular culture. Studies have shown that the development of Japanese popular culture has been heavily influenced by European and American culture, but has also demonstrated rebellion and reflection on past cultures and ideologies, ultimately opening up a wide range of cultural areas on this basis. The article takes the representative writers and works of contemporary Japan as the blueprint for research, and finds that Japanese pop culture has a unique rebellious character and humanistic sentiment in its spiritual connotation. In the present day, the Japanese national psyche, on the other hand, interacts and influences popular culture.

Public Opinions on Removing Disincentives and Introducing Incentives for Organ Donation: Proposing a European Research Agenda.

The shortage of organs for transplantations is increasing in Europe as well as globally. Many initiatives to the organ shortage, such as opt-out systems for deceased donation and expanding living donation, have been insufficient to meet the rising demand for organs. In recurrent discussions on how to reduce organ shortage, financial incentives and removal of disincentives, have been proposed to stimulate living organ donation and increase the pool of available donor organs. It is important to understand not only the ethical acceptability of (dis)incentives for organ donation, but also its societal acceptance. In this review, we propose a research agenda to help guide future empirical studies on public preferences in Europe towards the removal of disincentives and introduction of incentives for organ donation. We first present a systematic literature review on public opinions concerning (financial) (dis)incentives for organ donation in European countries. Next, we describe the results of a randomized survey experiment conducted in the United States. This experiment is crucial because it suggests that societal support for incentivizing organ donation depends on the specific features and institutional design of the proposed incentive scheme. We conclude by proposing this experiment's framework as a blueprint for European research on this topic.

A Multilevel Perspective on High-Performance Work System, Mindfulness, Employee Work Well-Being, and Employee Creative Engagement

As the basis of firm innovation, employee creativity engagement plays an important role in this process. According to strategic human resources management, high-performance work systems (HPWS) (organizational level) and mindfulness (individual level) trigger employee creativity in improving several work-related outcomes like work well-being and employee creativity. However, existing studies that have considered the relationships between HPWS and the underlying/boundary mechanism (organization-to-employee) are scarce. A cross-level influence of the hierarchical linear model based on 44 enterprises and 382 employees in Taiwan indicated: Based on the findings of the study, HPWS and mindfulness have significant positive effects on employee creativity. While HPWS enhanced employee creative engagement by increasing employee work well-being, at the same time, employee mindfulness could improve employee creative engagement by increasing employee work well-being. We also find strong evidence that the system is an important organizational factor that modifies work well-being and employee creative engagement relationship; furthermore, employees’ work well-being may affect mood disturbances and stress reduction in association with creative engagement and mindfulness. The findings of our study shed light on a blueprint for future research into HPWS, mindfulness, and employee creativity is presented. Taking these findings into account, we discussed them both theoretically and practically.

NFT auction: Implementing smart contracts for decentralized transactions

In the wake of blockchain and Web3 technological advancements, Non-Fungible Tokens (NFTs) have emerged as prominent digital assets within the realms of art, gaming, and virtual commodities. Unlike their traditional counterparts, NFT auctions harness the virtues of decentralization, transparency, and immutability, ushering in a new era for trading artworks and other digital assets. This paper embarks on an exploration, first laying down the foundational principles of blockchain technology and NFTs. A comparative analysis follows, juxtaposing the dynamics of NFT auctions with the modus operandi of traditional auctions. Within the theoretical scaffold, the nuances of decentralization and trust in NFT auctions are elucidated, spotlighting the pivotal role of smart contracts throughout the auction trajectory. The emphasis also gravitates towards transparency and security, two cornerstones ensuring the integrity of the auction process. Diving into the methodology, this section delineates the research blueprint and the techniques employed for program testing. Delving into the practicalities, the discourse meticulously unpacks the architecture and operability of the smart contract, gauging its efficacy through rigorous assessments. Beyond the present scope, the paper ventures to uncover potential applications and horizons awaiting NFT auctions across diverse sectors.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID(Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Influence of Investor Behavior on Investment Choices among Equity Fund Managers of Listed Firms at Nairobi Securities Exchange-Kenya

Purpose: This study sought to determine how market factors influence investment decisions in Nairobi Securities Exchange-Kenya. The study would offer valuable contributions from both a theoretical and practical standpoint where it contributes to the general understanding of the drivers of investment in the Nairobi Securities Exchange in Kenya.
 Methodology: The study adopted positivism philosophy because the study variables were based on facts derived from the empirical literature review and the theoretical premises discussed in chapter two. Its results are quantitative and explain the relationship between the variables quantitatively. This research used a descriptive research design that allows a researcher to get adequate data from a small population cost-effectively and easily by use of a questionnaire as the research instrument. It is the structure, or the blueprint of research that directs the process of research from the formulation of the research questions and hypotheses to reporting on the research findings Krishnan, (2015). Primary data was collected using standard questionnaires with both closed and open-ended questions. Cronbach’s Alpha Test was used to test the internal consistency reliability of measurements. Data was obtained from the unit trusts and pension funds in Nairobi County. The study was conducted during the 2010- 2019 period. This study adopted a census of all fund managers the Nairobi Securities Exchange that have been actively trading for the period starting 2010-2019. The target population for this study was 129 fund managers hence a census of all equity fund managers at the NSE. Quantitative data was coded to facilitate analysis using Statistical Package for Social Scientists (SPSS 23). The study performed tests on statistical assumptions such as test of regression assumptions and statistics used. This included tests of reliability, normality, autocorrelation, panel root test, cointegration, linearity, independence, heteroscedasticity, and multicollinearity. Data was extracted from the financial statements and NSE handbooks, Excel program was used to calculate ratios relevant to the study variables. Descriptive statistics were used to summarize the study variables; group behavior, accounting information, firm characteristics, and market factors of fund managers at NSE.
 Findings: The study concluded that more attention should be focused on firm characteristics to achieve the best investment choices.
 Unique Contribution to Theory, Practice and Policy: The study was guided by finance theories that acted as its base that supported the empirical literature review which included Resource Based Theory (RBT), agency theory, herding theory and prospect theory. More attention should be paid to the predictors in the order of the magnitude of their effect on investment decision-making.

Integrating multidisciplinary perspectives in complex anal fistula management: a blueprint for future research and precision surgery.

Integrating multidisciplinary perspectives in complex anal fistula management: a blueprint for future research and precision surgery.

Investigating the Impacts of Compulsive Sexual Behaviours on Women Using Descriptive Phenomenology: A Research Agenda

Abstract Introduction Sexual addiction (SA) and compulsive sexual behaviour (CSB) are concepts used to characterise a nascent field of research and phenomena that can have major personal, relational, and psychological effects on individuals, their intimate relationships, and society. Impacts are manifold and may include emotional, relational, physical, sexual, and/or spiritual consequences. Literary analysis suggests that there is a wide knowledge gap in systematic in-depth qualitative studies that examine the lived experiences of impacted women. Methods This conceptual paper presents a blueprint for qualitative research into female partner well-being following the discovery or disclosure of SA/CSBs by their male partners. After three years of collecting data (2021–2023), the prototype has been refined to the point where the descriptive phenomenology research design merits in-depth coverage of its constituent elements. Results and Contribution The qualitative methodologies of this paper were developed to give voice to and better comprehend this understudied demographic. This methodological article advances qualitative knowledge creation in an emergent field of investigation, offering prospects for healing and recovery for individuals and relationships. Conclusions This paper presents a comprehensive research design rather than any data or findings. This focus is intended and offers new prospects to build a nascent field of investigation. More specifically, other research may benefit from either adopting and/or adapting similar methodological approaches that examine the essences of human lived experiences. This paper lays the foundation for an important future research agenda. Policy Implications The research methodological design presented in this paper is suited to facilitate social policy development through targeted strategies that may better validate and deliver more appropriate care to women in need. More specifically, by applying the approaches presented in this paper to the in-depth study of SA/CSB-impacted intimate partners, there is an opportunity to promote social consciousness, enhance empathy, and advance this field of investigation.

Real Time Object Detection Using YOLOv4

Abstract: This research paper introduces a robust real-time object detection system, leveraging the cutting-edge capabilities of the YOLOv4 (You Only Look Once) deep learning framework.The integration of this system with a webcam in the Google Colab environment forms a novel and accessible platform for live object detection. The paper meticulously details the methodology behind theintegration, providing comprehensive insightsinto the intricatesteps taken to achieve seamless real-time detection. Key aspects covered include the configuration and acquisition of YOLOv4 model weights, setup of the Google Colab environment, and the challenges encountered in optimizing and streaming webcam feeds in this unique computational setting. Implementation details are articulated through Python code snippets, offering a practical guide for researchers and practitioners interested in replicating or extending the system. The code encompasses the initialization of YOLOv4, handling real-time webcam feeds, and harnessing GPU acceleration within the Google Colab framework to ensure optimalperformance. Results presented in the paper showcase the efficacy of the integrated system through real-time object detection on webcam feeds. Evaluation metrics, including accuracy and processing speed, provide a quantitative assessment of the system's performance. Comparative analyses against other state-of-the-art object detection methodologies further highlight the strengths and capabilities of the YOLOv4-based system. The discussion section delves into the advantages and limitations of the implemented system, offering insights into potential applications across domains such as surveillance, robotics, and human-computer interaction. The user-friendly nature of the Google Colab environment is emphasized, promoting accessibility to advanced computer visiontechnologies. In conclusion, this research significantly contributes to the democratization of computer vision technologies, providing a comprehensive blueprint for researchers and practitioners to implement real-time object detection systems. The paper concludes with recommendations for future research directions and improvements to further enhance the system's versatility and performance.

An iterative approach to developing a multifaceted implementation strategy for a complex eHealth intervention within clinical practice

BackgroundThe number of complex eHealth interventions has increased considerably. Despite available implementation theory outlining well-designed strategies, implementing complex interventions within practice proves challenging and often does not lead to sustainable use. To improve sustainability, theory and practice should be addressed during the development of an implementation strategy. By subsequently transparently reporting the executed theory-based steps and their corresponding practice findings, others can learn from these valuable lessons learned. This study outlines the iterative approach by which a multifaceted implementation strategy for a complex eHealth intervention in clinical practice was developed, tested and refined.MethodsWe implemented the BENEFIT program, an advanced eHealth platform with Personal Health Portal facilitating healthy living in cardiac patients. In six iterative phases alternating between theory and practice, the implementation strategy was developed, tested and refined. The initial implementation strategy (phase 1) was drawn up using the Implementation model and RE-AIM. Subsequently, this strategy was further updated in brainstorming sessions and group discussions with twenty key stakeholders from three cardiac care centres and then evaluated in a pilot (phases 2 and 3).ResultsThe pilot of the program led to the identification of (context-specific) key challenges in practice (phase 4), which were subsequently connected back to broader theory (phase 5) using the Consolidated Framework of Implementation Research (CFIR). In the final phase, practice recommendations tackling the key challenges were formulated (phase 6) based on CFIR theory, the CFIR-ERIC Matching Tool, and stakeholders’ input and feedback. These recommendations were then added to the refined strategy. Thus, executing this approach led to the realisation and use of a multifaceted theory-informed practice-based implementation strategy.ConclusionThis case study gives an in-depth description of an iterative approach to developing an evidence-based, practice-tailored strategy for implementing a complex eHealth intervention in cardiac care. As such, this study may serve as a blueprint for other researchers aspiring to implement complex eHealth interventions within clinical practice sustainably.

Dissecting thought patterns: Analyzing how cognitive fragmentation affects conceptualization and problem-solving abilities in junior high school students

Background: This research is rooted in the exploration of a nuanced understanding of the effect of cognitive fragmentation on the conceptual grasp and problem-solving competencies among junior high school students.Aim: The principal aim of this investigation is to delve into the way cognitive fragmentation influences the conceptualization and problem-solving faculties of pupils aged 12-14, from varied academic milieus.Method: Employing a qualitative research blueprint, specifically phenomenological inquiry, the study probes into the subjective experiences and cognitions of the participants. Purposefully chosen for this research, the participants consist of junior high school students. The multi-faceted data collection approach includes task-centered, in-depth individual interviews with students and Focus Group Discussions with educators. The amassed data are then meticulously examined through thematic analysis.Result: Findings of the research reveal diverse manifestations of cognitive fragmentation among the learners. A phenomenon termed 'Pseudo construction' emerges when learners articulate correct responses without wholly comprehending the foundational concepts. 'Mis analogical construction' is recognized when incorrect analogies are deployed in problem-solving, culminating in fallacious solutions. 'Construction holes' are detected when learners exhibit inconsistent responses owing to an absence of alignment with scientific principles.Conclusion: In summation, this inquiry furnishes invaluable insights and evidence-supported strategies to foster efficacious learning and surmount cognitive impediments within the sphere of junior high school education. The conclusions drawn herein contribute to a broader understanding of cognitive dynamics in mathematics education, offering a fresh perspective on enhancing educational practices.

Techno-enviro-socio-economic design and finite set model predictive current control of a grid-connected large-scale hybrid solar/wind energy system: A case study of Sokhna Industrial Zone, Egypt

This article offers a cohesive design optimization and control framework of a large-scale grid-connected battery and battery-less hybrid solar/wind system. Primarily, a techno-enviro-socio-economic design optimization and feasibility analysis were performed for eight distinct energy alternatives. Secondly, a finite-set model predictive current control (FS-MPCC) was proposed to improve both stability and dynamic behavior of the optimal energy alternative under various climatic circumstances. Moreover, finite-set model predictive control is furtherly employed to exploit the maximum permissible power from both solar and wind energies. The proposed framework is verified over a new case-study in Sokhna Industrial Zone in Suez, Egypt. The studied load demand combines both industrial and residential load sectors with a daily consumption of 40,500 kWh and of 4-MW peak. The design optimization results revealed that the grid-connected photovoltaic/wind turbines/converter system has superior sustainable and economic performances with the least net present cost ($17,371,980) and energy cost (0.0782 $/kWh). These values were less than those of the base-case system (grid-only) by 17 % and 22 %, respectively. Moreover, the reliability analysis found a tiny and tolerable daily capacity shortage of 5835-kWh despite the five annual grid outages. Besides, around 52 % of the total energy production was acquired from both solar and wind generation systems, which interpreted in a maximum saving in carbon dioxide emissions by 45.8 % compared to the base-case system and offered substantial social benefits in terms of creating nearly 10 jobs. The FS-MPCC results proved a reinforced dynamic behavior for the maximum power tracking profiles of solar and wind systems as well as in the DC-bus voltage profile regarding the over- and undershoot and the steady-state response. Compared to PI controller, the proposed FS-MPCC creates dq-axis voltages and currents with less disturbances and ripples which inject current/voltage to the grid with fewer harmonics and thus increases the generator's lifetime. To sum up, the proposed method features an integrative and compelling case to be used as an efficient tool to implement large-scale renewable energy projects. It could act as a blueprint for energy developers, researchers, investors, and authorities to achieve affordable and sustainable energy access.