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Integrated skills for parenting the adolescents (ISPA): An intervention to strengthen parent- adolescent relationship /
Review of Neuropsiquiatrica, Vol.76, Issue 4, pp.413-422, ISSN No: 1609-7394. -
Integrating Advanced Metabolomics with Plant Functional Genomics
Metabolomics encompasses the entire suite of small-molecule compounds or metabolites synthesized by an or ganism, whereas functional genomics refers to the gene-level functioning of an organism. The genome of a plant will dictate its metabolome, but the link between the two omics data may not always be clearly visible or properly explored. This chapter delves into the integration of advanced metabolomics with plant functional genomics, highlighting its pivotal role in advancing our understanding of plant biology and its applications in agriculture. Metabolomics provides a comprehensive analysis of small molecules, bridging the gap between genotype and phenotype by elucidating the dynamic interactions within plant systems. Key techniques such as mass spectrom etry and nuclear magnetic resonance are explored, emphasizing their importance in high-throughput and high-resolution metabolite profiling. The chapter further discusses the synergy between metabolomics and other omics technologies, including genomics, transcriptomics, and proteomics, underscoring its significance in iden tifying gene functions and metabolic pathways linked to complex traits such as stress tolerance. Applications in plant breeding are also highlighted, showcasing how metabolomics can drive the development of crops with en hanced stress resilience, yield, and nutritional quality. The chapter concludes by emphasizing the transformative potential of this integrated approach in shaping future agricultural practices and improving food security. CAB International 2025. All rights reserved. -
Integrating AI and Cybersecurity: Advancing Autonomous Vehicle Security and Response Mechanisms
The rapid evolution of autonomous and connected vehicles has led to their integration with numerous technologies and software, rendering them vulnerable targets for cybersecurity attacks. While efforts have traditionally focused on preventing these attacks, the escalating risk underscores the importance of also vindicating their wallop. Nevertheless, this procedure is often onerous & facade scalability confronted, particularly due to connectivity issues in automobiles. This research advises a vehicle-based vibrant imposition response scheme, enabling swift responses to a variety of incidents and reducing reliance on external security centers. The classification encompasses an inclusive range of probable retorts, a procedure for evaluating retorts, & innumerable assortment approaches. Implemented on an embedded platform, the solution was evaluated using two distinct cyberattack use cases, highlighting its adaptability, responsiveness, volume for dynamic arrangement constraint alterations & nominal memory trail. Concurrently, this paper presents an innovative (AVSF) that synergistically integrates (AI) and cybersecurity techniques to fortify AV resilience against evolving threats. Additionally, the framework incorporates advanced cybersecurity measures such as encryption, authentication, and intrusion detection to mitigate vulnerabilities and safeguard critical AV systems. The fusion of AI and cybersecurity not only enhances AV security posture but also enables intelligent cyber threat monitoring and response capabilities. Extensive simulations and experimental evaluations demonstrate the efficacy of the AVSF in real-time scenarios, contributing to the development of robust security solutions for autonomous vehicle deployment and advancing safer transportation systems in the era of AI-driven mobility. 2024 IEEE. -
Integrating AI into Corporate Social Responsibility (CSR) for Ethical and Sustainable Business Practices
The rapid advancement of artificial intelligence (AI) technologies has significantly transformed various facets of business operations, including corporate social responsibility (CSR). As businesses strive to align their growth strategies with ethical, social, and environmental responsibilities, AI emerges as a powerful tool to enhance the effectiveness of CSR initiatives. This research investigates the integration of AI into CSR, exploring its potential to drive more sustainable business practices, improve transparency, and foster ethical decision-making within organizations. By employing a combination of qualitative and quantitative research methods, this study examines how AI-powered analytics, automation, and decision-making frameworks can optimize CSR efforts. Key areas of exploration include AI's role in enhancing supply chain sustainability, optimizing resource allocation, detecting unethical business practices, and enabling real-time monitoring and reporting of CSR initiatives. 2026, IGI Global Scientific Publishing. -
Integrating AI Tools into HRM to Promote Green HRM Practices
The image of Human Resource Management (HRM) is undergoing a drastic transformation. The conventional methods are evolving due to the emergence of technology, especially with the integration of Artificial Intelligence (AI) and data analytics into the HR processes. With the rapidly changing concept of the overall growth of an organization, AI is becoming a vital stimulant for sustainable growth. AI-powered tools promote data-driven decision-making for talent acquisition, performance management, workforce training and development, optimization of energy consumption and waste reduction. Green HRM aligns these efforts by integrating sustainability considerations into talent management strategies, nurturing employees eco-engagement, and promoting environmentally responsible practices within the workforce. This research paper aims to explore the synergies between AI tools and Green HRM practices, investigating how the integration of AI technologies into HR processes can contribute to the promotion of environmental sustainability. By examining real-world case studies, this study aims to investigate the potential of AI-powered solutions in shaping the future of HRM through the lens of sustainability. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Integrating Artificial Intelligence in Education: Insights From a Teacher Training Workshop
This chapter explores the impact of an in-person AI training workshop on Chilean in-service teachers across a network of four schools. Through a mixed-methods approach-including pre-and post-surveys with qualitative and quantitative data-the study examines shifts in teacher attitudes, knowledge, and intentions to use AI in educational practice. Results show increased confidence, pedagogical alignment, and ethical awareness, particularly regarding inclusion and differentiated instruction. The chapter also highlights the importance of contextualized training, gender representation, and long-term support to ensure equitable and meaningful AI integration in Latin American classrooms. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Integrating artificial intelligence in Islamic financial management: Opportunities and challenges in maintaining Shariah compliance
The objective of this study is to examine the potential incorporation of Artificial Intelligence (AI) technology into financial management practices that are based on Islamic principles, with a particular emphasis on ensuring Shariah compliance. The literature analysis methodological approach is employed to identify the opportunities and challenges associated with the adoption of AI in the Islamic Finance (IF) environment. The results indicate that the implementation of AI can enhance the efficacy, transparency, and precision of IF operations. However, there are numerous challenges associated with Shariah compliance and ethics. The findings of this study emphasize the importance of establishing a regulatory framework that is consistent with Shariah principles in order to ensure the successful implementation of AI in Islamic financial institutions (IFI). The need for collaboration between finance experts and academics to ensure that the technology is implemented in accordance with Shariah principles, as well as the expansion of training for IF (Islamic Finance) practitioners regarding the implications of AI, are among the recommendations. Future research should examine the influence of more specific AI implementation strategies on Islamic conformance and operational efficacy in the context of IF. 2025 Early Ridho Kismawadi, Mohammad Irfan and Isnaini Harahap. All rights reserved. -
Integrating Artificial Intelligence in the Blue Economy: A Case-Based Study of Smart Marine Ecosystems for Climate Change Mitigation and Circular Economy
The Blue Economy represents a critical pathway toward sustainable development, balancing economic growth with the conservation of marine ecosystems. This chapter explores the transformative role of Artificial Intelligence (AI) in advancing sustainable practices within the Blue Economy through a series of global case studies. It examines how leading companies and initiativessuch as Sinay, Saildrone, Sea.AI, Buffalo Automation, IBM, Microsoft, Ocean Cleanup, and Veolia Groupleverage AI-driven solutions for real-time environmental monitoring, predictive climate modeling, autonomous navigation, and circular waste management. Key insights reveal that AI enables data-driven decision-making, reduces carbon emissions, enhances operational efficiency, and supports closed-loop recycling systems, while confronting challenges related to data integration, regulatory frameworks, and economic viability. Policy implications highlight the urgent need for adaptive regulations, open data ecosystems, and public-private partnerships to scale smart marine ecosystems globally. Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development. -
Integrating Behavioural Science using the Psycho-Intelligence Framework in Connected Systems
The fast-growing convergence of neuroscience, behaviour computing, and adaptive artificial intelligence (AI) offers the possibility to transform human, machine interaction. This work presents Psycho-Intelligence, a new, closed-loop system that merges electroencephalography (EEG) and inertial motion unit (IMU) signals to adaptively recognise and react to users' cognitive and affective states. Levying low-cost wearable sensors (Muse EEG and MPU-6050), the system has real-time signal acquisition, sophisticated preprocessing, spectral and statistical feature extraction, as well as multimodal fusion features. Dimensionality reduction and feature selection techniques, including Principal Component Analysis and XGBoost gain metrics, enhance learning optimally. Multiple machine learning algorithms like Random Forest, SVM and XGBoost are trained to identify engagement states with high accuracy, warranted by extensive testing through cross-validation, ROC AUC, and F1-scores. The pipeline is incorporated into an adaptive feedback system that can regulate chatbot tone, learning material, or interactive graphics based on detected user states. Statistical validation with linear mixed models confirms the robustness of EEG-derived measurements in engagement prediction. The research establishes a new paradigm for emotionally intelligent AI systems and provides a technical foundation for ethical, real-time psycho-behavioural intelligence for communication networks, education systems, and cognitive health monitoring. 2025 IEEE. -
Integrating Big Data Management with Machine Learning in Cloud Environments
In past years, the consideration of cloud environments for big data management and machine learning techniques has increased exponentially. However, the massive amount of data that is made by companies and Internet of Things (IoT) devices has presented the industry with a challenge in storage. In addition, conventional data management methods are unable to manage the complexity, diversity, and volume of this big data. Consequently, cloud environments integrate big data management and machine learning techniques. Combining big data management through cloud environments equipped with machine learning has multiple benefits. First, it is an efficient way to process and analyze large datasets in a distributed and scalable manner. Second, it helps businesses to provide insights and make time to make datadriven decisions. Thirdly, it enables the system to learn from data on an ongoing basis, which helps improve the quality and accuracy of the data. Now, this integration also enhances the overall performance of cloud systems as data management tasks are automated, minimizing manual efforts. Utilizing Big Data Management and Machine Learning Techniques in Cloud Environment to Address the Drawbacks of Conventional Data Management Approaches and Exploit the Value of Big Data These two technologies, when integrated, will allow the enterprise to manage significant amounts of data and derive important insights to arrive at better decisions. Cloud environments provide the automation and scalability required to push this integration further and change considerable data use in businesses. 2025 IEEE. -
Integrating brain-inspired computation with big-data analytics for advanced diagnostics in neuroradiology
Introduction: Neuroradiology encounters considerable difficulties owing to imaging data's intricacy and high-dimensional characteristics. Conventional diagnostic techniques often encounter challenges regarding precision and scalability, resulting in delays and possible misinterpretations. This paper presents the Big-Data Analytics-based Diagnostics (BDA-D) framework, a revolutionary method using computational models derived from neural architectures and sophisticated analytics to tackle these difficulties. Methods: The BDA-D architecture utilizes data mining, pattern recognition, and machine learning to glean useful neuroanatomical characteristics from massive datasets. By simulating human thought processes, this method speeds up clinical decision-making and improves diagnostic accuracy. To evaluate the effectiveness of the framework, it is put to the test in a clinical environment. Results and Discussion: Diagnostic precision, processing speed, and dependability are all enhanced by experimental validation. By detecting even the most minute neuroanatomical changes, BDA-D allows for more accurate diagnosis than traditional approaches. Based on the results, neuroradiologists may improve their practices by using cutting-edge computational methods to close the gap between data-driven analytics and their practical use in the clinic. BDA-D discovers important patterns from high-dimensional neuroimaging data through biologically inspired neural networks, reaching a remarkable diagnosis accuracy of 97.18%. Its 95.42% increase in processing speed allows rapid study of important disorders such as strokes and neurodegenerative diseases. BDA-D reduces inter-observer variability with a dependable value of 94.96%, increasing clinical confidence in AI-assisted diagnosis. Conclusion: A revolutionary change in neurodiagnostics, the BDA-D framework improves efficiency and reliability. This method has the potential to completely transform neuroradiology by combining big-data analytics with sophisticated computer models. It will allow for more rapid and precise diagnosis. 2025 The Authors -
INTEGRATING CLIMATE CHANGE, SOCIAL RESPONSIBILITY AND ELECTRONIC FINANCIAL INCLUSION: A PATHWAY TO SUSTAINABLE DEVELOPMENT
Purpose: This study explores the intersection of climate change social responsibility and electronic financial inclusion (EFI) as critical components of sustainable development. The research aims to identify the synergies between these domains and their potential to drive inclusive growth and resilience. Design/Methodology/Approach: The study integrates literature review and case studies to analyse the role of EFI in enhancing access to financial services, particularly for marginalised communities. It also examines corporate social responsibility (CSR) initiatives aimed at mitigating climate change and promoting environmental sustainability. The research study highlights successful integration models and best practices that demonstrate the impact of multistakeholder collaboration. Findings: The findings reveal that EFI significantly contributes to poverty reduction and economic empowerment by expanding financial access in underserved regions. Moreover, corporate initiatives in climate change mitigation, when aligned with social responsibility, enhance business resilience and foster sustainable practices. The study emphasises the importance of supportive policy frameworks and technological innovations in scaling these efforts. Research Limitations/Implications: The studys focus on case studies may limit the generalisability of the findings. Future research could explore broader geographic regions and diverse economic contexts. Originality/Value: This paper contributes to the understanding of how integrating climate action, social responsibility and EFI can create resilient, equitable and sustainable systems. It offers valuable insights for policymakers, businesses and practitioners aiming to advance sustainable development through innovative and inclusive strategies. 2025 Ernesto D. R. S. Gonzalez, Rajeev Sijariya, Amit Kumar Singh and Vikas Garg Published under exclusive licence by Emerald Publishing Limited. -
Integrating cyber-physical systems with intelligent transportation: Challenges and opportunities
Cyber-physical systems (CPS) are revolutionizing the transportation sector, wherein physical processes are combined with computational systems to create efficient, reliable, and safe transportation solutions. This chapter discusses the ways in which CPS impact contemporary transportation development. The theoretical and practical aspects of CPS have been considered as they follow with the intelligent traffic management systems and driverless cars within this scope of work. The first half of the chapter is then applied to architectural design in CPS, discussing how elements of the physical worldinteraction with cars and roads, for exampleare coupled with cyber systems, such as cloud computing, IoT, and communication networks. Important technical breakthroughs in these areas highlight the key aspects that make real-time decision-making and optimization of systems possible: 5G, edge computing, and artificial intelligence. The chapter also reviews simulation-based techniques in analyzing vehicle behavior and traffic flow, which encompasses insights into how CPS might improve traffic safety and efficiency. Simulations can study very complex transportation scenarios like collision avoidance and control of traffic without the need for real data. The chapter discusses cybersecurity risks, legal issues, and the need for standardized infrastructure to support intelligent transportation systems. It also focuses on the challenges presented by laws and policies in the field of CPS. The interaction of drivers, passengers, and traffic operators with these devices further helps grasp the human factor as well as the experience of a CPS user. The final section of the chapter discusses future directions of CPS research and development, specifically regarding how blockchain technology and quantum computing might advance transportation networks. This chapter will, therefore, give the reader a holistic understanding of how CPS may change the face of transportation in the future by bringing its non-data-driven components to the fore. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
Integrating deep learning in an IoT model to build smart applications for sustainable cities
These days, many CS experts focus their efforts on IoT. IoT is an emerging & cutting-edge technology that enables many items, including vehicles and home appliances, to connect and cooperate via mechanisms like machine to machine communication, big data, and AI. It has found use in a wide range of settings, from smart homes and cities, to healthcare and agriculture, to factory automation. Smart cities are becoming smarter, cars are getting more features, and health and fitness devices are getting more sophisticated thanks to the internet of things. Many problems that are directly relevant to the IoT's development have yet to be resolved. The exponential development of IoT has given birth to new problems, including concerns about personal data and security. There is need of a comprehensive approach that tackles the scalability, security, efficiency, and privacy concerns raised by the widespread deployment of IoT. 2023, IGI Global. -
Integrating Diverse Approaches in Medical Image Analysis: PAA-CNN and Feature Extraction Fusion for Classiation of Psychological Disorders using Anatomical Scans
A psychological disorder is a condition that impacts a persons behavior. Due to the contemporary way of life, a large number of individuals suffer from disorders like stress, depression, and other similar ones. These might turn into severe issues that would signiantly impact a persons quality of life. We present a sample framework that uses an Anatomical scan captured along with fMRI. Anatomical scans were used to extract characteristics, which were then utilized to classify using a random forest classir. In a follow-up experiment, CNN is applied to features obtained from the piecewise aggregate approximation method for multi-class classiation of psychological disorders. This method performs noticeably better than the conventional feature extraction techniques, and with this approach, obtained an accuracy of up to 79%. Combining several approaches may boost the classiation and prediction accuracy of medical data. 2025 The Authors. Published by Elsevier B.V. -
Integrating dye-sensitized solar cells and supercapacitors: portable powerpacks for future energy applications
Integrating energy storage and harvesting devices have been major challenges and significant needs of the time for upcoming energy applications. Photosupercapacitors are combined solar cell-supercapacitor devices which can provide next-generation portable powerpacks. Owing to advantages like economic and environmental friendliness, dye-sensitized solar cells (DSSCs) offer vast potential for being integrated with energy accumulation devices like supercapacitors. Over the past few years, various types of harvesting cum storage power devices combining DSSCs and supercapacitors have been reported. Over time the devices have improved in both performance and stability providing a broad outlook to possible future advancements including commercialization. We still have many challenges that are yet to be resolved in order to take these powerpacks to the next level of applications in portable and wearable electronics and communication devices. In this context, a detailed analysis and comparison of already reported photo-powered integrated supercapacitors based on DSSCs would give further insights into future advancements. In this review, we have discussed the development of photosupercapacitors, their fabrication strategies, and different materials used as counter electrodes, electrolytes, and dye sensitizers. Graphical Abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Integrating Education, Technology, and Sustainable Living: Advancing the Circular Economy for Future Generations
Sustainable living is crucial in reducing societys reliance on natural resources, a goal intimately connected to the principles of the circular economy. This conceptual framework highlights the interplay between education, technology, and the standard of living as fundamental aspects driving sustainable practices. Education empowers individuals with the knowledge and skills necessary to raise awareness and encourage sustainable behavior, shaping beliefs and intentions towards resource efficiency. However, recent studies suggests, increased access to information can paradoxically lead to greater complexities and dilemmas, creating challenges in enacting sustainable consumption and inadvertently slowing sustainable development efforts. Furthermore, the role of technology in the circular economy is indispensable. Advanced technological solutions facilitate the efficient use of resources, offering innovative approaches to mitigate environmental impact while enhancing the quality of life. Earlier literatures underscores the importance of education, funding, and innovation in green technology to achieve Sustainable Development Goals (SDGs) by 2030, highlighting the current state and research hotspots in this domain. A comprehensive literature review utilizing the Web of Science database reveals global contributions to SDG research, emphasizing the need for a balanced approach that integrates education, technology, and a sustainable standard of living. Together, these elements contribute to the development of a society that fosters a culture of sustainability. By promoting a circular economy, where resources are reused, recycled, and repurposed, we can ensure that the needs of the present are met without compromising the ability of future generations to thrive. This approach not only preserves environmental health but also cultivates resilient communities capable of navigating the complexities of sustainability in a rapidly changing world. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Integrating Emerging Technologies: Enhancing Supply Chain Optimization Through AI, IoT, and Blockchain
The rapid rise of technologies like AI, IoT, and blockchain is transforming supply chain management by boosting efficiency, transparency, and resilience. This paper examines how these technologies optimize supply chains, focusing on predictive analytics, real- time monitoring, and secure data exchange. AI excels in automation and decision- making, IoT enables real- time data gathering, and blockchain ensures trust and transparency. Case studies from Amazon, Maersk, Walmart, and Pfizer illustrate improvements in efficiency, risk reduction, and cost savings. Additionally, challenges like high costs, data privacy, and lack of standardization are discussed, along with future trends in edge computing, quantum computing, and digital twins. The study highlights AI, IoT, and blockchain as essential to building smarter, adaptable supply chains capable of thriving in todays global economy. 2025, IGI Global Scientific Publishing.