Recent Articles

Kevin George  ·  International Journal of Education, Pedagogy and Psychology  ·  03 Aug 2026

This commentary offers a fresh reading of Robert Frost's A Minor Bird by arguing that the poem's ethical force resides not only in the speaker's final act of self-correction but also in the significance of its title. Rather than treating "minor" as an objective description of the bird, the essay contends that it functions as a subjective act of classification that reveals the speaker's hierarchy of value. Through a close reading of the poem, it demonstrates how Frost shifts responsibility from the bird to the observer, exposing the ways in which seemingly innocent linguistic judgments precede attempts to silence unwanted voices. The movement from the speaker's private irritation to the universal assertion that there is "something wrong / In wanting to silence any song" transforms a domestic complaint into a broader meditation on language, perception, and ethical responsibility. Ultimately, the commentary argues that Frost presents moral growth as the recognition and rejection of the classificatory habits that diminish others before excluding them.

Karan Kumar Agrawal  ·  International Journal of Law, Politics and Governance  ·  31 Jul 2026

This paper examines the legal gap between factory workers and platform workers in India with respect to social security and welfare. Factory workers enjoy clear statutory protections under laws such as the EPF Act, 1952, the Employees’ State Insurance Act, 1948, and the Payment of Gratuity Act, 1972. These enactments guarantee contributions to provident funds, health insurance, maternity benefits, accident compensation, and gratuity. In contrast, platform workers—app‐based drivers and couriers engaged by companies like Ola, Zomato, and Uber—are classified as independent contractors and thus lie outside these schemes. Although the Code on Social Security, 2020 formally defines “gig worker” and “platform worker” and provides for welfare schemes, it does not automatically confer provident fund or insurance benefits upon these workers. The discretionary nature of scheme design, unclear funding obligations for aggregators, and absence of enforceable rights leave platform workers vulnerable. By analyzing statutory provisions, reviewing landmark domestic and foreign judgments on employment status, and comparing legislative responses in the UK, EU, and US, this paper demonstrates that existing tests of control and supervision are inadequate for modern digital work. It argues for a tailored legal category—such as “dependent contractor”—and recommends mandatory social security contributions, clear employer obligations, and access to minimum wages and collective bargaining. Such reforms will align India’s labour framework with constitutional principles of equality and social justice and extend essential welfare benefits to all workers, irrespective of the platform through which they are engaged. By examining statutory provisions, landmark judgments, and comparative approaches from the UK, the EU (Platform Work Directive, 2024), and the US (, this study aims to propose a “dependent contractor” category and recommend mandatory contributions, clear employer obligations, and collective bargaining rights for platform workers.

Abdullahi Muhammad Dutsun, O. E. Afinotan, S. O. Onubaye, S. H. Eromi, Hillary Ilemona Akor, M. A. Hayatu, Joshua Jiya, O. L. Airhiomwauhimwen  ·  International Journal of Physical and Chemical Sciences  ·  29 Jul 2026

Heat treatment is an important part of materials and metallurgical engineering. It allows the microstructure and mechanical properties to be enhanced by means of regulated thermal cycles. In Nigeria, this process is an essential one for industries such as the automotive industry, oil & gas, and construction industries. It is however, often limited by out dated equipment, insufficient quenching management and low energy efficiency. This article shows the importance of heat transfer in the metallurgical process of heat-treatment and examines the different enhancement methods to boost reliability and efficiency. The enhancement techniques which include mechanical agitation, jet impingement, nanofluids, surface modifications, ultrasonic agitation, and combined methods are examined. A comparative analysis is presented, with a focus on relevance to Nigeria’s iron and steel industry. The discussions show that cheaper retrofits, like mechanical agitation and surface modifications provide the fastest return on investment; these are already being utilized in the industry. By contrast, high-capital, specialized techniques such as ultrasonic-assisted quenching, or more innovative options such as nanofluids, are more useful for specific applications where improved process control or unique thermal characteristics create the need for the added costs and complexity. Implementing these techniques will lead to a reduction in waste and improvement in energy efficiency, which will ultimately result in making our nation’s metallurgical industry more competitive on a global scale.

Rekha Agarwal, RAJESH KUMAR MISHRA, Divyansh Mishra  ·  International Journal of Physical and Chemical Sciences  ·  28 Jul 2026

Cosmic ray modulation is one of the most fundamental processes in heliophysics, describing the temporal, spatial, and energy-dependent variation of galactic cosmic ray (GCR) intensities as they propagate through the turbulent heliosphere before reaching Earth. The heliosphere, formed by the continuous expansion of the solar wind and permeated by the heliospheric magnetic field (HMF), acts as a dynamic magnetic shield that modifies the transport of energetic charged particles through diffusion, convection, gradient and curvature drifts, and adiabatic energy changes. These transport mechanisms are strongly influenced by the approximately 11-year solar activity cycle and the 22-year Hale magnetic polarity cycle, resulting in long-term modulation of cosmic ray fluxes as well as short-term transient phenomena associated with coronal mass ejections (CMEs), interplanetary shocks, magnetic clouds, and high-speed solar wind streams. Understanding cosmic ray modulation is essential not only for advancing heliospheric physics but also for improving space weather forecasting, assessing radiation hazards to astronauts and spacecraft, protecting satellite electronics, ensuring aviation safety on polar routes, and investigating atmospheric ionization and cosmogenic isotope production. This review presents a comprehensive synthesis of the current understanding of galactic cosmic ray modulation by integrating classical transport theory, heliospheric plasma physics, long-term observational datasets, numerical simulations, and emerging artificial intelligence (AI) techniques. The review begins by discussing the origin, acceleration mechanisms, energy spectrum, and chemical composition of cosmic rays, followed by an examination of heliospheric structure, including the solar wind, Parker spiral magnetic field, heliospheric current sheet, termination shock, heliosheath, heliopause, and the local interstellar medium. Particular emphasis is placed on the Parker Transport Equation, which forms the theoretical foundation for describing cosmic ray propagation through the combined effects of anisotropic spatial diffusion, solar wind convection, gradient and curvature drifts, current-sheet drift, and adiabatic energy losses. The review further examines the modulation of cosmic rays during Solar Cycles 20–25, highlighting the influence of solar magnetic polarity reversals, heliospheric magnetic field evolution, magnetic turbulence, recurrent high-speed streams, and transient solar eruptions on cosmic ray intensity. A critical assessment is presented of observational evidence obtained from ground-based neutron monitor networks and major space missions, including Voyager 1 and 2, Ulysses, ACE, SOHO, STEREO, PAMELA, AMS-02, Parker Solar Probe, Solar Orbiter, and Aditya-L1, which together provide continuous measurements of energetic particles, solar wind plasma, and heliospheric magnetic fields across multiple spatial scales. Modern numerical approaches—including finite-difference methods, stochastic differential equation (SDE) models, Monte Carlo simulations, and three-dimensional magnetohydrodynamic (MHD) heliospheric models such as HelMod, WSA–ENLIL, and EUHFORIA—are critically compared with respect to their capabilities and limitations in reproducing observed modulation patterns. The review also highlights the rapidly expanding role of artificial intelligence and machine learning in cosmic ray research. Recent developments involving recurrent neural networks (RNNs), long short-term memory (LSTM) networks, convolutional neural networks (CNNs), transformer architectures, random forests, gradient boosting algorithms, physics-informed neural networks (PINNs), explainable artificial intelligence (XAI), and digital-twin frameworks are examined for their ability to improve prediction of neutron monitor counts, Forbush decreases, solar energetic particle events, and heliospheric transport parameters. These data-driven methods, when integrated with first-principles transport theory, offer significant potential for real-time forecasting and operational space weather services. Finally, the review identifies major scientific challenges related to turbulence modeling, time-dependent heliospheric structure, multi-scale particle transport, uncertainty quantification, and physics–AI integration. Future research directions are proposed that emphasize high-performance computing, data assimilation, digital heliosphere modeling, multi-spacecraft observations, and next-generation AI-assisted forecasting systems. By combining theoretical developments, observational advances, computational methodologies, and intelligent data-driven techniques, this review provides a comprehensive and up-to-date perspective on cosmic ray modulation and its broad implications for heliophysics, astrophysics, and space weather science.

Dr. Manish Kumar Yadav, Adv. Suraj Yadav  ·  International Journal of Law, Politics and Governance  ·  24 Jul 2026

The increasing integration of artificial intelligence (AI), blockchain technologies, and big data analytics into criminal justice systems is transforming the collection, authentication, analysis, and evaluation of digital evidence. While these innovations enhance investigative capabilities through automated data processing, forensic analysis, facial recognition, and predictive analytics, they also create significant challenges for evidentiary reliability. In particular, the proliferation of AI-generated content and increasingly sophisticated deepfakes has complicated the authentication of digital evidence, while predictive policing systems have raised concerns regarding algorithmic bias, transparency, accountability, and due process. Although existing scholarship has examined these technologies individually, relatively little research has explored their combined implications for digital evidence and criminal justice decision-making within a unified analytical framework. This research paper evaluates the implications of AI-generated content, blockchain authentication systems, and predictive policing technologies for the reliability, admissibility, and legitimacy of digital evidence in contemporary criminal justice systems.

Abdullahi Muhammad Dutsun, Dr. Shaib Abdulazeez Shehu, Joshua Jiya, Isaac Bala Taidi, Shaibu Onimisi Onubaye, Hillary Ilemona Akor, Misbahu Abdullahi Hayatu  ·  International Journal of Civil and Environmental Engineering  ·  23 Jul 2026

Niger State, often referred to as "the Power State," is endowed with vast mineral resources that offer substantial investment potential for Nigeria's economic diversification. This paper Niger State's mineral wealth and richness, emphasizing important reserves including iron ore, kaolin, gold, tantalite, and more, and evaluates the state's capacity to draw in both domestic and global investment. The review looks at current government incentives and policies for investors, including deferred royalties, exemptions from import and customs taxes for plant, machinery, and equipment used in mining operations, potential capitalization of exploration and survey costs, and state government infrastructure expansion. Challenges in the sector and recommendations for sustainable development were highlighted. with improved regulatory frameworks, enhanced security, and public-private partnerships, Niger State can become a mining powerhouse, contributing substantially to Nigeria’s GDP and job creation.

Dr. RAJESH KUMAR MISHRA, DIVYANSH MISHRA, Dr. REKHA AGARWAL  ·  International Journal of Physical and Chemical Sciences  ·  23 Jul 2026

Geomagnetic storms, driven primarily by coronal mass ejections (CMEs) and high-speed solar wind streams interacting with the Earth's magnetosphere, pose significant risks to satellite operations, power grid infrastructure, aviation, and communication systems. Traditional empirical and physics-based models of geomagnetic indices such as Dst and Kp, while physically interpretable, often struggle to capture the highly nonlinear and non-stationary dynamics of solar wind-magnetosphere coupling, particularly during the storm recovery phase. Artificial Intelligence (AI) techniques, including artificial neural networks, ensemble tree-based methods, and multilayer perceptron (MLP) models, have demonstrated considerable promise for improving the accuracy and lead time of geomagnetic storm forecasts. This paper (i) reviews the evolution of AI-based approaches to Dst/Kp prediction; (ii) proposes a consolidated methodological framework for building and validating AI-driven space-weather forecasting systems; and (iii) reports a complete, reproducible experimental case study in which a physically-grounded Burton-McPherron-Russell (BMR) ring-current simulator was used to generate a multi-year hourly solar-wind-driven Dst dataset, on which Random Forest, Gradient Boosting, Multilayer Perceptron, and linear baseline models were trained and evaluated under a chronologically leakage-aware train/validation/test protocol at 1-, 3-, and 6-hour forecast horizons. The best-performing model (MLP) achieved RMSE = 3.82 nT and R² = 0.956 at the 1-hour horizon, degrading to RMSE = 10.27 nT and R² = 0.684 at 6 hours, consistent with the general skill-decay pattern reported in the literature for physically driven Dst forecasting. Feature importance analysis confirmed that the most recent lagged Dst value and the 6-hour rolling mean of the southward IMF component (Bz) dominate predictive skill. Key challenges relating to data leakage, class imbalance for extreme events, multimodal data fusion, and model interpretability are discussed, along with directions for future research including physics-informed machine learning and probabilistic forecasting.

alfredndi, Manuela Wankam  ·  International Journal of Arts, Culture and Creative Studies  ·  23 Jul 2026

This paper argues for a systematic reconfiguration of pedagogical practice in higher-education courses on African oral literature by moving beyond an exclusive reliance on textual transcription and translation toward an integrated, ethically-grounded multimodal pedagogy that centers performance, context, and digitally mediated representations. Grounded in decolonial and constructivist pedagogies and informed by digital humanities practices, the study draws on a mixed-methods action-research project carried out in three universities (West, East, and Southern Africa) between 2021 and 2024 involving curricular redesign, instructor workshops, student praxis labs, community-partnered documentation, and pilot AI visualization modules. Primary data comprise classroom observations, interviews with instructors, focus groups with students and cultural practitioners, analysis of student artifacts (audio/video/AI-generated images), and usage metrics for digital repositories. Findings (n = 20) identify pedagogical, technical, ethical, and institutional enablers and barriers: notably, that multimodal instruction improves students’ embodied understanding of performance, that AI-generated imagery supports metaphor comprehension when co-curated with tradition-bearers, and that ethical protocols and community consent frameworks are essential to avoid cultural extractivism. The paper details a replicable pedagogical framework—The Performative-Digital Integrative Model (PDIM)—that prescribes steps for syllabus design, multimodal assessment, community partnership, digital-archival standards, and safe AI use. It concludes that while digital and AI tools substantially expand pedagogical possibilities, their deployment must be accompanied by robust cultural governance, capacity-building, and critical reflexivity. The paper offers concrete curricular templates, assessment rubrics, technical toolkits, and an agenda for further research including large-scale studies on learning outcomes, sustainability models for digital archives, and predictive analytics to map trajectories of oral-tradition transmission in digitally-mediated contexts.

SHALIKA SANTOSH, Ḍr. B. Charumathi  ·  International Journal of Technology and Emerging Research  ·  23 Jul 2026

The Andaman and Nicobar Islands in India, with their unique geographical isolation and limited infrastructure, present a distinct environment for Small and Medium-sized Enterprises. In such a context, digitalization has the potential to transform how local businesses operate, connect with markets, and manage resources. This study aims to explore the determinants of the impact of digitalization on SMEs operating in this ecologically sensitive and logistically challenging region. A structured questionnaire was developed with five core dimensions: awareness, training, usage, investment, and impact. Primary data was collected from 53 registered SMEs during May 2025. This study used Descriptive Statistics, ANOVA, and Correlation to get insights about the data. Further, using Structural Equation Modeling (SEM), this study validated the relationships among constructs and assessed the influence of awareness, training, usage, and investment on the impact. The SEM results reveal statistically significant relationships, indicating that awareness and training positively influence digital usage, training drives usage, digital usage significantly boosts investment, and investment strongly impacts overall digital outcomes for SMEs. The study underscores the need for structured training programs, policy support, and accessible digital infrastructure to enhance the digital maturity of island-based SMEs.

PRIYA, Dr. Jyoti kumari  ·  International Journal of Education, Pedagogy and Psychology  ·  22 Jul 2026

Access to appropriate vocational and entrepreneurial skills to secure sustainable jobs and enable independent living for children with intellectual disabilities is often challenging. Schooling-based education systems have been traditionally focused on academic performance with a minimal focus on developing the needed skills, limiting their economic contribution and social integration. Vocational training has proven to be an effective approach to imparting these children with occupational competencies, as well as with communication skills, abilities in transforming a problem into a solution, financial knowledge and self-confidence which are all important elements of entrepreneurship. The study is empirical research that involves a comparative analysis of the effectiveness of vocational training for the children with intellectual disability in special schools, inclusive education institutions and rehabilitation centres of the selected countries of the study. Structured questionnaires, interviews, and observations in a mixed-method research approach is used to collect the data from children, vocational instructors, teachers, and parents. This study evaluates important entrepreneurial skills like creativity, decision-making, team work, leadership, financial awareness and self-reliance and aims to discover the institutional, social and policy challenges that affect the training. The data analysis used is statistical analysis, which is used to analyse the relationship between vocational training and entrepreneurial skill development. The outcomes are anticipated to provide strong evidence that children with intellectual disabilities have improved enterprise capabilities, self-sufficiency and employability as a result of the successful development and application of vocational education. The study concludes with recommendations for policy support, available entrepreneurial education curricula, industry partnerships, capacity building of teachers and various other recommendations that include the role of the family in increasing the socioeconomic inclusion and quality of life for children with intellectual disabilities.

Avinash Vitthalrao Aneraye, Ms. Akanksha Chaudhary, Ms. Sunita  ·  International Journal of Education, Pedagogy and Psychology  ·  22 Jul 2026

A person who is older with a disability may have problems that go beyond disability. These can include ongoing and persistent pain, less mobility, reliance on other people for daily activities, loss of valued roles, feeling isolated, financial concerns, ageism, concerns for the future. Rehabilitation psychology takes on the challenge of these concerns by applying psychological knowledge to adjustment, participation, independence and/or quality of life. In this paper, authors examined the many psychological and social issues with which older patients with physical, sensory, cognitive and multiple disabilities frequently struggle and described such interventions that can be carried out in a hospital, rehabilitation center, home and community setting. The biopsychosocial model, Bandura's self-efficacy theory, the stress-and-coping model of Lazarus and Folkman, Baltes selection, optimization and compensation model and Ryff model of psychological well-being guide the analysis. The paper recognizes an important research gap: studies on rehabilitation tend to focus on mobility and basic functioning with less attention during the assessment of identity, autonomy, loneliness, meaningfulness, marital/ family relations and long-term psychological adaptation. Additionally, the literature is too limited in its focus on individuals with disabilities who are ageing onto its issues of diversity and culture, limited resources and infrastructure, and accessibility of older adults for digital services. It is suggested that rehabilitation should be person-centered, interdisciplinary, accessible and ever present in the individual's daily life to ensure effective rehabilitation. Psychological interventions including problem solving, motivational support, grief work, family counselling, peer support, foci on self-management, (SM) education, participation in the community and physical rehabilitation including AT should be combined. A simple practice framework is proposed that an ongoing cycle of assessment, shared goal setting, intervention, practice and review. The paper represents a consensus that the best rehabilitation approach is one that not only enables older adults to accomplish a task but restores their confidence, freedom of choice, social support and sense of dignity and helps them to once again enjoy a rich, fulfilling life.

Deepak Dandwate  ·  International Journal of Technology and Emerging Research  ·  22 Jul 2026

This research paper examines the critical relationship between emotional intelligence (EI) and leadership development in contemporary organizational contexts. Through analysis of current literature and data interpretation, this study explores how emotional intelligence competencies directly impact leadership effectiveness, team performance, and organizational outcomes. The findings suggest that leaders with higher emotional intelligence demonstrate superior performance in decision-making, team management, and organizational change initiatives.

RAJESH KUMAR MISHRA  ·  International Journal of Physical and Chemical Sciences  ·  21 Jul 2026

Artificial intelligence (AI) and machine learning (ML) are increasingly used as general-purpose research instruments across the physical sciences, accelerating tasks that were traditionally limited by trial-and-error experimentation, computational cost, or the sheer dimensionality of the underlying physics. Three areas illustrate this shift with particular clarity: computational materials discovery, nanostructured electrode design for energy storage, and space weather / heliophysics forecasting. Despite substantial progress in each area individually, limited work has examined them together, quantitatively, as expressions of a single underlying trend — the convergence of AI methodology with core physical and chemical science. Methods: This study used a narrative and scoping review methodology, incorporating quantitative benchmarks drawn directly from primary and independent critical sources. Peer-reviewed literature, preprints, direct observational monitoring data, and ResearchGate-hosted scholarly works published primarily between 2023 and 2026 were identified through structured searches combining terms from materials informatics, nanostructured energy-storage materials, and AI-based space weather forecasting. Sources were screened for topical relevance and synthesized thematically, with reported quantitative claims cross-checked against independent critical appraisal where available. Results: The synthesis identifies convergent innovation across three domains, with all three now quantitatively documented: (1) AI-driven inverse design (exemplified by a 2.2-million-structure materials search yielding roughly 380,000 candidate stable materials) is accelerating materials discovery, though independent re-analysis found only a small fraction of these structures met joint criteria of novelty, credibility, and utility; (2) nanostructured graphene–metal oxide composite electrodes span a wide reported performance envelope (specific capacitances from roughly 100 F/g to over 1000 F/g; energy densities up to roughly 100+ Wh/kg), with statistically designed synthesis optimization improving reproducibility; and (3) AI-assisted forecasting achieved approximately one-minute precision in reconstructing a major 2024 geomagnetic superstorm, in contrast to a roughly 40% amplitude error and nine-month timing error in the leading pre-cycle statistical/physical forecast of Solar Cycle 25's overall intensity. Discussion: A common methodological pattern recurs across all three domains: AI is used not to replace physical theory but to navigate high-dimensional parameter spaces that are analytically or computationally intractable by classical means alone, and the strongest, most defensible results are those subjected to independent, domain-expert critical appraisal rather than accepted at face value. Conclusion: Continued progress will depend on higher-quality shared datasets, physics-informed model architectures, standardized benchmarking protocols, and routine independent critical appraisal as a formal part of the AI-for-science publication cycle.

Kevin George  ·  International Journal of Education, Pedagogy and Psychology  ·  20 Jul 2026

This essay examines the Indian humanities classroom as both a site of postcolonial critique and a space in which the authority structures that postcolonial theory seeks to dismantle are frequently reproduced. Drawing on the work of Ngũgĩ wa Thiong'o, Audre Lorde, Derek Walcott, and Mikhail Bakhtin, it argues for a dialogic pedagogy that holds teachers accountable to the critical commitments their discipline professes. The essay proceeds through three movements: an opening reflection on the gap between scholarly self-representation and pedagogical practice; an account of classroom encounters — at a slum outreach school in Chennai and at Saint Berchmans College, Kerala — in which genuinely dialogic moments emerged; and a concluding argument for the postcolonial classroom as a site of ethical as well as intellectual responsibility. The essay notes, finally, that Kerala's pedagogical tradition offers a partial but instructive counterexample to the broader tendency of Indian higher education to reproduce the monologic classroom it nominally opposes.

alfredndi, Vernyuy Nyuyshi Gilbert, Manuela Wankam, Silas Manda  ·  International Journal of Education, Pedagogy and Psychology  ·  20 Jul 2026

This paper examines how cognitive load dynamics mediate the inefficiency of the learning curve observed when innovative pedagogical and research practices are introduced into higher education in Cameroon. Grounded in Cognitive Load Theory (CLT) and complementary evidence-based instructional design principles, the study combines a mixed-methods diagnostic of curricula, classroom practice, and institutional constraints with a synthesis of empirical literature. The paper identifies and analyses twenty principal findings showing how intrinsic, extraneous, and germane loads interact with contextual factors (large classes, bilingual instruction, limited infrastructure, variable student preparation) to produce slowed or regressive learning curves following innovation adoption. For each finding, we present theoretical interpretation, empirical reasoning, and actionable recommendations—emphasizing worked examples, scaffolding with systematic fading, modality choices, segmentation, pre-training, and assessment aligned to schema acquisition. The discussion situates Cameroon-specific constraints within global CLT evidence and proposes a policy-practice roadmap to accelerate efficient learning curves. Predictive analytics are introduced to model expected learning-curve trajectories under alternative design interventions. The paper concludes with implications for educators and policymakers, and a prioritized research agenda for empirically testing CLT-informed interventions in Cameroonian higher education.

Janet Adenuga, Dr. Adebayo Ade Adebola  ·  International Journal of Philosophy, Ethics and Humanities  ·  19 Jul 2026

This study examined the influence of accounting ethics on the performance of corporate entities, using Atlantic Textile Manufacturing Company in Lagos State, Nigeria, as a case study. The study adopted a descriptive survey research design and utilized primary data collected through structured questionnaires administered to 51 respondents drawn from accounting, finance, internal audit, and management departments. Data were analyzed using descriptive statistics, Pearson Product Moment Correlation, and regression analysis. Findings revealed that accounting ethics has a strong positive and statistically significant relationship with corporate performance (r = 0.655, p < 0.05). The study further established that ethical accounting practices significantly influence financial performance, operational efficiency, stakeholder confidence, and corporate sustainability. Ethical principles such as integrity, objectivity, professional competence, confidentiality, and due care were found to improve transparency, accountability, and managerial decision-making. The study concluded that accounting ethics is a major determinant of sustainable corporate performance in manufacturing firms. It recommended that organizations should strengthen ethical compliance frameworks, provide continuous ethics training for accounting personnel, and enforce strict adherence to professional accounting standards.

Dr. Ravi Ranjan Pandey  ·  International Journal of Philosophy, Ethics and Humanities  ·  19 Jul 2026

The climate issue is twofold centred on cities. They are the greatest contributors to emissions that accelerate warming and they focus the population and resources that are endangered by warming. That dual exposure is the beginning point in this paper and it poses a more difficult question than one can reasonably have with a typical survey. It is not merely the issue of what climate change does to urban ecosystems that are problematic, but why the instruments of managing urban ecologies continue to fail to match the magnitude of the challenge. It bases its argument on the numbers provided by Intergovernmental Panel on Climate Change, UN-Habitat, and some recent peer-reviewed literature, labeling the reaction to climate change in urban areas as being ambitious and lacking in coordination. Medellin green corridors and other examples of nature based interventions demonstrate that urban green areas can be used to quantifiably cool the city. However, their advantages are not equally spread and their form of governance is disregarded in a fragmented polycentric system of municipal networks, ministries of the national governments and private actors which are not accountable to each other. The discussion has come to the conclusion that it is no longer the knowledge or even technology that would be the decisive constraint on the action taken to improve the urban climate. It is the structure of governing: who governs, who funds and who cools off the first.

Alfred Ndi, Concilia Kum  ·  International Journal of Philosophy, Ethics and Humanities  ·  19 Jul 2026

This paper offers a comprehensive, evidence-based framework for determining the authenticity of videos of politicians, with particular emphasis on the Cameroonian context and comparable African information environments. Combining media-forensic practice, social verification methods, and critical theory, the paper synthesizes technical indicators (visual, audio, metadata), network and provenance analysis, and socio-political contextual checks into ten practical findings. Each finding is discussed in depth, with stepwise verification actions, expected limitations, and recommended escalation routes. The framework integrates insights from deepfake research, information disorder scholarship, and postcolonial critiques of platform governance to situate technical detection within broader power dynamics and digital sovereignty concerns. The paper concludes with policy and capacity-building recommendations for journalists, civil society, platform moderators, and citizens in Cameroon.

Sunny Devel  ·  International Journal of Sociology and Social Research  ·  19 Jul 2026

The issue of climate change and the degradation in biodiversity have ceased to be a far off environmental concern but a part of everyday strain on the lives of those who are in the most immediate contact with the environment. The paper discusses the impacts of these two crises on the lives and sustainability of tribal peoples in general with specific focus on forest-reliant Adivasi people in India as compared to the larger global context. It combines recent evidence of the global evaluation about the Intergovernmental Science Policy Platform on Biodiversity and Ecosystem Services, the Living Planet Report of the World Wide Fund on Nature, the temperature record verified by the World Meteorological Organization, the effects estimation of the Intergovernmental panel on climate change, and reads that information alongside census and forestry data about tribal populations. The main point is that the tribal communities are in a problematic dual position.

Dr. Pravinkumar bhimrao Moon  ·  International Journal of Technology and Emerging Research  ·  19 Jul 2026

Whisky production generates large volumes of organic co-products—primarily pot ale (liquid) and draff (solids)—which represent both an environmental disposal challenge and an opportunity as feedstock for renewable fuels. This review synthesizes the literature on converting whisky distilling wastes into green hydrogen, covering feedstock characterization, biological, thermochemical and electrochemical hydrogen pathways, and techno-economic and life-cycle perspectives. We place special emphasis on how artificial intelligence (AI) and machine learning (ML) methods are being applied (and can be further applied) to optimize yields, reduce costs, and enable robust real-time control. We identify promising hybrid routes (e.g., anaerobic pretreatment → reforming or novel two-stage electrolysis), review case studies and pilots, evaluate barriers (scale, water content, nutrient balance, impurity management), and outline a research roadmap linking process data, digital twins, and AI-driven optimization to accelerate deployment. Key recommendations include (1) integrated process design combining biological and electrochemical stages for small-/medium-scale distilleries, (2) systematic collection of sensor and performance data to train predictive models, and (3) life-cycle and techno-economic standardization to compare pathways.