Throwing shade on the dark side of AI

Artificial intelligence, AI, has become one of the defining technologies of what economists and policymakers describe as the Fourth Industrial Revolution. This is an era in which digital, physical, and biological systems are increasingly intertwined. In practical terms, AI refers to computer systems capable of performing tasks that typically require human intelligence, such as recognising patterns, learning from data, making predictions, and assisting in complex decisions.

Aside from the generative AI and search tools that are at the forefront of the media and economic hyperbole, analytical and related AI systems already underpin smart manufacturing platforms, digital twins for testing and optimising equipment performance, adaptive cybersecurity tools, medical diagnostics, and much more. It is unlikely that within a decade or so many occupations will not have been augmented or displaced by AI tools. The potential for productivity, innovation, and economic growth is great.

As with any new technology, however, there are good reasons to look closely at the social and economic impact AI might have. It would be prudent to put safeguards in place urgently given the way in which technologies have often amplified inequality, weakened democratic norms, and introduced new systemic risks in the past.

Research in the International Journal of Generative Artificial Intelligence has looked closely at many of the issues that are coming to the fore, such as labour disruption, deepfakes, the opacity of advanced AI models, bias, copyright, privacy, and security issues. Then, there is the issue of whether a superintelligent AI might surpass human abilities and redefine our very existence, perhaps even determining, algorithmically or some kind of awareness, that we as a species are redundant, or worse, a problem that needs to be removed.

The researchers suggest that at the geopolitical level, international coordination is a major challenge, not least given the rogue behaviour of some so-called state actors. The trajectory that AI takes in this Fourth Industrial Revolution is not fixed, nor is it predictable. We need to work together to ensure that it works for the benefit of humanity and the planet.

Min, H. (2026) ‘The dark side of artificial intelligence’, Int. J. Generative Artificial Intelligence in Business, Vol. 1, Nos. 1/2, pp.199–209.

Free sample articles newly available from International Journal of Powertrains

The following sample articles from the International Journal of Powertrains are now available here for free:

• Short-term load forecasting technique for power system based on grey correlation analysis and factor analysis
• Experimental study on cold start strategy of high-power fuel cell system
• Physics-based reverse recovery modelling of ultrafast recovery Si diodes with carrier lifetime control
• Performance evaluation of ant colony optimisation suggested energy management in using HOMER
• Energy management techniques for fuel cell hybrid electric vehicles: a critical review

Free Open Access issue published by International Journal of Critical Infrastructures

The International Journal of Critical Infrastructures has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Extraction of crack characteristics and local damage detection in complex hydraulic concrete structures
• BIM parametric modelling analysis of instability of concrete building components under continuous vibration

Free sample articles newly available from International Journal of Smart Technology and Learning

The following sample articles from the International Journal of Smart Technology and Learning are now available here for free:

• Revolutionising education: the evolution, current landscape and future of digital learning
• Challenges for teachers in integrating ICT into geography teaching and promoting map reading skills in secondary schools in Namibia
• Algerian students' satisfaction with using ICT in higher education: the application of the technology satisfaction model
• The effect of video-based tool approach on facilitating socioemotional regulation skills in CSCL environments
• Unveiling the social media surveillance research: themes, ethics and global implications
• Smart education: opportunities, challenges and future of traditional education

New Open Access article available: "Unethical leadership in the South African public sector tender processes through the lens of game theory"

The following International Journal of Business Governance and Ethics article, "Unethical leadership in the South African public sector tender processes through the lens of game theory", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

New Open Access article available: "AI in sustainable higher education: an interpretive structural model and MICMAC approach"

The following International Journal of Business and Globalisation article, "AI in sustainable higher education: an interpretive structural model and MICMAC approach", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

New Open Access article available: "Applying the Jidoka concept to white-collar departments: an examination of the JKK initiative at Toyota Motors"

The following International Journal of Automotive Technology and Management article, "Applying the Jidoka concept to white-collar departments: an examination of the JKK initiative at Toyota Motors", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access issue published by World Review of Entrepreneurship, Management and Sustainable Development

The World Review of Entrepreneurship, Management and Sustainable Development has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Entrepreneurship at the base of the pyramid: effectual logics and sustainable development
• Potential of digital marketing and determinants of the 5A marketing strategy: a case in Thailand

Free sample articles newly available from International Journal of Project Organisation and Management

The following sample articles from the International Journal of Project Organisation and Management are now available here for free:

• Critical factors and intention to use public private partnership in public projects in Ghana: the mediating role of institutional quality
• Project management methods against failure factors in complex infrastructure projects: the Netherlands view
• Driving forces for multinational construction consortiums: the case of a Greek mega-project
• Cross-functional integration case study from project management office: impacts, controversies and inhibitors
• A critique of project management research

Research pick: Sites of the underground - "Application of deep learning algorithms in the design of urban subway public art space"

Underground metro (subway) stations are no longer merely points of departure and arrival. As cities grow denser and transit networks expand, these spaces have the potential to function as some of the most widely shared public interiors in urban life. They are places where millions pass daily, cutting across age, income, and neighbourhood. They offer a rare platform for collective cultural experience. Stations can, suggests research in the International Journal of Environment and Sustainable Development, anchor local identity, narrate a city’s history, and shape how residents and visitors alike perceive the character of the urban environment.

The research addresses a practical question confronting transport authorities and urban designers: how can large-scale public art projects fit into this infrastructure as it changes? Traditional artist-led design processes, though highly creative, can be time-intensive. By contrast, deep learning has allowed computers to generate high-quality images at speed. The missing link is that the computer-generated images may not understand the cultural meaning that the images need to convey. There is also a need to take into account how well a design might be installed in a real site.

The researchers hope to bridge this gap and have developed a multi-stage framework that integrates cultural analysis, visual cognition modelling, and spatial feasibility testing into a single pipeline.

Their approach is based on a semantic labelling system. The system can organise cultural concepts, such as local history, regional traditions, and environmental identity, into a knowledge graph. This graph can map relationships between ideas, enabling the computer to understand individual symbols and how they fit with broader narratives.

The framework then uses Contrastive Language-Image Pretraining, CLIP, is a deep neural network trained on vast datasets of containing pairings of images and text. An additional layer simulates human perception through a visual attention prediction network, considering composition, spatial layout, and pedestrian flow. By predicting where passengers are likely to focus while moving through a station, the system can position key symbolic elements in high-attention zones. The researchers suggest this could improve not only the aesthetic impact of the art installation but also the way in which pedestrians navigate the subway stations.

Wang. Q. (2026) ‘Application of deep learning algorithms in the design of urban subway public art space’, Int. J. Environment and Sustainable Development, Vol. 25, No. 5, pp.44–72.

Free sample articles newly available from International Journal of Computing Science and Mathematics

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• Short-term power load prediction based on CNN-LSTM model
• Multi-objective optimisation of cigarette production planning and inventory management
• Offshore wind power prediction based on chaotic optimisation PSO-SCN-LSTM model
• A method for capturing English oral pronunciation errors based on speech recognition
• Visual communication method for multi feature media images based on interactive modelling
• A synergic deep learning approach for efficient grading of glioma via MRI images

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Cross-modal sentiment analysis of new media content based on an enhanced question-answering framework
• A fusion architecture of heterogeneous graph neural network and reinforcement learning for business innovation decision-making
• Investigation of a music genre data classification method based on an improved ECAPA-TDNN algorithm
• Mobile terminal-assisted interactive English learning design to facilitate knowledge deepening
• Fusing ConvLSTM and graph convolutional network for mapping the suitability of elderly-friendly tourist destinations

Free sample articles newly available from International Journal of Services, Economics and Management

The following sample articles from the International Journal of Services, Economics and Management are now available here for free:

• Research of the possibilities and results of the implementation of the principles of the green economy using Industry 4.0 technologies on the example of the utility sector
• Is the game worth a candle? Users' adoption of private cloud computing
• Telecommunications service industry collaboration with over the top services for optimising state revenue in Indonesia
• Entrepreneurial initiatives during pandemic in Bangladesh
• Analysis of critical success factors in robust service systems through fuzzy cognitive map

Free sample articles newly available from International Journal of Environmental Engineering

The following sample articles from the International Journal of Environmental Engineering are now available here for free:

• Assessment of daily and seasonal concentrations of particulates matters generated by rice mills in Makurdi using cluster analysis
• Kinetics of adsorption of pollutants removal from mine wastewater by a coal fly ash-based coagulant
• Exploring the intensity, duration and frequency of rainfall in selected Southern Nigeria's urban landscapes
• Environmental and economic modelling for municipal solid waste management strategies: a case study in OH, USA
• Electrochemical recovery of copper from the waste computer printed circuit board

Research pick: Rebuilding Syria ethically - "Mediating role of ethical intention between social norms, code of ethics and ethical decision-making"

In a country where the physical scars of war remain visible in shattered buildings and disrupted markets, research in the International Journal of Diplomacy and Economy suggests that the moral architecture of business may be just as important to recovery in Syria as capital investment and bricks & mortar.

A study of 200 business leaders working in international companies in Aleppo and Damascus finds that ethical decision-making in Syria can be explained, to a significant degree, by a well-established psychological framework known as the Theory of Planned Behaviour. This theory suggests that human behaviour is primarily shaped by intention, a person’s conscious plan or readiness to act. Those intentions, in turn, are influenced by three factors: personal attitudes, perceived social expectations, and perceived control over whether the behaviour is realistically achievable.

In practical terms, individuals are more likely to act ethically if they believe ethical conduct is right, think that others expect it of them, and feel capable of acting accordingly.

The researchers applied this theory in the context of Syria as part of an effort to understand how business leaders make ethical choices amid conflict, economic disruption, and institutional fragility. Their focus was Syria’s post-war reconstruction drive, a national strategy aimed at restoring infrastructure, reviving markets, and rebuilding social trust after years of violence.

Trust, the study notes, is not an abstract virtue in such an environment. It is a prerequisite for attracting investment, stabilising supply chains, and enabling cooperation between domestic firms and international partners. Ethical business conduct is thus a functional prerequisite of economic recovery.

For practitioners, the implications are concrete. The findings indicate that organisations seeking to strengthen ethical leadership cannot rely solely on written rules. Codes of ethics must be actively communicated and embedded within organisational culture, the shared values and practices that shape everyday work. When ethical expectations become part of that culture, they function as powerful social norms, guiding behaviour even in the absence of direct oversight.

Amoozegar, A., Lata, A., Falahat, M., Shakib, S., Kumar, M., Ramzani, S.R. and Yadav, M. (2026) ‘Mediating role of ethical intention between social norms, code of ethics and ethical decision-making’, Int. J. Diplomacy and Economy, Vol. 12, No. 5, pp.1–20.

Free sample articles newly available from International Journal of Accounting, Auditing and Performance Evaluation

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• Small and medium-sized entities as users of accounting services: do professional accountants meet the needs of their SME client?
• Fraud investigation skills for internal auditors
• The global credit sector in shadow of COVID-19: financial assessment
• Contents and determinants of corporate social responsibility reporting in the context of the Arab Spring crisis
• The role of big data in public sector accounting and budgeting practices: evidence from a pandemic environment of an emerging economy
• Economic policy uncertainty and earnings management: evidence from China
• Organisational justice, mediated by affective commitment, and time budget pressure effect to the millennial auditor turnover intention
• Successive economic cycles and the Fisher effect
• To what extent Covid-19 pandemic affect corporate risk disclosure: case of UAE listed companies
• Auditing in times of the coronavirus disease 2019 pandemic: qualitative research in the Tunisian context
• Corporate governance and financial stability of the English Premier League before and during COVID-19
• Interdependence between the Moroccan and international stock markets before and during the Covid-19 crisis
• The impact of risk-taking on performance of Islamic and conventional banks in Qatar, Saudi Arabia and UAE
• Do board and audit characteristics affect earnings management in times of Covid-19?
• Financial reporting considerations in response to the COVID-19 pandemic: empirical evidence from the UAE accounting professionals

Free sample articles newly available from International Journal of Sustainable Society

The following sample articles from the International Journal of Sustainable Society are now available here for free:

• Land use/land cover dynamics and its future scenarios in Luando Reserve, Angola
• Engaging ordinary people in sustainability transition: introducing elasticity and plasticity model for social change
• Circular economy model and sustainable development nexus in Bangladesh
• Effect of firm specific characteristics and interest rate on lease financing of listed consumer goods firms in Nigeria
• A sustainable territorial challenge: the irreversible impressions on waste and residue management from functional community workshops

Free sample articles newly available from International Journal of Arts and Technology

The following sample articles from the International Journal of Arts and Technology are now available here for free:

• A survey on the epistolary calligraphy art of Kim Jeonghui during his early exile period
• New media popular music recommendation system based on machine learning algorithm
• An analysis of text-to-image generative models as creativity support tools
• Personalised music experience based on fuzzy music emotion analysis and intelligent recommendation
• Colour configuration of residential interior spaces preferred by the older people in Jinan City

Free sample articles newly available from International Journal of Web and Grid Services

The following sample articles from the International Journal of Web and Grid Services are now available here for free:

• A survey on knowledge graph evolution: proliferation, dynamic embedding, and versioning
• Optimisation of multi-objective cloud manufacturing service selection based on dynamic adaptive bat algorithm
• IoT avatar: various objects in real space are anthropomorphised as avatars
• Intelligent cognitive internet of things-based spectrum sensing algorithm for future communication
• Improving accessibility of IT devices for individuals with disabilities by examining their characteristics and voice of customers

Free sample articles newly available from International Journal of Technology Management

The following sample articles from the International Journal of Technology Management are now available here for free:

• Innovation at the project-level: the role of organisational innovation capabilities
• Development and application of patent management maturity model: a capability-based perspective
• Does the techno-nationalism approach work for the nation's catch-up? The evaluation of MLP (2006-2020) in China
• Generational technological change, organisational search, and firm product innovation performance in new generational markets
• Artificial intelligence and business applications, an introduction

Research pick: The drugs do work - "Deep learning-based virtual screening system for drug molecules"

The earliest stage of drug discovery is governed by a simple constraint: there are far more possible drug-like molecules than any pharmaceutical laboratory could ever test. A new deep learning system, reported in the International Journal of Reasoning-based Intelligent Systems, offers a way to speed up research and could unblock industry bottlenecks.

Bringing a new pharmaceutical to market can take more than a decade and will inevitably cost billions of dollars in research and development, testing, regulatory compliance, and marketing. A large share of that investment is spent on identifying compounds that bind to biological targets, these are commonly proteins involved in disease, whether a protein found in a pathogen or a protein in our bodies involved in the disease. Virtual screening, so-called in silico studies, has for decades used computer models to predict which molecules from a library of candidates might be suitable for testing in vitro (in the laboratory) and ultimately in vivo (in animals, then humans).

That said, established methods fall into two categories. The first are receptor-based approaches, such as molecular docking, that simulate how a molecule fits into a protein’s three-dimensional binding site and estimate the strength of the bond that forms between. The accuracy of this approach depends on high-quality protein structures and simplified scoring formulae. A second approach is the ligand-based approach and this instead looks for compounds resembling known active molecules, using predefined chemical features, or descriptors.

These techniques can be computationally efficient and heavily successfully led to many pharmaceuticals on the market today. However, they rely heavily on prior knowledge and expert assumptions. In both cases, human-designed rules limit how much chemical complexity can be captured. The advent of deep learning systems is opening up a new approach.

Instead of manual feature selection, deep learning, a form of machine learning that uses multi-layered neural networks to detect patterns directly from raw data, can treat drug candidate molecules as graphs, with atoms as nodes and chemical bonds as edges. A graph neural network updates each atom’s representation based on its neighbours, allowing the model to learn subtle structural relationships.

Crucially, this new approach uses another information channel in addition to the graph. It handles the drug candidate’s SMILES string. A SMILES string is a unique text-based representation of the chemical structure of a molecule. By using structural and sequential representations together, the researchers could improve performance significantly. In tests on standard public benchmarks, the model achieved a score of 0.889; where 1.000 would be a perfect score. This score is a measure of how well the system distinguishes between active and inactive drug candidates. A score of 1 is ideal prediction whereas 0.5 reflects a 50:50 chance, a guess. Incredibly, the system could screen one million molecules in a quarter of an hour, which is 80 per cent faster than conventional approaches.

Zhang, C. (2026) ‘Deep learning-based virtual screening system for drug molecules’, Int. J. Reasoning-based Intelligent Systems, Vol. 18, No. 8, pp.44–55.

Research pick: Power to the people - "Quality inspection of power transmission towers based on point cloud registration"

Electricity pylons, or transmission towers, have been a critical component of energy infrastructure for decades. The structural integrity of these power towers, which stride across landscapes the world over, is vital to power supply and public safety.

A study in the International Journal of Energy Technology and Policy has investigated a novel, more precise and efficient way to inspect pylons using advanced 3D scanning and geometric analysis. The approach might speed up the shift from labour-intensive field checks to what might be referred to as a fully digital inspection regime.

The researchers explain that a laser system can be used to scan a pylon’s geometry in minute detail to generate a “point cloud”. This is a collection of millions of spatial points representing the pylon’s surface. To assess structural integrity, multiple scans are taken from different angles and then must be aligned into a single coordinate system in a registration process. This typically occurs in two stages: coarse registration, which provides an initial alignment, and fine registration, which refines it to high precision.

The lattice frameworks of pylons with their intersecting beams and sharp edges generate extremely large datasets and create ambiguities when identifying matching features, so registration even with the best algorithms is tough and consequently error-prone. In the IJETP paper, the researchers propose the use of Gaussian curvature in the feature-extraction process required for registration. Gaussian curvature is a mathematical measure of how a surface bends at a given point: flat areas have near-zero curvature, while sharp edges or corners have higher values. Because beam intersections and joints exhibit high curvature, they provide distinctive geometric markers for alignment.

Once aligned, the digital model of the pylon can then be compared with a high-precision reference design to identify geometric deviations. This allows engineers to detect misalignments or structural problems with confidence and so prioritise maintenance and repair across the power grid.

Qi, X., Yan, H., Tu, X., Liu, Y. and Ding, W. (2025) ‘Quality inspection of power transmission towers based on point cloud registration’, Int. J. Energy Technology and Policy, Vol. 20, No. 7, pp.3–22.

Free sample articles newly available from International Journal of Advanced Operations Management

The following sample articles from the International Journal of Advanced Operations Management are now available here for free:

• Defect detection while setting up an assembly line - analytical approach to reduce the N-dimensional solution space
• Supply chain management and logistics in the Arab region: current status and future trends
• Examining the impact of recruitment process outsourcing motivators on clients' satisfaction: a study of banking sector in India
• Implementing circular economy practices in Indian SMEs: analysis of challenges with case study
• The role of switching costs in third-party logistics

Free sample articles newly available from International Journal of Surface Science and Engineering

The following sample articles from the International Journal of Surface Science and Engineering are now available here for free:

• Investigation on the transient asperity contact behaviours of water-lubricated bearing under start-stop cycle
• Non-contact surface roughness measurement of blasted specimens using machine vision technique
• Studying the load capacity and frictional force in an engine based on microtexture's different dimensions
• Enhancing tribological and corrosion performance of SLM fabricated AlSi12Mg components through ultrasonic assisted magnetic abrasive finishing
• Investigation on the salt electrochemical corrosion resistance of a robust superhydrophobic thin film with controllably inlaid micro/nano composite structures

First issue: International Journal of Generative Artificial Intelligence in Business (free sample issue available)

The International Journal of Generative Artificial Intelligence in Business offers a leading interdisciplinary platform dedicated to exploring the transformative impact of generative AI across business functions. The journal addresses a critical gap in research on GenAI's strategic, operational, ethical and societal implications in areas such as marketing, finance, supply chain, human resources, entrepreneurship and strategy. IJGAIB aims to inform scholarship, practice and policy, establishing itself as a timely, innovative and globally relevant voice in the evolving AI-business landscape.

There is a free download of the papers from this first issue.

Research pick: Hey, teacher! Lead those kids online! - "Analysis of factors influencing student learning experience in the blended online-offline smart education model"

Educators are using digital platforms more and more alongside conventional classroom teaching. A study in the International Journal of Continuing Engineering Education and Life-Long Learning has taken a look at the important question of whether or not this “blended” educational model enhances learning.

Blended online-offline education, sometimes referred to as smart education, combines face-to-face instruction with tools such as learning management systems, digital resources, and data-driven feedback. It was already being used prior to the covid pandemic, but in 2020 it became a critical part of educational life and since then has become embedded in education. It is flexible and holds the promise of personalised learning. However, systematic research into how students experience offline-online education has not kept pace with digital developments.

The research in IJCEELL identified 14 different factors that could shape the student learning experience. They grouped these into five broad dimensions: course environment and platform, course design, teacher characteristics, learner characteristics and social interaction. The factors included the reliability and usability of digital systems, the clarity and coherence of course structure, the responsiveness of teachers, the capacity of students for self-directed learning, and the quality of peer engagement.

Rather than treating these factors as separate variables, the researchers examined how they interact to give particular outcomes. As such, they used an interpretive structural model to find the hierarchical relationships. In practical terms, this approach can distinguish between foundational elements, intermediary influences, and the educational outcomes.

Their structural model has course content and resource infrastructure at its foundations. Teaching interaction and learner-related factors such as motivation and self-regulation then sit on top of these foundations. The layer above that is the learning outcomes, including satisfaction and performance. As one might expect, the model showed that student experience emerges from interconnected factors from the base to the top, rather than isolated inputs.

The framework demonstrated more than 95 per cent accuracy and performed better than earlier approaches that used static surveys or business-derived models where factors are all treated independently. Ultimately, it showed that investment in digital technology alone is unlikely to transform learning outcomes without close attention also being paid to course design and teacher development.

Fang, Y. and Hu, J. (2026) ‘Analysis of factors influencing student learning experience in the blended online-offline smart education model’, Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 36, No. 7, pp.23–34.

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Early warning of college students' ideological public opinion based on TF-IDF and RFB neural network
• Optimal allocation model network of human resources in energy enterprises based on NSGA-II
• Multimodal deep learning for evidence assessment with algorithmic bias analysis in criminal law
• College students' career planning for the development of low-carbon renewable energy economy
• The synergy of educational resource allocation and teacher motivation based on NSGA-II model

Free Open Access issue published by International Journal of Data Mining, Modelling and Management

The International Journal of Data Mining, Modelling and Management has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Ensemble learning models for predicting the gaming addiction behaviours of adolescents
• Comparative analysis of distance measures in stock network construction and cluster analysis
• A frequent itemset generation approach in data mining using transaction-labelling dynamic itemset counting method
• Enhancing link prediction in dynamic social networks: a novel algorithm integrating global and local topological structures
• Sorting paired points: a dissimilarity measure based on sorting of series

Free Open Access special issue on "Green Supply Chain Management: Innovations in Sustainable Business Environment and Digital Transformation – Part 1" published by International Journal of Environment and Sustainable Development

The International Journal of Environment and Sustainable Development has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Dynamic monitoring and evolution of urban green space landscape sustainability based on spatiotemporal analysis algorithm
• Resilience enhancement in heterogeneous supply chain networks: complex network analysis and collaborative optimisation of intelligent systems
• Application of deep learning algorithms in the design of urban subway public art space
• Construction of simulation model of rural water and soil environment based on digital twin technology and GIS
• Collaborative dual-cycle for supply chain system construction based on distributed computing

Research pick: China goes green - "Empowering sustainable growth: the transformative impact of environmental protection inspections on heavy polluters"

For decades, China’s ascent to become the world’s second-largest economy was powered by coal-fired energy, steel mills, and chemical plants. The environmental toll grew increasingly visible. In 2016, Beijing launched one of its most sweeping regulatory interventions, the centralised Environmental Protection Inspection (EPI) programme. This would dispatch inspection teams to scrutinise the activities of local governments and major polluters.

Research in the International Journal of Environment and Pollution suggests that the programme has done more than curb emissions. It has improved what economists call green total factor productivity (GTFP) among some of the country’s heaviest polluters.

Traditional productivity measures assess how efficiently companies turn inputs such as labour and capital into output. They ignore pollution generated in the process. GTFP adjusts for this by counting emissions and other environmental damage as undesirable outputs. In effect, it measures not only how much a firm produces but also how cleanly it does so. A rise in GTFP means a company is generating more economic value for the same environmental cost or maintaining output while reducing pollution.

The research analysed almost a decade’s worth of data from Chinese A-share listed companies across heavily polluting industries. The researchers tracked changes over time using specialist efficiency models, which incorporated environmental factors into their productivity calculations. They then used statistics to compare firms subject to inspections with those that were not, before and after the introduction of the policy. This approach would isolate the effect of the inspections from other economic trends.

The results show a statistically significant increase in GTFP among heavily polluting enterprises following the inspections. Importantly, the gains do not appear to stem primarily from temporary production cuts to meet emissions targets. Instead, the evidence points to increased green technological innovation. Firms invested in cleaner technologies, energy-efficiency upgrades, and process improvements that reduced their environmental footprint in the long term.

Gu, Y., and Liu, C. (2026) ‘Empowering sustainable growth: the transformative impact of environmental protection inspections on heavy polluters’, Int. J. Environment and Pollution, Vol. 76, Nos. 1/2, pp.40–56.

New Open Access article available: "Mediating role of ethical intention between social norms, code of ethics and ethical decision-making"

The following International Journal of Diplomacy and Economy article, "Mediating role of ethical intention between social norms, code of ethics and ethical decision-making", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access special issue on "Adaptive E-Learning Technologies and Experiences" published by International Journal of Continuing Engineering Education and Life-Long Learning

The International Journal of Continuing Engineering Education and Life-Long Learning has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Construction of intelligent student management evaluation information system based on clustering algorithm
• Analysis of factors influencing student learning experience in the blended online-offline smart education model
• Study on fuzzy comprehensive evaluation of English teaching quality based on artificial neural network
• The strategy of empowering education development with artificial intelligence in the digital age
• The application effect of MOOC videos in English audio-visual teaching
• Cloud-based user behaviour analysis and personalised recommendation of sports teaching system based on big data analysis
• An evaluation of online English teaching learning effectiveness based on decision tree classification algorithm

Free sample articles newly available from International Journal of Intelligent Engineering Informatics

The following sample articles from the International Journal of Intelligent Engineering Informatics are now available here for free:

• Binary encoding-based morpheme boundary detection of Dogri language
• Channel minimised depth-wise CNN with node weighted tree-LSTM model to detect nested query-based SQL injection attacks
• Autoencoder with salp optimisation technique for exploring SNP-SNP interactions in Alzheimer's disease
• Sarcasm detection using enhanced glove and bi-LSTM model based on deep learning techniques
• A software engineering approach for conceptualising an online learning scenario for a deductive approach

Open Access special issue on "Multiscale Energy Systems for Renewable Energy Storage: Part 2" published by International Journal of Energy Technology and Policy

The International Journal of Energy Technology and Policy has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Quality inspection of power transmission towers based on point cloud registration
• Analysis on the development path of rural energy digital economy from the perspective of artificial intelligence
• Reinforcement learning-based optimisation of intelligent battery thermal management system data
• Flow field analysis of agitated displacement tank for cementing equipment
• Panoramic display of multi-dimensional production information and calculation of spatiotemporal evolution under the data-driven one-map of power grid
• Causal reinforcement learning-based operational performance evaluation of multi-source energy storage power stations

Free Open Access article available: "Research on distribution network fault identification based on active transfer learning and autoencoder"

The following International Journal of Environment and Pollution article, "Research on distribution network fault identification based on active transfer learning and autoencoder", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: Don’t be hanging on the telephone - "Forward neck posture on cervical pain among university students: effect of smartphone addiction"

A study of university students has demonstrated a link between heavy smartphone use, forward head posture, and neck pain. The work, published in the International Journal of Medical Engineering and Informatics, highlights growing concerns about the physical costs of constant digital connectivity among young adults.

The researchers surveyed 404 students in Malaysia aged between 17 and 30 years old in what is referred to as a cross-sectional study. In such a study, data are collected at a single point in time rather than over an extended period of months or years. The students, 216 male and 188 female, completed an online questionnaire detailing their smartphone habits and any physical problems they experienced, such as backache or neck pain.

The team’s statistical analysis revealed that those using their smartphones for prolonged periods tended to have a forward neck posture and suffer neck pain. The analysis suggests that just 1 per cent of those had neck pain purely by coincidence and that it was unconnected to posture and smartphone use.

The cervical spine has seven vertebrae that support the head and protect the spinal cord. Forward neck posture describes the common position adopted while looking down at a phone, in which the head tilts forward and downwards. This posture increases the effective weight borne by the neck, placing added strain on muscles, ligaments, and joints. Over time, such strain can lead to irritation of soft tissues, cause nerve compression, and even affect the natural curvature of the spine detrimentally.

Although the study does not establish cause and effect, the strength of the association and its consistency with previous research point to the obvious conclusion that forward head posture during smartphone use is a modifiable risk factor for mechanical neck pain. Given that this problem is reportedly on the increase among younger people, the suggestion is that a little education and guidance on posture and reducing smartphone use would be well placed to preclude an epidemic of chronic spinal problems in this demographic.

Antoniraj, S., Hassan, H.C. and Baleswamy, K. (2026) ‘Forward neck posture on cervical pain among university students: effect of smartphone addiction’, Int. J. Medical Engineering and Informatics, Vol. 18, No. 2, pp.198–205.

Free Open Access article available: "Research on green trade data prediction under global economic shock based on ConvLSTM model oriented towards reducing carbon emissions"

The following International Journal of Environment and Pollution article, "Research on green trade data prediction under global economic shock based on ConvLSTM model oriented towards reducing carbon emissions", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free sample articles newly available from International Journal of Bio-Inspired Computation

The following sample articles from the International Journal of Bio-Inspired Computation are now available here for free:

• Multi-agent reinforcement learning based on self-satisfaction in sparse reward scenarios
• Methanol price prediction method based on multimodal fusion by using CNN-GRU and attention mechanism
• MANET routing with deep maxout-based energy prediction using optimisation
• Research on estimation of permeability coefficients in microbial geotechnical soils based on data-driven models
• Improved Dirichlet mixture model clustering algorithm for medical data anomaly detection
• Determinate node selection for semi-supervised classification oriented graph convolutional networks

Free Open Access article available: "Urban environmental sustainability and welfare management optimisation based on ant colony optimisation and embedded systems"

The following International Journal of Environment and Pollution article, "Urban environmental sustainability and welfare management optimisation based on ant colony optimisation and embedded systems", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Digital economy and global value chain restructuring from a cross-country sustainable industry analysis"

The following International Journal of Environment and Pollution article, "Digital economy and global value chain restructuring from a cross-country sustainable industry analysis", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Research on emergency monitoring methods for landslide disasters based on improved atmospheric correction GB-SAR and multi-source data geocoding"

The following International Journal of Environment and Pollution article, "Research on emergency monitoring methods for landslide disasters based on improved atmospheric correction GB-SAR and multi-source data geocoding", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access issue published by International Journal of Environment and Pollution

The International Journal of Environment and Pollution has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

Free Open Access article available: "Empowering sustainable growth: the transformative impact of environmental protection inspections on heavy polluters"

The following International Journal of Environment and Pollution article, "Empowering sustainable growth: the transformative impact of environmental protection inspections on heavy polluters", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Promoting the transformation of digital economy structure based on artificial intelligence in the low carbon economy environment"

The following International Journal of Environment and Pollution article, "Promoting the transformation of digital economy structure based on artificial intelligence in the low carbon economy environment", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Prof. I-Hsien Ting appointed as new Editor in Chief of International Journal of Social Network Mining

Prof. I-Hsien Ting from the National University of Kaohsiung in Taiwan, ROC has been appointed to take over editorship of the International Journal of Social Network Mining.

Free Open Access article available: "Evaluation and trend prediction of the relationship between carbon emissions, energy, and sustainable growth based on neural networks"

The following International Journal of Environment and Pollution article, "Evaluation and trend prediction of the relationship between carbon emissions, energy, and sustainable growth based on neural networks", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Financial deepening and fiscal capacity: new empirical evidence from the association of Southeast Asian nations"

The following International Journal of Economics and Business Research article, "Financial deepening and fiscal capacity: new empirical evidence from the association of Southeast Asian nations", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Validating the rational and intuitive decision-making styles - RIDMS scale across nine countries"

The following International Journal of Economics and Business Research article, "Validating the rational and intuitive decision-making styles - RIDMS scale across nine countries", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Exploring the impact of older knowledge workers' career capital on career success: with self-efficacy and job crafting as mediators and perceived organisational support as a moderator"

The following International Journal of Economics and Business Research article, "Exploring the impact of older knowledge workers' career capital on career success: with self-efficacy and job crafting as mediators and perceived organisational support as a moderator", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: Look through clouds from one side now - "SenseNet: satellite image enhancement using optimised deep denoiser for cloud removal"

Thick cloud cover can completely obscure the surface of the earth from satellite view, while thinner haze and shadows distort the image of rural and urban regions. As such, many remote sensing images for monitoring climate, crops, and urban growth are only partially usable.

Research in the International Journal of Bio-Inspired Computation offers a way for satellites to see through clouds using a hybrid artificial intelligence system. The system essentially removes clouds from the images sent back by the satellite and reconstructs the land surface beneath with greater fidelity than is possible with earlier techniques. Almost all optical satellite images are affected by clouds to some degree, so improvements in AI cloud removal could expand the reliability of high-resolution Earth observation data.

Traditional approaches have relied either on physical models of atmospheric light scattering or on image-processing techniques that compare multiple images through time or across different wavelengths of light. Those methods are useful but struggle with varying cloud thickness or large, fully obscured areas. More recent machine learning systems, in which algorithms learn patterns from large datasets, have improved results, but they need clear reference images, without them, they simply produce blurred areas where the landscape was obscured by clouds.

The new approach is a deep denoising application known as SenseNet. It treats those image pixels with clouds or haze as being structured noise that can be removed. The system uses a model inspired by nature called a hybrid Coyote Fox Optimisation algorithm, which works by modelling the social, cooperative behaviour in canines to take the input data and process it to find the optimal solution. In computational terms, it helps tune the network’s internal parameters so that training does not stall on suboptimal solutions that would otherwise confound the learning algorithm.

Compared with existing denoising approaches, the system improved signal-to-noise ratios by more than two decibels and reduced residual errors. An improvement of just 2 dB is an almost 60 per cent improvement.

By clearing the clouds away, the system can more readily delineate agricultural boundaries and map road networks and bodies of water so that phenomena such as deforestation, crop yields, and infrastructure can be viewed with more detail. In persistently cloudy regions, including much of the tropics, more reliable cloud removal could reduce data gaps, supporting climate adaptation and disaster response strategies that increasingly depend on near-real-time satellite intelligence.

Gound, R.S. and Thepade, S.D. (2026) ‘SenseNet: satellite image enhancement using optimised deep denoiser for cloud removal’, Int. J. Bio-Inspired Computation, Vol. 27, No. 1, pp.45–59.

Free Open Access article available: "Anomaly detection and pattern recognition methods for high-dimensional data"

The following International Journal of Computer Applications in Technology article, "Anomaly detection and pattern recognition methods for high-dimensional data", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access issue published by International Journal of Economics and Business Research

The International Journal of Economics and Business Research has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Exploring the impact of older knowledge workers' career capital on career success: with self-efficacy and job crafting as mediators and perceived organisational support as a moderator
• Validating the rational and intuitive decision-making styles - RIDMS scale across nine countries
• Financial deepening and fiscal capacity: new empirical evidence from the association of Southeast Asian nations

Research pick: The concrete and the clay avoid the crumble - "An adaptive recognition of abnormal behaviour in deep excavation support construction site of high-rise buildings"

As cities build upwards to accommodate growing populations, the safety of deep excavation, the process of digging large foundation pits to anchor high-rise buildings, has become a significant challenge in the construction industry. These pits must withstand the problem of shifting of the underlying earth, changes in groundwater pressure, and the heavy machinery while remaining stable enough to protect workers and nearby structures. Failures at this stage can trigger collapses, flooding or structural damage.

Work in the International Journal of Critical Infrastructures discusses an AI (artificial intelligence) system designed to improve safety monitoring at deep foundation pit support sites. The system aims to identify abnormal behaviour, such as unsafe actions, improper equipment use, or entry in restricted zones without protective gear, in close to real time so that warnings can be sounded in a timely manner.

Construction sites have traditionally relied on manual supervision and earlier generations of automated monitoring. But these approaches often struggle to detect unsafe behaviour quickly and accurately. Many systems record high false acceptance rates, meaning they mistakenly classify dangerous actions as safe. Others process video feeds too slowly to intervene effectively in rapidly changing environments.

The new system combines several advanced AI techniques to address those weaknesses. It begins by extracting key frames from surveillance footage using the fractional Fourier transform. This is a mathematical method that analyses data across different domains. By identifying the most informative frames rather than scanning every second of video, the system reduces computational load but still retains critical information.

The system then uses a spatiotemporal graph convolutional network, a form of deep learning that analyses both space and time data. The spatial analysis examines how workers and machinery are positioned relative to one another, while the temporal analysis tracks how movements change over time. Unlike conventional image-recognition models that treat frames in isolation, this approach captures sequences of actions and interactions. This is vital for working out what is happening moment to moment on the construction site.

The final step is to use a hybrid model that combines a convolutional neural network (CNN) with a so-called long short-term memory network (LSTM). The CNN can recognise visual features such as body posture or equipment shape. The LSTM can detect patterns in sequences of data. Working together, those two tools allow the system to determine not only what is happening in a single frame, but whether a series of movements constitutes a safety violation.

In their tests on active deep excavation sites, the researchers got a minimum false acceptance rate of 2.43 per cent and a peak abnormal behaviour recognition accuracy of 99.12 per cent. Processing time was as low as 0.19 seconds per analysis cycle, allowing near real-time monitoring.

Qi, W. (2026) ‘An adaptive recognition of abnormal behaviour in deep excavation support construction site of high-rise buildings’, Int. J. Critical Infrastructures, Vol. 22, No. 7, pp.1–17.

Free Open Access article available: "DAFPN: a lightweight multi-objective framework for small object detection in remote sensing images"

The following International Journal of Computer Applications in Technology article, "DAFPN: a lightweight multi-objective framework for small object detection in remote sensing images", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Cloud computing based construction and empirical evaluation of the security risk early warning evaluation system of digital economy"

The following International Journal of Computer Applications in Technology article, "Cloud computing based construction and empirical evaluation of the security risk early warning evaluation system of digital economy", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Pose estimation technology of electronic components based on point cloud segmentation algorithm"

The following International Journal of Computer Applications in Technology article, "Pose estimation technology of electronic components based on point cloud segmentation algorithm", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Mean-shift-based moving target tracking algorithm in complex industrial environments"

The following International Journal of Computer Applications in Technology article, "Mean-shift-based moving target tracking algorithm in complex industrial environments", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access special issue published by International Journal of Computer Applications in Technology: "Machine Learning for Cloud-Edge Emerging Network Architectures: Part 1"

The International Journal of Computer Applications in Technology has published an Open Access special issue: "Machine Learning for Cloud-Edge Emerging Network Architectures: Part 1". 

All of the issue’s papers can be downloaded via the full-text links available here. 

• Digital media video image data processing based on computer vision
• Mean-shift-based moving target tracking algorithm in complex industrial environments
• Pose estimation technology of electronic components based on point cloud segmentation algorithm
• Cloud computing based construction and empirical evaluation of the security risk early warning evaluation system of digital economy
• DAFPN: a lightweight multi-objective framework for small object detection in remote sensing images
• Anomaly detection and pattern recognition methods for high-dimensional data

Free Open Access article available: "Digital media video image data processing based on computer vision"

The following International Journal of Computer Applications in Technology article, "Digital media video image data processing based on computer vision", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Deep learning-based virtual screening system for drug molecules"

The following International Journal of Reasoning-based Intelligent Systems article, "Deep learning-based virtual screening system for drug molecules", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Research on modified Biaffine method for Chinese semantic role labelling"

The following International Journal of Reasoning-based Intelligent Systems article, "Research on modified Biaffine method for Chinese semantic role labelling", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Identification and long-term temporal sequential change analysis of urban VOCs high-value areas based on GIS and remote sensing"

The following International Journal of Reasoning-based Intelligent Systems article, "Identification and long-term temporal sequential change analysis of urban VOCs high-value areas based on GIS and remote sensing", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: Building on innovation and collaboration - "Innovating for performance: the role of lean construction and strategic partnerships in construction firms’"

A large-scale study published in the International Journal of Business Innovation and Research has looked at what factors lead to sustained gains in the construction industry. The team looked at 226 nationally registered firms and found that operational efficiency and collaboration, long seen as the sector’s primary remedies for underperformance, are insufficient on their own to lead to sustained gains. Instead, the decisive factor is whether companies fundamentally rethink how they create, deliver, and capture value.

The research used a statistical tool known as Partial Least Squares Structural Equation Modelling to analyse information from the 226 companies and to look for any relationships between various organisational factors. The approach allowed them to look at how lean construction practices and strategic partnerships affect performance. It was also possible to discern whether business model innovation acts as a bridge between these strategies and measurable outcomes such as profitability, operational efficiency and competitive position.

Lean construction is a systematic project management approach designed to eliminate waste and maximise value throughout a project’s lifecycle. Waste includes excess materials, redundant labour, delays, reworking, and poor coordination between contractors. Unlike simple cost-cutting, lean methods emphasise continuous improvement, integrated workflows, and delivering greater value to clients.

The study confirms that those companies that adopt lean practices do tend to perform better. However, the most significant improvements did not stem solely from streamlining their processes. Instead, lean thinking proved most powerful when it also prompted broader strategic change.

That broader shift is captured in the concept of business model innovation. A business model defines how a company creates value for customers, how it delivers that value, and how it generates revenue. Innovation in this context involves reconfiguring those core elements. For example, this might include moving from one-off, project-based contracts to long-term integrated service models, adopting digital coordination platforms, redesigning revenue structures, and embedding sustainability into what the company offers to clients.

Business model innovation was found to have a strong and direct positive effect on performance. More importantly, it amplified the impact of lean construction. When lean methods were embedded within a redesigned business model, performance gains were significantly greater than when lean was treated as a stand-alone efficiency tool. The research found that partnerships boosted performance only when it allowed companies to innovate in their business models. Access to shared knowledge, resources, and trust-based relationships yielded gains only if companies used them to reconfigure how they compete and deliver value.

Arifin, J., Prabowo, H., Hamsal, M. and Elidjen, E. (2026) ‘Innovating for performance: the role of lean construction and strategic partnerships in construction firms’, Int. J. Business Innovation and Research, Vol. 39, No. 6, pp.1–25.

Free Open Access article available: "Adaboost algorithm-based cost risk assessment for university laboratory construction"

The following International Journal of Reasoning-based Intelligent Systems article, "Adaboost algorithm-based cost risk assessment for university laboratory construction", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Region-specific multi-scale meteorological forecasting based on data assimilation and reinforcement learning"

The following International Journal of Reasoning-based Intelligent Systems article, "Region-specific multi-scale meteorological forecasting based on data assimilation and reinforcement learning", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access issue published by International Journal of Reasoning-based Intelligent Systems

The International Journal of Reasoning-based Intelligent Systems has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Region-specific multi-scale meteorological forecasting based on data assimilation and reinforcement learning
• Adaboost algorithm-based cost risk assessment for university laboratory construction
• Identification and long-term temporal sequential change analysis of urban VOCs high-value areas based on GIS and remote sensing
• Research on modified Biaffine method for Chinese semantic role labelling
• Deep learning-based virtual screening system for drug molecules

Free Open Access article available: "Building organisational strategic resilience through leadership, design thinking, and business modelling"

The following International Journal of Business and Emerging Markets article, "Building organisational strategic resilience through leadership, design thinking, and business modelling", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free sample articles newly available from International Journal of Postharvest Technology and Innovation

The following sample articles from the International Journal of Postharvest Technology and Innovation are now available here for free:

• Assessment of on-farm sorghum grain loss under farmers' traditional postharvest practices in the East Hararghe Lowlands of Ethiopia
• Preserving freshness and nutrients: the impact of passive and active modified atmosphere packaging on ready-to-eat orange (var. Navel) segments
• Effect of high yielding varieties technology in agriculture: evidence from rural India
• Storability of organic and conventional sorghum grains at constant relative humidity, and varied temperatures
• Post-harvest quality assessment of guava fruit (Psidium guajava. L.) CV. 'Gola' in response to different packaging materials

Free Open Access article available: "Spatial domain semantic collaborative recognition model for complex emotions in artistic images"

The following International Journal of Information and Communication Technology article, "Spatial domain semantic collaborative recognition model for complex emotions in artistic images", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Virtual reality and actual technology in psychology: intermediate research and analysis"

The following International Journal of Information and Communication Technology article, "Virtual reality and actual technology in psychology: intermediate research and analysis", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• AI-powered recommendation and task assignment mechanism for interactive vocational English teaching
• Construction of digital art knowledge graph based on deep recurrent neural network
• Real-time AI-regulated animation-user interaction system in virtual reality environments
• Virtual reality and actual technology in psychology: intermediate research and analysis
• Spatial domain semantic collaborative recognition model for complex emotions in artistic images

Free Open Access article available: "Real-time AI-regulated animation-user interaction system in virtual reality environments"

The following International Journal of Information and Communication Technology article, "Real-time AI-regulated animation-user interaction system in virtual reality environments", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: A sign of the times - "Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication"

In the age of global branding, instantaneous communication, and generative AI images, the symbols that we see in our daily lives circulate at an unprecedented rate. A study in the International Journal of Information and Communication Technology argues that if the symbols we share are to foster understanding rather than confusion, designers must treat them as carriers of cultural meaning, not mere decoration.

The team has used communication science, design theory, and semiotics, the study of signs and how they create meaning, to propose a systematic, evidence-based framework to identify, refine and test traditional cultural symbols. Their concept echoes an insight by Ferdinand de Saussure that suggests that a sign is not simply a form but a form bound to shared content. A flower or mythical creature, in this view, evokes memories, values and beliefs as much as it depicts the object it illustrates.

As digital platforms accelerate the circulation and mutation of images, we experience the fragmentation of symbols and signs. Moreover, in the age of generative artificial intelligence, almost all content is being cannibalised and regurgitated as derivative works, visual motifs are thus losing their inherited symbolism or, at best, being misappropriated or diluted. In the face of these changes, the researchers suggest that semiotics has now become a necessary part of creativity and perhaps the only hope of our conserving our symbols and their significance.

In their paper, the researchers discuss a five-step process beginning with systematic data collection and identification of culturally significant symbols. They followed this with a cross-cultural analysis, design refinement, and empirical testing. Statistical analysis together with expert review allowed them to look at specific symbols, such as the blue-and-white porcelain motifs featuring the lotus, peony, and plum blossom. As a good example of symbolic art, these patterns scored highly for clarity, adaptability, and perceived authenticity. The lotus is widely associated in East Asia with purity and renewal, the peony with prosperity and honour, and the plum blossom with resilience in adversity. Their visual simplicity combined with layered symbolism appears to aid translation into contemporary branding, the analysis found. More complex imagery failed to ignite the imagination of general audiences, although it was recognised as culturally significant by the experts.

Quantitative evaluation thus shows the different priorities associated with authenticity and meaning, challenging assumptions of universal interpretation for even familiar symbols that might be used in marketing and branding.

Li, A. (2026) ‘Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication’, Int. J. Information and Communication Technology, Vol. 27, No. 9, pp.18–38.

Free Open Access article available: "Construction of digital art knowledge graph based on deep recurrent neural network"

The following International Journal of Information and Communication Technology article, "Construction of digital art knowledge graph based on deep recurrent neural network", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "AI-powered recommendation and task assignment mechanism for interactive vocational English teaching"

The following International Journal of Information and Communication Technology article, "AI-powered recommendation and task assignment mechanism for interactive vocational English teaching", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free sample articles newly available from International Journal of Structural Engineering

The following sample articles from the International Journal of Structural Engineering are now available here for free:

• Composition and performance of chopped carbon fibre-reinforced self-consolidating concrete: a review
• Multi-criteria analysis of impact strength in concrete with PET bottle waste additives
• Study of torsion and combined shear stresses in the central core of tall twisting buildings
• Theoretical and experimental analysis on impact resistance of metal rubber vibration isolator
• Study of the influence of water saturation on main mechanical properties of laterite dimension stones from Burkina Faso

Free Open Access article available: "Development of an AI-assisted spoken language assessment system for Japanese language teaching"

The following International Journal of Information and Communication Technology article, "Development of an AI-assisted spoken language assessment system for Japanese language teaching", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Innovative practice of AI-driven intelligent assessment system in university course teaching reform"

The following International Journal of Information and Communication Technology article, "Innovative practice of AI-driven intelligent assessment system in university course teaching reform", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Construction of mental health analysis model based on multi-modal feature learning and fusion network
• Evaluation of teaching effectiveness in data analysis courses using a behavioural big data model
• Federated learning-enabled personalised delivery and student privacy protection in universities
• Innovative practice of AI-driven intelligent assessment system in university course teaching reform
• Development of an AI-assisted spoken language assessment system for Japanese language teaching

Free Open Access article available: "Federated learning-enabled personalised delivery and student privacy protection in universities"

The following International Journal of Information and Communication Technology article, "Federated learning-enabled personalised delivery and student privacy protection in universities", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: AI decodes mental health - "A smart intelligent Internet of Things framework for predicting mental health"

Mental health problems are among the most pressing of public health challenges, affecting millions across different age groups and societies. Depression, anxiety, and stress-related conditions rank among the leading causes of diminished quality of life worldwide. They exact a heavy social toll and economic cost. Yet diagnosis still relies largely on self-reported symptoms and intermittent clinical interviews, which means diagnosis is vulnerable to memory lapse, stigma, and limited access to trained professionals.

Research in the International Journal of Networking and Virtual Organisations discusses an artificial intelligence (AI) diagnostic system that can spot early signs of various mental health conditions by analysing how people write online. The model, known as a Fossa-based Graph Neural Network (FbGNN), examines language patterns in text drawn from social media platforms and online forums. Instead of relying solely on questionnaires, it studies sentiment-driven textual information, the emotional tone, word choices and behavioural cues embedded in a person’s online writing.

The researchers explain that their system combines two advanced computational techniques. The first is the Fossa optimisation, a feature-selection method based on search strategies seen in nature. In machine learning, features are identifiable pieces of information, specific words, phrases or emotional markers. By applying Fossa optimisation, the system can filter out any irrelevant data from those features and identify pertinent indicators of mental distress.

The second component is a Graph Neural Network, a GNN. A GNN analyses relationships by representing information as a network of nodes and connections. Here, nodes correspond to features, and the connections are the interactions between them. This allows the model to detect complex patterns, such as recurring combinations of emotional expression and behavioural signals.

By training the system to classify text based on categories such as depression, anxiety, stress, bipolar disorder, suicidal ideation, and personality disorders, the team was able to then test its accuracy against known sample data. It was able to predict a person’s mental health status with an accuracy of almost 99 per cent in the trials. Such accuracy would be useful in screening for mental health problems among a cohort of users, such as students, employees, or any other group. It would allow healthcare follow-ups to be directed at those most likely to have problems that might be addressed and would only miss one in a hundred. Further refinements of the system could bring that accuracy closer to 100 per cent.

Shobitha, G.S., Kataksham, V.S., Nagalaxmi, T., Spandana, V., Sreelatha, G. and Radha, V. (2025) ‘A smart intelligent Internet of Things framework for predicting mental health’, Int. J. Networking and Virtual Organisations, Vol. 33, No. 3, pp.251–278.

Free Open Access article available: "Evaluation of teaching effectiveness in data analysis courses using a behavioural big data model"

The following International Journal of Information and Communication Technology article, "Evaluation of teaching effectiveness in data analysis courses using a behavioural big data model", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Construction of mental health analysis model based on multi-modal feature learning and fusion network"

The following International Journal of Information and Communication Technology article, "Construction of mental health analysis model based on multi-modal feature learning and fusion network", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Generative music composition teaching system based on mobile interaction"

The following International Journal of Information and Communication Technology article, "Generative music composition teaching system based on mobile interaction", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Temporal convolutional networks with language models for decoding music preferences in mental health profiling"

The following International Journal of Information and Communication Technology article, "Temporal convolutional networks with language models for decoding music preferences in mental health profiling", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Application of an AI-driven visual aesthetic scoring system for style calibration in art works"

The following International Journal of Information and Communication Technology article, "Application of an AI-driven visual aesthetic scoring system for style calibration in art works", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication"

The following International Journal of Information and Communication Technology article, "Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "The prediction model of higher vocational students' classroom participation based on the fusion of deep learning and support vector machine"

The following International Journal of Information and Communication Technology article, "The prediction model of higher vocational students' classroom participation based on the fusion of deep learning and support vector machine", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• The prediction model of higher vocational students' classroom participation based on the fusion of deep learning and support vector machine
• Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication
• Application of an AI-driven visual aesthetic scoring system for style calibration in art works
• Temporal convolutional networks with language models for decoding music preferences in mental health profiling
• Generative music composition teaching system based on mobile interaction

Free sample articles newly available from International Journal of Security and Networks

The following sample articles from the International Journal of Security and Networks are now available here for free:

• Pursuing multi-agent Nash equilibria amidst DoS attacks with stochastic perturbations
• Pre-coding techniques for enhanced codebooks on electricity information collection networks
• A neural network for disease recognition of radiological images of pneumonia
• Enhanced phishing URL identification using an integrated attention-based LSTM-CNN with hybrid features
• A semi-grant-free scheme based on electricity information collection networks

Free Open Access article available: "Bibliometric insights into green accounting research: analysing trends, impact, and theoretical foundations"

The following International Journal of Managerial and Financial Accounting article, "Bibliometric insights into green accounting research: analysing trends, impact, and theoretical foundations", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "An adaptive recognition of abnormal behaviour in deep excavation support construction site of high-rise buildings"

The following International Journal of Critical Infrastructures article, "An adaptive recognition of abnormal behaviour in deep excavation support construction site of high-rise buildings", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Prof. Athanasios Spyridakos appointed as new Editor in Chief of International Journal of Decision Support Systems

Prof. Athanasios Spyridakos from University of West Attica in Greece has been appointed to take over editorship of the International Journal of Decision Support Systems. The departing Editor in Chief, Prof. Nikolaos Matsatsinis, will continue to support the journal in the role of Consulting Editor.

Free Open Access article available: "How lighthouse companies are pioneering Indonesia's Industry 4.0 and 5.0 revolution? A soft system methodology approach"

The following International Journal of Services and Operations Management article, "How lighthouse companies are pioneering Indonesia's Industry 4.0 and 5.0 revolution? A soft system methodology approach", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access article available: "Innovating for performance: the role of lean construction and strategic partnerships in construction firms"

The following International Journal of Business Innovation and Research article, "Innovating for performance: the role of lean construction and strategic partnerships in construction firms", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: Keep your hands of my stack Jack, and Jill - "Minimising exposure to cyber frauds in digital finance: perspectives from technology threat avoidance theory"

Digital payments are a routine part of daily life for many people. As such, the risk of online fraud is rising alongside this convenience. Identity theft, email compromise, scams, and misleading investment schemes all exploit technological weaknesses and often user naivety and can lead to big financial losses.

Research in the American Journal of Finance and Accounting has looked at technological threat avoidance theory (TTAT), a framework used to understand how individuals respond to technology-related risks. The study sheds new light on what motivates users to protect themselves from online financial threats, if they do at all. It considers user attitudes towards fraud and the perception of potential financial loss with the aim of identifying the specific influences that lead to a user taking protective action.

The team surveyed users of online payment platforms and found that rather than an abstract fear of fraud, the decisive factor in whether or not people took preventative measures was simply the perceived financial loss. This finding suggests that awareness campaigns focused on general threats may be less effective than approaches that point out the direct financial consequences of online fraud.

Online fraud costs us roughly US$1 trillion per annum, and it is likely that figure is rising year on year. There are millions of reported cases and probably many more that are never reported. The losses that people bear when a victim of online fraud erodes overall trust in the digital systems on which we rely. Moreover, widespread, organised fraud can disrupt financial infrastructure, threatening broader economic stability and making it almost impossible for regulators to maintain oversight and control.

Facing such problems, the digital economy needs technological innovation in payment systems to incorporate effective strategies to influence user behaviour. Such strategies need to make it difficult for users to compromise themselves through technological naivety. Policymakers, platform developers, and financial educators also need to help in the design of interventions that align perceived risk with actual behaviour and so strengthen the individual against threats as well as help maintain trust in digital financial systems.

Peswani, R. and Vijay, P. (2026) ‘Minimising exposure to cyber frauds in digital finance: perspectives from technology threat avoidance theory’, American J. Finance and Accounting, Vol. 9, No. 1, pp.76–98.

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