The Tobacco Cutworm, or Cotton Cutworm, is a moth species native to Asia, it is considered a serious agricultural pest. The larvae of Spodoptera litura, to give the species its scientific binomial, are responsible for significant damage to economically vital crops such as vegetables, grains, and cotton, particularly. It can adapt easily to different environments and has developed resistance to conventional pesticides. These and other factors have made it a persistent and costly problem for farmers worldwide.

Research in the International Journal of Agriculture Innovation, Technology and Globalisation introduces a new system based on the Internet of Things (IoT) that might be able to address this agricultural threat by improving monitoring and allowing more targeted response to the species.

Jheng-Hong Hu, Ming-Yao Chiang, Jenn-Kuo Tsai, and Chiling Chen of the Ministry of Agriculture in Taichung City and Chau-Chin Lin of the Society of Subtropical Ecology in Taipei City, have suggested that by using an IoT system that brings together infrared automatic counting devices, low-power LoRa (Long Range) wireless data transmission and mobile platforms, it should be possible to monitor Tobacco Cutworm infestations in real time. Such an automated approach would provide timely alerts, allowing farmers to act quickly and prevent widespread crop damage.

The team has conducted field trials in partnership with the Taiwan Agricultural Research Institute and local farmers and demonstrated the system's effectiveness when compared with manual monitoring as well as its adaptability for practical use. Fundamentally, the approach allows for a more timely response that avoids the use of blanket pesticide spraying and uses more focused treatment with effective materials. It will be effective in a wide range of agricultural settings, from small farms to large commercial enterprises.

Hu, J-H., Chiang, M-Y., Tsai, J-K., Lin, C-C. and Chen, C. (2024) 'Internet of things technology applied in monitoring and warning of Spodoptera litura Fabricius (tobacco cutworm) occurrences', Int. J. Agriculture Innovation, Technology and Globalisation, Vol. 4, No. 3, pp.257–272.
DOI: 10.1504/IJAITG.2024.143907

The Anthropocene is a relatively recent term, coined to define the epoch in which human activity is increasingly dictating environmental and biological change on earth as previous periods driven by natural occurrences did in pre-history; during the Pleistocene, for instance. Technically, the current epoch is the Holocene, but human activity has altered the world so significantly, that, with our usual species-centric perspective, we have shunned hubris and given the current epoch this new name in a fit of unaccustomed self-awareness.

Writing in the Interdisciplinary Environmental Review, Miti Mallick of Bankura University in Purandarpur, West Bengal, India, discusses how the concept of the Anthropocene plays out across the economic landscape too. While the Anthropocene has brought major improvements in living conditions for the wealthier nations, it is becoming ever clearer that the challenges of climate change and environmental degradation will demand more drastic measures from these same nations in terms of sustaining their own living standards and improving those of the majority that live in poverty.

At the heart of any such discourse is the concept of capitalism. This is the dominant global economic force that organizes production, labour, and the distribution of wealth. Capitalism is driven by the principles of private ownership and the pursuit of profit. It has been instrumental in driving what we consider economic growth but has also contributed to social inequality, environmental destruction, and a growing sense of disconnection between the economy and the planet's ecological limits.

Capitalism functions in liberal market economies, which emphasize decentralized markets, as well as in state-coordinated models, where government plays a more prominent role.

The consequences of capitalism have become increasingly difficult to ignore as historically the maximization of profits has been at the long-term cost of environmental and social considerations, the research argues. The rise of oligarchic capitalism, which benefits a select few and see multibillionaires in powerful positions within society, and the focus on technological innovation, have further worsened the social and environmental toll.

In the context of the Anthropocene, this economic model is coming under increasing scrutiny. It seems that capitalism as we know it may be at a pivot point. Given that scholars, activists, and policymakers are beginning to challenge the assumption that economic growth and ecological sustainability are inherently incompatible, there is a need for a new capitalism. One that redefines value in terms that extend beyond profit margins. This reimagined model of capitalism might centre on the well-being of individuals, communities, and the environment. Investments would no longer solely be evaluated on their financial returns but also on their potential to reduce inequality and promote sustainable development.

This putatively idyllic world may not be to everyone's taste especially some of those multibillionaires. While entrepreneurs, investors, and policymakers are increasingly being called to task, there is not necessarily the political will nor the motivation for egocentric oligarchs to imagine such a world. Plus ça change, plus c'est la même chose.

Mallick, M. (2025) 'How capitalism could be the new market in the Anthropocene era: a review', Interdisciplinary Environmental Review, Vol. 24, No. 1, pp.1–15.
DOI: 10.1504/IER.2025.143620

Research in the International Journal of Computational Vision and Robotics could lead to faster and more accurate robots for high-precision tasks in factories.

Delta robots are parallel computer-controlled machines that have a fixed base and a set of three arms connected to a platform. They are typically used for pick-and-place applications in industries like packaging, assembly, electronics fabrication, pharmaceutical production, and food processing. They can work very quickly, making precise movements for even delicate tasks. Unlike serial robots, the parallel kinematics of delta robots means arms and actuators work together to move the platform.

Riyadh A. Sarhan, Zaid H. Rashid, and Mohammed S. Hassan of the Technical University in Babylon, Iraq, are working to make delta robots even more reliable and have developed a novel control system that boosts their ability to make swift, precise movements. In their paper, they integrate fuzzy logic with an adaptive neuro-fuzzy inference system (ANFIS). This hybrid technology combines the best aspects of artificial neural networks and fuzzy logic to manage the complex kinematics, the mathematical description of the robot's movements, in order to improve performance significantly.

The improvement in control of precision delta robots should allow manufacturers to increase speed, quality, and overall efficiency on their production lines. Moreover, there is the potential in this hybrid control approach to allow delta robots to be more responsive to and to compensate for changes in their environment.

As industries continue to look for ways to improve automation, the research offers step towards faster, more accurate robotic systems.

Sarhan, R.A., Rashid, Z.H. and Hassan, M.S. (2025) 'Motion control of 3-DoF delta robot using adaptive neuro fuzzy inference system', Int. J. Computational Vision and Robotics, Vol. 15, No. 7, pp.1–16.
DOI: 10.1504/IJCVR.2025.143990

Digital therapeutics allow healthcare workers and patients use software is in the management and treatment of disease. The idea spans various healthcare areas, including mental health, chronic disease management, neurological disorders, addiction treatment, and rehabilitation.

Software-based interventions often offer personalized therapies through apps or digital platforms, using techniques like cognitive behavioural therapy, symptom tracking, and virtual exercises to help manage conditions such as mental health problems, diabetes, substance use, and recovery from physical injuries.

Research in the International Journal of Technology Transfer and Commercialisation, suggests that digital therapeutics have changed the healthcare landscape Of course, the rapid commercialisation of these products has continued apace but equally important is the challenge of the internationalisation of such systems allowing them to be expanded into foreign markets. Amy Lee and Grigorij Ljubownikow of The University of Auckland, New Zealand, have highlighted how these processes commercialisation and internationalisation, traditionally seen as separate, are deeply interconnected for companies that start out as born-digital enterprises.

These companies all operate in highly regulated environments. What sets them apart from conventional healthcare companies is their use of wholly digital solutions. The shift from conventional to digital was happening steadily up to around 2020 but was accelerated enormously by the pandemic and the urgent need for remote, or virtual, care.

The researchers point out that while traditional companies might commercialise their product domestically first and then branch out internationally, digital therapeutics firms have had to rethink this linear path because in the digital world global is essentially just as immediate and local a market as the domestic one. The research reveals that for these companies, international expansion is not a separate concern to be tackled later, but has to be a key factor in the broader strategy from the outset.

The research emphasises how collaboration, networking, and continuous learning within these companies can help them address the additional challenges of regulatory and reimbursement hurdles across international markets. While global may be perceived as the new local, there are still enormous differences in the socio-political and economic environments between countries. Navigating the diverse institutional and international frameworks requires not only innovation in product development but also flexibility in business models. Lee and Ljubownikow's findings thus offer insights into how firms can refine their strategies for global growth.

Lee, A. and Ljubownikow, G. (2024) 'The road to commercialisation: expanding digital therapeutics across international markets', Int. J. Technology Transfer and Commercialisation, Vol. 21, No. 5, pp.1–25.
DOI: 10.1504/IJTTC.2024.143991

Research in the International Journal of Computational Science and Engineering has developed a new approach to addressing ideological polarisation on social media. The problem of users generally encountering only like-minded perspectives and so reinforcing their own beliefs even in the face of conflicting evidence is highly divisive.

The phenomenon, known as the "echo chamber" effect or referred to as "filter bubbles", arises in part because the algorithms driving the position of content in one's social media apps. This, in turn, is driven largely by the need to keep users active and engaged on a particular platform. Too many contrary updates might drive users away, and that will ultimately reflect negatively on the advertising and other revenue streams for the companies that operate the platforms. By contrast, an echo chamber effect that reinforces their viewpoints will, for many people, be more attractive than one that doesn't.

Zaka Ul Mustafa and Muhammad Amir of the International Islamic University Islamabad, Manal Mustafa of Zaman Technologies Pvt Limited, Pakistan, and Muhammad Adnan Anwar of Ulisboa, Portugal, suggest that the social media platforms could benefit from the use of genetic algorithms (GAs). Such computational techniques inspired by the principles of evolutionary natural selection could reduce polarisation and the echo chamber effect but still respect the organic nature of online interactions, and so keep users engaged without being so divisive.

The team explains that current strategies to counter polarisation often involve connecting disparate groups (edge addition) or altering expressed views (opinion flipping). These methods are not only static, but also raise ethical concerns about the platforms interfering with user autonomy. A GA-based approach instead identifies influential nodes in the online social network and only subtly adjusts their highlighted connections to reduce polarisation. The critical contribution of the work lies in identifying network elements that disproportionately contribute to ideological divides, and then encouraging more diversity of interaction with minimal disruption to the organic nature of social media.

The team has tested their approach on real-world datasets that focus on polarised US political discourse. The datasets have communities clustered around distinct ideological groups, and so can provide a useful test for how well the method precludes polarisation and division. The results showed that the GA approach could foster connections between disparate groups, and this led to a measurable decrease in polarisation without fundamentally altering the network's overall structure.

Ul Mustafa, Z., Amir, M., Mustafa, M. and Anwar, M.A. (2025) 'Harmony amidst division: leveraging genetic algorithms to counteract polarisation in online platforms', Int. J. Computational Science and Engineering, Vol. 28, No. 7, pp.1–17.
DOI: 10.1504/IJCSE.2025.143956

As international trade and global security become more reliant on marine resources, the demand for advanced maritime surveillance and port management has never been greater. One of the big challenges in this area is the detection of ships in complex environments, a task that has traditionally relied on manual techniques. These methods, while functional, are often inadequate in dynamic, cluttered marine conditions, where varying sea states, weather patterns, and ship sizes can easily confound detection efforts.

Research in the International Journal of Information and Communication Technology has introduced a new approach to ship target detection. The research combines several cutting-edge deep learning techniques, "You Only Look Once" version 4 (YOLOv4), the Convolutional Block Attention Module (CBAM), and the transformer mechanism. The team of Weiping Zhou, Shuai Huang, and Qinjun Luo of Jiangxi Polytechnic University in JiuJiang, and Lisha Yu of Shanghai Cric information Technology Co. Ltd. In Shanghai, China, have combined these into a single algorithmic program that is both accurate and reliable in the identification of vessels in challenging conditions.

Modern, fast deep-learning models such as YOLOv4 out-class traditional methods by cutting out the multiple steps needed to process an image. YOLOv4 can scan and classify objects in a single pass, making it ideal for real-time surveillance over large expanses.

CBAM is a feature-enhancing technique that works by focusing the model's attention on the most important elements within a given image. This allows the hybrid system to identify ships even if they are surrounded by other vessels, docks, flotsam, and even rough seas. Conventional techniques often failed in distinguishing vessel from background in such images. The transformer mechanism is a powerful system that further improves the capacity of the model to process features at different levels, ensuring that important detail are not missed.

The team explains that this combined effort allows their system to outperform earlier models, particularly in the detection of smaller vessels and ships in complex maritime environments. They tested the approach on the Ship Sea Detection Dataset (SSDD), which includes remote sensing images of various marine conditions. Their results demonstrated superior speed and precision, especially when identifying minor or obscured targets. Given the critical importance of timely and accurate detection in maritime security, the implications of this improvement are significant.

Zhou, W., Huang, S., Luo, Q. and Yu, L. (2024) 'Research on a ship target detection method in remote sensing images at sea', Int. J. Information and Communication Technology, Vol. 25, No. 12, pp.29–45.
DOI: 10.1504/IJICT.2024.143631

Architects and industrial designers play an important part in what we might term the circular economy (CE). This is a sustainability framework that aims to minimize waste by reusing and regenerating resources. Research in the Journal of Design Research has surveyed practitioners in The Netherlands and Sweden to see whether there is growing enthusiasm for circular design strategies and what significant challenges remain to be overcome.

Giliam Dokter, Jonathan Edgardo Cohen, Sofie Hagejärd, Oskar Rexfelt, and Liane Thuvander of Chalmers University of Technology, Gothenburg, Sweden, surveyed 114 professionals. They found that almost two-thirds of them engaged with CE-related projects, while a similar proportion reported that there were shifts within their organizations to support such initiatives.

The team reports that techniques such as "design for disassembly", the crafting products or buildings for easy dismantling and reuse, are all part of this move towards greater sustainability. They point out that circular business models, emphasize regeneration over consumption and the associated principles are commonly applied in CE-focused projects undertaken by the survey participants.

It was found that architects tend to prioritize material reuse at the building level, while industrial designers have more of a focus on making it possible to disassemble products. Both groups are advancing creative solutions that reflect the principles of CE, however, even if their approaches are different and the substantial barriers they face are apparent.

The survey revealed that a lack of reliable knowledge about materials and the tools needed to evaluate environmental and economic impacts during design is one of the biggest barriers to adopting the principles of the CE in both architecture and industrial design. The research points out that choosing sustainable materials requires precise data about the lifecycle of these materials and their potential reuse. However, such information is often scarce or fragmented.

In addition to this dearth of relevant information there are also factors such as regulatory and market challenges that are beyond the immediate control of those working to CE principles and such barriers might hamper their efforts towards sustainability regardless of their efforts and focus.

Dokter, G., Cohen, J.E., Hagejärd, S., Rexfelt, O. and Thuvander, L. (2024) 'Mapping the practice of circular design: a survey study with industrial designers and architects in the Netherlands and Sweden', J. Design Research, Vol. 21, Nos. 3/4, pp.177–209.
DOI: 10.1504/JDR.2024.143685

Online shopping in China, particularly among young people, is a vast enterprise. Online retail sales amounted to about 16 trillion yuan in 2024, approximately 2 trillion US dollars. Indeed, online shopping has transformed the way youngsters approach buying everything from clothing to gadgets, especially in the post-pandemic era where old shopping habits have been abandoned by many people.

Much of the research into online consumer behaviour has focused on the after-sales experience. Now, a study in the International Journal of Data Science, turns the research lens to look more closely at the pre-purchase stage. In so doing, Nanhua Duan and Jingwen Zhang of Northwestern Polytechnical University in Shaanxi, China, hoped to understand how young Chinese consumers perceive value before they hit the all-important "buy now" button when shopping online.

The team explains that the concept of Customer Perceived Value (CPV) is at the core of their research. CPV refers to the overall worth a consumer assigns to a product based on the benefits they expect in relation to the cost. For experiential products, this perception is even more complex because the product's value is influenced by a variety of factors that may not be immediately obvious. The same is true for clothing when one cannot touch or try on an item before making a buying decision.

To home in on the factors involved, the team has proposed a new framework, which identifies six key dimensions that influence CPV when young Chinese consumers shop online for clothing and similar items. These are: word-of-mouth value, service value, aesthetic value, cost value, quality value, and brand value. Each of these, they found, plays a critical role in shaping the consumer's expectations prior to purchase.

The findings are particularly relevant to China's booming apparel market, which has seen rapid growth among digitally consumers. The research emphasizes that young buyers are not just concerned with the price tag or material quality alone. Indeed, they also consider factors like the reputation of the brand, the service experience, and how well a product aligns with their personal style or social status. This is where the online shopping environment differs from traditional brick-and-mortar shops, where the tactile nature of the shopping experience provides more immediate and obvious feedback and the potential for impulse buys or purchases prompted by an enthusiastic sales assistant.

For retailers and brands looking to tap into the ever-growing online market, understanding the six dimensions of CPV could offer insight into how to develop a more compelling online experience. It is, the research suggests, no longer sufficient to highlight the physical attributes of a product, companies must also now showcase the brand and its reputation as well as the quality of service.

In practical terms, the findings could mean that companies could benefit from focusing on positive reviews, clear and appealing product images, and smooth, customer-friendly websites. There might even be potential for developing innovative ways to display the products that might involve interactive elements, such as changing viewing angles, product colours and styles, and perhaps even offering options to see different models wearing the items. There is huge potential for the marketers that learn how to persuade people to click that "buy now" button.

Duan, N. and Zhang, J. (2025) 'The development of a product-layer perceived value scale for the online experience products of young Chinese consumers: take online apparel as an example', Int. J. Data Science, Vol. 10, No. 5, pp.1–21.
DOI: 10.1504/IJDS.2025.143886

Many work-related activities come with a risk of musculoskeletal problems, not least working at a desk. They are perhaps more commonly seen in the industrial or manual labour settings where repetitive movements, awkward postures, considerable muscular force and vibration, and lifting heavy objects are problematic.

A new study in the International Journal of Human Factors and Ergonomics introduces a tool that could be used by employers to assess the risk of such problems to their workers. The tool, the Ergonomist Assistant for Evaluation (ERAIVA), could streamline the process of identifying risky postures, which might lead to chronic pain and issues such as repetitive strain injury over time.

Where workers perform tasks that involve awkward body positions, repetitive movements, and heavy lifting there is an increased risk of debilitating conditions such as back pain and injury, carpal tunnel syndrome, and tendinitis. Previously, assessing such risks was done only on an ad hoc basis and not necessarily systematically, to the detriment of workers moreover the assessment itself was labour and time intensive, requiring experts to visually monitor workers or examine video footage of their activities.

Veeresh Elango, Lars Hanson, and Anna Syberfeldt of the University of Skövde, Staffan Hedelin and Johan Sandblad of Scania CV AB in Södertälje, and Mikael Forsman of the KTH Royal Institute of Technology in Stockholm, Sweden, explain that ERAIVA addresses these shortcomings by offering an automated way to analyse and annotate video recordings of industrial tasks. The technology could avoid human error in assessing work tasks and the posture and activity of individuals carrying out those tasks. Such a system could allow posture and other problems to be corrected and reduce the risk of musculoskeletal problems.

The system is easy to use and so reduces the need for expert assessment and remediation. Engineers and operators, as well as risk assessors, can all work together with the results it provides to identify and mitigate risks in the workplace.

Elango, V., Hedelin, S., Hanson, L., Sandblad, J., Syberfeldt, A. and Forsman, M. (2024) 'Evaluating ERAIVA – a software for video-based awkward posture identification', Int. J. Human Factors and Ergonomics, Vol. 11, No. 6, pp.1–16.
DOI: 10.1504/IJHFE.2024.143861

Online education is now ubiquitous and in recent years has changed fundamentally the way many people learn. Various platforms have opened up access to knowledge for millions of people. However, there remains an ongoing challenge: how to accurately measure and enhance the quality of teaching in these digital spaces.

Conventional evaluation tools focus on test scores and student satisfaction surveys. However, these often overlook the students' emotional experience of the course. Research in the International Journal of Information and Communication Technology, proposes a new solution that could change the way online teaching is assessed, getting closer to the heart of emotional matters.

The new work by Ruiting Bai of Puyang Medical College in Puyang, China, introduces the EduSent-Dig model, which can carry out advanced sentiment analysis and use big data techniques to evaluate teaching quality. By analysing the student emotional response given in their course feedback, the model can extract the nuances of online teaching that work most effectively. Rather than flagging the feedback as simply "positive" or "negative", EduSent-Dig identifies specific emotional undercurrents such as joy, frustration, or surprise. It does so by using analytical tools such as Bi-LSTM, a deep learning framework, and Word2Vec, which converts words into numerical representations for computational analysis.

The study reveals that emotional experiences are not just peripheral to learning; they are central to it. How students feel about their coursework directly affects their motivation, engagement, and whether they complete a course. As such, the new model in identifying and interpreting sentiment accurately, can provide educators and course designers with insights into how to improve their educational offering. Moreover, real-time sentiment analysis undertaken as a course progresses might even allow teachers to fine tune their teaching dynamically, tailoring lessons to student needs on an ad hoc basis. This could transform the way courses are designed and how they are developed as the students progress through them. All in, the insights could foster a more empathetic and effective learning environment.

Bai, R. (2024) 'Big data-driven deep mining of online teaching assessment data under affective factor conditions', Int. J. Information and Communication Technology, Vol. 25, No. 11, pp.35–51.
DOI: 10.1504/IJICT.2024.143412

We are pleased to announce that the International Journal of Data Mining and Bioinformatics is now an Open Access-only journal. All accepted articles submitted from 23rd January 2025 onwards will be Open Access, and will require an article processing charge of US $1600.

Prof. Renato Pereira from the University of Lisbon in Portugal has been appointed to take over editorship of the International Journal of Intellectual Property Management.

Prof. Junfeng Xia from Anhui University in China has been appointed to take over editorship of the International Journal of Computational Biology and Drug Design.

Prof. Andry Sedelnikov from Samara National Research University in Russia has been appointed to take over editorship of the International Journal of Mathematical Modelling and Numerical Optimisation.