Evaluating the Impact of Lighting Conditions on Workers' Safety and Health in Industrial Settings

open access articleLighting is a key element of design that plays an important role in affecting workers’ health and safety in industrial workspaces. Given the scarcity of scientific studies addressing visual environments in relation to workers health in industrial buildings, this field study was conducted to explore workers' responses to multiple lighting scenarios inside production halls on their occupational health and safety in six factories in Sadat City, Egypt. Self-assessments of 456 factory workers during day and night shifts were collected and correlated to light measurements collected at the factories. The statistical analysis of data revealed a significant reduction in workers reporting eye strain, alleviating headaches, and enhancing the ability to concentrate under daylight conditions compared to mixed and/or artificial lighting conditions. Moreover, it was found that lighting levels lower than 140 lux led to visual fatigue(p=0.03), headaches (p=0.014), drowsiness (p=0.004), and rapid loss of concentration (p=0.149) among workers. Poor lighting was shown to increase the likelihood of making occupational errors. Despite the health benefits of natural light compared to artificial lighting, glare from sunlight can sometimes cause headaches. This study emphasizes the importance of improving lighting quality in production halls within industrial environments, as it is a crucial factor in maintaining the health and safety of workers and enhancing professional performance

Good Enough Ethics by Design: AI and Alternative Digital Realities

Good Enough Ethics by Design: AI and Alternative Digital Realities is based on research from the EU-funded SHARESPACE project, the book shows how GEE can be applied across emerging technologies and calls for an iterative, inclusive ethics culture - one that embeds reflection into innovation without stifling it.Good Enough Ethics explores how society can ethically navigate the accelerating complexity of technological innovation. Tracing developments from cave paintings to the industrial age to AI and the Metaverse, the book explores reactive approaches - such as GDPR and the Online Safety Act - and examines proactive strategies like Ethics by Design, which integrates ethics throughout product development. Yet such frameworks often prove too rigid or burdensome in practice. Inspired by Donald Winnicott’s idea of good enough parenting, the authors propose Good Enough Ethics (GEE) - a pragmatic, flexible model that balances ethical responsibility with real-world constraints. Rather than aiming for perfection, GEE emphasises empowering technologists to act ethically without paralysis. Based on research from the EU-funded SHARESPACE project, the book shows how GEE can be applied across emerging technologies and calls for an iterative, inclusive ethics culture - one that embeds reflection into innovation without stifling it

A Novel TLS-Based Fingerprinting Approach That Combines Feature Expansion and Similarity Mapping

open access articleMalicious domains are part of the landscape of the internet but are becoming more prevalent and more dangerous both to companies and to individuals. They can be hosted on various technologies and serve an array of content, including malware, command and control and complex phishing sites that are designed to deceive and expose. Tracking, blocking and detecting such domains is complex, and very often it involves complex allowlist or denylist management or SIEM integration with open-source TLS fingerprinting techniques. Many fingerprinting techniques, such as JARM and JA3, are used by threat hunters to determine domain classification, but with the increase in TLS similarity, particularly in CDNs, they are becoming less useful. The aim of this paper was to adapt and evolve open-source TLS fingerprinting techniques with increased features to enhance granularity and to produce a similarity-mapping system that would enable the tracking and detection of previously unknown malicious domains. This was achieved by enriching TLS fingerprints with HTTP header data and producing a fine-grain similarity visualisation that represented high-dimensional data using MinHash and Locality-Sensitive Hashing. Influence was taken from the chemistry domain, where the problem of high-dimensional similarity in chemical fingerprints is often encountered. An enriched fingerprint was produced, which was then visualised across three separate datasets. The results were analysed and evaluated, with 67 previously unknown malicious domains being detected based on their similarity to known malicious domains and nothing else. The similarity-mapping technique produced demonstrates definite promise in the arena of early detection of malware and phishing domains

A contribution-driven weighted grey relational analysis model and its application in identifying the drivers of carbon emissions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A number of Grey Relational Analysis (GRA) models have been developed, but their practical application could yields inconsistent or contradictory results in some situations, complicating decision-making. To address this issue, the framework for determining the Core Model Confidence Set in Grey Relational Analysis (Core GRA-MCS) is presented, and a contribution-driven weighted GRA (CDWGRA) model is proposed. First, the concept of the stability coefficient of GRA models is introduced based on the Kendall coefficient (KC). This stability coefficient quantifies the consistency of the set in system analysis. Next, a framework for determining the Core GRA-MCS is established. This framework uses the stability coefficient, Borda count, and Deng's grey relational degree to identify a subset of GRA models that reliably represent the system's characteristics. For the models in Core GRA-MCS, a weighted aggregation is performed using Deng's grey relational degree as the weight, forming the CDWGRA model. The model provides a unified approach to synthesizing results from multiple GRA models. Finally, the proposed model is used to identify the drivers of carbon emissions in the Yellow River Basin, China. The analysis identifies six key driving factors: Primary Industry, Tertiary Industry, Urbanization Rate, Urban Disposable Income, Natural Gas consumption, and Primary Electricity and Other Energy. These factors highlight the influence of economic activity, energy structure, industrial structure, and social development on regional carbon emissions. The comparative analysis and stability analysis show that the CDWGRA model improves the consistency and reliability of GRA-based analysis, confirming its validity and utility in studying complex systems

Transformative trends: commercial platforms revolutionizing rice farming in Nigeria's agricultural value chain

open access articleThis review explores recent advancements in Nigeria's rice farming sector, focusing on the integration of digitalization within the agricultural value chain. By conducting a systematic analysis Seventy-Eight (78) publications from the past 14 years, the study investigates how digital platforms, such as AgricTech apps and e-commerce solutions, are transforming rice farming by connecting farmers, processors, marketers, and fabricators to streamline operations and boost efficiency. The review not only highlights the transformative potential of digital technologies in boosting crop yields and enhancing supply chain transparency but also addresses the significant challenges that hinder widespread adoption. These challenges include poor internet connectivity, limited digital literacy among rural farmers, and financial constraints. Despite these obstacles, the findings reveal promising opportunities for innovation, driven by the adoption of digital platforms that link stakeholders more effectively and improve access to global markets. The review emphasizes the urgent need for targeted interventions such as expanding digital literacy programs, improving rural internet infrastructure, and offering financial support mechanisms that can accelerate technology adoption and ensure an equitable, tech-driven agricultural future in Nigeria. In conclusion, this review stresses the pivotal role of digitalization in transforming Nigeria’s rice farming sector and provides actionable recommendations to policymakers, agribusinesses, and development agencies. It calls for a coordinated effort to overcome existing barriers and unlock the full potential of agricultural value chain data, positioning Nigeria as a key player in the global agricultural market

Current Issues: Is the workplace about to get better or worse for disabled people in the United Kingdom?

open access articleIn the United Kingdom, the new labour government has recently unveiled two new bills, the Employment Rights Bill and Equality Race and Disability Bill, that seem to strengthen the 2010 Equality Act. However, it is not clear how these bills will address the disability employment gap. The government’s policy to Make Work Pay has many good points like more transparency in terms of race, gender and disability pay gaps but it also raises questions about what devolvement to local authorities to get more disabled and chronically ill people into work will look like? This seems to target disabled and chronically ill people and does not think about how to create more enabling workplace environments following the social model

Integrating Citation Heterogeneity to Measure the Quality of Academic Journals

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Evaluating the quality of academic journals is important and complex. The journal impact factor (IF), which is the most widely used indicator to measure the quality of academic journals, assumes that all citations are homogeneous. The use of this indicator has been criticized widely due to its inherent limitations. In recent years, several sophisticated indicators have been proposed to allow the weighting of citations from different journals. However, the recursive computation process of these indicators requires a huge amount of data. This article proposes a new indicator with citation heterogeneity to measure journal quality, which is named the Citation Author Affiliation Index (CAAI). The CAAI is based on the assumption that citing paper authors’ institutions can be ranked and are considered a proxy to measure the quality of citations (in a statistical sense). It is shown that the CAAI is easy to use and interpret, time-efficient, and adaptable. The effectiveness of the CAAI is validated by using Web of Science citation data from journals in several research categories

Do we measure what should be measured? Towards a research and theoretical agenda for STI measurement in Africa

open access articleA persistent critique of standard science, technology and innovation (STI) indicators is that they remain reliant on concepts and theories transposed from the literature on STI in high-income countries. It is widely recognized that their relevance for African countries is limited, so we may not be measuring what we should be measuring, to promote development goals. To inform a shift from critique to building meaningful alternatives, the paper conducts a systematic review of the literature on STI measurement in Africa. The analysis highlights that STI measurement in Africa is under-researched, but the knowledge base is growing. The strongest trends relate to the adoption and extension of traditional standard STI indicators. More recent is a focus on environmental sustainability, digitalization and the informal sector, with most scholars based in South Africa and Nigeria. The main contribution is a research agenda to facilitate theory building as a foundation for designing contextually relevant STI indicators

A GRA-based heterogeneous multi-attribute group decision-making method with attribute interactions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In the era of VUCA (Volatility, Uncertainty, Complexity, Ambiguity), multi-attribute group decision-making (MAGDM) problems face the challenges of heterogeneous uncertainty in decision information and complex interactions between attributes, which greatly affect the reliability of decision-making outcomes. To address these challenges, this paper proposes a novel heterogeneous MAGDM method based on grey relational analysis (GRA) that considers attribute interactions. First, the heterogeneous information is integrated, including crisp numbers, generalized grey numbers, intuitionistic fuzzy numbers, hesitant fuzzy numbers, and probabilistic linguistic term sets. Then, by incorporating the 2-additive Choquet integral into GRA, we establish a heterogeneous grey interactive relational model and explore its properties. Subsequently, a heterogeneous grey relational Mahalanobis-Taguchi System is designed to estimate the Shapley values of attributes. Additionally, a two-stage resolution mechanism, comprising a consensus reaching process followed by a grey relational multi-objective programming model, is devised to determine the interaction indices. Finally, the effectiveness of the proposed method is demonstrated through a case study from China’s aviation manufacturing industry, along with sensitivity analysis and comparison analyses

Tubulin targeting agents and their implications in non-cancer disease management

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Microtubules act as molecular ‘‘tracks’’ for intracellular transport of accessory proteins to enable them to assemble into various larger structures, such as spindle fibers formed during the cell cycle. Microtubules provide an organizational framework for healthy functioning of various cellular processes which work through the process of dynamic instability, driven by hydrolysis of GTP. In their role, tubulin proteins undergo various modifications and in doing so modulate various healthy or pathogenic functioning of physiological processes within cells. In this review, we provide a detailed update of small molecule chemical agents which interact with tubulin, along with their implications, specifically in non-cancer disease management