Articles

The construction industry remains one of the most hazardous sectors globally, with Nigeria experiencing a high incidence of workplace accidents despite the adoption of Occupational Health and Safety Management (OHSM) frameworks. This study evaluated the effectiveness of OHSM practices in improving workplace safety across construction companies in Nigeria’s coastal cities. A cross-sectional design was employed, combining quantitative surveys of construction workers (n = 1,400) with qualitative interviews of 35 managers and supervisors. Quantitative data were analyzed using SPSS version 28, while thematic analysis was applied to qualitative responses. Findings revealed a generally positive perception of OHSM, with 54.4% of workers rating OHS policy effectiveness as “Good” and 52.0% rating health outcomes as “Good.” However, accident frequency remained a concern, with 46.4% reporting accidents occurred “Occasionally” and 31.9% acknowledging them as “Frequent” or “Very Frequent.” Comparative analysis showed indigenous firms were rated higher in policy effectiveness and health outcomes but also reported slightly higher accident frequencies than international firms. Thematic analysis identified five key monitoring and evaluation strategies including routine inspections, regular training, audits, behavioural reinforcement, and access control, Also, five measures of OHSM effectiveness, including compliance observation, incident tracking, KPIs, employee feedback, and benchmarking. OHSM was found to positively influence project outcomes by reducing compensation costs, enhancing reputation, and improving supervision and quality of work. OHSM practices in Nigeria’s construction sector are perceived as effective in policy and health outcomes, yet accident rates remain a critical challenge. The study underscores the importance of continuous training, stricter enforcement, behavioural reinforcement, and systematic performance evaluation.

<b>Background:</b> Tobacco endgame, defined as elimination of commercial tobacco sales The U.S. tobacco control landscape is a complex, adaptive system shaped by diverse stakeholders, evolving products and regulations, shifting social norms, and the strategic countermeasures of a powerful industry. Managing such complexity requires more than isolated interventions—it demands a coordinated, enterprise-wide approach that accounts for dynamic interactions, feedback loops, and emergent risks. <b>Objective:</b> Drawing on complex systems thinking, Zachman enterprise architecture model, and public health best practices, we conceptualize tobacco control as an evolving enterprise progressing through six interconnected phases: (1) Conception &#x26; Initiation, (2) Policy &#x26; System Design, (3) Implementation &#x26; Operation, (4) Evaluation &#x26; Adaptation, (5) Consolidation &#x26; Endgame Transition, and (6) Sustainment or Sunset. Each phase incorporates governance structures, performance benchmarks, and transition criteria designed to manage interdependence and reduce systemic vulnerabilities. <b>Results:</b> The lifecycle framing emphasizes how tobacco control in the U.S. can evolve as a complex, adaptive enterprise—integrating public health objectives with legal, operational, and cultural change processes. This model supports strategic sequencing, cross-sector alignment, and risk mitigation against emergent industry tactics, enabling a resilient and measurable pathway to the endgame. <b>Conclusions:</b> Seeing tobacco control as a complex enterprise that operates under a lifecycle model may offer a roadmap for achieving and sustaining the tobacco endgame. Using this approach may enhance policy coherence, resource efficiency, and adaptability, ensuring tobacco endgame is achieved.

The pharmaceutical industry is undergoing a profound transformation driven by advancements in Information Technology (IT), with Enterprise Resource Planning (ERP) systems playing a pivotal role in reshaping operations. These systems offer integrated solutions that streamline key business processes, such as production, inventory management, supply chain optimization, regulatory compliance, and data integration, contributing significantly to operational efficiency and organizational agility. This paper explores the evolution and impact of ERP systems within the pharmaceutical sector, highlighting their contributions to overcoming the industry’s inherent challenges, including complex regulatory requirements, the need for accurate and real-time data, and the demand for supply chain resilience. The integration of cloud-based ERP solutions, the incorporation of emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), and enhanced data analytics capabilities have revolutionized pharmaceutical IT. These advancements not only reduce operational costs, improve forecasting accuracy, and enhance collaboration but also ensure compliance with stringent global regulations, such as Good Manufacturing Practices (GMP) and FDA guidelines. Moreover, ERP systems have been instrumental in managing the pharmaceutical supply chain, ensuring product traceability, and improving inventory control and order fulfillment processes. This manuscript examines how ERP systems enable pharmaceutical companies to maintain high standards of product quality, improve decision-making, and ensure the safety and efficacy of drugs through robust tracking and auditing mechanisms. A case study of a pharmaceutical company that implemented an ERP system demonstrates the tangible benefits, including increased operational efficiency, improved compliance rates, and enhanced customer satisfaction. However, despite the clear advantages, challenges such as customization complexities, data integration issues, and resistance to change remain. As the pharmaceutical industry continues to evolve, ERP systems will remain a cornerstone of digital transformation, facilitating smarter decision-making, better resource management, and enhanced collaboration across global operations. This paper also identifies future trends, including the potential of AI and blockchain technologies in further strengthening ERP systems and transforming the pharmaceutical landscape.

Bead jewellery is common in all Ghanaian communities. Bead jewellers are well-known for their important bead jewellery production and have advanced to the Master craft level. The industry can be utilized if the industry's difficulties are discovered and remedied. The study area for the research includes Ghana's Eastern, Ashanti, and Greater Accra Regions. The study's population included bead jewellers, bead jewellery firms, bead dealers, bead aficionados, clients, and bead makers. With a sample size of 30, data was gathered mostly through direct observations, interviews, and document reviews. The study went over the procedure for securing land for a bead jewellery workshop. According to a survey conducted by the Ghanaian Chamber of Commerce and Industry (GCCII), Ghanaian bead jewellers should use qualified designers. Cost pooling in legal services, accounting, and consulting is likely to save money.

This study examines the influence of socio-demographic factors on work-family conflict among management staff in star-rated hotels in the Accra Metropolis. The research aims to explore how variables such as gender, age, marital status, and educational background impact the experiences of work-family conflict among hotel managers. A quantitative research design was employed, and data were collected through structured questionnaires distributed to a purposive sample of hotel managers. The findings reveal significant associations between socio-demographic characteristics and work-family conflict, highlighting the complexities of balancing work responsibilities with family obligations in the hospitality industry. The implications of the study underscore the importance of tailored interventions to support the well-being of hotel managers, while the recommendations emphasise the implementation of work-life balance programs, support for family obligations, promotion of diversity and inclusion, and continuous training and development. It is recommended that hotel organisations create a supportive work environment that enhances the job satisfaction and productivity of their management staff. This study contributes valuable insights to the existing literature on work-family conflict in the hospitality sector and provides a foundation for future research endeavours in this area.

Consumer behavior is evolving, demanding a wide range of products with fast shipping and reliable service. The automotive aftermarket industry, worth billions, requires efficient distribution systems to stay competitive. Manufacturers strive to balance growth with product and service excellence. Distributors and retailers face the challenge of maintaining competitive pricing while keeping inventory levels low. An adequate supply chain and accurate product data are crucial for product availability and reducing stock issues. This ultimately increases profits and customer satisfaction.

The technologies for cloud ERP (Enterprise Resource Planning) have revolutionized the field of information technologies. Any kind of business can benefit from their flexibility, affordability, scalability, adaptation, availability, and customizable data. An advancement of classic ERP, cloud enterprise resource planning (C-ERP) provides the benefits of cloud computing (CC), including resource elasticity and ease of use. The rise of cloud computing affects on-premise ERP systems in terms of architecture and cost. Cloud-based ERP systems make the claim to be appropriate for digital corporate settings. System quality, security, vendor lock-in, and data accessibility are recognized as the technological issues. Industry 4.0 refers to the re-engineering and revitalization of modern factories through the integration of cloud-based operations, industrial internet connectivity, additive manufacturing, and cybersecurity platforms. One of the four main pillars of Industry 4.0, cloud-based Enterprise Resource Planning (Cloud ERP), is a component of cloud operations that aids in achieving greater standards of sustainable performance.

This charge-ahead paper suggests that transitioning the automotive industry towards a zero-carbon ecosystem from material to end-of-life can be accomplished through disruptive zero-carbon manufacturing in the broad area of all-electric vehicle production technology. To accomplish zero carbon emission automotive manufacturing in the vehicle assembly domain, future paradigms must converge on the decoupling of carbon dioxide emissions from automobile manufacturing and use the design, processing, and manufacturing conditions. The envisioned zero carbon emission vehicle manufacturing domain consists of two complementary components: (a) making more efficient use of energy and (b) reducing carbon in energy use. This paper presents the status of key scientific and technological advancements to bring the manufacturing model of today to a zero-carbon ecosystem for the entire automotive industry of tomorrow. This paper suggests the groundbreaking application of dynamic and distributed predictive scheduling algorithms and open sensing and visualization technology to meet the zero carbon emission vehicle manufacturing goals. Power-aware high-performance computing clusters have recently become a viable solution for sustainable production. Advances in scalable and self-adaptive monitoring, predictive analytics, timeline-based machine learning, and digital replica of cyber-physical systems are also seen co-evolving in the zero carbon manufacturing future. These methods are inspired by initiatives to decouple gross domestic product growth and energy-related carbon dioxide emissions. Stakeholders could co-design and implement shared roadmaps to transition the automotive manufacturing sector with relevant societal and environmental benefits. The automated mobility sector offers a program, an industry-leading example of transforming an automotive production facility to carbon neutrality status. The conclusions from this paper challenge automotive manufacturers to engage in industry offsetting and carbon tax programs to drive continuous improvement and circular vehicle flows via a multi-directional zero-carbon smart grid.

Failure prediction can be achieved through prognostics, which provides timely warnings before failure. Failure prediction is crucial in an effective prognostic system, allowing preventive maintenance actions to avoid downtime. The prognostics problem involves estimating the remaining useful life (RUL) of a system or component at any given time. The RUL is defined as the time from the current time to the time of failure. The goal is to make accurate predictions close to the failure time to provide early warnings. J S Grewal and J. Grewal provide a comprehensive definition of RUL in their paper "The Kalman Filter approach to RUL estimation." A process is a quadruple (XU f P), where X is the state space, U is the control space, P is the set of possible paths, and f represents the transition between states. The process involves applying control values to change the system's state over time.

Practice guidelines recommend fixed combinations of calcipotriol, a topical vitamin D analogue, and betamethasone dipropionate, a high potency corticosteroid, as first line topical treatment for mild to moderate plaque psoriasis of the body and scalp. A new foaming lotion for treatment of Psoriasis was developed and patented by the Spanish Ministry of Industry, Trade and Tourism (Invention patent reference number 202030824). The foaming lotion is composed of clobetasol, papaverine hydrochloride, spironolactone, milk-peptide-complex and propylene glycol. Three cases with moderate Psoriasis aged 34, 36 and 66 years old were treated with our new foaming lotion for 7-8 days. The three patients reported important improvement in the itching sensations and remission of the scaled lesions. Before and after application of the new foaming lotion, Psoriasis Area Severity Index (PASI) scores improved in the first patient from 24.3 to 1.8, in the second patient from 26.1 to 1.8, and in the third patient from 27 to 1.8. Our results show the short-term effectiveness of the new foaming lotion in treating moderate and extensive Psoriasis. Long follow-up is needed to evaluate the remission period of Psoriasis and possible side effects of the new topical treatment.

The building construction industry holds a crucial role in the reduction of greenhouse gas emissions globally. The targets for greenhouse gas emissions may not be achieved without a defined strategic plan to meet up with the set targets from various sectors of the economy. Recognizing the enormous potential that the building industry holds in contributing to global greenhouse gas GHG emission reduction, this study describes a framework on how optimization techniques can be used as a guide for emission reduction targets for the housing sector using illustrations of the onsite and offsite building construction industry. Given that some of the GHG gases are also sources of air pollution, this study includes a discussion on how the effort to address air pollution can be used to find a consensus towards addressing the concern about GHG emissions. This study presents procedures for simplified methods of estimation of GHG emissions that various municipalities around the globe can use to estimate and report the emissions from the building construction industry. The study presents a unifying strategy for emission management. The study also demonstrates how programming methods can be applied to GHG emissions management. The approach used in this study is transferable to other industries. The study recommends a unifying strategy for the management and control of emissions in the building construction industry. The study also recommends a coordinated effort in sharing best practices for emission control and management from all jurisdictions globally. In the effort to reduce global emission targets, further studies like this and its expansion is recommended for all sectors of the global economy. It is recommended that these studies should be followed by a concrete effort to achieve good implementation of sustainable emission reduction targets globally.

The unrelenting proliferation of data, entwined with the prevalence of mobile devices, has given birth to an unprecedented growth of information obscured by noise. With the Internet of Things and myriad endpoint devices generating vast volumes of sensitive and critical data, organizations are tasked with extracting actionable intelligence from this deluge. Governments and enterprises alike, even under pressure from regulatory boards, have strived to harness the power of data and leverage it to enhance safety and security, maximize performance, and mitigate risks. However, the adversaries themselves have capitalized on the unequal battle of big data and artificial intelligence to inflict widespread chaos. Therefore, the demand for big data analytics and AI/ML for high-fidelity intelligence, surveillance, and reconnaissance is at its highest. Today, in the cybersecurity realm, the detection of adverse incidents poses substantial challenges due to the sheer variety, volume, and velocity of deep packet inspection data. State-of-the-art detection techniques have fallen short of detecting the latest attacks after a big data breach incident. On the other hand, computational intelligence techniques such as machine learning have reignited the search for solutions for diverse monitoring problems. Recent advancements in AI/ML frameworks have the potential to analyze IoT/edge-generated big data in near real-time and assist risk assessment and mitigation through automated threat detection and modeling in the big data and AI/ML domain. Industry best practices and case studies are examined that endeavor to showcase how big data coupled with AI/ML unlocks new dimensions and capabilities in improved vigilance and monitoring, prediction of adverse incidents, intelligent modeling, and future uncertainty quantification by data resampling correction. All of these avenues lead to enhanced robustness, security, safety, and performance of industrial processes, computing, and infrastructures. A view of the future and how the potential threats due to the misuse of new technologies from bandwidth to IoT/edge, blockchain, AI, quantum, and autonomous fields is discussed. Cybersecurity is again playing out at a pace set by adversaries with low entry barriers and debilitating tools. The need for innovative solutions for defense from the emerging threat landscape, harnessing the power of new technologies and collaboration, is emphasized.

The Blockchain technology uses different type of database that transact data in blocks and then chained each data blocks. When data fills one block, it is chained the same data onto previous block therefore, all the data blocks are stored in chronological order. The blockchain technology can help to ensure that data in supply chain is reliable, accurate and can be shared with all stakeholders without any manipulation. It makes supply chain more transparent and end-to-end digital visibility of data source. Blockchain is stringent technology which fill the gap between stakeholders by providing transparent unmanipulated and truthful data in supply chain. There are many initiatives has been taken by multiple regulatory bodies with partnering with supply chain stakeholders including pharmaceutical manufacturer, distributors and dispensers. In USA, Food and Drug Administration’s regulatory body Drug Supply Chain Security Act (DSCSA) initi-ated pilot program in 2019 with the partnership of leading pharmaceuticals distributors to au-thenticating saleable returns to distributor from supply chain partners. DSCSA used MediLedger blockchain interoperable technology for process evaluation and it robustness for mitigating risk of drug counterfeiting possibilities in supply chain. The DSCSA found that pilot project was suc-cessful and results were astonishing. Later it was declared that blockchain technology can also be used for meeting DSCSA’s 2023 Act for unit level traceability.

The healthcare access is fundamental rights for every human being. It is Governments responsibility to provide good healthcare services and infrastructure to its citizen. Since last few decades, Government and healthcare industries are struggling to minimize the adverse events impacting people health due to fake medicine. The world health organization also predicted that 4 out of 10 medicines in developing and poor countries are either fake or potentially adulterated. Counterfeit drugs cost billions of dollars deficit to world economy and reduce research and development (R&#x26;D) funds allocation from organizations. Stopping counterfeit medicine into supply chain is main challenge for Government and regulatory authorities. The Government and regulatory authorities are now making stringent guidelines to prohibit criminals and counterfeiters to supply fake medicine in markets. Healthcare industry need stringent regulations and secure technologies provide sage and authentic drugs to patients. The FDA has published the 10 years roadmap to implement the drug traceability in United States. The Healthcare Distribution Alliance (HDA) has also mandated to print several barcodes and human readable data in product packaging hierarchy. The FDA is participating in pilot project with leading pharmaceutical drug manufacturer and wholesales to use blockchain technology in interoperable digital network for securing digital traceability data transfer between authorized trading partners.

The advancement of modern manufacturing is synonymous with the growth of automation. Automation replaces human operators, improves productivity and quality, and reduces costs. However, the initial financial cost and knowledge requirements can be barriers to embracing automation. Manufacturers are now seeking smart manufacturing, known as the fourth industrial revolution. Smart manufacturing goes beyond automation and utilizes IoT, AI, and big data for optimized production. In a smart factory, production can be linked and controlled innovatively, leading to increased performance, agility, and reduced costs.

This paper includes the impacts of the Internet of Things (IoT), Big Data, and other emerging technologies in the vehicle production sector, digital connectivity, and sustainable transport system. Automated and intelligent transportation for safe, efficient, and sustainable transport systems will be stressed. Key factors to promote automated or connected vehicles including connected environment, integration of all transport modes, advanced cooperative systems, and policy enforcement will be discussed. This paper contains the Axiomatic Categorisation Framework (AFS) for the dynamic alignment in a collection of disparate functions in cyber-physical systems (CPS). Developed system is enhanced for breaking the rules within autonomous vehicles (AV). It means the human personal injury is inevitable while the vehicle does not do any rules. Especially in complicated traffic situations, many of the constraints are mutually exclusive, and there is no way to obey all of them at a time. Also, there is no way to ensure that the self-driving vehicle has priority in all situations [1]. Public distrust in AV systems has to be increased and the investment in this technology has to slow down. Instead, a human driver should be partially responsible for operation. The development of a driver-behavior assistant (DBA) system is proposed, which should be able to break the rules for the distances of such slow development. It is intended to be effective in non-deterministic situations while maintaining the safety of the AV and those involved in the event. A driver's actions would not only be acceptable as a driving strategy but also would be predictable, and therefore other road users could unambiguously react.

The manufacturing industry has embraced modern technologies such as big data, machine learning, and artificial intelligence. This paper examines AI and machine learning developments in the manufacturing industry, comparing current practices and data-driven projects. It aims better to understand these technologies and their potential benefits and challenges. The research identifies opportunities for innovative business solutions and explores industry practices and research results. The paper focuses on implementation rather than technical aspects, aiming to enhance knowledge in this area.

The equipment used in the construction industry is usually associated with a high impact on the environment. Although sustainable design has shown to be a main player among the initiatives focused on reducing environmental impact, it has been driven by the workers and processes, leaving the equipment endeavors in more restrictive and later stages. The equipment industry has been a constant target of environmental standards and economic pressure, but the increasing technological development allows it to respond to sustainability and safety expectations while enhancing its performance. However, there are still several limitations that lead this sector to be one of the last to reach upgrading levels in terms of development. A study identified some gaps in the equipment design that require a greater effort to effectively support the workers and companies towards sustainable construction. This chapter is based on a study aiming to understand the consolidated knowledge of technologically sustainable equipment design and to identify the challenges left for its full development. The findings support the development of innovative eco-friendly equipment, taking into consideration sustainable materials and product guidelines, as well as green economy initiatives. It also supports complex system approaches and safety by design specificities to establish a corporate knowledge of sustainable equipment and align it with the new regulations of the construction industry. The chapter introduces the context of construction equipment in terms of new challenges when faced with the need to provide construction work with a greater capacity for safety, from an environmental and energy efficiency perspective, and within the paradigm of sustainability. Then, it presents the concept of sustainable equipment considering its principles, followed by a characterization of the agents involved in its life cycle.

Emerging smart medical instruments combined with advanced smart industrial equipment facilitate the collection of vast volumes of critical data. This data not only enables significantly more accurate and cost-effective diagnosis and maintenance but also enriches the datasets available for AI algorithms, leading to improved insights and outcomes. The integration of high-speed and ultra-reliable telecommunications infrastructure is crucial, as it supports the cloud model. This model allows for off-device aggregation in the cloud, which effectively offloads infrastructure demands and provides an extended runway for future technological improvements before the deployment of the next generation of devices. However, in certain scenarios, latency and bandwidth limitations present significant challenges. These limitations require that a substantial amount of AI and machine learning processing is conducted directly on the transmitted data, which places rigorous demands on both the processing subsystems and the communications links themselves. The current project directly addresses the accelerator side of this multifaceted issue. It will carry out comprehensive end-to-end demonstrations leveraging pilot 5G networks and telemedicine facilities, collaborating closely with major industry participants to showcase the capabilities and potential of this innovative technology. This collaborative effort is essential to pushing the boundaries of what is possible in smart medical instruments and industrial applications [1].

Migrating enterprise policy systems to .NET Core is a key objective of digital transformation in the Insurance IT ecosystem. This change directly addresses strategic drivers: enabling adoption of cloud-first development, resisting market pressure for more flexible and usable enterprise solutions, and preparing for changing demands from regulation and compliance. Phases of operational benefit aligned with risk mitigation form the basis of the migration roadmap, with a strong focus on engaging all relevant stakeholders. Market pressure for a SEAMLESS user experience across ALL applications is a fundamental driver for Investment in digital transformation. Gaps remain in enterprise Operations, where Legislative and regulatory accountability Demand rigid and complex solutions that Liberty has not yet been able to provide. New risk-based capital requirements, Data-Sovereignty controls, Controls for sensitive Data in the Cloud, and new Audit requirements create a long list of challenges for the ecosystem that can no longer be Deferred. At the same time, Cross-organisational integration is becoming more important and integrating partners from the insurance supply-chain requires a much more flexible approach to development and Deployment. These factors combine to generate a credible case for accelerated digital investment with a focus on Migration to Cloud Platforms, with related Risk mitigation, Quality Improvements, and flexibility benefits that close Industry gaps.