Search Results (86)

Starting from the Industrial Revolution in the 18th century to date, urban areas have faced increasing environmental challenges due to the diffusion of harmful substances, resulting from vehicular traffic, the activities of different industries, waste, and building construction, etc. These pollutants are dangerous, since they pose a threat to both the environment and human health. Phytoremediation is an environmentally friendly and low-cost technique that uses plants and their associated microorganisms to clean-up contaminated sites. In this review, we explore its main applications in urban settings. Specifically, we investigate how phytoremediation works, highlighting the most effective plants for its success in a city context. Moreover, we also describe the main factors influencing its effectiveness, such as soil, climate, and pollutants. In this regard, several case studies, conducted worldwide, have reported on how phytoremediation can successfully reclaim contaminated areas, transforming them into reusable city green spaces, with reduced costs compared to traditional remediation techniques (e.g., soil replacement, soil washing, etc.). Moreover, by integrating it into urban planning, cities can address environmental pollution, while promoting biodiversity, enhancing the landscape, and increasing its social acceptance. This nature-based solution offers a practical path toward more sustainable and resilient urban environments, especially in regard to the climate change framework. Full article

The communication of organizations with the internal and external environment is one of the most important tools for the growth and development of both an organization and its employees over time. Considerable importance is attached to the way in which information is received and transmitted, as well as to the dissemination of knowledge. In the era of the 4th Industrial Revolution, e-government, and digital transformation, special communication skills and competences are required of everyone. Especially in the pandemic era, new and complex problems have emerged. Communication helps to overcome friction and disagreements and at the same time influences the performance of employees. Communication spreads knowledge directly and effectively through all hierarchical levels, so that all employees are involved in decision-making. One of the features of communication is openness, which refers to unrestricted access to information and knowledge for all stakeholders. This article presents the results of a study conducted among industrial food executives. The study presents the main factors that contribute to effective communication in organizations. The results are particularly important, and any use of the results will contribute significantly to improving communication in companies. Full article

Background: Nursing and midwifery expertise exceeds the realms of clinical and biomedical knowledge. With the healthcare system transforming towards the Fourth Industrial Revolution (4IR), midwives are expected to broaden their knowledge and skills to provide quality care through the use of digital health technologies. However, there is a paucity of studies that look at the perceptions of midwives towards these digital health technologies. Objective: Hence, in this case, the authors sought to investigate the perceptions of the midwives towards the adoption of digitalized triage system in their maternity units, prior to designing and implementing the digitalized system. This was undertaken to avoid imposing a huge change upon the midwives which will consequently affect the widespread implementation of the proposed system. Methods: A sequential exploratory research design within a pragmatic paradigm underpinned this study to gain a comprehensive understanding of the midwives’ perceptions on the adoption of a digitalized triage system in the maternity units. The qualitative phase embraced purposive sampling to select participants, and data saturation was reached at 20th midwife. Meanwhile, the quantitative phase embraced a stratified sampling technique and the sample size was 155. The mixed methodological analysis was conducted using a case-comparison analytical strategy. Results: The study revealed that the midwives perceived that the adoption of a digitalized triage system would improve their skills and enhance positive health outcomes for the patients. However, they were concerned with implementation challenges such as the availability of resources and network connectivity. Conclusions: The findings suggested that midwives in this modern era are accepting of digital health interventions as they perceive them to be useful. However, the digital health intervention was also perceived to possibly be affected by external factors such as digital illiteracy, lack of resources and internet connectivity failures. Therefore, there is a need for the development of guidelines and a conceptual framework dedicated to facilitating the widespread implementation of digital triaging in maternity units in South Africa. Full article

The 78th Annual Society of Cosmetic Chemists (SCC) Scientific Meeting showcased the pivotal role of artificial intelligence (AI) in transforming the beauty and personal care industry. The session “AI Beauty Revolution” highlighted cutting-edge advancements, including AI-driven ingredient discovery, personalized product development, and sustainable practices. Key presentations explored applications such as computational tools for product benchmarking, precision prebiotics for microbiome modulation, and physics-based modeling combined with machine learning for antioxidant screening. The discussions emphasized the importance of combining AI insights with experimental validation to ensure accuracy and reliability while fostering innovation. As AI continues to drive personalization, efficiency, and sustainability in cosmetics, collaborative efforts across disciplines will remain crucial for realizing its full potential. Full article

This article reviews the literature on both (a) the general theory of public corruption and its evolution over time; and (b) the history of urban public corruption during the modern period into the present. In addition, this article conducts a historical narrative form of representation to structure the historical facts, synthesizing chronologically disparate elements into a synchronic unity, with the focus of the narrative on “urban public corruption”, both empirically (i.e., how its manifestation changed over time in particular times and places) and conceptually (i.e., how the ideas about these manifestations altered with the passage of time). The period considered is mainly from the onset of the Industrial Revolution in the mid-18th century, up to the present time, with a major focus on contemporary developments. This review illustrates that the extraction of rents has always been a key feature of urban corruption. Nonetheless, not all extraction is alike institutionally and historically. The analysis presented here indicates that the modern notion of corruptions has been the product of a long evolution which, no doubt, is not over. The present idea is of corruption as a technocratic one of a “coherent, discrete referent” based on rational choice theory, which can be applied to define acts as corrupt regardless of social context. This is found to be not applicable in all times and places. Defining what constitutes a “corrupt” act varies considerably across cultures, across times, between nations and cities, and sometimes even within them. This article closes with a template about possible behavioral spheres of urban corruption, incorporating overlaps and gaps between “rational”, “maximizing”, and “atomistic” motivations. The conclusion is that the current consensual “rational choice” understandings only apply to those acts which incorporate all three aspects, with variants drawn from “behavioral” economics expanding applicability somewhat, but still leaving out a great deal of city corruption on the ground which is much more social and institutional than present understandings allow for. Full article

The revolution in biotechnology at the end of the 20th century has improved agricultural productivity, reduced environmental impact, and enhanced food nutrition. However, genetically modified food (GMF) consumption remains low, particularly in the European Union, including Spain. This study develops a GMF acceptance model based on the Theory of Planned Behavior, incorporating five key variables alongside gender and age as control factors. Attitude-related variables include perceived benefit (PB) and perceived risk (PR). Perceived control factors involve food neophobia (PHOB) and knowledge (KNOWL) about GMFs. Additionally, subjective norm (SN) is considered. Using a sample of 728 Spanish consumers, the model was validated, explaining 70% of the variance and demonstrating strong predictive capability. The results so PB, KNOWL, and SN positively influence GMF acceptance, whereas PR and PHOB have negative effects. PB and SN emerged as the most influential variables, which are also highlighted as priorities in the importance–performance map analysis (IPMA). Based on these findings, strategies have been proposed to enhance perceived benefits and influence subjective norms, potentially increasing GMF acceptance. This study provides valuable insights into consumer behavior and offers guidance for policymakers and industry stakeholders to promote the adoption of GMFs. Full article

The 5th Generation Mobile Communication (5G) plays a significant role in the Fourth Industrial Revolution (4IR), facilitating significant improvements and innovations in various fields. The 3rd Generation Partnership Project (3GPP) is currently standardizing the Authentication and Key Management for Application (AKMA) system for the 5G convergence applications (5G cAPPs). The Transport Layer Security (TLS) is recommended as the application-specific Ua* protocol between User Equipment (UE) and Application Function (AF) to securely transmit the AKMA identifiers of UE as well as guarantee traffic protection. Among TLS protocols, session resumption in TLS 1.2 and the Pre-Shared Key (PSK) modes of TLS 1.3 are particularly desirable for Ua*. Unfortunately, the integration of PSK options of TLS 1.3, namely PSK-only, PSK-(EC)DHE, and 0-RTT (0 Round-Trip Time) modes, with AKMA has not yet been thoroughly investigated; hence, security, performance, compatibility, and effectiveness remain uncertain. In response, this paper explores the integration of the TLS 1.3 PSK options with AKMA and investigates the said metrics by conducting formal security verification and emulating exemplary applications. According to the formal verification and experimental results, the PSK-(EC)DH mode shows a security strength trade-off with efficiency. On the one hand, the 0-RTT mode demonstrates better efficiency but exhibits drawbacks on forward secrecy and replay attacks. The result suggests that 0-RTT mode has to be approved to ensure seamless integration of the TLS 1.3 PSK option with AKMA. In addition, adjustment on the AKMA architecture is also imperative to enhance security level. Full article

Additive manufacturing (AM) plays a significant role in the 4th Industrial Revolution due to its flexibility, allowing AM equipment to be connected, monitored, and controlled in real time. In advance, the minimum waste of material, the agility of manufacturing complex geometries, and the ability to use recycled materials can provide an advantage to this manufacturing method. On the other hand, the poor strength and durability of the thermoplastics used in the manufacturing process are the major drawback that keeps AM behind common production methods such as casting and machining. Fibre-reinforced polymers can enhance mechanical properties, advance AM from the commonly used polymers, and make AM competitive against conventional production methods. The main focus of the current review is to examine the work conducted in the field of reinforced additively manufactured technologies in the literature of recent years. More specifically, this review discusses the conducted research in the composite fibre coextrusion (CFC) additive manufacturing techniques developed over the past years and the materials that can be used. In addition, this study includes an up-to-date comprehensive review of the evaluation of fibre-reinforced 3D printing along with its benefits in terms of mechanical response, namely tensile, flexural, compression and energy absorption, anisotropy, and dynamic properties. Finally, this review highlights possible research gaps regarding fibre-reinforced AM and proposes future directions, such as deeper investigations into energy absorption and anisotropy, to position fibre-reinforced AM as a preferred fabrication method for ready-to-use parts in cutting-edge industries, including automotive, aerospace, and biomedical sectors. Full article

In the manufacturing industry, which is facing the 4th Industrial Revolution, various process data are being collected from various sensors, and efforts are being made to construct more efficient processes using these data. Many studies have demonstrated high accuracy in predicting defect rates through image data collected during the process using two-dimensional (2D) convolutional neural network (CNN) algorithms, which are effective in image analysis. However, in an environment where numerous process data are recorded as numerical values, the application of 2D CNN algorithms is limited. Thus, to perform defect prediction through the application of a 2D CNN algorithm in a process wherein image data cannot be collected, this study attempted to develop a defect prediction technique that can visualize the data collected in numerical form. The polyurethane foam manufacturing process was selected as a case study to verify the proposed method, which confirmed that the defect rate could be predicted with an average accuracy of 97.32%. Consequently, highly accurate defect rate prediction and verification of the basis of judgment can be facilitated in environments wherein image data cannot be collected, rendering the proposed technique applicable to processes other than those in this case study. Full article

Even in the epoch of the 4th Industrial Revolution, technologies are introducing human–machine/technology interactions that must be appropriately managed to prevent or reduce avoidable human errors. In recent years, power plants have started examining ways to manage human errors attributable to maintenance, thereby improving performance, safety, and well-being. Maintenance management requires the integration of human factors engineering (HFE) principles with maintenance practices to handle the issue of human errors. When adopting human factors engineering interventions to enhance maintenance, power plants must demonstrate the capacity for change to ensure effective management of change and realize the intervention’s benefits. The main focus in power plants is usually on the technical side of change, with less emphasis on human factors. This study aimed to develop and trial a model for determining the capacity for change to aid HFE adoption in electric power systems maintenance. A quantitative and cross-sectional survey was conducted with maintenance personnel working in South African power plants. The results showed that management commitment, knowledge, and employee involvement are associated with the capacity for change in the maintenance of power plants. This study extends previous studies on the capacity for change when adopting unconventional interventions in maintenance such as HFE principles. Full article

Amid the changes brought about by the 4th Industrial Revolution, numerous studies have been undertaken to develop smart factories, with a strong emphasis on knowledge-based manufacturing through smart factory construction. Advances in manufacturing data collection, fusion, and mining technologies have significantly bolstered the utilization of knowledge-based manufacturing. Data mining technology is widely employed for facility maintenance and failure prediction. Smart factory operations are pursuing automation and autonomization. Automation of production planning is also essential to achieve automation and autonomy in factory operations, from planning to execution. With the advancement of data mining technology, it is possible to automate production planning for the production planning and prediction of future production through information based on current conditions based on the past. The baseline information generated based on the current situation is suitable for automating short-term operational planning. If we generate time series reference information based on data from the past to the present, we can also automate long-term operation planning. By measuring the results of productivity improvements in mass-produced products from the past to the present and extrapolating them to future products, time series baseline information on production time is generated. If the baseline information is used for long-term planning, it can be used to predict future production capacity and facility shortages. This study presents a methodology and utilization method for calculating the rate of change in production time, which can be applied to production plan prediction and equipment investment capacity forecasting in future factory operations, using historical time series production time data. Full article

The objective of this study is to assess the current and future potential of the digital economy in Bangladesh, with the goal of fostering national development and prosperity by the year 2041. Concurrently, this study examines the various aspects of the digital economy through the lens of the Fourth Industrial Revolution and emerging technologies, specifically focusing on the utilization of information and communication technology (ICT) in Bangladesh. The methodology section employs a qualitative approach to ascertain the research objectives, utilizing secondary data. The purpose of this study is to provide an overview of the contemporary status of the digital economy, focusing on emerging trends that have a significant impact on the national gross domestic product (GDP). Companies and individuals possess an understanding of the digital economy, which has the potential to mitigate the digital divide and establish a robust connection between technology and the economy. The research contributes to a more thorough understanding that Bangladesh is ranked 40th out of 193 nations at present; with the advancement of the digital economy, it will move up to 24th place in 2034. Future research can perhaps be expanded by adopting a qualitative methodology to explore the concept of a smart Bangladesh. Full article

The electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialisation, population growth, urbanisation and, of course, the evolution of modern technologies in this 4th industrial revolution era. Such a rapid increase in energy demand introduces a huge challenge into the power system, which has paved way for network operators to seek alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such an increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a DC TNEP model that minimises the capital costs of additional transmission lines, network reinforcements, generator operation costs and the costs of renewable energy penetration, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model was tested in several IEEE test systems in multi-period scenarios. We also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variable decomposition techniques. Moreover, we intend to provide additional recommendations in terms of in which particular year (within a 20 year planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. This is achieved by running incremental period simulations from the base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time, even for large power grid system. Full article