Evolution Of Industry Research Articles

FROM ACADEMIA TO INDUSTRY: A JOURNEY OF INNOVATION IN CHEMICAL ENGINEERING - INTERVIEW WITH PROFESSOR FERNANDO LUIZ PELLEGRINI PESSOA

Background: The interview with Professor Dr. Fernando Luiz Pellegrini Pessoa covers his extensive career and contributions to chemical engineering, focusing on innovations and sustainability. Objectives: To explore Professor Pellegrini's experiences in various areas of chemical engineering, including teaching methods, research in supercritical extraction, biodiesel production, and process intensification. Methods: Semi-structured interview addressing topics such as academic and industrial career, teaching methods, ongoing research, and future perspectives for the chemical industry. Results: Professor Pellegrini highlighted the importance of practical application of theoretical knowledge, the development of the Water Source Diagram method, advances in supercritical extraction and biodiesel production, and the need for process intensification in the industry. Discussion: The interview revealed the importance of integration between academia and industry, the need for teaching methods that facilitate learning, and the challenges in implementing sustainable and efficient technologies in the chemical industry. Conclusion: Professor Pellegrini emphasizes the importance of process intensification and sustainability in the evolution of the chemical industry. He highlights the need for greater collaboration between academia and industry to address future challenges and implement innovative solutions.

Ensemble adversarial training-based robust model for multi-horizon dynamic line rating forecasting against adversarial attacks

Dynamic line rating (DLR) forecasting is critical in the effective and economical utilization of overhead lines (OHLs) in smart grids, which facilitates the integration of renewable energy sources and reduces infrastructure upgrade costs. The forecasting techniques used for DLR rely on weather data collected from sensors as well as data communication, which can introduce a potential vulnerability to adversarial attacks. Hence, this work utilizes extreme gradient boosting (XgBoost), categorical boosting (CatBoost), and random forest as ensemble learning techniques for multi-horizon forecasting, while investigating their vulnerability by introducing adversarial attacks using two different attack models with variable data contamination and perturbations. Additionally, ensemble adversarial training (EAT)-based countermeasure is proposed for robust and accurate DLR forecasting. Experimental results indicate the outperformance of the CatBoost method compared to XgBoost and random forest models under normal conditions, while highlighting the vulnerability of all models to adversarial attacks in terms of root mean square error (RMSE) and mean absolute percentage error (MAPE). The proposed CatBoost with EAT significantly mitigates the impacts of adversarial attacks and retains accuracy under normal conditions. This research contributes to developing an accurate, cyber-resilience, and reliable forecasting methodology for line rating technology, leading towards academic and industrial developments in smart grids.

Agglomeration externalities, industry life cycle and firm survival: evidence from Chinese manufacturing start-ups

ABSTRACT This paper examines the impact of the industrial life cycle on the relationship between agglomeration externalities and the survival of manufacturing start-ups. The empirical study in the Chinese context finds that at the growth and intermediate stages of the industrial life cycle, specialisation and related variety reduce the survival risk of start-ups, whereas unrelated variety does not affect the survival risk. At the mature stage, specialisation and related variety do not affect the survival risk, but unrelated variety reduces the survival risk. This paper enriches the research on the benefits of agglomeration externalities from the perspective of industry evolution.

Evaluating the benefits and risks of facial recognition payment systems adoption in Malaysia

PurposeCurrent developments in the FinTech payment industry have shown a rapid revolution in Industry 4.0, and understanding the factors affecting individual acceptance of facial recognition payment (FRP) is crucial. Hence, this study aims to evaluate the benefits and risks of FRP system adoption in Malaysia.Design/methodology/approachThe perceived risks and benefits framework is adopted as the foundation in this study to examine the various risks and benefits that users perceive, along with the trust factor, to study the relationships between these variables. Data were collected via an online questionnaire, and the hypotheses were tested using Partial Least Squares analysis on 277 responses.FindingsThe results revealed that perceived risk is a significant predictor of users' intention to use the FRP system. Privacy risk and financial risk significantly influence perceived risks, while security risk does not. Although convenience, perceived ease of use and perceived trust positively influence perceived benefits, perceived benefits do not significantly influence adoption intention. Moreover, perceived trust negatively affects perceived risks while positively affecting both perceived benefits and adoption intention. Additionally, personal innovativeness moderates the relationship between perceived risks and the intention to use the FRP system.Practical implicationsThis study helps policymakers and service providers understand individuals’ concerns and expectations regarding FRP systems. It aids practitioners in developing strategies to build trust, address innovativeness differences and mitigate risks, serving as a roadmap for integrating these systems into Malaysia's financial landscape.Originality/valueThis study distinguishes itself from prior research by evaluating FRP system adoption in Malaysia through the lens of perceived risks and benefits framework. It also explores personal innovativeness as a moderator, examining its impact on the relationship between usage intention and perceived risks and benefits. Additionally, it highlights perceived trust as a crucial factor influencing individuals' intention to adopt FRPs.

Investigating Influence of Mo Elements on Friction and Wear Performance of Nickel Alloy Matrix Composites in Air from 25 to 800 °C

Rapid developments in aerospace and nuclear industries pushed forward the search for high-performance self-lubricating materials with low friction and wear characteristics under severe environment. In this paper, we investigated the influence of the Mo element on the tribological performance of nickel alloy matrix composites from room temperature to 800 °C under atmospheric conditions. The results demonstrated that composites exhibited excellent lubricating (with low friction coefficients of 0.19–0.37) and wear resistance properties (with low wear rates of 2.5–28.1 × 10−5 mm3/Nm), especially at a content of elemental Mo of 8 wt. % and 12 wt. %. The presence of soft metal Ag on the sliding surface as solid lubricant resulted in low friction and wear rate in a temperature range from 25 to 400 °C, while at elevated temperatures (600 and 800 °C), the effective lubricant contributed to the formation of a glazed layer rich in NiCr2O4, BaF2/CaF2, and Ag2MoO4. SEM, EDS, and the Raman spectrum indicated that abrasive and fatigue wear were the main wear mechanisms for the studied composites during sliding against the Si3N4 ceramic ball. The obtained results provide an insightful suggestion for future designing and fabricating solid lubricant composites with low friction and wear properties.

Historical Analysis of Resilience in Spanish Desalination Companies: Period 1980–2024

This article analyzes the evolution and resilience of the Spanish desalination industry in response to shifting market conditions and technological challenges. Initially focused on domestic projects, Spanish companies leveraged the AGUA Program (Actions for the Management and Use of Water; the acronym does not correspond exactly in English, as it is translated from Spanish) to build expertise, which later facilitated their successful international expansion as local demand declined. The industry has adapted to diverse international regulations and local conditions, demonstrating both flexibility and competitiveness. In recent years, there has been an increasing focus on integrating renewable energy into desalination processes to mitigate rising energy costs and address environmental concerns. This shift not only reduces CO2 emissions but also stabilizes operational costs, underscoring the sector’s ongoing innovation and adaptability.

Integrating Artificial Intelligence into Traditional Sports: A Case Study of the Asian Games and Future Directions for Modernization

Abstract: This paper explores the integration of Artificial Intelligence (AI) into traditional sports, addressing a critical gap in existing research through a qualitative case study of the Asian Games. AI's application in modern sports has demonstrated its potential to enhance event management, athlete preparation, and scoring fairness. However, its adoption in traditional sports, such as Wushu and Chinese wrestling, remains limited. This study examines the challenges and opportunities associated with applying AI to traditional sports, offering development strategies to modernize these disciplines. By analyzing the impact of AI in modern competitive sports, the research proposes specific recommendations for integrating AI into traditional sports, aiming to preserve their cultural heritage while advancing their global relevance. Limitations include the focus on a single event and the exclusion of the most recent AI developments. Future research should consider a broader range of global sporting events and incorporate the latest advancements in AI technology. This study provides a theoretical and practical foundation for the application of AI in traditional sports, with implications for future technological innovation and the evolution of the sports industry.

Skill capabilities behind the scenes: the role of occupational portfolio in regional industrial evolution

ABSTRACT An increasing number of studies confirm that regional diversification is path dependent, with new industries building on pre-existing ones. However, these studies typically overlook the role of skill capabilities and the interactions between skills and industries. In this research, based on the concept of industry–occupation cross-relatedness, the influence of skill capabilities on industrial diversification across Chinese regions was investigated. The findings indicate that regions can diversify into skill-related activities following a skill path-dependent process. Furthermore, a theoretical framework integrating industry–occupation cross-relatedness and economic complexity was introduced that enabled the adoption of various diversification strategies based on regional skill capabilities.

Towards the year 2049: The next 25 years of occupational health and safety research.

In this discussion paper, we close our 2024 series reflecting on the successes, failures, and promises of occupational health and safety research in celebration of the 50th anniversary of the Scandinavian Journal of Work, Environment & Health (SJWEH). This paper aims to elaborate on the future of our research field. We conducted a narrative review of lessons learned in the series, examining insights gained and key takeaways. Additionally, we explored the current and anticipated agendas of major institutions, including the World Health Organization and the European Union, on occupational health and safety, as well as potential developments in the academic publishing industry. Occupational health and safety research has significantly evolved over the last 50 years, emphasizing longitudinal study designs, enriching observational data with registry-based information, and expanding the scope of hazardous determinants impacting workers` health. Novel statistical approaches have further enabled researchers to address complex associations, such as mediation effects, and to strengthen causal inference in observational studies. At the same time, the publishing business is changing rapidly, with artificial intelligence poised to reshape both research practices and the landscape of academic publishing. In the changing landscape of research and academic publishing, our goal is for SJWEH to continue to be a leading source of high-quality research dedicated to protecting and improving workers' health. We are curious and excited to see where all these current and anticipated changes will lead in the years to come.

NEO-INDUSTRIALIZATION AND INTELLECTUAL PROPERTY IN BRAZIL

Neoindustrialization represents a significant evolution of traditional industry, marked by the adoption of disruptive technologies that transform production processes and business models geared towards Industry 5.0. The concept of Neoindustrialization has gained relevance in contemporary economic and technological debates. This term refers to a new phase of industrial development characterized by the advanced integration of digital technologies, automation, artificial intelligence and sustainable innovation. At the same time, intellectual property emerges as a crucial pillar, playing a central role in protecting and promoting the innovations that drive this transformation. These changes bring significant benefits, such as increased productivity, reduced costs and the creation of new markets. However, they also present challenges, such as the need to retrain the workforce and adapt existing infrastructures. The methodology used to conduct the research was the qualitative, quantitative and bibliographic method. The objective of this research was to identify which actions within the NIB are geared towards Intellectual Property policy.

Study on the synergistic evolution of environment and industry-a case study of provinces along the yellow river basin

The ecological protection and high-quality development of the provinces along the Yellow River Basin have become a major national strategy in China. However, the synergistic development of the environment and industry within the basin still faces numerous challenges. Research studies on the synergistic evolution of industry with the environment are important to guide future development of the provinces. This paper combines panel data from eight provinces in the Yellow River Basin from 2011 to 2020, utilizes the Entropy Weight TOPSIS method to evaluate the growth index of subsystems, and then employs the L-V model to measure the interaction force and synergistic degree of the environmental and industrial subsystems in the provinces along the Yellow River Basin. Finally, it simulates the synergistic evolution paths of each province under different scenarios. The study shows that: 1. From 2011 to 2020, the synergy effects in the upper and middle reaches of the Yellow River Basin exhibited an upward trend, while the synergy effects in the lower reaches demonstrated a downward trend. In the upper reaches, the shift was from mild non-synergy to mild synergy, in the middle reaches from mild non-synergy to strong synergy, and in the lower reaches from strong synergy to strong non-synergy. 2. The development model in the upper and middle reaches transitioned from a weakly beneficial relationship between industry and the environment to a mutually beneficial symbiotic model. In contrast, the lower reaches shifted from a mutually beneficial symbiotic model to a state of weak industrial benefits and strong environmental harm, ultimately reaching a state where both industry and the environment mutually harmed each other. 3. According to the forecast of industrial and environmental synergy for the next 30 years, Qinghai, Inner Mongolia, Ningxia, and Shanxi provinces would benefit the most from adopting a mutually beneficial symbiotic model. However, as the development of a symbiotic model requires more external support and incurs higher costs, it is essential for each province to select its development model based on its own economic conditions. Based on this, this paper provides a theoretical basis for the development of the environment and industry in the provinces along the Yellow River Basin.

Navigating the intersection of computer technology and IoT: Innovations, challenges, and strategies for privacy protection

Abstract. The integration of computer technology in the Internet of Things (IoT) has introduced new efficiencies, and conveniences in many sectors. However, this integration has also brought some serious challenges, and one of the most pressing ones is the need for more effective protection of privacy. This paper investigates some of the latest security developments in IoT industry, including encryption, blockchain, and artificial intelligence. Furthermore, it highlights the important challenges in IoT technology by providing an overview of data overload, regulatory and security issues in IoT devices. Besides, possible solutions to these problems are suggested in this paper. In addition, a detailed conclusion is made, which includes three future plans and some important recommendations to researchers, practitioners, and policymakers who are interested in achieving effective IoT security and privacy. The paper will have a positive impact on the research community, as it will highlight the growing need to invest in research and collaboration to improve the security of the IoT ecosystems.

A Review on Mixed Reality Operating Systems : Current Trends, Challenges and Prospects

This comprehensive article explores the rapidly evolving landscape of Mixed Reality (MR) operating systems, examining their core functionalities, architectural components, and the cutting-edge trends shaping their development. The article provides an in-depth analysis of the challenges facing MR OS developers, including interoperability, scalability, and user experience optimization, while offering insights into potential solutions. A comparative article of leading MR platforms highlights the diverse approaches and capabilities within the current ecosystem. The article delves into future prospects, discussing the integration of artificial intelligence, advanced user interaction paradigms, and their potential impact across various industries. Additionally, it addresses strategies for overcoming current limitations and explores the broader implications of MR technology on society, including ethical considerations and privacy concerns. By synthesizing current research and industry developments, this paper offers a comprehensive overview of the state of MR operating systems, their potential applications, and the transformative role they are poised to play in shaping human-computer interaction and digital experiences. The article concludes by emphasizing the critical importance of continued innovation in MR operating systems for advancing the field and realizing the full potential of mixed reality technology in both personal and professional domains.

Machine learning, banking, industry, digitalization, innovation

Aim: The application of artificial intelligence (AI) offers an encouraging avenue for developments in the banking industry. Methods: The study adopted a scoping review of methodology to provide a comprehensive overview of relevant research regarding the potential uses and challenges of AI in banking. Consumer expectations have evolved, emphasizing features such as payment gateways, swift transactions, and resilient banking services. Results: Major utilization of the AI in banking industry includes enhanced customer engagement, satisfaction, and relationships, personalized financial guidance, smart digital wallets, regulation compliance and collaborative efforts, forecasting, tracking market trends, decision-making and problem-solving, anti-money laundering and fraud detection, automation of repetitive, large and time-intensive tasks, enhanced cybersecurity, and opportunity for digital financial inclusion. Conclusion: Users encounter challenges involving security issues, privacy concerns, and the complexity of technology in AI-driven banking services. Recommendation: While AI holds a crucial role in the banking industry, successful implementation demands ample allocation and consistent, predictable utilization of AI practices.

We're in it for the long haul: How corporate venture capital helps alleviate financial market frictions in social entrepreneurship

The financing of social entrepreneurship is a noted challenge. The scale of problems and potential solutions are daunting, and the time required for solutions to come to fruition often involve investment horizons that are too long for traditional investors. Using an exploratory case study of the energy industry we provide evidence that industry incumbents are one potential solution to help alleviate the market coordination problem inherent to financing social ventures. As a going concern, we find that corporate investors exhibit temporal benevolence and can provide investment horizons necessary for solutions to be developed and diffused. At the same time, commitment from an incumbent brings resource predictability that encourages others in the value chain to engage with social ventures that show promise. In this regard incumbents are able to participate in their industry's evolution while providing an underappreciated role in supporting the social entrepreneurship ecosystem.

Creative Industries And Economic Value: A Review Of Innovation, Impact, And Policy Support

This paper provides a comprehensive review of creative industries, examining their economic impact, innovation potential, and policy frameworks across different national contexts. Drawing from recent research and official reports, it analyzes how creative industries have evolved from traditional cultural activities to become significant drivers of economic growth and innovation in the digital age. The review synthesizes evidence from multiple countries, showing that creative industries demonstrate significant economic contributions, with the UK creative sector contributing £108 billion in GVA and employing 2.3 million people, while countries like South Korea and China report contributions of 6.3% and 4.3% to their respective GDPs. The findings of the review reveal that while creative industries show substantial positive economic impacts, including employment generation and revenue growth, their effects vary across regions and contexts. The paper highlights this sector's crucial role in driving innovation, particularly through digital transformation and new business model development. The paper also examines the critical role of cultural policy in supporting creative industries, finding that countries with dedicated creative industry policies have seen significant increases in sector employment over the past five years. The findings suggest that understanding the multifaceted nature of creative industries is crucial for developing effective policies and support mechanisms in both developed and emerging economies. This review contributes to the literature by providing a systematic analysis of recent developments in creative industries while identifying gaps in current research and suggesting future research directions for the development of creative industries in emerging economies.

Phase coded waveforms for integrated sensing and communication systems

AbstractNowadays, especially with the developments in the automotive industry, it has become a highly popular topic for radar and communication systems to operate on the same platform and perform joint tasks to increase situational awareness. Sharing the hardware of the radar and communication systems and using a joint waveform for both functions eliminate interference problems between the systems, increasing the effectiveness of the joint task. In studies where radar signals are utilised for communication functions, continuous wave frequency modulation or intra‐pulse frequency modulation is generally employed to transmit communication signals. There are a few studies in the literature on joint radar and communication waveforms using phase modulation. In these studies, phase modulation is not employed directly for both functions. As a contribution to the literature, this study evaluates the usage of joint radar and communications waveforms, such as Barker sequences and Zadoff–Chu sequences as opposed to linear frequency modulation. We compare these waveforms terms of range‐speed detection and symbol error rate.

Spatial analysis and soft computational modeling for hazard assessment of potential toxic elements in potable groundwater

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L−1) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

Explore Innovation and Practice of Collaborative Training Mode for Vocational Education Teachers Based on Modern Industrial College

The contemporary vocational education landscape is rapidly evolving, necessitating an innovative approach in the preparation of vocational education teachers. Central to this transformation is the integration of collaborative practices within training modalities to meet the changing demands of modern industries. This study presents an innovative collaborative training mode for vocational education teachers, pioneered by the Modern Industrial College framework. Investigating the proficiency requirements of teachers within the context of contemporary industrial advancements, this model emphasizes an amalgamation of industry-academia collaboration, multidisciplinary teaching competencies, and a curriculum responsive to technological innovation. Through a methodical examination that qualitative analyses, this research validates the effectiveness of the proposed training mode in enhancing teacher readiness and adaptability to industrial evolutions. The study concludes with a comprehensive set of recommendations tailored to policy-makers, educational institutions, and industries that aspire to uplift the standards of vocational education. These guidelines are poised to facilitate a robust platform for vocational teacher training that aligns closely with the needs of the modern workforce and the imperatives of industrial growth.

Évaluation de l’impact économique et du parcours patient lors du traitement de l’occlusion coronaire totale chronique

Chronic total occlusion (CTO) of coronary arteries is defined as complete absence of antegrade coronary flow without iodine passage, since more than 3 months. Coronary revascularization is a highly resource-intensive angioplasty procedure involving numerous medical devices (MDs). Its consumption and associated costs are not covered by either the medical act classification (CCAM) or the hospitalization fees and additional MD funding. The primary aim of this study is to analyze the financial sustainability of this activity for a public healthcare institution and to assess the budgetary impact of CTO treatment on the most expensive items of expenditure. The secondary aim is to describe the patient's intra-hospital pathway. CTO revascularization stays are categorized under the code 05K06 "Vascular Stents without Myocardial Infarction". Major cost items were identified using national coded expenditure data and compared with those from our cost study. Every CTO intervention from January to November 2021 were retrospectively retrieved. Establishment purchase prices in 2021 were used to determine MD costs. Clinical data were extracted from electronic patient records. Operative data (procedure duration, professionals involved, and MD used) were extracted. Human Resources (HR) costs were integrated into the calculations. A Sankey diagram was created. Data are expressed as mean ± standard deviation. In our study, 41 patients underwent 45 interventions. The median was 65 years. 78% of interventions were successful with a median duration of 113 minutes. 222 different MD references were used, with 27% reimbursed additionally and 73% funded within the homogeneous group of stays (HGS). The total cost of MD described in the coded expenditure data is 2142euro, of which 721euro is funded within the HGS. In our cohort, it represented averages of 2736euro ± 1393euro and 1710euro ± 926euro, respectively. Regarding HR, the total cost described in the coded expenditure data was 442euro compared to 410euro ± 169euro in our cohort. Finally, patient pathway analysis showed an average length of stay (LOS) of 1.8 days. Two pathways were identified depending on admission context: weekday hospitalization or cardiac intensive care. CTO revascularization is a planned intervention with a short LOS and a highly standardized patient pathway. Our study highlights a proliferation of MD references used during CTO revascularization due to innovative industrial developments. The cost differential with coded expenditure data confirms the need for a revision of the procedure and its categorization within an HGS, which is currently non-specific.