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In this paper, we propose a multi-block relaxed-dual linear inertial alternating direction method of multipliers (MBRD-LIADMM) for solving the nonconvex and nonsmooth multi-block optimization problems with nonseparable structures, which combines the inertial technology, the relaxed-dual term and linear ADMM. The paper not only gives the simple condition to ensure the boundedness of the iterative sequence generated by the algorithm, but also proves the global convergence under the help of Kurdyka-Łojasiewicz property, which means that the generated sequence converges to a stationary point of the problem. Finally, two experiments are carried out to demonstrate the feasibility and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Play-to-earn (P2E) is a new form of monetised gaming based on blockchain and crypto-currency technology. Such games offer opportunities to combine gaming with speculative investment through the purchase of tradable in-game currencies and assets (non-fungible tokens). In this paper, we investigate the profile of people most likely to be attracted to this emerging form of gaming. A sample of 560 participants aged between 18-65 (M = 28.3, SD = 8.3) were recruited via Prolific to complete an online survey that included measures of gaming (Petry's Internet Gaming Disorder Scale) and gaming risk (Problem Gambling Severity Index), measures of gaming motivation and impulsivity. Other existing engagement in gaming monetization as well as digital asset ownership was also assessed. P2E interest was associated with higher gambling risk scores, but not with internet gaming disorder. P2E gamers also scored higher on extrinsic motivation and monetised gaming was generally associated with higher impulsivity. The results suggest that P2E may be attractive to those with a pre-existing interest in financially risky activities. Policy implications include the increasing need to monitor the growth of digital asset technology and the increasing convergence of gambling, financial speculation and gaming and the potential for increasing financial harm in gaming populations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Sciences & Information Technology is the property of Arab Journal of Sciences & Research Publishing (AJSRP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study attempted to analyze success factors of art technology convergence startups using the ERIS model to provide practical insights for future startups. This case study was focused on Yeolmae Company Inc, which had launched Korea's first online art collective purchase platform 'Art & Company' and issued the first arts-based fractional investment securities. This research performed literature reviews and interviews. Key findings are as follows. Entrepreneur factor showed that the founder leveraged business knowledge as an accountant and art experience from gallery work to create a unique business model. Resource factor revealed that the company secured KRW 26.2 billion (approx. USD 20 million) in investments and resources such as advanced storage facilities and a data-based pricing system, enhancing competitiveness. Industry environment factor showed positive changes due to increased MZ generation investment in art and government amendments to the Capital Market Act. Strategy factor revealed that trust was secured through blockchain-based transparent investment platforms with artworks offered at various price points. [ABSTRACT FROM AUTHOR]

The increase in energy demand due to industrial development and urbanization has resulted in the development of large-scale energy facilities. Republic of Korea's petrochemical industrial complexes serve as prime examples of this phenomenon. However, because of complex processes and aging facilities, many of which have been in operation for over a decade, these industrial complexes are prone to process-deviation-related accidents. Chemical accidents in energy facilities involving high-pressure liquids or gases are especially dangerous; therefore, proactive accident prevention is critical. This study is also relevant to corporate environment, social, and governance (ESG) management. Preventing chemical accidents to protect workers from injury is critical for business and preventing damage to surrounding areas from chemical accidents is a key component of ESG safety. In this study, we collected accident data, specifically injury-related incidents, from Republic of Korea's petrochemical industrial complexes, which are the foundation of the energy industry. We analyzed the causes of accidents in a step-by-step manner. Furthermore, we conducted a risk analysis by categorizing accident data based on the level of risk associated with each analysis result; we identified the main causes of accidents and "high-risk process stages" that posed significant risk. The analysis reveals that the majority of accidents occur during general operations (50%, 167 cases) and process operations (39%, 128 cases). In terms of incident types, fire/explosion incidents accounted for the highest proportion (43%, 144 cases), followed by leakage incidents (24%, 78 cases). Furthermore, we propose a disaster safety artificial intelligence (AI) model to prevent major and fatal accidents during these high-risk process stages. A detailed analysis reveals that human factors such as accumulated worker fatigue, insufficient safety training, and non-compliance with operational procedures can significantly increase the likelihood of accidents in petrochemical facilities. This finding emphasizes the importance of introducing measurement sensors and AI convergence technologies to help humans predict and detect any issues. Therefore, we selected representative accident cases for implementing our disaster safety model. [ABSTRACT FROM AUTHOR]

In both private and Government sectors, the convergence of digital technologies and environmental, social, and governance assessment addresses concerns regarding sustainable practices. This study explores crucial ESG activities for sustainable digital supply chain focusing on their promotion of sustainable businesses. Initially, a literature review and experts input identified 12 potential activities. Using the Best‐Worst Method, these activities were ranked, and their interactions were evaluated through Total Interpretive Structural Modeling and the Matrix of Cross‐Impact Multiplication Applied to Classification technique. The key activities identified include "circular economy practices and waste reduction," "energy efficiency and reduction in carbon emissions," and "data privacy and cybersecurity." Understanding these activities enables organizations to mitigate environmental impact, enhance social performance, and improve governance practices in supply chains. The implications extend to fostering environmentally conscious supply chains in a rapidly evolving digital landscape, aligning with "sustainable development goals," including justice, responsible consumption, clean energy, and climate action. [ABSTRACT FROM AUTHOR]

Green technology has received continuous attention and facing challenges of transformation because of the growing environmental concern, especially the carbon emissions resulting in global warming. In the Industry 4.0 era, green technology transforms into smart green technology benefits from the convergence with digital technologies. However, little research investigates the role of green and digital technology convergence (GDC) on carbon emission reduction. This study proposes a novel measurement of the GDC level of enterprise based on the network method and examines its pattern and dynamic. Moreover, we empirically analyze the impact of GDC on carbon emission reduction. Results show that GDC has a significant carbon reduction effect. Moreover, GDC reduces enterprises' carbon emissions by improving green innovation quality. Furthermore, an enterprise's technology convergence capability moderates the focal relationship. The heterogeneity analysis results reveal that the carbon reduction effect of GDC is stronger in large, state-owned, non-labor-intensive and heavy-pollution enterprises. The findings contribute to a better understanding of the fusion of greening and digitalization and provide useful insights for sustainable development policy-making. [ABSTRACT FROM AUTHOR]

Do new manufacturing technologies of the Industry 4.0 (I4.0) boost TFP growth? By adopting a distance-to-frontier framework, this paper explores whether the adoption of (advanced) digital technologies affect the sectoral TFP growth rates across manufacturing industries of 14 European countries, during the period 2009–2019. We rely on a novel measure of adoption of I4.0 technologies (namely, advanced industrial robots, additive manufacturing and industrial internet of things), exploiting highly detailed (8-digit level) information on imports of capital goods embodying such technologies. Our results suggest that adopting new digital manufacturing technologies of the I4.0 brings quantitatively important and statistically significant contributions to sectoral TFP growth rates, although these are mostly concentrated in countries close to the technology frontier. In turn, these technologies seem to have hampered the process of convergence between European technological leaders and laggards over the last decade. [ABSTRACT FROM AUTHOR]

This paper explores the development of digital and green collaboration, empirically examining both the linear and nonlinear impacts of the convergence of digital and green technologies on regional total factor productivity (TFP). Using data from 30 provinces and cities in China from 2010 to 2022, the study constructs a panel threshold model with business environment and intellectual property protection as threshold variables to investigate their roles in mediating the effects of digital–green technology convergence on regional TFP. The key findings are as follows: (1) The linear analysis reveals that the convergence of digital and green technologies significantly enhances regional TFP. (2) The nonlinear analysis demonstrates a nonlinear relationship between the convergence of these technologies and regional TFP. (3) The threshold effect test identifies a single-threshold effect for the business environment, showing that once the threshold is surpassed, the positive influence of the convergence of digital and green technologies on TFP increases. Additionally, a double-threshold effect is found with intellectual property protection; as intellectual property protection surpasses the first and second thresholds, the positive impact initially strengthens but then weakens. (4) A heterogeneity analysis shows that the convergence of digital and green technologies significantly contributes to TFP in the eastern regions, while the effects in central and western regions are not significant. [ABSTRACT FROM AUTHOR]

The article "The Nontechnical Skills Innovators Need" explores the importance of nontechnical skills in innovation, particularly in the context of the rise of generative artificial intelligence (gen AI). It discusses how skills from liberal arts, social sciences, empathy, and design thinking play crucial roles in fostering innovation and creating comprehensive solutions. The text emphasizes the need for a diverse set of nontechnical skills alongside technical expertise to address complex global challenges effectively. [Extracted from the article]

This paper constructs a digital technology multilayer convergence network model to explore the mechanisms of digital technology convergence. The analysis is based on patent data from China's A-share listed companies from 2012 to 2021. The results show a continuous increase in network scale and structural complexity, with intensified cross-domain interactions. The company collaboration subnetwork evolved from decentralization to a more centralized structure, while the technology convergence subnetwork expanded and became increasingly complex. Core technologies maintained dominant positions, and the co-evolution between companies and technologies showed sustained development. This study reveals intricate interdependencies between technological convergence and company collaboration, providing theoretical insights and practical implications for digital technology innovation and strategic decision-making. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) remains a leading cause of morbidity and mortality among women worldwide, with triple-negative breast cancer (TNBC) posing significant treatment challenges due to its aggressive phenotype and resistance to conventional therapies. Recent advancements in nanocarrier technology offer promising solutions for enhancing drug delivery, improving bioavailability, and increasing drug accumulation at tumor sites through targeted approaches. This review delves into the latest innovations in BC detection and treatment, highlighting the role of nanocarriers like polymeric micelles, liposomes, and magnetic nanoparticles in overcoming the limitations of traditional therapies. Additionally, the manuscript discusses the integration of cutting-edge diagnostic tools, such as multiplex PCR-Nested Next-Generation Sequencing (mPCR-NGS) and blood-based biomarkers, which are revolutionizing early detection and molecular profiling of BC. The convergence of these technologies not only enhances therapeutic outcomes but also paves the way for personalized medicine in BC management. This comprehensive review underscores the potential of nanocarriers in transforming BC treatment and emphasizes the critical importance of early detection in improving patient prognosis. [ABSTRACT FROM AUTHOR]

The Fifth Industrial Revolution is ushering in a profound era of technological advancement and societal transformation, prompting a critical examination of the evolving role of libraries in this digital landscape. Traditionally regarded as the custodians of knowledge, libraries must adapt to these changing dynamics of the digital world while preserving their core principles. This study looks into the strategic integration of advanced technologies, aiming to redefine the mission of libraries in the face of complex challenges. The Fifth Industrial Revolution encompasses a convergence of diverse technologies, including the Internet of Things (IoT), cloud computing, biotechnology, nanotechnology, and quantum computing, all underpinned by the currency of data. Artificial intelligence (AI) is a focal point, promising enhancements in user experiences and operational efficiency, however, it also raises critical ethical and privacy concerns that challenge fundamental library principles. This research employs an interpretive content/document analysis approach to examine the evolving roles of libraries, considering their pivotal function in bridging the digital divide, providing equitable access to technology and digital resources, advancing research and innovation, and fostering community engagement. The study underscores the imperative to address challenges related to data privacy, digital inclusion, resource allocation, intellectual property, and sustainability. However, despite these challenges, libraries are poised to remain indispensable pillars of education, research, and community interaction. To do so, they must embrace technology strategically to redefine their roles and expand their influence within evolving knowledge systems. [ABSTRACT FROM AUTHOR]

Copyright of Logos: A Journal, of Religion, Philosophy Comparative Cultural Studies & Art (08687692) is the property of Logos and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to analyze the trends of research conducted on companies using social media. Social media is one of the online platforms for sharing or exchanging individual thoughts, experiences, and opinions, and with the development of the IT environment, the use of social media has also grown rapidly. In recent years, research in the field of business administration or economics on the use of social media is also showing a significant increase. Contents posted on social media directly or indirectly affect corporate performance or corporate value. This study summarized the results of empirical research on this. This study proposes a technology-based convergence study on the economic effect of social media, and looks forward to expanding research in this field. [ABSTRACT FROM AUTHOR]

Copyright of Art Time is the property of Ataturk University Coordinatorship of Scientific Journals and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper examines the mediating effect of R&D alliance network dynamics on the relationship between technology convergence and firm innovation quality, it further investigates the moderating effect of degree assortativity in the inventor network. An empirical analysis is conducted based on a panel negative binomial regression model with data of Chinese high‐tech firms listed on the Shanghai and Shenzhen Stock from 2000 to 2018. The results show that novel technology convergence not only contributes to innovation quality directly but also indirectly through ego‐network expansion. The relationship between reinforced technology convergence and innovation quality is inverted U‐shaped, partially mediated by ego‐network stability. In addition, degree assortativity suppresses the effects of novel technology convergence on ego‐network expansion and innovation quality and steepens the inverted U‐shaped relationships of reinforced technology convergence with ego‐network stability and innovation quality. This paper contributes to the relevant literature by revealing the links between technology convergence, ego‐network dynamics, and innovation quality, and emphasizing the importance of inventor collaboration ties formation mechanism in knowledge searching and convergent innovation. Furthermore, the conclusion provides managerial suggestions for high‐tech firms to coordinate internal and external resources to improve technical impacts. [ABSTRACT FROM AUTHOR]

The following article explores the rise of "cringe culture" in online ecosystems and applies the spirit of internet irony to movies considered "so bad, they're good." Drawing from scholarship on camp, trash, and historical badfilm, I advance a twenty-first-century canon of cringe cinema, sourced from social media and online forums, divided into films that encourage our compassion or conversely, provoke our contempt. Finally, I contend that the internet plays a radical new role in the nature of cult spectatorship and debate if cringe is mere schadenfreude or the next generation in the politics of taste. [ABSTRACT FROM AUTHOR]

Binary combinatorial optimization plays a crucial role in various scientific and engineering fields. While deterministic approaches have traditionally been used to solve these problems, stochastic methods, particularly metaheuristics, have gained popularity in recent years for efficiently handling large problem instances. Ant Colony Optimization (ACO) is among the most successful metaheuristics and is frequently employed in non‐binary combinatorial problems due to its adaptability. Although for binary combinatorial problems ACO can suffer from issues such as rapid convergence to local minima, its eminently parallel structure means that it can be exploited to solve large and complex problems also in this field. In order to provide a versatile ACO implementation that achieves competitive results across a wide range of binary combinatorial optimization problems, we introduce a parallel multicolony strategy with an improved cooperation scheme to maintain search diversity. We evaluate our proposal (Binary Parallel Cooperative ACO, BiPCACO) using a comprehensive benchmark framework, showcasing its performance and, most importantly, its flexibility as a successful all‐purpose solver for binary combinatorial problems. [ABSTRACT FROM AUTHOR]

We prove mixing convergence of the least squares estimator of autoregressive parameters for supercritical autoregressive processes of order 2 with Gaussian innovations having real characteristic roots with different absolute values. We use an appropriate random scaling such that the limit distribution is a two-dimensional normal distribution concentrated on a one-dimensional ray determined by the characteristic root having the larger absolute value. [ABSTRACT FROM AUTHOR]

Due to their simplicity and global convergence properties, the conjugate gradient (CG) methods are widely used for solving unconstrained optimization problems, especially those of large scale. To establish the global convergence and to obtain better numerical performance in practice, much effort has been devoted to develop new CG methods or even to modify well- known methods. In 2012, Rivaie et al., have proposed a new CG method, called RMIL which has good numerical results and globally convergent under the exact line search. However, in 2016, Dai has pointed out a mistake in the steps of the proof of global convergence of RMIL and hence to guarantee the global convergence he suggested a modified version of RMIL, called RMIL+. In this paper, we present another modified version of RMIL, which is globally convergent via the exact line search. Furthermore, to support the theoretical proof of the global convergence of the modified version in practical computation, a numerical experiment based on comparing it with RMIL, RMIL+, and CG-DESCENT was done. [ABSTRACT FROM AUTHOR]

The convergence of information and communication technologies has introduced new and advanced capabilities to Industrial Control Systems. However, concurrently, it has heightened their vulnerability to cyber attacks. Consequently, the imperative for new security methods has emerged as a critical need for these organizations to effectively identify and mitigate potential threats. This paper introduces an innovative approach by proposing a dynamic vulnerability severity calculator. Our methodology encompasses the analysis of environmental topology and the effectiveness of deployed security mechanisms, coupled with the utilization of the Common Vulnerability Scoring System framework to adjust detected vulnerabilities based on the specific environment. Moreover, it evaluates the quantity of vulnerabilities and their interdependencies within each asset. Additionally, our approach integrates these factors into a comprehensive Fuzzy Cognitive Map model, incorporating attack paths to holistically assess the overall vulnerability score. To validate the efficacy of our proposed method, we present a relative case study alongside several modified scenarios, demonstrating its effectiveness in practical applications. [ABSTRACT FROM AUTHOR]

The modern medical system is convergence of cutting-edge technologies and advancements in the healthcare environment. In the modern medical system, the storage of electronic health records is generally leased out to third-party cloud service providers (CSPs). But, CSPs cannot be entirely relied upon due to the potential security and privacy issues. This article presents Multi-Authority and Hierarchical Attribute-Based Encryption Scheme (MH-ABE) scheme to promote secure information sharing and protect patient's privacy. The utilization of CP-ABE in conjunction with multiple Attribute Authorities within the proposed MH-ABE scheme presents a scalable and fine-grained approach to data access control. The proposed MH-ABE scheme incorporates the utilization of a Hierarchical Access Tree to effectively encrypt numerous files concurrently, hence reducing the computational and storage cost. The proposed scheme has also been evaluated using a comparative analysis with existing schemes, emphasizing the assessment of computational and storage costs. The findings of this analysis demonstrate improved performance and efficiency of the proposed ciphertext policy based encryption scheme. The proposed MH-ABE scheme incorporates features such as policy hiding and revocation, and it exhibits resilience against attacks, including collusion resistance, Indistinguishability under chosen-plaintext attack and forward secrecy. [ABSTRACT FROM AUTHOR]

This paper reports on research into co-creation labs as a tool for exploring environmental communication. Co-creation labs are novel spaces for experimentation, social learning, and trans-disciplinary as well as cross-sectoral collaboration for sustainability transformations. This paper examines the approach taken by researchers to theorising, via a repurposing of the 2×2 scenario matrix, a series of "labs" that represent diverse spaces in which to explore co-creative convergence through transformative learning processes. In addition, examples from work done to date are offered to illustrate progress in implementing these labs and testing the strengths and weaknesses of these co-creative spaces. [ABSTRACT FROM AUTHOR]

This article positions Additive Manufacturing (AM) within the broader context of historical technological revolutions, recognizing its transformative impact while acknowledging that future generations may perceive it as an early-stage technology. AM has evolved through several industrial revolutions, particularly benefiting from advancements in Artificial Intelligence (AI) and the Internet of Things (IoT). The convergence of traditional manufacturing techniques with these contemporary innovations has created a favorable environment for the widespread adoption of AM technologies. The article emphasizes the need for AM to fully embrace this integration to achieve its potential. The discussion highlights that the core objective of Focused Beam Additive Manufacturing (FBAM) is to control the solidification process, ensuring the production of sound and reliable components on the first attempt. Despite being a multidisciplinary technology, all relevant disciplines converge on achieving a flawless melting and solidification process. This involves precise modulation of energy sources, effective powder management, motion control systems, and temperature/environment regulation, all aimed at producing microstructurally and geometrically flawless components. The article concludes that the success of FBAM depends on the careful orchestration of these multidisciplinary activities, centered around a well-controlled solidification process, to deliver high-quality components that meet business needs. [ABSTRACT FROM AUTHOR]

To explore whether digital finance can reduce agricultural carbon emissions, promote regional convergence, and foster inclusivity in rural revitalization and shared prosperity, this paper uses the provincial-level index of digital financial inclusion to analyze the impact of digital financial inclusion on the intensity of agricultural carbon emissions and the Degum Gini coefficient (D-Gini coefficient) of regional carbon emission intensity in 30 sample provinces from 2010 to 2020. It examines the mechanism of the impact of digital financial inclusion on both variables to understand the underlying factors better. The main conclusions are as follows: (1) Digital financial inclusion significantly reduces the intensity of agricultural carbon emissions and narrows the gap in carbon emission intensity between regions. (2) The unconditional quantile regression coefficients show that the negative coefficients of the digital financial inclusion index and the three-dimensional indices decrease with increasing quantiles. However, the significant effects vary significantly at different quantiles. (3) Technological progress and the government's ability to allocate financial resources play a significant mediating role, and the income gap between urban and rural areas can be further narrowed, as well as the carbon emission intensity gap between provinces. The empirical results are robust and proven by replacing the econometric analysis method, changing the core variables, and other methods. [ABSTRACT FROM AUTHOR]

Empirical macroeconomics has highlighted the existence of technology clubs in the world. Are such clubs converging in terms of technological progress, and if so, at what speed? And, what is the role of technology convergence in output convergence? To answer these research questions, we here propose a pragmatic nonparametric test. Using a sample of 81 countries over the 1965–2014 period, we find that the 'Advanced' technology club defines the best practice technology in the world, and that the club of the 'Followers' but not the 'Marginalized' one shows technology convergence. Only in the 'Followers' indeed is technology convergence related to output convergence. [ABSTRACT FROM AUTHOR]

The purpose of this research is to investigate the revolutionary potential of artificial intelligence (AI) to enhance the capabilities of immersive gaming experiences in the metaverse. Individuals are able to engage in a wide range of activities inside the metaverse, which is a network of interconnected virtual locations. There is a convergence of blockchain technology, augmented reality technology, and virtual reality technology for this. In metaverse gaming, artificial intelligence makes it possible to create dynamic environments, customise gameplay, enhance social connections, and create realistic non-player characters (NPCs). It is necessary to find solutions to problems such as data privacy, algorithmic bias, and ethical concerns in order to fully achieve the benefits of artificial intelligence (AI) while guaranteeing the safety and confidence of users. Using a mixed-methods approach that combines quantitative analysis, expert interviews, and a literature review, this study provides insights on the present usage, impacts, and future potentials of artificial intelligence in metaverse gaming. [ABSTRACT FROM AUTHOR]

Summary: One of the practical preferences of cloud service providers is to use specialized physical hosts. In other words, the goal is to place homogeneous virtual machines (VMs) on the physical host according to performance criteria such as energy consumption, resource wastage, and utilization. virtual machine placement (VMP) falls into NP‐hard knapsack problems. To overcome the time complexity, the use of heuristic and metaheuristic methods has attracted the attention of researchers. In this paper, we use an entropy‐based method for VMP for the first time. The proposed method tries to place the VMs on physical machines by considering the type of VMs to minimize entropy. Entropy is a measurable property that is more associated with disorder, randomness, or uncertainty. We use one of the most common entropy criteria called the Gini coefficient. In summary, among the different placement combinations of VMs, those that can minimize the Gini coefficient are preferred. We then solve the multi‐objective problem with the non‐dominated sorting genetic algorithm (NSGA‐III). We also combine this method with differential evolution methods to improve the quality of solutions. Recent research in other engineering fields has shown that combining metaheuristic methods with differential evolution methods increases the rate of convergence toward the optimal solution. The simulation results on the CloudSim simulator, along with statistical analysis, show that the entropy‐based method has a significant improvement over the state‐of‐the‐art methods in terms of significant performance criteria such as utilization, resource wastage, and energy consumption. [ABSTRACT FROM AUTHOR]

In this paper, the power method is discussed in mathematical detail with respect to the convergence, analysis, numerical computations and multiplicity. Deflation as well as avoiding deflation are described for symmetric positive definite matrices. Variations of the power method are discussed. Projections are applied to some distributions of the spectrum. [ABSTRACT FROM AUTHOR]

This document is an editorial introducing a special issue on "Systems Engineering and Knowledge Management." It explains that systems engineering is a transdisciplinary approach to developing engineered systems, involving cooperation between business and technical stakeholders. Knowledge management is described as a field that encompasses both technical and organizational management approaches. The editorial then briefly introduces the manuscripts included in the special issue, which cover topics such as success factors in IT service projects, decision-making techniques using fuzzy sets, strategic planning of projects, adapting e-commerce applications to IoT and cloud computing, optimizing residential appliance scheduling, and improving recommender systems using language models. This collection of papers explores the application of advanced technologies in systems engineering across various domains. The papers cover topics such as healthcare, finance, social media analysis, supply chain management, computer vision, cloud computing, smart city development, engineering optimization, genomics, optimization problems, and cybersecurity. The use of technologies like artificial intelligence, machine learning, blockchain, data analytics, bioinformatics, and swarm intelligence is examined to address complex challenges in interconnected systems. The papers also emphasize the importance of knowledge management in effectively utilizing the vast amounts of data generated by these systems. Overall, these papers contribute to interdisciplinary research and innovation in systems engineering to improve the resilience, efficiency, and sustainability of complex systems in the digital age. [Extracted from the article]

Spectral indices developed to extract features from satellite images are simple and fast methods that reduce processing time compared to traditional satellite image classification. In this paper, the effectiveness of the normalized difference building index (NDBI), the normalized difference vegetation index (NDVI), and the Normalized Difference Water Index (NDWI) were evaluated in land cover mapping and detecting its changes in the period from 2013 to 2023 in Fayoum Governorate, Egypt, using Landsat 8-OLI images. The results of supervised classification showed a decrease in green areas between 2013 and 2023 by 76.03 square kilometers, with a slight decrease in the areas occupied by water amounting to 3.8 square kilometers and an increase in built-up areas by 79.83 square kilometers, at the expense of green lands. On the other hand, the results of using spectral indices showed a decrease in green areas between 2013 and 2023 by 91.12 square kilometers, with a slight decrease in the areas occupied by water amounting to 3.35 square kilometers. Meanwhile, it was noticed that, increasing in the built-up areas by 94.47 square kilometers at the expense of green areas. The results showed a general convergence in the changes in the studied classes during the study period, with a great convergence in the change in the area of the water bodies resulted from the classification and from the NDWI and a convergence in the effectiveness of both the NDVI and NDBI. Finally, the effectiveness of the spectral indices in land cover mapping using check points was evaluated. The results showed a high percentage of the number of correctly identified check points for the NDWI index, with this percentage being noticeably low in the case of the NDVI and NDBI. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ciência & Saúde Coletiva is the property of Associacao Brasileira de Pos-Graduacao em Saude Coletiva and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The three-dimensional (3D) printing technology has led to transformative shift in prosthodontics. This review summarizes the evolution, processing techniques, materials, integration of digital plan, challenges, clinical applications and future directions of 3D printing in prosthodontics. It appraises from the launch of 3D printing to its current applications in prosthodontics. The convergence of printing technology with digital dentistry has facilitated the creation of accurate, customized prostheses, redefining treatment planning, design, and manufacturing processes. The progression of this technology is from generating models to prosthesis like-fixed dental prosthesis (FDP), implants, and splints. Additionally, it exhibits more wide capabilities. The exploration of materials for 3D printing provides various options like polymers, ceramics, metals, and hybrids, each with distinctive properties that are applicable to different clinical scenarios. The combination of 3D-printing technology and digital workflow simplifies the processes of data transfer, computer-aided design (CAD) design to fabrication, decreasing errors and chairside time. The clinical benefits include enhanced accuracy, comfort, conservative lab procedures, and economics. Challenges in the technology involve significant aspects like initial investment, material availability, and skill requirements. Future trends emphasize on research for improved materials, bioprinting integration, artificial intelligence (AI) application, regularization efforts to ensure safe and common use of the technology. 3D printing offers promise in prosthodontics, addressing challenges through research. The material improvements will promote its broader adoption and revolutionize the future of dental rehabilitation. [ABSTRACT FROM AUTHOR]

This document is a response to a comment made by Robertas Damaševičius regarding an article on info-autopoiesis and artificial general intelligence (AGI). The response addresses specific points raised in the comment and clarifies the author's position. It emphasizes that info-autopoiesis, the self-creation of information, is fundamental only to humans and not achievable by artificial creations. The article argues for the impossibility of achieving AGI using info-autopoiesis and suggests that resources should be directed towards more achievable goals in AI. The response also discusses the relationship between biological aspects of human intelligence and AI research, highlighting the use of neural networks and considering the architecture of AGI. It concludes by stating that info-autopoiesis sets a limit to human knowledge based on fundamental principles and that all human creations are syntactic and incapable of semantic interpretation. The text discusses the concept of info-autopoiesis and its application to AI research. Info-autopoiesis is a framework that aims to explain how living organisms function, and the paper explores its potential implications for AI and AGI development. The author acknowledges the limitations of info-autopoiesis and emphasizes the need for interdisciplinary collaboration and ethical considerations in AI research. The text concludes by suggesting areas for further research and expressing gratitude for the comments and suggestions provided by Robertas Damaševičius. [Extracted from the article]

Technology integration in the tourism industry has resulted in many innovations and advancements. The study investigates the impact of digital technologies on various experience parameters of pilgrimage tourism. It critically examines the convergence of digital technologies and pilgrimage tourism, focusing on the implementation of Tourism Experience Model in this domain. Revitalization of pilgrimage through tourism has become a significant trend as pilgrimage sites draw a wide range of people seeking unique and extraordinary experiences. By identifying the critical variables that contribute to life-changing pilgrimage experiences, the study seeks to improve the management of pilgrimage paths and provide insights into the factors that lead to improved tourist experience. The study also analyzes the role of digital technologies in destination marketing, tourist engagement, and evolution of pilgrimage tourism ecosystems, focusing on heritage preservation and community empowerment. [ABSTRACT FROM AUTHOR]

Against the backdrop of swiftly changing industrial environments, this study aims to investigate the influence of technology convergence on the sustainable innovation of manufacturing enterprises. The purpose of this research is to determine the future competitiveness and expansion potential of industries by evaluating the impact of technological convergence on innovation performance, which serves as a significant metric for assessing the sustainability of corporate innovation practices. Specifically, the relationships among three characteristics of technological convergence and enterprise innovation performance—betweenness, closeness, and clustering—are analyzed. Using the financial, property, and patent data of listed companies in China's automotive manufacturing industry, an empirical study is conducted using a negative binomial regression model. Enhancing all three technology convergence characteristics is found to be conducive to enhancing sustainable innovation. Meanwhile, the corporate knowledge base plays a mediating role in which the effect of knowledge base width on clustering technology integration is more strongly mediated by the effect of knowledge base depth on approaching technology integration. The results of this study are useful for policymakers, corporate strategists, and innovation managers who are looking to enhance sustainable innovation practices within their organizations. By understanding the critical roles of betweenness, closeness, and clustering in technological convergence, stakeholders can better position their firms to leverage these attributes for improved innovation performance and competitive advantage. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear observer for a variable-speed wind energy conversion system (WECS) utilizing a permanent magnet synchronous generator (PMSG). The study addresses the design of high-gain sampled-data observers based on the nonlinear WECS model, supported by formal convergence analysis. An essential aspect of this observer design is the incorporation of a time-varying gain, significantly enhancing system performance. Convergence of estimation errors is demonstrated using the input-to-state stability method. Simulation of the proposed observer is conducted using the MATLAB-Simulink tool. The obtained results are presented and analyzed to showcase the overall effectiveness of the proposed system. [ABSTRACT FROM AUTHOR]

AbstractBias-adjusted three-step latent class (LC) analysis is a popular technique for estimating the relationship between LC membership and distal outcomes. Since it is impossible to randomize LC membership, causal inference techniques are needed to estimate causal effects leveraging observational data. This paper proposes two novel strategies that make use of propensity scores to estimate the causal effect of LC membership on a distal outcome variable. Both strategies modify the bias-adjusted three-step approach by using propensity scores in the last step to control for confounding. The first strategy utilizes inverse propensity weighting (IPW), whereas the second strategy includes the propensity scores as control variables. Classification errors are accounted for using the BCH or ML corrections. We evaluate the performance of these methods in a simulation study by comparing it with three existing approaches that also use propensity scores in a stepwise LC analysis. Both of our newly proposed methods return essentially unbiased parameter estimates outperforming previously proposed methods. However, for smaller sample sizes our IPW based approach shows large variability in the estimates and can be prone to non-convergence. Furthermore, the use of these newly proposed methods is illustrated using data from the LISS panel. [ABSTRACT FROM AUTHOR]