Search Results (300)

This paper reports on the use of acetyl-L-valine (Ac-Val) as an effective and precise pH modifier for inducing hydrogel formation. Ac-Val offers several advantages: it is fully water-soluble, overcoming dissolution issues, and allows for stock solution preparation to fine-tune trigger volume and final material pH. As a weaker carboxylic acid compared to inorganic acids, Ac-Val enables more controlled pH variation. For comparison, a commercial lactic acid (LA) solution was also evaluated. The reliability of Ac-Val as a pH modifier was tested on three amino acid derivatives—Boc-Dopa(Bn)₂-OH, Lau-Dopa(Bn)₂-OH, and Pal-Phe-OH, all known to be efficient gelators. These molecules, sharing common structural features, form gels varying in transparency, robustness, and elasticity. Notably, Pal-Phe-OH is a supergelator. A key benefit of Ac-Val lies in its ability to cause an instantaneous pH modification, allowing for precise pH adjustment before the gel network forms. This pH-change approach with Ac-Val demonstrates broad applicability, enabling the creation of gels with tailored pH values for various acidic molecules, which is particularly valuable for applications like drug delivery where specific pH environments are crucial. Full article

Artificial intelligence technologies, particularly machine learning and computer vision, are being increasingly utilized to preserve, restore, and create immersive virtual experiences with cultural artifacts and sites, thus aiding in conserving cultural heritage and making it accessible to a global audience. This paper examines the performance of Generative Adversarial Networks (GAN), especially Style-Based Generator Architecture (StyleGAN), as a deep learning approach for producing realistic images of Egyptian monuments. We used Sigmoid loss for Language–Image Pre-training (SigLIP) as a unique image–text alignment system to guide monument generation through semantic elements. We also studied truncation methods to regulate the generated image noise and identify the most effective parameter settings based on architectural representation versus diverse output creation. An improved discriminator design that combined noise addition with squeeze-and-excitation blocks and a modified MinibatchStdLayer produced 27.5% better Fréchet Inception Distance performance than the original discriminator models. Moreover, differential evolution for latent-space optimization reduced alignment mistakes during specific monument construction tasks by about 15%. We checked a wide range of truncation values from 0.1 to 1.0 and found that somewhere between 0.4 and 0.7 was the best range because it allowed for good accuracy while retaining many different architectural elements. Our findings indicate that specific model optimization strategies produce superior outcomes by creating better-quality and historically correct representations of diverse Egyptian monuments. Thus, the developed technology may be instrumental in generating educational and archaeological visualization assets while adding virtual tourism capabilities. Full article

This theoretical essay aims to analyze some of the socio-economic innovations introduced by Platform Capitalism Specifically, it focuses on two main aspects: first, the digital platform as a radical organizational innovation. Digital platforms represent a structural novelty in the market economy, signaling a new organization of production and labor. Second, the essay examines the role of platforms in directly generating value through the concept of “network value”. To this end, it explores the function of “business intelligence” as a strategic and competitive tool. Finally, the paper discusses the key issues associated with platform capitalism, which could threaten its social sustainability and contribute to economic and financial instability. These issues include the increasing commodification of everyday activities, the devaluation of paid labor in favor of free production driven by platform users (the so-called prosumers), and the emergence of proprietary and financial monopolies. Hence, digital platforms do not inherently ensure comprehensive social and environmental sustainability unless supported by targeted economic policy interventions. Conclusively, it is emphasized that defining robust social welfare frameworks—which account for emerging value creation processes—is imperative. Simultaneously, policymakers must incentivize the proliferation of cooperative platforms capable of fostering experimental circular economy models aligned with ecological sustainability. Full article

In the context of algorithm selection, the careful design of benchmark functions and problem instances plays a pivotal role in evaluating the performance of optimization methods. Traditional benchmark functions have been criticized for their limited resemblance to real-world problems and insufficient coverage of the problem space. Exploratory landscape analysis (ELA) offers a systematic framework for characterizing objective functions, based on quantitative landscape features. This study proposes a method for generating benchmark functions tailored to single-objective continuous optimization problems with boundary constraints using predefined ELA feature vectors to guide their construction. The process begins with the creation of random decision variables and corresponding objective values, which are iteratively adjusted using the covariance matrix adaptation evolution strategy (CMA-ES) to ensure alignment with a target ELA feature vector within a specified tolerance. Once the feature criteria are met, the resulting topological map point is used to train a neural network to produce a surrogate function that retains the desired landscape characteristics. To validate the proposed approach, functions from the well-known Black Box Optimization Benchmark (BBOB) suite are replicated, and novel functions are generated with unique ELA feature combinations not found in the original suite. The experiment results demonstrate that the synthesized landscapes closely resemble their BBOB counterparts and preserve the consistency of the algorithm rankings, thereby supporting the effectiveness of the proposed approach. Full article

A reliable prediction of the remaining useful life of critical electronic components, such as insulated gate bipolar transistors, is necessary for preventing failures in many industrial applications. Recently, diverse machine-learning techniques have been used for this task. However, they are generally focused on capturing the temporal dependencies or on representing the probabilistic nature of the degradation of the device. This work proposes a neural network architecture that combines long short-term memory and mixture density networks to address both targets simultaneously when modeling the remaining useful life. The proposed model was trained and evaluated using a real dataset of insulated gate bipolar transistors, demonstrating a high capacity for predicting the remaining useful life of the validation devices. The proposed model outperformed the other algorithms considered in the study in terms of root mean squared error and coefficient of determination. In general terms, an average reduction of at least 18% of the root mean squared error was obtained when compared with the second-best model among those considered in this work, but in some specific cases, the root mean squared error during the prediction of remaining useful life decreased up to 21%. In addition to the high performance obtained, the characteristics of the network output also facilitated the creation of confidence intervals, which are more informative than solely exact values for decision-making. Full article

Collaborative business ecosystems (CBEs) are increasingly exposed to disruptive events (e.g., pandemics, supply chain breakdowns, cyberattacks) that challenge organizational adaptability and value creation. Traditional approaches to resilience and robustness often fail to capture the full range of systemic responses. This study introduces a unified mathematical framework to evaluate four crisis response modes—plasticity, resilience, transformative resilience, and antifragility—within complex adaptive networks. Grounded in complex systems and collaborative network theory, our model formalizes both internal organizational capabilities (e.g., adaptability, learning, innovation, structural flexibility) and strategic interventions (e.g., optionality, buffering, information sharing, fault-injection protocols), linking them to pre- and post-crisis performance via dynamic adjustment functions. A composite performance score is defined across four dimensions (Innovation, Contribution, Prestige, and Responsiveness to Business Opportunities), using capability–strategy interaction matrices, weighted performance change functions, and structural transformation modifiers. The sensitivity analysis and scenario simulations enable a comparative evaluation of organizational configurations, strategy impacts, and phase-transition thresholds under crisis. This indicator-based formulation provides a quantitative bridge between resilience theory and practice, facilitating evidence-based crisis management in networked business environments. Full article

The worldwide need for energy as well as environmental challenges have promoted the creation of sustainable power solutions. The combination of different working fluids is used for an organic Rankine cycle-powered vapor compression cycle (ORC-VCC) to deliver cooling applications. The selection of an appropriate working fluid significantly impacts system performance, efficiency, and environmental impact. The research evaluates possible working fluids to optimize the ORC-VCC system. Firstly, Artificial Neural Network (ANN)-derived models are used for exergy destruction ( E d t o t ) and heat exchanger total heat transfer capacity ( U A t o t ). Later on, multi-objective optimization was carried out using the acquired models for E d t o t and U A t o t using the Genetic Algorithm (GA) followed by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The optimization results showcase Decane ORC-R600a VCC as the best candidate for the ORC-VCC system; the values of E d t o t and U A t o t were found to be 24.50 kW and 6.71 kW/K, respectively. The research data show how viable it is to implement biogas-driven ORC-VCC systems when providing air conditioning capabilities. Full article

This study explored the impact of network structure on conflict and project value creation. Network density and network centrality are two network structure dimensions. A survey was undertaken among professionals working in Chinese construction projects. A total of 308 surveys were analyzed using the structural equation model. The results revealed that network centrality has a negative impact on project value creation while network density has a positive impact. Network centrality has a negative impact on substantive conflicts but a positive impact on affective conflicts. The link between centrality and project value creation is weakened by substantive conflict but strengthened by affective conflict. This research gives a new direction for construction project governance and project value management. Furthermore, this research validates the constructive role of substantive conflicts, as well as the destructive impact of affective conflicts, thereby adding to the literature on conflict governance. Full article

Quantum money represents an innovative approach to currency by encoding economic value within the quantum states of physical systems, utilizing the principles of quantum mechanics to enhance security, integrity, and transferability. This perspective article explores the definition and properties of quantum money. We analyze the process of transferring quantum money via quantum teleportation, using terrestrial and satellite-based quantum networks. Furthermore, we consider the impact of quantum money on the modern banking system, particularly in money creation. Finally, we conduct an analysis to assess the strengths and weaknesses of quantum money, as well as opportunities and threats associated with this emerging concept. Full article

Against the backdrop of the energy crisis and a rapidly advancing digital economy, electricity–computing synergy has become a strategic pathway to resolve energy constraints in computing power center and overcome renewable energy consumption challenges. This study breaks through the existing single-factor fragmented analysis method and systematically constructs a vertically progressive and horizontally coupled electricity–computing synergy planning model to deconstruct the core elements of computing power center construction and reconstruct the path of electricity–computing value co-creation. It proposes a multi-objective site selection decision-making method for computing power center based on linear weighting and the principle of reusability and universality, effectively avoiding the problem of overall system efficiency loss caused by single-objective optimization. Based on the empirical results from data from 31 provinces in China, this study classifies the endowments for computing power center construction, conducts targeted analyses of each province’s situation, and finds three major contradictions facing China’s computing power center: a spatial mismatch between green energy resources and service demand, a dynamic imbalance between electricity price advantages and comprehensive costs, and structural contradictions between talent reserves and sustainable development. Finally, a multi-dimensional integrated strategy was systematically constructed, encompassing demand-driven initiatives, electricity price adjustments, talent innovation, natural cold-source activation, and network upgrades, to provide guidance and policy toolkits for the government planning of computing power infrastructure development. Full article

The dependence of conventional epoxy resins on fossil fuels and the environmental and health hazards associated with bisphenol A (BPA) demand the creation of sustainable alternatives. Because lignin is a natural resource and has an aromatic ring skeleton structure, it could be used as an alternative to fossil fuels. This study effectively resolved this challenge by utilizing a sustainable one-step epoxidation process to transform lignin into a bio-based epoxy resin. The results verified the successful synthesis of epoxidized bamboo lignin through systematic characterization employing Fourier transform infrared spectroscopy, hydrogen spectroscopy/two-dimensional heteronuclear single-quantum coherent nuclear magnetic resonance, quantitative phosphorus spectroscopy, and gel permeation chromatography. Lignin-based epoxy resins had an epoxy equivalent value of 350–400 g/mol and a weight-average molecular weight of 4853 g/mol. Studies on the curing kinetics revealed that polyetheramine (PEA-230) demonstrated the lowest apparent activation energy (46.2 kJ/mol), signifying its enhanced curing efficiency and potential for energy conservation. Mechanical testing indicated that the PEA-230 cured network demonstrated the maximum tensile strength (>25 MPa), whereas high-molecular-weight polyetheramine (PEA-2000) imparted enhanced elongation to the material. Lignin-based epoxy resins demonstrated superior heat stability. This study demonstrates the conversion of bamboo lignin into bio-based epoxy resins using a simple, environmentally friendly synthesis process, demonstrating the potential to reduce fossil resource use, efficiently use waste, develop sustainable thermosetting materials, and promote a circular bioeconomy. Full article

This research is focused on water governance problems in La Marina Alta District, in the province of Alicante (southeastern Spain). The district has a public management body, Consorcio de Abastecimiento y Saneamiento de Aguas de los Municipios de La Marina Alta (CASAMA), which has been inoperative since its creation in 1987. Although La Marina Alta has sufficient water resources in situations of hydrological normality, they are significantly affected by the impacts of climate change, insufficient water treatment technology and the absence of storage and regulation infrastructure. As a consequence, periods of scarcity and overexploitation of aquifers, together with high-demand situations, have generated scenarios of a lack of drinking water with reputational damage and uncertainty for the future of agricultural operations. Thus, the aim of this work is to propose the adoption of integrated water resource management strategies that will increase the resilience of this sub-basin in La Marina Alta. To this end, the contribution of new non-conventional resources to the water pool, combined with an efficient network of infrastructure, and all this supported by effective governance structures, would be essential to achieve a sustainable balance between demand and supply, preserving the environmental values of the territory. Full article

The growing importance of customer experience management (CEM) in the tourism sector has led to a proliferation of research interests in satisfaction enhancement, loyalty, and value co-creation. This study proposes a systematic and exhaustive thematic and bibliometric analysis of 3874 articles on CEM in the tourism industry published in the Scopus database between 1979 and 2024. Following the guidelines of the PRISMA protocol, the study uses Bibliometrix (version 4.4.1) in R and VOSviewer (version 1.6.20) to map publication trends, author networks, thematic and chronological evolution, and influential contributions. A qualitative content analysis of the most cited works, guided by grounded theory, revealed the main antecedents, consequences, mediators, and moderators of customer experience management. This analysis is embodied in the proposal of a conceptual model that illustrates the dynamic relationship between these elements and provides the basis for future research for theoretical enrichment and empirical validation. The results offer actionable insights for academics and industry practitioners alike, with the aim of promoting authentic and memorable tourism experiences. Full article

The emphasis on collaborative governance and effective leadership to bring any social change is gaining prominence among researchers. This study investigates how leadership and collaborative governance can drive social change in waste management in Campania, using a qualitative, multi-site case study approach. Interviews of relevant politicians, public managers, citizens, waste management organizations and academics were conducted (2023–2024). This research uses the lens of multiple theoretical frameworks such as collaborative governance, network agency, public value framework and transformational leadership to explore different dynamics of the research such as stakeholder engagement, public value creation and leadership effectiveness in waste management. Moreover, several obstacles in the way of achieving social change in Campania concerning waste management and environmental sustainability are identified. The findings of this study added to the theoretical understanding of collaborative governance and social change through the demonstration of how transformational leadership, stakeholder participation and trust-based relationships drive good waste management while identifying structural limitations such as corruption and organized crime that hindered governance. Practically, it highlights five interconnected themes from interviews of leadership that civic leaders and managers must establish to promote positive social change: Difficulties in leadership effectiveness, civic potential unused, media mobilization, hope for a miracle and stakeholder engagement diversification. The public value framework is used to analyze the potential role of leadership in bringing change in society. The research findings are replicable and can be applied to a similar set of circumstances. This study advances existing research by addressing the gap in understanding how collaborative governance and transformational leadership can be integrated to tackle waste management and environmental sustainability challenges. The findings can be applied to other regions facing similar governance challenges, making it relevant for global sustainability efforts. Italy’s government has green-lighted projects to make these activities more visible while downplaying their negative impacts on the environment and public health. Full article

This paper analyzes the exploitability, economic viability, and impact of fleet-based 5G network extensions implemented in maritime environments, focusing on the Baltic Sea and Mediterranean as a case study. Through cost–benefit analysis and business model validation, we demonstrate how multi-hop 5G connectivity can reduce communication costs while improving service quality for maritime operators. Our findings indicate that implementing vessel-based 5G relay stations can achieve 80–90% coverage in key maritime corridors with a break-even period of 2–3 years. The study reveals that combining vessel-to-vessel relaying with strategic floating base stations can reduce connectivity costs by up to 40% compared to traditional satellite solutions, while enabling new revenue streams through premium services. We provide a detailed economic framework for evaluating similar implementations across different maritime routes and suggest policy recommendations for facilitating cross-border 5G maritime networks and introduce key use cases value creation for network extension. Full article