Hasil untuk "Engineering economy"

José Peixoto, Alexis Gonzalez, Janki Bhimani et al.

Programmable caching engines like CacheLib are widely used in production systems to support diverse workloads in multi-tenant environments. CacheLib's design focuses on performance, portability, and configurability, allowing applications to inherit caching improvements with minimal implementation effort. However, its behavior under dynamic and evolving workloads remains largely unexplored. This paper presents an empirical study of CacheLib with multi-tenant settings under dynamic and volatile environments. Our evaluation across multiple CacheLib configurations reveals several limitations that hinder its effectiveness under such environments, including rigid configurations, limited runtime adaptability, lack of quality-of-service support and coordination, which lead to suboptimal performance, inefficient memory usage, and tenant starvation. Based on these findings, we outline future research directions to improve the adaptability, fairness, and programmability of future caching engines.

Soumen Majhi, Anna Mancini, Giulio Cimini

Assessing the resilience of the economy requires accounting for its intrinsic multi-layer nature, by assessing for instance how disruptions at the firm level spread through the production network and propagate to the banking sector. Methods exist to measure the reverberation of shocks over the multilayer network of supply-customer relations among firms, corporate loans of banks and their interbank market exposures. However, empirical network data are often privacy protected and thus inaccessible to researchers and regulators. In this work we develop an unified framework, combining state-of-the art techniques to reconstruct the whole multilayer structure of the economy from balance sheet information of banks and firms, as well as dynamics of shock propagation from the inter-firm to the interbank layers. We showcase application of our methodology using data of the Italian economy. We identify the most systemically important firms and industries, as well as the most vulnerable banks, further assessing the determinants of systemic risk -- obtaining results coherent with the empirical literature on network contagion. Overall, our framework allows performing detailed network-based stress tests on a digital twin of the economy, without requiring detailed network information that is difficult to acquire.

Jarosław Gawdzik, Jolanta Latosińska, Paulina Berezowska-Kominek et al.

The increasing cost of energy and the need for low-carbon solutions have strengthened interest in wastewater as a stable and underutilized source of recoverable heat. This study assesses the technical feasibility, economic viability, and environmental benefits of a wastewater heat recovery system based on a case study of the Gorzyce municipal wastewater treatment plant in Poland. Water-to-water heat pump configurations and application scenarios are analyzed together with data-driven forecasting of wastewater outflow using artificial neural networks (MLP and RBF). Operational data from 2025 were used to estimate thermal potential and support system sizing. RBF networks provided more accurate flow forecasts than MLP models, improving reliability of energy recovery planning. Results show that even with a 1 K cooling depth, the annual heat recovery potential reaches about 1.16 GWh. The proposed heat pump system achieved the COP values of 3.0–3.4 and seasonal COP around 3.2, confirming high technical performance supported by stable wastewater temperatures. The recovered heat can fully cover the facility’s heating demand, demonstrating clear technical feasibility. The economic analysis indicates annual savings of about EUR 2310 compared to gas heating, with a simple payback period of roughly 13 years, reduced to 7–8 years when combined with on-site photovoltaics. Environmental benefits include CO₂ emission reductions of about 5.5 tones per year. Overall, wastewater heat recovery supported by predictive modeling and renewable electricity is a practical, cost-effective, and environmentally friendly solution for municipal infrastructure.

Deniss Klauson, Erki Lember, Jaak Jaaku

The recent changes in the European Union Wastewater Directive require micropollutant elimination from the effluents of wastewater treatment plants serving at least 150 000 population equivalents, and in some cases even starting from 10 000. While ozonation can degrade micropollutants without secondary wastes, the treated effluent composition must be considered, specifically the concentration of bromide (Br–). Depending on its amount and oxidant dose, bromide can potentially be oxidised to carcinogenic bromate (BrO3–). This research investigates bromide amounts in the effluents of Estonian wastewater treatment plants serving at least 10 000 population equivalents as preliminary work for quaternary wastewater treatment aimed at micropollutant removal.

Saba Sanami, Amir G. Aghdam

Reliable aero-engine anomaly detection is crucial for ensuring aircraft safety and operational efficiency. This research explores the application of the Fisher autoencoder as an unsupervised deep learning method for detecting anomalies in aero-engine multivariate sensor data, using a Gaussian mixture as the prior distribution of the latent space. The proposed method aims to minimize the Fisher divergence between the true and the modeled data distribution in order to train an autoencoder that can capture the normal patterns of aero-engine behavior. The Fisher divergence is robust to model uncertainty, meaning it can handle noisy or incomplete data. The Fisher autoencoder also has well-defined latent space regions, which makes it more generalizable and regularized for various types of aero-engines as well as facilitates diagnostic purposes. The proposed approach improves the accuracy of anomaly detection and reduces false alarms. Simulations using the CMAPSS dataset demonstrate the model's efficacy in achieving timely anomaly detection, even in the case of an unbalanced dataset.

Jyh-An Lee

Internet and digital technologies have facilitated copyright sharing in an unprecedented way, creating significant tensions between the free flow of information and the exclusive nature of intellectual property. Copyright owners, users, and online platforms are the three major players in the copyright system. These stakeholders and their relations form the main structure of the copyright-sharing economy. Using China as an example, this paper provides a tripartite perspective on the copyright ecology based on three categories of sharing, namely unauthorized sharing, altruistic sharing, and freemium sharing. The line between copyright owners, users, and platforms has been blurred by rapidly changing technologies and market forces. By examining the strategies and practices of these parties, this paper illustrate the opportunities and challenges for China's copyright industry and digital economy. The paper concludes that under the shadow of the law, a sustainable copyright-sharing model must carefully align the interests of businesses and individual users.

Pan LI, Lulu ZHANG, Hai CHEN et al.

Driven by the “dual carbon” goal, biomass liquid fuel has emerged as a vital solution for expanding fossil fuel reserves, reducing greenhouse gas emissions, and combating global warming and climate change. Its prominent “carbon reduction” characteristics make it a compelling choice. Fuel ethanol, the most widely utilized bioliquid fuel globally, is a renewable green fuel derived from cellulose in biomass, such as agricultural waste and wood, through microbial fermentation. It is characterized by high vaporization heat, a high octane number, and cleaner combustion, making it suitable for commercial production. Therefore, the development of fuel ethanol is a critical energy strategy to address energy constraints and promote the sustainable development of the circular economy in China. Fuel ethanol production usually involves raw material pretreatment, cellulase hydrolysis, and microbial fermentation. However, various challenges still hinder large-scale production. This paper discusses the production processes of fuel ethanol and evaluates its lifecycle, focusing on its potential to reduce greenhouse gas emissions. It also summarizes the economic benefits of various ethanol production technologies. Initially, the basic principles and current status of ethanol technology are described, highlighting challenges in producing fuel ethanol from lignocellulosic biomass. These challenges include cell wall stubbornness, multistep pretreatment processes, extended hydrolysis time, degradation product generation, and high production costs. Future research will concentrate on developing a comprehensive suite of technologies designed to optimize low-energy, high-efficiency, and environmentally friendly pretreatment processes for raw materials. This includes creating cost-effective and high-performance hydrolases crucial for enhancing enzyme formulation efficiency in biomass conversion. Additionally, genetic engineering techniques will be employed to cultivate microbial strains that are resistant to both heat and inhibition. These engineered strains will efficiently utilize both pentose and hexose sugars, significantly improving ethanol yields. By integrating these innovative approaches, we aim to boost the overall efficiency of fuel ethanol production and contribute to a more sustainable biorefining process. Life cycle evaluation studies of fuel ethanol production technologies have shown that fuel ethanol plays an important role in mitigating climate change and achieving net zero emission targets by sequestering carbon fixed during biomass growth compared to fossil fuels. Among these, second-generation fuel ethanol performs best, followed by first- and third-generation fuel ethanol. Power consumption is a major contributor to acidification potential and global warming potential, indicating a need for new technologies or alternative power structures can be developed to reduce environmental impact. However, there are issues in the evaluation process, such as inconsistent system boundaries, insufficient data inventories, and diverse evaluation models, necessitating the establishment of a unified standard to further improve the life cycle evaluation system. In addition, a comprehensive analysis of the cost-effectiveness of various ethanol technologies was conducted through a comprehensive life cycle economic assessment. Current pricing makes second-generation fuel ethanol more expensive than gasoline, prompting a focus on improving the efficiency and affordability of cellulase while encouraging the production of high-value by-products. This paper aims to provide valuable insights for future research in fuel ethanol refining technology.

Amani Abdallah Hepautwa, Amani Abdallah Hepautwa, Yusufu A. C. Jande et al.

This paper investigates the application of circular economy principles by recycling spent coffee grounds (SCG) to produce coffee ash biochar (CAB), which is then used in the creation of burnt red soil bricks (BRSB) fired at temperatures between 900 °C and 1,100 °C, with 10% Montmorillonite as an additive (Al-Hasani, 2024; Cano and Reyes-Vallejo and Sánchez-Albores and Sebastian and Cruz-Salomón and d. Hernández-Cruz and et al., Sustainability, 2025, 17(1), 99; Chop, Investigation of Coal Combustion Residuals for Ceramic Applications and Production, 2024; Chung et al., Waste and Biomass Valorization, 2021, 12, 6273–6291; George, Electrical and mechanical characteristics of carbonaceous composites, 2023; Goswami and Kushwaha and Kafle and Kim, Catalysts, 2022, 12(8), 817). Comprehensive comparisons were made using coffee ash pyrolyzed at temperatures of 300 °C, 350 °C, and 500 °C, as substitutes for red soil at replacement levels of 5%, 10%, 15%, and 20%. The results indicated a decreasing trend in the mechanical properties of the burnt red soil bricks with increasing coffee ash content. Under optimal water-cement (w/c) ratios, the compressive strength (CS) of red soil bricks containing 5% SCG increased by 49.7% compared to the control when pyrolyzed at 350 °C. For bricks with 10% SCG, compressive strength improved by 53.5%, while flexural strength (FS) increased by 66.1% and splitting tensile strength (TS) rose by 38.4% when pyrolyzed at 300 °C. Additionally, the study found significant reductions in water, chloride, and sulfur penetration by 41.5%, 44.4%, and 34.3%, respectively, indicating improved durability and resistance to environmental factors. The water permeability coefficient remained relatively consistent across samples. This innovative approach addresses the disposal challenges of spent coffee grounds while benefiting both the economy and the environment. This study demonstrates the feasibility of incorporating SCG into burnt red soil bricks and examines the impact of SCG on their performance. Experimental results were analyzed through range analysis and analysis of variance to identify optimal combinations for varying performance requirements. Microstructural evaluations were performed using Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Differential Scanning Calorimetry (DSC) techniques (Singh and Patel, Journal of Material Cycles and Waste Management, 2025, 27(1), 170–192). These analyses provided insights into the structural integrity and bonding mechanisms within the composite materials. The findings suggest that SCG pyrolyzed at 300 °C and 350 °C, particularly at a 10% and 5% replacement level, delivers the best mechanical and chemical performance (Hanfi and Saftah and Alsufyani and Alqahtani and Mahmoud, Radiation Physics and Chemistry, 2025, 226; Mohammed and Joy and Zahid and Rafid, Journal of Materials in Civil Engineering, 2025, 37(5)). The study highlights the environmental benefits of using spent coffee grounds (SCG) in red soil brick manufacturing, reducing landfill waste and carbon emissions. This approach promotes resource efficiency and sustainable construction. Future work will focus on durability and scalability for industrial applications.

Serena Giorgi, Monica Lavagna

AbstractEuropean Member States are required to promote initiatives and programs to shift their traditional linear economy into circular economy. The paper shows the Italian initiatives towards circular economy in the built environment, across different application level (national and local) and different drivers (top-down and bottom-up). The method of investigation regards an on-field research based on direct dialogue with various stakeholders of construction sector in the national context. The results show the current barriers to circular material flows and the successful initiatives in Italy. Firstly, the top-down strategies are reported, as well as existing standards, national regulations and local policy. Secondly, the bottom-up strategies are shown, stressing the local stakeholders involvement. Based on the discussion, potential improvements are highlighted to align the current Italian initiatives with the broader European Commission circular economy objectives, considering also the best practices developed in other European countries.

Yao Fu, Rameswar Panda, Xinyao Niu et al.

We study the continual pretraining recipe for scaling language models' context lengths to 128K, with a focus on data engineering. We hypothesize that long context modeling, in particular \textit{the ability to utilize information at arbitrary input locations}, is a capability that is mostly already acquired through large-scale pretraining, and that this capability can be readily extended to contexts substantially longer than seen during training~(e.g., 4K to 128K) through lightweight continual pretraining on appropriate data mixture. We investigate the \textit{quantity} and \textit{quality} of the data for continual pretraining: (1) for quantity, we show that 500 million to 5 billion tokens are enough to enable the model to retrieve information anywhere within the 128K context; (2) for quality, our results equally emphasize \textit{domain balance} and \textit{length upsampling}. Concretely, we find that naively upsampling longer data on certain domains like books, a common practice of existing work, gives suboptimal performance, and that a balanced domain mixture is important. We demonstrate that continual pretraining of the full model on 1B-5B tokens of such data is an effective and affordable strategy for scaling the context length of language models to 128K. Our recipe outperforms strong open-source long-context models and closes the gap to frontier models like GPT-4 128K.

Lora E. Fleming, Philip J. Landrigan, Oliver S. Ashford et al.

A healthy ocean is essential for human health, and yet the links between the ocean and human health are often overlooked. By providing new medicines, technologies, energy, foods, recreation, and inspiration, the ocean has the potential to enhance human health and wellbeing. However, climate change, pollution, biodiversity loss, and inequity threaten both ocean and human health. Sustainable realisation of the ocean’s health benefits will require overcoming these challenges through equitable partnerships, enforcement of laws and treaties, robust monitoring, and use of metrics that assess both the ocean’s natural capital and human wellbeing. Achieving this will require an explicit focus on human rights, equity, sustainability, and social justice. In addition to highlighting the potential unique role of the healthcare sector, we offer science-based recommendations to protect both ocean health and human health, and we highlight the unique potential of the healthcare sector tolead this effort.

Bahodirhon Safarov, Akmal Amirov, Nargiza Mansurova et al.

For every nation, the era of transition to a market economy is marked by a severe lack of financial resources. Bringing in sectors of the economy that yield the fastest and most efficient returns is one strategy to develop and overcome this issue. Agrotourism, which is seen as a new trend in the tourism business, is one of these industries. The Samarkand region is used as an example to examine the scientific and theoretical underpinnings of agrotourism as well as its geographical characteristics in this article. Furthermore, an agrotourism map of the region was created by evaluating each location’s potential for agrotourism, classifying the regions based on how desirable they are for agrotourism, and identifying the facilities and resources available for agrotourism. Factors affecting the market of tourist services in the area were studied, and forecast values of the volume of tourist services were determined.

Xiongying Yan, Weiwei Bao, Yalun Wu et al.

Abstract The development and implementation of microbial chassis cells have profound impacts on circular economy. Non-model bacterium Zymomonas mobilis is an excellent chassis owing to its extraordinary industrial characteristics. Here, the genome-scale metabolic model iZM516 is improved and updated by integrating enzyme constraints to simulate the dynamics of flux distribution and guide pathway design. We show that the innate dominant ethanol pathway of Z. mobilis restricts the titer and rate of these biochemicals. A dominant-metabolism compromised intermediate-chassis (DMCI) strategy is then developed through introducing low toxicity but cofactor imbalanced 2,3-butanediol pathway, and a recombinant D-lactate producer is constructed to produce more than 140.92 g/L and 104.6 g/L D-lactate (yield > 0.97 g/g) from glucose and corncob residue hydrolysate, respectively. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) demonstrate the commercialization feasibility and greenhouse gas reduction capability of lignocellulosic D-lactate. This work thus establishes a paradigm for engineering recalcitrant microorganisms as biorefinery chassis.

Medvedeva Yulia, Kolgan Maria, Simonyan Tatyana et al.

The article considers approaches to the concept of business model of business activity, considers its modern content in the context of taking into account the peculiarities and using the advantages of the digital economy. An analytical review of business models currently used by domestic and foreign companies with the allocation of e-commerce and innovation models is made. It is proven that the improvement of existing business models or the creation of new ones should be carried out through the re-engineering of their business processes. The classification of business processes according to various classification features which can be used in the process of reengineering, is given. Reengineering as a method of radical redesign of the company's business model, taking into account the main trends in the development of modern economy and the signals of key stakeholders is characterized in detail. Based on the results of the research, a conceptual model of hybrid reengineering for market adaptation of business models of Russian enterprises to the conditions of market economy is developed. Promising directions of its improvement were identified for all the main structural elements forming its integrity and synergetic character.

Edyta Kruk, Wiktor Halecki, Agnieszka Petryk et al.

To evaluate the quality of watercourses in the Western part of Carpathians from a hydro-chemical perspective, a systematic approach is required. This involves gradually excluding factors that contribute to the washing, mixing, and transportation of contaminants in the watercourse pathway. The model that considers spatial dependencies by autoregression was implemented in this study to determine the correlation between hydrodynamic and physico-chemical characteristics of waters at surface in different groups and forms of catchment use. The surface water at forested areas had the maximum average shear stress of 0.178 N∙m−2. The watercourse at sustained grassland had the maximum average Reynolds number (Re) of 23,654 and the minimum number of 0.426 at arable lands. Spatial autoregression analysis revealed space-time relations in various measurement points. When constructing the space-physical model, it is important to consider the influence of hydraulic characteristic parameters on the generation of physicochemical indicators in the flysch basin. Specifically, it may be beneficial to take into account the turbulent diffusion coefficient. The autoregression analysis demonstrated that for the ions P-PO43− and K+ in surface water on cropland and for total iron and the cation K+ ion grassland (p < 0.05), the turbulent diffusion coefficient proved to be of great importance. The study did not identify any physicochemical dependency for woodland surface waters. The findings can be utilised to create an erosion model that considers the contribution of material supply in a catchment area, specifically from weathered Carpathian flysch or surface runoff, to the alimentation of alluvial deposits.

Weijian Jin, Yajing Zhang

Cross-Department Coordination of Emergency Management (CDCEM) is considered a critical dimension in China to solve the problem of emergency management. The Decision Experiment and Decision-Making Trial and Evaluation Laboratory (DEMATEL) is a method used to build the structural correlation of criteria in uncertain environments to identify critical success factors (CSFs). There are coupling correlations and one-way correlations for interrelationship comparisons between selected factors of CDCEM. Therefore, there are two different assessment scales. However, most previous studies applied the DEMATEL method with a single assessment scale to identify CSFs. To fill this gap, an IFS-IVIFS-DEMATEL method is provided to comprehensively identify the CSFs of CDCEM in this study. The intuitionistic fuzzy set (IFS) is regarded as the assessment scales of coupling correlation, and the interval-valued intuitionistic fuzzy set (IFIVS) is regarded as the assessment scales of one-way correlation. The two different types of assessment scales were transformed into interval information in the improved approach. Then, using the conduction correlation among factors, a comprehensive correlation matrix was constructed. After that, the ranking of the central degree and cause degree of the factors according to the traditional DEMATEL method was obtained. Finally, a case study of Nanjing’s CDCEM was illustrated to demonstrate that the proposed method is more suitable and reasonable. It is found that the factors of “cross-department organization”, “cross-department information communication and transmission”, “information sharing technology platform”, “cross-department material supply capability”, and “cross-department prediction and early warning” in Nanjing are CSFs in CDCEM, which should be emphasized to strengthen CDCEM. The findings of this study shed light on the cross-department coordination of emergency management mechanisms in uncertain situations, which would be beneficial for improving the efficiency of governmental management.

Shuang Wu, Bo Yu, Shaoshan Liu et al.

With the advancement of robotics and AI technologies in the past decade, we have now entered the age of autonomous machines. In this new age of information technology, autonomous machines, such as service robots, autonomous drones, delivery robots, and autonomous vehicles, rather than humans, will provide services. In this article, through examining the technical challenges and economic impact of the digital economy, we argue that scalability is both highly necessary from a technical perspective and significantly advantageous from an economic perspective, thus is the key for the autonomy industry to achieve its full potential. Nonetheless, the current development paradigm, dubbed Autonomy 1.0, scales with the number of engineers, instead of with the amount of data or compute resources, hence preventing the autonomy industry to fully benefit from the economies of scale, especially the exponentially cheapening compute cost and the explosion of available data. We further analyze the key scalability blockers and explain how a new development paradigm, dubbed Autonomy 2.0, can address these problems to greatly boost the autonomy industry.

Jian-An Li, Li Wang, Wen-Jie Xie et al.

Pesticides are a kind of agricultural input, whose use can greatly reduce yield loss, regulate plant growth, effectively liberate agricultural productivity, and improve food security. The availability of pesticides in economies all over the world is ensured by pesticide redistribution through international trade and economies play different roles in this process. In this work, we measure and rank the importance of economies using nine node metrics in an evolutionary way. It is found that the clustering coefficient is correlated negatively with the other eight node metrics, while the other eight node metrics are positively correlated with each other and can be grouped into three communities (betweenness; in-degree, PageRank, authority, and in-closeness; out-degree, hub, and out-closeness). We further investigate the structural robustness of the international pesticide trade networks proxied by the giant component size under three types of shocks to economies (node removal in descending order, randomly, and in ascending order). The results show that, except for the clustering coefficient, the international pesticide trade networks are relatively robust under shocks to economies in ascending orders and randomly, but fragile under shocks to economies in descending order. In contrast, removing nodes with the clustering coefficient in ascending and descending orders gives similar robustness curves. Moreover, the structural robustness related to the giant component size evolves over time and exhibits an inverse U-shaped pattern.

Diana C. Hernández-Jaramillo, Rafael E. Vásquez

The Blue Economy, which is based on the sustainable use of the ocean, is demanding better understanding of marine ecosystems, which provide assets, goods, and services. Such understanding requires the use of modern exploration technologies, including unmanned underwater vehicles, in order to acquire quality information for decision-making processes. This paper addresses the design process for an underwater glider, to be used in oceanographic research, that was inspired by leatherback sea turtles (<i>Dermochelys coriacea</i>), which are known to have a superior diving ability and enhanced hydrodynamic performance. The design process combines elements from Systems Engineering and bioinspired design approaches. The conceptual and preliminary design stages are first described, and they allowed mapping the user’s requirements into engineering characteristics, using quality function deployment to generate the functional architecture, which later facilitated the integration of the components and subsystems. Then, we emphasize the shell’s bioinspired hydrodynamic design and provide the design solution for the desired vehicle’s specifications. The bioinspired shell yielded a lift coefficient increase due to the effect of ridges and a decrease in the drag coefficient at low angles of attack. This led to a greater lift-to-drag ratio, a desirable condition for underwater gliders, since we obtained a greater lift while producing less drag than the shape without longitudinal ridges.