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Modernity is characterised by a specific scientific paradigm based on binary logic. Neither freedom nor creativity have a place in this logical model. On the contrary, triadic logic enables rational consideration of an anthropological and social model compatible with both things: freedom and creativity, and therefore with Christianity. Furthermore, triadic logic provides us with a model of thought compatible with the current physical explanation of reality. [ABSTRACT FROM AUTHOR]

Sustainable waste management strategies are urgently needed due to an increasing global population and increased waste production. In this context, biorefineries have recently emerged as a promising approach to valorize waste streams and supply a broad range of products. This study presents the process model and life cycle assessment (LCA) of a biorefinery concept using a novel biochemical method, a so-called "dark photosynthesis" conversion. This process is coupled to a photo-fermentation using microalgae. Overall, the biorefinery concept can produce hydrogen, lutein, β-carotene, and proteins for animal feed. Apple pomace from apple juice production is used as feedstock for the primary conversion step. A process model was created with the process simulation software Aspen Plus® using experimental and literature data. Results from this model were then used in an LCA. The environmental impacts of the proposed biorefinery concept are relatively high, showing the need for process optimization in several areas. Energy system integration, stream recycling, and higher hydrogen yields are recognized as especially important for improving the environmental performance of this concept. Despite these findings, the model shows the feasibility of implementing the biochemical conversion technologies in a biorefinery concept for effectively utilizing residue streams. [ABSTRACT FROM AUTHOR]

This paper presents a novel decision-making framework for the life cycle management of aircraft components, integrating advanced data analytics, artificial intelligence, and predictive maintenance strategies. The proposed model addresses the challenges of balancing safety, reliability, and cost-effectiveness in aircraft maintenance. By using real-time health monitoring systems, failure probability models, and economic analysis, the framework enables more informed and dynamic maintenance strategies. The model incorporates a comprehensive approach that combines reliability assessment, economic analysis, and continuous re-evaluation to optimize maintenance, replacement, and life extension decisions. The optimization method on the base of genetic algorithm (GA) is employed to minimize total life cycle costs while maintaining component reliability within acceptable thresholds. The framework's effectiveness is demonstrated through case studies on three distinct aircraft components: mechanical, avionics, and engine. These studies showcase the model's versatility in handling different failure patterns and maintenance requirements. This study introduces a data-driven decision-making framework for optimizing the life cycle management of aircraft components, focusing on reliability, cost-effectiveness, and safety. To achieve optimal maintenance scheduling and resource allocation, a GA is employed, allowing for an effective exploration of complex solution spaces and enabling dynamic decision-making based on real-time data inputs. The GA-based optimization approach minimizes total life cycle costs while maintaining component reliability, with the framework's effectiveness demonstrated through case studies on key aircraft components. Key findings from the case study demonstrate significant cost reductions through optimization, with mechanical components showing a 10% more reduction in total life cycle costs, avionics components achieving a 14% more cost reduction, and engine components demonstrating a 7% more decrease in total costs. The research also presents an optimized dynamic maintenance schedule that adapts to real-time component health data, extending component lifespans and reducing unexpected failures. The framework effectively addresses key industry challenges such as no fault found events while minimizing unexpected failures and enhancing the overall reliability and safety of aircraft maintenance practices. Sensitivity analysis further demonstrates the model's robustness, showing stable performance under varying failure rates, maintenance costs, and degradation rates. The study contributes a scalable approach to predictive maintenance, balancing safety, cost, and resource allocation in dynamic operational environments. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau is the main permafrost area in China. Concrete structures constructed on permafrost are affected by the early negative-temperature environment. In particular, the negative-temperature environment seriously affects the strength growth process and the frost resistance of concrete (FRC). Therefore, this study considered the influence of the gas content, water–binder ratio (w/b), age, and other factors on the strength variation law and FRC under −3 °C curing conditions. Nuclear magnetic resonance (NMR) was used to analyze the pore structure of concrete before and after freeze–thaw cycles (FTCs). The results showed that the compressive strength of the concrete (CSC) under −3 °C curing was only 57.8–86.4% of that cured under standard conditions. The CSC under −3 °C curing showed an obvious age-lag phenomenon. The FRC under −3 °C curing was much lower than that under standard curing. The porosity of the concrete under −3 °C curing was greater, with a higher percentage of harmful and multi-harmful pores than that under standard curing. The concrete properties deteriorated primarily because curing at −3 °C hindered the hydration reaction compared with standard methods. This hindrance resulted in diminished hydration development, weakening the concrete's structural integrity. Under both curing conditions, when the gas content was between 3.2% and 3.8%, the frost resistance was the best. This is because a gas content within this range effectively enhances the internal pore structure, therefore relieving the swelling pressure caused by FTCs. Based on the freeze–thaw damage (FTD) model proposed by previous authors, a new model for the CSC under −3 °C curing reaching that of the concrete under standard curing for 28 d was established in this study. This advanced model was capable of accurately assessing the FTD of concrete structures in permafrost regions. Finally, the life expectancy of concrete in Northwest China was predicted. The life of the concrete reached 46.9 years under standard curing, while the longest life of the concrete under −3 °C curing was only 12.9 years. Therefore, attention should be paid to constructing and curing concrete structures in cold environments. [ABSTRACT FROM AUTHOR]

The semiconductor industry is a rapidly growing sector. As collection technologies for production data continue to improve and the Internet of Things matures, production data analysis improves, thus accelerating progress towards smart manufacturing. This not only enhances the process quality, but also increases product lifetime and reliability. Under the assumption of exponential distribution, the ratio of lifetime and warranty has been proposed as a lifetime performance index for electronic products. As unknown parameters of the index, to use point estimates to assess lifetime performance may cause misjudgment due to sampling errors. In addition, cost and time limitations often lead to small sample sizes that can affect the results of the analysis. Type-II censored data are widely applied in production and manufacturing engineering. Thus, this paper proposes an unbiased and consistent estimator of lifetime performance based on type-II censored data. The 100(1 − α)% confidence interval of the proposed index is derived based on its probability density function. Overly small sample sizes not only make the length estimates of lifetime performance index intervals for electronic products too long, but they also increase sampling errors, which distort the estimation and test results. We therefore used the aforementioned interval to construct a fuzzy test model for the assessment of product lifetime and further help manufacturers to be more prudent and precise to evaluate the performance of product life cycles. A numerical example illustrates the applicability of the proposed model. [ABSTRACT FROM AUTHOR]

Cement is one of the most produced materials globally. Population growth and urbanization cause an increased demand for the cement needed for expanding infrastructures. As a result of this circumstance, the cement industry must find the optimum compromise between increasing cement production and reducing the negative environmental impact of that production. Since cement production uses a lot of energy, resources and raw materials, it is essential to assess its environmental impact and determine methods for the sector to move forward in sustainable ways. This paper uses an integrated life cycle assessment (LCA) and a system dynamics (SDs) model to predict the long-term environmental impact and future dynamics of cement production in South Africa. The first step used the LCA midpoint method to investigate the environmental impact of 1 kg of Portland cement produced in South Africa. In the cement production process, carbon dioxide (CO2), nitrogen oxides (NOx), sulphur dioxide (SO2), methane (CH4) and particulate matter (PM) were the major gases emitted. Therefore, the LCA concentrated on the impact of these pollutants on global warming potential (GWP), ozone formation, human health, fine particulate matter formation and terrestrial acidification. The system dynamics model is used to predict the dynamics of cement production in South Africa. The LCA translates its results into input variables into a system dynamics model to predict the long-term environmental impact of cement production in South Africa. From our projections, the pollutant outputs of cement production in South Africa will each approximately double by the year 2040 with the associated long-term impact of an increase in global warming. These results are an important guide for South Africa's future cement production and environmental impact because it is essential that regulations for cement production are maintained to achieve long-term environmental impact goals. The proposed LCA–SD model methodology used here enables us to predict the future dynamics of cement production and its long-term environmental impact, which is the primary research objective. Using these results, a number of policy changes are suggested for reducing emissions, such as introducing more eco-blended cement productions, carbon budgets and carbon tax. [ABSTRACT FROM AUTHOR]

Although the construction industry has the potential to implement circular economy (CE) principles, the sector suffers from a veritable lack of initiatives to develop circular and regenerative design principles. However, existing buildings intended to be demolished could be considered as material banks for future constructions, with the aim to exploit anthropogenic resources, extend material/product efficiency, and reduce the extraction of natural resources. This concept of buildings as material banks is being studied more and more in the scientific literature, but it still requires the existing building stock to be fully digitalized, thus making materials reusable in new buildings starting from the architectural design stage. Moreover, the decision process regarding CE strategies requires the consideration of the environmental impacts of the deconstruction and end-of-life processes, which is essential in CE implementation. This paper introduces a digital platform for generating materials inventory and supporting the definition of reuse strategies. Then, by using digital tools in combination with life cycle assessment (LCA) studies of the deconstruction process and output of materials and components inventories, a method is defined and tested on a pilot building in Luxembourg. [ABSTRACT FROM AUTHOR]

Fine and ultrafine grinding of limestone are frequently used in the pharmaceutical, chemical, construction, food, and cosmetic industries, however, research investigations have not yet been published on the combination of energy and life cycle modeling. Therefore, the first aim of this research work was the examination of main grinding parameters of the limestone particles to determine an empiric energy-model. Dry and wet grinding experiments have been carried out with a Bond mill and a laboratory stirred ball mill. During the grinding processes, the grinding time and the filling ratio have been adjusted. The second goal of this research assessed the resources, emissions and environmental impacts of wet laboratory grinding with the help of life cycle assessment (LCA). The life cycle assessment was completed by applying the GaBi 8.0 (version: 10.5) software and the CML method. As a result of research, the determination of an empiric energy-model allowed to develop an estimated particle size distribution and a relationship between grinding fineness and specific grinding energy. The particle size distribution of ground materials can be exactly calculated by an empirical Rosin–Rammler function which represented well the function parameters on the mill characters. In accordance with LCA results, the environmental impacts for the mass of a useful product for different levels of specific energy with the building of approximation functions were determined. This research work sets up a new complex model with the help of mathematical equations between life cycle assessment and specific energy results, and so improves the energy and environmental efficiency of grinding systems. This research work facilitates the industry to make predictions for a production-scale plant using an LCA of pilot grinding processes. [ABSTRACT FROM AUTHOR]

Therefore, we can also infer that this part of the population can be individualistic in disaster management issues when they are capable of coping with COVID-19, and once they fail to cope, then they are likely to turn to a fatalistic disaster management culture, believing that COVID-19 is a force of nature, unpredictable and unavoidable, lacking confidence in the prevention of COVID-19, hoping to rely on the help of national disaster management authorities, but not taking national control measures, such as the strict use of DCTAs seriously. They will trust and cooperate with the disaster management measures of the national disaster management authority and will be highly compliant with these measures [[6]]. These people lack confidence in crisis resolution, and they expect the nation's disaster management authorities to take action, but do not take nationally issued information about disasters seriously, and do not seriously cooperate with disaster management [[6]]. [Extracted from the article]

In the "contributive" approach, balancing greenhouse gas (GHG) emissions cannot be considered comprehensive, as all footprints, such as ecological and water, shall be assessed and balanced by regenerative actions contributing not only to carbon removal, but also to the regeneration of biodiversity, land, and water. A survey on existing methodologies for the assessment of the damage (environmental burden) and the calculation of the environmental repair (offsets) has been presented in this work. Its outcome pointed out a lack of scientific knowledge on how to put metrics beyond the regenerative development model and in particular on how life cycle assessment (LCA) can scientifically support a number of key features essential to develop a new methodology. The proposed approach is based on three pillars: reduce, remove, and repair. Indeed, this paper aims to develop a methodological LCA-based approach for the definition of Regenerative Contribution Units (RCUs) to quantitatively assess the contribution of projects in line with Sustainable Developments Goals (SDGs) and the framework of regenerative model development. These regenerative units might be marketed locally and globally by enterprises interested in purchasing such assets to scientifically and ethically comply with their corporate ESG obligations. Furthermore, the novelty and feasibility of the proposed approach has been preliminarily investigated through an example of footprints balancing. [ABSTRACT FROM AUTHOR]

Intelligent transport systems are used in various transport systems, among which a special place is occupied by crewed autonomous transport systems such as space stations for deep space habitation. These objects have a complex and critical requirement for life support systems (LSSs) to maintain safe and habitable conditions for the crew in the isolated environment. This paper explores the different architectural options for life support systems (LSSs) in autonomous transport systems, specifically focusing on space stations. Three alternative LSS architectures are discussed: Open LSS (OLSS), Closed LSS (CLSS), and Mixed LSS (MLSS). Each architecture has its own advantages and disadvantages. OLSS relies on external resource delivery, reducing initial costs but increasing dependence on resupply missions. CLSS operates autonomously, generating resources onboard, but has higher initial costs and technological complexity. MLSS combines external delivery and onboard generation, providing flexibility and adaptability. The material emphasizes the importance of cost-effectiveness analysis at the early stages of design and identifies the boundary values of mission duration that determine the most effective LSS architecture choice. The material highlights the significance of striking the right balance between cost and performance to develop intelligent ecosystems of LSS for space stations and other autonomous transport systems. [ABSTRACT FROM AUTHOR]

The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective. References 1 Cao J., Liu D., Zhang G., Shang M. The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective. During the COVID-19 pandemic, many countries have used digital contact tracing apps (DCTAs) to implement contact tracing. [Extracted from the article]

Combined high and low cycle fatigue (CCF) generally induces the failure of aircraft gas turbine attachments. Based on the aero-engine load spectrum, accurate assessment of fatigue damage due to the interaction of high cycle fatigue (HCF) resulting from high frequency vibrations and low cycle fatigue (LCF) from ground-air-ground engine cycles is of critical importance for ensuring structural integrity of engine components, like turbine blades. In this paper, the influence of combined damage accumulation on the expected CCF life are investigated for turbine blades. The CCF behavior of a turbine blade is usually studied by testing with four load-controlled parameters, including high cycle stress amplitude and frequency, and low cycle stress amplitude and frequency. According to this, a new damage accumulation model is proposed based on Miner's rule to consider the coupled damage due to HCF-LCF interaction by introducing the four load parameters. Five experimental datasets of turbine blade alloys and turbine blades were introduced for model validation and comparison between the proposed Miner, Manson-Halford, and Trufyakov-Kovalchuk models. Results show that the proposed model provides more accurate predictions than others with lower mean and standard deviation values of model prediction errors. [ABSTRACT FROM AUTHOR]

Over the past few decades, several protocell models have been developed that mimic certain essential characteristics of living cells. These protocells tend to be highly reductionist simplifications of living cells with prominent bilayer membrane boundaries, encapsulated metabolisms and/or encapsulated biologically-derived polymers as potential sources of information coding. In parallel with this conventional work, a novel protocell model based on droplets is also being developed. Such water-in-oil and oil-in-water droplet systems can possess chemical and biochemical transformations and biomolecule production, self-movement, self-division, individuality, group dynamics, and perhaps the fundamentals of intelligent systems and evolution. Given the diverse functionality possible with droplets as mimics of living cells, this system has the potential to be the first true embodiment of artificial life that is an orthologous departure from the one familiar type of biological life. This paper will synthesize the recent activity to develop droplets as protocell models. [ABSTRACT FROM AUTHOR]

As bridge infrastructure ages, the deterioration of materials and hazard events reduce the service quality and compromise the safety of the structure. Therefore, there is a tremendous need for bridge maintenance planning, and such maintenance studies during recent years have focused on the life cycle aspect. To fulfill the budget requirements of life cycle maintenance, an important issue is to ensure that the limited maintenance budget is utilized in an effective way. However, there are few studies that have aimed to assess the topic of budget allocation and the adjustment of bridge life-cycle maintenance issues. In order to resolve such issues, a two-stage optimization model based on constraint programming (CP) is proposed in this study to deal with maintenance scheduling problems. This is facilitated by adopting the resource-constrained project scheduling problem (RCPSP) framework, in which, three plans according to the maintenance time point are considered (i.e., early, middle, and late plans). According to the RCPSP concepts, this study views the budget ceiling as the resource limit, and maintenance plans as activities, so that the feasibility of each maintenance plan depends on the sufficiency of the budget. As the first stage, Model-I (the life cycle lifespan evaluation model) takes a life cycle perspective, evaluating how long it will take to keep all bridges in a serviceable condition with minimum expenditure over the planning cycle, and evaluates the annual budgets that can be used as a reference for users to draft a budget plan. Based on the planning result from Model-I and the actual annual budget approved for the current year, the second stage, Model-II (the annual budget allocation model) then reallocates the actual budget to take into account the importance of all bridges and different costs and benefits of maintenance plans, and revises the suggested annual budget values obtained by Model-I for the following years. Through a case study, the optimized result demonstrates that annual recursive implementation of this two-stage model satisfies the need to adjust existing budgetary data, and provides management personnel with optimized and realistic maintenance decision support for bridge infrastructure. [ABSTRACT FROM AUTHOR]

Short glass fiber-reinforced (SGFR) thermoplastics are used in many industries manufactured by injection molding which is the most common technique for polymeric parts production. Glass fibers are commonly used as the reinforced material with thermoplastics and injection molding. In this paper, a critical plane-based fatigue damage model is proposed for tension–tension or tension–compression fatigue life prediction of SGFR thermoplastics considering fiber orientation and mean stress effects. Temperature and frequency effects were also included by applying the proposed damage model into a general fatigue model. Model predictions are presented and discussed by comparing with the experimental data from the literature. [ABSTRACT FROM AUTHOR]

Understanding battery characteristic behaviors is indispensable in designing and managing large-scale battery-based energy storage systems in high-power applications. This paper presents a practical-based characterization method to model the ohmic series resistance of lithium-ion batteries under life-cycle consideration. Aging cells were prepared in a controlled environment, and the testing information was automatically characterized using a developed computer-based battery test system. An experimental methodology based on the cycling of pulse tests is applied for modeling the ohmic series resistance. Several aspects of the testing parameters during the cycling operations, such as the characteristic changes of the ohmic series resistance, amplitudes of the periodic test current, cell capacity, state of charge, and the rate of change of the resistance increment, are also investigated and analyzed so as to fulfill the resistance model. The accuracy of the proposed model is verified by comparing the testing information, showing a satisfactory result. [ABSTRACT FROM AUTHOR]

The search for extraterrestrial life, recently fueled by the discovery of exoplanets, requires defined biosignatures. Current biomarkers include those of extremophilic organisms, typically archaea. Yet these cellular organisms are highly complex, which makes it unlikely that similar life forms evolved on other planets. Earlier forms of life on Earth may serve as better models for extraterrestrial life. On modern Earth, the simplest and most abundant biological entities are viroids and viruses that exert many properties of life, such as the abilities to replicate and undergo Darwinian evolution. Viroids have virus-like features, and are related to ribozymes, consisting solely of non-coding RNA, and may serve as more universal models for early life than do cellular life forms. Among the various proposed concepts, such as "proteins-first" or "metabolism-first", we think that "viruses-first" can be specified to "viroids-first" as the most likely scenario for the emergence of life on Earth, and possibly elsewhere. With this article we intend to inspire the integration of virus research and the biosignatures of viroids and viruses into the search for extraterrestrial life. [ABSTRACT FROM AUTHOR]

In existing models with an unknown link function, the issue of predictors containing both multiple functional data and multiple scalar data has not been studied. To fill this gap, we propose a generalized partially functional linear model, which not only models the relationship between multiple scalar and functional predictors and responses, but also automatically estimates the link function. Specifically, we use the functional principal component analysis method to reduce the dimensionality of functional predictors, estimate the regression coefficients using the maximum likelihood estimation method, estimate the link function using the method of local linear regression, iteratively obtain the final estimator, and establish the asymptotic normality of the estimator. The asymptotic normality is illustrated through simulation experiments. Finally, the proposed model is applied to study the influence of environmental, economic, and medical levels on life expectancy in China. In the study, functional predictors are the daily air quality index, temperature, and humidity of 58 cities in 2020, and scalar predictors are GDP and the number of beds in hospitals. The experimental results indicate that the unknown link function model has a smaller prediction error and better performance than both the model with the known link function and the model without a link function. [ABSTRACT FROM AUTHOR]

The production process requires massive amounts of minerals, fossil fuels, and energy. The efficient use of energy and natural resources appears to be crucial to the state of affairs. It should be noted that the post-consumer management of solar power plant elements results in a certain amount of power and matter, as well as harmful effects on the natural world. The major goal of this study was to examine the environmental effect of the solar power plant throughout its life cycle, taking into consideration the depletion of natural materials and mineral resources, using the ReCiPe 2016 model. A life cycle study was performed on an actual 2 MW solar power facility located in northern Poland. This study was conducted using the ReCiPe 2016 model and the Life Cycle Assessment (LCA) methodology. The analyzed renewable energy system's impact was assessed utilizing 22 impact categories, focusing mostly on the depletion of natural resources. A Life Cycle Assessment was conducted for two post-consumer development scenarios (landfill and recycling). This research focuses on the full solar power plant, not just the photovoltaic panels. Recycling, as a kind of post-consumer development, can provide major environmental benefits and minimize negative environmental consequences throughout the solar power plant's life cycle. The exceedingly harmful effects can be evident in losses related to water and the aquatic environment. The obtained study findings enabled the development of sustainable-friendly recommendations towards the continuous advancement of the life cycle of solar power plants, thereby reducing the use of rare earth minerals. [ABSTRACT FROM AUTHOR]

This study explores the water consumption and greenhouse gas (GHG) emissions in the Yarkand River Basin, focusing on their dynamic interactions across industrial sectors. Utilizing environmental input–output analysis (IOA), the CROPWAT model, and life cycle assessment (LCA), we quantified the historical evolution of physical and virtual water cycles in relation to the water–carbon nexus. Our findings reveal that the planting industry, particularly the production of export-oriented, water-intensive crops like cotton, significantly contributes to both blue and green water consumption, exacerbating regional water scarcity. The persistent external market demand drives this over-extraction, further strained by the basin's limited water retention capabilities. Although advancements have been made in reducing the per-unit water footprint of crops, total water consumption continues to rise due to agricultural expansion, intensifying pressure on blue water resources. Additionally, agricultural GHG emissions have surged, driven by increased electricity consumption, heavy fertilizer use, and escalating soil N2O emissions. In light of these challenges, our research underscores the critical need for integrated resource management strategies that align with sustainable development goals. By promoting efficient water allocation within the agricultural sector and diversifying crop structures downstream, we can enhance ecosystem resilience and reduce environmental degradation. Furthermore, the advancement of value-added agricultural processing and the implementation of innovative water conservation technologies are essential for fostering economic sustainability. These strategies not only mitigate the environmental impacts associated with agricultural practices but also strengthen the region's adaptive capacity in the face of climate change and fluctuating market demands. Our findings contribute to the broader discourse on sustainable agricultural practices, emphasizing the interconnectedness of water management, climate resilience, and economic viability in arid regions. [ABSTRACT FROM AUTHOR]

Today's work market is both unsteady and unpredictable, and this requires taking urgent and practical actions aiming at creating work opportunities and "better" jobs, promoting a social and solidarity economy, and encouraging the development of moral strength in the workplace. From the Life Design approach perspective, our study examines two variables necessary to cope with the current labor market, courage, and career adaptability, and their role in life satisfaction. Through courage, a full mediational model between life satisfaction and career adaptability was tested in the 525 (291 men and 234 women) employees involved in the present study. Results support the mediational model. Mainly, life satisfaction was predicted indirectly by career adaptability through courage. Such outcome has important implications for practice and highlights the need to support workers in planning their life design by developing career adaptability and workers' voluntary feeling to act, according to different levels of fear, when facing a threat to the achievement of a significant result or objective, which in turn will positively influence their feelings of life satisfaction. [ABSTRACT FROM AUTHOR]

In this study we analyzed the effects of silvicultural treatments on carbon (C) budgets in Pinus taeda L. (loblolly pine) plantations in the southeastern United States. We developed a hybrid model that integrated a widely used growth and yield model for loblolly pine with published allometric and biometric equations to simulate in situ C pools. The model used current values of forest product conversion efficiencies and forest product decay rates to calculate ex situ C pools. Using the model to evaluate the effects of silvicultural management systems on C sequestration over a 200 year simulation period, we concluded that site productivity (site quality), which can be altered by silviculture and genetic improvement, was the major factor controlling stand C density. On low productivity sites, average net C stocks were about 35% lower than in stands with the default average site quality; in contrast, on high quality sites, C stocks were about 38% greater than average productivity stands. If woody products were incorporated into the accounting, thinning was C positive because of the larger positive effects on ex situ C storage, rather than smaller reductions on in situ C storage. The use of biological rotation age (18 years) was not suitable for C sequestration, and extended rotation ages were found to increase stand C stock density. Stands with an 18-year-rotation length had 7% lower net C density than stands with a 22-year-rotation length; stands with a 35-year-rotation length had only 4% more C than stands harvested at age 22 years. The C sequestered in woody products was an important pool of C storage, accounting for ∼34% of the average net C stock. Changes in decomposition rate, associated with possible environmental changes resulting from global climate change, affected C storage capacity of the forest. When decay rate was reduced to 10% or increased to 20%, the C stock in the dead pool (forest floor and coarse woody debris) was reduced about 11.8 MgC·ha-1 or increased about 13.3 MgC·ha-1, respectively, compared to the average decay rate of 15%. The C emissions due to silvicultural and harvest activities were small (∼1.6% of the gross C stock) compared to the magnitude of total stand C stock. The C model, based on empirical and biological relationships, appears appropriate for use in regional C stock assessments for loblolly pine plantation ecosystems in the southern U.S. [ABSTRACT FROM AUTHOR]

The construction industry, business models, and smart cities are recognized as pivotal domains with profound implications for fostering sustainability, prompting extensive research endeavors. However, there remains a dearth of interdisciplinary integration within this sphere aimed at fostering sustainable development. Nevertheless, current studies suggest that research in this area could provide theoretical and practical guidance for the sustainable transformation of society and make a positive contribution to the realization of the Sustainable Development Goals (SDGs). Therefore, this paper aims to utilize an innovative mixed research approach combining macro-quantitative bibliometric analysis with subsequent micro-qualitative content examination based on the SDGs to explore the relationship between BIM and smart cities in promoting a sustainability-oriented business model, which provides a comprehensive understanding of the overall situation and development of research topics in the field and contributes to the improvement of the SDGs. The results show that, during the last 13 years (from the year 2011 to 2023), the period from the year 2011 to 2016 was the initial stage of the field, followed by a rapid growth after the year 2018, of which "BIM", "Smart City", "Business Model", "Building Life Cycle", "Urban Management", and "Business Model Innovation" are the keywords representing the current research hotspots. The circular economy model that has been developed since 2021 has contributed to life cycle stages, including "briefing stages" and "procurement stages". As such, the "whole life cycle", "strategic urban planning frameworks", and "sustainable business models" have become future research trends, whilst real-world applications such as "smart tourism", "e-government", and "green building" have emerged. Further, the key partnerships of "city managers", "corporate enterprises", and "public participation" for smart cities contribute to the achievement of SDGs 8 and 17 in terms of integrating urban information technology and urban infrastructure, policy regulation, knowledge-sharing, improving economic efficiency, and promoting sustainable economic growth. [ABSTRACT FROM AUTHOR]

Under fatigue loading, the interfacial fatigue life of fiber-reinforced polymer(FRP)–concrete is an important index for the analysis of the fatigue performance of reinforced concrete beams strengthened with FRP materials and the evaluation of the reinforcement effect. To solve the problems of the inconsistent and limited accuracy of existing fatigue life prediction models, gene expression programming (GEP) was used to study the interfacial fatigue life of FRP–concrete. Firstly, 219 sets of interfacial fatigue test data were collected, which included two kinds of reinforcement methods, namely, externally bonded (EB) reinforcement and near-surface-mounted (NSM) reinforcement; secondly, Pearson correlation analysis was used to determine the key factors affecting the fatigue life, and then GEP was used to explore the influence of different input forms on the prediction accuracy of the model. Fatigue life calculation formulas applicable to the two kinds of reinforcement methods, i.e., EB and NSM, were established, and a specific calculation formula was established. The model was subjected to parameter sensitivity analysis and variable importance analysis and was found to reflect the intrinsic relationship between the fatigue life and various factors. Finally, the GEP model was compared with the models proposed by other researchers. Five statistical indices, such as the coefficient of determination and the average absolute error, were selected to assess the model, and the results show that the GEP model has higher prediction accuracy than other models, with a coefficient of determination of 0.819, and indicators such as the average absolute error are also lower than those of the rest of the models. [ABSTRACT FROM AUTHOR]

In this research, we develop an extension of the stochastic routing model with a fixed capacity for the distribution of perishable products with a time window. We use theoretical probability distributions to model the life of transported products and travel times in the network. Our main objective is to maximize the probability of delivering products within the established deadline with a certain level of customer service. Our project is justified from the perspective of reducing the pollution caused by greenhouse gases generated in the process. To optimize the proposed model, we use a Generic Random Search Algorithm. Finally, we apply the idea to a real problem of designing strategies for the optimal management of perishable food distribution routes that involve a time window, the objective being to maximize the probability of meeting the time limit assigned to the route problem by reducing, in this way, the pollution generated by refrigerated transport. [ABSTRACT FROM AUTHOR]

This study aims to develop a comprehensive model for life cycle assessment and environmental damage cost calculations considering avoided emissions in different waste management scenarios using the system dynamics (SD) approach. Our analysis reveals that under the business-as-usual (BAU) scenario for the period 2020–2050, the total net greenhouse gas (GHG) emissions reach 12.5 Mt, with the highest environmental damage cost being USD 689 million. In contrast, an integrated management strategy encompassing recycling, composting, anaerobic digestion, and incineration results in a 195% reduction in net GHG emissions compared to the BAU Scenario. Concurrently, the environmental damage cost drops to USD 277 million, incorporating USD 347 million in savings, leading to a net environmental damage cost of USD −71 million. The findings affirm that accounting for emissions avoided across various treatment methods offers a more accurate estimate of environmental damage costs. Additionally, policies centered on integrated waste management are more likely to achieve sustainability. The study also demonstrates the utility of the SD approach in providing a holistic view of waste management systems and in evaluating the effectiveness of various policy strategies for sustainable waste management. [ABSTRACT FROM AUTHOR]

The internal mechanism affecting life loss caused by a dam-break flood is complicated. On the basis of analyzing the risk formation path, a risk evaluation indicator system was established which included the hazards, exposure and vulnerability factors. Variable Fuzzy Sets theory was introduced into the risk evaluation of life loss risk grades and applied to eight collapsed dams in China. According to the sequence of the risk grades of these dams, the evaluation result was mainly consistent with the actual mortality ranking sequence, showing that the model could be effectively applied to the risk evaluation of life loss in dam-break events. Aimed at the problem of large differences in the downstream population distribution of dams in China, this manuscript suggested that 10,000 people should be the basis for the grouping operation of dams in the risk evaluation. These Variable Fuzzy evaluation models and grouping suggestions could help stakeholders to allocate the funds for dam reinforcement more accurately and provide a scientific basis for the study of dam-break life loss and dam risk management. [ABSTRACT FROM AUTHOR]

Bioenergy utilization is ambitiously being promoted, attributed to its renewable and clean natures. China's provincial regions have distinct levels of agricultural development, and thus, different levels of agricultural bioresources (ABs) potentials. In this study, an integrated assessment model is developed to quantify the 3E benefits from the life cycle perspective, covering the whole process of energy-oriented ABs utilization. Integrating nine types of ABs and four types of energy conversion modes (direct combustion power generation, gasification power generation, briquette fuel and bioethanol), the model is applied to 31 provincial regions in China to uncover regional features of the 3E benefits. The results showcase that total energy benefits in all regions amount to 100.6 million tons of coal-equivalent, with the most for Henan, Heilongjiang, Shandong, Xinjiang and Jilin and the least for Tibet, Beijing, Shanghai, Qinghai and Hainan. The economic and environmental benefits of regions are consistent with the energy benefits, with a total amount of 10.5 billion USD and 229.2, 1.5 and 2.5 million t CO2, SO2 and NOx mitigations. Energy utilization proportion of ABs, allocation proportion, energy conversion coefficients, net profit coefficient and mitigation coefficients for four modes are the key parameters affecting regional 3E benefits. The results have policy implications on facilitating to reasonable and pertinent regional planning of energy-oriented ABs utilization. [ABSTRACT FROM AUTHOR]

The study considers ways to ensure the quality of the functioning of power equipment as one of the directions for ensuring the safety of energy complexes in the period of "green transformation". Based on the analysis, it is established that for an effective "green" transformation, it is necessary to ensure the energy safety of equipment operation, which is possible by developing effective science-based approaches to technical diagnostics of the state of power systems and individual equipment. The main objective of the study is to develop a Safety Management Model for Life Term Operation of power equipment, which takes into account changes in its condition at different stages of operation and allows for the prediction of further safe operation. The paper proposes an approach to researching the technical condition of power equipment, taking into account the deformations that occur during operation. The results of the calculation of stress intensity coefficients for longitudinal and transverse-postulated cracks in different modes are presented. Based on the calculated and experimentally obtained values, an approach to predicting the operating life of power equipment with regard to changes in technical characteristics is proposed. The results of the calculations showed that by changing the allowable load on the material of the energy equipment to 35 kgf/mm2, the estimated operational lifespan could be extended until 2035, ensuring all necessary safety conditions. It has been proven that with effective management and continuous safety diagnostics, nuclear power plants have the potential to operate beyond their standard design life of up to 30–40 years. This approach allows for the quality and safe operation of power equipment in the context of the transition to sustainable energy. [ABSTRACT FROM AUTHOR]

New propulsion technologies and the development of electromobility increase the environmental efficiency of the transport sector. However, the current structure of car fleets with a large number of old cars with worse environmental parameters undermines the benefits of technological progress in the automotive industry. Older cars may require a more extensive service, involving a thorough overhaul, repair or even replacement of many parts. The result of using additional resources is a deterioration of environmental performance. This study considers various maintenance and repair scenarios and focuses on the use phase using the example of the popular Ford Focus passenger car model. The life cycle optimization model was used for environmental assessment, which determines the optimal duration of the car use phase, accounting for detailed service information and the type and environmental efficiency class of the different fuel versions. This model can be an effective tool for car fleet management and car replacement policy. Detailed life cycle inventories of 40 Ford Focus II diesel and petrol cars that represent all maintenance and repairs are the inputs to the life cycle optimization model. The inventory data were provided by the Ford Service Center in Szczecin (Poland), which regularly serviced the cars with a mileage of up to 200,000 km. Inventory at other stages of the cars' life cycles was modeled using Ecoinvent data. The results show that by considering these vehicle servicing aspects on the basis of more detailed data, impact assessments are better represented compared to other studies. Depending on the replacement policy, the contribution of vehicle maintenance and repair can account for almost half of the cumulative life cycle burdens. [ABSTRACT FROM AUTHOR]

We explored the effect of the jump-diffusion process on a social benefit scheme consisting of life insurance, unemployment/disability benefits, and retirement benefits. To do so, we used a four-state Markov chain with multiple decrements. Assuming independent state-wise intensities taking the form of a jump-diffusion process and deterministic interest rates, we evaluated the prospective reserves for this scheme in which the individual is employed at inception. We then numerically demonstrated the state of the reserves for the scheme under jump-diffusion and non-jump-diffusion settings. By decomposing the reserve equation into five components, our numerical illustration indicated that an extension of the retirement age has a spillover effect that would increase government expenses for other social insurance programs. We also conducted sensitivity analyses and examined the total-reserves components by changing the relevant parameters of the transition intensities, which are the average jump-size parameter, average jump frequency, and diffusion parameters of the chosen states, with figures provided. Our computation revealed that the total reserve is most sensitive to changes in average jump frequency. [ABSTRACT FROM AUTHOR]

One approach to incorporate environmental sustainability in organisations is the implementation of Life Cycle Management (LCM). LCM is a comprehensive and integrated approach for measuring and managing environmental impacts. Successful sector-wide uptake of LCM has the potential to enable the environmental impacts associated with an industry sector to be efficiently measured and managed in a continual improvement process. There is an opportunity for the New Zealand primary sector to strengthen its competitiveness in the global market place by demonstrating the environmental credentials of its products and supporting the country’s “green and clean” image. Previous research has identified the barriers and enablers to successful LCM uptake by New Zealand primary sector Small and Medium sized Enterprises (SMEs) in a sector-based context. This paper builds on that foundation and presents a Life Cycle Management Uptake Evaluation Framework (LUEF) that allows both individual organisations and industry sectors to identify the key factors affecting successful LCM uptake and assess their level of maturity for each factor. The key factors used in this study are structure, culture, resource availability, LCM strategy, knowledge, market requirements and communication. The study employed a qualitative methodology and used face-to-face interviews with different stakeholders in the value chain for the New Zealand kiwifruit sector to inform the development of the framework. In the framework, each factor is represented as a maturity scale to allow organisations as well as industry sectors to assess their position on the scale. This will help them to create a baseline assessment, both for themselves as an organisation, as well as on an industry sector level. The baseline assessment will allow them to identify areas for improvements, which can be tracked over time by checking the progress on the scales in the individual areas. It can also be used as a communication tool for stakeholders in the supply chain (e.g., growers, post-harvest operators and staff from industry boards). These stakeholders can use the tool to measure and compare performance, including evaluating their own performance against the industry average, as well as performance of the industry sector over time. This is useful to engage these stakeholders and demonstrate that changes (such as reducing carbon footprints) have a positive impact and lead to progress (as well as highlighting any actions that need to be reviewed and adjusted). [ABSTRACT FROM AUTHOR]

The Daisyworld model illustrates the concept of biological homeostasis in the global environment by establishing a connection between the biota and environment, resulting in a single intertwined system known as Gaia. In essence, the Daisyworld model represents life by daisy populations whereas temperature represents the environment, establishing a population dynamics model to represent life–environment ecological interactions. The recent occurrence of extreme weather events due to climate change and the critical crises brought on by the COVID-19 pandemic are strengthening the arguments for the revenge of Gaia, a term used to describe the protective response of the global biota-environment system. This paper presents a novel Daisyworld parable to describe ecological life–environment interactions including the revenge of Gaia and the greenhouse effect. The revenge of Gaia refers to a change in the interplay between life and environment, characterized by the Gaia state that establishes the life-environment state of balance and harmony. This results in reaction effects that impact the planet's fertile regions. On the other hand, the greenhouse effect is incorporated through the description of the interactions of greenhouse gases with the planet, altering its albedo. Numerical simulations are performed using a nonlinear dynamics perspective, showing different ecological scenarios. An investigation of the system reversibility is carried out together with critical life–environment interactions. This parable provides a qualitative description that can be useful to evaluate ecological scenarios. [ABSTRACT FROM AUTHOR]

The modelling of IoT applications utilising the resources of cloud and fog computing is not straightforward because they have to support various trigger-based events that make human life easier. The sequence of tasks, such as performing a service call, receiving a data packet in the form of a message sent by an IoT device, and managing actuators or executing a computational task on a virtual machine, are often associated with and composed of IoT workflows. The development and deployment of such IoT workflows and their management systems in real life, including communication and network operations, can be complicated due to high operation costs and access limitations. Therefore, simulation solutions are often applied for such purposes. In this paper, we introduce a novel simulator extension of the DISSECT-CF-Fog simulator that leverages the workflow scheduling and its execution capabilities to model real-life IoT use cases. We also show that state-of-the-art simulators typically omit the IoT factor in the case of the scientific workflow evaluation. Therefore, we present a scalability study focusing on scientific workflows and on the interoperability of scientific and IoT workflows in DISSECT-CF-Fog. [ABSTRACT FROM AUTHOR]

Predictive analysis of the life of an electronic package requires a sequence of processes involving: (i) development of a finite element (FE) model, (ii) correlation of the FE model using experimental data, and (iii) development of a local model using the correlated FE model. The life of the critical components is obtained from the local model and is usually compared to the experimental results. Although the specifics of such analyses are available in the literature, a comparison among them and against the same electronic package with different user printed circuit board (PCB) thicknesses does not exist. This study addresses the issues raised during the design phase/life analysis, by considering a particular package with a variable geometric thickness of the user PCB. In this paper, the effect of stiffening the user PCB on the fatigue life of a ball grid array (BGA), SAC305 solder joint is studied. The board stiffness was varied by changing the thickness of the PCB, while the size of the substrate, chips, and solder balls were kept constant. The test vehicle consisted of BGA chips soldered to a user PCB. The thickness of the user PCB was varied, but the surface area of the BGA chip remained identical. The test vehicle was then modeled using a finite element analysis tool (ANSYS). Using a global/local modeling approach, the modal parameters in the simulations were correlated with experimental data. The first resonance frequency dwell test was carried out in ANSYS, and the high-cycle fatigue life was estimated using the stress-life approach. Following the simulation, the test vehicle was subjected to resonance fatigue testing by exciting at the first mode resonance frequency, the mode with the most severe solder joint failure. The resistance of the solder joint during the experiment was monitored using a daisy-chain circuit, and the point of failure was further confirmed using the destructive evaluation technique. Both the experimental and simulation results showed that stiffening the board will significantly increase the fatigue life of the solder joint. Although the amplitude of the acceleration response of the test vehicle will be higher due to board stiffening, the increase in natural frequencies will significantly reduce the amplitude of relative displacement between the PCB and the substrate. [ABSTRACT FROM AUTHOR]

In order to solve the problem of predicting the residual life of mechanical products accurately based on small-sample data, this paper proposes a small-sample adaptive residual life prediction model of mechanical products based on feature matching preprocessor-LSTM. First, aiming at the problem of low accuracy of remaining life prediction for small samples of mechanical products caused by multiple time scales and multiple fault states, the failure time data and performance degradation data are fused, and the failure rate and standard deviation are used as the remaining life prediction criteria to intuitively reflect The possibility of failure of a component or system at a certain point in time. Considering the demand of adaptive small-sample residual life prediction data, this paper establishes the adaptive matching pre-processor model of life characteristics. On this basis, the LSTM neural network is used to establish a small-sample adaptive residual life prediction model. Then, the XJTU-SY bearing life data set and the test data of the small-sample life characteristics measured by the RV reducer are used as the research objects, and a small amount of the data set is randomly selected. The remaining life expectancy is predicted from the sample data and compared with its standard remaining life, respectively. The comparison results show that the overall prediction error is small. This study shows that the remaining life prediction model established can better predict the remaining life of mechanical product sub-sample data and provides a feasible method for predicting the remaining life of mechanical product sub-samples. [ABSTRACT FROM AUTHOR]

To reduce the allocation of energy storage capacity in wind farms and improve economic benefits, this study is focused on the virtual synchronous generator (synchronverter) technology. A system accompanied by wind power, energy storage, a synchronous generator and load is presented in detail. A brief description of the virtual synchronous generator control strategy is given. The capacity allocation is based on different optimization goals and the optimal energy storage capacity configuration of the coordinated frequency modulation (FM) control strategy. The detail of the dual-loop control strategy is carried out by establishing the grid-connected transfer function model of the synchronverter energy storage and a theoretical model of life cycle cost is established. The optimal control strategy of coordinated FM for wind storage is implemented using MATLAB software. The simulation showed that the proposed strategy provided the energy storage capacity at high wind speed, which is configured to be 5.9% of the installed capacity of the wind turbine, marking a reduction of 26% compared with the 8% capacity required for independent support. In addition, the proposed method has improved the energy storage capacity configuration of the coordinated FM control strategy. [ABSTRACT FROM AUTHOR]

Recently, due to the ever-increasing global warming effect, the proportion of renewable energy sources in the electric power industry has increased significantly. With the increase in distributed power sources with adjustable outputs, such as energy storage systems (ESSs), it is necessary to define ESS usage standards for an adaptive power transaction plan. However, the life-cycle cost is generally defined in a quadratic formula without considering various factors. In this study, the life-cycle cost for an ESS is defined in detail based on a life assessment model and used for scheduling. The life-cycle cost is affected by four factors: temperature, average state-of-charge (SOC), depth-of-discharge (DOD), and time. In the case of the DOD stress model, the life-cycle cost is expressed as a function of the cycle depth, whose exact value can be determined based on fatigue analysis techniques such as the Rainflow counting algorithm. The optimal scheduling of the ESS is constructed considering the life-cycle cost using a tool based on reinforcement learning. Since the life assessment cannot apply the analytical technique due to the temperature characteristics and time-dependent characteristics of the ESS SOC, the reinforcement learning that derives optimal scheduling is used. The results show that the SOC curve changes with respect to weight. As the weight of life-cycle cost increases, the ESS output and charge/discharge frequency decrease. [ABSTRACT FROM AUTHOR]

As an approach to move towards a sustainable waste management system, circular economy (CE) is gaining an increased interest by most countries. Russia is among the countries where the CE is one of the priorities of the country's economy, with a market value of the CE is USD$ 755.05 billion. However, such a strategy is facing challenges and barriers which are country specific. This study aimed to review the status of the CE in Russia and to identify the obstacles that are hindering the country from achieving its objectives. Moreover, the study aimed to evaluate the role of eco-industrial parks (EIP) in Russia in promoting the CE model. The study findings indicate that the CE adoption in Russia is still in its early stages. To create an enabling environment for CE promotion in Russia, there is a need to overcome several institutional, technical, and social barriers. Russian higher educational institutions are playing a major role to create the critical mass of experts that will help the country transition towards a CE model. Using life cycle assessment (LCA) to analyze the environmental performance of one of the EIPs in Russia revealed that such enterprises are more sustainable than the business-as-usual scenarios, under which the generated solid waste is buried into landfill. The comparison shows that by diverting 1.813 million tons of mixed municipal solid waste that is generated in Moscow to EIP would lead to a reduction in environmental impacts. The total global warming potential of the EIP scenario is less, by 59%, than the direct landfilling scenario, while the eutrophication, acidification, smog, and ozone depletion are less, and fossil fuel depletion impacts under the second scenario are less, by 81%, 26%, 18%, and 81%, respectively. Furthermore, the health impacts including carcinogenic, non-carcinogenic, eco-toxicity were found to be 92%, 96%, and 96%, respectively, less than the baseline scenario. [ABSTRACT FROM AUTHOR]

Oasis settlements in Saharan lands present a particular model of life for rural individuals' adaptation to environmental challenges. This study investigated human outdoor thermal comfort in a palm grove of the Tolga region, Algeria, during the phenological cycle of the date palm. Date palms are the primary economic source of the cultivators, who mainly live in houses inside the cultivated area. For this study, an area of 21 hectares with 220 palm trees was selected. The phenological cycle of the date palm was divided into three growth stages, including seasonal variations as well. The cycle covers a period of 8 months from March to November. Therefore, on-site monitoring of the microclimate was performed during March–November 2021. The climatic factors of air temperature and humidity were monitored at an interval of 10 min. The discomfort index based on temperature ranges covering discomfort conditions was used. The results showed that the cultivators work under extreme temperatures for 5.5 months during the phenological cycle. The spring period was more comfortable, while slight to extreme discomfort was observed in the summer and fall seasons, especially between midday and 7 p.m. Temperatures below 25 °C are comfortable for the cultivators; however, severe discomfort occurs at 30 °C or above. Moreover, the humidity was not a dominant factor for discomfort. These findings can be helpful for architects and planners to devise solutions that can fulfil human comfort requirements and date palm cultivar conditions, specifically during extreme thermal situations. [ABSTRACT FROM AUTHOR]

Featured Application: The life cycle inventory of a composting facility is expected to predict the fate of individual waste fragments and compost quality. Mechanical composting is a popular treatment method for the mechanically separated organic fraction of municipal solid wastes to stabilize the waste material and reduce its environmental impacts. The model and life cycle inventory database are created based on the existing centralized mechanical composting facility located in Chania (Crete, Greece). This study aims to assess all stages of the composting process, wherein input-output flows are comprehensively analyzed based on specific waste fragments. The transfer coefficients are calculated for each waste fragment throughout the processes. The degradation rate is measured as kg of C and N released per Mg of the treated material. The results show that process degradation rates are independent of the initial fragmental composition. This is the first study that accurately models the fate of distinctive waste fragments in a composting plant, while the developed life cycle inventory (with regard to mass and energy balances) can be applied to estimate the environmental impacts regarding mechanical composting the organic fraction of municipal solid wastes. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between corporate shared institutional equity (SIE) holders and eco-transparency reporting (ETR). Specifically, it examines three distinct types of SIE: (1) common institutional shareholders with industry peers, (2) the average count of unique institutional owners holding shares in both the focal company and its peers, and (3) the total percentage of SIE within the focal company. The findings indicate that firms with higher levels of SIE are more likely to disclose ETR, signaling a commitment to enhancing public trust and aligning with governmental expectations. Furthermore, the study explores the impact of SIE across different stages of the firm's life cycle, revealing that the influence of SIE on ETR is more pronounced during the growth and mature stages. The results remain robust even when alternative thresholds for SIE are applied, such as adjusting from a 5% to a 3% threshold. To account for potential misspecification and omitted variables, propensity score matching (PSM), System generalized method of moments (Sys GMM) and two-stage least squares (2SLS) methods were employed. This research contributes to the literature by highlighting the role of shared institutional ownership in promoting environmental transparency, offering novel insights into how institutional investors can drive corporate sustainability practices across different firm life cycles. [ABSTRACT FROM AUTHOR]

Waste from electrical and electronic equipment (WEEE) is expected to reach 82 million metric tons by 2030, with a global average of 7.8 kg/cap/year. In 2022, the amount of WEEE generated in Laos was 3.6 kg/cap/year, with no formal collection or treatment facilities in place. An examination of WEEE management and repair practices in the capital of Laos, Vientiane, was conducted, involving a review of the relevant literature and data gathered from interviews and online surveys of a total of 82 families, 17 junkshops, and 16 repair shops. Additionally, the environmental impact of smartphone repair activities was determined by utilizing data from existing life cycle assessment studies. The findings highlight the challenges of WEEE management, including infrastructure deficit and policy gaps. The informal sector plays a significant role in WEEE collection and dismantling. Manual dismantling takes place in junkshops prior to exportation to Vietnam, Thailand, and China. Reuse and repair are common practices and are present in both formal and informal contexts. Smartphone repair is a prevalent service alongside cooling and freezing equipment repair. The primary obstacles of repair are linked to the quality and availability of spare parts, the absence of repair guidelines and technical expertise, complicated designs, and consumer awareness. Notwithstanding the challenges associated with repairs, this case study demonstrates the environmental benefits of smartphone repair, achieving a reduction of 44% in GHG emissions compared to the conventional replacement over a 7-year observation period. Recommendations are proposed to enhance WEEE management systems and advance the repair movement. [ABSTRACT FROM AUTHOR]

The development of a city needs the accumulation of culture, and historical buildings are the most direct witness of the rise and fall of a city. Like the human body, historical buildings have a certain life cycle, but the acceleration of urbanization and unreasonable use cause an irreversible reduction in the residual life of historical buildings. There is a notable lack of quantitative analysis regarding the residual life of historical buildings. Therefore, identifying the factors that influence their residual life is crucial for both preserving these buildings and sustaining urban culture. In order to obtain a more accurate correlation degree of influencing factors, a systematic-analysis model of influencing factors on the residual life of historical buildings based on the entropy weight method (EWM) and the grey relation analysis method (GRA) was established, so as to excavate the mechanism of the influencing factors on the residual life of historical buildings, accurately identify the main influencing factors on the residual life of historical buildings, and propose preventive measures. The results show that the structural system has the greatest influence on the residual life of historical buildings, followed by the enclosure system, and the equipment system. The research findings offer valuable insights for extending the residual life of historical buildings in the future. [ABSTRACT FROM AUTHOR]

This study presents a methodology for characterizing the constituent properties of composite materials by back-calculating from the laminate behavior under fatigue loading. Composite materials consist of fiber reinforcements and a polymer matrix, with the fatigue performance of the laminate governed by the interaction between these constituents. Due to the challenges in directly measuring the properties of individual fibers and the polymer matrix, a reverse-engineering approach was employed. Using the micro-mechanics of fatigue (MMFatigue), we predicted the laminate's fatigue behavior based on assumed constituent properties and compared these predictions with experimental data from fatigue tests. The properties of the fiber and polymer matrix were iteratively adjusted to minimize the differences between predictions and experimental results, enabling accurate fatigue characterization. To ensure robustness, three laminate angles—0°, 30°, and 60°—were evaluated at three temperatures: low temperature (LT: −40 °C), room temperature (RT: 25 °C), and high temperature (HT: 85 °C). The error, defined as the fatigue life difference between the prediction and the experimental results, were obtained as 2.48% at LT, 7.18% at RT, and 1.25% at HT for a laminate angle of 45°. Finally, the applicability of the multiscale-based fatigue life prediction method was demonstrated through studies on laminates with various angles under tension–compression, and compression–compression cyclic loads, as well as composite pressure vessels under cyclic loading. [ABSTRACT FROM AUTHOR]

This overview study investigates integrating advanced manufacturing technologies, specifically metal additive manufacturing (AM) and laser powder bed fusion (LPBF) processes, within Industry 4.0 and Industry 5.0 frameworks, to enhance sustainability and efficiency in industrial production and prototyping. The manufacturing sector, a significant contributor to global greenhouse gas emissions and resource consumption, is increasingly adopting technologies that reduce environmental impact while maintaining economic growth. Selective laser melting (SLM), as the subsection LPBF technologies, is highlighted for its capability to produce high-performance, lightweight, and complex components with minimal material waste, thus aligning with circular economy goals for metal alloys. Life cycle assessment (LCA) and life cycle costing (LCC) analyses are essential methods for evaluating the sustainability of any new technology. Sustainable technologies could support the concepts of the factory of the future (FoF), fulfilling the requirements of digital transformation and digital twins. This overview study reveals that implementing AM—specifically SLM—has the potential to reduce the environmental impact of manufacturing. It underscores the ability of these technologies to promote sustainable and efficient manufacturing practices, thereby accelerating the shift from Industry 4.0 to Industry 5.0. [ABSTRACT FROM AUTHOR]

This paper examines a discrete-time retrial queuing system that incorporates negative customers, system breakdowns, and repairs. In this model, an arriving customer has the option to go directly to the server, pushing the currently served customer, if any, to the front of the orbit queue, or to join the orbit based on a First-Come-First-Served (FCFS) discipline. The study also considers negative customers who not only remove the customer currently being served but also cause a server breakdown. An in-depth analysis of the model is conducted using a generating function approach, leading to the determination of the distribution and expected values of the number of customers in the orbit and the entire system. The paper explores the stochastic decomposition law and provides bounds for the difference between the steady-state distribution of this system and a comparable standard system. Recursive formulas for the steady-state distributions of the orbit and the system are developed. Additionally, it is shown that the studied discrete-time system can approximate the M/G/1 continuous-time version of the model. The research includes a detailed examination of the customer's sojourn time distribution in the orbit and the system, utilizing the busy period of an auxiliary system. The paper concludes with numerical examples that highlight how different system parameters affect various performance characteristics, and a section summarizing the key research contributions. [ABSTRACT FROM AUTHOR]