Explore the vast range of titles available.

The microbial‑induced carbonate precipitation (MICP), as an emerging biomineralization technology mediated by specific bacteria, has been a popular research focus for scientists and engineers through the previous two decades as an interdisciplinary approach. It provides cutting-edge solutions for various engineering problems emerging in the context of frequent and intense human activities. This paper is aimed at reviewing the fundaments and engineering applications of the MICP technology through existing studies, covering realistic need in geotechnical engineering, construction materials, hydraulic engineering, geological engineering, and environmental engineering. It adds a new perspective on the feasibility and difficulty for field practice. Analysis and discussion within different parts are generally carried out based on specific considerations in each field. MICP may bring comprehensive improvement of static and dynamic characteristics of geomaterials, thus enhancing their bearing capacity and resisting liquefication. It helps produce eco-friendly and durable building materials. MICP is a promising and cost-efficient technology in preserving water resources and subsurface fluid leakage. Piping, internal erosion and surface erosion could also be addressed by this technology. MICP has been proved suitable for stabilizing soils and shows promise in dealing with problematic soils like bentonite and expansive soils. It is also envisaged that this technology may be used to mitigate against impacts of geological hazards such as liquefaction associated with earthquakes. Moreover, global environment issues including fugitive dust, contaminated soil and climate change problems are assumed to be palliated or even removed via the positive effects of this technology. Bioaugmentation, biostimulation, and enzymatic approach are three feasible paths for MICP. Decision makers should choose a compatible, efficient and economical way among them and develop an on-site solution based on engineering conditions. To further decrease the cost and energy consumption of the MICP technology, it is reasonable to make full use of industrial by-products or wastes and non-sterilized media. The prospective direction of this technology is to make construction more intelligent without human intervention, such as autogenous healing. To reach this destination, MICP could be coupled with other techniques like encapsulation and ductile fibers. MICP is undoubtfully a mainstream engineering technology for the future, while ecological balance, environmental impact and industrial applicability should still be cautiously treated in its real practice.

This text provides an introduction to the cost modeling for electronic systems that is suitable for advanced undergraduate and graduate students in electrical, mechanical and industrial engineering, and professionals involved with electronics technology and development and management.

A four-compartmental fractional-order epidemic model has been investigated to understand the transmission mechanism of infectious diseases with the population’s memory effect. The existence and uniqueness criterion of the model solution of the proposed fractional-order model is verified. Utilizing the next-generation matrix method, a threshold quantity called, the basic reproduction number ( R 0 ) is obtained. The model possesses two equilibrium points, infection-free and endemic. The asymptotic stability (local and global) of the proposed system at the equilibrium points has been analyzed thoroughly. It is observed that the total number of infections during the disease is influenced by the fractional-order of the model which represents the population’s memory. A transcritical bifurcation is exhibited around the infection-free equilibrium point when the basic reproduction number crosses unity. Additionally, a fractional-order optimal control problem has been studied by considering two disease interventions: media awareness and treatment. The policy containing infectious disease spread has been determined based on a cost-effectiveness analysis. Sensitivity indices are computed to determine which parameters significantly impact R 0 and hence may used in controlling the disease. Some numerical simulations have been performed to verify analytical results by using MATLAB2022a.

Robots are perfect substitutes for skilled workforce on some repeatable, general, and strategically important tasks, but this substitution is not always feasible. Despite the evolution of robotics, some industries have been traditionally robot-reluctant because their processes involve large or specific parts and non-serialized products; thus, standard robotic solutions are not cost-effective. This work presents a novel approach for advanced manufacturing applied to the aerospace industry, combining the power and the repeatability of the robots with the flexibility of humans. The proposed approach is based on immersive and symbiotic collaboration between human workers and robots, presenting a safe, dynamic, and cost-effective solution for this traditionally manual and robot-reluctant industry. The proposed system architecture includes control, safety, and interface components for the new collaborative manufacturing process. It has been validated in a real-life case study that provides a solution for the manufacturing of aircraft ribs. The results show that humans and robots can share the working area simultaneously without physical separation safely, providing beneficial symbiotic collaboration and reducing times, risks, and costs significantly compared with manual operations.

A growing number of archaeologists are applying Geographic Information Science (GIS) technologies to their research problems and questions. Advances in GIS and its use across disciplines allows for collaboration and enables archaeologists to ask ever more sophisticated questions and develop increasingly elaborate models on numerous aspects of past human behavior. Least cost analysis (LCA) is one such avenue of inquiry. While least cost studies are not new to the social sciences in general, LCA is relatively new to archaeology; until now, there has been no systematic exploration of its use within the field. This edited volume presents a series of case studies illustrating the intersection of archaeology and LCA modeling at the practical, methodological, and theoretical levels. Designed to be a guidebook for archaeologists interested in using LCA in their own research, it presents a wide cross-section of practical examples for both novices and experts. The contributors to the volume showcase the richness and diversity of LCA’s application to archaeological questions, demonstrate that even simple applications can be used to explore sophisticated research questions, and highlight the challenges that come with injecting geospatial technologies into the archaeological research process.  

In this paper, an efficient event-triggered control is designed to address the leader-following consensus problem for the fractional-order multi-agent systems. First, in order to reduce the conservation of consensus criteria, a novel Wirtinger-based fractional-order integral inequality is proposed. Second, an adaptive control is designed by using a new event-triggered scheme without Zeno behavior, which can effectively reduce the communication cost in network. Later in order to analyze the consensus of the fraction-order leader-following systems, we employ a new approach based on fractional Lyapunov direct method. Finally, combining Wirtinger-based fractional-order integral inequality, the event-triggered adaptive control as well as the proposed consensus method, the consensus criteria of the leader-following fractional-order multi-agent systems are obtained. Two numerical examples are used to test the effectiveness and feasibility of the results presented in this study.

The realistic assessments of public health intervention strategies are of great significance to effectively combat the COVID-19 epidemic and the formation of intervention policy. In this paper, an extended COVID-19 epidemic model is devised to assess the severity of the pandemic and explore effective control strategies. The model is characterized by ordinary differential equations with seven-state variables, and it incorporates some parameters associated with the interventions (i.e., media publicity, home isolation, vaccination and face-mask wearing) to investigate the impacts of these interventions on the spread of the COVID-19 epidemic. Some dynamic behaviors of the model, such as forward and backward bifurcation, are analyzed. Specifically, we calibrate the model parameters using actual COVID-19 infected data in Brazil by Markov Chain Monte Carlo algorithm such that we can study the effects of interventions on a practical case. Through a comprehensive exploration of model design and analysis, model calibration, sensitivity analysis, implementation of optimal control problems and cost-effectiveness analysis, the rationality of our model is verified, and the effective strategies to combat the epidemic in Brazil are revealed. The results show that the asymptomatic infected individuals are the main drivers of COVID-19 transmission, and rapid detection of asymptomatic infections is critical to combat the COVID-19 epidemic in Brazil. Interestingly, the effect of the vaccination rate associated with pharmaceutical intervention on the basic reproduction number is much lower than that of non-pharmaceutical interventions (NPIs). Our study also highlights the importance of media publicity. To reduce the infected individuals, the multi-pronged NPIs have considerable positive effects on controlling the outbreak of COVID-19. The infections are significantly decreased by the early implementation of media publicity complemented with home isolation and face-mask wearing strategy. When the cost of implementation is taken into account, the early implementation of media publicity complemented with a face-mask wearing strategy can significantly mitigate the second wave of the epidemic in Brazil. These results provide some management implications for controlling COVID-19.

The integration of green‐gray infrastructures with advanced control approaches is revolutionizing the stormwater system retrofitting, emerging as an innovative strategy to mitigate urban flood risks. However, a major challenge lies in balancing the substantial investments of these infrastructure projects with their environmental benefits, such as reduced flooding volume and lower peak flow. Model predictive control (MPC), a dynamic and intelligent control approach, optimizes these environmental benefits but is underutilized in the system design phase for cost‐effectiveness analysis. This study introduces a multi‐scenario model framework that incorporates MPC and other control approaches into stormwater system designs, including the implementation of controlled storage tanks and green infrastructures. This framework provides comprehensive modeling tools for practitioners to evaluate the flood control benefits and costs across various infrastructure designs and control scenarios, ultimately identifying solutions that are both environmentally and economically viable. A case study conducted in a small urban catchment area in Shenzhen City, China, demonstrates the effectiveness of this framework. The results indicate that MPC outperforms other control scenarios, particularly under heavy or extreme rainfall conditions. Notably, MPC not only provides superior environmental benefits but also yields considerable cost savings, ranging from 1,787 to 9,371 USD per hectare compared to static control, equating to a 5% reduction in cost relative to rule‐based control. Such findings suggest that integrating MPC is a cost‐effective alternative to extensive infrastructure expansion for flood management, which significantly enhances the benefit contribution of controlled infrastructures without substantial additional expenses. Plain Language Summary Implementing advanced control methods for green‐gray infrastructures is a new method to reduce urban flooding. However, constructing and updating these infrastructures can be very expensive, which is a significant challenge for many urban areas. Our research explores how to use a smart control approach, specifically the model predictive control (MPC), to enhance environmental benefits and save money in the system design phase. We present a multi‐scenario model framework that combines MPC and other methods into the design of stormwater systems, which include controlled storage tanks and green infrastructures. This framework can be used to evaluate the flood control benefits and costs across various infrastructure designs and control scenarios, and to identify the solutions that are both environmentally and economically viable. We conducted a case study in Shenzhen City, China, to test our framework. The results show that MPC is effective particularly during heavy or extreme rainfalls, offering higher environmental benefits and cost savings compared to the scenarios without MPC. Integrating MPC is more cost‐effective than expanding infrastructures for flood management as it notably increases the benefit contribution of controlled infrastructures at a modest cost. Key Points A framework is proposed to assess the environmental and economic impacts of integrating model predictive control (MPC) with stormwater infrastructure designs Assessments are conducted in a small urban catchment involving heavy rainfall events The MPC yields higher environmental benefits and saves economic costs compared to other control approaches

Policy Points The World Health Organization has recommended sodium reduction as a “best buy” to prevent cardiovascular disease (CVD). Despite this, Congress has temporarily blocked the US Food and Drug Administration (FDA) from implementing voluntary industry targets for sodium reduction in processed foods, the implementation of which could cost the industry around$16 billion over 10 years. We modeled the health and economic impact of meeting the two‐year and ten‐year FDA targets, from the perspective of people working in the food system itself, over 20 years, from 2017 to 2036. Benefits of implementing the FDA voluntary sodium targets extend to food companies and food system workers, and the value of CVD‐related health gains and cost savings are together greater than the government and industry costs of reformulation. Context The US Food and Drug Administration (FDA) set draft voluntary targets to reduce sodium levels in processed foods. We aimed to determine cost effectiveness of meeting these draft sodium targets, from the perspective of US food system workers. Methods We employed a microsimulation cost‐effectiveness analysis using the US IMPACT Food Policy model with two scenarios: (1) short term, achieving two‐year FDA reformulation targets only, and (2) long term, achieving 10‐year FDA reformulation targets. We modeled four close‐to‐reality populations: food system “ever” workers; food system “current” workers in 2017; and subsets of processed food “ever” and “current” workers. Outcomes included cardiovascular disease cases prevented and postponed as well as incremental cost‐effectiveness ratio per quality‐adjusted life year (QALY) gained from 2017 to 2036. Findings Among food system ever workers, achieving long‐term sodium reduction targets could produce 20‐year health gains of approximately 180,000 QALYs (95% uncertainty interval [UI]: 150,000 to 209,000) and health cost savings of approximately $ 5.2 billion (95% UI:$3.5 billion to $ 8.3 billion), with an incremental cost‐effectiveness ratio (ICER) of$62,000 (95% UI: $ 1,000 to$171,000) per QALY gained. For the subset of processed food industry workers, health gains would be approximately 32,000 QALYs (95% UI: 27,000 to 37,000); cost savings, $ 1.0 billion (95% UI:$0.7bn to $ 1.6bn); and ICER,$486,000 (95% UI: $ 148,000 to $1,094,000) per QALY gained. Because many health benefits may occur in individuals older than 65 or the uninsured, these health savings would be shared among individuals, industry, and government. Conclusions The benefits of implementing the FDA voluntary sodium targets extend to food companies and food system workers, with the value of health gains and health care cost savings outweighing the costs of reformulation, although not for the processed food industry.