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The role of technology in education is becoming increasingly important, and the introduction of advanced technology and AI is transforming the way we learn. Virtual reality (VR) is an effective technology that enhances student engagement and improves learning outcomes. However, the cost of implementing VR is a significant concern for educational institutions, making integrating VR technology into education challenging. To address this challenge, this study aims to explore the costs associated with integrating VR into architectural, engineering, and construction (AEC) education. The study had three objectives: to identify relevant case studies that utilized VR in AEC education, to perform keyword analysis, and to conduct a cost analysis of the selected case studies. The thematic analysis identified VR applications in various categories, including VR platforms, construction safety training, design review simulators, civil engineering labs, building information modeling (BIM) integration, architectural design, and surveying engineering. The results revealed that the cost of VR varies based on the application, indicating that it is possible to implement VR in education even on a limited budget. This research provides valuable insights and recommendations for researchers and practitioners who want to adopt VR technology in AEC education effectively. [ABSTRACT FROM AUTHOR]

Background: The prevalence of neurological disorders is increasing worldwide. In recent decades, the conventional rehabilitation for people with neurological disorders has been often reinforced with the use of technological devices (robots and virtual reality). The aim of this systematic review was to identify the evidence on the economic cost of rehabilitation with robotic and virtual reality devices for people with neurological disorders through a review of the scientific publications over the last 15 years. Methods: A systematic review was conducted on partial economic evaluations (cost description, cost analysis, description of costs and results) and complete (cost minimization, cost-effectiveness, cost utility and cost benefit) studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The main data sources used were PubMed, Scopus and Web of Science (WOS). Studies published in English over the last 15 years were considered for inclusion in this review, regardless of the type of neurological disorder. The critical appraisal instrument from the Joanna Briggs Institute for economic evaluation and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) were used to analyse the methodological quality of all the included papers. Results: A total of 15 studies were included in this review. Ten papers were focused on robotics and five on virtual reality. Most of the studies were focused on people who experienced a stroke. The robotic device most frequently used in the papers included was InMotion® (Bionik Co., Watertown, MA, USA), and for those focused on virtual reality, all papers included used semi-immersive virtual reality systems, with commercial video game consoles (Nintendo Wii® (Nintendo Co., Ltd., Kyoto, Japan) and Kinect® (Microsoft Inc., Redmond, WA, USA)) being used the most. The included studies mainly presented cost minimization outcomes and a general description of costs per intervention, and there were disparities in terms of population, setting, device, protocol and the economic cost outcomes evaluated. Overall, the methodological quality of the included studies was of a moderate level. Conclusions: There is controversy about using robotics in people with neurological disorders in a rehabilitation context in terms of cost minimization, cost-effectiveness, cost utility and cost benefits. Semi-immersive virtual reality devices could involve savings (mainly derived from the low prices of the systems analysed and transportation services if they are applied through telerehabilitation programmes) compared to in-clinic interventions. [ABSTRACT FROM AUTHOR]

Wastewater reuse is a proven strategy to mitigate water stress in drought-prone regions. However, this practice is still limited due to high implementation costs, regulatory hurdles, and limited public acceptance. In regions with low reclaim rates, a thorough evaluation of the potential for reuse is needed to support decision-making, focusing on opportunities that address both low-hanging fruit and high-leverage projects. This paper introduces a streamlined, data-centric methodology for assessing wastewater reuse potential, adaptable to various regional contexts. The methodology involves comprehensive data collection and processing to evaluate wastewater treatment plant (WWTP) capabilities and identify potential users, allowing the prioritisation of case studies based on demand alignment. Different treatment and distribution systems are analysed to match WWTP capabilities with user needs, considering volume, quality, and infrastructure requirements. Cost analysis incorporates capital expenditure (CAPEX), operational expenditure (OPEX) and unit costs using novel cost functions for treatment and distribution. Risk analysis adheres to WHO methodology to ensure safety and sustainability. A case study in the Lisbon and Oeste areas in Portugal validates this approach, revealing key insights into the potential and economic viability of water reuse. By comparing tariffs and costs associated with different reuse scenarios, this paper offers benchmarks for the economic feasibility of reuse projects. [ABSTRACT FROM AUTHOR]

The strain-hardening geopolymer composite (SHGC) is a new type of fiber concrete with excellent ductility and environmental friendliness. However, the high cost of fibers greatly limits its widespread application. This paper proposes the use of untreated low-cost polyvinyl alcohol (PVA) fibers and polyethylene (PE) fibers to develop a low-cost, high-performance SHGC. Axial compression and axial tension tests were conducted on the SHGC with different PE fiber volume fractions (1%, 1.5%, and 2%) and different PVA fiber replacement ratios (0%, 25%, 50%, 75%, and 100%) to investigate the hybrid effects of fibers with different surface properties and to reveal the mechanism of fiber hybridization on the mechanical behavior of SHGCs. The results show that increasing the PE fiber volume fraction improves the compressive and tensile ductility of the SHGC while increasing the PVA fiber replacement rate impacts the strength indicators positively due to the good interface effect formed between its hydrophilic surface and the matrix. When the PVA fiber replacement ratio is 100%, the compressive strength (93.4 MPa) of the SHGC is the highest, with a 21.1% increase compared to the control group. However, the tensile strength shows a trend of first increasing and then decreasing with the increase in the PVA fiber replacement ratio, reaching the highest at a 25% replacement ratio, with a 12.5% increase compared to the control group. Furthermore, a comprehensive analysis of the economic and environmental performance of the SHGC indicates that a 25% PVA fiber replacement ratio results in the best overall economic benefits and relatively low actual costs, although the effect of fiber hybridization on carbon emission indicators is not significant. This paper provides new ideas and a theoretical basis for designing low-cost SHGCs. [ABSTRACT FROM AUTHOR]

The U.S. dairy sector is a significant emitter of methane and nitrous oxide, with the US EPA estimating it produced around 90 Tg CO2 eq. in 2021. This paper reviews the literature on and evaluates various mitigation actions for reducing GHG emissions in the U.S. dairy sector, focusing on both direct and indirect emission sources. We conducted a narrative literature review based on the cradle to gate life-cycle assessment method, covering the entire dairy supply chain up until milk enters retail establishments, including dairy and feed producing farm practices, processing, transportation, and their associated emissions/costs. The papers included were selected over a three year process depending on discussions with experts and issues mentioned in the emerging literature. We review significant opportunities for the U.S. dairy sector to reduce emissions, particularly through improved enteric fermentation and manure management practices. Additionally, we cover the potential for mitigating indirect emissions from feed production, processing, and transportation, areas less frequently covered in existing studies. This review also covers a gap in the literature by integrating economic findings including cost analysis and incentives to mitigate based on the social value of emissions reductions. [ABSTRACT FROM AUTHOR]

Operating time series data collected and stored in historian must be managed to extract their full potential. Part 1 of this paper proposed a structured way (a sophisticated approach) to process industrial data; this first part explains in detail the data processing framework used as the basis for the costing analysis present in the second part of this series. The framework considers the analysis scope definition, data management steps, and operating regimes detection and identification. The added value of this proposed framework is demonstrated in Part 2 via the use of cost accounting for operational problem-solving (debottlenecking), i.e., its practicality is validated via its application alongside a cost analysis on the brownstock washing department of a kraft pulp mill. The traditional debottlenecking approach assumes a single operating condition considering that operating regimes allow for a much more sophisticated debottlenecking study of the washing department. With the use of operations-driven cost modeling (contingent on activity-based costing concepts) and processed time series data corresponding to steady-state operation, incremental profit can be assigned to each operating regime in order to identify the most cost-efficient one. The overall objective of this two-part series is to convert processed industrial steady-state data and cost information into knowledge that can be used to optimize the washing department of a chemical pulp mill. More specifically, different operating regimes are assessed, and the most suitable operating strategy is defined. The application of activity-based costing on a large amount of historically processed industrial data led to the improvement in the operation. The identified optimal way to operate (pulp throughput, pulp conductivity, defoamer and bleaching chemical quantity, etc.) led to a profit of CAD 49 M per year. Lastly, a contribution analysis of the regimes based on PCA highlighted how the process was operated when the preferred performances happened. [ABSTRACT FROM AUTHOR]

Process variations during manufacturing lead to differences in the performance of the chips. In order to better utilize the performance of the chips, it is necessary to perform maximum operation frequency ( F m a x ) tests to place the chips into different speed bins. For most F m a x tests, significant efforts are put in place to reduce test cost and improve binning accuracy; e.g., our conference paper published in ICICM 2017 presents a novel binning sensor for low-cost and accurate speed binning. However, by promoting chips placed at the lower bins, because of conservative binning, into higher bins, the overall profit can greatly increase. Therefore, this paper, extended based on a conference paper, presents a novel and adaptive methodology for speed binning, in which the paths impacting the speed bin of a specific IC are identified and adapted by our proposed on-chip Binning Checker and Binning Adaptor. As a result, some parts at a bin margin can be promoted to higher bins. The proposed methodology can be used to optimize the F m a x yield of a digital circuit when it has redundant timing in clock tree, and it can be integrated into current F m a x tests with low extra cost. The proposed adaptive system has been implemented and validated on five benchmarks from ITC, ISCAS89, and OpenSPARCT2 core on 28 nm Altera FPGAs. Measurement results show that the number of higher bin chips is improved by 7–16%, and our cost analysis shows that the profit increase is between 1.18% and 3.04%. [ABSTRACT FROM AUTHOR]

Floating offshore wind (FOW) is rapidly gaining interest due to its large potential. In this regard, it is of special interest to determine the best locations for its installation. One of the main aspects when evaluating the feasibility of a project is the levelised cost of energy (LCOE), but there are many variables to consider when calculating it for FOW, and plenty of them are hard to find when the scope is all the suitable areas worldwide. This paper presents the calculation and analysis of the global LCOE with particular focus on the best countries and territories from an economic point of view, considering four types of platforms: semi-submersible, barge, spar, and tension leg platform (TLP). The model takes into account, on the one hand, wind data, average significant wave height, and distance to shore for an accurate calculation of delivered energy to the onshore substation and, on the other hand, bathymetry, distances, and existing data from projects to find appropriate functions for each cost with regression models (e.g., manufacturing, installation, operation and maintenance (O&M), and decommissioning costs). Its results can be used to assess the potential areas around the world and identify the countries and territories with the greatest opportunities regarding FOW. The lowest LCOE values, i.e., the optimal results, correspond to areas where wind resources are more abundant and the main variables of the site affecting the costs (water depth, average significant wave height, distance to shore, and distance to port) are as low as possible. These areas include the border between Venezuela and Colombia, the Canary Islands, Peru, the border between Western Sahara and Mauritania, Egypt, and the southernmost part of Argentina, with LCOEs around 90 €/MWh. Moreover, there are many areas in the range of 100–130 €/MWh. [ABSTRACT FROM AUTHOR]

In this paper, a bulk arrival and two-phase bulk service with active Bernoulli feedback, vacation, and breakdown is considered. The server provides service in two phases as mandatory according to the general bulk service rule, with minimum bulk size ′ a ′ and maximum bulk size ′ b ′ . In the first essential service (FES) completion epoch, if the server fails, with probability ′ δ ′ , then the renewal of the service station is considered. On the other hand, if there is no server failure, with a probability ′ 1 − δ ′ , then the server switches to a second essential service (SES) in succession. A customer who requires further service as feedback is given priority, and they join the head of the queue with probability β . On the contrary, a customer who does not require feedback leaves the system with a probability ′ 1 − β ′ . If the queue length is less than ′ a ′ after SES, the server may leave for a single vacation with probability ′ 1 − β ′ . When the server finds an inadequate number of customers in the queue after vacation completion, the server becomes dormant. After vacation completion, the server requires some time to start service, which is attained by including setup time. The setup time is initiated only when the queue length is at least ′ a ′ . Even after setup time completion, the service process begins only with a queue length 'N' (N > b). The novelty of this paper is that it introduces an essential two-phase bulk service, immediate Bernoulli feedback for customers, and renewal service time of the first essential service for the bulk arrival and bulk service queueing model. We aim to develop a model that investigates the probability-generating function of the queue size at any time. Additionally, we analyzed various performance characteristics using numerical examples to demonstrate the model's effectiveness. An optimum cost analysis was also carried out to minimize the total average cost with appropriate practical applications in existing data transmission and data processing in LTE-A networks using the DRX mechanism. [ABSTRACT FROM AUTHOR]

The impact of disability on people's lives is often underestimated because the extra costs of living with a disability are not accounted for. This paper analyzes several different methodologies for estimating those costs and explores their usefulness in designing inclusive social policies. For example, one approach is to measure what is currently being spent, while another is to estimate what would need to be spent for equal participation. These can be measured using statistical techniques or through a more qualitative methodology. Each of these methods has its advantages and disadvantages. The paper concludes with recommendations for which methodology fits which purpose, and how they can be used together to obtain a full accounting of the extra costs incurred by people with disabilities. [ABSTRACT FROM AUTHOR]

A well-designed institutional arrangement for urban village redevelopment projects (UVRPs) must consider transaction costs, but academic papers discussing it from the perspective of transaction cost economics are lacking. This paper applies theory of transaction cost economics to analyse the types and sizes of transaction costs and who bears these costs during redevelopment when implementing UVRPs in China. This paper finds that transactions in UVRPs have high asset specificity, high uncertainty and low frequency, which easily results in high levels of transaction costs. Based on 439 UVRPs collected from seven cities, this paper finds that UVRPs implemented with top–down institutional arrangements remain prevalent in China. Based on semi-structured interviews with participating parties, this paper proves that the sizes and types of transaction costs and the distribution of these costs borne by different participating parties vary with the change of stage under dissimilar institutional arrangements. This implies that a high level of transaction costs at one stage does not necessarily mean the costs stay high at another stage. Transaction costs have essential implications for process efficiency, so policymakers need to consider transaction costs and use hybrid institutional arrangements to enhance the efficiency and sustainability of policies. [ABSTRACT FROM AUTHOR]

The selection of an appropriate construction method stands as a pivotal decision in ensuring the success of any building project. This paper undertakes a comprehensive comparative analysis of cost and timeline implications between the top-down and bottom-up construction methodologies. The research focuses on ten distinct underground structure models, each characterized by varying depths and base areas. Through rigorous design and analysis, the cost and projected duration for each model are meticulously evaluated under the lens of both top-down and bottom-up construction techniques. The findings reveal that while the bottom-up approach emerges as the most cost-effective alternative at a depth of 8 m, the top-down method exhibits superior cost efficiency with increasing depth. Interestingly, alterations in the structure's base area exert a minimal influence on the cost differentials between the two methodologies. Moreover, the top-down construction method consistently outshines its counterpart in terms of project duration across all ten models examined, with the percentage increase in base area yielding insignificant impacts on project timeline discrepancies. This study furnishes construction project managers with invaluable insights to navigate the complexities of method selection. By judiciously considering parameters such as project scale, depth, and base area, managers can strategically optimize both cost and timeline outcomes, thereby facilitating the seamless execution of construction projects. [ABSTRACT FROM AUTHOR]

This work presents an innovative application of optimal control theory to the strategic scheduling of battery storage in the day-ahead electricity market, focusing on enhancing profitability while factoring in battery degradation. This study incorporates the effects of battery degradation on the dynamics in the optimisation framework. Considering this cost in economic analysis and operational strategies is essential to optimise long-term performance and economic viability. Neglecting degradation costs can lead to suboptimal operation and dispatch strategies. We employ a continuous-time representation of the dynamics, in contrast with many other studies that use a discrete-time approximation with rather coarse intervals. We adopt an equivalent circuit model coupled with empirical degradation parameters to simulate a battery cell's behaviour and degradation mechanisms with good support from experimental data. Utilising direct collocation methods with mesh refinement allows for precise numerical solutions to the complex, nonlinear dynamics involved. Through a detailed case study of Belgium's day-ahead electricity market, we determine the optimal charging and discharging schedules under varying objectives: maximising net revenues, maximising profits considering capacity degradation, and maximising profits considering both capacity degradation and internal resistance increase due to degradation. The results demonstrate the viability of our approach and underscore the significance of integrating degradation costs into the market strategy for battery operators, alongside its effects on the battery's dynamic behaviour. Our methodology extends previous work by offering a more comprehensive model that empirically captures the intricacies of battery degradation, including a fine and adaptive time domain representation, focusing on the day-ahead market, and utilising accurate direct methods for optimal control. This paper concludes with insights into the potential of optimal control applications in energy markets and suggestions for future research avenues. [ABSTRACT FROM AUTHOR]

Ensuring accountability and integrity in MQTT communications is important for enabling several IoT applications. This paper presents a novel approach that combines blockchain technology and the interplanetary file system (IPFS) to achieve non-repudiation and data integrity in the MQTT protocol. Our solution operates in discrete temporal rounds, during which the broker constructs a Merkle hash tree (MHT) from the messages received. Then the broker publishes the root on the blockchain and the MHT itself on IPFS. This mechanism guarantees that both publishers and subscribers can verify the integrity of the message exchanged. Furthermore, the interactions with the blockchain made by the publishers and the broker ensure they cannot deny having sent the exchanged messages. We provide a detailed security analysis, showing that under standard assumptions, the proposed solution achieves both data integrity and accountability. Additionally, we provided an experimental campaign to study the scalability and the throughput of the system. Our results show that our solution scales well with the number of clients. Furthermore, from our results, it emerges that the throughput reduction depends on the integrity check operations. However, since the frequency of these checks can be freely chosen, we can set it so that the throughput reduction is negligible. Finally, we provided a detailed analysis of the costs of our solution showing that, overall, the execution costs are relatively low, especially given the critical security and accountability benefits it guarantees. Furthermore, our analysis shows that the higher the number of subscribers in the system, the lower the costs per client in our solution. Again, this confirms that our solution does not present any scalability issues. [ABSTRACT FROM AUTHOR]

This paper presents a new layered plaster-based material for building purposes. First, a new manufacturing machine was designed to make the elaboration process easier. This manufacturing machine and the way it works are described. In this study, perlite and recycled glass wool (RGW) were added to traditional plaster with the aim of improving the performance of this material. Two series (with and without perlite) and three different layer configurations were developed and assessed. Recycled glass wool layered materials were subjected to both physical and mechanical characterisation to determine their suitability for precast elaboration. The addition of perlite resulted in a significant improvement in flexural strength. Moreover, the addition of RGW also gave rise to extra flexural strength when added. The two-layered samples performed better than the one-layered samples. Mechanical properties increased up to 75% when both the perlite and RGW layers were added. Potential Global Warming Potential (GWP 100) savings were also analysed, reporting up to 49% savings. A complementary cost analysis was performed, aimed at establishing potential savings in production costs; thus, 13–57% potential cost savings were reported. After that, a comparative analysis within the literature was conducted to contextualise the results obtained in this study. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) play a crucial role in tertiary sectors due to their eco-friendliness and sustainability when powered by clean energy. Integrating EV charging stations with renewable energy systems is essential to alleviate energy issues and grid pressure. Exploring this integration's feasibility is imperative for sustainable transportation. This study aims to provide a clear approach and methodology for examining the potential of integrating renewable energy technologies with EV charging stations at the district level. Additionally, the study investigates the energy, economic, and environmental benefits of an integrated system comprising photovoltaic/wind turbines (PV/WTs) connected to the electricity grid to meet the energy demand of a tertiary district consisting of five hotels in Egypt. Through the development of a simulation model, the paper verifies whether the proposed energy system can meet the district's energy demand. In addition, the simulation model has been employed to conduct a sensitivity analysis for investigating the impact of different charging rates on economic feasibility. The results indicate that a hybrid renewable energy system (HRES) integrated with an EV charging station can effectively relieve pressure on the electricity grid and provide electricity at competitive prices compared to the national grid. Moreover, the proposed energy system significantly reduces environmental emissions by up to 510 tons of CO2 per year and has the potential to decrease fossil fuel usage by 248 tons per year. Sensitivity analysis highlights the significant impact of charging prices on project profitability. [ABSTRACT FROM AUTHOR]

The reactive power (RP) control of the high voltage alternating current transmission system (HVAC TS) for offshore wind farms (OWFs) is a crucial task to assure the consistent and efficient operation of the system. The importance of RP compensation (RPC) in power system operation is to maintain voltage stability and reduce power losses. Offshore wind farms present unique challenges for power system operation due to their distance from the onshore grid, variable wind conditions, and complex electrical infrastructure. The HVAC TS is common for OWFs as it is well-suited for transmitting large amounts of power over long distances. In this paper, a literature-based analysis helps in improving the operation and reliability of OWFs, ultimately leading to greater renewable energy utilization. This paper concludes that optimal RPC is a critical task for ensuring the stable and efficient operation of HVAC TSs for OWFs. Advanced control and optimization techniques can help achieve an optimal RPC, thereby minimizing TLS and improving the overall system efficiency. Furthermore, the study investigates the possible benefits of incorporating novel technologies and approaches, such as RESs, into the power compensation process. By offering insightful information on how to optimize HVAC TSs for OWFs, for example, subsea power cables with multiple layers must be used to carry electricity from large offshore wind farms, the development of more sustainable and effective energy solutions is possible. The research concludes by stating that ensuring the steady and effective operation of HVAC TSs for OWFs is a crucial responsibility. Advanced optimization and control solutions can reduce TLS and increase system efficiency by assisting in achieving the optimal RPC. [ABSTRACT FROM AUTHOR]

Blockchain technology (BCT) can enable distributed collaboration, enhance data sharing, and automate back-end processes for digital twin (DT) decentralized applications (dApps) in the construction industry (CI) 4.0. The aim of this paper was to propose a software architecture and to develop a framework of smart contracts for blockchain-based digital twin (BCDT) dApps throughout the lifecycle of projects in CI 4.0. This paper leveraged the existing literature and action research interviews to identify and validate the critical industry problems, functional requirements (FRs), and non-functional requirements (NFRs) to be addressed by BCDT dApps in CI 4.0. Basic use cases were developed to design a framework of smart contracts for BCDT dApps throughout the lifecycle of projects. The analysis of an online survey was used to identify the key requirements and enablers to propose a software architecture for BCDT applications and to validate the requirements for developing the framework of a smart contract for BCDTs. The findings were: (1) The identification of key problems in CI 4.0 for each BIM/BCDT dimension (3D, 4D, 5D, 6D, 7D, 8D, and contractual (cD)) and the related FRs and NFRs for BCDT applications. Additionally, key use cases were designed to address the problems identified. (2) The proposed BCDT architecture permitted us to narrow gaps in the literature on blockchain-based decentralized digital twins. Moreover, the proposed BCDT architecture and smart-contract framework addressed the main requirements in the literature on BCDTs. (3) The study leveraged the non-fungible token (NFT) standard to develop a framework for smart contracts that addressed the key use cases and the related industry problems and functional requirements that were identified. The study also considered the contractual dimension (cD) as an overarching dimension in relation to the other BCDT dimensions. (4) We also compared the costs of several public blockchains for executing the proposed smart-contract framework throughout the lifecycle of a medium-sized building project. The cost analysis permitted the development of criteria to evaluate the suitability of blockchain networks for BCDT applications in CI 4.0 depending on the principal blockchain networks' properties (security, decentralization, scalability, and interoperability). Finally, this study resulted in a novel framework that included software architecture, smart-contract use cases, and selection criteria among blockchain networks for BCDT dApps in CI 4.0. [ABSTRACT FROM AUTHOR]

Enhancing energy efficiency in buildings plays a pivotal role in realizing the ambitious objective of achieving carbon neutrality by 2050, as outlined in the European Green Deal. Roofs represent the technical element most affected by energy phenomena related to heat transfer: in winter, roofing can lose up to 35% of heat, and the summer heat flux can even be higher. This paper provides a catalogue of optimized and sustainable solutions, with a specific focus on standardization and prefabrication principles, for enhancing the energy efficiency of the most prevalent types of roofs that characterize the national residential building heritage. The methodological approach that guided the research presented in this article was based on the identification and study of the most common roofings in the diverse national residential building heritage, followed by their classification according to their construction era. In the context of essential energy retrofitting of deteriorated residential building stock, 21 optimized standardized solutions have been identified. The outcome of performance evaluations of the proposed solutions allowed the implementation of a matrix that can be a valuable support for designers in selecting the most efficient precalculated and prefabricated solutions for the national residential building heritage based on energy performance and sustainability criteria. [ABSTRACT FROM AUTHOR]

In the context of emissions, carbon dioxide constitutes a predominant portion of greenhouse gases (GHGs), leading to the use of the term "carbon" interchangeably with these gases in climate-related discussions. The carbon market has emerged as a pivotal mechanism for emission regulation, allowing industries that struggle to meet emission reduction targets to acquire credits from those who have successfully curbed their emissions below stipulated levels. Thermoeconomics serves as a tool for analyzing multiproduct systems prevalent in diverse sectors, including sugarcane and alcohol mills, paper and pulp industries, steel mills, and cogeneration plants. These systems necessitate frameworks for equitable cost/emission allocation. This study is motivated by the need to expand the scope of thermoeconomic modeling to encompass expenses or revenues linked with the carbon market. By utilizing a cogeneration system as a representative case, this research aims to demonstrate how such modeling can facilitate the allocation of carbon market costs to final products. Moreover, it underscores the adaptability of this approach for internalizing other pertinent costs, encompassing expenses associated with environmental control devices, licenses, and permits. Although certain exergy disaggregation models depict an environmental component within diagrams, which is integral for addressing environmental burdens, even models without explicit environmental devices can effectively internalize carbon credits and allocate them to final products. The integration of carbon credits within thermoeconomic modeling introduces the capability to assess both the financial and environmental implications of emissions. This integration further incentivizes the reduction in GHGs and supports optimization endeavors concerning system design and operation. In summary, this study delves into the incorporation of carbon market dynamics into thermoeconomic modeling. It demonstrates the potential to allocate carbon-related costs, facilitates comprehensive cost analysis, encourages emission reduction, and provides a platform for enhancing system efficiency across industrial sectors. [ABSTRACT FROM AUTHOR]

Background: This study, using real-world data, assesses the impact of RS testing on treatment pathways and the associated economic consequences of such testing. This paper pertains to lobular breast cancer. Methods: A retrospective, observational study was undertaken between 2011 and 2019 on a cross-section of hormone receptor-positive (HR+), HER2-negative, lymph node-negative, early-stage breast cancer patients. All patients had ILC and had RS testing in Ireland. The patient population is representative of the national population. Patients were classified as low (RS ≤ 25) or high (RS > 25) risk. Patients aged ≤50 were stratified as low (RS 0–15), intermediate (RS 16–25), or high risk (RS > 25). Results: A total of 168 patients were included, most of whom had grade 2 (G2) tumors (n = 154, 92%). Overall, 155 patients (92.3%) had low RS (≤25), 12 (7.1%) had high RS (>25), and 1 (0.6%) had unknown RS status. In 29 (17.5%) patients aged ≤50 at diagnosis, RS was ≤15 in 16 (55%), 16–20 in 6 (21%), 21–25 in 5 (17%), >25 in 1 (3.5%), and unknown in 1 (3.5%). Post RS testing, 126 patients (78%) had a change in chemotherapy recommendation; all to hormone therapy. In total, only 35 patients (22%) received chemotherapy. RS testing achieved a 75% reduction in chemotherapy use, resulting in savings of €921,543.84 in treatment costs, and net savings of €387,283.84. Conclusions: The use of this test resulted in a 75% reduction in chemotherapy and a significant cost savings in our publicly funded health system. [ABSTRACT FROM AUTHOR]

Photosynthetically Active Radiation (PAR) is an important parameter in the plant photosynthesis process, which can relate to plant growth, crop water use, and leaf gas exchange. Previously, many researchers utilized commercially available sensors to monitor PAR. The high cost of the commercially available PAR sensors has limited researchers, agricultural professionals, and farmers to use and expand PAR monitoring in agricultural lands. Thus, this paper focuses on designing an affordable Internet of Things (IoT)-based PAR sensor monitoring system including 3D-printed enclosures (waterproof) for the sensors, performance evaluation of multiple light sensors, solar powering configuration, cloud setup, and cost analysis. Three sensors, including VTB8440BH photodiode, SI 1145, and LI-190R sensors, were evaluated. The 3D-printed waterproof enclosures were designed for the photodiode and SI 1145. Particle Boron was used for recording and sending the sensor data to the IoT webserver. Both the photodiode and SI 1145 were compared to LI-190R, which is the industry standard. In the calibration process, the R2 values of the photodiode and SI 1145 with LI-190R were 0.609 and 0.961, respectively. Field validation data shows that SI 1145 had a strong correlation with LI-190R. In addition, the performance evaluation data shows the photodiode had a weaker correlation with LI-190R than SI 1145. In conclusion, the study successfully developed and designed affordable and reliable IoT-based PAR sensor monitoring systems, including a 3D-printed housing, hardware, programming, and IoT website. SI 1145 with a glass filter is an alternative sensor to monitor PAR at a low cost and has the advantage of being connected to IoT microcontrollers. [ABSTRACT FROM AUTHOR]

The cost of producing one cubic meter of concrete structure, depending on the structure's shape, type, and complexity, can be variously high. The cost of concrete, reinforcement, formwork, and labor ratio varies. But unlike the cost of concrete and reinforcement, which tend to be similar in the terms of the conditions of a particular construction project, the cost of formwork and work with it are different for different contractors. It often depends on the appropriateness of the formwork system used, the optimal placement of the formwork sets, the minimization of downtime, and the efficiency of the carpenters' work. Formwork modeling in the construction preparation phase intervenes in this planning area, where construction sources are defined and quantified, and the time course of their deployment is determined. The current paper deals with optimizing formwork selection and deployment in concrete structure execution. Even if several requirements must be considered when selecting and modeling the formwork (e.g., construction time, quality of concrete structure, etc.), an effort to minimize the cost of formwork, and thus construction cost, plays the most significant role. A dynamic model for effective and optimal planning of formwork in construction projects, including formwork cost analysis, is presented in the paper. The included case study demonstrated the planning of the formwork through a software application developed based on the computational algorithm of the dynamic model presented. A case study is presented in the article as a research method. An office building with five above-ground floors and one underground floor was chosen for the case study. To solve the case study, the formwork for horizontal structures (i.e., beams and slabs) is considered. The goal of the case study is to identify research questions and apply time and cost optimization to a selected specific building. [ABSTRACT FROM AUTHOR]

Background: UAVs (Unmanned Aerial Vehicles) and SUGVs (Sidewalk Unmanned Ground Vehicles) are two prominent options to revolutionize last mile home delivery. However, there is no literature yet addressing a comprehensive assessment of them. To bridge this research gap, this paper aimed to compare UAVs to SUGVs in the context of urban parcel delivery from a practical, conceptual, technological, commercial, and environmental perspective. Methodology: Based on structured literature and web research, this paper provided a comparative status quo review of these two delivery concepts. We introduced a parameter-based cost calculus model to estimate the costs per shipment for each technology. To detect the key cost drivers, we applied a one-way sensitivity analysis, as well as a "full factorial design of experiment" approach. Results: These key cost drivers for both operations are the "number of vehicles per operator" and the "average beeline service radius". From today's commercial point of view, our model indicated better profitability of SUGVs. However, technical and regulatory developments may render different results in the future. As SUGVs emit significantly less noise than UAVs, we assume that SUGVs have an additional advantage for usage in autonomous urban last mile delivery from a resident's perspective. Conclusions: Both key cost drivers will significantly influence the commercial viability of unmanned home delivery services. Safety and security aspects will determine regulatory rules on "number of vehicles per operator". To increase the "average beeline service radius", UAVs could profit from mothership delivery concepts while SUGV delivery may co-use existing public transport infrastructure. [ABSTRACT FROM AUTHOR]

Consider a set of k identical asynchronous mobile agents located in an anonymous ring of n nodes. The classical Gather (or Rendezvous) problem requires all agents to meet at the same node, not a priori decided, within a finite amount of time. This problem has been studied assuming that the network is safe for the agents. In this paper, we consider the presence in the ring of a stationary process located at a node that disables any incoming agent without leaving any trace. Such a dangerous node is known in the literature as a black hole, and the determination of its location has been extensively investigated. The presence of the black hole makes it deterministically unfeasible for all agents to gather. So, the research concern is to determine how many agents can gather and under what conditions. In this paper we establish a complete characterization of the conditions under which the problem can be solved. In particular, we determine the maximum number of agents that can be guaranteed to gather in the same location depending on whether k or n is unknown (at least one must be known). These results are tight: in each case, gathering with one more agent is deterministically unfeasible. All our possibility proofs are constructive: we provide mobile agent algorithms that allow the agents to gather within a predefined distance under the specified conditions. The analysis of the time costs of these algorithms show that they are optimal. Our gathering algorithm for the case of unknown k is also a solution for the black hole location problem. Interestingly, its bounded time complexity is Θ (n) ; this is a significant improvement over the existing O (n log n) bounded time complexity. [ABSTRACT FROM AUTHOR]

This paper considers a construction procedure of a satellite reference angular motion in the vicinity of an unstable gravitational equilibrium position. The satellite is stabilized on the reference trajectory by the magnetic coils. The problem is solved in several stages. An optimization problem to be solved by the particle swarm optimization method is formulated at each stage. Cost functions are based on the linearized model analysis. The main stage is the construction of a special reference motion, which provides the minimum control torque projection on the geomagnetic induction vector. Optimal geomagnetic field dipole approximation for a given time interval is considered to reduce tracking errors. The paper compares combinations of different cost functions in terms of the terminal attitude accuracy in the presence of perturbations. [ABSTRACT FROM AUTHOR]

This paper presents the cloud vendor lock-in prediction framework (CVL), which aims to address the challenges that arise from vendor lock-in in cloud computing. The framework provides a systematic approach to evaluate the extent of dependency between service providers and consumers and offers predictive risk analysis and detailed cost assessments. At the heart of the CVL framework is the Dependency Module, which enables service consumers to input weighted factors that are critical to their reliance on cloud service providers. These factors include service costs, data transfer expenses, security features, compliance adherence, scalability, and technical integrations. The research delves into the critical factors that are necessary for dependency calculation and cost analysis, providing insights into determining dependency levels and associated financial implications. Experimental results showcase dependency levels among service providers and consumers, highlighting the framework's utility in guiding strategic decision-making processes. The CVL is a powerful tool that empowers service consumers to proactively navigate the complexities of cloud vendor lock-in. By offering valuable insights into dependency levels and financial implications, the CVL aids in risk mitigation and facilitates informed decision-making. [ABSTRACT FROM AUTHOR]

Augmented reality (AR) is a virtual technology that integrates virtual information and objects into real environments, offering unprecedented possibilities in such fields such as architecture, education, and healthcare. Real-time communication and security protocols are critical to the successful deployment of AR applications to ensure user immersion, prevent motion sickness, and address security problems. This paper proposes a secure user-to-user (U2U) and user-to-infrastructure (U2I) authentication protocol suitable for edge computing-based AR environments. We also employ extended Chebyshev chaotic maps and physical unclonable functions to ensure security and efficiency during the authentication process. The proposed protocol initiates session keys after U2I authentication when an AR user enters the edge node area, facilitating secure U2U authentication for sharing data with nearby users. We conduct comprehensive studies of the security robustness of the proposed protocol using formal and informal analyses, including "Burrows–Abadi–Needham logic", "Real-Or-Random model", the "Scyther tool" and informal security analyses. Furthermore, we measure the performance of cryptographic primitives using the "Multiprecision Integer and Rational Arithmetic Cryptographic Library" Cryptographic SDK. We perform a comparative analysis of security features and functionality, and we conduct a computational and communication cost analysis. The results reveal that the proposed protocol can provide security and efficiency for edge computing-based AR environments, presenting the methods for seamless and secure real-time AR data exchanges for U2I and U2U communications. [ABSTRACT FROM AUTHOR]

In this paper, we present a study on transferring human motions to a humanoid robot for stable and precise task execution. We employ a whole-body motion imitation system that considers the stability of the robot to generate a stable reproduction of the demonstrated motion. However, the initially acquired motions are usually suboptimal. To successfully perform the desired tasks, the transferred motions require refinement through reinforcement learning to accommodate the differences between the human demonstrator and the humanoid robot as well as task constraints. Our experimental evaluation investigates the impact of different cost function terms on the overall task performance. The findings indicate that the selection of an optimal combination of weights included in the cost function is of great importance for learning precise reaching motions that preserve both the robot's postural balance and the human-like shape of the demonstrated motions. We verified our methodology in a simulated environment and through tests on a real humanoid robot, TALOS. [ABSTRACT FROM AUTHOR]

The issue of transport in underground hard coal mines is very rarely described in the literature. The financial aspects of this issue are even less often analyzed. Publications in this area focus on technical issues and the safety of mining crews. More attention is paid to transport in open-pit mines. The above premises and practical needs imply the need to conduct economic analyses of transport systems in underground hard coal mines. This paper is a scientific communication, which presents the concept of a multi-criteria cost analysis as a tool to support the selection of the optimal transportation option in an underground hard coal mine. Considerations in this area have not been carried out in the relevant literature, and the problem of selecting a transportation option is a complex and necessary issue in the practice of underground mines with extensive mine workings. The methodology presented includes five cost criteria (costs of carrying out the transportation task; route expansion costs; rolling stock maintenance costs; depreciation costs; and additional personnel costs). The simultaneous application of criteria relating to utility properties in addition to cost criteria makes it possible to adopt a specific technical and organizational model of the transportation system based on the indication of the optimal solution, resulting from the mathematical construction of functions of objectives relating to utility and cost. The optimal variant of the designed system and configuration of the material transportation system in underground workings takes into consideration the following: (1) seven utility criteria (KU1—transportation task completion time; KU2—compatibility of transportation systems; KU3—continuous connectivity; KU4—co-use with other transportation tasks; KU5—safety; KU6—inconvenience; KU7—operation under overplanning conditions) and (2) five cost criteria (KK1—costs of implementing the transportation task; KK2—costs of route expansion; KK3—rolling stock maintenance costs; KK4—depreciation costs; KK5—additional personnel costs). Based on the aforementioned criteria, two objective functions are built for each option: utility and cost. They present divergent goals; therefore, they are non-cooperative functions. Both utility and costs strive for the maximum. In the developed methodology, an ideal point is usually a fictitious solution representing a set of maximum values among all the achievable values in a set of solutions, but it is impossible to achieve this simultaneously based on all the criteria. This point illustrates the maximum utility and lowest cost among the alternatives considered, which is obviously impossible for any of the variants to meet at the same time, although it indicates the possibilities of the technique and the range of costs. For the developed method, a so-called "PND" nadir point is also determined, representing the least-preferred level of achievement of all goals simultaneously, determined from the set of optimal points in the Pareto sense. The originality of the conceptual considerations undertaken stems from: filling the gap in the economic methodology of complex transportation systems evaluation; embedding considerations in the trend concerning complex transportation systems of underground mines; and focusing considerations on the pre-investment phase, making it possible to optimize costs before expenditures are incurred. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in China's manufacturing sector, the low-carbon transition of the steel industry is urgent. CO2 capture, utilization, and storage (CCUS) technology is one of the effective measures to reduce carbon emissions in steel industry. In this paper, a comprehensive assessment model of source–sink matching-levelized cost in China's steel industry is constructed to evaluate the potential, economy, and spatial distribution of CCUS retrofits of blast furnaces in the BF-BOF steel industry. The results show that, if no extra incentive policy is included, the levelized cost of carbon dioxide (LCOCD) of 111 steel plants with a 420.07 Mt/a CO2 abatement potential ranges from −134.87 to 142.95 USD/t. The levelized cost of crude steel (LCOS) range of steel plants after the CCUS retrofits of blast furnaces is 341.81 to 541.41 USD/t. The incentives such as carbon market and government subsidies will all contribute to the early deployment of CCUS projects. The CCUS technology could be prioritized for deployment in North China, Northwest China, and East China's Shandong Province, but more powerful incentives are still needed for current large-scale deployment. The research results can provide references for the early deployment and policy formulation of CCUS in China's steel industry. [ABSTRACT FROM AUTHOR]

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions. [ABSTRACT FROM AUTHOR]

In standalone microgrids, the Battery Energy Storage System (BESS) is a popular energy storage technology. Because of renewable energy generation sources such as PV and Wind Turbine (WT), the output power of a microgrid varies greatly, which can reduce the BESS lifetime. Because the BESS has a limited lifespan and is the most expensive component in a microgrid, frequent replacement significantly increases a project's operating costs. This paper proposes a capacity optimization method as well as a cost analysis that takes the BESS lifetime into account. The weighted Wh throughput method is used in this paper to estimate the BESS lifetime. Furthermore, the well-known Particle Swarm Optimization (PSO) algorithm is employed to maximize battery capacity while minimizing the total net present value. According to simulation results, the optimal adjusting factor of 1.761 yields the lowest total net present value of US$200,653. The optimal capacity of the BESS can significantly reduce the net present value of total operation costs throughout the project by extending its lifetime. When applied to larger power systems, the proposed strategy can further reduce total costs. [ABSTRACT FROM AUTHOR]

Cataract is a major cause of blindness worldwide. In particular, in low-income countries, the burden of disease as well as its direct and indirect economic cost are a major challenge for the population and economy. In many cases, it would be possible to prevent or cure blindness with a comparably simple cataract surgery, but many countries lack the resources to strengthen healthcare systems and implement broad cataract surgery programs reaching, in particular, the rural poor. In this paper, we analyse whether such an intervention could be cost-effective or even cost-saving for the respective health systems. We calculate the net value of the lifelong costs of cataract with and without surgery. This calculation includes direct costs (e.g., treatment, glasses, surgery) as well as indirect cost of the caregiver and the patient. We total all costs from the year of onset of cataract until death and discount the respective values to the year of onset. We define the surgery as cost-saving if the net-value of costs with surgery is lower than without surgery. If the cost per quality adjusted life year is lower than one gross national product per capita, we define the intervention as highly cost-effective. We find that the cost-effectiveness of cataract surgery depends on the age of onset of the disease and the age of surgery. If the surgery is performed with the beginning of severe impairment, even surgery of a 78-year-old patient is still cost-saving. Almost all possible constellations are highly cost-effective, only for the very old it is questionable whether the surgery should be performed. The simulations show that cataract surgery is one of the most cost-effective interventions. However, millions of people in low-income countries still have no chance to prevent or cure blindness due to limited resources. The findings of this paper clearly call for a stronger effort to reach poor and rural populations with this cost-effective service. [ABSTRACT FROM AUTHOR]

This paper presents the model for the identification of reference points on the lifetime curve of engineering systems. This curve commonly represents the increase and decline of failure in relation to time. A direct correlation between failure rate and costs is assumed in this paper, therefore, statistical and empirical analysis of costs provided reference points. This approach is used for positioning stages of the engineering system's lifetime with a minimal number of failures and costs, regardless of whether these are acceptable or not. The following three stages are usually identified: the beginning, the stationary part and the end of life. The boundaries between them are recognized on the basis of minimum total lifetime costs and on economic lifetime costs. Model is tested on the dozers, machines frequently used in the mining industry for the earthmoving operations, and which are characterized by high operating and maintenance costs. [ABSTRACT FROM AUTHOR]

Electronic medical records (EMRs) are extremely private data in the medical industry. Clinicians use the patient data that the EMR stores to quickly assess a patient's status and save diagnostic information. In the conventional medical model, it is easy for duplicate exams, medical resource waste, or the loss of medical records to happen when a patient is transferred between several medical facilities due to problems with data sharing and exchange, inadequate data privacy, security, confidentiality, and difficulties with data traceability. This paper recommends a Hyperledger Fabric-based strategy to promote the exchange of EMR models. With the use of Hyperledger Fabric, EMR stakeholders can be brought into the channel to facilitate data sharing. Attribute-based access control (ABAC) allows users to design the data access control policy, and the data access control may improve security. Any record stored in the blockchain can be viewed using the Hyperledger Fabric feature and it cannot be altered or destroyed, ensuring data traceability. Through proxy re-encryption, which makes sure that the data is not leaked during data exchange, data secrecy can be ensured. A module for medical tokens has now been added. Many foreign medical institutions currently use the medical token system, and the system described in this paper can use the tokens to pay for some medical expenses. The tokens are obtained by the patient's initiative to share their EMR with the medical institution for research, which is how many foreign medical institutions currently use the medical token mechanism. This paradigm can encourage the growth of medical data by enabling stakeholders to collaborate and share EMR trust. [ABSTRACT FROM AUTHOR]

The combination of new airframes with electric and hybrid-electric propulsion is a potential solution to decarbonize aviation. In this context, recent studies have proven that the box-wing airframe, if integrated on a hybrid-electric aircraft belonging to the regional category, can provide significant reductions in fuel consumption. In light of these promising results, this paper aims to present a broader comparison between the box-wing aircraft and the conventional tube-and-wing aircraft, in the context of regional hybrid-electric air transport. An economic analysis is assessed, and the effects deriving from the box-wing introduction, in terms of direct operating costs, are quantitatively evaluated by applying cost models that consider the integration of hybrid-electric propulsion. In parallel, a comparative analysis of greenhouse emissions is proposed, considering both flight- and production-related emissions. The environmental, economic, and operating improvements that the introduction of the box-wing configuration may provide in the context of future regional hybrid-electric aviation are critically detailed. In this regard, the proposed results show that a box-wing hybrid-electric aircraft can reduce cost and emission without affecting compliance with current airport aprons. Finally, a general summary is presented, providing a solution that represents a practical, incremental, and technological step in the path of commercial aviation decarbonization. [ABSTRACT FROM AUTHOR]

This paper aims to guide structural engineers on how to apply the rapid nonlinear time history analysis (RNLTHA) procedure effectively to predict seismic demand, taking into account ductility and overstrength, and effects of dynamic phenomena including cyclic degradation of strength and stiffness in structures, in a direct and expedient manner. The shortcoming of the conventional force-based approach of design involving the use of a force reduction factor to account for nonlinear effects is well recognised. Nonlinear static (pushover) analysis and dynamic nonlinear time history analysis (NLTHA) are offered as alternative methods of analysis by major codes of practices to achieve better optimisation in the use of materials. NLTHA has advantages over pushover analysis in being more direct and capable of capturing cyclic response behaviour. Despite the merits of NLTHA, its adoption in the industry has been limited, mainly because of the complexity and the higher analysis cost involved. RNLTHA proposed in this article uses a macroscopic model of the building to fulfil the purpose of NLTHA, whilst saving computational time and achieving a good degree of accuracy, as verified by comparison with results generated from SeismoStruct. [ABSTRACT FROM AUTHOR]

There is an increasing demand to simulate and optimize the performance and profit of comminution circuits, especially in low-grade ore processing, as is the case with critical metals minerals. Recent research has shown that the optimization result is greatly influenced by quality aspects of the products, such as cost, profit, and capacity. This paper presents a novel approach to performing a multi-objective technical and economic analysis of tantalum ore processing to increase the production of critical metals minerals. The article starts with mineral composition analysis to highlight the potential of strategies for balancing the process layout for maximized production. The introduction of a combined technical and economic analysis presents the possibility of improving the profit by rearranging the mass flow given the rock's mineral composition. Results show that selective comminution can improve process capacity by 23% and decrease production cost by 10% for the presented case. [ABSTRACT FROM AUTHOR]

By additive manufacturing technologies, an object is produced deposing material layer by layer. The piece grows along the build direction, which is one of the main manufacturing parameters of Additive Manufacturing (AM) technologies to be set-up. This process parameter affects the cost, quality, and other important properties of the manufactured object. In this paper, the Objective Functions (OFs), presented in the literature for the search of the optimal build direction, are considered and reviewed. The following OFs are discussed: part quality, surface quality, support structure, build time, manufacturing cost, and mechanical properties. All of them are distinguished factors that are affected by build direction. In the first part of the paper, a collection of the most significant published methods for the estimation of the factors that most influence the build direction is presented. In the second part, a summary of the optimization techniques adopted from the reviewed papers is presented. Finally, the advantages and disadvantages are briefly discussed and some possible new fields of exploration are proposed. [ABSTRACT FROM AUTHOR]

The superior mechanical characteristics of ultra-high-performance concrete (UHPC) have attracted the interest of many researchers worldwide. Researchers have attempted to perform comparative analyses on the behavior of UHPC versus conventional and high-strength concrete, with their aim being to gain more insights into the difference between different types of concrete. However, the current state-of-the-art revealed no direct comprehensive comparisons between their behaviors in ductile coupled shear walls under seismic loading. This paper explores a comprehensive side-by-side comparison in terms of seismic behavior and cost analysis for four 60-story archetype buildings. The reference building was designed using high-strength concrete with a strength of 60 MPa. The other three archetype variations incorporated three different UHPC grades: 150 MPa, 185 MPa, and 220 MPa. The plan configuration and the lateral force-resisting system (LFRS) were chosen according to the most common practice in the UAE. The main objective is to report the effect of UHPC on the LFRS (ductile coupled shear walls). Moreover, a simplified initial cost analysis (materials and labor) design was performed. The findings of this paper indicate that the use of UHPC is capable of improving the seismic performance behavior of the lateral system as well as reducing the total initial costs. [ABSTRACT FROM AUTHOR]

The electrical market scenario has changed drastically in the last decade. In the presence of increased competition and less tolerant players, more sophisticated methods are required to balance the diversity and differential pricing while promoting cooperation among the agents. In the monopolistic environment, the central utility incurred the total cost of the transmission expansion. But as the current scenario demands, there are several public and private market players. The growth will benefit all the players, so the total cost in transmission expansion can be divided among players as per the benefit received by each player. In this paper, a transmission system expansion planning problem in the cooperative environment using cooperative game theory (CGT) is framed for the power sector, in which various players can cooperate in a coordinated manner to maximize their benefit but ultimately strengthen the power grid. In this paper, we have modeled, analyzed and compared various cost allocation methods of cooperative game theory specifically for the cost allocation in a transmission expansion planning problem. The present work focuses on forming coalitions to calculate the costs using the forward search and frog leap optimization approach. We have compared the SCRB, BSV, ENSC, and ACA methods for transmission expansion planning while attempting to satisfy the axioms. We have also observed that bilateral Shapely value efficiently allocated the costs due to its decentralized approach and the sequencing of coalition formations to achieve the best possible cost allocations. [ABSTRACT FROM AUTHOR]

Direct-drive generators are recognised for their low maintenance compared with conventional drivetrains, largely due to their fewer working parts. However, consequent to low-speed operation, these machines necessitate large diameters and are subject to rigorous stiffness requirements. Significant internal and external forces influence structural integrity, so to design them efficiently, consideration of all operating parameters is imperative. Therefore, through Finite Element Analysis, this paper sets out to quantify the influence of each operating parameter on the integrity of a parametrically optimised rotor structure under established operating conditions and introduces operating temperature to the current models. An environmental impact analysis of the optimised rotor structure and cost analyses of both the optimised and unaltered structures are carried out simultaneous to the design process. We find the use of parameter optimisation alone to be insufficient for rotor structures of this scale due to high increased mass and costs of manufacture. A significant finding from this study is that the thermal effects on large-scale direct-drive generator structures may be vastly underestimated and have a much greater influence on structural integrity than first thought. [ABSTRACT FROM AUTHOR]

In this paper, we considered one of the problems that arise during drilling automation, namely the automation of lithology identification from drill cuttings images. Usually, this work is performed by experienced geologists, but this is a tedious and subjective process. Drill cuttings are the cheapest source of rock formation samples; therefore, reliable lithology prediction can greatly reduce the cost of analysis during drilling. To predict the lithology content from images of cuttings samples, we used a convolutional neural network (CNN). For training a model with an acceptable generalization ability, we applied dataset-cleaning techniques, which help to reveal bad samples, as well as samples with uncertain labels. It was shown that the model trained on a cleaned dataset performs better in terms of accuracy. Data cleaning was performed using a cross-validation technique, as well as a clustering analysis of embeddings, where it is possible to identify clusters with distinctive visual characteristics and clusters where visually similar samples of rocks are attributed to different lithologies during the labeling process. [ABSTRACT FROM AUTHOR]

The integration of photovoltaic panels and heat pumps in domestic environments is a topic that has been studied extensively. Due to their electrical nature and the presence of elements that add thermal inertia to the system (water tanks and the building itself), the functioning of compression heat pumps can be manipulated to try to fulfill a certain objective. In this paper, following a rule-based control concept that has been identified in commercial solutions and whose objective is to improve the self-consumption of the system by actively modulating the heat pump compressor, a parametric analysis is presented. By making use of a lab-tested model, the performance of the implemented control algorithm is analyzed. The main objective of this analysis is to identify and quantify the effects of the main parameters in the performance of the system, namely the climate (conditioning both heating and cooling demands), the photovoltaic installation size, the thermal insulation of the building and the control activation criteria. A total of 168 yearly simulations have been carried out. The results show that the average improvement in self-consumption is around 13%, while the cost is reduced by 2.5%. On the other hand, the heat from the heat pump and the power consumed increase by 3.7% and 5.2%, respectively. Finally, a linear equation to estimate the performance of the controller is proposed. [ABSTRACT FROM AUTHOR]

In this paper, a conceptual framework for investigating the PPP model as it relates to hospitals is proposed. When the PPP model is applied to healthcare (hospitals), it is possible to discover the path to success by developing a critical assessment and deriving a clear model. It is concluded that most PPP model implementations in hospitals around the world have produced favorable outcomes, both in terms of the performance of healthcare units and in terms of cost-effectiveness. Additionally, a path-to-success model that applies to hospitals is offered, taking into account six PPP model dimensions: (i) Environment; (ii) Potentiate Benefits; (iii) Constant Measure; (iv) Evaluation; (v) Management; and (vi) Enhance Strengths. The PPP model only applies case by case and under specific requirements that should be met cumulatively to provide additional value to healthcare's quality of service. The right conditions are created, the right benefits are amplified, public concerns are frequently assessed, private contributions are carefully considered, and all pressing challenges are managed by enhancing both public and private strengths. Leading decision- and action-making processes in corporate, governmental, and social sectors is the goal of managing PPP models. [ABSTRACT FROM AUTHOR]

Cranioplasty or cranial reconstruction is always a challenging procedure even for experienced surgeons. In this study, two different design techniques for customized cranial prostheses are assessed for cranial reconstruction. Mirror reconstruction is one of the commonly used reconstruction techniques that fails when cranial defects cross the midline of symmetry. Hence, there is a need for a design technique for the reconstruction of cranial defects irrespective of their location on the symmetrical plane. The anatomical reconstruction technique demonstrates its applicability for a wide spectrum of complex skull defects irrespective of the defective position in the anatomical structure. The paper outlines a methodological procedure involving a multi-disciplinary approach involving physicians and engineers in the design and reconstruction of customized cranial implants for asymmetrical skull defects. The proposed methodology is based on five foundation pillars including the multi-disciplinary approach, implant design process, additive-manufactured implant, implant fitting analysis, and cost and time analysis for the customized implant. The patient's computed tomography scan data are utilized to model a customized cranial implant, which is then fabricated using electron beam melting technology. The dimensional validation of the designed and fabricated titanium implant based on the anatomical approach results in a precision of 0.6345 mm, thus indicating a better fit than the standard mirroring method. The results of fitting accuracy also reveal that the manufactured implant's average deviation is very close to the planned reconstruction area with an error less than 1 mm, suggesting that the customized titanium implant fits the skull model quite precisely. The cost and time analysis reports that the cost for producing a customized cranial implant using electron beam melting technology is around USD 217.5 and the time taken to build is approximately 14 h and 27 min, which is low when compared to other studies. The cost and time analysis also demonstrates that the proposed design would be less burdensome to patients when compared to standard practice. Therefore, the new anatomical design process can be used effectively and efficiently to treat a number of diverse cranial abnormalities with the enhanced cranial implant design. [ABSTRACT FROM AUTHOR]

The growing number of space objects leads to increases in the potential risks of damage to satellites and generates space debris after colliding. Conjunction assessment analysis is the one of keys to evaluating the collision risk of satellites and satellite operators require the analyzed results as fast as possible to decide and execute collision maneuver planning. However, the computation time to analyze the potential risk of all satellites is proportional to the number of space objects. The conjunction filters and parallel computing techniques can shorten the computation cost of conjunction analysis to provide the analyzed results. Therefore, this paper shows the investigation of the conjunction filter performances (accuracy and computation speed): Smart Sieve, CSieve and CAOS-D (combination of both Smart Sieve and CSieve) in both a single satellite (one vs. all) and all space objects (all vs. all) cases. Then, all the screening filters are developed to implement an algorithm that executes General-purpose computing on graphics processing units (GPGPU) by using NVIDIAs Compute Unified Device Architecture (CUDA). The analyzed results show the comparison results of the accuracy of conjunction screening analysis and computation times of each filter when implemented with the parallel computation techniques. [ABSTRACT FROM AUTHOR]

Solar power occupies a significant position among global renewable energy sources due to its abundant energy potential. Consequently, its contribution to electricity generation is steadily increasing. However, obtaining peak efficiency from fixed solar photovoltaic (PV) panels is a formidable task due to their limited ability to consistently tap into solar energy. To tackle this issue and mitigate energy efficiency losses, the utilization of solar tracking systems has emerged as an exceptionally effective solution. These systems enable continuous adjustment of the panels' position to align with the sun's trajectory, optimizing energy absorption and enhancing overall performance. This paper presents the performance and cost analysis of three distinct solar panel tracking systems, namely, a fixed system, a single-axis system, and a dual-axis system. The systems are operated under identical coordinates and conditions. The production data are collected over a period of 15 days for comparative analysis. The tracking movements of the systems are controlled using Arduino. The mechanical components are specifically designed for the establishment of each system. The findings of this study indicate that both single-axis and dual-axis solar tracking systems outperformed fixed systems in terms of power generation. The single-axis system demonstrated a 24.367% increase in power production, while the dual-axis system showed a 32.247% increase compared to the fixed system. Moreover, a cost analysis was carried out considering the installation expenses and power production data of the three systems. It was determined that the single-axis tracking system achieved payback in 0.39 years less compared to the fixed system, while the dual-axis system achieved payback in 1.48 years less compared to the fixed system. Overall, this study underscores the advantages of implementing solar tracking systems, particularly in the single-axis and dual-axis configurations, as they contribute to higher power generation and cost-effectiveness compared to fixed systems. [ABSTRACT FROM AUTHOR]

(1) Background: Identifying hospital-related critical, and excellent, areas represents the main goal of this paper, in both a national and local setting. Information was collected and organized for an internal company's reports, regarding civil litigation that has been affecting the hospital, to relate the obtained results with the phenomenon of medical malpractice on a national scale. This is for the development of targeted improvement strategies, and for investing available resources in a proficient way. (2) Methods: In the present study, data from claims management in Umberto I General Hospital, Agostino Gemelli University Hospital Foundation and Campus Bio-Medico University Hospital Foundation, from 2013 to 2020 were collected. A total of 2098 files were examined, and a set of 13 outcome indicators in the assessment of "quality of care" was proposed. (3) Results: From the total number, only 779 records (37.1%) were attributable to the categories indexable for the present analysis. This data highlights how, following a correct and rigorous categorization of hospital events, it is possible to analyze these medico-legal aspects using a small number of indicators. Furthermore, it is important to consider how a consistent percentage of remaining events was difficult to index, and was also of poor scientific interest. (4) Conclusions: The proposed indicators do not require standards to be compared to, but provide a useful instrument for comparative purposes. In fact, in addition to comparative assessment between different business realities distributed throughout the territory, the use of outcome indicators allows for a longitudinal analysis evaluating the performance of an individual structure over time. [ABSTRACT FROM AUTHOR]