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Managing blood donations is a challenging problem due to the perishability of blood, limited donor pool, deferral time restrictions, and demand uncertainty. The problem addressed here combines two important aspects of blood supply chain management: the inventory control of blood products and the donation schedule. We propose a stochastic scenario-based reformulation of the blood donation management problem that adopts multicomponent apheresis and utilises donor pool segmentation into here-and-now and wait-and-see donors. We propose a flexible donation scheme that is resilient against demand uncertainty. This scheme enables more flexible donation schedules because wait-and-see donors may adjust their donation schedules according to the realised values of demand over time. We propose a column generation-based approach to solve the associated multi-stage stochastic donation tailoring problem. The numerical results show the effectiveness of the proposed optimisation model, which provides solutions with less than a 7% optimality gap on average with respect to a lower bound. It also improves the operational cost of the standard donation scheme that does not use wait-and-see donors by more than 18% on average. Utilising multicomponent apheresis and flexible wait-and-see donations are suggested for donation organisations because they yield significant cost reductions and resilient donation schedules. [ABSTRACT FROM AUTHOR]

This research explores how manufacturing overhead influences profit margins under different capacity allocation policies in a build-to-order context. By applying a multi-period Mixed-Integer-Programming model to assess industries with varying overhead structures, the study establishes a link between the levels of capacity allocation and profitability, underscoring the strategic significance of overhead costs in capacity management decisions. Our results indicate that industries with lower overhead costs benefit more significantly from increased capacity allocation, with up to a 25% improvement in profit, compared to a 5–10% improvement in higher overhead industries. Conversely, at full capacity demand rates, increased allocation levels detrimentally affect profit, particularly in industries with higher overhead ratios. The study utilises a 3-way ANOVA to confirm the significance of these findings, revealing that industry type, demand rates, and allocation levels are critical factors in optimising profit. This research highlights the need for a pragmatic approach to capacity allocation that aligns with industry characteristics and demand levels, steering away from revenue maximisation to a more holistic view of profitability that includes overhead cost management. [ABSTRACT FROM AUTHOR]

Project managers need reliable predictive analytics tools to make effective project intervention decisions throughout the project life cycle. This study uses Machine learning (ML) to enhance the reliability in project cost forecasting. A XGBoost forecasting model is developed and computational experiments are conducted using real data of 110 projects representing 1268 cost data points. The developed model performs better than some Earned value management (EVM), ML (Random forest, Support vector regression, LightGBM, and CatBoost), and non-linear growth (Gompertz and Logistic) models. The model produces more accurate estimates at the early, middle, and late stages of the project execution, allowing for early warning signals for more effective cost control. In addition, it shows more accurate estimates in most projects tested, suggesting consistency when repeatedly used in practice. Project forecasting studies mainly used ML to estimate the project duration; a few ML studies estimated the project cost at the project's conceptual stage. This study uses real data and EVM metrics, proposing an effective XGBoost model for forecasting the cost throughout the project life cycle. [ABSTRACT FROM AUTHOR]

This paper highlights the tight relationship between the picking and packing processes in warehouse management and the need to consider them as an integrated problem. The study describes and models this integrated problem as a mixed-integer programming model, to optimise overall labour costs by determining the assignment of the subsets of orders, i.e. batches, for picking and packing. To address the issue of model complexity, the paper presents a statistical-based framework for generating approximate models and selecting the optimal one through examination. Based on the examination results, a pair-swapping heuristic is additionally proposed to be combined as a hybrid algorithm. Numerical experiments based on a real-world case demonstrate the effectiveness of the framework-proposed and selected hybrid algorithm by comparison with other framework-proposed approximate models, a solver, and existing heuristics. Our findings indicate that the combined usage of integrated picking and packing processes planning and the hybrid algorithm proposed and selected within the statistical-based framework can effectively reduce the cost of warehouse management. [ABSTRACT FROM AUTHOR]

This clinical case outlines a comprehensive digital workflow for a minimally invasive multidisciplinary treatment. The process utilizes one open-source software for digital wax-up and one low-cost software to address esthetic concerns related to teeth misalignment. The patient's function was stabilized with a digitally made occlusal splint. The application of the described digital workflow technique, incorporating open-source, lowcost, and closed software, played a pivotal role in attaining a straightforward and predictable outcome with minimally invasive treatment. Furthermore, the continual evolution of technology contributes to the growing precision of dental procedures. The presented digital workflow helped formulate a predictable treatment plan, replicate a diagnostic digital wax-up, and achieve precise teeth alignment. This approach satisfactorily addressed the patient's esthetic concerns, providing an outstanding approximation of the definitive result. [ABSTRACT FROM AUTHOR]

Manufacturers are facing pressure to reduce electricity costs. Onsite renewable energy generation may be a solution, but its high capital cost and intermittent power generation limit its use. Grid-responsive smart manufacturing could effectively incorporate renewables in industrial processes. This study integrates grid-responsive smart manufacturing with renewables on an industrial plant scale and demonstrates both a favourable economic and environmental outcome. A user-friendly decision-aid model for energy management is provided to manufacturers. A case study shows how solar panels, industrial batteries, smart pumping strategies, and various combinations of those elements can save on electricity costs. Dynamic simulation results demonstrate that grid-responsive smart manufacturing can effectively lower peak demand. The economic results show that grid-responsive smart manufacturing and renewables synergistically optimise cost reductions. The solar coupled with smart pumping scenario shows annual cost savings of $755,200, accounting for 4.6% of the total electricity cost. Smart pumping alone saves $371,900 annually with a 0.7-year payback period, demonstrating how the manufacturing sector can utilise its own processes in load shifting. This study supports that incorporating grid-responsive smart manufacturing with renewables can effectively reduce electricity costs and emissions for industry. Abbreviations: e: Equivalent; GHG: Greenhouse gas; PBP: Payback period; PV: Photovoltaics; SP: Setpoint; VFD: Variable speed drives [ABSTRACT FROM AUTHOR]

This paper deals with the problem of optimising the network of a Third-Party Logistics (3PL) company, placing emphasis on the distinct characteristics of the 3PL environment. The goal is to minimise the warehousing and distribution costs for both forward and reverse product flows. A new Mixed Integer Linear Program (MILP) model is proposed to address this interesting problem. The related decisions include: selection of (a) warehouse(s) and the related product inventory quantities, (b) product unit loads transported, (c) truck combinations employed to perform the corresponding forward and reverse trips. The model was applied in a case study of a 3PL company to optimise part of its forward supply chain that comprises three warehouses, 23 suppliers and 53 customers. The results obtained were very encouraging, since overall warehousing and distribution costs were lowered by 10.8%. Sensitivity analysis indicated that additional savings may result from optimising warehousing capacities. The main contributions of this work are the inclusiveness of key aspects of the 3PL environment in the proposed model, as well as placing emphasis on warehousing costs and on management of truck capacities. A secondary contribution is the validation of the model's value through a comprehensive case study. [ABSTRACT FROM AUTHOR]

In public libraries, especially those in rural settings, it is important that every dime of library funding is leveraged effectively into serving the community. As part of a year-long project beginning in January 2023, we are evaluating item-level cost-effectiveness for each circulating item housed at the public library in Lakeville, Indiana. Through the use of big(ish) data, some custom Python scripting, and machine learning algorithms we hope to answer: How much money is saved by library patrons through their use of the public library's physical collection? How much money is saved by the community through the operation of a public library based on the use of the circulating collection? And are there any non-obvious traits which make an item or title a more or less cost-effective circulating asset? In this column, I will describe the scripts, share initial findings, discuss challenges, and investigate next steps. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Giardiasis, caused by the protozoan parasite Giardia intestinalis, poses a significant public health burden worldwide, particularly in regions with limited access to clean water and sanitation infrastructure. Understanding the transmission dynamics of giardiasis and evaluating intervention strategies are crucial for effective disease control. In this study, we apply the theory of optimal control to the giardiasis model. The model includes public health education, treatment, and sanitation as the control measures for giardiasis. The goal is to minimize the infections in the population brought on by interactions with asymptomatic, symptomatic, and contaminated environments while reducing the cost of the control measures. We accomplish this goal by using Pontryagin’s Maximum Principle, where fourth-order Runge–Kutta is used to perform numerical simulations for both forward and backward in-time schemes. We simulate the model under different control scenarios to determine which strategy could produce the greatest results. The results demonstrate that the control strategy combining the three control measures (public health education, treatment, and sanitation) proves to be more effective in curbing the spread of giardiasis. Moreover, the incremental cost-effectiveness ratio (ICER) is used to analyze cost-effectiveness. The cost-effectiveness analysis revealed that the strategy that contains treatment and sanitation is the best strategy to implement in the population in case of budget constraints. Hence, our study recommends that sanitizing the environment and treating the infected individuals immediately could be the best practice for controlling the spread of giardiasis disease on an entire population. [ABSTRACT FROM AUTHOR]

Purpose: The goal of this study was to assess the diagnostic value of FAST ankle ultrasound, performed by non-radiologist specialist physicians, compared to standard X-ray imaging for ankle and foot trauma in the emergency department. Additionally, we analyzed whether other variables, such as demographic characteristics of the included patients, could influence fracture detection with the diagnostic tools used. Methods: A non-randomized monocentric prospective diagnostic cohort study was conducted on 143 patients. Results: Ankle and foot fractures were more frequently detected by FAST ultrasound compared to standard radiography. Regarding the influence of demographic factors, age and the correlation between Body Mass Index and age significantly influenced the ability to detect fractures. Conclusion: FAST ultrasound demonstrated good diagnostic value in routine clinical practice for screening purposes and could be easily applied by non-radiologist specialist physicians. Implementing this approach may reduce time and costs in patient management, thereby aiding in alleviating triage congestion in the emergency department. Trial registration number and date of registration for prospectively registered trials: NCT05528432; 21-02-21. [ABSTRACT FROM AUTHOR]

Using data on Chinese A-share listed firms from 2012 to 2022, we examine the impact of management integrity on corporate financial distress. Our findings reveal a significant negative association between management integrity and financial distress, highlighting the crucial role of management integrity in mitigating financial distress. This effect is particularly pronounced among non-state-owned firms, firms operating in regions with inadequate legal systems, and firms with good corporate governance. Moreover, we demonstrate that management integrity directly contributes to a decrease in capital costs, thereby reducing corporate financial distress. [ABSTRACT FROM AUTHOR]

Solid oxide fuel cells (SOFCs) in microtubular geometry offer promising solutions for efficient power generation. However, conventional fabrication techniques, involving single extrusion of anode support followed by dip coating of other cell layers, often increase production costs, time and complexity. This study explores alternative methods to reduce these challenges, mainly focusing on tape casting combined with isostatic pressing to create microtubular anode supported electrolyte structures with a functional layer. The main goal is to minimize the fabrication cost and time by eliminating some fabrication steps, including pre-sintering of anode support and anode functional layer. Various fabrication routes are investigated in this respect, while evaluating manufacturability, microstructure, and electrochemical performance. The findings indicate that cell fabrication on green anode supports yields unsatisfactory outcomes. On the other hand, a performance improvement of approximately 43 % at 800 °C, compared to the conventional cell, is achievable with a cell in which the anode support, anode functional, and electrolyte layers are sequentially wrapped, followed by co-lamination and co-sintering. Therefore, this approach can be regarded as a more cost-effective and efficient fabrication route. • Various approaches are tested to reduce the production cost of microtubular SOFCs. • Tape casting and isostatic pressing can reduce fabrication steps, time and cost. • Sequential wrapping of layers enhances cell performance, yielding a 43% increase. • Pre-sintering steps are eliminated, simplifying fabrication and reducing cost. [ABSTRACT FROM AUTHOR]

Large-scale hydrogen storage at scales ranging from gigawatt-hours (GWh) to terawatt-hours (TWh) is currently projected to be an important component of the lowest cost options for a 100% variable renewable energy system, driven partly by benefits to the grid from converting variable renewable electricity into hydrogen and partly by the anticipated growing role of hydrogen in a future net-zero energy system. Lined engineered cavities (LEC)s are among the prospective types of underground storage technology because they enable hydrogen storage at high-pressure in the gaseous form and are expected to not rely on specific types of rock mass. They fill a niche in moderate storage capacity and cost because of their complementary advantages. An overview of various possible configurations and materials suitable for LECs for storing hydrogen is first reviewed to identify potential cost savings and performance improvements. Amongst the various LEC configurations, lined engineered shafts (LES) are identified as having the greatest potential for cost reduction in softer rock masses, such as sedimentary formations, due to reduced excavation and construction complexity. Despite these advantages, significant gaps remain in understanding the long-term behaviour of LES under cyclical loading, as revealed through a review of the theoretical and experimental techniques used to study similar LEC configurations. This review paper concludes with several recommendations for future research in numerical model formulation and material advancement, with strong potential to increase the feasibility of LESs for hydrogen storage. • Various configurations of lined engineered cavities (LEC) are explored. • Construction methods and costs of each LEC configuration is discussed. • Potential materials for impermeable liners and concrete linings are evaluated. • Impact of geomechanical properties and in-situ stress on LECs is analysed. • Current theoretical and experimental approaches in analysing LECs are reviewed. [ABSTRACT FROM AUTHOR]

AbstractHospitals are required to provide a social safety-net through charity care to indigent populations. This study aims to build upon previous research by examining the provision of charity care by hospitals using national, longitudinal data. We found no significant difference in the provision of charity care. However, we did find that hospital charity care ratio may be influenced by type of care, location, and market conditions. Policymakers need to determine the appropriate level of charity care to be provided by non-profit hospitals. Managers need to determine the appropriate cost management strategy to support their hospitals’ financial sustainability. [ABSTRACT FROM AUTHOR]

Pile burning of thinned residues is a critical tool to dispose of fuels and to reduce wildfire risk in overstocked, fire-prone forests globally. However, cost estimates of pile burning are limited. In the Western United States, where fuel reduction and pile burning are key strategies to mitigate risk of severe wildfire, previous reports estimate that the average cost of pile burning after machine treatment is $543 ac−1 ($1,343 ha−1). There is, however, limited information on the costs of hand thinning and pile burning. In response, this study quantified the costs of cutting and yarding, piling, and burning residues via two pathways: the USDA Forest Service (USFS) Activity Tracking System (FACTS) database, and interviews with 11 USFS fire management professionals from California, Oregon, and Washington. Interviews highlighted cost drivers, implementation constraints, and opportunities for efficiency improvements. The average costs of piling and burning machine piles as determined from the interviews were $735 ± $464 ac−1 ($1,817 ± $1,146 ha−1; all mean ± SD), 80% higher than reported in the FACTS database and 35% higher than previous reports. The average costs of piling and burning hand piles as determined from the interviews were $1,291 ± $717 ac−1 ($3,190 ± $1,722 ha−1), 135% higher than reported in the FACTS database. Interview participants reported proximity to roads and terrain as key cost drivers, and described common practices, challenges, and constraints to pile burning. Geospatial analyses supported interviewee-identified cost drivers, district road density (a proxy for accessibility) and district maximum elevation (a proxy for terrain). Simulations of direct emissions from pile burning on National Forests included in this study indicated annual emissions of 11,322 metric tons (MT) of particulate matter (PM), 8,029 MT of PM10, and 6,993 MT of PM2.5 across the study area. In addition, pile burning on these National Forests annually emits >1.7 million MT CO2, 61,515 MT of carbon monoxide, 3,823 MT of methane, and 3,211 MT of non-methane hydrocarbons. Given the economic, human health, and climate implications of current pile burning practice, removing residues as feedstocks for carbon-negative utilizations is recommended as a near-term priority. Policy mechanisms, such as feedstock production, transport, or offtake subsidies of a similar magnitude to such avoided costs, could efficiently incentivize residue removal and support such climate-positive utilizations. [ABSTRACT FROM AUTHOR]

Building Information Modelling (BIM) has emerged as a transformative tool in the Architecture, Engineering, and Construction (AEC) industries, offering significant potential to improve project efficiency and outcomes. This study explores the impact of BIM implementation on project time and cost by analyzing critical factors such as design errors, unbudgeted changes, Requests for Information (RFIs), labour dynamics, and scheduling across multiple case studies. Quantitative results reveal that BIM adoption reduces project timelines by an average of 20% and costs by 15%, while also decreasing design errors by 30% and RFIs by 25%. Furthermore, BIM enhances collaboration among stakeholders, improves design visualization, and facilitates better risk assessment, leading to more informed decision-making throughout the project lifecycle. These findings are synthesized into a decision-making framework that estimates the probability of errors, evaluates their potential time and cost implications, and ensures alignment with project budgets. The framework serves as a strategic guide for project teams to assess the suitability of BIM for specific projects, thereby optimizing decision-making processes and improving overall project performance. Additionally, the study examines the role of BIM in sustainability by reducing material waste and improving resource allocation. This study addresses a critical gap in the field by systematically evaluating the interrelationships among BIM's impacts on key project parameters, which have often been treated in isolation in prior research. The importance of this work lies in its provision of a structured methodology to harness BIM's capabilities, demonstrating its value in delivering significant time and cost efficiencies while enhancing project quality. By integrating empirical analysis with practical applications, this research contributes to the growing body of knowledge on BIM adoption and provides actionable insights for AEC professionals seeking to optimize project outcomes. [ABSTRACT FROM AUTHOR]

This paper deals with the potential of the different modes of transport on the Eurasian connection, focusing on rail, and comparing with sea and air. Since 2008, a substantial uptake of the rail connection has been observed. The main question then is whether the competitiveness of this land bridge is actual and sustainable or not. First, the paper focuses on the latest developments of the actual physical capacity on the Eurasian connection. Mainly under Chinese impetus, substantial improvements of rail connections but also border crossings have been made. Second, the paper focuses on the actual competitiveness of the different modes on the Eurasian connection in the current-day transport volumes. It can be observed that also the transport on the Eurasian connection has been growing, especially by rail. However, by far the largest volumes of transport still happen by maritime transport. The third and main question of the paper is on whether the land bridge by rail would cost-wise be competitive enough to favour a large shift from sea to land. An adapted version of a chain cost model applied to seven city pairs shows that the cost of the maritime solution is notably higher the further away from the coast origin and/or destination are located. For rail, such significant cost differences are not found. Furthermore, the value of the goods plays a bigger role for rail than for maritime transport. Air transport, due to its higher charges, typically is only used by higher-value goods. When comparing the (combinations of) transport modes, it turns out that the rail costs are on average 1.5 times to twice as high as when using maritime transport, but the more westward the origin on the Chinese territory, the closer the ratio gets to 1. The sensitivity analysis shows that in particular using longer trains will allow strongly further reducing generalized rail chain costs, easily over a third of the base case costs. Substantially less generalized chain cost reductions are achieved when shortening transit times, even when the latter goes up to half the initial transit time. Fourth, looking at what would be needed to make a further shift to rail materialize on the Eurasian connection, three items pop up: rail border crossing capacity, traffic balance between both directions and backups to the TEN-T rail network. [ABSTRACT FROM AUTHOR]

Introduction: Before implementing a new health care strategy, it is important to assess effectiveness but also to perform an economic evaluation. The goal of the present study was to perform a comparative economic evaluation of a new strategy aimed at using proposed implementation of the Plateletworks guidance (measurement of platelet function) with usual practice (delayed time to surgery) in patients on chronic antiplatelet treatment and scheduled for surgery with neuraxial anaesthesia due to proximal femur fracture. Methods: This is an economic evaluation carried out alongside a randomised controlled clinical trial at four centres in Spain. Patients were randomised to undergo either early platelet function-guided surgery (experimental group) or delayed surgery (control group). As AFFEcT trial results demonstrated significative difference between groups in the primary efficacy endpoint, the median time to surgery, a cost-effectiveness analysis was performed. Direct costs associated with hospitalisation until one-month post-discharge were considered and measured from a hospital perspective. All costs were reported in euros. Analyses were performed on a per protocol basis. Effectiveness outcome measures were the incremental cost and incremental cost per reduction in days to surgery. A deterministic sensitivity analysis was implemented to quantify uncertainty. Results: A total of 156 patients were randomized to the two groups (n = 78 per group). A total of 143 patients were included in the per protocol population (75 and 68 patients in the experimental and control groups, respectively). The median time to surgery was 2.30 days (IQR: 1.53–3.73) in the experimental group and 4.87 days (4.36–5.60) in the control group (a reduction of 2.40 days). Total costs during the 1-month study perioperative period were higher in the delayed surgery group (€18,495.19) than for the early surgery group (€16,497.59). The incremental cost was negative (€1,997.60), a statistically significant difference (P < 0.05). As measured by the reduction in time (days) to surgery, the incremental cost-effectiveness ratio (ICER) for early surgery was negative (777.28€/day). Sensitivity analysis demonstrated consistent cost saving. Conclusion: For patients on chronic antiplatelet treatment scheduled to undergo surgery for proximal femur fracture, an individualised strategy guided by a platelet function testing is a cost-saving and cost-effective strategy. [ABSTRACT FROM AUTHOR]

This study presents an innovative single-layered toggle flip-flop with highly polarized output designed specifically for Quantum-dot Cellular Automata (QCA), a cutting-edge nanocomputing approach. Building on the capabilities of this advanced flip-flop, a two-bit asynchronous down (ripple) counter was developed using QCADesigner 2.0.3, all within the QCA framework. The counter exhibits exceptional scalability and reliability, addressing key challenges in QCA circuit design. Energy efficiency and cost-effectiveness are standout features of the design, with a 53% improvement in energy efficiency and a 38% reduction in QCA-specific cost, as verified by QCADesigner-E 2.2 simulations. Furthermore, the physical stability of the proposed circuit was thoroughly examined through kink energy calculations, highlighting its robustness. These optimizations were achieved by avoiding complex crossovers and leveraging the benefits of the enhanced flip-flop architecture. The results underscore the significant potential of QCA in improving digital circuit performance, paving the way for more efficient, scalable, and cost-effective nanoelectronic designs and pushing the boundaries of next-generation nanocomputing solutions. [ABSTRACT FROM AUTHOR]

The motive of current work is to design a novel radial basis Bayesian regularization neural network (RB-BRNN) for solving the nonlinear fractional economic and environmental system (FEES). A radial basis activation function in the hidden layers is applied by taking 20 numbers of neurons. The mathematical FEES is presented in three classes, named as cost of control accomplishment, manufacturing elements competence and technical exclusion's diagnostics cost. A reference dataset is obtained using the Adams numerical results to reduce the mean square error (MSE) by taking the data for training 70%, while 15% is used for both testing and validation. The negligible absolute error values and comparison of the solutions develop the worth of computing RB-BRNN in order to solve the nonlinear dynamics of the FEES. Error diagrams, regression values, and the MSE performances are implemented to assess the precision of the designed solver. [ABSTRACT FROM AUTHOR]

Chronic care management is effective. Barriers to program durability include dependence on the provider–nurse duo to carry out labor-intensive services and the lack of a fiscally sustainable model. Between January and October 2022, an expanded chronic care management team—consisting of a provider, nurse, community health worker, and pharmacist—conducted a four-month intervention in an ambulatory setting. This intervention, using a convenience sample of 134 Medicare patients with uncontrolled type 2 diabetes or hypertension, demonstrated statistically significant improvements in controlling type 2 diabetes (P <.01) and blood pressure (P <.001). Direct provider workload decreased, and the Medicare reimbursement rate was 85.5%. (Am J Public Health. 2025;115(2):133–137. https://doi.org/10.2105/AJPH.2024.307886) [ABSTRACT FROM AUTHOR]

As an energy carrier characterized by its high energy density and eco-friendliness, hydrogen holds a pivotal position in energy transition. This paper elaborates on the scientific foundations and recent progress of photo- and electro-catalytic water splitting, including the corresponding mechanism, material design and optimization, and the economy of hydrogen production. It systematically reviews the research progress in photo(electro)catalytic materials, including oxides, sulfides, nitrides, noble metals, non-noble metal, and some novel photocatalysts and provides an in-depth analysis of strategies for optimizing these materials through material design, component adjustment, and surface modification. In particular, it is pointed out that nanostructure regulation, dimensional engineering, defect introduction, doping, alloying, and surface functionalization can remarkably improve the catalyst performance. The importance of adjusting reaction conditions, such as pH and the addition of sacrificial agents, to boost catalytic efficiency is also discussed, along with a comparison of the cost-effectiveness of different hydrogen production technologies. Despite the significant scientific advancements made in photo(electro)catalytic water splitting technology, this paper also highlights the challenges faced by this field, including the development of more efficient and stable photo(electro)catalysts, the improvement of system energy conversion efficiency, cost reduction, the promotion of technology industrialization, and addressing environmental issues. [ABSTRACT FROM AUTHOR]

Fully harnessing the inherent flexible adjustment potential of steel enterprises and fostering their interaction with the power grid is a crucial pathway to advancing green transformation. However, traditional research usually takes reducing energy consumption as the optimization goal, which limits the adjustment response capability, or ignores the storage and conversion constraints of secondary energy sources such as gas, steam, and electricity, making it difficult to fully explore and reasonably utilize the potential of multi-energy coordination. This study considers the production constraints of the surplus energy recovery and utilization system, establishes a collaborative scheduling model for a gas–steam–power system (GSPS) in an iron and steel enterprise, and proposes a demand response strategy that considers internal production constraints. Considering the time-of-use (TOU) tariff, iron and steel enterprises achieve a dynamic optimization adjustment range of electricity demand response through the conversion and storage process of gas, steam, and power. The adjustment capability of the GSPS reaches 26.94% of the initial electricity load, while reducing the total system energy cost by 2.24%. There is vast development potential of iron and steel enterprises participating in electricity demand response for promoting cost reduction and efficiency improvement, as well as enhancing the power grid flexibility. [ABSTRACT FROM AUTHOR]

In a traction power supply system, the design of traction substations significantly influences both the system's operational stability and investment costs, while the energy management strategy of the flexible substations affects the overall operational expenses. This study proposes a novel two-stage system optimization design method that addresses both the configuration of the system and the control parameters of traction substations. The first stage of the optimization focuses on the system configuration, including the optimal location and capacity of traction substations. In the second stage, the control parameters of the traction substations, particularly the droop rate of reversible converters, are optimized to improve regenerative braking energy utilization by applying a fuzzy logic-based adjustment strategy. The optimization process aims to minimize the total annual system cost, incorporating traction network parameters, power supply equipment costs, and electricity expenses. The parallel cheetah algorithm is employed to solve this complex optimization problem. Simulation results for Metro Line 9 show that the proposed method reduces the total annual project costs by 5.8%, demonstrating its effectiveness in both energy efficiency and cost reduction. [ABSTRACT FROM AUTHOR]

Heat pipes filled with a thermodynamic medium are energy-saving and stable heat exchangers that have been used for years in various fields of science and technology, including building heating and cooling installations. This article presents the results of research on the energy efficiency of wall-mounted concrete heating and cooling modules with heat pipes, which can be a structural element of external and internal walls of buildings for various purposes. A series of measurement tests were performed, which allowed the determination of how the thermal power and control parameters of the module (amplification factor and time constants) change under operating conditions. A first- and second-order inertial model was used to describe the control properties of the module. The measurements were performed in heating and cooling mode for three different values of supply water flow, both when increasing the supply temperature and when decreasing it. Based on the results of the measurements, calculations and analysis, it was found that the thermal power and control parameters of the module change significantly; these changes result from both the design features of the module (the type of thermodynamic medium in the heat pipe and the technical aspects of the execution and assembly of the connections between the collector and the heat pipe) and the operating conditions (the value of the direction of temperature change and the flow of the supply water). It was shown that the supply temperature has a much greater impact on the values of the module's control parameters than the flow rate of the supply water. The tested module is characterized by slow changes in temperature on its surface (high values of time constants). The time of stabilization of the temperature on the module's surface, after step forcing, is 8–10 h. This can cause greater fluctuations in the indoor air temperature, lower thermal comfort in the room and lower energy efficiency of the process. These issues can be prevented by using complex algorithms for thermal comfort control, which in turn increase the cost of the control system. [ABSTRACT FROM AUTHOR]

Objective: Japan has resumed its health technology assessment to decide how to reduce high-cost drug prices. While drug price rules in Japan are comprehensive, they do not necessarily capture differences in product characteristics. This study examined the drug price revision strategy in Japan using migraine treatment with triptans as an example. Cost data from fiscal years (FY) 2018, 2020, and 2022 were utilized. Methods: A cost-utility analysis was conducted from the perspective of healthcare payers, focusing on Japanese patients aged over 18 years experiencing migraines. The study employed a base-case model with probabilities derived from a network meta-analysis. Direct costs included medical and drug costs. Effectiveness was assessed using the European Quality of Life 5-dimensions—3-level questionnaire. Deterministic and probabilistic sensitivity analyses were conducted to examine the level of uncertainty. Results: In FY2018, sumatriptan and eletriptan were cost-effective; however, the other triptans were dominated by sumatriptan. In FY2020, sumatriptan and eletriptan were cost-effective, and rizatriptan was extended-dominated; nevertheless, the other triptans were dominated by sumatriptan. In FY2022, naratriptan and eletriptan were cost-effective; however, the other triptans were dominated by naratriptan. The hierarchy of triptan strategies varied in each fiscal year. Conclusions: This study provides valuable insights into the drug price revision strategy in Japan. The variations could be problematic because in Japan, formulary management of triptans, for example, those for migraine, may face revaluation every other year. Discussions regarding this issue will be further explored in the future. [ABSTRACT FROM AUTHOR]

Trochoidal machining could significantly improve cutting efficiency, enhance cutting stability, reduce cutting temperature, extend tool life, and reduce the cutting costs. However, in trochoidal machining, there are few studies focusing on modelling the instantaneous cutting power due to overlooking the importance of cutting temperature modelling. Also, instantaneous cutting power is an important basis for the optimization of trochoidal parameters and cutting parameters. In this work, we established a new and efficient method that could predict the instantaneous cutting power in trochoidal machining in high fidelity. First, the specific cutting energy of a given workpiece material, cutting tool, and cutting parameter in milling process was calibrated by cutting experiments. Second, the influence of the radial depth of cut on the specific cutting energy in milling process was quantitatively studied. Third, combining the obtained relationship between the specific cutting energy and radial depth of cut, the specific cutting energy curve in trochoidal machining was obtained. Then, a way to figure out the instantaneous material removal rate was proposed based on the acquired instantaneous 3D un-deform chip in trochoidal machining. Finally, based on the obtained specific cutting energy and instantaneous material removal rate, an accurate and efficient approach to predicting the instantaneous cutting power in trochoidal machining was proposed, and a practical application was demonstrated. The effectiveness of the proposed approach was validated by cutting experiments. The method proposed in this work could be adopted in cutting parameter optimization, tool-path optimization, and cutting temperature prediction in trochoidal machining. [ABSTRACT FROM AUTHOR]

In recent years, there has been growing interest in employing predictive methods to forecast the remaining useful life of industrial equipment. However, the challenge lies in how to take advantage of the dynamic predictive information to facilitate the maintenance of decision‐making. This problem becomes particularly challenging for complex industrial systems consisting of multiple components with economic dependencies. This paper aims at providing an effective maintenance strategy for multi‐component systems based on predictive information, while considering economic dependencies among different system components. To this end, a dynamic predictive maintenance (PdM) strategy that minimizes the mean maintenance cost over a decision period is proposed, where both long‐term and short‐term policies are integrated into the decision‐making framework. Specifically, the long‐term policy is formulated using predictions derived from historical degradation data through a Long Short‐Term Memory (LSTM) model. Concurrently, real‐time monitoring data is employed to forecast imminent degradation in components, serving as a basis for determining the necessity of short‐term adjustments. This paper embeds the consideration of economic dependencies among components within the maintenance strategy design and employs hierarchical clustering to establish an effective and efficient maintenance grouping policy. The experimental results demonstrate that our proposed strategy significantly outperforms conventional approaches, including block‐based and age‐based maintenance, resulting in substantial cost savings. The proposed strategy is also compared with a similar version without grouping, and the results verify the added value of the optimal maintenance grouping policy in cost reduction. Moreover, a comprehensive analysis of the proposed method is provided, including the impact of different inspection costs and inspection intervals on maintenance decision‐making, which can provide insightful guidance to various PdM scenarios in practice. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) is an immune-mediated disease that has a considerable health-related quality of life interference. Various disease-modifying therapies (DMTs) in MS management have been approved by the Food and Drug Administration or are currently used off-label. DMTs aim to slow down the progression of MS and decrease the frequency of relapses. This systematic review aimed to evaluate the budget impact of DMTs worldwide. Methods: A systematic search query was made to identify related articles in scientific databases. Eligible papers included their characteristics and model inputs, and results were extracted and reported. To critique the standard reporting of studies, a 32-item quality assessment checklist was used. Results: From 1865 records, 22 original budget-impact analyses (BIAs) were included. All BIAs were accepted in the quality assessment (Mean score: 84.4). The most used DMT was β-interferons and natalizumab among novel DMTs. The results of BIAs were highly sensitive to the route of administration, costs of side effects and administration, and presence of biosimilars. However, glatiramer acetate has not experienced significant discounts was the most reported budget-saving DMT. Conclusion: From the results, it can be concluded the budget impact of DMTs in managing symptoms and improving the quality of life of MS patients according to the setting included in the modeling and according to specific conditions and context is different and significantly affects the results of BIAs. For accurate predictions of the effects of DMTs on the distribution of budgets in the MS population, more specific BIAs with higher quality should be done. [ABSTRACT FROM AUTHOR]

Introduction: In some regions, NHS patients are able to self-refer to physiotherapy. Initial assessment and triage of these referrals is via telephone (PhysioDirect) or face-to-face (Physio Access Clinic). There is currently a scarcity of literature comparing both methods in physiotherapy triage. A multi-domain mixed-methods comparison was conducted to evaluate cost, outcomes & satisfaction of both methods. Method: Data was collected for telephone and face-to-face self-referrals from October 2021 to February 2022 and analysed to compare patient outcome, patient satisfaction, physiotherapist perception and cost between both delivery methods. Results: Outcomes were analysed across 2402 total patient contacts, with face-to-face assessment showing improved outcomes in all areas compared to telephone assessment. Patient satisfaction was greater following face-to-face assessment than telephone. Physiotherapists showed greater satisfaction, greater diagnostic confidence, greater feeling of support and improved learning with a face-to-face approach. Scaled to 150 patients per week face-to-face only was associated with an annual saving of over £40,000 compared to telephone only initial assessment. This is equivalent to 1503 physiotherapist hours and 550 administrative hours. Conclusion: Patients self-referring to musculoskeletal physiotherapy via a face-to-face clinic have improved outcomes with greater reported satisfaction. Physiotherapists preferred face-to-face appointments in all facets examined within this study. A significant annual cost saving was evident through face-to-face contact which is especially relevant in the current economic climate of the NHS. Given these notable advantages of face-to-face triage over telephone triage, these findings could inform the planning of future physiotherapy provision. [ABSTRACT FROM AUTHOR]

This article addresses the asynchronous guaranteed cost control (GCC) problems for interval type‐2 (IT2) fuzzy continuous‐time Markov jump systems (C‐TMJSs) with quantization and non‐consecutive transmission. A dynamic event‐triggered mechanism (ETM) for IT2 fuzzy C‐TMJSs is designed to address the limited bandwidth and communication burden, which incorporates mode‐dependent thresholds and weighting matrices. An asynchronous IT2 fuzzy guaranteed cost controller possessing unmatched premise variable information is developed to stabilize the considered system, achieving desired GCC performance. The relationship between system mode and controller mode is described by the hidden Markov model (HMM). A quantizer is employed to quantize the signal prior to transmission to the next node, modeled as a stochastic quantization utilizing the HMM. Furthermore, an improved mode‐dependent and fuzzy‐dependent Lyapunov function is constructed for stability analysis, and the conditions of optimal GCC performance are derived. Finally, two examples are performed to validate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In order to improve the monitoring efficiency of the multivariable autocorrelation process and reduce the cost of process control, an economic design method of residual Multivariate Exponentially Weighted Moving Average (MEWMA) control charts with variable sample size and sampling intervals (VSSIs) was proposed. First, residual MEWMA control charts with VSSI were designed for monitoring multivariable autocorrelation processes. Second, the economic model of the VSSI residual MEWMA control chart was established, and a data example was given. The optimal design parameters of the control chart were obtained by using a genetic algorithm to minimize the expected cost per unit time. Third, using orthogonal experimental design and regression analysis, a sensitivity analysis of the economic model was carried out to get the relationship between the model parameters and the design parameters of the control chart. Finally, through the optimality analysis, it was verified that the proposed economic model was superior to the models established by the variable sampling intervals strategy and the variable sample size strategy and had less expected cost per unit time. [ABSTRACT FROM AUTHOR]

The application of cost escalation rates to commercial construction projects has historically been a straightforward task for estimators. However, the onset of the post-COVID-19 recovery period has introduced unprecedented challenges. The surge in inflation, followed by sharp disinflation triggered by one of the most aggressive interest rate hike cycles in Federal Reserve history, has created significant obstacles in forecasting future costs, a situation unfamiliar to many contemporary construction cost estimators. Unlike previous research that predominantly focused on cost indices tracking labor rates and building materials, our study integrates the Turner Building Cost Index, which also accounts for the competitive condition of the marketplace. Although traditional academic forecasting tools may perform well during periods of gradual economic expansion, they often falter amidst recessions or sudden economic shocks. Recognizing the crucial role of the overall economy in future cost projections, our paper rigorously examines current economic conditions and emphasizes concerns stemming from recent monetary policy actions by the Federal Reserve. We introduce an integrated forecasting approach, combing quantitative analysis with qualitative insights from industry experts—a process referred to as decision science analysis. This method allows estimators to incorporate a comprehensive view of the current economic landscape, transcending conventional academic models. Our methodology projects costs across three scenarios: best-case, average, and worst-case. In the best-case scenario, assuming the US economy avoids a recession or sudden economic shock, the annual escalation rate is forecasted at 2.8% over the next 7 years. In contrast, a worst-case scenario characterized by a severe recession could cause a decrease in cost by 13% within 2 years of the index peak. This study underscores the importance of considering macroeconomic conditions during periods of heightened economic uncertainty. Furthermore, it showcases how effective collaboration between industry and academia can yield a robust and comprehensive forecasting approach, adaptable to any economic climate. Practical Applications: The leading US authority and educator in cost estimating has emphasized the necessity for practitioners to incorporate unexpected downturn in forecasts, as outlined in its guidelines. This study directly aligns with such industry calls for the inclusion of economic impacts on cost forecasting, contributing valuable perspectives to the existing body of knowledge. By introducing economic indicators, the study provides a deeper understanding of the current economy, employing a data-driven approach of forecasting commercial construction indices amid economic uncertainty. Diverging from conventional academic approaches, the research integrates a qualitative dimension through decision science and scenario analysis, fostering a closer connection between industry practitioners and academia. The deliberate use of simplified language and a straightforward technical structure enhances accessibility and adaptability, ensuring that the findings are readily embraced by industry professionals. This research is particularly relevant for construction cost estimators and project stakeholders aiming to enhance their understanding of imminent risks and opportunities in cost management. Regardless of the economic trajectory, readers will gain the capability to forecast future costs with heightened confidence and precision, offering invaluable insights for strategic decision-making in construction projects. We encourage continual dialogue between academia and industry, fostering a dynamic exchange of insights and knowledge. [ABSTRACT FROM AUTHOR]

In order to solve the problems of high production cost and complex control of the inverted arch of an unsupported prestressed concrete composite slab, a flange truss high-ductility concrete composite slab floor is proposed to change the structure and pouring material to meet the requirements of no support during construction. The crack distribution and bending performance of the flange truss high-ductile concrete composite slab floor (CRHDCS) under different structures are clarified through the test and numerical analysis of four different rib plate structure floors. According to the analysis results, the calculation formulas of the cracking moment and short-term stiffness before cracking are modified, and the equivalent short-term stiffness formula of a single web member of the "V" truss to this kind of bottom plate is established. The results show that, unlike the short-term stiffness-change law of typical concrete composite slabs after cracking, the short-term stiffness of the designed bottom plate in this paper includes a short-term increase stage. The numerical simulation results are the same as the experimental ones; the maximum error is 10%. The maximum errors between the modified cracking moment and the short-term stiffness calculation formula are 6% and 8%, respectively. The influence rates of removing flange plate, truss-inverted binding, and adding rib plate on the cracking bending moment of foundation structure are −81.5%, 11.0%, and 22.2% respectively, and the influence rates on short-term stiffness are −87.6%, −1.5%, and 37.5% respectively. [ABSTRACT FROM AUTHOR]

Purpose: Laser powder bed fusion (LPBF) additive manufacturing (AM) enables the design of complex parts using materials that are otherwise difficult to fabricate. Due to the high cost of machines, the parts produced by LBPF are expensive. Both researchers and industry are therefore focused on lowering costs by improving productivity while ensuring part quality. The purpose of this study is to quantify the productivity gains from using laser beam shaping, multi-laser printing and the use of large build chambers to print larger size parts. Design/methodology/approach: This paper performs an expert elicitation with 18 experts. Findings: This paper finds that experts believe that larger parts are less likely to print successfully. Increasing the part footprint is more detrimental to print success than increasing part height. Experts also believe that beam shaping is expected to provide limited print time improvement (median 4% reduction, 90% CI: 2%–25%) while improving part quality, whereas going from one to two lasers is expected to provide a median of 25% (90% CI: 10%–45%) print time improvement but degrade part quality. Through cost analysis of a representative part, this paper shows that the uncertainty in build success rates for large parts dominates expected cost reductions from laser beam shaping or multi-laser printing. Research limitations/implications: The study has three key limitations. First, it is possible that the sample of experts who agreed to take the survey biases the results. By definition, these are individuals who are willing to share what they know. There may be other experts who have a different view of the efficacy of the technologies evaluated here, but that view might be based on proprietary knowledge, which those experts are unable to share. Second, an elicitation captures what is known at a moment in time. As technology improves and as widespread deployment results in learning, the most consequential finding − that experts believed that success rates for large builds are likely to be low − may become less valid. Third, the overarching goal of this study is to assess technologies to improve AM productivity for high performance metal parts. A single study can only partially achieve this goal. The selection of technologies is constrained by both the desire to keep the study tractable and the suitability of expert elicitation as a method. For example, expert elicitation is not appropriate to assess the efficacy of technologies where sufficient empirical data or analytical techniques exist. Practical implications: The results show that AM research and policy initiatives, including standards and regulatory schemes, must support efforts to improve the repeatability and reliability of the technological innovations that are needed to deploy AM in cost-critical or high throughput applications. These results also reinforce the criticality of workforce development components of existing (and future) AM policy initiatives. The elicitation revealed a significant number of factors that must be considered and potentially managed to ensure successful builds. Notably, no experts interviewed discussed all factors. While this may be a consequence of availability bias, it suggests that inexperienced AM users and nonexpert decision-makers, including managers, who would like to adopt new AM technologies, may be unaware of the myriad mechanisms by which build failure can occur and may fail to take mitigating action. This result contradicts a common belief that complicated parts can be fabricated with little to no expertise (assuming access to a design file for the part). Workforce development programs will be essential to help AM users develop the knowledge required to successfully implement metal AM. Originality/value: Several strategies, including increasing the build volume to print larger parts or more parts at a time, using multiple lasers and beam shaping are proposed to improve the productivity of AM. However, the real-world efficacy of these strategies is not known. This work pools the judgment of experts to give decision-makers some insight into the current, real-world efficacy of these approaches. [ABSTRACT FROM AUTHOR]

The management of chronic myeloid leukemia (CML) now includes dose reduction (DR) and treatment-free remission (TFR). Evaluating the cost-effectiveness of lifelong-prescribed expensive tyrosine kinase inhibitors (TKIs) for CML is crucial. Prior cost-effectiveness evaluations state that imatinib is the favorable frontline TKI. Some of these evaluations address TFR, but not DR, nor aging and second-generation (2G)-TKIs upcoming patent expirations. This study evaluates the cost-effectiveness of frontline TKIs for CML patients including these factors. This Markov model evaluates the cost-effectiveness of frontline TKIs for newly diagnosed patients with CML using 17 health states. Transition probabilities, costs, and utilities were derived from literature data. Incremental cost-effectiveness ratios were calculated. Sensitivity analysis and model validation were conducted. Nilotinib is most effective (20.13 quality-adjusted life-years [QALYs]) and imatinib is least effective (17.25 QALYs) for the model including TFR and DR. Imatinib was favored over dasatinib (89.80%), nilotinib (62.70%), and bosutinib (78.40%), at a willingness-to-pay threshold of €80 000 per QALY. Without TFR and DR, fewer QALYs were generated. For patients at the age of 70 years, imatinib has a high probability of being more cost-effective than dasatinib, nilotinib, and bosutinib. With 50% 2GTKI cost reductions, nilotinib is considered more cost-effective compared with imatinib (98.40%), dasatinib (94.80%), and bosutinib (68.90%). The findings indicate that 2GTKIs are more effective in generating QALYs, including for older (age >70 years) patients. Given the current TKI prices, imatinib remains cost-effective. Including DR and TFR in CML management generates more QALYs. Cost reductions from expected 2GTKIs patent expirations will greatly increase their cost-effectiveness. Results may inform 2GTKIs cost discussions after patent expiration, potentially broadening global availability. The findings also emphasize the importance of aiming for TFR and DR in CML management. • Evidence on the cost-effectiveness of first- and second-generation (2G) tyrosine kinase inhibitors (TKIs) for chronic myeloid leukemia—considering treatment-free remission (TFR), dose reduction (DR), anticipated patent-expirations, and treatment in older patients—is limited. • 2GTKIs are the most effective, but imatinib remains cost-effective because of its lower price. TFR and DR increase quality-adjusted life-years and reduce costs. • TFR and DR offer the potential to optimize chronic myeloid leukemia management and resource allocation. Cost reductions after patent expirations could improve worldwide 2GTKIs access. [ABSTRACT FROM AUTHOR]

This article from the Journal of Neurological Surgery explores the cost differences between resecting meningiomas and gliomas, two common brain tumors. The study found that meningioma surgeries are significantly more expensive than glioma surgeries, with an average increase of $1,704.01. Factors such as tumor location and surgeon expertise also impact the overall costs of these surgeries. The application of Time-driven activity-based costing (TDABC) provides a more accurate reflection of intraoperative costs, offering valuable insights for cost management strategies in neurosurgical departments and reimbursement policies. [Extracted from the article]