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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.)

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]

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]

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]

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]

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]

In this paper, we study two schemes of pooled annuity funds: pools with and without fund managers. In the pool without managers, there are no artificial rules or management cost and we introduce Nash equilibrium to depict the simultaneous non-cooperative game among participants. Given others' strategies, participants choose optimal consumption and investment strategies to maximize their own utility. In the pool with managers, the fund manager makes artificial rules for consumption and investment, ensuring cooperation among participants. The manager then determines optimal consumption withdrawal and investment strategies to maximize the total utility of all participants. By using variational methods and recursive algorithms, semi-analytical solutions in both pools are obtained. Due to prisoner's dilemma, larger pools without managers induce more intense competition in consumption and reduce utility. Thus, there exists an optimal pool size and only homogeneous participants form the pool. Meanwhile, larger pools with managers diversify investment and longevity risks more sufficiently and the subsidy effect among participants is mitigated. Therefore, the perfect pool with infinite participants is recommended as the optimal pool. Moreover, the preference between the two optimal pools depends on risk aversion degree, management cost and flexibility in selecting the strategies. [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 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]

Prospective payments for health care providers require adequate risk adjustment (RA) to address systematic variation in patients' health care needs. However, the design of RA for provider payment involves many choices and difficult trade-offs between incentives for risk selection, incentives for cost control, and feasibility. Despite a growing literature, a comprehensive framework of these choices and trade-offs is lacking. This article aims to develop such a framework. Using literature review and expert consultation, we identify key design choices for RA in the context of provider payment and subsequently categorize these choices along two dimensions: (a) the choice of risk adjusters and (b) the choice of payment weights. For each design choice, we provide an overview of options, trade-offs, and key references. By making design choices and associated trade-offs explicit, our framework facilitates customizing RA design to provider payment systems, given the objectives and other characteristics of the context of interest. [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]

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]

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]

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]

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]

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]

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]

In this paper, the full state dependent event-triggered aperiodic intermittent control (FE-AIC) strategy based on input constraints is introduced to minimize energy consumption and enhance speed tracking accuracy in the high-speed train (HST) operation. Firstly, a dynamic model based on multi-mass-point (MMP) for HST has been established, transforming the cruise control problem into an error asymptotic convergence problem. Secondly, restricted FE-AIC (RFE-AIC) controller is designed separately in the presence and absence of external disturbances to realize tracking objects. The proposed control scheme is not only based on control input constraints, but also intermittent control with full state event dependence. The RFE-AIC scheme and the conditions for determining parameters are given, which ensures the stability of the ideal tracking speed and coupler deviation at the equilibrium point. Eventually, the availability of the proposed method in cruise control is confirmed through numerical simulations. It is proved that the RFE-AIC has better performance compared with the self-triggered and guaranteed optimal cruise control methods. • The RFE-AIC is applied in HST systems with disturbances and parameter uncertainties to reduce control costs due to intermittent event-triggered control. • The RFE-AIC method ensures the asymptotic speed tracking reachability of the HST system with fewer control iterations. • The robust RFE-AIC can effectively improve the velocity accuracy of the HST system with disturbances, and an optimization algorithm is provided to obtain the minimum control gain under input constraints. • Numerical simulations verify the effectiveness of the proposed RFE-AIC method. [ABSTRACT FROM AUTHOR]

Different project management processes have been used in software engineering to support managers in keeping project costs manageable. One of the essential processes in software engineering is to accurately and reliably estimate the required effort and cost to complete the projects. The domain of software cost estimation has witnessed a prominent surge in research activities in recent years and being an evolving process, it keeps opening new avenues, each with advantages and disadvantages, making it important to work out better options. This research aims to identify the factors that influence the software effort estimation using the constructive cost model (COCOMO), and artificial neural networks (ANN) model by introducing a novel cost estimation approach, COCOMO-ANN (CANN), utilizing a partially connected neural network (PCNN) with inputs derived from calibrated values of the COCOMO model. A publicly available dataset (COCOMONASA 2), various combinations of activation functions, and layer densities have been systematically explored, employing multiple evaluation metrics such as MAE, MRE, and MMRE. In the PCNN model, the ReLU activation function and a 1000-dense layer have demonstrated better performance. While layer density generally correlates with better outcomes, this correlation is not universally applicable for all activation functions and outcomes vary across different combinations. The use of the relationships between 26 key parameters of COCOMO in PCNN produced better results than FCNN by 0.59%, achieving an MRE of 6.55 and an MMRE of 7.04. The results indicated that the CANN model (COCOMO & ANN) presented better results than existing models. [ABSTRACT FROM AUTHOR]

This paper sought to determine the drivers and effective tips for combating the barriers to effective Cost Control systems in Engineering Infrastructure geared towards national development in the construction industry in Nigeria. A questionnaire was designed and distributed to some selected Architects, Quantity Surveyors, Structural, Mechanical and Electrical Engineers in Siegal Construction Company in Owerri, Imo State Nigeria. The study was carried out in south-eastern Nigeria and data collected analyzed by percentages and means. Results showed that, Training and education of Cost Control Client commitment and involvement and Government intervention, were considered as drivers to cost control system. Results also showed that amongst the eight items considered as barriers of cost control systems, unreliability of data, Separation of capital and running cost of project and Type of investor/user were prominent. Amongst seven items deemed as the necessary techniques for the improvement of Cost Control systems, Reengineering of building and maintenance Process, Integrated approach in infrastructural design and construction, and Introducing new construction and maintenance concepts, received the highest recommendations from the professionals. It is recommended that the above suggested views by the professionals be adopted by the construction industry as an effective technique to cost control systems towards national development. [ABSTRACT FROM AUTHOR]

In recent years Quantum Cellular Automata (QCA) technology has emerged as an ideal option to substitute the current CMOS technology. QCA offers operation in the terahertz range, small area, and low power in nano-scale circuit design. This paper explores the application of quantum dot cellular automata(QCA) technology in efficient floorplanning of digital code converters using the tile based architecture of QCA XOR gate. The proposed code converter circuits exhibits the benefits of low cell count, area, cost and low energy dissipation. The suggested layouts have achieved the 11.42% reduction in cell count, 29.53% reduction in total occupational area,30.93% reduction in cost and 11.52% increase in area utilization factor in comparison to similar counterparts. The functional validity of the suggested designs were validated using QCADesigner 2.0.3 tool. In addition, the energy dissipation analysis were calculated using the QCAPro tool at standard tunelling energy levels o 0.5EK, 1.0EK, 1.5EK. [ABSTRACT FROM AUTHOR]

This paper investigates how product market competition affects the performance of closely held small and medium enterprises (SMEs) in developing economies. In contrast to prior findings that focus on large publicly traded companies in developed economies, we find that market competition has a negative effect on firm performance. Our findings are robust to different measures of competition and firm performance and survive after addressing endogeneity issues. We provide evidence that the adverse effect of competition is channeled through increased corruption. Our findings further suggest that firms respond to competition by attempting to acquire more financial resources and government support, adopt quality improvement and cost reduction policies. The adverse effect of competition is especially strong for smaller firms. [ABSTRACT FROM AUTHOR]

Background: TearCare is an in-office procedure indicated to treat MGD and relieve DED signs and symptoms. MGD is a major cause of DED, a high-prevalence condition currently treated with medical therapies including over-the-counter and prescription drops. The BIA assessed the budget impact of increasing the TearCare market share against prescription drops in treating moderate to severe MGD-associated DED in US patients ≥ 18 years over 2 years. Research Design and Methods: Prescription drops used twice daily were compared to TearCare (used once per year for patients with moderate disease and twice for severe disease). The BIA assumed a health plan population with 1 million lives and incorporated population characteristics, treatment allocation, market share, and treatment persistence. Assuming a 20% increase in TearCare market share, the model calculated total per member per year/cost (PMPY/PMPM). Results: Results showed PMPY and PMPM savings of $34.47 and $2.87, respectively. Sensitivity analysis indicated sensitivity to the proportion of moderate DED patients using prescription drops, moderate to severe DED incidence, and cyclosporine 0.05% costs. If 10% of patients did not switch to TearCare, notable savings were still observed with PMPY and PMPM savings of $30.11 and $2.51 over 2 years. Conclusion: Results show cost savings with a TearCare market share increase in treating MGD-associated DED. [ABSTRACT FROM AUTHOR]

We provide an up-to-date literature review that describes the state of the art on the impact of digitalization on firm performance. Firms' digitalization processes are associated to productivity gains, innovation, costs reductions, and new business models and revenue opportunities. The bulk of empirical estimates reviewed for the firm-level support these findings. However, these results are not necessarily unanimous, as some research has not been able to verify these positive effects. Our findings point to a diminishing methodological quality due to the lack of robust strategies to eliminate endogeneity concerns, a problem driven by the inadequacy of public datasets to study the main object of this literature review. [ABSTRACT FROM AUTHOR]

Tool wear monitoring is crucial for quality control and cost reduction in manufacturing processes, of which drilling applications are one example. Identification of the wear area in images of cutting inserts is important to building a reliable ground truth for the development of indirect monitoring approaches. Therefore, we present a semantic image segmentation pipeline for wear detection on microscopy images of cutting inserts. A broadly used convolutional neural net, namely a U-Net, is trained with different preprocessing and optimisation task configurations: On the one hand the problem is considered as binary problem, and on the other hand as multiclass problem by differentiating the wear into two different types. By comparing these two problem formulations we investigate whether the separation of the two wear structures improves the performance of the recognition of the wear types. For both problem formulations three loss functions, i. e., Cross Entropy, Focal Cross Entropy, and a loss based on the Intersection over Union (IoU), are investigated.The use of different augmentation intensities during training suggests adequate but not too excessive augmentation, and that with optimal augmentation the choice of loss function gets less important. Furthermore, models are trained on image tiles of different sizes, which has an impact on producing artefacts on the whole image predictions performed by the overlap-tile strategy. In summary, the best performing models are binary models, trained on data with moderate augmentation and an IoU-based loss function. [ABSTRACT FROM AUTHOR]