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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]

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]

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]

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]

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.)

U.S. equity exchanges have experienced a dramatic increase in competition from new entrants, resulting in the fragmentation of trading across venues. While market quality has generally improved over this period, we show most of the improvements have accrued to the largest stocks. We then show this bifurcation in market quality is related to the fragmentation of trading. Theoretically, more exchange competition should reduce trading costs, yet it may also increase adverse selection for liquidity providers, leading to higher spreads. We document evidence of both effects (fragmentation improves market quality for large stocks while small stocks experience relatively worse quality). [ABSTRACT FROM AUTHOR]

The Joint Assembly Line Balancing and Feeding Problem (JALBFP) assigns a line feeding mode to each component (Assembly Line Feeding Problem) and each task to a workplace of a station (Assembly Line Balancing Problem). Current literature offers numerous optimisation models that solve these problems sequentially. However, only few optimisation models, provide a joint solution. To solve the JALBFP for a multi-manned assembly line, we propose a Mixed Integer Linear Programming (MILP) model and a heuristic that relies on the Adaptive Large Neighborhood Search (ALNS) framework by considering multiple workplaces per station and three different feeding policies: line stocking, travelling kitting and sequencing. The objective function minimises the cost of the whole assembly system which considers supermarket, transportation, assembly operations, and investment costs. Although the JALBFP requires higher computation times, it leads to a higher total cost reduction compared to the sequential approach. Through a numerical study, we validate the heuristic approach and find that the average deviation to the MILP model is around 1%. We also compare the solution of the JALBFP with that of the sequential approach and find an average total cost reduction of 10.1% and a maximum total cost reduction of 43.8%. [ABSTRACT FROM AUTHOR]

Recent economics of knowledge studies have highlighted the strong positive effects that the limited exhaustibility of knowledge and its cumulability exert on the recombinant generation of new technological knowledge. While existing empirical investigations primarily focus on the knowledge generation and technology production functions, the analysis of the cost of knowledge has received less attention. This paper aims to fill this gap by investigating the dynamics and determinants of patent costs in the European Union in the period 1992–2012. The analysis of patent unit costs in European countries, measured as the amount of research and development (R&D) expenditure per patent application to the European Patent Office (EPO), shows a steady decline and clear convergence toward lower levels, both in time and across countries. We find that a larger stock of patents and a higher technological variety and coherence of its composition are associated with a sharper reduction in patent costs. Our findings suggest that, in Europe, ideas have been getting cheaper. [ABSTRACT FROM AUTHOR]

The profit margin of construction enterprises has been continuously declining over the past few years, and the competition for contracts among construction enterprises turns out to be increasingly fierce. Construction contracting enterprises should consider the profitability of the construction contracting enterprise and its ability to continuously obtain orders when setting cost budget targets for project management departments. Thus, a dual objective decision-making model is built in this study, minimizing overall construction costs and maximizing owner satisfaction to clarify the contracting conditions of the project management department and facilitate decision-making optimization of cost and owner satisfaction goals. Moreover, the actual effect of the proposed model method is verified through case calculations. As indicated by the results, under the premise of maximizing owner satisfaction, the model optimization cost is lower than the actual cost that has already occurred. Furthermore, it conforms to the goal of maximizing owner satisfaction while fulfilling the goal of minimizing engineering costs.

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.)

In explaining the effectiveness of a human resource (HR) system within an organization, scholars have turned their attention to HR attributions, which capture employees' perceptions about the intentions behind their organization's HR practices, and have demonstrated that an HR system's content and process of communication drive employees to form specific HR attributions. However, current research has not yet explained why HR attributions differ among employees. We investigate the variability in HR attributions among individuals and the organizational factors that influence this variability. Using signaling theory and the concept of situational strength, we argue that employees' HR attributions vary less when signals sent by HR management are unambiguous and the conveyed information is consistent. Using an online scenario‐based experiment with 760 participants, our findings reveal that the configuration and the strength of an HR system as well as their combination have significant effects on the variability in HR attributions among employees, and these effects differ for the different HR attributions. [ABSTRACT FROM AUTHOR]

Platform-based product development has been applied extensively in discrete manufacturing industry to accommodate changing market demands. Nevertheless, while process industry manufacturers face similar market demands, the topic is only sparsely covered in literature. Through a systematic review of the literature, this study uncovers the definitions used, drivers behind, approaches and methods applied, and industry examples of platform-based product development in the process industry. Based on these analyses, a research agenda is then proposed to further the knowledge of this topic. The study identified existing definitions of key platform-related terms used in several studies and furthermore discovered new definitions for some terms. The most prominent drivers behind pursuing platform-based product development was found to be cost reduction and productivity of product development, with development lead time reduction playing a less significant role. Literature related to platform-based product development focuses primarily on product design and development issues, with less attention given to market, manufacturing, and supply chain issues. Only few industrial cases were identified within the process industry while multiple anecdotal descriptions were discovered. For future research, further insight into key platform concepts, applicability of existing methods, broader value chain focus and detailed industrial cases are considered relevant. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed optimization problem of networked Euler–Lagrange (EL) systems with actuator faults and unknown model parameters. In order to solve this issue, some event‐triggered fault‐tolerant (ETFT) optimal coordination algorithms with the mechanism of intermittent communication and intermittent controller update are designed for the first time to compensate for the impact of physical faults on the system, and reduce communication costs and control resource consumption. For practical applications, it is difficult for the system to have a secure environment if there exist malicious attacks blocking network channels among agents. Therefore, the resilient ETFT optimal coordination with intermittent communication subject to asynchronous denial‐of‐service (DoS) attacks is considered. Especially, auxiliary systems with adaptive gains are introduced in the algorithms due to the unavailability of the EL model parameters, which also enable virtual data exchange between agents and protect actual state information. Note that the algorithms are fully distributed as the global topology information is not required. Finally, the feasibility of the proposed algorithms is verified through numerical simulation of examples. [ABSTRACT FROM AUTHOR]

Background Control of schistosomiasis (SCH) relies on the regular distribution of preventive chemotherapy (PC) over many years. For the sake of sustainable SCH control, a decision must be made at some stage to scale down or stop PC. These "stopping decisions" are based on population surveys that assess whether infection levels are sufficiently low. However, the limited sensitivity of the currently used diagnostic (Kato-Katz [KK]) to detect low-intensity infections is a concern. Therefore, the use of new, more sensitive, molecular diagnostics has been proposed. Methods Through statistical analysis of Schistosoma mansoni egg counts collected from Burundi and a simulation study using an established transmission model for schistosomiasis, we investigated the extent to which more sensitive diagnostics can improve decision making regarding stopping or continuing PC for the control of S. mansoni. Results We found that KK-based strategies perform reasonably well for determining when to stop PC at a local scale. Use of more sensitive diagnostics leads to a marginally improved health impact (person-years lived with heavy infection) and comes at a cost of continuing PC for longer (up to around 3 years), unless the decision threshold for stopping PC is adapted upward. However, if this threshold is set too high, PC may be stopped prematurely, resulting in a rebound of infection levels and disease burden (+45% person-years of heavy infection). Conclusions We conclude that the potential value of more sensitive diagnostics lies more in the reduction of survey-related costs than in the direct health impact of improved parasite control. [ABSTRACT FROM AUTHOR]

In modern transportation systems, the potential for further reducing costs is severely limited. Increased competitiveness through cost reduction can be achieved if there is a collaboration among transportation companies. Participation in such collaboration can benefit all participating companies as a whole, as well as each company individually, by increasing the participants' competitiveness. In this study, we propose a game-theoretical approach for collaboration among transportation companies in a transportation system consisting of several independent transportation companies. We introduce a new transportation game called the cost transportation game (CTG) and prove that the CTG is a transferable utility game with a super additive characteristic function and a non-empty core. To obtain the core allocations, we introduce the restriction of a feasible solution and theoretically demonstrate that points in the core cannot be expressed only by dual optimal solutions but also by the optimal restrictive transportation scheme (ORTS), which implies that the points in the core can be obtained by solving ORTS and the core allocations can be realized by implementing ORTS. Finally, we present computational results for real-life and artificial instances. [ABSTRACT FROM AUTHOR]

• A new constellation lifecycle cost optimization problem was introduced. • Useful insights to the satellite burn-in problem can guide satellite manufacturers. • Long testing durations are undesirable; testing can be traded off with number of satellites produced. • Combining burn-in, warranty and availability analysis opens new paths for constellation research. Constellation lifecycle costs are an important metric for constellation designers. Recurring costs of mega constellations in particular are large relative to the non-recurring costs, yet little attention has been given to the reduction of recurring costs. Moreover, few studies exist on the impacts of pre-launch activities such as satellite testing on subsequent operational reliability. We thus study the lifecycle cost impacts of environmental stress screening during acceptance testing to minimize constellation lifecycle costs. Parallels are drawn with the field of electronics testing, and costs arising from burn-in, replacement and availability are considered in our formulation. A single-objective cost minimization problem and a multi-objective cost and unavailability minimization problem are presented to capture different mission applications that require different objectives. The effects of system homogeneity and the use of sparing strategies are investigated. We propose genetic algorithms to solve the optimization problems and give some insight into how burn-in should be carried out for minimizing total costs. The optimization is also applied to a case study of a proposed mission scenario and the constellation lifecycle costs of an optimized burn-in plan are compared to those of a typical "reliability target" burn-in plan. The optimization resulted in lifecycle cost savings of around 19% while significantly reducing the burn-in duration, showing much promise in the burn-in cost optimization approach. [ABSTRACT FROM AUTHOR]

Background: Indigenous populations have increased risk of developing diabetes and experience poorer treatment outcomes than the general population. The FORGE AHEAD program partnered with First Nations communities across Canada to improve access to resources by developing community-driven primary healthcare models. Methods: This was an economic assessment of FORGE AHEAD using a payer perspective. Costs of diabetes management and complications during the 18-month intervention were compared to the costs prior to intervention implementation. Cost-effectiveness of the program assessed incremental differences in cost and number of resources utilization events (pre and post). Primary outcome was all-cause hospitalizations. Secondary outcomes were specialist visits, clinic visits and community resource use. Data were obtained from a diabetes registry and published literature. Costs are expressed in 2023 Can$. Results: Study population was ~ 60.5 years old; 57.2% female; median duration of diabetes of 8 years; 87.5% residing in non-isolated communities; 75% residing in communities < 5000 members. Total cost of implementation was $1,221,413.60 and cost/person $27.89. There was increase in the number and cost of hospitalizations visits from 8/$68,765.85 (pre period) to 243/$2,735,612.37. Specialist visits, clinic visits and community resource use followed this trend. Conclusion: Considering the low cost of intervention and increased care access, FORGE AHEAD represents a successful community-driven partnership resulting in improved access to resources. [ABSTRACT FROM AUTHOR]

In this paper, a novel parametrized guaranteed cost control (PGCC) method with prescribed performance control (PPC) is proposed for nonlinear systems with unknown bounded uncertainties and external disturbances described by Euler‐Lagrange (EL) equations. The proposed method is capable of ensuring a robust optimal performance in the presence of dynamics constraints without the specific information of nonlinear perturbation. As a consequence, the conditions in the form of disturbances and uncertainties are also relaxed. The augmented model is converted by transforming the uncertainties and disturbances in the original system to a mismatched term using asymmetric PPC. By designing and modifying the novel guaranteed cost function to account for the maximum value of the nonlinear perturbation, an infinite‐horizon PGCC problem is proposed by the unconstrained stationary optimal control problem. The relevant proposed linear parametrized Hamilton‐Jacobian‐Bellman (PHJB) equation is approximated to solve by a critic‐only neural network (NN) with efficient computationally. Uniformly ultimately bounded stability is guaranteed via a Lyapunov‐based stability analysis. Finally, numerical simulation results demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) remains serious around the world and causes huge deaths and economic losses. Understanding the transmission dynamics of diseases and providing effective control strategies play important roles in the prevention of epidemic diseases. In this paper, to investigate the effect of delays on the transmission of COVID-19, we propose a delayed SEIR model to describe COVID-19 virus transmission, where two delays indicating the incubation and recovery periods are introduced. For this system, we prove its solutions are nonnegative and ultimately bounded with the nonnegative initial conditions. Furthermore, we calculate the disease-free and endemic equilibrium points and analyze the asymptotical stability and the existence of Hopf bifurcations at these equilibrium points. Then, by taking the weighted sum of the opposite number of recovered individuals at the terminal time, the number of exposed and infected individuals during the time horizon, and the system cost of control measures as the cost function, we present a delay optimal control problem, where two controls represent the social contact and the pharmaceutical intervention. Necessary optimality conditions of this optimal control problem are exploited to characterize the optimal control strategies. Finally, numerical simulations are performed to verify the theoretical analysis of the stability and Hopf bifurcations at the equilibrium points and to illustrate the effectiveness of the obtained optimal strategies in controlling the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

When a movement triggers effects with incompatible features, conflict between action and effect features creates costs for action planning and initiation. We investigated whether such action control costs also factor into action choices in terms of the principle of least effort. Participants completed a reaction-time experiment, where they were instructed to perform left and right mouse swipes in response to directional cues presented on the screen. Participants could select between two action options on each trial: Depending on which part of the screen (upper or lower) the action was performed in, the swipe resulted in a visual stimulus moving in the same (compatible) or in the opposite (incompatible) direction as the mouse. Incompatible action–effect mappings did indeed incur action control costs. In accordance with effort avoidance, the proportion of compatible choices was significantly above chance level, suggesting that action selection and initiation costs factor into participants preferences. Interestingly, however, participants' choice tendencies were not predicted by the actual increase in action-initiation costs in the incompatible condition. This indicates that effort-related decisions are not simply based on monitoring performance in the actual task, but they are also influenced by preestablished notions of action-planning costs. [ABSTRACT FROM AUTHOR]

Pharmaceutical waste is a serious threat to both human health and the environment. This article discusses the impact of pharmaceutical waste, and explores the possibility of reusing unwanted medicines to mitigate the problem and the current barriers to implementation. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To assess initiatives to manage the cost and outcomes of specialty care in organizations that participate in Medicare accountable care organizations (ACOs). STUDY DESIGN: Cross-sectional analysis of 2023 ACO survey data. METHODS: Analysis of responses to a 12-question web-based survey from 101 respondents representing 174 ACOs participating in the Medicare Shared Savings Program or the Realizing Equity, Access, and Community Health ACO model in 2023. RESULTS: Improving specialist alignment was a high priority for 62% of the 101 respondents and a medium priority for 34%. Only 11% reported that employed specialists were highly aligned and 7% reported that contracted specialists were highly aligned. A subset of ACOs reported major efforts to engage specialists in quality improvement projects (38%) and to convene specialists to develop evidence-based care pathways (30%). They also reported supporting primary care physicians through providing specialist directories (44%), specialist e-consults (23%), and sharing specialist cost data (20%). The most common challenges reported were the influence of fee-for-service payment on specialist behavior (58%), lack of data to evaluate specialist performance (53%), and insufficient bandwidth or ACO resources to address specialist alignment (49%). CONCLUSIONS: Engaging specialists in accountable care is an emerging area for ACOs but one with numerous challenges. Making better data on specialist costs and outcomes available to Medicare ACOs is essential for accelerating progress. [ABSTRACT FROM AUTHOR]

Background: Studies show that reducing the length of hospital stay (LOS) for surgical patients leads to cost savings. We hypothesize that LOS has a nonlinear relationship to cost of care and reduction may not have a meaningful impact on it. We have attempted to define the relationship of LOS to cost of care. We utilized the itemized bill, generated in real time, for hospital services. Materials: Adult patients admitted under General, Neuro, and Orthopedic surgery over a 3‐month period, with an LOS between 4 and 14 days, were the study population. Itemized bill details were analyzed. Charges in Pakistani rupees were converted to US dollar. Ethical exemption for study was obtained. Results: Of the 853 patients, 38% were admitted to General Surgery, 27% to Neurosurgery, and 35% to Orthopedics. A total of 64% of the patients had an LOS between 4 and 6 days; 36% had an LOS between 7 and 14 days. Operated and conservatively managed constituted 82% and 18%, respectively. Mean total charge for operated patients was higher $3387 versus $1347 for non‐operated ones. LOS was seen to have a nonlinear relationship to in‐hospital cost of care. The bulk of cost was centered on the day of surgery. This was consistent across all services. The last day of stay contributed 2.4%–3.2% of total charge. Conclusions: For surgical patients, the cost implications rapidly taper in the postoperative period. The contribution of the last day of stay cost to total cost is small. For meaningful cost containment, focus needs to be on the immediate perioperative period. [ABSTRACT FROM AUTHOR]

The 70 recommendations summarize the current status of preoperative risk evaluation of adult patients prior to elective non-cardiothoracic surgery. Based on the joint publications of the German scientific societies for anesthesiology and intensive care medicine (DGAI), surgery (DGCH), and internal medicine (DGIM), which were first published in 2010 and updated in 2017, as well as the European guideline on preoperative cardiac risk evaluation published in 2022, a comprehensive re-evaluation of the recommendation takes place, taking into account new findings, the current literature, and current guidelines of international professional societies. The revised multidisciplinary recommendation is intended to facilitate a structured and common approach to the preoperative evaluation of patients. The aim is to ensure individualized preparation for the patient prior to surgery and thus to increase patient safety. Taking into account intervention- and patient-specific factors, which are indispensable in the preoperative risk evaluation, the perioperative risk for the patient should be minimized and safety increased. The recommendations for action are summarized under "General Principles (A)," "Advanced Diagnostics (B)," and the "Preoperative Management of Continuous Medication (C)." For the first time, a rating of the individual measures with regard to their clinical relevance has been given in the present recommendation. A joint and transparent agreement is intended to ensure a high level of patient orientation while avoiding unnecessary preliminary examinations, to shorten preoperative examination procedures, and ultimately to save costs. The joint recommendation of DGAI, DGCH and DGIM reflects the current state of knowledge as well as the opinion of experts. The recommendation does not replace the individualized decision between patient and physician about the best preoperative strategy and treatment. [ABSTRACT FROM AUTHOR]

Background Due to chemotherapy-induced neutropenia or hematologic malignancies, immunocompromised cancer patients may have higher incidence of febrile nonhemolytic transfusion reactions compared with the general population and frequently require platelet transfusions. This quality improvement project compared the safety of transfusion using prestorage leukocyte-reduced and pooled whole blood–derived platelets (Acrodose/WBD) with conventionally produced poststorage WBD platelets (RDP) using an active hemovigilance system. Methods Every patient receiving a blood product at the hospital was virtually monitored in real time by trained nurses from a remote hemovigilance unit. These nurses monitor a digital dashboard, which populates a watch list of patients from the time blood product administration is initiated until 12 hours posttransfusion. Over the course of 6 months, 371 patients receiving 792 RDP transfusions and 423 patients receiving 780 Acrodose/WBD platelets transfusions were monitored for transfusion reactions. Results We identified 26 transfusion reactions in RDP but only 12 transfusion reactions in the Acrodose/WBD platelet group. Conclusion Acrodose platelet transfusion was associated with fewer transfusion reactions, which resulted in significant cost savings. [ABSTRACT FROM AUTHOR]

Background and Aim: Gastric intestinal metaplasia (GIM) is a high‐risk factor for the development of gastric cancer. Narrow‐band imaging (NBI) enables endoscopic grading of GIM (EGGIM). In the era of climate change, gastrointestinal endoscopists are expected to reduce greenhouse gas emissions and medical waste. Based on the diagnostic performance of NBI endoscopy, this study measured the environmental impact and reduced cost of implementing EGGIM during gastroscopy. Methods: Using NBI endoscopy in 242 patients, EGGIM classification and operative link on GIM (OLGIM) staging were prospectively performed in five different areas (lesser and greater curvatures of the corpus and antrum, and the incisura angularis). We estimated the environmental impact and cost reduction of the biopsy procedures and pathological processing if EGGIM were used instead of OLGIM. Results: The diagnostic accuracy of NBI endoscopy for GIM was 93.0–97.1% depending on the gastric area. When a high EGGIM score ≥ 5 was the cut‐off value for predicting OLGIM stages III–IV, the area under the curve was 0.862, sensitivity was 81.9%, and specificity was 90.4%. The reduction in the carbon footprint by EGGIM was −0.4059 kg carbon dioxide equivalents per patient, equivalent to 1 mile driven by a gasoline‐powered car. The cost savings were calculated to be $47.36 per patient. Conclusions: EGGIM is a reliable method for identifying high‐risk gastric cancer patients, thereby reducing the carbon footprint and medical costs in endoscopy practice. [ABSTRACT FROM AUTHOR]

The article describes the intensive care unit social work practice at Virginia Commonwealth University Health (VCUH) in the post-COVID era. Topics discussed include impact of the pandemic on visitation policies within the ICU setting and changes in how the ICU social worker facilitated communication between the family and healthcare team, importance of palliative care and advance care planning to supporting the patient's family, and team focus on best practices, education ad peer support.

A strong link exists between adequate supply chain management and nurse efficiency and satisfaction. Implementing Lean methodology, specifically 5S process improvement, staff created a unit-based supply room that was clean, safe, and well organized which led to reduced waste, greater efficiency, and cost savings. [ABSTRACT FROM AUTHOR]

This paper is an in-depth study that starts from a preliminary one, where we surveyed 141 ranchers from the town of Coto-Coto in Peru to obtain as much information as possible about the relationship between two economic variables, Activity Cost and Financial Management. Furthermore, we study the correlation of the first one of them with three other economic variables. To do this, we process the survey data using logical operators with the support of the plithogenic statistics theory. These results given in the form of plithogenic values are logically aggregated and were converted to crisp values and studied through the use of statistical tools, specifically Kendall's Tau b. The study of economic variables within the field of cattle farming is of great importance because it allows us to improve the productivity of this economic sector, which is also part of the most accepted human diet worldwide. A substantial advantage in the use of plithogeny is that linguistic values that are more natural for livestock farmers were processed, in addition, uncertainty and indeterminacy were taken into account by the use of neutrosophic numbers. [ABSTRACT FROM AUTHOR]

U.S. service members are at an enhanced risk for developing mental disorders. To address these challenges, while promoting operational readiness and improving mental health outcomes, the Department of Defense directed each service component to develop and implement universal resilience enhancing programs. This paper provides a review of theoretical approaches conceptualizing resilience to trauma, including the theoretical foundations of programs currently in place. The resilience programs of U.S. Army, U.S. Air Force, U.S. Navy and U.S. Marine Corps are described, and available program effectiveness data are reviewed. Gaps between theory and practice are identified and an alternative method of assessing psychological readiness in Army units that is informed by resilience theory is offered as one way to address these gaps and scientific concerns. By comprehensively assessing the stressors affecting Soldiers at regular intervals, military leaders may be able to better identify and mitigate stressors in a systematic way that bolsters individual and unit psychological fitness. An enhanced psychological readiness metric stands to strengthen the validity of current resilience programs, bring clarity to the mechanisms of resilience, and provide a novel way for leaders to promote readiness in their units. Application of this metric within the infrastructure of existing reporting systems stands to improve mental health outcomes for Service Members, enhance the psychological readiness of the force, and reduce healthcare costs over time. [ABSTRACT FROM AUTHOR]

To investigate the impact of kitchen waste compost on the formulation of rice seedling substrate, this study employed indoor seedling tray nursery methods. Six formulations, incorporating kitchen waste compost, peat, and vermiculite as raw materials, were prepared based on volume-specific gravity. The physicochemical characteristics of each seedling substrate were analyzed to assess their influence on rice seedling growth, considering the cost implications of synthesizing different formulations. The findings revealed a significant alteration in both the physicochemical parameters of the seedling substrate and the growth indexes of rice seedlings as the substitution of peat by kitchen waste compost increased. The formulation denoted as WF1 exhibited physicochemical parameters and growth indexes aligning with all applicable standards. Notably, key physicochemical indicators, including pH, electrical conductivity (EC), unit weight, and aeration porosity, increased gradually with the rising proportion of kitchen waste compost. Conversely, growth indicators such as seedling emergence rate, plant height, and stem thickness exhibited a gradual decline. The concentration of malondialdehyde (MDA) and antioxidant enzyme activities in rice seedling roots indicated that an increased presence of kitchen waste compost imposed significant stress on rice seedling growth. From a formulation cost perspective, integrating kitchen waste compost into the rice seedling substrate effectively reduced costs. The WF1 treatment demonstrated a 9.53% reduction in formulation cost compared to the CK treatment. The optimal formulation, consisting of 10% kitchen waste compost, 40% peat, and 50% vermiculite, was identified as better suited for the growth of rice seedlings, achieving a balance between growth performance and cost efficiency. In conclusion, incorporating kitchen waste compost in rice nursery substrate formulation can yield cost-effective solutions while maintaining acceptable growth parameters for rice seedlings. [ABSTRACT FROM AUTHOR]

Purpose Specialty medications often have high costs, pose difficulties with payor approval, and require additional monitoring. Earlier articles have defined various examples of clinical outcome measures (COMs); however, goals and benchmarks have not been well defined, and a gap in the literature exists. This study evaluated the effectiveness of our health-system specialty pharmacy (HSSP) patient management program (PMP) in achieving predefined COM goals. Methods Disease state protocols were developed within the HSSP, and clinical and adherence goals were created for each COM based on primary literature. This retrospective, single-center review examined outcomes and adherence data on patients enrolled in the PMP during 2022. The primary outcome was the number of predefined disease state COM goals met. Secondary outcomes included the number of predefined adherence goals met and annual financial impact. Results Of 1,431 patients whose records were reviewed, 1,053 met criteria for inclusion. The primary outcome analysis showed that 85% (33 of 39) of the predefined disease state goals were met. Predefined adherence goals were met, with an average proportion of days covered (PDC) for all specialty medications of >90%. The PMP yielded $5,167,043 in direct patient cost savings and $167,260 in cost avoidance. Conclusion The PMP yielded positive results in meeting goals set for the COMs in the disease states managed within the HSSP. COMs will remain a focus for HSSPs to help patients achieve desired clinical outcomes and HSSPs adhere to accreditation standards. More research in this field and standardization of COM goals may benefit the larger HSSP community. [ABSTRACT FROM AUTHOR]

Background: Expenditure on residential placements for people with intellectual disability (ID) in Ireland is considerable and expected to increase. Despite this, there is limited evidence on the factors driving variation in privately provided 'out‐of‐area' residential placement costs, including across Community Health Organisations (CHOs)/regions. This is important to help inform the delivery of services at best value. Methods: We analyse unit cost data from 2019 for a sample of 278 high‐cost publicly funded privately provided out‐of‐area residential placements for people with ID in Ireland. We undertake univariate analysis of the relationship between costs and a wide range of variables using t‐tests and one‐way analysis of variance. We employ multivariable regression analysis to examine how raw differentials in unit costs across regions can be accounted for by individual‐level characteristics. Results: We estimate average unit costs of €264 170 per annum in our sample. The univariate analysis shows considerable variation in costs across a range of personal, disability, psychiatry/psychological, forensic issues, behaviour and supports and plans related variables. We also find wide variation in average unit costs across CHOs/regions (F = 4.58, P < 0.001), ranging from €213 380 to €331 880. The multivariable analysis shows that regional differences remain even after accounting for a wide range of individual characteristics that influence costs. Conclusions: Our analysis shows that while the majority of differences in costs across regions can be explained, there is potential for cost savings in the provision of high‐cost publicly funded out‐of‐area residential placements in Ireland. Overall this can help to develop and implement a more sustainable disability residential funding model in a context of rising demand for services. It also has potential implications for the approach to procurement of services. [ABSTRACT FROM AUTHOR]

Web search is a crucial technology for the digital economy. Dominated by a few gatekeepers focused on commercial success, however, web publishers have to optimize their content for these gatekeepers, resulting in a closed ecosystem of search engines as well as the risk of publishers sacrificing quality. To encourage an open search ecosystem and offer users genuine choice among alternative search engines, we propose the development of an Open Web Index (OWI). We outline six core principles for developing and maintaining an open index, based on open data principles, legal compliance, and collaborative technology development. The combination of an open index with what we call declarative search engines will facilitate the development of vertical search engines and innovative web data products (including, e.g., large language models), enabling a fair and open information space. This framework underpins the EU‐funded project OpenWebSearch.EU, marking the first step towards realizing an Open Web Index. [ABSTRACT FROM AUTHOR]

In order to create higher benefits for enterprises in the university supply chain and make them meet the requirements of sustainable development, this study uses information ecology theory to study the cognitive management and transformation path of the green supply chain. Firstly, the related concepts of university supply chain management and green supply chain management are expounded, and the differences are mainly discussed. Then, the evaluation of supply chain greenness is studied. The fuzzy hierarchical comprehensive evaluation method combining quantitative and qualitative is used to establish the evaluation model. Finally, the proposed evaluation model is tested. The test results show that Suzhou University's greenness fuzzy evaluation score is 58.2 points, which is a medium level. The resource factor scored 61 points, the energy factor scored 52.9 points, the environmental factors scored 59.8 points, the economic factor scored 62.7 points, and the social factor scored 55.5 points. The company has obvious advantages in terms of resources and economy, but the level is not very high. The higher the cost synergy between enterprises and customers, the greater the environmental cost synergy. Therefore, manufacturing enterprises should strengthen communication and cooperation with customers. The higher the cost synergy control of manufacturing and waste recycling enterprises, the greater the synergy effect of environmental cost control. Therefore, increasing cooperation with waste recycling enterprises is conducive to developing environmental cost control and coordinated benefits. The proposed scheme provides some ideas for applying information ecology theory in the university supply chain. [ABSTRACT FROM AUTHOR]

Renewable energy sources have emerged as favorable alternatives for meeting ever-increasing global energy demand. To harness the maximum efficiency from renewable sources, dc-dc converters play a crucial role. While the design of dc-dc converters varies depending on specific application, certain features such as multiport capability and high gain are generally desirable. Multiport structures offer advantages such as compactness and cost reduction, allowing for the efficient integration of various energy sources, storage units, and loads. On the other hand, high gain characteristics enable the step-up of output voltages from renewable energy sources to usable levels. In recent years, numerous converter topologies proposed to address these requirements and enhance overall system performance. This study aims to assist and provide guidance to researchers in the field by reviewing and comparing the most recent advancements in the design and implementation of multiport high-gain dc-dc converters for renewable energy applications. Through a comprehensive analysis of the existing literature, the primary objective of this study is to facilitate knowledge transfer, identify research gaps, and inspire future research endeavors in this domain. By synthesizing the knowledge gained from these studies, researchers can contribute to ongoing advancement of multiport converter technology in the context of renewable energy applications. [ABSTRACT FROM AUTHOR]

This paper proposes an emended Harris hawk optimizer (EHHO) to solve the mixed energy generation scheduling problem with available resources from hydrothermal, pumped storage hydro, solar, and wind units while minimizing the operating cost, utilizing the available water, and satisfying the other operational constraints. Direct heuristics are applied to solve the constraints imposed on the generation scheduling problem. An optimistic binary optimizer is utilized to commit solar and wind units so that solar and wind units share a certain percentage of power demand to meet the uncertainty of renewable power. The hunting behavior of the hawks for the desired prey inspires the Harris hawk optimizer (HHO) because of its flexibility, sturdiness, and scalability features. Despite HHO giving premature convergence as it tends to trap into the local optima while solving complex non-linear optimization problems. Hence, the local search technique (LST) is employed with the HHO to overcome it. LST also empowers the exploitation phase of HHO. Two practical electric power test systems are successfully solved using the proposed EHHO. On implementing the proposed EHHO, with the penetration of pumped storage hydro units, savings in the cost of thermal units range from 3.90 to 11.44%. Further, with the penetration of wind and solar power, the savings in operating costs of thermal units have increased from 12.15 to 20.19%. The main idea and contribution of the proposed work is the thermal fuel cost reduction using renewable energy sources by utilizing EHHO. The convergence curves and whisker box plots demonstrate the EHHO's robustness while solving the electric power test systems. [ABSTRACT FROM AUTHOR]

• It describes a process of vacuum carbothermal reduction-directional condensation. • The obtained yields of Sn and Pb are superior to other treatment techniques. • Vacuum technology has once again proved to be a very useful method. Sn ash recycling is an industry with positive development prospects, as it provides better-protected resources, promotes sustainable development, and lays a solid foundation for future development. In this study, an innovative vacuum carbothermal reduction-directional condensation process was developed. The thermodynamic analysis results indicated that the initial reaction pressure and temperature for the carbothermal reduction of the system was 1–10 Pa and 998–1063 K, respectively. The saturation vapor pressure, separation coefficient, and condensation temperature of Sn, Pb, and Zn in the reduced products differed significantly, and their separation could be achieved by controlling the volatilization and condensation temperatures. A single-factor experiment investigated the effects of carbon ratio, temperature, and time on the reduction efficiency, direct yield, and recovery rate. The optimal experimental conditions were the ratio of MeO to C of 4:1, temperature of 1373 K, and time of 120 min. Sn, Pb, and Zn products were obtained at different positions. This process shortens the traditional process, reduces the reduction cost of Sn, and enables the implementation of the process, making it environmentally friendly. [ABSTRACT FROM AUTHOR]

Quantum key distribution, which ensures information-theoretically secret key generation, is currently advancing through photonic integration to achieve high performance, cost reduction, and compact size, thereby facilitating the large-scale deployment. Continuous-variable quantum key distribution is an attractive approach for photonic integrations due to its compatibility with off-the-shelf optical communication devices. However, its chip-based systems have encountered significant limitations primarily related to the shot-noise-limited receiver design, which demands low noise, wide bandwidth, high clearance, and well stability. Here, we report the implementation of a real local oscillator continuous-variable quantum key distribution system with an integrated silicon photonic receiver chip. Thanks to the well-designed chip-based homodyne detectors with a bandwidth up to 1.5 GHz and a clearance up to 7.42 dB, the transmission distance of the system has been extended to 28.6 km, achieving a secret key generation rate of Mbps level. This technological advancement enables the quantum key distribution systems with photonic integrated receivers to achieve the coverage in both access network scenarios and short-distance metropolitan interconnections, paving the way for the development of the next-generation quantum key distribution networks on a large scale. [ABSTRACT FROM AUTHOR]

Background: Migraine is a highly prevalent neurological disease with a substantial societal burden due to lost productivity. From a societal perspective, we assessed the cost-effectiveness of eptinezumab for the preventive treatment of migraine. Methods: An individual patient simulation of discrete competing events was developed to evaluate eptinezumab cost-effectiveness compared to best supportive care for adults in the United Kingdom with ≥ 4 migraine days per month and prior failure of ≥ 3 preventive migraine treatments. Individuals with sampled baseline characteristics were created to represent this population, which comprised dedicated episodic and chronic migraine subpopulations. Clinical efficacy, utility, and work productivity inputs were based on results from the DELIVER randomised controlled trial (NCT04418765). Timing of natural history events and treatment holidays—informed by the literature—were simulated to unmask any natural improvement of the disease unrelated to treatment. The primary outcomes were monthly migraine days, migraine-associated costs, quality-adjusted life years (QALYs), incremental cost-effectiveness ratio, and net monetary benefit, each evaluated over a 5-year time horizon from 2020. Secondary analyses explored a lifetime horizon and an alternative treatment stopping rule. Results: Treatment with eptinezumab resulted in an average of 0.231 QALYs gained at a saving of £4,894 over 5 years, making eptinezumab dominant over best supportive care (i.e., better health outcomes and less costly). This result was confirmed by the probabilistic analysis and all alternative assumption scenarios under the same societal perspective. Univariate testing of inputs showed net monetary benefit was most sensitive to the number of days of productivity loss, and monthly salary. Conclusions: This economic evaluation shows that from a societal perspective, eptinezumab is a cost-effective treatment in patients with ≥ 4 migraine days per month and for whom ≥ 3 other preventive migraine treatments have failed. Trial registration: N/A. [ABSTRACT FROM AUTHOR]

Short-term load forecasting (STLF) plays a vital role in ensuring the safe, efficient, and economical operation of power systems. Accurate load forecasting provides numerous benefits for power suppliers, such as cost reduction, increased reliability, and informed decision-making. However, STLF is a complex task due to various factors, including non-linear trends, multiple seasonality, variable variance, and significant random interruptions in electricity demand time series. To address these challenges, advanced techniques and models are required. This study focuses on the development of an efficient short-term power load forecasting model using the random forest (RF) algorithm. RF combines regression trees through bagging and random subspace techniques to improve prediction accuracy and reduce model variability. The algorithm constructs a forest of trees using bootstrap samples and selects random feature subsets at each node to enhance diversity. Hyperparameters such as the number of trees, minimum sample leaf size, and maximum features for each split are tuned to optimize forecasting results. The proposed model was tested using historical hourly load data from four transformer substations supplying different campus areas of the University of Beira Interior, Portugal. The training data were from January 2018 to December 2021, while the data from 2022 were used for testing. The results demonstrate the effectiveness of the RF model in forecasting short-term hourly and one day ahead load and its potential to enhance decision-making processes in smart grid operations. [ABSTRACT FROM AUTHOR]