Search

Needle selection plays a pivotal role in determining the success of fine needle aspiration (FNA) procedures. Two commonly utilized puncture needles for thyroid FNA are the conventional syringe needle and the stylet needle. Syringe needles are known for their cost-effectiveness in comparison to stylet needles. This study aimed to determine if FNA with syringe needles is non-inferior to FNA with stylet needles in terms of specimen adequacy while also comparing the direct costs associated with both needle types. A total of 220 thyroid nodules from 185 patients were prospectively included in this study. The same operator performed a total of four punctures on the same nodule twice using a syringe and a stylet needle. The results of this study show that the utilization of syringe needles for thyroid FNA was non-inferior to the use of stylet needles in terms of specimen adequacy. Cost analysis revealed that syringe needle FNA was not only less expensive (CNY 500.9 versus CNY 780) but also more effective (adequacy 85.91% versus 84.55%). In summary, given the global prevalence of FNA procedures, the economic considerations are paramount, and our findings support the routine use of syringe needles in thyroid FNA. [ABSTRACT FROM AUTHOR]

Violence across Latin America is an increasingly important factor influencing migration to the US. A particular form of violence that is experienced by many Latinx migrants is extortion. This research analyzes the extortion experiences of Latinx immigrant adults arriving at the US southern border and the impact these experiences have on mental health. We find that on average, participants paid $804 in extortion during their migration. The most common perpetrators of extortion in our study were police followed by immigration officials throughout Latin America. Pregnant participants were less likely to experience extortion and adults traveling with children were more likely to be extorted. Participants who were extorted for money reported significantly greater severity of post-traumatic stress disorder (PTSD) symptoms compared to those who were not extorted. This research is the first of its kind to analyze extortion experiences among Latinx immigrants to the US, quantifying the prevalence, amounts paid, countries where extortion occurs, and perpetrators of extortion. In addition, extortion experiences are associated with negative effects on the mental health of newly arrived Latinx immigrants to the US. Based upon these findings, we recommend that extortion should be considered a significant stressor in the migrant experience, particularly for those adults traveling with children. [ABSTRACT FROM AUTHOR]

India being more focused on its agricultural development requires information on energy input requirements for agro-based industries, where most of the energy is consumed by post-harvest operations. This study evaluates energy consumption by both the conventional method and the non-conventional method of agro-processing of maize on a small scale with the objectives of effective management of the limited resources in the agriculture, finding energy and cost-saving solutions for the two most energy- and cost-intensive post-harvest processes, providing energy-saving recommendations with suggestions for minimizing the involved cost of operation by focusing on the use of eco-friendly renewables in the agro-processing sector. Energy auditing with the help of energy tools and experimentally collected data was used for the energy analysis of the processes, and break-even analysis was used to find out the new selling price of the product using alternate energy sources for processing. The net energy and cost savings obtained through solar drying and solar milling were 545.38 GJ/yr, 50,017.50 GJ/yr, and USD 7,146.68, and USD 3,880, respectively. The findings reveal that drying and milling when accomplished by using solar energy offer perfect solution to much of the problem for small farm holders as well as for the environment by reducing 39.8 kg of CO2 emission. This research work will help to understand the use of energy analysis and the ways of its implementation in agro-based industries for the development of sustainable agriculture strategy. Policy directions provided help to improve policy regarding the integration of renewable energy in post-harvest processing operations. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the current literature on healthcare policies and cost analyses around international Voluntary Assisted Dying (VAD) laws. The study design is a mapping literature review following Preferred-Reporting-Items-for-Systematic-Reviews-and-Meta-Analyses (PRISMA) guidelines. Methods: Original research articles published between January 1990 to March 2023, investigating the financial cost and healthcare budget effect of VAD laws internationally. Citations were screened for relevance and eligibility, and any non-full-text research that did not explore cost analysis was excluded. The following data sources were screened: MEDLINE, PubMed, EMBASE, CINAHL and any relevant international health authority annual reports were also reviewed. Results: Of the 2790 screened articles, eight studies met the inclusion criteria and three were included in the mapping review. The reviewed studies included prospective studies, two Canadian and one US. Only one of the Canadian studies provided a cost analysis using data from current VAD laws. All three studies showed VAD laws would reduce healthcare spending, with the US approximating $627million in 1995. Canada approximating $17.1 to $77.1million in 2017 and $86.9 to $149.0million in 2021, overall, leading to an average percentage reduction in costs of approximately 87% compared to original costs of end-of-life care. Conclusion: This review identifies a scarcity in cost-analysis literature and provides a summary of the latest international VAD laws, from which a potential cost reduction is apparent. The absence of retrospectively collated financial VAD data highlights a need for future research to inform policymakers of the economic factors affecting current policies with a need for annual fiscal reports and to optimise future legislative frameworks internationally. Key points: - This study highlights the absence of cost analysis reports on the provision of VAD globally, at a time when VAD is becoming an evolving part of end-of-life care particularly in developed countries base on the notion of patient autonomy. - The impact of this study is its ability to inform future research and policymakers of the economic factors affecting current VAD policies with a need for annual fiscal reports and to optimise future legislative frameworks internationally. [ABSTRACT FROM AUTHOR]

Background: Hospital services are typically reimbursed using case-mix tools that group patients according to diagnoses and procedures. We recently developed a case-mix tool (i.e., the Queralt system) aimed at supporting clinicians in patient management. In this study, we compared the performance of a broadly used tool (i.e., the APR-DRG) with the Queralt system. Methods: Retrospective analysis of all admissions occurred in any of the eight hospitals of the Catalan Institute of Health (i.e., approximately, 30% of all hospitalizations in Catalonia) during 2019. Costs were retrieved from a full cost accounting. Electronic health records were used to calculate the APR-DRG group and the Queralt index, and its different sub-indices for diagnoses (main diagnosis, comorbidities on admission, andcomplications occurred during hospital stay) and procedures (main and secondary procedures). The primary objective was the predictive capacity of the tools; we also investigated efficiency and within-group homogeneity. Results: The analysis included 166,837 hospitalization episodes, with a mean cost of € 4,935 (median 2,616; interquartile range 1,011–5,543). The components of the Queralt system had higher efficiency (i.e., the percentage of costs and hospitalizations covered by increasing percentages of groups from each case-mix tool) and lower heterogeneity. The logistic model for predicting costs at pre-stablished thresholds (i.e., 80th, 90th, and 95th percentiles) showed better performance for the Queralt system, particularly when combining diagnoses and procedures (DP): the area under the receiver operating characteristics curve for the 80th, 90th, 95th cost percentiles were 0.904, 0.882, and 0.863 for the APR-DRG, and 0.958, 0.945, and 0.928 for the Queralt DP; the corresponding values of area under the precision-recall curve were 0.522, 0.604, and 0.699 for the APR-DRG, and 0.748, 0.7966, and 0.834 for the Queralt DP. Likewise, the linear model for predicting the actual cost fitted better in the case of the Queralt system. Conclusions: The Queralt system, originally developed to predict hospital outcomes, has good performance and efficiency for predicting hospitalization costs. [ABSTRACT FROM AUTHOR]

Growing concerns about seismic events enforced structural engineers and architects to embrace the hazardous effect of ground motion in design. To address this, researchers have developed various base isolation (BI) techniques. This study comprehensively reviews BI system types, techniques, and implementation. Exploring the dynamic response of three-dimensional BI devices and the mutual effects of isolation devices and soil-structure interaction during strong ground motion, the paper covers topics such as seismic isolation of nuclear power plants, cost analysis, and various optimization techniques. Furthermore, the paper investigates the behavior of isolation devices in beyond-design events, including blast and aircraft impact loading. In general, the seismic isolation and control device response is demonstrated through shaking table tests and computational analysis. The study sheds light on the functions of seismic isolation system by comparing them with fixed base structures. Additionally, the paper presents codal recommendations, recent advancements, and current practices, aligning them with historical developments and past reviews of different BI techniques, along with their advantages and disadvantages. In conclusion, the closing remarks emphasize the future research prospects in this field. [ABSTRACT FROM AUTHOR]

State-owned enterprises (SOEs) are present in key sectors of economies around the world. While they can provide an important public service, there is widespread concern that their activities and financial performance are hindered by corruption. In the meantime, cross-country analysis on the cost of corruption for SOEs remains scarce. We present new cross-country evidence on how corruption affects SOE performance using firm level data. We find that SOEs perform as well as private firms in core sectors when corruption is low but are significantly less efficient when corruption is high. We also show that, in turn, improvements in fiscal transparency and specific SOE governance reforms have the potential to improve SOE performance. [ABSTRACT FROM AUTHOR]

With the tremendous increase in the number of vehicles, the dense traffic created can lead to accidents and fatalities. In a traffic system, the costs for accidents are immeasurable. Numerous studies have been carried out to predict the cost of fatal accidents but have provided the actual values. Therefore, in this study, a monkey-based modular neural system (MbMNS) is developed to identify accident cost. The accident cases and cost data were collected and preprocessed to remove the noise, and the required features were extracted using the spider monkey function. Based on the extracted features, the accidents and the costs were identified. For rail engineering, this will support evaluating the number of railroad crossing accidents with different time intervals. The impact of every accident was also measured with different cost analysis constraints, including insurance, medical, and legal and administrative costs. Therefore, the present study contributes to the field by collecting and organizing the present railroad level crossing accident data from crossing inventory dashboards. Then, the introduction of a novel MbMNS for the cost analysis is the primary contribution of this study to further enrich the railroad level crossing protection system. The third contribution is the tuning of the prediction layer of a modular neural network to the desired level to achieve the highest predictive exactness score. Hence, the designed MbMNS was tested in the Python environment, and the results were validated with regard to recall, accuracy, F-measure, precision, and error values; a comparative analysis was also conducted to confirm the improvement. The novel MbMNS recorded high accuracy of 96.29% for accident and cost analysis, which is better than that reported for other traditional methods. [ABSTRACT FROM AUTHOR]

India's cement industry is the second largest in the world, generating 6.9% of the global cement output. Polycarbonate waste ash is a major problem in India and around the globe. Approximately 370,000 tons of scientific waste are generated annually from fitness care facilities in India. Polycarbonate waste helps reduce the environmental burden associated with disposal and decreases the need for new raw materials. The primary variable in this study is the quantity of polycarbonate waste ash (5, 10, 15, 20 and 25% of the weight of cement), partial replacement of cement, water-cement ratio and aggregates. The mechanical properties, such as compressive strength, split tensile strength and flexural test results, of the mixtures with the polycarbonate waste ash were superior at 7, 14 and 28 days compared to those of the control mix. The water absorption rate is less than that of standard concrete. Compared with those of conventional concrete, polycarbonate waste concrete mixtures undergo minimal weight loss under acid curing conditions. Polycarbonate waste is utilized in the construction industry to reduce pollution and improve the economy. This study further simulated the strength characteristics of concrete made with waste polycarbonate ash using least absolute shrinkage and selection operator regression and decision trees. Cement, polycarbonate waste, slump, water absorption, and the ratio of water to cement were the main components that were considered input variables. The suggested decision tree model was successful with unparalleled predictive accuracy across important metrics. Its outstanding predictive ability for split tensile strength (R2 = 0.879403), flexural strength (R2 = 0.91197), and compressive strength (R2 = 0.853683) confirmed that this method was the preferred choice for these strength predictions. [ABSTRACT FROM AUTHOR]

Seawater intrusion is a worldwide increasing challenge, which lowers the freshwater availability by salination of fresh groundwater resources in coastal areas. The abstraction-desalination-recharge (ADR) methodology can combat seawater intrusion, whereby desalination is hereby the key factor for the overall efficiency of aquifer remediation. Which desalination technique is suitable within ADR depends on several factors and was not discussed before. We use a multi-criteria decision analysis and cost analysis to compare nanofiltration, reverse osmosis, electrodialysis, and (membrane) capacitive deionization and show for three case scenarios which desalination technique is most suitable within ADR. Overall, electrodialysis, nanofiltration, and reverse osmosis have shown the best utility value for saline groundwater salinity of 1–10 g L−1, whereby electrodialysis is more suitable for lower salinities. The lowest desalination costs are calculated for nanofiltration and reverse osmosis with 0.3–0.6 € m−3 depending on specific energy costs. Even capacitive deionisation can be a suitable alternative for low, slightly saline groundwater (1 g L−1) if the technology readiness level and a lifetime of electrodes increase and material costs decrease. These new insights provide a data analysis, costs, and decision support for desalination which are needed for the holistic approach to counteract seawater intrusion. [ABSTRACT FROM AUTHOR]

Removing sour gas from any suitable gas sweetening technology in a cost-effective and environmentally responsible manner is a major challenge. This paper discusses how to safely and economically dispose of small amounts of acid gases resulting from the amine sweetening process. A two-stage Claus desulfurization unit was studied and simulated to treat acid gases resulting from natural gas sweetening operations in Ras Gharib oil fields (Egypt). These acid gases are used as feedstock for the proposed plant to produce a valuable product, such as elemental sulfur, which is used as a raw material in many industries. Although many sulfur recovery techniques are available for various conditions and applications, the Claus process is a critical and widely used method for recovering elemental sulfur from gaseous hydrogen sulfide. This work represents the potential benefits of treating acid gases with high hydrogen sulfide content. In addition, operational variables that could affect sulfur production and sulfur recovery efficiency of the studied Claus unit were studied and optimized. Aspen HYSYS simulation software (version 9) was used to evaluate the economic aspects and optimize the operational parameters of the unit for producing sulfur from acid background gases. The results showed that the maximum sulfur production was achieved at a catalytic converter reactor temperature of 270 °C and 210 °C for the first and second catalytic reactor, respectively, with an air flow rate of 933.3 kg mol/h. The economic study of the proposed desulfurization unit showed that the Claus unit would be economically acceptable with an expected return on investment of approximately 10% and an average payback period of 10 years. Moreover, the introduced plant has a positive impact on the environment by reducing the concentration of hydrogen sulfide in the gas from 69.58 to 0.16%. [ABSTRACT FROM AUTHOR]

Over-grazing in rangelands leads to a drastic decline in non-forage functions. The rangelands are exploited with no concern for the incurred externality costs. The cost–benefit livestock grazing enterprise and the net profit obtained per animal unit are calculated initially. Following this, the 5 regulation services of rangeland are measured and assessed. The economic analysis of livestock grazing enterprise in rangeland is run for 3 reimbursement conditions for grazing: (1) Concerning the condition of the study area, almost no payment is made for grazing; thus, forage cost is of no concern, (2) the value of grazed forage obtained and added to the forage costs, and (3) the value of regulation services is obtained and considered in the cost–benefit analysis in livestock grazing business. The value of forage and regulation services of 18 vegetation types, separated by the floristic physiognomy method, is obtained. The change in the value of regulation services in the rangelands subject to overstocking and proper stocking conditions is analyzed. The three conditions mentioned above benefit to cost ratios per animal unit are 2.01, 1.2, and 0.46, respectively, indicating that the third case lacks economic justification. Regarding the vegetation types with over-stocking, there are 6.5 units of negative externality effects per animal unit, which will be incurred on the society. The findings indicate the importance of externalities in economic justification of rangeland enterprises, which further could be used to correct the utilization process in the rangelands with poor economic justification. [ABSTRACT FROM AUTHOR]

The guaranteed cost finite-time stability of positive switched fractional-order systems (PSFS) with D-disturbance and impulse is studied based on the Φ -dependent average dwell time (Φ DADT) strategy. Firstly, the finite-time stability of the studied system is proved by constructing a linear co-positive Lyapunov function. Secondly, the system's guaranteed cost analysis is given with the estimated upper bound of the cost. In addition, the finite-time certain and robust controllers are designed to ensure the system's stabilization. A numerical example is finally given to signify the validity of the conclusions. [ABSTRACT FROM AUTHOR]

Introduction: Invasive meningococcal disease (IMD) caused by Neisseria meningitidis is a rapidly progressing, rare disease that often presents as meningitis or sepsis. It mostly affects infants and adolescents, with high fatality rates or long-term sequelae. In the Netherlands, serogroup B (MenB) is most prevalent. We aimed to estimate the economic burden of MenB-related IMD between 2015 and 2019, including direct and indirect medical costs from short- and long-term sequelae, from a societal perspective. Methods: IMD incidence was based on laboratory-based case numbers from the Netherlands Reference Laboratory for Bacterial Meningitis (Amsterdam UMC, Amsterdam, the Netherlands); there were 74 MenB cases on average per year in the study period 2015–2019. Case-fatality rate (3.8%) and percentage of patients discharged with sequelae (46%) were derived from literature. Direct costs included treatment costs of the acute phase, long-term sequelae, and public health response. Indirect costs were calculated using the human capital (HCA) and friction costs (FCA) approaches, in which productivity losses were estimated for patients and parents during the acute and sequelae phases. Costs were discounted by 4% yearly. Results: Estimated costs due to MenB IMD in an annual cohort were €3,094,199 with FCA and €9,480,764 with HCA. Direct costs amounted to €2,974,996, of which 75.2% were related to sequelae. Indirect costs related to sequelae were €52,532 with FCA and €5,220,398 with HCA. Conclusion: Our analysis reflects the high economic burden of MenB-related IMD in the Netherlands. Sequelae costs represent a high proportion of the total costs. Societal costs were dependent on the applied approach (FCA or HCA). Graphical Plain Language Summary: [ABSTRACT FROM AUTHOR]

Bioplastics has gained attention as a sustainable alternative to traditional petroleum-based plastics. Microalgae have become one of the more promising and environmentally benign feedstocks to produce bioplastics. The goal of this in-depth review study is to address both the possibilities and the difficulties of manufacturing microalgae-based bioplastics. The review begins by discussing the negative impacts that commercial plastics have on the environment, pollution, and resource depletion. It then introduces the idea of bioplastics and discusses their importance in reducing the previously mentioned issues brought on by plastics. The article discusses the distinctive qualities of microalgae as a sustainable biomass source, noting their rapid development, high lipid content, and low need for both land and water. The various production processes and procedures used to create microalgae-based bioplastics are thoroughly explored. To determine whether the mechanical, thermal, and barrier qualities were appropriate for different applications, they were examined. Biodegradability and shelf life are factors in environmental impact assessments that highlight their potential to help mitigate the negative effects of plastics. Economic viability is a crucial factor that is examined through cost analyses and discussions of the prospects and incentives for market growth. To provide a glimpse into the future of microalgae-based bioplastics as a sustainable material option, current trends and innovations are emphasized. This review advances our knowledge of microalgae-based bioplastics in the race for a more sustainable plastics industry by offering a fair evaluation of their advantages, disadvantages, and uses. [ABSTRACT FROM AUTHOR]

Background: Traumatic injuries are rising globally, disproportionately affecting low- and middle-income countries, constituting 88% of the burden of surgically treatable conditions. While contributing to the highest burden, LMICs also have the least availability of resources to address this growing burden effectively. Studies on the cost-of-service provision in these settings have concentrated on the most common traumatic injuries, leaving an evidence gap on other traumatic injuries. This study aimed to address the gap in understanding the cost of orthopaedic services in low-income settings by conducting a comprehensive costing analysis in two tertiary-level hospitals in Malawi. Methods: We used a mixed costing methodology, utilising both Top-Down and Time-Driven Activity-Based Costing approaches. Data on resource utilisation, personnel costs, medicines, supplies, capital costs, laboratory costs, radiology service costs, and overhead costs were collected for one year, from July 2021 to June 2022. We conducted a retrospective review of all the available patient files for the period under review. Assumptions on the intensity of service use were based on utilisation patterns observed in patient records. All costs were expressed in 2021 United States Dollars. Results: We conducted a review of 2,372 patient files, 72% of which were male. The median length of stay for all patients was 9.5 days (8–11). The mean weighted cost of treatment across the entire pathway varied, ranging from $195 ($136—$235) for Supracondylar Fractures to $711 ($389—$931) for Proximal Ulna Fractures. The main cost components were personnel (30%) and medicines and supplies (23%). Within diagnosis-specific costs, the length of stay was the most significant cost driver, contributing to the substantial disparity in treatment costs between the two hospitals. Conclusion: This study underscores the critical role of orthopaedic care in LMICs and the need for context-specific cost data. It highlights the variation in cost drivers and resource utilisation patterns between hospitals, emphasising the importance of tailored healthcare planning and resource allocation approaches. Understanding the costs of surgical interventions in LMICs can inform policy decisions and improve access to essential orthopaedic services, potentially reducing the disease burden associated with trauma-related injuries. We recommend that future studies focus on evaluating the cost-effectiveness of orthopaedic interventions, particularly those that have not been analysed within the existing literature. [ABSTRACT FROM AUTHOR]

In modern chip designs, shared resources are used extensively. Arbiters usage is crucial to settle conflicts when multiple requests compete for these shared resources. Making sure these arbiter circuits work correctly is vital not just for their proper functionality, but also for security reasons. The work in this paper introduces a method based on formal verification to thoroughly assess the proper functional aspects of various arbiter setups. This is achieved through SystemVerilog assertions and model checking. Additionally, we explore a non-invasive method for the modeling and insertion of different types of hardware Trojans. These Trojans, with their unique triggers and payloads, are modeled formally without the need for any alterations to the actual circuit. The results provide a detailed analysis of the cost involved in running the formal verification environment on versions of arbiters that are free from Trojans. This analysis is carried out using Questa PropCheck formal analysis tool, which offers valuable insights into the time and memory resources required. Furthermore, the results highlights how the formally modeled and inserted Trojans interfere with hold criteria of the arbiters' properties, where at least a single property fires due to the inserted Trojan. This work can be extended to be a generic approach with the potential to validate both the proper operation and security aspects of complex systems. [ABSTRACT FROM AUTHOR]

Dispersive solid-phase extraction (DSPE) and magnetic solid-phase extraction (MSPE) are methods of solid-phase sorption preconcentration. Compared to classical solid-phase extraction, these methods have a number of advantages, such as reduced consumption of sorbents and solvents, extraction time, and cost of analysis. The popularity of the method among the analysts is evidenced by the large number of reviews we have summarized in this publication. Information is systematized on different versions of these methods, differing in the way the preconcentration process is carried out, the nature of the sorbents used, and their combination with methods for the subsequent determination of the preconcentrated substances; examples of using DSPE and MSPE for the separation of organic compounds in the analysis of environmental samples, food products and biological fluids are given. [ABSTRACT FROM AUTHOR]

Background: Continuous renal replacement therapy (CRRT) support is crucial for critically ill patients and it is underexplored in specific situations. Experimental CRRT offers a means to gain insights into these scenarios, but the prohibitive cost of CRRT machines limits their accessibility. This study aimed to develop and validate a low-cost and precise dialysate controller for experimental CRRT. Results: Our results demonstrate a commendable level of precision in affluent flow control, with a robust correlation (R2 = 0.99) for continuous flow and a strong correlation (R2 = 0.95) for intermittent flow. Additionally, we observed acceptable agreement with a bias = 3.4 mL (upper limit 95% = 43.9 mL and lower limit 95% = − 37 mL) for continuous flow and bias = − 20.9 mL (upper limit 95% = 54 mL and lower limit 95% = − 95.7 mL) for intermittent flow, in this way, offering a precise CRRT dose for the subjects. Furthermore, we achieved excellent precision in the cumulative ultrafiltration net (UFnet), with a bias = − 2.8 mL (upper limit 95% = 6.5 mL and lower limit 95% = − 12 mL). These results remained consistent even at low affluent flow rates of 8, 12, and 20 mL/min, which are compatible with CRRT doses of 25–30 mL/kg for medium-sized animals. Moreover, the acceptable precision of our findings persisted when the dialysate controller was subjected to high filter dialysate chamber pressure for an extended duration, up to 797 min. Conclusions: The low-cost dialysate controller developed and tested in this study offers a precise means of regulating CRRT in experimental settings. Its affordability and accuracy render it a valuable instrument for studying CRRT support in unconventional clinical scenarios, particularly in middle-income countries' experimental ICU laboratories. [ABSTRACT FROM AUTHOR]

In this study, a continuous review (s,Q) inventory system with a service facility is examined. There is only one server and a limited number of customers waiting rooms in this facility. The demands arrive to the queueing-inventory system according to the Poisson process. Every customer needs a single product with a service period that is unpredictable and distributed arbitrarily. An external supplier replenishes the inventory, and the lead time for the reorder is predicated on an independent exponential distribution. Demands that arise during a stock out period must wait in the waiting area, and when the ordered items arrive, they are served using the first-come-first-serve queueing discipline. With the help of the imbedded Markov chain technique, we are able to compute the joint probability distribution of the number of customers in the system and the number of items in inventory at post-departure epoch. With the remaining service time of a customer in service as the supplementary variable, we are able to relate the system length distributions at post-departure and random epochs in order to determine the joint probability distribution at random epoch. The analysis of waiting time of an accepted customer in the queue is also examined. Several stationary system performance measures are computed and the total expected cost is determined under an appropriate cost structure to determine the optimal values for waiting space (N), reorder level (s), and order quantity (Q). In order to explain the important performance indicators of the system, some numerical findings are given for a variety of model parameters. [ABSTRACT FROM AUTHOR]

It is uncertain whether hydrocolloid dressings, a more costly intervention than offering standard care with petrolatum, is superior to prevent pressure ulcers among hospitalized high-risk adults. Randomized, parallel-group, open-label, superiority trial with an active control group, blinded for investigators, event validators, and analysts (December 1, 2015 to December 12, 2017). Eligible patients were ≥ 18 years of age with intact skin judged as high-risk for skin ulcers (Braden scale), admitted to surgical or medical wards of two tertiary-level hospitals. Participants were randomized (1:1) to protection with hydrocolloid dressings or petrolatum. The primary outcome was the first occurrence of pressure ulcers (with post-injury photographs adjudicated by three judges) under intention-to-treat analysis. Based on prior cost analysis, and the available resources (assumed incidence of 6 ulcers/1000 patient-days in controls), inclusion of up to 1500 participants allowed to surpass a one-sided superiority threshold > 5% based on a target efficacy > 40% for dressings. We planned an economic analysis using a decision tree model based on the effectiveness of the study results from a perspective of the third payer of health care. After inclusion of 689 patients (69 events), the trial was stopped for futility after a planned interim analysis (conditional power < 0.1 for all scenarios if the trial was completed). Pressure ulcers had occurred in 34 (10.2%) patients in the intervention group [9.6 per 1000 patient-days] and 35 (9.9%) participants in the control group [7.9 per 1000 patient-days], HR = 1.07 [95% CI 0.67 to 1.71]. The estimated incremental cost for dressings (a dominated strategy) was USD 52.11 per patient. Using hydrocolloid dressings was found similar to petrolatum for preventing pressure ulcers among hospitalized high-risk patients. As it conveys additional costs, and in this study was unlikely to demonstrate enough superiority, this strategy did not overcome conventional skin care. Trial registration: ClinicalTrials.gov identifier (NCT number): NCT02565745 registered on December 1, 2015. [ABSTRACT FROM AUTHOR]

Background: The escalating prevalence of type 2 diabetes (T2DM) poses an unparalleled economic catastrophe to developing countries. Cardiovascular diseases remain the primary source of costs among individuals with T2DM, incurring expenses for medications, hospitalizations, and surgical interventions. Compelling evidence suggests that the risk of cardiovascular outcomes can be reduced by three classes of glucose-lowering therapies (GLT), including SGLT2i, GLP-1A, and pioglitazone. However, an evidence-based and cost-effective protocol is still unavailable for many countries. The objective of the current study is to compare the effectiveness and cost-effectiveness of GLT in individuals with T2DM in Brazil. Methods: We employed Bayesian Networks to calculate the incremental cost-effectiveness ratios (ICER), expressed in international dollars (Int$) per disease-adjusted life years [DALYs] averted. To determine the effectiveness of GLT, we conducted a systematic review with network meta-analysis (NMA) to provide insights for our model. Additionally, we obtained cardiovascular outcome incidence data from two real-world cohorts comprising 851 and 1337 patients in primary and secondary prevention, respectively. Our cost analysis took into account the perspective of the Brazilian public health system, and all values were converted to Int$. Results: In the NMA, SGLT2i [HR: 0.81 (95% CI 0.69–0.96)], GLP-1A [HR: 0.79 (95% CI 0.67–0.94)], and pioglitazone [HR: 0.73 (95% CI 0.59–0.91)] demonstrated reduced relative risks of non-fatal cardiovascular events. In the context of primary prevention, pioglitazone yielded 0.2339 DALYs averted, with an ICER of Int$7,082 (95% CI 4,521–10,770) per DALY averted when compared to standard care. SGLT2i and GLP-1A also increased effectiveness, resulting in 0.261 and 0.259 DALYs averted, respectively, but with higher ICERs of Int$12,061 (95% CI: 7,227–18,121) and Int$29,119 (95% CI: 23,811–35,367) per DALY averted. In the secondary prevention scenario, all three classes of treatments were deemed cost-effective at a maximum willingness-to-pay threshold of Int$26,700. Notably, pioglitazone consistently exhibited the highest probability of being cost-effective in both scenarios. Conclusions: In Brazil, pioglitazone presented a higher probability of being cost-effective both in primary and secondary prevention, followed by SGLT2i and GLP-1A. Our findings support the use of cost-effectiveness models to build optimized and hierarchical therapeutic strategy in the management of T2DM. Trial registration: CRD42020194415. [ABSTRACT FROM AUTHOR]

Background: The United Arab Emirates (UAE) has one of the fastest growing adult populations with diabetes mellitus (DM). In 2018, approximately 1.4 million people in the UAE had DM, posing a significant societal cost burden. Owing to a lack in published research on the disease, the true extent of its effects may be unknown. Our study seeks to contribute to the DM literature by estimating its 2018 direct costs in the UAE. Methods: We used random sampling to estimate direct costs. A survey of 400 adults with types 1 and 2 DM captured patients' demographic data and history of medical services received. Direct complication costs were analyzed through a second survey involving 38 of the original 400 participants who experienced DM complications. We accompanied this qualitatively with structured interviews alongside medical consultants from Al Qassimi Hospital, Sharjah. Results: Direct types 1 and 2 DM costs amounted to approximately USD 4.16 billion, representing 23.25% of the UAE's total health expenditure and 1% of its gross domestic product in 2018. Total annual average direct costs per person amounted to USD 2968.98, 35.75% of which were related to hospitalization and complications, 23.26% to consultation, 16.11% to oral drugs, 9.94% to insulin drugs, 5.94% to DM devices, and 9.00% to other factors. Additionally, the average direct cost for type 1 DM (USD 7136.70) was almost 2.85 times higher than that of type 2 DM (USD 2505.90). Conclusion: Our findings can help address the economic implications of DM prevention and treatment in the UAE. [ABSTRACT FROM AUTHOR]

According to recent studies, head and neck cancers (HNC) make up a substantial proportion of all cancers in India and are proportionately high in the lower socioeconomic people practising tobacco and alcohol. Chemotherapy is a crucial component of treating HNC, and this study was carried out to determine the Cost Minimization Analysis (CMA) by comparing the price of the high and least expensive branded drugs marketed in India. This study was performed to understand the cost difference (CD), Cost ratio (CR) and percentage of cost variation (PCV) of both individual drugs and the standard anticancer regimens. The Current Index of Medical Stores was used to determine the costs of the most and least expensive branded medications and analysed. The results indicated that Paclitaxel-Cisplatin-5 Fluoruracil chemotherapy regimen exhibited the greatest variance in cost, with the Jan Aushadhi brand of medicine costing 8.1 times and 4.3 times less than the most expensive and cheapest branded drugs, respectively. The cost of the concurrent cisplatin regimen with Jan Aushadi Medicine was Rs 1764, Rs 3489.64 with the lowest branded drug, and Rs 8477 with the most expensive branded drug. Also when compared to Jan Aushadhi medication, the cost of Ciplatin was 4.8 times higher with the most expensive branded drug and 2 times higher with the least expensive branded drug. As far as the authors are aware of this is the first study that addresses the pharmacoeconomic appraisal of treating HNC with various chemotherapy and chemoirradiation regimens. This study will help oncologists, pharmacists, and healthcare workers comprehend the financial advantages of treating breast cancer with less expensive chemotherapeutic agents instead of brand-name medications. [ABSTRACT FROM AUTHOR]

The geometry-architecture relationship, which plays a limiting role in the building construction process, is an important concept in determining the identity of the buildings. Tessellations, which differentiate the structures from each other in the architectural design process, are among the methods that can be considered within the geometry-architecture relationship. In the world of modern architecture, it is possible to come across tessellation configurations in the formation of buildings, their facades, and load-bearing system designs. In this study, the reflections of tessellation patterns on steel load-bearing system designs were examined. In the first stage, the load-bearing patterns were analyzed by performing a situation analysis through the real structures with different tessellation configurations. Eight tessellation patterns were created with the most used geometries, and their geometric characteristics, structural performances, and costs were investigated. The models designed with the Grasshopper software were evaluated with the Sap2000 analysis program. To create a comparable structural framework and to link the tessellation patterns with the steel load-bearing systems, planar and single-curvature vault grid systems, in which symmetric/periodic types of tessellation can be applied, were used. Depending on the variation in tessellation modulations, optimum solutions were sought in load-bearing structure systems arranged according to grid density and grid factor values. As a result of structural analyses, systems that offer optimum solutions were shown with comparative analyses. Then the performances of geometric designs were discussed. Considering the cost-based scoring of the systems because of optimization, triangle-rectangle (3.3.3.4.4) in planar structures, rectangle (4.4.4.4) and triangle–hexagon (3.3.3.3.6) tessellation systems in single vault structures come to the fore. [ABSTRACT FROM AUTHOR]

The rapid growth of Internet users was the motivation of the emerge appearance of new computing models such as cloud computing, fog computing and edge computing. For this reason, the multi-server's architecture has been introduced to extend scalability and accessibility. To ensure that these servers can only be accessed by the authorized users, many authentication and key agreement schemes have been introduced for multi–server environments. In this paper, we propose an anonymous mutual authentication and key agreement scheme for multi-server architecture based on elliptic curve cryptography to achieve the required security services and resist the well-known security attacks. Furthermore, formal and informal security analysis is conducted to prove the security of the proposed scheme. Moreover, we provide a performance comparison with related work in terms of computational cost, communication cost and the number of messages transferred on the public channel. This performance comparison clearly shows that the proposed scheme is highly efficient in terms of computation, communication cost and security analysis as compared to other related schemes which makes the proposed scheme more suitable and practical for multi-server environments than other related schemes. [ABSTRACT FROM AUTHOR]

Acoustic metamaterials and metasurfaces often present complex geometries and microstructures. The development of models of reduced complexity is fundamental to alleviate the computational cost of their analysis and derivation of optimal designs. The main objective of this paper is the derivation and validation of a metacontinuum model for phase gradient-based metasurfaces. The method is based on the transformation acoustics framework and defines the metasurface in terms of anisotropic inertia and bulk modulus. Thermal and viscous dissipation effects in the metacontinuum are accounted for by introducing a complex-valued speed of sound. The model is implemented in a commercial FEM code, and its predictions are compared with numerical simulations on the original geometry and also using an equivalent boundary impedance approach. The results are examined for an exterior acoustics benchmark and for an in-duct installation in terms of transmission coefficient with the four-pole matrix method. The metacontinuum model gives solid results for the prediction of the acoustic properties of the examined metasurface samples for all the analyzed configurations, as accurate as the equivalent impedance model on which it is based and outperforming it in some circumstances. [ABSTRACT FROM AUTHOR]

Gun homicide rates have risen 35% across the USA since the start of the COVID-19 pandemic. One promising intervention to prevent violent crime is summer youth employment programs (SYEPs), which provide youth with meaningful workplace experiences, prosocial engagements, and developmental opportunities during the summer months, when many otherwise lack structure. This paper presents a cost analysis of violence prevention-focused SYEPs to help implementers understand the costs generally and in their own community contexts—to advocate for adoption and secure funding of, effectively budget for, and successfully implement SYEPs. Researchers use an ingredient-based costing approach and provide a template for implementers to use and adapt for their context. SYEPs with the goal of reaching youth who are justice-involved or at risk of being victims or perpetrators of violence can cost $3331 per youth assisted, with 54% of this cost directly paid to youth through stipends. Cost per youth is driven by the intensity of the mentoring and support that community organizations provide to the program participants. Knowing the cost per youth assisted can inform further analysis, implementation, and expansion of SYEPs. [ABSTRACT FROM AUTHOR]

Nitrogen (N) and phosphorus (P) losses to surface and coastal waters are still critically high across Europe and globally. Measures to mitigate and reduce these losses are being implemented both at the cultivated land surface and at the edge-of-fields. Woodchip bioreactors represent a new alternative in Denmark for treating agricultural drainage water, and the present study—based on two years of data from five Danish field-based bioreactors—determined N removal rates varying from 1.49 to 5.37 g N m−3 d−1 and a mean across all bioreactors and years of 2.90 g N m−3 d−1. The loss of phosphorus was relatively high the first year after bioreactor establishment with rates varying from 298.4 to 890.8 mg P m−3 d−1, but in the second year, the rates ranged from 12.2 to 77.2 mg P m−3 d−1. The investments and the costs of the bioreactors were larger than expected based on Danish standard investments. The cost efficiency analysis found the key issues to be the need for larger investments in the bioreactor itself combined with higher advisory costs. For the four woodchip bioreactors considered in the cost efficiency analysis, the N removal cost was around DKK 350 per kg N ($50 per kg N), which is ca. 50% higher than the standard costs defined by the Danish authorities. Based on the estimated costs of the four bioreactor facilities included in this analysis, a bioreactor is one of the most expensive nitrogen reduction measures compared to other mitigation tools. [ABSTRACT FROM AUTHOR]

Germany introduced prescription-based mobile health (mHealth) apps in October 2020, becoming the first country to offer them fully reimbursed by health insurance. These regulated apps, known as DiGAs, undergo a rigorous approval process similar to pharmaceuticals, including data protection measures and sometimes clinical trials. This study compares the user experience of DiGAs with non-prescription mHealth apps in Germany, analyzing both average app store ratings and written reviews. Our study pioneers the use of BERTopic for sentiment analysis and topic modeling in the mHealth research domain. The dataset comprises 15 DiGAs and 50 comparable apps, totaling 17,588 German-language reviews. Results reveal that DiGAs receive higher contemporary ratings than non-regulated apps (Android: 3.82 vs. 3.77; iOS: 3.78 vs. 3.53; p < 0.01; non-parametric Mann–Whitney–Wilcoxon test). Key factors contributing to positive user experience with DiGAs are customer service and personalization (15%) and ease of use (13%). However, challenges for DiGAs include software bugs (24%) and a cumbersome registration process (20%). Negative user reviews highlight concerns about therapy effectiveness (11%). Excessive pricing is the main concern for the non-regulated group (27%). Data privacy and security receive limited attention from users (DiGAs: 0.5%; comparators: 2%). In conclusion, DiGAs are generally perceived positively based on ratings and sentiment analysis of reviews. However, addressing pricing concerns in the non-regulated mHealth sector is crucial. Integrating user experience evaluation into the review process could improve adherence and health outcomes. [ABSTRACT FROM AUTHOR]

The increasing size of deep neural networks (DNNs) raises a high demand for distributed training. An expert could find good hybrid parallelism strategies, but designing suitable strategies is time and labor-consuming. Therefore, automating parallelism strategy generation is crucial and desirable for DNN designers. Some automatic searching approaches have recently been studied to free the experts from the heavy parallel strategy conception. However, these approaches all rely on a numerical cost model, which requires heavy profiling results that lack portability. These profiling-based approaches cannot lighten the strategy generation work due to the non-reusable profiling value. Our intuition is that there is no need to estimate the actual execution time of the distributed training but to compare the relative cost of different strategies. We propose SMSG (Symbolic Modeling for Strategy Generation), which analyses the cost based on the communication and computation semantics. With SMSG, the parallel cost analyses are decoupled from hardware characteristics. SMSG defines cost functions for each kind of operator to quantitatively evaluate the amount of data for computation and communication, which eliminates the heavy profiling tasks. Besides, SMSG introduces how to apply functional transformation by using the Third Homomorphism theorem to control the high searching complexity. Our experiments show that SMSG can find good hybrid parallelism strategies to generate an efficient training performance similar to the state of the art. Moreover, SMSG covers a wide variety of DNN models with good scalability. SMSG provides good portability when changing training configurations that a profiling-based approach cannot. [ABSTRACT FROM AUTHOR]

Collaborations between actors from different sectors (governments, firms, nonprofit organizations, universities, and other societal groups) have been promoted or mandated with increasing frequency to spur more innovative activities. This article argues that there is an essential gap in evaluating the issues of these collaborative arrangements on innovation and a need to theorize the costs of these arrangements systematically. This article identifies three implicit assumptions in current research that prevent a sound analysis of the costs of collaborative innovation and advances a new cost theory based on the integration of studies from several research fields and explanations provided by three main economic theories: transaction cost economics, game theory, and the knowledge-based view. In particular, four overarching factors are posited to impact the effectiveness of collaboration for innovation: governance (the number of collaborators and the hierarchical relationships among them); compactness (the degree of relationship formality that binds collaborators together); reliability (the quality of the relationships); and institutionalization (the extent to which the relationships have been pre-established by practice). We discuss the importance of leveraging these factors to determine an optimal governance structure that allows collaborating actors to minimize transaction, cooperation, and knowledge costs, and to reward participants proportionally to the cost they bear, in order to foster conditions of reciprocity, fair rates of exchange, and distributive justice. [ABSTRACT FROM AUTHOR]

This study investigates what factors relate to the coffee farmer's cooperative affiliation decision and whether this decision impacts the farmer's cash holdings. First, we propose a cooperative affiliation model based on transaction cost economics theory. There is a lack of consensus in the literature on what factors explain the farmer's cooperative affiliation decision in the coffee sector. Overall, we find that the more specialized coffee farmers are, the more likely they will become cooperative affiliates. This is consistent with transaction cost economics predicting that cooperatives are business structures that can reduce transaction costs and safeguard specialized assets from opportunistic behavior. Specifically, logit regression models suggest that shade-grown coffee plantations, off-farm income, coffee farming experience, low-level market competition, farmland size, altitude, and private farmland are statistically related to the farmer's decision to affiliate with cooperatives. Results on farmland size and shade-grown coffee plantations can be particularly relevant for scholars, policymakers, cooperative leaders, and extension professionals in the region. Second, based on the affiliation model, we employ propensity score matching to evaluate the impact of the farmer's cooperative affiliation decision on cash holdings, particularly on cash shortness. It is often claimed that farmers do not affiliate with cooperatives because these organizations cannot pay them in full at harvest and coffee collection time. It is believed that cooperatives' inability to pay farmers early increases the likelihood of farmers' cash shortness and their need for additional financing to operate or cover household needs. However, this study finds no evidence that the affiliation decision is related to the likelihood of the farmer experiencing cash shortness around harvesting and selling time. [ABSTRACT FROM AUTHOR]

Cloud computing is an essential part for individual and corporate users to perform resource intensive computation. During computation, the cost of execution abruptly changes with the dynamic requirements of the users. So, maintaining trade-off between the performance and the cost of computation has become extremely crucial. To resolve this, we have designed a dynamic pricing model for the IaaS cloud platforms that can set a lower bound of the base price for a cloud service and then compute the variable cost of execution based on the change in the user requirements. We have addressed an efficient mathematical cost analysis model considering all possible static and dynamic cost factors for computing a rational execution cost. Furthermore, we have presented a novel algorithm and implemented it within a simulated proposed service architecture for validating the results. We have compared our proposed model with existing models through extensive simulations. [ABSTRACT FROM AUTHOR]

Today, with the increasing electricity consumption and human needs for this energy, the availability of electricity has received more attention than before. Natural disasters, especially hurricanes, cause great damage to the power systems, leading to economic and social disruptions and public discontent. In general, reliability issues are not the perfect answer for evaluating the distribution network in the face of extreme events and the need for distribution network resilience studies. Resilience is the ability of the power system to withstand disruptions and rapid reconstruction against events that are unlikely to occur but have a high impact. In this paper, the preventive maintenance strategy is used for cost–benefit analysis of the objective function, which includes the cost of preventive maintenance, cost of resilience, and cost of reliability. In addition to cost analysis, reliability and resilience indicators in implementing various scenarios are analyzed. Finally, the system resilience diagrams for the severity of different accidents are presented. Based on the simulation results for several scenarios, the best preventive maintenance scenario is selected to improve the resilience level and reliability of the distribution network after the incident. The proposed strategy is implemented on the part of the standard test system to show the justification of the proposed approach. [ABSTRACT FROM AUTHOR]

Leakage from water distribution networks (WDNs) is inevitable. Therefore, during design a WDN, engineers add a percentage of each nodal water demand as leakage discharge to total node demand. The amount of leakage depends on the pressure, which is not known at the design stage. Considering a constant percentage of node demand in lieu of its leakage makes the problem worse. In this study, the effect of leakage on the optimal WDN design was investigated by developing the matrix form of the gradient algorithm while accounting for leakage using the pressure-dependent model. Non-dominated genetic algorithm version II (NSGA-II) was used as the optimization engine with two objectives which includes minimizing the network construction cost and minimizing the total network pressure deficiency. Two well-known two- and three-loop WDNs in literature were studied. The results indicated that the pressure-dependent leakage varies between 12.9 and 29.44% of the node demand while the network construction cost stays the same if compared with the fixed percentage leakage model, and the construction cost would increase by 17–31%, if leakage is not accounted for. This is expected the optimized diameters and hydraulic characteristics of the networks being affected by the leakage calculation method. [ABSTRACT FROM AUTHOR]

Determining which ports to call at in a maritime loop is considered as an important determinant factor for shipping companies which impacts not only on efficiency, and productivity but also on transportation costs. The port selection process becomes more challenging and sensitive if the market is for perishable goods such as fruits and vegetables. Specifically, this paper aims to develop an efficient maritime supply chain for reefer cargo. A case study of refrigerated cargo trade between West-Africa and West-Europe is investigated for which the main objective is to minimize the trade route's supply chain costs. To do so, the paper analyzes various scenarios based upon the different types of cargo (transshipment and non-transshipment), commodity types (dry and reefer), and a combination of different (un)loading ports in and the Rotterdam–Gibraltar range. Four African ports, namely Tema (Ghana), Douala (Cameroon), Abidjan (Ivory Coast), and Dakar (Senegal), are considered for the outbound leg (Africa–Europe), while several ports in the E.U. and the U.K. are selected as inbound leg. The analysis is initiated by applying a data-gathering strategy to get the relevant container flow from European ports to West-African ports. Then, a chain cost modelling approach is used to determine what the sailing schedule of the vessel should be. By performing the import/export cargo volume and maritime and supply chain costs are calculated, which can be used by the involved stakeholders to decide which ports are the best to call on a specific route. [ABSTRACT FROM AUTHOR]

Copyright of Fire Ecology is the property of Springer Nature 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.)

The economic repercussions of waiting for lumbar disc surgery have not been well studied. The primary goal of this study was to perform a cost-consequence analysis of patients receiving early vs late surgery for symptomatic disc herniation from a societal perspective. Secondarily, we compared patient factors and patient-reported outcomes. This is a retrospective analysis of prospectively collected data from the CSORN registry. A cost-consequence analysis was performed where direct and indirect costs were compared, and different outcomes were listed separately. Comparisons were made on an observational cohort of patients receiving surgery less than 60 days after consent (short wait) or 60 days or more after consent (long wait). This study included 493 patients with surgery between January 2015 and October 2021 with 272 patients (55.2%) in the short wait group and 221 patients (44.8%) classified as long wait. There was no difference in proportions of patients who returned to work at 3 and 12-months. Time from surgery to return to work was similar between both groups (34.0 vs 34.9 days, p = 0.804). Time from consent to return to work was longer in the longer wait group corresponding to an additional $11,753.10 mean indirect cost per patient. The short wait group showed increased healthcare usage at 3 months with more emergency department visits (52.6% vs 25.0%, p < 0.032), more physiotherapy (84.6% vs 72.0%, p < 0.001) and more MRI (65.2% vs 41.4%, p < 0.043). This corresponded to an additional direct cost of $518.21 per patient. Secondarily, the short wait group had higher baseline NRS leg, ODI, and lower EQ5D and PCS. The long wait group had more patients with symptoms over 2 years duration (57.6% vs 34.1%, p < 0.001). A higher proportion of patients reached MCID in terms of NRS leg pain at 3-month follow up in the short wait group (84.0% vs 75.9%, p < 0.040). This cost-consequence analysis of an observational cohort showed decreased costs associated with early surgery of $11,234.89 per patient when compared to late surgery for lumbar disc herniation. The early surgery group had more severe symptoms with higher healthcare utilization. This is counterbalanced by the additional productivity loss in the long wait group, which likely have a more chronic disease. From a societal economic perspective, early surgery seems beneficial and should be promoted. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 outbreak was defined as a pandemic on 11 March 2020 by the World Health Organization. After that, COVID-19 has enormously influenced health systems around the world, and it has claimed more than 4.2 million deaths until July 2021. The pandemic has led to global health, social and economic costs. This situation has prompted a crucial search for beneficial interventions and treatments, but little is known about their monetary value. This study is aimed at systematically reviewing the articles conducted on the economic evaluation of preventive, control and treatment strategies against COVID-19. Material and method: We searched PubMed, Web of Science, Scopus, and Google Scholar from December 2019 to October 2021 to find applicable literature to the economic evaluation of strategies against COVID-19. Two researchers screened potentially eligible titles and abstracts. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist was used to quality assessment of studies. Results: Thirty-six studies were included in this review, and the average CHEERS score was 72. Cost-effectiveness analysis was the most common type of economic evaluation, used in 21 studies. And the quality-adjusted life year (QALY) was the main outcome applied to measure the effectiveness of interventions, which was used in 19 studies. In addition, articles were reported a wide range of incremental cost-effectiveness ratio (ICER), and the lowest cost per QALY ($321.14) was related to the use of vaccines. Conclusion: Based on the results of this systematic review, it seems that all strategies are likely to be more cost-effective against COVID-19 than no intervention and vaccination was the most cost-effective strategy. This research provides insight for decision makers in choosing optimal interventions against the next waves of the current pandemic and possible future pandemics. [ABSTRACT FROM AUTHOR]

Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common form of non-Hodgkin's lymphoma with increasing prevalence. Although the disease burden associated with DLBCL is high, only limited data on healthcare resource utilization (HCRU) and associated costs of German patients with DLBCL is available. Methods: Using a large claims database of the German statutory health insurance with 6.7 million enrollees, we identified patients who were newly diagnosed with DLBCL between 2011 and 2018 (index date). Treatment lines were identified based on a predefined set of medication. HCRU and related costs were collected for the entire post index period and per treatment line. Results: A total of 2495 incident DLBCL patients were eligible for the analysis. The average follow-up time after index was 41.7 months. During follow-up, 1991 patients started a first-line treatment, 868 a second-line treatment, and 354 a third-line treatment. Overall, patients spent on average (SD) 5.24 (6.17) days per month in hospital after index. While on anti-cancer treatment, this number increased to nine (10.9) in first-line, 8.7 (13.7) in second-line, and 9.4 (15.8) in third-line treatments. Overall costs per patient per month (PPPM) increased from €421 (875.70) before to €3695 (4652) after index. While on a treatment line, PPPM costs were €17,170 (10,246) in first-line, €13,362 (12,685) in second-line, and €12,112 (16,173) in third-line treatments. Time-unadjusted absolute costs sum up to €59,868 (43,331), €35,870 (37,387), and €28,832 (40,540) during first-line, second-line, and third-line treatments, respectively. The main cost drivers were hospitalizations (71% of total costs) and drug acquisition costs (18% of total costs). Conclusions: The financial burden of DLBCL in Germany is high, mainly due to hospitalization and drug costs. Therefore, there is a high medical need for new cost-effective therapeutic options that can lower the disease burden and remain financially viable to support the growing number of patients with this aggressive disease. [ABSTRACT FROM AUTHOR]

In this work, a surface plasmon resonance (SPR) multiparameter sensor for simultaneous determination of refractive index and temperature was manufactured through a novel and low-cost approach. Monitoring these parameters is useful when biosensors are developed by exploiting SPR phenomena. A polymer planar optical structure was realized via inkjet 3D printing, by using photo-curable resins having tailored refractive index for device's core and cladding, respectively. The multiparameter sensor was fully designed, manufactured, and experimentally tested to check the numerical analyses run on a preliminary phase. In such a way, a temperature resolution equal to about 0.5 °C and a refractive index resolution equal to about 2 × 10−4 RIU (refractive index unit) were obtained. Next, even a quality control analysis of the 3D printed surface was carried out by following a novel approach that relies on the profile monitoring technique, with the aim to evaluate the suitability of the design and the geometric accuracy control. In addition, thanks to the cost analysis performed through a properly model, it was proved that the multiparameter sensor designed, manufactured, and tested satisfies the low-cost requirements, being the estimated cost ~ 23 €, which is an absolutely competitive cost if compared with other traditional sensors. In the end, even the performance of the sensor in terms of bulk sensitivity (equal to about 900 nm/RIU) resulted to be higher than similar devices already presented in the state-of-the-art, thus proving the validity of the developed SPR multiparameter sensor both in economic and performance terms. [ABSTRACT FROM AUTHOR]

Problems in the supply of electrical energy affect economic and social life and cause significant economic losses. In this study, the interruption costs of customers and distribution companies in 21 distribution regions in Turkey have been calculated and forecasts for the future have been realized. The aim here is to reveal the magnitude of the interruption costs with detailed analyses and methods that can be easily applied by decision makers and to support the decision-making processes. In this direction, the costs of interruption have been calculated by indirect analytical methods. Also, it is necessary to know how the interruption costs will change in the future to consider the interruption costs in investment plans. In this study, future forecasts have been performed using time series analyses and machine learning models. Additionally, solutions have been developed to facilitate the inclusion of interruption costs in the investment plans of the decision makers. With these solutions, the number and scope of investments can be increased. Thus, supply continuity performance will be increased in countries with high cost of interruptions and the losses incurred by the stakeholders in the energy sector will be reduced. [ABSTRACT FROM AUTHOR]

Methylene blue (MB) is a heterocyclic aromatic dye that is difficult to biodegrade due to its complex chemical structure. In this study, chemically prepared nano zero-valent aluminum (nZVAl) was investigated for the first time for one-step removal of MB from aqueous solutions under different experimental factors (pH, dosage, time, MB concentration, stirring rate, temperature, detergents, and ionic strength). The prepared nZVAl material was characterized using XRD, TEM, SEM, EDS, and FTIR. Results indicated that at an initial MB concentration of 10 mg/L, pH 10, nZVAl dosage 1.0 g/L, stirring rate 200 rpm, and temperature 30 °C, the removal efficiency of approximately 99.0% was achieved within an equilibrium time of 90 min. An improvement in MB removal efficiency was observed in the presence of inorganic salts, while the presence of detergents resulted in a reduction in MB removal efficiency. The isotherm adsorption data were best fitted by the Freundlich isotherm model (R2: 0.9569), while the kinetic data were well described by the pseudo-second-order (PSO) model (R2: 0.9999). Based on the thermodynamic study, the MB adsorption process is physically diffusion-controlled. The adsorption of MB onto nZVAl was accurately described using an artificial neural network (ANN) with a structure of 11–10–1 and R2 of 0.97. The overall cost of scaling up the adsorption unit to be used for MB removal from aqueous solutions under the optimum conditions is about US$1.31/m3. Consequently, this study opens the door for other researchers to test nZVAl in treating real textile wastewater. [ABSTRACT FROM AUTHOR]

Being one of the leading industries worldwide, the textile industry has been consuming large quantities of groundwater and discharging huge volumes of dye-contaminated effluents into our aquatic environment. Augmentation of water sources via reuse of treated effluents is therefore highly necessary. In the present study, the decolorization and degradation of synthetic toxic dye from an aqueous solution were investigated through an electro-biological route. Initially, decolorization of synthetic dye solutions (100, 500, and 1000 mg L−1) was carried out by electrooxidation process using mixed metal oxide and titanium as anode and cathode, respectively. The electrooxidation solutions were further treated using bacteria (Pseudomonas aeruginosa) that were isolated from petroleum-transporting pipelines. UV–Vis, TOC, chemical oxygen demand, and NMR analyses revealed that the biodegradation process with electrooxidation enhanced the mineralization of the synthetic dye solutions. An optimum NaCl electrolyte concentration of 3 g L−1 was sufficient to produce reactive species viz., free chlorine and hypochlorite, which are responsible for the Reactive Blue 19 (RB-19) decolorization. Among the three RB-19 concentrations, the highest removal percentage was noticed at 100 mg L−1 (100%) with energy consumption and energy costs equal to 5.44 kWh m−3 and 0.65 USD m−3, respectively. [ABSTRACT FROM AUTHOR]

Introduction: The treatment of multiple myeloma (MM) remains a challenge as patients eventually progress through several lines of therapy (LOTs), requiring use of multiple MM drug classes. In this retrospective US claims-database study, we examined the healthcare costs of patients with MM who received ≥ 4 prior LOTs, including triple-class exposure (TCE). Methods: Adult patients with MM were selected from the IBM MarketScan Commercial and Medicare claims databases (1 January 2012–30 June 2021). Eligible patients were required to have received at least four prior LOTs, and TCE (i.e., received a proteasome inhibitor, immunomodulatory drug, and anti–CD38-targeted monoclonal antibody) after the first-observed diagnosis of MM. The index date was defined as the initiation date of the first subsequent LOT after meeting the eligibility criteria for the study, and this date had to be after 1 January 2017 to capture contemporary cost estimates. The primary outcome measurements were all-cause and MM-related healthcare costs after the index date. Results: The study population included 68 patients with MM (63% men), with a mean age of 59.8 years. Mean duration from first-observed MM diagnosis until index date averaged 46.7 months. During a mean follow-up of 21.9 months, total all-cause healthcare costs averaged US$757,386 per patient (equivalent to US$34,610 per patient per month). MM-related healthcare costs (US$670,561 per patient) contributed on average 88.5% to the total all-cause healthcare costs; the majority (67.2%) of MM-related healthcare costs were attributed to drug and infusion costs (US$450,952 per patient). Conclusions: In this retrospective US claims-database study, patients with MM with ≥ 4 prior LOTs, including TCE, continued to experience high healthcare costs that were mostly attributable to anti-myeloma drugs and their administration. [ABSTRACT FROM AUTHOR]

Tuberculosis infection (TBI) frequently progresses to tuberculosis (TB) disease in people co-infected with human immunodeficiency virus (HIV). We examined the cost-effectiveness of single, sequential and no testing (total 12) strategies of TBI in HIV-infected people from the perspective of US healthcare provider. A decision-analytic model (20-year timeframe) was constructed to simulate TB-related outcomes: Direct medical cost and quality-adjusted life-years (QALYs). In the base-case analysis, the "confirm negative TST followed by QFT-Plus" strategy gained 0.1170 QALY at a total cost of USD3377. In the probabilistic sensitivity analysis of 10,000 Monte Carlo simulations, the probability of "confirm negative TST followed by QFT-Plus" to be accepted as cost-effective was the highest of all 12 strategies when the willingness-to-pay threshold exceeded 2340 USD/QALY. In conclusion, the strategy of "confirm negative TST followed by QFT-Plus" appears to be the preferred cost-effective option for TBI testing in HIV-infected people from the US healthcare provider's perspective. [ABSTRACT FROM AUTHOR]

With improvement in mastectomy skin flap viability and increasing recognition of animation deformity following sub-pectoral implant placement, there has been a transition toward pre-pectoral breast reconstruction. While studies have explored the cost effectiveness of implant-based breast reconstruction, few investigations have evaluated cost with respect to pre-pectoral versus sub-pectoral breast reconstruction. A retrospective review of 548 patients who underwent mastectomy and implant-based breast reconstruction was performed from 2017 to 2020. The demographic and surgical characteristics of the pre-pectoral and sub-pectoral cohorts were well matched, except for reconstructive staging, as patients who underwent pre-pectoral reconstruction were more likely to undergo single-stage instead of two-stage reconstruction. Comparison of institutional cost ratios by reconstructive technique revealed that the sub-pectoral approach was more costly (1.70 ± 0.44 vs 1.58 ± 0.31, p < 0.01). However, further stratification by laterality and reconstructive staging failed to demonstrate difference in cost by reconstructive technique. These results were confirmed by multivariable linear regression, which did not reveal reconstructive technique to be an independent variable for cost. This study suggests that pre-pectoral breast reconstruction is a cost-effective alternative to sub-pectoral breast reconstruction and may confer cost benefit, as it is more strongly associated with direct-to-implant breast reconstruction. [ABSTRACT FROM AUTHOR]

Agricultural commodities used for feed and food production are frequently contaminated with mycotoxins, such as Aflatoxin B1 (AFB1). In Europe, both the government and companies have monitoring programs in place for the presence of AFB1. With limited resources and following risk-based monitoring as prescribed in EU Regulation 2017/625, these monitoring programs focus on batches with the highest probability of being contaminated. This study explored the use of machine learning algorithms (ML) to design risk-based monitoring programs for AFB1 in feed products, considering both monitoring cost and model performance. Historical monitoring data for the presence of AFB1 in feed products (2005–2018; 5605 records in total) were used. Four different ML algorithms, including Decision tree, Logistic regression, Support vector machine and Extreme gradient boosting (XGB), were applied and compared to predict the high-risk feed batches to be considered for further AFB1 sampling and analysis. The monitoring cost included the cost of: sampling and analysis, disease burden, storage, and of recalling and destroying contaminated feed batches. The ML algorithms were able to predict the high-risk batches, with an AUC, recall, and accuracy higher than 0.8, 0.6, and 0.9, respectively. The XGB algorithm outperformed the other three investigated ML. Its incorporation would result into up to 96% reduction in monitoring cost in 2016–2018, as compared to the official monitoring program. The proposed approach for designing risk based monitoring programs can support authorities and industries to reduce the monitoring cost for other food safety hazards as well. [ABSTRACT FROM AUTHOR]

Live migration is an essential feature in virtual infrastructure and cloud computing datacenters. Using live migration, virtual machines can be online migrated from a physical machine to another with negligible service interruption. Load balance, power saving, dynamic resource allocation, and high availability algorithms in virtual data-centers and cloud computing environments are dependent on live migration. Live migration process has six phases that result in live migration cost. Several papers analyze and model live migration costs for different hypervisors, different kinds of workloads and different models of analysis. In addition, there are also many other papers that provide prediction techniques for live migration costs. It is a challenge for the reader to organize, classify, and compare live migration overhead research papers due to the broad focus of the papers in this domain. In this survey paper, we classify, analyze, and compare different papers that cover pre-copy live migration cost analysis and prediction from different angels to show the contributions and the drawbacks of each study. Papers classification helps the readers to get different studies details about a specific live migration cost parameter. The classification of the paper considers the papers' research focus, methodology, the hypervisors, and the cost parameters. Papers analysis helps the readers to know which model can be used for which hypervisor and to know the techniques used for live migration cost analysis and prediction. Papers comparison shows the contributions, drawbacks, and the modeling differences by each paper in a table format that simplifies the comparison. Virtualized Data-center and cloud computing clusters admins can also make use of this paper to know which live migration cost prediction model can fit for their environments. [ABSTRACT FROM AUTHOR]