Interest of D-dimer level,severity of COVID-19 and cost of management in Gabon

BACKGROUND Coronavirus disease 2019(COVID-19)is strongly associated with an increased risk of thrombotic events,including severe outcomes such as pulmonary embolism.Elevated D-dimer levels are a critical biomarker for assessing this risk.In Gabon,early implementation of anticoagulation therapy and D-dimer testing has been crucial in managing COVID-19.This study hypothesizes that elevated Ddimer levels are linked to increased COVID-19 severity.AIM To determine the impact of D-dimer levels on COVID-19 severity and their role in guiding clinical decisions.METHODS This retrospective study analyzed COVID-19 patients admitted to two hospitals in Gabon between March 2020 and December 2023.The study included patients with confirmed COVID-19 diagnoses and available D-dimer measurements at admission.Data on demographics,clinical outcomes,D-dimer levels,and healthcare costs were collected.COVID-19 severity was classified as non-severe(outpatients)or severe(inpatients).A multivariable logistic regression model was used to assess the relationship between D-dimer levels and disease severity,with adjusted odds ratios(OR)and 95%CI.RESULTS A total of 3004 patients were included,with a mean age of 50.17 years,and the majority were female(53.43%).Elevated D-dimer levels were found in 65.81%of patients,and 57.21%of these experienced severe COVID-19.Univariate analysis showed that patients with elevated D-dimer levels had 3.33 times higher odds of severe COVID-19(OR=3.33,95%CI:2.84-3.92,P<0.001),and this association remained significant in the multivariable analysis,adjusted for age,sex,and year of collection.The financial analysis revealed a substantial burden,particularly for uninsured patients.CONCLUSION D-dimer predicts COVID-19 severity and guides treatment,but the high cost of anticoagulant therapy highlights the need for policies ensuring affordable access in resource-limited settings like Gabon.

An Analysis and Prediction of Health Insurance Costs Using Machine Learning-Based Regressor Techniques

One of the most significant annual expenses that a person has is their health insurance coverage. Health insurance accounts for one-third of GDP, and everyone needs medical treatment to varying degrees. Changes in medicine, pharmaceutical trends, and political factors are only a few of the many factors that cause annual fluctuations in healthcare costs. This paper describes how a system may analyse a person’s medical history to display their insurance plans and make predictions about their health insurance premiums. The performance of four ML models—XGBoost, Lasso, KNN, and Ridge—is evaluated using R2-score and RMSE. The analysis of medical health insurance cost prediction using Lasso regression, Ridge regression, and K-Nearest Neighbours (KNN), and XGBoost (XGB) highlights notable differences in performance. KNN has the lowest R2-score of 55.21 and an RMSE of 4431.1, indicating limited predictive ability. Ridge Regression improves on this by an R2-score of 78.38 but has a higher RMSE of 4652.06. Lasso Regression slightly edges out Ridge with an R2-score of 79.78, yet it suffers from an advanced RMSE of 5671.6. In contrast, XGBoost excels with the highest R2-score of 86.81 and the lowermost RMSE of 4450.4, demonstrating superior predictive accuracy and making it the most effective model for this task. The best method for accurately predicting health insurance premiums was XGBoost Regression. The findings beneficial for policymakers, insurers, and healthcare providers as they can use this information to allocate resources more efficiently and enhance cost-effectiveness in the healthcare industry.

A Hybrid Model for Improving Software Cost Estimation in Global Software Development

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

Assessment of the Indirect Cost of Drug Resistant Tuberculosis Treatment to Patients in a High Burden, Low Income Setting in Mozambique

Introduction: Tuberculosis is closely linked to poverty, with patients facing significant indirect treatment costs. Treating drug-resistant tuberculosis further increases these expenses. Notably, there is a lack of published data on the indirect costs incurred by patients with drug-resistant tuberculosis in Mozambique. Objective: To assess the indirect costs, income reduction, and work productivity incurred by patients undergoing diagnosis and treatment for Drug-Resistant Tuberculosis (DRTB) in Mozambique during their TB treatment. Methods: As part of a comprehensive mixed-methods study conducted from January 2021 to April 2023, this research utilized a descriptive cross-sectional approach, incorporating both quantitative and qualitative methods. The primary goal was to evaluate the costs incurred by the national health system due to drug-resistant TB. Additionally, to explore the indirect costs experienced by patients and their families during treatment, semi-structured interviews were conducted with 27 individuals who had been undergoing treatment for over six months. Results: All survey participants unanimously reported a significant decline in labour productivity, with 70.3% experiencing a reduction in their monthly income. Before falling ill, the majority of respondents (33.3%) earned up to $76.92 monthly, representing the minimum earnings range, while 29.2% had a monthly income above $230.77, the maximum earnings range. Among those who experienced income loss, the majority (22.2%) reported a decrease of up to $76.92 per month, and 18.5% cited a loss exceeding $230.77 per month. Notably, patients with Drug-Resistant Tuberculosis (DRTB) have not incurred the direct costs of the disease, as these are covered by the government. Conclusion: The financial burden of treating Drug-Resistant Tuberculosis (DRTB), along with the income reduction it causes, is substantial. Implementing a patient-centred, multidisciplinary, and multisector approach, coupled with strong psychosocial support, can significantly reduce the catastrophic costs DRTB patients incur.

TRADE DEPENDENCIES AND TRANSACTION COSTS: THE OC-CUPATION OF DECELEA HIGHLIGHTS BOTH THE BENEFITS AND THE DRAWBACKS OF A MARITIME ECONOMY

Thucydides asserts that the occupation of Decelea by the Spartans in 413 BC made the grain supply for Athens costly by forcing the transport from land onto the sea.This calls into question the well-established consensus that sea transport was far cheaper than land transport.This paper contends that the cost of protecting supply lines-specifically the expenses associated with the warships which escorted the supply ships-rendered the grain transported on the new route exceptionally costly.In this paper,the benefits and drawbacks of a maritime economy,including transaction costs,trade dependencies,and the capabilities of warships and supply ships are discussed.

The Societal Cost of Schizophrenia in China from 2010 to 2024—A Literature Review

Background: Schizophrenia is a chronic disease related to long-lasting and tremendous effects on patient’s health in China, which is generally considered as a huge economic burden not only for patients but also for their caregivers and the whole society. Therefore, it is necessary to conduct an analysis of cost. Previous cost-of-illness (COI) studies have already provided some useful information on the economic burden that schizophrenia brought to global society, including China. Objectives: This systematic review aims to obtain a comprehensive understanding of the economic burden of schizophrenia in China. Method: A literature review was performed through CNKI, Wanfang, CQVIP, EMBASE and Medline databases to identify COI studies published between 2010-2024. The primary outcome of this review was societal cost per schizophrenia patient by cost component, including direct medical costs, non-medical costs and indirect medical costs. Results: 14 COI studies in schizophrenia were identified, covering 7 municipalities and 8 provinces of China. The annual societal cost per patient ranged from 10,765 CNY in Zhejiang province to 406,382 CNY in Xuancheng city (Anhui province). The ratio of indirect cost ranged from 66.6% to 96.8%. The main cost drivers were the productivity losses. There was an enormous heterogeneity between societal cost estimations that could be interpreted by the difference in economic state and regional healthcare resource allocation. Conclusions: This review highlights the large economic burden of schizophrenia in varied areas in China. Substantial cost variation was observed both nationwide and globally, which may be caused by the varied economic situation and healthcare policy. Limitation of this review was summarized, which may provide a useful guidance for the future COI studies in China.

A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

Cost-optimization based target reliabilities for design of structures exposed to fire

Adequacy of structural fire design in uncommon structures is conceptually ensured through cost-benefit analysis where the future costs are balanced against the benefits of safety investment.Cost-benefit analyses,however,are complicated and computationally challenging,and hence impractical for application to individual projects.To address this issue,design guidance proposes target reliability indices for normal design conditions,but no target reliability indices are defined for structural fire design.We revisit the background of the cost-optimization based approach underlying normal design target reliability indices then we extend this approach for the case of fire design of structures.We also propose a modified objective function for cost-optimization which simplifies the evaluation of target reliability indices and reduces the number of assumptions.The optimum safety level is expressed as a function of a new dimensionless variable named“Damage-to-investment indicator”(DII).The cost optimization approach is validated for the target reliability indices for normal design condition.The method is then applied for evaluating DII and the associated optimum reliability indices for fire-exposed structures.Two case studies are presented:(i)a one-way loaded reinforced concrete slab and(ii)a steel column under axial loading.This study thus provides a framework for deriving optimum(target)reliability index for structural fire design which can support the development of rational provisions in codes and standards.

Analysis of the Current Situation of Cost Management and Control of Highway Construction Projects

The highway engineering process is complex,coupled with a relatively long construction period,hence requires increased coordination between participating units to prevent economic disputes and efficiency losses.The main body of the construction project needs to strengthen the management and control of funds.In this regard,this paper analyzes the importance of cost management in highway projects by clarifying and analyzing the current cost management status quo problems and causes.The highway engineering cost control strategy and implementation methods are summarized to provide references for improving the quality of highway engineering.

Whole-Process Project Cost Management Based on Building Information Modeling (BIM)

The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.

Construction Cost Control Strategy of Finished House Based on BIM-5D

Building Information Modeling(BIM)technology can not only achieve project refinement management of the construction process based on a 3D model but also form a BIM-5D model based on the fusion of progress data and cost data to achieve the dynamic control of the whole process of project cost.This paper discusses the application of BIM-5D in the cost control of finished house construction,aiming to provide technical reference for China’s finished house project units,so that they can master how to realize the construction of cost control system based on BIM,the monitoring of the key coefficients of the cost,corrective action,to ensure that the project cost deviation is within the controllable range,and to make an effective guarantee for the economic benefits of the project construction.

Research on Intelligent Cost Estimation of Engineering Foundation Projects Based on CSIs Theory

Against the backdrop of rapid development in China’s construction and infrastructure sectors,discrepancies between project budgets and actual costs have become pronounced,manifesting in project overruns and suspensions,posing significant challenges.To address inaccuracies in investment targets and operational complexities,this study focuses on a beam-bridge construction project in a district of Shijiazhuang city as a case study.Drawing upon historical analogs,the project employs a Work Breakdown Structure(WBS)to decompose the engineering works.Building on theories of Cost Significant(CS)and Whole Life Costing(WLC),the study constructs Cost Significant Items(CSIs)and develops a CNN-BiLSTM-Attention neural network for nonlinear prediction.By identifying significant cost drivers in engineering projects,this paper presents a streamlined cost estimation method that significantly reduces computational burdens,simplifies data collection processes,and optimizes data analysis and forecasting,thereby enhancing prediction accuracy.Finally,validation with real-world cost fluctuation data demonstrates minor errors,meeting predictive requirements across project execution phases.

Cost Management and Cost Control of Photovoltaic Projects

With the rapid development of the photovoltaic(PV)industry and policy support,photovoltaic engineering has attracted much attention as a clean energy project.However,the complexity and huge investment scale of photovoltaic projects make cost management and cost control the key to project success.The purpose of this paper is to discuss the cost management and cost control strategies of photovoltaic projects,analyze their importance and challenges in the process of project implementation,and discuss the common cost control methods and techniques in photovoltaic projects,to improve cost management and cost control in photovoltaic projects,and to provide a reference for the sustainable development of the industry.

Discussion on Cost Budgeting and Cost Control Strategies for Prefabricated Construction Projects

In the process of China’s national economic development,the construction industry is a very important component and has a direct impact on the level of China’s economic construction.Nowadays,the development speed of the prefabricated construction industry is constantly accelerating.To effectively ensure the economic benefits of engineering projects,it is necessary to comprehensively strengthen cost budgeting and cost control.This article analyzes the cost budget of prefabricated construction projects,introduces the application advantages of prefabricated construction,and proposes specific cost budgeting and cost control measures,hoping to provide some reference for relevant researchers.

Cyberattack Ramifications, The Hidden Cost of a Security Breach

In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.

Resistance development,cross-resistance,and fitness costs associated with Aphis gossypii resistance towards sulfoxaflor and acetamiprid in different geographical regions

Aphis gossypii has become increasingly difficult to manage due to its strong insecticide resistance.In the laboratory,we established sulfoxaflor-resistant and acetamiprid-resistant strains in two A.gossypii populations with different basal insecticide resistance levels,and evaluated the effects of basal insecticide resistance on the resistance development and cross-resistance,as well as differences in fitness.Under the same selection pressure,Yarkant A.gossypii(with low basal insecticide resistance)evolved resistance to sulfoxaflor and acetamiprid more quickly than Jinghe A.gossypii(with high basal insecticide resistance),and the evolution of A.gossypii resistance to sulfoxaflor developed faster than acetamiprid in both Yarkant and Jinghe,Xingjiang,China.The sulfoxaflor-resistant strains selected from Yarkant and Jinghe developed significant cross-resistance to acetamiprid,imidacloprid,thiamethoxam and pymetrozine;while the acetamiprid-resistant strains developed significant cross-resistance to sulfoxaflor,imidacloprid,thiamethoxam,pymetrozine,and chlorpyrifos.The relative fitness of A.gossypii decreased as the resistance to sulfoxaflor and acetamiprid developed.The relative fitness levels of the sulfoxaflor-resistant strains(Yarkant-SulR and Jinghe-SulR)were lower than those of the acetamipridresistant strains(Yarkant-AceR and Jinghe-AceR).In addition,the relative fitness levels of sulfoxaflor-and acetamiprid-resistant strains were lower in Jinghe than in Yarkant.In summary,basal insecticide resistance of A.gossypii and insecticide type affected the evolution of resistance to insecticides in A.gossypii,as well as cross-resistance to other insecticides.The sulfoxaflor-and acetamiprid-resistant A.gossypii strains had obvious fitness costs.The results of this work will contribute to the insecticide resistance management and integrated management of A.gossypii.

Analysis of a passive ankle exoskeleton for reduction of metabolic costs during walking

Modern conflicts demand substantial physical and psychological exertion,often resulting in fatigue and diminished combat or operational readiness.Several exoskeletons have been developed recently to address these challenges,presenting various limitations that affect their operational or everyday usability.This article evaluates the performance of a dual-purpose passive ankle exoskeleton developed for the reduction of metabolic costs during walking,seeking to identify a force element that could be applied to the target population.Based on the 6-min walk test,twenty-nine subjects participated in the study using three different force elements.The results indicate that it is possible to reduce metabolic expenditure while using the developed exoskeleton.Additionally,the comfort and range of motion results verify the exoskeleton's suitability for use in uneven terrain and during extended periods.Nevertheless,the choice of the force element should be tailored to each user,and the control system should be adjustable to optimise the exoskeleton's performance.

Design and implementation of low-cost geomagnetic field monitoring equipment for high-density deployment

The observation of geomagnetic field variations is an important approach to studying earthquake precursors.Since 1987,the China Earthquake Administration has explored this seismomagnetic relationship.In particular,they studied local magnetic field anomalies over the Chinese mainland for earthquake prediction.Owing to the years of research on the seismomagnetic relationship,earthquake prediction experts have concluded that the compressive magnetic effect,tectonic magnetic effect,electric magnetic fluid effect,and other factors contribute to preearthquake magnetic anomalies.However,this involves a small magnitude of magnetic field changes.It is difficult to relate them to the abnormal changes of the extremely large magnetic field in regions with extreme earthquakes owing to the high cost of professional geomagnetic equipment,thereby limiting large-scale deployment.Moreover,it is difficult to obtain strong magnetic field changes before an earthquake.The Tianjin Earthquake Agency has developed low-cost geomagnetic field observation equipment through the Beijing–Tianjin–Hebei geomagnetic equipment test project.The new system was used to test the availability of equipment and determine the findings based on big data..

Feasibility of Scaling up the Cost-Competitive and Clean Electrolytic Hydrogen Supply in China

Scaling up clean hydrogen supply in the near future is critical to achieving China’s hydrogen development target.This study established an electrolytic hydrogen development mechanism considering the generation mix and operation optimization of power systems with access to hydrogen.Based on the incremental cost principle,we quantified the provincial and national clean hydrogen production cost performance levels in 2030.The results indicated that this mechanism could effectively reduce the production cost of clean hydrogen in most provinces,with a national average value of less than 2 USD·kg^(-1) at the 40-megaton hydrogen supply scale.Provincial cooperation via power transmission lines could further reduce the production cost to 1.72 USD·kg^(-1).However,performance is affected by the potential distribution of hydrogen demand.From the supply side,competitiveness of the mechanism is limited to clean hydrogen production,while from the demand side,it could help electrolytic hydrogen fulfil a more significant role.This study could provide a solution for the ambitious development of renewables and the hydrogen economy in China.