Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

Estimation of the Direct Cost of Management of Venous Thromboembolism in Three Reference Hospitals in the City of Yaoundé: A Retrospective Study over a Three-Year Period

Background: Venous thromboembolism (VTE) is a major public health problem due to its increasing frequency, mortality and management cost. This cost may require major financial efforts from patients, especially in developing countries like ours where less than 7% of the population has health insurance. This study aimed to estimate the direct cost of managing VTE in three reference hospitals in Yaoundé. Methods: This was a cross-sectional retrospective study over a three-year period (from January 1st 2018 to December 31 2020) carried out in the Cardiology departments of the Central and General Hospitals, and the Emergency Centre of the city of Yaoundé. All patients managed during the study period for deep vein thrombosis and pulmonary embolism confirmed by venous ultrasound coupled with Doppler and computed tomography pulmonary angiography respectively were included. For each patient, we collected sociodemographic and clinical data as well as data on the cost of consultation, hospital stay, workups and medications. These data were analysed using SPSS version 23.0. Results: A total of 92 patient’s records were analysed. The median age was 60 years [48 - 68] with a sex ratio of 0.53. The median direct cost of management of venous thromboembolism was 766,375 CFAF [536,455 - 1,029,745] or $1415 USD. Management of pulmonary embolism associated with deep vein thrombosis was more costly than isolated pulmonary embolism or deep vein thrombosis. Factors influencing the direct cost of management of venous thromboembolism were: hospital structure (p = 0.015), health insurance (p 0.001), type of pulmonary embolism (p = 0.021), and length of hospital stay (p = 0.001). Conclusion: Management of VTE is a major financial burden for our patients and this burden is influenced by the hospital structure, health insurance, type of pulmonary embolism and length of hospital stay.

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.

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.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

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.

An Analysis of the Accounting Costs Associated with 20-Month DR TB Regimens in Maputo City, Mozambique

Introduction: Socioeconomic and demographic conditions in a country can influence tuberculosis incidence and mortality, with nearly 95% of tuberculosis-related deaths occurring in poorer countries. Mozambique is among the 30 countries with the highest TB burden. Objective: The study aimed to estimate the average direct medical cost of treating drug-resistant tuberculosis in 19 health centers in Maputo City, Mozambique. Methods: A retrospective analysis of direct medical costs was conducted on patients aged 18 and older who completed 20-month drug-resistant tuberculosis treatment regimens in Maputo City in 2019. Results: This analysis covered 140 patients who completed a 20-month treatment regimen, with 64.3% (78) being male and 35.7% (62) female. Approximately 50% of the participants were aged between 29 and 47. The average direct medical cost of DRTB treatment was $4789.43, reaching up to $6568.00, with a standard deviation of $753.26, including clinical interventions and treatment. Conclusion: The direct medical costs for a basic treatment package for a patient with drug-resistant TB in Mozambique equal 36 minimum wages. Developing alternative and innovative funding mechanisms and identifying ways to mitigate costs through the use of generic medicines would be beneficial.

A Secure and Cost-Effective Training Framework Atop Serverless Computing for Object Detection in Blasting

The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of blasting.Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine learning.In this paper,we design a distributedmachine learning training application based on the AWS Lambda platform.Based on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively realized.It also encrypts the data set,effectively reducing the risk of data leakage.We rent a cloud server and a Lambda,and then we conduct experiments to evaluate our applications.Our results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.

Costs of Schizophrenia at Psychiatric Hospital of Bingerville (Ivory Coast)

Schizophrenia is classified as a priority mental disorder by the World Health Organization (WHO) and accounts for around 35% of diagnoses at the Bingerville Psychiatric Hospital (HPB). The aims of the study were to identify the cost drivers for hospitalization and to calculate the costs of managing schizophrenia in hospital, with a view to planning household expenditure on care. This pilot cross-sectional study involved 31 patients with schizophrenia who had been hospitalized in the various third-category wards at the HPB between 1st January 2019 and 31st May 2020. Sampling was accidental. The methods used to estimate costs were based on the actual costs of drugs, hospitalization and additional examinations which prices were known, and on patients’ estimations for certain expenses such as food and transport. Results: The sex ratio was 3.42, the mean age was 29.52 years. The mean length of stay was 46.19 days, and the most frequent clinical forms were paranoid schizophrenia (41.9%) and schizoaffective disorder (29%). The combination of haloperidol and chlorpromazine was the most common medications for initial treatment (67.8%) and maintenance treatment (41.9%). The average cost of hospitalization at HPB for schizophrenia was XOF 164,412 (€249.90). The average direct medical cost was XOF 105,412 (€160.226) and the average direct non-medical cost was XOF 59,000 (€89.68). The average daily cost of antipsychotic treatment was XOF 795/day (€1.2084). The high cost of drugs as a proportion of hospitalization costs suggested the need of a reflection on the simplification of prescribing practices, assistance in psychiatric emergencies and the development of other alternatives to psychiatric hospitalization in Côte d’Ivoire.

From the perspective of experimental practice: High-throughput computational screening in photocatalysis

Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.

Cost of Medical Treatment for Primary Open-Angle Glaucoma in Relation to Patients’ Income and Its Impact on the Prognosis of the Disease, in Bouaké University Hospital

Introduction: Medical treatment for POAG is continuous and lifelong treatment. The aim of this study was to evaluate the relationship between the cost of this treatment and patients’ income and the impact of this relationship on treatment compliance. Materials and Methods: Prospective cross-sectional study with a descriptive aim covering sociodemographic data, average incomes, and direct and indirect costs of treatment of 57 patients followed for POAG during the period from January 1, 2012, to December 31, 2016 (5 years). Results: The patients were aged 25 to 77 years (mean = 54.4 years) with a male predominance (sex ratio = 1.5). Retirees were the most represented (26.32%), followed by workers in the informal sector (14.04%) and housewives (12.28%). Patients who had an annual income less than or equal to 900,000 CFA francs (€1370.83) per year represented 56.14% and those who did not have health coverage represented 57.89%. The treatment was monotherapy (64.91%), dual therapy (31.58%) or triple therapy (3.05%) and the average ratio of “annual cost of treatment to annual income” was 0.56 with for maximum 2.23 and 0.02 as minimum. Patients who considered the cost of treatment unbearable for their income represented 78.95%. Conclusion: Prevention of blindness due to glaucoma requires early detection but also the establishment of health coverage mechanisms to improve compliance with medical treatment. In addition, consideration should be given to the development of glaucoma surgery in our country, the indication of which could be the first intention in certain patients, considering for those patients, the geographical and financial accessibility of medical treatment. .

A fast forward computational method for nuclear measurement using volumetric detection constraints

Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sources,the detector response can reflect various types of information of the medium.The Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex environments.However,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response results.Therefore,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is proposed.First,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo simulation.Then,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion model.The environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection volume.Finally,the method is applied to a neutron porosity tool for verification.In various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 p.u.In field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method.

A digital twin model-based approach to cost optimization of residential community microgrids

This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.

The potential impact of increased whole grain consumption among Chinese adults on reducing healthcare costs and carbon footprint

Excessive consumption of refined grains harms human health and ecosystem viability.Whole grains,as a healthy and sustainable alternative to refined grains,can benefit individual health by providing dietary fiber,B vitamins,and bioactive substances.Additionally,they aid in improving the environment due to their higher extraction rate and lower carbon emission during the processing stage.However,few studies have attempted to evaluate the economic and social benefits of increasing the amount of whole grain in grain intake.This paper estimates the potential savings in healthcare costs and reduced food carbon footprints(CFs)that could result from a shift toward whole grain consumption following the Chinese Dietary Guidelines(CDG).We investigate hypothetical scenarios where a certain proportion(5–100%)of Chinese adults could increase their whole grain intakes as proposed by CDG to meet the average shortfall of 30.2 g.In that case,the healthcare costs for associated diseases(e.g.,type2 diabetes mellitus(T2DM),cardiovascular disease(CVD),and colorectal cancer(CRC))are expected to reduce by a substantial amount,from USD 2.82 to 56.37 billion;the carbon emission levels are also projected to decrease by0.24–5.72 million tons.This study provides compelling evidence that advocating for the transition towards greater consumption of whole grain products could benefit individual health,the environment,and society,by reducing both healthcare costs and carbon emissions.

Computational fluid dynamics modeling of rapid pyrolysis of solid waste magnesium nitrate hydrate under different injection methods

This study developed a numerical model to efficiently treat solid waste magnesium nitrate hydrate through multi-step chemical reactions.The model simulates two-phase flow,heat,and mass transfer processes in a pyrolysis furnace to improve the decomposition rate of magnesium nitrate.The performance of multi-nozzle and single-nozzle injection methods was evaluated,and the effects of primary and secondary nozzle flow ratios,velocity ratios,and secondary nozzle inclination angles on the decomposition rate were investigated.Results indicate that multi-nozzle injection has a higher conversion efficiency and decomposition rate than single-nozzle injection,with a 10.3%higher conversion rate under the design parameters.The decomposition rate is primarily dependent on the average residence time of particles,which can be increased by decreasing flow rate and velocity ratios and increasing the inclination angle of secondary nozzles.The optimal parameters are injection flow ratio of 40%,injection velocity ratio of 0.6,and secondary nozzle inclination of 30°,corresponding to a maximum decomposition rate of 99.33%.

Impact of carbon disclosure on debt financing costs

Creditors,such as banks,often use disclosed environmental information to assess a company’s environmental risk and ensure the safety of debt funds.Consequently,carbon disclosures have become an important consideration for creditors when making investments.This study explores the relationship between carbon disclosure and debt financing costs using data on listed companies from 2008 to 2019.The results show that carbon disclosure can reduce the debt financing costs of enterprises,and that this influence is more significant for private companies than for state-owned enterprises.Instrumental variables and Propensity Score Matching(PSM)were used to evaluate the robustness of negative relationships.Furthermore,carbon disclosure has a more significant impact on debt costs with less environmental supervision pressure,weak residents’environmental awareness,and weak product market competition.These findings provide guidance for companies’carbon information disclosure and support the establishment of official carbon disclosure standards.

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.

Reliability-based life-cycle cost seismic design optimization of coastal bridge piers with nonuniform corrosion using different materials

Reinforcement corrosion is the main cause of performance deterioration of reinforced concrete(RC)structures.Limited research has been performed to investigate the life-cycle cost(LCC)of coastal bridge piers with nonuniform corrosion using different materials.In this study,a reliability-based design optimization(RBDO)procedure is improved for the design of coastal bridge piers using six groups of commonly used materials,i.e.,normal performance concrete(NPC)with black steel(BS)rebar,high strength steel(HSS)rebar,epoxy coated(EC)rebar,and stainless steel(SS)rebar(named NPC-BS,NPC-HSS,NPC-EC,and NPC-SS,respectively),NPC with BS with silane soakage on the pier surface(named NPC-Silane),and high-performance concrete(HPC)with BS rebar(named HPC-BS).First,the RBDO procedure is improved for the design optimization of coastal bridge piers,and a bridge is selected to illustrate the procedure.Then,reliability analysis of the pier designed with each group of materials is carried out to obtain the time-dependent reliability in terms of the ultimate and serviceability performances.Next,the repair time of the pier is predicted based on the time-dependent reliability indices.Finally,the time-dependent LCCs for the pier are obtained for the selection of the optimal design.

Numerical Analysis of Bacterial Meningitis Stochastic Delayed Epidemic Model through Computational Methods

Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal cord.It is a devastating disease and remains a significant public health challenge.This study investigates a bacterial meningitis model through deterministic and stochastic versions.Four-compartment population dynamics explain the concept,particularly the susceptible population,carrier,infected,and recovered.The model predicts the nonnegative equilibrium points and reproduction number,i.e.,the Meningitis-Free Equilibrium(MFE),and Meningitis-Existing Equilibrium(MEE).For the stochastic version of the existing deterministicmodel,the twomethodologies studied are transition probabilities and non-parametric perturbations.Also,positivity,boundedness,extinction,and disease persistence are studiedrigorouslywiththe helpofwell-known theorems.Standard and nonstandard techniques such as EulerMaruyama,stochastic Euler,stochastic Runge Kutta,and stochastic nonstandard finite difference in the sense of delay have been presented for computational analysis of the stochastic model.Unfortunately,standard methods fail to restore the biological properties of the model,so the stochastic nonstandard finite difference approximation is offered as an efficient,low-cost,and independent of time step size.In addition,the convergence,local,and global stability around the equilibria of the nonstandard computational method is studied by assuming the perturbation effect is zero.The simulations and comparison of the methods are presented to support the theoretical results and for the best visualization of results.

Effect of solvent on the initiation mechanism of living anionic polymerization of styrene:A computational study

For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics.