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”.

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.

Teaching Status and Teaching Reform Ideas of Physical Chemistry Experiments for Food Quality and Safety Major

Physical chemistry experiments are an important branch of chemical experiments.In view of problems and shortcomings in physical chemistry experiment teaching of food quality and safety major in Chengdu University,the teaching methods of physical chemistry experiment course of food quality and safety major were explored and practiced,aiming to arouse students enthusiasm for experiments and cultivate their ability of independent learning,comprehensive thinking and independent problem solving.

Study on the effect and mechanism of Swertia mussotii Franch. in the treatment of primary biliary cholangitis based on bioinformatics and in vitro experiments

Background:Primary biliary cholangitis(PBC)is a chronic biliary autoimmune liver disease characterized by intrahepatic cholestasis.Swertia mussotii Franch.(SMF)is a Tibetan medicine with hepatoprotective and anti-inflammatory activities.In this study,the therapeutic effect and potential mechanisms of SMF on PBC were investigated by bioinformatics analysis and in vitro experimental validation,with the aim of promoting the progress of SMF and PBC research.Methods:We first explored the therapeutic effects and key targets of SMF on PBC using a network pharmacology approach,further screened the core targets using the GSE79850 dataset,and finally validated the results using molecular docking techniques and in vitro experiments.Results:By bioinformatics analysis,we identified core targets of SMF for PBC treatment(STAT3,JAK2,TNF-α,and IL-1β)and important signaling pathways:JAK-STAT,TNF,and PI3K-AKT.The molecular docking results showed that the significant components of SMF had good binding properties to the core targets.In vitro experiments showed that SMF extracts improved the extent of epithelial-mesenchymal transition in human intrahepatic biliary epithelial cells and had a significant reversal effect on epithelial-mesenchymal transition process markers and potential targets in PBC.Conclusion:SMF may exert its therapeutic effects on PBC by acting on important targets such as STAT3,JAK2,TNF-α,IL-1β,Vimentin,and E-cadherin and the pathways in which they are involved.

Design and analysis of an advanced thermal management system for the solar close observations and proximity experiments spacecraft

In this paper,the mission and the thermal environment of the Solar Close Observations and Proximity Experiments(SCOPE)spacecraft are analyzed,and an advanced thermal management system(ATMS)is designed for it.The relationship and functions of the integrated database,the intelligent thermal control system and the efficient liquid cooling system in the ATMS are elaborated upon.For the complex thermal field regulation system and extreme space thermal environment,a modular simulation and thermal field planning method are proposed,and the feasibility of the planning algorithm is verified by numerical simulation.A solar array liquid cooling system is developed,and the system simulation results indicate that the temperatures of the solar arrays meet the requirements as the spacecraft flies by perihelion and aphelion.The advanced thermal management study supports the development of the SCOPE program and provides a reference for the thermal management in other deep-space exploration programs.

Exploration of playa surface crusts in Qehan Lake, China through field investigation and wind tunnel experiments

Globally,many lakes are drying up,leaving exposed lakebeds where wind erosion releases dust and sand rich in salt and harmful heavy metals into the atmosphere.Therefore,understanding the characteristics and spatial distribution of playa surface crusts is important to recognize the manifestation of salt dust storms.The objective of this study was to explore the playa surface crust types as well as their spatial distribution and evolution of Qehan Lake in Inner Mongolia Autonomous Region,China to understand the salt dust release potential of different types of playa surface crusts.Various crust characteristics were investigated by field sampling in Qehan Lake,and playa surface crusts were further divided into five types:vegetated areas,salt crusts,clay flats,curly crusts,and margins.It should be noted that curly crusts were distributed in clay flats and covered only a small area in Qehan Lake.The spatial distribution characteristics of playa surface crust types were obtained by supervised classification of remote sensing images,and the salt dust release potential of crusts was explored by the wind tunnel experiments.The field investigation of Qehan Lake revealed that playa surface crust types had a circum-lake band distribution from the inside to the outside of this lake,which were successively vegetated areas,clay flats,salt crusts,and margins.The spatial distribution patterns of playa surface crust types were mainly controlled by the hydrodynamics of the playa,soil texture,and groundwater.There was a significant negative correlation between crust thickness and electrical conductivity.The results of the wind tunnel experiments showed that the initial threshold of friction wind velocity for the salt dust release was higher in clay flats(0.7–0.8 m/s)than in salt crusts(0.5–0.6 m/s).Moreover,the particle leap impact processes occurring under natural conditions may reduce this threshold value.Salinity was the main factor controlling the difference in the initial threshold of friction wind velocity for the salt dust release of clay flats and salt crusts.This study provides a scientific reference for understanding how salt dust is released from a lakebed,which may be used for ecological restoration of dry salt lakes.

High-throughput experiments facilitate materials innovation:A review

Since the Material Genome Initiative(MGI) was proposed, high-throughput based technology has been widely employed in various fields of materials science. As a theoretical guide, material informatics has been introduced based on machine learning and data mining and high-throughput computation has been employed for large scale search, narrowing down the scope of the experiment trials. High-throughput materials experiments including synthesis, processing, and characterization technologies have become valuable research tools to pin down the prediction experimentally, enabling the discovery-to-deployment of advances materials more efficiently at a fraction of cost. This review aims to summarize the recent advances of high-throughput materials experiments and introduce briefly the development of materials design based on material genome concept. By selecting representative and classic works in the past years, various high-throughput preparation methods are introduced for different types of material gradient libraries, including metallic, inorganic materials, and polymers. Furthermore, high-throughput characterization approaches are comprehensively discussed, including both their advantages and limitations. Specifically, we focus on high-throughput mass spectrometry to analyze its current status and challenges in the application of catalysts screening.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Development of a High-throughput Sequencing Platform for Detection of Viral Encephalitis Pathogens Based on Amplicon Sequencing

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing.Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing.Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing.Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

High-throughput microfluidic production of carbon capture microcapsules:fundamentals,applications,and perspectives

In the last three decades,carbon dioxide(CO_(2)) emissions have shown a significant increase from various sources.To address this pressing issue,the importance of reducing CO_(2) emissions has grown,leading to increased attention toward carbon capture,utilization,and storage strategies.Among these strategies,monodisperse microcapsules,produced by using droplet microfluidics,have emerged as promising tools for carbon capture,offering a potential solution to mitigate CO_(2) emissions.However,the limited yield of microcapsules due to the inherent low flow rate in droplet microfluidics remains a challenge.In this comprehensive review,the high-throughput production of carbon capture microcapsules using droplet microfluidics is focused on.Specifically,the detailed insights into microfluidic chip fabrication technologies,the microfluidic generation of emulsion droplets,along with the associated hydrodynamic considerations,and the generation of carbon capture microcapsules through droplet microfluidics are provided.This review highlights the substantial potential of droplet microfluidics as a promising technique for large-scale carbon capture microcapsule production,which could play a significant role in achieving carbon neutralization and emission reduction goals.

High-throughput calculations combining machine learning to investigate the corrosion properties of binary Mg alloys

Magnesium(Mg)alloys have shown great prospects as both structural and biomedical materials,while poor corrosion resistance limits their further application.In this work,to avoid the time-consuming and laborious experiment trial,a high-throughput computational strategy based on first-principles calculations is designed for screening corrosion-resistant binary Mg alloy with intermetallics,from both the thermodynamic and kinetic perspectives.The stable binary Mg intermetallics with low equilibrium potential difference with respect to the Mg matrix are firstly identified.Then,the hydrogen adsorption energies on the surfaces of these Mg intermetallics are calculated,and the corrosion exchange current density is further calculated by a hydrogen evolution reaction(HER)kinetic model.Several intermetallics,e.g.Y_(3)Mg,Y_(2)Mg and La_(5)Mg,are identified to be promising intermetallics which might effectively hinder the cathodic HER.Furthermore,machine learning(ML)models are developed to predict Mg intermetallics with proper hydrogen adsorption energy employing work function(W_(f))and weighted first ionization energy(WFIE).The generalization of the ML models is tested on five new binary Mg intermetallics with the average root mean square error(RMSE)of 0.11 eV.This study not only predicts some promising binary Mg intermetallics which may suppress the galvanic corrosion,but also provides a high-throughput screening strategy and ML models for the design of corrosion-resistant alloy,which can be extended to ternary Mg alloys or other alloy systems.

Integrating artificial intelligence and high-throughput phenotyping for crop improvement

Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.

Finding biomarkers of experience in animals

At a time when there is a growing public interest in animal welfare,it is critical to have objective means to assess the way that an animal experiences a situation.Objectivity is critical to ensure appropriate animal welfare outcomes.Existing behavioural,physiological,and neurobiological indicators that are used to assess animal welfare can verify the absence of extremely negative outcomes.But welfare is more than an absence of negative outcomes and an appropriate indicator should reflect the full spectrum of experience of an animal,from negative to positive.In this review,we draw from the knowledge of human biomedical science to propose a list of candidate biological markers(biomarkers)that should reflect the experiential state of non-human animals.The proposed biomarkers can be classified on their main function as endocrine,oxidative stress,non-coding molecular,and thermobiological markers.We also discuss practical challenges that must be addressed before any of these biomarkers can become useful to assess the experience of an animal in real-life.

Experimental Investigation on Vertical Hydraulic Transport of Ores in Deepsea Mining

Deepsea mining has been proposed since the 1960s to alleviate the lack of resources on land.Vertical hydraulic transport of collected ores from the seabed to the sea surface is considered the most promising method for industrial applications.In the present study,an indoor model test of the vertical hydraulic transport of particles was conducted.A noncontact optical method has been proposed to measure the local characteristics of the particles inside a vertical pipe,including the local concentration and particle velocity.The hydraulic gradient of ore transport was evaluated with various particle size distributions,particle densities,feeding concentrations and mixture flow velocities.During transport,the local concentration is larger than the feeding concentration,whereas the particle velocity is less than the mixture velocity.The qualitative effects of the local concentration and local fluid velocity on the particle velocity and slip velocity were investigated.The local fluid velocity contributes significantly to particle velocity and slip velocity,whereas the effect of the local concentration is marginal.A higher feeding concentration and mixture flow velocity result in an increased hydraulic gradient.The effect of the particle size gradation is slight,whereas the particle density plays a crucial role in the transport.

Acceptance and Experience of HIV-Infected Adolescents in Two Hospitals in Yaoundé

Introduction: Access to antiretroviral drugs has improved the survival of children infected with the Human Immunodeficiency Virus (HIV). As they reach adolescence, they are confronted with various constraints related to the infection and its treatment, in addition to those of the growth period they are going through. The main aim of the study was to assess the acceptance and describe the experience of HIV infection by infected adolescents but also to investigate the factors associated with good acceptance and a positive experience. Methodology: The cross-sectional analytic study concerned HIV-infected adolescents aged 15 to 19 followed up at the Chantal Biya Foundation-Mother and Child Centre (CME-FCB) and the Yaoundé University Hospital Centre (CHUY) between February 2020 and June 2020. The study saw participants complete a questionnaire containing socio-demographic data and assessing acceptance and experience with the infection. Data analysis was accomplished using Epi info software version 7.2.2.6. Results: One hundred and thirteen HIV-infected adolescents were included in the study. The sex ratio was 0.68 and the mean age was 17 years. More than half of the adolescents had a good acceptance and positive experience with the infection. Related factors were the adolescent’s perception of good health and participation in an association with other infected adolescents. Conclusion: Emphasizing the psychological and educational follow-up of infected adolescents and encouraging their participation in associations for adolescents living with HIV could reduce the consequences of poor acceptance and ensure a better transition to adulthood. .

High-throughput calculation-based rational design of Fe-doped MoS_(2) nanosheets for electrocatalytic p H-universal overall water splitting

Electrocatalytic water splitting is crucial for H2generation via hydrogen evolution reaction(HER)but subject to the sluggish dynamics of oxygen evolution reaction(OER).In this work,single Fe atomdoped MoS_(2)nanosheets(SFe-DMNs)were prepared based on the high-throughput density functional theory(DFT)calculation screening.Due to the synergistic effect between Fe atom and MoS_(2)and optimized intermediate binding energy,the SFe-DMNs could deliver outstanding activity for both HER and OER.When assembled into a two-electrode electrolytic cell,the SFe-DMNs could achieve the current density of 50 mA cm^(-2)at a low cell voltage of 1.55 V under neutral condition.These results not only confirmed the effectiveness of high-throughput screening,but also revealed the excellent activity and thus the potential applications in fuel cells of SFe-DMNs.

High-throughput computational screening and in vitro evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione(C3),as a novel EGFR—HER2 dual inhibitor in gastric tumors

Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.

Multi-environment BSA-seq using large F3 populations is able to achieve reliable QTL mapping with high power and resolution: An experimental demonstration in rice

Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.

Analysis and experimental study on resistance-increasing behavior of composite high efficiency autonomous inflow control device

Bottom water coning is the main reason to reduce the recovery of horizontal bottom water reservoir. By water coning, we mean the oil-water interface changes from a horizontal state to a mound-shaped cone and breaks through to the wellbore. Autonomous inflow control device(AICD) is an important instrument maintain normal production after bottom water coning, however, the resistance increasing ability of the swirl type AICD is insufficient at present, which seriously affects the water control effect. Aiming this problem, this paper designs a multi-stage resistance-increasing and composite type AICD. The separation mechanism of oil-water two phases in this structure, the resistance form of oil-water single phase and the resistance-increasing principle of water phase are analyzed. Establishing the dual-phase multi-stage separation and resistance-increasing model, and verified by measuring the throttling pressure drop and oil-water volume fraction of the AICD, it is found that the composite type AICD has the effect of ICD and AICD at the same time, which can balance the production rate of each well section at the initial stage of production, delay the occurrence of bottom water coning. In the middle and later stages of production, water-blocking can be effectively increased to achieve water control and stable production.After structural sensitivity analysis, the influence law of various structural parameters on the water control performance of composite AICD was obtained. The simulation calculation results show that,compared with the existing swirl type AICD, composite AICD has higher sensitivity to moisture content,the water phase throttling pressure drop is increased by 4.5 times on average. The composite AICD is suitable for the entire stage of horizontal well production.