Facilitated Prediction of Micropollutant Degradation via UV-AOPs in Various Waters by Combining Model Simulation and Portable Measurement

The degradation of micropollutants in water via ultraviolet(UV)-based advanced oxidation processes(AOPs)is strongly dependent on the water matrix.Various reactive radicals(RRs)formed in UV-AOPs have different reaction selectivities toward water matrices and degradation efficiencies for target micropollutants.Hence,process selection and optimization are crucial.This study developed a facilitated prediction method for the photon fluence-based rate constant for micropollutant degradation(K′_(p,MP))in various UV-AOPs by combining model simulation with portable measurement.Portable methods for measuring the scavenging capacities of the principal RRs(RRSCs)involved in UV-AOPs(i.e.,HO^(·),SO_(4)^(·-),and Cl^(·))using a mini-fluidic photoreaction system were proposed.The simulation models consisted of photochemical,quantitative structure–activity relationship,and radical concentration steady-state approximation models.The RRSCs were determined in eight test waters,and a higher RRSC was found to be associated with a more complex water matrix.Then,by taking sulfamethazine,caffeine,and carbamazepine as model micropollutants,the k′_(p,MP) values in various UV-AOPs were predicted and further verified experimentally.A lower k′_(p,MP) was found to be associated with a higher RRSC for a stronger RR competition;for example,k′_(p,MP) values of 130.9 and 332.5 m^(2) einstein^(–1),respectively,were obtained for carbamazepine degradation by UV/H_(2)O_(2) in the raw water(RRSC=9.47×10^(4) s^(-1))and sand-filtered effluent(RRSC=2.87×10^(4) s^(-1))of a drinking water treatment plant.The developed method facilitates process selection and optimization for UV-AOPs,which is essential for increasing the efficiency and cost-effectiveness of water treatment.

Understanding long-term memory in global mean temperature:An attribution study based on model simulations

Long-term memory(LTM)in the climate system has been well recognized and applied in different research fields,but the origins of this property are still not clear.In this work,the authors contribute to this issue by studying model simulations under different scenarios.The global mean temperatures from pre-industrial control runs(pi Control),historical(all forcings)simulations,natural forcing only simulations(Historical Nat),greenhouse gas forcing only simulations(Historical GHG),etc.,are analyzed using the detrended fluctuation analysis.The authors find that the LTM already exists in the pi Control simulations,indicating the important roles of internal natural variability in producing the LTM.By comparing the results among different scenarios,the LTM from the piControl runs is further found to be strengthened by adding natural forcings such as the volcanic forcing and the solar forcing.Accordingly,the observed LTM in the climate system is suggested to be mainly controlled by both the‘internal’natural variability and the‘external’natural forcings.The anthropogenic forcings,however,may weaken the LTM.In the projections from RCP2.6 to RCP8.5,a weakening trend of the LTM strength is found.In view of the close relations between the climate memory and the climate predictability,a reduced predictability may be expected in a warming climate.

Model Simulations of Mesoscale Eddies and Deep Convection in the Labrador Sea

Deep convection in the Labrador Sea is confined within a small region in the southwest part of the basin.The strength of deep convection in this region is related to the local atmospheric and ocean characteristics,which favor processes of deep convection preconditioning and intense air-sea exchange during the winter season.In this study,we explored the effect of eddy-induced flux transport on the stratification of the Labrador Sea and the properties of deep convection.Simulations from an eddy-resolving ocean model are presented for the Labrador Sea.The general circulation was well simulated by the model,including the seasonal cycle of the deep Labrador Current.The simulated distribution of the surface eddy kinetic energy was also close to that derived from Topex-Poseidon satellite altimeter data,but with smaller magnitude.The energy transfer diagnostics indicated that Irminger rings are generated by both baroclinic and barotropic processes; however,when they propagate into the interior basin,the barotropic process also disperses them by converting the eddy energy to the mean flow.In contrast to eddy-permitting simulations,deep convection in the Labrador Sea was better represented in the eddyresolving model regarding their lateral position.Further analysis indicated that the improvement might be due to the lateral eddy flux associated with the resolved Irminger rings in the eddy-resolving model,which contributes to a realistic position of the isopycnal dome in the Labrador Sea and correspondingly a realistic site of deep convection.

Model simulations to determine optimal fishing effort and season duration for a tropical shrimp fishery

Kuwait's shrimp fishery presents typical tropical shrimp fishery characteristics with highly variable recruitment, fast growth and strong seasonal patterns. Both the General Production Model and Age-structured Model were chosen to assess the stock status of the Kuwait's shrimp fishery. The estimated Maximum Sustainable Yield(MSY) was 2 518 metric ton(t) with a corresponding fishing eff orts( f MSY) 7 265 standard boat-days from the General Production Model. Similar results from the Age-structured Model were 1 936 t and 6 449 boat-days respectively. Comparing these results with the average annual shrimp landings(1 772 t) and average fishing eff ort(9 710 boat-days) in the past 10 years, we concluded that the fishery was overfished. Model simulations to show the changes of recruitment, biomass and possible catch under different fishing eff ort scenarios indicated possible stock collapse if the fishing eff ort continually increase. But both shrimp recruitment and biomass will increase if the current fishing eff ort is reduced. Model simulations also showed a possible increase of MSY by delaying the opening or by closing the season earlier. Based on these results, recommendations to improve the management of Kuwait's shrimp fishery are presented.

Adsorption and Step Elution of Urokinase Using Affinity Chromatography-Comparison of Data with Rate Model Simulation

A non-equilibrium chromatographic rate model was employed to simulate the affinity chromatography of urokinase. The chromatography process was developed to a yield of high purity product of urokinase from crude materials. The affinity gel used in the process was prepared by an epichlorohydrin-activation method using epichlorohydrin activated Sepharose 4B as a matrix and p-aminobenzamidine as a ligand. The chromatographic process were numerically simulated and analyzed with the aid of VERSE-LC computer simulator. Considering the basic principles, rate model with the back mixing in column inlet was utilized in simulating and studying the effect of the column inlet pattern on other parameters. Comparison of the simulation results with the experimental data showed that the rate model can be used to describe the affinity chromatography of urokinase in a fixed bed column with satisfactory accuracy.

Assessing Drought Vulnerability of Bulgarian Agriculture through Model Simulations

This study assesses vulnerability of agriculture to drought, using WINISAREG model and seasonal SPI2-index for eight climate regions （1951-2004）. Results relative to Plovdiv show that in soils of large TAW （total available water） net irrigation requirements NIRs range from 0 to 380 mm. In soils of small TAW, NIRs reach 440 mm in the very dry year. NIRs in Sofia/Silistra are about 100 mm smaller than in Plovdiv while in Sandanski they are 30-110 mm larger. Rainfed maize is associated with great yield variability （29% 〈 Cv 〈 72%）. Considering an economical RYD （relative yield decrease） threshold, 32% of years are risky when TA Wis large in Plovdiv that is double than in Sofia and half than in Sandanski. In North Bulgaria the risky years are 10% in Pleven/Silistra that is half than in Lom. In Plovdiv region reliable relationships （R2 〉 91%） were found relating the SPI2 ＂July-Aug.＂ with simulated RYD of rainfed maize while remaining relationships were less accurate （73% 〈 R2 〈 86%）. Economical losses are produced when High Peak Season SPI2 〈 ＋ 0.20 in Sandanski, SPI2 〈 - 0.50 in Plovdiv and SPI2 〈 - 0.90 in Sofia. In North Bulgaria the SPI2 threshold ranges from - 0.75 to - 1.50. Derived reliable relationships and SPl-thresholds are used for drought vulnerability mapping.

Diagnostic of capacitively coupled radio frequency plasma from electrical discharge characteristics：comparison with optical emission spectroscopy and fluid model simulation

The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.

Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.

Application of Patient Simulators Combined with Internet plus Scenario Simulation Teaching Models on Intravenous Infusion Nursing Education in China

Objective: To explore the effectiveness of applying patient simulators combined with Internet Plus scenario simulation teaching models on intravenous (IV) infusion nursing education, and to provide scientific evidence for the implementation of advanced teaching models in future nursing education. Methods: Enrolled 60 nurses who took the IV infusion therapy training program in our hospital from January 2022 to December 2023 for research. 30 nurses who were trained in traditional teaching models from January to December 2022 were selected as the control group, and 30 nurses who were trained with simulation-based teaching models with methods including simulated patients, internet, online meetings which can be replayed and scenario simulation, etc. from January to December 2023 were selected as the experimental group. Evaluated the learning outcomes based on the Competency Inventory for Nursing Students (CINS), Problem-Solving Inventory (PSI), comprehensive learning ability, scientific research ability, and proficiency in the theoretical knowledge and practical skills of IV infusion therapy. Nursing quality, the incidence of IV infusion therapy complications and nurse satisfaction with different teaching models were also measured. Results: The scientific research ability, PSI scores, CINS scores, and comprehensive learning ability of the experimental group were better than those of the control group (P 0.05), and their assessment results of practical skills, nursing quality of IV infusion therapy during training, and satisfaction with teaching models were all better than those of the control group with statistical significance (P < 0.05). The incidence of IV infusion therapy complications in the experimental group was lower than that in the control group, indicating statistical significance (P < 0.05). Conclusions: Teaching models based on patient simulators combined with Internet Plus scenario simulation enable nursing students to learn more directly and practice at any time and in any place, and can improve their proficiency in IV infusion theoretical knowledge and skills (e.g. PICC catheterization), core competencies, problem-solving ability, comprehensive learning ability, scientific research ability and the ability to deal with complicated cases. Also, it helps provide high-quality nursing education, improve the nursing quality of IV therapy, reduce the incidence of related complications, and ensure the safety of patients with IV therapy.

Multi-scenario Simulation and Spatial-temporal Analysis of LUCC in China's Coastal Zone Based on Coupled SD-FLUS Model

Increased human activities in China's coastal zone have resulted in the depletion of ecological land resources.Thus,conducting current and future multi-scenario simulation research on land use and land cover change(LUCC)is crucial for guiding the healthy and sustainable development of coastal zones.System dynamic(SD)-future land use simulation(FLUS)model,a coupled simulation model,was developed to analyze land use dynamics in China's coastal zone.This model encompasses five scenarios,namely,SSP1-RCP2.6(A),SSP2-RCP4.5(B),SSP3-RCP4.5(C),SSP4-RCP4.5(D),and SSP5-RCP8.5(E).The SD model simulates land use demand on an annual basis up to the year 2100.Subsequently,the FLUS model determines the spatial distribution of land use for the near term(2035),medium term(2050),and long term(2100).Results reveal a slowing trend in land use changes in China's coastal zone from 2000–2020.Among these changes,the expansion rate of construction land was the highest and exhibited an annual decrease.By 2100,land use predictions exhibit high accuracy,and notable differences are observed in trends across scenarios.In summary,the expansion of production,living,and ecological spaces toward the sea remains prominent.Scenario A emphasizes reduced land resource dependence,benefiting ecological land protection.Scenario B witnesses an intensified expansion of artificial wetlands.Scenario C sees substantial land needs for living and production,while Scenario D shows coastal forest and grassland shrinkage.Lastly,in Scenario E,the conflict between humans and land intensifies.This study presents pertinent recommendations for the future development,utilization,and management of coastal areas in China.The research contributes valuable scientific support for informed,long-term strategic decision making within coastal regions.

Application of Modelica Based Multi- Domain Modeling and Simulation for Gravity-1

In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.

Multi-agent Based Hierarchy Simulation Models of Carrier-based Aircraft Catapult Launch

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.

Quantifying the Cloud Water Resource:Methods Based on Observational Diagnosis and Cloud Model Simulation

Based on the concepts of cloud water resource(CWR)and related variables proposed in the first part of this study,this paper provides details of two methods to quantify the CWR.One is diagnostic quantification(CWR-DQ)based on satellite observations,precipitation products,and atmospheric reanalysis data;and the other is numerical quantification(CWR-NQ)based on a cloud resolving model developed at the Chinese Academy of Meteorological Sciences(CAMS).The two methods are applied to quantify the CWR in April and August 2017 over North China,and the results are evaluated against all available observations.Main results are as follows.(1)For the CWR-DQ approach,reference cloud profiles are firstly derived based on the Cloud Sat/CALIPSO joint satellite observations for 2007–2010.The NCEP/NCAR reanalysis data in 2000–2017 are then employed to produce three-dimensional cloud fields.The budget/balance equations of atmospheric water substance are lastly used,together with precipitation observations,to retrieve CWR and related variables.It is found that the distribution and vertical structure of clouds obtained by the diagnostic method are consistent with observations.(2)For the CWR-NQ approach,it assumes that the cloud resolving model is able to describe the cloud microphysical processes completely and precisely,from which four-dimensional distributions of atmospheric water vapor,hydrometeors,and wind fields can be obtained.The data are then employed to quantify the CWR and related terms/quantities.After one-month continuous integration,the mass of atmospheric water substance becomes conserved,and the tempospatial distributions of water vapor,hydrometeors/cloud water,and precipitation are consistent with observations.(3)Diagnostic values of the difference in the transition between hydrometeors and water vapor(Cvh-Chv)and the surface evaporation(Es)are well consistent with their numerical values.(4)Correlation and bias analyses show that the diagnostic CWR contributors are well correlated with observations,and match their numerical counterparts as well,indicating that the CWR-NQ and CWR-DQ methods are reasonable.(5)Underestimation of water vapor converted from hydrometeors(Chv)is a shortcoming of the CWR-DQ method,which may be rectified by numerical quantification results or by use of advanced observations on higher spatiotemporal resolutions.

DYNAMIC MODEL AND SIMULATION OF A NOVEL ELECTRO-HYDRAULIC FULLY VARIABLE VALVE SYSTEM FOR FOUR-STROKE AUTOMOTIVE ENGINES

In modem four-stroke engine technology, variable valve timing and lift control offers potential benefits for making a high-performance engine. A novel electro-hydraulic fully variable valve train for four-stroke automotive engines is introduced. The construction of the nonlinear mathematic model of the valve train system and its dynamic analysis are also presented. Experimental and simulation results show that the novel electro-hydraulic valve train can achieve fully variable valve timing and lift control. Consequently the engine performance on different loads and speeds will be significantly increased. The technology also permits the elimination of the traditional throttle valve in the gasoline engines and increases engine design flexibility.

Numerical simulation of typhoon- induced storm surge on the coast of Jiangsu Province,China,based on coupled hydrodynamic and wave models

In order to facilitate engineering design and coastal flooding protection, the potential storm surge induced by a typhoon is studied.Using an unstructured mesh, a coupled model which combines the advanced circulation （ ADCIRC ） hydrodynamic model and simulating waves nearshore （ SWAN ） model is applied to analyze the storm surge and waves on the coast of Jiangsu Province.The verifications of wind velocity, tidal levels and wave height show that this coupling model performs well to reflect the characteristics of the water levels and waves in the studied region.Results show that the effect of radiation stress on storm surge is significant, especially in shallow areas such as the coast of Jiangsu Province and the Yangtze estuary.By running the coupled model, the simulated potential flooding results can be employed in coastal engineering applications in the Jiangsu coastal area, such as storm surge warnings and extreme water level predictions.

Two-Dimensional Static Numerical Modeling and Simulation of AlGaN/GaN HEMT

AIGaN/GaN HEMTs are investigated by numerical simulation from the self-consistent solution of Schr6dinger-Poisson-hydrodynamic （HD） systems. The influences of polarization charge and quantum effects are considered in this model. Then the two-dimensional conduction band and electron distribution, electron temperature characteristics, Id versus Vd and Id versus Vg, transfer characteristics and transconductance curves are obtained. Corresponding analysis and discussion based on the simulation results are subsequently given.

Methods of Validating Simulation Model and Program Design

Validating simulation model is one of the important aspects for modeling and simulation. Some methods of validating model are compared and analyzed. Several typical methods, such as TIC’s inequality coefficient, gray interconnected analysis, direct spectrum estimation, maximum entropy spectral estimation based on Burg or Marple, are chosen and programmed in C language. Some examples by using the program are given. The results show that the program is available and it is best to adopt multi methods for validating models.

Quantifying Responses of Winter Wheat Physiological Processes to Soil Water Stress for Use in Growth Simulation Modeling

A deep understanding of crop-water eco-physiological relations is the basis for quantifying plant physiological responses to soil water stress. Pot experiments were conducted to investigate the winter wheat crop-water relations under both drought and waterlogging conditions in two sequential growing seasons from 2000 to 2002, and then the data were used to develop and validate models simulating the responses of winter wheat growth to drought and waterlogging stress. The experiment consisted of four treatments, waterlogging (keep 1 to 2 cm water layer depth above soil surface), control (70%-80% field capacity), light drought (40%-50% field capacity) and severe drought (30%-40% field capacity) with six replicates at five stages in the 2000-2001 growth season. Three soil water content treatments (waterlogging, control and drought) with two replicates were designed in the 2001-2002 growth season. Waterlogging and control treatments are the same as in the 2000-2001 growth season. For the drought treatment, no water was supplied and the soil moisture decreased from field capacity to wilting point. Leaf net photosynthetic rate, transpiration rate, predawn leaf water potential, soil water potential, soil water content and dry matter weight of individual organs were measured. Based on crop-water eco-physiological relations, drought and waterlogging stress factors for winter wheat growth simulation model were put forward. Drought stress factors integrated soil water availability, the sensitivity of different development stages and the difference between physiological processes (such as photosynthesis, transpiration and partitioning). The quantification of waterlogging stress factor considered different crop species, soil water status, waterlogging days and sensitivity at different growth stages. Data sets from the pot experiments revealed favorable performance reliability for the simulation sub-models with the drought and waterlogging stress factors.

Rice Yield Estimation by Integrating Remote Sensing with Rice Growth Simulation Model

Since remote sensing can provide information on the actual status of an agricultural crop, the integration between remote sensing data and crop growth simulation models has become an important trend for yield estimation and prediction.The main objective of this research was to combine a rice growth simulation model with remote sensing data to estimate rice grain yield for different growing seasons leading to an assessment of rice yield at regional levels. Integration between NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) data and the rice growth simulation model ORYZA1 to develop a new software, which was named as Rice-SRS Model, resulted in accurate estimates for rice yield in Shaoxing, China, with an estimation error reduced to 1.03% and 0.79% over-estimation and 0.79% under-estimation for early, single and late season rice, respectively. Selecting suitable dates for remote sensing images was an important factor which could influence estimation accuracy. Thus, given the different growing periods for each rice season, four images were needed for early and late rice, while five images were preferable for single season rice.Estimating rice yield using two or three images was possible, however, if images were obtained during the panicle initiation and heading stages.