Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.

Comparison of WRF Model Physics Parameterizations over the MENA-CORDEX Domain

We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinations among two Planetary Boundary Layer (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The 2-year simulations (December 1988-November 1990) have been compared with gridded observational data and station measurements for several variables, including total precipitation and maximum and minimum 2-meter air temperature. An objective ranking method of the 12 different simulations and the selection procedure of the best performing configuration for the MENA domain are based on several statistical metrics and carried out for relevant sub-domains and individual stations. The setup for cloud microphysics is found to have the strongest impact on temperature biases while precipitation is most sensitive to the cumulus parameterization scheme and mainly in the tropics.

Inter-comparisons of thermodynamic sea-ice modeling results using various parameterizations of radiative flux

Radiative fluxes are of primary importance in the energy and mass balance of the sea-ice cover. Various parameterizations of the radiative fluxes are studied in a thermodynamic sea-ice model. Model outputs of the surface radiative and heat fluxes and mass balance are compared with observations. The contribution of short-wave radiation is limited to a long part of winter. Therefore, simple schemes are often sufficient. Errors in estimations of the short-wave radiation are due mainly to cloud effects and occasionally to multi-reflection between surface and ice crystals in the air. The long-wave radiation plays an important role in the ice surface heat and mass balance during most part of a winter. The effect of clouds on the accuracy of the simple radiative schemes is critical, which needs further attention. In general, the accuracy of an ice model depends on that of the radiative fluxes.

Parameterizations of Surface Radiation in the Semiarid Grasslands of Inner Mongolia under Clear-Sky Conditions Using MODIS Data

A set of improved and efficient radiation parameterization schemes for surface radiation balance components under clear- sky conditions was developed by using general surface measurements and MODIS data. The set of schemes was then adapted for regions similar to the present study sites under different grazing intensities and varying degrees of drought in the semiarid grasslands of Inner Mongolia. Specifically, we mainly improved two schemes for estimating downward shortwave and longwave radiation at the surface, which could be applied to regions with certain degrees of drought. The validation datasets were from ground-based observations at various grazing sites during the growing season （May to September） of different drought years, 2005 and 2006. Through comparisons of parameterized versus measured radiation values, the increased or modified factors in the original schemes demonstrated improved estimation accuracy, and the rationalities of input parameters and variables were analyzed. The regional instantaneous net radiation estimations had root-mean-square errors of less than 30 W m-2 compared with ground measurements at the sites during the study period. The statistical results showed the improved schemes are suitable for estimating surface net radiation in regional semiarid areas during the growing season. Analyses of the sensitivity of the schemes to corresponding variables were conducted to ascertain the major error sources of the schemes and potential variables for improving the performance of the schemes in agreement with observations.

Observational Diagnosis of Cloud Phase in the Winter Antarctic Atmosphere for Parameterizations in Climate Models

The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer （MODIS） and Cloud-Aerosol Lidar with Orthogonal Polarization （CALIOP） instruments for the period 2000-2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months （June, July, and August） reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0°C. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ～20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs （ -40°C） for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.

THE IMPACT OF CUMULUS PARAMETERIZATIONS AND MICROPHYSICS SCHEMES UNDER DIFFERENT COMBINATIONS ON TYPHOON TRACK PREDICTION

This study examines the effects of cumulus parameterizations and microphysics schemes on the track forecast of typhoon Nabi using the Weather Research Forecast model. The study found that the effects of cumulus parameterizations on typhoon track forecast were comparatively strong and the typhoon track forecast of Kain-Fritsch (KF) was superior to that of Betts-Miller (BM). When KF was selected, the simulated results would be improved if microphysics schemes were selected than otherwise. The results from Ferrier, WSM6, and Lin were very close to those in the best track. KF performed well with the simulations of the western extension and eastern contraction changes of a North Pacific high as well as the distribution and strength of the typhoon wind field.

Impacts of salinity parameterizations on temperature simulation over and in a hypersaline lake

In this paper,we introduced parameterizations of the salinity effects(on heat capacity,thermal conductivity,freezing point and saturated vapor pressure) in a lake scheme integrated in the Weather Research and Forecasting model coupled with the Community Land Model(WRF-CLM). This was done to improve temperature simulation over and in a saline lake and to test the contributions of salinity effects on various water properties via sensitivity experiments. The modified lake scheme consists of the lake module in the CLM model,which is the land component of the WRF-CLM model. The Great Salt Lake(GSL) in the USA was selected as the study area. The simulation was performed from September 3,2001 to September 30,2002. Our results show that the modif ied WRF-CLM model that includes the lake scheme considering salinity effects can reasonably simulate temperature over and in the GSL. This model had much greater accuracy than neglecting salinity effects,particularly in a very cold event when that effect alters the freezing point. The salinity effect on saturated vapor pressure can reduce latent heat flux over the lake and make it slightly warmer. The salinity effect on heat capacity can also make lake temperature prone to changes. However,the salinity effect on thermal conductivity was found insignificant in our simulations.

Sensitivity Analysis of Ensemble Simulations on a Torrential Rainfall Case over South China Using Multiple PBL and SL Parameterizations

A good representation of the interaction between the planetary boundary layer(PBL)and the surface layer(SL)in numerical models is of great importance for the prediction of the initiation and development of convection.This study examined an ensemble that consists of the available suites of PBL and SL parameterizations based on a torrential rainfall event over south China.The sensitivity of the simulations was investigated against objective measurements using multiple PBL and SL parameterization schemes.The main causes of the bias from different parameterization schemes were further analysed by comparing the good and bad ensemble members.The results showed that good members tended to underestimate the rainfall amount but presented a decent evolution of mesoscale convective systems that were responsible for the torrential rainfall.Using the total energy mass flux(TEMF)scheme,the bad members overestimated the amount and spatial coverage of rainfall.The failure of the bad member was due to a spurious convection initiation(CI)resulting from the overestimated high-θe elevated air.The spurious CI developed and expanded rapidly,causing intensive and extensive rainfall over south China.Consistent with previous studies,the TEMF scheme tends to produce a warmer and moister PBL environment.The detailed sensitivity analysis of this case may provide reference for the operational forecast of rainfall over south China using multiple PBL and SL parameterizations.

Dark Parameterizations,Equivalent Partner Fields and Integrable Systems

After introducing dark parameters into the traditional physical models, some types of new phenomena may be found. An important difficult problem is how to directly observe this kind of physical phenomena. An alternative treatment is to introduce equivalent multiple partner fields. If use this ideal to integrable systems, one may obtain infinitely many new coupled integrable systems constituted by the original usuM field and partner fields. The idea is illustrated via the celebrate KdV equation. From the procedure, some byproducts can be obtained： A new method to find exact solutions of some types of coupled nonlinear physical problems, say, the perturbation KdV systems, is provided; Some new localized modes such as the staggered modes can be found and some new interaction phenomena like the ghost interaction are discovered.

Evaluating Parameterizations for Turbulent Fluxes over the Landfast Sea-Ice Surface in Prydz Bay, Antarctica

It is crucial to appropriately determine turbulent fluxes in numerical models.Using data collected in East Antarctica from 8 April to 26 November 2016,this study evaluates parameterization schemes for turbulent fluxes over the landfast seaice surface in five numerical models.The Community Noah Land Surface Model with Multi-Parameterizations Options(Noah_mp)best replicates the turbulent momentum flux,while the Beijing Climate System Model(BCC_CSM)produces the optimum sensible and latent heat fluxes.In particular,two critical issues of parameterization schemes,stability functions and roughness lengths,are investigated.Sensitivity tests indicate that roughness lengths play a decisive role in model performance.Based on the observed turbulent fluxes,roughness lengths over the landfast sea-ice surface are calculated.The results,which can provide a basis for setting up model parameters,reveal that the dynamic roughness length(z0m)increases with the increase of frictional velocity(u*)when u*≤0.4 m s^(−1) and fluctuates around 10^(−3 )m when u*>0.4 m s^(−1);thermal roughness length(z0t)is linearly related to the temperature gradient between air and sea-ice surface(ΔT)with a relation of lg(z0t)=−0.29ΔT−3.86;and the mean water vapor roughness length(z0q)in the specific humidity gradient(Δq)range ofΔq≤−0.6 g kg^(−1) is 10^(−6) m,3.5 times smaller than that in the range ofΔq˃−0.6 g kg^(−1).

Validation for a tropical belt version of WRF: sensitivity tests on radiation and cumulus convection parameterizations

Version 3.9 of WRF-ARW is run with a tropical belt configuration for a period from 2012 to 2016 in this study. The domain covers the entire tropics between 45°S and 45°N with a spatial resolution of about 45 km. In order to verify two radiation schemes and four cumulus convection schemes, eight experiments are performed with different combinations of physics parameterization schemes. The results show that eight experiments present reasonable spatial patterns of surface air temperature and precipitation in boreal summer, with the spatial correlation coefficient (COR) between simulated and observed temperature exceeding 0.95, and that between simulated and observed precipitation ranges from 0.65 to 0.82. The four experiments with the RRTMG radiation scheme show a better performance than the other four experiments with the CAM radiation scheme. In the four experiments with the RRTMG radiation scheme, the COR between simulated and observed surface air temperature is about 0.98, and that between simulated and observed precipitation ranges from 0.76 to 0.82. Comparatively, the two experiments using the new Tiedtke cumulus parameterization scheme can simulate better diurnal variation of precipitation in boreal summer than the other six experiments. In particular, for the diurnal cycle of precipitation over land and ocean, the experiment using the RRTMG radiation scheme and the new Tiedtke cumulus convection scheme shows that the peaks of precipitation rate appear at 0400 LST and 1600 LST, in agreement with observation.

Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

Performance Evaluation of Three Parameterizations on Internal Tidal Mixing in the Northern Pacific

The accurate assessment of the energy dissipation of internal tides(ITs)is of great importance because ITs contribute significantly to abyssal mixing.Thus,in this study,the IT-driven dissipation and diapycnal diffusion in the northern Pacific are esti-mated using parameterizations proposed by St.Laurent et al.(2002),Koch-Larrouy et al.(2007),and de Lavergne et al.(2020)(hereaf-ter referred to as LSJ02,KL07,and dL20,respectively).The performances of the three parameterizations are evaluated by comparing the calculated results with fine structure observations.In particular,the dissipation estimated by LSJ02 parameterization shows a bottom-intensified characteristic,with the patterns showing good agreement with the observations near seamounts.Moreover,43%of the results calculated using the LSJ02 parameterization have errors lower than one order of magnitude in the generation sites of ITs.Meanwhile,the strongest dissipation estimated by the KL07 parameterization shifts to the thermocline,with the results showing the highest level of consistency with observations in the generation sites.The proportion of results with errors lower than one order of magnitude is 80.7%.Furthermore,the results calculated by dL20 parameterization agree well with the observations in the upper and middle layers,with the parameterization showing an accurate estimation of the remote dissipation.The percentages of the errors lower than one order of magnitude between the dL20 parameterization and observations account for 77.1%and 88.7%in the genera-tion sites and far-field regions,respectively.

A Novel On-Site-Real-Time Method for Identifying Characteristic Parameters Using Ultrasonic Echo Groups and Neural Network

On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.

Skeleton-Based Volumetric Parameterizations for Lattice Structures

Lattice structures with excellent physical properties have attracted great research interest.In this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice structures.The skeleton model is divided into three types of nodes.And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes.The unit-cell is assembled with distinct nodes according to the geometric features.The final lattice structure is created by the periodic arrangement of unit-cells.Several different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed method.The quality is assessed in terms of the value of the Jacobian matrix.Moreover,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.

Effect of Different Microphysical Parameterizations on the Simulations of a South China Heavy Rainfall

A heavy rainfall event in south China was simulated by the Weather Research and Forecasting(WRF) model with three microphysics schemes, including the Morrison scheme, Thompson scheme, and Milbrandt and Yau scheme(MY), which aim to evaluate the capability to reproduce the precipitation and radar echo reflectivity features, and to evaluate evaluate their differences in microphysics and the associated thermodynamical and dynamical feedback. Results show that all simulations reproduce the main features crucial for rainfall formation. Compared with the observation, the MY scheme performed better than the other two schemes in terms of intensity and spatial distribution of rainfall. Due to abundant water vapor, the accretion of cloud droplets by raindrops was the dominant process in the growth of raindrops while the contribution of melting was a secondary effect. Riming processes, in which frozen hydrometeors collect cloud droplets mainly, contributed more to the growth of frozen hydrometeors than the Bergeron process. Extremely abundant snow and ice were produced in the Thompson and MY schemes respectively by a deposition process. The MY scheme has the highest condensation and evaporation, but the lowest deposition. As a result, in the MY scheme, the enhanced vertical gradient of condensation heating and evaporation cooling at low levels produces strong positive and weak negative potential vorticity in Guangdong, and may favor the formation of the enhanced rainfall center over there.

Transient elastography with controlled attenuation parameter for the diagnosis of colorectal polyps in patients with nonalcoholic fatty liver disease

BACKGROUND The severity of nonalcoholic fatty liver disease(NAFLD)and lipid metabolism are related to the occurrence of colorectal polyps.Liver-controlled attenuation parameters(liver-CAPs)have been established to predict the prognosis of hepatic steatosis patients.AIM To explore the risk factors associated with colorectal polyps in patients with NAFLD by analyzing liver-CAPs and establishing a diagnostic model.METHODS Patients who were diagnosed with colorectal polyps in the Department of Gastroenterology of our hospital between June 2021 and April 2022 composed the case group,and those with no important abnormalities composed the control group.The area under the receiver operating characteristic curve was used to predict the diagnostic efficiency.Differences were considered statistically significant when P<0.05.RESULTS The median triglyceride(TG)and liver-CAP in the case group were significantly greater than those in the control group(mmol/L,1.74 vs 1.05;dB/m,282 vs 254,P<0.05).TG and liver-CAP were found to be independent risk factors for colorectal polyps,with ORs of 2.338(95%CI:1.154–4.733)and 1.019(95%CI:1.006–1.033),respectively(P<0.05).And there was no difference in the diagnostic efficacy between liver-CAP and TG combined with liver-CAP(TG+CAP)(P>0.05).When the liver-CAP was greater than 291 dB/m,colorectal polyps were more likely to occur.CONCLUSION The levels of TG and liver-CAP in patients with colorectal polyps are significantly greater than those patients without polyps.Liver-CAP alone can be used to diagnose NAFLD with colorectal polyps.

Parameter-Free Shifted Laplacian Reconstruction for Multiple Kernel Clustering

Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian reconstruction.Traditional MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.