QSAR Study of Nitrobenzenes’ Toxicity to Tetrahymena Pyriformis Using Semi-empirical Quantum Chemical Methods

The molecular geometries and electronic structures of 30 nitrobenzenes have been calculated by using semi-empirical MO AM1 and PM3 methods. EHOMO, ELUMO, ENHOMO, ENLUMO, AE, QNO2, Qc and V were selected as the structural descriptors. The acute toxicity （-log/C50） of nitrobenzenes to tetrahymena pyriformis along with the above eight structural parameters was used to establish the quantitative structure-activity relationships （QSARs）. The results indicate that the established model based on AM I method is superior to that on PM3 method not only for the stability but also for the predictive powers of the model. Based on AM1 parameters, a further classifying discussion was presented for the study of nitrobenzene toxic mechanism. The results show that the substituents, nitro group and halogen substituents on the aromatic ring are crucial to the chemicals＇ toxicity. For nitrobenzenes without halogen or other substituent, the reduction of nitro group is the main route. However, for those with halogen substituents, their next lowest unoccupied molecular orbital may take part in the toxic action betweeen the chemicals and macromolecules, and ENLUMO has the most important effect on these chemicals＇ toxicity.

Relationships between moment magnitude and fault parameters:theoretical and semi-empirical relationships

Fault parameters are important in earthquake hazard analysis.In this paper,theoretical relationships between moment magnitude and fault parameters including subsurface rupture length,downdip rupture width,rupture area,and average slip over the fault surface are deduced based on seismological theory.These theoretical relationships are further simplified by applying similarity conditions and an unique form is established.Then,combining the simplified theoretical relationships between moment magnitude and fault parameters with seismic source data selected in this study,a practical semi-empirical relationship is established.The seismic source data selected is also to used to derive empirical relationships between moment magnitude and fault parameters by the ordinary least square regression method.Comparisons between semi-empirical relationships and empirical relationships show that the former depict distribution trends of data better than the latter.It is also observed that downdip rupture widths of strike slip faults are saturated when moment magnitude is more than 7.0,but downdip rupture widths of dip slip faults are not saturated in the molnent magnitude rangcs of this study.

Towards a semi-empirical model of the sea ice thickness based on hyperspectral remote sensing in the Bohai Sea

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness（SEMSIT） that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands（spectral dimension information） are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.

Comparative Study among Different Semi-Empirical Models for Soil Salinity Prediction in an Arid Environment Using OLI Landsat-8 Data

Salt-affected soils, caused by natural or human activities, are a common environmental hazard in semi-arid and arid landscapes. Excess salts in soils affect plant growth and production, soil and water quality and, therefore, increase soil erosion and land degradation. This research investigates the performance of five different semi-empirical predictive models for soil salinity spatial distribution mapping in arid environment using OLI sensor image data. This is the first attempt to test remote sensing based semi-empirical salinity predictive models in this area: the Kingdom of Bahrain. To achieve our objectives, OLI data were standardized from the atmosphere interferences, the sensor radiometric drift, and the topographic and geometric distortions. Then, the five semi-empirical predictive models based on the Normalized Difference Salinity Index (NDSI), the Salinity Index-ASTER (SI-ASTER), the Salinity Index-1 (SI-1), the Soil Salinity and Sodicity Index-1 and Index-2 (SSSI-1 and SSSI-2), developed for slight and moderate salinity in agricultural land, were implemented and applied to OLI image data. For validation purposes, a fieldwork was organized and different important spots-locations representing different salinity levels were visited, photographed, and localized using an accurate GPS (σ ≤ ±30 cm). Based on this a priori knowledge of the soil salinity, six validation sites were selected to reflect non-saline, low, moderate, high and extreme salinity classes, descriptive statistics extracted from polygons and/or transects over these sites were used. The obtained results showed that the models based on NDSI, SI-1 and SI-ASTER all failed to detect salinity bounds for both extreme salinity (Sabkhah) and non-saline conditions. In Fact, NDSI and SI-ASTER gave respectively only 35% dS/m and 25% dS/m in extreme salinity validation site, while SI-1 and SI-ASTER indicated 38% dS/m and 39% dS/m in non-saline validation site. Therefore, these three models were deemed inadequate for the study site. However, both SSSI-1 and SSSI-2 allowed a detection of the previous salinity bounds and furthermore described similarly and correctly the urban-vegetation areas and the open-land areas. Their predicted EC is around 10% dS/m for non-saline urban soil, about 25% dS/m for low salinity urban-vegetation soil, approximately 30% to 75% dS/m, respectively, for moderate to high salinity soils. SSSI-2 based semi-empirical salinity models was able to differentiate the high salinity versus extreme salinity in areas where both exist and was very accurate to highlight the pure salt where SSSI-1 has reach saturation for both salinity classes. In conclusion, reliable salinity map was produced using the model based on SSSI-2 and OLI sensor data that allows a better characterization of the soil salinity problem in an Arid Environment.

A semi-empirical formula for evaluating residual strain of soils under earthquake loading

A new semi-empirical formula for evaluating the residual strain of soils under earthquake loading is presented in this paper based on the incremental method and the increment model proposed by the authors.When the incident loading is uniform,the results calculated by the new formula are nearly the same as those by the existing formula.For excitation of the random earthquake loading,the results calculated by the new formula are compared to the results obtained by dynamic triaxial tests.The dynamic triaxial tests had been performed considering different seismic waves,confining stresses, consolidation ratios,and types of cohesive soils.The comparison between the calculated and tested results indicate that the presented formula can efficiently and practically describe the time-dependent process of the soil residual strains under actual seismic loads.

An improved semi-empirical friction model for gas-liquid two-phase flow in horizontal and near horizontal pipes

Pressure drop and liquid hold-up are two very important fluid flow parameters in design and control of multiphase flow pipelines.Friction factors play an important role in the accurate calculation of pressure drop.Various empirical and semi-empirical closure relations exist in the literature to calculate the liquid-wall,gas-wall and interfacial friction in two-phase pipe flow.However most of them are empirical correlations found under special experimental conditions.In this paper by modification of a friction model available in the literature,an improved semiempirical model is proposed.The proposed model is incorporated in the two-fluid correlations under equilibrium conditions and solved.Pressure gradient and velocity profiles are validated against experimental data.Using the improved model,the pressure gradient deviation from experiments diminishes by about 3%;the no-slip condition at the interface is satisfied and the velocity profile is predicted in better agreement with the experimental data.

Adaptive semi-empirical model for non-contact atomic force microscopy

Non-contact atomic force microscope is a powerful tool to investigate the surface topography with atomic resolution.Here we propose a new approach to estimate the interaction between its tips and samples,which combines a semi-empirical model with density functional theory(DFT)calculations.The generated frequency shift images are consistent with the experiment for mapping organic molecules using CuCO,Cu,CuCl,and CuO_(x)tips.This approach achieves accuracy close to DFT calculation with much lower computational cost.

Simulation of a DI Diesel Engine Performance Fuelled on Biodiesel Using a Semi-Empirical 0D Model

Diesel engines have proven over the years important in terms of efficiency and fuel consumption to power generation ratio. Many research works show the potential of biodiesel as a substitute for conventional gasoil. Mainly, previous and recent researches have focused on experimental investigation of diesel engine performance fuelled by biodiesel. Researches on the mathematical description of diesel engine process running on biodiesel are scarce, and mostly about chemical and thermodynamic description of the combustion process of biodiesel rather than performance studies. This work describes a numerical investigation on the performance analysis of a diesel engine fuelled by palm oil biodiesel. The numerical investigation was made using a semi empirical 0D model based on Wiebe’s and Watson’s model which was implemented via the open access numerical calculation software Scilab. The model was validated first by comparing with experimental pressure and performance data of a one cylinder engine at rated speed and secondly by comparing with a six cylinders engine performance data at various crankshaft rotational speeds. Simulations were then made to analyze the engine performance when running on biodiesel. The calculations were made at constant combustion duration and constant coefficient of excess air. Results showed that the model matches the overall experimental data, such as the power output and peak cylinder pressure. The ignition delay was somehow underestimated by the model for the first experiment, which caused a slight gap on in cylinder pressure curve, whereas it predicted the average ignition delay fairly well for the second set of validation. The simulations of engine performance when running on biodiesel confirmed results obtained in previous experimental researches on biodiesel. The model will be further investigated for engine control when shifting to biodiesel fuel.

Salt-Affected Soil Mapping in an Arid Environment Using Semi-Empirical Model and Landsat-OLI Data

The aim of this research is to map the salt-affected soil in an arid environment using an advanced semi-empirical predictive model, Operational Land Imager (OLI) data, a digital elevation model (DEM), field soil sampling, and laboratory and statistical analyses. To achieve our objectives, the OLI data were atmospherically corrected, radiometric sensor drift was calibrated, and distortions of topography and geometry were corrected using a DEM. Then, the soil salinity map was derived using a semi-empirical predictive model based on the Soil Salinity and Sodicity Index-2 (SSSI-2). The vegetation cover map was extracted from the Transformed Difference Vegetation Index (TDVI). In addition, accurate DEM of 5-m pixels was used to derive topographic attributes (elevation and slope). Visual comparisons and statistical validation of the semi-empirical model using ground truth were undertaken in order to test its capability in an arid environment for moderate and strong salinity mapping. To accomplish this step, fieldwork was organized and 120 soil samples were collected with various degrees of salinity, including non-saline soil samples. Each one was automatically labeled using a digital camera and an accurate global positioning system (GPS) survey (σ ≤ ± 30 cm) connected in real time to the geographic information system (GIS) database. Subsequently, in the laboratory, the major exchangeable cations (Ca2+, Mg2+, Na+, K+, Cl- and SO42-), pH and the electrical conductivity (EC-Lab) were extracted from a saturated soil paste, as well as the sodium adsorption ratio (SAR) being calculated. The EC-Lab, which is generally accepted as the most effective method for soil salinity quantification was used for statistical analysis and validation purposes. The obtained results demonstrated a very good conformity between the derived soil salinity map from OLI data and the ground truth, highlighting six major salinity classes: Extreme, very high, high, moderate, low and non-saline. The laboratory chemical analyses corroborate these results. Furthermore, the semi-empirical predictive model provides good global results in comparison to the ground truth and laboratory analysis (EC-Lab), with correlation coefficient (R2) of 0.97, an index of agreement (D) of 0.84 (p < 0.05), and low overall root mean square error (RMSE) of 11%. Moreover, we found that topographic attributes have a substantial impact on the spatial distribution of salinity. The areas at a relatively high altitude and with hard bedrock are less susceptible to salinity, while areas at a low altitude and slope (≤2%) composed of Quaternary soil are prone to it. In these low areas, the water table is very close to the surface (≤1 m), and the absence of an adequate drainage network contributes significantly to waterlogging. Consequently, the intrusion and emergence of seawater at the surface, coupled with high temperature and high evaporation rates, contribute extensively to the soil salinity in the study area.

Application of GC/EIMS in Combination with Semi-Empirical Calculations for Identification and Investigation of Some Volatile Components in Basil Essential Oil

Volatile components in the extracts of basil leaves (Ocimum basilicum L.) were identified by gas chromatography/mass spectrometry (GC/MS) with electron ionization (EI) mode. The major volatile components of basil under investigation are α-pinene, sabinene, β-pinene, d-limonene, eucalyptol, l-linalool and estragole. Electron ionization mass spectra of these compounds have been obtained and investigated. Furthermore, the semi-empirical MNDO [Modified Neglect of Diatomic Overlap] method was used to calculate the thermochemical data for the structural properties of these compounds.

A synthetic semi-empirical physical model of secondary electron yield of metals under E-beam irradiation

Calculations of secondary electron yield（SEY） by physical formula can hardly accord with experimental results precisely. Simplified descriptions of internal electron movements in the calculation and complex surface contamination states of real sample result in notable difference between simulations and experiments. In this paper, in order to calculate SEY of metal under complicated surface state accurately, we propose a synthetic semi-empirical physical model. The processes of excitation of internal secondary electron（SE） and movement toward surface can be simulated using this model.This model also takes into account the influences of incident angle and backscattering electrons as well as the surface gas contamination. In order to describe internal electronic states accurately, the penetration coefficient of incident electron is described as a function of material atom number. Directions of internal electrons are set to be uniform in each angle. The distribution of internal SEs is proposed by considering both the integration convergence and the cascade scattering process.In addition, according to the experiment data, relationship among desorption gas quantities, sample ultimate temperature and SEY is established. Comparing with experiment results, this synthetic semi-empirical physical model can describe the SEY of metal better than former formulas, especially in the aspect of surface contaminated states. The proposed synthetic semi-empirical physical model and presented results in this paper can be helpful for further studying SE emission, and offer an available method for estimating and taking advantage of SE emission accurately.

Improvement of Bare Soil Semi-Empirical Radar Backscattering Models (Oh and Dubois) with SAR Multi-Spectral Satellite Data (X-, C- and L-Bands)

The objective of this study is to improve the performance of semi-empirical radar backscatter models, which are mainly used in microwave remote sensing (Oh 1992, Oh 2004 and Dubois). The study is based on satellite and ground data collected on bare soil surfaces during the Multispectral Crop Monitoring experimental campaign of the CESBIO laboratory in 2010 over an agricultural region in southwestern France. The dataset covers a wide range of soil (viewing top soil moisture, surface roughness and texture) and satellite (at different frequencies: X-, C- and L-bands, and different incidence angles: 24.3° to 53.3°) configurations. The proposed methodology consists in identifying and correcting the residues of the models, depending on the surface properties (roughness, moisture, texture) and/or sensor characteristics (frequency, incidence angle). Finally, one model has been retained for each frequency domain. Results show that the enhancements of the models significantly increase the simulation performances. The coefficient of correlation increases of 23% in mean and the simulation errors (RMSE) are reduced to below 2 dB (at the X and C-bands) and to 1 dB at the L-band, compared to the initial models. At the X- and C-bands, the best performances of the modified models are provided by Dubois, whereas Oh 2004 is more suitable for the L-band (r is equal to 0.69, 0.65 and 0.85). Moreover, the modified models of Oh 1992 and 2004 and Dubois, developed in this study, offer a wider domain of validity than the initial formalism and increase the capabilities of retrieving the backscattering signal in view of applications of such approaches to stronglycontrasted agricultural surface states.

Degradation prediction of proton exchange membrane fuel cell stack using semi-empirical and data-driven methods

Degradation prediction of proton exchange membrane fuel cell(PEMFC)stack is of great significance for improving the rest useful life.In this study,a PEMFC system including a stack of 300 cells and subsystems has been tested under semi-steady operations for about 931 h.Then,two different models are respectively established based on semi-empirical method and data-driven method to investigate the degradation of stack performance.It is found that the root mean square error(RMSE)of the semi-empirical model in predicting the stack voltage is around 1.0 V,while the predicted voltage has no local dynamic characteristics,which can only reflect the overall degradation trend of stack performance.The RMSE of short-term voltage degradation predicted by the DDM can be less than 1.0 V,and the predicted voltage has accurate local variation characteristics.However,for the long-term prediction,the error will accumulate with the iterations and the deviation of the predicted voltage begins to fluctuate gradually,and the RMSE for the long-term predictions can increase to 1.63 V.Based on the above characteristics of the two models,a hybrid prediction model is further developed.The prediction results of the semi-empirical model are used to modify the input of the data-driven model,which can effectively improve the oscillation of prediction results of the data-driven model during the long-term degradation.It is found that the hybrid model has good error distribution(RSEM=0.8144 V,R2=0.8258)and local performance dynamic characteristics which can be used to predict the process of long-term stack performance degradation.

An improved semi-empirical relationship for cluster radioactivity

An improved semi-empirical relationship for cluster radioactivity half-lives is proposed by introducing an accurate charge radius formula and an analytic expression of the preformation probability.Moreover,the cluster radioactivity half-lives for the daughter nuclei around ^(208)Pb or its neighbors and the ^(12)C radioactivity half-life of114Ba are calculated within the improved semi-empirical relationship.It is shown that the accuracy of the new relationship is improved significantly compared to its predecessor.In addition,the cluster radioactivity half-lives that are experimentally unavailable for the trans-lead and trans-tin nuclei are predicted by the new semi-empirical formula.These predictions might be useful for searching for the new cluster emitters of the two islands in future experiments.

Semi-empirical Model of the White Light Flare on September 19, 1979

The intensities of the continuum emission and the Call K line of the white light flare with 3B importance on September 19, 1979 are measured and analyzed. Their variations with time are given. It is indicated that the continuum emission of this flare appeared in the early impulsive phase and lasted for about 5～6 min, with the time of maximum intensity 2～3 min earlier than that for the microwave radio burst. Based on the non-LTE theory, a semi-emplrical model at a time with the continuum emission being relatively intensive is presented. The resuhs show that the temperature in the flare photosphere is increased by 150～250 K, and that the continuum emission is produced mainly by the negative hydrogen ion. Finally, some discussions about the heating mechanism are also presented, implying that the heating energy may come from the lower atmosphere itself.

Semi-Empirical, Multi-Wavelength Raman Gain Engineering Algorithm with Pump Interaction Compensation Technique

We propose a simple algorithm for the precise engineering of multi-channel gain profile of Raman amplifier. By employing a linear approximation in the pump interaction calculation, together with a semi-empirical pump power correction using the simplistic output signal spectrum measurement, excellent gain engineering capability has been demonstrated for various target gain profiles, within +/- 0.4dB of error.

Prediction of the theoretical and semi-empirical model of ambient temperature

It is well known that the ambient temperature is a sensitive parameter which has a great effect on biology, technology, geology and even on human behavior. A prediction is a statement about an uncertain event. It is often, but not always, based upon experience or knowl- edge. Although guaranteed accurate information about the future is in many cases impossible, prediction can be useful to assist in making plans about possible developments. As a result, temperature profiles can be developed which accurately represent the expected ambient temperature exposure that this environment experiences during mea- surement. The ambient temperature over time is modeled based on the previous Train and Tmax data and using a Lagrange interpolation. To observe the comprehensive variation of ambient temperature the profile must be determined numerically. The model proposed in this paper can provide an acceptable way to measure the change in ambient temperature.

Vapor intrusion in buildings: Development of semi-empirical models including lateral separation between the building and the pollution source

Future constructions in the context of the industrial wastelands reuse may be exposed to Vapor Intrusion(VI).VI can be evaluated by combining in-situ measures and analytical models to evaluate exposure risk in future indoor environments.However,the assumptions in the existing models may reduce their accuracy when they do not meet the characteristics of real situations.Wrong estimations of indoor concentration levels may lead to inappropriate solutions against VI.In this context,new semi-empirical models(SEM)are proposed in order to better specify pollution scenarios and thus increase the accuracy of VI estimations.This development is based on a parametric study(numerical CFD)and a dimensionless analysis combined to existing VI models that consider a continuous source distribution in the soil.These expressions allow to better take into account the source position in the soil(i.e.depth and lateral source/building separation),soil properties(air permeability,diffusion coefficient of the pollutant,…)and building features(building foundation,indoor pressure,air exchange rate,…)in the estimation of indoor concentration levels.The obtained results with the proposed SEM were compared with a numerical CFD model and available experimental data,showing good accuracy in the estimation of VI.Given the advantages of these new models,they can provide better precision in the health risk assessments associated with VI.Furthermore,these expressions can be easily integrated into building ventilation codes allowing to consider air exchange rate and indoor pressure variations over time.

A new semi-empirical formula for total cross sections of electron scattering from triatomic molecules at 30—5000 eV

Total cross sections （TCSs） of electrons scattering from triatomic molecules over the energy range from 30 to 5000 eV are investigated employing a new semi-empirical formula. The TCSs of electrons scattering from triatomic molecules SO2, NO2, and CO2 are calculated. The quantitative TCSs are in good agreement with those obtained by experiments. It is shown that the results derived from the semi-empirical formula are much closer to the measurements than other calculations.

Description of martensitic transformation kinetics in Fe-C-X(X = Ni,Cr,Mn,Si) system by a modified model

Controlling the content of athermal martensite and retained austenite is important to improving the mechanical properties of high-strength steels,but a mechanism for the accurate description of martensitic transformation during the cooling process must be addressed.At present,frequently used semi-empirical kinetics models suffer from huge errors at the beginning of transformation,and most of them fail to exhibit the sigmoidal shape characteristic of transformation curves.To describe the martensitic transformation process accurately,based on the Magee model,we introduced the changes in the nucleation activation energy of martensite with temperature,which led to the varying nucleation rates of this model during martensitic transformation.According to the calculation results,the relative error of the modified model for the martensitic transformation kinetics curves of Fe-C-X(X = Ni,Cr,Mn,Si) alloys reached 9.5% compared with those measured via the thermal expansion method.The relative error was approximately reduced by two-thirds compared with that of the Magee model.The incorporation of nucleation activation energy into the kinetics model contributes to the improvement of its precision.