Levenberg Marquadt Research Articles

Circular dichroic investigation of factors that affect inclusion complexes of cyclodextrins as a drug carrier

Drug/cyclodextrin (CyD) inclusion complexes have become one of the most widely used approaches to increase aqueous solubility of poorly soluble drugs, to increase their bioavailability and stability, to reduce undesirable side effects and prevent drug–drug and drug–excipient interactions. Although drug molecules as well as CyDs exhibit detectable changes in their physicochemical properties upon complexation, to date, the interaction of CyDs with drugs is not well understood. So far, only few methods can be applied to obtain structural information on drug/CyD complexes. Circular dichroism spectroscopy (CD) has often been used to study molecular binding, nevertheless, rarely do these studies exploit the full potential of optical techniques. The objective of this article is to highlight important factors that affect drug/CyD binding interaction in particular β-CyD. On the basis of chirality, (S)-(+)-ibuprofen, meta-chlorobenzoic acid and aspirin were used to study binding interaction with β-CyD using CD. Based on CD equations for a simple 1:1 binding complex, the Levenberg–Marquadt non-linear equation was used for binding analysis and the production of simulated graphical presentations to explain the effect of various factors that influence the binding reaction and the binding curve. The results show reliability indicated by the binding constant which is in agreement with literature values. In addition, the effect of guest/host concentrations and the extent of binding on the inclusion complexes are elucidated with accuracy. This work provides useful information that can prove valuable in drug binding studies.

Fast approximation to pixelwise relaxivity maps: Validation in iron overloaded subjects

PurposeLiver iron quantification by MRI has become routine. Pixelwise (PW) fitting to the iron-mediated signal decay has some advantages but is slower and more vulnerable to noise than region-based techniques. We present a fast, pseudo-pixelwise mapping (PPWM) algorithm. Materials and MethodsThe PPWM algorithm divides the entire liver into non-contiguous groups of pixels sorted by rapid relative relaxivity estimates. Pixels within each group of like-relaxivity were binned and fit using a Levenberg–Marquadt algorithm. ResultsThe developed algorithm worked about 30 times faster than the traditional PW approach and generated R2* maps qualitatively and quantitatively similar. No systematic difference was observed in median R2* values with a coefficient of variability (CoV) of 2.4%. Intra-observer and inter-observer errors were also under 2.5%. Small systematic differences were observed in the right tail of the R2* distribution resulting in slightly lower mean R2* values (CoV of 4.2%) and moderately lower SD of R2* values for the PPWM algorithm. Moreover, the PPWM provided the best accuracy, giving a lower error of R2* estimates. ConclusionThe PPWM yielded comparable reproducibility and higher accuracy than the TPWM. The method is suitable for relaxivity maps in other organs and applications.

Prediction of the solubility of quartz in salt solutions from 25 °C to 900 °C using the 3-parameter Non-Random Two-Liquid (NRTL) model

By being able to accurately predict the behavior of silica contained in hot, high pressure water, it is possible to understand and evaluate many important subsurface chemical and geological processes. In this paper, the solubility of quartz is estimated using a 3-parameter Non-Random Two Liquid (NRTL) model, which is commonly used to predict phase equilibrium for a range of chemical processes. Model parameters were fitted to published binary interaction data (e.g. solubility data, vapor–liquid equilibrium data) using a Levenberg–Marquadt algorithm. The model is then extended to ternary systems with dissolved NaOH to predict the solubility of quartz in alkaline hydrothermal media.With no alteration to the NRTL model beyond its basic multi-component form, the model predicted silica solubilities in NaOH–water solutions from 0°C to 900°C, 0.5–3000bar and pH values between 7 and 14 (room temperature/pressure equivalent) with an average error of 62%. As literature reports discrepancies between solubility data by up to an order of magnitude, the predictions seemed reasonable.It was found that the majority of the NRTL model error occurred between 100°C and 200°C because of insensitivity to NaOH concentration. A correction term was added that modeled residual error as a function of sodium hydroxide concentration. The model error was decreased from 62% to 28%. In so doing, the error in calculating the solubility data between 100°C and 200°C was reduced to 25%. While more solubility data is needed to confirm the model accuracy over the broad temperature ranges for which the model was developed, the corrected NRTL model provides a good estimate of solubility from 0.00001mol/kg to 10mol/kg NaOH molality, 0–900°C and 0.1–3000bar.

Artificial Neural Network Modeling for Biosorption of Pb (II) Ions on Nanocellulose Fibers

This study investigates the efficiency of nanocellulose fibers (NCFs) derived from rice straw for the abatement of lead ions from aqueous solution. The maximum biosorption of lead (II) is found to be 94.21 % at pH 6.5 and equilibrium time of 40 min by using NCFs of 0.5 g/200 ml (test volume) and initial concentration of 25 mg/L of lead concentration. The data collected from laboratory-scale experimental setup are used to train a multilayer perceptron network combined with backpropagation and Levenberg–Marquadt algorithm. Different artificial neural network (ANN) architectures were tested by varying network topology as a function of number of neurons in the hidden layer of ANN model. A single-layer ANN model with ten hidden neurons at 1,000 epochs using sigmoidal transfer function has been found to have the best predictive performance. The network is found to be working satisfactorily with minimum mean squared error (5.8472E-05) and mean absolute error (1.38845310688678) during training phase. Comparison between the network results and experimental data gives a high degree of correlation coefficient (R 2 = 0.995) indicating that the model is able to predict the sorption efficiency with reasonable accuracy. The influence of each parameter on the variable studied was assessed, and pH, volume of the test solution, biomass dose, metal concentration, and contact time were found to be the most significant factors. Simulations based on the developed ANN model can estimate the behavior of the biosorption phenomenon process under different conditions.

English

Recently, Gene expression profiling by microarray technique has been effectively utilized for classification and diagnostic guess- ing of cancer nodules in the field of medical sciences. But the techniques used for cancer classification is still in its lower level. There are various drawbacks in the existing classification techniques such as low testing accuracy, high training time, unreliability, etc. Moreover, mi- croarray data consists of a high degree of noise. Gene ranking techniques such as T-Score, ANOVA, etc are later proposed to overcome those problems. But those approaches will sometimes wrongly predict the rank when large database is used. To overcome these issues, this paper mainly focuses on the development of an effective feature selection and classification technique for microarray gene expression cancer diagnosis for provide significant accuracy, reliability and less error rate. In this paper, Wrapper feature selection approach called the GA-FSVML approach is used for the effective feature selection of genes. In FSVML, the RBF kernel function in SVM is trained using modi- fied Levenberg Marquadt algorithm. This approach proposes a Fast SVM Learning (FSVML) technique for the classification tasks. The ex- periment is performed on lymphoma data set and the result shows the better accuracy of the proposed FSVML with GA-FSVML classifica- tion approach when compared to the standard existing approaches.

Non-ambiguous recovery of Biot poroelastic parameters of cellular panels using ultrasonicwaves

The inverse problem of the recovery of the poroelastic parameters of open-cell soft plastic foam panels is solved by employing transmitted ultrasonic waves (USW) and the Biot–Johnson–Koplik–Champoux–Allard (BJKCA) model. It is shown by constructing the objective functional given by the total square of the difference between predictions from the BJKCA interaction model and experimental data obtained with transmitted USW that the inverse problem is ill-posed, since the functional exhibits several local minima and maxima. In order to solve this problem, which is beyond the capability of most off-the-shelf iterative nonlinear least squares optimization algorithms (such as the Levenberg Marquadt or Nelder–Mead simplex methods), simple strategies are developed. The recovered acoustic parameters are compared with those obtained using simpler interaction models and a method employing asymptotic phase velocity of the transmitted USW. The retrieved elastic moduli are validated by solving an inverse vibration spectroscopy problem with data obtained from beam-like specimens cut from the panels using an equivalent solid elastodynamic model as estimator. The phase velocities are reconstructed using computed, measured resonance frequencies and a time–frequency decomposition of transient waves induced in the beam specimen. These confirm that the elastic parameters recovered using vibration are valid over the frequency range ofstudy.

Analysis of Italian seismicity by using a nonextensive approach

Using the INGV (National Institute of Geophysics and Volcanology) seismic catalogue, nonextensive analysis of the instrumental seismicity of Italy was performed. The time span of the analyzed catalogue is from April 16, 2005 to March 31, 2009, and only events with magnitude M L ≥ 1.9 were considered. The analysis of the spatial variation of the nonextensive parameters q and a was performed by means of scanning the Italian territory by a 1° × 1° spatial window, with a shift of 0.2° in longitude and latitude. The nonextensive parameters were estimated by means of the Levenberg–Marquadt nonlinear least square fitting method, and the obtained results were checked for stability with the variation of a 0 and q 0 , the initial values of the parameters in the fitting procedure. It was found that the q value is relatively low in areas, in which the strongest events (M w > 5.5 during the last 40 years) occurred. This finding could suggest that different earthquake triggering mechanisms govern the Italian seismicity, stick–slip-like where q is relatively low and fragment-asperity interaction-type where q is relatively high. Of course new analyses from different areas are needed in order to test such findings.

Separation of Cd and Ni from multicomponent aqueous solutions by nanofiltration and characterization of membrane using IT model

Removal of heavy metals from wastewater is of critical importance due to their high toxicity and tendency to accumulate in living organisms. In the present work, performance of a nanofiltration (NF) membrane has been studied to separate cadmium and nickel ions from multicomponent aqueous solutions at different operating conditions. It is observed that the separation of cadmium and nickel ions increases with increase in applied pressure and decreases with increase in feed concentration at a constant feed flow rate. The maximum observed solutes rejection of cadmium and nickel ions are 80.57% and 85.27% for CdCl 2–NiCl 2–water system and 97.26% and 98.90% for CdSO 4–NiSO 4–water system, respectively, for an initial feed concentration of 0.005 g/L. This difference in rejection is due to the charge density of the anions. It is also observed that the order of solute rejection sequence is inversely proportional to the diffusion coefficient. The NF membrane is characterized by an irreversible thermodynamics (IT) based Spiegler–Kedem model, coupled with film theory. Boundary-layer thickness and membrane transport parameters are estimated using Levenberg–Marquadt method. The estimated parameters are used to predict the membrane performance and found that the predicted values are in satisfactory agreement with the experimental results.

Inverse problem of recovery of poroelastic parameters of cancellous bone by inversion of transmitted ultrasonic data.

This investigation addresses the inverse problem (IP) of the retrieval of the macroscopic poroelastic parameters of cancellous bone using transmitted ultrasonic waves. The IP is solved by minimizing the objective functional (OF), which is a measure of the discrepancy, in the least squares sense, between the trial and measured data pertaining to the transmitted USW. In this study the Biot–Johnson–Koplik was employed as the interaction model (IM). A close examination of the OF computed using this IM and measured ultrasonic data transmitted through the cancellous bone showed that it exhibited several local minima and maxima. Most off-the-shelf iterative nonlinear least squares optimization algorithms (such as the Levenberg–Marquadt or Nelder–Mead simplex methods) could not retrieve a nonambiguous solution. A simple method for resolving this problem without ambiguity by using two distinct transducer central frequencies is proposed. Finally the recovered acoustic parameters are compared with those obtained using classical methods.

Treatment of landfill leachates by nanofiltration

Landfill leachate contains high concentrations of organic matter, color, heavy metals and toxic substances. This study presents the feasibility of a commercial nanofiltration membrane (NF-300) in the removal of pollutants from a landfill leachate generated from the Treatment Stabilization and Disposal Facility in Gujarat state of India. Two different leachate samples (Leachates A and B) were collected from the downstream side of closed landfill cells A and B. The average quality of the leachate was 67 719 mg/L COD, 217 mg/L ammonical nitrogen, 22 418 mg/L BOD, 3847 mg/L chlorides and 909 mg/L sulphate. The operating variables studied were applied pressure (4–20 atm), feed flowrate (5–15 L/min) and pH (2, 4, 5.5 and 6.7). It was observed that the solute rejection ( R O) increased with increase in feed pressure and decreased with increase in feed concentration at constant feed flowrate. In the present study, the rejection of cations followed the sequence: R O (Cr 3+) > R O (Ni 2+) > R O (Zn 2+) > R O (Cu 2+) > R O (Cd 2+) for leachates A and B. The order of solute rejection sequence is inversely proportional to the diffusion coefficients. The rejection of sulphate ions by the NF-300 membrane was 83 and 85%, while the rejection of chlorides was 62 and 65% for leachates A and B, respectively. The NF-300 membrane was characterized by using the combined-film theory-Spiegler–Kedem (CFSK) model based on irreversible thermodynamics and the ion transport model based on the extended Nernst–Planck equation. The membrane transport parameters were estimated using the Levenberg–Marquadt method. The estimated parameters were used to predict the membrane performance and the predicted values are in good agreement with the experimental results.

Magnetorelaxometry for localization and quantification of magnetic nanoparticles for thermal ablation studies

In magnetic heating treatments, intratumorally injected superparamagnetic iron oxide nanoparticles (MNP) exposed to an externally applied alternating magnetic field generate heat, specifically at the tumor region. This inactivates cancer cells with minimal side effects to the normal tissue. Therefore, the quantity of MNP needs to be thoroughly controlled to govern adequate heat production. Here, we demonstrate the capability of magnetorelaxometry (MRX) for the non-invasive quantification and localization of MNP accumulation in small animal models. The results of our MRX measurements using a multichannel vector magnetometer system with 304 SQUIDs (superconductive quantum interference device) on three mice hosting different carcinoma models (9L/lacZ and MD-AMB-435) are presented. The position and magnitude of the magnetic moment are reconstructed from measured spatial magnetic field distributions by a magnetic dipole model fit applying a Levenberg–Marquadt algorithm. Therewith, the center of gravity and the total amount of MNP accumulation in the mice are determined. Additionally, for a fourth mouse the distribution of MNP over individual organs and the tumor is analyzed by single-channel SQUID measurements, obtaining a sensitive spatial quantification. This study shows that magnetorelaxometry is well suited to monitor MNP accumulation before cancer therapy, with magnetic heating being an important precondition for treatment success.

A new spinning reserve requirement forecast method for deregulated electricity markets

Ancillary services are necessary for maintaining the security and reliability of power systems and constitute an important part of trade in competitive electricity markets. Spinning Reserve (SR) is one of the most important ancillary services for saving power system stability and integrity in response to contingencies and disturbances that continuously occur in the power systems. Hence, an accurate day-ahead forecast of SR requirement helps the Independent System Operator (ISO) to conduct a reliable and economic operation of the power system. However, SR signal has complex, non-stationary and volatile behavior along the time domain and depends greatly on system load. In this paper, a new hybrid forecast engine is proposed for SR requirement prediction. The proposed forecast engine has an iterative training mechanism composed of Levenberg–Marquadt (LM) learning algorithm and Real Coded Genetic Algorithm (RCGA), implemented on the Multi-Layer Perceptron (MLP) neural network. The proposed forecast methodology is examined by means of real data of Pennsylvania–New Jersey–Maryland (PJM) electricity market and the California ISO (CAISO) controlled grid. The obtained forecast results are presented and compared with those of the other SR forecast methods.

Rejection behavior of nickel ions from synthetic wastewater containing Na 2SO 4, NiSO 4, MgCl 2 and CaCl 2 salts by nanofiltration and characterization of the membrane

Nanofiltration (NF) has attracted increasing attention over the recent years due to the development of new applications. This paper presents the separation of heavy metal ions such as nickel from synthetic wastewater of nickel electroless plating industry. The wastewater from nickel electroless plating industry contains various metals such as nickel, sodium, magnesium and zinc. In order to ascertain the effect of ion rejection in a mixed salt system, the rejection behaviour of nickel ion in synthetic wastewater of Na 2SO 4, NiSO 4, MgCl 2 and CaCl 2 is tested by using NF300. The maximum observed solute rejection of nickel ion is 97.96% and 96.87% for an initial feed concentration of 5 and 10 ppm, respectively. The NF300 membrane is characterized by using combined film theory–Spiegler–Kedem (CFSK) model based on irreversible thermodynamics and ion transport model based on the extended Nernst–Planck equation. Boundary layer thicknesses, enrichment factors, concentration polarization modulus as well as membrane transport parameters are estimated by using the Levenberg–Marquadt method. The estimated parameters are used to predict the membrane performance and found that the predicted values are in good agreement with the experimental results.

Vibration based stiffness reconstruction of beams and frames by observing their rotations under harmonic excitations — Numerical analysis

Recent progress in data acquisition technology makes it possible to measure not only translational but also angular vibrations of beam and frame structures. This raises a question whether these new methods can effectively be applied in damage structural detection and localization. For this purpose a damage detection method aiming at reconstructing the stiffness distributions of a structure from its vibration measurements is tested when rotational degrees of freedom are added to the dynamic model of the structure. The stiffness reconstruction is formulated as a minimization problem in terms of harmonic vibrations of the structure and its finite element model. Two examples of a beam and frame structure are analyzed in detail. To better test the damage detection algorithm, measuring noise with various levels has been added to the analyzed signal. The results of the numerical analyses show that the application of genetic algorithms and a Levenberg–Marquadt local search appeared to be even more effective in damage detection when the angular amplitudes of harmonic vibrations are acquired. This creates good prospects for the future applications of angular accelerometers in structural health monitoring of civil engineering structures.

Phonon characterization of nano-crystals by Raman spectroscopy

Proposed herein is a method based on the Levenberg–Marquadt technique to retrieve an approximated average phonon dispersion curve from Raman spectra of nano-sized crystals. To this end we deal with a modified form of the well-known phonon confinement model in which the intrinsic linewidth Γ 0 is replaced by an effective linewidth Γ. An application to experimental results obtained on TiO 2 nano-crystals is presented as a test of the method.

Integrated interpretation of geophysical data in the archaeological site of Europos (northern Greece)

AbstractA multimethod geophysical survey was carried out in the archaeological site of Europos (northern Greece), to study the combined effectiveness and the merits of an integrated approach.Resistivity mapping was used to detect the shallower remains of the subsurface structures. Also, resistivity tomographies were carried out along dense profiles, to obtain further information on the vertical and lateral extent of the buried bodies. Two‐dimensional inversion of resistivity data was performed using the smoothness constrained and robust inversion schemes.The magnetic total and residual field maps of the area studied are presented. Two‐dimensional inversion of magnetic profiles was performed using the Levenberg–Marquadt method. The results of the magnetic data processing are in agreement with the anomalous zones that are revealed by the resistivity prospection.The results obtained by different methods assisted the interpretation of the three‐dimensional subsurface structures inferred by the resistivity tomographies.A comparison of the results of the applied surveying methods was made, checking for the relative merits and demerits of the different techniques. Their combination is discussed, in terms of providing enhanced views contradicting the use of a single method. Technical disadvantages of the multimethod approach are also pointed out. Copyright © 2005 John Wiley & Sons, Ltd.

PARAFAC and missing values

Missing values are a common occurrence in chemometrics data, and different approaches have been proposed to deal with them. In this work, two different concepts based on two algorithms are compared in their efficiency in dealing with incomplete data when fitting the PARAFAC model: single imputation (SI) combined with a standard PARAFAC-alternating least squares (ALS) algorithm, and fitting the model only to the existing elements using a computationally more expensive method (Levenberg–Marquadt) appropriately modified and optimised. The performance of these two algorithms and the effect of the incompleteness of the data on the final model have been evaluated on the basis of a Monte Carlo study and real data sets with different amounts and patterns of missing values (randomly missing values, randomly missing spectra/vectors, and systematically missing spectra/vectors). The evaluation is based on the quality of the solution as well as on computational aspects (time requirement and number of iterations). The results show that a PARAFAC model can be correctly determined even when a large fraction of the data is missing (up to 70%), and that the pattern matters more than the fraction of missing values. Computationally, the Levenberg–Marquadt-based approach appeared superior for the pattern of missing values typical of fluorescence measurements when the fraction of missing elements exceeded 30%.