Residual Root Mean Square Error Research Articles

Potential bioremediation of lead and phenol by sunflower seed husk and rice straw-based biochar hybridized with bacterial consortium: a kinetic study

Environmental pollution is a global phenomenon and troublesome fact that poses a grave risk to all living entities. Via coupling carbonaceous feedstocks with outstanding microbial activity, kinetic experiments were established using the consortium of Proteus mirabilis and Raoultella planticola, biochar-derived sunflower seed husk (SHB) and rice straw (RSB), and their composites, which investigated at 30 °C (150 rpm) to eliminate 700 mg L−1 lead (120 h) and phenol (168 h) from synthetic wastewater. The derived biochars physicochemical properties of were studied. According to adsorption capacity (qe), consortium-SHB composites and consortium-RSB composites removed lead completely (70 mg g−1) within 48 h and 66 h, respectively. Besides, phenol was remediated entirely after 42 h and 48 h by both composite systems (69.90 mg g−1), respectively, comparing with bacterial consortium only or parent SHB and RSB. Moreover, four kinetic models were studied to describe the bioremediation process. Fractional power and Elovich models could be recommended for describing the adsorption kinetics for lead and phenol removal by the studied biomaterials with high correlation coefficient (R2 ≥ 0.91 for Pb2+ and ≥ 0.93 for phenol) and lower residual root mean square error (RMSE) and chi-square (X2). Overall, bacterial consortium-biochar composites exhibited greater remediation of lead and phenol than the sum of each single bacterial consortium and biochar systems; reflecting synergistic interaction of adsorptive capability of biochar and metabolic performance of bacterial consortium, as denoted by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). The current study addressed the successful design of employing functional remediating consortium immobilized on waste biomass-derived biochar as a conducive alternative eco-sorbent and economic platform to detoxify organic and inorganic pollutants.

Multi-stage image registration based on list-mode proton radiographies for small animal proton irradiation: A simulation study

We present a multi-stage and multi-resolution deformable image registration framework for image-guidance at a small animal proton irradiation platform. The framework is based on list-mode proton radiographies acquired at different angles, which are used to deform a 3D treatment planning CT relying on normalized mutual information (NMI) or root mean square error (RMSE) in the projection domain.We utilized a mouse X-ray micro-CT expressed in relative stopping power (RSP), and obtained Monte Carlo simulations of proton images in list-mode for three different treatment sites (brain, head and neck, lung). Rigid transformations and controlled artificial deformation were applied to mimic position misalignments, weight loss and breathing changes. Results were evaluated based on the residual RMSE of RSP in the image domain including the comparison of extracted local features, i.e. between the reference micro-CT and the one transformed taking into account the calculated deformation.The residual RMSE of the RSP showed that the accuracy of the registration framework is promising for compensating rigid (>97% accuracy) and non-rigid (∼95% accuracy) transformations with respect to a conventional 3D-3D registration. Results showed that the registration accuracy is degraded when considering the realistic detector performance and NMI as a metric, whereas the RMSE in projection domain is rather insensitive.This work demonstrates the pre-clinical feasibility of the registration framework on different treatment sites and its use for small animal imaging with a realistic detector. Further computational optimization of the framework is required to enable the use of this tool for online estimation of the deformation.

Potassium Hydroxide Activation as an Adsorbent for Kinetic Models of Hexavalent Chromium Adsorptions onto <i>Garcinia mangosteen</i> Shell

The utilized adsorption kinetic models, i.e., pseudo-zero order, pseudo-first-order, pseudo-second order, intraparticle diffusion, Bangham’s pore diffusion, liquid film diffusion, modified Freundlich and Elovich models have been cultivated the hexavalent chromium adsorption process. A high correlation coefficient (R2) and a small residual root mean square error (RMSE) and Chi-square (χ2) can be depicted in the pseudo-first order for the kinetic adsorption process of hexavalent chromium adsorption on the activated mangosteen shell with potassium hydroxide and carbonized at 400 °C for 2 h as a biochar adsorbent which has a specific surface area of 164 m2/g.

An Ionospheric Total Electron Content Model with a Storm Option over Japan Based on a Multi-Layer Perceptron Neural Network

Ionospheric delay has a severe effect on reducing the accuracy of positioning and navigation of single-frequency receivers. Therefore, it is necessary to construct a precise regional ionospheric model for real-time Global Navigation Satellite System (GNSS) applications. The total electron contents (TECs) of 839 GNSS stations affiliated with the GPS Earth Observation Network were used to build a Japanese ionospheric model (JIM) based on a multi-layer perceptron neural network. During quiet space conditions, the correlation coefficient between the targets and the predictions of the JIM was about 0.98, and the root-mean square error (RMSE) of TEC residuals was ~1.5TECU, while under severe space events, the correlation coefficient increased to 0.99, and the corresponding RMSE dropped to 0.96 TECU. Moreover, the JIM model successfully reconstructed the two-dimensional (time vs latitude) TEC maps, and the TEC maps had evident hourly and seasonal variations. Most of TEC residuals accumulated between universal time 01–06 with an averaged magnitude of 1-2TECU. Furthermore, the JIM model had a perfect prediction performance under various kinds of complex space environments. In the quiet days, the prediction accuracy of the JIM was nearly equal to the global ionosphere map (GIM), and in some moments, the JIM was more competitive than the GIM. In the disturbed days, the RMSEs of TEC residuals were proportional to the solar wind speed and were inversely proportional to the geomagnetic Dst value. The maximum RMSE of the JIM was lower than 2TECU, while the corresponding RMSEs for the IRI and TIE-GCM exceeded 5TECU.

Comparison of forecasting accuracy for Madden Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEW) using Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim precipitation forecast data for Indonesia

Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim forecast data analyzed using second-order autoregressive AR(2) and space-time-spectra analysis methods (respectively) revealed contrasting results for predicting Madden Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEW) phenomena over Indonesia. This research used the same 13-year series of daily TRMM 3B42 V7 derived datasets and ERA-Interim reanalysis model datasets from the European Center for Medium-Range Weather Forecasts (ECMWF) for precipitation forecasts. Three years (2016 to 2018) of the filtered 3B42 and ERA-Interim forecast data was then used to evaluate forecast accuracy by looking at correlation coefficients for forecast leads from day +1 through day +7. The results revealed that rainfall estimation data from 3B42 provides better results for the shorter forecast leads, particularly for MJO, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and inertia-gravity phenomena in zonal wavenumber 1 (IG1), but gives poor correlation for Kelvin waves for all forecast leads. A consistent correlation for all waves was achieved from the filtered ERA-Interim precipitation forecast model, and although this was quite weak for the first forecast leads it did not reach a negative correlation in the later forecast leads except for IG1. Furthermore, Root Mean Square Error (RMSE) was also calculated to complement forecasting skills for both data sources, with the result that residual RMSE for the filtered ERA-Interim precipitation forecast was quite small during all forecast leads and for all wave types. These findings prove that the ERA-Interim precipitation forecast model remains an adequate precipitation model in the tropics for MJO and CCEW forecasting, specifically for Indonesia.

The synthesis of biochar-supported nano zero-valent iron composite and its adsorption performance in removal of malachite green

The new composite material was synthesised bonding nano zero-valent iron (NZVI) with liquid-phase chemical reduction method on the support material obtained by carbonising the organic waste mandarin peel, and the surface characteristics of it were determined by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) and zero point of charge (pHzpc). The effectiveness of the composite as an adsorbent in the removal of malachite green (MG) was investigated with different parameters. Equilibrium data were employed to different adsorption isotherms used in aqueous solutions, and the most suitable isotherm was found as Freundlich isotherm with the highest R2 =0.999 and the lowest chi-square (χ2) and residual root-mean-square error (RMSE) values. The maximum adsorption capacity was 909.09 mg/g according to Langmuir isotherm. When the kinetic data were analysed, the most appropriate kinetic model was determined as pseudo-second-order with the lowest χ2 and RMSE and the highest R2 (≥0.987) values. The adsorption process was carried out as endothermic (∆H°=145.79 kJ/mol) and spontaneously (∆G°≤−2.89kJ/mol) according to thermodynamic parameters. Also, it was possible to say that the irregularity at the adsorbent-adsorbate interface increased due to positive entropy. NZVI/carbonised mandarin peel (CMP) with high adsorption capacity could be used effectively to remove many industrial wastes.

Prediction model for gray leaf spot disease of fodder Sorghum

Gray leaf spot (caused by Cercospora sorghi Ellis & Everh.) is one of the most destructive foliar disease in fodder sorghum. Prediction model for gray leaf spot disease in fodder sorghum was developed based on 10-year (2010–2019) disease and weather data. It can occur during week-29 (third week of July) to week-43 (last week of October) in a year. Gray leaf spot had very strong, significantly negative correlation (r) with weekly average temperature (r = − 0.77), while moderate correlation was found with weekly average relative humidity (r = − 0.41), rainy days (r = − 0.44), sunshine hours (r = 0.35) and wind speed (r = − 0.36). Rainfall (r = − 0.29) and evaporation (r = − 0.23) had low correlation with gray leaf spot severity. Prediction model was developed using multiple regression coupled with goodness of fit statistics using R2 and Akaike information criteria (AIC). The prediction model included weekly average temperature, relative humidity and rainy days as predictor variables with R2 and AIC value of 0.70 and 819.03 respectively. The model was validated using leave one out cross validation (LOOCV) strategy and difference between observed residual root mean square error (RMSE) and as predicted using LOOCV was taken as indicator of model accuracy. Residual RMSE was 12.05 while that predicted through LOOCV was 12.46, indicating that model will perform fairly well on an independent data set. This prediction model can be used for efficient prediction to manage gray leaf spot disease of fodder sorghum.

Ground diameter-height models of naturally regenerated seedlings and saplings under broad-leaved mixed forest in Maoershan Mountains.

Based on the investigation data of seedlings and saplings from 48 plots in natural broad-leaved forest of Maoershan Experimental Forest Farm of Northeast Forestry University in Heilongjiang Province, the optimum model of ground diameter (D0) - height (H) was selected from eight alternative models as the basic model for the main regeneration tree species, and then the stand factors were parameterized, and the mixed effect model of sampling plot level was developed. The basic model and the mixed effect model were tested by independent samples. The results showed that there was a significant positive correlation between ground diameter and tree height of seedlings and saplings and that power function or model containing power function could better fit the relationship. The introduction of stand factors [dominant height of forest (HT), average diameter at breast height (Dg), basal area of forest (BA)] could improve the fitting effect of the model, with the residual root mean square error (RMSE) of each tree species decreasing by 1.3%-7.4% (average 3.8%), adjusted coefficient of determination (Ra2) only increasing by 0.1%-1.1% (average 0.6%) and Akaike info criterion (AIC) decreasing by 3.2%-35.2% (average 11.4%). Mixed effect models were developed for 10 tree species, such as Ulmus propinqua, Tilia and Fraxinus mandshurica. The Ra2 of mixed effect models was larger than that of the basic model, with an enhancement of 0.5%-3.5% (average 2.2%). RMSE and AIC decreased by 3.9%-20.3% (ave-rage 13.9%) and 4.0%-44.4% (average 22.3%) than that of the basic model. Model test results showed that, compared with the basic model, the average absolute error (MAE) of mixed effect model was reduced by 0.0001-0.46 m, with an average reduction of 0.08 m, and the average prediction error percentage (MPSE) decreased by 0.1%-6.2%, with an average reduction of 2.0%. The mixed effect model could improve the fitting effect and prediction ability of the model. The ground diameter-height model of seedlings and samplings of main regeneration species in broad-leaved mixed forest was developed in this study, which provides a reference for structure analysis and stand growth prediction of natural broad-leaved forest.

Removal of ciprofloxacin from simulated wastewater by pomegranate peels.

The adsorption of Ciprofloxacin (CPX) from aqueous solution by Pomegranate peels (POP) was investigated in a batch process. The influence of time (5-60min) and CPX concentration (100-10,000mg/L) on the adsorption ability of POP was studied. The POP was characterized by FTIR, scanning electron microscopy (SEM), and Zeta sizer. The kinetic of adsorption was analyzed by the pseudo-first-order and the pseudo-second-order kinetic equations using non-linear regression analysis. As well as non-linear regression analysis of Langmuir and Freundlich models were applied to specify the best non-linear curves, fitted to experimental data and estimate isotherm parameters. In order to assess the best-fit kinetic model or adsorption isotherm, three error analysis methods were used to evaluate the result of adsorption process, namely the sum of the squares of the errors (SSE), residual root mean square error (RMSE), and chi-square (χ2). On the basis of low three error analysis and high correlation (R2) of determination, it can be concluded that both the non-linear form of pseudo-second-order kinetic model and non-linear form of Langmuir are best suited to explain the adsorption of CPX onto POP. The maximum adsorption capacity for pomegranate peel as calculated by non-linear Langmuir curve was much higher than in previous work (999mg/g) at natural pH (4-5) and 25°C. The high adsorption capacity of POP makes them very low-cost and effective adsorbent materials for CPX from aqueous solution.

Accuracy assessment of wireless transponder tracking in the operating room environment.

To evaluate the applicability of the Calypso® wireless transponder tracking system (Varian Medical Systems Inc., USA) for real-time tumor motion tracking during surgical procedures on tumors in non-rigid target areas. An accuracy assessment was performed for an extended electromagnetic field of view (FoV) of 27.5 × 27.5 × 22.5cm (which included the standard FoV of 14 × 14 × 19cm) in which 5DOF wireless Beacon® transponders can be tracked. Using a custom-made measurement setup, we assessed single transponder relative accuracy, absolute accuracy and jitter throughout the extended FoV at 1440 locations interspaced with 2.5cm in each orthogonal direction. The NDI Polaris Spectra optical tracking system (OTS) was used as a reference. Measurements were taken in a room without surrounding distorting factors and repeated in an operating room (OR). In the OR, the influence of a carbon fiber and regular stainless steel OR tabletop was investigated. The calibration of the OTS and transponder system resulted in an average root-mean-square error (RMSE) vector of 0.03cm. For both the standard and extended FoV, all accuracy measures were dependent on transponder to tracking array (TA) distances and the absolute accuracy was also dependent on TA to OR tabletop distances. This latter influence was reproducible, and after calibrating this, the residual error was below 0.1cm RMSE within the entire standard FoV. Within the extended FoV, this residual RMSE did not exceed 0.1cm for transponder to TA distances up to 25cm. This study shows that transponder tracking is promising for accurate tumor tracking in the operating room. This applies when using the standard FoV, but also when using the extended FoV up to 25cm above the TA, substantially increasing flexibility.

The Comparison of Canopy Height Profiles Extracted from Ku-band Profile Radar Waveforms and LiDAR Data

An airborne Ku-band frequency-modulated continuous waveform (FM-CW) profiling radar, Tomoradar, records the backscatter signal from the canopy surface and the underlying ground in the southern boreal forest zone of Finland. The recorded waveforms are transformed into canopy height profiles (CHP) with a similar methodology utilized in large-footprint light detection and ranging (LiDAR). The point cloud data simultaneously collected by a Velodyne® VLP-16 LiDAR on-board the same platform represent the frequency of discrete returns, which are also applied to the extraction of the CHP by calculating the gap probability and incremental distribution. To thoroughly explore the relationships of the CHP derived from Tomoradar waveforms and LiDAR data we utilized the effective waveforms of one-stripe field measurements and comparison them with four indicators, including the correlation coefficient, the root-mean-square error (RMSE) of the difference, and the coefficient of determination and the RMSE of residuals of linear regression. By setting the Tomoradar footprint as 20 degrees to contain over 95% of the transmitting energy of the main lobe, the results show that 88.17% of the CHPs derived from Tomoradar waveforms correlated well with those from the LiDAR data; 98% of the RMSEs of the difference ranged between 0.002 and 0.01; 79.89% of the coefficients of determination were larger than 0.5; and 98.89% of the RMSEs of the residuals ranged from 0.001 to 0.01. Based on the investigations, we discovered that the locations of the greatest CHP derived from the Tomoradar were obviously deeper than those from the LiDAR, which indicated that the Tomoradar microwave signal had a stronger penetration capability than the LiDAR signal. Meanwhile, there are smaller differences (the average RMSEs of differences is only 0.0042 when the total canopy closure is less than 0.5) and better linear regression results in an area with a relatively open canopy than with a denser canopy.

Crop height monitoring with digital imagery from Unmanned Aerial System (UAS)

Crop height is a very important attribute to assess overall crop condition, irrigation, and estimation of terminal yield. In this study, a novel method to monitor crop height of Sorghum (Sorghum bicolor) using an Unmanned Aerial System (UAS) is proposed. UAS data were acquired seven times over the growing season and each aerial acquisition included over 200 images with significant image overlap at an altitude of 50m above ground. Ortho-mosaic image and 3D point cloud were generated by applying the Structure from Motion (SfM) algorithm to the images. Ground control points (GCPs) were installed around the study area and they were surveyed using a real time kinematic (RTK) GPS unit for accurate geo-referencing of the geospatial data products. A Digital Terrain Model (DTM) and Digital Surface Model (DSM) were generated from the 3D point cloud data, and a Crop Height Model (CHM) was then created by subtracting DTM from DSM. Uniform crop grids along the center line of each variety were defined for further processing. The maximum CHM value within each individual grid was taken to represent crop height of the grid, and average of all grid heights over the whole area of each variety was calculated as crop height of individual variety. These measurements were compared with manual crop height measurements. Root Mean Square Error (RMSE) between field measurements and the proposed approach was 0.33m. In addition, the height estimates from both field measurement and the proposed approach could be used to derive a growth curve by fitting a sigmoidal curve. The residual RMSEs between the observed and predicted value of the curve established from UAS and field measurements were calculated as 0.05m and 0.1m, respectively. The growth curve results showed that the proposed approach indicated less RMSE and generated more reliable growth curves for monitoring sorghum height.

UT (University of Tehran) isotherm as a novel and useful adsorption isotherm for investigation of adsorptive removal of pollutants

In this research, a novel and dose-indepentent adsorption isotherm consisting of dimensionless expressions called “UT isotherm” was developed. On the other hand, the theoretical base of empirical isotherms, including Redlich–Peterson and Freundlich, was stated. The performance of the proposed isotherm was evaluated by adsorption of methylene blue, crystal violet, malachite green, and gentamicin using various adsorbents (fibrous cellulose sulfate, activated carbon, and graphene oxide). Dose-dependency of Freundlich and Redlich–Peterson models were investigated using a deviation factor (DF) obtained from variable and constant-dose experiments. Residual root-mean-square error (RMSE) and chi-square test (χ2) were used to evaluate agreement between experimental data and predictions using models. The proposed model was compared with Langmuir, Freundlich, Redlich–Peterson, and Radke-Prausnitz models. A comparison of obtained model with Freundlich isotherm showed that KF was dependent on adsorbenet dosage (D) and qm. Furthermore, the experimental results revealed that Freundlich constant was decreased by increasing D. On the other hand, the empirical and undefined parameters of Redlich–Peterson isotherm (KR and αR) were found to be dependent on qm and desorption constant (Kd). Because αR was also dependent on D, Redlich–Peterson model could not fit experimental data at variable-dose experiments. Useful equations were introduced for calculation of qm using Freundlich and Redlich-Peterson parameters. Also, a dimensionless parameter called free capacity fraction (FCF) was presented. According to the experimental results, Freundlich model was more accurate than Langmuir model when FCF was lower than 0.005.

MO-FG-CAMPUS-IeP3-02: Gradient Nonlinearity Calibration and Correction for Full-Volume Imaging of a Compact Asymmetric MRI Gradient System

Purpose: Due to engineering limitations, the spatial encoding gradient fields generated by an MRI scanner are inherently nonlinear and images must undergo geometric correction prior to display. The gradient nonlinearity (GNL) of a conventional symmetric whole-body gradient is typically characterized using a spherical harmonic polynomial (SHP) expansion of magnetic gradient fields with up to fifth-order terms. Only odd-order terms are required due to design symmetry (i.e., 3rd/5th-order). Recently, a high-performance asymmetric gradient system was developed which exhibits more complex GNL. Here, the GNL across the 26cm diameter-spherical-volume (DSV) of this system is characterized using a phantom-based iterative calibration procedure. Methods: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) phantom was scanned with a 3D IR-FSPGR sequence (sagittal acquisition, Nx=Ny=256, Nz=196, Δx=Δy=1.05mm, Δz=1.3mm, BW=±125kHz) on the asymmetric gradient system. The phantom (20cm diameter with 160 spherical fiducials of 1.0/1.5cm diameter) was imaged at isocenter and at spatial offsets of ±3cm along the superior/inferior, right/left, anterior/posterior axes to cover the 26cm DSV. The spatial positions of fiducials were measured from MR images and compared with the design positions to extract distortion field, which is then used to fit the SHP model using an iterative calibration procedure. The effect of higher-order terms was tested by incrementally increasing the model order from 5 to 10. The calibrated coefficients were then used to geometrically correct the images, and for each case the residual root-mean-square-error (RMSE) was determined. For comparison, RMSE was also determined for images corrected using coefficients obtained from electromagnetic simulation. Results: The calibrated coefficients (10th-order) reduce RMSE from 0.96mm (using a 10th-order correction from electromagnetic simulation) to 0.36mm. Conclusion: The model parameters for GNL correction over the 26cm DSV of an asymmetric gradient system were successfully determined. The use of calibrated coefficients up to 10thorder coefficients including even-order terms yielded improved geometric accuracy (RMSE) comparable to conventional symmetric gradients. Funding support: NIH R01EB010065

TH-CD-207-11: Gradient Nonlinearity Calibration and Correction for Head-Only Asymmetric Gradient System

Purpose: Due to engineering limitations, the gradient fields in clinical MRI inevitably contain high-order, nonlinear components. The presence of gradient nonlinearity (GNL) causes image geometrical distortion. Standard correction methods are based on parameterization of the simulated gradient fields with spherical harmonic polynomials. Conventional whole-body gradient systems typically employ symmetric designs, and the GNL for such systems usually contains only odd-order terms (up to 5th-order). Recently, a high-performance, head-only gradient system was developed. Due to asymmetric design, this new system exhibits more complex GNL profiles. Here, we demonstrate measurement-based high-order(N>5) GNL-correction on this new system using a fiducial phantom and iterative model-fitting procedure. Methods: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) phantom was scanned with a 3D IR-FSPGR sequence (sagittal acquisition plane, Nx=Ny=256, Nz=196, x= y=1.05mm, z=1.3mm, BW=125kHz) on the head-only gradient system operating at 80mT/m, 500T/m/s. This phantom contains 160 fiducial spheres (diameter=1.0 or 1.5cm) that are distributed within a diameter=20cm spherical shell. The spatial positions of the fiducials were then measured from the distorted images and fit using a spherical harmonic polynomial model and iterative fitting procedure. The model order was increased from 1 to 10 step-by-step to test the effects of including high-order terms (N>5). Then, the coefficients were used to correct distortion. The residual root-mean-square-error (RMSE) was calculated from fiducial positions tracked from GNL-corrected images. Results: The RMSE analysis shows that GNL-distortion is reduced from 3.93 to 0.39mm by using correction terms up to 7th-order including both even-and odd-order terms. The addition of higher orders (N>7) provides negligible benefit. Conclusion: The GNL of a high-performance, head-only gradient system was successfully measured. The use of up to 7th-order correction terms was found to be sufficient for correcting GNL-distortion in a typical brain scan. These techniques could also improve geometric accuracy for whole-body MRI systems used for radiation therapy planning.

Performance optimization of a bendable parabolic cylinder collimating X-ray mirror for the ALS micro-XAS beamline 10.3.2.

The Advanced Light Source (ALS) beamline (BL) 10.3.2 is an apparatus for X-ray microprobe spectroscopy and diffraction experiments, operating in the energy range 2.4-17 keV. The performance of the beamline, namely the spatial and energy resolutions of the measurements, depends significantly on the collimation quality of light incident on the monochromator. In the BL 10.3.2 end-station, the synchrotron source is imaged 1:1 onto a set of roll slits which form a virtual source. The light from this source is collimated in the vertical direction by a bendable parabolic cylinder mirror. Details are presented of the mirror design, which allows for precision assembly, alignment and shaping of the mirror, as well as for extending of the mirror operating lifetime by a factor of ∼10. Assembly, mirror optimal shaping and preliminary alignment were performed ex situ in the ALS X-ray Optics Laboratory (XROL). Using an original method for optimal ex situ characterization and setting of bendable X-ray optics developed at the XROL, a root-mean-square (RMS) residual surface slope error of 0.31 µrad with respect to the desired parabola, and an RMS residual height error of less than 3 nm were achieved. Once in place at the beamline, deviations from the designed optical geometry (e.g. due to the tolerances for setting the distance to the virtual source, the grazing incidence angle, the transverse position) and/or mirror shape (e.g. due to a heat load deformation) may appear. Due to the errors, on installation the energy spread from the monochromator is typically a few electron-volts. Here, a new technique developed and successfully implemented for at-wavelength (in situ) fine optimal tuning of the mirror, enabling us to reduce the collimation-induced energy spread to ∼0.05 eV, is described.

The sorption of sulfamethazine on soil samples: Isotherms and error analysis

In this paper, batch sorption of sulfamethazine on eight soil samples (six from Croatia and two from Bosnia and Hercegovina) with different organic matter contents ranging from 1.52 to 12.8% was investigated. The effects of various parameters such as agitation time, initial concentration, and ionic strength on the sulfamethazine sorption were studied. The experimental data were analysed using a one-parameter model, Linear isotherm, and two two-parameter models, the Freundlich and Dubinin–Radushkevich isotherms. The goodness of fit was measured using the linear regression and the determination coefficient (R2) value. Also, the equilibrium data of the two-parameter models were analysed using the residual root mean square error (RMSE), the sum of squares of errors (ERRSQ), and a composite fractional error function (HYBRID).Non-linear regression has better characteristics for analysing experimental data. The obtained sorption coefficients Kd (from 0.25 to 8.10mL/g) and the Freundlich sorption coefficients KF (from 1.16 to 7.99 (μg/g)(mL/μg)1/n) exhibited quite low values, which indicated that sulfamethazine is weakly adsorbed on the evaluated soils, is highly mobile, and has a great potential to penetrate and pollute the ground water. The Dubinin–Radushkevich isotherm was used to estimate the apparent free energy of sorption.

A low-radiation exposure protocol for 3D QCT of the spine

Cadaver and phantom measurements and simulations confirmed that radiation exposure in 3D QCT of the spine can be reduced if 80 kV instead of 120 kV protocols are used; 120 mAs and slice thicknesses of 1-1.3 mm should be usable but obese patient will require higher milliampere-second settings. To develop a low-radiation exposure CT acquisition protocol for 3D QCT of the thoracolumbar spine. Twenty-six cadavers were scanned with a standard protocol of 120 kV, 100 mAs and with a low-dose protocol using 90 kV, 150 mAs. The scan range included the vertebrae T6 to L4. Each vertebra was segmented and the integral volume and BMD of the total vertebral body were determined. Effective dose values were estimated. The impact of milliampere-second reduction on image quality was simulated by adding noise. One hundred ninety-six vertebrae were analyzed. Integral volume as well as integral BMD correlated significantly (p < 0.001) between standard and low-dose protocols (volume, r (2) = 0.991, residual root mean square (RMS) error, 0.77 cm(3); BMD, r (2) = 0.985, RMS error, 4.21 mg/cm(3)). The slope significantly differed from 1 for integral BMD but not for volume hinting at residual field inhomogeneity differences between the two voltage settings that could be corrected by cross-calibration. Compared to the standard protocol, effective dose was reduced by over 50 % in the low-dose protocol. Adding noise in the 90 kV images to simulate a reduction from 150 to 100 mAs did not affect the results for integral volume or BMD. For 3D QCT of the spine, depending on scanner type, 80 or 90 kV instead of 120 kV protocols may be considered as an important option to reduce radiation exposure; 120 mAs and slice thicknesses of 1-1.5 mm are usable if segmentation is robust to noise. In obese patients, higher milliampere-second settings will be required.

Evaluation of the Use ofAcacia niloticaLeaf as an Ecofriendly Adsorbent for Cr (VI) and Its Suitability in Real Waste Water: Study of Residual Errors

The present paper aims to investigate the physical characteristics ofAcacia niloticaleaves (MVM) relative to their use as an adsorbent for removal of hazardous Cr (VI) from waste water. The adsorbent was characterized by FTIR and SEM studies. The applicability of the Langmuir model to MVM was proved by the high coefficient of determination. Eight error analysis methods, namely, residual root mean square error (RMSE), chi-square (χ2), sum of the square of the errors (ERRSQ), composite functional error (HYBRD), derivative of Marquardt's percent standard deviation (MPSD), average relative error (ARE), sum of absolute error (EABS), and average percentage error (APE) were used to evaluate the suitability of the adsorption isotherm. Desorption reveals that recovery of the metal from adsorbent was possible. The ecofriendly adsorbent MVM is expected to be an environmentally and economically feasible adsorbent for the removal of Cr (VI) from aqueous solution and real waste water.

Efficacy of physically pretreated Mangifera indica biomass for Cu2+ and Zn2+ sequestration

To develop a strategy for the eradication of Cu2+ and Zn2+ from contaminated waters, the waste biomass of Mangifera indica was pretreated physically (autoclaved, boiled and heated) for assessing the uptake capacity of native and pretreated biomass for Cu2+ and Zn2+ biosorption on batch scale, concentrating on pH, pretreatment, biosorbent dose, metal concentration, contact time and temperature as operational parameters. To measure the goodness-of-fit error functions as sum of square error (SSE), chi-square (χ2) and residual root mean square error (RMSE) were used. Best results were obtained at pH 5 (80.65 mg/g) and 6 (94.25 mg/g) for Cu2+ and Zn2+, respectively, with autoclaved leaves. Sorption capacity of biomasses was found to be decreased with increase in biosorbent dose and temperature while it increased with increase in metal ion concentration and with time. Freundlich isotherm was found favorable to describe sorption mechanism, whereas pseudo-second-order kinetic model was best employed to describe sorption rate.