Higher Root Mean Square Research Articles

The authentication of peaberry and civet ground roasted robusta coffee using UV-visible spectroscopy and PLS-DA method with two different particle sizes

The objective of this research was to investigate the influence of particle size of ground roasted coffee samples in the authentication of peaberry and civet coffee using UV-visible spectroscopy combined with partial least squares-discriminant analysis (PLS-DA) method. For this purpose, we provide a total of 80 samples of peaberry and civet coffee with two different particle size of 1680 micrometer (mesh 12) and 297 micrometer (mesh 50). The all coffee samples were extracted using hot distilled water (90-98°C). UV-visible spectral data of the all coffee samples were acquired using a UV-visible spectrometer in transmittance mode. The result showed that the different absorbance spectra were observed for the different particle sizes of peaberry and civet coffee samples. The absorbance of samples having particle size of 297 micrometer (mesh 50) is higher than that of particle size of 1680 micrometer (mesh 12). The calibration model was developed using PLS-DA method for samples having same particle size and resulted in acceptable result with high coefficient of determination (R2) (R2=0.99 both for mesh 12 and 50, respectively), low root mean square error of calibration (RMSEC), and high residual prediction deviation (RPD). However, the performance of the prediction results was very low for samples having different particle size with high bias and high root mean square error of prediction (RMSEP).

Inter-comparison of remotely sensed precipitation datasets over Kenya during 1998–2016

The paucity of reliable ground based datasets remains a major challenge over Kenya. In the advent of extreme wetness or drought events, reliable precipitation estimates for local characterization is a long overdue process. In the present study, four Satellite derived Precipitation Estimates (SPE): TMPA V7 3B42, PERSIANN-CDR, CHIRPS, and ARC2, are assessed over four homogeneous zones in Kenya with gauge based data during 1998–2016. Results show that variations of SPE products are based on complex geomorphology of different climatic zones. All SPE products depict bimodal annual precipitation pattern with west-east gradient representing heavier to lighter precipitation events. The Monthly analysis reveal good statistical agreement with reference datasets despite underestimation of precipitation in most regions. Seasonal precipitation events show that the PERSIANN-CDR perform better along low altitude humid climate and western zones around Lake Basin while ARC2 has uniform performance as gauge stations over highlands regions. Strong positive linear relationship on annual scale is evident in most SPE products with CHIRPS, ARC2, and TMPA exhibiting relatively high correlation (r) and minimum root mean square error (RMSE), except for PERSIANN-CDR. Overall, the findings of this study show the potentials of SPE products for applications over study domain. The TMPA V7 and PERSIANN-CDR could be useful in understanding individual floods events. Since the CHIRPS perform relatively well over ASAL regions, it could be utilized in monitoring droughts events.

In-depth evolution of tellurium films deposited by Frequency Assisted Thermal Evaporation in Vacuum (FATEV)

In order to enlighten the in-depth organization of thin tellurium films, deposited by the frequency assisted thermal evaporation in vacuum (FATEV) approach, morphological, structural and spectroscopic investigations were performed. Spectroscopic ellipsometry (SE) and cross-section scanning electron microscopy (SEM) showed a change of the growth mechanism upon application of higher vibrations’ input frequencies during the films deposition. The films, deposited by conventional thermal evaporation in vacuum with no vibrations applied, as well as these, deposited by FATEV with application of 50 Hz vibrations, were characterized by initial densification followed by 2D nanoparticles growth when a certain threshold thickness was reached. On the other hand, the high-frequency vibrations of 4 and 10 kHz preconditioned growth of tellurium nanoribbons oriented towards the z-axis from the very beginning of the film formation. The topography changes, observed by atomic force microscopy (AFM) and scanning electron microscopy, showed highly porous surfaces (with high root mean square surface roughness) formed by distinct nanoblades for the films, deposited at low input frequencies, while the films, deposited under the impact of vibrations in the kilohertz range, were much more ordered, and hence their surface was significantly smoother. The structural parameters of the samples were investigated by X-ray diffraction (XRD) analysis.

Rapid Assessment of Monovarietal Portuguese Extra Virgin Olive Oil's (EVOO's) Fatty Acids by Fourier‐Transform Near‐Infrared Spectroscopy (FT‐NIRS)

A rapid method for the evaluation of fatty acids (FA) of monovarietal Portuguese extra virgin olive oils (EVOOs) (n = 82) from Alentejo, south‐central region of Portugal, is developed based on Fourier‐transform near‐infrared spectroscopy (FT‐NIRS). The contents of FA‐components (previously determined per conventional gas chromatography) are correlated with FT‐NIRS data (independent variable), by means of full cross‐validation partial least squares regression (CVPLSR). CVPLSR is run using standard normal variate (SNV) data pre‐processing and the nonlinear iterative partial least squares (NIPALS) algorithm. Obtained correlation models are characterized with good statistics: high correlation coefficients (R > 0.85) and low root mean square errors (RMSE < 2.04). Obtained values of the residual predictive deviation (RPD) of CVPLSR‐model, higher than 5.0 (C18:1, C18:2, MUFA, PUFA) confirm the FT‐NIRS as a potential method for rapid quality control of EVOO's FA.Practical Applications: In this work for the first time, fatty acid (FA) profile of monovarietal extra virgin olive oil (EVOO) samples of the greatest olive region in Portugal—Alentejo—is analyzed by Fourier‐transform near‐infrared spectroscopy (FT‐NIRS) and chemometrics. Obtained high‐quality results allow one to recommend this technique from monitoring to quality control analysis of FA (in particular, of representative unsaturated FA), in a great number of olive oil samples, in near‐real time.Quality of olive oil can be assessed by target or non‐target analysis and it is of mandatory importance. Fourier‐transform near‐infrared spectroscopy (FT‐NIRS), combined with chemometrics, for the analysis of the fatty acid profile of varietal olive oils from Alentejo (Portugal) can be a useful technique for quality control. Furthermore, FT‐NIRS is rapid, non‐destructive, and a more environmental friendly technique.

Development of Superhydrophobic Coating on Copper for Enhanced Corrosion Resistance in Chloride Medium

In this paper, a simple and economic method of superhydrophobic (SHP) surface modification of copper surfaces with water contact angle (WCA) of 147° ± 0.1° and roll-off angle of 5° is reported. SHP copper surfaces were synthesized by annealing copper foil in air and then coated with silica nanoparticles dispersed in silane solution. Scanning electron microscopy analysis of the SHP Cu surfaces showed the uniform distribution of spherical micron-sized CuO particles throughout the surface. Atomic force microscopy images of silane-coated surfaces showed increased valleys and peaks with higher root mean square and average roughness contributed by the silica nanoparticles. X-ray photoelectron spectroscopy results further confirmed the micron-sized CuO particles in the outer layer with silane containing silica nanoparticles, which contributed to the micro-/nano-roughness causing a phenomenal improvement in the WCA values. Electrochemical studies carried out in aqueous chloride environments demonstrated the corrosion resistance of superhydrophobic copper surface as evident from the shift in open-circuit potential values towards the nobler direction, increase in the charge transfer resistance and lower anodic current as compared with the fresh copper foil.

Characterization and evaluation of reactive dye adsorption onto Biochar Derived from Turbinaria conoides Biomass

Biochar, produced from brown seaweed Turbinaria conoides through microwave assisted pyrolysis, was employed as a sorbent for the remediation of Remazol brilliant blue R (RBB). Pyrolysis experiments were conducted at different processing conditions and the resulting products of microwave pyrolysis (biochar, bio‐oil, and gas) at each condition were quantified. The optimum yield of 27.3 wt% for the biochar was achieved by applying pyrolysis conditions including power of 280 W and feedstock ratio of 10:4 as seaweed: activated carbon. The biochar was characterized using Fourier transform infrared spectroscopy, energy dispersive X‐ray analysis and scanning electron microscope. The results indicated that pyrolysis increased roughness and number of pores on the biochar surface thereby enhanced the sorption potential of seaweed. Adsorption experiments revealed that optimum RBB biosorption occurred at pH 2 for seaweed‐derived biochar with maximum RBB sorption capacity of 85.3 mg/g. Application of different isotherm models (Freundlich, Langmuir, and Toth) indicated that the three‐parameter Toth model resulted in improved prediction of isotherm data with less % error, high correlation coefficient, less chi‐square and root mean square error values. The experimental kinetics data analyzed using different models highlighted that the pseudo‐second order kinetic model produced superior description of the experimental data. The elution experiments carried out using various elutants (0.1 M HNO3, HCl, H2SO4, NaOH, Na2CO3, and EDTA) indicated that NaOH performed better in releasing RBB from dye‐bounded biochar with elution efficiency of 99.5%. The regenerated biochar sample was restored and successfully employed for three sorption‐elution cycles. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13143, 2019

Effects of variable selection and processing of NIR and ATR-IR spectra on the prediction of extractive content in Eucalyptus bosistoana heartwood.

The use of quick attenuated total reflectance infrared (ATR-IR) spectroscopy and near infrared (NIR) spectroscopy to predict extractives content (EC) in heartwood of E. bosistoana with partial least squares regression (PLSR) models was studied. Different spectra pre-processing methods and variable selection were tested for calibration optimisation. While variable selection substantially improved the NIR-PLSR models, only small effects were observed for spectra pre-processing methods and ATR-IR-PLSR models. Both of the NIR-PLSR and ATR-IR-PLSR models yielded reliably EC results with high R2 and low root mean square error (RMSE). NIR based models performed better (RMSE 0.9%) than ATR-IR based models (RMSE 1.6%). Analysis showed that the models were based on IR signals assigned to chemical structures known from eucalyptus heartwood extracts. Combined with PLSR and variable selection, both, ATR-IR and the NIR spectroscopy, can be used to quickly predict EC in E. bosistoana, a measure needed in tree breeding and the quality control of for durable timber.

Assessment of Dual Frequency GNSS Observations from a Xiaomi Mi 8 Android Smartphone and Positioning Performance Analysis

On May 2018 the world’s first dual-frequency Global Navigation Satellite System (GNSS) smartphone produced by Xiaomi equipped with a Broadcom BCM47755 chip was launched. It is able to receive L1/E1/ and L5/E5 signals from GPS, Galileo, Beidou, and GLONASS (GLObal NAvigation Satellite System) satellites. The main aim of this work is to achieve the phone’s position by using multi-constellation, dual frequency pseudorange and carrier phase raw data collected from the smartphone. Furthermore, the availability of dual frequency raw data allows to assess the multipath performance of the device. The smartphone’s performance is compared with that of a geodetic receiver. The experiments were conducted in two different scenarios to test the smartphone under different multipath conditions. Smartphone measurements showed a lower C/N0 and higher multipath compared with those of the geodetic receiver. This produced negative effects on single-point positioning as showed by high root mean square error (RMS). The best positioning accuracy for single point was obtained with the E5 measurements with a DRMS (horizontal root mean square error) of 4.57 m. For E1/L1 frequency, the 2DRMS was 5.36 m. However, the Xiaomi Mi 8, thanks to the absence of the duty cycle, provided carrier phase measurements used for a static single frequency relative positioning with an achieved 2DRMS of 1.02 and 1.95 m in low and high multipath sites, respectively.

Assimilation of Synthetic SWOT River Depths in a Regional Hydrometeorological Model

The SWOT (Surface Water and Ocean Topography) mission, to be launched in 2021, will provide water surface elevations, slopes, and river width measurements for rivers wider than 100 m. In this study, synthetic SWOT data are assimilated in a regional hydrometeorological model in order to improve the dynamics of continental waters over the Garonne catchment, one of the major French catchments. The aim of this paper is to demonstrate that the sequential assimilation of SWOT-like river depths allows the correction of river bed roughness coefficients and thus simulated river depths. An extended Kalman filter is implemented and the data assimilation strategy was applied to four experiments of gradually increasing complexity regarding observation and model error over the 1995–2000 period. With respect to a “true” river state, assimilating river depths allows the proper retrieval of constant and spatially distributed roughness coefficients with a root mean square error of 1 m1/3 s−1, and the estimation of associated river depths. It was also shown that river depth differences can be assimilated, resulting in a higher root mean square error for roughness coefficients with respect to the true river state. Finally, the last experiment shows how one can take into account more realistic sources of SWOT error measurements, in particular the importance of the estimation of the tropospheric water content in the process.

An Angle Estimation Method for Monostatic MIMO Radar Based on RCC-FLOM Algorithm

The performance of the angle estimation algorithm based on the two-order or higher order cumulants in the impact noise background will decline sharply. Therefore, it is necessary to study the new algorithm to estimate target angle in the impact noise background. In order to solve the angle estimation problem of coherent sources in the impulse noise background, a conjugate rotation invariant subspace algorithm based on reduced order fractional lower order covariance matrix is proposed. Use the reduced dimension lower order fraction covariance matrix to reduce the impulse noise influence. And according to the conjugate rotation invariant subspace, the coherent source is decohered. The Monte-Carlo experiments show that the proposed algorithm has the advantages of high estimation probability and low root mean square error in the case of low signal-to-noise ratio, compared with the existing FLOM-MUSIC algorithm and FLOM-Unitary ESPRIT algorithm.

Estimation of Missing Values Using Hybrid Fuzzy Clustering Mean and Majority Vote for Microarray Data

Rapid development in microarray experiments leads toward generating a large amount of genes expressions. Handling such a massive amount of gene expressions is a challenge using traditional methods especially multiple missing expression values exist. This article proposed a novel hybrid fuzzy clustering mean and majority vote to yield better performance. The proposed method will be evaluated with other three imputation methods and trained with four publicly available microarray datasets. The experimental results show that the proposed method has promising results that able to replace the missing data as well as achieves high accuracy rates and low root mean square error values.

LW-NIR hyperspectral imaging for rapid prediction of TVC in chicken flesh

Total viable count (TVC) is often used as an important indicator for chicken freshness evaluation. In this study, 112 fresh chicken flesh samples were acquired after slaughtered and their hyperspectral images were collected in the LW-NIR (900-1700 nm) range. The full LW-NIR spectra (486 wavebands) within the images were extracted and applied to related to reference TVC values measured in different storage period, using partial least squares regression (PLSR) algorithm, resulting in high correlation coefficients (R) and low root mean square errors (RMSE), for either raw spectra or pretreatment spectra. By using regression coefficients (RC) method, 20, 18, 17 and 20 optimal wavebands were respectively selected from raw spectra, baseline correction (BC) spectra, Savitzky-Golay convolution smoothing (SGCS) spectra and standard normal variate (SNV) spectra and applied for the optimization of original full waveband PLSR model. By comparison, RC-PLSR model based on the SGCS spectra showed a better performance in TVC prediction with RC of 0.98 and RMSEC of 0.35 log10 CFU/g in calibration set, and RP of 0.98 and RMSEP of 0.44 log10 CFU/g in prediction set. At last, by transferring the best RC-PLSR model, the dynamic TVC change during the storage was visualized by color maps to indicate the TVC spoilage degree. The overall study revealed that LW-NIR hyperspectral imaging combined with PLSR could be used to predict the freshness of chicken flesh. Keywords: hyperspectral imaging, chicken, TVC, partial least square regression (PLSR) DOI: 10.25165/j.ijabe.20191203.4444 Citation: H Wang, H J He, H J Ma, F S Chen, Z L Kang, M M Zhu, et al. LW-NIR hyperspectral imaging for rapid prediction of TVC in chicken flesh. Int J Agric & Biol Eng, 2019; 12(3): 180–186.

Multivariate calibration for carbon nanotubes in the environment using the microwave induced heating method

With continuous increase in production and application of various types of carbon nanotubes (CNTs), the presence of a mixture of different types of CNTs in the environment cannot be neglected. Since distinct types of CNTs have different influences on environmental and human health, the environmental quantification of each type of CNTs has become a critical step in all CNTs-related studies. However, most of existing quantification methods have not been implemented to determine mass/concentration of individual type of CNTs in multi-component samples. Therefore, the goal of the present paper is to develop Chemometrics-based multivariate calibration approaches for simultaneously quantifying individual type of CNTs in the environment with the microwave induced temperature rise spectra. Motivated by successful applications of partial least square regression (PLS), least square-support vector machine (LS-SVM) and artificial neural networks (ANN) in measuring specific contaminants in mixtures, the potential of applying these techniques in predicting quantities of Single-walled CNTs, Multi-walled CNTs and carboxylate Multi-walled CNTs in environmental matrices (agricultural soil and anaerobic sludge) was investigated in this study. Our results revealed that the developed LS-SVM model presented high R2 and low root mean square error of prediction (RMSEP) in both 2-component and 3-component matrices, while the resulted ANN model was only accurate in the 2-component matrix. The PLS model was found to be ineffective in interpreting relationship between the microwave induced temperature rises and mass of CNTs as indicated by small R2 and large RMSEP.

Regulation of Substrate-Target Distance on the Microstructural, Optical and Electrical Properties of CdTe Films by Magnetron Sputtering.

Cadmium telluride (CdTe) films were deposited on glass substrates by direct current (DC) magnetron sputtering, and the effect of substrate-target distance (Dts) on properties of the CdTe films was investigated by observations of X-ray diffraction (XRD) patterns, atomic force microscopy (AFM), UV-VIS spectra, optical microscopy, and the Hall-effect measurement system. XRD analysis indicated that all samples exhibited a preferred orientation along the (111) plane, corresponding to the zinc blende structure, and films prepared using Dts of 4 cm demonstrated better crystallinity than the others. AFM studies revealed that surface morphologies of the CdTe films were strongly dependent on Dts, and revealed a large average grain size of 35.25 nm and a high root mean square (RMS) roughness value of 9.66 nm for films fabricated using Dts of 4 cm. UV-VIS spectra suggested the energy band gap (Eg) initially decreased from 1.5 to 1.45 eV, then increased to 1.68 eV as Dts increased from 3.5 to 5 cm. The Hall-effect measurement system revealed that CdTe films prepared with a Dts of 4 cm exhibited optimal electrical properties, and the resistivity, carrier mobility, and carrier concentration were determined to be 2.3 × 105 Ω∙cm, 6.41 cm2∙V−1∙S−1, and 4.22 × 1012 cm−3, respectively.

Modeling the Effects of Soil Variability, Topography, and Management on the Yield of Barley

A better understanding of processes involved in crop production as well as the use of models as tools for managing agricultural systems are main reasons for the development of growth models. During the last three decades, the complexity of models increased from simple input-output relationships to highly sophisticated mechanistic process oriented models. Nevertheless, today, the simpler crop yield models have received a wider application, e.g., in management oriented decisions for plant production and in the evaluation of field experiments at multiple scales. The spatial variability considerably influences the experimental error variance which is particularly relevant in highly managed production experiments and in breeding nurseries. Therefore, the purpose of this study was to predict the yield of barley based on regressions and analysis of variance/covariance (ANOVA, ANCOVA) in a long-term static nitrogen fertilizer experiment receiving six different forms of nitrogen and three levels of nitrogen. The factors were the level of fertilization and the applied N-fertilizer forms. As covariates, the apparent soil electrical conductivity (ECa), relief parameters, and location coordinates were used. These covariates were served as proxies for site conditions. The apparent conductivity was measured with different sensors (EM38, EM38-MK2) and in all possible configurations. The ANOVA indicated smaller R2-values and higher root mean square differences (RMSD) in comparison to the ANCOVA ((fertilized plots ANOVA: R2 = 0.21, RMSD = 5.23 dt ha−1; ANCOVA: R2 = 0.845, RMSD = 2.30 dt ha−1). Besides the form and level of fertilization, conductivity readings were the most important covariates accounting for the averaged long-term yields. Looking at the individual years, ECa occurred in the ANCOVA models in five of 11 years, whereas topographic covariates (mainly variables with the parameter slope in the derivation) appeared in eight years in the models. The introduction of plot-wise, time-invariant soil and relief parameters improved the discrimination of testing and modelling the treatment performance within the long-term field trial. The high degree of explanatory power in yield prediction delivered by static soil parameters makes them highly attractive and can contribute to an improved evaluation of production oriented field experiments.

Cardiovascular and autonomic responses to passive arm or leg movement in men and women.

Women display an attenuated mechanoreflex during leg movement; however, sex differences in the response to arm movement are unknown. Men (n = 12) and women (n = 10) performed passive arm or leg movement where either the right elbow or right knee was passively flexed/extended for 3min at 30 times/min. Mean arterial pressure (MAP), cardiac output index (Qi), and heart rate (HR) were continuously measured and 1-min averages along with peak values were obtained. Heart rate variability was measured at baseline and throughout 3min of passive movement. Men had a greater average HR (P = 0.006) and Qi (P = 0.05) responses to passive limb movement compared to women. Men also had a greater (P = 0.02) and faster (P = 0.04) peak Qi response compared to women. During arm movement, men exhibited a greater change of average MAP compared to both women (P = 0.002) and leg movement (P = 0.05). Movement of either limb in both sexes decreased low-frequency power (LF; P = 0.04), decreased low-frequency to high-frequency ratio (LF/HF; P = 0.03), and increased high-frequency power (HF; P = 0.01) of heart rate variability. Women had lower pulse wave velocity (P = 0.02), higher root mean square of the successive differences (RMSSD; P = 0.04), lower LF power (P = 0.04), higher HF power (P = 0.03), and higher cardiovagal baroreceptor sensitivity (P = 0.003) compared to men at all time points. We have found sex- and limb-dependent responses where men exhibit higher blood pressure in response to passive arm movement compared to women and compared to leg movement.

Precipitable Water Vapour Retrieval from GPS Precise Point Positioning and NCEP CFSv2 Dataset during Typhoon Events.

Radiosonde is extensively used for understanding meteorological parameters in the vertical direction. Four typhoon events, including three landfalls (MERANTI, NEPARTAK, and MEGI) and one non-landfall (MALAKAS), were chosen in analysing the precipitable water vapour (PWV) characteristics in this study. The spatial distribution of the three radiosonde stations in Zhejiang province does not meet the requirement in analysing changes in PWV during typhoon event. Global position system (GPS) observations are an alternative method for deriving the PWV. This enables improvements in the temporal–spatial resolution of PWV computed by the radiosonde measurements. The National Centers for Environmental Prediction (NCEP) re-analysed data were employed for interpolating temperature and atmosphere pressure at the GPS antennas height. The PWV computed from GPS observations and NCEP re-analysed data were then compared with the true PWV. The maximum difference of radiosonde and GPS PWV was not more than 30 mm at Taiz station. The Root-Mean-Square (RMS) of PWV differences between radiosonde and GPS was not more than 5 mm in January, February, March, November, and December. It was slightly greater than 5 mm in April. High RMS in May, June, July, August, September, and October implies that differences in GPS and radiosonde PWVs are evident in these months. Correlation coefficients of GPS and radiosonde PWVs were more than 0.9, indicating that the changes in GPS and radiosonde PWVs are similar. Radiosonde calculated PWVs were used for GPS PWV calibration for understanding the PWV changes during the period of a typhoon event. The results from three landfall typhoons show that the average PWV over Zhejiang province is increasing and approaching China mainland. In contrast, MALAKAS did not make landfall and shows a decreasing PWV trend, although it was heading to China mainland. Generally, the PWV change can be used to predict whether the typhoon will make landfall in these cases. PWV spatial distribution of MERANTI shows that PWV peaks change along the typhoon epicenter over Zhejiang province.

In silico approach to identify non-synonymous SNPs with highest predicted deleterious effect on protein function in human obesity related gene, neuronal growth regulator 1 (NEGR1)

Neuronal growth regulator 1 (NEGR1) is a candidate gene for human obesity, which encodes the neural cell adhesion and growth molecule. The aim of the current study was to recognize the non-synonymous SNPs (nsSNPs) with the highest predicted deleterious effect on protein function of the NEGR1 gene. We have used five computational tools, namely, PolyPhen, SIFT, PROVEAN, MutPred and M-CAP, to predict the deleterious and pathogenic nsSNPs of the NEGR1 gene. Homology modeling approach was used to model the native and mutant NEGR1 protein models. Furthermore, structural validation was performed by the PROCHECK server to interpret the stability of the predicted models. We have predicted four potential deleterious nsSNPs, i.e., rs145524630 (Ala70Thr), rs267598710 (Pro168Leu), rs373419972 (Arg239Cys) and rs375352213 (Leu158Phe), which might be involved in causing obesity phenotypes. The predicted mutant models showed higher root mean square deviation and free energy values under the PyMoL and SWISS-PDB viewer, respectively. Additionally, the FTSite server predicted one nsSNP, i.e., rs145524630 (Ala70Thr) out of four identified nsSNPs found in the NEGR1 protein-binding site. There were four potential deleterious and pathogenic nsSNPs, i.e., rs145524630, rs267598710, rs373419972 and rs375352213, identified from the above-mentioned tools. In future, further functional in vitro and in vivo analysis could lead to better knowledge about these nsSNPs on the influence of the NEGR1 gene in causing human obesity. Hence, the present computational examination suggest that predicated nsSNPs may feasibly be a drug target and play an important role in contributing to human obesity.

Microstructural and optical properties of polyvinyl alcohol/manganese chloride composite film

Films of pure polyvinyl alcohol (PVA) and its manganese chloride filled polymer composite film (MPVA) were prepared and their optical properties were evaluated. XRD, UV–vis, and FTIR analyses reveal that there is strong interaction between polyvinyl alcohol and manganese chloride. Interchain separation (R) for pristine PVA and MPVA composite films was found as 5.60 and 4.69 Ǻ, respectively, thus showing polymer chains are more compact in MPVA. Optical band gap of polyvinyl alcohol was reduced on incorporation of manganese chloride in polyvinyl alcohol to cause approximately 2.5‐fold increase in optical conductivity. Refractive index of MPVA was found to be higher than that of PVA in the visible range up to 710 nm but beyond that it became lower than that of PVA. Abbe Number was decreased on incorporation of manganese chloride to PVA with concomitant increase in dispersion energy. Urbach energy (Eu) for PVA and MPVA was found to be 0.70 and 0.82 eV, respectively. AFM study reveals formation of sunflower like assembled texture at nano‐scale level in MPVA film and it exhibits a higher root mean square (RMS) roughness and absorbance than those of pristine PVA film. Average oscillation wavelength (λ0) was found to be close to the respective absorption edge; and MPVA showed higher oscillation strength (S0) than that of PVA. POLYM. COMPOS., 40:E765–E775, 2019. © 2018 Society of Plastics Engineers

Investigating Discharge Behaviour of a Sharp-Edged Circular Orifice Flow under Low Head from Unsteady Experimental Procedure and Computational Fluid Dynamics

A circular sharp-edged orifice is a hydraulic flow device used to measure and control the outflow from channels, detention ponds, reservoirs and tanks. In this study experimentation was carried out at the Soil and Water Conservation Laboratory, University of Ibadan to investigate the discharge coefficient Cd of circular sharp-edged orifice at low head. The experiment was conducted using four different orifice diameters (4.5, 6.0, 7.5, 9.0cm). Flow characteristics in Cd for each orifice diameter were observed. A relationship between Cd and likely independent variables that could affect Cd was determined from dimensional analysis. Simple and multiple regression models of these variables were established. The simulation experimentation of the flow was carried out using COMSOL Multiphysics with Navier-Stokes equation as the governing equation. Data were analysed using ANOVA at α0.05.It was found that the Cd increased as head reduced, and higher increase was observed at lower head. Coefficient of determination (R2) showed that 99.3% variability in Cd is due to Reynolds number-Re and Froude’s number-Fr but only significant at 4.5cm orifice diameter (P < 0.05). Simulation results were similar in trend to experimental results; however, 4.5cm orifice diameter had the highest Root Mean Square Error (RMSE) of 1.9877 for Cd and 0.029 for Fr and minimal errors observed as the diameter increased. This study demonstrated that Cd cannot be taken as a constant value when dealing with low head; however, the simulation was able to forecast the trend but could not predict the exact values.Keywords: Orifice, Computational Fluid Dynamics, Navier-Stokes equations, Discharge Coefficient, Open Channel flow.