Mean Value Of Correlation Coefficient Research Articles

Coastal Waveform Retracking for HY-2B Altimeter Data by Determining the Effective Trailing Edge and the Low Noise Leading Edge

As an important remote sensing technology, satellite altimetry provides a large amount of observations of sea surface height over the global ocean. In coastal areas, the accuracy of satellite altimetry data decreases greatly due to issues arise in the vicinity of land, related to poorer geophysical corrections and artifacts in the altimeter reflected signals linked to the presence of land within the instrument footprint. To improve the application of HY-2B altimetry data in coastal areas, this study proposes a coastal waveform retracking strategy for HY-2B altimetry mission, which depends on the effective trailing edge and the leading edge, which are less affected by coastal ‘contamination’, to retrieve accurate waveform information. The HY-2B pass 323 and pass 196 data are reprocessed, and the accuracy of the reprocessing results in the range of 0–40 km offshore is validated against the tide gauge data and compared with the HY-2B standard SGDR data. According to the analysis conclusion, the accuracy of the reprocessed data is higher than that of the SGDR data and has good performance within 15 km offshore. For the pass 323, the mean value of correlation coefficient and RMS of the reprocessed data against the corresponding tide gauge data are 0.893 and 45.1 cm, respectively, in the range within 0–15 km offshore, and are 0.86 and 33.6 cm, respectively, in the range beyond 15 km offshore. For the pass 196, the mean value of correlation coefficient and RMS of the reprocessed data against the corresponding tide gauge data in the range within 0–12 km offshore are 0.84 and 33.0 cm, respectively, and in the range within 0–5 km offshore to the island are 0.90 and 29.3 cm, respectively, and in the range beyond 5 km offshore to the island are 0.92 and 36.2 cm, respectively, which are all better than the corresponding values of the SGDR data, especially in the range closed to the land. The results indicate that the proposed coastal waveform retracking strategy for HY-2B altimetry greatly improves the quality of HY-2B altimetry data in coastal areas.

CNN-BiLSTM-Attention Model in Forecasting Wave Height over South-East China Seas

Though numerical wave models have been applied widely to significant wave height prediction, they consume massive computing memory and their accuracy needs to be further improved. In this paper, a two-dimensional (2D) significant wave height (SWH) prediction model is established for the South and East China Seas. The proposed model is trained by Wave Watch III (WW3) reanalysis data based on a convolutional neural network, the bi-directional long short-term memory and the attention mechanism (CNN-BiLSTM-Attention). It adopts the convolutional neural network to extract spatial features of original wave height to reduce the redundant information input into the BiLSTM network. Meanwhile, the BiLSTM model is applied to fully extract the features of the associated information of time series data. Besides, the attention mechanism is used to assign probability weight to the output information of the BiLSTM layer units, and finally, a training model is constructed. Up to 24-h prediction experiments are conducted under normal and extreme conditions, respectively. Under the normal wave condition, for 3-, 6-, 12- and 24-h forecasting, the mean values of the correlation coefficients on the test set are 0.996, 0.991, 0.980, and 0.945, respectively. The corresponding mean values of the root mean square errors are measured at 0.063 m, 0.105 m, 0.172 m, and 0.281 m, respectively. Under the typhoon-forced extreme condition, the model based on CNN-BiLSTM-Attention is trained by typhoon-induced SWH extracted from the WW3 reanalysis data. For 3-, 6-, 12- and 24-h forecasting, the mean values of correlation coefficients on the test set are respectively 0.993, 0.983, 0.958, and 0.921, and the averaged root mean square errors are 0.159 m, 0.257 m, 0.437 m, and 0.555 m, respectively. The model performs better than that trained by all the WW3 reanalysis data. The result suggests that the proposed algorithm can be applied to the 2D wave forecast with higher accuracy and efficiency.

VME-DWT: An Efficient Algorithm for Detection and Elimination of Eye Blink From Short Segments of Single EEG Channel.

Recent advances in development of low-cost single-channel electroencephalography (EEG) headbands have opened new possibilities for applications in health monitoring and brain-computer interface (BCI) systems. These recorded EEG signals, however, are often contaminated by eye blink artifacts that can yield the fallacious interpretation of the brain activity. This paper proposes an efficient algorithm, VME-DWT, to remove eye blinks in a short segment of the single EEG channel. The proposed algorithm: (a) locates eye blink intervals using Variational Mode Extraction (VME) and (b) filters only contaminated EEG interval using an automatic Discrete Wavelet Transform (DWT) algorithm. The performance of VME-DWT is compared with an automatic Variational Mode Decomposition (AVMD) and a DWT-based algorithms, proposed for suppressing eye blinks in a short segment of the single EEG channel. The VME-DWT detects and filters 95% of the eye blinks from the contaminated EEG signals with SNR ranging from -8 to +3 dB. The VME-DWT shows superiority to the AVMD and DWT with the higher mean value of correlation coefficient (0.92 vs. 0.83, 0.58) and lower mean value of RRMSE (0.42 vs. 0.59, 0.87). The VME-DWT can be a suitable algorithm for removal of eye blinks in low-cost single-channel EEG systems as it is: (a) computationally-efficient, the contaminated EEG signal is filtered in millisecond time resolution, (b) automatic, no human intervention is required, (c) low-invasive, EEG intervals without contamination remained unaltered, and (d) low-complexity, without need to the artifact reference.

Demosaicking based on channel-correlation adaptive dictionary learning

Image demosaicking is the problem of reconstructing color images from raw images captured using a digital camera with a color filter array. Sparse representation-based demosaicking method achieves superior performance on the commonly used Kodak dataset; however, it performs inferior on the IMAX dataset. We analyze that the factor of the sparse representation-based demosaicking methods that perform inconsistently is channel-correlation, which we define as the mean value of correlation coefficients between the RGB channels. Accordingly, we propose a channel-correlation adaptive dictionary learning-based demosaicking method. Different from the sparse representation-based demosaicking methods that use a fixed dictionary, our method trains a general dictionary on training image patches with various channel-correlations. Then, we learn a function matrix between the general dictionary and channel-correlations. For a raw image patch with an estimated channel-correlation, we compute a dictionary corresponding to its channel-correlation through the function matrix. Finally, we demosaick it with the corresponding dictionary using the sparse representation model. Experiments confirm that the proposed method performs adaptively well on raw images with various channel-correlations.

Correlation between corrosion indices and corrosiveness of groundwater: a study with reference to selected areas of Krishna District, Andhra Pradesh, India

The aim of the present study was to determine the aggressiveness of groundwater samples towards corrosion of various commercially important metals and to study the correlation between theoretical and experimental values of corrosiveness. For this purpose, 20 groundwater samples were collected in different mandals of Krishna District, Andhra Pradesh, India, and the metals selected were carbon steel, aluminium, copper and cupronickel alloy. The corrosiveness was determined by using gravimetric measurements. Further, corrosion and scaling indices, namely Langelier index (LI), aggressive index (AI), Ryznar index (RI), Puckorius index (PI) and Larson–Skold index (LS), were calculated with the help of various water quality parameters of all the samples to estimate their corrosivity. The experimental values of corrosion rates were attempted to correlate with various indices calculated and quality parameters determined in case of all the samples. It is observed that there is a significant lack of correlation between the indices and corrosion rates. Among the five indices taken into account, LI, AI and RI indicate scaling tendency of water samples, as inferred by their mean values, 0.657, 12.576 and 6.612, respectively, while the other two indices, PI and LS with the mean values of 8.141 and 1.188, respectively, suggest the corrosive behaviour. Further, the mean values of correlation coefficients, 0.18 and 0.27 for PI and LS, respectively, are higher compared with those for LI, AI and RI. The mean values of correlation coefficients of dissolved oxygen, chlorides and electrolytic conductivity are 0.33, 0.25 and 0.25, respectively, which are relatively higher compared with those of other quality parameters. The probable reasons for low correlation coefficients are explored based on the statistical data. Also, it was concluded that one of the significant factors, namely dissolved oxygen which has strong influence on corrosion of metals, was considered in none of the indices, leading to very low correlation between the theoretical and experimental values of corrosiveness.

3D Correlation Mapping between Changes in Cartilage T1ρ and Thickness Over 1-year after ACL Reconstruction using Atlas-based Methods

Purpose: Subjects with anterior cruciate ligament (ACL) injury are at risk for post-traumatic osteoarthritis (PTOA). T1ρ MRI has been used to detect early degeneration after ACL injury and reconstruction. Previous studies also revealed significant changes in cartilage thickness after ACL injury, with thickness increasing in some compartments while decreasing in other compartments. However, the correlation between the change in T1ρ and the change in cartilage thickness has not been demonstrated. A better understanding of these correlations will help with staging the cartilage degeneration status after ACL injury. Very recently, a novel atlas-based method was developed which permits voxel-based relaxometry analysis (VBR). The goal of this study was to apply the atlas-based method to evaluate the local voxel-by-voxel correlation between changes in T1ρ and changes in thickness from baseline to 6-months and 1-year after ACL reconstruction (ACLR). Methods: Bilateral knees were scanned using a 3T MRI scanner for twenty-five patients with ACL injuries prior to surgical reconstruction (baseline, BL), and 6-months (6M) and 1-year (1Y) after ACLR (age = 28.4 ± 8.2 years, BMI = 23.8± 2.7 kg/m2, 10 female). The imaging protocol included the 3D MAPSS T1ρ/T2 sequence used for cartilage relaxation times quantification and high-resolution 3D FSE (CUBE) used for WORMS grading and semi-automatic cartilage segmentation. Those segmentations were used to define a voxel based thickness map for each subject. An atlas based registration approach was then used to morph all the T1ρ-weighted images and the thickness maps to the same reference space, and T1ρ maps were computed in the atlas space allowing for voxel-by-voxel correspondence between T1ρ and thickness. Longitudinal changes in cartilage thickness and T1ρ, as well as the local Pearson correlation coefficients between changes in T1ρ and changes in thickness were calculated voxel-by-voxel. Both analyses were adjusted for age, gender and BMI. The level of significance was set at p<0.05. Percentage of significant voxel (PSV, %) with positive or negative correlation and the mean value of correlation coefficients (R) were calculated in each compartment. Results: Significant increases of T1ρ in MFC and trochlea, and significant decreases of T1ρ in patella were observed; while significant increases of cartilage thickness in patella and significant decreases of cartilage thickness in trochlea were observed (Fig. 1 A–B). The most significant correlation between changes in T1ρ and changes in thickness was observed in patella, LFC, trochlea and MFC (Fig. 1C). In the patella, significant negative correlation was found between changes in T1ρ and changes in thickness from BL to 6M (38.4% voxels, R=−0.536) and from BL to 1Y (15.1% voxels, R=−0.590) (Tab1). This correlation was primarily the result of a decrease in T1ρ and an increase in thickness, while in other compartments, the negative correlations primarily resulted from an increase in T1ρ and a decrease in thickness. From 6M to 1Y, in LFC, a large decrease of the positive correlation PSV (from 11.2% to 2.5%) and a slight increase of negative correlation PSV were observed. There is an increasing trend of the total cartilage WORMS scores from BL (2.0±2.1) to 6M (2.2±2.1) and 1Y (2.4±2.3), but the increase was not significant. Conclusions: In this study, the local correlation between changes in cartilage matrix composition and changes in cartilage thickness was analyzed voxel-by-voxel using a novel 3D atlas-based method. Significant correlations were observed between ΔT1ρ and ΔΤhickness from BL to 6M and 1Y after ACLR. A positive correlation with increase in T1ρ and thickness may suggest the cartilage is at very early stages of degeneration with tissue swelling; while a negative correlation with increase in T1ρ and decrease in thickness may suggest later stages that cartilage begins to experience tissue loss. From 6M to 1Y, there is a general trend of decreasing positive correlation percentage while an increasing negative correlation percentage (Figure 2) in the femoral condyles and trochlea, suggests a progression of cartilage degeneration, confirmed by change in WORMS. In patella, the negative correlation was driven by the decrease of T1ρ and increase of thickness, which may be associated with changes in loading to patella-femoral joint (PFJ) as well as changes in activities after ACLR. Longer follow-up analysis is warranted to better understand cartilage degeneration progression after ACL injury. Funding from NIH/NIAMS P50 AR060752.

Comparing the structure of an emerging market with a mature one under global perturbation

In this paper we investigate the Tehran stock exchange (TSE) and Dow Jones Industrial Average (DJIA) in terms of perturbed correlation matrices. To perturb a stock market, there are two methods, namely local and global perturbation. In the local method, we replace a correlation coefficient of the cross-correlation matrix with one calculated from two Gaussian-distributed time series, whereas in the global method, we reconstruct the correlation matrix after replacing the original return series with Gaussian-distributed time series. The local perturbation is just a technical study. We analyze these markets through two statistical approaches, random matrix theory (RMT) and the correlation coefficient distribution. By using RMT, we find that the largest eigenvalue is an influence that is common to all stocks and this eigenvalue has a peak during financial shocks. We find there are a few correlated stocks that make the essential robustness of the stock market but we see that by replacing these return time series with Gaussian-distributed time series, the mean values of correlation coefficients, the largest eigenvalues of the stock markets and the fraction of eigenvalues that deviate from the RMT prediction fall sharply in both markets. By comparing these two markets, we can see that the DJIA is more sensitive to global perturbations. These findings are crucial for risk management and portfolio selection.

Validated HPTLC method of analysis for artemether and its formulations

A simple, sensitive, precise and rapid high-performance thin-layer chromatographic (HPTLC) method of analysis for artemether both as a bulk drug and in pharmaceutical formulations was developed and validated. The method employed TLC aluminum plates precoated with silica gel 60F-254 as the stationary phase. The solvent system consisted of toluene–ethyl acetate–formic acid (8:2:0.3, v/v/v) as mobile phase. Densitometric analysis of artemether was carried out in the reflectance mode at 565 nm. The system was found to give compact spots for artemether ( R f value of 0.50 ± 0.03). The linear regression analysis data for the calibration plots showed good linear relationship with r 2 = 0.9904 in the concentration range 200–1000 ng per spot. The mean value of correlation coefficient, slope and intercept were 0.9904 ± 0.011, 7.27 ± 0.11 and 166.24 ± 56.92, respectively. The method was validated for precision, accuracy, recovery and robustness. The limits of detection and quantitation were 65.91 and 197.74 ng per spot, respectively. The method has been successfully applied in the analysis of lipid based parenteral formulations and marketed oral solid dosage formulation.

Stability indicating high-performance thin-layer chromatographic determination of nelfinavir mesylate as bulk drug and in pharmaceutical dosage form

A sensitive, selective, precise and stability indicating high-performance thin-layer chromatographic method of analysis of nelfinavir mesylate both as a bulk drug and in formulations was developed and validated. The method employed TLC aluminium plates precoated with silica gel 60F-254 as the stationary phase. The solvent system consisted of toluene–methanol–acetone (7:1.5:1.5, v/v/v). This system was found to give compact spots for nelfinavir mesylate ( R f value of 0.45±0.02). Nelfinavir mesylate was subjected to acid and alkali hydrolysis, oxidation, dry heat treatment and photodegradation. Also the peaks of degraded products were well resolved from the pure drug with significantly different R f values. Densitometric analysis of nelfinavir mesylate was carried out in the absorbance mode at 250 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r 2=0.999±0.002 in the concentration range of 1000–6000 ng per spot. The mean value of correlation coefficient, slope and intercept were 0.999±0.002, 0.014±0.001 and 21.73±1.26, respectively. The method was validated for precision, robustness and recovery. The limits of detection and quantitation were 60 and 140 ng per spot, respectively. Statistical analysis proves that the method is repeatable and selective for the estimation of the said drug. As the method could effectively separate the drug from its degradation products, it can be employed as a stability indicating one.

Stability indicating HPTLC determination of clopidogrel bisulphate as bulk drug and in pharmaceutical dosage form

A sensitive, selective, precise and stability indicating high-performance thin layer chromatographic method of analysis of clopidogrel bisulphate both as a bulk drug and in formulations was developed and validated in pharmaceutical dosage form. The method employed TLC aluminium plates precoated with silica gel 60F-254 as the stationary phase. The solvent system consisted of carbon tetrachloride–chloroform–acetone (6:4:0.15, v/v/v). This system was found to give compact spots for clopidogrel bisulphate (R f value of 0.30±0.01). Clopidogrel bisulphate was subjected to acid and alkali hydrolysis, oxidation, photodegradation and dry heat treatment. Also the degraded products were well separated from the pure drug. Densitometric analysis of clopidogrel bisulphate was carried out in the absorbance mode at 230 nm. The linear regression data for the calibration plots showed good linear relationship with r 2=0.999±0.001 in the concentration range of 200–1000 ng. The mean value of correlation coefficient, slope and intercept were 0.999±0.001, 0.093±0.011 and 8.83±0.99, respectively. The method was validated for precision, accuracy, ruggedness and recovery. The limits of detection and quantitation were 40 and 120 ng per spot, respectively. The drug undergoes degradation under acidic and basic conditions, oxidation and dry heat treatment. All the peaks of degraded product were resolved from the standard drug with significantly different R f values. This indicates that the drug is susceptible to acid–base hydrolysis, oxidation and dry heat degradation. Statistical analysis proves that the method is reproducible and selective for the estimation of the said drug. As the method could effectively separate the drug from its degradation products, it can be employed as a stability indicating one.

Stability-indicating HPTLC determination of tizanidine hydrochloride in bulk drug and pharmaceutical formulations

A simple, selective, precise and stability-indicating high-performance thin-layer chromatographic method of analysis of tizanidine hydrochloride both as a bulk drug and in formulations was developed and validated. The method employed TLC aluminium plates precoated with silica gel 60F-254 as the stationary phase. The solvent system consisted of toluene–acetone–ammonia (5:5:0.1, v/v/v). This system was found to give compact spots for tizanidine hydrochloride ( R f value of 0.32±0.01). Tizanidine hydrochloride was subjected to acid and alkali hydrolysis, oxidation and photodegradation. Also, the degraded product was well separated from the pure drug. Densitometric analysis of tizanidine hydrochloride was carried out in the absorbance mode at 315 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r 2=0.9922 in the concentration range 300–1000 ng per spot. The mean value of correlation coefficient, slope and intercept were 0.9922±0.002, 0.064±0.001 and 38.09±1.71, respectively. The method was validated for precision, recovery and robustness. The limits of detection and quantitation were 88 and 265 ng per spot, respectively. The drug does not undergo degradation under acidic and basic conditions. The samples degraded with hydrogen peroxide showed additional peak at R f value of 0.12. This indicates that the drug is susceptible to oxidation. Statistical analysis proves that the method is repeatable and selective for the estimation of said drug. As the method could effectively separate the drug from its degradation product, it can be employed as a stability-indicating one.

Stability Indicating HPTLC Determination of Linezolid as Bulk Drug and in Pharmaceutical Dosage Form

A simple, selective, precise, and stability-indicating high-performance thin layer chromatographic method of analysis of Linezolid both as a bulk drug and in formulations was developed and validated in pharmaceutical dosage form. The method employed TLC aluminium plates precoated with silica gel 60F-254 as the stationary phase. The solvent system consisted of toluene–acetone (5:5, v/v). This system was found to give compact spots for Linezolid (Rf value of 0.29 ± 0.01). Linezolid was subjected to acidic, alkali hydrolysis, oxidation, and photodegradation. The degraded products also were well separated from the pure drug. Densitometric analysis of Linezolid was conducted in the absorbance mode at 254 nm. The linear regression data for the calibration plots showed good linear relationship with r2 = 0.997 ± 0.001 in the concentration range of 300–800 ng/spot. The mean value of correlation coefficient, slope, and intercept were 0.998 ± 0.003, 0.15 ± 0.009, and 19.52 ± 1.66 respectively. The method was validated for precision, accuracy, ruggedness, and recovery. The limits of detection and quantification were 20 ng/spot and 50 ng/spot, respectively. The drug undergoes degradation under acidic and basic conditions, oxidation and photo degradation. All the peaks of degraded product were resolved from the standard drug with significantly different Rf values. This indicates that the drug is susceptible to acid–base hydrolysis, oxidation, and photo degradation. Statistical analysis proves that the method is reproducible and selective for the estimation of the said drug. Because the method could effectively separate the drug from its degradation products, it can be used as a stability indicating one.

Simplified in-line sample preparation for amino acid analysis in carbohydrate containing samples

This report describes a new, automated chromatographic procedure eliminating carbohydrates from amino acid samples prior to their analysis by anion-exchange chromatography and integrated amperometric detection. In the first step, a sample is brought onto a short cation-exchange column (trap column) in hydrogen form. Carbohydrates are passing through this column, while only amino acids are retained. Subsequently, the cation-exchange column, holding the amino acid fraction, is switched in-line with the gradient pump and separator column. The mobile phase used at the beginning of the separation (NaOH; pH 12.7) transfers amino acids from the trap column onto the anion-exchange column and the amino acid separation is completed without any interference by carbohydrates. All common amino acids are recovered following the carbohydrate removal step. The average value of their recovery is 88.1%. The calibration plots were tested between 12.5 and 500 pmol (amounts injected). The mean value of correlation coefficients of calibration plots was calculated as 0.99. The mean value of relative standard deviations from five replicates was 3.9%. The usefulness of the method is illustrated with two chromatograms of a carrot juice sample obtained before and after the in-line removal of carbohydrates.

HPTLC determination of nimesulide from pharmaceutical dosage forms.

A simple, rapid, reproducible and stability indicating high performance thin-layer chromatographic method for the analysis of Nimesulide both the bulk drug and from pharmaceutical formulations is reported. The mobile phase selected consists of Cyclohexane-Ethylacetate [60:40, v/v]. It gave compact spots both for Nimesulide and its degraded products at Rf values 0.44 and 0.712, respectively. Densitometric analysis of nimesulide was carried out at 295 nm. The calibration curve of Nimesulide in methanol was linear in the range of 100-900 ng. The mean value of correlation coefficient, slope and intercept were 0.9989+/-0.0011, 504.655+/-0.0013 and 85331.56+/-0.0253, respectively. The limits of detection and quantitation were 60 and 100 ng, respectively. The drug content was within the limits (+/-5% of the labelled content of the formulations). The recovery of Nimesulide was about 99.5%.

Trimetazidine: stability indicating RPLC assay method.

An accurate, specific and reproducible reversed phase liquid chromatographic method for the determination of trimetazidine hydrochloride in presence of its degradation products is reported. The mobile phase consisted of water-acetonitrile-triethylamine (90:10:0.1, v/v/v) adjusted with o-phosphoric acid to a pH of 3.3. Chromatography was performed using C-18 column at a flow rate of 1.0 ml/min and the drug along with its degraded products was detected at 270 nm. The calibration curve of trimetazidine hydrochloride in methanol was linear in the range 500-3000 ng. The mean value of correlation coefficient, slope and intercept were 0.99859 &# 0.001, 17.7986 &# 0.0709 and 482.56 &# 147.03, respectively. The limits of detection and quantitation were 5 and 20 ng, respectively. The recovery of trimetazidine hydrochloride was about 99-100%. This method was utilized to analyze trimetazidine hydrochloride from conventional tablets and controlled release pellets in the presence of commonly used excipients.

Stability indicating HPTLC determination of Trimetazidine as bulk drug and in pharmaceutical formulations.

A simple, selective, precise and stability-indicating high-performance thin-layer chromatographic method of analysis of trimetazidine hydrochloride both as a bulk drug and in formulations is reported. The mobile phase composition was n-butanol-water-methanol-ammonia (20%) (14:0.2:0.2:2, v/v/v/v). Densitometric analysis of trimetazidine hydrochloride was carried out in the absorbance mode at 254 nm. the calibration curve of trimetazidine hydrochloride in methanol was linear in the range 400 -- 2400 ng. The mean value of correlation coefficient, slope and intercept were 0.99815 and #61617;0.001, 0.4849 and #61617;0.001 and 31.633 and #61617;5.996 respectively. The limits of detection and quantitation were 50 and 80 ng respectively. The recovery of trimetazidine hydrochloride was about 98 -- 100%. This method was utilized to analyze trimetazidine hydrochloride from conventional tablets and controlled release pellets in the presence if commonly used excipients.

High-performance thin-layer chromatographic determination of diltiazem hydrochloride as bulk drug and in pharmaceutical preparations

A simple, rapid, selective and precise high-performance thin-layer chromatographic method for the analysis of diltiazem hydrochloride both as a bulk drug and in pharmaceuticals is reported. The mobile phase composition was ethyl acetate–methanol–strong ammonia solution (80:10:10, v/v). Densitometric analysis of diltiazem hydrochloride was carried out at 238 nm. The calibration curve of diltiazem hydrochloride in distilled water was linear in the range 40–400 ng. The mean value of correlation coefficient, slope and intercept were 0.997±0.0008, 0.0617±0.0012 and 7.16±0.2562, respectively. The limits of detection and quantitation were 20 ng and 40 ng, respectively. The recovery of diltiazem hydrochloride was about 99.5%. The method was utilized to analyse diltiazem hydrochloride from conventional and sustained release tablets in the presence of commonly used excipients.

Direct Densitometry of Paper Chromatograms of Food Colors and Other Dyes by Transparent Methods

A method for the quantitative analysis of 8 kinds of food colors and 8 kinds of similar dyes, of which 12 dyes were water-soluble and 4 were oil-soluble, was presented. The method consist of paper chromatography and direct densitometry of the resultant spot peak areas on the spots of paper chromatograms transparently scanned through the filter with approximately maximum wave length of each dye in the visible region.As the result, the integrated readings of peak areas on the spots were approximately proportional to the root square of dye amounts or concentrations. In the total regression equations between peak areas and the root squares of dye amounts, mean value of correlation coefficient was 0.992 with the slit (0.5×5.0mm).