EXPERIMENTAL AND THEORETICAL DETERMINATION OF STRUCTURAL, VIBRATIONAL, MOLECULAR, ELECTRONIC, NLO, NBO, AND THERMODYNAMIC CHARACTERISTICS OF PENTABROMOPHENOL AND PENTAFLUROPHENOL#.

Fourier Transform Raman (3500-100 \wn) and Fourier Transform infrared spectra (4000-400 \wn) were measured for Pentabromophenol (PBP) and Pentaflurophenol (PFP). UV-Visible (200-400 nm) spectrum, along with 1H and 13C NMR spectra were also recorded, for PBP. Torsional potentials, optimized structure parameters, barrier height to internal rotation, harmonic vibrational frequencies, general valance force field, potential energy distribution (PED), along with infrared and Raman intensities were evaluated, for PBP and PFP. DFT was used in conjunction with B3LYP functional with 6-311++G(d,p) basis set, for the computations. Scaling process was employed to get a better fit between the measured and computed frequencies. The rms error between them was 9.7 and 7.0 \wn, for PBP and PFP, respectively. Unambiguous vibrational assignments were arrived at by using PED and eigenvectors. In order to understand the nature of intermolecular hydrogen bond in these molecules geometry optimization was made for dimers of PBP and PFP. Further, using Gauge Independent Atomic orbital (GIAO) approach 1H and 13C NMR chemical shifts were evaluated and compared with corresponding experimentally measured shifts for PBP. In the same way, Time-dependent Density Functional Theory (TD-DFT) was used to simulate UV-Visible spectrum of PBP and compared with its experimental spectrum. HOMO and LUMO energies along with associated electronic parameters were generated. In order to find reactive sites in PBP and PFP molecular electrostatic surface potential (MESP) diagrams were drawn. The values of dipole moment, polarizability and hyperpolarizability of these molecules were computed to determine their NLO behavior. To understand the stability of the molecules (PBP and PFP) caused by charge delocalization, natural bond orbital (NBO) analysis was made for both PBP and PFP. Thermodynamic parameters were also evaluated for both the molecules. \\ Key words: Pentabromophenol, Pentaflurophenol, Vibrational spectra, Intermolecular hydrogen bond, DFT, Hyperpolarizability \# A part of this work appeared in J. Mol. Struct. 1180 (2019) 665-675 \

Bandwidth Enhancement in Microstrip Patch Antenna Using Rhombus Shape Slot

The Microstrip antennas are the low profile radiators. It is so because of their numerous features such as low volume, compactness, low fabrication cost and mechanical robustness. Numerous techniques have been suggested to improve the Microstrip patch antenna characteristics. In this paper we discuss the slot coupled patch antenna, one with a rectangular patch and other one with a rhombus shaped patch. And study the antenna characteristics of both the antenna such as bandwidth, radiation loss and gain. The results indicate the impact of changing patch on the antenna performance. To excite the structure the microstrip line is placed below the slot. The slot is made between the feed line and the radiating patch substrate. Fields from the microstrip line will be coupled to the patch through this narrow slot. ANSYS HFSS is used to carry out the procedure DOI: 10.17762/ijritcc2321-8169.150313

A NEW STABILITY-INDICATING RP-HPLC-PDA METHOD FOR SIMULTANEOUS ESTIMATION OF TRIPLICATE MIXTURE OF RAMIPRIL, ATORVASTATIN AND CLOPIDOGREL IN TABLET DOSAGE FORM

Objective: To develop a novel, accurate, precise and linear reverse phase high performance liquid chromatographic (RP-HPLC) method for simultaneous quantitative estimation of ramipril, atorvastatin and clopidogrel in Atamra-CV tablet and validate as per international conference on harmonization (ICH) guidelines and to perform the force degradation studies using the developed method.Methods: In the present work, the good chromatographic separation was achieved isocratically using a shim-pack HPLC Kromasil 150 mm x 4.6 mm, 5 m. m. And mobile phase consisting of 0.05 M potassium dihydrogen orthophosphate pH 3 adjusted with orthophosphoric acid and acetonitrile in the ratio (52:48), at flow rate 1 ml/min and column temperature (30 °C). The effluents obtained were monitored at 210 nm with the UV-visible detector.Results: The retention time of ramipril, atorvastatin and clopidogrel was found to be 2.893 min, 5.012 min and 6.102 min respectively. The linearity of ramipril, atorvastatin and clopidogrel was found in the range of 25-150 % and the correlation coefficient for ramipril, atorvastatin and clopidogrel were>0.999. The high recovery values (98%-101%) indicate a satisfactory accuracy. The low percent relative standard deviation (% RSD) values in the precision study reveals that the method is precise. The three-drug samples were subjected to stress conditions of acidic and alkaline hydrolysis, oxidation, photolysis and thermal degradation. The proposed method proved to be stability-indicating by resolution of the analytes from their forced-degradation products.Conclusion: The developed method is novel, simple, precise, rapid, accurate and reproducible for simultaneous estimation of ramipril, atorvastatin and clopidogrel tablet dosage form. Hence the proposed method may find practical applications as a quality-control tool in the simultaneous analysis of the three drugs in combined dosage forms in quality-control laboratories. The proposed method was made use of photodiode array (PDA) as a tool for peak identification and purity confirmation

REVERSED PHASE-HIGH PERFORMANCE LIQUID CHROMATOGRAPHY METHOD DEVELOPMENT AND VALIDATION OF ATORVASTATIN IN BULK DRUG AND FORMULATION

Objective: To develop and validate a simple, selective, rapid, precise, and accurate high performance liquid chromatographic (HPLC) method fordetermination of atorvastatin in bulk and its pharmaceutical formulation product.Method: Reversed phase-HPLC (RP-HPLC) method was performed by a mobile phase consisting mixture of methanol and ammonium acetate buffer(pH 4.5) in the proportion 60:40 v/v. A ZORBAX Eclipse plus C(4.6 mm × 100 mm, 3.5 μ) column was used as a stationary phase. HPLC analysis ofatorvastatin was carried out at a wavelength of 241 nm with a flow rate of 1 ml/minute.18 Results: The linear regression analysis data for the calibration curve showed a good linear relationship with a correlation coefficient 0.9984. Thelinear regression equation was y=3726540.2x+27390388.1. This was found to give a sharp peak of atorvastatin at a retention time of 2.77 minutes.Validation parameters were evaluated for the method according to the ICH (Q2R1) guidelines. The limit of detection and limit of quantification for themethod were 0.6721 μg/mL and 1.9989 μg/mL, respectively. The % relative standard deviation values for intra-day precision and inter-day precisionwere found to be 0.31% and 0.30%, respectively. An accuracy of the method was determined through recovery studies which were found to be within97.57-102.22%.Conclusion: The method was validated for system suitability, accuracy, precision, robustness, and ruggedness. The precision, accuracy, sensitivityshort retention time and composition of the mobile phase indicated that this method is better than the earlier methods developed for the quantificationof atorvastatin.Keywords: Atorvastatin, Reversed phase-high performance liquid chromatographic method development, Validation

Fault Diagnosis In Batch Process Monitoring

Every process plant nowadays highly complex to produce high-quality products and to satisfy de- mands in time. Other than that, plant safety is also crucial event had to be taken care to increase plant e�ciency. Due to poor monitoring strategies leads to huge loss of income and valuable time to regain its normal behavior. So, when there is any fault occurs in the plant it should be detected and need to take supervisory action before propagating it to new locations and new equipment failure leads to plant halt. Therefore process monitoring is very crucial event had to be done e�ectively. In Chapter 1 Importance of fault detection and diagnosis(FDD) in plant monitoring, what are the typical situations will leads to fault and their causes of fault is discussed. How data will be transformed in di�erent stages in diagnostic system before certain action, desirable characteristics for good diagnostic systems are discussed brie y. And in �nal part of this chapter what are the basic classi�cations of FDD methods are discussed. Principle component analysis is multivariate statistical technique helps to extract major information with few dimensions. Dimensionality of reduced space is very low compared to original dimension of data set. Number of principle component(PC) selection depends on variability or information required in lower dimensional space. So PCA is e�ective dimensionality reduction technique. But for process monitoring both PC and residual space are important. In chapter 2 mainly discussed about PCA and its theory. Batch Process Monitoring is relatively not easy to monitor compared to Continuous process be- cause of their dynamic nature and non-linearity in the data. So there are methods like MPCA(multi- way Principle component analysis), MCA(multi-way correspondence analysis) and Kernal PCA, Dis- similarity Index based(DISSIM) etc., are there to monitor batch process. Kernal based methods need to choose right kernal based on the non-linearity in the data. Dissimilarity Index based methods well suits for continuous process monitoring since it can able to detect the changes in distribution of data. Extension of DISSIM method to batch process monitoring is EDISSIM, which is discussed in chapter 3. And also MPCA is very traditional method which can able to detect abnormal sample but these cannot be able to detect small mean deviations in measurements. Multi Way PCA is applied after unfolding the data. Batch data Unfolding discussed in section 3.2 and selection of control lim- its discussed in 3.2.3. Apart from these methods there is another strategy called Pattern matching method introduced by Johannesmeyer. This method will helps to quickly locate the similar patterns in historical database. In Process industries we frequently collect the data so that there will be lot of data available. But there will be less information containing in it, used PCA to extract main information. In pattern matching strategy to detect the similar patterns in historical data base we need to provide some quantitative measure of similarity between two data sets those are similarity factors. So by using PCA method we are extracting high informative data in lower dimensional space. So Using PCA method similarity factors are calculated. Di�erent similarity factors and their calculation is shown in chapter 4. On-line monitoring of Acetone Butanol batch process discussed using pattern matching strategy. Acetone Butanol fermentation process mathematical model will be simulated to di�erent nominal values with di�erent operating conditions to develop historical database. In this case study there will be 500 batches with �ve operations conditions like one NOC and 4 di�erent faulty operation batches. In each batch there will be 100 batches. After calculation of similarity factors instead of going for candidate pool selection directly we are trying to detect the batches which are similar to snapshot data. Performance of On-line monitoring using pattern matching strategy is discussed. On-line monitoring strategy will change the way we are anticipating iv the un�lled data. Here we are trying to �ll with reference batch data. Reference data will be average of NOC batches. The performance of this method veri�ed in MATLAB as shown in section 4.3. In Chapter 5 described average PC's(Principle components) model. This method will helps to decrease the e�orts in candidate pool selection and evaluation to �nd snapshot data in historical database. And also Incremental average model building and model updating will improves the quality of model ultimately.In incremental average model building If any of the snapshot data classi�ed as any of the already existed operating condition data set it will be used in building average model. If not existed in any of the operating condition data set utilized to update average model. This method applied on Acetone Butanol fermentation process data and veri�ed. Because of the fact that batch data highly non linear in nature So PCA not able to handle non-linear correlations. And pattern matching approach using PCA average model not give good discrimination. For better discrimination ability and self aggregation can be possible using Corresponding Analysis because of non-linear scaling. In chapter 6 pattern matching approach using corresponding analysis has been discussed brie y. Results obtained using CA based similarity factor displayed for Acetone Butanol fermentation process case study

Current Control of Three Phase Grid – Connected PV Inverter Using Fuzzy Logic Controller

Distributed Generation (DG) is now widely employed in many electricity generation networks. It is mostly based on energy storage and renewable energy sources such as wind turbines (WT), photovoltaic cells (PV) and fuel cells to minimize pollution and greenhouse gas emissions. For large scale installations, a three phase power electronic inverter utilized to interface the source of renewable energy to the utility grid. The inverter and the associated control system are at the core of the energy conversion process and their operation is essential to inject high power quality, low harmonic distortion, current to the grid. For this reason international harmonic and power quality recommendations, such as IEEE Standard 519 and 1547, are often in place to limit the harmonic currents injected into the grid. Typically, 5% current total harmonic distortion (THD) limit is imposed. A Fuzzy controller is also implemented in this project in order to reduce the total harmonic distortion. In addition, the fuzzy and  adaptive PR controller offers superior output power regulation, and improved power quality performance. Results are analyzed through MATLAB/SIMULINK environmen

Improvement of Grid Current Compensator in Distributed Generation System

This paper Proposed a new current control topology for grid-connected based distributed generation (DG), which helps the DG to exchange a sinusoidal current into the utility grid despite the distorted grid voltage and nonlinear local load conditions. The proposed current controller is outlined in the synchronous reference casing and made out of a Fuzy controller. Consequently, the control methodology can be incredibly rearranged effectively. What's more, the proposed control strategy does not require the nearby load current estimation or symphonious investigation of the framework voltage. In this manner, the proposed control technique can be effectively embraced into the conventional DG control framework without establishment of additional equipment. In spite of the lessened number of sensors, the framework current quality is altogether progressed. The operation standard of the proposed control technique is examined in detail, and its viability is approved through watching absolute symphonious bending (THD) and the results verified through MATLAB/SIMULINK environment

Modified Firefly Optimization with Deep Learning based Multimodal Biometric Verification Model

Biometric security has become a main concern in the data security field. Over the years, initiatives in the biometrics field had an increasing growth rate. The multimodal biometric method with greater recognition and precision rate for smart cities remains to be a challenge. By comparison, made with the single biometric recognition, we considered the multimodal biometric recognition related to finger vein and fingerprint since it has high security, accurate recognition, and convenient sample collection. This article presents a Modified Firefly Optimization with Deep Learning based Multimodal Biometric Verification (MFFODL-MBV) model. The presented MFFODL-MBV technique performs biometric verification using multiple biometrics such as fingerprint, DNA, and microarray. In the presented MFFODL-MBV technique, EfficientNet model is employed for feature extraction. For biometric recognition, MFFO algorithm with long short-term memory (LSTM) model is applied with MFFO algorithm as hyperparameter optimizer. To ensure the improved outcomes of the MFFODL-MBV approach, a widespread experimental analysis was performed. The wide-ranging experimental analysis reported improvements in the MFFODL-MBV technique over other models

A prospective study on clinical profile and incidence of acute kidney injury due to hair dye poisoning

Background: Globally suicides are mounting at an alarming rate over the last few decades thus claiming the most productive age group of the society. Developing country like India is no exception to this needless increasing toll.Methods: This study was a prospective observational study with 31 patients recruited at Osmania General Hospital between November 2011 – October 2013. Patients of alleged hair dye ingestion admitted in MICU were taken up for study after the exclusion criteria were ruled out. Informed consent was obtained from every patient or patient’s relatives. All routine laboratory investigations were done basing on standard clinical procedures and protocols and patient related clinical information were recorded on the prepared proforma from the time of hospital admission till discharge or death. The presence of AKI was defined and graded as per the RIFLE criteria.Results: The present work examines 31 cases of suicidal ingestion of hair dye, out of which males were 6 (19.35%) and females were 25 (80.64%). It was observed that the tendency to commit suicide was more in the age group 21 -30 years with males (30%) and females (70%). 19% of total patients who ingested more than 50 ml of dye had developed Acute Kidney injury requiring hemodialysis. Upon treatment about 58% of patients were discharged from hospital in good general health condition, Four patients expired due to respiratory complications with pneumonia, ARDS, sepsis and ARF.Conclusions: So in current scenario of emerging hair dye poisoning, it is imperative for a timely intervention by reducing the time of admission in hospital and also early management by clinicians is the need of an hour

DEVELOPMENT AND VALIDATION OF STABILITY INDICATING REVERSE PHASE HIGH‑PERFORMANCE LIQUID CHROMATOGRAPHIC METHOD FOR THE ESTIMATION OF PIRIBEDIL IN BULK DRUG

ABSTRACTObjective: A simple, precise, fast, economic, accurate, robust, and stability indicating isocratic reverse phase high-performance liquid chromatographicmethod was developed for the analysis of Piribedil.Method: The chromatographic conditions were standardized using Unisol C-18 (4.6 × 150 mm × 3.0 μ) column with UV detection at 244 nm, and themobile phase composed of methanol:acetate buffer-pH 5.0 (85:15, v/v).Results: The retention time of Piribedil was found to be 3.4 minutes. The calibration curve was linear with correlation coefficient of 0.999 over aconcentration range of 20-100 μg/ml with linear regression equationy=74,69,224.37x−39,46,924.90. The limit of detection and limit of quantitationwere found to be 0.04 and 0.4 μg/ml, respectively.Conclusion: The proposed method has been validated according to the ICH guidelines. Piribedil was subjected to stress conditions includingacidic, alkaline, oxidation, photolysis, and thermal degradation. Piribedil is more sensitive to photolytic stress. There are no interfering peaks fromdegradation products at analyte retention time, and thus the method is specific for the estimation of Piribedil in the presence of degradation products.Thus, the proposed method can be successfully applied in the routine quality control and stability samples of Piribedil in bulk drug.Keywords: Piribedil, Validation, Stability indicating, Reverse phase high-performance liquid chromatographic