Reverse Phase Chromatographic Method of Analysis for Assay and Content Uniformity Estimation of Drug Substance Sitagliptin, Metformin and Empagliflozin from Available Marketed Formulation

A new method of analysis with reverse phase chemistry was designed and developed. Validation for method of analysis was performed for its intended use to calculate assay and content uniformity of drug substance sitagliptin, metformin and empagliflozin in the drug products. The method has a run time of 10 minutes on X-bridge C18 column having 250 mm length, 4.6 mm internal diameter and Particle Size of 5µm, by the use of 0.1% Trifluoroacetic acid Buffer 40%: Methanol 40%: Acetonitrile 20% ratio as constituent composition in the proposed mobile phase and chromatography run at wavelength of 224 nm. The retention time of Metformin, Empagliflozin and Sitagliptin, were 3.383, 5.571 and 6.429 minutes, respectively. International Conference on Harmonization guideline was referred for validation. The method showed adequate sensitivity for precision, linearity and accuracy parameter (between the range 25-75μg/mL, 250-750μg/mL and 2.5-7.5μg/mL for sitagliptin, metformin and empagliflozin respectively). The percentage recoveries obtained for sitagliptin, metformin and empagliflozin are in the range of 98.0 – 102.0 %. As results are within the acceptance [1], hence the new developed and proposed method is suitable for quantification of one, two or three component drugs, separately or in combination.

A Novel Analytical Method for Simultaneous Quantification of Silodosin and Tadalafil by RP-HPLC

The Reverse phase HPLC method was developed for simultaneous determination of Silodosin and Tadalafil in single analytical method. Chromatographic separation was achieved on a Supelco C8 (150mmx4.6mm, 5µm) column applying an isocratic elution based on premix of potassium phosphate dibasic buffer pH (4.3) and acetonitrile in the ratio of (70:30 v/v) as mobile. Validation parameters specificity, precision and robustness have been observed to be desirable over the concentration ranges of 80-240 µg/ml for Silodosin and 50-150 µg/ml for Tadalafil in accuracy parameter and 128-192 µg/ml for Silodosin and 80-120 µg/ml for Tadalafil in linearity parameter. All the variables have been studied to optimize the chromatographic conditions. The optimized approach verified through validation and confirmed to be intended purpose for the quality control of the mentioned drugs, as per ICH guidelines. For simultaneous quantification of Silodosin and Tadalafil, the developed method was found to be genuinely exact precise, accurate, linear, fast and cost effective.

Translation Quality Analysis of Japanese Oral Translation (Tsuyaku)

The oral translation course at the Japanese Language Education Study Program, Universitas Brawijaya does not impose special requirements for students who want to take it. For this reason, this study aims to analyse the quality of student’s oral translations and to determine the competencies that affect the results of student’s Japanese-Indonesian oral translations. In the translation quality, special parameters are used as measurement tools, which are: accuracy, fluency, and clarity. Meanwhile, the parameters to determine the competence that affects the translation results using the bilingual sub-competence, extralinguistic sub-competence, nation translation sub-competence, instrumental sub-competence, strategic sub-competence, psychological sub-competence. This research uses descriptive qualitative method. The data used in this study were the transcripts of the results of the oral translation exercises from the audio “Nihongo Soumatome Mondai” that was played. The data collection technique uses primary and secondary sources. The analysis in this study used Miles and Huberman theory (reduction, data display, and verification). The result of accuracy parameter is inaccurate and the fluency parameter of the most translated result is fluent. In the clarity parameter, the highest number of translated results is non-acceptable. This shows that although students are fluent, their translation result are not acceptable. Meanwhile, the translation competence that affects the translation results of students who take the tsuuyaku course is the lack of a bilingual sub-competency factor or mastery of the source language of a translator. Although they already had the basics of translation before, however, due to the low bilingual sub-competence, no matter how well the translation theory has been mastered, it is still difficult to produce an accurate and clear translation.

MEMS-Based Electrochemical Seismometer with a Sensing Unit Integrating Four Electrodes

This paper presents a new process to fabricate a sensing unit of electrochemical seismometers using only one silicon–glass–silicon bonded wafer. By integrating four electrodes on one silicon–glass–silicon bonded wafer, the consistency of the developed sensing unit was greatly improved, benefiting from the high alignment accuracy. Parameter designs and simulations were carried out based on this sensing unit, which indicated that the sensitivities of the developed electrochemical seismometer decreased with the decrease in the number of flow holes in the sensing unit, and the initial stabilization time decreased gradually with the decrease in the thickness of the glass layer. Based on experimental results of four devices, the peak sensitivity was quantified as 5345.45 ± 43.78 V/(m/s) at 2 Hz, which proved high consistency of the fabricated electrochemical seismometer. In terms of the responses to random ground motions, high consistencies between the developed electrochemical seismometer and the commercial counterpart of CME6011 (R-sensors, Moscow, Russia) were found, where the developed electrochemical seismometer produced comparable noise levels to those of CME6011. These results validated the performance of the device and it may function as an effective tool for a variety of applications.

High-Accuracy Parameter Estimation for Damped Signal via Three Weighted DFT Samples

Recently, accurate parameter estimation of the damped complex exponential plays an increasingly important role in the field of precise measurement. However, the estimation variance of interpolation-based algorithms for the parameter estimation cannot be asymptotic to the Crámer-Rao lower bound (CRLB). This paper originally proposes a generalized, fast, and the accurate two-iteration estimator (TIE) based on the discrete Fourier transform (DFT). It can be operated by an arbitrary window (symmetric or asymmetric window). Theoretical estimation variances of the frequency and the damping factor for arbitrary windows are derived, respectively. Furthermore, extensive computer simulations are performed to compare the performance of the TIE with other state-of-the-art algorithms in the literature. The results support the theoretical findings and verify that high-accuracy parameter estimation can be ensured by the proposed algorithm. More importantly, the estimation variances returned by the TIE with the rectangle window exactly track the CRLB for a damped single tone.

Performance Analysis of Machine Learning Algorithms Used for Web Based Phishing Detection

Phishing is a cybercrime technique in which the attacker creates a copy of genuine websites with the same color pattern, layout, font, and logo and with a domain name that matches with the real one. Then, broadcast this fake website through various online modes like emails and social media. The attacker creates lucrative offers or discounts to lure in people to click on the phishing link. Once the user clicks on this phishing link, they a re directed to the duplicate website that the attacker had created. The user believes that it is the real website and enters his/her login details and other confidential data. This data is stored on the attacker’s server thus giving him full access to the victim’s data. The phishing attack is mainly targeted to collect confidential data of the victim. This data includes Username, Passwords, Bank details, security Credit card numbers etc. Machine Learning algorithms are being used widely in detecting phishing websites. This paper shows performance analysis of three Machine learning algorithms used for URL phishing detection. These algorithms are Extreme Learning Machine, Support Vector Machine and Naïve Bayes algorithm. The paper analyses these algorithms on the parameters of Accuracy, Precision, Recall, F1 score and Confusion matrix. The dataset includes 11,000 entries and 30 features from UC Irvine dataset repository. The literature survey shows how only importance is given to only one parameter i.e., Accuracy parameter when analyzing performance of the URL phishing detection algorithms. This paper concludes on how Accuracy parameter does not show full picture on the overall performance of the URL phishing detection algorithms and also how Precision and Recall parameters are very important in understanding the working of these algorithms.

Spiking Neural Network with Linear Computational Complexity for Waveform Analysis in Amperometry

The paper describes the architecture of a Spiking Neural Network (SNN) for time waveform analyses using edge computing. The network model was based on the principles of preprocessing signals in the diencephalon and using tonic spiking and inhibition-induced spiking models typical for the thalamus area. The research focused on a significant reduction of the complexity of the SNN algorithm by eliminating most synaptic connections and ensuring zero dispersion of weight values concerning connections between neuron layers. The paper describes a network mapping and learning algorithm, in which the number of variables in the learning process is linearly dependent on the size of the patterns. The works included testing the stability of the accuracy parameter for various network sizes. The described approach used the ability of spiking neurons to process currents of less than 100 pA, typical of amperometric techniques. An example of a practical application is an analysis of vesicle fusion signals using an amperometric system based on Carbon NanoTube (CNT) sensors. The paper concludes with a discussion of the costs of implementing the network as a semiconductor structure.

An Analytical Model for the Stiffness of Slotted Disk Springs

The slotted disk spring is an important part of ultrasonic motors. Its mechanical properties directly affect the running stability of the motor. In this study, an analytical model is developed to solve the preload problem for slotted disk springs used in ultrasonic motors. The outer conical ring of the slotted disk spring is modeled using the conical shell theory. The inner separated teeth are modeled by the cantilever beam theory. An analytical mechanical model for the force-displacement relationship of the entire slotted disk spring is then developed. The results of the experiment based on a force-displacement transducer and the results from the analytical model, a finite element calculation, and the Schremmer formula are compared to validate the analytical model. The results show that the proposed model has the highest accuracy. Parameter-sensitivity analysis for the slotted disk spring is finally performed, and a new slotted disk spring with a long zero-stiffness interval is designed for a 40[Formula: see text]mm traveling wave rotary ultrasonic motor.

DEVELOPMENT OF COD (CHEMICAL OXYGEN DEMAND) ANALYSIS METHOD IN WASTE WATER USING SPECTRODIRECT

Increased human activities will cause various problems, one of which is water pollution in water sources because it receives a pollution load that exceeds its carrying capacity. In the context of environmental conservation, the government has set quality standards for liquid waste produced by various industries and other activities in a Decree of the State Minister for the Environment. COD (Chemical Oxygen Demand) is one of the most important parameters in wastewater quality standards. This study aims to validate the COD analysis method which refers to COD Thermoreactor System (LOVIBOND brand) at Pakuan University Service Laboratory, to ensure the validity of COD analysis results at Pakuan University Service Laboratory. Spectrodirect COD analysis method provides results that meet the requirements of accuracy, precision, LOD, and LOQ which is quite good. The results of the Coefficient of Variation give good results with a value of 1.8841% indicating the accuracy of the analysis method is good. The accuracy parameter also gives good results and meets the requirements with a% recovery value of 98.70351%. Overall, it can be stated that the spectrodirect analysis method tested is an accurate, precise, simple, and economical method for determining COD levels

Multiparameter Elastic Full Waveform Inversion of Ocean Bottom Seismic Four-Component Data Based on A Modified Acoustic-Elastic Coupled Equation

Ocean bottom seismometer (OBS) can record both pressure and displacement data by modern marine seismic acquisitions with four-component (4C) sensors. Elastic full-waveform inversion (EFWI) has shown to recover high-accuracy parameter models from multicomponent seismic data. However, due to limitation of the standard elastic wave equation, EFWI can hardly simulate and utilize the pressure components. To remedy this problem, we propose an elastic full-waveform inversion method based on a modified acoustic-elastic coupled (AEC) equation. Our method adopts a new misfit function to account for both 1C pressure and 3C displacement data, which can easily adjust the weight of different data components and eliminate the differences in the order of magnitude. Owing to the modified AEC equation, our method can simultaneously generate pressure and displacement records and avoid explicit implementation of the boundary condition at the seabed. Besides, we also derive a new preconditioned truncated Gauss–Newton algorithm to consider the Hessian associated with ocean bottom seismic 4C data. We analyze the multiparameter sensitivity kernels of pressure and displacement components and use two numerical experiments to demonstrate that the proposed method can provide more accurate multiparameter inversions with higher resolution and convergence rate.