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The current study developed a method for quantifying four drugs—Sulfamethoxazole, Trimethoprim, Isoniazid, and Pyridoxine—in rabbit plasma. The method uses gradient liquid chromatography based on analytical quality by design. To achieve separation, a Eclip Plus C18 (250 mm × 5 mm, 4.6 µm) column with L1 packing was used, and analytes were detected at 254 nm at ambient temperature. The optimized mobile phase consisted of 50 mM potassium dihydrogen phosphate buffer (pH 6.5) and Methanol. The concentration of Methanol was 3% (0–5 min), 15% (5–15 min), 55% (15–27 min), and 3% Methanol until the end of the 30-min runtime, and the flow rate was set at 0.95 mL/min. Control Noise Experimentation was used to screen studies, revealing that flow rate, pH, and Methanol concentration significantly affected the analytical attributes. The study identified critical attributes (resolution and asymmetric factor) and developed a quality target method profile. A central composition design was used to optimize the essential parameters. The method developed for the drugs showed peaks at retention times of 6.990 min for Isoniazid, 7.880 min for Pyridoxine, 15.530 min for Sulfamethoxazole, and 26.890 min for Trimethoprim, respectively. The method was validated with linearity in the range of 10–640 ng ml −1 , with R 2 of 0.9993, 0.9987, 0.9993, and 0.9992 for Sulfamethoxazole, Trimethoprim, Isoniazid, and Pyridoxine, respectively.

Compounds containing thiazole moieties, commonly referred to as thiazole derivatives, exhibit a broad range of biological activities encompassing antipsychotic, anticancer, analgesic, antiallergic, antihypertensive, antibacterial, anti-inflammatory, antimalarial, and antifungal properties. [...]these thiazole-containing scaffolds are pivotal constituents in over 70 experimental drugs, indicating the ongoing exploration and potential therapeutic applications of thiazole-derived compounds in pharmaceutical research and development. Most naturally occurring thiazole rings are found in microbial and marine sources. [...]thiazoles or compounds containing them have several uses as pharmacological agents, making thiazole an effective nucleus (Rajiani & Ismail, 2019; Singh et al., 2020) analgesic, anticancer, antibacterial, antiallergic, antihypertensive, antiinflammatory, antimalarial, antifungal and antipsychotic. According to molecular orbital techniques, thiazole molecules are aromatic and contain some dienic character, as evidenced by the pi-bond ordering. The boiling points of free thiazole lie between the range of 116°C to 118°C. Thiazole is characterized by its flammability and pale-yellow liquid form, emitting a fragrance similar to pyridine.

A simple, sensitive, accurate, precise, and reproducible UV- spectrophotometric method and RP-HPLC methods were developed and validated for the estimation of Famotidine and Ofloxacin in bulk drug and pharmaceutical formulation. The Linearity regression was detected and shows a good linear relationship; in the concentration range of 10-50µg/mL (R2 >0.9908) for famotidine and 10-50µg/mL (r2>0.9913) for ofloxacin. The UV – spectrophotometric estimation was carried out by the first-order derivative spectrophotometric method and absorbance were recorded at 273 and 280nm. Beers range were found to be 5-50µg/mL, respectively for both drugs while, correlation coefficient r2 > 0.9988 and 0.9941 for famotidine and ofloxacin. The isoabsorptive point was found to be 274nm in HPLC optimized mobile phase composition, potassium dihydrogen orthophosphate: methanol (60:40). Chromatographic condition consisted of mobile phase potassium dihydrogen orthophosphate buffer pH 2.3, methanol (60:40v/v), run time 30 min, C-18 column (ODS Hypersil) and flow rate 0.8mL/minute. The retention time for famotidine and ofloxacin were found to be 2.44 min, 7.99 min. respectively, and detection at λmax 274nm for both drugs (overlain spectra). The UV methods and RP-HPLC showed good reproducibility and recovery with the percent relative standard deviation (RSD) less than 5%. As per ICH guidelines, the developed method was validated for linearity, accuracy, precision, Sandell's sensitivity, and repeatability proving its utility in the estimation of famotidine and ofloxacin in house tablet formulation.

A precise and accurate liquid chromatography method was developed to simultaneously determine linagliptin and empagliflozin in spiked human plasma. The method utilized a C8 Eclipse Plus column (25cm X 5mm and 4.6µm) packed with L1 material, with a flow rate of 1mL/min. The mobile phase consisted of a mixture of acetonitrile, methanol, and 20mM potassium dihydrogen orthophosphate (pH 3.5) in a ratio of 26:19:55% (v/v). Detection was performed at 230nm, and the total run time was 15minutes. The retention time for linagliptin was 4.30 minutes, while for empagliflozin it was 10.35 minutes. The linear range for quantification was found to be 50-750 ng/mL for linagliptin and 30-960ng/mL for empagliflozin. The regression equations for linagliptin and empagliflozin were y = 181.24x+11241 and y = 393.64x+19552, respectively, with high regression coefficients (R2) of 0.9997 and 0.9995. Protein precipitation using a mixture of acetonitrile and methanol (70:30) was employed for extraction. The method demonstrated good recovery percentages ranging from 89.728±5.010 to 95.806±2.828 for linagliptin and 85.593±5.661 to 95.150±1.593 for empagliflozin. Extensive validation was conducted to assess linearity, accuracy, precision, recovery, and stability of the method.

Cognitive radio (CR) technology has evolved over the traditional radio to successfully utilize the unused frequency spectrum. In CR the secondary users (SUs) perform cooperative spectrum sensing to access the available frequency band. The opportunistic nature of sensing prevents any interference with primary users (PUs) in the network. However, the presence of security threats like malicious users (MUs) strongly influences the performance. In CR network, MUs act like normal SUs and transmit false information to the fusion center and degrades the performance. To overcome this issue, we proposed an extreme learning machine (ELM) based approach to classify the legitimate SUs with the MUs. In this work, ELM is used as a classifier to separate the legitimate SUs and MUs. Extensive simulation results are presented to highlight the effectiveness of the proposed approach. The proposed approach highlights significant improvement in terms of training time and provides better trade-off compare to the other competitive techniques in the literature.

Relative humidity (RH) sensors have been fabricated with polyaniline-encased multiwall carbon nanotube (MWCNT) matrix. MWCNT matrices were grown on oxidized Si substrates by catalytic chemical vapour deposition technique. The MWCNT matrices were made hydrophilic by acid treatment. The sensing properties of MWCNTs were improved by encasing the acid-treated MWCNT matrix with PANI. PANI was synthesized via in situ chemical oxidation technique using three acid dopants, named as 5-sulfosalicylic acid, 4-nitrobenzoic acid and hydrochloric acid (HCl). A growth time variation of the PANI was also performed from 1.5 to 2.5 h. The time-varying sensor resistance was recorded with RH change, and RH sensing properties of the corresponding sensors were investigated with the measured data. Doping variation exhibited that CNT–PANI sensor, fabricated with HCl dopant, showed the highest response (42.6% at 90% RH). Synthesis time variation of PANI from 1.5 to 2.5 h exhibited that with an increase in synthesis time, the sensor responsivities degraded from 42.6 to 19.5% at 90% RH. Excellent repeatability, linear response behaviour (R2 = 0.992), low hysteresis loss (± 2.68%) were exhibited by the fabricated RH sensing devices. A facile transfer technology was developed in order to transfer the MWCNT on PET substrate for fabrication of flexible RH sensor. A practical application on human respiration monitoring was demonstrated with the wearable and flexible RH sensors. The humidity sensing mechanism and electron transfer process were schematically explained with the aid of energy band diagram.

This article explores the scope of feature extraction and maximum entropy-based fuzzy clustering (MEFC) on eigenvalue-based cooperative spectrum sensing (CSS). The sensed primary user (PU) signal at secondary users (SUs) is pre-processed first by using principal component analysis (PCA). This pre-processed signal is sent to the fusion center (FC) for feature extraction. To extract the features, a two-stage procedure is adopted. In the first stage, the signal matrix is divided and then reassembled using ordered decomposition and recombination (ODAR) scheme. After the ODAR process, the covariance matrix and the corresponding eigenvalues are obtained. In the second stage, the features are selected based on the maximum, second maximum, and minimum eigenvalues to form a three dimensional (3D) feature vector. Feature vector obtained from measured eigenvalues are classified into channel available and unavailable class by performing clustering and classification in 3D space. The MEFC algorithm is used to train a classifier for spectrum sensing to avoid complex threshold derivation. The proposed algorithm is then compared with some of the recent decomposition-based feature extraction techniques for spectrum sensing. The results demonstrate that the proposed CSS method using the MEFC algorithm in multidimensional space provides an improvement in detection performance. This shows the effectiveness of the proposed algorithm to improve the performance of spectrum sensing.

ZnO nanorod-based UV photosensing devices are synthesized using one-pot synthesis method, and their sensing properties are studied with the variation of nanorod growth area. With the variation of electrode position for the maximum growth area, the UV photosensing properties are thoroughly examined. Structural, morphological and optical properties are studied using XRD, FEG-SEM, FEG-TEM and UV–VIS spectroscopy. AC electrical conductivity, dielectric measurements and modulus spectroscopy at room temperature in a frequency range from5 Hz to 5 MHz are performed. During the electrical conduction processes in the sample, the physical parameters of ZnO nanostructures such as dielectric constant, relaxation frequency and electrical conductivity are examined at dark and UV-illuminated condition. The dependence of conductivity, dielectric constants and modulus with frequency and UV on–off conditions are discussed. The correlation between response and recovery time with growth surface area of ZnO nanostructure is established with the help of complex impedance spectroscopy. The imaginary part of electrical modulus versus angular frequency is drawn, and the value of stretch exponent (β) is calculated for maximum and minimum surface area under dark and UV-illuminated condition from where the type of relaxation process is studied.

In this study, various morphological configurations of zinc oxide (ZnO) were fabricated onto the carbon nanotube (CNT) network by influencing the pH levels of the growth solution (specifically, pH values of 5, 7, and 9). The CNT network was fabricated using the thermal chemical vapour deposition method, while the ZnO nanostructure was synthesised using the chemical bath deposition technique. The growth of the multi-walled CNT network was confirmed by utilising field emission gun transmission electron microscopy and Raman spectroscopy. On the other hand, the investigation of the distinct morphology of pH-dependent ZnO on the CNT network was confirmed by employing field emission scanning electron microscopy. Three specific types of UV photo-sensing devices were manufactured utilising the synthesised samples, and a comprehensive investigation was conducted to analyse their UV-responsive characteristics. The analysis of the UV-responsive behaviour involved subjecting the devices to an array of UV LEDs. The intensity of the 365 nm UV LED array varied between 18.7 and 95.22 μW/cm 2 . For a device fabricated with ZnO grown at pH 5, the maximum photocurrent was recorded to be 40.7 ± 0.26 μA, and the external quantum efficiency was 5359 ± 73%. The device also showed remarkable responsivity to UV radiation with a pulsing frequency of 500 Hz. Exceptional response time and recovery time of 316 μs and 364 μs have been measured for the device.