In medical practice, nonsteroidal anti-inflammatory drugs (NSAIDs) are often used to treat osteoarthritis and rheumatoid arthritis. Ibuprofen is a well-known NSAID, analgesic, and antipyretic medication. This chemical is an active ingredient of several oral medications that are offered in tablet, gel pellet, and syrup forms and has higher efficacy, tolerance, and side effect rates than other compounds, including pyrazolone derivatives. We present a unique plasma-assisted desorption/ionization mass spectrometry (PADI-MS) approach for improving pharmaceutically important solids using an ibuprofen tablet as a model solid sample. The goal of the study is to create an innovative mass spectrometric method that could be used for quick and accurate analysis in the development of pharmaceutically relevant compounds. Sniffer tubes were used to route sample ions into a single quadrupole MS, with each acquisition lasting for 1 minute. Without any prior preparation, samples of ibuprofen tablets were directly exposed to PADI plasma for one minute at an atmosphere pressure. The approach is rapid, easy to use, and needs little to no sample preparation. In this study, the settings were improved by optimization of several parameters, such as plasma power, plasma-to-sample distance, and inner/outer flows of helium carrier gas, which were found to be 8 W, 2 mm, and 284 mL/min, respectively. The PADI-MS method provides a real-time information about structural features on the compounds. Ibuprofen tablets were used as a paradigm for pharmaceutically significant materials and direct PADI-MS analysis without a preliminary sample -treatment appeared to be successful: according to PADI-MS data a medication can be examined after one minute of plasma exposure.
Background. Body mass index (BMI) is a person's weight in kilograms (or pounds) divided by the square of height in meters (or feet). Obesity affects a wide spectrum of age groups, from the young to the elderly, and there are several eye diseases related to obesity like diabetic retinopathy, floppy eyelid syndrome, retinal vein occlusion, stroke-related vision loss, age-related macular degeneration, and possibly, refractive errors. Refractive errors (RE) are optical imperfections related to the focusing ability of the eye and are the main cause of visual impairment which may result in missed education and employment opportunities, lower productivity and impaired quality of life. Aim. The study aimed to find an association between bod
... Show MoreAn investigation was conducted to suggest relations for estimating yield and properties of the improved light lubricating oil fraction produced from furfural extraction process by using specified regression.
Mass transfer in mixer-settler has been studied. Mass transfer coefficient of continuous phase, mass transfer coefficient of dispersed phase and the overall mass transfer coefficient extraction of light lubes oil distillate fraction by furfural are calculated in addition to all physical properties of individual components and the extraction mixtures.
The effect of extraction variables were studied such as extraction temperature which ranges from 70 to 110°C and solvent to oil ratio which ranges from 1:1 to 4:1 (wt/wt
... Show MoreThe inelastic longitudinal electron scattering form factors are calculated for the low-lying excited states of 7Li {the first excited state 2121TJ (0.478 MeV) and the second excited state 2127TJ (4.63 MeV)}. The exact value of the center of mass correction in the translation invariant shell model (TISM) has been included and gives good results. A higher 2p-shell configuration enhances the form factors for high q-values and resolves many discrepancies with the experiments. The data are well described when the core polarization (CP) effects are included through effective nucleon charge. The results are compared with other theoretical models.
Keyword: 7Li inelastic electron scattering form factors calculated with exact
This study proposed control system that has been presented to control the electron lens resistance in order to obtain a stabilized electron lens power. This study will layout the fundamental challenges, hypothetical plan arrangements and development condition for the Integrable Optics Test Accelerator (IOTA) in progress at Fermilab. Thus, an effective automatic gain control (AGC) unit has been introduced which prevents fluctuations in the internal resistance of the electronic lens caused by environmental influences to affect the system's current and power values and keep them in stable amounts. Utilizing this unit has obtained level balanced out system un impacted with electronic lens surrounding natural varieties.
The majority of real-world problems involve not only finding the optimal solution, but also this solution must satisfy one or more constraints. Differential evolution (DE) algorithm with constraints handling has been proposed to solve one of the most fundamental problems in cellular network design. This proposed method has been applied to solve the radio network planning (RNP) in the forthcoming 5G Long Term Evolution (5G LTE) wireless cellular network, that satisfies both deployment cost and energy savings by reducing the number of deployed micro base stations (BSs) in an area of interest. Practically, this has been implemented using constrained strategy that must guarantee good coverage for the users as well. Three differential evolution
... Show MoreThe issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
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