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As an appropriate quantity of hydroquinone (HQ) is essential to safeguard inhibition characteristics by eliminating the risk of self-polymerization of vinyl acetate monomer (VAM), the determination of the HQ content in VAM is very crucial to ensure the stability of VAM during storage and transportation as well as to achieve the possibility of a proper polymerization reaction. In this study, a simple, cheap, time-saving, and easy method has been developed by which the HQ content in VAM can be measured quickly based on the measurement of UV-Vis absorbance of the HQ content at 293 nm using methanol as a blank. No color development is required for this determination process, and the HQ content in the VAM can be measured directly without any further processing. The limit of detection, limit of quantification, linearity range, accuracy, precision, robustness, and measurement uncertainty of this method have been measured and analyzed and found to be within the acceptable limit and range. The method shows linearity within 0.36–25.0 ppm HQ content in the solution range with a regression coefficient of 0.9999, a relative spike recovery of 101.35%, precision of 1.36%, relative bias of 0.55%, and robustness with a temperature variation of −5 °C.

Tea is the third most consumed beverage in Saudi Arabia (a country in the Middle East) after water and Arabian coffee. Hence, a large amount of consumed tea leaves is discarded as solid waste. Waste tea leaves (WTLs) have no commercial value and could be considered as an environmentally sustainable costless material. This work aimed to manufacture an adsorbent material from the discarded WTLs and charge-transfer (CT) interaction and use this adsorbent material effectively for the removal of different kinds of pollutants from water. The adsorbent material was manufactured in three steps. First, a CrFeO3 metal composite was synthesized from the CT interaction between FeCl3 and CrCl3 with urea. Second, activated carbons were prepared from consumed WTLs using facile and clean treatments of pre-carbonization, and a simple potassium hydroxide (KOH) activation treatment. Finally, the adsorbent material was fabricated by grounding CrFeO3 composite with the activated carbons in a 1:10 molar ratio (metal composite to activated carbons). The prepared materials were characterized spectroscopically and morphologically using FT-IR, XRD, SEM/EDX, and TEM analysis. The synthesized absorbent material was used to adsorb two organic dyes (Azocarmine G2; M1, and Methyl violet 2B; M2), and two commercial pesticides (Tiller 480SL; M3, and Acochem 25% WP; M4) from aqueous solution, and it showed promising adsorption efficacy. The minimum adsorbent material’s dosage to obtain a maximum removal efficiency (R%) for M1, M2, M3, and M4 removal from 100 mL solution (100 mg/L) was 0.11, 0.14, 0.13, and 0.12 g, respectively. The max R% for M1 (96.8%) was achieved in the first 45 min, the max R% for M2, 95.5%, was achieved during the first 55 min, and the max R% for M3 (96.4%) was achieved in the first 35 min, while the max R% for M4, 98.6%, was achieved during the first 35 min.

Biliary fibrosis is the driving pathological process in cholangiopathies such as primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). Cholangiopathies are also associated with cholestasis, which is the retention of biliary components, including bile acids, in the liver and blood. Cholestasis may worsen with biliary fibrosis. Furthermore, bile acid levels, composition and homeostasis are dysregulated in PBC and PSC. In fact, mounting data from animal models and human cholangiopathies suggest that bile acids play a crucial role in the pathogenesis and progression of biliary fibrosis. The identification of bile acid receptors has advanced our understanding of various signaling pathways involved in regulating cholangiocyte functions and the potential impact on biliary fibrosis. We will also briefly review recent findings linking these receptors with epigenetic regulatory mechanisms. Further detailed understanding of bile acid signaling in the pathogenesis of biliary fibrosis will uncover additional therapeutic avenues for cholangiopathies.

Breakout is one of the major accidents that often arise in the continuous casting shops of steel slabs in Bokaro Steel Plant, Jharkhand, India. Breakouts cause huge capital loss, reduced productivity, and create safety hazards. The existing system is not capable of predicting breakout accurately, as it considers only one process parameter, i.e., thermocouple temperature. The system also generates false alarms. Several other process parameters must also be considered to predict breakout accurately. This work has considered multiple process parameters (casting speed, mold level, thermocouple temperature, and taper/mold) and developed a breakout prediction system (BOPS) for continuous casting of steel slabs. The BOPS is modeled using an artificial neural network with a backpropagation algorithm, which further has been validated by using the Keras format and TensorFlow-based machine learning platforms. This work used the Adam optimizer and binary cross-entropy loss function to predict the liquid breakout in the caster and avoid operator intervention. The experimental results show that the developed model has 100% accuracy for generating an alarm during the actual breakout and thus, completely reduces the false alarm. Apart from the simulation-based validation findings, the investigators have also carried out the field application-based validation test results. This validation further unveiled that this breakout prediction method has a detection ratio of 100%, the frequency of false alarms is 0.113%, and a prediction accuracy ratio of 100%, which was found to be more effective than the existing system used in continuous casting of steel slab. Hence, this methodology enhanced the productivity and quality of the steel slabs and reduced substantial capital loss during the continuous casting of steel slabs. As a result, the presented hybrid algorithm of artificial neural network with backpropagation in breakout prediction does seem to be a more viable, efficient, and cost-effective method, which could also be utilized in the more advanced automated steel-manufacturing plants.

Three new transition-metal complexes were produced by refluxing azodicarbonamide (ADCA) with nickel(II), copper(II), and zinc(II) solutions in a mixture of 50% (v/v) methanol and water. The magnitude of chelation between metal ions and ligand molecules was assessed by FT-IR, UV, elemental analysis, TGA, conductivity, mass, and magnetic susceptibility measurements. FT-IR analysis suggested a bi-dentate chelation in all complexes, which takes place through the N-azo and O-carbonyl groups. Based on the measurement of magnetic moments and spectral analysis, a distorted octahedral geometry was proposed for Ni(II) and Cu(II) complexes, whereas zinc complex showed a hexa-coordinated geometry. The optical band gaps of the nickel(II), copper(II) and zinc(II) complexes were found to be 1.91, 2.50, and 1.96 eV, respectively, which means that they can be employed as semiconductors and that they are in the same range as highly effective photovoltaic materials. The Urbach energy parameters were also estimated from other optical parameters. The biological activity of azodicarbonamide and its synthesized complexes has been screened against the selected gram bacteria (+ve) and fungi.

Mold breakout is one of the significant problems in a continuous casting machine (caster). It represents one of the key areas within the steel production facilities of a steel plant. A breakout event on a caster will always cause safety hazards, high repair costs, loss of production, and shutdown of the caster for a short while. In this paper, a logic-judgment-based mold breakout prediction system has been developed for a continuous casting machine. This system developed new algorithms to detect the different sticker behaviors. With more algorithms running, each algorithm is more specialized in the other behaviors of stickers. This new logic-based breakout prediction system (BOPS) not only detects sticker breakouts but also detects breakouts that takes place due to variations in casting speed, mold level fluctuation, and taper/mold problems. This system also finds the exact location of the breakout in the mold and reduces the number of false alarms. The task of the system is to recognize a sticker and prevent a breakout. Moreover, the breakout prediction system uses an online thermal map of the mold for process visualization and assisting breakout prediction. This is done by alerting the operating staff or automatically reducing the cast speed according to the location of alarmed thermocouples, the type of steel, the tundish temperature, and the size of the cold slab width. By applying the proposed model in an actual steel plant, field application results show that it could timely detect all 13 breakouts with a detection ratio of 100%, and the frequency of false alarms was less than 0.056% times/heat. It has the additional advantage of not needing a lot of learning data, as most neural networks do. Thus, this new logical BOPS system should not only detect the sticker breakouts but also detect breakouts taking place due to variations in casting speed and mold level fluctuation.

Glucokinase activators are considered as new therapeutic arsenals that bind to the allosteric activator sites of glucokinase enzymes, thereby maximizing its catalytic rate and increasing its affinity to glucose. This study was designed to identify potent glucokinase activators from prenylated flavonoids isolated from medicinal plants using molecular docking, molecular dynamics simulation, density functional theory, and ADMET analysis. Virtual screening was carried out on glucokinase enzymes using 221 naturally occurring prenylated flavonoids, followed by molecular dynamics simulation (100 ns), density functional theory (B3LYP model), and ADMET (admeSar 2 online server) studies. The result obtained from the virtual screening with the glucokinase revealed arcommunol B (−10.1 kcal/mol), kuwanon S (−9.6 kcal/mol), manuifolin H (−9.5 kcal/mol), and kuwanon F (−9.4 kcal/mol) as the top-ranked molecules. Additionally, the molecular dynamics simulation and MM/GBSA calculations showed that the hit molecules were stable at the active site of the glucokinase enzyme. Furthermore, the DFT and ADMET studies revealed the hit molecules as potential glucokinase activators and drug-like candidates. Our findings suggested further evaluation of the top-ranked prenylated flavonoids for their in vitro and in vivo glucokinase activating potentials.

A novel, fast and sensitive enantioselective HPLC assay with a new core–shell isopropyl carbamate cyclofructan 6 (superficially porous particle, SPP) chiral column (LarihcShell-P, LSP) was developed and validated for the enantiomeric separation and quantification of verapamil (VER) in rat plasma. The polar organic mobile phase composed of acetonitrile/methanol/trifluoroacetic acid/triethylamine (98:2:0.05: 0.025, v/v/v/v) and a flow rate of 0.5 mL/min was applied. Fluorescence detection set at excitation/emission wavelengths 280/313 nm was used and the whole analysis process was within 3.5 min, which is 10-fold lower than the previous reported HPLC methods in the literature. Propranolol was selected as the internal standard. The S-(−)- and R-(+)-VER enantiomers with the IS were extracted from rat plasma by utilizing Waters Oasis HLB C18 solid phase extraction cartridges without interference from endogenous compounds. The developed assay was validated following the US-FDA guidelines over the concentration range of 1–450 ng/mL (r2 ≥ 0.997) for each enantiomer (plasma) and the lower limit of quantification was 1 ng/mL for both isomers. The intra- and inter-day precisions were not more than 11.6% and the recoveries of S-(−)- and R-(+)-VER at all quality control levels ranged from 92.3% to 98.2%. The developed approach was successfully applied to the stereoselective pharmacokinetic study of VER enantiomers after oral administration of 10 mg/kg racemic VER to Wistar rats. It was found that S-(−)-VER established higher Cmax and area under the concentration-time curve (AUC) values than the R-(+)-enantiomer. The newly developed approach is the first chiral HPLC for the enantiomeric separation and quantification of verapamil utilizing a core–shell isopropyl carbamate cyclofructan 6 chiral column in rat plasma within 3.5 min after solid phase extraction (SPE).

This article aimed to synthesis, spectroscopic, physicochemical characterizations, and catalytic studies on some ofloxacin (OFL) complexes with ruthenium(III) [Ru(III)] metal ions. The Ru(III)-OFL complex, [Ru(OFL)2(Cl)2]Cl and two mixed-ligand complexes, [Ru(OFL)(AA)(H2O)2]Cl2 derived from OFL as the primary ligand and amino acids [AA, either glycine (Gly) or alanine (Ala)] as the secondary ligands, were synthesized and characterized using microanalytical, spectroscopic, and physical techniques including element composition, molar conductivity, infrared, electronic spectra, thermal, X-ray powder diffraction (XRD), Energy dispersive X-ray spectroscopy (EDX), Scanning electron microscopy (SEM), and Transmittance electron microscopy (TEM) analyses. The element analysis data describe the formation of 1:2 [Ru(III):OFL] and 1:1:1 [Ru(III):OFL:AA] complexes. The octahedral geometry of the complexes was confirmed by their magnetic moment and diffused reflectance. Fourier Transform Infrared spectroscopic (FTIR) measurements suggested that the ligands chelated with Ru(III) ions through the nitrogen atoms of the piperazine ring. In vitro antibacterial efficiency of the OFL compounds was evaluated by paper disc diffusion method. Significant antimicrobial activities were observed for some compounds of the series.

Water is diminishing in many places of the globe due to human intervention and climate variability. This study was conducted to assess water sustainability in the Amu Darya basin, the largest river catchment of central Asia, using two Gravity Recovery and Climate Experiment (GRACE) satellite solutions with a spatial resolution of 0.5°. Spatial variability of water sustainability was estimated by integrating reliability, resiliency and vulnerability. In addition, the Modified Mann–Kendall (MMK) test was utilized to detect the significant trends in water availability. Findings show a significant decline in the basin’s water supply, especially after 2010. Water availability was more variable in the east and a small area in the south. Trend analysis revealed higher declination in water availability in the range of −0.04 to −0.08 cm/year in the tundra and warm dry continental climate zones and the delta region of the basin ending in the Aral Sea in the cold desert climate zone. Water resources in the cold semi-arid (steppe) and most parts of the cold desert climate are more sustainable than the rest of the basin. Overall, the results indicate that water resources availability in a large-scale basin with climate diversity could be well assessed using the method used in this study.

The spread of the Dengue virus over the world, as well as multiple outbreaks of different serotypes, has resulted in a large number of deaths and a medical emergency, as no viable medications to treat Dengue virus patients have yet been found. In this paper, we provide an in silico virtual screening and molecular dynamics-based analysis to uncover efficient Dengue infection inhibitors. Based on a Google search and literature mining, a large phytochemical library was generated and employed as ligand molecules. In this investigation, the protein target NS2B/NS3 from Dengue was employed, and around 27 compounds were evaluated in a docking study. Phellodendroside (−63 kcal/mole), quercimeritrin (−59.5 kcal/mole), and quercetin-7-O-rutinoside (−54.1 kcal/mole) were chosen based on their binding free energy in MM-GBSA. The tested compounds generated numerous interactions at Lys74, Asn152, and Gln167 residues in the active regions of NS2B/NS3, which is needed for the protein’s inhibition. As a result, the stable mode of docked complexes is defined by various descriptors from molecular dynamics simulations, such as RMSD, SASA, Rg, RMSF, and hydrogen bond. The pharmacological properties of the compounds were also investigated, and no toxicity was found in computational ADMET properties calculations. As a result, this computational analysis may aid fellow researchers in developing innovative Dengue virus inhibitors.