The search for sustainable, cost-effective and environmentally friendly corrosion inhibitors for hydrochloric acid (HCl) solution in industrial applications has garnered increasing interest in plant extracts and their refined metabolites. In this research, Cleome arabica L. (CA) extract, found in the Algerian Sahara, was considered due to its low cost compared to other studied plants and higher content of active compounds, thereby emerging as a promising candidate and offering the potential to promote a circular economy model. This study assessed the effectiveness of CA extract as a green corrosion inhibitor for AISI 1045 carbon steel in 0.5 M HCl solution and highlighted its potential to advance the field of green corrosion inhibitors. ATR-FTIR and LC-ESI-MS/MS analyses revealed the presence of significant organic compounds, including coumaric acid (74.58%), 4-methoxybenzoic acid (12.53%), and kaempferol (8.05%), which contributed to the corrosion inhibition. The inhibitory effectiveness of the CA extract was evaluated at five concentrations, ranging from 0.125 to 1 g L-1, using weight loss measurements, potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS). The highest inhibition efficiency (η = 94.45%) was observed at a CA extract concentration of 1 g L-1 after 196 hours of immersion in 0.5 M HCl. Thermodynamic analysis using the Langmuir adsorption isotherm yielded a ΔG ads value of -24.737 kJ mol-1, indicating the spontaneous adsorption of CA molecules onto the AISI 1045 surfaces, forming a protective layer, which was confirmed by SEM/EDX analysis. Density functional theory (DFT) calculations showed a significant correlation with the experimental data, confirming that CA extract is a highly efficient and environmentally friendly corrosion inhibitor.
Under the roof of solid industrialization and accelerated intensification of multiple ranges of mobilization, a huge rise in precious fuel consumption and pollution was observed. Based on the recent hardships of fossil fuels, experts are undoubtedly eager in carrying out their research in renewable environment-friendly fuels. There have been many reviews of works considering the parameters and standards of biodiesel, which is only from various vegetable and seed oils. But very little review work was carried out on only plant-based biofuel. Plant-based fuel has a lower viscosity and higher volatility properties. The target of this review was to make a bridge to overcome these research gaps. This review extensively studies the biological background, production outcome, properties, and reliability of plant-based biofuel and also deeply investigates the feasibility of usage in a diesel engine. From deep investigation it was identified that most of the low viscous fuel had higher brake thermal efficiency (BTE) (2% to 4%) and NOx emission (5% to 10%) than high viscous biodiesel. The formation of hydrocarbon (HC), CO, and smoke emission was similar to high viscous biodiesel. Overall, the low viscous fuel effectively improves the engine behaviors.
The correction of grammatical errors in natural language processing is a crucial task as it aims to enhance the accuracy and intelligibility of written language. However, developing a grammatical error correction (GEC) framework for low-resource languages presents significant challenges due to the lack of available training data. This article proposes a novel GEC framework for low-resource languages, using Arabic as a case study. To generate more training data, we propose a semi-supervised confusion method called the equal distribution of synthetic errors (EDSE), which generates a wide range of parallel training data. Additionally, this article addresses two limitations of the classical seq2seq GEC model, which are unbalanced outputs due to the unidirectional decoder and exposure bias during inference. To overcome these limitations, we apply a knowledge distillation technique from neural machine translation. This method utilizes two decoders, a forward decoder right-to-left and a backward decoder left-to-right, and measures their agreement using Kullback-Leibler divergence as a regularization term. The experimental results on two benchmarks demonstrate that our proposed framework outperforms the Transformer baseline and two widely used bidirectional decoding techniques, namely asynchronous and synchronous bidirectional decoding. Furthermore, the proposed framework reported the highest F1 score, and generating synthetic data using the equal distribution technique for syntactic errors resulted in a significant improvement in performance. These findings demonstrate the effectiveness of the proposed framework for improving grammatical error correction for low-resource languages, particularly for the Arabic language.
Tobacco products are widely recognized as a major contributor to death. Cigarette smoke contains several toxic chemicals including heavy metals particulate causing high health risks. However, limited information has been available on the health risks associated with the heavy metals in cigarettes commonly sold in the Bangladeshi market. This study evaluated the concentrations and potential health risks posed by ten concerned heavy metals in ten widely consumed cigarette brands in Bangladesh using an atomic absorption spectrometer. The concentration (mg/kg) ranges of heavy metals Pb, Cd, Cr, As, Co, Ni, Mn, Fe, Cu, and Zn vary between 0.46-1.05, 0.55-1.03, 0.80-1.2, 0.22-0.40, 0.46-0.78, 2.59-3.03, 436.8-762.7, 115.8-184.4, 146.6-217.7, and 34.0-42.7, respectively. We assume that the heavy metals content among cigarette brands is varied due to the differences in the source of tobacco they use for cigarette preparation. The carcinogenic risks posed by heavy metals follow the order of Cr > Co > Cd > As > Ni > Pb, while the non-carcinogenic risks for Cu, Zn, Fe, and Mn were greater than unity (HQ > 1), except for Fe. The existence of toxic heavy metals in cigarette tobacco may thus introduce noticeable non-carcinogenic and carcinogenic health impacts accompanying inhalation exposure. This study provides the first comprehensive report so far on heavy metal concentration and associated health risks in branded cigarettes commonly sold in Bangladesh. Hence, this data and the information provided can serve as a baseline as well as a reference for future research and have potential implications for policy and legislation in Bangladesh.