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This study aims to synthesize new disperse dyes based on novel pyrazolyl quinolinone derivatives EQ1 and EQ2 and evaluate their characteristics after dyeing them on a polyester fabric.

New dispersed dyes based on pyrazolyl quinolinone derivatives were prepared and confirmed by different analyses, such as infrared spectroscopy, elemental microanalysis and nuclear magnetic resonance spectroscopy. They were dyed on a polyester fabric. The characteristics of dyed polyester were determined by color measurements such as a*, b*, L*, C*, E, Ho, R% and color strength. The electronic structures of EQ1 and EQ2 in gaseous state were investigated using density functional theory/B3LYP/6-311++G (d, p) level of theory.

The suitability of the prepared dyestuffs for dyeing on polyester fabrics has been investigated. The study was concerned with comparing the contrasting depth of shade and levelness. The study was concerned mainly with dye uptake and color measurements at two different temperatures. The results showed that the exhaustion values of dyes inside the polyester at 130°C were higher than those obtained at conventional dyeing temperature (100°C). The exhaustion values of EQ2 were greater than those of EQ1 at 130°C with 2.2%, while the brightness of EQ2 was higher than that of EQ1 at the two investigated temperatures. The results of molecular orbital calculations show that the studied compounds are planar. In addition, the ionization potential of EQ1 was lower than that of EQ2. The results of the theoretical study helped in understanding the dyeing behavior of the investigated azo dyes.

The prepared disperse dyes based on pyrazolyl quinolinone derivatives could be used in textile dyeing of polyester on an industrial scale.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

Owing to the toxicity, biodegradability, and cost of most corrosion inhibitors, research attention is now focused on the development of environmentally benign, biodegradable, cheap, and efficient options. In consideration of these facts, chrysin, a phytocompound of Populus tomentosa (Chinese white poplar) has been isolated and investigated for its anticorrosion abilities on carbon steel in a mixed acid and chloride system. This highlights the main purpose of the study.

Chrysin was isolated from Populus tomentosa using column chromatography and characterized using Fourier Transform Infrared Spectroscopy and Nuclear Magnetic Resonance Spectroscopy. The investigations are outlined based on theory (Fukui indices, condensed density functional theory and molecular dynamic simulation) and experiments (electrochemical, gravimetry and surface morphology examinations).

Theoretical evaluations permitted the description of the adsorption characteristics, and molecular interactions and orientations of chrysin on Fe substrate. The interaction energy for protonated and neutral chrysin on Fe (110) were −149.10 kcal/mol and −143.28 kcal/mol, respectively. Moreover, experimental investigations showed that chrysin is a potent mixed-type corrosion inhibitor for steel, whose effectiveness depends on its surrounding temperature and concentration. The optimum inhibition efficiency of 78.7% after 24 h for 1 g/L chrysin at 298 K indicates that the performance of chrysin, as a pure compound, compares favorably with other phytocompounds and plant extracts investigated under similar conditions. However, the inhibition efficiency decreased to 62.5% and 51.8% at 318 K after 48 h and 72 h, respectively.

The novelty of this study relies on the usage of a pure compound in corrosion suppression investigation, thus eliminating the unknown influences obtainable by the presence of multi-phytocompounds in plant extracts, thereby advancing the commercialization of bio-based corrosion inhibitors.

Alzheimer’s disease (AD), the most common cause of dementia, is a neurodegenerative disorder caused by the aggregation of amyloid-beta (Aβ) at outside of neuron cells and also due to tau aggregation inside the cell. Corosolic acid is aimed to be selected as a main active constituent of Lagerstroemia speciosa for the study.

In the present study, molecular docking of corosolic acid and tau protein was examined using PyRx-v.0.8 software. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties were described and a molecular dynamics study of the bound complex was performed using Desmond.

The docking score and interactions suggested that the corosolic acid (CID:6918774) could bind to tau protein to prevent the fibrillar network, to prevent AD. During simulation corosolic acid-bound protein root mean square deviation (RMSD) values showed more stability when compared to the Apo form of protein. Molecular dynamics study of tau protein and corosolic acid complex gave the insights to develop a drug-like candidate against AD.

The use of corosolic acid of Lagerstroemia speciosa to prevent AD is supported by preliminary analysis on a computational basis. This compound should explore in terms of experimental strategies for the further drug development process. However, in vitro and in vivo evaluation studies are required to suggest the use of corosolic acid against AD.

Gallic acid is a substance that is widely found in nature. Initially, it was only used as a corrosion inhibitor to retard the rate of corrosion of metals. In recent years, with intensive research by scholars, the modification of coatings containing gallic acid has become a hot topic in the field of metal protection. This study aims to summarize the various preparation methods of gallic acid and its research progress in corrosion inhibitors and coatings, as well as related studies using quantum chemical methods to assess the predicted corrosion inhibition effects and to systematically describe the prospects and current status of gallic acid applications in the field of metal corrosion inhibition and protection.

First, the various methods of preparation of gallic acid in industry are understood. Second, the corrosion inhibition principles and research progress of gallic acid as a metal corrosion inhibitor are presented. Then, the corrosion inhibition principles and research progress of gallic acid involved in the synthesis and modification of various rust conversion coatings, nano-coatings and organic resin coatings are described. After that, studies related to the evaluation and prediction of gallic acid corrosion inhibition on metals by quantum chemical methods are presented. Finally, new research ideas on gallic acid in the field of corrosion inhibition and protection of metals are summarized.

Gallic acid can be used as a corrosion inhibitor or coating in metal protection.

There is a lack of research on the synergistic improvement of gallic acid and other substances.

The specific application of gallic acid in the field of metal protection was summarized, and the future research focus was put forward.

To the best of the authors’ knowledge, this paper systematically expounds on the research progress of gallic acid in the field of metal protection for the first time and provides new ideas and directions for future research.

Effective communication is crucial in the medical field where different stakeholders use various terminologies to describe and classify healthcare concepts such as ICD, SNOMED CT, UMLS and MeSH, but the problem of polysemy can make natural language processing difficult. This study explores the contextual meanings of the term “pattern” in the biomedical literature, compares them to existing definitions, annotates a corpus for use in machine learning and proposes new definitions of terms such as “Syndrome, feature” and “pattern recognition.”

Entrez API was used to retrieve articles form PubMed for the study which assembled a corpus of 398 articles using a search query for the ambiguous term “pattern” in the titles or abstracts. The python NLTK library was used to extract the terms and their contexts, and an expert check was carried out. To understand the various meanings of the term, the contextual environment was analyzed by extracting the surrounding words of the term. The expert determined the appropriate size of the context for analysis to gain a more nuanced understanding of the different meanings of the term pattern.

The study found that the categories of meanings of the term “pattern” are broader in biomedical publications than in common definitions, and new categories have been emerging from the term's use in the biomedical field. The study highlights the importance of annotated corpora in advancing natural language processing techniques and provides valuable insights into the nuances of biomedical language.

The study's findings demonstrate the importance of exploring contextual meanings and proposing new definitions of terms in the biomedical field to improve natural language processing techniques.

The main purpose of the present work is to introduce two new Schiff bases as corrosion inhibitors (CIs) for carbon steel (CS). The anti-corrosion performance of these Schiff bases having N and S heteroatoms in their structures was investigated and compared in 2 M HCl electrolyte. The inhibitory activity of these Schiff bases was also assessed.

Common electrochemical assays like potentiodynamic polarization and electrochemical impedance measurements were used to evaluate the ability of compounds in reduction of the rate of corrosion. Quantum chemical calculations (QCCs) were also used to examine the corrosion inhibitive and the process related to the electrical and structural characteristics of the molecules acting as CIs.

The electrochemical measurements indicate that both Schiff bases acted as the efficient CIs of CS in 2 M HCl electrolyte. The adsorption of the Schiff base on the surface of the CS caused the corrosion to be inhibited. The change of Gibbs energies indicated that both physical and chemical interactions are involved in the adsorption of NNS and SNS on CS surfaces. The predicted QCCs of the CIs neutral and positively charged versions were well-aligned with those obtained by electrochemical experiments.

Using electrochemical experiments and quantum chemical modelings, two new Schiff bases, N-2-((2-nitrophenyl)thio)phenyl)-1-(pyrrole-2-yl)methanimine (NNS) and N-2-((2-nitrophenyl)thio)phenyl)-1-(thiophen-2-yl)methanimine (SNS), were evaluated as anti-corrosion agents for CS in 2 M HCl electrolyte. The DFT calculations were considered to compute the quantum chemical parameters of the inhibitors.

The purpose of this study is to introduce the concept of Ecopoiesis. Introduction of the concept of ecopiesis, which explains the linkage strategy between relational and energetic resources (sustainability) that enable the relational viability of living things.

The design is based on the use of the relationship between abduction, epigenesis, cismogenesis and morphogenesis.

This paper concludes with a counter-intuitive proposal to the dominant lines of thought, distinguishing: Complexity as vital interweaving, Aristotelian Oikos as communitarian distinction, Organism-Entorno from relational theory (beyond the interactional), in a cybernetic referential framework that allows tending to sustain and sustain life from Ecopoiesis.

According to a relational theory of cognition, the sources of knowledge go beyond genetic and environmental factors. In the sphere of explanation, this study moves from “how much,” “why” and “how” to “why not.” Thus, the processes involved in understanding the living are forced to move from the logic of parts to the logic of patterns, which implies developing an explanation that considers the unique characteristics of development, encompassing the diverse origins of the organization of the living.

This study aims to prevent mild steel (MS) against corrosion in 0.5 M HCl solution, 2-amino-4-methoxy-6-methyl-1,3,5-triazine was used. The effectiveness of the compound as a corrosion inhibitor was studied via electrochemical, surface and theoretical calculation techniques.

For concentrations ranging from 0.5 to 10.0 mM, almost similar polarization resistances were obtained from electrochemical impedance spectroscopy (EIS) and linear polarization resistance tests. It also investigated inhibitive activity of 2-amino-4-methoxy-6-methyl-1,3,5-triazine on the steel surface using scanning electron and atomic force microscope instruments. Langmuir adsorption is the best matched isotherm for the adsorption of the inhibitor to the steel surface.

EIS method was used to determine inhibition efficiency, which was determined to be 95.7% for 10.0 mM inhibitor containing acid solution. Density functional theory’s predictions for quantum chemistry agreed well with the other experimental results.

The methods used in this study are effective and applicable; the used organic inhibitor is 2-amino-4-methoxy-6-methyl-1,3,5-triazine; and protective effectiveness is important, which is crucial for the task of MS corrosion prevention.

This paper aims to investigate the corrosion inhibition ability of 4–(4-nitrophenyl) thiazol-2-amine (NPT) on the copper in 1 M HCl.

The corrosion inhibitory ability of NPT on the copper in 1 M HCl was studied by electrochemical impedance spectroscopy, scanning electron microscopy and atomic force microscopy. Theoretical calculations (molecular dynamics simulation, density functional theory and the nucleus independent chemical shift [NICS] as aromaticity indicator of the molecule) were also performed.

The corrosion inhibition efficacy of this compound was about 80%. Nyquist plots display a small arc contributed to the film or oxide layer resistance and a large loop associated with charge transfer resistance. The inhibitor adsorption was under Langmuir’s adsorption model. ΔG⁰_ads values point to the presence of physical and chemical adsorption. Results of quantum chemical calculations showed that NPT has better interaction with copper than NPTH⁺. NICS of NPT in benzene or thiazole rings was less negative compared to NICS of NPTH⁺. Thus NPT shows less aromaticity compared with NPTH⁺, showing NPT can have better interaction with copper than NPTH⁺. NPT had more negative E_int value and more interactions with the Cu relative to NPTH⁺, this result was in agreement with the results of quantum chemical calculations.

NPT is an efficient corrosion inhibitor for copper in HCl. Theoretical calculations showed that NPT can have better interaction with copper than NPTH⁺. The results of the theoretical studies were in good agreement with the experimental studies.