Impregnated copper ferrite on mesoporous graphitic carbon nitride: An efficient and reusable catalyst for promoting ligand‐free click synthesis of diverse 1,2,3‐triazoles and tetrazoles

Magnetic CuFe₂O₄/g‐C₃N₄ hybrids were synthesized through a facile method and their catalytic performances were evaluated in click chemistry for the first time. The structural and morphological characterization of prepared materials was carried out by different techniques such as X‐ray diffraction, high‐resolution transmission electron microscopy, field emission scanning electron microscopy, Fourier infrared spectroscopy, vibrating sample magnetometry, thermogravimetric analysis, and N₂ adsorption–desorption analysis (Brunauer–Emmett–Teller surface area). The utilization of magnetic CuFe₂O₄/g‐C₃N₄ enabled superior performance in the one‐pot azide–alkyne cycloaddition reaction in water using alkyl halides and epoxides as azide precursors without the need of any additional agents. The present system is broad in scope and especially practical for the synthesis of macrocyclic triazoles and also tetrazoles. In addition, the catalytic system highly fulfills the demands of “green click chemistry” with its convenient conditions, especially easy access to a variety of significant products in low catalyst loading and simple work‐up and isolation procedure.     

CuI/Fe3O4 NPs@Biimidazole IL‐KCC‐1 as a leach proof nanocatalyst for the synthesis of imidazo[1,2‐a]pyridines in aqueous medium

In the present work, an innovative leach proof nanocatalyst based on dendritic fibrous nanosilica (DFNS) modified with ionic liquid loaded Fe₃O₄ NPs and CuI salts was designed and applied for the rapid synthesis of imidazo[1,2‐a]pyridines from the reaction of phenyl acetylene, 2‐aminopyridine, and aldehydes in aqueous medium. The structure of the synthesized nanocatalyst was studied by field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), Fourier transform infrared (FT‐IR), flame atomic absorption spectroscopy (FAAS), energy‐dispersive X‐ray (EDX), and X‐ray diffraction (XRD), vapor–liquid–solid (VLS), and adsorption/desorption analysis (Brunauer–Emmett–Teller [BET] equation) instrumental techniques. CuI/Fe₃O₄NPs@IL‐KCC‐1 with high surface area (225 m² g^?1) and porous structure not only exhibited excellent catalytic activity in aqueous media but also, with its good stability, simply recovered by an external magnet and recycled for eight cycles without significant loss in its intrinsic activity. Higher catalytic activity of CuI/Fe₃O₄NPs@IL‐KCC‐1 is due to exceptional dendritic fibrous structure of KCC‐1 and the ionic liquid groups that perform as strong anchors to the loaded magnetic nanoparticles (MNPs) and avoid leaching them from the pore of the nanocatalyst. Green reaction media, shorter reaction times, higher yields (71–97%), easy workup, and no need to use the chromatographic column are the advantages of the reported synthetic method.     

Generating and analyzing spatial social networks

In this paper, we propose a class of models for generating spatial versions of three classic networks: Erdös-Rényi (ER), Watts-Strogatz (WS), and Barabási-Albert (BA). We assume that nodes have geographical coordinates, are uniformly distributed over an m × m Cartesian space, and long-distance connections are penalized. Our computational results show higher clustering coefficient, assortativity, and transitivity in all three spatial networks, and imperfect power law degree distribution in the BA network. Furthermore, we analyze a special case with geographically clustered coordinates, resembling real human communities, in which points are clustered over k centers. Comparison between the uniformly and geographically clustered versions of the proposed spatial networks show an increase in values of the clustering coefficient, assortativity, and transitivity, and a lognormal degree distribution for spatially clustered ER, taller degree distribution and higher average path length for spatially clustered WS, and higher clustering coefficient and transitivity for the spatially clustered BA networks.     

A Universal DNA Aptamer that Recognizes Spike Proteins of Diverse SARS-CoV-2 Variants of Concern

We report on a unique DNA aptamer, denoted MSA52, that displays universally high affinity for the spike proteins of wildtype SARS-CoV-2 as well as the Alpha, Beta, Gamma, Epsilon, Kappa, Delta and Omicron variants. Using an aptamer pool produced from round 13 of selection against the S1 domain of the wildtype spike protein, we carried out one-round SELEX experiments using five different trimeric spike proteins from variants, followed by high-throughput sequencing and sequence alignment analysis of aptamers that formed complexes with all proteins. A previously unidentified aptamer, MSA52, showed K_d values ranging from 2 to 10 nM for all variant spike proteins, and also bound similarly to variants not present in the reselection experiments. This aptamer also recognized pseudotyped lentiviruses (PL) expressing eight different spike proteins of SARS-CoV-2 with K_d values between 20 and 50 pM, and was integrated into a simple colorimetric assay for detection of multiple PL variants. This discovery provides evidence that aptamers can be generated with high affinity to multiple variants of a single protein, including emerging variants, making it well-suited for molecular recognition of rapidly evolving targets such as those found in SARS-CoV-2.     

Interval Ostrowski-type methods with guaranteed convergence

In this paper, interval extensions of the classic Ostrowski and its modified method are introduced. Also, error analysis and convergence will be discussed. Some implemented examples with INTLAB are also included to illustrate the validity and applicability of the schemes. The results of proposed methods are compared with the results of the interval Newton method.     

A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment

The purpose of this paper is to design a new extension of the ELECTRE, known as the elimination and choice translating reality method, for multi-criteria group decision-making problems based on intuitionistic fuzzy sets. This method is widely utilized when a set of alternatives should be identified and evaluated with respect to a set of conflicting criteria by reflecting decision makers’ (DMs’) preferences. However, handling the exact data and numerical measure is difficult to be precisely focused because the DMs’ judgments are often vague in real-life decision problems and applications. A more realistic and practical approach can be to use linguistic variables expressed in intuitionistic fuzzy numbers instead of numerical data to model DMs’ judgments and to describe the inputs in the ELECTRE method. The proposed intuitionsitic fuzzy ELECTRE utilizes the truth-membership function and non-truth-membership function to indicate the degrees of satisfiability and non-satisfiability of each alternative with respect to each criterion and the relative importance of each criterion, respectively. Then, a new discordance intuitionistic index is introduced, which is extended from the concept of the fuzzy distance measure. Outranking relations are defined by pairwise comparisons and a decision graph is depicted to determine which alternative is preferable, incomparable or indifferent in the intuitionistic fuzzy environment. Finally, a comprehensive sensitivity analysis is employed to further study regarding the impact of threshold values on the final evaluation, and a comparative analysis is demonstrated with an application example in flexible manufacturing systems between the proposed ELECTRE method and the existing intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method.     

A quantile-based Time at Risk: A new approach for assessing risk in financial markets

In this paper, we provide a new measure for evaluation of risk in financial markets. This measure is based on the return interval of critical events in financial markets or other investment situations. Our main goal was to devise a model like Value at Risk (VaR). As VaR, for a given financial asset, probability level and time horizon, gives a critical value such that the likelihood of loss on the asset over the time horizon exceeds this value is equal to the given probability level, our concept of Time at Risk (TaR), using a probability distribution function of return intervals, provides a critical time such that the probability that the return interval of a critical event exceeds this time equals the given probability level. As an empirical application, we applied our model to data from the Tehran Stock Exchange Price Index (TEPIX) as a financial asset (market portfolio) and reported the results.