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Water pollution stemming from textile dyes, particularly methylene blue (MB), represents a formidable challenge to both the environment and human well-being. In response to this pressing issue, scientists have redirected their focus toward eco-friendly nanocatalysts as a viable remediation strategy. Nanocatalysts crafted from precious metals like platinum, palladium, and gold have indisputably demonstrated their efficacy in combatting water pollution. Nonetheless, their restricted availability and substantial costs have spurred investigations into non-precious metal-based nanocatalysts. Research outcomes have revealed that non-noble metal (FeNi)-based nanocatalysts, synthesized using natural reductants, exhibit highly promising performance in degrading methylene blue. These alternatives not only deliver impressive efficiency but also incur lower production expenses compared to their noble metal counterparts. The ecological benefits inherent in these nanocatalysts offer a sustainable means of mitigating water pollution attributed to textile dyes. Through detailed synthesis experiments, precipitation-assisted method demonstrated a slightly superior yield of 69.11% with catalytic activity of 16260 μmol MB/gNiFe.

ABSTRACT The French clitic pro-form en represents a wide range of heterogeneous constituents: de-PP complements and adjuncts, partitive objects, and prepositionless objects of cardinals. The main goal of this paper is to formalize this relationship computationally in terms of genitive case. This is apparently the first non-transformational counterpart to Kayne (1975)’s unified analysis, which derives en from a deep structure with de by means of syntactic transformations. Transformational grammars are problematic from the parsing perspective. In order to test our analysis automatically on a large amount of data, we implemented it in a computational grammar of French in the Lexical-Functional Grammar (LFG) formalism using the XLE system. This non-transformational framework is particularly fit for expressing systematic relationships between heterogeneous structures and has successfully been used for the implementation of natural language grammars since the 1980s. We tested the implementation on 320 grammatical sentences and on an equal number of ungrammatical examples. It analyzed all grammatical examples and blocked almost 95% of the ungrammatical ones, showing a high empirical adequacy of the grammar.

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