Green advancements towards the electrochemical synthesis of heterocycles.

Heterocyclic chemistry is a large field with diverse applications in the areas of biological research and pharmaceutical advancement. Numerous initiatives have been proposed to further enhance the reaction conditions to reach these compounds without using harmful compounds. This paper focuses on the recent advances in the eco-friendly and green synthetic procedures to synthesize N-, S-, and O-heterocycles. This approach demonstrates considerable potential in accessing such compounds while circumventing the need for stoichiometric quantities of oxidizing/reducing agents or catalysts containing precious metals. Merely employing catalytic quantities of these substances proves sufficient, thereby offering an optimal means of contributing to resource efficiency. Renewable electricity plays a crucial role in generating environmentally friendly electrons (oxidant/reductant) that serve as catalysts for a series of reactions. These reactions involve the production of reactive intermediates, which in turn allow the synthesis of new chemical bonds, enabling beneficial transformations to occur. Furthermore, the utilization of metals as active catalysts in electrochemical activation has been recognized as an effective approach for achieving selective functionalization. The aim of this review was to summarize the electrochemical synthetic procedures so that the undesirable side reactions can be considerably reduced and the practical potential range of the chemical reactions can be expanded significantly.

AI Tools for Assessing Human Fertility Using Risk Factors: A State-of-the-Art Review.

Infertility has massively disrupted social and marital life, resulting in stressful emotional well-being. Early diagnosis is the utmost need for faster adaption to respond to these changes, which makes possible via AI tools. Our main objective is to comprehend the role of AI in fertility detection since we have primarily worked to find biomarkers and related risk factors associated with infertility. This paper aims to vividly analyse the role of AI as an effective method in screening, predicting for infertility and related risk factors. Three scientific repositories: PubMed, Web of Science, and Scopus, are used to gather relevant articles via technical terms: (human infertility OR human fertility) AND risk factors AND (machine learning OR artificial intelligence OR intelligent system). In this way, we systematically reviewed 42 articles and performed a meta-analysis. The significant findings and recommendations are discussed. These include the rising importance of data augmentation, feature extraction, explainability, and the need to revisit the meaning of an effective system for fertility analysis. Additionally, the paper outlines various mitigation actions that can be employed to tackle infertility and its related risk factors. These insights contribute to a better understanding of the role of AI in fertility analysis and the potential for improving reproductive health outcomes.

BWOA assisted PIDF-(1+I) controller for intelligent load frequency management of standalone micro-grid.

The study made in this paper has been directed towards a novel load frequency management (LFM) scheme for solar-wind-based standalone micro-grid (SMG). For LFM, this brief deals with the introduction of proportional-integral-derivative with filter - (one plus integral), i.e., PIDF-(1+I) cascade controller. A maiden endeavor has been performed to employ a recently developed black widow optimization algorithm (BWOA) to obtain the supplementary controller parameters. The considered SMG consists of the wind turbine generator, diesel engine generator, solar photovoltaic as distributed generation unit, and flywheel and ultra-capacitor are considered as energy storage systems. Generation rate constraints and governor dead-band type power system's nonlinearities are also included in this study. This work aims to mitigate the effect of mismatch in demand and generation and minimize the change in frequency deviation (CFD). The maximum obtained CFD with the proposed controller is 0.048 Hz, which is entirely satisfactory and under the permissible limit of IEEE standard. A vivid comparative analysis of artificial bee colony and BWOA tuned controllers like conventional PID, PIDF, and PIDF-(1+I) is also performed. Finally, the detailed robustness assessment of the proposed controller with its real-time implementation through the standard New England IEEE 39 test bus system presents the controller's superiority.

Investigation of high optical gain in complex type-II InGaAs/InAs/GaAsSb nano-scale heterostructure for MIR applications.

This paper reports a comprehensive theoretical study of W-shaped complex type-II InGaAs/InAs/GaAsSb nano-scale heterostructure consisting of two quantum wells of InAs material using the six-band k.p theory. The entire structure has been supposed to be grown on InP substrate. In order to optimize the optical gain, the probability densities of electrons and holes were optimized in the heterostructure. Following these calculations, dispersion relations for electron and hole energies, and transverse electric and transverse magnetic polarizations dependent dipole matrix elements and momentum matrix elements were calculated and, finally, the optical gain in both polarization modes was calculated. For this optimized complex heterostructure, a very high optical gain of the order of ∼4500 cm-1 in the regime of mid-infrared wavelength ∼3.2 µm has been achieved. The results suggest that the designed nano-heterostructure may be utilized for mid-infrared region (MIR) applications such as chemical and bio-molecular sensing of molecules, for the applications of spectroscopy in the "fingerprint region" of molecular science, and for detection of atmospheric gases that respond to 3.2 µm wavelength.