Graphene, an innovative nanocarbon, has been discovered as a significant technological material. Increasing utilization of graphene has moved research towards the development of sustainable green techniques to synthesize graphene and related nanomaterials. This review article is basically designed to highlight the significant sustainability aspects of graphene. Consequently, the sustainability vision is presented for graphene and graphene nanocomposites. Environmentally sustainable production of graphene and ensuing nanomaterials has been studied. The formation of graphene, graphene oxide, reduced graphene oxide, and other derivatives has been synthesized using ecological carbon and green sources, green solvents, non-toxic reagents, and green routes. Furthermore, the utilization of graphene for the conversion of industrial polymers to sustainable recycled polymers has been studied. In addition, the recycled polymers have also been used to form graphene as a sustainable method. The implication of graphene in the sustainable energy systems has been investigated. Specifically, high specific capacitance and capacitance retention were observed for graphene-based supercapacitor systems. Subsequently, graphene may act as a multi-functional, high performance, green nanomaterial with low weight, low price, and environmental friendliness for sustainable engineering and green energy storage applications. However, existing challenges regarding advanced material design, processing, recyclability, and commercial scale production need to be overcome to unveil the true sustainability aspects of graphene in the environmental and energy sectors.

In recent years, the pathological diagnosis of glomerular diseases typically involves the study of glomerular his-to pathology by specialized pathologists, who analyze tissue sections stained with Periodic Acid-Schiff (PAS) to assess tissue and cellular abnormalities. In recent years, the rapid development of generative adversarial networks composed of generators and discriminators has led to further developments in image colorization tasks. In this paper, we present a generative adversarial network by Spectral Normalization colorization designed for color restoration of grayscale images depicting glomerular cell tissue elements. The network consists of two structures: the generator and the discriminator. The generator incorporates a U-shaped decoder and encoder network to extract feature information from input images, extract features from Lab color space images, and predict color distribution. The discriminator network is responsible for optimizing the generated colorized images by comparing them with real stained images. On the Human Biomolecular Atlas Program (HubMAP)—Hacking the Kidney FTU segmentation challenge dataset, we achieved a peak signal-to-noise ratio of 29.802 dB, along with high structural similarity results as other colorization methods. This colorization method offers an approach to add color to grayscale images of glomerular cell tissue units. It facilitates the observation of physiological information in pathological images by doctors and patients, enabling better pathological-assisted diagnosis of certain kidney diseases.

This report intends to enhance the reviews on leadership literature by conducting a bibliometric study on 198 publications focused on transformational leadership research. These papers were published in the Scopus database between 1997 and 2023. Employing quantitative bibliometric analysis, the study aims to identify both current and prospective research trajectories pertaining to transformational leadership issues. To the best of our current understanding, there exists no scholarly investigation that examines the bibliographic data pertaining to transformational leadership domains. Therefore, this work represents a distinctive and original contribution to the existing body of literature. This study additionally offers a comprehensive examination of the patterns and paths inside a visual and schematic framework for the investigation of this subject matter. This may facilitate researchers in comprehending the prevailing patterns and prospective avenues for research, so empowering future authors to carry out their investigations with greater efficacy. There exists a number of underexplored themes or subjects pertaining to transformational leadership matters, such as knowledge sharing, leadership styles, digital transformation, innovative work behavior, competitive advantage and digital transformation. This discovery offers useful insights into the heterogeneous nature of this area across multiple disciplines.

This investigation derives formulas to predict the mixed convective surface conductance of a flat isotropic surface roughness having a convex perimeter in a Newtonian fluid with a steady forced flow in the plane of that roughness. Heat transfer measurements of a 30.5 cm square rough plate with forced air velocities between 0.1 m/s and 2.5 m/s were made by the present apparatus in two inclined and all five orthogonal orientations. The present work’s formulas are compared with 104 measurements in twelve data-sets. The twelve data-sets have root-mean-square relative error (RMSRE) values between 1.3% and 4% relative to the present theory. The present work’sformulas are also compared with 78 measurements in 28 data-sets on five vertical rough surfaces in horizontal flow from prior work. The five stucco data-sets have RMSRE values between 2.5% and 6.5%; the other data-sets have RMSRE values between 0.2% and 5%.