Cellulose nanocrystal, known as CNCs, is a form of material that can be produced by synthesizing carbon from naturally occurring substances, such as plants. Due to the unique properties it possesses, including a large surface area, impressive mechanical strength, and the ability to biodegrade, it draws significant attention from researchers nowadays. Several methods are available to prepare CNC, such as acid hydrolysis, enzymatic hydrolysis, and mechanical procedures. The characteristics of CNC include X-ray diffraction, transmission electron microscopy, dynamic light scattering, etc. In this article, the recent development of CNC preparation and its characterizations are thoroughly discussed. Significant breakthroughs are listed accordingly. Furthermore, a variety of CNC applications, such as paper and packaging, biological applications, energy storage, etc., are illustrated. This study demonstrates the insights gained from using CNC as a potential environmentally friendly material with remarkable properties.

Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.

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.