Over the past decade, extensive research has been devoted in developing cost-effective, robust, and efficient photoelectrodes for sustainable hydrogen production via photoelectrochemical (PEC) water splitting, aiming to address the growing global energy crisis. Among various materials, antimony-based chalcogenide semiconductors, such as Sb2Se3, Sb2S3 and Sb2(S,Se)1-x have emerged as promising candidates for PEC photocathodes, as they meet key criteria including, suitable band gap (1.1 to 1.7 eV), superior optoelectronic properties, high absorption coefficient and outstanding photocorrosion stability, making them highly suitable for solar-driven hydrogen generation. This review outlines the basic principles of PEC water splitting with its key parameter calculations and typical device configurations. Recent advancements in antimony chalcogenide based photocathodes are thoroughly reviewed, with reference to the intrinsic optoelectronic properties, morphological effects, the role of cocatalyst incorporation and protective interfacial layer engineering in enhancing device performance. The review article concludes with existing challenges and future research directions, highlighting the potential of antimony chalcogenide photocathodes for low-cost, efficient solar hydrogen production, tandem device architectures, and commercial-scale applications. © 2026 International Solar Energy Society.

Currently, artificial intelligence (AI) has been widely used in medical imaging for accurate disease classification. However, the current existing approaches offer centralized learning environments that make them prone to security risks. These security risks may hinder the accuracy of disease classification, leading to a reduced survival rate. To address these issues, a novel multi-class brain tumor classification strategy was proposed in this work using federated learning. The proposed approach integrates the features of federated learning with the Deep CapsNet approach (FL-DCN), offering both accuracy and privacy. The proposed framework consists of four modules: data collection and preprocessing, feature extraction, and classification. In the data collection and preprocessing module, the brain Magnetic Resonance Imaging (MRI) images are collected and preprocessed to ensure consistency and quality. In the feature extraction module, a U-Net architecture was employed for extracting the most significant attributes present in the images. Here, a dual outcome structure was enabled to implement the segmentation and feature extraction process simultaneously. The outcome of this stage is high-level feature and tumor masks for CapsNet. In the classification module, a federated learning environment was created, and the extracted features are distributed across multiple local nodes. Here, each node has trained three elements, such as primary capsules, digit capsules, and dynamic routing. Moreover, primary capsules contain 32 capsules and 8D activation vectors; similarly, digit capsules consist of 4 capsules and 16D vectors used to match the tumor classes. Consequently, the local node uses Deep CapsNet to learn the spatial and hierarchical patterns within the images. Finally, Federated Averaging (FedAvg) was employed to combine the model parameters of the local models into a global model, which produces the classification outcomes. The presented methodology is implemented in the Python tool and validated across the public database. The implementation results are determined and validated across the existing technologies in terms of accuracy, precision, recall, F-measure, error rate, and computational efficiency. While comparing the conventional model, this study demonstrates that the FL framework can attain privacy-protected brain tumor classification from brain MRI image datasets without compromising much accuracy as well as precision parameters. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026.

A new measurement of the magnetic anomaly a(mu) of the positive muon is presented based on data taken from 2020 to 2023 by the Muon g - 2 Experiment at Fermi National Accelerator Laboratory (FNAL). This dataset contains over 2.5 times the total statistics of our previous results. From the ratio of the precession frequencies for muons and protons in our storage ring magnetic field, together with precisely known ratios of fundamental constants, we determine a(mu) = 1 165 920 710(162) x 10(-12) (139 ppb) for the new datasets, and a(mu) = 1 165 920 705(148) x 10(-12) (127 ppb) when combined with our previous results. The new experimental world average, dominated by the measurements at FNAL, is a(mu)(exp) = 1 165 920 715(145) x 10(-12) (124 ppb). The measurements at FNAL have improved the precision on the world average by over a factor of 4.

In this study, thermoplastic polyurethane (TPU)/0.25 wt% of aluminium filler was successfully fabricated using single screw extruder machine. The fabricated filaments were examined for differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), and X-ray diffraction (XRD). During filament fabrication, the parameters for pure TPU, such as die temperature (160–190 °C), screw speed (400 to 450 rpm), extruder current (2.1 to 2.2 A), were chosen. Similarly, for TPU/aluminium filaments, die temperature (190 –160 °C), screw speed (60 rpm), and extruder current (2.9 A) were chosen. Regarding the experimental results, the TGA of TPU/aluminium samples showed higher degradation than pure TPU samples at 850 °C. DSC results showed a minor effect from adding aluminium fillers in the first cycle. However, there was a significant change observed in the melting behavior in the subsequent cycles, which showed enhanced thermal stability and dimensional control at elevated temperatures. FTIR results confirmed interactions between aluminum fillers and TPU, as evidenced by the reduction in the intensity of C = O and N–H stretching bands, which indicated disrupted hydrogen bonds. SEM images showed that aluminium fillers were well embedded in the TPU matrix without any voids, which help in effective load transfer across the matrix. EDS results confirmed the presence of aluminium and oxygen and indicated the formation of Al2O3 during filament extrusion. Besides, XRD results exhibited a sharp crystalline peak and indicated improved structural stability due to adding aluminium fillers into TPU matrix. © The Author(s) 2026.

This research article explores the role of media, cinema, and literature in fostering professional and vocational development. The study aims to investigate how these forms of expression contribute to skill acquisition, knowledge enhancement, and personal growth, ultimately shaping individuals' professional trajectories. By exploring the impact of media, cinema, and literature on various aspects of professional development, such as skill acquisition, networking, personal branding, and cultural competence, this research highlights the significance of integrating these mediums into educational and training programs. The findings of this research indicate that media, cinema, and literature play a crucial role in skill acquisition and knowledge enhancement. Through exposure to diverse narratives and perspectives, individuals develop critical thinking skills, creativity, and problem-solving abilities. Media literacy skills enable individuals to critically analyse and interpret media messages, while cinema serves as an educational tool that enhances understanding of different cultures and perspectives. Literature, on the other hand, enhances communication skills, including reading comprehension, critical thinking, and verbal expression. The implications of this research are significant for educators, trainers, and policymakers. Integrating media, cinema, and literature into educational and training programs can create a more holistic and enriching learning environment.

Teachers may create a stimulating learning environment where students can develop important intellectual and social skills that will benefit them for the rest of their lives by using the correct teaching strategies. A teacher can assist students with a variety of interests, talents, and learning preferences by implementing one of the available frameworks. To increase your student's chances of succeeding in the classroom, whether you work in the education sector as a teacher or another professional, you might find it helpful to learn about cutting-edge instructional practices. Teaching techniques are approaches that teachers can use to make learning easier and pique students' motivation and interest in the material. Different teaching philosophies include game-based study, differentiated study, lecture-based method, technology-based pedagogy, group and individual study, inquiry-based study, kinesthetic study, game-based study, and expeditionary study. You can enhance your methods by trying out various teaching techniques while presenting the same course, communicating with other educators to acquire their insights, and being flexible. Due to the quick changes in the modern world, the Education System is currently dealing with a wide range of problems. An excellent teaching strategy helps students overcome their preconceptions and motivates them to study by putting them in a situation where they start to believe that they are the ones who come up with the solutions and who are responsible for the change. Professors that are respected both nationally and locally serve as ideal role models for educators who are enthusiastic about effective teaching methods of professional courses, providing them with ideas, insights, and the best teaching methods.(Journal of Advances in Medical Education & Professionalism v.4(4); 2016 Oct PMC5065908)

Language is one of the most marked, conspicuous, as well as fundamental characteristics of the faculties of man. Language is a system of sounds, words, patterns, etc., used by humans to communicate thoughts and feelings. Language is a system of communication which consists of a set of sounds and written symbols which are used by the people of a particular country or region for talking or writing in. The importance of language for man and society cannot be minimized. Language is not only a mode of communication between individuals but also a way for the expression of their personality. Man is remarkably distinguished from animals not only in his use of language but also in his thought process. This use has been termed by Chomsky as “the creative aspect of language; Chomsky suggests that “the normal use of language is innovative, in sense that much of what we say in the course of normal language use is entirely new, not a reception of anything that we have heard before and not even “similar” in “pattern” to sentences or discourse that we have heard in the past” (Chomsky, p.10). Language has its true being in conversation in the exercise and promotion and understanding between peoples. Language should not be a means to impose or transmit my will to another. Above all, language is a living process in which a community of life is lived out. It should be thought that human language as a special and unique living process, in that in linguistic communication, world and human worldview is disclosed. This disclosure, this function of language means that language does not draw attention to itself but transparent to the realities that are manifested through it. Since learning a language is part of our knowledge, it becomes one of the key factors in competitiveness. In the advanced industrial society of today, the basic knowledge of a single or more language has become indispensable.