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This article examines the temporal and phenomenological philosophies of Gilles Deleuze, Félix Guattari, and Paolo Virno, specifically in relation to the transmedia franchises of the Japanese game studio, Type-Moon. Against linear, national, and majoritarian grand narratives of the historical, the otaku artists, writers, and developers responsible for the Fate series postulate whether it is possible to harness the intense and affective forces described by Jay Lampert as “the Joan of Arc effect” in the blink of an eye or in the palm of your hand. Through a philosophical and formal analysis of three spinoff series from the Fate franchise, this article investigates how Type-Moon’s deployment of the “anime machine” encourages its viewers and users to see and feel the abundance of flowing “nomadic memories” or counter-historical visions from the perspective of minor populations. Through this highly embodied and tactile experience of transhistorical (un)becomings, Type-Moon’s series offer a deterritorialized, post-national world-image of the otaku database which mediates between the overloading affects of becoming-woman and the digitally encoded logic of transversal through the frames, windows, interfaces, devices, platforms, and bodies that constitute Type-Moon’s vibrant anime ecology.

The name \"Heidi\" is known and loved all over the world, due to Swiss author, Johanna Spyri's works, Heidis Lehr- und Wanderjahre (1880) and Heidi kann brauchen, was es gelernt hat (1881), which form part of the classic international children's literature canon. These stories have since crossed national boarders, by manifesting transnationally in several culture products. The focus of this article lies on the transnational trafic between the original Heidi (1881) and its adaptations. Because \"Heidi\" as a cultural phenomenon contains universal themes, the product was able to spread globally. This journey stretches from the Swiss Alps, to Japan and finally finds a home in South Africa and Afrikaans. Included in the article is an overview of how the Heidi text manifested in several cultures and its transnational movement, spanning time and place. The popularity of the animation series in South Africa among Afrikaans speaking people is analysed, along with suggestions for possible reasons for this big following and prevalence . The central argument of the article is that \"Heidi\" as cultural product has had a transnational journey from the Alps, to anime and Afrikaans. Keywords: \"Heidi\", anime, transnationalism, cultural product, Afrikaner identity.

The Material World Knight is an anime-style superhero from Lu Yang’s artwork The Great Adventure of Material World—Game Film (2020) who battles oppressive binary systems on his quest for transcendence. This article uses discourse and visual analysis to study how this short film employs references to Buddhist philosophy and Japanese anime to reconceptualize subjectivity. The study draws on posthuman theory by Rosi Braidotti and Donna Haraway to show how the artwork produces a post-dualist, posthuman, relational concept of subjectivity while also complicating any straightforward interpretations in favor of maintaining complexity and “staying with the trouble.”

Image super-resolution (ISR) technology aims to enhance resolution and improve image quality. It is widely applied to various real-world applications related to image processing, especially in medical images, while relatively little appliedto anime image production. Furthermore, contemporary ISR tools are often based on convolutional neural networks (CNNs), while few methods attempt to use transformers that perform well in other advanced vision tasks. We propose a so-called anime image super-resolution (AISR) method based on the Swin Transformer in this work. The work was carried out in several stages. First, a shallow feature extraction approach was employed to facilitate the features map of the input image’s low-frequency information, which mainly approximates the distribution of detailed information in a spatial structure (shallow feature). Next, we applied deep feature extraction to extract the image semantic information (deep feature). Finally, the image reconstruction method combines shallow and deep features to upsample the feature size and performs sub-pixel convolution to obtain many feature map channels. The novelty of the proposal is the enhancement of the low-frequency information using a Gaussian filter and the introduction of different window sizes to replace the patch merging operations in the Swin Transformer. A high-quality anime dataset was constructed to curb the effects of the model robustness on the online regime. We trained our model on this dataset and tested the model quality. We implement anime image super-resolution tasks at different magnifications (2×, 4×, 8×). The results were compared numerically and graphically with those delivered by conventional convolutional neural network-based and transformer-based methods. We demonstrate the experiments numerically using standard peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), respectively. The series of experiments and ablation study showcase that our proposal outperforms others.