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How does the decoloniality debate relate to heritage practice in China? Although postcolonial consciousness has coincided worldwide with persis- tent efforts to pluralize voices and practices in the public sphere and led to a plethora of strategies for initiating a process of decolonization (Lazzari et al., this section), China has remained away from these debates (Li, 2021; Liang, 2022) and maintains an ambivalent and ambiguous relationship with discourses on colonialism. Drawing on examples related to ethnicity and rurality, this essay illustrates the limits of decoloniality in the Chinese context and sheds light on how Chinese cultural heritage practices (re)produce hierarchies and racialized narratives to consolidate the nation. Like the other case studies examined in this special section, China’s position in colonial history allows us to de-center the conversation on decoloniality mainly based on Western history. Yet, China also adopts the hegemonic Western notion of cultural heritage promoted by the UNESCO narratives and imposes its own “authorized heritage discourse” (Smith, 2006) to implement “civilization process” policies (Jacka, 2009) toward marginalized populations, such as ethnic minorities and other subaltern groups of citizens (noneducated, poor, rural, illegal migrants). Consequently, we address this state-led societal transformation through the concept of coloniality, resulting in the celebration of a developed unified Sinicized nation beyond its differences. Cultural heritage is used as a form of social engineering, based on power relations between the state and society, revealing constant tensions between promotion and control. Yet, grassroots forms of appropriation of cultural narratives and alternative heritage practices exist in China that could be likened to decolonial approaches. However, they are more limited forms of resistance and claims for community empowerment, visibility, and rights than reactions induced by decolonial mobilizations worldwide. Relying on the theory of the postcolonial gaze and how the legacies of colonialism continue to structure modernity even after the collapse of colonial empires (Meinhof et al., 2017, 8), we argue that cultural heritage in China is a powerful tool that reproduces as well as reshapes structural inequalities between ethnic and social groups and entrenches them in the official narratives about producing “high-valued” Sinicized citizens to develop a more “harmonious society” and perform the “China Dream” (Zhu & Maags, 2020).

Whether a document is of historical or contemporary significance, typography plays a crucial role in its composition. From the earliest forms of writing in Mesopotamia to the early days of modern printing, typographic techniques have evolved and transformed, resulting in changes to the features of typography. By analyzing these features, we can gain insights into specific time periods, geographical locations, and messages conveyed through typography. Therefore, in this paper, we aim to investigate the feasibility of training a model to classify serif types without knowledge of the font and character. We also investigate how to train a vectorial-based image model able to group together fonts with similar features. Specifically, we compare the use of state-of-the-art image classification methods, such as the EfficientNet-B2 and the Vision Transformer Base model with different patch sizes, and the state-of-the-art fine-grained image classification method, TransFG, on the serif classification task. We also evaluate the use of the DeepSVG model to learn to group fonts with similar features. Our investigation reveals that fine-grained image classification methods are better suited for the serif classification tasks and that leveraging the character labels helps to learn more meaningful font similarities. This repository contains: - Paper published in the Journal of data mining and digital humanities: WasimEtAl_Toward_Automatic_Typography_Analysis__Serif_Classification_and_Font_Similarities.pdf - Two datasets: The first for serif classification consisting of 126666 training and 2914 font-independent testing images in raster format. The second dataset for svg based similarity learning consists of 124010 training and 2914 font-independent testing images. The images have been categorized into sans-serif, linear-serif, slab-serif, and triangular serif by a designer at the EPFL+ECAL Lab font_serif_dataset.zip font_svg_dataset.zip - model weights: serif_B_16_long_checkpoint.bin: refers to TransFG ViT B/16 Backend serif_B_32_long_checkpoint.bin: refers to TransFG ViT B/32 Backend ViT-B_16.npz ViT-B_32.npz are publicly available at: https://github.com/TACJu/TransFG and were used for training TransFG ViT B/16 Backend and TransFG ViT B/32 Backend - code: https://github.com/TalalWasim/GEST-Serif

Social media is increasingly being employed to develop Cultural Ecosystem Services (CES) indicators. The image-sharing platform Flickr has been one of the most popular sources of data. Most large-scale studies, however, tend to only use the number of images as a proxy for CES due to the challenges associated with processing large amounts of this data but this does not fully represent the benefit generated by ecosystems in terms of the positive experiences expressed by users in the associated text. To address this gap, we apply several Computer Vision (CV) and natural language processing (NLP) models to link CES estimates for Great Britain based on the content of images to sentiment measures using the accompanying text, and compare our results to a national, geo-referenced survey of recreational well-being in England. We find that the aesthetic quality of the landscape and the presence of particular wildlife results in more positive sentiment. However, we also find that different physical settings correlate with this sentiment and that sentiment is sometimes more strongly related to social activities than many natural factors. Still, we find significant associations between these CES measures, sentiment and survey data. Our findings illustrate that integrating sentiment analysis with CES measurement can capture some of the positive benefits associated with CES using social media. The additional detail provided by these novel techniques can help to develop more meaningful CES indicators for recreational land use management.

AbstractThe ongoing war in Ukraine has profoundly impacted the Ukrainian scientific community. Numerous researchers have either emigrated or transitioned to alternate professions. For those who remain in research, the destruction of civil infrastructure and psychological stress may dramatically slow down research progress. There is limited knowledge concerning the war’s influence on Ukrainian research. This study presents the results of a representative survey of over 2500 Ukrainian scientists. The data suggest that by the Fall of 2022, about 18.5% of the population of Ukrainian scientists fled the country. Notably, these emigrant scientists were amongst the most research-active in Ukraine. However, a significant portion of these migrant scientists are under precarious contracts at their host institutions. Of the scientists who stayed in Ukraine, about 15% have left research, and the others experience a marked reduction in research time. A large number of stayers have lost access to critical input for their research (23.5%) or cannot physically access their institution (20.8%). Finally, should the war stop today, it seems that Ukraine has already lost about seven percent of its scientists. These observations bear significant policy implications. In light of the vulnerable position of migrant scientists, the provision of more and longer scholarships emerges as a paramount concern for this group of scientists. Concerning stayers, institutions across Europe and beyond can offer a host of support programs, such as remote visiting programs, access to digital libraries and computing resources, as well as collaborative research grants.

Audiovisual (AV) archives, as an essential reservoir of our cultural assets, are suffering from the issue of accessibility. The complex nature of the medium itself made processing and interaction an open challenge still in the field of computer vision, multimodal learning, and human-computer interaction, as well as in culture and heritage. In recent years, with the raising of video retrieval tasks, methods in retrieving video content with natural language (text-to-video retrieval) gained quite some attention and have reached a performance level where real-world application is on the horizon. Appealing as it may sound, such methods focus on retrieving videos using plain visual-focused descriptions of what has happened in the video and finding videos such as instructions. It is too early to say such methods would be the new paradigms for accessing and encoding complex video content into high-dimensional data, but they are indeed innovative attempts and foundations to build future exploratory interfaces for AV archives (e.g., allow users to write stories and retrieve related snippets in the archive, or encoding video content at high-level for visualisation). This work filled the application gap by examining such text-to-video retrieval methods from an implementation point of view and proposed and verified a classifier-enhanced workflow to allow better results when dealing with in-situ queries that might have been different from the training dataset. Such a workflow is then applied to the real-world archive from Télévision Suisse Romande (RTS) to create a demo. At last, a human-centred evaluation is conducted to understand whether the text-to-video retrieval methods improve the overall experience of accessing AV archives.

Abstract Practices that reuse concrete pieces in new building or infrastructure projects are currently diversifying as concrete reuse gains more and more relevance for sustainability. The present research provides a yet missing identification of the main approaches to these practices and introduces a new set of criteria to compare them. Five types of sourced concrete pieces are identified, three resulting from careful deconstruction and two from demolition. The study shows that approaches allowing the best re-utilization rate of the structural capacities of the concrete pieces are less compatible with current demolition practices, in contrast to approaches reusing debris. The reuse of wall and slab panels, beams, and columns is a promising approach as it implies a low to medium level of constraints on the new design while recovering the capabilities of discarded reinforced concrete equivalently. A few dozen built precedents have already applied this approach to precast components, but applications reusing cast-in-place concrete are lacking, despite considerable CO2 emissions reduction.

Abstract Building replacement (BR) – i.e., the demolition of existing structures and subsequent construction of new buildings on the same site – is often understood as a necessary urban planning strategy despite significant environmental implications regarding solid waste generation, raw material depletion, and embodied greenhouse gas emissions. Besides, BR may also be considered an effective form of urban mining. Yet it has not been adequately studied in academic literature. Current studies often adopt a simplified ‘black box’ approach that overlooks the intricate internal mechanisms and fails to capture the interconnected material flows within the building stock. To address these gaps, this paper utilizes descriptive statistics and bipartite graph analysis to examine the transformation patterns of BR across three spatial scales in the city of Zurich. The analysis encompasses 1,018 replacement projects involving 6,115 building units from 2000 to 2019. By comparing the characteristics of demolished and newly constructed groups, the study reveals insights into the dynamic nature of BR. From a broader perspective, the combination of the various heterogeneous BR-related findings in this paper highlights the need to evaluate the application of circular economy principles to large building stocks with a more nuanced understanding of building stock dynamics over time.

Maximizing solar energy production in Switzerland is key to meet energy transition goals. Understanding in detail the current situation, and the potential for expansion is important to develop effective strategies. With this study, we want to contribute to federal and academic efforts to measure solar energy by estimating the net energy produced by photovoltaic (PV) installations when considering their embodied energy. We calculated the values of all energy produced by PV installations across Switzerland from 1991-2021 and subtracted the embodied energy used to manufacture the PV panels and their mounting system. We considered four different types: freestanding, attached-complex, attached-simple and integrated, with progressively decreasing values of embodied energy for the supporting structure. The results show that in 2022, 50% of PV installations were producing net energy, which accounts for an accumulated historical value of 1.000 GWh, implying that 6% of the historical PV generation is net energy. If mounting systems were minimized, the accumulated net energy would reach 23%, showing the importance of integrating PV panels in building elements. These findings suggest that policies to support the diffusion of photovoltaic panels should also ensure long term use of existing installations and consider the mounting systems’ embodied energy for new ones. Peer Reviewed