This study proposes a systematic policy framework that leverages special tax measures to steer stakeholder behavior toward urban cultural heritage conservation. Integrating comparative policy analysis, microeconomic modeling, systematic policy framework construction and case studies from China, we design a synergistic system of tax incentives and disincentives across income, consumption, and property taxes. The framework is contextualized within China’s forthcoming Cultural Heritage Conservation Law and demonstrates how fiscal instruments can align individual economic rationality with collective conservation goals. A three-stage decision model – grounded in Multi-Criteria Decision Analysis (MCDA) – is introduced to assess the suitability, necessity, and balancing of tax interventions. Based on the analysis of secondary sources and policy documents, empirical case studies in Suzhou and Tianshui are used to illustrate the framework’s efficacy and limitations. The findings offer a transferable model for sustainable urban governance, with relevance for rapidly urbanizing regions globally.
Zahra Rahimi Afzal, Tara Esmaeilbeig, Mojtaba Soltanalian
et al.
Parameter-Efficient Fine-Tuning (PEFT) is a popular class of techniques that strive to adapt large models in a scalable and resource-efficient manner. Yet, the mechanisms underlying their training performance and generalization remain underexplored. In this paper, we provide several insights into such fine-tuning through the lens of linearization. Fine-tuned models are often implicitly encouraged to remain close to the pretrained model. By making this explicit, using an Euclidean distance inductive bias in parameter space, we show that fine-tuning dynamics become equivalent to learning with the positive-definite neural tangent kernel (NTK). We specifically analyze how close the fully linear and the linearized fine-tuning optimizations are, based on the strength of the regularization. This allows us to be pragmatic about how good a model linearization is when fine-tuning large language models (LLMs). When linearization is a good model, our findings reveal a strong correlation between the eigenvalue spectrum of the NTK and the performance of model adaptation. Motivated by this, we give spectral perturbation bounds on the NTK induced by the choice of layers selected for fine-tuning. We empirically validate our theory on Low Rank Adaptation (LoRA) on LLMs. These insights not only characterize fine-tuning but also have the potential to enhance PEFT techniques, paving the way to better informed and more nimble adaptation in LLMs.
Each King in their respective reigns attempted to shape visual culture according to their intellectual and ideological foundations. In some periods, these changes were explicit and evident, while in others, they were implicit and gradual. The Zand era also possesses distinctive artistic characteristics, including a particular type of Mihrab design. In other words, one of the identifying components of Zand-era visual culture is a type of "Mihrab" design. The Zand Mihrab design exhibits unique visual elements that serve as an iconic representation of the visual culture of that period, along with other visual components, forming the artistic characteristics of the era. The art of the Zand era is full of innovative designs, among which the repetition of a type of frame similar to the types of altars is thought-provoking. Introducing the mentioned frame as an identity identifier and searching for its frequency and how it is manifested in the Zand heritage is the concern of this article. The design of a mihrab with a corrugation, which is often seen in the art of the Zand, is a combination of two crescent and pointed arches, which has brought the upper part, especially the crown of the arch, to the fore in a new form. The mentioned design is an innovative frame in the Zend era and has a hybrid form that is inspired by two crescent and pointed arches in the crown part. The discovery of such distinctive markers necessitates research in this field, as the lack of attention to the study framework may result in misattributing artworks to the Zand era or the early years of the Qajar period without proper identification. The adoption of Mihrab designs imprinted on dateless artifacts and handicrafts of the Zand era will serve as an identity marker of that period. While motifs inspired by arches and muqarnas are prominent in Islamic art, the present study argues that the "Mihrab" design discussed here, is a distinguished visual characteristic of Zand-era art.Research Objective: The primary objective is to introduce, classify, and study the form of the "Mihrab" frame in Zand-era artworks to define one of its visual elements and cultural markers. The secondary objective is to establish the "Zand Mihrab" as an identity marker.Research Questions: How can the unique work of the "Zand Frame" be explained as an identity marker in artworks from the second half of the 12th century and the first half of the 13th century AH? How is the identity marker of the "Zand motif" interpreted in terms of innovation in the design of the Mihrab?In terms of the hypothesis it is assumed that the "Mihrab" design is an identity marker of the art in the Zand era.Research Methodology: This research is primarily theoretical, as it aims to explore the visual phenomenon known as the "Zand Mihrab" design and to elucidate its characteristics and qualities. The research employs a descriptive-analytical approach, utilizing library research, document analysis, virtual observations, and field visits to collect information and concepts. Data was gathered through written texts and images, focusing on 19 samples of visual arts from the Zand period, including tiles of Vakil mosque, the pavilion, the Haft-Tanan mansion, as well as objects and artifacts such as carpets, tombstones, a wooden door located in the Qazvin Museum, and a fabric piece containing a "Mihrab" frame.Results: The quantitative findings of this research indicate a prevalence of the "Mihrab" design in the Vakil mosque compared to other architectural structures and artistic works of the mentioned period. The study of the chronological evolution of the "Zand Mihrab" design demonstrates its invention and flourishing in the second half of the 12th century AH and persisted during the first half of the 13th century AH.Another significant finding of this research is that, although the studied design carries spiritual meanings, it has been transformed in usage during the Zand period and manifested in non-religious architectural structures and artifacts. The "Mihrab" design is found in works such as the Vakil mosque (religious), the pavilion, and the Abdul Razzaq Khan mansion (palace), as well as in Vakil School (educational) and the decoration of objects and tombstones. The Zand-era artists, through innovation in the design and modern visual composition of the Mihrab arch by iterating and harmonizing the application of the motif, and ultimately the utilization of the principle of diversity, transformed the "Mihrab" design into an identity element of the Zand period. Thus, in addition to its original invention, the repetition and diverse application of this form in various arts and architectures have turned the spiritual figure of Mihrab design into a symbol of Zand's identity and an integral part of the visual culture.
Studies of the rotational velocities of intermediate-mass main-sequence stars are crucial for testing stellar evolution theory. They often rely on spectroscopic measurements of the projected rotation velocities. These not only suffer from the unknown projection factor but tend to ignore additional line-profile broadening mechanisms aside from rotation, such as pulsations and turbulent motions near the stellar surface. This limits the accuracy of Veq distributions. We use asteroseismic measurements to investigate the distribution of the equatorial rotation velocity, its ratio with respect to the critical rotation velocity, and the specific angular momentum for several thousands of BAF-type stars, covering a mass range from 1.3M$_\odot$ to 8.8M$_\odot$ and almost the entire core-hydrogen burning phase. We rely on high-precision model-independent internal rotation frequencies, as well as on masses and radii from asteroseismology to deduce Veq, Veq/Vcrit, and J/M for 2937 gravity-mode pulsators in the Milky Way. The sample stars have rotation frequencies between almost zero and 33$μ$Hz, corresponding to rotation periods above 0.35d. We find that intermediate-mass stars experience a break in their J/M occurring in the mass interval $[2.3,2.7]\,$M$_\odot$. We establish unimodal Veq and Veq/Vcrit distributions for the mass range $[1.3,2.5[$M$_\odot$, while stars with $M\in[2.5,8.8]$M$_\odot$ reveal some structure in their distributions. We find that the near-core rotation slows down as stars evolve, pointing to very efficient angular momentum transport. The kernel density estimators of the asteroseismic internal rotation frequency, equatorial rotation velocity, and specific angular momentum of this large sample of intermediate-mass field stars can conveniently be used for population synthesis studies and to fine-tune the theory of stellar rotation across the main sequence evolution.
Detecting toxic content using language models is crucial yet challenging. While substantial progress has been made in English, toxicity detection in French remains underdeveloped, primarily due to the lack of culturally relevant, human-annotated, large-scale datasets. In this work, we release ToxiFrench, a dataset of 53,622 French online comments together with a balanced benchmark split for systematic evaluation. The dataset is constructed via a semi-automated annotation pipeline that reduces manual labeling to only 10% through high-confidence LLM-based pre-annotation and human verification, while ensuring statistical alignment with human-only annotation. We then benchmark a broad range of models and uncover a counterintuitive finding: Small Language Models (SLMs) often surpass larger models in robustness and generalization on this task. Motivated by this finding, we propose a novel Chain-of-Thought (CoT) fine-tuning strategy using a Dynamic Weighted Loss (DWL) that progressively emphasizes the model's final decision and significantly improves faithfulness. Our fine-tuned 4B model (Qwen3-4B) achieves state-of-the-art performance on the benchmark. It improves its balanced accuracy by 10% over its baseline and achieves better performance than GPT-4o and DeepSeek-R1 on our benchmark, while successfully retaining cross-lingual capabilities.
Purpose: This study explores interactive poetry therapy as a method for empathetic reading in holistic, emotional literature education. Design: Five experienced teachers participated in a descriptive case study by attending interactive empathetic reading sessions during in-service education. The participants, inspired by an extract from a novel, wrote personal stories and presented them for group discussions. Methodology: The data, consisting of audio recordings of the dialogues and the researchers’ associated notes, were analysed via thematic content analysis. Three main themes, which are presented under the headings: Story level; narrative meanings; Individual level; emotions relating to storytelling moments; and Communal level; issues of welfare and self-care. Findings: The results indicated that the writers’ personal stories and the group dialogues based on them prompted the participants to reflect on their own experiences and emotions, and prompted them to examine ethically challenging issues in the teaching profession. Originality: The study of empathetic reading in teachers’ in-service education provide more understanding of possibilities for teachers to increase their knowledge of the value of stories and narratives.
The fine-tuning of pre-trained language models has a great success in many NLP fields. Yet, it is strikingly vulnerable to adversarial examples, e.g., word substitution attacks using only synonyms can easily fool a BERT-based sentiment analysis model. In this paper, we demonstrate that adversarial training, the prevalent defense technique, does not directly fit a conventional fine-tuning scenario, because it suffers severely from catastrophic forgetting: failing to retain the generic and robust linguistic features that have already been captured by the pre-trained model. In this light, we propose Robust Informative Fine-Tuning (RIFT), a novel adversarial fine-tuning method from an information-theoretical perspective. In particular, RIFT encourages an objective model to retain the features learned from the pre-trained model throughout the entire fine-tuning process, whereas a conventional one only uses the pre-trained weights for initialization. Experimental results show that RIFT consistently outperforms the state-of-the-arts on two popular NLP tasks: sentiment analysis and natural language inference, under different attacks across various pre-trained language models.
Analizamos en el presente trabajo una estatua del tipo convencionalmente denominado Orante sumerio, depositada en el Museo Arqueológico Nacional (Madrid), y expuesta actualmente en sus salas de Egipto, Nubia y Oriente Próximo. Revisaremos la pieza en detalle, comentando sus características y estado de conservación, haremos una breve referencia al significado que pudo tener en la sociedad en que surgió, y finalmente nos plantearemos su posible origen geográfico y su cronología, así como ciertos elementos que tal vez podrían ser indicios de una discutible antigüedad.
History of the arts, Museums. Collectors and collecting
Thomas C. Nicholas, Adam E. Stones, Adam Patel
et al.
Amorphous calcium carbonate (ACC) is an important precursor for biomineralisation in marine organisms. Among the key outstanding problems regarding ACC are how best to understand its structure and how to rationalise its metastability as an amorphous phase. Here, we report high-quality atomistic models of ACC generated by using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently-developed inversion approach, we extract from these models the effective Ca$\boldsymbol\cdots$Ca interaction potential governing ACC formation. This potential contains minima at two competing distances, corresponding to the two different ways in which carbonate ions bridge Ca$^{2+}$-ion pairs. We reveal an unexpected mapping to the Lennard-Jones--Gauss (LJG) model normally studied in the context of computational soft-matter, with the empirical LJG parameters for ACC taking values known to promote structural complexity. In this way we show that both the complex structure of ACC and its resilience to crystallisation are actually encoded in the geometrically-frustrated effective interactions between Ca$^{\boldsymbol 2+}$ ions.
Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann
et al.
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million German medical documents and has been shown to achieve new state-of-the-art performance on eight different medical benchmarks covering a wide range of disciplines and medical document types. In addition to evaluating the overall performance of the model, this paper also conducts a more in-depth analysis of its capabilities. We investigate the impact of data deduplication on the model's performance, as well as the potential benefits of using more efficient tokenization methods. Our results indicate that domain-specific models such as medBERTde are particularly useful for longer texts, and that deduplication of training data does not necessarily lead to improved performance. Furthermore, we found that efficient tokenization plays only a minor role in improving model performance, and attribute most of the improved performance to the large amount of training data. To encourage further research, the pre-trained model weights and new benchmarks based on radiological data are made publicly available for use by the scientific community.
In this paper, we introduce Coarse-Fine Networks, a twostream architecture which benefits from different abstractions of temporal resolution to learn better video representations for long-term motion. Traditional Video models process inputs at one (or few) fixed temporal resolution without any dynamic frame selection. However, we argue that, processing multiple temporal resolutions of the input and doing so dynamically by learning to estimate the importance of each frame can largely improve video representations, specially in the domain of temporal activity localization. To this end, we propose (1) ‘Grid Pool’, a learned temporal downsampling layer to extract coarse features, and, (2) ‘Multi-stage Fusion’, a spatio-temporal attention mechanism to fuse a finegrained context with the coarse features. We show that our method outperforms the state-of-the-arts for action detection in public datasets including Charades with a significantly reduced compute and memory footprint. The code is available at https://github.com/kkahatapitiya/Coarse-Fine-Networks.
This article explores the role of glass as a medium in the fine arts rather than as a craft form. It includes a short history of glass as an art medium, the development of glass technologies and their application in the field of fine art. It reflects the distinctiveness of glass as a sculptural medium due to its optical properties and transparency; glass’s inherent characteristics create the unique possibility of using the space both outside and inside a solid object. This article, furthermore, demonstrates the importance of specific individuals in bringing glass as a fine art medium to the fore, in particular Adriano Berengo. Berengo proves exceptional in promoting glass in the field of fine arts and has been particularly effective in encouraging well-known artists to experiment with it as a medium. The article discusses the impact of his efforts to establish cooperation with great names from all over the world, from Ai Weiwei to Tony Cragg and from Jaume Plensa to César, who have passed through Adriano Berengo’s studio.
A Poincaré-Einstein metric $g$ is called non-degenerate if there are no non-zero infinitesimal Einstein deformations of $g$, in Bianchi gauge, that lie in $L^2$. We prove that a 4-dimensional Poincaré-Einstein metric is non-degenerate if it satisfies a certain chiral curvature inequality. Write $R_+$ for the part of the curvature operator of g which acts on self-dual 2-forms. We prove that if $R_+$ is negative definite then $g$ is non-degenerate. This is a chiral generalisation of a result due to Biquard and Lee, that a Poincaré-Einstein metric of negative sectional curvature is non-degenerate
This research is an attempt to find an objective system to preserve the cultural identity in design. The proposed framework will guide designers to identify the main features and the specific design language of traditional cultural products, then take advantage of these features to give more diversity to the traditional style and help it keep pace with the rapid developments in the field of design. There is no doubt that traditional crafts are an important source of inspiration when generating new ideas, so this paper includes an analysis of a popular traditional Kuwaiti product called Sadu. The results of the analysis showed the most common features of geometric shapes present among the Sadu products that directly affect the approach suggested by the study. Then a group of designs inspired by Sadu were created based on the results of the questionnaire.Keywords:Heritage - Identity - Handicrafts - Sadu - Geometric shapes
Diederik Aerts, Jonito Aerts Arguëlles, Lester Beltran
et al.
We present the results of two tests where a sample of human participants were asked to make judgements about the conceptual combinations {\it The Animal Acts} and {\it The Animal eats the Food}. Both tests significantly violate the Clauser-Horne-Shimony-Holt version of Bell inequalities (`CHSH inequality'), thus exhibiting manifestly non-classical behaviour due to the meaning connection between the individual concepts that are combined. We then apply a quantum-theoretic framework which we developed for any Bell-type situation and represent empirical data in complex Hilbert space. We show that the observed violations of the CHSH inequality can be explained as a consequence of a strong form of `quantum entanglement' between the component conceptual entities in which both the state and measurements are entangled. We finally observe that a quantum model in Hilbert space can be elaborated in these Bell-type situations even when the CHSH violation exceeds the known `Cirel'son bound', in contrast to a widespread belief. These findings confirm and strengthen the results we recently obtained in a variety of cognitive tests and document and image retrieval operations on the same conceptual combinations.
Alfian Candra Ayuswantana, Agus Sachari, Irfansyah Irfansyah
Abstrak
Wayang Jekdong hidup dan berkembang dalam konteks sosial-budaya Arek yang sangat khas. Budaya Arek sebagai sub-budaya Jawa Timur menyebar dari pantai utara Jawa Timur ke pedalaman sepanjang aliran sungai Brantas menyebabkan pengaruh nilai-nilai Islam kental terasa pada budaya Arek. Nilai-nilai Islam yang kuat salah satunya dapat dilihat dalam wayang boneka Jekdong sebagai artefak budaya masyarakat budaya Arek. Penelitian ini berfokus pada pengamatan visual pada boneka Jekdong yang mewakili nilai-nilai Islam melalui bentuk boneka. Pengamatan dilakukan dengan pendekatan etnografi melalui proses analisis komponen visual Spradley dalam wayang Jekdong yang didukung oleh teori semiotika dyadic Saussure-Barthes. Hasil analisis menunjukkan bahwa ada pengaruh nilai-nilai Islam yang diwakili dalam bentuk boneka wayang Jekdong terutama pada tokoh Dewa (dewa atau dewa tertinggi) dan Resi (pertapa). Bentuk budaya Arek sebagai komunitas Islam pesisir sangat jelas terlihat terutama pada atribut pakaian yang ditampilkan seperti keberadaan turban putih, khaftan, qamis, dan sepatu Persia. Diharapkan dengan penelitian ini dapat memberikan kontribusi ilmiah tentang wayang golek Jekdong dalam sudut pandang ilmiah seni di provinsi Jawa Timur khususnya.
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Kata Kunci: budaya Arek, busana, wayang Jekdong, Islam pesisir
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Abstract
The Jekdong puppets lives and develops in a very distinctive Arek socio-cultural context. The Arek culture as East Java sub-culture spreads from the north coast of East Java to the depths along with the Brantas river flow causing the influence of Islamic values upon the Arek Culture. Strong Islamic values, one of them can be seen within Jekdong puppets as a cultural artifact of the Arek society. This research focuses on visual observations on Jekdong puppets that represent Islamic values through the form of puppets. Observations performed with an ethnographic approach through a process of Spradley's visual components analyzing in Jekdong puppets and supported by the dyadic semiotics theory of Saussure-Barthes. The results of the analysis show that there are influences of Islamic values that represented in the form of Jekdong puppets, especially in Dewa (deity or supreme being) and Resi (hermits or saints) figures. The form of Arek culture as an Islamic coastal community is very clearly visible, especially in the fashion attributes that displayed such as the existence of white turban, Kaftan, Qamis, and Persian shoes. It expected that this research could provide scientific contributions about the Jekdong puppet show puppet in the scientific viewpoint of art, particularly in East Java province.
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Keywords: Arek culture, coastal Islam, fashion, Jekdong puppet
Peer assessment is a popular technique for a more fine-grained evaluation of individual students in group projects. Its effect on the evaluation is well studied. However, its effects on the learning abilities of students are often overlooked. In this paper, we explore self-evaluation, motivation, and study time of students in relation to peer assessment, as part of an ongoing project at our local Faculty of Engineering Technology. The aggregated measurements of two years so far show that: (1) students get much better at evaluating their own project on some, but not all, of the evaluation criteria after a peer assessment session, (2) students report in a follow-up survey that they are more motivated to work on their project, and (3) the relation between motivation and time spent on the project increases. These results suggest that peer grading could have positive long-term effects on the reflective, and therefore lifelong learning, skills of students. A better understanding of the evaluation criteria results in more accurate self and peer grades, emphasizing the importance of properly defining and communicating these criteria throughout the semester.
Laith Sakka, Kirshanthan Sundararajah, Ryan R. Newton
et al.
Applications in many domains are based on a series of traversals of tree structures, and fusing these traversals together to reduce the total number of passes over the tree is a common, important optimization technique. In applications such as compilers and render trees, these trees are heterogeneous: different nodes of the tree have different types. Unfortunately, prior work for fusing traversals falls short in different ways: they do not handle heterogeneity; they require using domain-specific languages to express an application; they rely on the programmer to aver that fusing traversals is safe, without any soundness guarantee; or they can only perform coarse-grain fusion, leading to missed fusion opportunities. This paper addresses these shortcomings to build a framework for fusing traversals of heterogeneous trees that is automatic, sound, and fine-grained. We show across several case studies that our approach is able to allow programmers to write simple, intuitive traversals, and then automatically fuse them to substantially improve performance.
Ahmed Hosny, Michael Schwier, Christoph Berger
et al.
Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among others. Additionally, the availability of open-source computational frameworks has lowered the barriers to implementing state-of-the-art methods across multiple domains. Albeit leading to major performance breakthroughs in some tasks, effective dissemination of deep learning algorithms remains challenging, inhibiting reproducibility and benchmarking studies, impeding further validation, and ultimately hindering their effectiveness in the cumulative scientific progress. In developing a platform for sharing research outputs, we present ModelHub.AI (www.modelhub.ai), a community-driven container-based software engine and platform for the structured dissemination of deep learning models. For contributors, the engine controls data flow throughout the inference cycle, while the contributor-facing standard template exposes model-specific functions including inference, as well as pre- and post-processing. Python and RESTful Application programming interfaces (APIs) enable users to interact with models hosted on ModelHub.AI and allows both researchers and developers to utilize models out-of-the-box. ModelHub.AI is domain-, data-, and framework-agnostic, catering to different workflows and contributors' preferences.