Hasil untuk "Languages and literature of Eastern Asia, Africa, Oceania"

F. Rafiqi, A. Maksum

This study examines the strategic role of sake as an instrument of cultural diplomacy within the framework of trade relations between Japan and Europe, using a theoretical approach that combines the concepts of soft power, gastrodiplomacy, and nation branding. Sake, as a traditional Japanese fermented beverage rooted in the spiritual and social practices of society, has undergone a reorientation of its function from domestic consumption to a symbol of national cultural identity promoted internationally. Through the Cool Japan policy, the Japanese government actively positions sake as a key element in public diplomacy, linking cultural heritage with export trade strategies.The implementation of the EU-Japan Economic Partnership Agreement (EPA) since 2018, which includes geographical indication (GI) protection, provides additional legitimacy for the authenticity of sake in the European market. Promotional strategies involving culinary festivals, cross-industry collaborations, and product narratives emphasizing aesthetic value, origins, and traditional production techniques have successfully enhanced European public perception of sake and, more broadly, of Japan. Export data shows significant growth, with France, the United Kingdom, and Germany contributing the most, indicating the success of this approach in expanding market penetration. However, this dynamic is not without criticism, including the commodification of cultural values, exclusion of small producers, and the risk of reducing the spiritual meaning of sake in a commercialized context.Therefore, this study emphasizes the importance of cultural diplomacy that not only highlights visual appeal and market narratives but also commits to preserving values and the participation of local cultural communities. In conclusion, sake diplomacy offers an intriguing model for the integration of culture and economy in international relations, demonstrating that cultural products can serve as an effective means to build cross-national relations rooted in empathy, experience, and appreciation for the uniqueness of traditions.

Steven M. Radil, Nick Dorward, Olivier Walther et al.

Existing models of political violence often emphasize discrete transitions, when conflicts emerge, escalate, or subside, without considering the longer trajectories of violence that accumulate across time and space. This paper introduces a spatially explicit longitudinal sequence analysis to address this gap. Using event-level data from the Armed Conflict Location and Event Dataset covering Africa from 1997 to 2024, we classify locations according to the intensity and spatial concentration of violence, tracing how these states evolve into distinct conflict trajectories. Applying optimal matching and clustering techniques, we identify six recurrent patterns ranging from short-lived, localized outbreaks to protracted high-intensity conflicts. We further assess how these trajectories align across neighboring areas, revealing evidence of spatial interdependence, particularly in border regions. By highlighting the temporal rhythms and geographic linkages of political violence, the study advances conflict research beyond isolated transitions and provides a framework for understanding the life cycles of violence.

Delia Rabie

Kexin Chen, Yuyang Du, Junyou Li et al.

The development of AI-assisted chemical synthesis tools requires comprehensive datasets covering diverse reaction types, yet current high-throughput experimental (HTE) approaches are expensive and limited in scope. Chemical literature represents a vast, underexplored data source containing thousands of reactions published annually. However, extracting reaction information from literature faces significant challenges including varied writing styles, complex coreference relationships, and multimodal information presentation. This paper proposes ChemMiner, a novel end-to-end framework leveraging multiple agents powered by large language models (LLMs) to extract high-fidelity chemical data from literature. ChemMiner incorporates three specialized agents: a text analysis agent for coreference mapping, a multimodal agent for non-textual information extraction, and a synthesis analysis agent for data generation. Furthermore, we developed a comprehensive benchmark with expert-annotated chemical literature to evaluate both extraction efficiency and precision. Experimental results demonstrate reaction identification rates comparable to human chemists while significantly reducing processing time, with high accuracy, recall, and F1 scores. Our open-sourced benchmark facilitates future research in chemical literature data mining.

Bijay Adhikari, Pratibha Kulung, Jakesh Bohaju et al.

Automating brain tumor segmentation using deep learning methods is an ongoing challenge in medical imaging. Multiple lingering issues exist including domain-shift and applications in low-resource settings which brings a unique set of challenges including scarcity of data. As a step towards solving these specific problems, we propose Convolutional adapter-inspired Parameter-efficient Fine-tuning (PEFT) of MedNeXt architecture. To validate our idea, we show our method performs comparable to full fine-tuning with the added benefit of reduced training compute using BraTS-2021 as pre-training dataset and BraTS-Africa as the fine-tuning dataset. BraTS-Africa consists of a small dataset (60 train / 35 validation) from the Sub-Saharan African population with marked shift in the MRI quality compared to BraTS-2021 (1251 train samples). We first show that models trained on BraTS-2021 dataset do not generalize well to BraTS-Africa as shown by 20% reduction in mean dice on BraTS-Africa validation samples. Then, we show that PEFT can leverage both the BraTS-2021 and BraTS-Africa dataset to obtain mean dice of 0.8 compared to 0.72 when trained only on BraTS-Africa. Finally, We show that PEFT (0.80 mean dice) results in comparable performance to full fine-tuning (0.77 mean dice) which may show PEFT to be better on average but the boxplots show that full finetuning results is much lesser variance in performance. Nevertheless, on disaggregation of the dice metrics, we find that the model has tendency to oversegment as shown by high specificity (0.99) compared to relatively low sensitivity(0.75). The source code is available at https://github.com/CAMERA-MRI/SPARK2024/tree/main/PEFT_MedNeXt

Franciszek Piszcz

There is a vast gap in the quality of IDE tooling between static languages like Java and dynamic languages like Python or JavaScript. Modern frameworks and libraries in these languages heavily use their dynamic capabilities to achieve the best ergonomics and readability. This has a side effect of making the current generation of IDEs blind to control flow and data flow, which often breaks navigation, autocompletion and refactoring. In this thesis we propose an algorithm that can bridge this gap between tooling for dynamic and static languages by statically analyzing dynamic metaprogramming and runtime reflection in programs. We use a technique called abstract interpretation to partially execute programs and extract information that is usually only available at runtime. Our algorithm has been implemented in a prototype analyzer that can analyze programs written in a subset of JavaScript.

Mike Cruchten

Automata operating on pairs of words were introduced as an alternative way of capturing acceptance of regular $ω$-languages. Families of DFAs and lasso automata operating on such pairs followed, giving rise to minimisation algorithms, a Myhill-Nerode theorem and language learning algorithms. Yet Kleene theorems for such a well-established class are still missing. We introduce rational lasso languages and expressions, show a Kleene theorem for lasso languages and explore the connection between rational lasso and $ω$-expressions, which yields a Kleene theorem for $ω$-languages with respect to saturated lasso automata. For one direction of the Kleene theorems, we also provide a Brzozowski construction for lasso automata from rational lasso expressions.

Adriel Josias Bébiné

This paper deals with the associated motion (AM) system in Nuasúɛ (A62A), a Bantu language spoken in Cameroon. It aims at determining the coding means and the grammatical properties of AM categories (motion and direction), their grammatical characteristics and their interactions with non-spatial verbal categories. Nuasúɛ has a complex AM system where prior motion and (mono-/bi-)directional motion are marked in a single verb word by two distinct satellites, of which the first is a high tone melody and the second is one of four polysemous directionals: the ventive àsɪ= and three itives kà-, à‑, ɲa=. The distribution and reading of these directionals correlate with the grammatical categories of (im)perfectivity, (non-)finiteness and the (ir)realis, when associated with the events described by the various verb words. Furthermore, in the case of a combination of spatial and non-spatial categories, there are two possible. When both are marked by tonal morphemes in a single verb word a tonal redistribution occurs. However, when both are marked by segmental morphemes, four types of motion echo constructions can be distinguished, each reflecting a different degree of separability/integration between the motion and the non-motion events.

Qusai Khraisha, Sophie Put, Johanna Kappenberg et al.

Systematic reviews are vital for guiding practice, research, and policy, yet they are often slow and labour-intensive. Large language models (LLMs) could offer a way to speed up and automate systematic reviews, but their performance in such tasks has not been comprehensively evaluated against humans, and no study has tested GPT-4, the biggest LLM so far. This pre-registered study evaluates GPT-4's capability in title/abstract screening, full-text review, and data extraction across various literature types and languages using a 'human-out-of-the-loop' approach. Although GPT-4 had accuracy on par with human performance in most tasks, results were skewed by chance agreement and dataset imbalance. After adjusting for these, there was a moderate level of performance for data extraction, and - barring studies that used highly reliable prompts - screening performance levelled at none to moderate for different stages and languages. When screening full-text literature using highly reliable prompts, GPT-4's performance was 'almost perfect.' Penalising GPT-4 for missing key studies using highly reliable prompts improved its performance even more. Our findings indicate that, currently, substantial caution should be used if LLMs are being used to conduct systematic reviews, but suggest that, for certain systematic review tasks delivered under reliable prompts, LLMs can rival human performance.

Anna A. Ślączka

Yip Ka-Fai

This paper investigates an understudied topic in adverbial clauses, converbs, which are verb forms that mark adverbial subordination. Focusing on converbal clauses in Cantonese, I show that they do not share a uniform syntax and should be divided into two classes, formed by central converbs (such as conditional clauses formed by V-can1) and peripheral converbs (such as inferential clauses formed by V-dak1) respectively. The central class adjoins low to the event/proposition level projections of the main clauses and has an impoverished internal structure, whereas the peripheral class attaches high to the discourse level projections of the main clauses and has an articulated internal structure. The distinction displays remarkable parallelism with the central-peripheral dichotomy of adverbial clauses proposed by Haegeman (2003a, 2003b, 2010), calling for a unified syntax of adverbial clauses formed by converbs and by subordinators, which is achievable under an agreement analysis of converbs.

Rufus H. Gouws, D.J. Prinsloo

This article, the third in a series of three on lexicographic data boxes, firstly focuses on a number of aspects of data boxes in bilingual dictionaries with the emphasis on different approaches in bilingual dictionaries with an African language as one of the members of the treated language pair. It is not possible to provide a comprehensive discussion within the limitations of an article. Then the discussion proceeds by looking at some new ways of using data boxes in online dictionaries. It is shown that the possibilities of the new medium allow lexicographers to employ data boxes in both traditional and non-traditional ways. It is argued that data boxes are expected to fulfil a variety of purposes ranging from navigational information and the provision of salient information to giving access to relevant data in dictionary-internal and dictionary-external sources. Lexicographers of online dictionaries have introduced new ways of using data boxes that have not yet been fully discussed in metalexicographic literature. This article gives an identification and a brief discussion of some of these innovative uses of data boxes. It stresses the potential that the online environment offers lexicography. Practical and theoretical lexicographers need to be aware of these possibilities and challenges. By embarking on a more comprehensive use of data boxes dictionaries can become even better containers of knowledge and can serve their users in an optimal way.

Yagoub Adam, Suraju Sadeeq, Judit Kumuthini et al.

Polygenic risk score (PRS) analysis is a powerful method been used to estimate an individual's genetic risk towards targeted traits. PRS analysis could be used to obtain evidence of a genetic effect beyond Genome-Wide Association Studies (GWAS) results i.e. when there are no significant markers. PRS analysis has been widely applied to investigate the genetic basis of several traits including rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies showed that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we reviewed the conventional PRS methods and their application to sub-saharan Africa communities. We concluded that the limiting factor of applying PRS analysis to sub-saharan populations is the lack of sufficient GWAS data. Also, we recommended developing African-specific PRS tools

Karine Ferreira Maciel

Este trabalho busca apresentar a recepção inicial que é dedicada a Adília Lopes no Brasil pela crítica editorial. O principal objetivo é apresentar quais editoras, revistas e críticos proporcionaram esse acolhimento da poetisa, comentando brevemente as causas da notoriedade da autora. Para tanto, mostraremos as organizações de antologias portuguesas pós-Pessoa editadas no Brasil e compactuaremos da teoria da estética da recepção de Hans Robert Jauss.

Jorge C. Lucero, Sławek Staworko

An F-system is a computational model that performs a folding operation on words of a given language, following directions coded on words of another given language. This paper considers the case in which both given languages are regular, and it shows that the class of languages generated by such F-systems is a proper subset of the class of linear context-free languages.

Gábor Kósa

A Lü Buwei 呂不韋 (i. e. 3. sz.) nevéhez kötődő Lüshi chunqiu 呂氏春秋 17. könyve egy olyan hivatalnoklistát tartalmaz, amely tagjainak nevéhez valamilyen kulturális jelenség megteremtése kötődik. Jelen tanulmányban e listákon szereplő 26 személyt (Da Nao 大橈, Qian Ru 黔如, Rong Cheng 容成, Xi He 羲和, Shang Yi 尚儀, Hou Yi  益, Hu Cao 胡曹, Yi Yi 夷羿, Zhu Rong 祝融, Yi Di 儀狄, Gao Yuan 高元, Yu Xu 虞姁, Bo Yi 伯益, Chi Ji 赤冀, Cheng Ya  雅, Han Ai 寒哀, Wang Hai 王亥, Shi Huang 史皇, Wu Peng 巫彭, Wu Xian巫咸, Xi Zhong 奚仲, Cang Jie 蒼頡, Houji 后稷, Gao Yao 皋陶, Kunwu 昆吾, Gun 鯀) és a velük kapcsolatos információkat tekintem át.

Amalya Navyca Putri

Tujuan penelitian ini untuk menjelaskan penggunaan konjungsi subordinatif kausal dan temporal dalam wacana berita online bereputasi nasional. Peneltian ini menggunakan pendekatan kualitatif. Data penelitian ini berupa konjungsi kausal dan temporal yang digunakan dalam sebuah kalimat dalam wacana berita online bereputasi nasional. Sumber data penelitian ini adalah berita-berita online bereputasi nasional yang terdapat dalam media online kompas.com, detik.com, dan tribunnews.com edisi bulan November 2018 pada tanggal 1-30 yang sudah diunduh dan disimpan. Pengumpulan data dilakukan dengan teknik dokumentasi. Hasil penelitian ini menunjukkan bahwa ditemukan adanya konjungsi kausal berupa konjungsi penyebaban dan konjungsi pengakibatan, serta konjungsi temporal dalam wacana berita online bereputasi nasional yang terdapat dalam kompas.com, detik.com, dan tribunnews.com edisi November 2018 tanggal 1-30 yang telah diunduh dan disimpan. Kata Kunci: konjungsi subordinatif, penyebaban, pengakibatan, temporal, wacana berita The purpose of this study is to explain the use of causal and temporal subordinate conjunctions in a nationally reputable online news discourse. This study uses a qualitative approach. This study data is in the form of causal and temporal conjunctions used in a sentence in a nationally reputable online news discourse. The source of this study data is national reputable online news contained in the online media kompas.com, detik.com, and tribunnews.com of the November 2018 edition that has been downloaded and saved. Data collection is done by documentation techniques. The results of this study indicate that there were found causal conjunctions in the form of causal conjunctions and impact conjunctions, as well as temporal conjunctions in nationally reputable online news discourses contained in the November 2018 edition issue of kompas.com, detik.com, and tribunnews.com that has been downloaded and saved. Keyword: subordinative conjunction, cause, effect, temporal, news discourse

Usman Nazir, Numan Khurshid, Muhammad Ahmed Bhimra et al.

This paper proposes to employ a Inception-ResNet inspired deep learning architecture called Tiny-Inception-ResNet-v2 to eliminate bonded labor by identifying brick kilns within "Brick-Kiln-Belt" of South Asia. The framework is developed by training a network on the satellite imagery consisting of 11 different classes of South Asian region. The dataset developed during the process includes the geo-referenced images of brick kilns, houses, roads, tennis courts, farms, sparse trees, dense trees, orchards, parking lots, parks and barren lands. The dataset is made publicly available for further research. Our proposed network architecture with very fewer learning parameters outperforms all state-of-the-art architectures employed for recognition of brick kilns. Our proposed solution would enable regional monitoring and evaluation mechanisms for the Sustainable Development Goals.

Rita Gitik, Eliyahy Rips

We prove that the closure of the one-sided Dyck language in a free monoid is a two-sided Dyck language.

Mirac Suzgun, Sebastian Gehrmann, Yonatan Belinkov et al.

In this paper, we systematically assess the ability of standard recurrent networks to perform dynamic counting and to encode hierarchical representations. All the neural models in our experiments are designed to be small-sized networks both to prevent them from memorizing the training sets and to visualize and interpret their behaviour at test time. Our results demonstrate that the Long Short-Term Memory (LSTM) networks can learn to recognize the well-balanced parenthesis language (Dyck-$1$) and the shuffles of multiple Dyck-$1$ languages, each defined over different parenthesis-pairs, by emulating simple real-time $k$-counter machines. To the best of our knowledge, this work is the first study to introduce the shuffle languages to analyze the computational power of neural networks. We also show that a single-layer LSTM with only one hidden unit is practically sufficient for recognizing the Dyck-$1$ language. However, none of our recurrent networks was able to yield a good performance on the Dyck-$2$ language learning task, which requires a model to have a stack-like mechanism for recognition.