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Optimizing HTR and Reading Order Strategies for Chinese Imperial Editions with Few-Shot Learning
No full textInternational audienceIn this study, we tackle key challenges in layout analysis, reading order, and text recognition of historical Chinese texts. As part of the CHI-KNOW-PO Corpus project, which aims to digitize and publish an online edition of 60,000 xylographed documents, we have developed and released a specialized small dataset to address this common issues in HTR of historical documents in Chinese. Our approach combines a CNN-based instance segmentation model with a local algorithmic model for reading order, achieving a mean precision of 95.0% and a recall of 93.0% in region detection, and a 97.81% accuracy in reading order. Text recognition is conducted using a CRNN model enhanced with GAN-augmented data, effectively addressing few-shot learning challenges with an average accuracy of 98.45%, demonstrating the effectiveness of a small and targeted dataset over a large-scale approach. This research not only advances the digitization and analytical processing of Chinese historical documents but also sets a new benchmark for subsequent digital humanities efforts
Deep estimation of the intensity and timing of natural selection from ancient genomes
No full textInternational audienceLeveraging past allele frequencies has proven to be key for identifying the impact of natural selection across time. However, this approach suffers from imprecise estimations of the intensity ( s ) and timing ( T ) of selection, particularly when ancient samples are scarce in specific epochs. Here, we aimed to bypass the computation of allele frequencies across arbitrarily defined past epochs and refine the estimations of selection parameters by implementing convolutional neural networks (CNNs) algorithms that directly use ancient genotypes sampled across time. Using computer simulations, we first show that genotype‐based CNNs consistently outperform an approximate Bayesian computation (ABC) approach based on past allele frequency trajectories, regardless of the selection model assumed and the number of available ancient genotypes. When applying this method to empirical data from modern and ancient Europeans, we replicated the reported increased number of selection events in post‐Neolithic Europe, independently of the continental subregion studied. Furthermore, we substantially refined the ABC‐based estimations of s and T for a set of positively and negatively selected variants, including iconic cases of positive selection and experimentally validated disease‐risk variants. Our CNN predictions support a history of recent positive and negative selection targeting variants associated with host defence against pathogens, aligning with previous work that highlights the significant impact of infectious diseases, such as tuberculosis, in Europe. These findings collectively demonstrate that detecting the footprints of natural selection on ancient genomes is crucial for unravelling the history of severe human diseases
Le Dieu guerrier des psaumes d’Asaf
No full textInternational audienceThis paper examines representations of God as warrior in the Psalms of Asaf, paying particular attention to the fact that these texts share similar ways of depicting divinity with surrounding cultures. It highlights a variety of representations, images and metaphors that are not reducible to one another.cet article examine les représentations guerrières de Dieu dans les psaumes d’Asaf, en portant l’attention à la pluralité des arrière-plans culturels environnant qui ont produit des figurations similaires de leurs divinités
Un drame politique au XVIIe siècle. Li Yu 李玉, <i>Qingzhong pu</i> 清忠譜 (Le chant des purs et des loyaux) : Traduction de la scène 6, « Ma xiang » 罵像 : « Insultes à la statue »
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L’oasis de Dadan, de l’âge du Bronze à l’époque islamique ancienne (2500 av. – 1100 apr. J.-C.) : la perspective urbaine
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La dialectologie aux colonies : l’école d’Alger et l’étude des parlers du Maghreb (1880-1910)
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La Consécration Elaborée de l'Aiguière, appelée Luminaire Clarifiant le Principe de la Sublimation (sMin byed don gsal sgron me zhes bya ba spros bcas bum pa’i dbang)
No full textTargeting a lineage-specific PI3Kɣ–Akt signaling module in acute myeloid leukemia using a heterobifunctional degrader molecule
No full textInternational audienceDose-limiting toxicity poses a major limitation to the clinical utility of targeted cancer therapies, often arising from target engagement in nonmalignant tissues. This obstacle can be minimized by targeting cancer dependencies driven by proteins with tissue-restricted and/or tumor-restricted expression. In line with another recent report, we show here that, in acute myeloid leukemia (AML), suppression of the myeloid-restricted PIK3CG/p110γ–PIK3R5/p101 axis inhibits protein kinase B/Akt signaling and compromises AML cell fitness. Furthermore, silencing the genes encoding PIK3CG/p110γ or PIK3R5/p101 sensitizes AML cells to established AML therapies. Importantly, we find that existing small-molecule inhibitors against PIK3CG are insufficient to achieve a sustained long-term antileukemic effect. To address this concern, we developed a proteolysis-targeting chimera (PROTAC) heterobifunctional molecule that specifically degrades PIK3CG and potently suppresses AML progression alone and in combination with venetoclax in human AML cell lines, primary samples from patients with AML and syngeneic mouse models