Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics

Text-to-image generation models represent the next step of evolution in image synthesis, offering a natural way to achieve flexible yet fine-grained control over the result. One emerging area of research is the fast adaptation of large text-to-image models to smaller datasets or new visual concepts. However, many efficient methods of adaptation have a long training time, which limits their practical applications, slows down research experiments, and spends excessive GPU resources. In this work, we study the training dynamics of popular text-to-image personalization methods (such as Textual Inversion or DreamBooth), aiming to speed them up. We observe that most concepts are learned at early stages and do not improve in quality later, but standard model convergence metrics fail to indicate that. Instead, we propose a simple drop-in early stopping criterion that only requires computing the regular training objective on a fixed set of inputs for all training iterations. Our experiments on Stable Diffusion for a range of concepts and for three personalization methods demonstrate the competitive performance of our approach, making adaptation up to 8 times faster with no significant drops in quality.Comment: Code: https://github.com/yandex-research/DVAR. 19 pages, 14 figure

The OECD Model Tax Convention and its commentaries as a source of interpretation of double taxation treaties in Ukraine

Interpretation of double taxation treaties is of utmost importance for application of their norms according to the criteria of good faith in compliance with the provisions of the Vienna Convention on the Law of Treaties. At the same time, there is no consensus in understanding the role of the OECD MC and its Commentaries as means of interpretation of double taxation treaties. As it is demonstrated on the basis of the development of court practice in Ukraine, the present situation does not add certainty to implementation of double taxation treaties and might even have the negative effect on investment climate in a state of source of income. The article does also contain the ways of improvement of application of the OECD MC and its Commentaries during the implementation of double taxation treaties of Ukraine including (1) preparation of the letter on issue of application of the OECD MC and its Commentaries as a source of interpretation of double taxation treaties by the Supreme Court of Ukraine, (2) granting of the technical assistance to tax authorities of Ukraine in the area of application of double taxation treaties in accordance with the international standards such as the OECD MC and its Commentaries and (3) translation of the OECD MC and its Commentaries into Ukrainian language

Haplotype analysis of APOE intragenic SNPs

BACKGROUND: APOE epsilon4 allele is most common genetic risk factor for Alzheimer\u27s disease (AD) and cognitive decline. However, it remains poorly understood why only some carriers of APOE epsilon4 develop AD and how ethnic variabilities in APOE locus contribute to AD risk. Here, to address the role of APOE haplotypes, we reassessed the diversity of APOE locus in major ethnic groups and in Alzheimer\u27s Disease Neuroimaging Initiative (ADNI) dataset on patients with AD, and subjects with mild cognitive impairment (MCI), and control non-demented individuals. RESULTS: We performed APOE gene haplotype analysis for a short block of five SNPs across the gene using the ADNI whole genome sequencing dataset. The compilation of ADNI data with 1000 Genomes identified the APOE epsilon4 linked haplotypes, which appeared to be distant for the Asian, African and European populations. The common European epsilon4-bearing haplotype is associated with AD but not with MCI, and the Africans lack this haplotype. Haplotypic inference revealed alleles that may confer protection against AD. By assessing the DNA methylation profile of the APOE haplotypes, we found that the AD-associated haplotype features elevated APOE CpG content, implying that this locus can also be regulated by genetic-epigenetic interactions. CONCLUSIONS: We showed that SNP frequency profiles within APOE locus are highly skewed to population-specific haplotypes, suggesting that the ancestral background within different sites at APOE gene may shape the disease phenotype. We propose that our results can be utilized for more specific risk assessment based on population descent of the individuals and on higher specificity of five site haplotypes associated with AD

Globally invariant metabolism but density-diversity mismatch in springtails.

Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning

Global fine-resolution data on springtail abundance and community structure

Springtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data.</p

Global fine-resolution data on springtail abundance and community structure

CODE AVAILABILITY : Programming R code is openly available together with the database from Figshare.SUPPLEMENTARY MATERIAL 1 : Template for data collectionSUPPLEMENTARY MATERIAL 2 : Data Descriptor WorksheetSpringtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data.Open Access funding enabled and organized by Projekt DEAL.http://www.nature.com/sdatahj2024Plant Production and Soil ScienceSDG-15:Life on lan

Hidden state refinement for optical flow forecasting

In recent years the topic of optical flow has become well-spread due to computation power support and optical flow estimation applications used on mobile phones and edge devices: video editors, frame stabilizations, and autonomous driving feature providers. This work analyzes multiple approaches to optical flow estimation and finds the main problems of the optical flow methods: slow convergence and long execution of the prediction algorithm. We propose to solve the slow convergence and long execution time with hidden state refinement to provide the initialization for optical flow estimation based on several previous frames and their hidden state transformations, which imitates the pixel movement at the hidden state level. The proposed method uses CNN, LSTM, and Transformer blocks which help to achieve the optical flow estimation and hidden state refinement to speed up the system. We used Sintel, KITTY-15, FlyingChairs, FlyingThings, HD1K, DAVIS, and YouTubeVOS datasets for our experiment