28 research outputs found
LayoutDM: Discrete Diffusion Model for Controllable Layout Generation
Controllable layout generation aims at synthesizing plausible arrangement of
element bounding boxes with optional constraints, such as type or position of a
specific element. In this work, we try to solve a broad range of layout
generation tasks in a single model that is based on discrete state-space
diffusion models. Our model, named LayoutDM, naturally handles the structured
layout data in the discrete representation and learns to progressively infer a
noiseless layout from the initial input, where we model the layout corruption
process by modality-wise discrete diffusion. For conditional generation, we
propose to inject layout constraints in the form of masking or logit adjustment
during inference. We show in the experiments that our LayoutDM successfully
generates high-quality layouts and outperforms both task-specific and
task-agnostic baselines on several layout tasks.Comment: To be published in CVPR2023, project page:
https://cyberagentailab.github.io/layout-dm
Towards Flexible Multi-modal Document Models
Creative workflows for generating graphical documents involve complex
inter-related tasks, such as aligning elements, choosing appropriate fonts, or
employing aesthetically harmonious colors. In this work, we attempt at building
a holistic model that can jointly solve many different design tasks. Our model,
which we denote by FlexDM, treats vector graphic documents as a set of
multi-modal elements, and learns to predict masked fields such as element type,
position, styling attributes, image, or text, using a unified architecture.
Through the use of explicit multi-task learning and in-domain pre-training, our
model can better capture the multi-modal relationships among the different
document fields. Experimental results corroborate that our single FlexDM is
able to successfully solve a multitude of different design tasks, while
achieving performance that is competitive with task-specific and costly
baselines.Comment: To be published in CVPR2023 (highlight), project page:
https://cyberagentailab.github.io/flex-d
Generative Colorization of Structured Mobile Web Pages
Color is a critical design factor for web pages, affecting important factors
such as viewer emotions and the overall trust and satisfaction of a website.
Effective coloring requires design knowledge and expertise, but if this process
could be automated through data-driven modeling, efficient exploration and
alternative workflows would be possible. However, this direction remains
underexplored due to the lack of a formalization of the web page colorization
problem, datasets, and evaluation protocols. In this work, we propose a new
dataset consisting of e-commerce mobile web pages in a tractable format, which
are created by simplifying the pages and extracting canonical color styles with
a common web browser. The web page colorization problem is then formalized as a
task of estimating plausible color styles for a given web page content with a
given hierarchical structure of the elements. We present several
Transformer-based methods that are adapted to this task by prepending
structural message passing to capture hierarchical relationships between
elements. Experimental results, including a quantitative evaluation designed
for this task, demonstrate the advantages of our methods over statistical and
image colorization methods. The code is available at
https://github.com/CyberAgentAILab/webcolor.Comment: Accepted to WACV 202
Indigo-Mediated Semi-Microbial Biofuel Cell Using an Indigo-Dye Fermenting Suspension
Aizome (Japanese indigo dyeing) is a unique dyeing method using microbial activity under anaerobic alkaline conditions. In indigo-dye fermenting suspensions; microorganisms reduce indigo into leuco-indigo with acetaldehyde as a reductant. In this study; we constructed a semi-microbial biofuel cell using an indigo-dye fermenting suspension. Carbon fiber and Pt mesh were used as the anode and cathode materials, respectively. The open-circuit voltage (OCV) was 0.6 V, and the maximum output power was 32 µW cm−2 (320 mW m−2). In addition, the continuous stability was evaluated under given conditions starting with the highest power density; the power density rapidly decreased in 0.5 h due to the degradation of the anode. Conversely, at the OCV, the anode potential exhibited high stability for two days. However, the OCV decreased by approximately 80 mV after 2 d compared with the initial value, which was attributed to the performance degradation of the gas-diffusion-cathode system caused by the evaporation of the dispersion solution. This is the first study to construct a semi-microbial biofuel cell using an indigo-dye fermenting suspension
Mechanistic Insights into Indigo Reduction in Indigo Fermentation : A Voltammetric Study
Indigo is one of the oldest natural blue dyes. Microorganisms and their enzymatic activities are deeply involved in the traditional indigo staining procedure. To elucidate the mechanism of the microbial indigo reduction, we directly performed cyclic voltammetry on alkaline fermenting dye suspensions. A pair of characteristic redox peaks of leuco-indigo was observed in a supernatant fluid of the fermenting dye suspension. On the other hand, it was found that the indigo/leuco-indigo redox couple mediated two-way microbially catalyzed oxidation and reduction in a sediment-rich suspension of the fermenting suspension. Acetaldehyde was supposed to be the electron donor and acceptor of the catalytic reactions. In order to verify the bioelectrocatalytic reaction, we isolated indigo-reducing bacterium K2-3′ from the fermenting suspension, and the two-way bioelectrocatalysis was successfully restaged in a model system containing K2-3′ and methyl viologen (as a soluble mediator instead of indigo) as well as acetaldehyde at pH 10
Pre-stroke physical activity is associated with post-stroke physical activity and sedentary behavior in the acute phase
This study investigated the link between pre-stroke and acute-stage physical activity (PA) and sedentary behavior. Forty individuals with stroke (aged 73.6 ± 8.9 years) were enrolled. Post-stroke activity, including metabolic equivalents (METs), sedentary behavior, light PA, and moderate-to-vigorous PA (MVPA), was measured using a tri-axial accelerometer (ActiGraph wGT3X-BT) over 11 consecutive days starting from the 4th day post-stroke. Pre-stroke PA levels were assessed using the International Physical Activity Questionnaire (IPAQ). We measured skeletal muscle mass index (SMI) and phase angle using a bioelectrical impedance analyzer (Inbody S10) upon admission. Physical therapists assessed the Brunnstrom recovery stage (BRS) within 3 days post-stroke. Total daily activity averaged 1.05 ± 0.05 METs. Throughout the day, 91.2 ± 5.1, 7.6 ± 4.1, and 1.2 ± 1.3% was spent in sedentary behavior, light PA, and MVPA, respectively. Only pre-stroke PA was independently associated with METs (β = 0.66), sedentary behavior (β = -0.58), light PA (β = 0.50), and MVPA (β = 0.71) after adjusting for age, sex, stroke severity, and activities of daily living. This suggests that pre-stroke PA might play a crucial role in reducing sedentary behavior and promoting PA during the acute phase
Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana
We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is ~32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene
Gene Organization in Rice Revealed by Full-Length cDNA Mapping and Gene Expression Analysis through Microarray
Rice (Oryza sativa L.) is a model organism for the functional genomics of monocotyledonous plants since the genome size is considerably smaller than those of other monocotyledonous plants. Although highly accurate genome sequences of indica and japonica rice are available, additional resources such as full-length complementary DNA (FL-cDNA) sequences are also indispensable for comprehensive analyses of gene structure and function. We cross-referenced 28.5K individual loci in the rice genome defined by mapping of 578K FL-cDNA clones with the 56K loci predicted in the TIGR genome assembly. Based on the annotation status and the presence of corresponding cDNA clones, genes were classified into 23K annotated expressed (AE) genes, 33K annotated non-expressed (ANE) genes, and 5.5K non-annotated expressed (NAE) genes. We developed a 60mer oligo-array for analysis of gene expression from each locus. Analysis of gene structures and expression levels revealed that the general features of gene structure and expression of NAE and ANE genes were considerably different from those of AE genes. The results also suggested that the cloning efficiency of rice FL-cDNA is associated with the transcription activity of the corresponding genetic locus, although other factors may also have an effect. Comparison of the coverage of FL-cDNA among gene families suggested that FL-cDNA from genes encoding rice- or eukaryote-specific domains, and those involved in regulatory functions were difficult to produce in bacterial cells. Collectively, these results indicate that rice genes can be divided into distinct groups based on transcription activity and gene structure, and that the coverage bias of FL-cDNA clones exists due to the incompatibility of certain eukaryotic genes in bacteria
The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force
「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection
DOCK2 is involved in the host genetics and biology of severe COVID-19
「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target