435 research outputs found
The seventh zinc finger motif of A20 is required for the suppression of TNF-α-induced apoptosis
AbstractThe ubiquitin-editing enzyme A20 suppresses nuclear factor-κB (NF-κB) activation and tumor necrosis factor-α (TNF-α)-induced apoptosis in a deubiquitinating and ubiquitin ligase activity-dependent manner. Although recent studies revealed that A20 regulates NF-κB independently of its enzymatic activity through its seventh zinc finger motif (ZnF7), the involvement of ZnF7 in TNF-α-induced apoptosis is not clear. In this study, ZnF7 was found to be important for A20-mediated suppression of TNF-α-induced apoptosis. We also found that the ubiquitin ligases cIAP1/2 are required for A20 to suppress TNF-α-induced apoptosis. Because A20 binds to cIAP1/2 through ZnF7, these results suggest that A20 may control cIAP1/2 when suppressing TNF-α-induced apoptosis
Audio-frequency magnetotelluric imaging of the Hijima fault, Yamasaki fault system, southwest Japan
Granules for Association Rules and Decision Support in the getRNIA System
This paper proposes granules for association rules in Deterministic Information Systems (DISs) and Non-deterministic Information Systems (NISs). Granules for an association rule are defined for every implication, and give us a new methodology for knowledge discovery and decision support. We see that decision support based on a table under the condition P is to fix the decision Q by using the most proper association rule P〵Rightarrow Q. We recently implemented a system getRNIA powered by granules for association rules. This paper describes how the getRNIA system deals with decision support under uncertainty, and shows some results of the experiment
Análise de despesa com pessoal e encargos sociais da companhia Petrobrás
Monografia (graduação)—Universidade de BrasÃlia, Faculdade de Economia, Administração, Contabilidade e Gestão de PolÃticas Públicas, Departamento de Ciências Contábeis e Aturais, 2016.A situação econômica atual, a qual o Brasil está passando, é justificativa para dar inicio a
estudos que analisem os impactos nos resultados de empresas. A companhia Petrobras é uma
sociedade de economia mista atuante no ramo de transformação e comercialização de
petróleo, gás e energia. Esta companhia será utilizada em nosso estudo de caso por ser uma
importante empresa para a economia brasileira. O objetivo deste trabalho é descrever dados
contábeis, por meio de uma pesquisa básica, referentes a encargos sociais, folha de pagamento
e demissões com finalidade de observar estruturas e o impacto que geram no lucro antes da
incidência de impostos com a utilização da ferramenta de análise vertical. A justificativa foi a
de levantar assuntos presentes relacionados à crise econômica, sendo relevante o
detalhamento da composição de itens para analisar o impacto gerado no lucro/produtividade.
Foram utilizados dados atinentes aos perÃodos compreendidos entre 2011 e 2015. Os
resultados descreveram efeitos significativos dos encargos sociais no LAIR e no EBITDA,
mesmo em perÃodo de menor valor de folha de pagamento e de gastos relacionados à s
despesas com pessoal. Sendo que o número de funcionários não apresentou relação direta com
os valores de despesa com pessoal e encargos sociais.The current economic situation, which Brazil is going through, is justification for starting
studies that analyze the impacts on companies' results. Petrobras is a mixed-capital company
active in the petroleum, gas and energy transformation and commercialization sector. This
company will be used in our case study as an important company for the Brazilian economy.
The objective of this paper is to describe accounting data, through a basic research, related
to social charges, payroll and dismissals in order to observe structures and the impact they
generate in the profit before tax incidence with the use of the analysis tool vertical. The
justification was to raise present issues related to the economic crisis, being relevant the
detailing of the composition of items to analyze the impact generated in the profit /
productivity. Data were used for the periods between 2011 and 2015. The results described
significant effects of social charges on the LAIR and EBITDA, even in the period of lower
payroll and expenses related to personnel expenses. As the number of employees did not
present a direct relationship with the amounts of personnel expenses and social charges
Zyxin is a novel interacting partner for SIRT1
<p>Abstract</p> <p>Background</p> <p>SIRT1 is a mammalian homologue of NAD+-dependent deacetylase sirtuin family. It regulates longevity in several model organisms and is involved with cell survival, differentiation, metabolism among other processes in mammalian cells. SIRT1 modulates functions of various key targets via deacetylation. Recent studies have revealed SIRT1 protects neurons from axonal degeneration or neurodegeneration. Further, SIRT1 null mice exhibit growth retardation and developmental defects, suggesting its critical roles in neurons and development.</p> <p>Results</p> <p>To identify novel binding partners for SIRT1 in the central nervous system, we performed yeast two-hybrid screening on human fetal brain cDNA library and found that zyxin is a possible binding partner. SIRT1 and zyxin transcript were both preferentially expressed in developmental mouse brain. Zyxin accumulates in the nucleus where it is co-localized with SIRT1 after treatment with leptomycin B in COS-7 cells. Furthermore, SIRT1 deacetylates zyxin, suggesting SIRT1 could interact with nuclear-accumulated zyxin and modulate its function through deacetylation.</p> <p>Conclusion</p> <p>Zyxin could be a novel interacting partner of SIRT1. Zyxin is an adaptor protein at focal adhesion plaque, regulating cytoskeletal dynamics and signal transduction to convey signal from the ECM (extracellular matrix) to the nucleus. Our results raise the possibility that SIRT1 regulates signal transmission from ECM to the nucleus by modulating the functions of zyxin via deacetylation.</p
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
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
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
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