184 research outputs found
ΠΠΎΠ½ΡΠ΅ΠΏΡΡΠ°Π»ΡΠ½ΡΠ΅ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΡΡ ΠΏΠΎΡΠΎΠΊΠΎΠ² ΠΊΠΎΠΌΠΌΠ΅ΡΡΠ΅ΡΠΊΠΈΡ Π±Π°Π½ΠΊΠΎΠ²
Π Π°Π·Π²ΠΈΡΠΈΠ΅ ΡΡΠ½ΠΎΡΠ½ΠΎΠ³ΠΎ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΠΈΡ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π° ΠΏΡΠΎΡΠΈΠ²ΠΎΡΠ΅ΡΠΈΠΉ, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠ²Π»ΡΡΡΡΡ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ Π΄Π»Ρ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΠΎΡΡΠΎΡΠ½ΠΈΡ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. ΠΡΠΎ ΠΏΡΠΎΠΈΡΡΠ΅ΠΊΠ°Π΅Ρ Π² Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΌΠ΅ΡΠ΅ ΠΈΠ·-Π·Π° ΡΠ±ΠΎΠ΅Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ Π² ΡΡΡΠ°Π½Π΅. ΠΠ΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ ΠΏΠΎΠΊΠ° Π΅ΡΠ΅ Π΄ΠΎ ΠΊΠΎΠ½ΡΠ° ΠΌΠ΅ΡΡ ΠΈ ΡΠΎΡΠΌΡ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ Π²ΠΌΠ΅ΡΠ°ΡΠ΅Π»ΡΡΡΠ²Π° Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΡ.Π ΠΎΠ·Π²ΠΈΡΠΎΠΊ ΡΠΈΠ½ΠΊΠΎΠ²ΠΎΠ³ΠΎ Π³ΠΎΡΠΏΠΎΠ΄Π°ΡΡΠ²Π°Π½Π½Ρ Π²ΡΠ΄Π±ΡΠ²Π°ΡΡΡΡΡ Π² ΡΠΌΠΎΠ²Π°Ρ
Π±Π΅Π·Π»ΡΡΡ ΡΡΠΏΠ΅ΡΠ΅ΡΠ½ΠΎΡΡΠ΅ΠΉ, ΡΠΊΡ Ρ ΡΠΏΠ΅ΡΠΈΡΡΡΠ½ΠΈΠΌΠΈ Π΄Π»Ρ ΡΡΡΠ°ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°Π½Ρ Π²ΡΡΡΠΈΠ·Π½ΡΠ½ΠΎΡ Π΅ΠΊΠΎΠ½ΠΎΠΌΡΠΊΠΈ. Π¦Π΅ Π²ΠΈΠ½ΠΈΠΊΠ°Ρ Π·Π½Π°ΡΠ½ΠΎΡ ΠΌΡΡΠΎΡ ΡΠ΅ΡΠ΅Π· Π·Π±ΠΎΡ Π΅ΠΊΠΎΠ½ΠΎΠΌΡΡΠ½ΠΎΡ ΠΏΠΎΠ»ΡΡΠΈΠΊΠΈ Π² ΠΊΡΠ°ΡΠ½Ρ. ΠΠ΅ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Ρ ΠΏΠΎΠΊΠΈ ΡΠΎ Π΄ΠΎ ΠΊΡΠ½ΡΡ ΠΌΡΡΠΈ Ρ ΡΠΎΡΠΌΠΈ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΎΠ³ΠΎ Π²ΡΡΡΡΠ°Π½Π½Ρ Π² Π΅ΠΊΠΎΠ½ΠΎΠΌΡΠΊΡ
Connectionist Temporal Modeling for Weakly Supervised Action Labeling
We propose a weakly-supervised framework for action labeling in video, where
only the order of occurring actions is required during training time. The key
challenge is that the per-frame alignments between the input (video) and label
(action) sequences are unknown during training. We address this by introducing
the Extended Connectionist Temporal Classification (ECTC) framework to
efficiently evaluate all possible alignments via dynamic programming and
explicitly enforce their consistency with frame-to-frame visual similarities.
This protects the model from distractions of visually inconsistent or
degenerated alignments without the need of temporal supervision. We further
extend our framework to the semi-supervised case when a few frames are sparsely
annotated in a video. With less than 1% of labeled frames per video, our method
is able to outperform existing semi-supervised approaches and achieve
comparable performance to that of fully supervised approaches.Comment: To appear in ECCV 201
Computational mechanics research and support for aerodynamics and hydraulics at TFHRC. Quarterly report January through March 2011. Year 1 Quarter 2 progress report.
This project was established with a new interagency agreement between the Department of Energy and the Department of Transportation to provide collaborative research, development, and benchmarking of advanced three-dimensional computational mechanics analysis methods to the aerodynamics and hydraulics laboratories at the Turner-Fairbank Highway Research Center for a period of five years, beginning in October 2010. The analysis methods employ well-benchmarked and supported commercial computational mechanics software. Computational mechanics encompasses the areas of Computational Fluid Dynamics (CFD), Computational Wind Engineering (CWE), Computational Structural Mechanics (CSM), and Computational Multiphysics Mechanics (CMM) applied in Fluid-Structure Interaction (FSI) problems. The major areas of focus of the project are wind and water loads on bridges - superstructure, deck, cables, and substructure (including soil), primarily during storms and flood events - and the risks that these loads pose to structural failure. For flood events at bridges, another major focus of the work is assessment of the risk to bridges caused by scour of stream and riverbed material away from the foundations of a bridge. Other areas of current research include modeling of flow through culverts to assess them for fish passage, modeling of the salt spray transport into bridge girders to address suitability of using weathering steel in bridges, vehicle stability under high wind loading, and the use of electromagnetic shock absorbers to improve vehicle stability under high wind conditions. This quarterly report documents technical progress on the project tasks for the period of January through March 2011
Satellite-based trends of solar radiation and cloud parameters in Europe
Solar radiation is the main driver of the Earth\u2019s climate. Measuring solar radiation and analysing its
interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application
Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records,
with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common
framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation,
top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe
and covers the time period from 1992 to 2015. A high correlation between these three variables has been found
over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and
a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends
in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records,
which are mostly derived independently from each other. The results of this study indicate that one of the main
reasons for the positive trend in surface solar radiation since the 1990\u2019s is a decrease in cloud coverage even if
an aerosol contribution cannot be completely ruled out
COVID-19 therapy target discovery with context-aware literature mining
The abundance of literature related to the widespread COVID-19 pandemic is
beyond manual inspection of a single expert. Development of systems, capable of
automatically processing tens of thousands of scientific publications with the
aim to enrich existing empirical evidence with literature-based associations is
challenging and relevant. We propose a system for contextualization of
empirical expression data by approximating relations between entities, for
which representations were learned from one of the largest COVID-19-related
literature corpora. In order to exploit a larger scientific context by transfer
learning, we propose a novel embedding generation technique that leverages
SciBERT language model pretrained on a large multi-domain corpus of scientific
publications and fine-tuned for domain adaptation on the CORD-19 dataset. The
conducted manual evaluation by the medical expert and the quantitative
evaluation based on therapy targets identified in the related work suggest that
the proposed method can be successfully employed for COVID-19 therapy target
discovery and that it outperforms the baseline FastText method by a large
margin.Comment: Accepted to the 23rd International Conference on Discovery Science
(DS 2020
Multi-channel Transformers for Multi-articulatory Sign Language Translation
Sign languages use multiple asynchronous information channels (articulators),
not just the hands but also the face and body, which computational approaches
often ignore. In this paper we tackle the multi-articulatory sign language
translation task and propose a novel multi-channel transformer architecture.
The proposed architecture allows both the inter and intra contextual
relationships between different sign articulators to be modelled within the
transformer network itself, while also maintaining channel specific
information. We evaluate our approach on the RWTH-PHOENIX-Weather-2014T dataset
and report competitive translation performance. Importantly, we overcome the
reliance on gloss annotations which underpin other state-of-the-art approaches,
thereby removing future need for expensive curated datasets
Zero-shot language transfer for cross-lingual sentence retrieval using bidirectional attention model
We present a neural architecture for cross-lingual mate sentence retrieval which encodes sentences in a joint multilingual space and learns to distinguish true translation pairs from semantically related sentences across languages. The proposed model combines a recurrent sequence encoder with a bidirectional attention layer and an intra-sentence attention mechanism. This way the final fixed-size sentence representations in each training sentence pair depend on the selection of contextualized token representations from the other sentence. The representations of both sentences are then combined using the bilinear product function to predict the relevance score. We show that, coupled with a shared
multilingual word embedding space, the proposed model strongly outperforms unsupervised cross-lingual ranking functions, and that further boosts can be achieved by combining the two approaches. Most importantly, we demonstrate the model's effectiveness in zero-shot language transfer settings: our multilingual framework boosts cross-lingual sentence retrieval performance for unseen language pairs without any training examples. This enables robust cross-lingual sentence retrieval
also for pairs of resource-lean languages, without any parallel data
A new method for the determination of low-level actinium-227 in geological samples
Author Posting. Β© The Author(s), 2012. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Radioanalytical and Nuclear Chemistry 296 (2013): 279-283, doi:10.1007/s10967-012-2140-0.We developed a new method for the determination of 227Ac in geological samples. The method uses extraction chromatographic techniques and alpha-spectrometry and is applicable for a range of natural matrices. Here we report on the procedure and results of the analysis of water (fresh and seawater) and rock samples. Water samples were acidified and rock samples underwent total dissolution via acid leaching. A DGA (N,N,Nβ,Nβ-tetra-n-octyldiglycolamide) extraction chromatographic column was used for the separation of actinium. The actinium fraction was prepared for alpha spectrometric measurement via cerium fluoride micro-precipitation. Recoveries of actinium in water samples were 80Β±8 % (number of analyses n=14) and in rock samples 70Β±12 % (n=30). The minimum detectable activities (MDA) were 0.017-0.5 Bq kg-1 for both matrices. Rock sample 227Ac activities ranged from 0.17 to 8.3 Bq kg-1 and water sample activities ranged from below MDA values to 14 Bq kg-1of 227Ac. From the analysis of several standard rock and water samples with the method we found very good agreement between our results and certified values
Evaluation of variants in the selectin genes in age-related macular degeneration
<p>Abstract</p> <p>Background</p> <p>Age-related macular degeneration (AMD) is a common disease of the elderly that leads to loss of the central visual field due to atrophic or neovascular events. Evidence from human eyes and animal models suggests an important role for macrophages and endothelial cell activation in the pathogenesis of AMD. We sought to determine whether common ancestral variants in genes encoding the selectin family of proteins are associated with AMD.</p> <p>Methods</p> <p>Expression of E-selectin, L-selectin and P-selectin was examined in choroid and retina by quantitative PCR and immunofluorescence. Samples from patients with AMD (n = 341) and controls (n = 400) were genotyped at a total of 34 SNPs in the <it>SELE</it>, <it>SELL </it>and <it>SELP </it>genes. Allele and genotype frequencies at these SNPs were compared between AMD patients and controls as well as between subtypes of AMD (dry, geographic atrophy, and wet) and controls.</p> <p>Results</p> <p>High expression of all three selectin genes was observed in the choroid as compared to the retina. Some selectin labeling of retinal microglia, drusen cores and the choroidal vasculature was observed. In the genetic screen of AMD versus controls, no positive associations were observed for <it>SELE </it>or <it>SELL</it>. One SNP in <it>SELP </it>(rs3917751) produced p-values < 0.05 (uncorrected for multiple measures). In the subtype analyses, 6 SNPs (one in <it>SELE</it>, two in <it>SELL</it>, and three in <it>SELP</it>) produced p-values < 0.05. However, when adjusted for multiple measures with a Bonferroni correction, only one SNP in <it>SELP </it>(rs3917751) produced a statistically significant p-value (p = 0.0029).</p> <p>Conclusions</p> <p>This genetic screen did not detect any SNPs that were highly associated with AMD affection status overall. However, subtype analysis showed that a single SNP located within an intron of <it>SELP </it>(rs3917751) is statistically associated with dry AMD in our cohort. Future studies with additional cohorts and functional assays will clarify the biological significance of this discovery. Based on our findings, it is unlikely that common ancestral variants in the other selectin genes (<it>SELE </it>and <it>SELL</it>) are risk factors for AMD. Finally, it remains possible that sporadic or rare mutations in <it>SELE</it>, <it>SELL</it>, or <it>SELP </it>have a role in the pathogenesis of AMD.</p
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