8,324 research outputs found
Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation
We address the unsupervised learning of several interconnected problems in
low-level vision: single view depth prediction, camera motion estimation,
optical flow, and segmentation of a video into the static scene and moving
regions. Our key insight is that these four fundamental vision problems are
coupled through geometric constraints. Consequently, learning to solve them
together simplifies the problem because the solutions can reinforce each other.
We go beyond previous work by exploiting geometry more explicitly and
segmenting the scene into static and moving regions. To that end, we introduce
Competitive Collaboration, a framework that facilitates the coordinated
training of multiple specialized neural networks to solve complex problems.
Competitive Collaboration works much like expectation-maximization, but with
neural networks that act as both competitors to explain pixels that correspond
to static or moving regions, and as collaborators through a moderator that
assigns pixels to be either static or independently moving. Our novel method
integrates all these problems in a common framework and simultaneously reasons
about the segmentation of the scene into moving objects and the static
background, the camera motion, depth of the static scene structure, and the
optical flow of moving objects. Our model is trained without any supervision
and achieves state-of-the-art performance among joint unsupervised methods on
all sub-problems.Comment: CVPR 201
Complex I dysfunction underlies the glycolytic switch in pulmonary hypertensive smooth muscle cells.
ATP is essential for cellular function and is usually produced through oxidative phosphorylation. However, mitochondrial dysfunction is now being recognized as an important contributing factor in the development cardiovascular diseases, such as pulmonary hypertension (PH). In PH there is a metabolic change from oxidative phosphorylation to mainly glycolysis for energy production. However, the mechanisms underlying this glycolytic switch are only poorly understood. In particular the role of the respiratory Complexes in the mitochondrial dysfunction associated with PH is unresolved and was the focus of our investigations. We report that smooth muscle cells isolated from the pulmonary vessels of rats with PH (PH-PASMC), induced by a single injection of monocrotaline, have attenuated mitochondrial function and enhanced glycolysis. Further, utilizing a novel live cell assay, we were able to demonstrate that the mitochondrial dysfunction in PH-PASMC correlates with deficiencies in the activities of Complexes I-III. Further, we observed that there was an increase in mitochondrial reactive oxygen species generation and mitochondrial membrane potential in the PASMC isolated from rats with PH. We further found that the defect in Complex I activity was due to a loss of Complex I assembly, although the assembly of Complexes II and III were both maintained. Thus, we conclude that loss of Complex I assembly may be involved in the switch of energy metabolism in smooth muscle cells to glycolysis and that maintaining Complex I activity may be a potential therapeutic target for the treatment of PH
TRACE: 5D Temporal Regression of Avatars with Dynamic Cameras in 3D Environments
Although the estimation of 3D human pose and shape (HPS) is rapidly
progressing, current methods still cannot reliably estimate moving humans in
global coordinates, which is critical for many applications. This is
particularly challenging when the camera is also moving, entangling human and
camera motion. To address these issues, we adopt a novel 5D representation
(space, time, and identity) that enables end-to-end reasoning about people in
scenes. Our method, called TRACE, introduces several novel architectural
components. Most importantly, it uses two new "maps" to reason about the 3D
trajectory of people over time in camera, and world, coordinates. An additional
memory unit enables persistent tracking of people even during long occlusions.
TRACE is the first one-stage method to jointly recover and track 3D humans in
global coordinates from dynamic cameras. By training it end-to-end, and using
full image information, TRACE achieves state-of-the-art performance on tracking
and HPS benchmarks. The code and dataset are released for research purposes.Comment: Project page: https://www.yusun.work/TRACE/TRACE.htm
How does conformational flexibility influence key structural features involved in activation of anaplastic lymphoma kinase?
Anaplastic Lymphoma Kinase (ALK) plays a major role in developing tumor processes and therefore has emerged as a validated therapeutic target. Applying atomistic molecular dynamics simulations on the wild type enzyme and the nine most frequently occurring and clinically important activation mutants we revealed important conformational effects on key interactions responsible for the activation of the enzyme
High-throughput testing in head and neck squamous cell carcinoma identifies agents with preferential activity in human papillomavirus-positive or negative cell lines.
Head and neck squamous cell carcinoma (HNSCC) is a common cancer diagnosis worldwide. Despite advances in treatment, HNSCC has very poor survival outcomes, emphasizing an ongoing need for development of improved therapeutic options. The distinct tumor characteristics of human papillomavirus (HPV)-positive vs. HPV-negative disease necessitate development of treatment strategies tailored to tumor HPV-status. High-throughput robotic screening of 1,433 biologically and pharmacologically relevant compounds at a single dose (4 μM) was carried out against 6 HPV-positive and 20 HPV-negative HNSCC cell lines for preliminary identification of therapeutically relevant compounds. Statistical analysis was further carried out to differentiate compounds with preferential activity against cell lines stratified by the HPV-status. These analyses yielded 57 compounds with higher activity in HPV-negative cell lines, and 34 with higher-activity in HPV-positive ones. Multi-point dose-response curves were generated for six of these compounds (Ryuvidine, MK-1775, SNS-032, Flavopiridol, AZD-7762 and ARP-101), confirming Ryuvidine to have preferential potency against HPV-negative cell lines, and MK-1775 to have preferential potency against HPV-positive cell lines. These data comprise a valuable resource for further investigation of compounds with therapeutic potential in the HNSCC
Optical performance and results from the alignment and testing of the cameras for the MOONS spectrograph.
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Text mining MEDLINE to support public health
Today’s society is data rich and information driven, with access to numerous data sources available that have the potential to provide new insights into areas such as disease prevention, personalised medicine and data driven policy decisions. This paper describes and demonstrates the use of text mining tools developed to support public health institutions to complement their data with other accessible open data sources, optimize analysis and gain insight when examining policy. In particular we focus on the exploration of MEDLINE, the biggest structured open dataset of biomedical knowledge. In MEDLINE we utilize its terminology for indexing and cataloguing biomedical information – MeSH – to maximize the efficacy of the dataset
OxyCAP UK: Oxyfuel Combustion - academic Programme for the UK
The OxyCAP-UK (Oxyfuel Combustion - Academic Programme for the UK) programme was a £2 M collaboration involving researchers from seven UK universities, supported by E.On and the Engineering and Physical Sciences Research Council. The programme, which ran from November 2009 to July 2014, has successfully completed a broad range of activities related to development of oxyfuel power plants. This paper provides an overview of key findings arising from the programme. It covers development of UK research pilot test facilities for oxyfuel applications; 2-D and 3-D flame imaging systems for monitoring, analysis and diagnostics; fuel characterisation of biomass and coal for oxyfuel combustion applications; ash transformation/deposition in oxyfuel combustion systems; materials and corrosion in oxyfuel combustion systems; and development of advanced simulation based on CFD modelling
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