ContextVP: Fully Context-Aware Video Prediction

Video prediction models based on convolutional networks, recurrent networks, and their combinations often result in blurry predictions. We identify an important contributing factor for imprecise predictions that has not been studied adequately in the literature: blind spots, i.e., lack of access to all relevant past information for accurately predicting the future. To address this issue, we introduce a fully context-aware architecture that captures the entire available past context for each pixel using Parallel Multi-Dimensional LSTM units and aggregates it using blending units. Our model outperforms a strong baseline network of 20 recurrent convolutional layers and yields state-of-the-art performance for next step prediction on three challenging real-world video datasets: Human 3.6M, Caltech Pedestrian, and UCF-101. Moreover, it does so with fewer parameters than several recently proposed models, and does not rely on deep convolutional networks, multi-scale architectures, separation of background and foreground modeling, motion flow learning, or adversarial training. These results highlight that full awareness of past context is of crucial importance for video prediction.Comment: 19 pages. ECCV 2018 oral presentation. Project webpage is at https://wonmin-byeon.github.io/publication/2018-ecc

The Politics of Social Filtering

Social filtering – the selective engagement with people, communication and other information as a result of the recommendations of others – has always taken place. However, the possibilities of the Internet combined with the growth of online social networking activities have enabled this process to become rapidly more extensive, easier and potentially problematic. This paper focuses on the analysis of the politics of social filtering through social network sites. It argues that what is needed is both a closer examination and evaluation of these processes and also the development of a framework through which to begin such an evaluation. There is also a second intent: to (re)assert the argument that any analysis necessarily needs to take into account and critique the development, implementation and use of technologies (this includes the software, algorithms and code)themselves as well as the people that build and use them

Reinforced Axial Refinement Network for Monocular 3D Object Detection

Monocular 3D object detection aims to extract the 3D position and properties of objects from a 2D input image. This is an ill-posed problem with a major difficulty lying in the information loss by depth-agnostic cameras. Conventional approaches sample 3D bounding boxes from the space and infer the relationship between the target object and each of them, however, the probability of effective samples is relatively small in the 3D space. To improve the efficiency of sampling, we propose to start with an initial prediction and refine it gradually towards the ground truth, with only one 3d parameter changed in each step. This requires designing a policy which gets a reward after several steps, and thus we adopt reinforcement learning to optimize it. The proposed framework, Reinforced Axial Refinement Network (RAR-Net), serves as a post-processing stage which can be freely integrated into existing monocular 3D detection methods, and improve the performance on the KITTI dataset with small extra computational costs.Comment: Accepted by ECCV 202

Longitudinal impact of process-oriented guided inquiry learning on the attitudes, self-efficacy and experiences of pre-medical chemistry students

A follow-up study was conducted with foundation-year chemistry students who were taught in an inquiry- and role-based, small-group active learning environment in order to evaluate their attitudes, experiences and self-efficacy during pre-medical chemistry courses. The study adopted a mixedmethods research design that involved both experimental and comparison groups. Using the CAEQ (Chemistry Attitudes and Experiences Questionnaire) and the ASCI v2 (Attitude toward the Study of Chemistry Inventory), the findings of this study indicated that inquiry-based chemistry learning experience improves the students’ intellectual accessibility and emotional satisfaction as well as develops their self-efficacy levels while pursuing intensive pre-medical courses in chemistry. The results of the qualitative data analyses using a course experience questionnaire indicated that the process-oriented guided inquiry learning (POGIL) experience helped the students succeed in rigorous pre-medical chemistry courses and gained some process skills required in the medical programme as listed by the AAMC (American Association of Medical Colleges)

Two-Minute k-Space and Time–accelerated Aortic Four-dimensional Flow MRI: Dual-Center Study of Feasibility and Impact on Velocity and Wall Shear Stress Quantification

PURPOSE: To investigate the two-center feasibility of highly k-space and time (k-t)–accelerated 2-minute aortic four-dimensional (4D) flow MRI and to evaluate its performance for the quantification of velocities and wall shear stress (WSS). MATERIALS AND METHODS: This cross-sectional study prospectively included 68 participants (center 1, 11 healthy volunteers [mean age ± standard deviation, 61 years ± 15] and 16 patients with aortic disease [mean age, 60 years ± 10]; center 2, 14 healthy volunteers [mean age, 38 years ± 13] and 27 patients with aortic or cardiac disease [mean age, 78 years ± 18]). Each participant underwent highly accelerated 4D flow MRI (k-t acceleration, acceleration factor of 5) of the thoracic aorta. For comparison, conventional 4D flow MRI (acceleration factor of 2) was acquired in the participants at center 1 (n = 27). Regional aortic peak systolic velocities and three-dimensional WSS were quantified. RESULTS: k-t–accelerated scan times (center 1, 2:03 minutes ± 0:29; center 2, 2:06 minutes ± 0:20) were significantly reduced compared with conventional 4D flow MRI (center 1, 12:38 minutes ± 2:25; P < .0001). Overall good agreement was found between the two techniques (absolute differences ≤15%), but proximal aortic WSS was significantly underestimated in patients by using k-t–accelerated 4D flow when compared with conventional 4D flow (P ≤ .03). k-t–accelerated 4D flow MRI was reproducible (intra- and interobserver intraclass correlation coefficient ≥0.98) and identified significantly increased peak velocities and WSS in patients with stenotic (P ≤ .003) or bicuspid (P ≤ .04) aortic valves compared with healthy volunteers. In addition, k-t–accelerated 4D flow MRI–derived velocities and WSS were inversely related to age (r ≥−0.53; P ≤ .03) over all healthy volunteers. CONCLUSION: k-t–accelerated aortic 4D flow MRI providing 2-minute scan times was feasible and reproducible at two centers. Although consistent healthy aging- and disease-related changes in aortic hemodynamics were observed, care should be taken when considering WSS, which can be underestimated in patients

Habitat structure: a fundamental concept and framework for urban soil ecology

Habitat structure is defined as the composition and arrangement of physical matter at a location. Although habitat structure is the physical template underlying ecological patterns and processes, the concept is relatively unappreciated and underdeveloped in ecology. However, it provides a fundamental concept for urban ecology because human activities in urban ecosystems are often targeted toward management of habitat structure. In addition, the concept emphasizes the fine-scale, on-the-ground perspective needed in the study of urban soil ecology. To illustrate this, urban soil ecology research is summarized from the perspective of habitat structure effects. Among the key conclusions emerging from the literature review are: (1) habitat structure provides a unifying theme for multivariate research about urban soil ecology; (2) heterogeneous urban habitat structures influence soil ecological variables in different ways; (3) more research is needed to understand relationships among sociological variables, habitat structure patterns and urban soil ecology. To stimulate urban soil ecology research, a conceptual framework is presented to show the direct and indirect relationships among habitat structure and ecological variables. Because habitat structure serves as a physical link between sociocultural and ecological systems, it can be used as a focus for interdisciplinary and applied research (e.g., pest management) about the multiple, interactive effects of urbanization on the ecology of soils

A pivotal role for starch in the reconfiguration of 14C-partitioning and allocation in Arabidopsis thaliana under short-term abiotic stress.

Plant carbon status is optimized for normal growth but is affected by abiotic stress. Here, we used 14C-labeling to provide the first holistic picture of carbon use changes during short-term osmotic, salinity, and cold stress in Arabidopsis thaliana. This could inform on the early mechanisms plants use to survive adverse environment, which is important for efficient agricultural production. We found that carbon allocation from source to sinks, and partitioning into major metabolite pools in the source leaf, sink leaves and roots showed both conserved and divergent responses to the stresses examined. Carbohydrates changed under all abiotic stresses applied; plants re-partitioned 14C to maintain sugar levels under stress, primarily by reducing 14C into the storage compounds in the source leaf, and decreasing 14C into the pools used for growth processes in the roots. Salinity and cold increased 14C-flux into protein, but as the stress progressed, protein degradation increased to produce amino acids, presumably for osmoprotection. Our work also emphasized that stress regulated the carbon channeled into starch, and its metabolic turnover. These stress-induced changes in starch metabolism and sugar export in the source were partly accompanied by transcriptional alteration in the T6P/SnRK1 regulatory pathway that are normally activated by carbon starvation

A Comprehensive Model of Audiovisual Perception: Both Percept and Temporal Dynamics

The sparse information captured by the sensory systems is used by the brain to apprehend the environment, for example, to spatially locate the source of audiovisual stimuli. This is an ill-posed inverse problem whose inherent uncertainty can be solved by jointly processing the information, as well as introducing constraints during this process, on the way this multisensory information is handled. This process and its result - the percept - depend on the contextual conditions perception takes place in. To date, perception has been investigated and modeled on the basis of either one of two of its dimensions: the percept or the temporal dynamics of the process. Here, we extend our previously proposed audiovisual perception model to predict both these dimensions to capture the phenomenon as a whole. Starting from a behavioral analysis, we use a data-driven approach to elicit a Bayesian network which infers the different percepts and dynamics of the process. Context-specific independence analyses enable us to use the model's structure to directly explore how different contexts affect the way subjects handle the same available information. Hence, we establish that, while the percepts yielded by a unisensory stimulus or by the non-fusion of multisensory stimuli may be similar, they result from different processes, as shown by their differing temporal dynamics. Moreover, our model predicts the impact of bottom-up (stimulus driven) factors as well as of top-down factors (induced by instruction manipulation) on both the perception process and the percept itself

Induction of CD4+CD25+FOXP3+ Regulatory T Cells during Human Hookworm Infection Modulates Antigen-Mediated Lymphocyte Proliferation

Hookworm infection is considered one of the most important poverty-promoting neglected tropical diseases, infecting 576 to 740 million people worldwide, especially in the tropics and subtropics. These blood-feeding nematodes have a remarkable ability to downmodulate the host immune response, protecting themselves from elimination and minimizing severe host pathology. While several mechanisms may be involved in the immunomodulation by parasitic infection, experimental evidences have pointed toward the possible involvement of regulatory T cells (Tregs) in downregulating effector T-cell responses upon chronic infection. However, the role of Tregs cells in human hookworm infection is still poorly understood and has not been addressed yet. In the current study we observed an augmentation of circulating CD4+CD25+FOXP3+ regulatory T cells in hookworm-infected individuals compared with healthy non-infected donors. We have also demonstrated that infected individuals present higher levels of circulating Treg cells expressing CTLA-4, GITR, IL-10, TGF-β and IL-17. Moreover, we showed that hookworm crude antigen stimulation reduces the number of CD4+CD25+FOXP3+ T regulatory cells co-expressing IL-17 in infected individuals. Finally, PBMCs from infected individuals pulsed with excreted/secreted products or hookworm crude antigens presented an impaired cellular proliferation, which was partially augmented by the depletion of Treg cells. Our results suggest that Treg cells may play an important role in hookworm-induced immunosuppression, contributing to the longevity of hookworm survival in infected people