Digesting omni-video along routes for navigation

poster abstractOmni-directional video records complete visual information along a route. Though replaying an omni-video presents reality, it requires significant amount of memory and communication bandwidth. This work extracts distinct views from an omni-video to form a visual digest named route sheet for navigation. We sort scenes at the motion and visibility level and investigate the similarity/redundancy of scenes in the context of a route. We use source data from 3D elevation map or omni-videos for the view selection. By condensing the flow in the video, our algorithm can generate distinct omni-view sequences with visual information as rich as the omni-video for further scene indexing and navigation with GIS data

Imidazole-thiazolidinone inhibits oesophageal cancer cell proliferation via induction of apoptosis and cell cycle arrest at S phase

Purpose: To investigate the effect of imidazole-thiazolidinone on oesophageal cancer (OC) cell proliferation, and the mechanism of action involved.Methods: Human OC cells (HCE-6 and KYSE-1170) were cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10 % fetal bovine serum (FBS) and 1 % penicillin/streptomycin solution at 37 ˚C for 24 h in a humidified atmosphere of 5 % CO2 and 95 % air. After attaining 60 -  70 % confluency, the cells were treated with serum-free medium and graded concentrations of imidazolethiazolidinone (up to 160 μM) for 24 h. Normal cell culture without imidazole-thiazolidinone served as control. Cells in logarithmic growth phase were selected and used in this study. Cell proliferation and apoptosis were assessed using 3 (4,5 dimethyl thiazol 2 yl) 2,5 diphenyl 2H tetrazolium bromide (MTT), and flow cytometric assays, respectively. The levels of expression of apoptosis-related proteins were determined using Western blotting.Results: Treatment of HCE-6 and KYSE-1170 cells with imidazole-thiazolidinone for 48 h led to significant and dose-dependent reduction in their  proliferation, as well as significant and dosedependent increase in the number of apoptotic cells (p < 0.05). Light microscopy revealed significantreduction in HCE-6 cell count, detached cells, reduced cell size and irregular cytoplasmic vacuoles. Imidazole-thiazolidinone treatment significantly and dose-dependently decreased HCE-6 and KYSE-1170 cell migration, and arrested HCE-6 cell cycle at S phase (p < 0.05). In HCE-6 cells, imidazolethiazolidinone treatment significantly and dose-dependently upregulated the expressions of cleaved caspase-3/8/9 and bax, but down-regulated bcl-2 expression significantly and dose-dependently (p < 0.05). However, metalloproteinases 2 and 9 (MMP-2 and MMP-9) expressions in HCE-6 and KYSE-1170 cells were significantly and dose-dependently down-regulated by imidazole-thiazolidinone treatment (p < 0.05).Conclusion: The results obtained in this study suggest that imidazole-thiazolidinone suppresses OC cell proliferation via induction of apoptosis and arrest of cell cycle at S phase. Keywords: Imidazole-thiazolidinone, Oesophageal cancer, Metastasis, Cell cycle arrest, Apoptosi

Design Arguments – an examination of how designers argue for their designs

To communicate a design can be seen as consisting of at least two aspects: presentation and argumentation. In our research we have taken on the task of studying how practicing interaction designers approach the challenge of presenting and arguing for their designs. We have chosen to label our object of study, or unit of analysis, a design argument. Based on three studies, we have developed a descriptive framework that can be used to describe, analyze, and compare design arguments. The paper ends with some discussions and reflections concerning the potential relevance, use, and implications of a framework of design arguments

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process

Transformer Hawkes process models have shown to be successful in modeling event sequence data. However, most of the existing training methods rely on maximizing the likelihood of event sequences, which involves calculating some intractable integral. Moreover, the existing methods fail to provide uncertainty quantification for model predictions, e.g., confidence intervals for the predicted event's arrival time. To address these issues, we propose SMURF-THP, a score-based method for learning Transformer Hawkes process and quantifying prediction uncertainty. Specifically, SMURF-THP learns the score function of events' arrival time based on a score-matching objective that avoids the intractable computation. With such a learned score function, we can sample arrival time of events from the predictive distribution. This naturally allows for the quantification of uncertainty by computing confidence intervals over the generated samples. We conduct extensive experiments in both event type prediction and uncertainty quantification of arrival time. In all the experiments, SMURF-THP outperforms existing likelihood-based methods in confidence calibration while exhibiting comparable prediction accuracy