DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity

Nowadays, events usually burst and are propagated online through multiple modern media like social networks and search engines. There exists various research discussing the event dissemination trends on individual medium, while few studies focus on event popularity analysis from a cross-platform perspective. Challenges come from the vast diversity of events and media, limited access to aligned datasets across different media and a great deal of noise in the datasets. In this paper, we design DancingLines, an innovative scheme that captures and quantitatively analyzes event popularity between pairwise text media. It contains two models: TF-SW, a semantic-aware popularity quantification model, based on an integrated weight coefficient leveraging Word2Vec and TextRank; and wDTW-CD, a pairwise event popularity time series alignment model matching different event phases adapted from Dynamic Time Warping. We also propose three metrics to interpret event popularity trends between pairwise social platforms. Experimental results on eighteen real-world event datasets from an influential social network and a popular search engine validate the effectiveness and applicability of our scheme. DancingLines is demonstrated to possess broad application potentials for discovering the knowledge of various aspects related to events and different media

Tidal signals in ocean-bottom magnetic measurements of the Northwestern Pacific: observation versus prediction

Motional induction in the ocean by tides has long been observed by both land and satellite measurements of magnetic fields. While these signals are weak (∼10 nT) when compared to the main magnetic field, their persistent nature makes them important for consideration during geomagnetic field modelling. Previous studies have reported several discrepancies between observations and numerical predictions of the tidal magnetic signals and those studies were inconclusive of the source of the error. We address this issue by (1) analysing magnetometer data from ocean-bottom stations, where the low-noise and high-signal environment is most suitable for detecting the weak tidal magnetic signals, (2) by numerically predicting the magnetic field with a spatial resolution that is 16times higher than the previous studies and (3) by using four different models of upper-mantle conductivity. We use vector magnetic data from six ocean-bottom electromagnetic (OBEM) stations located in the Northwestern Pacific Ocean. The OBEM tidal amplitudes were derived using an iteratively re-weighted least-squares (IRLS) method and by limiting the analysis of lunar semidiurnal (M2), lunar elliptic semidinurnal (N2) and diurnal (O1) tidal modes to the night-time. Using a 3-D electromagnetic induction solver and the TPX07.2 tidal model, we predict the tidal magnetic signal. We use earth models with non-uniform oceans and four 1-D mantle sections underneath taken from Kuvshinov and Olsen, Shimizu etal. and Baba etal. to compare the effect of upper-mantle conductivity. We find that in general, the predictions and observations match within 10-70 per cent across all the stations for each of the tidal modes. The median normalized percent difference (NPD) between observed and predicted amplitudes for the tidal modes M2, N2 and O1 were 15 per cent, 47 per cent and 98 per cent, respectively, for all the stations and models. At the majority of stations, and for each of the tidal modes, the higher resolution (0.25°×0.25°) modelling gave amplitudes consistently closer to the observations than the lower resolution (1°×1°) modelling. The difference in lithospheric resistance east and west of the Izu-Bonin trench system seems to be affecting the model response and observations in the O1 tidal mode. This response is not seen in the M2 and N2 modes, thereby indicating that the O1 mode is more sensitive to lithospheric resistanc

Use of Physiotherapy Prior to Total Knee Arthroplasty-Results of the Prospective FInGK Study

Background: Data regarding physiotherapy (PT) utilization prior to total knee arthroplasty (TKA) are insufficient. Therefore, this study aims to examine which percentage of patients receive PT within 12 months prior to TKA and which factors are associated with its use. Methods: Consecutive patients (≥18 years) undergoing primary or revision TKA in a German university hospital were recruited. A questionnaire including information on PT utilization, demography, and socioeconomics was collected one day prior to surgery and linked to medical hospital records. Multivariable logistic regression was conducted to determine variables associated with the use of PT. Results: A total of 241 out of 283 (85%) patients participated (60% female; mean age: 68.4 years). Overall, 41% received PT at least once during 12 months prior to TKA, women more frequently than men (48% vs. 29%). Although high disease burden was associated with increased utilization, about one in two in this condition did not receive PT. Multivariable logistic regression showed that age 75+ years, low education level, and moderate-to-severe depressive symptoms were associated with decreased PT utilization. Conclusions: We found low use of recommended PT management in patients prior to TKA. This potential underuse was even higher in some vulnerable subgroups, indicating inequalities. Prescribers as well as patients should integrate PT more consistently into osteoarthritis management

The potential of Landsat time series to characterize historical dynamic and monitor future disturbances in human-modified rainforests of Indonesia

In this study we demonstrated for the first time the potential of using full time series from high spatial resolution (30 m) Landsat satellites, covering a period from 1987-2017, for characterizing historical dynamics in Indonesian humid tropical rainforests. Our special focus was on mapping forest disturbance and post-disturbance regrowth, which in turn can potentially be used to map primary (undisturbed) forests, secondary (disturbed/degraded) forests, and forest land converted to oil palm plantation. We applied the Breaks For Additive Season and Trend (BFAST) Monitor framework for continuous change detection; BFAST is a generic and transparent method, which can be used for near-real-time monitoring. To verify our approach, a preliminary spatial accuracy assessment was carried out for disturbance detection using 418 sample pixels interpreted from very high spatial resolution images acquired through Digital Globe viewing service. Besides, we identified the sources of detection errors and approaches to overcome them. Implementation of the potential map product in existing international and national policies will be discusse

Perceiving locations of moving objects across eye blinks

Eye blinks cause disruption of visual input that generally goes unnoticed. It is thought that the brain uses active suppression to prevent awareness of the gaps, but it is unclear how suppression would affect the perception of dynamic events, when visual input changes across the blink. Here we addressed this question by studying the perception of moving objects around eye blinks. In Experiment 1 (N = 16), we observed that when motion terminates during a blink, the last perceived position is shifted forward from its actual last position. In Experiment 2 (N = 8), we found that motion trajectories were perceived as more continuous when the object jumped backward during the blink, cancelling a fraction of the space it travelled. This suggests subjective underestimation of blink duration. These results reveal the strategies used by the visual system to compensate for disruptions and maintain perceptual continuity: time elapsed during eye blinks is perceptually compressed and filled with extrapolated information