11,171 research outputs found
Collider search of light dark matter model with dark sector decay
We explore the possibility that the dark matter relic density is not produced
by thermal mechanism directly, but by the decay of other heavier dark sector
particles which on the other hand can be produced by the thermal freeze-out
mechanism. Using a concrete model with a light dark matter from dark sector
decay, we study the collider signature of the dark sector particles in
association with Higgs production processes. We find that the future lepton
colliders can be a better place to probe the signature of this kind of light
dark matter model than the hadron collider such as LHC. Meanwhile, it is found
that a Higgs factory with center of mass energy 250 GeV has a better potential
to resolve the signature of this kind of light dark matter model than the Higgs
factory with center of mass energy 350 GeV.Comment: 15 pages, 14 figure
Noninvasive prediction of Blood Lactate through a machine learning-based approach.
We hypothesized that blood lactate concentration([Lac]blood) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [Lac]blood noninvasively during constant work rate (CWR) exercise of various intensities. 31 healthy participants were recruited and each underwent 4 cardiopulmonary exercise tests: one incremental and three CWR tests (low: 35% of peak work rate for 15 min, moderate: 60% 10 min and high: 90% 4 min). At the end of each CWR test, venous blood was sampled to determine [Lac]blood. 31 trios of CWR tests were employed to construct the mathematical model, which utilized exponential regression combined with Taylor expansion. Good fitting was achieved when the conditions of low and moderate intensity were put in one model; high-intensity in another. Standard deviation of fitting error in the former condition is 0.52; in the latter is 1.82 mmol/liter. Weighting analysis demonstrated that, besides heart rate, respiratory variables are required in the estimation of [Lac]blood in the model of low/moderate intensity. In conclusion, by measuring noninvasive cardio-respiratory parameters, [Lac]blood during CWR exercise can be determined with good accuracy. This should have application in endurance training and future exercise industry
Audeosynth: music-driven video montage
We introduce music-driven video montage, a media format that offers a pleasant way to browse or summarize video clips collected from various occasions, including gatherings and adventures. In music-driven video montage, the music drives the composition of the video content. According to musical movement and beats, video clips are organized to form a montage that visually reflects the experiential properties of the music. Nonetheless, it takes enormous manual work and artistic expertise to create it. In this paper, we develop a framework for automatically generating music-driven video montages. The input is a set of video clips and a piece of background music. By analyzing the music and video content, our system extracts carefully designed temporal features from the input, and casts the synthesis problem as an optimization and solves the parameters through Markov Chain Monte Carlo sampling. The output is a video montage whose visual activities are cut and synchronized with the rhythm of the music, rendering a symphony of audio-visual resonance.postprin
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