1,524 research outputs found
Forecasting Player Behavioral Data and Simulating in-Game Events
Understanding player behavior is fundamental in game data science. Video
games evolve as players interact with the game, so being able to foresee player
experience would help to ensure a successful game development. In particular,
game developers need to evaluate beforehand the impact of in-game events.
Simulation optimization of these events is crucial to increase player
engagement and maximize monetization. We present an experimental analysis of
several methods to forecast game-related variables, with two main aims: to
obtain accurate predictions of in-app purchases and playtime in an operational
production environment, and to perform simulations of in-game events in order
to maximize sales and playtime. Our ultimate purpose is to take a step towards
the data-driven development of games. The results suggest that, even though the
performance of traditional approaches such as ARIMA is still better, the
outcomes of state-of-the-art techniques like deep learning are promising. Deep
learning comes up as a well-suited general model that could be used to forecast
a variety of time series with different dynamic behaviors
Fracturing ranked surfaces
Discretized landscapes can be mapped onto ranked surfaces, where every
element (site or bond) has a unique rank associated with its corresponding
relative height. By sequentially allocating these elements according to their
ranks and systematically preventing the occupation of bridges, namely elements
that, if occupied, would provide global connectivity, we disclose that bridges
hide a new tricritical point at an occupation fraction , where
is the percolation threshold of random percolation. For any value of in the
interval , our results show that the set of bridges has a
fractal dimension in two dimensions. In the limit , a self-similar fracture is revealed as a singly connected line
that divides the system in two domains. We then unveil how several seemingly
unrelated physical models tumble into the same universality class and also
present results for higher dimensions
Passively Q-switched Yb : YAG laser with Cr4+: YAG as the saturable absorber
By using a continuous-wave Ti:sapphire laser as a pumping source, we demonstrated a passively Q-switched Yb:YAG laser at room temperature with Cr4+:YAG as the saturable absorber. We achieved an average output power of as much as 55 mW at 1.03 mum with a pulse width (FWHM) as short as 350 ns. The initial transmission of the Cr4+:YAG has an effect on the pulse duration (FWHM) and the repetition rate of the Yb:YAG passively Q-switched laser. The Yb:YAG crystal can be a most promising passively Q-switched laser crystal for compact, efficient, solid-state lasers. (C) 2001 Optical Society of America
Superchemistry: dynamics of coupled atomic and molecular Bose-Einstein condensates
We analyze the dynamics of a dilute, trapped Bose-condensed atomic gas
coupled to a diatomic molecular Bose gas by coherent Raman transitions. This
system is shown to result in a new type of `superchemistry', in which giant
collective oscillations between the atomic and molecular gas can occur. The
phenomenon is caused by stimulated emission of bosonic atoms or molecules into
their condensate phases
Dark soliton states of Bose-Einstein condensates in anisotropic traps
Dark soliton states of Bose-Einstein condensates in harmonic traps are
studied both analytically and computationally by the direct solution of the
Gross-Pitaevskii equation in three dimensions. The ground and self-consistent
excited states are found numerically by relaxation in imaginary time. The
energy of a stationary soliton in a harmonic trap is shown to be independent of
density and geometry for large numbers of atoms. Large amplitude field
modulation at a frequency resonant with the energy of a dark soliton is found
to give rise to a state with multiple vortices. The Bogoliubov excitation
spectrum of the soliton state contains complex frequencies, which disappear for
sufficiently small numbers of atoms or large transverse confinement. The
relationship between these complex modes and the snake instability is
investigated numerically by propagation in real time.Comment: 11 pages, 8 embedded figures (two in color
Convergence and divergence in the evolution of cat skulls: temporal and spatial patterns of morphological diversity
Background: Studies of biological shape evolution are greatly enhanced when framed in a phylogenetic perspective.
Inclusion of fossils amplifies the scope of macroevolutionary research, offers a deep-time perspective on tempo and mode
of radiations, and elucidates life-trait changes. We explore the evolution of skull shape in felids (cats) through morphometric
analyses of linear variables, phylogenetic comparative methods, and a new cladistic study of saber-toothed cats.
Methodology/Principal Findings: A new phylogenetic analysis supports the monophyly of saber-toothed cats
(Machairodontinae) exclusive of Felinae and some basal felids, but does not support the monophyly of various sabertoothed
tribes and genera. We quantified skull shape variation in 34 extant and 18 extinct species using size-adjusted linear
variables. These distinguish taxonomic group membership with high accuracy. Patterns of morphospace occupation are
consistent with previous analyses, for example, in showing a size gradient along the primary axis of shape variation and a
separation between large and small-medium cats. By combining the new phylogeny with a molecular tree of extant Felinae,
we built a chronophylomorphospace (a phylogeny superimposed onto a two-dimensional morphospace through time). The
evolutionary history of cats was characterized by two major episodes of morphological divergence, one marking the
separation between saber-toothed and modern cats, the other marking the split between large and small-medium cats.
Conclusions/Significance: Ancestors of large cats in the ‘Panthera’ lineage tend to occupy, at a much later stage,
morphospace regions previously occupied by saber-toothed cats. The latter radiated out into new morphospace regions
peripheral to those of extant large cats. The separation between large and small-medium cats was marked by considerable
morphologically divergent trajectories early in feline evolution. A chronophylomorphospace has wider applications in
reconstructing temporal transitions across two-dimensional trait spaces, can be used in ecophenotypical and functional
diversity studies, and may reveal novel patterns of morphospace occupation
Transplantation of canine olfactory ensheathing cells producing chondroitinase ABC promotes chondroitin sulphate proteoglycan digestion and axonal sprouting following spinal cord injury
Olfactory ensheathing cell (OEC) transplantation is a promising strategy for treating spinal cord injury (SCI), as has been demonstrated in experimental SCI models and naturally occurring SCI in dogs. However, the presence of chondroitin sulphate proteoglycans within the extracellular matrix of the glial scar can inhibit efficient axonal repair and limit the therapeutic potential of OECs. Here we have used lentiviral vectors to genetically modify canine OECs to continuously deliver mammalian chondroitinase ABC at the lesion site in order to degrade the inhibitory chondroitin sulphate proteoglycans in a rodent model of spinal cord injury. We demonstrate that these chondroitinase producing canine OECs survived at 4 weeks following transplantation into the spinal cord lesion and effectively digested chondroitin sulphate proteoglycans at the site of injury. There was evidence of sprouting within the corticospinal tract rostral to the lesion and an increase in the number of corticospinal axons caudal to the lesion, suggestive of axonal regeneration. Our results indicate that delivery of the chondroitinase enzyme can be achieved with the genetically modified OECs to increase axon growth following SCI. The combination of these two promising approaches is a potential strategy for promoting neural regeneration following SCI in veterinary practice and human patients
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