596 research outputs found
The Size Conundrum: Why Online Knowledge Markets Can Fail at Scale
In this paper, we interpret the community question answering websites on the
StackExchange platform as knowledge markets, and analyze how and why these
markets can fail at scale. A knowledge market framing allows site operators to
reason about market failures, and to design policies to prevent them. Our goal
is to provide insights on large-scale knowledge market failures through an
interpretable model. We explore a set of interpretable economic production
models on a large empirical dataset to analyze the dynamics of content
generation in knowledge markets. Amongst these, the Cobb-Douglas model best
explains empirical data and provides an intuitive explanation for content
generation through concepts of elasticity and diminishing returns. Content
generation depends on user participation and also on how specific types of
content (e.g. answers) depends on other types (e.g. questions). We show that
these factors of content generation have constant elasticity---a percentage
increase in any of the inputs leads to a constant percentage increase in the
output. Furthermore, markets exhibit diminishing returns---the marginal output
decreases as the input is incrementally increased. Knowledge markets also vary
on their returns to scale---the increase in output resulting from a
proportionate increase in all inputs. Importantly, many knowledge markets
exhibit diseconomies of scale---measures of market health (e.g., the percentage
of questions with an accepted answer) decrease as a function of number of
participants. The implications of our work are two-fold: site operators ought
to design incentives as a function of system size (number of participants); the
market lens should shed insight into complex dependencies amongst different
content types and participant actions in general social networks.Comment: The 27th International Conference on World Wide Web (WWW), 201
Boundary-Aware Proposal Generation Method for Temporal Action Localization
The goal of Temporal Action Localization (TAL) is to find the categories and
temporal boundaries of actions in an untrimmed video. Most TAL methods rely
heavily on action recognition models that are sensitive to action labels rather
than temporal boundaries. More importantly, few works consider the background
frames that are similar to action frames in pixels but dissimilar in semantics,
which also leads to inaccurate temporal boundaries. To address the challenge
above, we propose a Boundary-Aware Proposal Generation (BAPG) method with
contrastive learning. Specifically, we define the above background frames as
hard negative samples. Contrastive learning with hard negative mining is
introduced to improve the discrimination of BAPG. BAPG is independent of the
existing TAL network architecture, so it can be applied plug-and-play to
mainstream TAL models. Extensive experimental results on THUMOS14 and
ActivityNet-1.3 demonstrate that BAPG can significantly improve the performance
of TAL
Unified Quantum State Tomography and Hamiltonian Learning Using Transformer Models: A Language-Translation-Like Approach for Quantum Systems
Schr\"odinger's equation serves as a fundamental component in characterizing
quantum systems, wherein both quantum state tomography and Hamiltonian learning
are instrumental in comprehending and interpreting quantum systems. While
numerous techniques exist for carrying out state tomography and learning
Hamiltonians individually, no method has been developed to combine these two
aspects. In this study, we introduce a new approach that employs the attention
mechanism in transformer models to effectively merge quantum state tomography
and Hamiltonian learning. By carefully choosing and preparing the training
data, our method integrates both tasks without altering the model's
architecture, allowing the model to effectively learn the intricate
relationships between quantum states and Hamiltonian. We also demonstrate the
effectiveness of our approach across various quantum systems, ranging from
simple 2-qubit cases to more involved 2D antiferromagnetic Heisenberg
structures. The data collection process is streamlined, as it only necessitates
a one-way generation process beginning with state tomography. Furthermore, the
scalability and few-shot learning capabilities of our method could potentially
minimize the resources required for characterizing and optimizing quantum
systems. Our research provides valuable insights into the relationship between
Hamiltonian structure and quantum system behavior, fostering opportunities for
additional studies on quantum systems and the advancement of quantum
computation and associated technologies.Comment: 15 pages, 10 figure
Revealing a 3D Fermi Surface Pocket and Electron-Hole Tunneling in UTe with Quantum Oscillations
Spin triplet superconductor UTe is widely believed to host a
quasi-two-dimensional Fermi surface, revealed by first principal calculations,
photoemission and quantum oscillation measurements. An outstanding question
still remains as to the existence of a three-dimensional Fermi surface pocket,
which is crucial for our understanding of the exotic superconducting and
topological properties of UTe. This 3D Fermi surface pocket appears in
various theoretical models with different physics origins but has not been
detected experimentally. Here for the first time, we provide concrete evidence
for a relatively isotropic, small Fermi surface pocket of UTe via quantum
oscillation measurements. In addition, we observed high frequency quantum
oscillations corresponding to electron-hole tunneling between adjacent electron
and hole pockets. The coexistence of 2D and 3D Fermi surface pockets, as well
as the breakdown orbits, provides a test bed for theoretical models and aid the
realization of a unified understanding of superconducting state of UTe
from the first-principles approach
Prevalence of ideal cardiovascular health and its relationship with relative handgrip strength in rural northeast China
ObjectivesWe aimed to investigate ideal cardiovascular health (CVH), its relationship with handgrip strength, and its components in rural China.MethodsWe conducted a cross-sectional study of 3,203 rural Chinese individuals aged ≥35 years in Liaoning Province, China. Of these, 2,088 participants completed the follow-up survey. Handgrip strength was estimated using a handheld dynamometer and was normalized to body mass. Ideal CVH was assessed using seven health indicators (smoking, body mass index, physical activity, diet, cholesterol, blood pressure, and glucose). Binary logistic regression analyses were performed to assess the correlation between handgrip strength and ideal CVH.ResultsWomen had a higher rate of ideal cardiovascular health (CVH) than men (15.7% vs. 6.8%, P < 0.001). Higher handgrip strength correlated with a higher proportion of ideal CVH (P for trend <0.001). After adjusting for confounding factors, the odds ratios (95% confidence interval) of ideal CVH across increasing handgrip strength tripartite were 1.00 (reference), 2.368 (1.773, 3.164), and 3.642 (2.605, 5.093) in the cross-sectional study and 1.00 (reference), 2.088 (1.074, 4.060), and 3.804 (1.829, 7.913) in the follow-up study (all P < 0.05).ConclusionIn rural China, the ideal CVH rate was low, and positively correlated with handgrip strength. Grip strength can be a rough predictor of ideal CVH and can be used to provide guidelines for improving CVH in rural China
Application simulation of a resistive type superconducting fault current limiter (SFCL) in a transmission and wind power system
Due to the increased fault-level currents, superconducting fault current limiter (SFCL) is more likely to penetrate into a low voltage and medium voltage transmission network to improve their stability and lower the electric devices capacity. Therefore it is important to model a SFCL in power system to analyze its performance and study its characteristics. In this paper, a simulation model for a resistive type SFCL consisted of YBCO tapes is developed using Matlab/Simulink software. This model will take into account SFCL's internal electromagnetic behavior by coupling its internal resistance and the current density characteristics based on the E-J power law. Finally, the SFCL simulation model is applied in a transmission and a wind farm power grid, respectively. Different fault limiting scenarios are investigated and the results show that the SFCL is effective in limiting fault currents with a maximum of 50% in transmission lines, particularly for wind farm networks
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