26,350 research outputs found
Assessing Negotiation Outcomes Matters in Classroom Settings
It is hardly disputable that negotiation outcomes count in real world negotiation settings. In classroom settings, however, the negotiation outcomes often do not count. In many negotiation courses, for the negotiators it does not really matter in any tangible dimensions what kind of outcomes they achieve through the negotiation – not only that they do not need to bear the (hypothetical) consequence of the agreement (or its lack of), but also that the negotiation outcomes do not affect their performance assessment in the negotiation course. Thus on the issue of whether negotiation outcomes count, this type of class-room negotiation is drastically different from those in real world settings. But does that difference really matter? Would it make any difference in terms of student learning? These are the question the current study aims to address
Blue Phosphorene Oxide: Strain-tunable Quantum Phase Transitions and Novel 2D Emergent Fermions
Tunable quantum phase transitions and novel emergent fermions in solid state
materials are fascinating subjects of research. Here, we propose a new stable
two-dimensional (2D) material, the blue phosphorene oxide (BPO), which exhibits
both. Based on first-principles calculations, we show that its equilibrium
state is a narrow-bandgap semiconductor with three bands at low energy.
Remarkably, a moderate strain can drive a semiconductor-to-semimetal quantum
phase transition in BPO. At the critical transition point, the three bands
cross at a single point at Fermi level, around which the quasiparticles are a
novel type of 2D pseudospin-1 fermions. Going beyond the transition, the system
becomes a symmetry-protected semimetal, for which the conduction and valence
bands touch quadratically at a single Fermi point that is protected by
symmetry, and the low-energy quasiparticles become another novel type of 2D
double Weyl fermions. We construct effective models characterizing the phase
transition and these novel emergent fermions, and we point out several exotic
effects, including super Klein tunneling, supercollimation, and universal
optical absorbance. Our result reveals BPO as an intriguing platform for the
exploration of fundamental properties of quantum phase transitions and novel
emergent fermions, and also suggests its great potential in nanoscale device
applications.Comment: 23 pages, 5 figure
Practical Deep Reinforcement Learning Approach for Stock Trading
Stock trading strategy plays a crucial role in investment companies. However,
it is challenging to obtain optimal strategy in the complex and dynamic stock
market. We explore the potential of deep reinforcement learning to optimize
stock trading strategy and thus maximize investment return. 30 stocks are
selected as our trading stocks and their daily prices are used as the training
and trading market environment. We train a deep reinforcement learning agent
and obtain an adaptive trading strategy. The agent's performance is evaluated
and compared with Dow Jones Industrial Average and the traditional min-variance
portfolio allocation strategy. The proposed deep reinforcement learning
approach is shown to outperform the two baselines in terms of both the Sharpe
ratio and cumulative returns
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