Effect of antenna element properties and array orientation on performance of MIMO systems

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Breakdown and recovery in traffic flow models

Most car-following models show a transition from laminar to ``congested'' flow and vice versa. Deterministic models often have a density range where a disturbance needs a sufficiently large critical amplitude to move the flow from the laminar into the congested phase. In stochastic models, it may be assumed that the size of this amplitude gets translated into a waiting time, i.e.\ until fluctuations sufficiently add up to trigger the transition. A recently introduced model of traffic flow however does not show this behavior: in the density regime where the jam solution co-exists with the high-flow state, the intrinsic stochasticity of the model is not sufficient to cause a transition into the jammed regime, at least not within relevant time scales. In addition, models can be differentiated by the stability of the outflow interface. We demonstrate that this additional criterion is not related to the stability of the flow. The combination of these criteria makes it possible to characterize commonalities and differences between many existing models for traffic in a new way

Insights Into the Chinese Pangolin's (Manis pentadactyla) Diet in a Peri-Urban Habitat: A Case Study From Hong Kong

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How do equity markets react to COVID-19? Evidence from emerging and developed countries

Based on the supply of stock market returns hypothesis, we argue that the unprecedented adverse shock of COVID-19 on the countries’ economic growth translates into a negative shock to the stock markets. According to the institutional theory, we also argue that the impact of COVID-19 in emerging countries is different from developed countries. Based on the overreaction hypothesis, we expect that the market reaction during the stabilizing period of COVID-19 spread is different from the market reaction during the infection period. Using high-frequency daily data across 53 emerging and 23 developed countries from January 14 to August 20, 2020, we find that COVID-19 cases and deaths adversely affect stock returns and increase volatility and trading volume. Cases and deaths affected stock returns and volatility in the emerging markets, while only cases of COVID-19 affected stock returns, volatility, and trading volume in the developed markets. COVID-19 cases and deaths are related to returns, volatility, and trading volume for emerging countries during the rising infection of COVID-19 (pre-April 2020), while cases and mortality rates are related to returns, volatility, and trading volume in developed countries during the stabilizing spread (post-April 2020). Therefore, the emerging markets’ investors seem to react to COVID-19 cases and mortality rates differently from those in the developed markets across two different periods of COVID-19 infection

Bounds on Dimension Reduction in the Nuclear Norm

$\newcommand{\schs}{\scriptstyle{\mathsf{S}}_1}$For all $n \ge 1$, we give an explicit construction of $m \times m$ matrices $A_1,\ldots,A_n$ with $m = 2^{\lfloor n/2 \rfloor}$ such that for any $d$ and $d \times d$ matrices $A'_1,\ldots,A'_n$ that satisfy \|A'_i-A'_j\|_{\schs} \,\leq\, \|A_i-A_j\|_{\schs}\,\leq\, (1+\delta) \|A'_i-A'_j\|_{\schs} for all $i,j\in\{1,\ldots,n\}$ and small enough $\delta = O(n^{-c})$, where $c> 0$ is a universal constant, it must be the case that $d \ge 2^{\lfloor n/2\rfloor -1}$. This stands in contrast to the metric theory of commutative $\ell_p$ spaces, as it is known that for any $p\geq 1$, any $n$ points in $\ell_p$ embed exactly in $\ell_p^d$ for $d=n(n-1)/2$. Our proof is based on matrices derived from a representation of the Clifford algebra generated by $n$ anti-commuting Hermitian matrices that square to identity, and borrows ideas from the analysis of nonlocal games in quantum information theory.Comment: 16 page