Modeling Spacing Distribution of Queuing Vehicles in Front of a Signalized Junction Using Random-Matrix Theory

Modeling of headway/spacing between two consecutive vehicles has many applications in traffic flow theory and transport practice. Most known approaches only study the vehicles running on freeways. In this paper, we propose a model to explain the spacing distribution of queuing vehicles in front of a signalized junction based on random-matrix theory. We show that the recently measured spacing distribution data well fit the spacing distribution of a Gaussian symplectic ensemble (GSE). These results are also compared with the spacing distribution observed for car parking problem. Why vehicle-stationary-queuing and vehicle-parking have different spacing distributions (GSE vs GUE) seems to lie in the difference of driving patterns

Many-body non-Hermitian skin effect under dynamic gauge coupling

We study an atom-cavity hybrid system where fermionic atoms in a one-dimensional lattice are subject to a cavity-induced dynamic gauge potential. The gauge coupling leads to highly-degenerate steady states in which the fermions accumulate to one edge of the lattice under an open boundary condition. Such a phenomenon originates from the many-body Liouvillian superoperator of the system, which, being intrinsically non-Hermitian, is unstable against boundary perturbations and manifests the non-Hermitian skin effect. Contrary to the single-body case, the steady state of a multi-atom system is approached much slower under the open boundary condition, as the long-time damping of the cavity mode exhibits distinct rates at different times. This stage-wise slowdown is attributed to the competition between light-assisted hopping and the dynamic gauge coupling, which significantly reduces the steady-state degeneracy under the open boundary condition, as distinct hosts of quasi-steady states dominate the dynamics at different time scales.Comment: 13 pages, 7 figure

Comparative proteomic profiling reveals molecular characteristics associated with oogenesis and oocyte maturation during ovarian development of Bactrocera dorsalis (Hendel)

Time-dependent expression of proteins in ovary is important to understand oogenesis in insects. Here, we profiled the proteomes of developing ovaries from Bactrocera dorsalis (Hendel) to obtain information about ovarian development with particular emphasis on differentially expressed proteins (DEPs) involved in oogenesis. A total of 4838 proteins were identified with an average peptide number of 8.15 and sequence coverage of 20.79%. Quantitative proteomic analysis showed that a total of 612 and 196 proteins were differentially expressed in developing and mature ovaries, respectively. Furthermore, 153, 196 and 59 potential target proteins were highly expressed in early, vitellogenic and mature ovaries and most tested DEPs had the similar trends consistent with the respective transcriptional profiles. These proteins were abundantly expressed in pre-vitellogenic and vitellogenic stages, including tropomyosin, vitellogenin, eukaryotic translation initiation factor, heat shock protein, importin protein, vitelline membrane protein, and chorion protein. Several hormone and signal pathway related proteins were also identified during ovarian development including piRNA, notch, insulin, juvenile, and ecdysone hormone signal pathways. This is the first report of a global ovary proteome of a tephritid fruit fly, and may contribute to understanding the complicate processes of ovarian development and exploring the potentially novel pest control targets