Relationship between promoter sequence and its strength in gene expression

In this study, through various tests one theoretical model is presented to describe the relationship between promoter strength and its nucleotide sequence. Our analysis shows that, promoter strength is greatly influenced by nucleotide groups with three adjacent nucleotides in its sequence. Meanwhile, nucleotides in different regions of promoter sequence have different effects on promoter strength. Based on experimental data for {\it E. coli} promoters, our calculations indicate, nucleotides in -10 region, -35 region, and the discriminator region of promoter sequence are more important than those in spacing region for determining promoter strength. With model parameter values obtained by fitting to experimental data, four promoter libraries are theoretically built for the corresponding experimental environments under which data for promoter strength in gene expression has been measured previously

Existence and uniqueness of solution of the differential equation describing the TASEP-LK coupled transport process

In this paper, the existence and uniqueness of solution of a specific differential equation is studied. This equation originates from the description of a coupled process by totally asymmetric simple exclusion process (TASEP) and Langmuir kinetics (LK). In the fields of physics and biology, the properties of the TASEP-LK coupled process have been extensively studied by Monte Carlo simulations and numerical calculations, as well as detailed experiments. However, so far, no rigorous mathematical analysis has been given to the corresponding differential equations, especially their existence and uniqueness of solution. In this paper, using the upper and lower solution method, the existence of solution of the steady state equation is obtained. Then using a generalized maximum principle, we show that the solution constructed from the upper and lower solution method is actually the unique solution in C∞ space. Moreover, the existence and uniqueness of solution of the time dependent differential equation are also obtained in one specific space X\b{eta}. Our results imply that the previous results obtained by numerical calculations and Monte Carlo simulations are theoretically correct, especially the most important phase diagram of particle density along the travel track under different model parameters. The study in this paper provides theoretical foundations for the analysis of TASEP-LK coupled process. At the same time, the methods used in this paper may be instructive for studies about the more general cases of the TASEP-LK process, such as the one with multiple travel tracks or the one with multiple particle species.Comment: This paper has been thoroughly modified and submited again to arXiv by my coauther Jingwei Li. So I think it is betetr for me to withdraw from my account. see arXiv:1905.12235v

Elites’ Social Networks and Politics in the Han Empire (202 B.C.E.–220 C.E.)

Social networks were heavily intertwined with elites’ social status and political power throughout the Han dynasty. This article introduces the Han Elites’ Social Network Dataset, an open-access dataset that the author collected primarily through manual labor. It contains data on Han elites’ marriage, kinship, patron-client, teacher-disciple, friendship, and recommender-nominee relationships. The article then visualizes and analyzes these social networks in relation to Han politics. It argues that social networks provided individuals with channels for upward social mobility and access to political careers, and that the reliance on different types of networks contributed to the formation of political cliques as well as the growing conflict between the inner court and the outer court

SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications

Drones or general Unmanned Aerial Vehicles (UAVs), endowed with computer vision function by on-board cameras and embedded systems, have become popular in a wide range of applications. However, real-time scene parsing through object detection running on a UAV platform is very challenging, due to limited memory and computing power of embedded devices. To deal with these challenges, in this paper we propose to learn efficient deep object detectors through channel pruning of convolutional layers. To this end, we enforce channel-level sparsity of convolutional layers by imposing L1 regularization on channel scaling factors and prune less informative feature channels to obtain "slim" object detectors. Based on such approach, we present SlimYOLOv3 with fewer trainable parameters and floating point operations (FLOPs) in comparison of original YOLOv3 (Joseph Redmon et al., 2018) as a promising solution for real-time object detection on UAVs. We evaluate SlimYOLOv3 on VisDrone2018-Det benchmark dataset; compelling results are achieved by SlimYOLOv3 in comparison of unpruned counterpart, including ~90.8% decrease of FLOPs, ~92.0% decline of parameter size, running ~2 times faster and comparable detection accuracy as YOLOv3. Experimental results with different pruning ratios consistently verify that proposed SlimYOLOv3 with narrower structure are more efficient, faster and better than YOLOv3, and thus are more suitable for real-time object detection on UAVs. Our codes are made publicly available at https://github.com/PengyiZhang/SlimYOLOv3