Localization length of the 1+11+1 continuum directed random polymer

In this paper, we study the localization length of the $1+1$ continuum directed polymer, defined as the distance between the endpoints of two paths sampled independently from the quenched polymer measure. We show that the localization length converges in distribution in the thermodynamic limit, and derive an explicit density formula of the limiting distribution. As a consequence, we prove the $\tfrac32$-power law decay of the density, confirming the physics prediction of Hwa-Fisher \cite{fisher}. Our proof uses the recent result of Das-Zhu \cite{daszhu}.Comment: v2, 18 pages, minor revision, final versio

LRDNet: A lightweight and efficient network with refined dual attention decorder for real-time semantic segmentation

Most of the current popular semantic segmentation convolutional networks are focus on accuracy and require large amount of computation, which is using complex models. In order to realize real-time performance in practical applications, such as embedded systems and mobile devices, lightweight semantic segmentation has become a new need, where the network model should keep good accuracy in very limited computing budget. In this paper, we propose a lightweight network with the refined dual attention decorder (termed LRDNet) for better balance between computational speed and segmentation accuracy. In the encoding part of LRDNet, we offer an asymmetric module based on the residual network for lightweight and efficiency. In this module, a combination of decomposition convolution and deep convolution is used to improve the efficiency of feature extraction. In the decoding part of LRDNet, we use a refined dual attention mechanism to reduce the complexity of the entire network. Our network attained precise real-time segmentation results on Cityscapes, CamVid datasets. Without additional processing and pretraining, the LRDNet model achieves 70.1 Mean IoU in the Cityscapes test set. With a parameter value below 0.66 M, it can be up to 77 FPS

Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications

This work was supported by a restricted research grant of Bayer AG

Some Inequalities Combining Rough and Random Information

Rough random theory, generally applied to statistics, decision-making, and so on, is an extension of rough set theory and probability theory, in which a rough random variable is described as a random variable taking “rough variable” values. In order to extend and enrich the research area of rough random theory, in this paper, the well-known probabilistic inequalities (Markov inequality, Chebyshev inequality, Holder’s inequality, Minkowski inequality and Jensen’s inequality) are proven for rough random variables, which gives a firm theoretical support to the further development of rough random theory. Besides, considering that the critical values always act as a vital tool in engineering, science and other application fields, some significant properties of the critical values of rough random variables involving the continuity and the monotonicity are investigated deeply to provide a novel analytical approach for dealing with the rough random optimization problems

Improving the Effect of Digital Live Broadcasting Activities Based on Configuration Analysis

[Purpose/Significance] Digital live streaming is an important way for enterprises to carry out online activities. Incorporating clear set qualitative comparative analysis into the research on improving the effectiveness of enterprise digital live streaming activities is an innovation in the application of configuration analysis methods and a new breakthrough in the field of improving activity effectiveness. By identifying elements or combinations of elements that can create greater value for enterprise digital live streaming activities, and adopting various ways to enhance these element combinations, the goal of improving the effectiveness of enterprise digital live streaming activities can be achieved, which has innovative guiding significance for enterprise development. [Method/Process] Based on the consideration of sample homogeneity, the background data of the digital live streaming activity of Guangxi Zhongyan Industry Co., Ltd. was used as the data source. Four influencing factors related to the digital live streaming activity were selected as conditional variables using literature induction and problem oriented methods, and some conditional variables were assigned values using linear discriminant dimensionality reduction. At the same time, the activity effect was used as the outcome variable, configuration analysis was conducted on digital live streaming activities in the tobacco industry through clear set qualitative comparative analysis, and combined with SOR model and the 4I theory, a configuration path for improving the effectiveness was generated. [Conclusions/Results] Research has found that a single factor does not constitute a necessary condition for improving the effectiveness of digital live streaming activities. There are two configuration paths: game assisted and topic supported, which can improve the effectiveness of digital live streaming activities. The mechanism of action can be summarized as follows: rich topic types are conducive to meeting users' curiosity psychology, topic popularity and game quantity can ensure users' participation in live streaming, and user interaction work is the basic guarantee for improving user retention. Meanwhile, these two paths can be applied to different forms of digital live streaming, and enterprises should choose according to their own needs and refine the paths in practice. In addition, although this article explores the key paths to improve the effectiveness of digital live streaming activities, due to limitations in research samples and industry fields, it has not fully revealed the various factors that affect the effectiveness of digital live streaming, and there is a certain degree of subjectivity in the criteria for assigning variables. Therefore, further revisions and improvements are needed in future research

Sequence-Specific Detection of DNA Strands Using a Solid-State Nanopore Assisted by Microbeads

Simple, rapid, and low-cost detection of DNA with specific sequence is crucial for molecular diagnosis and therapy applications. In this research, the target DNA molecules are bonded to the streptavidin-coated microbeads, after hybridizing with biotinylated probes. A nanopore with a diameter significantly smaller than the microbeads is used to detect DNA molecules through the ionic pulse signals. Because the DNA molecules attached on the microbead should dissociate from the beads before completely passing through the pore, the signal duration time for the target DNA is two orders of magnitude longer than free DNA. Moreover, the high local concentration of target DNA molecules on the surface of microbeads leads to multiple DNA molecules translocating through the pore simultaneously, which generates pulse signals with amplitude much larger than single free DNA translocation events. Therefore, the DNA molecules with specific sequence can be easily identified by a nanopore sensor assisted by microbeads according to the ionic pulse signals

Preparation of magnetically recoverable bentonite–Fe3O4–MnO2 composite particles for Cd(II) removal from aqueous solutions

In this study, bentonite–Fe3O4–MnO2 composite was synthesized by combining bentonite with Fe3O4 and MnO2 through co-precipitation. Vibrating-sample magnetometry, scanning electron microscopy with energy-dispersive X-ray spectrometry, transmission electron microscopy, Brunauer–Emmett–Teller measurements, and X-ray powder diffraction techniques were used to characterize the composite. The composite consists of Fe3O4 nanoparticles orderly assembled on the surface of bentonite and an outer layer of MnO2 sheets. The composite’s particles possess a saturation magnetization of 13.4–30.5 emu/g and a high specific surface area (203.89 m2/g). The adsorption behaviors of the composite in Cd(II) removal were evaluated by batch equilibrium experiments. Kinetic and isothermal data fit well the pseudo-second-order and the Freundlich models, respectively. Adsorption reached equilibrium within 30 min, and the Freundlich capacity of the composite was 35.35 mg/g. The adsorption capacity of Cd(II) increased with increasing pH and was dependent on the ionic strength. Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy showed the combination of surface hydroxyl groups of the composite and Cd(II) in the solution. The prepared composite can be easily recycled and reused by taking advantage of its magnetic properties. The results show that the designed composite is a promising absorbent for the treatment of Cd-contaminated water.Accepted versio