Flexible Network Binarization with Layer-wise Priority

How to effectively approximate real-valued parameters with binary codes plays a central role in neural network binarization. In this work, we reveal an important fact that binarizing different layers has a widely-varied effect on the compression ratio of network and the loss of performance. Based on this fact, we propose a novel and flexible neural network binarization method by introducing the concept of layer-wise priority which binarizes parameters in inverse order of their layer depth. In each training step, our method selects a specific network layer, minimizes the discrepancy between the original real-valued weights and its binary approximations, and fine-tunes the whole network accordingly. During the iteration of the above process, it is significant that we can flexibly decide whether to binarize the remaining floating layers or not and explore a trade-off between the loss of performance and the compression ratio of model. The resulting binary network is applied for efficient pedestrian detection. Extensive experimental results on several benchmarks show that under the same compression ratio, our method achieves much lower miss rate and faster detection speed than the state-of-the-art neural network binarization method.Comment: More experiments on image classification are planne

Synthesis, biological evaluation and mechanism studies of C-23 modified 23-hydroxybetulinic acid derivatives as anticancer agents

A series of C-23 modified 23-hydroxybetulinic acid (HBA) derivatives were synthesized and evaluated for their antiproliferative activity against a panel of cancer cell lines (A2780, A375, B16, MCF-7 and HepG2). The biological screening results showed that most of the derivatives exhibited more potent antiproliferative activity than HBA, and compound 6e exhibited the most potent activity with IC50 values of 2.14 μM, 2.89 μM, and 3.97 μM against A2780, B16, and MCF-7 cells, respectively. Further anticancer mechanism studies revealed that compound 6e induced the generation of intracellular reactive oxygen species (ROS) and reduction of mitochondrial membrane potential (MMP) of B16 cells in a dose-dependent manner. Moreover, western blot analysis indicated that compound 6e downregulated the expression of anti-apoptotic protein Bcl-2 and upregulated the expression of proapoptotic protein Bax, activation of caspase 3 to induce cell apoptosis. Meanwhile, compound 6e significantly inhibited the phosphorylation of MEK, ERK, and Akt without affecting the expression of MEK, ERK, and Akt. Furthermore, the in vivo anti-tumor activity of 6e was validated (tumor inhibitory ratio of 68.4% at the dose of 30 mg/kg) in mice with B16 melanoma

Design, synthesis and anticancer properties of isocombretapyridines as potent colchicine binding site inhibitors

A series of novel isocombretapyridines were designed and synthesized based on a lead compound isocombretastatin A-4 (isoCA-4) by replacing 3,4,5-trimethoxylphenyl with substituent pyridine nucleus. The MTT assay results showed that compound 20a possessed the most potent activities against all tested cell lines with IC50 values at nanomolar concentration ranges. Moreover, 20a inhibited tubulin polymerization at a micromolar level and also displayed potent anti-vascular activity in vitro. Further mechanistic studies were conducted to demonstrate that compound 20a could bind to the colchicine site of tubulin,and disrupte the cell microtubule networks, induce G2/M phase arrest, promote apoptosis and depolarize mitochondria of K562 cells in a dose-dependent manner. Notably, 20a exhibited more potent tumor growth inhibition activity with 68.7% tumor growth inhibition than that of isoCA-4 in H22 allograft mouse model without apparent toxicity. The present results suggested that compound 20a may serve as a promising potent microtubule-destabilizing agent candidate for the development of therapeutics to treat cancer

Characterization and gene expression patterns analysis implies BSK family genes respond to salinity stress in cotton

Identification, evolution, and expression patterns of BSK (BR signaling kinase) family genes revealed that BSKs participated in the response of cotton to abiotic stress and maintained the growth of cotton in extreme environment. The steroidal hormone brassinosteroids (BR) play important roles in different plant biological processes. This study focused on BSK which were downstream regulatory element of BR, in order to help to decipher the functions of BSKs genes from cotton on growth development and responses to abiotic stresses and lean the evolutionary relationship of cotton BSKs. BSKs are a class of plant-specific receptor-like cytoplasmic kinases involved in BR signal transduction. In this study, bioinformatics methods were used to identify the cotton BSKs gene family at the cotton genome level, and the gene structure, promoter elements, protein structure and properties, gene expression patterns and candidate interacting proteins were analyzed. In the present study, a total of 152 BSKs were identified by a genome-wide search in four cotton species and other 11 plant species, and phylogenetic analysis revealed three evolutionary clades. It was identified that BSKs contain typical PKc and TPR domains, the N-terminus is composed of extended chains and helical structures. Cotton BSKs genes show different expression patterns in different tissues and organs. The gene promoter contains numerous cis-acting elements induced by hormones and abiotic stress, the hormone ABA and Cold-inducing related elements have the highest count, indicating that cotton BSK genes may be regulated by various hormones at different growth stages and involved in the response regulation of cotton to various stresses. The expression analysis of BSKs in cotton showed that the expression levels of GhBSK06, GhBSK10, GhBSK21 and GhBSK24 were significantly increased with salt-inducing. This study is helpful to analyze the function of cotton BSKs genes in growth and development and in response to stress

Baipenzhu Reservoir Inflow Flood Forecasting Based on a Distributed Hydrological Model

For reservoir basins, complex underlying surface conditions, short flood confluence times, and concentrated water volumes make inflow flood forecasting difficult and cause forecast accuracies to be low. Conventional flood forecasting models can no longer meet the required forecast accuracy values for flood control operations. To give full play to the role of reservoirs in flood control and to maximize the use of reservoir flood resources, high-precision inflow flood forecasting is urgently needed as a support mechanism. In this study, the Baipenzhu Reservoir in Guangdong Province was selected as the study case, and an inflow flood forecast scheme was designed for the reservoir by a physically based distributed hydrological model, the Liuxihe model. The results show that the Liuxihe model has strong applicability for flood forecasting in the studied reservoir basin and that the simulation results are very accurate. This study also found that the use of different Digital Elevation Model (DEM) data sources has a certain impact on the structure of the Liuxihe model, but the constructed models can both simulate the inflow flood process of the Baipenzhu Reservoir well. At the same time, the Liuxihe model can reflect the spatial variation in rainfall well, and using the Particle swarm optimization (PSO) algorithm to optimize the initial model parameters can greatly reduce the uncertainty of the model forecasts. According to China’s hydrological information forecast standards, the Liuxihe model forecast schemes constructed by the two data sources are rated as Grade A and can be used for real-time flood forecasting in the Baipenzhu Reservoir basin