Review: Modeling of nitrogen removal and control strategy in continuous-flow-intermittent-aeration process

The continuous-flow-intermittent-aeration process was introduced to achieve nitrogen removal in a  wastewater treatment plant (WWTP). Without structural readjustment of completed mixed activated-sludge treatment unit, operation scheme of intermittent aeration would be upgraded to promote the WWTP  performance. As an aid of the implementation, mathematical simulation models were developed as an  invaluable tool. Due to some uncertainties associated with the mechanisms and quantification of the process, some simplification in a reliable model should be addressed progressively by using the relevant information  drawn from the existing models, the literature and the works on the experiments. An unsteady-state model for the upgrade of WWTP process was developed. The model predictions are coincident with the practical trends of the effluents, which the error percentages are about 10%. Moreover, the model facilitates the insight into  nitrogen removal with the process operational conditions. The study could provide some valuable reference and recommendation on the design and operation of the municipal WWTP.Key words: Kinetic model, nitrification, denitrification, process control, continuous flow, intermittent aeration

SPACE-TIME GRAPH-BASED CONVOLUTIONAL NEURAL NETWORKS OF STUDY ON MOVEMENT RECOGNITION OF FOOTBALL PLAYERS

Behaviour recognition technology is an interdisciplinary technology, integrating many research achievements in computer vision, deep learning, pattern recognition and other fields. The key information of bone data on human behavior can not only accurately describe the motion posture of the human body in three-dimensional space, but also its rigid connection structure is robust to various external interference factors. However, the behavioral recognition algorithm is influenced by different factors such as background, light and environment, which is easy to lead to unstable recognition accuracy and limited application scenarios. To address this problem, in this paper, we propose a noise filtering algorithm based on data correlation and skeleton energy model filtering, construct a set of football player data sets, using the ST-GCN algorithm to train the skeleton characteristics of football players, and construct a behavior recognition system applied to football players. Finally, by comparing the accuracy of Deep LSTM, 2s-AGCN and the algorithm in this paper, the accuracy of TOP1 and TOP5 is 39.97% and 66.34%, respectively, which are significantly higher than the other two algorithms. It can realize the statistics of athletes and analyze the technical and tactical movements of players on the football field

[N,N-Bis(diphenyl­phosphan­yl)propanamine-κ2 P,P′]dichloridonickel(II)

In the title complex, [NiCl2(C27H27NP2)], the Ni2+ ion is coordinated by two chloride ions and two P atoms of the bidentate N,N-bis­(diphenyl­phosphan­yl)propyl ligand to generate a strongly distorted cis-NiCl2P2 square-planar geometry for the metal ion. A NiP2N rhombus occurs within the chelating ligand

Low Expression of DYRK2 (Dual Specificity Tyrosine Phosphorylation Regulated Kinase 2) Correlates with Poor Prognosis in Colorectal Cancer.

Dual-specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) is a member of dual-specificity kinase family, which could phosphorylate both Ser/Thr and Tyr substrates. The role of DYRK2 in human cancer remains controversial. For example, overexpression of DYRK2 predicts a better survival in human non-small cell lung cancer. In contrast, amplification of DYRK2 gene occurs in esophageal/lung adenocarcinoma, implying the role of DYRK2 as a potential oncogene. However, its clinical role in colorectal cancer (CRC) has not been explored. In this study, we analyzed the expression of DYRK2 from Oncomine database and found that DYRK2 level is lower in primary or metastatic CRC compared to adjacent normal colon tissue or non-metastatic CRC, respectively, in 6 colorectal carcinoma data sets. The correlation between DYRK2 expression and clinical outcome in 181 CRC patients was also investigated by real-time PCR and IHC. DYRK2 expression was significantly down-regulated in colorectal cancer tissues compared with adjacent non-tumorous tissues. Functional studies confirmed that DYRK2 inhibited cell invasion and migration in both HCT116 and SW480 cells and functioned as a tumor suppressor in CRC cells. Furthermore, the lower DYRK2 levels were correlated with tumor sites (P = 0.023), advanced clinical stages (P = 0.006) and shorter survival in the advanced clinical stages. Univariate and multivariate analyses indicated that DYRK2 expression was an independent prognostic factor (P < 0.001). Taking all, we concluded that DYRK2 a novel prognostic biomarker of human colorectal cancer

[N,N-Bis(diphenyl­phosphan­yl)benzyl­amine-κ2 P,P′]dichloridonickel(II) dichloro­methane monosolvate

In the title solvated complex, [NiCl2(C31H27NP2)]·CH2Cl2, the Ni2+ ion is coordinated by two chloride ions and two P atoms of the chelating N,N-bis­(diphenyl­phosphan­yl)benzyl ligand to generate a strongly distorted cis-NiCl2P2 square-planar geometry for the metal ion. In the crystal, the components are linked by C—H⋯Cl inter­actions

Monetary policy, cash holding and corporate investment: evidence from China

This paper uses 13,766 firm-year observations between 2003 and 2013 from China to investigate the effects of monetary policy on corporate investment and the mitigating effects of cash holding. We find that tightening monetary policy reduces corporate investment while cash holdings mitigate such adverse effects. The cash mitigating role is especially significant for financially constrained firms, non-state-owned enterprises (non-SOEs) and those firms located in a less developed financial market. Cash holding also improves investment efficiency when monetary policy is tightening and tightening monetary policy enhances the ‘cash-cash flow’ sensitivity. Our empirical evidence calls for a critical evaluation on the monetary policies implemented in China which are less effective for state-owned enterprises. It also calls for a necessity for local government to further develop regional financial markets to protect vulnerable businesses, such as non-SOEs and financially constrained firms, from external shocks in order to maintain their sustainable growth and competitive advantages

MHSA-Net: Multi-Head Self-Attention Network for Occluded Person Re-Identification

This paper presents a novel person re-identification model, named Multi-Head Self-Attention Network (MHSA-Net), to prune unimportant information and capture key local information from person images. MHSA-Net contains two main novel components: Multi-Head Self-Attention Branch (MHSAB) and Attention Competition Mechanism (ACM). The MHSAM adaptively captures key local person information, and then produces effective diversity embeddings of an image for the person matching. The ACM further helps filter out attention noise and non-key information. Through extensive ablation studies, we verified that the Structured Self-Attention Branch and Attention Competition Mechanism both contribute to the performance improvement of the MHSA-Net. Our MHSA-Net achieves state-of-the-art performance especially on images with occlusions. We have released our models (and will release the source codes after the paper is accepted) on https://github.com/hongchenphd/MHSA-Net.Comment: Submitted to IEEE Transactions on Image Processing (TIP