The Post-IPO Performance in the PRC

The long-run underperformance of IPOs (Initial Public Offerings) is one of the three “New Issues Puzzles” It indicates that if investors buy IPOs and hold for more than three years they will get negative abnormal returns It is necessary to examine the long-run performance of IPOs in China because it benefits how to enhance the efficiency of IPOs market and provides insight of emerging market This paper empirically examines the performance for three years after listing of 76 Shanghai Stock Exchange IPOs form 2002 to 2007, the matched company as the benchmark, the matched company comes from the same industry and similar circulated stock value with listed companies. First it computes the long-run excess returns of the IPOs with types of models. Then it examines whether the underperformance has statistical significance or not. After that, it analyzes the relationship between the variables and long-run performance of IPOs. Research documents that the IPOs significantly underperformed the matched companies. The cumulative abnormal returns over the three years listing are -0.18446. The buy and hold abnormal returns over three years after listing are-0.01284. At last, using the cross-sectional analysis to analyze the factors that affect the long-run performance of IPOs, the regression result shows that EPS is the basic reason; the intrinsic value, issue characteristics and the investors’ sentiment (overoptimistic) are the main reason for long-run performance of IPOs. This paper analyzes the reason of this phenomenon, then from the reason puts forward relevant suggestions: firstly, improving the information disclosure; secondly, evaluating the rational investors; thirdly, strengthening market supervision

Research on the development of carrier intelligent cloud network under the background of IPv6+

With the increasingly mature 5G technology in our country, the government has comprehensively promoted IPv6 scale deployment, the rapid improvement of network quality of the three operators, and gradually transformed to IPv6+, the carrying network is more fl exible, and the user opening service is more convenient, which has promoted the development of intelligent cloud network of China’s carriers. Operators should actively respond to the challenges of IPv6+ era, based on their own intelligent cloud network development needs, the use of SRv6 technology, promote cloud network integration, carrying a variety of online services; Provide integrated cloud network products and services, build an intelligent operation and maintenance system, and improve user satisfaction; To build IPv6 networking capability of the whole network and build intelligent cloud network; Do a good job in the construction of IPv6 network information security, improve the security defense capability of intelligent cloud network, ensure the smooth operation of network, and inject new vitality into the 2B industry market for operators

Diagnose Pathogens in Drinking Water via Magnetic Surface-Enhanced Raman Scattering (SERS) Assay

Rapid identification and diagnosis of bacteria and other microorganisms is a great challenge for drinking water safety due to the increasing frequency of pathogenic infections. Raman spectroscopy is a non-destructive tool to characterize the biochemical fingerprints of bacterial cells and its signal can be improved by surface-enhanced Raman scattering (SERS). Thus, Raman scattering has a huge potential in fast diagnosis of pathogens in drinking water, with low cost and high reproducibility. In this work, we developed a novel fast diagnosis method to detect aquatic pathogens via magnetic SERS assay. With chemical coprecipitation synthesis and surface glucose reduction, the silver-coated magnetic nanoparticles (Ag@MNPs) had a welldeveloped core-shell structure and high efficiency to capture bacterial cells. Ag@MNPs achieved 103 enhancement factor for rhodamine 6G and the limit of detection was 10-9 M. The magnetic SERS assay also successfully detected various bacteria (A. baylyi and E. coli) with high sensitivity (105 CFU/mL). This platform provided a promising and easy-operation approach for pathogen detection for food and drinking water safety

DHX33 transcriptionally controls genes involved in the cell cycle

The RNA helicase DHX33 has been shown to be a critical regulator of cell proliferation and growth. However, the underlying mechanisms behind DHX33 function remain incompletely understood. We present original evidence in multiple cell lines that DHX33 transcriptionally controls the expression of genes involved in the cell cycle, notably cyclin, E2F1, cell division cycle (CDC), and minichromosome maintenance (MCM) genes. DHX33 physically associates with the promoters of these genes and controls the loading of active RNA polymerase II onto these promoters. DHX33 deficiency abrogates cell cycle progression and DNA replication and leads to cell apoptosis. In zebrafish, CRISPR-mediated knockout of DHX33 results in downregulation of cyclin A2, cyclin B2, cyclin D1, cyclin E2, cdc6, cdc20, E2F1, and MCM complexes in DHX33 knockout embryos. Additionally, we found the overexpression of DHX33 in a subset of non-small-cell lung cancers and in Ras-mutated human lung cancer cell lines. Forced reduction of DHX33 in these cancer cells abolished tumor formation in vivo. Our study demonstrates for the first time that DHX33 acts as a direct transcriptional regulator to promote cell cycle progression and plays an important role in driving cell proliferation during both embryo development and tumorigenesis

Matrix converter open circuit fault behavior analysis and diagnosis with a model predictive control strategy

A novel fast and reliable open circuit fault diagnosis strategy for a Matrix Converter with a Finite Control Set Model Predictive Control strategy is proposed in this paper. Current sensors are located ahead of the clamp circuit to measure the output currents in order to improve the speed of fault diagnosis. In addition, the current recirculating path during a single open circuit switch fault condition is given in detail with the aim of contributing more expert knowledge to the fault diagnosis. The proposed fault diagnosis method is applicable over the whole range of modulation index

Preparing and characterizing Fe3O4@cellulose nanocomposites for effective isolation of cellulose-decomposing microorganisms

This study developed Fe3O4@cellulose nanocomposites by co-precipitation synthesis for bacteria capture and isolation. By surface modification with cellulose, the Fe3O4@cellulose nanocomposites have 20 nm average particle size and 3.3–24.9 emu/g saturation magnetization. Living bacteria could be captured by the Fe3O4@cellulose nanocomposites and harvested by magnetic field, with high efficiency (95.1%) and stability (>99.99%). By metabolizing cellulose and destroying the Fe3O4@cellulose@bacteria complex, cellulose-decomposing microorganisms lost the magnetism. They were therefore able to be isolated from the inert microbial community and the separation efficiency achieved over 99.2%. This research opened a door to cultivate the uncultivable cellulose-decomposing microorganisms in situ and further characterize their ecological functions in natural environment

Matrix converter open circuit fault diagnosis with asymmetric one zero SVM

An open-circuit fault detection and diagnosis strategy for a direct matrix converter is proposed in this paper. The current recirculating path during an open circuit condition is considered in detail with the aim of contributing more expert knowledge to the fault detection system for matrix converter. Simulation results are presented demonstrate the open circuit fault behavior of matrix converter. This expert knowledge is extremely important for the fault detection system to avoid false diagnosis. This work leads to the presentation of a reliable and fast fault detector for the Matrix Converter

Application of amodal segmentation for shape reconstruction and occlusion recovery in occluded tomatoes

Common object detection and image segmentation methods are unable to accurately estimate the shape of the occluded fruit. Monitoring the growth status of shaded crops in a specific environment is challenging, and certain studies related to crop harvesting and pest detection are constrained by the natural shadow conditions. Amodal segmentation can focus on the occluded part of the fruit and complete the overall shape of the fruit. We proposed a Transformer-based amodal segmentation algorithm to infer the amodal shape of occluded tomatoes. Considering the high cost of amodal annotation, we only needed modal dataset to train the model. The dataset was taken from two greenhouses on the farm and contains rich occlusion information. We introduced boundary estimation in the hourglass structured network to provide a priori information about the completion of the amodal shapes, and reconstructed the occluded objects using a GAN network (with discriminator) and GAN loss. The model in this study showed accuracy, with average pairwise accuracy of 96.07%, mean intersection-over-union (mIoU) of 94.13% and invisible mIoU of 57.79%. We also examined the quality of pseudo-amodal annotations generated by our proposed model using Mask R-CNN. Its average precision (AP) and average precision with intersection over union (IoU) 0.5 (AP50) reached 63.91%,86.91% respectively. This method accurately and rationally achieves the shape of occluded tomatoes, saving the cost of manual annotation, and is able to deal with the boundary information of occlusion while decoupling the relationship of occluded objects from each other. Future work considers how to complete the amodal segmentation task without overly relying on the occlusion order and the quality of the modal mask, thus promising applications to provide technical support for the advancement of ecological monitoring techniques and ecological cultivation

A modulated model predictive control scheme for the brushless doubly-fed induction machine

This paper proposes a modulated model predictive control (MMPC) algorithm for a brushless double-fed induction machine. The Brushless Doubly-Fed Induction Machine has some important advantages over alternative solutions for brushless machine applications. The proposed modulation technique achieves a fixed switching frequency, which gives good system performance. The paper examines the design and implementation of the modulation technique and simulation results verify the operation of the proposed modulation technique

Preparation Parameter Analysis and Optimization of Sustainable Asphalt Binder Modified by Waste Rubber and Diatomite

In this study, crumb rubber and diatomite were used to modify asphalt binder. Wet process was adopted as a preparation method, and the corresponding preparation process was determined firstly. The effects of six preparation parameters (crumb rubber concentration, diatomite concentration, shear time, shear speed, shear temperature, and storing time) on properties of modified asphalt binder (penetration at 25°C, softening point, ductility, viscosity at 135°C, elastic recovery, and penetration index) were investigated, and multiresponse optimization was conducted using the response surface method. The results revealed that softening points, viscosity, elastic recovery, and penetration index increase, while penetration and ductility decrease with the increase of crumb rubber concentration. Softening points, viscosity, and penetration index increase, while penetration and ductility decrease with the increase of diatomite concentration, which presents little influence on elastic recovery of binder. Shear temperature presented significant effects on penetration, softening point, viscosity, and ductility. Shear speed, shear time, and storing time have similar effects on binder properties because of their similar mechanism of action. Based on the model obtained from the response surface method, optimized preparation parameters corresponding to specific criteria can be determined, which possess favorable accuracy compared with experimental results