Precision Higgs physics at the CEPC

The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS and CMS Collaborations marked the beginning of a new era in high energy physics. The Higgs boson will be the subject of extensive studies of the ongoing LHC program. At the same time, lepton collider based Higgs factories have been proposed as a possible next step beyond the LHC, with its main goal to precisely measure the properties of the Higgs boson and probe potential new physics associated with the Higgs boson. The Circular Electron Positron Collider~(CEPC) is one of such proposed Higgs factories. The CEPC is an $e^+e^-$ circular collider proposed by and to be hosted in China. Located in a tunnel of approximately 100~km in circumference, it will operate at a center-of-mass energy of 240~GeV as the Higgs factory. In this paper, we present the first estimates on the precision of the Higgs boson property measurements achievable at the CEPC and discuss implications of these measurements.Comment: 46 pages, 37 figure

Research on High Brightness Light Source Equipment for Wind Tunnel Test

The experimental technology of high brightness light source was studied in sub-transonic supersonic wind tunnel. The elevation light source should be installed on the smooth wall of the tunnel, and the elevation camera should be installed in the safe area of the lower wall of the wind tunnel. The falling image of the missile model in the test is reflected into the elevation camera through a reflector mounted on a curved knife. The full trajectory images and aerodynamic parameters of projectiles of embedded weapons in aircraft can be obtained by the wind tunnel dual-view angle, high brightness light path system and six-degree-of-freedom image analysis system. The newly developed high brightness light source system makes the image clearer and the accuracy of model angle of attack identification less than 0.2 degrees, which is conducive to the analysis of model trajectory. The optical system is designed reasonably, so that the motion trajectory and six-degree-of-freedom data of the model can be obtained easily by using the dual-view technology. Wind tunnel tests under complex aerodynamic conditions of sub-transonic supersonic and multi-body interference have been completed, and all parameters have reached or surpassed the existing technical indicators, meeting the requirements of wind tunnel test research on ejection of embedded weapons in aircraft

A 3D Coverage Algorithm Based on Complex Surfaces for UAVs in Wireless Multimedia Sensor Networks

Following the development of wireless multimedia sensor networks (WMSN), the coverage of the sensors in the network constitutes one of the key technologies that have a significant influence on the monitoring ability, quality of service, and network lifetime. The application environment of WMSN is always a complex surface, such as a hilly surface, that would likely cause monitoring shadowing problems. In this study, a new coverage-enhancing algorithm is presented to achieve an optimal coverage ratio of WMSN based on three-dimensional (3D) complex surfaces. By aiming at the complex surface, the use of a 3D sensing model, including a sensor monitoring model and a surface map calculation algorithm, is proposed to calculate the WMSN coverage information in an accurate manner. The coverage base map allowed the efficient estimation of the degree of monitoring occlusion efficiently and improved the system’s accuracy. To meet the requests of complex 3D surface monitoring tasks for multiple sensors, we propose a modified cuckoo search algorithm that considers the features of the WMSN coverage problem and combines the survival of the fittest, dynamic discovery probability, and the self-adaptation strategy of rotation. The evaluation outcomes demonstrate that the proposed algorithm can describe the 3D covering field but also improve both the coverage quality and efficiency of the WMSN on a complex surface

Laser stripe image denoising using convolutional autoencoder

Convolutional autoencoders are making a significant impact on computer vision and signal processing communities. In this work, a convolutional autoencoder denoising method is proposed to restore the corrupted laser stripe images of the depth sensor, which directly reduces the external noise of the depth sensor so as to increase its accuracy. To reduce the amount of training data and avoid overfitting, a patch size of the laser stripe image is determined, on the basis of which a small-scale dataset called Laser Stripe Image Patch (LSIP) is created. Also, a 14-layers convolutional autoencoder is constructed to reduce the noise of the image patches, which can learn the most salient features on the LSIP dataset. Moreover, the trained convolutional autoencoder is applied to an omnidirectional structured light system. Experimental results demonstrate that the proposed method obtains useful features and superior performance both visually and quantitatively on denoising tasks, and significantly improves the accuracy of the structured light system. Keywords: Convolutional autoencoder, Deep learning, Depth perception, Image denoising, Laser stripe, Structured ligh

The unique gut microbiome of giant pandas involved in protein metabolism contributes to the host’s dietary adaption to bamboo

Abstract Background The gut microbiota of the giant panda (Ailuropoda melanoleuca), a global symbol of conservation, are believed to be involved in the host’s dietary switch to a fibrous bamboo diet. However, their exact roles are still largely unknown. Results In this study, we first comprehensively analyzed a large number of gut metagenomes giant pandas (n = 322), including 98 pandas sequenced in this study with deep sequencing (Illumina) and third-generation sequencing (nanopore). We reconstructed 408 metagenome-assembled genomes (MAGs), and 148 of which (36.27%) were near complete. The most abundant MAG was classified as Streptococcus alactolyticus. A pairwise comparison of the metagenomes and meta-transcriptomes in 14 feces revealed genes involved in carbohydrate metabolism were lower, but those involved in protein metabolism were greater in abundance and expression in giant pandas compared to those in herbivores and omnivores. Of note, S. alactolyticus was positively correlated to the KEGG modules of essential amino-acid biosynthesis. After being isolated from pandas and gavaged to mice, S. alactolyticus significantly increased the relative abundance of essential amino acids in mice jejunum. Conclusions The study highlights the unique protein metabolic profiles in the giant panda’s gut microbiome. The findings suggest that S. alactolyticus is an important player in the gut microbiota that contributes to the giant panda’s dietary adaptation by more involvement in protein rather than carbohydrate metabolism. Video Abstrac