Application of Dual-Energy X-Ray Image Detection of Dangerous Goods Based on YOLOv7

X-ray security equipment is currently a more commonly used dangerous goods detection tool, due to the increasing security work tasks, the use of target detection technology to assist security personnel to carry out work has become an inevitable trend. With the development of deep learning, object detection technology is becoming more and more mature, and object detection framework based on convolutional neural networks has been widely used in industrial, medical and military fields. In order to improve the efficiency of security staff, reduce the risk of dangerous goods missed detection. Based on the data collected in X-ray security equipment, this paper uses a method of inserting dangerous goods into an empty package to balance all kinds of dangerous goods data and expand the data set. The high-low energy images are combined using the high-low energy feature fusion method. Finally, the dangerous goods target detection technology based on the YOLOv7 model is used for model training. After the introduction of the above method, the detection accuracy is improved by 6% compared with the direct use of the original data set for detection, and the speed is 93FPS, which can meet the requirements of the online security system, greatly improve the work efficiency of security personnel, and eliminate the security risks caused by missed detection.

Research on the Pedestrian Re-Identification Method Based on Local Features and Gait Energy Images

The appearance of pedestrians can vary greatly from image to image,and different pedestrians may look similar in a given image.Such similarities and variabilities in the appearance and clothing of individuals make the task of pedestrian re-identification very challenging.Here,a pedestrian re-identification method based on the fusion of local features and gait energy image(GEI)features is proposed.In this method,the human body is divided into four regions according to joint points.The color and texture of each region of the human body are extracted as local features,and GEI features of the pedestrian gait are also obtained.These features are then fused with the local and GEI features of the person.Independent distance measure learning using the cross-view quadratic discriminant analysis(XQDA)method is used to obtain the similarity of the metric function of the image pairs,and the final similarity is acquired by weight matching.Evaluation of experimental results by cumulative matching characteristic(CMC)curves reveals that,after fusion of local and GEI features,the pedestrian re-identification effect is improved compared with existing methods and is notably better than the recognition rate of pedestrian re-identification with a single feature.

Ultrahard X-ray multifunctional application beamline at the SSRF

The ultrahard X-ray multifunctional application beamline(BL12SW)is a phase-II beamline project at the Shanghai Syn-chrotron Radiation Facility.The primary X-ray techniques used at the beamline are high-energy X-ray diffraction and imaging using white and monochromatic light.The main scientific objectives of ultrahard X-ray beamlines are focused on two research areas.One is the study of the structural properties of Earth’s interior and new materials under extreme high-temperature and high-pressure conditions,and the other is the characterization of materials and processes in near-real service environments.The beamline utilizes a superconducting wiggler as the light source,with two diamond windows and SiC discs to filter out low-energy light(primarily below 30 keV)and a Cu filter assembly to control the thermal load entering the subsequent optical components.The beamline is equipped with dual monochromators.The first was a meridional bending Laue monochromator cooled by liquid nitrogen,achieving a full-energy coverage of 30-162 keV.The second was a sagittal bending Laue monochromator installed in an external building,providing a focused beam in the horizontal direction with an energy range of 60-120 keV.There were four experimental hutches:two large-volume press experimental hutches(LVP1 and LVP2)and two engineering material experimental hutches(ENG1 and ENG2).Each hutch was equipped with various near-real service conditions to satisfy different requirements.For example,LVP1 and LVP2 were equipped with a 200-ton DDIA press and a 2000-ton dual-mode(DDIA and Kawai)press,respectively.ENG1 and ENG2 provide in situ tensile,creep,and fatigue tests as well as high-temperature conditions.Since June 2023,the BL12SW has been in trial operation.It is expected to officially open to users by early 2024.

Dynamic analysis of granite rockburst based on the PIV technique

This paper describes the deep rockburst simulation system to reproduce the granite instantaneous rockburst process.Based on the PIV(Particle Image Velocimetry)technique,quantitative analysis of a rockburst,the images of tracer particle,displacement and strain fields can be obtained,and the debris trajectory described.According to the observation of on-site tests,the dynamic rockburst is actually a gas–solid high speed flow process,which is caused by the interaction of rock fragments and surrounding air.With the help of analysis on high speed video and PIV images,the granite rockburst failure process is composed of six stages of platey fragment spalling and debris ejection.Meanwhile,the elastic energy for these six stages has been calculated to study the energy variation.The results indicate that the rockburst process can be summarized as:an initiating stage,intensive developing stage and gradual decay stage.This research will be helpful for our further understanding of the rockburst mechanism.

Simulation study on reconstruction model of three-dimensional temperature distribution within visible range in furnace

This paper presents a reconstruction model of three-dimensional temperature distribution in furnace based on radiative energy images captured by charge-coupled device （CCD） cameras within the visible wavelength range. Numerical simulation case was used in this study and a zigzag eccentric temperature distribution was assumed to verify the model. Least square QR-factorization （LSQR） method was introduced to deal with reconstruction equation. It is found that the reconstructed temperature distributions in low-temperature areas had some fluctuations and high-temperature areas were reconstructed well. The whole reconstruction relative error was mainly due to errors in low-temperature areas and the relative error for highest-temperature reconstruction was quite small.

Comparison of modelled-and remote sensing-derived daily snow line altitudes at Ulugh Muztagh,northern Tibetan Plateau

The ice cap Ulugh Muztagh in the central Kunlun Shan at the northern fringe of the Tibetan Plateau is a very isolated region with arid cold conditions. No observational, meteorological or glaciological ground truth data is available. Using the Moderate-resolution Imaging Spectroradiometer(MODIS) Level 1 radiance Swath Data(MOD02QKM) with a spatial resolution of 250 m, transient snow lines during the months of July to September in 2001 to 2014 are derived. Results are used to calibrate the physical based Coupled Snowpack and Ice surface energy and Mass balance model(COSIMA). The model runs on a representative detail region of Ulugh Muztagh(UM) on a digital elevation model with the same spatial resolution as the MODIS bands. In the absence of field observations, the model is driven solely by dynamically downscaled global analysis data from the High Asia Refined analysis(HAR). We compare remote sensing derived and modelled mean regional transient snow line altitudes in the course of consecutive summer seasons in 2008 to 2010. The resulting snow line altitude(SLA) and annual equilibrium line altitude(ELA) proxy of both methods coincide very well in their interannual variability in accordance with interannual variability of climatic conditions. Since SLAs of both methods do notconsistently agree on a daily basis a usage of remote sensing derived SLAs for model calibration in the absence of field observation data is only limitedly feasible for daily analysis. ELA approximation using the highest SLA at the end of ablation period may not be applied to UM because the negative winter mass balance(MB) is not reflected in the summer SLA. The study reveals moderate negative MB for UM throughout the modelling period. The mean regional MB of UM accounts for-523±410 mm w.e. a-1 in the modelling period. Hence UM seems not to belong to the area of the ‘Karakorum anomaly' comprising a region of positive mass balances in recent years which has its centre presumably in the Western Kunlun Shan.

Relationship between Serum Uric Acid Levels and Kidney Arteriole Resistance in Patients with Type 2 Diabetes Associated with Hypertension

Objectives To investigate the relationship between serum uric acid levels and arteriole resistance detected with the color Doppler energy imaging (CDEI) and to explore the risks of impaired regulation of vascular tone by uric acid in kidneys of hypertension patients. Methods In 12 healthy control cases, 28 non-diabetic hypertension (nNIDDM +H) cases and 25 type 2 diabetic hypertension (NIDDM+H) cases, uric acid (UA) levels were measured with uricase-peroxidase method. Arteriole resistance index (RI) and pulsate index (PI) in separate sections of renal artery included MAR, SRA, IRA were detected using CDEI with 2.1~4.2 Hz Doppler transducer in kidneys. Results In comparison, UA was significantly higher in non-diabetic hyper- tension group and diabetic hypertension group than in control group (P<0.01, separately). UA levels was also significantly higher in NIDDM+H group than in nNIDDM+H, P < 0.029. RI in separate sections of renal artery was significantly higher in nNIDDM+H, or NIDDM+H group than in control group ( all P < 0.01) , and it was significantly higher in NIDDM +H than nNIDDM+H groups (P < 0.05 and P < 0.01). In nNIDDM +H and NIDDM +H groups UA levels and IRA-RI could be elevated significantly following with the impaired heart function being aggravated (χ2 = 13.028, P=0.005, χ2=13.29, P=0.004); the dosage of HCT being increased (χ2 =14.216, P=0.001, χ2 = 14.661, P=0.001); the levels of GHbA1 being excessed unnormally (P=0.000). The correlation between UA and IRA-RI in both hypertension groups were directly related, in nNIDDM+H group r=0.842, P=0.000, in NIDDM+H group, r=0.797, P=0.000. Conclusions Uric acid levels and IRA-RI in hyper-tension patients were directly related. Uric acid levels and IRA-RI could be partly dependent on the severity of heart dysfunction, diuretic dose, and serum glucose status of diabete patients in long-term. Uric acid and the xanthine oxidase metabolic pathway may contribute to impaired regulation of arteriole tone in hypertension patients.

Image reconstruction of a neutron scatter camera

Recently, Sandia Laboratories developed a neutron scatter camera to detect special nuclear materials. This camera exhibits the following advantages: high efficiency, direction discrimination, neutron-gamma discrimination ability, and wide field of view. However, using the direct projection method, the angular resolution of this camera is limited by uncertainties in the energies estimated from pulse height and time of flight measurements. In this study, we established an eight-element neutron scatter camera and conducted the experiment with a ^(252)Cf neutron source. The results show that it has an angular resolution better than 8°(1s) and a detection efficiency of approximately 2.6′10-4. Using maximum likelihood expectation maximization method, the image artifact was eliminated, and the angular resolution was improved. We proposed an average scattering angle method to estimate the scattering energy of neutrons and Compton gamma rays. As such, we can obtain a recognizable image and energy spectrum of the source with some degradation of energy and image resolutions. Finally, a newly measured light response function based on the MPD^(-4) device was used for image reconstruction. Although we did not obtain a better result than that of the standard light response function, we have observed the effects of light response function on image reconstruction.

Recent progress on single-molecule nanocatalysis based on single-molecule fluorescence microscopy

Understanding the heterogeneous catalytic properties of nanoparticles is of great significance for the development of high efficient nanocatalysts, but the intrinsic heterogeneities of nanocatalysts were always covered in traditional ensemble studies. This issue can be overcome if one can follow the catalysis of individual nanoparticles in real time. This paper mainly summarizes recent developments in single- molecule nanocatalysis at single particle level in Changchun Institute of Applied Chemistry, Chinese Academy of Sciences. These developments include the revealing of catalytic kinetics of different types （plane ＆ edge） of surface atoms on individual Pd nanocubes, the observing of in situ deactivation of indi- vidual carbon-supported Pt nanoparticles during the electrocatalytic hydrogen-oxidation reaction, and the measurement of catalytic activation energies on single nanocatalysts for both product formation process and dissociation process, etc. These studies further indicate the advantages or unique abilities of single-molecule methods in the studies of nanocatalvsis or even chemical reactions.

A partition approach for robust gait recognition based on gait template fusion

Gait recognition has significant potential for remote human identification,hut it is easily influenced by identity-unrelated factors such as clothing,carrying conditions,and view angles.Many gait templates have been presented that can effectively represent gait features.Each gait template has its advantages and can represent different prominent information.In this paper,gait template fusion is proposed to improve the classical representative gait template(such as a gait energy image)which represents incomplete information that is sensitive to changes in contour.We also present a partition method to reflect the different gait habits of different body parts of each pedestrian.The fused template is cropped into three parts(head,trunk,and leg regions)depending on the human body,and the three parts are then sent into the convolutional neural network to learn merged features.We present an extensive empirical evaluation of the CASIA-B dataset and compare the proposed method with existing ones.The results show good accuracy and robustness of the proposed method for gait recognition.