Stroke Extraction of Chinese Character Based on Deep Structure Deformable Image Registration

Stroke extraction of Chinese characters plays an important role in the field of character recognition and generation. The most existing character stroke extraction methods focus on image morphological features. These methods usually lead to errors of cross strokes extraction and stroke matching due to rarely using stroke semantics and prior information. In this paper, we propose a deep learning-based character stroke extraction method that takes semantic features and prior information of strokes into consideration. This method consists of three parts: image registration-based stroke registration that establishes the rough registration of the reference strokes and the target as prior information; image semantic segmentation-based stroke segmentation that preliminarily separates target strokes into seven categories; and high-precision extraction of single strokes. In the stroke registration, we propose a structure deformable image registration network to achieve structure-deformable transformation while maintaining the stable morphology of single strokes for character images with complex structures. In order to verify the effectiveness of the method, we construct two datasets respectively for calligraphy characters and regular handwriting characters. The experimental results show that our method strongly outperforms the baselines. Code is available at https://github.com/MengLi-l1/StrokeExtraction.Comment: 10 pages, 8 figures, published to AAAI-23 (oral

Caffeine Effect on Cognitive Function during a Stroop Task: fNIRS Study

Acting as a brain stimulant, coffee resulted in heightening alertness, keeping arousal, improving executive speed, maintaining vigilance, and promoting memory, which are associated with attention, mood, and cognitive function. Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical method to monitor brain activity by measuring the absorption of the near-infrared light through the intact skull. This study is aimed at acquiring brain activation during executing task performance. The aim is to explore the effect of coffee on cognitive function by the fNIRS neuroimaging method, particularly on the prefrontal cortex regions. The behavioral experimental results on 31 healthy subjects with a Stroop task indicate that coffee can easily and effectively modulate the execute task performance by feedback information of the response time and accuracy rate. The findings of fNIRS showed that apparent hemodynamic changes were detected in the bilateral VLPFC regions and the brain activation regions varied with different coffee conditions

Vibration Response of the Interfaces in Multi-Layer Combined Coal and Rock Mass under Impact Load

The stress wave generated by impact or dynamic load will produce significant reflection and transmission at the rock coal or rock interface during the propagation process. This will produce dynamic effects such as dynamic tensile, stress superposition and mutation. These dynamic effects will lead to obvious vibration at the interfaces, which is a key factor leading to dynamic damage and the failure of coal and rock mass. In the process of underground engineering excavation, the dynamic damage of a series of layered rock masses is one of the important factors causing geological disasters. Based on the two–dimensional similar material simulation experiment, the coal and rock mass combined of five layers of fine sandstone, medium sandstone, coal, coarse sandstone and mudstone was taken as the research object, and single and multi-point excitation (synchronous/step-by-step) were used to test the time–history vibration curves of rock–coal and rock–rock interfaces under impact load. It was concluded that the change of extreme value of vibration amplitude presented two stages: first increase, and then attenuation. Most of them required 2.25 cycles to reach the peak value, and the dynamic attenuation of amplitude conformed to the law of exponential. Based on Fast Fourier transform (FFT), the spectrum structures of the amplitude–frequency of interface vibration were studied, and the two predominant frequencies were 48.9~53.7 Hz and 92.4 Hz, respectively. Based on the Hilbert-Huang transform and energy equation, 5~7 vibration modes (IMF) were obtained by decomposing the time–history curves. The three modes, IMF1, IMF2, and IMF3, contained high energy and were effective vibration modes. IMF2 accounted for the highest proportion and was the main vibration mode whose predominant frequencies were concentrated in 45.6~50.2 Hz. Therefore, IMF2 played a decisive role in the whole vibration process and had an important impact on the dynamic response, damage and failure of coal and rock mass. In real conditions, the actual predominant frequencies can be converted according to the size and mechanical properties of the coal and rock mass, and the vibration response characteristics of the interfaces between coal and rock mass under impact load were preliminarily revealed. This study can provide reference for monitoring and early warning of coal and rock dynamic disasters, prevention and control of coal and gas outburst and technical development

Vibration Response of the Interfaces in Multi-Layer Combined Coal and Rock Mass under Impact Load

The stress wave generated by impact or dynamic load will produce significant reflection and transmission at the rock coal or rock interface during the propagation process. This will produce dynamic effects such as dynamic tensile, stress superposition and mutation. These dynamic effects will lead to obvious vibration at the interfaces, which is a key factor leading to dynamic damage and the failure of coal and rock mass. In the process of underground engineering excavation, the dynamic damage of a series of layered rock masses is one of the important factors causing geological disasters. Based on the two–dimensional similar material simulation experiment, the coal and rock mass combined of five layers of fine sandstone, medium sandstone, coal, coarse sandstone and mudstone was taken as the research object, and single and multi-point excitation (synchronous/step-by-step) were used to test the time–history vibration curves of rock–coal and rock–rock interfaces under impact load. It was concluded that the change of extreme value of vibration amplitude presented two stages: first increase, and then attenuation. Most of them required 2.25 cycles to reach the peak value, and the dynamic attenuation of amplitude conformed to the law of exponential. Based on Fast Fourier transform (FFT), the spectrum structures of the amplitude–frequency of interface vibration were studied, and the two predominant frequencies were 48.9~53.7 Hz and 92.4 Hz, respectively. Based on the Hilbert-Huang transform and energy equation, 5~7 vibration modes (IMF) were obtained by decomposing the time–history curves. The three modes, IMF1, IMF2, and IMF3, contained high energy and were effective vibration modes. IMF2 accounted for the highest proportion and was the main vibration mode whose predominant frequencies were concentrated in 45.6~50.2 Hz. Therefore, IMF2 played a decisive role in the whole vibration process and had an important impact on the dynamic response, damage and failure of coal and rock mass. In real conditions, the actual predominant frequencies can be converted according to the size and mechanical properties of the coal and rock mass, and the vibration response characteristics of the interfaces between coal and rock mass under impact load were preliminarily revealed. This study can provide reference for monitoring and early warning of coal and rock dynamic disasters, prevention and control of coal and gas outburst and technical development

Aero-Engine Remaining Useful Life Estimation Based on CAE-TCN Neural Networks

With the rapid growth of the aviation fields, the remaining useful life (RUL) estimation of aero-engine has become the focus of the industry. Due to the shortage of existing prediction methods, life prediction is stuck in a bottleneck. Aiming at the low efficiency of traditional estimation algorithms, a more efficient neural network is proposed by using Convolutional Neural Networks (CNN) to replace Long-Short Term Memory (LSTM). Firstly, multi-sensor degenerate information fusion coding is realized with the convolutional autoencoder (CAE). Then, the temporal convolutional network (TCN) is applied to achieve efficient prediction with the obtained degradation code. It does not depend on the iteration along time, but learning the causality through a mask. Moreover, the data processing is improved to further improve the application efficiency of the algorithm. ExtraTreesClassifier is applied to recognize when the failure first develops. This step can not only assist labelling, but also realize feature filtering combined with tree model interpretation. For multiple operation conditions, new features are clustered by K-means++ to encode historical condition information. Finally, an experiment is carried out to evaluate the effectiveness on the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) datasets provided by the National Aeronautics and Space Administration (NASA). The results show that the proposed algorithm can ensure high-precision prediction and effectively improve the efficiency

Cellular Phenotypic Transformation in Heart Failure Caused by Coronary Heart Disease and Dilated Cardiomyopathy: Delineating at Single-Cell Level

Heart failure (HF) is known as the final manifestation of cardiovascular diseases. Although cellular heterogeneity of the heart is well understood, the phenotypic transformation of cardiac cells in progress of HF remains obscure. This study aimed to analyze phenotypic transformation of cardiac cells in HF through human single-cell RNA transcriptome profile. Here, phenotypic transformation of cardiomyocytes (CMs), endothelial cells (ECs), and fibroblasts was identified by data analysis and animal experiments. Abnormal myosin subunits including the decrease in Myosin Heavy Chain 6, Myosin Light Chain 7 and the increase in Myosin Heavy Chain 7 were found in CMs. Two disease phenotypes of ECs named inflammatory ECs and muscularized ECs were identified. In addition, myofibroblast was increased in HF and highly associated with abnormal extracellular matrix. Our study proposed an integrated map of phenotypic transformation of cardiac cells and highlighted the intercellular communication in HF. This detailed definition of cellular transformation will facilitate cell-based mapping of novel interventional targets for the treatment of HF

Infrared thermography‐based diagnostics on power equipment: State‐of‐the‐art

Abstract As a non‐contact temperature distribution measurement method, infrared thermography (IRT) has emerged as an indispensable tool in condition monitoring and fault diagnosis of electrical equipment based on the absolute and relative temperature values. Manual fault inspection, as an expert‐experiences based evaluation method, has formed a mature technical scheme with a large number of application cases. However, the efficiency and accuracy of manual fault inspection are being challenged by the rapid growth in the number of equipment in power grid. The situation is improving with the advanced of image processing technique. Machine‐assisted fault diagnosis provides a novel method to assist human beings to complete fault diagnosis under the intervention of human prior knowledge. However, the limitations of infrared images bring challenges to image analysis processing especially target detection. In pursuit of automatic fault diagnosis, deep learning algorithms are introduced to achieve target detection in the complex environment. This study reviews the development of IRT‐based diagnostics beginning with the general procedures, objects, and limitations of IRT‐based fault inspection, and then gives an insight into the popular machine‐assisted fault diagnosis as well as image‐based intelligent fault identification. In addition, the future recommendations of IRT are also provided from construction of intelligent infrared detection system, establishment of an open and shared infrared image database and comprehensive utilization of joint visualization diagnosis technology

Maize/peanut intercropping increases photosynthetic characteristics, 13C-photosynthate distribution, and grain yield of summer maize

Intercropping is used widely by smallholder farmers in developing countries to increase land productivity and profitability. We conducted a maize/peanut intercropping experiment in the 2015 and 2016 growing seasons in Shandong, China. Treatments included sole maize (SM), sole peanut (SP), and an intercrop consisting of four rows of maize and six rows of peanut (IM and IP). The results showed that the intercropping system had yield advantages based on the land equivalent ratio (LER) values of 1.15 and 1.16 in the two years, respectively. Averaged over the two years, the yield of maize in the intercropping was increased by 61.05% compared to that in SM, while the pod yield of peanut was decreased by 31.80% compared to SP. Maize was the superior competitor when intercropped with peanut, and its productivity dominated the yield of the intercropping system in our study. The increased yield was due to a higher kernel number per ear (KNE). Intercropping increased the light transmission ratio (LTR) of the ear layer in the maize canopy, the active photosynthetic duration (APD), and the harvest index (HI) compared to SM. In addition, intercropping promoted the ratio of dry matter accumulation after silking and the distribution of 13C-photosynthates to grain compared to SM. In conclusion, maize/peanut intercropping demonstrated the potential to improve the light condition of maize, achieving enhanced photosynthetic characteristics that improved female spike differentiation, reduced barrenness, and increased KNE. Moreover, dry matter accumulation and 13C-photosynthates distribution to grain of intercropped maize were improved, and a higher grain yield was ultimately obtained

Response of Leaf Senescence, Photosynthetic Characteristics, and Yield of Summer Maize to Controlled-Release Urea-Based Application Depth

To explore the response of summer maize leaf senescence, photosynthetic characteristics, and yield to the depth of one-time base application of controlled-release urea, which provides a theoretical basis for the light and simplified production of summer maize. Seven treatments were set up with Zhengdan 958 as the material under field conditions, including no nitrogen fertilizer (CK), surface spreading (DP0), furrow application depth of 5 cm (DP5), 10 cm (DP10), 15 cm (DP15), 20 cm (DP20), 25 cm (DP25). The results showed that under the same nitrogen application rate, there are significant differences in the effects of summer maize leaf senescence and photosynthetic characteristics with the increase of fertilization depth, and DP10 and DP15 have the best effects. The LAI of DP10 and DP15 increased by 5.1% and 5.5% compared to DP0 at tasseling stage, and chlorophyll content increased by 6.8% and 7.3% in 10 days after tasseling. Compared with DP0, superoxide dismutase (SOD) increased by 13.1% and 10.5%, the content of soluble protein increased significantly, while the content of malondialdehyde (MDA) decreased by 9.8% and 10.8%, respectively. In addition, Pn and Gs of the ear-leaf significantly increased by 13.9%, 16.5%, and 26.1% and 31.9% at tasseling stage, respectively, over DP0, while Ci decreased by 22.3% and 26.4%, respectively; meanwhile, the photochemical quenching (qP) and quantum yield (ΦPSII) of the reaction center of photosystem II (PSII) of the ear-leaf were significantly improved, the non-photochemical quenching (NPQ) was significantly reduced. The yield of DP10 and DP15 heightened significantly; two-year average value increased by 5.7% and 6.0% compared with DP0; the kernels per spike and 1000-kernels weight increased by 4.8%, 5.2%, and 4.1%, 5.2%, respectively. Comprehensive analysis of LAI, chlorophyll content, various protective enzyme activities and MDA, soluble protein content showed that 10–15 cm is the appropriate fertilization depth when the nitrogen application rate of controlled-release urea is 225 kg N per hectare. In consequence, optimizing fertilization depth of controlled-release urea as a simplified fertilization mode could improve the nitrogen utilization efficiency and obtain higher yield in summer maize, which provides technical support for large-scale application of controlled-release urea

Response of Leaf Senescence, Photosynthetic Characteristics, and Yield of Summer Maize to Controlled-Release Urea-Based Application Depth

To explore the response of summer maize leaf senescence, photosynthetic characteristics, and yield to the depth of one-time base application of controlled-release urea, which provides a theoretical basis for the light and simplified production of summer maize. Seven treatments were set up with Zhengdan 958 as the material under field conditions, including no nitrogen fertilizer (CK), surface spreading (DP0), furrow application depth of 5 cm (DP5), 10 cm (DP10), 15 cm (DP15), 20 cm (DP20), 25 cm (DP25). The results showed that under the same nitrogen application rate, there are significant differences in the effects of summer maize leaf senescence and photosynthetic characteristics with the increase of fertilization depth, and DP10 and DP15 have the best effects. The LAI of DP10 and DP15 increased by 5.1% and 5.5% compared to DP0 at tasseling stage, and chlorophyll content increased by 6.8% and 7.3% in 10 days after tasseling. Compared with DP0, superoxide dismutase (SOD) increased by 13.1% and 10.5%, the content of soluble protein increased significantly, while the content of malondialdehyde (MDA) decreased by 9.8% and 10.8%, respectively. In addition, Pn and Gs of the ear-leaf significantly increased by 13.9%, 16.5%, and 26.1% and 31.9% at tasseling stage, respectively, over DP0, while Ci decreased by 22.3% and 26.4%, respectively; meanwhile, the photochemical quenching (qP) and quantum yield (ΦPSII) of the reaction center of photosystem II (PSII) of the ear-leaf were significantly improved, the non-photochemical quenching (NPQ) was significantly reduced. The yield of DP10 and DP15 heightened significantly; two-year average value increased by 5.7% and 6.0% compared with DP0; the kernels per spike and 1000-kernels weight increased by 4.8%, 5.2%, and 4.1%, 5.2%, respectively. Comprehensive analysis of LAI, chlorophyll content, various protective enzyme activities and MDA, soluble protein content showed that 10–15 cm is the appropriate fertilization depth when the nitrogen application rate of controlled-release urea is 225 kg N per hectare. In consequence, optimizing fertilization depth of controlled-release urea as a simplified fertilization mode could improve the nitrogen utilization efficiency and obtain higher yield in summer maize, which provides technical support for large-scale application of controlled-release urea