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Railway transportation has been integrated into people's lives. According to the "Notice on the release of the General Technical Specification of High-speed Railway Power Supply Safety Testing (6C System) System" issued by the National Railway Administration of China in 2012, it is required to install pantograph and slide monitoring devices in high-speed railway stations, station throats and the inlet and exit lines of high-speed railway sections, and it is required to detect the damage of the slider with high precision. It can be seen that the good condition of the pantograph slider is very important for the normal operation of the railway system. As a part of providing power for high-speed rail and subway, the pantograph must be paid attention to in railway transportation to ensure its integrity. The wear of the pantograph is mainly due to the contact power supply between the slide block and the long wire during high-speed operation, which inevitably produces scratches, resulting in depressions on the upper surface of the pantograph slide block. During long-term use, because the depression is too deep, there is a risk of fracture. Therefore, it is necessary to monitor the slider regularly and replace the slider with serious wear. At present, most of the traditional methods use automation technology or simple computer vision technology for detection, which is inefficient. Therefore, this paper introduces computer vision and deep learning technology into pantograph slide wear detection. Specifically, this paper mainly studies the wear detection of the pantograph slider based on deep learning and the main purpose is to improve the detection accuracy and improve the effect of segmentation. From a methodological perspective, this paper employs a linear array camera to enhance the quality of the data sets. Additionally, it integrates an attention mechanism to improve segmentation performance. Furthermore, this study introduces a novel image stitching method to address issues related to incomplete images, thereby providing a comprehensive solution. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Although alpha‐band activity has long been a focus of psychophysiological research, its modulation by emotional value during picture perception has only recently been studied systematically. Here, we review these studies and report that the most consistent alpha oscillatory pattern indexing emotional processing is an enhanced desynchronization (ERD) over posterior sensors when viewing emotional compared with neutral pictures. This enhanced alpha ERD is not specific to unpleasant picture content, as previously proposed for other measures of affective response, but has also been observed for pleasant stimuli. Evidence suggests that this effect is not confined to the alpha band but that it also involves a desynchronization of the lower beta frequencies (8–20 Hz). The emotional modulation of alpha ERD occurs even after massive stimulus repetition and when emotional cues serve as task‐irrelevant distractors, consistent with the hypothesis that evaluative processes are mandatory in emotional picture processing. A similar enhanced ERD has been observed for other significant cues (e.g., conditioned aversive stimuli, or in anticipation of a potential threat), suggesting that it reflects cortical excitability associated with the engagement of the motivational systems. We review studies on alpha‐band activity during picture perception, and report that the most consistent alpha oscillatory pattern indexing emotional processing is an enhanced desynchronization (ERD) over posterior sensors when viewing emotional compared with neutral pictures. Consistent with other measures of emotional reactivity, alpha ERD is modulated by highly arousing picture contents, suggesting that it reflects cortical excitability associated with the engagement of the motivational systems. [ABSTRACT FROM AUTHOR]

Railway transportation has been integrated into people’s lives. According to the “Notice on the release of the General Technical Specification of High-speed Railway Power Supply Safety Testing (6C System) System” issued by the National Railway Administration of China in 2012, it is required to install pantograph and slide monitoring devices in high-speed railway stations, station throats and the inlet and exit lines of high-speed railway sections, and it is required to detect the damage of the slider with high precision. It can be seen that the good condition of the pantograph slider is very important for the normal operation of the railway system. As a part of providing power for high-speed rail and subway, the pantograph must be paid attention to in railway transportation to ensure its integrity. The wear of the pantograph is mainly due to the contact power supply between the slide block and the long wire during high-speed operation, which inevitably produces scratches, resulting in depressions on the upper surface of the pantograph slide block. During long-term use, because the depression is too deep, there is a risk of fracture. Therefore, it is necessary to monitor the slider regularly and replace the slider with serious wear. At present, most of the traditional methods use automation technology or simple computer vision technology for detection, which is inefficient. Therefore, this paper introduces computer vision and deep learning technology into pantograph slide wear detection. Specifically, this paper mainly studies the wear detection of the pantograph slider based on deep learning and the main purpose is to improve the detection accuracy and improve the effect of segmentation. From a methodological perspective, this paper employs a linear array camera to enhance the quality of the data sets. Additionally, it integrates an attention mechanism to improve segmentation performance. Furthermore, this study introduces a novel image stitching method to address issues related to incomplete images, thereby providing a comprehensive solution.

To realize the real-time monitoring of the lodging and cavitation state of the rape blanket seedling transplanter, a real-time online monitoring system set for cavitation and lodging based on machine vision was designed. The system was mainly composed of an image acquisition module, a height sensor, and an IPC (Industrial Personal Computer). When the system starts to work, the height of the lens from the ground and the collected images are saved in real time, and the operating status of the equipment is judged according to the height of the lens from the ground, and the actual corresponding size of the image pixels is corrected. We proposed a calculation method for judging the cavitation and lodging state of the seedlings based on the comparison between the actual planting position and the theoretical planting position of the seedlings. The processing and analysis software for the cavitation and lodging monitoring system of the rape blanket transplanter was compiled, and the monitoring system was developed. The dynamic test showed that the maximum absolute error of the cavitation recognition rate was 1.23%, and the maximum absolute error of the lodging recognition rate was 3.80%. The total time consumed of a 1 m image collected in real time from the collection, image processing and stitching, to seedling status recognition of the rape blanket seedling field was about 1 s. The accuracy and system processing time of the seedling cavitation and lodging state judgment can meet the accuracy and real-time requirements of cavitation and lodging state recognition for field transfer of rape blanket seedlings. [ABSTRACT FROM AUTHOR]

Enhanced visual cortex activation by negative compared to neutral stimuli is often attributed to modulating feedback from the amygdala, but evidence from lesion studies is scarce, particularly regarding differential effects of left and right amygdala lesions. Therefore, we compared visual cortex activation by negative and neutral complex scenes in an event‐related fMRI study between 40 patients with unilateral temporal lobe resection (TLR; 19 left [lTLR], 21 right [rTLR]), including the amygdala, and 20 healthy controls. We found preserved hemodynamic emotion modulation of visual cortex in rTLR patients and only subtle reductions in lTLR patients. In contrast, rTLR patients showed a significant decrease in visual cortex activation irrespective of picture content. In line with this, healthy controls showed small emotional modulation of the left amygdala only, while their right amygdala was activated equally by negative and neutral pictures. Correlations of activation in amygdala and visual cortex were observed for both negative and neutral pictures in the controls. In both patient groups, this relationship was attenuated ipsilateral to the TLR. Our results support the notion of reentrant mechanisms between amygdala and visual cortex and suggest laterality differences in their emotion‐specificity. While right medial temporal lobe structures including the amygdala seem to influence visual processing in general, the left medial temporal lobe appears to contribute specifically to emotion processing. Still, effects of left TLR on visual emotion processing were relatively subtle. Therefore, hemodynamic correlates of visual emotion processing are likely supported by a distributed cerebral network, challenging an amygdalocentric view of emotion processing. [ABSTRACT FROM AUTHOR]

To realize the real-time monitoring of the lodging and cavitation state of the rape blanket seedling transplanter, a real-time online monitoring system set for cavitation and lodging based on machine vision was designed. The system was mainly composed of an image acquisition module, a height sensor, and an IPC (Industrial Personal Computer). When the system starts to work, the height of the lens from the ground and the collected images are saved in real time, and the operating status of the equipment is judged according to the height of the lens from the ground, and the actual corresponding size of the image pixels is corrected. We proposed a calculation method for judging the cavitation and lodging state of the seedlings based on the comparison between the actual planting position and the theoretical planting position of the seedlings. The processing and analysis software for the cavitation and lodging monitoring system of the rape blanket transplanter was compiled, and the monitoring system was developed. The dynamic test showed that the maximum absolute error of the cavitation recognition rate was 1.23%, and the maximum absolute error of the lodging recognition rate was 3.80%. The total time consumed of a 1 m image collected in real time from the collection, image processing and stitching, to seedling status recognition of the rape blanket seedling field was about 1 s. The accuracy and system processing time of the seedling cavitation and lodging state judgment can meet the accuracy and real-time requirements of cavitation and lodging state recognition for field transfer of rape blanket seedlings.

A location algorithm and a spectral extraction algorithm for a static broadband snapshot imaging spectrometer (SBSIS) are presented. The high-energy target is dispersed into a V-shaped pseudo-image (VPI) in the focal plane of the SBSIS. The location algorithm accurately calculates the target azimuth based on the one-to-one mapping relationship between the intersection position of the extension lines of the two arms of the VPI and the azimuth of the target. The spectral extraction algorithm is described to extract the characteristic spectrum of the target based on the azimuth angle of the target and the VPI. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cemented paste backfill is critical for the development of green mines, the safe exploitation of mineral resources deep underground, and the efficient disposal of solid wastes produced by mining. In this paper, the mechanism underpinning how the pumping agent works was studied. The number, area, and fractal dimension of pores in the microstructure of fresh paste were quantitatively analyzed using scanning electron microscopy (SEM), image processing, and fractal theory, and the response of flocs was investigated. The results show that floc networks disintegrated and the liquid network became the dominant structure under the action of the pumping agent, which enhanced the lubrication and promotion of multi-scale particles. In addition, the force chains became fragile and scattered, diminishing the yield stress of the paste. The pores had a more homogenized dimension and the porosity was 15.52% higher. The increase in the fractal dimension of the pores indicated that there was a higher self-similarity, in terms of microstructure, with a strengthened liquid network. The migration of floc structures contributed to the enhancement of the fluidity and rheology of the paste. This study provides insights into the effects of floc and liquid networks on the performance of paste, and it is of engineering significance in terms of realizing safe and efficient CPB operations.

In three experiments, learners used computerized learning material, which consisted of static pictures and on-screen text relating to the physiology of vision in one of two formats. The formats differed in method of access to text. Accessing text by clicking on picture components was hypothesized to produce superior learning to linear access (i.e., clicking the forward and backward buttons; Exps. 1 to 3). In addition, the investigation tested whether effects were dependent on learners' domain-specific prior knowledge (Exp. 2) and computer attitude (Exp. 3). Results indicated that pictorial access to text promotes learning about pictures (picture completion and picture labeling) but not text (verbal retention). Effects on transfer performance were inconsistent. Mode of access effects was not dependent on prior knowledge but on computer attitude. Pictorial access to text mainly fostered learning when learners had a negative attitude towards computers, whereas positive-attitude learners exhibited no learning benefits. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In a deep mine winding hoist system, the lateral oscillation of the catenary rope is an important evaluation index of orderly rope arrangement and engineering safety. Different boundary excitations will appear when the wire rope winds on symmetrical or asymmetrical grooves, which results in the different dynamic responses of the hoisting system. In this article, the vibration equations of a deep mine hoisting system are established by using the Hamilton principle, and excitation functions of different crossover zone layouts are deduced. The operation curves are introduced to conduct the experiment based on a certain experimental platform. The lateral oscillation of the catenary rope is recorded by high-speed cameras, and an effective image processing method is proposed to obtain the vibration response of a certain point in the catenary rope. The numerical simulations are compared with the experimental results to prove the vibration models derived in this article are valid. The models could provide reliable basis for the grooves type selection in deep mine hoisting. [ABSTRACT FROM AUTHOR]

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the development of information technology, educators combine the teaching contents of basic computer knowledge with the abundant materials available online, having raised the interestingness and attraction of the teaching practice of computer basic course. This paper aims to design an IEBOOK- based experimental operation platform of computer basic course which can overcome the defects of traditional experimental operation platform of inconvenience and less abundance of contents by combining IEBOOK software and an interactive display technology (including input module, picture processing module, touch screen, image addition module, and output module) of electronic courseware. The results show that the IEBOOK-based experimental operation platform effectively combine classroom teaching and after-class review, Q&A and resources exchange, and largely raise students' interest in computer basic course learning, self-management sills and communicative competence via mobile devices such as mobile phone and tablet PC. [ABSTRACT FROM AUTHOR]

The impact of anxiety-provoking stimuli on the Sustained Attention to Response Task (SART; Robertson, Manly, Andrade, Baddeley, & Yiend, 1997), and response inhibition more generally, is currently unclear. Participants completed four SARTs embedded with picture stimuli of two levels of emotion (negative or neutral) and two levels of task-relevance (predictive or non-predictive of imminent No-Go stimuli). Negative pictures had a small but detectable adverse effect on performance regardless of their task-relevance. Overall, response times and rates of commission errors were more dependent upon the predictive value (relevance) of the pictures than their attention-capturing nature (i.e., negative valence). The findings raise doubt over whether anxiety improves response inhibition, and also lend support to a response strategy perspective of SART performance, as opposed to a mindlessness or mind-wandering explanation. [ABSTRACT FROM AUTHOR]

Cognitive theories on causes of developmental dyslexia can be divided into language-specific and general accounts. While the former assume that words are special in that associated processing problems are rooted in language-related cognition (e.g., phonology) deficits, the latter propose that dyslexia is rather rooted in a general impairment of cognitive (e.g., visual and/or auditory) processing streams. In the present study, we examined to what extent dyslexia (typically characterized by poor orthographic representations) may be associated with a general deficit in visual long-term memory for details. We compared object- and detail-related visual long-term memory performance (and phonological skills) between dyslexic primary school children and IQ-, age- and gender-matched controls. The results revealed that while the overall amount of long-term memory errors was comparable between groups, dyslexic children exhibited a greater portion of detail-related errors. The results suggest that not only phonological, but also general visual resolution deficits in long-term memory may play an important role in developmental dyslexia.

This study proposed a vessel segmentation method based on Gabor features. According to the eigenvector of Hessian matrix of each pixel in the image, the vessel direction of each point was obtained to set the direction angle of Gabor filter, and the Gabor features of different vessel width at each point were extracted to establish the 6D vectors of each point. By reducing the dimension of the 6D vector, the 2D vector of each point was obtained and fused with the original image G channel. U-Net neural network was used to classify the fused image to segment vessels. The experimental results of this method in DRIVE dataset showed that this method had a good effect on the detection of small vessels and vessels at the intersection.