Frontal EEG Asymmetry and Middle Line Power Difference in Discrete Emotions

A traditional model of emotion cannot explain the differences in brain activities between two discrete emotions that are similar in the valence-arousal coordinate space. The current study elicited two positive emotions (amusement and tenderness) and two negative emotions (anger and fear) that are similar in both valence and arousal dimensions to examine the differences in brain activities in these emotional states. Frontal electroencephalographic (EEG) asymmetry and midline power in three bands (theta, alpha and beta) were measured when participants watched affective film excerpts. Significant differences were detected between tenderness and amusement on FP1/FP2 theta asymmetry, F3/F4 theta and alpha asymmetry. Significant differences between anger and fear on FP1/FP2 theta asymmetry and F3/F4 alpha asymmetry were also observed. For midline power, midline theta power could distinguish two negative emotions, while midline alpha and beta power could effectively differentiate two positive emotions. Liking and dominance were also related to EEG features. Stepwise multiple linear regression results revealed that frontal alpha and theta asymmetry could predict the subjective feelings of two positive and two negative emotions in different patterns. The binary classification accuracy, which used EEG frontal asymmetry and midline power as features and support vector machine (SVM) as classifiers, was as high as 64.52% for tenderness and amusement and 78.79% for anger and fear. The classification accuracy was improved after adding these features to other features extracted across the scalp. These findings indicate that frontal EEG asymmetry and midline power might have the potential to recognize discrete emotions that are similar in the valence-arousal coordinate space

Ecological footprint (EF): An expanded role in calculating resource productivity (RP) using China and the G20 member countries as examples

AbstractAs resources become scarcer measuring resource productivity (RP) is more important. Quantifying the value of natural resources is challenging but the ecological footprint (EF) concept provides one method of uniformly describing a variety of natural resources. Current assessments of RP mainly revolve around output efficiency of resources, namely the ratio of GDP to natural resource usage.This paper develops a new method of calculating the RP by using the EF as an indicator of the natural resource input and gross domestic product (GDP) as the output in the equation of RP=GDP/EF. A regression analysis is carried out using GDP per capita and RP of China from 1997 to 2011, and a comparative analysis with the members of the G20 countries according to their RP and per capita GDP in 2008. The results indicate that RP correlates with the per capita GDP, showing that RP is a valid indicator which can be used to measure a country’s level of economic development

The estimation of vehicle speed and stopping distance by pedestrians crossing streets in a naturalistic traffic environment

The ability to estimate vehicle speed and stopping distance accurately is important for pedestrians to make safe road crossing decisions. In this study, a field experiment in a naturalistic traffic environment was conducted to measure pedestrians&#39; estimation of vehicle speed and stopping distance when they are crossing streets. Forty-four participants (18-45 years old) reported their estimation on 1043 vehicles, and the corresponding actual vehicle speed and stopping distance were recorded. In the speed estimation task, pedestrians&#39; performances change in different actual speed levels and different weather conditions. In sunny conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 40 km/h but were able to accurately estimate speeds that were lower than 40 km/h. In rainy conditions, pedestrians tended to underestimate actual vehicle speeds that were higher than 45 km/h but were able to accurately estimate speeds ranging from 35 km/h to 45 km/h. In stopping distance estimation task, the accurate estimation interval ranged from 60 km/h to 65 km/h, and pedestrians generally underestimated the stopping distance when vehicles were travelling over 65 km/h. The results show that pedestrians have accurate estimation intervals that vary by weather conditions. When the speed of the oncoming vehicle exceeded the upper bound of the accurate interval, pedestrians were more likely to underestimate the vehicle speed, increasing their risk of incorrectly deciding to cross when it is not safe to do so. (C) 2015 Elsevier Ltd. All rights reserved.</p

MGMAE: Motion Guided Masking for Video Masked Autoencoding

Masked autoencoding has shown excellent performance on self-supervised video representation learning. Temporal redundancy has led to a high masking ratio and customized masking strategy in VideoMAE. In this paper, we aim to further improve the performance of video masked autoencoding by introducing a motion guided masking strategy. Our key insight is that motion is a general and unique prior in video, which should be taken into account during masked pre-training. Our motion guided masking explicitly incorporates motion information to build temporal consistent masking volume. Based on this masking volume, we can track the unmasked tokens in time and sample a set of temporal consistent cubes from videos. These temporal aligned unmasked tokens will further relieve the information leakage issue in time and encourage the MGMAE to learn more useful structure information. We implement our MGMAE with an online efficient optical flow estimator and backward masking map warping strategy. We perform experiments on the datasets of Something-Something V2 and Kinetics-400, demonstrating the superior performance of our MGMAE to the original VideoMAE. In addition, we provide the visualization analysis to illustrate that our MGMAE can sample temporal consistent cubes in a motion-adaptive manner for more effective video pre-training.Comment: ICCV 2023 camera-ready versio

Serum miR-377 Can Be Used as a Diagnostic Marker for Acute Coronary Syndrome and Can Regulate Proinflammatory Factors and Endothelial Injury Markers

The diagnostic value of microRNA-377 (miR-377) in patients with acute coronary syndrome (ACS) and explored miR-377’s potential mechanisms. We performed an qRT-PCR to assess serum miR-377 levels in ACS patients and coronary artery ligation rat models. The diagnostic value of miR-377 was evaluated by determining the ROC curve. An ELISA assay was conducted to detect the model rat endothelial damage markers von Willebrand factor (vWF) and heart-type fatty acid binding protein (H-FABP), and proinflammatory cytokines TNF-α, IL-6, and IL-1β. The serum miR-377 level was elevated in the ACS patients and significantly increased in the ACS rats. MiR-377 has a high diagnostic value in ACS patients, with a 0.844 ROC, 76.47% specificity, and 87.10% sensitivity. MiR-377 was positively correlated with the expressions of vWF, H-FABP, cTnI, TNF-α, IL-6, and IL-1β. In ACS rats, reducing the expression of miR-377 significantly inhibited the increases in vWF, H-FABP, TNF-α, IL-6, and IL-1β. An elevated miR-377 level can be used as a diagnostic marker in patients with ACS. A reduction of miR-377 may alleviate ACS by improving myocardial damage such as endothelial injury and the inflammatory response

A computational cognition model of perception, memory, and judgment

The mechanism of human cognition and its computability provide an important theoretical foundation to intelligent computation of visual media. This paper focuses on the intelligent processing of massive data of visual media and its corresponding processes of perception, memory, and judgment in cognition. In particular, both the human cognitive mechanism and cognitive computability of visual media are investigated in this paper at the following three levels: neurophysiology, cognitive psychology, and computational modeling. A computational cognition model of Perception, Memory, and Judgment (PMJ model for short) is proposed, which consists of three stages and three pathways by integrating the cognitive mechanism and computability aspects in a unified framework. Finally, this paper illustrates the applications of the proposed PMJ model in five visual media research areas. As demonstrated by these applications, the PMJ model sheds some light on the intelligent processing of visual media, and it would be innovative for researchers to apply human cognitive mechanism to computer science.</p

Effects of 1.84 GHz radio-frequency electromagnetic field on sperm maturation in epididymis microenvironment

In recent years, intense interest has been drawn to the effects of radio-frequency electromagnetic field (RF-EMF) on reproduction. To explore the effects of RF-EMF on sperm maturation in epididymis microenvironment, 24 male Sprague Dawley (SD) rats were randomly divided into three exposed groups (SAR 1, 2 and 4 W/kg) and one sham group. The rats in exposed group were exposed to 1.84 GHz RFEMF for 5 days (1 h/day). After that, the rats were anaesthetized immediately and epididymis were taken out. Half of them were fixed in 4% formalin and the others were placed in tissue homogenate. The morphology of sperm and microstructure of epididymis were observed under microscope after hematoxylin eosin (HE) staining. Expression of Bin1b protein was detected by immunohistochemistry; the level of glutathione (GSH) and enzymes including superoxide dismutase (SOD), acid  phosphatase (ACP), alkaline phosphatase (ALP) and disaccharidase were determined by commercial kits. It was found that,  compared with sham group, the sperm morphology and microstructure of epididymis did not change obviously; similarly, there was no significant change in Bin1b protein expression and the levels of GSH, SOD, ACP and ALP in exposure group. These results  suggest that 1.84 GHz RF-EMF under this experimental condition could not affect the sperm maturation in epididymis  microenvironment of SD rats.Keywords: 1.84 GHz, radio-frequency electromagnetic field (RF-EMF), epididymis, sperm maturation, Bin1