Which word makes you feel more negative? “Nausea” or “corpse”

In the field of emotional language research, emotional words have always been the main stimulus for researchers to explore the cognitive mechanisms underlying emotional language processing. In previous studies, most of the emotion-label words (e.g., nausea) and emotion-laden words (e.g., corpse) were collectively referred to as emotion words without distinguishing between the two categories. The main purpose of this study was to explore the emotion effect and cognitive processing mechanism between emotion-label word and emotion-laden word, including two experiments. In experiment 1, An Affective Simon Task was administered to explore the emotion effects of two valence (positive and negative) emotion-label words and emotion-laden words. The results showed that the emotion-label words, regardless of the valence, induced significant Simon effects, while the emotion-laden words only showed Simon effects on the negative valence, which initially proved that the two types of words had different emotional effect. Experiment 2 further explored the cognitive processing mechanism of emotion-label words and emotion-laden words by employing event-related potential (ERP) technology. The ERP data revealed that (1) regardless of the valence, emotion-label words were elicited larger P100 than emotion-laden words and mainly appear in the left posterior sites, (2) regardless of the valence, emotion-laden words elicited larger N170 than emotion-label words, and there was no hemispheric difference, (3) regardless of the valence, emotion-label word and emotion-laden words elicited in similar Late Positivity Complex (LPC) in central sites. According to the current findings, emotion-label words and emotion-laden words had significant differences in emotion effect and cognitive processing. The emotional information in emotion-label words was perceived earlier, while the emotional information in emotion-laden words had stronger physiological activation.</p

PO-190 Exercise Training Protects Against Cardiac Pathological Remodeling in Myocardial Infarction rats via Improving Mitochondrial Biogenesis

Objective &nbsp;Growing evidence suggests that exercise training reverses cardiac pathological remodeling and cardiac dysfunction during myocardial infarction (MI), but the underlying mechanisms have not been fully understood. In this study, we investigated the impact of exercise training on cardiac function, myocardial fibrosis, apoptosis, oxidative stress and mitochondrial biogenesis. Methods Sprague Dawley rats were subjected to MI by permanent ligation of the left anterior descending (LAD) coronary artery or Sham operation. Rats with MI were randomly assigned to sedentary MI group (MI) and MI with exercise training group (MI+EX), and compared to sham-operated group (Sham). Haemodynamics and Masson staining were conducted to evaluate the effect of exercise training on cardiac function and myocardial fibrosis. Myocardial apoptosis, oxidative stress, mitochondrial biogenesis and molecular signaling mechanism were analyzed. Results &nbsp;Exercise training significantly improves cardiac function and mitigates the MI-induced cardiac pathological remodeling. Meanwhile, Exercise training significantly attenuates MI-induced apoptosis, oxidative stress and mitochondrial biogenesis. In addition, activation of PI3K pathway following MI is further induced by exercise training. Conclusions &nbsp;Exercise training protects against MI-induced cardiac dysfunction and pathological remodeling through preventing myocardial apoptosis and oxidative stress, and enhancing mitochondrial biogenesis

Effects of Design Parameters on Performance of Brushless Electrically Excited Synchronous Reluctance Generator

Permanent magnet synchronous generators, doubly fed induction generators, and traditional electrically excited synchronous generators are widely used for wind power applications, especially large offshore installations. In order to eliminate brushes and slip rings for improved reliability and maintenance-free operation, as well as to avoid costly permanent magnets, a novel brushless electrically excited synchronous reluctance generator having many outstanding advantages has been proposed in this paper. The fundamental operating principles, finite element analysis design studies and performance optimization aspects have been thoroughly investigated by simulations and experimentally under different loading conditions. The effects of different pole combinations and rotor dimensions on the magnetic coupling capacity of this machine have been specifically addressed and fully verified by off-line testing of the 6/2 pole and 8/4 pole prototypes with magnetic barrier reluctance rotor and a new hybrid cage rotor offering superior performance

Understanding Indigenous People’s Information Practices and Internet Use: A Ngarrindjeri Perspective

Little is known about indigenous people’s interactions with the Internet as well as their attitudes, values, and skills in using the Internet and information and communication technologies to retain their knowledge. We present the preliminary results of the research undertaken with Ngarrindjeri people living from the Lower Murray River Lakes and the Coorong areas in South Australia, and then review the implications of these findings for designing interventions. Twenty-one Ngarrindjeri volunteers participated in the questionnaires, interviews and field observation. The results show that, following family members, the Internet was considered to be the second most important source for obtaining various sorts of information. Though having types of hesitation and cultural cautions, the indigenous participants embraced the Internet and online resources with great enthusiasm. The findings suggest that it is critical to adapt Internet technology to incorporate indigenous cultures including their information and social practices when we design and deliver information products and services for indigenous people

Role of leisure sedentary behavior on type 2 diabetes and glycemic homeostasis: a Mendelian randomization analysis

PurposeUtilize Mendelian randomization (MR) to examine the impact of leisure sedentary behavior (LSB) on the prevalence of type 2 diabetes mellitus (T2D) and glycemic homeostasis impairment, as well as to identify potential mediating pathways involved in these associations.MethodsWe chose genetic variants linked to LSB from a large genome-wide association study (GWAS) to use as instrumental variables (IVs). Then, we used a two-sample MR study to investigate the link between LSB and T2D and glycemic homeostasis. Multivariate MR (MVMR) and mediation analysis were also used to look at possible mediating paths.ResultsMR analysis showed a genetical link between leisure TV watching and T2D (OR 1.64, 95% CI 1.39-1.93, P&lt; 0.001) and impaired Glycemic Homeostasis, while leisure computer use seemed to protect against T2D prevalence (OR 0.65, 95% CI 0.50-0.84, P&lt; 0.001). It was found that leisure TV watching increases the risk of T2D through higher BMI (mediation effect 0.23, 95% CI 0.11-0.35, P&lt; 0.001), higher triglycerides (mediation effect 0.07, 95% CI 0.04-0.11, P&lt; 0.001), and less education (mediation effect 0.16, 95% CI 0.08-0.24, P&lt; 0.001). Sensitivity and heterogeneity analyses further substantiated the robustness of these findings. Reverse MR analysis did not yield significant results.ConclusionThis study shows LSB is linked to a higher rate of T2D and impaired glycemic homeostasis through obesity, lipid metabolism disorders, and reduced educational attainment

Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning

In the field of quantitative trading, it is common practice to transform raw historical stock data into indicative signals for the market trend. Such signals are called alpha factors. Alphas in formula forms are more interpretable and thus favored by practitioners concerned with risk. In practice, a set of formulaic alphas is often used together for better modeling precision, so we need to find synergistic formulaic alpha sets that work well together. However, most traditional alpha generators mine alphas one by one separately, overlooking the fact that the alphas would be combined later. In this paper, we propose a new alpha-mining framework that prioritizes mining a synergistic set of alphas, i.e., it directly uses the performance of the downstream combination model to optimize the alpha generator. Our framework also leverages the strong exploratory capabilities of reinforcement learning~(RL) to better explore the vast search space of formulaic alphas. The contribution to the combination models' performance is assigned to be the return used in the RL process, driving the alpha generator to find better alphas that improve upon the current set. Experimental evaluations on real-world stock market data demonstrate both the effectiveness and the efficiency of our framework for stock trend forecasting. The investment simulation results show that our framework is able to achieve higher returns compared to previous approaches.Comment: Accepted by KDD '23, ADS trac

BiOBr nanoflakes with strong Kerr nonlinearity towards hybrid integrated photonic devices

© 2020 SPIE. As a new group of advanced 2D layered materials, bismuth oxyhalides, i.e., BiOX (X = Cl, Br, I), have recently become of great interest. In this work, we characterize the third-order optical nonlinearities of BiOBr, an important member of the BiOX family. The nonlinear absorption and Kerr nonlinearity of BiOBr nanoflakes at both 800 nm and 1550 nm are characterized via the Z-Scan technique. Experimental results show that BiOBr nanoflakes exhibit a large nonlinear absorption coefficient β ∼ 10-7 m/W as well as a large Kerr coefficient n2 ∼ 10-14 m2/W. We also note that the n2 of BiOBr reverses sign from negative to positive as the wavelength is changed from 800 nm to 1550 nm. We further characterize the thickness-dependent nonlinear optical properties of BiOBr nanoflakes, finding that the magnitudes of β and n2 increase with decreasing thickness of the BiOBr nanoflakes. Finally, we integrate BiOBr nanoflakes into silicon integrated waveguides and measure their insertion loss, with the extracted waveguide propagation loss showing good agreement with mode simulations based on ellipsometry measurements. These results confirm the strong potential of BiOBr as a promising nonlinear optical material for high-performance hybrid integrated photonic devices