Individual mean-variance relation and stock-level investor sentiment

This research studies the effect of stock-level investor sentiment on individual stock returns’ mean-variance relation. Using unique buy and sell volume data of retail investors in Korean stock market, we find that a positive mean-variance relation is undermined among high-sentiment stocks, but holds among low-sentiment stocks. We adopt buy-sell imbalances of retail investors for individual stocks as a measure of stock-level investor sentiment. Further, our findings provide empirical evidence of a strong riskreturn trade-off among stocks with low retail concentration (e.g., large capitalization, high-priced, and growth stocks). Existing research only analyzes market-wide investor sentiment. However, we study the effect of stock-level investor sentiment on individual stock returns. Therefore, our findings suggest novel implications about the investment strategy that the stock-level investor sentiment is important when constructing portfolios based on variance

Hu.4-1BB-Fc fusion protein inhibits allergic inflammation and airway hyperresponsiveness in a murine model of asthma

Purpose4-1BB (CD 137) is a costimulatory molecule expressed on activated T-cells. Repression by 4-1BB is thought to attenuate Th2-mediated allergic reactions. The aim of this study was to investigate the effect of 4-1BB on allergic airway inflammation in a murine asthma model.MethodsBALB/c mice were sensitized to and challenged with ovalbumin (OVA). Hu.4-1BB-Fc was administered 1 day before the first OVA sensitization or 1 day after the second OVA sensitization. Following antigen challenge, airway responsiveness to methacholine was assessed and bronchoalveolar lavage (BAL) fluid was analyzed. Total immunoglobulin (Ig) E, OVA-specific IgE, IgG1, and IgG2a levels in sera were measured by enzyme-linked immunosorbent assay. Lung pathology was also evaluated.ResultsIn mice treated with Hu.4-1BB-Fc before the first OVA sensitization, there was a marked decrease in airway hyperresponsiveness, total cell count, and eosinophil count in the BAL fluid. In addition, Hu.4-1BB-Fc treatment decreased serum OVA-specific IgG1 levels and increased serum IgG2a level significantly compared with the corresponding levels in mice sensitized to and challenged with OVA. Hu.4-1BB-Fc-treated mice also showed suppressed peribronchial and perivascular inflammatory cell infiltration. In contrast, treatment with Hu.4-1BB-Fc 1 day after sensitization had no effect on airway hyperresponsiveness and showed less suppression of inflammation in lung tissue.ConclusionAdministration of Hu.4-1BB-Fc can attenuate airway inflammation and hyperreactivity in a mouse model of allergic airway inflammation. In addition, administration before sensitization may be more effective. These findings suggest that 4-1BB may be a useful therapeutic molecule against asthma

Automating Rey Complex Figure Test scoring using a deep learning-based approach: a potential large-scale screening tool for cognitive decline

Background The Rey Complex Figure Test (RCFT) has been widely used to evaluate the neurocognitive functions in various clinical groups with a broad range of ages. However, despite its usefulness, the scoring method is as complex as the figure. Such a complicated scoring system can lead to the risk of reducing the extent of agreement among raters. Although several attempts have been made to use RCFT in clinical settings in a digitalized format, little attention has been given to develop direct automatic scoring that is comparable to experienced psychologists. Therefore, we aimed to develop an artificial intelligence (AI) scoring system for RCFT using a deep learning (DL) algorithm and confirmed its validity. Methods A total of 6680 subjects were enrolled in the Gwangju Alzheimers and Related Dementia cohort registry, Korea, from January 2015 to June 2021. We obtained 20,040 scanned images using three images per subject (copy, immediate recall, and delayed recall) and scores rated by 32 experienced psychologists. We trained the automated scoring system using the DenseNet architecture. To increase the model performance, we improved the quality of training data by re-examining some images with poor results (mean absolute error (MAE) ≥ 5 [points]) and re-trained our model. Finally, we conducted an external validation with 150 images scored by five experienced psychologists. Results For fivefold cross-validation, our first model obtained MAE = 1.24 [points] and R-squared (R2 ) = 0.977. However, after evaluating and updating the model, the performance of the final model was improved (MAE = 0.95 [points], R2 = 0.986). Predicted scores among cognitively normal, mild cognitive impairment, and dementia were significantly different. For the 150 independent test sets, the MAE and R2 between AI and average scores by five human experts were 0.64 [points] and 0.994, respectively. Conclusion We concluded that there was no fundamental difference between the rating scores of experienced psychologists and those of our AI scoring system. We expect that our AI psychologist will be able to contribute to screen the early stages of Alzheimers disease pathology in medical checkup centers or large-scale community-based research institutes in a faster and cost-effective way.This research was supported by the Technology Innovation Program (20022810, Development and Demonstration of a Digital System for the evaluation of geriatric Cognitive impairment) funded By the Ministry of Trade, Industry & Energy(MOTIE, Korea), by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2020R1F1A1052932), by the Healthcare AI Convergence Research & Development Program through the National IT Industry Promotion Agency of Korea (NIPA) funded by the Ministry of Science and ICT(No.1711120216), by the KBRI basic research program through the Korea Brain Research Institute funded by the Ministry of Science and ICT (22-BR-03–05), and by the Korea National Institute of Health research project (project No. 2021-ER1007-01)

Production of Hydrogen and Carbon Black by Methane Decomposition Using DC-RF Hybrid Thermal Plasmas

A continuous production of carbon black and hydrogen has been investigated by thermal decomposition of methane using a prototype processing system of DC-RF hybrid thermal plasma, which has great advantage over other thermal sources like combustion or DC plasma torches in synthesizing new nanostructured materials by providing high-temperature environment and longer residence time for reactant gases due to its larger hot core region and lower flow velocity. Appropriate operation conditions and reactor geometries for the effective synthesis process are predicted first from the relevant theoretical bases, such as thermodynamic equilibrium calculations, two-dimensional thermal flow analysis, and chemical kinetic simulation. Based on these derived operation and design parameters, a reaction chamber and a DC-RF hybrid torch are fabricated for the processing system, which is followed by methane decomposition experiments with it. The methane injected into the processing system is converted mostly into hydrogen with a small volume fraction of acetylene, and fine carbon particles of 20-50 nm are identified from their TEM images. Material analyses of BET, DBP and XRD indicate that the synthesized carbon black has excellent properties such as large surface area, high electrical conductivity, and highly graphitized structures with good crystallization

Growth characteristics and productivity of cold-tolerant “Kowinearly” Italian ryegrass in the northern part of South Korea

The objective of this research is to evaluate differences in growth characteristics and productivity between Kowinearly and Florida 80 Italian ryegrass varieties in regions with severely cold winters. This research was carried out in Suwon (in central South Korea) and Yonchun (in northern South Korea) during the 2002 2006 growing seasons. Kowinearly is a diploid variety with green leaf colour and a semi prostrate growth habit in autumn and a semi-erect one in spring. There were differences among the varieties in terms of cold tolerance, heading date, and forage yield in Yonchun. The winter field survival of Kowinearly was 85%, while that of Florida 80 was 43%. The dry matter yield of Kowinearly in Yonchun was 9,662 kg/ha, which was 31% more than that of Florida 80. In Suwon, the heading date of Kowinearly was May 7, which was 2 days later than that of Florida 80. In Yonchun, Kowinearly’s heading date was May 12, 1 day earlier than that of Florida 80. These results indicate that Kowinearly has good cold tolerance, and that in spring, it starts growth earlier than Florida 80, because of its higher cold tolerance.Keywords: Italian ryegrass, Kowinearly, cold tolerance, new variety, forage cro

Catalpol Modulates Lifespan via DAF-16/FOXO and SKN-1/Nrf2 Activation in

Catalpol is an effective component of rehmannia root and known to possess various pharmacological properties. The present study was aimed at investigating the potential effects of catalpol on the lifespan and stress tolerance using C. elegans model system. Herein, catalpol showed potent lifespan extension of wild-type nematode under normal culture condition. In addition, survival rate of catalpol-fed nematodes was significantly elevated compared to untreated control under heat and oxidative stress but not under hyperosmolality conditions. We also found that elevated antioxidant enzyme activities and expressions of stress resistance proteins were attributed to catalpol-mediated increased stress tolerance of nematode. We further investigated whether catalpol’s longevity effect is related to aging-related factors including reproduction, food intake, and growth. Interestingly, catalpol exposure could attenuate pharyngeal pumping rate, indicating that catalpol may induce dietary restriction of nematode. Moreover, locomotory ability of aged nematode was significantly improved by catalpol treatment, while lipofuscin levels were attenuated, suggesting that catalpol may affect age-associated changes of nematode. Our mechanistic studies revealed that mek-1, daf-2, age-1, daf-16, and skn-1 are involved in catalpol-mediated longevity. These results indicate that catalpol extends lifespan and increases stress tolerance of C. elegans via DAF-16/FOXO and SKN-1/Nrf activation dependent on insulin/IGF signaling and JNK signaling