We examine the effect of media coverage on firm innovation. Using a comprehensive sample of corporate news coverage and patenting over the period from 2000 to 2012, we find a negative relation ...between media coverage and firm innovation. We further document the two offsetting economic mechanisms underlying the impact of media coverage on innovation: the media’s role of short-term pressure on managers relates negatively to innovation, while its role of mitigating financial constraints is positively associated with innovation. Our findings provide new insights into the effect of news coverage on firms’ long-term growth.
Political uncertainty leads to greater information asymmetry among contracting parties to the firm, resulting in an increased demand for accounting conservatism. Exploiting the exogenous variation in ...political uncertainty induced by the U.S. gubernatorial election cycle over the period 1963-2016, we find that the asymmetric timeliness of news recognition increases with political uncertainty. Our political uncertainty hypothesis operates through the contracting demand channel. Accordingly, we find that the political uncertainty effect is more pronounced for firms in states with lower electoral participation, for firms with greater industry exposures to contracting needs, for firms with higher leverage and lower managerial ownership, and for firms with stronger internal corporate governance mechanisms.
Most myoelectric prosthetic hands use a fixed pattern recognition model to identify the user's hand motion commands. Since surface electromyogram (sEMG) characteristics vary with time, it is ...difficult to employ the fixed pattern recognition model in identifying hand motion commands stably for a long period of time. In order to adapt to the gradual changes in sEMG characteristics, we utilized incremental learning based on the wavelet neural network (WNN) ensemble, and used negative correlation learning (NCL) to train it. To verify the effect of the proposed method, a group of subjects executed six hand motions in a continual experiment for more than 2 h. Compared with the fixed pattern recognition model, the classification accuracy rate of incremental learning with nonintegration becomes substantially improved. In addition, the results of the WNN ensemble with the fixed-size mode are more stable than those of the WNN ensemble with the growth mode. The experimental results demonstrate that our method can recognize the gradual changes in sEMG characteristics stably. Using the proposed method, the average accuracy rate is found to be 92.17%, even after a long period of time. Moreover, since the update time is short, the proposed method can be successfully applied in myoelectric prosthetic hands.
Surface electromyogram (sEMG) signals can be applied in medical, rehabilitation, robotic, and industrial fields. As a typical application, a myoelectric prosthetic hand is controlled by the sEMG ...signals of the amputee's residual muscles. To improve the dexterity of the myoelectric prosthetic hand, additional hand motion commands need to be classified. The more sEMG sensors are used, the more hand motion commands can be classified. However, the amputee's residual muscles are limited. In order to improve the practicability of the myoelectric prosthetic hand, it is critical to investigate the effective pattern recognition algorithms to deal with the sEMG signals detected by fewer sensors, while identifying as many hand motion commands as possible. Current pattern recognition algorithms for sEMG signals are challenged by limited recognition patterns and unsteady classification accuracy rates. To solve these dilemmas, we employed discrete wavelet transform (DWT) and wavelet neural network (WNN) algorithms to improve the pattern recognition effects of sEMG signals. In addition, the back propagation and gradient descent algorithms were utilized to train WNN. In this work, we only used three sEMG sensors to classify and recognize six kinds of hand motion commands. The maximum identification accuracy rate is 100%, and an average classification accuracy rate of the proposed WNN is 94.67%, which is substantially better than the artificial neural network (ANN) algorithm.
Global antiretroviral therapy has entered a new era. Integrase strand transfer inhibitor (INSTI) has become the first choice in acquired immunodeficiency syndrome (AIDS) treatment. Because INSTI has ...high antiviral efficacy, rapid virus inhibition, and good tolerance. However, INSTIs may increase the risk of obesity. Each INSTI has its unique impact on weight gain in patients with human immunodeficiency virus (HIV)/AIDS. This study systematically assessed different INSTIs in causing significant weight gain in HIV/AIDS patients by integrating data from relevant literature.
PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), China Science and Technology Journal Database (VIP), and Wanfang databases were searched to find studies on the influence of different INSTIs in weight gain. Data on weight change were extracted, and a network meta-analysis was performed.
Eight studies reported weight changes in HIV/AIDS patients were included. Results of the network meta-analysis showed that the weight gain of HIV/AIDS patients treated with Dolutegravir (DTG) was significantly higher than that of Elvitegravir (EVG) MD = 1.13, (0.18-2.07). The consistency test results showed no overall and local inconsistency, and no significant difference in the results of the direct and indirect comparison was detected (p > 0.05). The rank order of probability was DTG (79.2%) > Bictegravir (BIC) (77.9%) > Raltegravir (RAL) (33.2%) > EVG (9.7%), suggesting that DTG may be the INSTI drug that causes the most significant weight gain in HIV/AIDS patients.
According to the data analysis, among the existing INSTIs, DTG may be the drug that causes the most significant weight gain in HIV/AIDS patients, followed by BIC.
With the rise of the network society, as the mapping Internet space, the public opinion has become the most active way of expressing social public opinion. It gradually gets deeply involved in the ...development and change of various social phenomena, social problems and social events, and evolves into the real politics and public management. In this context, it is of great practical significance to explore the evolution process and laws of online public opinions and systematically analyze the influence mechanism in the evolution process of online public opinions. This paper comprehensively uses the modeling simulation, empirical analysis, fuzzy systems and other research methods, adopts the reasonable abstraction of the main behavior characteristics, behavior motives and network relations of network users, and then constructs the evolution model of network public opinion in the complex social network. Besides, from the new research perspective of network members and network relations of the dynamic interaction between the government, media and netizen, this paper makes an in-depth study on the influence mechanism of the dynamic evolution of online public opinion.
Myopia is the most common form of refractive eye disease, and the prevalence is increasing rapidly worldwide. However, the key metabolic alterations in individuals with high myopia are not understood ...clearly, and serum biomarkers remain to be determined. The objectives of this study were to identify serum biomarkers and investigate the metabolic alterations of myopia. The serum metabolomics profiling was investigated on 30 high myopia cases and 30 controls (without myopia) using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS), and an independent additional cohort including 20 cases and 19 controls were investigated to validate potential metabolite candidates for biomarkers. According to the metabolic differences, the myopia patients and controls could be divided into different clusters and nine metabolites were found to be closely correlated with myopia. In the cohort of validation, eight metabolites were confirmed. Metabolic pathway analyses of these metabolites of high myopia involved abnormal phospholipid, diacylglycerol, amino acid, and vitamin metabolism, which were closely correlated with oxidative stress and inflammation. Multiple logistic regression analyses showed that γ-glutamyltyrosine and 12-oxo-20-trihydroxy-leukotriene B4 were potential biomarkers of myopia with a combined high sensitivity (97%), specificity (90%), and area under the curve value (0.983). These findings may contribute to an understanding of the pathophysiological changes and pathogenesis of myopia, and provide novel insight into the early prevention and control of high myopia.
•A two-stage study was conducted using metabolomics analyses of high myopia.•Eight metabolites were found correlated with myopia in both discovery and validation cohorts.•Myopia patients had abnormal phospholipid, diacylglycerol, amino acid, and vitamin metabolism.•The γ-glutamyltyrosine and 12-oxo-20-trihydroxy-leukotriene B4 were potential myopia biomarkers.•These findings may provide a novel insight into the early prevention and control of high myopia.
We study the impacts of country-level information asymmetry, investors' home-country bias, effectiveness of contract enforcement mechanisms, and accessibility of legal recourse on IPO underpricing in ...36 countries around the globe. We find evidence consistent with all four of our hypotheses. First, we find a positive and significant effect of country-level information asymmetry on IPO underpricing. Second, our empirical evidence is consistent with the agency-cost-based explanation of IPO underpricing. We find that lower cost to entice the block holders, measured by domestic investors' home-country bias, reduces IPO underpricing. Third, we find that effective contract enforcement mechanisms help to reduce IPO underpricing. Finally, we find a positive relation between the accessibility of legal recourse and IPO underpricing.
► We study the impacts of country-level factors on IPO underpricing in 36 countries around the globe. ► We find a positive and significant effect of country-level information asymmetry on IPO underpricing. ► We find that lower cost to entice the block holders reduces IPO underpricing. ► We find that effective contract enforcement mechanisms help to reduce IPO underpricing. ► Finally, we find a positive relation between the accessibility of legal recourse and IPO underpricing.
Background Theoretically, stress is positively correlated with posttraumatic growth (PTG). However, evidence for a correlation between fear of cancer recurrence (FCR), a cancer-specific stressor, and ...PTG is mixed. The present study aimed to systematically investigate the overall effect size between the two and to explore moderators that may influence this relationship. Methods From the earliest available date to October 2023, a comprehensive search was conducted in seven databases. Correlation coefficients (r) were calculated using Stata software. Publication type, continent, trauma role, gender, FCR measurements, PTG measurements, sample size, age, and time since diagnosis were used to examine moderating effects. The National Heart, Lung, and Blood Institute’s (NHLBI) assessment tool was used to evaluate study quality. Results A total of 14 studies, involving 17 samples and 3,701 participants, were included. The studies found a small association between FCR and PTG ( r = 0.161, 95% CI: 0.070–0.249, p < 0.01) and large heterogeneity ( I 2 = 85.5%). The strength of the association varied according to the publication type and FCR measurement. Conclusion The current review suggests a small but significant positive correlation between FCR and PTG. Future studies would benefit from exploring additional moderators and the use of standardized, validated FCR measurement tools. Systematic review registration PROSPERO , identifier CRD42023460407.
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