Detection of imprinting and heterogeneous maternal effects on high blood pressure using Framingham Heart Study data

Both imprinting and maternal effects could lead to parent-of-origin patterns in complex traits of human disorders. Statistical methods that differentiate these two effects and identify them simultaneously by using family-based data from retrospective studies are available. The usual data structures include case-parents triads and nuclear families with multiple affected siblings. We develop a likelihood-based method to detect imprinting and maternal effects simultaneously using data from prospective studies. The proposed method utilizes both affected and unaffected siblings in nuclear families by modeling familial genotypes and offspring's disease status jointly. Maternal effect is usually modeled as a fixed effect under the assumption that maternal variant allele(s) has (have) identical effect on any offspring. However, recent studies report that different people may carry different amounts of substances encoded by the mother's variant allele(s) (called maternal microchimerism), which could result in heterogeneity of maternal effects. The proposed method incorporates the heterogeneity of maternal effects by adding a random component to the logit of the penetrance. Our method was applied to the Framingham Heart Study data in two steps to detect single-nucleotide polymorphisms (SNPs) that may be associated with high blood pressure. In the first step, SNPs that affect susceptibility of high blood pressure through minor allele, genomic imprinting, or maternal effects were identified by using the proposed model without the random effect component. In the second step, we fitted the mixed effect model to the identified SNPs that have significant maternal effect to detect heterogeneity of the maternal effects

Research on the Application Strategy of Virtual Reality Technology under the Background of Media Integration -- Take Chinese Minnan Culture Short Video as an Example

In this study, an experiment was designed to verify the communication effects and impacts of virtual reality technology on the viewers of a short video on Minnan cultural content. A control experiment and a questionnaire survey were chosen as the main research methods. According to the requirements of the experiment, the research subjects meeting the requirements were selected and divided into the control group and the experimental group. At the end of the experiment, a questionnaire survey was conducted on all the participants. The results and data of the questionnaire were analyzed at the end.By analyzing the data from the results of the questionnaire and with almost similar other variables in the control group, the minor effects of some subjective and objective factors on the experiment were excluded. The samples of the two groups showed significant differences in all eight items of the questionnaire, including the degree of interest in the content of the short videos, the richness of the content of the short videos, the rating of the degree of integration of the traditional culture and the short videos, the rating of the sense of visual experience and satisfaction with the content of this part of the short videos, the willingness to create this kind of short videos, the likelihood of recommending this kind of short videos to your family members or friends, the complete explanation of the connotation of traditional culture by using the short videos, and whether or not it will attract you to watch the similar content the next time, and the question of whether the traditional culture is fully explained through the short videos.It was found by analyzing the result data of this experiment and the questionnaire survey conducted after the experiment. Compared with Group B who watched the short video of Minnan culture supported by virtual reality technology, the audience of Group A had a better sense of video viewing and content experience, and gained a better viewing and using experience. This method makes traditional culture better disseminated and presented with the help of virtual reality technology. Therefore, we believe that combining virtual reality technology with short videos of Minnan culture can better spread the traditional culture of Minnan. And virtual reality technology has the characteristics of low cost and easy to operate. It is convenient for short video creators to choose and create

Research on the External Communication of Chinese Culture Empowered by Short Videos in Rural China -- Take the Short Video Content of YouTube Platform as an Example

Using YouTube as the platform and rural short videos as the entry point, this study investigates how Chinese rural short videos empower the external dissemination of Chinese culture on the YouTube platform. By using comparative analysis and content analysis research methods to select samples and construct categories, the aim is to compare rural and non rural themed Chinese short videos, as well as the similarities and differences in text structure and symbol types between Chinese rural short videos and foreign rural short videos, to analyze the empowerment of rural elements combined with different themes, and to summarize the dissemination content characteristics of Chinese rural short videos that have successfully gained popularity on the YouTube platform

Internet protocol television (IPTV): The Killer application for the next-generation internet

Internet Protocol Television (IPTV) will be the killer application for the next-generation Internet and will provide exciting new revenue opportunities for service providers. However, to deploy IPTV services with a full quality of service (QoS) guarantee, many underlying technologies must be further studied. This article serves as a survey of IPTV services and the underlying technologies. Technical challenges also are identified

Acqui-hiring or Acqui-quitting: Post-M&A Turnover Prediction via a Dual-fit Model

Gaining highly skilled human capital is one of the primary reasons for corporate mergers and acquisitions (M&A), especially for knowledge-intensive industries. However, the inevitable tensions brought by the divergent cultures and organizational misalignment during the M&A process result in high talent turnover rate and ultimately the integration failure. Hence, it is imperative to understand and prepare for the potential effects of M&A process on employee turnover. To this end, we propose a novel dual-fit model induced heterogeneous Graph Neural Network (GNN) model to predict the talent turnover trend in the post-M&A process, by taking into account the complex relationship among the acquirer firm, the acquiree firm, and the acquired employees. Specifically, we creatively design a dual-fit model comprised of both the firm-level compatibility and employee-firm fit. Extensive evaluations on large-scale real-world data clearly demonstrate the effectiveness of our approach

El género gramatical en una gramática del español como segunda lengua

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Filología, Departamento de Lengua Española y Teoría de la Literatura y Literatura Comparada, leída el 11-12-2015Depto. de Lengua Española y Teoría de la LiteraturaFac. de FilologíaTRUEunpu

Don't Stop Learning: Towards Continual Learning for the CLIP Model

The Contrastive Language-Image Pre-training (CLIP) Model is a recently proposed large-scale pre-train model which attracts increasing attention in the computer vision community. Benefiting from its gigantic image-text training set, the CLIP model has learned outstanding capabilities in zero-shot learning and image-text matching. To boost the recognition performance of CLIP on some target visual concepts, it is often desirable to further update the CLIP model by fine-tuning some classes-of-interest on extra training data. This operation, however, raises an important concern: will the update hurt the zero-shot learning or image-text matching capability of the CLIP, i.e., the catastrophic forgetting issue? If yes, could existing continual learning algorithms be adapted to alleviate the risk of catastrophic forgetting? To answer these questions, this work conducts a systemic study on the continual learning issue of the CLIP model. We construct evaluation protocols to measure the impact of fine-tuning updates and explore different ways to upgrade existing continual learning methods to mitigate the forgetting issue of the CLIP model. Our study reveals the particular challenges of CLIP continual learning problem and lays a foundation for further researches. Moreover, we propose a new algorithm, dubbed Learning without Forgetting via Replayed Vocabulary (VR-LwF), which shows exact effectiveness for alleviating the forgetting issue of the CLIP model.Comment: 12 pages, 5 figure