Hereditary myopathy is a large group of hereditary disease that mainly manifests as muscle atrophy and weakness, with strong genetic and phenotypic heterogeneity. In recent years, with greater understanding of its molecular basis, the classification of hereditary myopathy has become more accurate serving as a significant guidance for clinical diagnosis. This article reviews the clinical features, molecular mechanisms, accurate diagnostic strategies, and treatment of hereditary myopathy.
Key words:
Hereditary myopathy; Clinical features; Molecular mechanisms; Diagnosis; Treatment
Abstract This paper investigates optimal decisions for private banking development in China under two innovative organizational structures—the big retail mode (BRM) and the independent development mode (IDM). Under the BRM, the retail and private banking divisions form a cooperative relationship wherein the former transfers high-net-worth customers to the latter. In addition, retail banking receives a share of private banking revenues. We investigate the optimal revenue-sharing ratio between the two divisions and the optimal effort by private banking to serve transferred customers within the cooperative relationship. The analytical results show that as the private banking division becomes more developed, the optimal revenue-sharing ratio decreases, and the private banking division’s optimal effort to serve transferred customers decreases because it puts more effort into acquiring new customers. Under the IDM, the two divisions form a competitive relationship since they compete to acquire customers independently. We investigate customer acquisition efforts in this interdivisional competition. Optimal customer acquisition efforts by both divisions increase in potential assets and rates of return. This paper contributes to the literature by (1) analyzing financial innovation by private banks from an organizational perspective; (2) providing an economic analysis for private banking development in China.
The fault system is an important ore-channeling and ore-hosting structure,which plays an important role in controlling the migration and accumulation of ore-forming fluid.The fractal dimension value of the fault system is a comprehensive embodiment of the fault amount,scale,assembly pattern and dynamic mechanism.It can be a quantitative parameter to describe the complexity of the fault system.The distribution of ore deposit(occurrences) is controlled by fracture in Taxkorgan-Shache area of Xinjiang,and the fractal geometry study of the Ⅰ,Ⅱ-1,Ⅱ-2 and Ⅲ metallogenic districts indicated that these fracture systems possess the well statistical self-similar character,and the fractal dimension value were as follows: 1.49,1.33,1.34 and 1.22.The quantitative ordination of the metallogenic potential in this area isⅠⅡⅢ,and the target ores of the meta-llogenic districts are lead-zinc-copper deposit,lead-zinc polymetallic deposit and magnetite.This study points out the orientation of prospecting in Taxkorgan-Shache of Xinjiang Uygur Autonomous Region.
This paper focuses on the analysis of classified application scenarios in 5G positioning. As a result of distinguishing requirements of various businesses, 5G positioning has developed a series of specific techniques to meet these demands. Two types of application functions include business and management functions. A potential network topology for 5G positioning is proposed in order to meet the characteristics and requirements of high-accuracy mobile positioning under the basic frame of 5G communications. Both properties of integration and localization has become primary driving forces of 5G positioning.
The large-scale access of renewable energy sources such as wind power will affect the operation and dispatch of the power system, and will affect the safe and stable of the power grid. The ESS has the ability to respond quickly, which can reduce the impact of wind power on the grid. Based on a hybrid energy storage with a certain capacity, a corresponding rolling optimization control strategy is proposed. Using batteries and super capacitor as energy storage media, an optimal control model targeting the state of charge of the hybrid energy storage system is established, and the solution is solved by a particle swarm optimization algorithm. The simulation example shows that a HESS with a certain capacity on the generation side can achieve a smooth grid connection. The control strategy proposed in this paper extends the service life of the battery.
One of the most significant differences of M5 over previous forecasting competitions is that it was held on Kaggle, an online platform of data scientists and machine learning practitioners. Kaggle provides a gathering place, or virtual community, for web users who are interested in the M5 competition. Users can share code, models, features, loss functions, etc. through online notebooks and discussion forums. This paper aims to study the social influence of virtual community on user behaviors in the M5 competition. We first research the content of the M5 virtual community by topic modeling and trend analysis. Further, we perform social media analysis to identify the potential relationship network of the virtual community. We study the roles and characteristics of some key participants that promote the diffusion of information within the M5 virtual community. Overall, this study provides in-depth insights into the mechanism of the virtual community's influence on the participants and has potential implications for future online competitions.
Predictions combination, as a combination model approach with adjustments in the output space, has flourished in recent years in research and competitions. Simple average is intuitive and robust, and is often used as a benchmark in predictions combination. However, some poorly performing sub-models can reduce the overall accuracy because the sub-models are not selected in advance. Even though some studies have selected the top sub-models for the combination after ranking them by mean square error, the covariance of them causes this approach to not yield much benefit. In this paper, we suggest to consider the diversity of sub-models in the predictions combination, which can be adopted to assist in selecting the most diverse model subset in the model pool using negative correlation learning. Three publicly available datasets are applied to evaluate the approach. The experimental results not only show the diversity of sub-models in the predictions combination incorporating negative correlation learning, but also produce predictions with accuracy far exceeding that of the simple average benchmark and some weighted average methods. Furthermore, by adjusting the penalty strength for negative correlation, the predictions combination also outperform the best sub-model. The value of this paper lies in its ease of use and effectiveness, allowing the predictions combination to embrace both diversity and accuracy.
Abstract Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity‐based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajectories. Two groups of analytic units, including MeSH terms and their co‐occurrences, are employed independently by the indicator to measure the change of knowledge. The effectiveness of the proposed indicators was evaluated against the four datasets of scientific breakthroughs derived from four recognition trials. In terms of identifying scientific breakthroughs, the proposed disruption indicator based on MeSH co‐occurrences outperforms that based on MeSH terms and three earlier citation‐based disruption indicators. It is also shown that in our indicator, measuring the change of knowledge inspired by the focal paper in its evolutionary trajectory is a larger contributor than measuring the change created by the focal paper. Our study not only offers empirical insights into conceptual understanding of scientific breakthroughs but also provides practical disruption indicator for scientists and science management agencies searching for valuable research.
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