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[This corrects the article DOI: 10.3389/fped.2023.1064104.].

IntroductionFragile X syndrome (FXS) is a X-linked neurodevelopmental disorder (NDD). This study aims to investigate the incidence of FXS in Chinese children and analyze the comprehensive clinical characteristics of these FXS children.MethodsChildren diagnosed with idiopathic NDD were recruited between 2016 and 2021 from the department of Child Health Care, Children's Hospital of Fudan University. We combined tetraplet-primed PCR-capillary electrophoresis and whole exome sequencing (WES)/panel or array-based comparative genomic hybridization (array-CGH) to identify the size of the CGG repeats and the mutations or copy number variations (CNVs) in the genome and in FMR1. The clinical features of FXS children were analyzed according to pediatricians' recording, parental questionnaires, the results of examinations and follow-up.ResultsThe incidence of FXS in Chinese children with idiopathic NDD was 2.4% (42/1753) and in those with FXS, 2.38% had a deletion (1/42). Here, we present the clinical characteristics of 36 children with FXS. Overweight was observed in two boys. The average intelligence quotient (IQ)/development quotient (DQ) of all FXS patients was 48. The average ages of meaningful words and walking alone were 2 years and 10 months and 1 year and 7 months, respectively. The most frequent repetitive behavior was stimulated by hyperarousal to sensory stimulation. On social aspects, social withdrawal, social anxiety, and shyness accounted for 75%, 58%, and 56% of the total number of children, respectively. Approximately 60% of FXS children in this cohort were emotionally labile and prone to temper tantrums. Self-injury and aggression toward others could also be observed, at 19% and 28%, respectively. The most frequent behavioral problem was attention-deficit hyperactivity disorder (ADHD) seen in 64% and the most common facial features were a narrow and elongated face and large or prominent ears in 92% of patients.DiscussionScreening of FMR1 full mutation provides the possibility for patients' further medical supports and the clinical features of FXS children obtained in this study will increase the understanding and diagnosis of FXS.

With the increasing scarcity of conventional energy and environmental degradation, countries around the world are increasing their investment in renewable energy development. In order to make a scientific investment evaluation of renewable energy projects, this paper examines the analysis and control of their financial data. The intelligent analysis system of financial data is constructed based on OLAP. Logistic regression model and decision tree algorithm model are selected as the operation algorithm of the system to complete the intelligent analysis of data. Combining random forest algorithm and autoregressive moving average model, under the guidance of Bagging idea, the financial status of renewable energy projects after investment is judged in order to achieve the purpose of dynamic control. According to the results of analysis and control of financial data of renewable energy projects, it is known that the correct probability of intelligent analysis of financial data reached 94.5%, 83.1%, and 92.7% for different sample sizes of data sets, respectively. There were significant improvements in the efficiency of capital usage and asset quality, with an increase in capital concentration of 30.42%, an increase in inventory turnover from 10.68% to 13.04%, and an increase in the recovery rate of overdue accounts receivable from 60.31% to 67.83%. It has been proven that the method can help investors to better utilize uncertainty to improve the investment value of project, providing investors with a new way of thinking about decision-making.

In today’s rapid development of the economic environment, the company’s financial crisis can significantly reflect the enterprise crisis, and it has a significant impact on the development of the enterprise. Therefore, the prediction of the company’s financial crisis and the establishment of an early warning system have important practical significance. Based on the method of pattern recognition and artificial intelligence, this paper establishes a new forecasting model of corporate financial crisis, predicts its financial index data and realises the dynamic financial crisis warning. The model developed in this paper employs pattern recognition and artificial intelligence, and is thus endowed with high classification accuracy, good anti-noise ability and the ability to be sorted according to the importance of its index features.

ObjectiveTo investigate and analyze the epidemiological characteristics of a wild mushroom poisoning event in Qinhuangdao City, identify the species of poisonous mushroom, summarize the experience of investigation and treatment, and put forward prevention and control measures, and provide reference for the treatment and prevention of wild mushroom poisoning patients.MethodsThe poisoning events were analyzed by using the method of epidemiological investigation, morphological identification and mushroom toxin detection.ResultsFour villagers in Qinhuangdao city had nausea, abdominal pain, diarrhea, sweating and shivering after eating wild mushrooms. Patients were treated with vomiting, gastric lavage, atropine and other symptomatic treatment in the hospital, and the prognosis of the patients was good. After morphological identification and toxin detection, it was determined that food poisoning caused by mushroom of inocybe.ConclusionThis is the first reported poisoning event caused by mushroom of inocybe in Hebei Province. The reason of poisoning was misguided by the Internet and poor self-awareness of food safety. Therefore, publicity and education should be strengthened, enhancing the awareness to prevent the poisoning of wild mushroom.

Fe2O3 is one of the most important lithium storage materials and has attracted increasing interest owing to its good capacity in theory, abundant reserves, and better security. The utilization of Fe2O3 materials is hampered by their inferior cycle performance, low rate performance, and restricted composite variety. Herein, the heterostructure of Fe2O3@SnO2 with hexahedral structure was manufactured by two- step hydrothermal strategy, while the SnO2 nanopillars were epitaxially grown in six faces, not in the twelve edges of hexahedral Fe2O3 cubes, which comes from maximizing lattice matching on the six surfaces of Fe2O3. Furthermore, the experimental results prove that the hexahedral Fe2O3@SnO2 heterostructure exhibits remarkably enhanced electrochemical reversibility and reaction kinetics and delivers an impressive initial discharge capacity (1742 mA h g−1 at 4 A g−1), great rate performance (565 mA h g−1 at 5 A g−1), and stable long-term durability (661 mA h g−1 after 4000 cycles at 4 A g−1) as an anode for LIBs. The result of the finite element mechanical simulation further indicates that the SnO2 nanopillars grow on the six surfaces but not on the twelve edges of the hexahedral Fe2O3 cube, which would provide great rate performance and long-term stability. This study underlines the merits of the heterostructure and offers a useful design routine for superior electrode materials in LIBs. [ABSTRACT FROM AUTHOR]

Surfaces with translucent and wear-resistant effects have a wide range of applications, especially as protective layers. In this work, a simple and convenient method for the preparation of porous magnesium fluoride (MgF2) coatings was proposed. Nano-porous MgF2 powder was prepared with sol–gel and phase separation methods by optimizing the polymer amount and used for the preparation of thick layers onto PVC substrates. The automated surface area and porosity analyzer (BET) and scanning electron microscopy (SEM) confirmed that the layers containing 0.028‰ PEO presented a 3D structure with pore sizes in the range of 16 nm. The layer reached 93% transmittance in the visible region, a Vickers hardness value of 2889.1 kg/mm2, and a friction coefficient of 0.2 in the wear test. [ABSTRACT FROM AUTHOR]