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Background To investigate the effect of bone cement on the curative effect of percutaneous kyphoplasty (PKP) in the treatment of osteoporotic vertebral compression fracture (OVCF). Methods A total of 323 patients with OVCF who underwent PKP in our hospital between January 2018 and June 2020 were enrolled. According to the viscosity and distribution of the bone cement, the patients were divided into a high viscosity (HV) group and a low viscosity (LV) group, and into a central distribution (central) group and a lateral distribution (lateral) group, and their baseline characteristics, perioperative parameters, efficacy indicators, and complications indicators were compared. Results In the HV group, the amount of bone cement injected and the number of patients with centrally distributed bone cement were significantly higher than those in the LV group, while the operation time and the number of patients with laterally distributed bone cement were significantly lower. Further, the bone cement viscosity in the central group was significantly higher than that in the lateral group. Before surgery, there were no significant differences between the groups in terms of the posterior back visual analog scale (VAS) score, Oswestry dysfunction index (ODI), Cobb angle, vertebral height, or anterior vertebral height (AVH) of the fractured vertebral body. However, after surgery, both the ODI and the Cobb angle were notably reduced and the AVH was increased in the HV group. Meanwhile, in the central group, the VAS, Cobb angle, and ODI were all dramatically reduced. Conclusions Centrally distributed high-viscosity bone cement can reduce the Cobb angle and the incidence of bone cement leakage in patients with OVCF who undergo PKP, thereby improving the curative effect.

Objective. To investigate the different efficacy of proximal femoral nail antirotation (PFNA) combined with or without a microexternal fixator in the treatment of coral-plane femoral intertrochanteric fractures. Methods. 120 patients with intertrochanteric coronal fractures who received treatment in four hospitals from February 2020 to February 2021 were retrospectively included in this study. They were divided into control (PFNA alone, n = 60) and combined treatment group (a microexternal fixator + PFNA, n = 60) according to different surgery methods. All patients were followed up for 6 months. Operative time, amount of intraoperative blood loss, postoperative length of hospital stays, fracture healing time, Harris hip score, modified Barthel index, hip function excellent and good rate, and incidence of complications were compared between the two groups. Results. There were no significant differences in operative time, amount of intraoperative blood loss, postoperative length of hospital stay, and incidence of complications between the two groups (all P > 0.05). Fracture healing time in the combined treatment group was significantly shorter than that in the control group ( P P P 66.67%, P

Automatic image annotation is a challenging research problem that includes a large number of tags and various features. Traditional shallow machine learning algorithms lack generalization performance when dealing with complex classification problems. Automatic image annotation based on a stacked auto-encoder (SAE) is proposed to enhance the annotation generalization performance. In this paper, two kinds of strategies, the annotation model and the annotation process, are proposed to solve the main problem of unbalanced data in image annotation. 1) For the annotation model itself, to improve the annotation effect of low frequency tags, we propose a balanced and stacked auto-encoder (BSAE) that can enhance training for low frequency tags. On the basis of this model, a robust BSAE (RBSAE) algorithm which enhances training for sub BSAE model by group is proposed to enhance the annotation stability. This strategy ensures that the model itself has a strong ability to deal with the problem of unbalanced data. 2) For the annotation process, we propose a framework of attribute discrimination annotation (ADA). We first take an unknown image. Then we construct a local equilibrium dataset based on the unknown image and discriminate the high- and low-frequency attribute of the image to determine the corresponding annotation process. One process called the local semantic propagation (LDE-SP) algorithm annotates the low frequency image and the RBSAE algorithm annotates the high frequency image. This strategy improves the overall image annotation effect and ensures that the annotation process has a strong ability to deal with the problem of unbalanced data. For each SAE (including BSAE and RBSAE) annotation model, we propose two kinds of optimization methods, namely, one that is based on non-linear optimization and one on linear optimization. Experimental results on three benchmark datasets show that the proposed model outperforms the previous models in many performance indices.

Computing education has been expanding into K-12 schools in many countries. The new national curriculum standards in China are going to include computational thinking as a core literacy for every student and make computer programming as a required module in the information technology course. Hence, it is imperative to understand the difficulties Chinese students may face when learning to program. This study investigated Chinese middle students' difficulties in learning to program in Python using the student data in an automated assessment system. Our results showed that the students struggled with fundamental Python syntax and programming rules. We also found that Chinese students faced a special difficulty, which was using correct punctuation symbols in code. We noted that many syntax errors students made were due to the use of Chinese punctuation symbols, which look almost identical to the English equivalents but are invalid to the Python interpreter. Our results suggest that when teaching a programming course to Chinese middle school students, teachers should first help students develop certain typing skills (e.g., switching input methods, distinguishing Chinese and English punctuation symbols, etc.). Such preparation may reduce students' mistakes in code. Finally, future research directions are discussed, including examining the effects of the typing skill training, designing feedback components for the automated assessment system, and so forth.