Torsion of right middle lobe after a right upper lobectomy

Lobar torsion after lung resection is a quite rare complication. A 50-year-old woman presented typical features on chest radiographs and CT(computed tomography) scan of lobar torsion after a right upper lobectomy. After emergency lobectomy of right middle lobe, the patient recovered well and discharged 10 days after the second operation

Predicting microRNA precursors with a generalized Gaussian components based density estimation algorithm

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are short non-coding RNA molecules, which play an important role in post-transcriptional regulation of gene expression. There have been many efforts to discover miRNA precursors (pre-miRNAs) over the years. Recently, <it>ab initio </it>approaches have attracted more attention because they do not depend on homology information and provide broader applications than comparative approaches. Kernel based classifiers such as support vector machine (SVM) are extensively adopted in these <it>ab initio </it>approaches due to the prediction performance they achieved. On the other hand, logic based classifiers such as decision tree, of which the constructed model is interpretable, have attracted less attention.</p> <p>Results</p> <p>This article reports the design of a predictor of pre-miRNAs with a novel kernel based classifier named the generalized Gaussian density estimator (G²DE) based classifier. The G²DE is a kernel based algorithm designed to provide interpretability by utilizing a few but representative kernels for constructing the classification model. The performance of the proposed predictor has been evaluated with 692 human pre-miRNAs and has been compared with two kernel based and two logic based classifiers. The experimental results show that the proposed predictor is capable of achieving prediction performance comparable to those delivered by the prevailing kernel based classification algorithms, while providing the user with an overall picture of the distribution of the data set.</p> <p>Conclusion</p> <p>Software predictors that identify pre-miRNAs in genomic sequences have been exploited by biologists to facilitate molecular biology research in recent years. The G²DE employed in this study can deliver prediction accuracy comparable with the state-of-the-art kernel based machine learning algorithms. Furthermore, biologists can obtain valuable insights about the different characteristics of the sequences of pre-miRNAs with the models generated by the G²DE based predictor.</p

Technical aspects of single-port thoracoscopic surgery for lobectomy

Thoracoscopic Surgery is in common use in routine surgical practice. With the advancement of the various techniques and instruments required, mini wounds and fewer thoracoports become practical in recent years. Here, we report our experience of performing lobectomy with radical lymph node dissection in 3 patients using regular straight endoscopic instruments. We demonstrate the feasibility of such techniques and discuss the key points of effectively performing the procedures. Because of the favorable outcomes, we encourage such procedures to be widely applied in surgical operations of various types

Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses

With a growing number of online reviews, consumers often rely on these reviews to make purchase decisions. However, little is known about managerial responses to online hotel reviews. This paper reports on a framework to integrate visual analytics and machine learning techniques to investigate whether hotel managers respond to positive and negative reviews differently and how to use a deep-learning approach to prioritize responses. In this study, forty 4- and 5-star hotels in London with 91,051 reviews and 70,397 responses were collected and analyzed. Visual analyses and machine learning were conducted. The results indicate most hotels (72.5%) showing no preference to respond to positive and negative reviews. Our proposed deep-learning approach outperformed existing algorithms to prioritize responses

ELEMENTARY SCHOOL BOYS’ SOCCER KICK SKILL ANALYSIS

The purpose of this study is aimed to analyze elementary school boys’ kicking skills on the perspective of motor skills. The data is collected by Vicon Motion Analysis System (250Hz). The parameters include the compare of the instant joint angles and the time proportion during the process of the kicking toward the different kick performance groups. The participants are 36 elementary boy soccer players (age: 11.7±0.3 yrs; height: 1.42±0.13 m; weight: 37.5±13.0 kg). The subjects were divided to two groups according to the instance kicking ball speed. The result indicated that the high ball speed group players have greater extremity joint angles than the low ball speed group. No difference was found on the time proportion during the process of the kicking. We suggest that the learning of kicking skill can start with the lower speed in the beginner stage

Association between health examination items and body mass index among school children in Hualien, Taiwan

BACKGROUND: To assess the prevalence of obesity and major physical examination items including dental caries, myopia, pinworm, hematuria, and proteinuria among school children in Hualien, Taiwan. In addition, the health status differences between gender, grader, levels of residence urbanization, and body mass index (BMI) were examined. METHODS: Cross-sectional studies with a total of 11,080 students (age, 7–14 years) in grades 1, 4, and 7 were evaluated for weight, height, routine physical examination, and urine analysis during the 2010 Student Health Examination in Hualien. Frequencies, Chi-square test, and logistic regression were conducted using SPSS. RESULTS: Of the 11,080 students evaluated, 1357 (12.2%) were overweight, and 1421 (12.8%) were obese. There were significant differences in overweight/obese prevalence by gender, by grader, and by levels of residence urbanization. Dental caries, myopia, and obesity were the most prevalent health problems among these students (75.6%, 33.0%, and 12.8%, respectively). In crude and adjusted analyses, research results showed that there were significant differences in the prevalence of major physical examination items between different gender, grader, levels of residence urbanization, and BMI groups. Girls had a higher prevalence of dental caries, myopia, and hematuria than boys (all p < 0.01), whereas boys had a higher prevalence of pinworm than girls (p = 0.02). Students in higher grades had significantly higher prevalence of myopia, hematuria, and proteinuria (all p < 0.01), whereas students in lower grades had higher prevalence of dental caries and pinworm (p < 0.01). Students with abnormal BMI had lower prevalence of pinworm (p < 0.01). Students residing in suburban and rural areas had higher prevalence of dental caries, pinworm, and hematuria (all p < 0.01), and lower prevalence of myopia than students residing in urban areas (all p < 0.01). CONCLUSION: Routine health examination provides an important way to detect students’ health problems. Our study elucidated major health problems among school children in Hualien, Taiwan. In addition, the results also indicated that the prevalence of health problems had a significant relationship with gender, grader, levels of residence urbanization, and BMI. It is suggested that school health interventions should consider students’ health profiles along with their risk factors status in planning