Alien Registration- Kirkos, Andrew (Lewiston, Androscoggin County)

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Dietary Intakes and Nutritional Status of a Greek Team of Female Volleyball Players

Aim: The purpose of this study was to assess the dietary intakes and nutritional status of a nationally ranked team of female volleyball players. Methods: The subjects completed a general history questionnaire and 7-day food and physical activity records. Anthropometric measurements included height, weight, triceps and subscapular skinfolds and mid-upper-arm circumference. Biochemical assessment included parameters for protein, lipid, and iron status. Results: All subjects had normal menstrual cycles and body fat values (27 %) at levels higher than for optimum performance. Most were in negative energy balance and had low energy (30 kcal/kg/d), carbohydrate (3.8 g/kg/d) and protein (1.0 g/kg/d) intakes. Fat intakes were high (39 %) and micronutrient intakes were below recommended levels, except for vitamin C, vitamin B12 and niacin. Biochemical indices were normal except for iron and lipid status of some players. Conclusion: These results indicate that the players of this team have dietary intakes that place them at risk for nutritional shortages and compromised performance; they need professional counseling regarding nutrition practices for optimum health and performance

Intelligent Financial Fraud Detection Practices: An Investigation

Financial fraud is an issue with far reaching consequences in the finance industry, government, corporate sectors, and for ordinary consumers. Increasing dependence on new technologies such as cloud and mobile computing in recent years has compounded the problem. Traditional methods of detection involve extensive use of auditing, where a trained individual manually observes reports or transactions in an attempt to discover fraudulent behaviour. This method is not only time consuming, expensive and inaccurate, but in the age of big data it is also impractical. Not surprisingly, financial institutions have turned to automated processes using statistical and computational methods. This paper presents a comprehensive investigation on financial fraud detection practices using such data mining methods, with a particular focus on computational intelligence-based techniques. Classification of the practices based on key aspects such as detection algorithm used, fraud type investigated, and success rate have been covered. Issues and challenges associated with the current practices and potential future direction of research have also been identified.Comment: Proceedings of the 10th International Conference on Security and Privacy in Communication Networks (SecureComm 2014

Complex Pediatric Elbow Injury: An Uncommon Case

BACKGROUND: There is paucity of literature describing complex elbow trauma in the pediatric population. We described a case of an uncommon pediatric elbow injury comprised of lateral condyle fracture associated with posterolateral dislocation of elbow. CASE PRESENTATION: A 12-year-old boy sustained a direct elbow trauma and presented with Milch type II lateral condyle fracture associated with posterolateral dislocation of elbow. Elbow dislocation was managed by closed reduction. The elbow stability was assessed under general anaesthesia, followed by open K-wiring for the lateral condylar fracture fixation. The patient had an uneventful recovery with an excellent outcome at 39 months follow-up. CONCLUSION: Complex pediatric elbow injuries are quite unusual to encounter, the management of such fractures can be technically demanding. Concomitant elbow dislocation should be managed by closed reduction followed by open reduction and internal fixation (K-wires or cannulated screws) of the lateral condyle fracture

Coracoid Abnormalities and Their Relationship with Glenohumeral Deformities in Children with Obstetric Brachial Plexus Injury

<p>Abstract</p> <p>Background</p> <p>Patients with incomplete recovery from obstetric brachial plexus injury (OBPI) usually develop secondary muscle imbalances and bone deformities at the shoulder joint. Considerable efforts have been made to characterize and correct the glenohumeral deformities, and relatively less emphasis has been placed on the more subtle ones, such as those of the coracoid process. The purpose of this retrospective study is to determine the relationship between coracoid abnormalities and glenohumeral deformities in OBPI patients. We hypothesize that coracoscapular angles and distances, as well as coracohumeral distances, diminish with increasing glenohumeral deformity, whereas coracoid overlap will increase.</p> <p>Methods</p> <p>39 patients (age range: 2-13 years, average: 4.7 years), with deformities secondary to OBPI were included in this study. Parameters for quantifying coracoid abnormalities (coracoscapular angle, coracoid overlap, coracohumeral distance, and coracoscapular distance) and shoulder deformities (posterior subluxation and glenoid retroversion) were measured on CT images from these patients before any surgical intervention. Paired Student t-tests and Pearson correlations were used to analyze different parameters.</p> <p>Results</p> <p>Significant differences between affected and contralateral shoulders were found for all coracoid and shoulder deformity parameters. Percent of humeral head anterior to scapular line (PHHA), glenoid version, coracoscapular angles, and coracoscapular and coracohumeral distances were significantly lower for affected shoulders compared to contralateral ones. Coracoid overlap was significantly higher for affected sides compared to contralateral sides. Significant and positive correlations were found between coracoscapular distances and glenohumeral parameters (PHHA and version), as well as between coracoscapular angles and glenohumeral parameters, for affected shoulders. Moderate and positive correlations existed between coracoid overlap and glenohumeral parameters for affected shoulders. On the contrary, all correlations between the coracoid and glenohumeral parameters for contralateral shoulders were only moderate or relatively low.</p> <p>Conclusions</p> <p>These results indicate that the spatial orientation of the coracoid process differs significantly between affected and contralateral shoulders, and it is highly correlated with the glenohumeral deformity. With the progression of glenohumeral deformity, the coracoid process protrudes more caudally and follows the subluxation of the humeral head which may interfere with the success of repositioning the posteriorly subluxed humeral head anteriorly to articulate with the glenoid properly.</p

Identification of financial statement fraud in Greece by using computational intelligence techniques

The consequences of financial fraud are an issue with far-reaching for investors, lenders, regulators, corporate sectors and consumers. The range of development of new technologies such as cloud and mobile computing in recent years has compounded the problem. Manual detection which is a traditional method is not only inaccurate, expensive and time-consuming but also they are impractical for the management of big data. Auditors, financial institutions and regulators have tried to automated processes using statistical and computational methods. This paper presents comprehensive research in financial statement fraud detection by using machine learning techniques with a particular focus on computational intelligence (CI) techniques. We have collected a sample of 2469 observations since 2002 to 2015. Research gap was identified as none of the existing researchers address the association between financial statement fraud and CI-based detection algorithms and their performance, as reported in the literature. Also, the innovation of this research is that the selection of data sample is aimed to create models which will be capable of detecting the falsification in financial statements

Thoracic cord compression caused by disk herniation in Scheuermann’s disease: A case report and review of the literature

We present the case of a 14-year-old male with Scheuermann’s disease and significant neurological deficit due to thoracic disk herniation at the apex of kyphosis. He was treated with an anterior decompression, anterior and posterior fusion in the same setting using plate, cage and a segmental instrumentation system. The patient had an excellent outcome with complete neurological recovery

Modelling bankruptcy prediction models in Slovak companies

An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression) and early artificial intelligence models (e.g. artificial neural networks), there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest) to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models