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With the advance of network and multimedia technologies, the traffic of network video services has dramatically increased. In order to support the QoS (Quality of Service) and QoE (Quality of Experience) of network video services, it is important to model network layer QoS parameters and application layer QoE appropriately. This paper presents a statistical model between network layer QoS parameters and MOS (Mean Opinion Score) values, by analyzing the statistical characteristics of the video bit rate and jitter in given MOS ranges. Compared with existing approaches, this model can provide video service providers and network operators with more appropriate suggestions for setting network layer QoS parameters under given user's QoE level, and thus has good application prospect in related field.

Using several variables known to be related to prostate cancer, a multivariate classification method is developed to predict the onset of clinical prostate cancer. A multivariate mixed-effects model is used to describe longitudinal changes in prostate specific antigen (PSA), a free testosterone index (FTI), and body mass index (BMI) before any clinical evidence of prostate cancer. The patterns of change in these three variables are allowed to vary depending on whether the subject develops prostate cancer or not and the severity of the prostate cancer at diagnosis. An application of Bayes' theorem provides posterior probabilities that we use to predict whether an individual will develop prostate cancer and, if so, whether it is a high-risk or a low-risk cancer. The classification rule is applied sequentially one multivariate observation at a time until the subject is classified as a cancer case or until the last observation has been used. We perform the analyses using each of the three variables individually, combined together in pairs, and all three variables together in one analysis. We compare the classification results among the various analyses and a simulation study demonstrates how the sensitivity of prediction changes with respect to the number and type of variables used in the prediction process.

With the calculation methods for the sectional curvature ductility of reinforced concrete flexural components, analysis was conducted on the factors affecting the formation of plastic hinges at the ends of RC frame beams and their rotational capacities; on the basis of which, singly-doubly reinforced rectangular section method for flexural design calculation was put forth, which is favorable to the realization of beam hinge mechanism. The analysis of a practical design case shows that the method proposed is not only beneficial to the formation of plastic hinges at the beam ends and their rotational capacities, but also results in considerable reduction of longitudinal reinforcement, hence lowering of cost, ease of construction, so that it is worthy of popularization and application in design practice.

In this work, support vector classification (SVC) algorithm was used to build structure-activity relationship (SAR) model of the 5-hydroxytryptamine type 3 (5-HT3) receptor antagonists with 26 compounds. In a benchmark test, SVC was compared with several techniques of machine learning currently used in the field. The prediction performance of the model was discussed on the basis of the leave-one-out cross-validation. The results show that the accuracy of prediction of SVC model was higher than those of back propagation artificial neural network (BP ANN), K-nearest neighbor (KNN) and Fisher methods.

OBJECTIVES: To determine the changes in serum erythropoietin with age in patients with and without anemia and to assess the importance of certain comorbidities on changes in erythropoietin level and the development of anemia. DESIGN: Clinical history, hematological parameters, and serum erythropoietin levels were examined at 1- to 2-year intervals for 8 to 30 years. SETTING: Baltimore Longitudinal Study on Aging (BLSA), National Institute on Aging. PARTICIPANTS: One hundred forty-three BLSA participants. MEASUREMENTS: Complete blood count and serum chemistries were performed at the time of each visit, and archived serum samples were used for erythropoietin level. RESULTS: Although all subjects were healthy and without anemia at the time of initial evaluation, some developed chronic illnessFmost notably hypertension and diabetes mellitus. Erythropoietin levels rose significantly for the group as a whole, and the slope of the rise was found to be greater for those who did not have associated diabetes mellitus or hypertension. During the subsequent years, subjects who developed anemia but did not have hypertension or diabetes mellitus had the greatest slope in erythropoietin rise over time, whereas those with hypertension or diabetes mellitus and anemia had the lowest erythropoietin slope. CONCLUSION: The increase in serum erythropoietin with aging may be compensation for subclinical blood loss, increased red blood cell turnover, or increased erythropoietin resistance of red cell precursors. It is suspected that, with very advanced age, or in those with compromised renal function (e.g., diabetes mellitus or hypertension), the compensatory mechanism becomes inadequate and anemia results. J Am Geriatr Soc 53:1360–1365, 2005.

Aim: To discriminate 32 phenethyl-amines between antagonists and agonists, and predict the activities of these compounds. Methods: The support vector machine (SVM) is employed to investigate the structure-activity relationship (SAR)/quantitative structure-activity relationship (QSAR) of phenethyl-amines based on molecular descriptors. Results: By using the leave-one-out cross-validation (LOOCV) test, 1 optimal SAR and 2 optimal QSAR models for agonists and antagonists were attained. The accuracy of prediction for the classification of phenethyl-amines by using the LOOCV test is 91.67%, and the accuracy of prediction for teh classification of phenethyl-amines by using the independent test is 100%; the results are better than those of the Fisher, the artificial neural network (ANN), and the K-nearest neighbor models for this real world data. The RMSE (root mean square error) of antagonists' QSAR model is 0.5881, and the RMSE of agonists' QSAR model is 0.4779, which are better than those of the multiple linear regression, partial least squares, and ANN models for this real world data. Conclusion: The SVM can be used to investigate the SAR and QSAR of phenethylamines and could be a promising tool in the field of SAR/QSAR research.

To explore the causes of the postoperative complications of the penile elongation and the measures to prevent them in order to raise the success rate of the penile elongation. 1 000 patients who had received the penile elongation were reviewed and analyzed for the causes of postoperative complications, and the measures of prevention and treatment were discussed. Our results showed that, of the 1 000 cases, 64 had the postoperative complications, including 20 cases of edema of prepuce, 15 cases of flap necrosis, 12 hematoma, 9 infections, and 8 cases of fat and clumsy penis. It is concluded that correct operative manipulation, strict aseptic measures and necessary postoperative care and management could avoid or reduce the postoperative complications. When complications happened, a satisfactory result can be achieved with timely and correct treatment in the majority of the patients.