A BIOMECHANICAL STUDY ON THE SCALE OF THE TIBIA

The purpose of this paper was to provide current biomechanical data on the tibia. X-ray pictures of the tibia were taken of 45 young boys, performing weight lifting and jumping. Some inactive subjects were also included. Measurements were taken to establish length, and thickness indexes Sporting background had no effect on the length or thickness index of the tibia as measured by the Ohla formula

Decision Engineering Analysis of Fraud Information Disclosure after China's Share-Splitting Reform

AbstractThis paper outlines a dynamic game model to analyze the fraud information disclosure by listed companies in China since the share-splitting reform in 2005. By analyzing the conditions of coalition-proof Nash equilibrium between large shareholders and the manager, exogenous variables’ effects on the equilibrium as well as the first-order condition of the maximum utility of the supervisory department, it is concluded that efficient capital markets require a high supervising probability and intensity of penalty to the “insider” and shortened the intervals between supervising conducts as well. Moreover, there exists a unique optimum incentive stock option ratio over which fraud information disclosure becomes more rampant. This results in a higher intensity of penalty to the manager given more stock option incentive and, in contrast, a higher intensity of penalty to large shareholders of a well managed and efficiently capital-structured company once fraud information disclosure is detected. The model's conclusions are consistent with the facts of listed companies in China. Finally, the model makes sharp suggestions for the mechanism design of stock option incentive as well as suggestions for the supervisory department to achieve efficiency of capital markets in China

Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio

Automatic designing computationally efficient neural networks has received much attention in recent years. Existing approaches either utilize network pruning or leverage the network architecture search methods. This paper presents a new framework named network adjustment, which considers network accuracy as a function of FLOPs, so that under each network configuration, one can estimate the FLOPs utilization ratio (FUR) for each layer and use it to determine whether to increase or decrease the number of channels on the layer. Note that FUR, like the gradient of a non-linear function, is accurate only in a small neighborhood of the current network. Hence, we design an iterative mechanism so that the initial network undergoes a number of steps, each of which has a small `adjusting rate' to control the changes to the network. The computational overhead of the entire search process is reasonable, i.e., comparable to that of re-training the final model from scratch. Experiments on standard image classification datasets and a wide range of base networks demonstrate the effectiveness of our approach, which consistently outperforms the pruning counterpart. The code is available at https://github.com/danczs/NetworkAdjustment

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p\u3c0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p\u3c0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p\u3c0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions