Abstract Short communication Multi-user data multiplexing for digital multimedia broadcasting

following a period of time of careful reflection. Now, the next generation of digital broadcast services will not be limited to digital audio but also extended to a variety of multimedia data services as well as mobile application services. However, the current approaches for transporting multimedia content over wireless networks for the DMB require significant overhead. In this paper, we propose a new approach for multi-user data multiplexing with several access points serving a number of wireless terminals for the DMB. By modifying the multiplexer header, multiplexing time, and handling of time-critical data, the duplication overhead can be considerably decreased when compared to existing schemes. Ó 2006 Elsevier B.V. All rights reserved

Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning

Most models for predicting malignant pancreatic intraductal papillary mucinous neoplasms were developed based on logistic regression (LR) analysis. Our study aimed to develop risk prediction models using machine learning (ML) and LR techniques and compare their performances. This was a multinational, multi-institutional, retrospective study. Clinical variables including age, sex, main duct diameter, cyst size, mural nodule, and tumour location were factors considered for model development (MD). After the division into a MD set and a test set (2:1), the best ML and LR models were developed by training with the MD set using a tenfold cross validation. The test area under the receiver operating curves (AUCs) of the two models were calculated using an independent test set. A total of 3,708 patients were included. The stacked ensemble algorithm in the ML model and variable combinations containing all variables in the LR model were the most chosen during 200 repetitions. After 200 repetitions, the mean AUCs of the ML and LR models were comparable (0.725 vs. 0.725). The performances of the ML and LR models were comparable. The LR model was more practical than ML counterpart, because of its convenience in clinical use and simple interpretability

Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning

Most models for predicting malignant pancreatic intraductal papillary mucinous neoplasms were developed based on logistic regression (LR) analysis. Our study aimed to develop risk prediction models using machine learning (ML) and LR techniques and compare their performances. This was a multinational, multi-institutional, retrospective study. Clinical variables including age, sex, main duct diameter, cyst size, mural nodule, and tumour location were factors considered for model development (MD). After the division into a MD set and a test set (2:1), the best ML and LR models were developed by training with the MD set using a tenfold cross validation. The test area under the receiver operating curves (AUCs) of the two models were calculated using an independent test set. A total of 3,708 patients were included. The stacked ensemble algorithm in the ML model and variable combinations containing all variables in the LR model were the most chosen during 200 repetitions. After 200 repetitions, the mean AUCs of the ML and LR models were comparable (0.725 vs. 0.725). The performances of the ML and LR models were comparable. The LR model was more practical than ML counterpart, because of its convenience in clinical use and simple interpretability

pn-Heterojunction Effects of Perylene Tetracarboxylic Diimide Derivatives on Pentacene Field-Effect Transistor

We investigated the heterojunction effects of perylene tetracarboxylic diimide (PTCDI) derivatives on the pentacene-based field-effect transistors (FETs). Three PTCDI derivatives with different substituents were deposited onto pentacene layers and served as charge transfer dopants. The deposited PTCDI layer, which had a nominal thickness of a few layers, formed discontinuous patches on the pentacene layers and dramatically enhanced the hole mobility in the pentacene FET. Among the three PTCDI molecules tested, the octyl-substituted PTCDI, PTCDI-C8, provided the most efficient hole-doping characteristics (p-type) relative to the fluorophenyl-substituted PTCDIs, 4-FPEPTC and 2,4-FPEPTC. The organic heterojunction and doping characteristics were systematically investigated using atomic force microscopy, 2D grazing incidence X-ray diffraction studies, and ultraviolet photoelectron spectroscopy. PTCDI-C8, bearing octyl substituents, grew laterally on the pentacene layer (2D growth), whereas 2,4-FPEPTC, with fluorophenyl substituents, underwent 3D growth. The different growth modes resulted in different contact areas and relative orientations between the pentacene and PTCDI molecules, which significantly affected the doping efficiency of the deposited adlayer. The differences between the growth modes and the thin-film microstructures in the different PTCDI patches were attributed to a mismatch between the surface energies of the patches and the underlying pentacene layer. The film-morphology-dependent doping effects observed here offer practical guidelines for achieving more effective charge transfer doping in thin-film transistors