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32), regional (p = 0.50), or distant (p = 0.76) failures between unilateral and bilateral radiation therapy. By Kaplan-Meier estimates, OS (3-year OS bilateral = 71.67%, unilateral = 77.90%, p = 0.50) and DFS (3-year DFS bilateral = 77.92%, unilateral = 69.43%, p = 0.63) were similar between the two treatment approaches. Lastly, multivariate analysis did not demonstrate any significant differences in outcome by treatment volumes (OS HR = 0.74, 95% CI 0.31, 1.81, p = 0.51; DFS HR 0.68, 95% CI 0.24, 1.93, p = 0.47). CONCLUSIONS Unilateral radiation therapy compared with bilateral produced similar survival.BACKGROUND Sexually explicit media exposure during early adolescence has been found to be associated with risky sexual behavior. However, previous study suffered from methodological issue, such as selection bias. Furthermore, little is known about the effect of multi-modality sexually explicit media exposure on risky sexual behavior, and how this relationship can be applied to non-western societies. OBJECTIVES This study aimed to improve upon previous studies by using instrumental variable estimation. In addition, this study also included multi-modality of sexually explicit media and three risky sexual behavior measure from a sample of Taiwanese adolescents. METHODS Participants were recruited from a prospective longitudinal study (Taiwan Youth Project). All were in 7th grade (mean age = 13.3) when the study was initiated in 2000. Sexually explicit media exposure, including ever-exposure and number of modalities exposed to, was measured in wave 2 (8th grade). Risky sexual behavior was measured in waves 8 (mean age = 20.3) and 10 (mean age = 24.3). A two-stage least squares regression was employed, with pubertal timing as the instrumental variable. RESULTS About 50% of participants had been exposed to sexual media content by 8th grade, from an average of one modality. PQR309 research buy Sexually explicit media exposure predicted early sexual debut, unsafe sex, and multiple sexual partners (all p less then .05). Furthermore, exposure to more media modalities increased the likelihood of risky sexual behaviors. However, only the effect on early sexual debut was gender invariant. CONCLUSIONS Exposure to sexually explicit media in early adolescence had a substantive relationship with risky sexual behavior in the emerging adulthood. Knowledge of this causal like effect provides a basis for building better preventive programs in early adolescence. One prominent way is early education on media literacy, and physicians themselves may need to be familiar with such content to initiate it.PURPOSE To accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a post-processing 3D denoising technique to maintain high accuracy and precision. METHODS 3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and low standard deviation (as a surrogate for precision) is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Following the results from the healthy subjects, three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising. RESULTS In the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P = 0.99 and P = 0.99 for accuracy, P = 0.64 and P = 0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P less then 0.05) but was independent on the number of T1-weighted images after denoising. CONCLUSION We demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.The traditional full-scan method is commonly used for identifying critical links in road networks. This method simulates each link to be closed iteratively and measures its impact on the efficiency of the whole network. It can accurately identify critical links. However, in this method, traffic assignments are conducted under all scenarios of link disruption, making this process prohibitively time-consuming for large-scale road networks. This paper proposes an approach considering the traffic flow betweenness index (TFBI) to identify critical links, which can significantly reduce the computational burden compared with the traditional full-scan method. The TFBI consists of two parts traffic flow betweenness and endpoint origin-destination (OD) demand (rerouted travel demand). There is a weight coefficient between these two parts. Traffic flow betweenness is established by considering the shortest travel-time path betweenness, link traffic flow and total OD demand. The proposed approach consists of the following main steps. First, a sample road network is selected to calibrate the weight coefficient between traffic flow betweenness and endpoint OD demand in the TFBI using the network robustness index. This index calculates changes in the whole-system travel time due to each link's closure under the traditional full-scan method. Then, candidate critical links are pre-selected according to the TFBI value of each link. Finally, a given number of real critical links are identified from the candidate critical links using the traditional full-scan method. The applicability and computational efficiency of the TFBI-based approach are demonstrated for the road network in Changchun, China.

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