In wind tunnel experiments, the inter-car gaps are designed in such a way as to separate the force measurements for each car and prevent the interference between cars during tests. Moreover, the inter-car gap has a significant effect on the aerodynamic drag of a train. In order to guide the design of the inter-car gaps between cars in wind tunnel experiments, the impact of the inter-car gap length on the aerodynamic characteristics of a 1/8th scale high-speed train is investigated using computational fluid dynamics. The shear stress transport k-! model is used to simulate the flow around a highspeed train. The aerodynamic characteristics of the train with 10 different inter-car gap lengths are numerically simulated and compared. The 10 different inter-car gap lengths are 5, 8, 10, 15, 20, 30, 40, 50, 60, and 80 mm. Results indicate that the aerodynamic drag coefficients obtained using computational fluid dynamics fit the experimental data well. Rapid pressure variations appear in the upper and lower parts of the inter-car gaps. With the increase of the inter-car gap length, the drag force coefficient of the head car gradually increases. The total drag force coefficients of the trains with the inter-car gap length less than 10 mm are practically equal to those of the trains without inter-car gaps. Therefore, it can be concluded from the present study that 10 mm is recommended as the inter-car gap length for the 1/8th scale highspeed train models in wind tunnel experiments.

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In this paper, we comprehensively study the NLOV UV turbulence effect through simulated and experimental results. A Monte Carlo NLOS UV turbulence channel model, which incorporates the effects of multiple scattering and turbulence attenuation, is proposed based on previous work. To validate this model, a series of outdoor experiments is conducted to investigate the received-signal energy distribution and channel path loss under the turbulence circumstance for the first time. These experimental and simulated results are valuable for studying NLOS UV channel and communication system design.

In this study, the long-distance non-line-of-sight (NLOS) ultraviolet (UV) communication channel is characterised using experimental data and theoretical modelling. Experimental measurements of path loss and pulse broadening effects at distances of up to 4 km are reported and analysed, and comparisons between the field test data and a Monte Carlo multiple-scattering channel model provides strong evidence for the validity of the theoretical modelling approach. In addition, measurements probing the effects of turbulence are also considered, but in this case, the authors find limited experimental support for existing turbulence models, an important result suggesting the need for refined turbulence modelling. Finally, implications for NLOS UV communication performance at long ranges are examined. Overall, the experimental and numerical results serve to advance the study of NLOS UV channel modelling, an essential component of communication system design.

The numerical simulation based on Reynolds time-averaged equation is one of the approved methods to evaluate the aerodynamic performance of trains in crosswind. However, there are several turbulence models, trains may present different aerodynamic performances in crosswind using different turbulence models. In order to select the most suitable turbulence model, the inter-city express 2 (ICE2) model is chosen as a research object, 6 different turbulence models are used to simulate the flow characteristics, surface pressure and aerodynamic forces of the train in crosswind, respectively. 6 turbulence models are the standard k-ε, Renormalization Group (RNG) k-ε, Realizable k-ε, Shear Stress Transport (SST) k-ω, standard k-ω and Spalart-Allmaras (SPA), respectively. The numerical results and the wind tunnel experimental data are compared. The results show that the most accurate model for predicting the surface pressure of the train is SST k-ω, followed by Realizable k-ε. Compared with the experimental result, the error of the side force coefficient obtained by SST k-ω and Realizable k-ε turbulence model is less than 1 %. The most accurate prediction for the lift force coefficient is achieved by SST k-ω, followed by RNG k-ε. By comparing 6 different turbulence models, the SST k-ω model is most suitable for the numerical simulation of the aerodynamic behavior of trains in crosswind. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

BACKGROUND:The authors compared treatment adherence rates and outcome in Caucasian and African American patients with inflammatory breast cancer (IBC). METHODS: The records of 55 (25 Caucasian and 30 African American) IBC patients treated with curative intent from 1995 to 2009 were reviewed. All patients received neoadjuvant doxorubicin (Adriamycin) and/or taxane-based chemotherapy, and mastectomy with or without radiotherapy. The median follow-up period for Caucasian and African American patients was similar (39.5 months and 36.1 months, respectively). RESULTS: There was no difference between races in median age, tumor size, grade, and receptor status at diagnosis. The number of patients who completed neoadjuvant chemotherapy, surgery, and radiotherapy did not differ by race (84% of Caucasians vs 86.7% of African Americans) nor did the median length of time to complete trimodality treatment (263 [range, 207-422] days for Caucasians vs 262 [range, 165-371] days for African Americans). There was a trend toward slightly higher pathological complete response rates in Caucasian than African American women (20% in Caucasians vs 6.7% in African Americans, P ¼ .23). Despite slightly better response rates to neoadjuvant chemotherapy, Caucasian patients did not have higher 3-year local control rates (70% in Caucasians vs 64% in African Americans, P ¼ .73). However, there was a trend toward higher 3-year overall survival in Caucasian versus

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