Purpose Sphingosine kinases (SK1 and SK2) regulate tumor growth by generating the mitogenic and pro-inflammatory lipid sphingosine 1-phosphate (S1P). This phase I study investigated the safety, pharmacokinetics, pharmacodynamics and anti-tumor activity of ABC294640, a first-in-class orally-available inhibitor of SK2. Experimental Design Escalating doses of ABC294640 were administered orally to patients with advanced solid tumors in sequential cohorts at the following dose levels: 250 mg qd, 250 mg bid, 500 mg bid and 750 mg bid, continuously in cycles of 28 days. Serial blood samples were obtained to measure ABC294640 concentrations and sphingolipid profiles. Results 22 patients were enrolled, and 21 received ABC294640. The most common drug-related toxicities were nausea, vomiting and fatigue. Among the four patients at 750 mg bid, one had dose-limiting grade 3 nausea and vomiting, and two were unable to complete Cycle 1 due to diverse drug-related toxicities. The 500 mg bid dose level was established as the Recommended Phase II Dose. ABC294640 administration resulted in decreases in S1P levels over the first 12 hours, with return to baseline at 24 hours. The best response was a partial response in a patient with cholangiocarcinoma at 250 mg qd, and stable disease was observed in 6 patients with various solid tumors across dose levels. Conclusions At 500 mg bid, ABC294640 is well tolerated and achieves biologically-relevant plasma concentrations. Changes in plasma sphingolipid levels may provide a useful pharmacodynamic biomarker for ABC294640.

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The use of neural network techniques to localize an acoustic point source in a homogeneous medium is demonstrated. The input data are the cosines of the phase difference measurements at an array with N detectors. Only the most fundamental types of neural network systems will be considered. Use will be made of linear and sigmoid-type neurons in a single-layer network. The performance of the single-layer network is very satisfactory for a wide range of configuration parameters if the resolution and sampling conditions are satisfied. Once the parameters of the neural network are determined, the computational effort to determine a new source location is minimal. However, when a source/detector configuration is considered that does not satisfy the resolution and sampling conditions, the single-layer network will not consistently perform well.

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Mismatched training and testing conditions for speaker identification exist when speech is subjected to a different channel for the two cases. This results in diminished speaker identification performance. Finding features that show little variability to the filtering effect of different channels will make speaker identification systems more robust thereby achieving a better performance. It has been shown that subtracting the mean of the pole filtered linear predictive (LP) cepstrum from the actual LP cepstrum results in a robust feature. This feature is known as the pole filtered mean removed LP cepstrum. Another robust feature is the adaptive component weighted (ACW) cepstrum particularly with mean removal. In this paper, we combine the ACW cepstrum with the pole filtering concept to configure a more robust new feature, namely, the pole filtered mean removed ACW cepstrum. This new method is fast and shows a higher performance then the pole filtered mean removed LP cepstrum and the mean removed ACW cepstrum. Experimental results are given for the TIMIT database involving a variety of mismatched conditions.

(CUA) has an affiliation with the local high schools in the Washington DC area whose goal is to stimulate interest in engineering among high school students. There are currently 14 participating high schools, many of which include a student population with high minority and female enrollment (two of the schools are all-girls). As part of this initiative, CUA is currently funded by the National Science Foundation on a 4 year project called "The Connections Program". Through this program, the affiliated high schools have access to the computing facilities of the University. This includes Internet access, use of CUA's scientific applications (e.g., math and science related applications such as Matlab and Mathematica), and on-line library catalog access. A crucial part of the project is multi-tiered training. An ethics statement and fair usage policy has been drafted to ensure that the provided resources will be used in the appropriate fashion.

Vertical integration is a powerful curricular tool that allows students to better appreciate the interconnections among the concepts acquired and learned in different courses. it can be used to bring a modern topic at all levels of the undergraduate curriculum with little additional resources. this paper gives a brief survey of various vertical integration efforts and describes one effort at integrating biometrics throughout the curriculum. the focus is on three senior level projects (speaker, face and iris recognition) that not only rely on vertical integration but also reinforce design, software skills and knowledge of stEm concepts. the freshman through junior levels are also described. the assessment results show that students acquire specific learning outcomes and perceive the value of vertical integration. iEEE circUits And systEms mAgAzinE third QUArtEr 2014

earned her MBA from Widener University and dual degrees in Industrial Engineering and Business Management from The Pennsylvania State University. Ms. Basantis spent 15 years in industry at the Boeing Company working as an Engineer on projects related to defense aircraft including the V-22 Osprey and CH-46 and CH-47 tandem rotor helicopters along with being a Composite Manger on the 757 and 767 commercial aircraft programs. Ms. Basantis has experience in the development and implementation of new and innovative technologies in the manufacturing processes associated with revolutionary, new assembly methods and concepts for aircraft application. She is experienced in the utilization of lean manufacturing, total quality management, and ISO concepts and specifications in the implementation of these processes. As Engineering Outreach Director, Ms. Basantis collaborates with industry on initiatives that include, but not limited to professionalism, internship experience, job placement, student development and enrichment, as well as concentrated faculty research. Ms. Basantis provides leadership to The College of Engineering's STEM initiatives and has done so for the past 10 years. Middle and High school camps and field experiences are held under her guidance and expertise.