CEDs from diagnostic and interventional imaging for pediatric oncology patients vary considerably according to diagnoses, individual clinical courses, and imaging modalities used. Increased awareness may promote strategies to reduce the radiation burden to this population.

SUMMARYThis paper presents a novel application of backstepping controller for autonomous landing of a rotary wing UAV (RUAV). This application, which holds good for the full flight envelope control, is an extension of a backstepping algorithm for general rigid body velocity control. The nonlinear RUAV model used in this paper includes the flapping and servo dynamics. The backstepping-based controller takes advantage of the 'decoupling' of the translation and rotation dynamics of the rigid body, resulting in a two-step procedure to obtain the RUAV control inputs. The first step is to compute desired thrusts and flapping angles to achieve the commanded position and the second step is to compute control inputs, which achieve the desired thrusts and flapping angles. This paper presents a detailed analysis of the inclusion of a flapping angle correction term in control. The performance of the proposed algorithm is tested using a high-fidelity RUAV simulation model. The RUAV simulation model is based on miniature rotorcraft parameters. The closed-loop response of the rotorcraft indicates that the desired position is achieved after a short transient. The Eagle RUAV control inputs, obtained using high-fidelity simulation results, clearly demonstrate that this algorithm can be implemented on practical RUAVs.

Advances in technology make it happen to have massive amount of information in the form of multiple variables per object. The use of multivariate approaches for modeling the real-life phenomena is natural in such situation. There are numerous multivariate approaches in the literature, and its a challenge to stay updated on the possibilities. Partial least squares (PLSs) are one of the many modeling approaches for high-throughput data, and its use in different fields to address the variety of problems has been increased in recent years. We therefore present an overview of PLS's applications. The objective of this paper is to give a comprehensive overview on the advances in PLS algorithm together with its applications for regression, classification, variable selection, and survival analysis problems covering genomics, chemometrics, neuroinformatics, process control, computer vision, econometric, environmental studies, and so on. We have mainly presented different PLS approaches and their applications, so that the reader can easily get an understanding of possibility to use PLS for their own field. For further reading, literature references together with software availability are provided. Figure 2. Illustration of partial least squares (PLS) algorithm, and how to use it for regression, classification, variable selection, and survival analysis, is presented. For regression, trained regression coefficients together with test data provide the fitted response, while variable selection is actually to find the subset of X. In classification and survival analysis, usually, the influential PLS scores are respectively used with linear discriminant analysis (LDA) or with quadratic discriminant analysis (QDA) and proportional hazard regression.

Background. Despite concerns regarding ionizing radiation exposures from diagnostic imaging procedures in pediatric patients, many are deemed unavoidable or even mandated by treatment protocols. A prior review at our institution found patients with lymphoma had a higher median cumulative radiation exposure (191 mSv) versus other oncology subgroups (61 mSv). Purpose. Estimations of cumulative diagnostic radiation exposures were tabulated for 5 years from the first diagnostic scan for 30 consecutive lymphoma patients diagnosed in 2001. Each individual imaging procedure was reviewed and classified as protocol mandated or discretionary (for disease surveillance, good patient care or radiologist request). Results. Almost all patients (28/29) received chemotherapy; one had surgery only. Individual cumulative radiation exposures ranged from 10 to 642 mSv. Over 5 years, 690 procedures were performed; 303 (44%) X-rays, 203 (29%) CTs, 157 (23%) radionucleotide, and 27 (4%) interventional procedures. Of these, 238 (34%) were protocol required and 452 (66%) discretionary (224 as part of good patient care for a co-morbid illness and 228 for evaluation of possible disease progression/surveillance). A total of 86/217 (40%) studies (including 43 CTs and 38 radionucleotide scans) were performed when the recurrence risk was low (>2 years off therapy). Conclusions. The majority of ionizing radiation procedures in this lymphoma cohort were discretionary. Given the excellent outcome of this group and the long-term risks; rational use of discretionary surveillance procedures is necessary. Guidelines for the appropriate use of surveillance imaging based on probability of risk recurrence must be developed in order to minimize ionizing radiation exposure. Pediatr Blood Cancer. 2010;55:407-413.

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