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Abstract:The aim of this study is to propose a novel data analysis approach, 'Analysis of Characterizing Phases' (ACP), that detects and examines phases of variance within a sample of curves utilizing the time, magnitude and magnitude-time domain; and to compare the findings of ACP to discrete point analysis in identifying performance related factors in vertical jumps. Twenty five vertical jumps were analyzed. Discrete point analysis identified the initial-to-maximum rate of force development (p = .006) and the time from initial-tomaximum force (p = .047) as performance related factors. However, due to inter-subject variability in the shape of the force curves (i.e non-, uni-and bi-modal nature), these variables were judged to be functionally erroneous. In contrast, ACP identified the ability to:apply forces for longer (p < .038), generate higher forces (p < .027) and produce a greater rate of force development (p < .003) as performance related factors. Analysis of Characterizing Phases showed advantages over discrete point analysis in identifying performance related factors because it: (i) analyses only related phases, (ii) analyses the whole data set, (iii) can identify performance related factors that occur solely as a phase, (iv) identifies the specific phase over which differences occur, and (v) analyses the time, magnitude and combined magnitude-time domains.

Intraoperative neuromonitoring (IONM) has yielded an increasing effect on thyroid surgery. During IONM, the recurrent laryngeal nerve is stimulated electrically and an acoustically transformed electromyographic signal is derived via either a needle electrode placed in the vocalis muscle or an electrode adjusted to the intubation tube. The IONM is used for identifying and predicting the function of the recurrent laryngeal nerve. Especially under difficult anatomic conditions, IONM has proven a valuable tool for identification of recurrent laryngeal nerves. This can lead to decreased occurrence of nerve palsy rates, as shown in numerous studies. The reliability of the IONM signal (defined as the correlation between intraoperative signal interpretation and postoperative vocal cord function) is reflected by a specificity as high as 98.2%, as shown by German multicenter studies. Thus, normal vocal cord function could be demonstrated postoperatively in over 98.2% of patients with intraoperatively unchanged neuromonitoring signals. If the neuromonitoring signal changed during operation, 39% of the patients suffered from transient vocal cord immobility and 12% had permanent loss of vocal cord function.

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Abstract. The notion of ball convexity, considered in finite dimensional real Banach spaces, is a natural and useful extension of usual convexity; one replaces intersections of half-spaces by suitable intersections of balls. A subset S of a normed space is called ball convex if it coincides with its ball hull, which is obtained as intersection of all balls (of fixed radius) containing S. Ball convex sets are closely related to notions like ball polytopes, complete sets, bodies of constant width, and spindle convexity. We will study geometric properties of ball convex bodies in normed spaces, for example deriving separation theorems, characterizations of strictly convex norms, and an application to complete sets. Our main results refer to minimal representations of ball convex bodies in terms of their ball exposed faces, to representations of ball hulls of sets via unions of ball hulls of finite subsets, and to ball convexity of increasing unions of ball convex bodies.

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