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The Eastern Alps are a belt of major deformation formed by the convergence and collision of Europe with the Adriatic microcontinent. A major tectonic boundary can be defined between the dominantly continental Austroalpine domain, which represents the northerly fringe of Adria; and the Pennine oceanic domain, which once lay between the Austroalpine domain and Europe. This boundary is one of the key areas for unravelling the convergent tectonic history of the Eastern Alps. The main emphasis of this thesis is on the deformational behaviour of the Austroalpine domain and its implications for the regional tectonic processes that were instrumental in forming the structure of the Eastern Alps. The data for this work are derived from structural and metamorphic studies in the S.E. Tauern in profiles straddling the boundary, and a review of the published regional geology. The first manifestation of convergence is the development of a broad zone of thickened crust, including both Pennine and Austroalpine units, which underwent Cretaceous burial metamorphism. Postdating this thermal event in the Austroalpine domain, there was a further phase of regional deformation, which caused substantial reduction in the structural thickness. To the south of the Tauern Window, a study of the associated kinematic development gives a minimum estimate of 10km for this thinning, which radiometric dating suggests took place while convergence was still active. A comparable 10km post-metamorphic thinning is suggested throughout the Austroalpine domain in the Eastern Alps by the shortfall in the overburden compared to the depth of burial indicated by the Cretaceous metamorphic conditions. Major extension in a dominantly convergent tectonic setting cannot be accounted for by the paradigm of plate tectonics and implies that body forces acting on the thickened crust of the destructive margin were a major driving force for deformation.

Many authors have proposed that sprint and distance front crawl swimmers differ in their stroke characteristics, however little three-dimensional quantitative data is provided to support these assumptions. It is currently unknown whether sprint and distance swimmers exhibit distinct stroke characteristics when swimming at the same pace. There were two main purposes of this study: 1) to determine whether there are distinct kinematic and kinetic differences between sprint and distance front crawl swimmers, and 2) to investigate whether stroke characteristics of front crawl swimmers, in terms of kinematic and kinetic variables change with swimming speed. Fifteen male national/international front crawl swimmers (17.87 +/- 2.33yrs; 73.87 +/- 8.72kg; 183.02 +/- 6.84cm) volunteered to participate in this study. This sample was composed of seven sprint (SG) and eight distance (DG) swimmers. Each testing session required swimmers to perform four 25m sprints and one 400m max effort (front crawl), with no pacing strategy, in a randomised order. Each trial was performed through a 6.75m3 calibrated space and recorded by six gen-locked JVC KY32 CCD cameras (4 below and 2 above water) sampling at a frequency of 50 fields per second. All trials were processed using ‘APAS’ software to obtain 3D coordinate data. Anthropometric measures were quantified using the elliptical zone method. Both data sets were entered into a bespoke MATLAB program which output: average swim velocity (Vav), stroke length (SL), stroke frequency (SF), stroke index (SI), vertical and lateral displacement for each segment, shoulder and hip roll angle, and elbow joint angle variables (1st back, shoulder x, end back, hand exit and recovery elbow angle). Stroke phase (entry, pull, push and recovery) durations (%) were quantified at instants corresponding to percentiles of the stroke cycle. Centre of mass position data were obtained from the digitised 3D data using a 14 segment rigid link body model in conjunction with the body segment parameter data obtained by the elliptical zone method. Component whole body velocity (VCOMHor), acceleration (accCOM) and net force (forceCOM) were derived from the centre of mass position data. Variables were statistically analysed in SPSS v.14.0, using a General Linear Model, repeated measures analysis of variance. The results indicated that the groups differed (p<0.05) with respect to the duration of the pull phase, the occurrence of max left and right shoulder roll and the temporal sequencing of the shoulders and hips rolling at both sprint and distance pace. Other variables approached significance between the groups, particularly when distance swimming, such as the duration of the push phase (p=0.082), the Vav (p=0.071) and average VCOMHor (p=0.071). The stroke kinematic variables that changed between paces (p<0.05) were the duration of the entry, pull, push, hand exit and recovery phases; the elbow angle at the end back position and the push phase range; total shoulder and hip roll; the sum average vertical displacement of the foot; the time to max vertical and lateral displacement of the finger; the time at max right elbow extension; the average VCOMHor, Min VCOMHor and Max VCOMHor. The stroke kinetic variables that changed between paces (p<0.05) were the Min accCOM, Max accCOM, range of accCOM, min forceCOM and max forceCOM. Other variables approached significance between the paces such as the entry elbow angle (p=0.084), the max right elbow extension (p=0.056), the finger lateral range (p=0.067) and the time to max accCOM (p=0.079). The SG displayed shorter durations of the pull and push phases than the DG for both paces, which was linked to the faster horizontal velocity and/or vertical acceleration of the hand. The sequencing order of the shoulders and hips changed between groups and paces, which was speculated to be controlled by the magnitude of the leg-kick. The main changes between paces were the greater magnitude of elbow angle at both the end back position and the push phase range, which contributed to the adjustment of kinetic variables. SL, SF, SI, Vav and the duration of the all the stroke phases changed between sprint and distance pace in order to meet the physiological requirements of the race distance. The prolonged duration of the entry phase, when distance swimming, resulted in a delayed attainment of the catch position and maximum stroke depth. Moreover, the magnitude of shoulder and hip roll increased at distance compared to sprint pace, which in turn influenced the magnitude of average vertical and range of lateral displacement of the finger between paces. In conclusion, contrary to the literature, SG and DG differed only with respect to the duration of the pull and push stroke phases and the sequencing order of the shoulders and hips. All swimmers adjust the majority of kinematic and kinetic variables depending on the swim pace in order to optimise performance for that race distance.

This work introduces the use of optimal control methods for path planning and control of autonomous vehicles in an obstacle-rich environment. Traditional techniques harbor non-optimal, closed architectures primarily derived at a time when computational complexity could significantly hinder overall system performance. Advancements in computing power, miniaturization, and numerical methods permit the utilization of online, optimal path planning and control, thereby improving system flexibility and autonomy. The backbone of this concept is state-of-the-art optimal control techniques involving pseudospectral methods and sequential quadratic programming. Although this research focuses on a robotic car or Unmanned Ground Vehicle (UGV), several systems, including an Unmanned Aerial Vehicle (UAV) and a pendulum on a rotational base, are detailed for the purpose of illustrating the technique's modularity. With respect to the UGV, optimal control methods permit the optimization of maneuver parameters while accounting for complex vehicle kinematics and workspace obstacles, represented as dynamic and path constraints respectively. The path constraints are modeled such that an obstacle of any shape or size can be included. Maneuvering trajectories are first generated in an open-loop architecture, followed by an application of these same techniques in feedback form. Lastly, model fidelity is increased to improve control over vehicle behavior and closed-loop performance and a local knowledge scenario is evaluated.

Sharks are an objectively diverse group of animals; ranging in maximum size from 2,000cm (whale shark) to 17cm (dwarf lantern shark); occupying habitats that are periodically terrestrial (epaulette shark) to the deepest parts of the ocean (frilled shark); relying on a diversity of diets from plankton to marine mammals; with vast amounts of morphology diversity such as the laterally expanded heads of hammerhead species, the elongate caudal fins of thresher species, and the tooth embedded rostrum of saw shark species representing some of the anatomical extremes. Yet despite these obvious differences in morphology, physiology, and ecology, the challenges associated with studying hard to access, large bodied, pelagic animals have limited our comparative understanding of form and function as it relates to swimming within this group. The majority of shark swimming studies examine species that succeed in captivity, which are usually benthic associated sharks that spend time resting on the substrate. These studies have also been limited by the use of flumes, in which the unidirectional flow and small working area precludes the analysis of larger animals, volitional swimming, and maneuvering. The few existing volitional kinematics studies on sharks quantify two-dimensional kinematics which are unable to capture movements not observable in the plane of reference. With this study, we quantified the volitional swimming kinematics of sharks in relation to morphological, physiological, and ecological variation among species. We developed a technique to analyze three-dimensional (3D) kinematics in a semi-natural, large volume environment, which, to our knowledge, provides the first3D analysis of volitional maneuvering in sharks. We demonstrated that Pacific spiny dogfish and bonnethead sharks rotate the pectoral fins substantially during yaw (horizontal) maneuvering and is correlated with turning performance. We proposed that ecomorphological differences correlate with the varied maneuvering strategies we observed between the two species. We also found that there is some mechanical constraint on shark pectoral fin shape that is explained by phylogenetic relationships but describe a continuum of morphological variables within that range. We propose standardized terminology and methodology for the future assessment of shark pectoral fin morphology and function. As with previous studies, the ease of access to species was a challenge in this study and future studies should continue to assess the functional ecomorphology of shark pectoral fins among species. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

The ability to perform well during the sprint start and early acceleration phases of sprint running is critical. Many forms of training interventions are utilised to give a sprinter a competitive edge over their opponents in these particular phases. Despite this fact, there has been limited research on the technical and power type training strategies appropriate to improve sprint kinematics and the associated sprint performance in the sprint start and early acceleration phases. PURPOSE: To determine the best sprint start and early acceleration phase kinematic determinants, investigate the effect that load has on the kinematics of the sprint start and early acceleration performance and to determine how various physical characteristics may influence both resisted and unresisted sprint running. METHODS: Ten male track sprinters (mean ± SD: age 20 ± 3 years; height 1.82 ± 0.06 m; weight 76.7 ± 7.9 kg; 100 m personal best: 10.87 + 0.36 s {10.37 - 11.42 s}) attended two testing sessions. The first session required the athletes to sprint twelve 10 m sprints from a block start under unresisted and resisted (10% & 20% body mass) sled conditions. The second session required each athlete to complete an anthropometric assessment (height, mass, 3 bone lengths, 2 bone widths) and a variety of vertical (squat jump, countermovement jump, continuous straight legged jump) and horizontal (single leg hop for distance, single leg triple hop for distance) jump tests (3 trials each). Centre of gravity, joint and segment kinematics were calculated from 2D analysis utilising a kinematic analysis system (Ariel Performance Analysis System, U.S.A.). Means and standard deviations are presented for kinematic and performance measures. Pearson's product-moment correlation coefficients were employed to establish relationships between sprint start (block) performance variables and 10 m sprint performance. A linear regression analysis was used to quantify the relationships between the dependent variables (start performance and 10 m sprint time) and selected kinematic independent variables. ANOVA's with repeated measures were used to determine if there was a significant interaction between the kinematics under the various loaded conditions. A stepwise multiple regression and linear regression analysis were used for the prediction of unresisted and resisted sprint times from anthropometrical and functional performance measures. RESULTS: Mean horizontal block acceleration was identified as the start performance variable with the strongest relationship to 10 m sprint time. The most significant kinematic predictors of mean horizontal block acceleration were a large horizontal block velocity, short start time, and low thigh angle of the front block leg with respect to the horizontal at block takeoff. Sprint time over 10 m was best predicted by a large mean horizontal block acceleration (sprint start performance), increased angle of the front arm shoulder at step takeoff, and increased angle of front upper arm at step takeoff. Sprint start kinematics significantly altered as a result of resisted sled towing were start time (increase) and push-off angle from the blocks (decrease). Step length, stance time and propulsion time significantly increased, whereas flight time and flight distance significantly decreased under loaded conditions. A load of 20% body mass was revealed to be the better training load to utilise during resisted sled sprinting, especially for athletes who performed faster than 2.10 s for a 10 m sprint from a block start. The countermovement jump exercise was a strong predictor of both 10 m and 100 m sprint time. The continuous straight legged jump test was revealed to be a good predictor of resisted sprints over 10m.CONCLUSION: Consideration should be given to the technical training aspects of sprint start performance and forceful arm movements during step takeoff for improving sprint start and early acceleration sprint performance from starting blocks. These technical training aspects should also be supplemented with resisted sled towing with a load of 20% body mass and countermovement jump training to improve sprint ability.

The phase of greatest acceleration (0-30 metres) during sprinting is thought to be critical for success in many sporting situations. Methods for improving acceleration phase performance are therefore an important area of study for conditioners and sports scientists. Typically a variety of resistance training techniques are used to improve strength and power of the lower limb musculature that is important to sprinting performance. One such technique is resisted sprinting which involves the use of apparatus such as weighted vests and sleds to provide movement specific overload to athletes. The purpose of this thesis was primarily, to compare sprint times, step variables and joint kinematics when sprinting with a vest loaded at 15% and 20% of the athlete's body mass and towing a sled with 15% and 20% of body mass. A secondary aim was to examine the effect of a six-week training program utilising resisted sprinting on acceleration phase performance in three athletes.In the first study, 20 semi-elite subjects performed five 30-metre sprints: one unloaded sprint, two sled sprints loaded at 15% of their body mass and 20% of their body mass, and two vest sprints with the same loads relative to body mass. Each sprint was videoed in the sagittal plane at five, 15 and 25 metres from the start of the 30-metre sprint and times were recorded at 10 and 30-metres using timing lights. Video data were digitised and the following step variables were calculated: step length, step frequency, stance phase duration and swing phase duration. Stance phase angles of the trunk, thigh, knee and ankle were also calculated. Step length, step frequency and swing phase duration during vest and sled sprinting were found to decrease significantly (P<0.05) when compared to unloaded sprinting values. Stance phase duration during vest and sled sprinting increased compared to unloaded sprinting values (P<0.05). Additionally, sled towing displayed significantly greater (P<0.05) trunk flexion at foot strike and toe-off, and significantly greater (P<0.05) knee flexion at foot strike than both the unloaded and vest sprinting conditions. Sled towing also induced significantly greater thigh extension at toe-off compared to the vest conditions (P<0.05). Thus the addition of load to the athlete via vest sprinting and sled towing may influence performance in different ways, and hence the objective of the athlete should be considered when choosing which of these techniques to use.In the second study, a single subject research design was utilised to assess whether sled towing and vest sprinting resulted in changes in performance over a six-week period of training. In this study, three subjects trained twice a week for six weeks using resisted sprinting. Subjects were randomly assigned to sled training, vest training or combination training (one training session a week with each apparatus). Subjects were tested at baseline, after three weeks of training and after six weeks of training for 10 and 30-metre sprint times and selected step variables (step length, step frequency and stance phase duration). Data analysis involved both visual analysis of graphed data and statistical analysis using the two standard deviation band method. The combination training subject improved performance over both 10 and 30 metres. Step variable data were inconclusive regarding the mechanisms behind these improvements. Neither sled towing nor vest sprinting resulted in significant improvements in performance. The results indicated that the use of both training apparatus in unison may be required in order to improve performance during the acceleration phase of sprinting.

There are many situations in which contact between two bodies is at a single point so there can be no tensile (force). This form of contact only provides a single degree of restraint, and is defined as a unidirectional point contact. The analysis of Reuleaux shows that four suitably placed frictionless point contacts are required to completely restrain an object in a plane. The objective of the thesis is to allow user-placement of three contacts and to find acceptable range for placement of the fourth. If the fourth contact is anywhere in the range, the four forces fulfill the requirement for total planar restraint, i.e. all translations and rotations in a plane are prevented. This project considers the directions and placement allowed for the fourth force but does not take into consideration the magnitudes or friction coefficients of any of the four forces. In this research a program named Planar Restraint Design Assistant (PRDA) was developed to analyze positions of the four restraint forces. A planar object is first specified by the user; the program accepts AutoCAD images for more complex objects. For three given restraint forces PRDA determines a range of the fourth force such that total restraint is achieved. In addition, PRDA allows the user to arrange three restraint forces until a desired range of the fourth restraint force is obtained. Results are shown in visual form with accompanying graphs for numerical interpretation. A program user's guide and a program learning guide are provided as shown in the report with illustrative examples. Program source code in QuickBASIC is included in the report. / Graduation date: 1995