Systems analysis of gaze stabilization behaviour and imaging of motor systems in the blowfly calliphora

A fast and powerful gaze stabilization reflex supports self-motion es- timation and flight control in flies. Changes in body posture are conveyed by a variety of sensory modalities and compensated for by fast and accurate head movements. This thesis aims to further our understanding of the behavioural basis of compensatory head move- ments, and presents a first foray into the in vivo imaging of the motor systems that actuate these control reflexes. Major sensors that contribute to gaze stabilisation are the visual ocelli and compound eyes on the head, and the mechanosensory halteres on the thorax. The integration of visual feedback and mechanosensory feedforward control gives rise to a two-degree-of-freedom controller, a design which is extensively used in engineering applications. I per- formed a linear systems analysis of compensatory head roll in response to forced thorax oscillations in the fly. The feedforward pathway ex- hibited a high bandwidth and constant gain and reduced the response delay of the reflex. Large stability margins in the feedback pathway supplied by the compound eyes guaranteed stable behaviour in the face of response variability. The occlusion of the ocelli did not change the gain of the feedback pathway, but significantly reduced the la- tency. I investigated the use of iodine-enhanced computed x-ray microto- mography (microCT) to perform fast three-dimensional imaging of the neck and flight motor systems. Virtual dissections of major func- tional units illustrate the possibilities and limitations of microCT. To observe the configuration of motor systems in behaving flies I per- formed gated microtomography using hard x-rays at the TOMCAT beamline of the Swiss Light Source, a third generation synchrotron. While 3D tomograms of the neck motor system proved elusive, this thesis presents the first in vivo tomograms of the flight motor and wing hinge during tethered flight.Open Acces

Passive Pneumatic Stabilization Device for Assisting in Reduction of Femoral Shaft Fractures

During treatment of femoral shaft fractures, not only the actual fracture reduction but also the retention of the achieved reduction is essential. Substantial forces may apply to the bone fragments, due to multidirectional muscular contraction. Furthermore, forces from manipulation of one bone fragment may be transferred over the soft tissues onto the other fragments, thus hindering accurate fracture reduction. Once a sufficient reduction has been achieved, this position must be retained whilst definitive internal fixation is performed. Conventional methods comprise mounting patients on a traction table and applying manual distraction or employing special distraction devices, such as the AO distractor device. These approaches, however, only insufficiently stabilize both main fragments. For example, on the traction table the proximal femoral fragment can pivot around the hip joint thus complicating precise reduction. A novel pneumatic stabilization device to assist surgeons during operative procedures is described. This passive holding device "Passhold” connects to one main fragment through a minimally invasive bone interface and statically locks the fragment's position. Thereafter, only the other main fragment is manipulated to achieve reduction. Mutual interference of the reciprocal fragment positions, due to soft-tissue force transfer during manipulation, is avoided. The authors examined the stability of the novel retention device on a test rig and proved its functionality under sterile settings using cadaver tests. It is concluded that this device largely facilitates the operative procedure in femoral shaft fractures, is sufficiently stable and ergonomically suitable for intraoperative deploymen

In Vivo Time- Resolved Microtomography Reveals the Mechanics of the Blowfly Flight Motor

Dipteran flies are amongst the smallest and most agile of flying animals. Their wings are driven indirectly by large power muscles, which cause cyclical deformations of the thorax that are amplified through the intricate wing hinge. Asymmetric flight manoeuvres are controlled by 13 pairs of steering muscles acting directly on the wing articulations. Collectively the steering muscles account for <3% of total flight muscle mass, raising the question of how they can modulate the vastly greater output of the power muscles during manoeuvres. Here we present the results of a synchrotron-based study performing micrometre-resolution, time-resolved microtomography on the 145 Hz wingbeat of blowflies. These data represent the first four-dimensional visualizations of an organism's internal movements on sub-millisecond and micrometre scales. This technique allows us to visualize and measure the three-dimensional movements of five of the largest steering muscles, and to place these in the context of the deforming thoracic mechanism that the muscles actuate. Our visualizations show that the steering muscles operate through a diverse range of nonlinear mechanisms, revealing several unexpected features that could not have been identified using any other technique. The tendons of some steering muscles buckle on every wingbeat to accommodate high amplitude movements of the wing hinge. Other steering muscles absorb kinetic energy from an oscillating control linkage, which rotates at low wingbeat amplitude but translates at high wingbeat amplitude. Kinetic energy is distributed differently in these two modes of oscillation, which may play a role in asymmetric power management during flight control. Structural flexibility is known to be important to the aerodynamic efficiency of insect wings, and to the function of their indirect power muscles. We show that it is integral also to the operation of the steering muscles, and so to the functional flexibility of the insect flight motor

Wider Access to Genotypic Space Facilitates Loss of Cooperation in a Bacterial Mutator

Understanding the ecological, evolutionary and genetic factors that affect the expression of cooperative behaviours is a topic of wide biological significance. On a practical level, this field of research is useful because many pathogenic microbes rely on the cooperative production of public goods (such as nutrient scavenging molecules, toxins and biofilm matrix components) in order to exploit their hosts. Understanding the evolutionary dynamics of cooperation is particularly relevant when considering long-term, chronic infections where there is significant potential for intra-host evolution. The impact of responses to non-social selection pressures on social evolution is arguably an under-examined area. In this paper, we consider how the evolution of a non-social trait – hypermutability – affects the cooperative production of iron-scavenging siderophores by the opportunistic human pathogen Pseudomonas aeruginosa. We confirm an earlier prediction that hypermutability accelerates the breakdown of cooperation due to increased sampling of genotypic space, allowing mutator lineages to generate non-cooperative genotypes with the ability to persist at high frequency and dominate populations. This may represent a novel cost of hypermutability

Low-Overhead Reinforcement Learning-Based Power Management Using 2QoSM

With the computational systems of even embedded devices becoming ever more powerful, there is a need for more effective and pro-active methods of dynamic power management. The work presented in this paper demonstrates the effectiveness of a reinforcement-learning based dynamic power manager placed in a software framework. This combination of Q-learning for determining policy and the software abstractions provide many of the benefits of co-design, namely, good performance, responsiveness and application guidance, with the flexibility of easily changing policies or platforms. The Q-learning based Quality of Service Manager (2QoSM) is implemented on an autonomous robot built on a complex, powerful embedded single-board computer (SBC) and a high-resolution path-planning algorithm. We find that the 2QoSM reduces power consumption up to 42% compared to the Linux on-demand governor and 10.2% over a state-of-the-art situation aware governor. Moreover, the performance as measured by path error is improved by up to 6.1%, all while saving power

Low-Overhead Reinforcement Learning-Based Power Management Using 2QoSM

With the computational systems of even embedded devices becoming ever more powerful, there is a need for more effective and pro-active methods of dynamic power management. The work presented in this paper demonstrates the effectiveness of a reinforcement-learning based dynamic power manager placed in a software framework. This combination of Q-learning for determining policy and the software abstractions provide many of the benefits of co-design, namely, good performance, responsiveness and application guidance, with the flexibility of easily changing policies or platforms. The Q-learning based Quality of Service Manager (2QoSM) is implemented on an autonomous robot built on a complex, powerful embedded single-board computer (SBC) and a high-resolution path-planning algorithm. We find that the 2QoSM reduces power consumption up to 42% compared to the Linux on-demand governor and 10.2% over a state-of-the-art situation aware governor. Moreover, the performance as measured by path error is improved by up to 6.1%, all while saving power