The Enduring Power of Comic Strips

A chapter in an edited volumeThis chapter argues that the power of comics resides in the historic appearance and modulation of the affective possibilities of the comic strip register. On this basis, it explores how this power is realized in popular visual literature, which derives from, develops and transforms the historic contingencies of reading. Analysing examples in the work of Leo Baxendale, Michiko Hasegawa, Kaz, Christophe Blaine, R. J. Ivankovic, Catherine Anyango, Seth Tobocman, Keiji Nakazawa, Debbie Drechsler and Nicola Streeten, it describes a number of ways in which comics engage with and manipulate these historic contingencies, discussing the use of comedy, satire and parody and the development of political protest and life writing as sub-genres that are fundamentally engaged with readers’ habits and expectations. Finally, the chapter focuses on the opportunities that visual story showing and depictive drawing continue to provide to comics artists to achieve this engagement

Imaging bacteria and biofilms on hardware and periprosthetic tissue in orthopedic infections

Infection is a major complication of total joint arthroplasty (TJA) surgery, and even though it is now as low as 1 % in some hospitals, the increasing number of primary surgeries translates to tens of thousands of revisions due to prosthetic joint infection (PJI). In many cases the only solution is revision surgery in which the hardware is removed. This process is extremely long and painful for patients and is a considerable financial burden for the health-care system. A significant proportion of the difficulties in diagnosis and treatment of PJI are associated with biofilm formation where bacteria attach to the surface of the prosthesis and periprosthetic tissue and build a 3-D biofilm community encased in an extracellular polymeric slime (EPS) matrix. Bacteria in biofilms have a low metabolic rate which is thought to be a major contributor to their recalcitrance to antibiotic treatment. The diagnosis of biofilm infections is difficult due to the fact that bacteria in biofilms are not readily cultured with standard clinical microbiology techniques. To identify and visualize in situ biofilm bacteria in orthopedic samples, we have developed protocols for the collection of samples in the operating room, for molecular fluorescent staining with 16S rRNA fluorescence in situ hybridization (FISH), and for imaging of samples using confocal laser scanning microscopy (CLSM). Direct imaging is the only method which can definitively identify biofilms on implants and complements both culture and culture-independent diagnostic method

Neuro-Genetic Adaptive Attitude Control

It has previously been demonstrated that for smooth dynamic systems, using relatively few sample points from a single trajectory, a neural network can be trained to perform very accurate short-term prediction over a large part of the phase space. In this paper, we exploit the capability of a Locally Predictive Network (LPN) to derive an adaptive control architecture for a satellite equipped with controllable, bidirectional thrusters on each of the three principal axes. It is assumed that a hardware implementation of the neural network is available. The inputs for the network are a small history of system states up to the present time and a set of current control inputs, the outputs are the next system state. Once the LPN has been trained successfully, at each time step a genetic algorithm searches the space of hypothetical control inputs. Given a set of control signals, the LPN is used to predict the state of the system at the next sample point. This enables the ‘fitness’ of each set of hypothetical control torques to be evaluated very rapidly. In effect, the genetic algorithm determines a satisfactory solution to the inverse kinematic problem in time to apply the solution (set of control torques) at the next control point. With the exception of the neuromodelling (which is repeated only when the system dynamics change), the whole process is then repeated. The results presented indicate that such an architecture is easily able to master the attitude control problem for arbitrary slew angles, with arbitrary a priori unknowndynamics and noise in the sensor system