Inspired by taxonomist Jack Goody’s theorizing of ‘ancient lists’ as ‘intellectual technologies’, this book analyzes listing practices in modern and contemporary formations of power, and how they operate in the installation and securing of the milieus of circulation that characterize Michel Foucault’s conception of governmentality. Propelling the list’s role in the delimitation and policing of risky and threatening elements from out of history and into a contemporary analysis of power, this work demonstrates how assemblages of computer, statistical, and list technologies first deployed by the Nazi regime continue to resonate significantly in the segmenting and constitution of a critical classification of contemporary homo sapiens: the terrorist class, or homo sacer.
A major challenge for disaster scholars and policymakers is to understand the power dimension in response networks, particularly relating to collaboration and coordination. We propose a conceptual framework to study interests and negotiations in and between various civic and professional, response networks drawing on the concepts of “programming” and “switching” proposed by Manuel Castells in his work on the network society. Programming in disaster response refers to the ability to constitute response networks and to program/reprogram them in terms of the goals assigned to the network. Switching is the ability to connect different net-works by sharing common goals and combining resources. We employ these concepts to understand how the US Federal Emergency Management Agency organized its response in the aftermath of Hurricanes Katrina and Sandy. Our conceptual framework can be used both by disaster scholars and policymakers to understand how networked power is constructed and utilized.
The primary aims of this study were (1) to evaluate whole-body mechanical efficiency (ME) in a large group of chronic obstructive pulmonary disease (COPD) patients with a wide range of degrees of illness and (2) to examine how ME in COPD is related to absolute work rate and indices of disease severity during exercise testing. A total of 569 patients (301 male patients; GOLD stage I: 28, GOLD stage II: 166, GOLD stage III: 265, and GOLD stage IV: 110) with chronic obstructive pulmonary disease (COPD) were included in the data analysis. Individual maximal workload (watt), peak minute ventilation ((Equation is included in full-text article.)E, L/min body temperature and pressure, saturated), and peak oxygen uptake ((Equation is included in full-text article.)O2, mL/min standard temperature and pressure, dry) were determined from a maximal incremental cycle ergometer test. Ventilatory and metabolic response parameters were collected during a constant work rate test at 75% of the individual maximal workload. From the exercise responses of the constant work rate test, the gross ME was calculated. The mean whole-body gross ME was 11.0 ± 3.5% at 75% peak power. The ME declined significantly (P < .001) with increasing severity of the disease when measured at the same relative power. Log-transformed absolute work rate (r = .87, P < .001) was the strongest independent predictor of gross ME. Body mass was the single other variable that contributed significantly to the linear regression model. Gross ME in COPD was largely predicted by the absolute work rate (r = .87; P < .001) while indices of the severity of the disease did not predict ME in COPD.
Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
The demand for mobile agents in industrial environments to perform various tasks is growing tremendously in recent years. However, changing environments, security considerations and robustness against failure are major persistent challenges autonomous agents have to face when operating alongside other mobile agents. Currently, such problems remain largely unsolved. Collaborative multi-platform Cyber- Physical-Systems (CPSs) in which different agents flexibly contribute with their relative equipment and capabilities forming a symbiotic network solving multiple objectives simultaneously are highly desirable. Our proposed SMART-AGENTS platform will enable flexibility and modularity providing multi-objective solutions, demonstrated in two industrial domains: logistics (cycle-counting in warehouses) and agriculture (pest and disease identification in greenhouses). Aerial vehicles are limited in their computational power due to weight limitations but offer large mobility to provide access to otherwise unreachable places and an “eagle eye” to inform about terrain, obstacles by taking pictures and videos. Specialized autonomous agents carrying optical sensors will enable disease classification and product recognition improving green- and warehouse productivity. Newly developed micro-electromechanical systems (MEMS) sensor arrays will create 3D flow-based images of surroundings even in dark and hazy conditions contributing to the multi-sensor system, including cameras, wireless signatures and magnetic field information shared among the symbiotic fleet. Integration of mobile systems, such as smart phones, which are not explicitly controlled, will provide valuable information about human as well as equipment movement in the environment by generating data from relative positioning sensors, such as wireless and magnetic signatures. Newly developed algorithms will enable robust autonomous navigation and control of the fleet in dynamic environments incorporating the multi-sensor data generated by the variety of mobile actors. The proposed SMART-AGENTS platform will use real-time 5G communication and edge computing providing new organizational structures to cope with scalability and integration of multiple devices/agents. It will enable a symbiosis of the complementary CPSs using a combination of equipment yielding efficiency and versatility of operation.
