What is a logical diagram?

Robert Brandom’s expressivism argues that not all semantic content may be made fully explicit. This view connects in interesting ways with recent movements in philosophy of mathematics and logic (e.g. Brown, Shin, Giaquinto) to take diagrams seriously - as more than a mere “heuristic aid” to proof, but either proofs themselves, or irreducible components of such. However what exactly is a diagram in logic? Does this constitute a semiotic natural kind? The paper will argue that such a natural kind does exist in Charles Peirce’s conception of iconic signs, but that fully understood, logical diagrams involve a structured array of normative reasoning practices, as well as just a “picture on a page”

In the Imaginal Realm Before She Could Read: A Healing A/r/tographic Inquiry

This healing a/r/tographic inquiry ritually cycles through ancestral time to the present inspired by a recently found small grey book above the author’s dad’s desk—10 years after his death. This article shines light and memory onto spirit infused matrixial borderspace(s) through the co-mingling of text and image; returning to a site where text first met image in the early years of the author’s life. She is both the young dreaming artist-child and the responsible artist/researcher/teacher seeking embodied relational imaginal knowledge through the light of both image and word

Wounds need air

A personal essay in the first-person voice describes the artist’s lived experience navigating the American medical industrial complex with multiple misdiagnosed chronic pain disorders. The artist’s personal story spans thirty years and is contextualized by illness, gender, race, age, ability, class, and is grounded in the artistic expression of self. Descriptions of mental illness, physical disability, and access to proper healthcare are weaved into an examination of embodied knowledge

Optical flow by multi-scale annotated keypoints: A biological approach

Optical flow is the pattern of apparent motion of objects in a visual scene and the relative motion, or egomotion, of the observer in the scene. In this paper we present a new cortical model for optical flow. This model is based on simple, complex and end-stopped cells. Responses of end-stopped cells serve to detect keypoints and those of simple cells are used to detect orientations of underlying structures and to classify the junction type. By combining a hierarchical, multi-scale tree structure and saliency maps, moving objects can be segregated, their movement can be obtained, and they can be tracked over time. We also show that optical flow at coarse scales suffices to determine egomotion. The model is discussed in the context of an integrated cortical architecture which includes disparity in stereo vision

Parrot Interpreter: Representation, Extinction and the Electronic Information Environment

Humans, it seems, can’t get enough of parrots. Ethnography, folklore, psychology, and, of course, imaginative literature all offer copious evidence of our fantasy of living with, communicating with and even being parrots. The natural history of parrots and the cultural history of parrots present something of a conundrum: on the one hand, a massive destructiveness (illegal bird and feather trade, environment destruction, scientific collections); on the other, an often erotically inflected sympathetic identification leading to the production of new forms. It’s strange to realise that Europe is infested with a shadow population of captive and inbred budgerigars, whose numbers far exceed those remaining in the wild and who can never return to their origins. If, as our privileged other, our uncanny mimic and double, the parrot still fails to survive, what does this tell us about our economy of desire? It seems that to know is to consume and destroy; and that the apparent contrast between the operations of the rainforest loggers and bird-trappers and the sentimental representations and transformations parrot suffers in human society is overdrawn. How is this contradiction to be explained

Odour-mediated host seeking and discrimination in mosquitoes : chemistry, neurobiology and behaviour

The majority of the world’s population is at risk of one or more mosquito-borne diseases that are transmitted by blood-feeding female mosquitoes, affecting both human health and economic development. Especially Anopheles gambiae, the principal malaria vector, and Aedes aegypti, the vector of dengue and yellow fever, are of primary concern due to their strong specialisation on human hosts, and the high number of casualties caused by the pathogens they transmit. Host seeking and discrimination are crucial for disease transmission, and are predominantly mediated by olfaction. Using a wind tunnel system and a custom analysis pipeline, this thesis confirms that the two mosquito species use volatile host cues, derived from breath and body, differentially, as carbon dioxide on its own drives host seeking in Ae. aegypti, but not in An. gambiae (paper I). To discriminate between host and nonhost species (paper V), Ae. aegypti encode human identity by the relative activation of two glomeruli within the antennal lobe, the primary olfactory centre, of which one is tuned to long-chain aldehydes enriched in human odour. A synthetic blend mimicking the glomerular activation elicited host seeking in Ae. aegypti (paper II). Next to preferring human over non-human hosts, Ae. aegypti also prefer some human individuals to others, which was demonstrated to be affected by the ABO blood type and pregnancy or menstrual cycle phase. Analysis of the volatiles associated with individual volunteers, identified 1-octen-3-ol to be significantly associated with very high attractiveness (paper III). The molecular regulation of host seeking acquisition during An. gambiae female adult maturation was independent of odorant receptor gene AgamOR39 expression (paper IV). The results presented in this thesis contribute to the understanding of mosquito host seeking and discrimination from multiple perspectives, which is a prerequisite to ultimately develop novel tools for mosquito monitoring and control

Cavitation Control for Enhanced Comminution of Renal Calculi.

Shock wave lithotripsy (SWL) revolutionized the treatment of kidney stones when first introduced three decades ago. Instead of open stone surgery, ultrasonic shock waves could be applied from outside the body to fragment stones in-situ, offering a non-invasive approach to stone therapy. Although still widely utilized for the treatment of stones, SWL has yet to realize its full potential. Incomplete stone fragmentation and damage to surrounding tissues are common problems plaguing SWL procedures, and despite the fact that much progress has been made in understanding the mechanisms underlying these phenomena, implementation of this knowledge to improve clinical outcomes has been minimal. One of the fundamental components underlying stone fragmentation in SWL is the energetic formation and collapse of microscopic bubbles. This behavior—known as cavitation—can be incited by extremely intense ultrasound pulses such as the shock waves administered in lithotripsy procedures. The role of cavitation in SWL is twofold: violent collapse of bubbles generated at the stone surface confers large stresses to the structure of the stone, and is a crucial component of fragmentation; contrastingly, bubbles generated away from the stone along the acoustic propagation path can block energy from reaching the stone and compromise comminution efficacy. The work in this dissertation seeks to augment conventional SWL procedures through strategic control of the cavitation environment surrounding a kidney stone. This is achieved by way of two ultrasonic pulsing strategies designed to either enhance or suppress cavitation activity: 1) Histotripsy sequences, developed previously as a non-invasive therapeutic ultrasound technology for the mechanical fractionation of tissue structures, utilize very intense bursts of ultrasound to initiate and control a cavitational bubble cloud. 2) Bubble removal sequences, developed herein to mitigate unwanted cavitation activity, utilize low amplitude ultrasound bursts to stimulate the consolidation and de facto removal of cavitation bubble nuclei. Through appropriate application of these modalities for cavitation control, it is possible to enhance the comminution process for faster, more complete stone treatments. Ultimately, it is our hope that the concepts developed in this dissertation will provide the foundation for an enhanced first-line treatment for the non-invasive removal of kidney stones.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111431/1/duryalex_1.pd

APPLICATIONS OF MACHINE LEARNING AND COMPUTER VISION FOR SMART INFRASTRUCTURE MANAGEMENT IN CIVIL ENGINEERING

Machine Learning and Computer Vision are the two technologies that have innovative applications in diverse fields, including engineering, medicines, agriculture, astronomy, sports, education etc. The idea of enabling machines to make human like decisions is not a recent one. It dates to the early 1900s when analogies were drawn out between neurons in a human brain and capability of a machine to function like humans. However, major advances in the specifics of this theory were not until 1950s when the first experiments were conducted to determine if machines can support artificial intelligence. As computation powers increased, in the form of parallel computing and GPU computing, the time required for training the algorithms decreased significantly. Machine Learning is now used in almost every day to day activities. This research demonstrates the use of machine learning and computer vision for smart infrastructure management. This research’s contribution includes two case studies – a) Occupancy detection using vibration sensors and machine learning and b) Traffic detection, tracking, classification and counting on Memorial Bridge in Portsmouth, NH using computer vision and machine learning. Each case study, includes controlled experiments with a verification data set. Both the studies yielded results that validated the approach of using machine learning and computer vision. Both case studies present a scenario where in machine learning is applied to a civil engineering challenge to create a more objective basis for decision-making. This work also includes a summary of the current state-of-the -practice of machine learning in Civil Engineering and the suggested steps to advance its application in civil engineering based on this research in order to use the technology more effectively

Comparison of ultrasound vector flow imaging and CFD simulations with PIV measurements of flow in a left ventricular outflow trackt phantom - Implications for clinical use and in silico studies

In this study we have compared two modalities for flow quantification from measurement data; ultrasound (US) and shadow particle image velocimetry (PIV), and a flow simulation model using computational fluid dynamics (CFD). For the comparison we have used an idealized Quasi-2D phantom of the human left ventricular outflow tract (LVOT). The PIV data will serve as a reference for the true flow field in our setup. Furthermore, the US vector flow imaging (VFI) data has been post processed with model-based regularization developed to both smooth noise and sharpen physical flow features. The US VFI flow reconstruction results in an underestimation of the flow velocity magnitude compared to PIV and CFD. The CFD results coincide very well with the PIV flow field maximum velocities and curl intensity, as well as with the detailed vortex structure, however, this correspondence is subject to exact boundary conditions.publishedVersio