Mapping posthuman discourse and the evolution of living information

The discourse that surrounds and constitutes the post-human emerged as a response to earlier claims of an essential or universal human or human nature. These discussions claim that the human is a discursive construct that emerges from various configurations of nature, embodiment, technology, and culture, configurations that have also been variously shaped by the forces of social history. And in the absence of an essential human figure, post-human discourses suggest that there are no restrictions or limitations on how the human can be reconfigured. This axiom has been extended in light of a plethora of technological reconfigurations and augmentations now potentially available to the human, and claims emerge from within this literature that these new technologies constitute a range of possibilities for future human biological evolution. This thesis questions the assumption contained within these discourses that technological incursions or reconfigurations of the biological human necessarily constitute human biological or human social evolution by discussing the role the evolution theories plays in our understanding of the human, the social, and technology. In this thesis I show that, in a reciprocal process, evolution theory draws metaphors from social institutions and ideologies, while social institutions and ideologies simultaneously draw on metaphors from evolution theory. Through this discussion, I propose a form of evolution literacy; a tool, I argue, is warranted in developing a sophisticated response to changes in both human shape and form. I argue that, as a whole, our understanding of evolution constitutes a metanarrative, a metaphor through which we understand the place of the human within the world; it follows that historical shifts in social paradigms will result in new definitions of evolution. I show that contemporary evolution theory reflects parts of the world as codified informatic systems of associated computational network logic through which the behaviour of participants is predefined according to an evolved or programmed structure. Working from within the discourse of contemporary evolution theory I develop a space through which a version of the post-human figure emerges. I promote this version of the post-human as an Artificial Intelligence computational programme or autonomous agent that, rather than seeking to replace, reduce or deny the human subject, is configured as an exosomatic supplement to and an extension of the biological human

Integrating Income Tax and National Insurance: an interim report

Income Tax and National Insurance are now sufficiently similar that merging them appears to be a plausible option, yet still sufficiently different that integration raises significant difficulties. This paper surveys the potential benefits of integration - increased transparency and reduced administrative and compliance costs - and the potential obstacles, assessing the extent to which each of the differences between Income Tax and NICs - in particular the contributory principle, the levying of an employer charge and the differences in tax base - constitute serious barriers to integration. The paper concludes that few of the difficulties look individually prohibitive, but that trying too hard to avoid significant reform of the current policy framework could produce a merged tax so complicated as to nullify much or all of the benefits of integration.Taxation, social insurance, administration

University of Southern Indiana\u27s Solar Eclipse Experience

The University of Southern Indiana Eclipse Ballooning team\u27s experience from May 2016 to August 2017 is comprehensively reviewed. Experience gained during four rehearsal balloon flights is covered, including the need to coordinate with a pre-Senior Design class assisting in three of the flights. Challenges encountered were: learning ballooning techniques, reconfiguring the pod stack, adding new hardware, like a grounding rod and 3D printed standoff, losing tracking visibility due to server crashes at the Borealis hub, and making quick software turnarounds. The students found the networking afforded by the entire experience to be one of the highlights of the project

Label-free quantitative chemical imaging and classification analysis of adipogenesis using mouse embryonic stem cells

Stem cells have received much attention recently for their potential utility in regenerative medicine. The identification of their differentiated progeny often requires complex staining procedures, and is challenging for intermediary stages which are a priori unknown. In this work, the ability of label‐free quantitative coherent anti‐Stokes Raman scattering (CARS) micro‐spectroscopy to identify populations of intermediate cell states during the differentiation of murine embryonic stem cells into adipocytes is assessed. Cells were imaged at different days of differentiation by hyperspectral CARS, and images were analysed with an unsupervised factorization algorithm providing Raman‐like spectra and spatially resolved maps of chemical components. Chemical decomposition combined with a statistical analysis of their spatial distributions provided a set of parameters that were used for classification analysis. The first 2 principal components of these parameters indicated 3 main groups, attributed to undifferentiated cells, cells differentiated into committed white pre‐adipocytes, and differentiating cells exhibiting a distinct protein globular structure with adjacent lipid droplets. An unsupervised classification methodology was developed, separating undifferentiated cell from cells in other stages, using a novel method to estimate the optimal number of clusters. The proposed unsupervised classification pipeline of hyperspectral CARS data offers a promising new tool for automated cell sorting in lineage analysis

Soft Decision Analyzer

The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the receiver under test is subjected to conditions where its performance degrades to high error rates (30 percent or beyond). The design incorporates a number of features, such as watchdog triggers that permit the SDA system to recover from large receiver upsets automatically and continue accumulating performance analysis unaided by operator intervention. This accommodates tests that can last in the order of days in order to gain statistical confidence in results and is also useful for capturing snapshots of rare events

Human GUCY2C-Targeted Chimeric Antigen Receptor (CAR)-Expressing T Cells Eliminate Colorectal Cancer Metastases.

One major hurdle to the success of adoptive T-cell therapy is the identification of antigens that permit effective targeting of tumors in the absence of toxicities to essential organs. Previous work has demonstrated that T cells engineered to express chimeric antigen receptors (CAR-T cells) targeting the murine homolog of the colorectal cancer antigen GUCY2C treat established colorectal cancer metastases, without toxicity to the normal GUCY2C-expressing intestinal epithelium, reflecting structural compartmentalization of endogenous GUCY2C to apical membranes comprising the intestinal lumen. Here, we examined the utility of a human-specific, GUCY2C-directed single-chain variable fragment as the basis for a CAR construct targeting human GUCY2C-expressing metastases. Human GUCY2C-targeted murine CAR-T cells promoted antigen-dependent T-cell activation quantified by activation marker upregulation, cytokine production, and killing of GUCY2C-expressing, but not GUCY2C-deficient, cancer cells in vitro. GUCY2C CAR-T cells provided long-term protection against lung metastases of murine colorectal cancer cells engineered to express human GUCY2C in a syngeneic mouse model. GUCY2C murine CAR-T cells recognized and killed human colorectal cancer cells endogenously expressing GUCY2C, providing durable survival in a human xenograft model in immunodeficient mice. Thus, we have identified a human GUCY2C-specific CAR-T cell therapy approach that may be developed for the treatment of GUCY2C-expressing metastatic colorectal cancer

Detecting depression and malingering using response times on the Personality Assessment Inventory

The detection of individuals who are malingering psychological dysfunction has proven to be a difficult task (Rogers, 1997). This study was conducted to investigate whether response times on the Personality Assessment Inventory could differentiate among asymptomatic controls (n = 15), clinically depressed individuals (n = 12), and a group instructed to malinger depression (n = 19). Conventional responses and item response latencies were recorded for the Negative Impression, Positive Impression, Depression - Affective, Depression — Cognitive, and Depression - Physiological scales. Discriminant function analyses revealed that conventional scores correctly classified 100% of the controls, 91.7% o f the depressed, and 73.7% of the malingerers. Standardized response latencies correctly classified 73.3% of controls, 58.3% of depressed, and 84.2% of malingerers. Classification rates for raw response latencies were 73.3%, 50.0%, and 78.9% respectively. Finally, a new scale composed of items from the above subscales maxim ally discrim inating malingerers from depressed individuals could correctly classify 100% o f depressed and 91.7% of malingerers. These findings are consistent with other research (Fekken & Holden, 1994) suggesting that response latencies might provide meaningful information

The influence of personality traits on mood induction and memory

This study examines how recall measured over three time periods can be affected by mood induction, personality traits, and image characteristics. There were 101 people who participated in Session 1, 92 participants completed Session 2, and 77 participants completed Session 3. Subjects were randomly assigned to a group with negative mood induction or to a control group. Personality traits were measured using the NEO-FFI. The participants were asked to view 57 images and rate them by pleasantness and arousal. Following the presentation of images participants were asked to recall as many images as possible immediately after the presentation, one day after presentation, and one week after presentation. Generalized Linear Models were used to analyze the data. Unpleasant images were recalled with greater frequency during all three time periods. In addition, a quadratic expression was used to demonstrate that pleasant images also were recalled with greater frequency than neutral images. The personality trait of Neuroticism was negatively correlated with recall during Session 1 and Session 3. It is postulated that higher levels of Neuroticism provide a protective role when viewing negative images through reduced attention. Alternatively, it is possible that people with a higher level of Neuroticism may be desensitized to negative images and therefore less affected by unpleasant images. People who experienced a negative mood induction experienced images more pleasantly although this did not affect recall ability. This study is one of the first to examine how mood induction can interact with personality variables the hedonic valence of the images to affect recall over three time periods. The implications for these findings are discussed and suggestions are provided for future research