The Phenomenology of Kantian Respect for Persons

Emotions can be understood generally from two different perspectives: (i) a third-person perspective that specifies their distinctive functional role within our overall cognitive economy and (ii) a first-person perspective that attempts to capture their distinctive phenomenal character, the subjective quality of experiencing them. One emotion that is of central importance in many ethical systems is respect (in the sense of respect for persons or so-called recognition-respect). However, discussions of respect in analytic moral philosophy have tended to focus almost entirely on its functional role, in particular the behaviors that respect disposes us to engage in (or refrain from). Here we wish to investigate the phenomenal character of respect, what it is like to feel respect for persons. Since Kant is the reference point for modern discussions of respect, we try to reconstruct Kant’s account of the phenomenology of respect, but also endeavor to refine his account in light of our own phenomenological observations

Perceptual phenomenology

I am looking at an apple. The apple has a lot of properties and some, but not all, of these are part of my phenomenology at this moment: I am aware of these properties. And some, but not all, of these properties that I am aware of are part of my perceptual (or sensory) phenomenology. If I am attending to the apple’s color, this property will be part of my perceptual phenomenology. The property of being a granny smith apple from Chile is unlikely to be part of my perceptual phenomenology. Here are two problems for anyone who is interested in conscious experience in general, and perceptual experience in particular: (a) How can we tell which properties are part of our phenomenology and which ones are not? (b) How can we tell which properties are part of our perceptual phenomenology and which ones are part of our non-perceptual phenomenology? I will focus on (b) in this paper. My aim is twofold: I propose a methodology for answering the question of which properties are part of our perceptual phenomenology and I provide an example for how this methodology could be applied

Multi-Camera Crowd Monitoring: The SAFEST Approach

International audienceThis paper presents the current state of people counting approach created for the SAFEST project. A video based surveillance system for monitoring crowd behaviour is developed. The system detects dangerous situations by analysing the dynamics of the crowd density. Therefore we developed a grid-based people counting algorithm which provides density per cell for the global view on the monitored area. Since multiple cameras may observe same parts of the monitored area, the challenge is not only to count people seen by single cameras , but also to merge the views. Therefore we first detect people seen by each camera separately and then sum the results to a global representation. In order to avoid multiple counting of same objects, the output of cameras in the overlapped regions are weighted

Area & Perimeter Surveillance in SAFEST using Sensors and the Internet of Things

International audienceSAFEST is a project aiming to provide a comprehensive solution to ensure the safety and security of the general public and critical infrastructures. The approach of the project is to design a lightweight, distributed system using heterogeneous, networked sensors, able to aggregate the input of a wide variety of signals (e.g. camera, PIR, radar, magnetic, seismic, acoustic). The project aims for a proof-of-concept demonstration focusing on a concrete scenario: crowd monitoring, area and perimeter surveillance in an airport, realized with a prototype of the system, which must be deployable and foldable overnight, and leverage autoconfiguration based on wireless communications and Internet of Things. This paper reviews the progress towards reaching this goal, which is planned for 2015

Two novel loci, COBL and SLC10A2, for Alzheimer's disease in African Americans

INTRODUCTION: African Americans' (AAs) late-onset Alzheimer's disease (LOAD) genetic risk profile is incompletely understood. Including clinical covariates in genetic analyses using informed conditioning might improve study power. METHODS: We conducted a genome-wide association study (GWAS) in AAs employing informed conditioning in 1825 LOAD cases and 3784 cognitively normal controls. We derived a posterior liability conditioned on age, sex, diabetes status, current smoking status, educational attainment, and affection status, with parameters informed by external prevalence information. We assessed association between the posterior liability and a genome-wide set of single-nucleotide polymorphisms (SNPs), controlling for APOE and ABCA7, identified previously in a LOAD GWAS of AAs. RESULTS: Two SNPs at novel loci, rs112404845 (P = 3.8 × 10-8), upstream of COBL, and rs16961023 (P = 4.6 × 10-8), downstream of SLC10A2, obtained genome-wide significant evidence of association with the posterior liability. DISCUSSION: An informed conditioning approach can detect LOAD genetic associations in AAs not identified by traditional GWAS

Inhibition of Autoimmune Diabetes in NOD Mice by miRNA Therapy.

Autoimmune destruction of the pancreatic islets in Type 1 diabetes is mediated by both increased proinflammatory (Teff) and decreased regulatory (Treg) T lymphocytes resulting in a significant decrease in the Treg:Teff ratio. The non-obese diabetic (NOD) mouse is an excellent in vivo model for testing potential therapeutics for attenuating the decrease in the Treg:Teff ratio and inhibiting disease pathogenesis. Here we show for the first time that a bioreactor manufactured therapeutic consisting of a complex of miRNA species (denoted as TA1) can effectively reset the NOD immune system from a proinflammatory to a tolerogenic state thus preventing or delaying autoimmune diabetes. Treatment of NOD mice with TA1 resulted in a systemic broad-spectrum upregulation of tolerogenic T cell subsets with a parallel downregulation of Teff subsets yielding a dramatic increase in the Treg:Teff ratio. Moreover, the murine-derived TA1 was highly effective in the inhibition of allorecognition of HLA-disparate human PBMC. TA1 demonstrated dose-responsiveness and exhibited equivalent or better inhibition of allorecognition driven proliferation than etanercept (a soluble TNF receptor). These findings demonstrate that miRNA-based therapeutics can effectively attenuate or arrest autoimmune disease processes and may be of significant utility in a broad range of autoimmune diseases including Type 1 diabetes

Tumour necrosis factor receptor trafficking dysfunction opens the TRAPS door to pro-inflammatory cytokine secretion

The related TNFR1 studies within the Turner laboratory were funded by Barts and The London Charitable Foundatio

Bless Me, Father

https://works.swarthmore.edu/alum-books/1296/thumbnail.jp

De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO

Abstract By mediating interatomic interactions, water molecules play a major role in protein–protein, protein–DNA and protein–ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software because of high computational costs. To challenge this situation, we analyzed the binding characteristics of 60,000 waters from high resolution crystal structures and used the observed parameters to implement the prediction of water molecules in the protein design and side chain-packing software MUMBO. To reduce the complexity of the problem, we incorporated water molecules through the solvation of rotamer pairs instead of relying on solvated rotamer libraries. Our validation demonstrates the potential of our algorithm by achieving recovery rates of 67% for bridging water molecules and up to 86% for fully coordinated waters. The efficacy of our algorithm is highlighted further by the prediction of 3 different proteinligand complexes. Here, 91% of water-mediated interactions between protein and ligand are correctly predicted. These results suggest that the new algorithm could prove highly beneficial for structure-based protein design, particularly for the optimization of ligand-binding pockets or protein–protein interfaces