Normative Alethic Pluralism

Some philosophers have argued that truth is a norm of judgement and have provided a variety of formulations of this general thesis. In this paper, I shall side with these philosophers and assume that truth is a norm of judgement. What I am primarily interested in here are two core questions concerning the judgement-truth norm: (i) what are the normative relationships between truth and judgement? And (ii) do these relationships vary or are they constant? I argue for a pluralist picture—what I call Normative Alethic Pluralism (NAP)—according to which (i) there is more than one correct judgement-truth norm and (ii) the normative relationships between truth and judgement vary in relation to the subject matter of the judgement. By means of a comparative analysis of disagreement in three areas of the evaluative domain—refined aesthetics, basic taste and morality—I show that there is an important variability in the normative significance of disagreement—I call this the variability conjecture. By presenting a variation of Lynch’s scope problem for alethic monism, I argue that a monistic approach to the normative function of truth is unable to vindicate the conjecture. I then argue that normative alethic pluralism provides us with a promising model to account for it

Non-visual functions of crustacean eyestalk ganglia

Ablation experiments demonstrated that in several crustacean groups, the proximal eyestalk ganglia are important in a variety of behavior patterns: 1. Chemical elicitation of feeding via the antennules is altered in lobsters, hermit crabs, and some brachyuran crabs by bilateral eyestalk ablation; the ablation of one antennule and the contralateral eyestalk is effective in lobsters and hermit crabs;Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47106/1/359_2005_Article_BF01245153.pd

Inter-laboratory Variation in the Chemical Analysis of Acidic Forest Soil Reference Samples from Eastern North America

Long-term forest soil monitoring and research often requires a comparison of laboratory data generated at different times and in different laboratories. Quantifying the uncertainty associated with these analyses is necessary to assess temporal changes in soil properties. Forest soil chemical properties, and methods to measure these properties, often differ from agronomic and horticultural soils. Soil proficiency programs do not generally include forest soil samples that are highly acidic, high in extractable Al, low in extractable Ca and often high in carbon. To determine the uncertainty associated with specific analytical methods for forest soils, we collected and distributed samples from two soil horizons (Oa and Bs) to 15 laboratories in the eastern United States and Canada. Soil properties measured included total organic carbon and nitrogen, pH and exchangeable cations. Overall, results were consistent despite some differences in methodology. We calculated the median absolute deviation (MAD) for each measurement and considered the acceptable range to be the median 6 2.5 3 MAD. Variability among laboratories was usually as low as the typical variability within a laboratory. A few areas of concern include a lack of consistency in the measurement and expression of results on a dry weight basis, relatively high variability in the C/N ratio in the Bs horizon, challenges associated with determining exchangeable cations at concentrations near the lower reporting range of some laboratories and the operationally defined nature of aluminum extractability. Recommendations include a continuation of reference forest soil exchange programs to quantify the uncertainty associated with these analyses in conjunction with ongoing efforts to review and standardize laboratory methods

Serratamolide is a hemolytic factor produced by Serratia marcescens

Serratia marcescens is a common contaminant of contact lens cases and lenses. Hemolytic factors of S. marcescens contribute to the virulence of this opportunistic bacterial pathogen. We took advantage of an observed hyper-hemolytic phenotype of crp mutants to investigate mechanisms of hemolysis. A genetic screen revealed that swrW is necessary for the hyper-hemolysis phenotype of crp mutants. The swrW gene is required for biosynthesis of the biosurfactant serratamolide, previously shown to be a broad-spectrum antibiotic and to contribute to swarming motility. Multicopy expression of swrW or mutation of the hexS transcription factor gene, a known inhibitor of swrW expression, led to an increase in hemolysis. Surfactant zones and expression from an swrW-transcriptional reporter were elevated in a crp mutant compared to the wild type. Purified serratamolide was hemolytic to sheep and murine red blood cells and cytotoxic to human airway and corneal limbal epithelial cells in vitro. The swrW gene was found in the majority of contact lens isolates tested. Genetic and biochemical analysis implicate the biosurfactant serratamolide as a hemolysin. This novel hemolysin may contribute to irritation and infections associated with contact lens use. © 2012 Shanks et al

Crayfish Recognize the Faces of Fight Opponents

The capacity to associate stimuli underlies many cognitive abilities, including recognition, in humans and other animals. Vertebrates process different categories of information separately and then reassemble the distilled information for unique identification, storage and recall. Invertebrates have fewer neural networks and fewer neural processing options so study of their behavior may reveal underlying mechanisms still not fully understood for any animal. Some invertebrates form complex social colonies and are capable of visual memory–bees and wasps, for example. This ability would not be predicted in species that interact in random pairs without strong social cohesion; for example, crayfish. They have chemical memory but the extent to which they remember visual features is unknown. Here we demonstrate that the crayfish Cherax destructor is capable of visual recognition of individuals. The simplicity of their interactions allowed us to examine the behavior and some characteristics of the visual features involved. We showed that facial features are learned during face-to-face fights, that highly variable cues are used, that the type of variability is important, and that the learning is context-dependent. We also tested whether it is possible to engineer false identifications and for animals to distinguish between twin opponents

World radiocommunication conference 12 : implications for the spectrum eco-system

Spectrum allocation is once more a key issue facing the global telecommunications industry. Largely overlooked in current debates, however, is the World Radiocommunication Conference (WRC). Decisions taken by WRC shape the future roadmap of the telecommunications industry, not least because it has the ability to shape the global spectrum allocation framework. In the debates of WRC-12 it is possible to identify three main issues: enhancement of the international spectrum regulatory framework, regulatory measures required to introduce Cognitive Radio Systems (CRS) technologies; and, additional spectrum allocation to mobile service. WRC-12 eventually decided not to change the current international radio regulations with regard to the first two issues and agreed to the third issue. The main implications of WRC-12 on the spectrum ecosystem are that most of actors are not in support of the concept of spectrum flexibility associated with trading and that the concept of spectrum open access is not under consideration. This is explained by the observation that spectrum trading and spectrum commons weaken state control over spectrum and challenge the main principles and norms of the international spectrum management regime. In addition, the mobile allocation issue has shown the lack of conformity with the main rules of the regime: regional spectrum allocation in the International Telecommunication Union (ITU) three regions, and the resistance to the slow decision making procedures. In conclusion, while the rules and decision-making procedures of the international spectrum management regime were challenged in the WRC-12, the main principles and norms are still accepted by the majority of countries

Evidentialism and Moral Encroachment

Moral encroachment holds that the epistemic justification of a belief can be affected by moral factors. If the belief might wrong a person or group more evidence is required to justify the belief. Moral encroachment thereby opposes evidentialism, and kindred views, which holds that epistemic justification is determined solely by factors pertaining to evidence and truth. In this essay I explain how beliefs such as ‘that woman is probably an administrative assistant’—based on the evidence that most women employees at the firm are administrative assistants—motivate moral encroachment. I then describe weaknesses of moral encroachment. Finally I explain how we can countenance the moral properties of such beliefs without endorsing moral encroachment, and I argue that the moral status of such beliefs cannot be evaluated independently from the understanding in which they are embedded

Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive behaviors that typically emerge by 24 months of age. To develop effective early interventions that can potentially ameliorate the defining deficits of ASD and improve long-term outcomes, early detection is essential. Using prospective neuroimaging of 59 6-month-old infants with a high familial risk for ASD, we show that functional connectivity magnetic resonance imaging correctly identified which individual children would receive a research clinical best-estimate diagnosis of ASD at 24 months of age. Functional brain connections were defined in 6-month-old infants that correlated with 24-month scores on measures of social behavior, language, motor development, and repetitive behavior, which are all features common to the diagnosis of ASD. A fully cross-validated machine learning algorithm applied at age 6 months had a positive predictive value of 100% [95% confidence interval (CI), 62.9 to 100], correctly predicting 9 of 11 infants who received a diagnosis of ASD at 24 months (sensitivity, 81.8%; 95% CI, 47.8 to 96.8). All 48 6-month-old infants who were not diagnosed with ASD were correctly classified [specificity, 100% (95% CI, 90.8 to 100); negative predictive value, 96.0% (95% CI, 85.1 to 99.3)]. These findings have clinical implications for early risk assessment and the feasibility of developing early preventative interventions for ASD

Early brain development in infants at high risk for autism spectrum disorder

Brain enlargement has been observed in children with Autism Spectrum Disorder (ASD), but the timing of this phenomenon and its relationship to the appearance of behavioral symptoms is unknown. Retrospective head circumference and longitudinal brain volume studies of 2 year olds followed up at age 4 years, have provided evidence that increased brain volume may emerge early in development.1, 2 Studies of infants at high familial risk for autism can provide insight into the early development of autism and have found that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life3,4. These observations suggest that prospective brain imaging studies of infants at high familial risk for ASD might identify early post-natal changes in brain volume occurring before the emergence of an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that cortical surface area hyper-expansion between 6-12 months of age precedes brain volume overgrowth observed between 12-24 months in the 15 high-risk infants diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep learning algorithm primarily using surface area information from brain MRI at 6 and 12 months of age predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81%, sensitivity of 88%). These findings demonstrate that early brain changes unfold during the period in which autistic behaviors are first emerging