Rich Situated Attitudes

We outline a novel theory of natural language meaning, Rich Situated Semantics [RSS], on which the content of sentential utterances is semantically rich and informationally situated. In virtue of its situatedness, an utterance’s rich situated content varies with the informational situation of the cognitive agent interpreting the utterance. In virtue of its richness, this content contains information beyond the utterance’s lexically encoded information. The agent-dependence of rich situated content solves a number of problems in semantics and the philosophy of language (cf. [14, 20, 25]). In particular, since RSS varies the granularity of utterance contents with the interpreting agent’s informational situation, it solves the problem of finding suitably fine- or coarse-grained objects for the content of propositional attitudes. In virtue of this variation, a layman will reason with more propositions than an expert

Structural Ordering and Symmetry Breaking in Cd_2Re_2O_7

Single crystal X-ray diffraction measurements have been carried out on Cd_2Re_2O_7 near and below the phase transition it exhibits at Tc' ~195 K. Cd_2Re_2O_7 was recently discovered as the first, and to date only, superconductor with the cubic pyrochlore structure. Superlattice Bragg peaks show an apparently continuous structural transition at Tc', however the order parameter displays anomalously slow growth to ~Tc'/10, and resolution limited critical-like scattering is seen above Tc'. High resolution measurements show the high temperature cubic Bragg peaks to split on entering the low temperature phase, indicating a (likely tetragonal) lowering of symmetry below Tc'.Comment: 4 pages, 4 figure

Molecular analyses reveal consistent food web structure with elevation in rainforest Drosophila – parasitoid communities

The analysis of interaction networks across spatial environmental gradients is a powerful approach to investigate the responses of communities to global change. Using a combination of DNA metabarcoding and traditional molecular methods we built bipartite Drosophila-parasitoid food webs from six Australian rainforest sites across gradients spanning 850 m in elevation and 5° Celsius in mean temperature. Our cost-effective hierarchical approach to network reconstruction separated the determination of host frequencies from the detection and quantification of interactions. The food webs comprised 5-9 host and 5-11 parasitoid species at each site, and showed a lower incidence of parasitism at high elevation. Despite considerable turnover in the relative abundance of host Drosophila species, and contrary to some previous results, we did not detect significant changes to fundamental metrics of network structure including nestedness and specialisation with elevation. Advances in community ecology depend on data from a combination of methodological approaches. It is therefore especially valuable to develop model study systems for sets of closely-interacting species that are diverse enough to be representative, yet still amenable to field and laboratory experiments

Molecular analyses reveal consistent food web structure with elevation in rainforest Drosophila – parasitoid communities

The analysis of interaction networks across spatial environmental gradients is a powerful approach to investigate the responses of communities to global change. Using a combination of DNA metabarcoding and traditional molecular methods we built bipartite Drosophila – parasitoid food webs from six Australian rainforest sites across gradients spanning 850 m in elevation and 5°C in mean temperature. Our cost-effective hierarchical approach to network reconstruction separated the determination of host frequencies from the detection and quantification of interactions. The food webs comprised 5–9 host and 5–11 parasitoid species at each site, and showed a lower incidence of parasitism at high elevation. Despite considerable turnover in the relative abundance of host Drosophila species, and contrary to some previous results, we did not detect significant changes to fundamental metrics of network structure including nestedness and specialisation with elevation. Advances in community ecology depend on data from a combination of methodological approaches. It is therefore especially valuable to develop model study systems for sets of closely-interacting species that are diverse enough to be representative, yet still amenable to field and laboratory experiments

Degrees of belief, expected and actual

A framework of degrees of belief, or credences, is often advocated to model our uncertainty about how things are or will turn out. It has also been employed in relation to the kind of uncertainty or indefiniteness that arises due to vagueness, such as when we consider “a is F” in a case where a is borderline F. How should we understand degrees of belief when we take into account both these phenomena? Can the right kind of theory of the semantics of vagueness help us answer this? Nicholas J.J. Smith defends a unified account, according to which “degree of belief is expected truth-value”; this builds on his Degree Theory of vagueness that offers an account of the semantics and logic of vagueness in terms of degrees of truth. I argue that his account fails. Degree theories of vagueness do not help us understand degrees of belief and, I argue, we shouldn’t expect a theory of vagueness to yield a detailed uniform story about this. The route from the semantics to psychological states needn’t be straightforward or uniform even before we attempt to combine vagueness with probabilistic uncertainty

First Principles Investigation of Ferromagnetism and Ferroelectricity in Bismuth Manganite

We present results of local spin density approximation (LSDA) pseudopotential calculations for the perovskite structure oxide, bismuth manganite (BiMnO3). The origin of the differences between bismuth manganite and other perovskite manganites is determined by first calculating total energies and band structures of the high symmetry cubic phase, then sequentially lowering the magnetic and structural symmetry. Our results indicate that covalent bonding between bismuth cations and oxygen anions stabilizes different magnetic and structural phases compared with the rare earth manganites. This is consistent with recent experimental results showing enhancement of charge ordering in doped bismuth manganite

RNAseq Analyses Identify Tumor Necrosis Factor-Mediated Inflammation as a Major Abnormality in ALS Spinal Cord

ALS is a rapidly progressive, devastating neurodegenerative illness of adults that produces disabling weakness and spasticity arising from death of lower and upper motor neurons. No meaningful therapies exist to slow ALS progression, and molecular insights into pathogenesis and progression are sorely needed. In that context, we used high-depth, next generation RNA sequencing (RNAseq, Illumina) to define gene network abnormalities in RNA samples depleted of rRNA and isolated from cervical spinal cord sections of 7 ALS and 8 CTL samples. We aligned \u3e50 million 2X150 bp paired-end sequences/sample to the hg19 human genome and applied three different algorithms (Cuffdiff2, DEseq2, EdgeR) for identification of differentially expressed genes (DEG’s). Ingenuity Pathways Analysis (IPA) and Weighted Gene Co-expression Network Analysis (WGCNA) identified inflammatory processes as significantly elevated in our ALS samples, with tumor necrosis factor (TNF) found to be a major pathway regulator (IPA) and TNFα-induced protein 2 (TNFAIP2) as a major network “hub” gene (WGCNA). Using the oPOSSUM algorithm, we analyzed transcription factors (TF) controlling expression of the nine DEG/hub genes in the ALS samples and identified TF’s involved in inflammation (NFkB, REL, NFkB1) and macrophage function (NR1H2::RXRA heterodimer). Transient expression in human iPSC-derived motor neurons of TNFAIP2 (also a DEG identified by all three algorithms) reduced cell viability and induced caspase 3/7 activation. Using high-density RNAseq, multiple algorithms for DEG identification, and an unsupervised gene co-expression network approach, we identified significant elevation of inflammatory processes in ALS spinal cord with TNF as a major regulatory molecule. Overexpression of the DEG TNFAIP2 in human motor neurons, the population most vulnerable to die in ALS, increased cell death and caspase 3/7 activation. We propose that therapies targeted to reduce inflammatory TNFα signaling may be helpful in ALS patients