Believing Probabilistic Contents: On the Expressive Power and Coherence of Sets of Sets of Probabilities

Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs. Probabilistic contents are sets of probability functions. Probabilistic belief states, in turn, are modeled by sets of probabilistic contents, or sets of sets of probability functions. We argue that this Mossean framework is of considerable interest quite independently of its role in Moss’ account of probabilistic knowledge or her semantics for epistemic modals and probability operators. It is an extremely general model of uncertainty. Indeed, it is at least as general and expressively powerful as every other current imprecise probability framework, including lower probabilities, lower previsions, sets of probabilities, sets of desirable gambles, and choice functions. In addition, we partially answer an important question that Moss leaves open, viz., why should rational agents have consistent probabilistic beliefs? We show that an important subclass of Mossean believers avoid Dutch bookability iff they have consistent probabilistic beliefs

Spectral gene set enrichment (SGSE)

Motivation: Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. Results: We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes the statistical association between gene sets and principal components (PCs) using our principal component gene set enrichment (PCGSE) method. The overall statistical association between each gene set and the spectral structure of the data is then computed by combining the PC-level p-values using the weighted Z-method with weights set to the PC variance scaled by Tracey-Widom test p-values. Using simulated data, we show that the SGSE algorithm can accurately recover spectral features from noisy data. To illustrate the utility of our method on real data, we demonstrate the superior performance of the SGSE method relative to standard cluster-based techniques for testing the association between MSigDB gene sets and the variance structure of microarray gene expression data. Availability: http://cran.r-project.org/web/packages/PCGSE/index.html Contact: [email protected] or [email protected]

Principal component gene set enrichment (PCGSE)

Motivation: Although principal component analysis (PCA) is widely used for the dimensional reduction of biomedical data, interpretation of PCA results remains daunting. Most existing methods attempt to explain each principal component (PC) in terms of a small number of variables by generating approximate PCs with few non-zero loadings. Although useful when just a few variables dominate the population PCs, these methods are often inadequate for characterizing the PCs of high-dimensional genomic data. For genomic data, reproducible and biologically meaningful PC interpretation requires methods based on the combined signal of functionally related sets of genes. While gene set testing methods have been widely used in supervised settings to quantify the association of groups of genes with clinical outcomes, these methods have seen only limited application for testing the enrichment of gene sets relative to sample PCs. Results: We describe a novel approach, principal component gene set enrichment (PCGSE), for computing the statistical association between gene sets and the PCs of genomic data. The PCGSE method performs a two-stage competitive gene set test using the correlation between each gene and each PC as the gene-level test statistic with flexible choice of both the gene set test statistic and the method used to compute the null distribution of the gene set statistic. Using simulated data with simulated gene sets and real gene expression data with curated gene sets, we demonstrate that biologically meaningful and computationally efficient results can be obtained from a simple parametric version of the PCGSE method that performs a correlation-adjusted two-sample t-test between the gene-level test statistics for gene set members and genes not in the set. Availability: http://cran.r-project.org/web/packages/PCGSE/index.html Contact: [email protected] or [email protected]

World Accumulation and Planetary Life, or, Why Capitalism Will Not Survive Until the ‘Last Tree is Cut

How does capitalism work through the web of life

Method and apparatus for shape and end position determination using an optical fiber

A method of determining the shape of an unbound optical fiber includes collecting strain data along a length of the fiber, calculating curvature and bending direction data of the fiber using the strain data, curve-fitting the curvature and bending direction data to derive curvature and bending direction functions, calculating a torsion function using the bending direction function, and determining the 3D shape from the curvature, bending direction, and torsion functions. An apparatus for determining the 3D shape of the fiber includes a fiber optic cable unbound with respect to a protective sleeve, strain sensors positioned along the cable, and a controller in communication with the sensors. The controller has an algorithm for determining a 3D shape and end position of the fiber by calculating a set of curvature and bending direction data, deriving curvature, bending, and torsion functions, and solving Frenet-Serret equations using these functions

System and method for determination of the reflection wavelength of multiple low-reflectivity bragg gratings in a sensing optical fiber

A system and method for determining a reflection wavelength of multiple Bragg gratings in a sensing optical fiber comprise: (1) a source laser; (2) an optical detector configured to detect a reflected signal from the sensing optical fiber; (3) a plurality of frequency generators configured to generate a signal having a frequency corresponding to an interferometer frequency of a different one of the plurality of Bragg gratings; (4) a plurality of demodulation elements, each demodulation element configured to combine the signal produced by a different one of the plurality of frequency generators with the detected signal from the sensing optical fiber; (5) a plurality of peak detectors, each peak detector configured to detect a peak of the combined signal from a different one of the demodulation elements; and (6) a laser wavenumber detection element configured to determine a wavenumber of the laser when any of the peak detectors detects a peak

Cheap Food and Bad Climate: From Surplus Value to Negative-Value in the Capitalist World-Ecology

Capitalism, understood as a world-ecology that joins accumulation, power, and nature in dialectical unity, has been adept at evading so-called Malthusian dynamics through an astonishing historical capacity to produce, locate, and occupy cheap natures external to the system. In recent decades, the last frontiers have closed, and this astonishing historical capacity has withered. This “withering” is perhaps most evident in capitalism’s failure to offer a new, actually productive, agricultural model—as agrobiotechnology failed to deliver on its promissory notes. Moving from bad to worse, a second set of contradictions is now mediated through climate change. Climate change, one among many ongoing biospheric shifts, is interwoven with the totality of neoliberal agriculture’s contradictions to produce a new contradiction: negative value. This signals the emergence of forms of nature that are increasingly hostile to capital accumulation and that can be temporarily fixed (if at all) only through increasingly costly, toxic, and dangerous strategies. The rise of negative value—whose accumulation has been latent for much of capitalist history—therefore suggests a significant and rapid erosion of opportunities for the appropriation of new streams of unpaid work/energy. As such, these new limits are qualitatively different from the nutrient and resource depletion of earlier, developmental crises of the longue dure´e Cheap Food model. These contradictions, within capital, arising from negative value, are today encouraging an unprecedented shift toward a radical ontological politics, within capitalism as a whole, that destabilizes crucial points of agreement in the modern world-system: What is food? What is nature? What is valuable