Detecting word substitutions in text

Searching for words on a watchlist is one way in which large-scale surveillance of communication can be done, for example in intelligence and counterterrorism settings. One obvious defense is to replace words that might attract attention to a message with other, more innocuous, words. For example, the sentence the attack will be tomorrow" might be altered to the complex will be tomorrow", since 'complex' is a word whose frequency is close to that of 'attack'. Such substitutions are readily detectable by humans since they do not make sense. We address the problem of detecting such substitutions automatically, by looking for discrepancies between words and their contexts, and using only syntactic information. We define a set of measures, each of which is quite weak, but which together produce per-sentence detection rates around 90% with false positive rates around 10%. Rules for combining persentence detection into per-message detection can reduce the false positive and false negative rates for messages to practical levels. We test the approach using sentences from the Enron email and Brown corpora, representing informal and formal text respectively

Backprop as Functor: A compositional perspective on supervised learning

A supervised learning algorithm searches over a set of functions $A \to B$ parametrised by a space $P$ to find the best approximation to some ideal function $f\colon A \to B$. It does this by taking examples $(a,f(a)) \in A\times B$, and updating the parameter according to some rule. We define a category where these update rules may be composed, and show that gradient descent---with respect to a fixed step size and an error function satisfying a certain property---defines a monoidal functor from a category of parametrised functions to this category of update rules. This provides a structural perspective on backpropagation, as well as a broad generalisation of neural networks.Comment: 13 pages + 4 page appendi

Temporal Landscapes: A Graphical Temporal Logic for Reasoning

We present an elementary introduction to a new logic for reasoning about behaviors that occur over time. This logic is based on temporal type theory. The syntax of the logic is similar to the usual first-order logic; what differs is the notion of truth value. Instead of reasoning about whether formulas are true or false, our logic reasons about temporal landscapes. A temporal landscape may be thought of as representing the set of durations over which a statement is true. To help understand the practical implications of this approach, we give a wide variety of examples where this logic is used to reason about autonomous systems.Comment: 20 pages, lots of figure

Combination immunotherapy induces distinct T-cell repertoire responses when administered to patients with different malignancies.

BackgroundCTLA-4 blockade with ipilimumab is Food and Drug Administration-approved for melanoma as a monotherapy and has been shown to modulate the circulating T-cell repertoire. We have previously reported clinical trials combining CTLA-4 blockade with granulocyte-macrophage colony-stimulating factor (GM-CSF) in metastatic melanoma patients and in metastatic castration resistant prostate cancer (mCRPC) patients. Here, we investigate the effect that cancer type has on circulating T cells in metastatic melanoma and mCRPC patients, treated with ipilimumab and GM-CSF.MethodsWe used next-generation sequencing of T-cell receptors (TCR) to compare the circulating T cells of melanoma and mCRPC patients receiving the same treatment with ipilimumab and GM-CSF by Wilcoxon rank sum test. Flow cytometry was utilized to investigate specific T-cell populations. TCR sequencing results were correlated with each T-cell subpopulation by Spearman's rank correlation coefficient. Of note, 14 metastatic melanoma patients had samples available for TCR sequencing and 21 had samples available for flow cytometry analysis; 37 mCRPC patients had samples available for sequencing of whom 22 have TCR data available at both timepoints; 20 of these patients had samples available for flow cytometry analysis and 16 had data available at both timepoints.ResultsWhile melanoma and mCRPC patients had similar pretreatment circulating T-cell counts, treatment induces greater expansion of circulating T cells in melanoma patients. Metastatic melanoma patients have a higher proportion of clones that increased more than fourfold after the treatment compared with mCRPC patients (18.9% vs 11.0%, p=0.017). Additionally, melanoma patients compared with mCRPC patients had a higher ratio of convergent frequency (1.22 vs 0.60, p=0.012). Decreases in clonality induced by treatment are associated with baseline CD8+ T-cell counts in both patient groups, but are more pronounced in the melanoma patients (r=-0.81, p<0.001 vs r=-0.59, p=0.02).Trial registration numbersNCT00064129; NCT01363206

A Strong Impact of Genetic Background on Gut Microflora in Mice

Genetic background affects susceptibility to ileocolitis in mice deficient in two intracellular glutathione peroxidases, GPx1 and GPx2. The C57BL/6 (B6) GPx1/2 double-knockout (DKO) mice have mild ileocolitis, and 129S1/Sv (129) DKO mice have severe inflammation. We used diet to modulate ileocolitis; a casein-based defined diet with AIN76A micronutrients (AIN) attenuates inflammation compared to conventional LabDiets. Because luminal microbiota induce DKO ileocolitis, we assessed bacterial composition with automated ribosomal intergenic-spacer analysis (ARISA) on cecal DNA. We found that mouse strain had the strongest impact on the composition of microbiota than diet and GPx genotypes. In comparing AIN and LabDiet, DKO mice were more resistant to change than the non-DKO or WT mice. However, supplementing yeast and inulin to AIN diet greatly altered microflora profiles in the DKO mice. From 129 DKO strictly, we found overgrowth of Escherichia coli. We conclude that genetic background predisposes mice to colonization of potentially pathogenic E. coli