Abstract. Interactive provers typically use higher-order logic, while automatic provers typically use first-order logic. In order to integrate interactive provers with automatic ones, it is necessary to translate higher-order formulae to first-order form. The translation should ideally be both sound and practical. We have investigated several methods of translating function applications, types and λ-abstractions. Omitting some type information improves the success rate, but can be unsound, so the interactive prover must verify the proofs. This paper presents experimental data that compares the translations in respect of their success rates for three automatic provers.

In this paper, we put forward a novel approach for change detection in synthetic aperture radar (SAR) images. The approach classifies changed and unchanged regions by fuzzy c-means (FCM) clustering with a novel Markov random field (MRF) energy function. In order to reduce the effect of speckle noise, a novel form of the MRF energy function with an additional term is established to modify the membership of each pixel. In addition, the degree of modification is determined by the relationship of the neighborhood pixels. The specific form of the additional term is contingent upon different situations, and it is established ultimately by utilizing the least-square method. There are two aspects to our contributions. First, in order to reduce the effect of speckle noise, the proposed approach focuses on modifying the membership instead of modifying the objective function. It is computationally simple in all the steps involved. Its objective function can just return to the original form of FCM, which leads to its consuming less time than that of some obviously recently improved FCM algorithms. Second, the proposed approach modifies the membership of each pixel according to a novel form of the MRF energy function through which the neighbors of each pixel, as well as their relationship, are concerned. Theoretical analysis and experimental results on real SAR datasets show that the proposed approach can detect the real changes as well as mitigate the effect of speckle noises. Theoretical analysis and experiments also demonstrate its low time complexity.Index Terms-Fuzzy clustering, image change detection, Markov random field (MRF), synthetic aperture radar (SAR). 1063-6706

Irrelevant clauses in resolution problems increase the search space, making proofs hard to find in a reasonable amount of processor time. Simple relevance filtering methods, based on counting symbols in clauses, improve the success rate for a variety of automatic theorem provers and with various initial settings. We have designed these techniques as part of a project to link automatic theorem provers to the interactive theorem prover Isabelle. We have tested them for problems involving thousands of clauses, which yield poor results without filtering. Our methods should be applicable to other tasks where the resolution problems are produced mechanically and where completeness is less important than achieving a high success rate with limited processor time.

The neuroimmunological and behavioral consequences of a high-fat diet (HFD) are not well delineated. This is especially true when short term (24 h) fasting is used as a physiologic stressor. In this study, we examined the impact of a HFD on learning and memory and depressive-like behaviors to understand how fasting impacts neuroimmunity and if obesity modulates the response. Mice were fed diets containing either 10% (LFD mice) or 60% (HFD mice) calories from fat for 10-12 wks. Gene transcripts for 26 pro-/anti-inflammatory cytokines and markers of macrophage activation were examined in adipose tissue and whole brain. Mouse learning and memory (spontaneous alternation, novel object) and depressive like behaviors (saccharin preference, burrowing, forced swim) were studied in the fed and fasted state as were gene transcripts for F4/80, CD11b, IL-1alpha, IL-1beta, IL-1R1, IL-1R2, IL-1RA, IL-6 and TNF-alpha in cortex, hippocampus and hypothalamus. In the fed state, HFD mice compared to LFD mice had reduced locomotor activity, were adverse to saccharin and burrowed less. After fasting, LFD mice verse HFD mice lost 18% vs 5% of their body weight, respectively. In addition, HFD mice failed to down-regulate gene transcripts for the myeloid-cell associated proteins F4/80, CD11b and IL-1alpha in the brain, failed to appropriately explore a novel object, failed to reduce locomotor activity and had increased saccharin consumption and burrowing. These data indicate that fasting induces an anti-inflammatory effect on the neuroimmune system which a HFD prevents. This breakdown appears linked to the IL-1 system because of the association of this cytokine with memory and learning.

Caffeine, an antagonist of the adenosine receptor A1R, is used as a dietary supplement to reduce body weight, although the underlying mechanism is unclear. Here, we report that adenosine level in the cerebrospinal fluid, and hypothalamic expression of A1R, are increased in the diet-induced obesity (DIO) mouse. We find that mice with overexpression of A1R in the neurons of paraventricular nucleus (PVN) of the hypothalamus are hyperphagic, have glucose intolerance and high body weight. Central or peripheral administration of caffeine reduces the body weight of DIO mice by the suppression of appetite and increasing of energy expenditure. We also show that caffeine excites oxytocin expressing neurons, and blockade of the action of oxytocin significantly attenuates the effect of caffeine on energy balance. These data suggest that caffeine inhibits A1Rs expressed on PVN oxytocin neurons to negatively regulate energy balance in DIO mice.