Nonapproximability Results for Partially Observable Markov Decision Processes

We show that for several variations of partially observable Markov decision processes, polynomial-time algorithms for finding control policies are unlikely to or simply don't have guarantees of finding policies within a constant factor or a constant summand of optimal. Here "unlikely" means "unless some complexity classes collapse," where the collapses considered are P=NP, P=PSPACE, or P=EXP. Until or unless these collapses are shown to hold, any control-policy designer must choose between such performance guarantees and efficient computation

False-Name Manipulation in Weighted Voting Games is Hard for Probabilistic Polynomial Time

False-name manipulation refers to the question of whether a player in a weighted voting game can increase her power by splitting into several players and distributing her weight among these false identities. Analogously to this splitting problem, the beneficial merging problem asks whether a coalition of players can increase their power in a weighted voting game by merging their weights. Aziz et al. [ABEP11] analyze the problem of whether merging or splitting players in weighted voting games is beneficial in terms of the Shapley-Shubik and the normalized Banzhaf index, and so do Rey and Rothe [RR10] for the probabilistic Banzhaf index. All these results provide merely NP-hardness lower bounds for these problems, leaving the question about their exact complexity open. For the Shapley--Shubik and the probabilistic Banzhaf index, we raise these lower bounds to hardness for PP, "probabilistic polynomial time", and provide matching upper bounds for beneficial merging and, whenever the number of false identities is fixed, also for beneficial splitting, thus resolving previous conjectures in the affirmative. It follows from our results that beneficial merging and splitting for these two power indices cannot be solved in NP, unless the polynomial hierarchy collapses, which is considered highly unlikely

Naturally Occurring Deletion Mutants of the Pig-Specific, Intestinal Crypt Epithelial Cell Protein CLCA4b without Apparent Phenotype.

The human CLCA4 (chloride channel regulator, calcium-activated) modulates the intestinal phenotype of cystic fibrosis (CF) patients via an as yet unknown pathway. With the generation of new porcine CF models, species-specific differences between human modifiers of CF and their porcine orthologs are considered critical for the translation of experimental data. Specifically, the porcine ortholog to the human CF modulator gene CLCA4 has recently been shown to be duplicated into two separate genes, CLCA4a and CLCA4b. Here, we characterize the duplication product, CLCA4b, in terms of its genomic structure, tissue and cellular expression patterns as well as its in vitro electrophysiological properties. The CLCA4b gene is a pig-specific duplication product of the CLCA4 ancestor and its protein is exclusively expressed in small and large intestinal crypt epithelial cells, a niche specifically occupied by no other porcine CLCA family member. Surprisingly, a unique deleterious mutation of the CLCA4b gene is spread among modern and ancient breeds in the pig population, but this mutation did not result in an apparent phenotype in homozygously affected animals. Electrophysiologically, neither the products of the wild type nor of the mutated CLCA4b genes were able to evoke a calcium-activated anion conductance, a consensus feature of other CLCA proteins. The apparently pig-specific duplication of the CLCA4 gene with unique expression of the CLCA4b protein variant in intestinal crypt epithelial cells where the porcine CFTR is also present raises the question of whether it may modulate the porcine CF phenotype. Moreover, the naturally occurring null variant of CLCA4b will be valuable for the understanding of CLCA protein function and their relevance in modulating the CF phenotype

Model Checking CTL is Almost Always Inherently Sequential

The model checking problem for CTL is known to be P-complete (Clarke, Emerson, and Sistla (1986), see Schnoebelen (2002)). We consider fragments of CTL obtained by restricting the use of temporal modalities or the use of negations---restrictions already studied for LTL by Sistla and Clarke (1985) and Markey (2004). For all these fragments, except for the trivial case without any temporal operator, we systematically prove model checking to be either inherently sequential (P-complete) or very efficiently parallelizable (LOGCFL-complete). For most fragments, however, model checking for CTL is already P-complete. Hence our results indicate that, in cases where the combined complexity is of relevance, approaching CTL model checking by parallelism cannot be expected to result in any significant speedup. We also completely determine the complexity of the model checking problem for all fragments of the extensions ECTL, CTL+, and ECTL+

Intuitionistic implication makes model checking hard

We investigate the complexity of the model checking problem for intuitionistic and modal propositional logics over transitive Kripke models. More specific, we consider intuitionistic logic IPC, basic propositional logic BPL, formal propositional logic FPL, and Jankov's logic KC. We show that the model checking problem is P-complete for the implicational fragments of all these intuitionistic logics. For BPL and FPL we reach P-hardness even on the implicational fragment with only one variable. The same hardness results are obtained for the strictly implicational fragments of their modal companions. Moreover, we investigate whether formulas with less variables and additional connectives make model checking easier. Whereas for variable free formulas outside of the implicational fragment, FPL model checking is shown to be in LOGCFL, the problem remains P-complete for BPL.Comment: 29 pages, 10 figure

Mucin granule-associated proteins in human bronchial epithelial cells: the airway goblet cell "granulome"

<p>Abstract</p> <p>Background</p> <p>Excess mucus in the airways leads to obstruction in diseases such as chronic bronchitis, asthma, and cystic fibrosis. Mucins, the highly glycosolated protein components of mucus, are stored in membrane-bound granules housed in the cytoplasm of airway epithelial "goblet" cells until they are secreted into the airway lumen via an exocytotic process. Precise mechanism(s) of mucin secretion, including the specific proteins involved in the process, have yet to be elucidated. Previously, we have shown that the Myristoylated Alanine-Rich C Kinase Substrate (MARCKS) protein regulates mucin secretion by orchestrating translocation of mucin granules from the cytosol to the plasma membrane, where the granules dock, fuse and release their contents into the airway lumen. Associated with MARCKS in this process are chaperone (Heat Shock Protein 70 [HSP70], Cysteine string protein [CSP]) and cytoskeletal (actin, myosin) proteins. However, additional granule-associated proteins that may be involved in secretion have not yet been elucidated.</p> <p>Methods</p> <p>Here, we isolated mucin granules and granule membranes from primary cultures of well differentiated human bronchial epithelial cells utilizing a novel technique of immuno-isolation, based on the presence of the calcium activated chloride channel hCLCA1 (the human ortholog of murine Gob-5) on the granule membranes, and verified via Western blotting and co-immunoprecipitation that MARCKS, HSP70, CSP and hCLCA1 were present on the granule membranes and associated with each other. We then subjected the isolated granules/membranes to liquid chromatography mass spectrometry (LC-MS/MS) to identify other granule associated proteins.</p> <p>Results</p> <p>A number of additional cytoskeletal (e.g. Myosin Vc) and regulatory proteins (e.g. Protein phosphatase 4) associated with the granules and could play a role in secretion were discovered. This is the first description of the airway goblet cell "granulome."</p

Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics

Spatial context in images induces perceptual phenomena associated with salience and modulates the responses of neurons in primary visual cortex (V1). However, the computational and ecological principles underlying contextual effects are incompletely understood. We introduce a model of natural images that includes grouping and segmentation of neighboring features based on their joint statistics, and we interpret the firing rates of V1 neurons as performing optimal recognition in this model. We show that this leads to a substantial generalization of divisive normalization, a computation that is ubiquitous in many neural areas and systems. A main novelty in our model is that the influence of the context on a target stimulus is determined by their degree of statistical dependence. We optimized the parameters of the model on natural image patches, and then simulated neural and perceptual responses on stimuli used in classical experiments. The model reproduces some rich and complex response patterns observed in V1, such as the contrast dependence, orientation tuning and spatial asymmetry of surround suppression, while also allowing for surround facilitation under conditions of weak stimulation. It also mimics the perceptual salience produced by simple displays, and leads to readily testable predictions. Our results provide a principled account of orientation-based contextual modulation in early vision and its sensitivity to the homogeneity and spatial arrangement of inputs, and lends statistical support to the theory that V1 computes visual salience

Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception

Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas