An LP-Based Approach for Goal Recognition as Planning

Goal recognition aims to recognize the set of candidate goals that are compatible with the observed behavior of an agent. In this paper, we develop a method based on the operator-counting framework that efficiently computes solutions that satisfy the observations and uses the information generated to solve goal recognition tasks. Our method reasons explicitly about both partial and noisy observations: estimating uncertainty for the former, and satisfying observations given the unreliability of the sensor for the latter. We evaluate our approach empirically over a large data set, analyzing its components on how each can impact the quality of the solutions. In general, our approach is superior to previous methods in terms of agreement ratio, accuracy, and spread. Finally, our approach paves the way for new research on combinatorial optimization to solve goal recognition tasks.Comment: 8 pages, 4 tables, 3 figures. Published in AAAI 2021. Updated final authorship and tex

Scintillation counter with MRS APD light readout

START, a high-efficiency and low-noise scintillation detector for ionizing particles, was developed for the purpose of creating a high-granular system for triggering cosmic muons. Scintillation light in START is detected by MRS APDs (Avalanche Photo-Diodes with Metal-Resistance-Semiconductor structure), operated in the Geiger mode, which have 1 mm^2 sensitive areas. START is assembled from a 15 x 15 x 1 cm^3 scintillating plastic plate, two MRS APDs and two pieces of wavelength-shifting optical fiber stacked in circular coils inside the plastic. The front-end electronic card is mounted directly on the detector. Tests with START have confirmed its operational consistency, over 99% efficiency of MIP registration and good homogeneity. START demonstrates a low intrinsic noise of about 10^{-2} Hz. If these detectors are to be mass-produced, the cost of a mosaic array of STARTs is estimated at a moderate level of 2-3 kUSD/m^2.Comment: 6 pages, 5 figure

Control of Candida albicans Metabolism and Biofilm Formation by Pseudomonas aeruginosa Phenazines

Candida albicans has developmental programs that govern transitions between yeast and filamentous morphologies and between unattached and biofilm lifestyles. Here, we report that filamentation, intercellular adherence, and biofilm development were inhibited during interactions between Candida albicans and Pseudomonas aeruginosa through the action of P. aeruginosa-produced phenazines. While phenazines are toxic to C. albicans at millimolar concentrations, we found that lower concentrations of any of three different phenazines (pyocyanin, phenazine methosulfate, and phenazine-1-carboxylate) allowed growth but affected the development of C. albicans wrinkled colony biofilms and inhibited the fungal yeast-to-filament transition. Phenazines impaired C. albicans growth on nonfermentable carbon sources and led to increased production of fermentation products (ethanol, glycerol, and acetate) in glucose-containing medium, leading us to propose that phenazines specifically inhibited respiration. Methylene blue, another inhibitor of respiration, also prevented the formation of structured colony biofilms. The inhibition of filamentation and colony wrinkling was not solely due to lowered extracellular pH induced by fermentation. Compared to smooth, unstructured colonies, wrinkled colony biofilms had higher oxygen concentrations within the colony, and wrinkled regions of these colonies had higher levels of respiration. Together, our data suggest that the structure of the fungal biofilm promotes access to oxygen and enhances respiratory metabolism and that the perturbation of respiration by bacterial molecules such as phenazines or compounds with similar activities disrupts these pathways. These findings may suggest new ways to limit fungal biofilms in the context of disease. IMPORTANCE: Many of the infections caused by Candida albicans, a major human opportunistic fungal pathogen, involve both morphological transitions and the formation of surface-associated biofilms. Through the study of C. albicans interactions with the bacterium Pseudomonas aeruginosa, which often coinfects with C. albicans, we have found that P. aeruginosa-produced phenazines modulate C. albicans metabolism and, through these metabolic effects, impact cellular morphology, cell-cell interactions, and biofilm formation. We suggest that the structure of C. albicans biofilms promotes access to oxygen and enhances respiratory metabolism and that the perturbation of respiration by phenazines inhibits biofilm development. Our findings not only provide insight into interactions between these species but also provide valuable insights into novel pathways that could lead to the development of new therapies to treat C. albicans infections

Folksonomies and clustering in the collaborative system CiteULike

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tripartite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient reflects the semantical patterns among tags, providing useful ideas for the designing of more efficient methods of data classification and spam detection.Comment: 9 pages, 5 figures, iop style; corrected typo

Control of Candida albicans Metabolism and Biofilm Formation by Pseudomonas aeruginosa Phenazines

Candidaalbicanshasdevelopmentalprogramsthatgoverntransitionsbetweenyeastandfilamentousmorphologies and between unattached and biofilm lifestyles. Here, we report that filamentation, intercellular adherence, and biofilm develop- ment were inhibited during interactions between Candida albicans and Pseudomonas aeruginosa through the action of P. aeruginosa-produced phenazines. While phenazines are toxic to C. albicans at millimolar concentrations, we found that lower concentrations of any of three different phenazines (pyocyanin, phenazine methosulfate, and phenazine-1-carboxylate) allowed growth but affected the development of C. albicans wrinkled colony biofilms and inhibited the fungal yeast-to-filament transition. Phenazines impaired C. albicans growth on nonfermentable carbon sources and led to increased production of fer- mentation products (ethanol, glycerol, and acetate) in glucose-containing medium, leading us to propose that phenazines specif- ically inhibited respiration. Methylene blue, another inhibitor of respiration, also prevented the formation of structured colony biofilms. The inhibition of filamentation and colony wrinkling was not solely due to lowered extracellular pH induced by fer- mentation. Compared to smooth, unstructured colonies, wrinkled colony biofilms had higher oxygen concentrations within the colony, and wrinkled regions of these colonies had higher levels of respiration. Together, our data suggest that the structure of the fungal biofilm promotes access to oxygen and enhances respiratory metabolism and that the perturbation of respiration by bacterial molecules such as phenazines or compounds with similar activities disrupts these pathways. These findings may sug- gest new ways to limit fungal biofilms in the context of disease

Motor sequences; separating the sequence from the motor: A longitudinal rsfMRI study

In motor learning, sequence specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific decreases in functional connectivity during overall learning in the right supplementary motor area (SMA). We found that connectivity changes in a key region of the motor network, the superior parietal cortex (SPC) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA that has previously been identified in online task-based learning studies, and extends it to resting state network changes after sequence-specific MSL