Synchronizations in Team Automata for Groupware Systems

Team automata have been proposed in Ellis (1997) as a formal framework for modeling both the conceptual and the architectural level of groupware systems. Here we define team automata in a mathematically precise way in terms of component automata which synchronizeon certain executions of actions.At the conceptual level, our model serves as a formal framework in whichbasic groupware notions can be rigorously defined and studied.At the architectural level, team automata can be used as building blocksin the design of groupware systems.     

The linear landscape of external contextual languages

The class of external contextual languages isstrictly included in the class of linear languages. A reason for the strict inclusion in linear languages is that external contextual grammars generate languages in the exhaustive way: each sentential form belongs to the language of a grammar. In this paper we study the effect of adding various squeezing mechanisms to the basic classes of exhaustive contextual grammars. We obtain in this way a characterization of linear languages and a whole landscape of sublinear families. By restricting the contexts to be one-sided (only left-sided or only right-sided) we obtain a characterization of regular languages — here the subregular landscape reduces to two families.     

Structure and electrochemical reactivity of new sulphur–silicon podands adsorbed on silver or gold surfaces

By the self-assembly monolayer (SAM) organization, three new podands belonging to silylpropanethiols have been tested as to their ability to form nanolayers protecting the noble metal surface (gold or silver) and to form complexes with monovalent metal cations on the metal surfaces. The stable self-assembled chemisorbed layers, providing protection to metal surface against electrooxidation and capable of blocking propylene carbonate (PC) electroreduction and Li electrodeposition were produced. Reflection-absorption infrared spectroscopy (RAIRS) indicated cleavage of the S–H bond upon adsorption of species 1–3 with the formation of S–Ag bonds on the metal surface. By cyclic voltammetry, it was found that the primary adsorbate formed on a Au electrode at E _ad (between −0.2 and −1.2 V vs. SCE) underwent reductive desorption at E < −1.3 V vs. SCE. The structures of 1–3 and their complexes with Na⁺ cations on the Ag surfaces were calculated and visualized by the AM1d semi-empirical method.     

Catalytic destruction of methyl tertiary butyl ether (MTBE) using oxidized carbon

Decomposition of methyl tert-butyl ether (MTBE) in the gas phase was studied using carbon catalysts with chemically modified surface. Carbon samples with different surface chemical properties were obtained from commercial activated carbon D43/1 (CarboTech, Essen, Germany) by oxidation in liquid phase with various oxidants as well as in air. The catalytic tests were performed in a flow reactor at a temperature range of 353–473 K. Isobutene and methanol are the only products of the MTBE decomposition. The generation of surface acidic oxides considerably enhances the catalytic activity of the carbons. However, the activity is controlled not only by the number and strength of acidic groups, but also by their accessibility. The most active carbon is that oxidized with air at 673 K, which contains pores wider than the pores of other oxidized carbons.     

Apex graph grammars and attribute grammars

Summary Apex graph grammars are a particular type of directed node-label controlled (DNLC) graph grammars: the embedding edges are established between terminal nodes only. Apex graph grammars, slightly generalized, can generate the sets of dependency graphs of attribute grammars. The other way around, every apex graph language can be obtained from such a dependency graph language by a graph replacement (which is an operation analogous to a string homomorphism).     

Visual detection of blemishes in potatoes using minimalist boosted classifiers

This paper introduces novel methods for detecting blemishes in potatoes using machine vision. After segmentation of the potato from the background, a pixel-wise classifier is trained to detect blemishes using features extracted from the image. A very large set of candidate features, based on statistical information relating to the colour and texture of the region surrounding a given pixel, is first extracted. Then an adaptive boosting algorithm (AdaBoost) is used to automatically select the best features for discriminating between blemishes and non-blemishes. With this approach, different features can be selected for different potato varieties, while also handling the natural variation in fresh produce due to different seasons, lighting conditions, etc. The results show that the method is able to build “minimalist” classifiers that optimise detection performance at low computational cost. In experiments, blemish detectors were trained for both white and red potato varieties, achieving 89.6% and 89.5% accuracy, respectively.     

Hydrogen production by steam reforming of ethanol over Co/CeO2 catalysts: Effect of cobalt content

The Co/CeO₂ catalysts obtained by co-precipitation method were used in the steam reforming of ethanol (SRE). The influence of cobalt active phase content (15–29 wt%), the reaction temperature (420–600 °C) and H₂O/EtOH molar ratio (12/1 and 6/1) were examined. The physicochemical characterization revealed that the cobalt content of the catalyst influences the metal-support interaction which results in catalyst performance in SRE process. The differences between catalytic properties of the Co/CeO₂ catalysts with different metal loading in SRE process decayed at 500 °C for H₂O/EtOH = 12/1. The best performance among the tested catalysts showed the 29Co/CeO₂ catalyst with the highest cobalt content, exhibiting the highest ethanol conversion, selectivity to two most desirable products and the lowest selectivity to by-products in comparison with catalysts containing smaller amount of metal. Its catalytic properties results probably from its unique physicochemical properties, i.e this catalyst contains large amount of cobalt but the metal crystallites are relatively small. Regardless cobalt content, an increase in the water-to-ethanol molar ratio in the feed increased the concentration of hydrogen an carbon dioxide and decreased formation of carbon monoxide, acetone, aldehyde and ethylene.     

Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture

Agricultural robots rely on semantic segmentation for distinguishing between crops and weeds to perform selective treatments and increase yield and crop health while reducing the amount of chemicals used. Deep‐learning approaches have recently achieved both excellent classification performance and real‐time execution. However, these techniques also rely on a large amount of training data, requiring a substantial labeling effort, both of which are scarce in precision agriculture. Additional design efforts are required to achieve commercially viable performance levels under varying environmental conditions and crop growth stages. In this paper, we explore the role of knowledge transfer between deep‐learning‐based classifiers for different crop types, with the goal of reducing the retraining time and labeling efforts required for a new crop. We examine the classification performance on three datasets with different crop types and containing a variety of weeds and compare the performance and retraining efforts required when using data labeled at pixel level with partially labeled data obtained through a less time‐consuming procedure of annotating the segmentation output. We show that transfer learning between different crop types is possible and reduces training times for up to 80%. Furthermore, we show that even when the data used for retraining are imperfectly annotated, the classification performance is within 2% of that of networks trained with laboriously annotated pixel‐precision data.     

Bacteriophages vB_Sen-TO17 and vB_Sen-E22, Newly Isolated Viruses from Chicken Feces,Specific for Several Salmonella enterica Strains

Two newly discovered bacteriophages, isolated from chicken feces and infecting Salmonella enterica strains, are described in this report. These phages have been named vB_Sen-TO17 and vB_Sen-E22, and we present their molecular and functional characterization. Both studied viruses are able to infect several S. enterica strains and develop lytically, but their specific host ranges differ significantly. Electron microscopic analyses of virions have been performed, and full genome sequences were determined and characterized, along with molecular phylogenetic studies. Genomes of vB_Sen-TO17 (ds DNA of 41,658 bp) and vB_Sen-E22 (dsDNA of 108,987 bp) are devoid of homologs of any known or putative gene coding for toxins or any other proteins potentially deleterious for eukaryotic cells. Both phages adsorbed efficiently (>95% adsorbed virions) within 10 min at 42 °C (resembling chicken body temperature) on cells of most tested host strains. Kinetics of lytic development of vB_Sen-TO17 and vB_Sen-E22, determined in one-step growth experiments, indicated that development is complete within 30–40 min at 42 °C, whereas burst sizes vary from 9 to 79 progeny phages per cell for vB_Sen-TO17 and from 18 to 64 for vB_Sen-E22, depending on the host strain. Virions of both phages were relatively stable (from several percent to almost 100% survivability) under various conditions, including acidic and alkaline pH values (from 3 to 12), temperatures from −80 °C to 60 °C, 70% ethanol, chloroform, and 10% DMSO. These characteristics of vB_Sen-TO17 and vB_Sen-E22 indicate that these phages might be considered in further studies on phage therapy, particularly in attempts to eliminate S. enterica from chicken intestine.