Promotion by vanadium compound of the elementary reaction steps in the synthesis gas reaction catalyzed by rhodium

In order to understand the promoting effect of V compd. on Rh catalysts in synthesis gas conversion, changes in reaction rates of elementary steps and the surface concn. of intermediates have been monitored. V promotion enhances the rate of CO dissocn. which is the most important effect. Reactive surface carbon is stabilized by V which results in a slightly decreased reactivity in methane formation. Transient expts. using isotopes and GCMS detection show that CO insertion is not promoted by V. The hydrogenation of ethanal to ethanol is enhanced by V while the desorption rate of ethanal is decrease

Dynamics of an exclusion process with creation and annihilation

We examine the dynamical properties of an exclusion process with creation and annihilation of particles in the framework of a phenomenological domain-wall theory, by scaling arguments and by numerical simulation. We find that the length- and time scale are finite in the maximum current phase for finite creation- and annihilation rates as opposed to the algebraically decaying correlations of the totally asymmetric simple exclusion process (TASEP). Critical exponents of the transition to the TASEP are determined. The case where bulk creation- and annihilation rates vanish faster than the inverse of the system size N is also analyzed. We point out that shock localization is possible even for rates proportional to 1/N^a, 1<a<2.Comment: 16 pages, 8 figures, typos corrected, references added, section 4 revise

Nonhydrothermal Synthesis and Properties of Saponite-Like Materials

Abstract-Main features of nonhydrothermal synthesis of saponite-like materials containing Zn(II) and Mg(II) cations in octahedral networks were studied. Optimal conditions for the synthesis were determined. The influence exerted by the double-charged structure-forming cation on the rate of structure formation in the synthesized materials and also on their pore structure and thermal stability was studied

Forage Data Hub – A Platform for Sharing Valuable Datasets for Resilience

In accord with the necessity to enhance ecosystem services and productivity in food systems, is the increase of data availability at multiple scales and over time. To help meet this need, we discuss the development of a National Forage Data Hub which will act as a platform to curate, share, and analyze data pertaining to forage systems. This centralized hub will leverage existing datasets by bridging multiple sources including forage crop—soil, water, and nutrient availability—yield (animal and crop) potential (and gaps)— climate—management systems at high spatial and temporal resolution enabling system interaction assessments through next-generation analytics. This novel approach to existing datasets will integrate Big Data at the soilwater- plant-animal-climate nexus to advance data storage technology systems for multiple trophic-level research projects

SNGuess: A method for the selection of young extragalactic transients

With a rapidly rising number of transients detected in astronomy, classification methods based on machine learning are increasingly being employed. Their goals are typically to obtain a definitive classification of transients, and for good performance they usually require the presence of a large set of observations. However, well-designed, targeted models can reach their classification goals with fewer computing resources. This paper presents SNGuess, a model designed to find young extragalactic nearby transients with high purity. SNGuess works with a set of features that can be efficiently calculated from astronomical alert data. Some of these features are static and associated with the alert metadata, while others must be calculated from the photometric observations contained in the alert. Most of the features are simple enough to be obtained or to be calculated already at the early stages in the lifetime of a transient after its detection. We calculate these features for a set of labeled public alert data obtained over a time span of 15 months from the Zwicky Transient Facility (ZTF). The core model of SNGuess consists of an ensemble of decision trees, which are trained via gradient boosting. Approximately 88% of the candidates suggested by SNGuess from a set of alerts from ZTF spanning from April 2020 to August 2021 were found to be true relevant supernovae (SNe). For alerts with bright detections, this number ranges between 92% and 98%. Since April 2020, transients identified by SNGuess as potential young SNe in the ZTF alert stream are being published to the Transient Name Server (TNS) under the AMPEL_ZTF_NEW group identifier. SNGuess scores for any transient observed by ZTF can be accessed via a web service. The source code of SNGuess is publicly available.Comment: 14 pages, 10 figures, Astronomy & Astrophysics (A&A), Forthcoming article, source code https://github.com/nmiranda/SNGues