Metastable Phase Selection and Partitioning for Zr(1−x)AlxO(2−x/2) Materials Synthesized with Liquid Precursors

Aqueous solutions of zirconium acetate and aluminum nitrate were spray pyrolyzed at 250°C and upquenched to different temperatures to yield metastable solid solutions of composition Zr_{(1− x )}Al_xO_{(2− x /2)}. An amorphous oxide forms first during pyrolysis which subsequently crystallizes as a single phase for x ≤ 0.57 (≤40 mol% Al₂O₃). The crystallization temperature increased with Al₂O₃ content. Electron diffraction, supported by Raman spectroscopy, indicates that the initial phase is tetragonal. At higher temperatures, the initial solid solation partitions to other metastable phases, viz., t -ZrO₂+γ-Al₂O₃, prior to achieving their equilibrium phase assemblage, m -ZrO₂+α-Al₂O₃. Partitioning yields a nanocomposite microstructure with grain sizes of 20–100 nm, compared to the 3 to 5 nm in the initial, single phase. Compositions containing 45 to 50 mol% Al₂O₃ concurrently crystallize and partition. The structure selected during crystallization and the partitioning phenomena are discussed in terms of diffusional constraints during crystallization, which are conceptually similar to those operating during rapid solidification.     

The effect of NO2 on the activity of fresh and aged zeolite catalysts in the NH3-SCR reaction

The activity of fresh and hydrothermally aged zeolite-based catalysts in the NH₃-selective catalytic reduction (SCR) reaction with excess of oxygen were studied. In addition, the effect of NO₂ in the gas feed as well as the acidity of the catalysts for the SCR activity was investigated. The studied catalysts were hydrogen, copper, iron and silver ion exchanged ZSM-5, mordenite, beta, ferrierite, and Y-zeolites. The investigation verifies that the zeolite-based catalysts are very promising for the ammonia SCR reaction. Especially, the activity at low and high temperatures was higher than the activity of commercial vanadia-based catalysts. From the studied catalysts, Fe-beta was the most potential one. The presence of NO₂ in the inlet flow enhanced significantly the catalytic activity of fresh and hydrothermally aged zeolite catalysts. This suggests that the oxidation of NO to NO₂ is probably the rate-determining step for the SCR reaction.     

O3R: Ontology-based mechanism for a human-centered environment targeted at the analysis of navigation patterns

Web Usage Mining (WUM) is the application of data mining techniques over Web server logs in order to extract navigation usage patterns. The analysis of mining patterns for assessing the knowledge they reveal is a critical phase in WUM. The main challenges are: (a) mining algorithms yield a huge number of patterns and (b) there is a significant semantic gap between URLs and events performed by users. In this paper, we describe the pattern analysis mechanisms integrated in O3R (Ontology-based Rules Retrieval and Rummaging), a human-centered environment for the analysis of navigation rules. O3R explores the synergy of mechanisms for retrieving and analyzing patterns. Filtering and clustering allow users to retrieve subsets of patterns with specific characteristics, in order to deal with the large volume of patterns. Rummaging mechanisms are targeted at assessing the meaning and relevance of pattern with regard to the domain, and it is particularly suitable for exploratory analysis. The distinctive feature of O3R is that is dynamically associates meaning to patterns using the concepts and relationships of a domain ontology, as a means of reducing the gap between syntactic URLs and semantic events performed by users. The paper describes the mechanisms in detail, and explores their synergic integration in the O3R prototype. It also reports two case studies that evaluate the use of O3R for the analysis of navigation patterns of a learning site.     

The effects of the number of links and navigation support on cognitive load and learning with hypertext: The mediating role of reading order

Problems in learning with hypertext systems have been claimed to be caused by high levels of disorientation and cognitive load. This was recognized by DeStefano and LeFevre [DeStefano, D., & LeFevre, J. -A., (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23(3), 1616–1641.] who predicted an increase of cognitive load and impairment of learning for hypertexts with a higher number of links per page. From a practical perspective, several navigation support techniques, such as providing link suggestions, have been proposed for guiding learners and reducing cognitive overload. In an experiment, we tested DeStefano and LeFevre’s predictions as well as the usefulness of link suggestions. Participants used different versions of a hypertext, either with 3-links or 8-links per page, presenting link suggestions or not. We tested their cognitive load and learning outcomes. Results showed that there was a benefit of using link suggestions for learning, but no effect of number of links on learning was found. Moreover, the effects of our manipulations on cognitive load were mediated by the reading order that participants selected. Implications for research and the design of navigation support systems are discussed.     

The complementary exponential geometric distribution: Model, properties, and a comparison with its counterpart

In this paper, we proposed a new two-parameter lifetime distribution with increasing failure rate, the complementary exponential geometric distribution, which is complementary to the exponential geometric model proposed by Adamidis and Loukas (1998). The new distribution arises on a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the maximum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its reliability and failure rate functions, moments, including the mean and variance, variation coefficient, and modal value. The parameter estimation is based on the usual maximum likelihood approach. We report the results of a misspecification simulation study performed in order to assess the extent of misspecification errors when testing the exponential geometric distribution against our complementary one in the presence of different sample size and censoring percentage. The methodology is illustrated on four real datasets; we also make a comparison between both modeling approaches.     

Groundwater Model Calibration by Meta-Heuristic Algorithms

Groundwater models are computer models that simulate or predict aquifer conditions by using input data sets and hydraulic parameters. Commonly, hydraulic parameters are extracted by calibration, using observed and simulated aquifer conditions. The accuracy of calibration affects other modeling processes, especially the hydraulic head simulation. Meta-heuristic algorithms are good candidates to determine optimal/near-optimal parameters in groundwater models. In this paper, two meta-heuristic algorithms: (1) particle swarm optimization (PSO) and (2) pattern search (PS) are applied and compared in the Ghaen aquifer, by considering the sum of the squared deviation (SSD) between observed and simulated hydraulic heads and the sum of the absolute value of deviation (SAD) between observed and simulated hydraulic heads as the objective functions. Results show that obtained values of the objective function are enhanced significantly by using the PS algorithm. Accordingly, PS improves (decreases) the SSD and SAD by 0.20 and 2.36 percent, respectively, compared to results reported by using the PSO algorithm. Results also indicate that the proposed PS optimization tool is effective in the calibration of aquifer parameters.     

Discussion of “Assessments of Impacts of Climate Change and Human Activities on Runoff with SWAT for the Huifa River Basin, Northeast China” by Aijing Zhang; Chi Zhang; Guobin Fu; Bende Wang; Zhenxin Bao; and Hongxing Zheng

Zhang et al. (Water Resour Manag doi:10.1007/s11269-012-0182-2, 2012) studied the impacts of climate change and human activities on the runoff for the Huifa River basin. They employed a soil and water assessment tool (SWAT), which was calibrated for the baseline period 1956–1964, and then used to reconstruct the natural runoff for the climate change period 1965–2000. Results showed that both climate change and human activities decrease the observed runoff. Climate change impacts on annual runoff were ?37.7, ?59.5, +36.9, and ?45.2 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively, compared with the baseline period 1956–1964. Human activities decreased runoff and caused a relatively larger magnitude impact than those of climate change after 1985. Human activities decreased the annual runoff by ?32.9, ?46.8, ?67.8, and ?54.9 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively. Human activities further decreased runoff in wet years due to regulation and storage of water projects.