Three-phase slug flow in microchips can provide beneficial reaction conditions for enzyme liquid-liquid reactions

Here, we introduce a solution to low stability of a two-phase slug flow with a chemical reaction occurring at the phase interface in a microfluidic reactor where substantial merging of individual reacting slugs results in the loss of uniformity of the flow. We create a three-phase slug flow by introducing a third fluid phase into the originally two-phase liquid-liquid slug flow, which generates small two-phase liquid slugs separated by gas phase. Introduction of the third phase into our system efficiently prevents merging of slugs and provides beneficial reaction conditions, such as uniform flow pattern along the whole reaction capillary, interfacial area with good reproducibility, and intensive water-oil interface renewal. We tested the three-phase flow on an enzyme hydrolysis of soybean oil and compared the reaction conversion with those from unstable two-phase slug flows. We experimentally confirmed that the three-phase slug flow arrangement provides conversions and pressure drops comparable or even better with two-phase liquid-liquid arrangements.     

Multiple solution methods and multiple outcomes—is it a task for kindergarten children?

Engaging students with multiple solution problems is considered good practice. Solutions to problems consist of the outcomes of the problem as well as the methods employed to reach these outcomes. In this study we analyze the results obtained from two groups of kindergarten children who engaged in one task, the Create an Equal Number Task. This task had five possible outcomes and five different methods which may be employed in reaching these outcomes. Children, whose teachers had attended the program Starting Right: Mathematics in Kindergartens, found more outcomes and employed more methods than children whose teachers did not attend this program. Results suggest that the habit of mind of searching for more than one outcome and employing more than one method may be promoted in kindergarten.     

Large-scale similarity data management with distributed Metric Index

Metric space is a universal and versatile model of similarity that can be applied in various areas of non-text information retrieval. However, a general, efficient and scalable solution for metric data management is still a resisting research challenge. In this work, we try to make an important step towards such management system that would be able to scale to data collections of billions of objects. We propose a distributed index structure for similarity data management called the Metric Index (M-Index) which can answer queries in precise and approximate manner. This technique can take advantage of any distributed hash table that supports interval queries and utilize it as an underlying index. We have performed numerous experiments to test various settings of the M-Index structure and we have proved its usability by developing a full-featured publicly-available Web application.     

The ability-track glass ceiling of Israeli schooling: lessons from a comparative analysis of Israeli and Australian PISA 2012 data

Israeli students ranked in the bottom third of the countries surveyed by PISA 2012 in mathematical literacy, while the gap between the highest and lowest scores was the second largest in the OECD. This paper explores which variables led to disparities in mathematical literacy between different socioeconomic levels and between Israeli Arabs and Jews as well as in comparison with Australian students. Different instructional approaches that are known in the literature to have a positive impact on students’ achievement are not observed in the relationship between teachers and students in Israel. In Israel, schools contribute to the perpetuation of socioeconomically driven educational inequality by using tracks that are characterised by different teaching pedagogies and different content, with little or no upward mobility between tracks, leading to structural exclusion. By comparison, in Australia, ability tracking is less rigid and mathematical literacy far higher than in Israel. The policy implication is that either teachers must work differently in a track-based system to overcome the process of exclusion dictated by the structure itself or the system must reduce the use of tracking.     

History

EDISON'S ELECTRIC LIGHT: BIOGRAPHY OF AN INVENTION by Robert Friedel, et al. (New Brunswick, NJ: Rutgers University Press, 1986—$27.95 until July 1st, then $35)

ENGINEERS & ELECTRONS: A CENTURY OF ELECTRICAL PROGRESS by John D. Ryder and Donald G. Fink (IEEE Press, 345 East 47th St., New York 10017—price not given)

THE MAKING OF A PROFESSION: A CENTURY OF ELECTRICAL ENGINEERING IN AMERICA by A. Michal McMahon (New York: IEEE Press, see address to left, 1984—price not given)

IBM'S EARLY COMPUTERS by Charles J. Bashe, et al (Cambridge, MA: MIT Press, 1986—$27.50)

THE POWER OF THE PRESS: THE BIRTH OF AMERICAN POLITICAL REPORTING by Thomas C. Leonard (New York: Oxford, 1986—$22.50)     

Deductive reasoning: in the eye of the beholder

This study examines ways of approaching deductive reasoning of people involved in mathematics education and/or logic. The data source includes 21 individual semi-structured interviews. The data analysis reveals two different approaches. One approach refers to deductive reasoning as a systematic step-by-step manner for solving problems, both in mathematics and in other domains. The other approach emphasizes formal logic as the essence of the deductive inference, distinguishing between mathematics and other domains in the usability of deductive reasoning. The findings are interpreted in light of theory and practice.

Discourse-aware rumour stance classification in social media using sequential classifiers

Rumour stance classification, defined as classifying the stance of specific social media posts into one of supporting, denying, querying or commenting on an earlier post, is becoming of increasing interest to researchers. While most previous work has focused on using individual tweets as classifier inputs, here we report on the performance of sequential classifiers that exploit the discourse features inherent in social media interactions or ‘conversational threads’. Testing the effectiveness of four sequential classifiers – Hawkes Processes, Linear-Chain Conditional Random Fields (Linear CRF), Tree-Structured Conditional Random Fields (Tree CRF) and Long Short Term Memory networks (LSTM) – on eight datasets associated with breaking news stories, and looking at different types of local and contextual features, our work sheds new light on the development of accurate stance classifiers. We show that sequential classifiers that exploit the use of discourse properties in social media conversations while using only local features, outperform non-sequential classifiers. Furthermore, we show that LSTM using a reduced set of features can outperform the other sequential classifiers; this performance is consistent across datasets and across types of stances. To conclude, our work also analyses the different features under study, identifying those that best help characterise and distinguish between stances, such as supporting tweets being more likely to be accompanied by evidence than denying tweets. We also set forth a number of directions for future research.     

A note on a method for summarizing unclassified FTE positions and unclassified dollars

A methodology is presented in this paper for summarizing university tenure commitments in terms of faculty positions and unclassified dollars by department or school.