Who Drops out? A Study of Secondary School Dropouts in Connecticut

The purpose of the study was to investigate the relationships between the dropout pattern and student characteristics such as gender, ethnicity and grade level among exited students from grade 7 to grade 12. The study included 57,709 students from grades 7-12 in the 2006-2007 school year in Connecticut. A logistic regression analysis was conducted to examine demographic factors related to student dropout pattern. This study provides empirical evidence of identifying secondary school students in Connecticut who were more likely to drop out. Identifying the groups of high risk students would help practitioners and policy makers to develop prevention programs or make interventions to reduce student attrition at the early stage, and thus, to close the achievement gap among these groups

Draft Genome Sequences of Propionibacterium acnes Type Strain ATCC6919 and Antibiotic-Resistant Strain HL411PA1.

Propionibacterium acnes is a major skin commensal and is associated with acne vulgaris, the most common skin disease. Here we report the draft genome sequences of two P. acnes strains, the type strain ATCC6919 and an antibiotic-resistant strain, HL411PA1

Optimising shape analysis to quantify volcanic ash morphology

AbstractAccurate measurements of volcanic ash morphology are critical to improving both our understanding of fragmentation processes and our ability to predict particle behaviour. In this study, we present new ways to choose and apply shape parameters relevant to volcanic ash characterisation. First, we compare shape measurements from different imaging techniques, including cross-sectional (2-D) and projected area images, and discuss their respective applications. We then focus on specific information that can be obtained from shape analysis of 2-D images. Using cluster analysis as an unbiased method to identify key controls on particle morphology, we find that four shape parameters – solidity, convexity, axial ratio, and form factor – can effectively account for the morphological variance within most ash samples. Importantly, these parameters are scaled to values between 0 and 1, and therefore contribute evenly to discrimination diagrams. In particular, co-variation in convexity and solidity can be used to distinguish different juvenile ash components based on characteristic bubble properties. By reducing observations of natural samples to simplified ash geometries, we quantify morphological changes associated with variations in the relative size and shape of bubbles and particles. Using this relationship, we assess the potential application of size-dependent shape analysis for inferring the underlying bubble size distribution, and thus the pre-fragmentation conditions. Finally, we show that particle shape analysis that includes the full range of available grain sizes can contribute not only measurements of particle size and shape, but also information on size-dependent densities

Coastal Waters

Coastal water, specifically coastal erosion, has been a growing problem due to human impact.https://digitalcommons.imsa.edu/unsdg_infographics/1009/thumbnail.jp

Does the way in which a firm interacts with its network partners influence its formulation of product innovation strategies?

Peer reviewedPostprin

Instance complexity of Boolean functions

In the area of query complexity of Boolean functions, the most widely studied cost measure of an algorithm is the worst-case number of queries made by it on an input. Motivated by the most natural cost measure studied in online algorithms, the competitive ratio, we consider a different cost measure for query algorithms for Boolean functions that captures the ratio of the cost of the algorithm and the cost of an optimal algorithm that knows the input in advance. The cost of an algorithm is its largest cost over all inputs. Grossman, Komargodski and Naor [ITCS'20] introduced this measure for Boolean functions, and dubbed it instance complexity. Grossman et al. showed, among other results, that monotone Boolean functions with instance complexity 1 are precisely those that depend on one or two variables. We complement the above-mentioned result of Grossman et al. by completely characterizing the instance complexity of symmetric Boolean functions. As a corollary we conclude that the only symmetric Boolean functions with instance complexity 1 are the Parity function and its complement. We also study the instance complexity of some graph properties like Connectivity and k-clique containment. In all the Boolean functions we study above, and those studied by Grossman et al., the instance complexity turns out to be the ratio of query complexity to minimum certificate complexity. It is a natural question to ask if this is the correct bound for all Boolean functions. We show a negative answer in a very strong sense, by analyzing the instance complexity of the Greater-Than and Odd-Max-Bit functions. We show that the above-mentioned ratio is linear in the input size for both of these functions, while we exhibit algorithms for which the instance complexity is a constant