University of Waterloo

About: University of Waterloo is a education organization based out in Waterloo, Ontario, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 36093 authors who have published 93906 publications receiving 2948139 citations. The organization is also known as: UW & uwaterloo.

Calibration of the Total Carbon Column Observing Network using aircraft profile data

Abstract: The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column av- erage dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with suffi- cient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Orga- nization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale in- strumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total col- umn data within error.

Sonication of proteins causes formation of aggregates that resemble amyloid.

Abstract: Despite the widespread use of sonication in medicine, industry, and research, the effects of sonication on proteins remain poorly characterized. We report that sonication of a range of structurally diverse proteins results in the formation of aggregates that have similarities to amyloid aggregates. The formation of amyloid is associated with, and has been implicated in, causing of a wide range of protein conformational disorders including Alzheimer's disease, Huntington's disease, Parkinson's disease, and prion diseases. The aggregates cause large enhancements in fluorescence of the dye thioflavin T, exhibit green-gold birefringence upon binding the dye Congo red, and cause a red-shift in the absorbance spectrum of Congo red. In addition, circular dichroism reveals that sonication-induced aggregates have high beta-content, and proteins with significant native alpha-helical structure show increased beta-structure in the aggregates. Ultrastructural analysis by electron microscopy reveals a range of morphologies for the sonication-induced aggregates, including fibrils with diameters of 5-20 nm. The addition of preformed aggregates to unsonicated protein solutions results in accelerated and enhanced formation of additional aggregates upon heating. The dye-binding and structural characteristics, as well as the ability of the sonication-induced aggregates to seed the formation of new aggregates are all similar to the properties of amyloid. These results have important implications for the use of sonication in food, biotechnological and medical applications, and for research on protein aggregation and conformational disorders.

Riemann's Hypothesis and tests for primality

Abstract: The purpose of this paper is to present new upper bounds on the complexity of algorithms for testing the primality of a number. The first upper bound is 0(n1/7); it improves the previously best known bound of 0(n1/4) due to Pollard [11]. The second upper bound is dependent on the Extended Riemann Hypothesis (ERH): assuming ERH, we produce an algorithm which tests primality and runs in time 0((log n)4) steps. Thus we show that primality is testable in time a polynomial in the length of the binary representation of a number. Finally, we give a partial solution to the relationship between the complexity of computing the prime factorization of a number, computing the Euler phi function, and computing other related functions.

The use of machine learning algorithms in recommender systems: A systematic review

Abstract: Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of artificial intelligence. However, choosing a suitable machine learning algorithm for a recommender system is difficult because of the number of algorithms described in the literature. Researchers and practitioners developing recommender systems are left with little information about the current approaches in algorithm usage. Moreover, the development of recommender systems using machine learning algorithms often faces problems and raises questions that must be resolved. This paper presents a systematic review of the literature that analyzes the use of machine learning algorithms in recommender systems and identifies new research opportunities. The goals of this study are to (i) identify trends in the use or research of machine learning algorithms in recommender systems; (ii) identify open questions in the use or research of machine learning algorithms; and (iii) assist new researchers to position new research activity in this domain appropriately. The results of this study identify existing classes of recommender systems, characterize adopted machine learning approaches, discuss the use of big data technologies, identify types of machine learning algorithms and their application domains, and analyzes both main and alternative performance metrics.

Being alone, playing alone and acting alone: Distinguishing among reticence, and passive- and active-solitude in young children.

Abstract: 3 forms of solitude were studied in young children--reticence (onlooker and unoccupied behavior), solitary-passive behavior (solitary-constructive and -exploratory play), and solitary-active behavior (solitary-functional and -dramatic play). 48 4-year-old children grouped in quartets of same-sex unfamiliar peers were observed in several situations. Mothers completed the Colorado Temperament Inventory. Results indicated that (1) solitary-passive, solitary-active, and reticent behaviors were nonsignificantly intercorrelated; (2) reticence was stable and associated with the demonstration of anxiety and hovering near others, whereas solitary-passive and solitary-active play were stable yet unrelated to anxiety and hovering; (3) reticence during free play was generally associated with poor performance and displays of wariness in several other social situations, while solitary-passive and -active play were not; (4) reticence was associated with maternal ratings of child shyness, while solitary-active behavior was associated with maternal ratings of impulsivity. Results are discussed in terms of the underlying mechanisms associated with reticence and passive and active withdrawal.