A key policy question is whether the benefits of additional medical expenditures exceed their costs. We propose a new approach for estimating marginal returns to medical spending based on variation in medical inputs generated by diagnostic thresholds. Specifically, we combine regression discontinuity estimates that compare health outcomes and medical treatment provision for newborns on either s...

BACKGROUND Betaine, beetroot juice, and supplemental nitrate have recently been reported to improve certain aspects of exercise performance, which may be mechanistically linked to increased nitric oxide. The purpose of the present study was to investigate the effect of betaine supplementation on plasma nitrate/nitrite, a surrogate marker or nitric oxide, in exercise-trained men. METHODS We us...

Assigning putative functions to novel proteins and the discovery of sequence correlates of protein function are important challenges in bioinformatics. In this paper, we explore several machine learning approaches to data-driven construction of classifiers for assigning protein sequences to appropriate Gene Ontology (GO) function families using a class conditional probabilistic representation o...

In this paper, we discuss the results of the IUCL system in the NLI Shared Task 2017. For our system, we explore a variety of phonetic algorithms to generate features for Native Language Identification. These features are contrasted with one of the most successful type of features in NLI, character n-grams. We find that although phonetic features do not perform as well as character n-grams alon...

In the present study, the authors measured vascular functioning of the forearm of 25 male subjects via ultrasound (Doppler imaging) at time zero and after 4 hours after consuming a high-fat meal. Using a single-blinded crossover design, the subjects either consumed a placebo oil (no DHA/EPA present) or fish oil (providing a total amount of DHA/EPA amounting to 5.4 grams-3.24 grams DHA plus 2.16...

In this paper, an extension of n-grams is proposed. In this extension, the memory of the model (n) is not fixed a priori. Instead, first, large memories are accepted and afterwards, merging criteria are applied to reduce complexity and to ensure reliable estimations. The results show how the perplexity obtained with x-grams is smaller than that of n-grams. Furthermore, the complexity is smaller...

The n-gram analysis technique breaks up a text document into several n-character long unique grams, and produces a vector whose components are the counts of these grams. A typical corpus contains hundreds of thousands of such grams. Wavelet compression reduces the dimension of the n-gram vectors, and speeds up document query operations. Document vectors with their dimensions reduced to four com...

The three ICSI systems involved in the evaluations are the keyword HMM supervector system [1], the GMM supervector system, and the keyword phone lattice N-grams system [2], which we enhanced by including prosodic N-grams. Descriptions of the keyword HMM supervector and keyword phone lattice Ngrams + prosodic N-grams systems will be discussed in sections 3 and 4. A description of the GMM superve...

We presented our system for PAN 2016 Author Clustering task. Our software used simple character n-grams to represent the document collection. We then ran K-Means clustering optimized using the Silhouette Coefficient. Our system yields competitive results and required only a short runtime. Character n-grams can capture a wide range of information, making them effective for authorship attribution...

We have analyzed the SPEX algorithm by Bernstein and Zobel [1] for detecting co-derivative documents using duplicate n-grams. Though we totally agree with the claim that not using unique n-grams can greatly increase efficiency and scalability of the process of detecting co-derivative documents, we have found serious bottlenecks in the way SPEX finds the duplicate n-grams. We propose a solution ...