Amherst College

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.org.

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Simulated gastro-intestinal digestion is widely employed in many fields of food and nutritional sciences, as conducting human trials are often costly, resource intensive, and ethically disputable. As a consequence, in vitro alternatives that determine endpoints such as the bioaccessibility of nutrients and non-nutrients or the digestibility of macronutrients (e.g. lipids, proteins and carbohydrates) are used for screening and building new hypotheses. Various digestion models have been proposed, often impeding the possibility to compare results across research teams. For example, a large variety of enzymes from different sources such as of porcine, rabbit or human origin have been used, differing in their activity and characterization. Differences in pH, mineral type, ionic strength and digestion time, which alter enzyme activity and other phenomena, may also considerably alter results. Other parameters such as the presence of phospholipids, individual enzymes such as gastric lipase and digestive emulsifiers vs. their mixtures (e.g. pancreatin and bile salts), and the ratio of food bolus to digestive fluids, have also been discussed at length. In the present consensus paper, within the COST Infogest network, we propose a general standardised and practical static digestion method based on physiologically relevant conditions that can be applied for various endpoints, which may be amended to accommodate further specific requirements. A frameset of parameters including the oral, gastric and small intestinal digestion are outlined and their relevance discussed in relation to available in vivo data and enzymes. This consensus paper will give a detailed protocol and a line-by-line, guidance, recommendations and justifications but also limitation of the proposed model. This harmonised static, in vitro digestion method for food should aid the production of more comparable data in the future.

This paper disentangles the impact of schools and teachers in influencing achievement with special attention given to the potential problems of omitted or mismeasured variables and of student and school selection. Unique matched panel data from the UTD Texas Schools Project permit the identification of teacher quality based on student performance along with the impact of specific, measured components of teachers and schools. Semiparametric lower bound estimates of the variance in teacher quality based entirely on within-school heterogeneity indicate that teachers have powerful effects on reading and mathematics achievement, though little of the variation in teacher quality is explained by observable characteristics such as education or experience. The results suggest that the effects of a costly ten student reduction in class size are smaller than the benefit of moving one standard deviation up the teacher quality distribution, highlighting the importance of teacher effectiveness in the determination of school quality.

In today's world, there is no shortage of information. However, for a specific information need, only a small subset of all of the available information will be useful. The field of information retrieval (IR) is the study of methods to provide users with that small subset of information relevant to their needs and to do so in a timely fashion. Information sources can take many forms, but this thesis will focus on text based information systems and investigate problems germane to the retrieval of written natural language documents. Central to these problems is the notion of "topic." In other words, what are documents about? However, topics depend on the semantics of documents and retrieval systems are not endowed with knowledge of the semantics of natural language. The approach taken in this thesis will be to make use of probabilistic language models to investigate text based information retrieval and related problems. One such problem is the prediction of topic shifts in text, the topic segmentation problem. It will be shown that probabilistic methods can be used to predict topic changes in the context of the task of new event detection. Two complementary sets of features are studied individually and then combined into a single language model. The language modeling approach allows this problem to be approached in a principled way without complex semantic modeling. Next, the problem of document retrieval in response to a user query will be investigated. Models of document indexing and document retrieval have been extensively studied over the past three decades. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. Much of the reason for this is that the indexing component requires inferences as to the semantics of documents. Instead, an approach to retrieval based on probabilistic language modeling will be presented. Models are estimated for each document individually. The approach to modeling is non-parametric and integrates the entire retrieval process into a single model. One advantage of this approach is that collection statistics, which are used heuristically for the assignment of concept probabilities in other probabilistic models, are used directly in the estimation of language model probabilities in this approach. The language modeling approach has been implemented and tested empirically and performs very well on standard test collections and query sets. In order to improve retrieval effectiveness, IR systems use additional techniques such as relevance feedback, unsupervised query expansion and structured queries. These and other techniques are discussed in terms of the language modeling approach and empirical results are given for several of the techniques developed. These results provide further proof of concept for the use of language models for retrieval tasks.

Abstract An algorithm is proposed for solving the stereoscopic matching problem. The algorithm consists of five steps: (1) Each image is filtered at different orientations with bar masks of four sizes that increase with eccentricity; the equivalent filters are one or two octaves wide. (2) Zero-crossings in the filtered images, which roughly correspond to edges, are localized. Positions of the ends of lines and edges are also found. (3) For each mask orientation and size, matching takes place between pairs of zero-crossings or terminations of the same sign in the two images, for a range of dis­parities up to about the width of the mask’s central region. (4) Wide masks can control vergence movements, thus causing small masks to come into correspondence. (5) When a correspondence is achieved, it is stored in a dynamic buffer, called the 2½-D sketch. It is shown that this proposal provides a theoretical framework for most existing psychophysical and neurophysiological data about stereopsis. Several critical experimental predictions are also made, for instance about the size of Panum’s area under various conditions. The results of such experiments would tell us whether, for example, co-operativity is necessary for the matching process.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Journal Article The Logic of Collective Action: Public Goods and the Theory of Groups, by Mancur Olson Get access The Logic of Collective Action: Public Goods and the Theory of Groups by Mancur OlsonCambridge, Mass., Harvard University Press, 1965.—x, 176 pp. $4.50. Earl Latham Earl Latham Amherst College Search for other works by this author on: Oxford Academic Google Scholar Political Science Quarterly, Volume 82, Issue 1, March 1967, Pages 145–148, https://doi.org/10.2307/2147334 Published: 15 March 1967

In this and two companion papers, we report on an extended empirical study of the simulated annealing approach to combinatorial optimization proposed by S. Kirkpatrick et al. That study investigated how best to adapt simulated annealing to particular problems and compared its performance to that of more traditional algorithms. This paper (Part I) discusses annealing and our parameterized generic implementation of it, describes how we adapted this generic algorithm to the graph partitioning problem, and reports how well it compared to standard algorithms like the Kernighan-Lin algorithm. (For sparse random graphs, it tended to outperform Kernighan-Lin as the number of vertices become large, even when its much greater running time was taken into account. It did not perform nearly so well, however, on graphs generated with a built-in geometric structure.) We also discuss how we went about optimizing our implementation, and describe the effects of changing the various annealing parameters or varying the basic annealing algorithm itself.

We extensively compare, qualitatively and quantitatively, 41 state-of-the-art models (29 salient object detection, 10 fixation prediction, 1 objectness, and 1 baseline) over seven challenging data sets for the purpose of benchmarking salient object detection and segmentation methods. From the results obtained so far, our evaluation shows a consistent rapid progress over the last few years in terms of both accuracy and running time. The top contenders in this benchmark significantly outperform the models identified as the best in the previous benchmark conducted three years ago. We find that the models designed specifically for salient object detection generally work better than models in closely related areas, which in turn provides a precise definition and suggests an appropriate treatment of this problem that distinguishes it from other problems. In particular, we analyze the influences of center bias and scene complexity in model performance, which, along with the hard cases for the state-of-the-art models, provide useful hints toward constructing more challenging large-scale data sets and better saliency models. Finally, we propose probable solutions for tackling several open problems, such as evaluation scores and data set bias, which also suggest future research directions in the rapidly growing field of salient object detection.

I. OVERVIEW. 1. Introduction. 2. Peer Instruction. 3. Motivating the Students. 4. A Step-by-Step Guide to Preparing for a Peer Instruction Lecture. 5. Sample Lecture. 6. Epilogue. II. RESOURCES. 7. Mechanics Baseline Test. 8. Force Concept Inventory. 9. Questionnaire Results. 10. Reading Quizzes. 11. Concept Tests. 12. Conceptual Exam Questions. Appendix: Disk Instructions. Index.

A fundamental task of language acquisition is to extract abstract algebraic rules. Three experiments show that 7-month-old infants attend longer to sentences with unfamiliar structures than to sentences with familiar structures. The design of the artificial language task used in these experiments ensured that this discrimination could not be performed by counting, by a system that is sensitive only to transitional probabilities, or by a popular class of simple neural network models. Instead, these results suggest that infants can represent, extract, and generalize abstract algebraic rules.

Abstract Empirical analysis of peer effects on student achievement has been open to question because of the difficulties of separating peer effects from other confounding influences. While most econometric attention has been directed at issues of simultaneous determination of peer interactions, we argue that issues of omitted and mismeasured variables are likely to be more important. We control for the most important determinants of achievement that will confound peer estimates by removing student and school‐by‐grade fixed effects in addition to observable family and school characteristics. The analysis also addresses the reciprocal nature of peer interactions and the interpretation of estimates based upon models using past achievement as the measure of peer group quality. The results indicate that peer achievement has a positive effect on achievement growth. Moreover, students throughout the school test score distribution appear to benefit from higher achieving schoolmates. On the other hand, the variance in achievement appears to have no systematic effect. Copyright © 2003 John Wiley & Sons, Ltd.

The dramatic increase in antimicrobial resistance for pathogenic bacteria constitutes a key threat to human health. The Centers for Disease Control and Prevention has recently stated that the world is on the verge of entering the "post-antibiotic era", one where more people will die from bacterial infections than from cancer. Recently, nanoparticles (NPs) have emerged as new tools that can be used to combat deadly bacterial infections. Nanoparticle-based strategies can overcome the barriers faced by traditional antimicrobials, including antibiotic resistance. In this tutorial review, we have highlighted multiple nanoparticle-based approaches to eliminate bacterial infections, providing crucial insight into the design of elements that play critical roles in creating antimicrobial nanotherapeutics. In particular, we have focused on the pivotal role played by NP-surface functionality in designing nanomaterials as self-therapeutic agents and delivery vehicles for antimicrobial cargo.

Fast pyrolysis of lignocellulosic biomass produces a renewable liquid fuel called pyrolysis oil that is the cheapest liquid fuel produced from biomass today. Here we show that pyrolysis oils can be converted into industrial commodity chemical feedstocks using an integrated catalytic approach that combines hydroprocessing with zeolite catalysis. The hydroprocessing increases the intrinsic hydrogen content of the pyrolysis oil, producing polyols and alcohols. The zeolite catalyst then converts these hydrogenated products into light olefins and aromatic hydrocarbons in a yield as much as three times higher than that produced with the pure pyrolysis oil. The yield of aromatic hydrocarbons and light olefins from the biomass conversion over zeolite is proportional to the intrinsic amount of hydrogen added to the biomass feedstock during hydroprocessing. The total product yield can be adjusted depending on market values of the chemical feedstocks and the relative prices of the hydrogen and biomass.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTSelf-Assembling CapsulesM. Morgan Conn and Julius RebekView Author Information Department of Chemistry, Amherst College, Amherst, Massachusetts 01002-5000, and Skaggs Institute for Chemical Biology and the Department of Chemistry, Scripps Research Institute, 10550 North Torrey Pines Rd., La Jolla, California 92037 Cite this: Chem. Rev. 1997, 97, 5, 1647–1668Publication Date (Web):August 5, 1997Publication History Received14 November 1996Revised1 April 1997Published online5 August 1997Published inissue 1 August 1997https://pubs.acs.org/doi/10.1021/cr9603800https://doi.org/10.1021/cr9603800research-articleACS PublicationsCopyright © 1997 American Chemical SocietyRequest reuse permissionsArticle Views7683Altmetric-Citations961LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Ions,Molecules,Noncovalent interactions,Oligomers,Receptors Get e-Alerts

application of polygenic scores in clinical practice.

Previous work on the solubility of oxygen in freshwater has been extended to seawater. Measurements of the Henry coefficient in the ranges 0° < t < 45° C and 0< S < 50 fit the Setschenow relationship for the variation with salinity. The temperature dependence of the Setschenow coefficient for oxygen is found to be K = 0.0225034 ‒ 13.6083/ T + 2,565.68/ T 2 . The equation for the Henry coefficient as a function of temperature and salinity is used to calculate values for unit standard atmospheric concentrations (USAC) in freshwater and seawater in equilibrium with air at a total pressure of 1 atmosphere. It is estimated that the possible error in the new USAC values is no greater than ±0.1% and probably less. Tables and equations are presented for obtaining accurate USAC values in the ranges 0° < t < 40°C and 0 < S < 40. Simple procedures are given for calculating standard atmospheric concentrations at pressures different from 1 atm. The presence of sea salt has a negligible effect on the fractionation of the oxygen isotopes during solution.

Introduction The quintic threefold Toric geometry Mirror symmetry constructions Hodge theory and Yukawa couplings Moduli spaces Gromov-Witten invariants Quantum cohomology Localization Quantum differential equations The mirror theorem Conclusion Singular varieties Physical theories Bibliography Index.