California Polytechnic State University

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.

Computer systems cannot improve organizational performance if they aren't used. Unfortunately, resistance to end-user systems by managers and professionals is a widespread problem. To better predict, explain, and increase user acceptance, we need to better understand why people accept or reject computers. This research addresses the ability to predict peoples' computer acceptance from a measure of their intentions, and the ability to explain their intentions in terms of their attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables. In a longitudinal study of 107 users, intentions to use a specific system, measured after a one-hour introduction to the system, were correlated 0.35 with system use 14 weeks later. The intention-usage correlation was 0.63 at the end of this time period. Perceived usefulness strongly influenced peoples' intentions, explaining more than half of the variance in intentions at the end of 14 weeks. Perceived ease of use had a small but significant effect on intentions as well, although this effect subsided over time. Attitudes only partially mediated the effects of these beliefs on intentions. Subjective norms had no effect on intentions. These results suggest the possibility of simple but powerful models of the determinants of user acceptance, with practical value for evaluating systems and guiding managerial interventions aimed at reducing the problem of underutilized computer technology.

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.

Previous research indicates that perceived usefulness is a major determinant and predictor of intentions to use computers in the workplace. In contrast, the impact of enjoyment on usage intentions has not been examined. Two studies are reported concerning the relative effects of usefulness and enjoyment on intentions to use, and usage of, computers in the workplace. Usefulness had a strong effect on usage intentions in both Study 1, regarding word processing software (β=.68), and Study 2, regarding business graphics programs (β=.79). As hypothesized, enjoyment also had a significant effect on intentions in both studies, controlling for perceived usefulness (β=.16 and 0.15 for Studies 1 and 2, respectively). Study 1 found that intentions correlated 0.63 with system usage and that usefulness and enjoyment influenced usage behavior entirely indirectly through their effects on intentions. In both studies, a positive interaction between usefulness and enjoyment was observed. Together, usefulness and enjoyment explained 62% (Study 1) and 75% (Study 2) of the variance in usage intentions. Moreover, usefulness and enjoyment were found to mediate fully the effects on usage intentions of perceived output quality and perceived ease of use. As hypothesized, a measure of task importance moderated the effects of ease of use and output quality on usefulness but not on enjoyment. Several implications are drawn for how to design computer programs to be both more useful and more enjoyable in order to increase their acceptability among potential users.

Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.

It is increasingly necessary for researchers in all fields to write computer code, and in order to reproduce research results, it is important that this code is published. We present Jupyter notebooks, a document format for publishing code, results and explanations in a form that is both readable and executable. We discuss various tools and use cases for notebook documents.

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

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

This paper develops and tests a conceptual model of the effects of store name, brand names and price discounts on consumers' evaluations (store image, brand quality perceptions, internal reference prices, and value perceptions) and purchase intentions. The moderating effects of consumer knowledge and prior ownership on the proposed relationships in the model are also explored. A store's perceived image is influenced by the store name and the quality of merchandise it carries. Results also indicate that internal reference price is influenced by price discounts, brand name, and a brand's perceived quality. The influence of price discounts on a brand's perceived quality was minimal. Price discounts, internal reference price, and brand's perceived quality exerted significant influence on perceived value. Perceived value and store image, in turn, positively influenced purchased intentions. High knowledge respondents are more influenced by brand name, while low knowledge respondents are more influenced by price discounts. Low knowledge consumers are also swayed by store name and brand name.

Abstract Developed herein is an improved pushover analysis procedure based on structural dynamics theory, which retains the conceptual simplicity and computational attractiveness of current procedures with invariant force distribution. In this modal pushover analysis (MPA), the seismic demand due to individual terms in the modal expansion of the effective earthquake forces is determined by a pushover analysis using the inertia force distribution for each mode. Combining these ‘modal’ demands due to the first two or three terms of the expansion provides an estimate of the total seismic demand on inelastic systems. When applied to elastic systems, the MPA procedure is shown to be equivalent to standard response spectrum analysis (RSA). When the peak inelastic response of a 9‐storey steel building determined by the approximate MPA procedure is compared with rigorous non‐linear response history analysis, it is demonstrated that MPA estimates the response of buildings responding well into the inelastic range to a similar degree of accuracy as RSA in estimating peak response of elastic systems. Thus, the MPA procedure is accurate enough for practical application in building evaluation and design. Copyright © 2001 John Wiley & Sons, Ltd.

The authors expand and integrate prior price-perceived value models within the context of price comparison advertising. More specifically, the conceptual model explicates the effects of advertised selling and reference prices on buyers’ internal reference prices, perceptions of quality, acquisition value, transaction value, and purchase and search intentions. Two experimental studies test the conceptual model. The results across these two studies, both individually and combined, support the hypothesis that buyers’ internal reference prices are influenced by both advertised selling and reference prices as well as the buyers’ perception of the product's quality. The authors also find that the effect of advertised selling price on buyers’ acquisition value was mediated by their perceptions of transaction value. In addition, the effects of perceived transaction value on buyers’ behavioral intentions were mediated by their acquisition value perceptions. The authors suggest directions for further research and implications for managers.

This report of the American Dairy Science Association Committee on the Nomenclature, Classification, and Methodology of Milk Proteins reviews changes in the nomenclature of milk proteins necessitated by recent advances of our knowledge of milk proteins. Identification of major caseins and whey proteins continues to be based upon their primary structures. Nomenclature of the immunoglobulins consistent with new international standards has been developed, and all bovine immunoglobulins have been characterized at the molecular level. Other significant findings related to nomenclature and protein methodology are elucidation of several new genetic variants of the major milk proteins, establishment by sequencing techniques and sequence alignment of the bovine caseins and whey proteins as the reference point for the nomenclature of all homologous milk proteins, completion of crystallographic studies for major whey proteins, and advances in the study of lactoferrin, allowing it to be added to the list of fully characterized milk proteins.

Using segment information from Compustat, we find that the investment by a segment of a diversified firm depends on the cash flow of the firm's other segments, but significantly less than it depends on its own cash flow. The investment by segments of highly diversified firms is less sensitive to their cash flow than the investment of comparable single-segment firms. The sensitivity of a segment's investment to the cash flow of other segments does not depend on whether its investment opportunities are better than those of the firm's other segments.

Dhruv Grewal, Kent B. Monroe, R. Krishnan, The Effects of Price-Comparison Advertising on Buyers' Perceptions of Acquisition Value, Transaction Value, and Behavioral Intentions, Journal of Marketing, Vol. 62, No. 2 (Apr., 1998), pp. 46-59

Beliefs, attitudes, and intentions are important factors in the adoption of computer technologies. While contemporary representations have focused on explaining the act of using computers, the role of learning to use the computer needs to be better understood within the overall adoption process. Inadequate learning can curtail the adoption and use of a potentially productive system. We introduce a new theoretical model, the theory of trying, in which computer learning is conceptualized as a goal determined by three attitude components: attitude toward success, attitude toward failure, and attitude toward the process of goal pursuit. Intentions to try and actual trying are the theoretical mechanisms linking these goal-directed attitudes to goal attainment. An empirical study is conducted to ascertain the construct validity and utility of the new theory within the context of the adoption of a word processing package. Specifically, we examine convergent validity, internal consistency reliability, stability, discriminant validity, criterion related validity, predictive validity, and nomological validity in a longitudinal field study of 107 users of the program. The new theory is compared to two models: the theory of reasoned action from the field of social psychology and the technology acceptance model, recently introduced in the management literature. Overall, the findings stress the importance of scrutinizing the goals of decision makers and their psychological reactions to these goals in the prediction of the adoption of computers.

We report the first measurement of charged particle elliptic flow in Pb-Pb collisions at sqrt[S(NN)] =2.76 TeV with the ALICE detector at the CERN Large Hadron Collider. The measurement is performed in the central pseudorapidity region (|η|<0.8) and transverse momentum range 0.2<p t<5.0 GeV/c. The elliptic flow signal v₂, measured using the 4-particle correlation method, averaged over transverse momentum and pseudorapidity is 0.087 ± 0.002(stat) ± 0.003(syst) in the 40%-50% centrality class. The differential elliptic flow v₂ p t reaches a maximum of 0.2 near p t =3 GeV/c. Compared to RHIC Au-Au collisions at sqrt[S(NN)] 200 GeV, the elliptic flow increases by about 30%. Some hydrodynamic model predictions which include viscous corrections are in agreement with the observed increase.

We present an updated and revised analysis of the relationship between the Hß broad-line region (BLR) radius and the luminosity of the active galactic nucleus (AGN). Specifically, we have carried out two-dimensional surface brightness decompositions of the host galaxies of nine new AGNs imaged with the Hubble Space Telescope Wide Field Camera 3. The surface brightness decompositions allow us to create "AGN-free" images of the galaxies, from which we measure the starlight contribution to the optical luminosity measured through the ground-based spectroscopic aperture. We also incorporate 20 new reverberation-mapping measurements of the Hß time lag, which is assumed to yield the average Hß BLR radius. The final sample includes 41 AGNs covering four orders of magnitude in luminosity. The additions and updates incorporated here primarily affect the low-luminosity end of the R BLR-L relationship. The best fit to the relationship using a Bayesian analysis finds a slope of , consistent with previous work and with simple photoionization arguments. Only two AGNs appear to be outliers from the relationship, but both of them have monitoring light curves that raise doubt regarding the accuracy of their reported time lags. The scatter around the relationship is found to be 0.19 ± 0.02 dex, but would be decreased to 0.13 dex by the removal of these two suspect measurements. A large fraction of the remaining scatter in the relationship is likely due to the inaccurate distances to the AGN host galaxies. Our results help support the possibility that the R-L relationship could potentially be used to turn the BLRs of AGNs into standardizable candles. This would allow the cosmological expansion of the universe to be probed by a separate population of objects, and over a larger range of redshifts.

Bioluminescence spans all oceanic dimensions and has evolved many times--from bacteria to fish--to powerfully influence behavioral and ecosystem dynamics. New methods and technology have brought great advances in understanding of the molecular basis of bioluminescence, its physiological control, and its significance in marine communities. Novel tools derived from understanding the chemistry of natural light-producing molecules have led to countless valuable applications, culminating recently in a related Nobel Prize. Marine organisms utilize bioluminescence for vital functions ranging from defense to reproduction. To understand these interactions and the distributions of luminous organisms, new instruments and platforms allow observations on individual to oceanographic scales. This review explores recent advances, including the chemical and molecular, phylogenetic and functional, community and oceanographic aspects of bioluminescence.

The coronavirus-disease 2019 (COVID-19) was announced as a global pandemic by the World Health Organization. Challenges arise concerning how to optimally support the immune system in the general population, especially under self-confinement. An optimal immune response depends on an adequate diet and nutrition in order to keep infection at bay. For example, sufficient protein intake is crucial for optimal antibody production. Low micronutrient status, such as of vitamin A or zinc, has been associated with increased infection risk. Frequently, poor nutrient status is associated with inflammation and oxidative stress, which in turn can impact the immune system. Dietary constituents with especially high anti-inflammatory and antioxidant capacity include vitamin C, vitamin E, and phytochemicals such as carotenoids and polyphenols. Several of these can interact with transcription factors such as NF-kB and Nrf-2, related to anti-inflammatory and antioxidant effects, respectively. Vitamin D in particular may perturb viral cellular infection via interacting with cell entry receptors (angiotensin converting enzyme 2), ACE2. Dietary fiber, fermented by the gut microbiota into short-chain fatty acids, has also been shown to produce anti-inflammatory effects. In this review, we highlight the importance of an optimal status of relevant nutrients to effectively reduce inflammation and oxidative stress, thereby strengthening the immune system during the COVID-19 crisis.

I. Introduction, 221.—II. The sample of innovations, 222.—III. Estimation of social benefits: product innovations used by firms, 222.—IV. Parallel innovative efforts, time horizon, and rates of return, 226.—V. Product innovations used by households, 229.—VI. Process innovations, 231.—VII. Social and private rates of return, 233.—VIII. Factors associated with the gap between social and private rates of return, 235.—IX. Unemployment, repercussions on other markets, and future changes in technology, 238.—X. Conclusion, 239.