University of Georgia

Abstract Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.

Abstract Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.

Plastics have outgrown most man-made materials and have long been under environmental scrutiny. However, robust global information, particularly about their end-of-life fate, is lacking. By identifying and synthesizing dispersed data on production, use, and end-of-life management of polymer resins, synthetic fibers, and additives, we present the first global analysis of all mass-produced plastics ever manufactured. We estimate that 8300 million metric tons (Mt) as of virgin plastics have been produced to date. As of 2015, approximately 6300 Mt of plastic waste had been generated, around 9% of which had been recycled, 12% was incinerated, and 79% was accumulated in landfills or the natural environment. If current production and waste management trends continue, roughly 12,000 Mt of plastic waste will be in landfills or in the natural environment by 2050.

Plastic debris in the marine environment is widely documented, but the quantity of plastic entering the ocean from waste generated on land is unknown. By linking worldwide data on solid waste, population density, and economic status, we estimated the mass of land-based plastic waste entering the ocean. We calculate that 275 million metric tons (MT) of plastic waste was generated in 192 coastal countries in 2010, with 4.8 to 12.7 million MT entering the ocean. Population size and the quality of waste management systems largely determine which countries contribute the greatest mass of uncaptured waste available to become plastic marine debris. Without waste management infrastructure improvements, the cumulative quantity of plastic waste available to enter the ocean from land is predicted to increase by an order of magnitude by 2025.

We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.

MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/.

A separate and distinct interaction with both the actual e-vendor and with its IT Web site interface is at the heart of online shopping. Previous research has established, accordingly, that online purchase intentions are the product of both consumer assessments of the IT itself—specifically its perceived usefulness and ease-of-use (TAM)—and trust in the e-vendor. But these perspectives have been examined independently by IS researchers. Integrating these two perspectives and examining the factors that build online trust in an environment that lacks the typical human interaction that often leads to trust in other circumstances advances our understanding of these constructs and their linkages to behavior. Our research on experienced repeat online shoppers shows that consumer trust is as important to online commerce as the widely accepted TAM use-antecedents, perceived usefulness and perceived ease of use. Together these variable sets explain a considerable proportion of variance in intended behavior. The study also provides evidence that online trust is built through (1) a belief that the vendor has nothing to gain by cheating, (2) a belief that there are safety mechanisms built into the Web site, and (3) by having a typical interface, (4) one that is, moreover, easy to use.

Offered here is a conceptual model that comprehensively describes essential aspects of corporate social performance. The three aspects of the model address major questions of concern to academics and managers alike: (1) What is included in corporate social responsibility? (2) What are the social issues the organization must address? and (3) What is the organization's philosophy or mode of social responsiveness?

The establishment of measurement invariance across groups is a logical prerequisite to conducting substantive cross-group comparisons (e.g., tests of group mean differences, invariance of structural parameter estimates), but measurement invariance is rarely tested in organizational research. In this article, the authors (a) elaborate the importance of conducting tests of measurement invariance across groups, (b) review recommended practices for conducting tests of measurement invariance, (c) review applications of measurement invariance tests in substantive applications, (d) discuss issues involved in tests of various aspects of measurement invariance, (e) present an empirical example of the analysis of longitudinal measurement invariance, and (f) propose an integrative paradigm for conducting sequences of measurement invariance tests.

A review of prior, relevant literature is an essential feature of any academic project. An effective review creates a firm foundation for advancing knowledge. It facilitates theory development, closes areas where a plethora of research exists, and uncovers areas where research is needed. In the information systems (IS) field, we see few published review articles. As a result, the progress of our field is impeded. To address this concern, the MIS Quarterly launched MISQ Review several years ago. The clear intention was to accelerate the accumulation of IS knowledge. A particular goal was to advance the state of theory within the IS field. The stated purpose of MISQ Review is to promote MIS research by publishing articles that conceptualize research areas and survey and synthesize prior research. These articles will provide important input in setting directions for future research.1 The lack of theoretical progress in the IS field may be surprising. From an empirical viewpoint, the IS field resembles other management fields. Specifically, as fields of inquiry develop, their theories are often placed on a hierarchy from ad hoc classification systems (in which categories are used to summarize empirical observations), to taxonomies (in which the relationships between the categories can be described), to conceptual frameworks (in which propositions summarize explanations and predictions), to

The growing interest in Structured Equation Modeling (SEM) techniques and recognition of their importance in IS research raises the need to compare and contrast the different types of SEM techniques so that research designs can be selected appropriately. After assessing the extent to which these techniques are currently being used in IS research, the article presents a running example which analyzes the same dataset via three very different statistical techniques. It then compares two classes of SEM: covariance-based SEM and partial-least-squares-based SEM. Finally, the article discusses linear regression models and suggests guidelines as to when SEM techniques and when regression techniques should be used. The article concludes with heuristics and rule of thumb thresholds to guide practice, and a discussion of the extent to which practice is in accord with these guidelines.

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Bibliogr.: p. 207-219

High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at http://kobas.cbi.pku.edu.cn.

The principles of ecological succession bear importantly on the relationships between man and nature. The framework of successional theory needs to be examined as a basis for resolving man’s present environmental crisis. Most ideas pertaining to the development of ecological systems are based on descriptive data obtained by observing changes in biotic communities over long periods, or on highly theoretical assumptions; very few of the generally accepted hypotheses have been tested experimentally. Some of the confusion, vagueness, and lack of experimental work in this area stems from the tendency of ecologists to regard “succession” as a single straightforward idea; in actual fact, it entails an interacting complex of processes, some of which counteract one another.

Although researchers have begun cataloging the incredible diversity of bacteria found in soil, we are largely unable to interpret this information in an ecological context, including which groups of bacteria are most abundant in different soils and why. With this study, we examined how the abundances of major soil bacterial phyla correspond to the biotic and abiotic characteristics of the soil environment to determine if they can be divided into ecologically meaningful categories. To do this, we collected 71 unique soil samples from a wide range of ecosystems across North America and looked for relationships between soil properties and the relative abundances of six dominant bacterial phyla (Acidobacteria, Bacteroidetes, Firmicutes, Actinobacteria, alpha-Proteobacteria, and the beta-Proteobacteria). Of the soil properties measured, net carbon (C) mineralization rate (an index of C availability) was the best predictor of phylum-level abundances. There was a negative correlation between Acidobacteria abundance and C mineralization rates (r2 = 0.26, P < 0.001), while the abundances of beta-Proteobacteria and Bacteroidetes were positively correlated with C mineralization rates (r2 = 0.35, P < 0.001 and r2 = 0.34, P < 0.001, respectively). These patterns were explored further using both experimental and meta-analytical approaches. We amended soil cores from a specific site with varying levels of sucrose over a 12-month period to maintain a gradient of elevated C availabilities. This experiment confirmed our survey results: there was a negative relationship between C amendment level and the abundance of Acidobacteria (r2 = 0.42, P < 0.01) and a positive relationship for both Bacteroidetes and beta-Proteobacteria (r2 = 0.38 and 0.70, respectively; P < 0.01 for each). Further support for a relationship between the relative abundances of these bacterial phyla and C availability was garnered from an analysis of published bacterial clone libraries from bulk and rhizosphere soils. Together our survey, experimental, and meta-analytical results suggest that certain bacterial phyla can be differentiated into copiotrophic and oligotrophic categories that correspond to the r- and K-selected categories used to describe the ecological attributes of plants and animals. By applying the copiotroph-oligotroph concept to soil microorganisms we can make specific predictions about the ecological attributes of various bacterial taxa and better understand the structure and function of soil bacterial communities.

A highly specific and sensitive fluorescing DNA stain, 4′6‐diamidino‐2‐phenylindole (DAPI) was compared with acridine orange (AO) for counting aquatic microflora. Use of DAPI improved visualization and counting of <1‐ µ m bacteria and blue‐green algae in seston‐rich samples and extended sample storage to at least 24 weeks.

Emerging infectious diseases (EIDs) of free-living wild animals can be classified into three major groups on the basis of key epizootiological criteria: (i) EIDs associated with "spill-over" from domestic animals to wildlife populations living in proximity; (ii) EIDs related directly to human intervention, via host or parasite translocations; and (iii) EIDs with no overt human or domestic animal involvement. These phenomena have two major biological implications: first, many wildlife species are reservoirs of pathogens that threaten domestic animal and human health; second, wildlife EIDs pose a substantial threat to the conservation of global biodiversity.

The number of prokaryotes and the total amount of their cellular carbon on earth are estimated to be 4-6 x 10(30) cells and 350-550 Pg of C (1 Pg = 10(15) g), respectively. Thus, the total amount of prokaryotic carbon is 60-100% of the estimated total carbon in plants, and inclusion of prokaryotic carbon in global models will almost double estimates of the amount of carbon stored in living organisms. In addition, the earth's prokaryotes contain 85-130 Pg of N and 9-14 Pg of P, or about 10-fold more of these nutrients than do plants, and represent the largest pool of these nutrients in living organisms. Most of the earth's prokaryotes occur in the open ocean, in soil, and in oceanic and terrestrial subsurfaces, where the numbers of cells are 1.2 x 10(29), 2.6 x 10(29), 3.5 x 10(30), and 0. 25-2.5 x 10(30), respectively. The numbers of heterotrophic prokaryotes in the upper 200 m of the open ocean, the ocean below 200 m, and soil are consistent with average turnover times of 6-25 days, 0.8 yr, and 2.5 yr, respectively. Although subject to a great deal of uncertainty, the estimate for the average turnover time of prokaryotes in the subsurface is on the order of 1-2 x 10(3) yr. The cellular production rate for all prokaryotes on earth is estimated at 1.7 x 10(30) cells/yr and is highest in the open ocean. The large population size and rapid growth of prokaryotes provides an enormous capacity for genetic diversity.

Extant explanations of why users behave in particular ways toward information technologies have tended to focus predominantly on instrumental beliefs as drivers of individual usage intentions. Prior work in individual psychology, however, suggests that holistic experiences with technology as captured in constructs such as enjoyment and flow are potentially important explanatory variables in technology acceptance theories. In this paper, we describe a multidimensional construct labeled cognitive absorption and defined as a state of deep involvement with software. Cognitive absorption, theorized as being exhibited through the five dimensions of temporal dissociation, focused immersion, heightened enjoyment, control, and curiosity, is posited to be a proximal antecedent of two important beliefs about technology use: perceived usefulness and perceived ease of use. In addition, we propose that the individual traits of playfulness and personal innovativeness are important determinants of cognitive absorption. Based on the conceptual definition of this construct, operational measures for each dimension are developed. Using the World Wide Web as the target technology, scale validation indicates that the operational measures have acceptable psychometric properties and confirmatory factor analysis supports the proposed multi-dimensional structure. Structural equation analysis provides evidence for the theorized nomological net of cognitive absorption. Theoretical and practical implications are offered.