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Graphs play a key role in data analytics. Graphs and the software systems used to work with them are highly diverse. Algorithms interact with hardware in different ways and which graph solution works best on a given platform changes with the structure of the graph. This makes it difficult to decide which graph programming framework is the best for a given situation. In this paper, we try to make sense of this diverse landscape. We evaluate five different frameworks for graph analytics: SuiteS-parse GraphBLAS, Galois, the NWGraph library, the Graph Kernel Collection, and GraphIt. We use the GAP Benchmark Suite to evaluate each framework. GAP consists of 30 tests: six graph algorithms (breadth-first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) on five graphs. The GAP Benchmark Suite includes high-performance reference implementations to provide a performance baseline for comparison. Our results show the relative strengths of each framework, but also serve as a case study for the challenges of establishing objective measures for comparing graph frameworks.

Background: Combining computational toxicology with ExpoCast exposure estimates and ToxCast[TM] assay data gives us access to predictions of human health risks stemming from exposures to chemical mixtures. Objectives: We explored, through mathematical modeling and simulations, the size of potential effects of random mixtures of aromatase inhibitors on the dynamics of women's menstrual cycles. Methods: We simulated random exposures to millions of potential mixtures of 86 aromatase inhibitors. A pharmacokinetic model of intake and disposition of the chemicals predicted their internal concentration as a function of time (up to 2 y). A ToxCast[TM] aromatase assay provided concentration--inhibition relationships for each chemical. The resulting total aromatase inhibition was input to a mathematical model of the hormonal hypothalamuspituitary--ovarian control of ovulation in women. Results: Above 10% inhibition of estradiol synthesis by aromatase inhibitors, noticeable (eventually reversible) effects on ovulation were predicted. Exposures to individual chemicals never led to such effects. In our best estimate, ~ 10% of the combined exposures simulated had mild to catastrophic impacts on ovulation. A lower bound on that figure, obtained using an optimistic exposure scenario, was 0.3%. Conclusions: These results demonstrate the possibility to predict large-scale mixture effects for endocrine disrupters with a predictive toxicology approach that is suitable for high-throughput ranking and risk assessment. The size of the effects predicted is consistent with an increased risk of infertility in women from everyday exposures to our chemical environment. https://doi.org/10.1289/EHP742, Introduction Concern is growing worldwide over the negative human health and environmental impacts of chemical pollutants that can interfere with the production, metabolism, and action of natural hormones, the so-called [...]

Pthreads is the library of POSIX standard functions for concurrent, multithreaded programming. The POSIX standard only defines an application programming interface (API) to the C programming language, not to Fortran. Many scientific and engineering applications are written in Fortran. Also, many of these applications exhibit functional, or task-level, concurrency. They would benefit from multithreading, especially on symmetric multiprocessors (SMP). We present here an interface to that part of the Pthreads library that is compatible with standard Fortran. The contribution consists of two primary source files: a Fortran module and a collection of C wrappers to Pthreads functions. The Fortran module defines the data structures, interface and initialization routines used to manage threads. The stability and portability of the Fortran API to Pthreads has been demonstrated using common mathematical computations on several SMP systems. Categories and Subject Descriptors: D.1.3 [Concurrent Programming]: Parallel Programming; G.4 [Mathematical Software]: Parallel and vector implementations General Terms: Algorithms, Languages, Performance, Standardization Additional Key Words and Phrases: Scientific computing, symmetric multi-processor, mathematical software, POSIX Threads, Pthreads, Fortran

Neither informatics (e.g., Goldsmith et al. 2014) nor gas chromatography-mass spectrometry (GC/MS) (e.g., Steinemann et al. 2011, Dodson et al. 2012, Steinemann 2015) can provide a complete picture of the [...]

BACKGROUND: Simultaneous or sequential exposure to multiple environmental stressors can affect chemical toxicity. Cumulative risk assessments consider multiple stressors but it is impractical to test every chemical combination to which people are exposed. New methods are needed to prioritize chemical combinations based on their prevalence and possible health impacts. OBJECTIVES: We introduce an informatics approach that uses publicly available data to identify chemicals that co-occur in consumer products, which account for a significant proportion of overall chemical load. METHODS: Fifty-five asthma-associated and endocrine disrupting chemicals (target chemicals) were selected. A database of 38,975 distinct consumer products and 32,231 distinct ingredient names was created from online sources, and PubChem and the Unified Medical Language System were used to resolve synonymous ingredient names. Synonymous ingredient names are different names for the same chemical (e.g., vitamin E and tocopherol). RESULTS: Nearly one-third of the products (11,688 products, 30%) contained ≥ 1 target chemical and 5,229 products (13%) contained > 1. Of the 55 target chemicals, 31 (56%) appear in ≥ 1 product and 19 (35%) appear under more than one name. The most frequent three-way chemical combination (2-phenoxyethanol, methyl paraben, and ethyl paraben) appears in 1,059 products. Further work is needed to assess combined chemical exposures related to the use of multiple products. CONCLUSIONS: The informatics approach increased the number of products considered in a traditional analysis by two orders of magnitude, but missing/incomplete product labels can limit the effectiveness of this approach. Such an approach must resolve synonymy to ensure that chemicals of interest are not missed. Commonly occurring chemical combinations can be used to prioritize cumulative toxicology risk assessments. http://dx.doi.org/10.1289/ehp.1510529, Introduction Much of the work in assessing risks associated with chemical exposure focuses on individual chemicals. However, communities face exposure from a variety of sources and the chemical load (also [...]

A comprehensive molecular model study was done on the conformational transitions in potential and free energy space for furanoses and 2'deoxynucleosides. Results show that the P and X transitions in the deoxynucleosides are not energetically coupled in the most plausible pathways for C2'-endo/anti to C3'-endo/syn. These results suggest that v(sub m) contributes entropically to furanose flexibility in a manner that is not apparent in potential energy calculations.