bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of the international comparability of population-based routine hospital data set derived comorbidity scores for patients with lung cancer
Authors: Lüchtenborg Margreet , Morris Eva J A , Tataru Daniela , Coupland Victoria H , Smith Andrew , Milne Roger L , te Marvelde Luc , Baker Deborah , Young Jane , Turner Donna , Nishri Diane , Earle Craig , Shack Lorraine , Gavin Anna , Fitzpatrick Deirdre , Donnelly Conan , Lin Yulan , Møller Bjørn , Brewster David H , Deas Andrew , Huws Dyfed W , White Ceri , Warlow Janet , Rashbass Jem , Peake Michael D 
Published: October 2017

IntroductionThe International Cancer Benchmarking Partnership (ICBP) identified significant international differences in lung cancer survival. Differing levels of comorbid disease across ICBP countries has been suggested as a potential explanation of this variation but, to date, no studies have quantified its impact. This study investigated whether comparable, robust comorbidity scores can be derived from the different routine population-based cancer data sets available in the ICBP jurisdictions and, if so, use them to quantify international variation in comorbidity and determine its influence on outcome.MethodsLinked population-based lung cancer registry and hospital discharge data sets were acquired from nine ICBP jurisdictions in Australia, Canada, Norway and the UK providing a study population of 233 981 individuals. For each person in this cohort Charlson, Elixhauser and inpatient bed day Comorbidity Scores were derived relating to the 4–36 months prior to their lung cancer diagnosis. The scores were then compared to assess their validity and feasibility of use in international survival comparisons.ResultsIt was feasible to generate the three comorbidity scores for each jurisdiction, which were found to have good content, face and concurrent validity. Predictive validity was limited and there was evidence that the reliability was questionable.ConclusionThe results presented here indicate that interjurisdictional comparability of recorded comorbidity was limited due to probable differences in coding and hospital admission practices in each area. Before the contribution of comorbidity on international differences in cancer survival can be investigated an internationally harmonised comorbidity index is required.
The molecular basis for an ancient colour mutant in sweet pea (Lathyrus odoratus)
Authors: Xue Xinxin , Cronk Quentin C.B. 
Published: October 2017

The classic A1 locus in sweet pea (Lathyrus odoratus) was investigated by Bateson, Punnett, and Saunders in the early 20th century history of Mendelian genetics. The mutation, in the form of the pink and white cultivar ‘Painted Lady’, is known from the 18th century. We show that this locus is associated with a single base pair mutation (332 G/A) in the flavonoid 3′,5′-hydroxylase (F3′5′H) gene. This results in an amino acid change (111 glycine/aspartic acid) in the conserved substrate recognition site 1 of the enzyme. The mutant flower lacks the blue pigment delphinidin and is thus pink and white, rather than purple and blue as in the wild-type. This single amino acid change at a functionally important site appears to convert the enzyme from primary F3′5′H activity to a relatively efficient F3′H, as suggested by heterologous transformation into Arabidopsis PAP1D (a mutant line that produces anthocyanin constitutively).
Uncertainty estimation for a geological model of the Sandstone greenstone belt, Western Australia – insights from integrated geological and geophysical inversion in a Bayesian inference framework
Authors: Wellmann J. Florian , de la Varga Miguel , Murdie Ruth E. , Gessner Klaus , Jessell Mark 
Published: October 2017

Abstract
The spatial relationship between different rock types and relevant structural features is an important aspect in the characterization of ore-forming systems. Our knowledge about this geological architecture is often captured in 3D structural geological models. Multiple methods exist to generate these models, but one important problem remains: structural models often contain significant uncertainties. In recent years, several approaches have been developed to consider uncertainties in geological prior parameters that are used to create these models through the use of stochastic simulation methods. However, a disadvantage of these methods is that there is no guarantee that each simulated model is geologically reasonable – and that it forms a valid representation in the light of additional data (e.g. geophysical measurements). We address these shortcomings here with an approach for the integration of structural geological and geophysical data into a framework that explicitly considers model uncertainties. We combine existing implicit structural modelling methods with novel developments in probabilistic programming in a Bayesian framework. In an application of these concepts to a gold-bearing greenstone belt in Western Australia, we show that we are able to significantly reduce uncertainties in the final model by additional data integration. Although the final question always remains whether a predicted model suite is a suitable representation of accuracy or not, we conclude that our application of a Bayesian framework provides a novel quantitative approach to addressing uncertainty and optimization of model parameters.
The Applied Pi Calculus
Authors: Abadi Martín , Blanchet Bruno , Fournet Cédric 
Published: October 2017

We study the interaction of the programming construct “new,” which generates statically scoped names, with communication via messages on channels. This interaction is crucial in security protocols, which are the main motivating examples for our work; it also appears in other programming-language contexts.
We define the applied pi calculus, a simple, general extension of the pi calculus in which values can be formed from names via the application of built-in functions, subject to equations, and be sent as messages. (In contrast, the pure pi calculus lacks built-in functions; its only messages are atomic names.) We develop semantics and proof techniques for this extended language and apply them in reasoning about security protocols.
This article essentially subsumes the conference paper that introduced the applied pi calculus in 2001. It fills gaps, incorporates improvements, and further explains and studies the applied pi calculus. Since 2001, the applied pi calculus has been the basis for much further work, described in many research publications and sometimes embodied in useful software, such as the tool ProVerif, which relies on the applied pi calculus to support the specification and automatic analysis of security protocols. Although this article does not aim to be a complete review of the subject, it benefits from that further work and provides better foundations for some of it. In particular, the applied pi calculus has evolved through its implementation in ProVerif, and the present definition reflects that evolution.
Declarative Probabilistic Programming with Datalog
Authors: BáRány Vince , Cate Balder Ten , Kimelfeld Benny , Olteanu Dan , Vagena Zografoula 
Published: October 2017

Probabilistic programming languages are used for developing statistical models. They typically consist of two components: a specification of a stochastic process (the prior) and a specification of observations that restrict the probability space to a conditional subspace (the posterior). Use cases of such formalisms include the development of algorithms in machine learning and artificial intelligence.
In this article, we establish a probabilistic-programming extension of Datalog that, on the one hand, allows for defining a rich family of statistical models, and on the other hand retains the fundamental properties of declarativity. Our proposed extension provides mechanisms to include common numerical probability functions; in particular, conclusions of rules may contain values drawn from such functions. The semantics of a program is a probability distribution over the possible outcomes of the input database with respect to the program. Observations are naturally incorporated by means of integrity constraints over the extensional and intensional relations. The resulting semantics is robust under different chases and invariant to rewritings that preserve logical equivalence.
Simple, Accurate, Analytical Time Modeling and Optimal Tile Size Selection for GPGPU Stencils
Authors: Prajapati Nirmal , Ranasinghe Waruna , Rajopadhye Sanjay , Andonov Rumen , Djidjev Hristo , Grosser Tobias 
Published: October 2017

Stencil computations are an important class of compute and data intensive programs that occur widely in scientific and engineeringapplications. A number of tools use sophisticated tiling, parallelization, and memory mapping strategies, and generate code that relies on vendor-supplied compilers. This code has a number of parameters, such as tile sizes, that are then tuned via empirical exploration.
We develop a model that guides such a choice. Our model is a simple set of analytical functions that predict the execution time of the generated code. It is deliberately optimistic, since tile sizes and, moreover, the optimistic assumptions are intended to enable we are targeting modeling and parameter selections yielding highly tuned codes.
We experimentally validate the model on a number of 2D and 3D stencil codes, and show that the root mean square error in the execution time is less than 10% for the subset of the codes that achieve performance within 20% of the best. Furthermore, based on using our model, we are able to predict tile sizes that achieve a further improvement of 9% on average.
SC-Haskell
Authors: Vollmer Michael , Scott Ryan G. , Musuvathi Madanlal , Newton Ryan R. 
Published: October 2017

A core, but often neglected, aspect of a programming language design is its memory (consistency) model. Sequential consistency~(SC) is the most intuitive memory model for programmers as it guarantees sequential composition of instructions and provides a simple abstraction of shared memory as a single global store with atomic read and writes. Unfortunately, SC is widely considered to be impractical due to its associated performance overheads.
Perhaps contrary to popular opinion, this paper demonstrates that SC is achievable with acceptable performance overheads for mainstream languages that minimize mutable shared heap. In particular, we modify the Glasgow Haskell Compiler to insert fences on all writes to shared mutable memory accessed in nonfunctional parts of the program. For a benchmark suite containing 1,279 programs, SC adds a geomean overhead of less than 0.4\% on an x86 machine.
The efficiency of SC arises primarily due to the isolation provided by the Haskell type system between purely functional and thread-local imperative computations on the one hand, and imperative computations on the global heap on the other. We show how to use new programming idioms to further reduce the SC overhead; these create a virtuous cycle of less overhead and even stronger semantic guarantees (static data-race freedom).
Checking Concurrent Data Structures Under the C/C++11 Memory Model
Authors: Ou Peizhao , Demsky Brian 
Published: October 2017

Concurrent data structures often provide better performance on multi-core processors but are significantly more difficult to design and test than their sequential counterparts. The C/C++11 standard introduced a weak memory model with support for low-level atomic operations such as compare and swap (CAS). While low-level atomic operations can significantly improve the performance of concurrent data structures, they introduce non-intuitive behaviors that can increase the difficulty of developing code.
In this paper, we develop a correctness model for concurrent data structures that make use of atomic operations. Based on this correctness model, we present CDSSPEC, a specification checker for concurrent data structures under the C/C++11 memory model. We have evaluated CDSSPEC on 10 concurrent data structures, among which CDSSPEC detected 3 known bugs and 93% of the injected bugs.
Pagoda
Authors: Yeh Tsung Tai , Sabne Amit , Sakdhnagool Putt , Eigenmann Rudolf , Rogers Timothy G. 
Published: October 2017

Massively multithreaded GPUs achieve high throughput by running thousands of threads in parallel. To fully utilize the hardware, workloads spawn work to the GPU in bulk by launching large tasks, where each task is a kernel that contains thousands of threads that occupy the entire GPU.
GPUs face severe underutilization and their performance benefits vanish if the tasks are narrow, i.e., they contain < 500 threads. Latency-sensitive applications in network, signal, and image processing that generate a large number of tasks with relatively small inputs are examples of such limited parallelism.
This paper presents Pagoda, a runtime system that virtualizes GPU resources, using an OS-like daemon kernel called MasterKernel. Tasks are spawned from the CPU onto Pagoda as they become available, and are scheduled by the MasterKernel at the warp granularity. Experimental results demonstrate that Pagoda achieves a geometric mean speedup of 5.70x over PThreads running on a 20-core CPU, 1.51x over CUDA-HyperQ, and 1.69x over GeMTC, the state-of- the-art runtime GPU task scheduling system.
Contention in Structured Concurrency
Authors: Acar Umut A. , Ben-David Naama , Rainey Mike 
Published: October 2017

Over the past two decades, many concurrent data structures have been designed and implemented. Nearly all such work analyzes concurrent data structures empirically, omitting asymptotic bounds on their efficiency, partly because of the complexity of the analysis needed, and partly because of the difficulty of obtaining relevant asymptotic bounds: when the analysis takes into account important practical factors, such as contention, it is difficult or even impossible to prove desirable bounds.
In this paper, we show that considering structured concurrency or relaxed concurrency models can enable establishing strong bounds, also for contention. To this end, we first present a dynamic relaxed counter data structure that indicates the non-zero status of the counter. Our data structure extends a recently proposed data structure, called SNZI, allowing our structure to grow dynamically in response to the increasing degree of concurrency in the system.

Using the dynamic SNZI data structure, we then present a concurrent data structure for series-parallel directed acyclic graphs (sp-dags), a key data structure widely used in the implementation of modern parallel programming languages. The key component of sp-dags is an
in-counter
data structure that is an instance of our dynamic SNZI. We analyze the efficiency of our concurrent sp-dags and in-counter data structures under nested-parallel computing paradigm. This paradigm offers a structured model for concurrency. Under this model, we prove that our data structures require amortized

(1) shared memory steps, including contention. We present an implementation and an experimental evaluation that suggests that the sp-dags data structure is practical and can perform well in practice.
Processor-Oblivious Record and Replay
Authors: Utterback Robert , Agrawal Kunal , Lee I-Ting Angelina , Kulkarni Milind 
Published: October 2017

Record-and-replay systems are useful tools for debugging non-deterministic parallel programs by first recording an execution and then replaying that execution to produce the same access pattern. Existing record-and-replay systems generally target thread-based execution models, and record the behaviors and interleavings of individual threads. Dynamic multithreaded languages and libraries, such as the Cilk family, OpenMP, TBB, etc., do not have a notion of threads. Instead, these languages provide a processor-oblivious model of programming, where programs expose task-parallelism using high-level constructs such as spawn/sync without regard to the number of threads/cores available to run the program. Thread-based record-and-replay would violate the processor-oblivious nature of these programs, as they incorporate the number of threads into the recorded information, constraining the replayed execution to the same number of threads.
In this paper, we present a processor-oblivious record-and-replay scheme for such languages where record and replay can use different number of processors and both are scheduled using work stealing. We provide theoretical guarantees for our record and replay scheme --- namely that record is optimal for programs with one lock and replay is near-optimal for all cases. In addition, we implemented this scheme in the Cilk Plus runtime system and our evaluation indicates that processor-obliviousness does not cause substantial overheads.
Grammar-aware Parallelization for Scalable XPath Querying
Authors: Jiang Lin , Zhao Zhijia 
Published: October 2017

Semi-structured data emerge in many domains, especially in web analytics and business intelligence. However, querying such data is inherently sequential due to the nested structure of input data. Existing solutions pessimistically enumerate all execution paths to circumvent dependencies, yielding sub-optimal performance and limited scalability.
This paper presents GAP, a parallelization scheme that, for the first time, leverages the grammar of the input data to boost the parallelization efficiency. GAP leverages static analysis to infer feasible execution paths for specific con- texts based on the grammar of the semi-structured data. It can eliminate unnecessary paths without compromising the correctness. In the absence of a pre-defined grammar, GAP switches into a speculative execution mode and takes potentially incomplete grammar extracted either from prior inputs. Together, the dual-mode GAP reduces the execution paths from all paths to a minimum, therefore maximizing the parallelization efficiency and scalability. The benefits of path elimination go beyond reducing extra computation -- it also enables the use of more efficient data structures, which further improves the efficiency. An evaluation on a large set of standard benchmarks with diverse queries shows that GAP yields significant efficiency increase and boosts the speedup of the state-of-the-art from 2.9X to 17.6X on a 20-core ma- chine for a set of 200 queries.
Flaxseed Consumption Inhibits Chemically Induced Lung Tumorigenesis and Modulates Expression of Phase II Enzymes and Inflammatory Cytokines in A/J Mice
Authors: Chikara Shireen , Mamidi Sujan , Sreedasyam Avinash , Chittem Kishore , Pietrofesa Ralph , Zuppa Athena , Moorthy Ganesh , Dyer Neil , Christofidou-Solomidou Melpo , Reindl Katie M. 
Published: October 2017

Abstract
Flaxseed consumption is associated with reduced oxidative stress and inflammation in lung injury models and has shown anticancer effects for breast and prostate tissues. However, the chemopreventive potential of flaxseed remains unexplored for lung cancer. In this study, we investigated the effect of flaxseed on tobacco smoke carcinogen (NNK)–induced lung tumorigenesis in an A/J mouse model. Mice exposed to NNK were fed a control diet or a 10% flaxseed-supplemented diet for 26 weeks. Flaxseed-fed mice showed reduced lung tumor incidence (78%) and multiplicity, with an average of 2.7 ± 2.3 surface lung tumor nodules and 1.0 ± 0.9 H&E cross-section nodules per lung compared with the control group, which had 100% tumor incidence and an average of 10.2 ± 5.7 surface lung tumor nodules and 3.9 ± 2.6 H&E cross-section nodules per lung. Furthermore, flaxseed-fed mice had a lower incidence of adenocarcinomas compared with control-fed mice. Western blotting performed on normal lung tissues showed flaxseed suppressed phosphorylation (activation) of p-AKT, p-ERK, and p-JNK kinases. RNA-Seq data obtained from normal lung and lung tumors of control and flaxseed-fed mice suggested that flaxseed intake resulted in differential expression of genes involved in inflammation-mediated cytokine signaling (IL1, 6, 8, 9, and 12α), xenobiotic metabolism (several CYPs, GSTs, and UGTs), and signaling pathways (AKT and MAPK) involved in tumor cell proliferation. Together, our results indicate that dietary flaxseed supplementation may be an effective chemoprevention strategy for chemically induced lung carcinogenesis by altering signaling pathways, inflammation, and oxidative stress. Cancer Prev Res; 11(1); 27–37. ©2017 AACR.
Genetic Variants in Metabolic Signaling Pathways and Their Interaction with Lifestyle Factors on Breast Cancer Risk: A Random Survival Forest Analysis
Authors: Jung Su Yon , Papp Jeanette C. , Sobel Eric M. , Zhang Zuo-Feng 
Published: October 2017

Abstract
Genetic variants in the insulin-like growth factor-I (IGF-I)/insulin resistance axis may interact with lifestyle factors, influencing postmenopausal breast cancer risk, but these interrelated pathways are not fully understood. In this study, we examined 54 single-nucleotide polymorphisms (SNP) in genes related to IGF-I/insulin phenotypes and signaling pathways and lifestyle factors in relation to postmenopausal breast cancer, using data from 6,567 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies. We used a machine-learning method, two-stage random survival forest analysis. We identified three genetic variants (AKT1 rs2494740, AKT1 rs2494744, and AKT1 rs2498789) and two lifestyle factors [body mass index (BMI) and dietary alcohol intake] as the top five most influential predictors for breast cancer risk. The combination of the three SNPs, BMI, and alcohol consumption (≥1 g/day) significantly increased the risk of breast cancer in a gene and lifestyle dose-dependent manner. Our findings provide insight into gene–lifestyle interactions and will enable researchers to focus on individuals with risk genotypes to promote intervention strategies. These data also suggest potential genetic targets in future intervention/clinical trials for cancer prevention in order to reduce the risk for breast cancer in postmenopausal women. Cancer Prev Res; 11(1); 44–51. ©2017 AACR.
A Novel Application of Structural Equation Modeling Estimates the Association between Oxidative Stress and Colorectal Adenoma
Authors: Eldridge Ronald C. , Goodman Michael , Bostick Roberd M. , Fedirko Veronika , Gross Myron , Thyagarajan Bharat , Flanders W. Dana 
Published: October 2017

AbstractIn vitro evidence implicates oxidative stress in many adverse health conditions, including colorectal neoplasia. In human studies, however, oxidative stress is measured by imperfect biomarkers, which are inconsistently associated with health outcomes. Structural equation modeling (SEM) offers one possible solution by modeling a latent (unobserved) construct from multiple biomarkers. Our goal was to investigate the association of a latent oxidative stress variable with colorectal adenoma. Using SEM, we analyzed pooled data from two cross-sectional studies of colorectal adenoma (n = 526) that measured five plasma biomarkers of oxidative stress and inflammation that comprised the latent oxidative stress variable: F2-isoprostanes (FIP), fluorescent oxidation products (FOP), mitochondrial DNA (MtDNA) copy number, γ-tocopherol (Gtoc), and C-reactive protein (CRP). Higher levels of oxidative stress were associated with colorectal adenoma [OR = 3.23 per SD increase in oxidative stress; 95% confidence interval (CI), 1.28–8.18]. The latent variable estimate was considerably stronger than the associations of adenoma with the individual biomarkers, which were modest and mostly nonsignificant. Risk factors were associated with adenoma via the oxidative stress pathway, particularly overweight and obesity with an OR = 1.50; 95% CI, 1.10–2.81; and OR = 2.95; 95% CI, 1.28–12.45, respectively. Oxidative stress may be positively associated with colorectal adenoma, and important risk factors may act through this mechanism, but the cross-sectional design of the current study precludes observing the directionality of associations. The presence of an adenoma could affect levels of the circulating biomarkers; thus, we should be cautious of strong conclusions until the findings are replicated in a follow-up study. Cancer Prev Res; 11(1); 52–58. ©2017 AACR.