35 research outputs found
Community Detection Based on Modularity and k-Plexes
Abstract(#br)Community identification is of great worth for analyzing the structure or characteristics of a complex network. Many community detection methods have been developed, such as modularity-based optimization models, which are widely used but significantly restricted in âresolution limitâ. In this paper, we propose a novel algorithm, called modularity optimization with k -plexes (MOKP), to solve this problem, and this algorithm can identify communities smaller than a scale. The proposed algorithm uses k -plexes to generate community seeds from the whole network and assigns the remaining nodes by modularity optimization. To save computational time, we further propose the improved MOKP algorithm (IMOKP) by reducing the scale of the network before community seeds generation and adjusting rules of nodes assignment. Extensive experimental results demonstrate our proposed algorithms perform better than several state-of-the-art algorithms in terms of accuracy of detected communities on various networks, and can effectively detect small communities in terms of a newly defined index, namely small community level, on multiple networks as well
Carbon-sensitive pedotransfer functions for plant available water
Currently accepted pedotransfer functions show negligible effect of management-induced changes to soil organic carbon (SOC) on plant available water holding capacity (ΞAWHC), while some studies show the ability to substantially increase ΞAWHC through management. The Soil Health Institute\u27s North America Project to Evaluate Soil Health Measurements measured water content at field capacity using intact soil cores across 124 long-term research sites that contained increases in SOC as a result of management treatments such as reduced tillage and cover cropping. Pedotransfer functions were created for volumetric water content at field capacity (ΞFC) and permanent wilting point (ΞPWP). New pedotransfer functions had predictions of ΞAWHC that were similarly accurate compared with Saxton and Rawls when tested on samples from the National Soil Characterization database. Further, the new pedotransfer functions showed substantial effects of soil calcareousness and SOC on ΞAWHC. For an increase in SOC of 10 g kgâ1 (1%) in noncalcareous soils, an average increase in ΞAWHC of 3.0 mm 100 mmâ1 soil (0.03 m3 mâ3) on average across all soil texture classes was found. This SOC related increase in ΞAWHC is about double previous estimates. Calcareous soils had an increase in ΞAWHC of 1.2 mm 100 mmâ1 soil associated with a 10 g kgâ1 increase in SOC, across all soil texture classes. New equations can aid in quantifying benefits of soil management practices that increase SOC and can be used to model the effect of changes in management on drought resilience
Community detection in graphs
The modern science of networks has brought significant advances to our
understanding of complex systems. One of the most relevant features of graphs
representing real systems is community structure, or clustering, i. e. the
organization of vertices in clusters, with many edges joining vertices of the
same cluster and comparatively few edges joining vertices of different
clusters. Such clusters, or communities, can be considered as fairly
independent compartments of a graph, playing a similar role like, e. g., the
tissues or the organs in the human body. Detecting communities is of great
importance in sociology, biology and computer science, disciplines where
systems are often represented as graphs. This problem is very hard and not yet
satisfactorily solved, despite the huge effort of a large interdisciplinary
community of scientists working on it over the past few years. We will attempt
a thorough exposition of the topic, from the definition of the main elements of
the problem, to the presentation of most methods developed, with a special
focus on techniques designed by statistical physicists, from the discussion of
crucial issues like the significance of clustering and how methods should be
tested and compared against each other, to the description of applications to
real networks.Comment: Review article. 103 pages, 42 figures, 2 tables. Two sections
expanded + minor modifications. Three figures + one table + references added.
Final version published in Physics Report
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Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage
Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity
The ABC130 barrel module prototyping programme for the ATLAS strip tracker
For the Phase-II Upgrade of the ATLAS Detector, its Inner Detector,
consisting of silicon pixel, silicon strip and transition radiation
sub-detectors, will be replaced with an all new 100 % silicon tracker, composed
of a pixel tracker at inner radii and a strip tracker at outer radii. The
future ATLAS strip tracker will include 11,000 silicon sensor modules in the
central region (barrel) and 7,000 modules in the forward region (end-caps),
which are foreseen to be constructed over a period of 3.5 years. The
construction of each module consists of a series of assembly and quality
control steps, which were engineered to be identical for all production sites.
In order to develop the tooling and procedures for assembly and testing of
these modules, two series of major prototyping programs were conducted: an
early program using readout chips designed using a 250 nm fabrication process
(ABCN-25) and a subsequent program using a follow-up chip set made using 130 nm
processing (ABC130 and HCC130 chips). This second generation of readout chips
was used for an extensive prototyping program that produced around 100
barrel-type modules and contributed significantly to the development of the
final module layout. This paper gives an overview of the components used in
ABC130 barrel modules, their assembly procedure and findings resulting from
their tests.Comment: 82 pages, 66 figure
The James Webb Space Telescope Mission
Twenty-six years ago a small committee report, building on earlier studies,
expounded a compelling and poetic vision for the future of astronomy, calling
for an infrared-optimized space telescope with an aperture of at least .
With the support of their governments in the US, Europe, and Canada, 20,000
people realized that vision as the James Webb Space Telescope. A
generation of astronomers will celebrate their accomplishments for the life of
the mission, potentially as long as 20 years, and beyond. This report and the
scientific discoveries that follow are extended thank-you notes to the 20,000
team members. The telescope is working perfectly, with much better image
quality than expected. In this and accompanying papers, we give a brief
history, describe the observatory, outline its objectives and current observing
program, and discuss the inventions and people who made it possible. We cite
detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space
Telescope Overview, 29 pages, 4 figure
The association among cytochrome P450 3A, progesterone receptor polymorphisms, plasma 17-alpha hydroxyprogesterone caproate concentrations, and spontaneous preterm birth
Background Infants born <37 weeksâ gestation are of public health concern since complications associated with preterm birth are the leading cause of mortality in children <5 years of age and a major cause of morbidity and lifelong disability. The administration of 17-alpha hydroxyprogesterone caproate reduces preterm birth by 33% in women with history of spontaneous preterm birth. We demonstrated previously that plasma concentrations of 17-alpha hydroxyprogesterone caproate vary widely among pregnant women and that women with 17-alpha hydroxyprogesterone caproate plasma concentrations in the lowest quartile had spontaneous preterm birth rates of 40% vs rates of 25% in those women with higher concentrations. Thus, plasma concentrations are an important factor in determining drug efficacy but the reason 17-alpha hydroxyprogesterone caproate plasma concentrations vary so much is unclear. Predominantly, 17-alpha hydroxyprogesterone caproate is metabolized by CYP3A4 and CYP3A5 enzymes. Objective We sought to: (1) determine the relation between 17-alpha hydroxyprogesterone caproate plasma concentrations and single nucleotide polymorphisms in CYP3A4 and CYP3A5; (2) test the association between progesterone receptor single nucleotide polymorphisms and spontaneous preterm birth; and (3) test whether the association between plasma concentrations of 17-alpha hydroxyprogesterone caproate and spontaneous preterm birth varied by progesterone receptor single nucleotide polymorphisms. Study Design In this secondary analysis, we evaluated genetic polymorphism in 268 pregnant women treated with 17-alpha hydroxyprogesterone caproate, who participated in a placebo-controlled trial to evaluate the benefit of omega-3 supplementation in women with history of spontaneous preterm birth. Trough plasma concentrations of 17-alpha hydroxyprogesterone caproate were measured between 25-28 weeks of gestation after a minimum of 5 injections of 17-alpha hydroxyprogesterone caproate. We extracted DNA from maternal blood samples and genotyped the samples using TaqMan (Applied Biosystems, Foster City, CA) single nucleotide polymorphism genotyping assays for the following single nucleotide polymorphisms: CYP3A4*1B, CYP3A4*1G, CYP3A4*22, and CYP3A5*3; and rs578029, rs471767, rs666553, rs503362, and rs500760 for progesterone receptor. We adjusted for prepregnancy body mass index, race, and treatment group in a multivariable analysis. Differences in the plasma concentrations of 17-alpha hydroxyprogesterone caproate by genotype were evaluated for each CYP single nucleotide polymorphism using general linear models. The association between progesterone receptor single nucleotide polymorphisms and frequency of spontaneous preterm birth was tested using logistic regression. A logistic model also tested interaction between 17-alpha hydroxyprogesterone caproate concentrations with each progesterone receptor single nucleotide polymorphism for the outcome of spontaneous preterm birth. Results The association between CYP single nucleotide polymorphisms *22, *1G, *1B, and *3 and trough plasma concentrations of 17-alpha hydroxyprogesterone caproate was not statistically significant (P =.68,.44,.08, and.44, respectively). In an adjusted logistic regression model, progesterone receptor single nucleotide polymorphisms rs578029, rs471767, rs666553, rs503362, and rs500760 were not associated with the frequency of spontaneous preterm birth (P =.29,.10,.76,.09, and.43, respectively). Low trough plasma concentrations of 17-alpha hydroxyprogesterone caproate were statistically associated with a higher frequency of spontaneous preterm birth (odds ratio, 0.78; 95% confidence ratio, 0.61â0.99; P =.04 for trend across quartiles), however no significant interaction with the progesterone receptor single nucleotide polymorphisms rs578029, rs471767, rs666553, rs503362, and rs500760 was observed (P =.13,.08,.10,.08, and.13, respectively). Conclusion The frequency of recurrent spontaneous preterm birth appears to be associated with trough 17-alpha hydroxyprogesterone caproate plasma concentrations. However, the wide variation in trough 17-alpha hydroxyprogesterone caproate plasma concentrations is not attributable to polymorphisms in CYP3A4 and CYP3A5 genes. Progesterone receptor polymorphisms do not predict efficacy of 17-alpha hydroxyprogesterone caproate. The limitations of this secondary analysis include that we had a relative small sample size (n = 268) and race was self-reported by the patients
Peripheries of cohesive subsets
Network analysts have developed a number of techniques for identifying cohesive subgroups in networks. In general, however, no consideration is given to actors that do not belong to a given group. In this paper, we explore ways of identifying actors that are not members of a given cohesive subgroup, but who are sufficiently well tied to the group to be considered peripheral members. We then use this information to explore the structure of the network as a whole