bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating Bias of Illumina-Based Bacterial 16S rRNA Gene Profiles
Authors: Kennedy Katherine , Hall Michael W. , Lynch Michael D. J. , Moreno-Hagelsieb Gabriel , Neufeld Josh D. 
Published: July 2014

ABSTRACT
Massively parallel sequencing of 16S rRNA genes enables the comparison of terrestrial, aquatic, and host-associated microbial communities with sufficient sequencing depth for robust assessments of both alpha and beta diversity. Establishing standardized protocols for the analysis of microbial communities is dependent on increasing the reproducibility of PCR-based molecular surveys by minimizing sources of methodological bias. In this study, we tested the effects of template concentration, pooling of PCR amplicons, and sample preparation/interlane sequencing on the reproducibility associated with paired-end Illumina sequencing of bacterial 16S rRNA genes. Using DNA extracts from soil and fecal samples as templates, we sequenced pooled amplicons and individual reactions for both high (5- to 10-ng) and low (0.1-ng) template concentrations. In addition, all experimental manipulations were repeated on two separate days and sequenced on two different Illumina MiSeq lanes. Although within-sample sequence profiles were highly consistent, template concentration had a significant impact on sample profile variability for most samples. Pooling of multiple PCR amplicons, sample preparation, and interlane variability did not influence sample sequence data significantly. This systematic analysis underlines the importance of optimizing template concentration in order to minimize variability in microbial-community surveys and indicates that the practice of pooling multiple PCR amplicons prior to sequencing contributes proportionally less to reducing bias in 16S rRNA gene surveys with next-generation sequencing.
Algorithm 944
Authors: Antonelli Laura , Corsaro Stefania , Marino Zelda , Rizzardi Mariarosaria 
Published: July 2014

We present Talbot Suite, a C parallel software collection for the numerical inversion of Laplace Transforms, based onTalbot's method. It is designed to fit both single and multiple Laplace inversion problems, which arise in several application and research fields.In our software, we achieve high accuracy and efficiency, making full use of modern architectures and introducing two different levels of parallelism: coarse and fine grained parallelism. They offer a reasonable tradeoff between accuracy, the main aspect for a few inversions, and efficiency, the main aspect for multiple inversions. To take into account modern high-performance computing architectures, Talbot Suite provides different software versions: an OpenMP-based version for shared memory machines and a MPI-based version for distributed memory machines. Moreover, oriented to hybrid architectures, a combined MPI/OpenMP-based implementation is provided too. We describe our parallel algorithms and the software organization. We also report some performance results. Our software includes sample programs to call the Talbot Suite functions from C and from MATLAB.
The Ultrasmall soft processor
Authors: Tanaka Yuichiroh , Sato Shimpei , Kise Kenji 
Published: July 2014

A soft processor is a processor that is implemented using logic synthesis mainly targeting programmable logic device like FPGA and it becomes a common component for FPGA designs. The supersmall soft processor (small-core) developed at University of Toronto is an unique soft processor because its main concern is very low hardware cost while supporting 32-bit ISA.
With the same concept as small-core, we are developing the ultrasmall soft processor (UltraSmall) based on smallcore. The goal of this project is to implement the smallest 32-bit ISA soft processor while aiming to achieve high performance. We propose UltraSmall and describe its key ideas and implementations. The evaluation results indicate that the hardware cost of UltraSmall is smaller than smallcore in the latest FPGA while achieving 1.8x performance of small-core.
Exploiting entities for query expansion
Authors: Brandão Wladmir Cardoso 
Published: July 2014

A substantial fraction of web search queries contain references to entities, such as persons, organizations, and locations. This signi cant presence of named entities in queries provides an opportunity for web search engines to improve their understanding of the user's information need.
In this thesis, we investigate the entity-oriented query expansion process. Particularly, we propose two novel and effective query expansion approaches that exploit semantic sources of evidence to devise discriminative term features, and machine learning techniques to effectively combine these features in order to rank candidate expansion terms. As a result, not only do we select effective expansion terms, but we also weigh these terms according to their predicted effectiveness. In addition, since our query expansion approaches consider Wikipedia infoboxes as a source of candidate expansion terms, a frequent obstacle is that only about 20% of Wikipedia articles have an infobox. To overcome this problem we propose WAVE, a self-supervised approach to autonomously generate infoboxes for Wikipedia articles.
First, we propose UQEE, an unsupervised entity-oriented query expansion approach, which effectively selects expansion terms using taxonomic features devised by the semantic structure implicitly provided by infobox templates. We show that query expansion using infoboxes presents a better trade-off between retrieval performance and query latency. Moreover, we demonstrate that the automatically generated infoboxes provided by WAVE are as effective as manually generated infoboxes for query expansion. Lastly, we propose L2EE, a learning to rank approach for entity-oriented query expansion, which considers semantic evidence encoded in the content of Wikipedia article fields, and automatically labels training examples proportionally to their observed retrieval effectiveness.
Experiments on three TREC web test collections attest the effectiveness of L2EE, with significant gains compared to UQEE and state-of-the-art pseudo-relevance feedback and entity-oriented pseudo-relevance feedback approaches.
SPSB1 May Have MET Its Match during Breast Cancer Recurrence
Authors: Qin Yuanbo , McAllister Sandra S. 
Published: July 2014

Abstract
Summary: Disease recurrence is the most common cause of death for patients with breast cancer, yet little is known about the molecular mechanisms underlying this process. Using inducible transgenic mouse model systems, Feng and colleagues identified SPSB1 as a determinant of breast cancer recurrence by virtue of its ability to protect tumor cells from apoptosis through c-MET activation. Cancer Discov; 4(7); 760–1. ©2014 AACR.
See related article by Feng et al., p. 790
A Little pRB Can Lead to Big Problems
Authors: Hinds Philip W. 
Published: July 2014

Abstract
Summary: Germline deletion of RB1, the gene encoding the retinoblastoma tumor-suppressor protein pRB, predisposes to eye tumor formation upon loss of the remaining wild-type allele. Many functions affecting cell-cycle control, cell-cycle exit, and numerous other processes involved in the transformed phenotype have been ascribed to pRB, and deregulation of these processes is generally thought to result from complete loss of pRB in both hereditary and sporadic tumors in multiple tissues. Loss of just one allele of RB1 is now shown to lead to replication stress and aneuploidy in both mouse and human cells, and the mechanism through which this haploinsufficient phenotype is achieved may open up new opportunities for interceding both in tumor initiation and in treatment of extant tumors. Cancer Discov; 4(7); 764–5. ©2014 AACR.
See related article by Coschi et al., p. 840
Early Auditory Evoked Potential Is Modulated by Selective Attention and Related to Individual Differences in Visual Working Memory Capacity
Authors: Giuliano Ryan J. , Karns Christina M. , Neville Helen J. , Hillyard Steven A. 
Published: July 2014

Abstract
A growing body of research suggests that the predictive power of working memory (WM) capacity for measures of intellectual aptitude is due to the ability to control attention and select relevant information. Crucially, attentional mechanisms implicated in controlling access to WM are assumed to be domain-general, yet reports of enhanced attentional abilities in individuals with larger WM capacities are primarily within the visual domain. Here, we directly test the link between WM capacity and early attentional gating across sensory domains, hypothesizing that measures of visual WM capacity should predict an individual's capacity to allocate auditory selective attention. To address this question, auditory ERPs were recorded in a linguistic dichotic listening task, and individual differences in ERP modulations by attention were correlated with estimates of WM capacity obtained in a separate visual change detection task. Auditory selective attention enhanced ERP amplitudes at an early latency (ca. 70–90 msec), with larger P1 components elicited by linguistic probes embedded in an attended narrative. Moreover, this effect was associated with greater individual estimates of visual WM capacity. These findings support the view that domain-general attentional control mechanisms underlie the wide variation of WM capacity across individuals.
Predicting a Decadal Shift in North Atlantic Climate Variability Using the GFDL Forecast System
Authors: Msadek Rym , Delworth T. L. , Rosati A. , Anderson W. , Vecchi G. , Chang Y.-S. , Dixon K. , Gudgel R. G. , Stern W. , Wittenberg A. , Yang X. , Zeng F. , Zhang R. , Zhang S. 
Published: July 2014

Abstract
Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.
Projected Changes in Temperature and Precipitation Extremes in China by the CMIP5 Multimodel Ensembles
Authors: Zhou Botao , Wen Qiuzi Han , Xu Ying , Song Lianchun , Zhang Xuebin 
Published: July 2014

Abstract
This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986–2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes [including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p)], is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role.
Ground Clutter Mitigation for Weather Radars Using the Autocorrelation Spectral Density
Authors: Torres Sebastián M. , Warde David A. 
Published: July 2014

Abstract
Radar returns from the ground, known as ground clutter, can contaminate weather signals, often resulting in severely biased meteorological estimates. If not removed, these contaminants may artificially inflate quantitative precipitation estimates and obscure polarimetric and Doppler signatures of weather. A ground-clutter filter is typically employed to mitigate this contamination and provide less biased meteorological-variable estimates. This paper introduces a novel adaptive filter based on the autocorrelation spectral density, which is capable of mitigating the adverse effects of ground clutter without unnecessarily degrading the quality of the meteorological data. The so-called Clutter Environment Analysis using Adaptive Processing (CLEAN-AP) filter adjusts its suppression characteristics in real time to match dynamic atmospheric environments and meets Next Generation Weather Radar (NEXRAD) clutter-suppression requirements.
Ensemble Kalman Filtering with Residual Nudging: An Extension to State Estimation Problems with Nonlinear Observation Operators
Authors: Luo Xiaodong , Hoteit Ibrahim 
Published: July 2014

Abstract
The ensemble Kalman filter (EnKF) is an efficient algorithm for many data assimilation problems. In certain circumstances, however, divergence of the EnKF might be spotted. In previous studies, the authors proposed an observation-space-based strategy, called residual nudging, to improve the stability of the EnKF when dealing with linear observation operators. The main idea behind residual nudging is to monitor and, if necessary, adjust the distances (misfits) between the real observations and the simulated ones of the state estimates, in the hope that by doing so one may be able to obtain better estimation accuracy.
In the present study, residual nudging is extended and modified in order to handle nonlinear observation operators. Such extension and modification result in an iterative filtering framework that, under suitable conditions, is able to achieve the objective of residual nudging for data assimilation problems with nonlinear observation operators. The 40-dimensional Lorenz-96 model is used to illustrate the performance of the iterative filter. Numerical results show that, while a normal EnKF may diverge with nonlinear observation operators, the proposed iterative filter remains stable and leads to reasonable estimation accuracy under various experimental settings.
The Climatology and Characteristics of Rossby Wave Packets Using a Feature-Based Tracking Technique
Authors: Souders Matthew B. , Colle Brian A. , Chang Edmund K. M. 
Published: July 2014

Abstract
This paper describes an objective, track-based climatology of Rossby wave packets (RWPs). NCEP–NCAR reanalysis wind and geopotential height data at 300 hPa every 6 h were spectrally filtered using a Hilbert transform technique under the assumption that RWPs propagate along a waveguide defined by the 14-day running average of the 300-hPa wind. Track data and feature-based descriptive statistics, including area, average intensity, intensity volume (intensity multiplied by area), intensity-weighted centroid position, and velocity, were gathered to describe the interannual, annual, seasonal, and regime-based climatology of RWPs. RWPs have a more pronounced seasonal cycle in the Northern Hemisphere (NH) than the Southern Hemisphere (SH). RWPs are nearly nonexistent in the summer months (June–August; JJA) in the NH, while there is nearly continuous RWP activity downstream of South Africa during austral summer (December–February; DJF). Interannual variability in RWP frequency and intensity in the Northern Hemisphere is found to be strongly connected with the large-scale flow regimes such as El Niño–Southern Oscillation and the Arctic Oscillation. Enhanced RWP activity is also found to coherently propagate from the Pacific into the Atlantic on average when the Arctic Oscillation switches from a positive to a negative phase. No significant long-term (~30 yr) trend in RWP frequency, activity, or amplitude is found.
The Impacts of Representing the Correlation of Errors in Radar Data Assimilation. Part I: Experiments with Simulated Background and Observation Estimates
Authors: Jacques Dominik , Zawadzki Isztar 
Published: July 2014

Abstract
In radar data assimilation, statistically optimal analyses are sought by minimizing a cost function in which the variance and covariance of background and observation errors are correctly represented. Radar observations are particular in that they are often available at spatial resolution comparable to that of background estimates. Because of computational constraints and lack of information, it is impossible to perfectly represent the correlation of errors. In this study, the authors characterize the impact of such misrepresentations in an idealized framework where the spatial correlations of background and observation errors are each described by a homogeneous and isotropic exponential decay. Analyses obtained with perfect representation of correlations are compared to others obtained by neglecting correlations altogether. These two sets of analyses are examined from a theoretical and an experimental perspective. The authors show that if the spatial correlations of background and observation errors are similar, then neglecting the correlation of errors has a small impact on the quality of analyses. They suggest that the sampling noise, related to the precision with which analysis errors may be estimated, could be used as a criterion for determining when the correlations of errors may be omitted. Neglecting correlations altogether also yields better analyses than representing correlations for only one term in the cost function or through the use of data thinning. These results suggest that the computational costs of data assimilation could be reduced by neglecting the correlations of errors in areas where dense radar observations are available.
Systematic design of transmitter and receiver architectures for flexible filter bank multi-carrier signals
Authors: Gutiérrez Esteban , López-Salcedo José A , Seco-Granados Gonzalo 
Published: July 2014

Abstract
Multi-carrier (MC) signaling is currently in the forefront of a myriad of systems, either wired or wireless, due to its high spectral efficiency, simple equalization, and robustness in front of multipath and narrowband interference sources. Despite its widespread deployment, the design of efficient architectures for MC systems becomes a challenging task when adopting filter bank multi-carrier (FBMC) modulation due to the inclusion of band-limited shaping pulses into the signal model. The reason to employ these pulses is the numerous improvements they offer in terms of performance, such as providing higher spectral confinement and no frequency overlap between adjacent subcarriers. These attributes lead to a reduced out-of-band power emission and a higher effective throughput. The latter is indeed possible by removing the need of cyclic prefix, which is in charge of preserving orthogonality among subcarriers in conventional MC systems. Nevertheless, the potential benefits of FBMC modulations are often obscured when it comes to an implementation point of view. In order to circumvent this limitation, the present paper provides a unified framework to describe all FBMC signals in which both signal design and implementation criteria are explicitly combined. In addition to this, we introduce the concept of flexible FBMC signals that, unlike their traditional MC counterparts, do not impose restrictions on the signal parameters (i.e., symbol rate, carrier spacing, or sampling frequency). Moreover, our framework also proposes a methodology that overcomes the implementation issues that characterize FBMC systems and allows us to derive simple, efficient, and time-invariant transmitter and receiver architectures.
Factors influencing lengths of stay in the intensive care unit for surviving trauma patients: a retrospective analysis of 30,157 cases
Authors: Böhmer Andreas B , Just Katja S , Lefering Rolf , Paffrath Thomas , Bouillon Bertil , Joppich Robin , Wappler Frank , Gerbershagen Mark U 
Published: July 2014

Abstract
Introduction
There are many potential influencing factors that affect the duration of intensive care treatment for patients who have survived multiple trauma. Yet the respective factors’ relevance to ICU length of stay (LOS) has been rarely studied. Thus, the aim of the present study was to investigate to what extent specific factors influence ICU LOS in surviving trauma patients.

Methods
We retrospectively analyzed a dataset of 30,157 surviving trauma patients from the TraumaRegister DGU® who were older than six years of age and received subsequent intensive care treatment for more than one day, from 2002 to 2011. Univariate analysis and multiple linear regression analysis were used to examine 25 categorical pre- and post-trauma parameters.

Results
Univariate analysis confirmed the impact of all analyzed factors. In subsequent multiple linear regression analyses, coefficients ranged from -1.3 to +8.2 days. The factors that influenced the prolongation of ICU LOS most were renal failure (+8.1 days), sepsis (+7.8 days) and respiratory failure (+4.9 days). Patients spent one additional day in the ICU for every 5 additional points on the Injury Severity Score (regression coefficient +0.2 per point). Furthermore, massive transfusion (+3.3 days), invasive ventilation (+3.1 days), and an initial Glasgow Coma Scale score ≤8 (+3.0 days) had a significant impact on ICU LOS. The coefficient of determination for the model was 44% (R2).

Conclusions
Treatment regimens, as well as secondary effects and complications of trauma and intensive care treatment, prolong ICU LOS more than the mechanism of trauma or pre-trauma patient conditions. Successful prevention of complicated courses of illness, such as sepsis and renal and respiratory failure, could significantly abbreviate the ICU stay in trauma patients. Therefore, the staff’s attention should be focused on preventive strategies.