bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailoring nonlinear optical properties of Bi2Se3 through ion irradiation
Authors: Tan Yang , Guo Zhinan , Shang Zhen , Liu Fang , Böttger Roman , Zhou Shengqiang , Shao Jundong , Yu Xuefeng , Zhang Han , Chen Feng 
Published: February 2016

AbstractThe nonlinear optical property of topological insulator bismuth selenide (Bi2Se3) is found to be well-tailored through ion irradiation by intentionally introducing defects. The increase of the optical modulation depth sensitively depends on the careful selection of the irradiation condition. By implementing the ion irradiated Bi2Se3 film as an optical saturable absorber device for the Q-switched wave-guide laser, an enhanced laser performance has been obtained including narrower pulse duration and higher peak power. Our work provides a new approach of tailoring the nonlinear optical properties of materials through ion irradiation, a well-developed chip-technology, which could find wider applicability to other layered two-dimensional materials beyond topological insulators, such as graphene, MoS2, black phosphours etc.
Thermal and mechanical stability of retained austenite in 1%C bearing steels with varying Si contents
Authors: Sourmail T. , Millot-Méheux M. 
Published: February 2016

The present study is concerned with thermal and mechanical stability of retained austenite (RA) obtained in high-carbon, high-silicon steels after quenching and tempering. Through the investigation of three different alloy compositions with Si content of ∼0.3, 0.6 and 1.2 wt-%, it is shown that increasing silicon dramatically increases thermal stability. Compression tests on quenched and tempered specimens indicate that RA was also mechanically more stable when present in higher silicon steels. This paper is part of a Themed Issue on Recent developments in bearing steels.
Host trait combinations drive abundance and canopy distribution of atmospheric bromeliad assemblages
Authors: Chaves Cleber Juliano Neves , Dyonisio Júlio César , Rossatto Davi Rodrigo 
Published: February 2016

Abstract
Epiphytes are strongly dependent on the conditions created by their host's traits and a certain degree of specificity is expected between them, even if these species are largely abundant in a series of tree hosts of a given environment, as in the case of atmospheric bromeliads. Despite their considerable abundance in these environments, we hypothesize that stochasticity alone cannot explain the presence and abundance of atmospheric bromeliads on host trees, since host traits could have a greater influence on the establishment of these bromeliads. We used secondary and reforested seasonal forests and three distinct silvicultures to test whether species richness, phylogenetic diversity and functional diversity of trees can predict the differential presence, abundance and distribution of atmospheric bromeliads on hosts. We compared the observed parameters of their assemblage with null models and performed successive variance hierarchic partitions of abundance and distribution of the assemblage to detect the influence of multiple traits of the tree hosts. Our results do not indicate direct relationships between the abundance of atmospheric bromeliads and phylogenetic or functional diversity of trees, but instead indicate that bromeliads occurred on fewer tree species than expected by chance. We distinguished functional tree patterns that can improve or reduce the abundance of atmospheric bromeliads, and change their distribution on branches and trunk. While individual tree traits are related to increased abundance, species traits are related to the canopy distribution of atmospheric bromeliad assemblages. A balance among these tree functional patterns drives the atmospheric bromeliad assemblage of the forest patches.
SMART on FHIR: a standards-based, interoperable apps platform for electronic health records
Authors: Mandel Joshua C , Kreda David A , Mandl Kenneth D , Kohane Isaac S , Ramoni Rachel B 
Published: February 2016

Abstract
Objective In early 2010, Harvard Medical School and Boston Children’s Hospital began an interoperability project with the distinctive goal of developing a platform to enable medical applications to be written once and run unmodified across different healthcare IT systems. The project was called Substitutable Medical Applications and Reusable Technologies (SMART).
Methods We adopted contemporary web standards for application programming interface transport, authorization, and user interface, and standard medical terminologies for coded data. In our initial design, we created our own openly licensed clinical data models to enforce consistency and simplicity. During the second half of 2013, we updated SMART to take advantage of the clinical data models and the application-programming interface described in a new, openly licensed Health Level Seven draft standard called Fast Health Interoperability Resources (FHIR). Signaling our adoption of the emerging FHIR standard, we called the new platform SMART on FHIR.
Results We introduced the SMART on FHIR platform with a demonstration that included several commercial healthcare IT vendors and app developers showcasing prototypes at the Health Information Management Systems Society conference in February 2014. This established the feasibility of SMART on FHIR, while highlighting the need for commonly accepted pragmatic constraints on the base FHIR specification.
Conclusion In this paper, we describe the creation of SMART on FHIR, relate the experience of the vendors and developers who built SMART on FHIR prototypes, and discuss some challenges in going from early industry prototyping to industry-wide production use.
Effects of an e-Prescribing interface redesign on rates of generic drug prescribing: exploiting default options
Authors: Malhotra Sameer , Cheriff Adam D , Gossey J Travis , Cole Curtis L , Kaushal Rainu , Ancker Jessica S 
Published: February 2016

Abstract
Objective Increasing the use of generic medications could help control medical costs. However, educational interventions have limited impact on prescriber behavior, and e-prescribing alerts are associated with high override rates and alert fatigue. Our objective was to evaluate the effect of a less intrusive intervention, a redesign of an e-prescribing interface that provides default options intended to “nudge” prescribers towards prescribing generic drugs.
Methods This retrospective cohort study in an academic ambulatory multispecialty practice assessed the effects of customizing an e-prescribing interface to substitute generic equivalents for brand-name medications during order entry and allow a one-click override to order the brand-name medication.
Results Among drugs with generic equivalents, the proportion of generic drugs prescribed more than doubled after the interface redesign, rising abruptly from 39.7% to 95.9% (a 56.2% increase; 95% confidence interval, 56.0–56.4%; P  &lt; .001). Before the redesign, generic drug prescribing rates varied by therapeutic class, with rates as low as 8.6% for genitourinary products and 15.7% for neuromuscular drugs. After the redesign, generic drug prescribing rates for all but four therapeutic classes were above 90%: endocrine drugs, neuromuscular drugs, nutritional products, and miscellaneous products.
Discussion Changing the default option in an e-prescribing interface in an ambulatory care setting was followed by large and sustained increases in the proportion of generic drugs prescribed at the practice.
Conclusions Default options in health information technology exert a powerful effect on user behavior, an effect that can be leveraged to optimize decision making.
Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation
Authors: Evans R Scott , Benuzillo Jose , Horne Benjamin D , Lloyd James F , Bradshaw Alejandra , Budge Deborah , Rasmusson Kismet D , Roberts Colleen , Buckway Jason , Geer Norma , Garrett Teresa , Lappé Donald L 
Published: February 2016

Abstract
Objective Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients.
Methods Dictated free-text reports from the previous 24 h were analyzed each day with natural language processing (NLP), to help improve the early identification of hospitalized patients with HF. A second application that uses an Intermountain Healthcare-developed predictive score to determine each HF patient’s risk for 30-day hospital readmission and 30-day mortality was also developed. That information was included in an identification and predictive risk report, which was evaluated at a 354-bed hospital that treats high-risk HF patients.
Results The addition of NLP-identified HF patients increased the identification score’s sensitivity from 82.6% to 95.3% and its specificity from 82.7% to 97.5%, and the model’s positive predictive value is 97.45%. Daily multidisciplinary discharge planning meetings are now based on the information provided by the HF identification and predictive report, and clinician’s review of potential HF admissions takes less time compared to the previously used manual methodology (10 vs 40 min). An evaluation of the use of the HF predictive report identified a significant reduction in 30-day mortality and a significant increase in patient discharges to home care instead of to a specialized nursing facility.
Conclusions Using clinical decision support to help identify HF patients and automatically calculating their 30-day all-cause readmission and 30-day mortality risks, coupled with a multidisciplinary care process pathway, was found to be an effective process to improve HF patient identification, significantly reduce 30-day mortality, and significantly increase patient discharges to home care.
A method for modeling co-occurrence propensity of clinical codes with application to ICD-10-PCS auto-coding
Authors: Subotin Michael , Davis Anthony R 
Published: February 2016

Abstract
Objective Natural language processing methods for medical auto-coding, or automatic generation of medical billing codes from electronic health records, generally assign each code independently of the others. They may thus assign codes for closely related procedures or diagnoses to the same document, even when they do not tend to occur together in practice, simply because the right choice can be difficult to infer from the clinical narrative.
Methods We propose a method that injects awareness of the propensities for code co-occurrence into this process. First, a model is trained to estimate the conditional probability that one code is assigned by a human coder, given than another code is known to have been assigned to the same document. Then, at runtime, an iterative algorithm is used to apply this model to the output of an existing statistical auto-coder to modify the confidence scores of the codes.
Results We tested this method in combination with a primary auto-coder for International Statistical Classification of Diseases-10 procedure codes, achieving a 12% relative improvement in F -score over the primary auto-coder baseline. The proposed method can be used, with appropriate features, in combination with any auto-coder that generates codes with different levels of confidence.
Conclusions The promising results obtained for International Statistical Classification of Diseases-10 procedure codes suggest that the proposed method may have wider applications in auto-coding.
The Association Between Chronic Pain and Cardiac Disease
Authors: Fayaz Alan , Watt Hilary C. , Langford Richard M. , Donaldson Liam J. 
Published: February 2016

Objectives:
Chronic pain may increase the risk of cardiac disease, but the extent to which confounding variables account for this association has yet to be satisfactorily established. This study aims to examine the possibility of an independent association between these 2 variables.

Methods:
We applied logistic regression analysis to data from 8596 adults surveyed in a population study of the health of the population of England. The association between cardiac disease (angina and/or myocardial infarction) and chronic pain (pain lasting >3 months) was explored, taking account of 10 potentially confounding variables including the regular use of nonsteroidal anti-inflammatory drugs.

Results:
Participants reporting chronic pain (n=3023) were more likely to experience cardiac disease than those without pain: odds ratio (OR), 1.55; 95% confidence interval (CI), 1.15-2.07. Subsets of participants fulfilling various criteria for high-intensity chronic pain demonstrated stronger associations with cardiac disease suggesting a “dose-response” element to the relationship: chronic widespread pain (OR, 3.3; 95% CI, 1.42-7.68); higher-disability chronic pain (OR, 2.35; 95% CI, 1.71-3.23); and higher average chronic pain score (OR, 1.95; 95% CI, 1.40-2.71). Adjustment for regular prescription of nonsteroidal anti-inflammatory drugs did not reduce the association of chronic pain with cardiac disease.

Discussion:
Patients reporting chronic pain, in particular those most severely affected, may be at significantly increased risk of cardiac disease. Future studies should focus on determining whether reducing the impact of chronic pain can improve cardiac health.
Multiple Levels of Suffering
Authors: Mathur Vani A. , Kiley Kasey B. , Haywood Carlton , Bediako Shawn M. , Lanzkron Sophie , Carroll C. Patrick , Buenaver Luis F. , Pejsa Megan , Edwards Robert R. , Haythornthwaite Jennifer A. , Campbell Claudia M. 
Published: February 2016

Objective:
People living with sickle cell disease (SCD) experience severe episodic and chronic pain and frequently report poor interpersonal treatment within health-care settings. In this particularly relevant context, we examined the relationship between perceived discrimination and both clinical and laboratory pain.

Methods:
Seventy-one individuals with SCD provided self-reports of experiences with discrimination in health-care settings and clinical pain severity, and completed a psychophysical pain testing battery in the laboratory.

Results:
Discrimination in health-care settings was correlated with greater clinical pain severity and enhanced sensitivity to multiple laboratory-induced pain measures, as well as stress, depression, and sleep. After controlling for relevant covariates, discrimination remained a significant predictor of mechanical temporal summation (a marker of central pain facilitation), but not clinical pain severity or suprathreshold heat pain response. Furthermore, a significant interaction between experience with discrimination and clinical pain severity was associated with mechanical temporal summation; increased experience with discrimination was associated with an increased correlation between clinical pain severity and temporal summation of pain.

Discussion:
Perceived discrimination within health-care settings was associated with pain facilitation. These findings suggest that discrimination may be related to increased central sensitization among SCD patients, and more broadly that health-care social environments may interact with pain pathophysiology.
16S rRNA amplicon sequencing for epidemiological surveys of bacteria in wildlife: the importance of cleaning post-sequencing data before estimating positivity, prevalence and co-infection
Authors: Galan Maxime , Razzauti Maria , Bard Emilie , Bernard Maria , Brouat Carine , Charbonnel Nathalie , Dehne-Garcia Alexandre , Loiseau Anne , Tatard Caroline , Tamisier Lucie , Vayssier-Taussat Muriel , Vignes Helene , Cosson Jean François 
Published: February 2016

SummaryHuman impact on natural habitats is increasing the complexity of human-wildlife interfaces and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents collected from 24 villages in Senegal, including 208Mus musculus domesticus, 189Rattus rattus, 93Mastomys natalensisand 221Mastomys erythroleucus.Seven major genera of pathogenic bacteria were detected in their spleens:Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, StreptobacillusandOrientia. The last five of these genera have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable for continuous pathogen surveillance in the context of disease monitoring programs.
Validation of a habitat suitability index for oyster restoration
Authors: Theuerkauf Seth J. , Lipcius Romuald N. 
Published: February 2016

AbstractHabitat suitability index (HSI) models provide spatially explicit information on the capacity of a given habitat to support a species of interest, and their prevalence has increased dramatically in recent years. Despite caution that the reliability of HSIs must be validated using independent, quantitative data, most HSIs intended to inform terrestrial and marine species management remain unvalidated. Furthermore, of the eight HSI models developed for eastern oyster (Crassostrea virginica) restoration and fishery production, none has been validated. Consequently, we developed, calibrated, and validated an HSI for the eastern oyster to identify optimal habitat for restoration in a tributary of Chesapeake Bay, the Great Wicomico River (GWR). The GWR harbors an unparalleled, restored oyster population, and therefore serves as an excellent model system for assessing the validity of the HSI. The HSI was derived from GIS layers of bottom type, salinity, and water depth (surrogate for dissolved oxygen), and was tested using live adult oyster density data from a survey of high vertical relief reefs (HRR) and low vertical relief reefs (LRR) in the sanctuary network. Live adult oyster density was a statistically significant sigmoid function of the HSI, which validates the HSI as a robust predictor of suitable oyster reef habitat for rehabilitation or restoration. In addition, HRR had on average 103-116 more adults m-2than LRR at a given level of the HSI. For HRR, HSI values ≥0.3 exceeded the accepted restoration target of 50 live adult oysters m−2. For LRR, the HSI was generally able to predict live adult oyster densities that meet or exceed the target at HSI values ≥0.3. The HSI indicated that there remain large areas of suitable habitat for restoration in the GWR. This study provides a robust framework for HSI model development and validation, which can be refined and applied to other systems and previously developed HSIs to improve the efficacy of native oyster restoration.
Aging shapes the population-mean and ‐dispersion of gene expression in human brains
Authors: Brinkmeyer-Langford Candice L. , Guan Jinting , Ji Guoli , Cai James J. 
Published: February 2016

AbstractHuman aging is associated with cognitive decline and an increased risk of neurodegenerative disease. Our objective for this study was to evaluate potential relationships between age and variation in gene expression across different regions of the brain. We analyzed the Genotype-Tissue Expression (GTEx) data from 54 and 101 tissue samples across 13 brain regions in post-mortem donors of European descent aged between 20 and 70 years at death. After accounting for the effects of covariates and hidden confounding factors, we identified 1,446 protein-coding genes whose expression in one or more brain regions is correlated with chronological age at a false discovery rate of 5%. These genes are involved in various biological processes including apoptosis, mRNA splicing, amino acid biosynthesis, and neurotransmitter transport. The distribution of these genes among brain regions is uneven, suggesting variable regional responses to aging. We also found that the aging response of many genes, e.g.,TP37andC1QA, depends on individuals’ genotypic backgrounds. Finally, using dispersion-specific analysis, we identified genes such asIL7R,MS4A4E, andTERF1/TERF2whose expressions are differentially dispersed by aging, i.e., variances differ between age groups. Our results demonstrate that age-related gene expression is brain region-specific, genotype-dependent, and associated with both mean and dispersion changes. Our findings provide a foundation for more sophisticated gene expression modeling in the studies of age-related neurodegenerative diseases.
Cell Segmentation with Random Ferns and Graph-cuts
Authors: Browet A. , De Vleeschouwer C. , Jacques L. , Mathiah N. , Saykali B. , Migeotte I. 
Published: February 2016

ABSTRACTThe progress in imaging techniques have allowed the study of various aspect of cellular mechanisms. To isolate individual cells in live imaging data, we introduce an elegant image segmentation framework that effectively extracts cell boundaries, even in the presence of poor edge details. Our approach works in two stages. First, we estimate pixel interior/border/exterior class probabilities using random ferns. Then, we use an energy minimization framework to compute boundaries whose localization is compliant with the pixel class probabilities. We validate our approach on a manually annotated dataset.