bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk of breast cancer by prior screening results among women participating in BreastScreen Norway
Authors: Lilleborge Marie , Falk Ragnhild S. , Russnes Hege , Sauer Torill , Ursin Giske , Hofvind Solveig 
Published: June 2019

BackgroundA premalignant lesion in the breast is associated with an increased risk of breast cancer. The aim of this article was to identify women with an increased risk of breast cancer based on prior screening results (PSRs).MethodsThis registry‐based cohort study followed women who participated in the organized breast cancer screening program in Norway, BreastScreen Norway, in 1995‐2016. Incidence rates and incidence rate ratios were used to estimate absolute and relative risks of breast cancer associated with PSRs. Histopathological characteristics of subsequent breast cancers were presented by PSRs.ResultsThis study included 762,643 women with up to 21 years of follow‐up. In comparison with negatively screened women, increased incidence rate ratios of 1.8, 2.0, 2.9, and 3.8 were observed after negative additional imaging, for benign biopsy, for hyperplasia with atypia, and for carcinoma in situ, respectively. Subsequent breast cancers did not differ in tumor diameter or histological grade, whereas the proportion of lymph node–positive breast cancers decreased as the presumed malignancy potential of PSRs increased.ConclusionsThe risk of subsequent breast cancer increased with the presumed malignancy potential of PSRs, whereas the tumor characteristics of subsequent cancers did not differ except for the lymph node status. Women with screen‐detected benign lesions or hyperplasia with atypia might benefit from more frequent screening.
Augmented resistive immersed surfaces valve model for the simulation of cardiac hemodynamics with isovolumetric phases
Authors: This Alexandre , Boilevin‐Kayl Ludovic , Fernández Miguel A. , Gerbeau Jean‐Frédéric 
Published: June 2019

AbstractIn order to reduce the complexity of heart hemodynamics simulations, uncoupling approaches are often considered for the modeling of the immersed valves as an alternative to complex fluid‐structure interaction (FSI) models. A possible shortcoming of these simplified approaches is the difficulty to correctly capture the pressure dynamics during the isovolumetric phases. In this work, we propose an enhanced resistive immersed surfaces (RIS) model of cardiac valves, which overcomes this issue. The benefits of the model are investigated and tested in blood flow simulations of the left heart where the physiological behavior of the intracavity pressure during the isovolumetric phases is recovered without using fully coupled fluid‐structure models and without important alteration of the associated velocity field.
Bioequivalence of Ertugliflozin/Metformin Fixed‐Dose Combination Tablets and Coadministration of Respective Strengths of Individual Components
Authors: Dawra Vikas Kumar , Liang Yali , Wei Hua , Pelletier Kathleen , Shi Haihong , Hickman Anne , Bass Almasa , Terra Steven G. , Zhou Susan , Krishna Rajesh , Sahasrabudhe Vaishali 
Published: June 2019

AbstractA fixed‐dose combination (FDC) of ertugliflozin, a selective sodium‐glucose cotransporter 2 inhibitor, and immediate‐release metformin is approved for the treatment of type 2 diabetes mellitus in the United States and European Union. Four open‐label, randomized, 2‐period, single‐dose, crossover studies were conducted under fasted conditions in healthy subjects to demonstrate bioequivalence of the ertugliflozin/metformin FDC tablets and coadministration of the individual components at respective strengths. In each study, 32 or 34 subjects received an ertugliflozin/metformin FDC tablet (2.5 mg/500 mg, 7.5 mg/850 mg, or 7.5 mg/1000 mg) and the respective doses of individual components (ertugliflozin with US‐ or EU‐sourced metformin [Glucophage]). Plasma samples for ertugliflozin and metformin concentrations were collected for 72 hours in each period. For both ertugliflozin and metformin, the 90% confidence intervals for the adjusted geometric mean ratio (FDC : coadministration) for area under the plasma concentration–time profile from time zero extrapolated to infinity and maximum observed plasma concentration were within acceptance criteria for bioequivalence. The majority of adverse events were mild in intensity. The studies demonstrated that each strength of FDC tablet is bioequivalent to respective doses of coadministered individual components, supporting that safety and efficacy can be bridged to the individual components used in phase 3 studies evaluating ertugliflozin in combination with metformin.
Calling Star Alleles With Stargazer in 28 Pharmacogenes With Whole Genome Sequences
Authors: Lee Seung‐been , Wheeler Marsha M. , Thummel Kenneth E. , Nickerson Deborah A. 
Published: June 2019

Variation in the enzymatic activity of pharmacogenes is defined by star alleles (haplotypes) comprised of single‐nucleotide variants, small insertion‐deletions, and large structural variants. We recently developed Stargazer, a next‐generation sequencing‐based tool to call star alleles for the clinically important CYP2D6 gene. Here, we present the utility of extending Stargazer to call star alleles for 28 pharmacogenes using whole genome sequencing (WGS) data. We applied Stargazer to WGS data from 70 ethnically diverse samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM). These reference samples were extensively characterized by GeT‐RM using multiple pharmacogenetic testing assays. In all 28 genes, Stargazer recalled 100% of star alleles (N = 92) present in GeT‐RM's consensus genotypes (N = 1,559). Stargazer also detected star alleles not previously reported by GeT‐RM, including complex structural variants. Our results demonstrate that combining WGS data and Stargazer enables automated, accurate, and comprehensive genotyping of pharmacogenes in the human genome.
Estrogen‐Containing Oral Contraceptives Are Associated With Polycystic Liver Disease Severity in Premenopausal Patients
Authors: van Aerts René M.M. , Bernts Lucas H.P. , Gevers Tom J.G. , Kievit Wietske , Koopmans Lisanne , Nieboer Theodoor E. , Nevens Frederik , Drenth Joost P.H. 
Published: June 2019

The association between estrogen‐containing oral contraceptives and history of pregnancies with disease severity in women with polycystic liver disease (PLD) is unclear. We performed a cross‐sectional cohort study to assess this association by selecting female patients with PLD of which imaging was available prior to any liver volume‐reducing therapy. Patients received a questionnaire to collect detailed information on estrogen use and pregnancies. Preplanned subgroup analyses were performed on premenopausal and postmenopausal patients. The questionnaire was returned by 287 of 360 selected patients (80%). There was no significant association between estrogen‐containing oral contraceptives and height‐adjusted total liver volume (hTLV) in the total group (P = 0.06) and postmenopausal subgroup (P = 0.7). By contrast, each year of exposure corresponds with a 1.45% higher hTLV (P = 0.02) in the premenopausal subgroup, equivalent to a 15.5% higher hTLV for every 10 years of use. Pregnancy duration was not associated with hTLV. In conclusion, patients with PLD should avoid exogenous estrogens.
Competition in technology and innovation, motivation crowding, and environmental policy
Authors: Graafland Johan 
Published: June 2019

AbstractThis paper investigates the theoretical and empirical relevance of motivation crowding theory for owner–managers' motivation towards sustainable development. Motivation crowding theory has argued that external pressures enforce (crowd in) moral motivation if these pressures are perceived as supportive. On the basis of this theory, we conjecture that a competitive environment that is characterized by a high intensity of competition on innovation will crowd in moral motivation towards sustainable development if owner–managers believe that environmental policy practices increase the innovative capability of their company. Test results on survey data filled out by 650 owner–managers support this hypothesis. These results imply that policy makers, who aim at stimulating innovation as well as sustainable development, should inform managers about the innovation‐enhancing effects of environmental policy practices.
A pairing‐free identity‐based handover AKE protocol with anonymity in the heterogeneous wireless networks
Authors: Lei Liting , Zhang Wenfang , Wang Yu , Wang Xiaomin 
Published: June 2019

SummaryNowadays, seamless roaming service in heterogeneous wireless networks attracts more and more attention. When a mobile user roams into a foreign domain, the process of secure handover authentication and key exchange (AKE) plays an important role to verify the authenticity and establish a secure communication between the user and the access point. Meanwhile, to prevent the user's current location and moving history information from being tracked, privacy preservation should be also considered. However, existing handover AKE schemes have more or less defects in security aspects or efficiency. In this paper, a secure pairing‐free identity‐based handover AKE protocol with privacy preservation is proposed. In our scheme, users' temporary identities will be used to conceal their real identities during the handover process, and the foreign server can verify the legitimacy of the user with the home server's assistance. Besides, to resist ephemeral private key leakage attack, the session key is generated from the static private keys and the ephemeral private keys together. Security analysis shows that our protocol is provably secure in extended Canetti‐Krawczyk (eCK) model under the computational Diffie‐Hellman (CDH) assumption and can capture desirable security properties including key‐compromise impersonation resistance, ephemeral secrets reveal resistance, strong anonymity, etc. Furthermore, the efficiency of our identity‐based protocol is improved by removing pairings, which not only simplifies the complex management of public key infrastructure (PKI) but also reduces the computation overhead of ID‐based cryptosystem with pairings. It is shown that our proposed handover AKE protocol provides better security assurance and higher computational efficiency for roaming authentication in heterogeneous wireless networks.
An effective back‐off selection technique for reliable beacon reception in VANETs
Authors: Shah Syed Adeel Ali , Ahmed Ejaz , Ahsan Qureshi Muhammad , Jan Sadeeq , MD Noor Rafidah 
Published: June 2019

SummaryIn safety‐critical scenarios, reliable reception of beacons transmitted by a subject vehicle is critical to avoid vehicle collision. According to the employed contention window sizes in IEEE 802.11p, beacons are transmitted with a small contention window size. As a result, multiple vehicles contend for the shared channel access by selecting the same back‐off slot. This is a perfect recipe for synchronous collisions wherein reliable beacon delivery cannot be guaranteed for any vehicle. We consider the problem of selecting the back‐off slots from the current contention window to provide reliable delivery of beacons transmitted by a subject vehicle to its neighbors. Given a safety scenario, we propose a Pseudo‐Random Number Generator (PRNG)‐inspired back‐off selection (PBS) technique. The proposed technique works on the hypothesis that synchronous collisions of beacons transmitted by a subject vehicle can be reduced if all its neighbors select different back‐off slots (ie, not the back‐off slot selected by the subject vehicle). The discrete‐event simulations demonstrate that PBS can increase the overall message reception from a subject vehicle, in comparison with the uniform random probability back‐off selection in IEEE 802.11p.
Prognostic impact of Framingham heart failure criteria in heart failure with preserved ejection fraction
Authors: Löfström Ulrika , Hage Camilla , Savarese Gianluigi , Donal Erwan , Daubert Jean‐Claude , Lund Lars H. , Linde Cecilia 
Published: June 2019

AbstractAimsThis study aims to assess prognostic impact of Framingham criteria for heart failure (FC‐HF) in patients with stable heart failure (HF) with preserved ejection fraction (HFpEF).Methods and resultsIn the prospective Karolinska‐Rennes (KaRen) study, we assessed stable HFpEF patients after an acute HF episode. We evaluated associations between the four descriptive models of HFpEF and the composite endpoint of all‐cause mortality and HF hospitalization. The descriptive models were FC‐HF alone, FC‐HF + natriuretic peptides (NPs) according to the PARAGON trial, FC‐HF + NPs + echocardiographic HFpEF criteria according to European Society of Cardiology HF guidelines, and FC‐HF + NPs + echocardiographic criteria according to the PARAGON trial. Out of the 539 patients enrolled in KaRen, 438 returned for the stable state revisit after 4–8 weeks, 13 (2.4%) patients died before the planned follow‐up, and 88 patients (16%) declined or were unable to return. Three hundred ninety‐nine patients have FC registered at follow‐up, and among these, the four descriptive models were met in 107 (27%), 82 (22%), 61 (21%), and 69 (22%) patients, and not met in 292 (73%). The 107 patients that had FC‐HF at stable state (descriptive model 1) could also be part of the other models because all patients in models 1–4 had to fulfil the FC‐HF. The patients in model 0 did not fulfil the criteria for FC‐HF but could have single FC. Of single FC, only pleural effusion predicted the endpoint [hazard ratio (HR) 3.38, 95% confidence interval (CI) 1.47–7.76, P = 0.004]. Patients without FC‐HF had better prognosis than patients meeting FC‐HF. The unadjusted associations between the four HFpEF descriptive models and the endpoint were HR 1.54, 95% CI 1.14–2.09, P = 0.005; HR 1.71, 95% CI 1.24–2.36, P = 0.002; HR 1.95, 95% CI 1.36–2.81, P = 0.001; and HR 2.05, 95% CI 1.45–2.91, P < 0.001, for descriptive models 1–4, respectively. No descriptive model independently predicted the endpoint.ConclusionsIn ambulatory HFpEF patients, a quarter met FC‐HF, while most met NP and echocardiography criteria for HF. Residual FC‐HF tended to be associated with increased risk for mortality and HF hospitalization, further strengthened by NPs and echocardiographic criteria, highlighting its role in clinical risk assessment.
Design and optimization of a fused‐silica microfluidic device for separation of trivalent lanthanides by isotachophoresis
Authors: Bottenus Danny , Branch Shirmir , Lackey Hope , Ivory Cornelius , Katalenich Jeff , Clark Sue , Lines Amanda 
Published: June 2019

AbstractElemental analysis of rare earth elements is essential in a variety of fields including environmental monitoring and nuclear safeguards; however, current techniques are often labor intensive, time consuming, and/or costly to perform. The difficulty arises in preparing samples, which requires separating the chemically and physically similar lanthanides. However, by transitioning these separations to the microscale, the speed, cost, and simplicity of sample preparation can be drastically improved. Here, all fourteen non‐radioactive lanthanides (lanthanum through lutetium minus promethium) are separated by ITP for the first time in a serpentine fused‐silica microchannel (70 µm wide × 70 µm tall × 33 cm long) in <10 min at voltages ≤8 kV with limits of detection on the order of picomoles. This time includes the 2 min electrokinetic injection time at 2 kV to load sample into the microchannel. The final leading electrolyte consisted of 10 mM ammonium acetate, 7 mM α‐hydroxyisobutyric acid, 1% polyvinylpyrrolidone, and the final terminating electrolyte consisted of 10 mM acetic acid, 7 mM α‐hydroxyisobutyric acid, and 1% polyvinylpyrrolidone. Electrophoretic electrodes are embedded in the microchip reservoirs so that voltages can be quickly applied and switched during operation. The limits of detection are quantified using a commercial capacitively coupled contactless conductivity detector (C4D) to calculate ITP zone lengths in combination with ITP theory. Optimization of experimental procedures and reproducibility based on statistical analysis of subsequent experimental results are addressed. Percent error values in band length and conductivity are ≤8.1 and 0.37%, respectively.
Mathematical model to reduce loop mediated isothermal amplification (LAMP) false‐positive diagnosis
Authors: Schneider Lindsay , Blakely Hannah , Tripathi Anubhav 
Published: June 2019

AbstractLoop mediated isothermal amplification (LAMP) is a nucleic acid amplification technique performed under isothermal conditions. The output of this amplification technique includes multiple different sizes of deoxyribonucleic acid (DNA) structures which are identified by a banding pattern on gel electrophoresis plots. Although this is a specific amplification technique, the complexity of the primer design and amplification still lead to the issue of obtaining false‐positive results, especially when a positive reading is determined solely by whether there is any banding pattern in the gel electrophoresis plot. Here, we first performed extensive LAMP experiments and evaluated the DNA structures using microchip electrophoresis. We then developed a mathematical model derived from the various components that make up an entire LAMP structure to predict the full LAMP structure size in base pairs. This model can be implemented by users to make predictions for specific, DNA size dependent, banding patterns on their gel electrophoresis plots. Each prediction is specific to the target sequence and primers used and therefore reduces incorrect diagnosis errors through identifying true‐positive and false‐positive results. This model was accurately tested with multiple primer sets in house and was also translatable to different DNA and RNA types in previously published literature. The mathematical model can ultimately be used to reduce false‐positive LAMP diagnosis errors for applications ranging from tuberculosis diagnostics to E. coli to numerous other infectious diseases.
Stripe‐based fragility analysis of multispan concrete bridge classes using machine learning techniques
Authors: Mangalathu Sujith , Jeon Jong‐Su 
Published: June 2019

SummaryA framework for the generation of bridge‐specific fragility curves utilizing the capabilities of machine learning and stripe‐based approach is presented in this paper. The proposed methodology using random forests helps to generate or update fragility curves for a new set of input parameters with less computational effort and expensive resimulation. The methodology does not place any assumptions on the demand model of various components and helps to identify the relative importance of each uncertain variable in their seismic demand model. The methodology is demonstrated through the case study of a multispan concrete bridge class in California. Geometric, material, and structural uncertainties are accounted for in the generation of bridge numerical models and their fragility curves. It is also noted that the traditional lognormality assumption on the demand model leads to unrealistic fragility estimates. Fragility results obtained by the proposed methodology can be deployed in a risk assessment platform such as HAZUS for regional loss estimation.
Smart modeling by using artificial intelligent techniques on thermal performance of flat‐plate solar collector using nanofluid
Authors: Sadeghzadeh Milad , Ahmadi Mohammad Hossein , Kahani Mostafa , Sakhaeinia Hossein , Chaji Hossein , Chen Lingen 
Published: June 2019

AbstractIn the current study, Multilayer Perceptron Artificial Neural Network (MLP‐ANN) mode, Radial Basis Function Artificial Neural Network (RBF‐ANN), and Elman Back Propagation Neural Network (Elamn BP‐ANN) are developed to predict the thermal efficiency of a flat‐plate solar collector. TiO2 (20 nm)/water nanofluids are prepared using two‐step method and used in the designed solar system. All experiments are done in Mashhad city, Iran (Longitude/Latitude: 36.2605°N, 59.6168°E), according to EUROPEAN STANDARD EN 12975‐2 as a quasi‐dynamic test (QDT) method, and the solar collector is exposed to the south with the tilt angle of 55°. Three levels of inlet temperature (ambient air temperature, 52 and 74°C), 3 levels of volumetric flow rate (36, 72, and 108 L/(m2.h)), and 4 levels of nanofluid concentrations (0, 0.1, 0.2, and 0.3 wt.%) are considered as the input data, and the thermal efficiency of the solar system is calculated. According to the output results of developed models, the best prediction of thermal performance is obtained by MLP‐ANN model, although other generated models are also able to predict the efficiency of the solar collector with appropriated accuracy.
A constrained framework for context‐aware remote E‐healthcare (CARE) services
Authors: Sharma Ashutosh , Kumar Rajiv 
Published: June 2019

AbstractRecently, due to the health awareness among the current generations, it leads us to give special attention to the remote E‐healthcare services. The remote E‐healthcare services have been categorized mainly into three categories: primary care, secondary care, and emergency care. Due to the categorized remote healthcare services, the resources must have to be utilized efficiently. Therefore, context‐aware modelling for the remote E‐healthcare (CARE) services has been used to save the resource wastage. The CARE services have been divided into three categories primary context‐aware remote E‐healthcare, secondary context‐aware remote E‐healthcare, and emergency context‐aware remote E‐healthcare (E‐CARE). Three different algorithms have been proposed for the performance analysis. The result shows that the proposed algorithms for the primary context‐aware remote E‐healthcare and secondary context‐aware remote E‐healthcare do not make more difference in the routing. However, the selection of the path for the E‐CARE shows that the hop count of the path has been increased. The increase in the hop count leads to an increase in energy efficiency and the life of the services. Additionally, observation made from our assigned algorithm E‐CARE shows that it performs extremely well for the E‐healthcare services without incrementing the time complexity. Furthermore, major characteristics of the algorithm has been explored and analyzed for the E‐healthcare services.
Using social media mining technology to improve stock price forecast accuracy
Authors: Huang Jia‐Yen , Liu Jin‐Hao 
Published: June 2019

AbstractMany stock investors make investment decisions based on stock‐price‐related chip indicators. However, in addition to quantified data, financial news often has a nonnegligible impact on stock price. Nowadays, as new reviews are posted daily on social media, there may be value in using web opinions to improve the performance of stock price prediction. To this end, we use logistic regression to screen the chip indicators and establish a basic stock price prediction model. Then, we employ text mining technology to quantify the unstructured data of social media opinions on stock‐related news into sentiment scores, which are found to correlate significantly with the change extent of the stock price. Based on the findings that the higher the sentiment scores, the lower the prediction accuracy of the logistic regression model, we propose an improved prediction approach that integrates sentiment scores into the logistic regression model. Our results show that the proposed model can improve the prediction accuracy for stock prices, and can thus provide a new reference for investment strategies for stock investors.