bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Implementation of School Ticket Ticketing Service Platform Based on Kubernetes Container Self-Scalable Technology
Authors: Huang Yiting , Wang Mantao , Zou Lin , Zhao Anqi , Yao Yuanzhou , Yao Fengying 
Published: August 2019

Abstract
The current system of line colonel tickets booking in colleges and universities is not able to predict the high and low peak of student booking flow in time, which leads to the unreasonable allocation of computer resources. In order to optimize the online booking experience of campus students, this paper proposes a design scheme of the school bus ticket booking service platform based on Kubernetes container self-expanding technology. The experiment shows that the platform can monitor and predict the booking situation of students, timely respond to the high and low peak period of student booking on campus, ensure the smooth experience of students booking online, which reflects the advantages of the platform.
Application of EXCEL commonly used in navigation data processing
Authors: Dai Xiuliang , Ji Chao , Wang Hongzhi 
Published: August 2019

Abstract
Aiming at the problem of large amount of data calculation and collation in navigation work, several EXCEL data processing methods of commonly used nautical tables are presented based on the advantages of EXCEL with its flexible use, strong expansibility and easy storage. All the calculation processes involved in common nautical tables can be realized by manually inputting corresponding parameters through formula input and logical setting. This method not only reduces the amount of manual calculation, but also improves the accuracy and accuracy of data calculation and realizes the electronic storage of data, which is of great benefit to improve the efficiency of navigation.
Weak Convergence of Iterative Approximation for Fixed Points of A Monotone α-nonexpansive Mapping
Authors: Zhang Rong 
Published: August 2019

Abstract
In this paper, a modified approximation method is introduced for finding the fixed point of α-nonexpansive mapping in a uniformly convex Banach space with a partial order. Moreover, the weak convergence theorems of the fixed point of α-nonexpansive mapping are established under Opial and weak-Opial conditions, respectively.
Topic classification: 47H05; 47H09; 47H10 CLC number: O177.91 Document code: A
Topology Verification of Low Voltage Distribution Network Based on k-means Clustering Algorithm
Authors: Wang Junyi , Ji Xingquan , Li Kejun , Sun Qiaoyu 
Published: August 2019

Abstract
Aiming at the problem of topology connection error existing in GIS system of low voltage distribution network, a topology verification algorithm using AMI voltage measurement data combined with k-means clustering algorithm is proposed. Firstly, the voltage data of the consumers in the low-voltage substation area is obtained by the AMI measurement system. Then k-means clustering algorithm is used by the similarity to cluster the voltage curves to identify and verify the users connected on the incorrectly transformer stations. An improved method of noise processing using data density set is proposed to solve the problem of initial cluster centre selection in k-means. For the problem of k value selection, an automatic correction of optimal k value is proposed. The feasibility and effectiveness of the improved k-means clustering algorithm in topology verification are verified by a practical example.
An Optimization Algorithm of Robust Principal Component Analysis and Its Application
Authors: Xia Xinyuan , Gao Fei 
Published: August 2019

Abstract
With the rapid development of robust principal component analysis (RPCA), it has been widely used in signal processing, pattern recognition, computer vision and other fields. The RPCA model has characteristics of complete reconstruction of the original signal from the noise pollution, high-dimensional and high-order complex signals. In order to solve the problems of slow iteration speed and low recovery accuracy in typical algorithms, an improved robust principal component analysis (RPCA) algorithm is studied. Firstly, the idea of smooth approximate zero norm is introduced to build the objective optimization function, then the inertial momentum is used to optimize each iteration of the matrix recovery process, finally, the model parameters are optimized by the grid method. Through simulation and comparative analysis, the results show that the improved algorithm has high accuracy, fast processing speed and remarkable application effect in field of logging data processing.
A method of the people-serving police station location problem
Authors: Lu Peng , Wang Jijin , Ning Weixun , Xiao Xiaoqiang 
Published: August 2019

Abstract
The people-serving police station location problem targets to optimize the location of the police stations and minimize total costs. However, it is very difficult to directly give the solution to the problem. To solve the problem, a method of extending demand points is proposed, which can convert the original problem into a binary integer programming problem. By randomly generating maps, the GNU linear programming kit (GLPK) package is used to solve and verify the converted method.
Composite reduced-kernel weighted extreme learning machine for imbalanced data classification
Authors: Wang Dafei , Xie Wujie , Dong Wenhan 
Published: August 2019

Abstract
In order to solving the problem that the weighted extreme learning machine based on the ensemble learning method enhances the classification performance while increasing the running time of the algorithm, starting from the perspective of multi-core learning, a weighted extreme learning machine based on composite kernel functions and reduced-kernel technique is proposed. The composite kernel function based on Gaussian kernel and Polynomial kernel weighted combination is designed, which effectively improves the classification performance of weighted extreme learning machine. Meanwhile, based on the sample distribution characteristics of the imbalanced dataset, the balanced input sub-matrix is designed to reduce the computational cost of the composite kernel method. The eight binary classification imbalanced datasets of KEEL dataset repository were used for testing. The experimental results show that compared with the original weighted extreme learning machine algorithm, the G- mean and AUC classification performance indicators of the composite reduced-kernel weighted extreme learning machine algorithm are improved in each dataset, and the computation cost is effectively reduced.
Systematic Review of the Use of Telepathology During Intraoperative Consultation
Authors: Dietz Robin L , Hartman Douglas J , Pantanowitz Liron 
Published: August 2019

AbstractObjectiveTo compare studies that used telepathology systems vs conventional microscopy for intraoperative consultation (frozen-section) diagnosis.MethodsA total of 56 telepathology studies with 13,996 cases in aggregate were identified through database searches.ResultsThe concordance of telepathology with the reference standard was generally excellent, with a weighted mean of 96.9%. In comparison, we identified seven studies using conventional intraoperative consultation that showed a weighted mean concordance of 98.3%. Evaluation of the risk of bias showed that most of these studies were low risk.ConclusionsDespite limitations such as variation in reporting and publication bias, this systematic review provides strong support for the safety of using telepathology for intraoperative consultations.
Role of Inflammatory Biomarkers in the Prevalence and Incidence of Hypertension Among HIV-Positive Participants in the START Trial
Authors: Ghazi Lama , Baker Jason V , Sharma Shweta , Jain Mamta K , Palfreeman Adrian , Necsoi Coca , Murray Daniel D , Neaton James D , Drawz Paul E 
Published: August 2019

Abstract

BACKGROUND
The association between hypertension (HTN) and inflammatory biomarkers (interleukin-6 [IL-6] and high-sensitivity C-reactive protein [hsCRP]) in HIV-positive persons with CD4+ count &gt;500 cells/mm3 is unknown.

METHODS
We studied HTN in participants of the Strategic Timing of AntiRetroviral Treatment (START) trial of immediate vs. deferred antiretroviral therapy (ART) in HIV-positive, ART naive adults with CD4+ count &gt; 500 cells/mm3. HTN was defined as having a systolic blood pressure (BP) ≥140 mmHg, a diastolic BP ≥90 mmHg, or using BP-lowering therapy. Logistic and discrete Cox regression models were used to study the association between baseline biomarker levels with prevalent and incident HTN.

RESULTS
Among 4,249 participants with no history of cardiovascular disease, the median age was 36 years, 55% were nonwhite, and the prevalence of HTN at baseline was 18.9%. After adjustment for race, age, gender, body mass index (BMI), diabetes, smoking, HIV RNA and CD4+ levels, associations of IL-6 and hsCRP with HTN prevalence were not significant (OR per twofold higher:1.10, 95% confidence interval [CI]: 0.99, 1.20 for IL-6 and 1.05, 95% CI: 0.99, 1.10 for hsCRP). Overall incidence of HTN was 6.8 cases/100 person years. In similarly adjusted models, neither IL-6 (Hazard ratios [HR] per twofold higher IL-6 levels: 0.97, 95% CI: 0.88, 1.08) nor hsCRP (HR per twofold higher hsCRP levels: 0.97, 95% CI: 0.92, 1.02) were associated with risk of incident HTN. Associations did not differ by treatment group. Age, race, gender, and BMI were significantly associated with both the prevalence and incidence of HTN.

CONCLUSIONS
Traditional risk factors and not baseline levels of IL-6 or hsCRP were associated with the prevalence and incidence of HTN in START.
Exaggerated Aortic Pulse Pressure and Wave Amplitude During Muscle Metaboreflex Activation in Type 2 Diabetes Patients
Authors: Figueroa Arturo , Maharaj Arun , Johnson Sarah A , Fischer Stephen M , Arjmandi Bahram H , Jaime Salvador J 
Published: August 2019

Abstract

Background
Peripheral mean arterial pressure (MAP) responses to muscle metaboreflex activation using postexercise muscle ischemia (PEMI) in type 2 diabetes patients (T2D) are contradictory. Given that aortic pulse pressure (PP) and wave reflections are better indicators of cardiac load than peripheral MAP, we evaluated aortic blood pressure (BP) and wave amplitude during PEMI.

METHODS
Aortic BP and pressure wave amplitudes were measured at rest and during PEMI following isometric handgrip at 30% maximum voluntary contraction (MVC) in 16 T2D and 15 controls. Resting aortic stiffness (carotid-femoral pulse wave velocity, cfPWV) and fasting blood glucose (FBG) were measured.

RESULTS
Increases in aortic MAP (Δ26 ± 2 mmHg vs. Δ17 ± 2 mmHg), PP (Δ15 ± 2 mmHg vs. Δ10 ± 1 mmHg), augmentation index (AIx) (Δ8.2 ± 1.0% vs. Δ4.5 ± 1.3%), augmented pressure (AP) (Δ11 ± 1 mmHg vs. Δ5 ± 1 mmHg), forward (Pf) (Δ9 ± 1 mmHg vs. Δ5 ± 1 mmHg), and backward pressure waves (Pb) (Δ10 ± 1 mmHg vs. Δ5 ± 1 mmHg) responses to PEMI were greater in T2D than controls (P &lt; 0.05). Aortic PP, but not MAP, response to PEMI was correlated to Pf (r = 0.63, P &lt; 0.001) and Pb (r = 0.82, P &lt; 0.001) responses and cfPWV (r = 0.37, P &lt; 0.05).

CONCLUSIONS
Aortic BP and pressure wave responses to muscle metaboreflex activation are exaggerated in T2D. Aortic PP during PEMI was related to increased wave reflection, forward wave amplitude, and aortic stiffness in T2D patients.
Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression
Authors: Wang Jiebiao , Devlin Bernie , Roeder Kathryn 
Published: August 2019

Abstract

Motivation
Patterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects.

Results
Complementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g. multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL).

Availability and implementation
We implement this method as an R package MIND, hosted on https://github.com/randel/MIND.

Supplementary information
Supplementary data are available at Bioinformatics online.
New concepts in C. difficile management
Authors: Mahida Y R 
Published: August 2019

Abstract

Background
Clostridium difficile infection is transmitted via spores, and the disease is mediated via secreted toxins. It represents a significant healthcare problem, and clinical presentation can range from asymptomatic carriage to life-threatening pseudomembranous colitis.

Sources of data
publications in the field, with a focus on recent developments and concepts.

Areas of agreement
infection control measures, antibiotic stewardship and current management of the initial episode of C. difficile infection.

Areas of controversy
selection and sequence of interventions for the management of recurrent C. difficile infection; management of persistent carriers of toxigenic C. difficile in patients at high risk of subsequent C. difficile infection.

Growing points
use of faecal microbiota transplantation for recurrent C. difficile infection.

Areas timely for developing research
role of specific microbiota-mediated interventions and vaccination in the treatment and prevention of C. difficile infection.
Sensitive Determination of C-Alkylated Flavonoids by HPLC-ESI-MS/MS Using Multiple Reaction Monitoring Approach: Pseudarthria hookeri as a Case Study
Authors: Faraz Ina , Ali Arslan , Ul Haq Faraz , Tchamgoue Joseph , Kouam Simeon F , Miana Ghulam Abbas , Musharraf Syed Ghulam 
Published: August 2019

AbstractOne of the major problems with the formulation of herbal medicines is the quality control of plant material to ensure its efficacy and safety. Quality control of medicinal plants requires analysis of many bioactive compounds present in the plant. C-alkylated flavonoids are an important bioactive subclass of flavonoids. A simple, rapid, sensitive and selective method is presented here for the quantification of bioactive C-alkylated flavonoids. This is the first quantitative method for analysis of C-alkylated flavonoids based on the multiple reaction monitoring (MRM) approach so far. This study focuses on method development for quantification of bioactive C-alkylated flavonoids. Quantification of a total of five C-alkylated flavonoids was done employing the MRM approach on an HPLC-QqQ-MS instrument. LODs and LOQs for quantified flavonoids were in the range of 0.41–1.32 and 1.23–3.96 ng/mL, respectively. Linear calibration curves between 25 and 1500 ng/mL were obtained with the regression coefficients of ≥0.996. Accuracy (% bias) and precision (% RSD) of the analyses were found to be less than 5%. Developed HPLC-ESI-MS/MS can be employed as a quality control method of plant raw materials.
Chemometrically Assisted Development of Ultra-High-Performance Liquid Chromatography Method for the Simultaneous Quantification of Sofosbuvir, Daclatasvir and Ledipasvir in Pharmaceutical Dosage Forms
Authors: Labidi Aymen , El Atrache Latifa Latrous 
Published: August 2019

Abstract
A new ultra-high-performance liquid chromatography method for the simultaneous quantification of sofosbuvir, daclatasvir and ledipasvir was developed. Two combinations of these direct-acting antivirals are used in hepatitis C virus infection therapy and show high efficacy and safety. Fractional factorial design was used for screening the most influential factors on separation and time analysis. These significant factors were optimized using a central composite design. The optimum resolution was carried out by using a Waters XBridge C18 column (150 mm, 4.6 mm ID, 5 μm) at a temperature of 35°C ± 2°C and acetonitrile/sodium perchlorate buffer (10 mM, pH = 3.2) (40: 60 v/v) as mobile phase at a flow rate of 1.5 mL min−1. UV detection was set at λ = 210 nm. A short chromatographic separation time was achieved. The developed method was validated according to the accuracy profile approach and was found specific, precise, faithful and accurate. The detection limits were between 0.07 and 0.13 μg mL−1. Hence, this novel method can be employed for the routine quality control analysis and in dissolution profile studies of generics containing these products.
Effective User Preference Clustering in Web Service Applications
Authors: Wang Yan , Zhou Jian-tao , Li Xinyuan , Song Xiaoyu 
Published: August 2019

Abstract
The research on personalized recommendation of Web services plays an important role in the field of Web services technology applications. Fortunately, not all users have completely different service preferences. Due to the same application scenarios and personal interests, some users have the same preferences for certain types of Web services. This paper explores the problem of user clustering in the service environment, grouping users according to their service preferences. It helps service providers to identify and characterize the preferences of similar users and provide them with customized services. We propose two combination-based clustering algorithms which make full use of the advantages of the K-means algorithm and the affinity propagation algorithm. In addition, a three-stage clustering process is elaborated to improve the accuracy of user clustering. To reduce the time complexity of the algorithms, we create a parallel execution model of the algorithms implemented by a higher-order MapReduce sequence linking technology. Extensive experiments on simulated datasets and real datasets are performed on the comparisons between the proposed algorithms and the other combination-based clustering algorithms. The experimental results substantiate that the proposed algorithms can effectively distinguish user group with different preferences.
Direction-based Spatial Skyline for Retrieving Arbitrary-Shaped Surrounding Objects
Authors: Shen Bojie , Islam Saiful , Taniar David 
Published: August 2019

AbstractRetrieval of arbitrary-shaped surrounding data objects has many potential applications in spatial databases including nearby arbitrary-shaped object-of-interests retrieval surrounding a user. In this paper, we propose directional zone concept to determine directional similarity among spatial data objects. Then, we propose a novel query, called direction-based spatial skyline (DSS), which retrieves non-dominated arbitrary-shaped surrounding data objects in spatial databases for a user. The proposed DSS query is rotationally invariant as well as fair. We develop efficient algorithms for processing DSS queries in spatial databases by designing novel data pruning techniques using R-Tree data indexing scheme. Finally, we demonstrate the effectiveness and efficiency of our approach by conducting extensive experiments with real datasets.
Uncertainties and challenges in surgical and transcatheter tricuspid valve therapy: a state-of-the-art expert review
Authors: Chang Chun Chin , Veen Kevin M , Hahn Rebecca T , Bogers Ad J J C , Latib Azeem , Oei Frans B S , Abdelghani Mohammad , Modolo Rodrigo , Ho Siew Yen , Abdel-Wahab Mohamed , Fattouch Khalil , Bosmans Johan , Caliskan Kadir , Taramasso Maurizio , Serruys Patrick W , Bax Jeroen J , van Mieghem Nicolas M D A , Takkenberg Johanna J M , Lurz Philip , Modine Thomas , Soliman Osama 
Published: August 2019

Abstract
Tricuspid regurgitation (TR) is a frequent and complex problem, commonly combined with left-sided heart disease, such as mitral regurgitation. Significant TR is associated with increased mortality if left untreated or recurrent after therapy. Tricuspid regurgitation was historically often disregarded and remained undertreated. Surgery is currently the only Class I Guideline recommended therapy for TR, in the form of annuloplasty, leaflet repair, or valve replacement. As growing experience of transcatheter therapy in structural heart disease, many dedicated transcatheter tricuspid repair or replacement devices, which mimic well-established surgical techniques, are currently under development. Nevertheless, many aspects of TR are little understood, including the disease process, surgical or interventional risk stratification, and predictors of successful therapy. The optimal treatment timing and the choice of proper surgical or interventional technique for significant TR remain to be elucidated. In this context, we aim to highlight the current evidence, underline major controversial issues in this field and present a future roadmap for TR therapy.
Effects of allochthonous dissolved organic matter input on microbial composition and nitrogen-cycling genes at two contrasting estuarine sites
Authors: Happel Elisabeth M , Markussen Trine , Teikari Jonna E , Huchaiah Vimala , Alneberg Johannes , Andersson Anders F , Sivonen Kaarina , Middelboe Mathias , Kisand Veljo , Riemann Lasse 
Published: August 2019

ABSTRACTHeterotrophic bacteria are important drivers of nitrogen (N) cycling and the processing of dissolved organic matter (DOM). Projected increases in precipitation will potentially cause increased loads of riverine DOM to the Baltic Sea and likely affect the composition and function of bacterioplankton communities. To investigate this, the effects of riverine DOM from two different catchment areas (agricultural and forest) on natural bacterioplankton assemblages from two contrasting sites in the Baltic Sea were examined. Two microcosm experiments were carried out, where the community composition (16S rRNA gene sequencing), the composition of a suite of N-cycling genes (metagenomics) and the abundance and transcription of ammonia monooxygenase (amoA) genes involved in nitrification (quantitative PCR) were investigated. The river water treatments evoked a significant response in bacterial growth, but the effects on overall community composition and the representation of N-cycling genes were limited. Instead, treatment effects were reflected in the prevalence of specific taxonomic families, specific N-related functions and in the transcription of amoA genes. The study suggests that bacterioplankton responses to changes in the DOM pool are constrained to part of the bacterial community, whereas most taxa remain relatively unaffected.
The Methylotroph Gene Order Browser (MGOB) reveals conserved synteny and ancestral centromere locations in the yeast family Pichiaceae
Authors: Douglass Alexander P , Byrne Kevin P , Wolfe Kenneth H 
Published: August 2019

ABSTRACT
The yeast family Pichiaceae, also known as the ‘methylotrophs clade’, is a relatively little studied group of yeasts despite its economic and clinical relevance. To explore the genome evolution and synteny relationships within this family, we developed the Methylotroph Gene Order Browser (MGOB, http://mgob.ucd.ie) similar to our previous gene order browsers for other yeast families. The dataset contains genome sequences from nine Pichiaceae species, including our recent reference sequence of Pichia kudriavzevii. As an example, we demonstrate the conservation of synteny around the MOX1 locus among species both containing and lacking the MOX1 gene for methanol assimilation. We found ancient clusters of genes that are conserved as adjacent between Pichiaceae and Saccharomycetaceae. Surprisingly, we found evidence that the locations of some centromeres have been conserved among Pichiaceae species, and between Pichiaceae and Saccharomycetaceae, even though the centromeres fall into different structural categories—point centromeres, inverted repeats and retrotransposon cluster centromeres.