bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dural Venous Sinus Thrombosis after Vestibular Schwannoma Surgery: The Anticoagulation Dilemma
Authors: Brahimaj Bledi C. , Beer-Furlan Andre , Crawford Fred , Nunna Ravi , Urban Matthew , Wu Gary , Abello Eric , Chauhan Vikrant , Kocak Mehmet , Muñoz Lorenzo , Wiet Richard M. , Byrne Richard W. 
Published: November 2019

Abstract
Introduction Dural venous sinus thrombosis (DVST) is a relatively understudied complication of vestibular schwannoma (VS) surgery. Several studies have examined this topic; however, there is limited data on the incidence, clinical progression, and proper management of this patient population.
Methods A retrospective review was performed for patients undergoing surgery for VS at a single institution. All postoperative imaging was reviewed for incidence of DVST. Demographic data were collected including tumor and surgical characteristics along with postoperative course.
Results A total of 63 patients underwent resection of their VS. The incidence of DVST was 34.9%. The operative time was greater in the dural venous sinus thrombosis (DSVT) group, at an average of 6.69 hours versus 4.87 in the no DSVT cohort (p = 0.04). Tumor size was correlationally significant (p = 0.051) at 2.75 versus 2.12 cm greatest diameter. The translabyrinthine approach was most prevalent (68.2%). The side of the thrombosis was ipsilateral to the tumor and surgery in all patients. The sigmoid sinus was most commonly involved (95.5%). Of them, 85% patients had a codominant or thrombus contralateral to the dominant sinus. All patients were asymptomatic. No patients were treated with anticoagulation. Resolution of thrombus was seen in five (22.7%) of the patients on last follow-up imaging. There were no hemorrhagic complications.
Conclusion The overall incidence of DVST was (34.9%) of 63 patients who underwent VS surgery. All patients were asymptomatic and none were treated with anticoagulation. In our study, continuing to observe asymptomatic patients did not lead to any adverse events.
The Role of Interventional Radiology in the Pretransplant Management of Hepatocellular Carcinoma and Portal Vein Thrombosis
Authors: Shmelev Karen , Thornburg Bartley 
Published: November 2019

AbstractHepatocellular carcinoma (HCC) is the most common primary liver tumor and is currently the leading indication for liver transplantation in the United States. Liver transplantation may provide a curative option for patients with HCC, but some present outside of the transplant criteria. Additionally, as the criteria for liver transplant eligibility in HCC are expanded and the incidence of disease increases, waitlist times are becoming progressively longer, which increases the chance of a patient suffering from disease progression while awaiting an organ becoming ineligible for transplant. Multiple studies have demonstrated the successful use of locoregional therapies, including trans-arterial chemoembolization and trans-arterial radioembolization, in downstaging HCC to within transplant criteria, as well as in preventing progression of disease in patients already listed for transplant. Cirrhotic patients also commonly develop portal vein thrombosis (PVT), which is a contraindication to transplantation at many centers. PVT can lead to worsened outcomes after transplant depending on the type of portal venous reconstruction that is performed. The purpose of this article is to discuss the integral role of interventional radiology in the care of these patients, including the role of transarterial therapies in the pretransplant treatment of HCC and the use of endovascular techniques to recanalize thrombosed portal veins in order to establish or maintain transplant eligibility.
Reading comprehension across languages
Authors: McClung Nicola A. , Pearson P. David 
Published: November 2019

AbstractOrthographic depth, the degree of spelling-to-sound consistency in a language, has been hypothesized to affect the ease with which children learn to read words. However, the relationship between orthographic depth and reading comprehension is less well understood. In this study, focusing on countries in which two international assessments (PISA and PIRLS) were given in two or more languages, we examine data from elementary and high-school readers of Finnish, Swedish, Italian, German, Dutch, French and English). Findings suggest that that there may be some trade-offs between shallow and deep orthographies in terms of the specific ways that they map onto the phonological and deep meaning representations required for cognitive processing during an activity such as comprehension. These trade-offs serve to differentially support or inhibit readers depending on where they are situated on the achievement continuum.
Effects of non-native word shapes in the recognition and recall of medicine names
Authors: Pires Carla , Correia Susana , Costa Márcia , Cavaco Afonso , Vigário Marina 
Published: November 2019

AbstractMistakes involving medicine brand names may lead to serious medication errors and even patients’ death. We tested the effect of medicine brand names shape – native vs. non-native spelling – in two groups of Portuguese speaking subjects: (i) pharmacy clients (older and less educated); (ii) graduate students (younger and more educated). We run a recognition task and an immediate recall task, testing three groups of names with: (1) non-native graphemes, (2) non-native grapho-/phonotactics, (3) native patterns. Results showed that names with non-native properties, especially non-native graphemes, were recalled significantly worse. Non-native patterns had a null effect in the recognition task, possibly due to a facilitating effect of the odd, non-native feature, compensating for the extra demand imposed by non-native patterns on processing. Less educated, older participants consistently performed significantly worse than more educated, younger subjects across experiments. The results suggest the pertinence of adapting medicine names to the language of target users.
The development of adverbial clause functions in Hebrew narrative and expository writing across adolescence
Authors: Brandes Gilad , Ravid Dorit 
Published: November 2019

AbstractInterclausal subordination, serving various functions in written discourse, has been studied mostly from a quantitative perspective in later language development. The current study applied a discourse-functional approach to a quantitative and qualitative examination of subordinate Adverbial Clauses (ACs) in Hebrew writing development.Analysis targeted narrative and expository texts, written by Hebrew speaker-writers in grades 4, 7, 11, and university students. Adverbial clauses were counted, and classified according to function. In narratives, they delineated either plotlineevents, surroundingdescriptions, or subjectiveinterpretations. Expository ACs served toenlarge onthe current argument,anchornew arguments in previous discourse, ormove on, initiating a new topic.Narrative ACs had similar prevalence across development, but shifted functionally, favoring interpretive roles in older writers. Expository ACs retained their enlarging-on and anchoring functions, while decreasing in quantity, parallel to an increase in alternative, clause-internal devices. The study underscores the usefulness of a functionally-oriented perspective in revealing developmental changes in the syntax-discourse interface.
Coherent Controlling Single Photon Asymmetric Transmission in the Atom Chirally Coupled Waveguide System*
Authors: Hu Wei , Ma Xiao-San , Wang Bing , Huang Xian-Shan , Cheng Mu-Tian 
Published: November 2019

Abstract
We theoretically investigate the influences of two coherent driving fields on the asymmetric transmission of single photon in the atom-waveguide system. The atom is considered as a Λ system. One transition of the atom chirally couples to the waveguide. The other transition is driven by two coherent driving fields. The transmission probabilities for the single photon incidents from the left (Tlr
) and right (Trl
) are given respectively. The calculated results show that one can realize Tlr
= 0 (Trl
≠ 0) or Trl
= 0 (Tlr
≠ 0) by manipulating the phase difference between the two coherent driving fields. The influence of the decay rate of the metastable state on the asymmetric transmission is also discussed.
α Decay Properties of Even-Even Nuclei296–308120 Within the Two-Potential Approach*
Authors: Xu Jun-Yao , Chen Jiu-Long , Deng Jun-Gang , Cheng Jun-Hao , Liu Hong-Ming , Li Xiao-Hua 
Published: November 2019

Abstract
In the present work, we predict the α decay half-lives of unknown even-even nuclei296–308120 within the two-potential approach, whose α decay energy Qα
is calculated using WS3+ mass model. To reduce the deviations between the predictions and experimental data due to nuclear shell effect, the analytic formula of α decay hindrance factor is introduced to the two-potential approach, whose parameters had been extracted from even-even nuclei in the region of 82 < Z ≤ 126 and 152 < N ≤ 184 in our previous work [Deng et al., Chin. Phys. C 42 (2018) 044102]. In addition, for comparing, we use a type of α decay general formula Universal Decay Law (UDL) and a semi-empirical formula in the superheavy nucleus (SEMFLS) to calculate the half-lives of even-even nuclei296–308120. The results indicate that our predicted values and the calculated values of the above two empirical formulas are mutually confirmed. Meanwhile, we systematically study α decay chains of296–308120 and predict the decay modes for superheavy nuclei to help to identify new superheavy isotopes.
Structure, Electronic, and Mechanical Properties of Three Fully Hydrogenation h-BN: Theoretical Investigations*
Authors: Pu Chun-Ying , Lv Lin-Xia , Zhou Da-Wei , Yu Jia-Hui , Tang Xin 
Published: November 2019

Abstract

The structural, electronic, elastic, mechanical properties and stress-strain relationship of chair, boat, and stirrup conformers of fully hydrogenated h-BN (fh-BN) are investigated in this work using the Perdew-Burke-Ernzerhof (PBE) function in the frame of density functional theory. The achieved results for the lattice parameters and band gaps of three conformers in this research are in good accordance with other theoretical results. The band structures of three conformers show that the chair, boat, and stirrup are direct band gap with a band gaps of (3.12, 4.95, and 4.95 eV), respectively. To regulate the band structures of fh-BN, we employ a hybrid functional of Heyd-Scuseria-Ernzerhof (HSE06) calculations and the band gaps are 3.84 (chair), 6.12 (boat), and 6.18 eV (stirrup), respectively. The boat and stirrup fh-BN exhibits varying degrees of mechanical anisotropic properties with respect to the Young’s modulus and Poisson’s ratio, while the chair fh-BN exhibits the mechanical isotropic properties. Furthermore, tensile strains are applied in the armchair and zigzag directions related to tensile deformation of zigzag and armchair nanotubes, respectively. We find that the ultimate strains in zigzag and armchair deformations in stirrup conformer are 0.34 and 0.25, respectively, larger than the strains of zigzag (0.29) and armchair (0.18) deformations in h-BN although h-BN can surstain a surface tension up to the maximum stresses higher than those of three conformers of fh-BN. Furthermore, the band gap energies in three conformers can be modulated effectively with the biaxial tensile strain.
Natural Neighbor Algorithm for Breast Cancer Diagnosis
Authors: Li Shuxiang , Yang Lijun , Chen Peiyu , Yang Cheng 
Published: November 2019

Abstract
Machine learning to diagnose breast cancer is an important, real-world medical problem. As one of the most popular machine learning algorithm, K-Nearest Neighbors (KNN) algorithm is widely used in breast cancer classification and can provide high classification accuracy and effective diagnostic capabilities. However, selection of parameter K is still an unsolved problem for K-Nearest Neighbors (KNN). To address the problem, we introduce a novel neighbor form, Natural Neighbor (NaN), which is obtained adaptively by its search algorithm. We firstly use a noise filter, which called edited natural neighbor algorithm (ENaN), to eliminate the noises and global outliers of Wisconsin’s breast cancer prognosis dataset. Then, cleaned data set and natural neighbor algorithm are used to construct a new non parameter diagnostic system. The main advantages of the proposed algorithm are that it does not need any parameters and can maintain high classification accuracy. Experiments show that the classification accuracy of proposed method is similar to the highest classification accuracy obtained by traditional K-Nearest Neighbors algorithm with different K values.
Design and Implementation of the Enterprise Cluster Manager
Authors: Chen Chen , Cheng Ming , Yang Yang 
Published: November 2019

Abstract
A practical cluster manager is designed to fulfill the management requirements of server resources allocation to multi-UE processes and optimize the security, storage and retrieval of big data. Based on the application background of cluster manager, it introduces the structural designs, including frame, database, member node, master node and internal workflow. Meanwhile, it expounds the optimizing processes of cluster manager, including load balance algorithms, emergency processing, partition store of big data and others. Finally, the feasibility of whole schedules is verified by the test data of practical application, providing a reference for the subsequent research on cluster management.
Research on Image Recognition Method Based on Deep Learning
Authors: Jing Luo 
Published: November 2019

Abstract
With the rise of artificial intelligence technology, computer vision, image processing, image recognition, voice recognition and other technologies have gradually entered the public’s vision. This paper focuses on image recognition. This paper discusses the original image acquisition, image information preprocessing, image feature extraction, pattern classification and recognition results. Analyzes VGG-19 network, VGG improved has realized the image quick recognition, studies input and output points, the number of neurons by convolution neural network, and finally concludes that the deep learning method can shorten the training time, improve the identification results, also the requirement for images in the image library is greatly reduced, the demand for hardware is not too high.
Edge Property Based Stream Order Reduce the Performance of Stream Edge Graph Partition
Authors: Ayall T , Duan H , Liu C 
Published: November 2019

Abstract
The graph data is found everywhere in various disciplines, such as in social networks, biological networks, chemical compounds, and computer vision, etc. Currently, the size of graph data has dramatically increased; all disciplines have extracted knowledge from a graph by partitioning and distributing large-scale graph into different clusters using the distributed graph processing system or graph database. However, the graph partitioning has impacted to speed up or slow down the performance of those systems. Even if the stream edge graph partition has shown better partition quality than vertex graph partition for skew degree distribution of a graph and supports big graph partitioning, stream graph edge partitioners are affected by stream orders. In this study, we propose two edge properties based stream order models, TFB(Tree edges First, then Backward edges follow) and BFT(Backward edges First, then Tree edges follow). And study the effect of stream order on stream graph edge partitioners. The results show that TFB and BFT models significantly affect the quality of stream edge partition, except hashing. All algorithms show the best partitioning quality by Random order than other orders, TFB, BFT, BFS(Breadth-First Search), and DFS(Depth-First Search).
Detection of SQL Injection Attacks Based on Improved TFIDF Algorithm
Authors: Li Yingbo , Zhang Bin 
Published: November 2019

Abstract
Detecting SQL injection attacks (SQLIAs) effectively is one of the critical issues to be solved in Web secure fields. Aiming at the problem that the distribution of feature words in the same kind of statements is not considered when using TFIDF algorithm to vectorize the text of SQL statements, a method of detecting SQLIAs based on improved Term Frequency-Inverse Document Frequency (TFIDF) algorithm is proposed. Firstly, TFIDF algorithm is improved based on the distribution of feature words in the same kind of statements. Then, the improved TFIDF (ITFIDF) algorithm is used to vectorize the dataset of SQL statements to increase the feature weight of the SQL statement. Finally, the detection of SQLIAs is carried out based on Support Vector Machine (SVM). The experimental results show that the combination of SVM and ITFIDF has higher accuracy, recall rate and F-score compared with other similar methods. At the same time, the experimental results also show that SVM has better classification performance when dealing with this problem than other machine learning models such as DNN and Decision Tree.
I Workshop on Modeling and Simulation for Science and Engineering
Authors: Giraldo Suarez E , Zuluaga Díaz B , V-Niño E D 
Published: November 2019

This proceeding presents the contributions of the participants of the First Workshop on Modeling and Simulation for Science and Engineering (I WMSSE) conducted in the city of Pereira, Colombia, on August 20 and 21, 2019.
The conference was attended by more than 100 participants and received around 30 presentations or posters. The I WMSSE has been contributed with workshops, presentation and posters that aimed to show progress in different fields of research of undergraduate and graduate students as well as research groups, where it involved mathematical and physical modeling in areas of interest such as the dynamic systems model, the control system, process control, energy flow and mechatronic systems, and multidisciplinary sciences.
The scientific program was quite dense, however, the attendees established academic networks among the participants. The program allowed a high level of talks and an adequate environment for scientific dissemination, we thank the organizers and hosts of the Universidad Tecnológica de Pereira, Colombia, for the event and promote the space to develop the conferences. We also want to thank the members of the organizing committee, as well as the members of the scientific committee.
List of Organizing Committee, International Committee, National Committees, Logos are available in the pdf
Mathematical analysis of an epidemic through qualitative analysis with a third order model
Authors: Devia Narváez D , Devia Narváez D , Ospina R 
Published: November 2019

Abstract
The present article exposes the analysis of the dynamic model of an epidemic, which from certain considerations pretends to present the way in which for a given population the dispersion of a virus can occur, initially the preliminary concepts of the theory are exposed of dynamic systems to then incur the qualitative solution forms of greatest use in the specialized literature, finally the third order dynamic model of the epidemic is exposed, where the considerations and analysis procedures to obtain the final results are shown.
Optimal power flow solution in direct current grids using Sine-Cosine algorithm
Authors: Giraldo J A , Montoya O D , Grisales-Noreña L F , Gil-González W , Holguín M 
Published: November 2019

Abstract
In the next years, Colombian power system will have the connection of distributed generators and constant power loads; Therefore, it is necessary to propose the analysis methods that allow establishing the minimum requirements that have to be satisfied for the power system to guarantee an optimal power flow in order to preserve safe and reliable operation of it. For this purpose, in this paper presents an optimal power flow in direct current resistive grids with constant power loads and distributed generators. The optimal power flow problem is formulated as a master-slave optimization algorithm. The master stage covers the dispatching of all the distributed generators by using the Sine-Cosine algorithm. In the slave stage an efficient power flow method based on successive approximations is employed to determine the voltage variables and evaluate the objective function of the problem, which corresponds to the power loss minimization. A direct current distribution network composed by 21 nodes is used as test case by comparing its numerical performance with nonlinear optimization packages and two metaheuristic approaches named black-hole optimization and continuous genetic algorithm. All the simulations are conducted via MATLAB software.
Volumetric quantification in ovarian pathology using abdomino-pelvic computed tomography
Authors: Valbuena O , Vera M I , Vera M , Gelvez-Almeida E , Huérfano Y , Borrero M , Salazar-Torres J , Salazar W 
Published: November 2019

Abstract
Pathological ovary is categorized into cystic tumors, solid tumors and mixed, according to the content of the affected ovary. Accordingly, the degree of benignity or malignity thereof is established. The imaging study for the preliminary morphological assessment of PO is ultrasound, in its pelvic and transvaginal modalities, for which well-established criteria are available. Once the ultrasound findings suggest malignancy, complementary studies such as abdominal-pelvic tomography images and tumor markers are requested. This type of images has challenging problems called noise, artifacts and low contrast. In this paper, in order to address these problems, a computational technique is proposed to characterize a pathological ovary. To do this, a thresholding and the median and gradient magnitude filters are applied, preliminarily, to complete the preprocessing stage. Then, during the segmentation, the algorithm of region growing is used to extract the three-dimensional morphology of the pathological ovary. Using this morphology, the volume of the pathological ovary is calculated and it allows selecting the surgical-medical behavior to approach this kind of ovary. The validation of the proposed technique indicates that the results are promising. This technique can be useful in the detection and monitoring the diseases linked to pathological ovary.
The experimental chemical hardness in the interaction between β-tubulin and epothilone B
Authors: Corzo S P , Bueno P R , Miranda D A 
Published: November 2019

Abstract
We showed the use of the experimental chemical hardness in the analysis of the interaction between β-tubulin and epothilone B. The interaction is analyzed by exposing the Epothilone B to a sensor based on an organic self-assembled monolayer functionalized with Beta tubulin. The proposed methodology is nondestructive and label-free. It allows us to compare the interaction between Beta-tubulin and different concentrations of the pharmacological molecule, i.e., epothilone B. The interaction is analyzed by the experimental hardness obtained according to the Miranda-Bueno methodology. We observed a linear behavior between the logarithm of the chemical hardness and the logarithm of epothilone B concentration. The results suggest the experimental chemical hardness can be used to compare the interaction of β-tubulin with epothilone B and with other pharmacological molecules.