bluuebunny/crossref_metadata_2025_split huggingface dataset:
El marketing político
Authors: Cifuentes G. Alvaro H. 
Published: June 2021

RESUMENSi un candidato desea ser elegido, las técnicas de marketing aplicadas a la política, le son imprescindibles. El marketing político (Politing) es el análisis metódico de los diferentes segmentos que integran el ámbito político de una sociedad y de los factores que puedan modificarlos. Se aplican al candidato, a los votantes, al análisis de la publicidad política, a los simpatizantes, a desconocedores del partido y a los indecisos.Los candidatos colombianos lo están aplicando, y compañías nuestras exportan servicios de asesoría de países suramericanos.Promocionar un candidato implica estructurar una compañía tal como una empresa, aplicando técnicas de ventas, de fijación de cuotas y de planeación estratégica.
Cambios fisiológicos y mecanismos genéticos asociados a la marchitez vascular causada por Fusarium en tomate: una revisión actualizada
Authors: Carmona Sandra L. , Villarreal-Navarrete Andrea , Burbano-David Diana , Soto-Suárez Mauricio 
Published: June 2021

El cultivo de tomate (Solanum lycopersicum), una de las hortalizas más cultivadas en el mundo, se enfrenta a diferentes patógenos del suelo que afectan su morfología, fisiología, bioquímica y regulación genética de las plantas. El hongo fitopatógeno Fusarium oxysporum f. sp. lycopersici (Fol) agente causal de la marchitez vascular del tomate causa pérdidas superiores al 60% en este cultivo. En esta revisión se presentan los mecanismos fisiológicos, bioquímicos y moleculares desarrollados en la interacción tomate – Fol. La co-evolución entre plantas y patógenos ha facilitado el desarrollo de mecanismos de defensa en las plantas que les permite protegerse frente a los efectos nocivos de la invasión por parte del patógeno, mientras que los patógenos implementan estrategias para imponerse frente a la resistencia de las plantas. Las consecuencias fisiológicas del ataque por Fol incluyen respuestas al déficit hídrico, regulaciones en la conductancia estomática, cambios en la fotosíntesis, así como alteraciones en los contenidos de clorofila y su fluorescencia. Estos cambios pueden ser explicados, en parte, con base en respuestas oxidativas, producción de metabolitos secundarios y activación de vías de señalización hormonales que hacen parte de una compleja red bioquímica activada tras la infección por el patógeno.
Patient Representation From Structured Electronic Medical Records Based on Embedding Technique: Development and Validation Study
Authors: Huang Yanqun , Wang Ni , Zhang Zhiqiang , Liu Honglei , Fei Xiaolu , Wei Lan , Chen Hui 
Published: June 2021

Background
The secondary use of structured electronic medical record (sEMR) data has become a challenge due to the diversity, sparsity, and high dimensionality of the data representation. Constructing an effective representation for sEMR data is becoming more and more crucial for subsequent data applications.

Objective
We aimed to apply the embedding technique used in the natural language processing domain for the sEMR data representation and to explore the feasibility and superiority of the embedding-based feature and patient representations in clinical application.

Methods
The entire training corpus consisted of records of 104,752 hospitalized patients with 13,757 medical concepts of disease diagnoses, physical examinations and procedures, laboratory tests, medications, etc. Each medical concept was embedded into a 200-dimensional real number vector using the Skip-gram algorithm with some adaptive changes from shuffling the medical concepts in a record 20 times. The average of vectors for all medical concepts in a patient record represented the patient. For embedding-based feature representation evaluation, we used the cosine similarities among the medical concept vectors to capture the latent clinical associations among the medical concepts. We further conducted a clustering analysis on stroke patients to evaluate and compare the embedding-based patient representations. The Hopkins statistic, Silhouette index (SI), and Davies-Bouldin index were used for the unsupervised evaluation, and the precision, recall, and F1 score were used for the supervised evaluation.

Results
The dimension of patient representation was reduced from 13,757 to 200 using the embedding-based representation. The average cosine similarity of the selected disease (subarachnoid hemorrhage) and its 15 clinically relevant medical concepts was 0.973. Stroke patients were clustered into two clusters with the highest SI (0.852). Clustering analyses conducted on patients with the embedding representations showed higher applicability (Hopkins statistic 0.931), higher aggregation (SI 0.862), and lower dispersion (Davies-Bouldin index 0.551) than those conducted on patients with reference representation methods. The clustering solutions for patients with the embedding-based representation achieved the highest F1 scores of 0.944 and 0.717 for two clusters.

Conclusions
The feature-level embedding-based representations can reflect the potential clinical associations among medical concepts effectively. The patient-level embedding-based representation is easy to use as continuous input to standard machine learning algorithms and can bring performance improvements. It is expected that the embedding-based representation will be helpful in a wide range of secondary uses of sEMR data.
ASSESSING THE QUALITY OF COVID-19 DATA: EVIDENCE FROM NEWCOMB-BENFORD LAW
Authors: Jošić Hrvoje , Žmuk Berislav 
Published: June 2021

The COVID-19 infection started in Wuhan, China, spreading all over the world, creating global healthcare and economic crisis. Countries all over the world are fighting hard against this pandemic; however, there are doubts on the reported number of cases. In this paper Newcomb-Benford Law is used for the detection of possible false number of reported COVID-19 cases. The analysis, when all countries have been observed together, showed that there is a doubt that countries potentially falsify their data of new COVID-19 cases of infection intentionally. When the analysis was lowered on the individual country level, it was shown that most countries do not diminish their numbers of new COVID-19 cases deliberately. It was found that distributions of COVID-19 data for 15% to 19% of countries for the first digit analysis and 30% to 39% of countries for the last digit analysis do not conform with the Newcomb-Benford Law distribution. Further investigation should be made in this field in order to validate the results of this research. The results obtained from this paper can be important for economic and health policy makers in order to guide COVID-19 surveillance and implement public health policy measures.
Effect of Arabica Coffee Bean Extract (Coffea arabica) as a Growth Inhibitor of Enterococcus faecalis ATCC 29212
Authors: Parnomo Trimurti 
Published: June 2021

Arabica coffee seeds contain a composition of Caffeine, Chlorogenic acid, Flavonoids, and Trigonelline. The purpose of this study is to test the antibacterial of Arabica coffee seed extract against bacterium Enterococcus faecalis at concentrations of 1,5625%, 3,125%, 6,25%, 12,5%, 25%, 50% and 100%. The extraction method using maceration with solvent 96%. Antibacterial activity test was done by using the Kirby and Bauer diffusion test method. The results showed that Arabica coffee seed extract could provide inhibition starting from 3,125% with an average diameter of inhibition zone of 1,16 mm to the largest concentration of 100% with an average zone diameter of inhibition of 14,6 mm. At the same time, the average diameter of the inhibitory zone of antibiotic ampicillin at a concentration of 1% as a control (+) is 24,6 mm. The results showed that the greater concentration, the greater the inhibitory zones are formed.
Keywords: Coffea arabica, Enterococcus faecalis, antibacterial, inhibition zone
CHARACTERIZATION OF IRON PRODUCTION WITH MILLSCALE BY PRODUCT REDUCTION
Authors: Nurdiyansah Lukman Faris , Darsono Nono , Khaerudini Deni Shidqi 
Published: June 2021

Millscale is a large by product of metal factory. Many methods to recycled it to many applications. The aim of this research is recycled millscale to produce the iron by reduction method with graphite as reductant agent. The reduction process was deed by milled millscale and graphite powder with 4:1 weight ratio was by used High Energy Milling with 4, 6, 12 hours milling time variations. The powder then was characterized by X-Ray Diffraction (XRD), Vibrating Sample Magnetometer (VSM) and SEM-EDS test. The XRD test result is Fe3C as a main phase then carbon, magnetite, wustite and Iron as a minor phase. The percentage of iron composition is increase during milling times amount to 6; 10.9; 13 %. The remanence for the 4, 6, and 12 hours of milling time variation, is 2.89, 3.39, and 4.98 emu/g, for the coercivity (Hc) is 209.58, 188.47, and 223.65 Oe and the magnetic saturation number is 22.59, 30.7, 39.15 emu/g, from Hc value it is concluded that the powder has superparamagnetic behavior. From SEM-EDS is knowed that the distribution of Fe is more uniform on the surface samples with the increase of milling time.
DEVELOPMENT AND CHARACTERIZATION OF SOLID CU / CUSO4 REFERENCE ELECTRODES
Authors: Dewi Marysca Shintya , Alva Sagir , Wan Jamil Wan Adil 
Published: June 2021

In this research, a solid Cu/CuSO4 reference electrode has been developed. In this development process, the Cu/CuSO4 solid reference electrode provided consists of two types, namely the Cu/CuSO4 I solid reference electrode (ERP Cu/CuSO4 I) and the Cu/CuSO4 II solid reference electrode (ERP Cu/CuSO4 II). ERP Cu/CuSO4 I was prepared using two layers, namely the Cu/CuSO4 layer and the cellulose acetate layer which were placed sequentially on the surface of the planar type Cu electrode. Meanwhile, ERP Cu/CuSO4 II was prepared using three layers, namely a layer of cotton fiber/cellulose acetate, a layer of Cu/CuSO4, and a layer of cotton/cellulose acetate placed in sequence on the surface of the planar type Cu electrode, where the CuSO4 layer is between the two layers of cotton/cellulose acetate. Both types of Cu/CuSO4 solid reference electrodes were characterized by testing DmV in various concentrations of KCl solution and ERP Cu/CuSO4 II has been produced as the best reference electrode for Cu/CuSO4 solids with a DmV value of 3.3 mV. Furthermore, ERP Cu/CuSO4 II was selected for characterization using cyclic voltammetry (CV) testing, response vs Cl sensor testing, and drif testing. In CV testing, ERP Cu/CuSO4 provides a voltammogram graph pattern similar to the Ag/AgCl reference electrode as a commercial reference electrode. Meanwhile, in testing the response vs sensor Cl, ERP Cu/CuSO4 II gave a Nernstian number value of -50.1 mV/decade with a test range of 0.1-10-3 M. ERP Cu/CuSO4 II showed fairly good stability, namely with a drift value of 0.46 mV/minute which is achieved after the conditioning process after 12 minutes.
EFFECT OF WELDING HEAT INPUT ON THE CORROSION RATE OF CARBON STEEL MMA WELDING
Authors: Sitorus Melvin Bismark H 
Published: June 2021

AbstractSteel is one of materials which often used on steel construction, bridge construction, and high rise building construction. Construction using welding joint is expected able to withstand construction loads for a long time. After a while weldment will be exposed to corrosion that will be construction failure in turn. One of the most important parameter in welding is heat input, however it hasn’t obtain correlation between heat input and corrosion rate on MMA (Manual Metal Arch) weldment on mild steel. This paper aims to obtain correlation between heat input and corrosion rate of low carbon steel with MMA welding. The result was show that corrosion rate tend to decrease with adding of duration, where higher corrosion rate at heat input 0,8108 kJ/mm was 68,68 gm/m2 hr at duration 5 hour.
Real-Time Turkish Sign Language Recognition Using Cascade Voting Approach with Handcrafted Features
Authors: Karacı Abdulkadir , Akyol Kemal , Turut Mehmet Ugur 
Published: June 2021

Abstract
In this study, a machine learning-based system, which recognises the Turkish sign language person-independent in real-time, was developed. A leap motion sensor was used to obtain raw data from individuals. Then, handcraft features were extracted by using Euclidean distance on the raw data. Handcraft features include finger-to-finger, finger -to-palm, finger -to-wrist bone, palm-to-palm and wrist-to-wrist distances. LR, k-NN, RF, DNN, ANN single classifiers were trained using the handcraft features. Cascade voting approach was applied with two-step voting. The first voting was applied for each classifier’s final prediction. Then, the second voting, which voted the prediction of all classifiers at the final decision stage, was applied to improve the performance of the proposed system. The proposed system was tested in real-time by an individual whose hand data were not involved in the training dataset. According to the results, the proposed system presents 100 % value of accuracy in the classification of one hand letters. Besides, the recognition accuracy ratio of the system is 100 % on the two hands letters, except “J” and “H” letters. The recognition accuracy rates were 80 % and 90 %, respectively for “J” and “H” letters. Overall, the cascade voting approach presented a high average classification performance with 98.97 % value of accuracy. The proposed system enables Turkish sign language recognition with high accuracy rates in real time.
VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the Description of Resources
Authors: Djama Ouahiba 
Published: June 2021

Abstract
The description of resources and their relationships is an essential task on the web. Generally, the web users do not share the same interests and viewpoints. Each user wants that the web provides data and information according to their interests and specialty. The existing query languages, which allow querying data on the web, cannot take into consideration the viewpoint of the user. We propose introducing the viewpoint in the description of the resources. The Resource Description Framework (RDF) represents a common framework to share data and describe resources. In this study, we aim at introducing the notion of the viewpoint in the RDF. Therefore, we propose a View-Point Resource Description Framework (VP-RDF) as an extension of RDF by adding new elements. The existing query languages (e.g., SPARQL) can query the VP-RDF graphs and provide the user with data and information according to their interests and specialty. Therefore, VP-RDF can be useful in intelligent systems on the web.
Solving Systems of Linear Equations Based on Approximation Solution Projection Analysis
Authors: Lavendels Jurijs 
Published: June 2021

Abstract
The paper considers an iterative method for solving systems of linear equations (SLE), which applies multiple displacement of the approximation solution point in the direction of the final solution, simultaneously reducing the entire residual of the system of equations. The method reduces the requirements for the matrix of SLE. The following SLE property is used: the point is located farther from the system solution result compared to the point projection onto the equation. Developing the approach, the main emphasis is made on reduction of requirements towards the matrix of the system of equations, allowing for higher volume of calculations.
Feature extraction and gait classification in hip replacement patients on the basis of kinematic waveform data
Authors: Dindorf Carlo , Teufl Wolfgang , Taetz Bertram , Becker Stephan , Bleser Gabriele , Fröhlich Michael 
Published: June 2021

Abstract

Study aim: To find out, without relying on gait-specific assumptions or prior knowledge, which parameters are most important for the description of asymmetrical gait in patients after total hip arthroplasty (THA).

Material and methods: The gait of 22 patients after THA was recorded using an optical motion capture system. The waveform data of the marker positions, velocities, and accelerations, as well as joint and segment angles, were used as initial features. The random forest (RF) and minimum-redundancy maximum-relevance (mRMR) algorithms were chosen for feature selection. The results were compared with those obtained from the use of different dimensionality reduction methods.

Results: Hip movement in the sagittal plane, knee kinematics in the frontal and sagittal planes, marker position data of the anterior and posterior superior iliac spine, and acceleration data for markers placed at the proximal end of the fibula are highly important for classification (accuracy: 91.09%). With feature selection, better results were obtained compared to dimensionality reduction.

Conclusion: The proposed approaches can be used to identify and individually address abnormal gait patterns during the rehabilitation process via waveform data. The results indicate that position and acceleration data also provide significant information for this task.
Critical Success Factors of New Product Development: Evidence from Select Cases
Authors: Dwivedi Rajeev , Karim Fatma Jaffar , Starešinić Berislava 
Published: June 2021

Abstract

Background: The unique, yet complex, new product development (NPD) process represents one of firms’ most significant operations that impose high weightage onto its profitability margins and market reputation.

Objectives: The object of the research is to identify critical success factors (CSFs) of a new product development in Dubai firms.

Methods/Approach: The paper uses literature as a basis for identifying critical success factors for a new product development, which is supported by a semi-structured interview of senior management-level executives in Dubai.

Results: To pinpoint a set of the most influential CSFs, 12 factors for the NPD process are highlighted, based on their reoccurrence patterns in the literature and semi-structured interviews. Impact levels of 12 CSFs on the NPD process are expressed through a presentation from the highest to the lowest recurrent factor.

Conclusions: Each CSF’s role in driving the NPD process to success has also been justified using real-time evidence, depicted throughout 4 case studies from different industries.
Differences in Slovenian NUTS 3 Regions and Functional Regions by Gender
Authors: Drobne Samo 
Published: June 2021

Abstract

Background: Regions at the level of NUTS 3, which is a system used in the EU for various analyses and statistical reports, can be defined as functional regions in terms of labour markets, education areas, and supply markets.

Objectives: This study analyses the functional regions of Slovenia, differentiated by gender, and their correspondence with the statistical regions at the level of NUTS 3.

Methods/Approach: Functional regions are analysed as labour market areas, which are modelled according to the CURDS method, and evaluated using the fuzzy set approach.

Results: The analysis of functional regions resulted in ten regions for male commuters and fourteen regions for female commuters. Only four of the twelve functional regions for commuters relate to the corresponding statistical regions. Functional region Ljubljana is much larger than the corresponding statistical region, mainly at the expense of neighbouring regions. In recent decades, two new functional regions have been created which are becoming candidates for inclusion in the system of NUTS 3 regions.

Conclusions: A detailed analysis showed that functional region Velenje is becoming an important local labour market and should be included in the system of NUTS 3 regions of Slovenia, while the Central Sava Statistical Region should be removed from it.
The Effect of External Knowledge Sources on Organizational Innovation in Small and Medium Enterprises in Germany
Authors: Basit Shoaib Abdul 
Published: June 2021

Abstract

Background: Firms increasingly depend on external actors for the process of generating innovation. Interaction with these actors might occur through an official collaboration agreement or via external actors as the source of information.

Objectives: Although open innovation has received more attention, still less is known about its effect on organizational innovation. To fill this gap, this study investigates the impact of various external knowledge sources on the willingness of small and mediumsized enterprises to introduce organizational innovation.

Methods/Approach: To achieve the proposed objective, the German Community Innovation Survey conducted in 2017 is used for the econometric analysis.

Results: Different external sources of knowledge are relevant for the introduction of organizational innovation in small firms (customers in the private sector, competitors, conferences, and crowdsourcing) compared to medium-sized firms (customers in the private sector and industry associations).

Conclusions: External knowledge sources are more important for small firms compared to medium firms, and those small firms are more likely to use various sets of external knowledge.
Gender Disparity in Students’ Choices of Information Technology Majors
Authors: Zhang Yu , Gros Tristen , Mao En 
Published: June 2021

Abstract

Background: The gender disparity in the Information Technology (IT) field has persisted over the years. In 2018, only 27.2% of IT workers were women. Once hired, women face more challenges, and they are leaving the field twice as fast as men are. The misconception that women are weak in tech is one of the root causes of gender disparity issues in IT.

Objectives: We examine the gender disparity in students’ choices of IT majors, as well as the decision process of Computer Information Systems (CIS) graduates.

Methods/Approach: We use the United States public universities’ student data from 2010 to 2018. Both the Pooled and the Satterthwaite t-test are used to investigate the gender disparity issue among the students.

Results: Our results support our hypothesis that female students are statistically less likely to choose CIS than their male peers are. An additional analysis of students’ grades in CIS courses shows that female students perform equally well as male students do. We did not find any evidence that it takes longer for female students to get the CIS degree; however, female students did change their majors more often.

Conclusions: Female students tend to avoid IT majors; they often think they may not do well in the courses; however, such an assumption is not true. Our findings provide strategies for university and high school administration to be more proactive in developing recruiting strategies to attract and retain female CIS students.