Search results for: penalized spline regression method

Authors: Saih Mohamed, Rouijaa Hicham, Ghammaz Abdelilah

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This paper presents circuit models to analyze the conducted susceptibility of multiconductor shielded cables in frequency domains using Branin’s method, which is referred to as the method of characteristics. These models, Which can be used directly in the time and frequency domains, take into account the presence of both the transfer impedance and admittance. The conducted susceptibility is studied by using an injection current on the cable shield as the source. Two examples are studied, a coaxial shielded cable and shielded cables with two parallel wires (i.e., twinax cables). This shield has an asymmetry (one slot on the side). Results obtained by these models are in good agreement with those obtained by other methods.

Keywords: circuit models, multiconductor shielded cables, Branin’s method, coaxial shielded cable, twinax cables

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Authors: Saad Bin Nasir

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The study identifies the impact of inflation and foreign exchange rate on foreign direct investment in Pakistan. Inflation and exchange rates are used as independent variables and foreign direct investment is taken as dependent variable. Discreet time series data has been used from the period of 1999 to 2009. The results of regression analysis reveal that high inflation has negative impact on foreign direct investment and higher exchange rates has positive impact on foreign direct investment in Pakistan. The inflation and foreign exchange rates both are insignificant in the analysis.

Keywords: inflation rate, foreign exchange rate, foreign direct investment, foreign assets

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Authors: Haftay Abraha Tadesse, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from January to September 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli, Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI: (4.69 27.10) were associated with an overall bacterial contamination.About 95.5% of the tested isolates were sensitive to chloramphenicol and norfloxacin while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor hand washing practice and not using glove during meat handling showed significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, e. coli, salmonella species

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Authors: N. Dahbi, M. Daoudi

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This paper deals with the use of computational method based on Monte Carlo simulation in order to investigate the transport phenomena of the electron in HgCdTe narrow band gap semiconductor. Via this method we can evaluate the time dependence of the transport parameters: velocity, energy and mobility of electrons through matter (HgCdTe).

Keywords: Monte Carlo, transport parameters, HgCdTe, computational mechanics

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Authors: Emiel Caron

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Patent databases contain patent related data, organized in a relational data model, and are used to produce various patent statistics. These databases store raw data about scientific references cited by patents. For example, Patstat holds references to tens of millions of scientific journal publications and conference proceedings. These references might be used to connect patent databases with bibliographic databases, e.g. to study to the relation between science, technology, and innovation in various domains. Problematic in such studies is the low data quality of the references, i.e. they are often ambiguous, unstructured, and incomplete. Moreover, a complete bibliographic reference is stored in only one attribute. Therefore, a computerized cleaning and disambiguation method for large patent databases is developed in this work. The method uses rule-based scoring and clustering. The rules are based on bibliographic metadata, retrieved from the raw data by regular expressions, and are transparent and adaptable. The rules in combination with string similarity measures are used to detect pairs of records that are potential duplicates. Due to the scoring, different rules can be combined, to join scientific references, i.e. the rules reinforce each other. The scores are based on expert knowledge and initial method evaluation. After the scoring, pairs of scientific references that are above a certain threshold, are clustered by means of single-linkage clustering algorithm to form connected components. The method is designed to disambiguate all the scientific references in the Patstat database. The performance evaluation of the clustering method, on a large golden set with highly cited papers, shows on average a 99% precision and a 95% recall. The method is therefore accurate but careful, i.e. it weighs precision over recall. Consequently, separate clusters of high precision are sometimes formed, when there is not enough evidence for connecting scientific references, e.g. in the case of missing year and journal information for a reference. The clusters produced by the method can be used to directly link the Patstat database with bibliographic databases as the Web of Science or Scopus.

Keywords: clustering, data cleaning, data disambiguation, data mining, patent analysis, scientometrics

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Authors: Triana Fitriastuti, Pipiet Larasatie, Alex Vanderstraten

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Many scholars have demonstrated the negative impacts of the perception of organizational politics on organizational outcomes. The model proposed in this study analyzes the impact of the perception of organizational politics on job satisfaction. In the same way, ingratiation as a moderator variable is tested. We applied regression analysis to test the hypothesis. The findings of the current research, which was conducted with 240 employees in the public sector in Indonesia, show that the perception of organizational politics has a negative effect on job satisfaction. In contrast, ingratiation plays a role that fully moderates the relationship between organizational politics and organizational outcomes and changes the correlation between the perception of organizational politics on job satisfaction. Employees who use ingratiation as a coping mechanism tend to do so when they perceive a high degree of organizational politics.

Keywords: ingratiation, impression management, job satisfaction, perception of organizational politics

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Authors: A. Rezaei, M. Huisman, W. Van Paepegem

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Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

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Authors: Mahmoud A. Rabah, Said El Sheikh

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This work shows the preparation of chromium nanoparticles from tannery waste solution on glassy carbon by chemical method compared to electrokinetic process. The waste solution contains free and soluble fats, calcium, iron, magnesium and high sodium in addition to the chromium ions. Filtration helps removal of insoluble matters. Diethyl ether successfully extracted soluble fats. The method started by removing calcium as insoluble oxalate salts at hot conditions in a faint acidic medium. The filtrate contains iron, magnesium, chromium ions and sodium chloride in excess. Chromium was separated selectively as insoluble hydroxide sol-gel at pH 6.5, filtered and washed with distilled water. Part of the gel reacted with sulfuric acid to produce chromium sulfate solution having 15-25 g/L concentration. Electrokinetic deposition of chromium nanoparticles on a carbon cathode was carried out using platinum anode under different galvanostatic conditions. The chemical method involved impregnating the carbon specimens with chromium hydroxide gel followed by reduction using hydrazine hydrate or by thermal reduction using hydrogen gas at 1250°C. Chromium grain size was characterized by TEM, FT-IR and SEM. Properties of the Cr grains were correlated to the conditions of the preparation process. Electrodeposition was found to control chromium particles to be more identical in size and shape as compared to the chemical method.

Keywords: chromium, electrodeposition, nanoparticles, tannery waste solution

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Authors: Erdal Akyol, Mutlu Alkan

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Multi criteria decision analysis (MDCA) covers both data and experience. It is very common to solve the problems with many parameters and uncertainties. GIS supported solutions improve and speed up the decision process. Weighted grading as a MDCA method is employed for solving the geotechnical problems. In this study, geotechnical parameters namely soil type; SPT (N) blow number, shear wave velocity (Vs) and depth of underground water level (DUWL) have been engaged in MDCA and GIS. In terms of geotechnical aspects, the settlement suitability of the municipal area was analyzed by the method. MDCA results were compatible with the geotechnical observations and experience. The method can be employed in geotechnical oriented microzoning studies if the criteria are well evaluated.

Keywords: GIS, spatial analysis, multi criteria decision analysis, geotechnics

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Authors: Jin-Lung Guan, Jyh-Cherng Gu, Chun-Wei Huang, Hsin-Hung Chang

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This investigation develops a revisable method for estimating the estimate value of equivalent 10 Hz voltage flicker (DV10) of a DC Electric Arc Furnace (EAF). This study also discusses three 161kV DC EAFs by field measurement, with those results indicating that the estimated DV10 value is significantly smaller than the survey value. The key point is that the conventional means of estimating DV10 is inappropriate. There is a main cause as the assumed Qmax is too small. Although DC EAF is regularly operated in a constant MVA mode, the reactive power variation in the Main Transformer (MT) is more significant than that in the Furnace Transformer (FT). A substantial difference exists between estimated maximum reactive power fluctuation (DQmax) and the survey value from actual DC EAF operations. However, this study proposes a revisable method that can obtain a more accurate DV10 estimate than the conventional method.

Keywords: voltage flicker, dc EAF, estimate value, DV10

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Authors: Seyed Amin Vakili, Sahar Sadat Vakili, Seyed Ehsan Vakili, Nader Abdoli Yazdi

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Differential equations are of fundamental importance in engineering and applied mathematics, since many physical laws and relations appear mathematically in the form of such equations. The equilibrium state of structures consisting of one-dimensional elements can be described by an ordinary differential equation. The response of these kinds of structures under the loading, namely relationship between the displacement field and loading field, can be predicted by the solution of these differential equations and on satisfying the given boundary conditions. When the effect of change of geometry under loading is taken into account in modeling of equilibrium state, then these differential equations are partially integrable in quartered. They also exhibit instability characteristics when the structures are loaded compressively. The purpose of this paper is to represent the ability of the Modified Newmark Method in analyzing flexural-torsional instability of struts for both bifurcation and non-bifurcation structural systems. The results are shown to be very accurate with only a small number of iterations. The method is easily programmed, and has the advantages of simplicity and speeds of convergence and easily is extended to treat material and geometric nonlinearity including no prismatic members and linear and nonlinear spring restraints that would be encountered in frames. In this paper, these abilities of the method will be extended to the system of linear differential equations that govern strut flexural torsional stability.

Keywords: instability, torsion, flexural, buckling, modified newmark method stability

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Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

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Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: M. Yousaf, S. Usman

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The present study focused on the investigation of the effects of roughness elements on heat transfer during natural convection in a rectangular cavity using a numerical technique. Roughness elements were introduced on the bottom hot wall with a normalized amplitude (A*/H) of 0.1. Thermal and hydrodynamic behavior was studied using a computational method based on Lattice Boltzmann method (LBM). Numerical studies were performed for a laminar natural convection in the range of Rayleigh number (Ra) from 103 to 106 for a rectangular cavity of aspect ratio (L/H) 2 with a fluid of Prandtl number (Pr) 1.0. The presence of the sinusoidal roughness elements caused a minimum to the maximum decrease in the heat transfer as 7% to 17% respectively compared to the smooth enclosure. The results are presented for mean Nusselt number (Nu), isotherms, and streamlines.

Keywords: natural convection, Rayleigh number, surface roughness, Nusselt number, Lattice Boltzmann method

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Authors: Julien Deborde, Thomas Milcent, Stéphane Glockner, Pierre Lubin

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A fully Eulerian method is developed to solve the problem of fluid-elastic structure interactions based on a 1-fluid method. The interface between the fluid and the elastic structure is captured by a level set function, advected by the fluid velocity and solved with a WENO 5 scheme. The elastic deformations are computed in an Eulerian framework thanks to the backward characteristics. We use the Neo Hookean or Mooney Rivlin hyperelastic models and the elastic forces are incorporated as a source term in the incompressible Navier-Stokes equations. The velocity/pressure coupling is solved with a pressure-correction method and the equations are discretized by finite volume schemes on a Cartesian grid. The main difficulty resides in that large deformations in the fluid cause numerical instabilities. In order to avoid these problems, we use a re-initialization process for the level set and linear extrapolation of the backward characteristics. First, we verify and validate our approach on several test cases, including the benchmark of FSI proposed by Turek. Next, we apply this method to study the wave damping phenomenon which is a mean to reduce the waves impact on the coastline. So far, to our knowledge, only simulations with rigid or one dimensional elastic structure has been studied in the literature. We propose to place elastic structures on the seabed and we present results where 50 % of waves energy is absorbed.

Keywords: damping wave, Eulerian formulation, finite volume, fluid structure interaction, hyperelastic material

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Authors: Houcine Naim, Abdelatif Hassini, Noureddine Benabadji, Alex Van Den Bossche

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In this paper, two models to estimate the overall monthly average daily radiation on a horizontal surface were applied to the site of Oran (35.38 ° N, 0.37 °W). We present a comparison between the first one is a regression equation of the Angstrom type and the second model is developed by the present authors some modifications were suggested using as input parameters: the astronomical parameters as (latitude, longitude, and altitude) and meteorological parameters as (relative humidity). The comparisons are made using the mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), and mean absolute bias error (MABE). This comparison shows that the second model is closer to the experimental values that the model of Angstrom.

Keywords: meteorology, global radiation, Angstrom model, Oran

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Authors: Gigih Supriyatno

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SQL injection is one of the most common types of attacks and has a very critical impact on web servers. In the worst case, an attacker can perform post-exploitation after a successful SQL injection attack. In the case of forensics web servers, web server analysis is closely related to log file analysis. But sometimes large file sizes and different log types make it difficult for investigators to look for traces of attackers on the server. The purpose of this paper is to help investigator take appropriate steps to investigate when the web server gets attacked. We use attack scenarios using SQL injection attacks including PHP backdoor injection as post-exploitation. We perform post-mortem analysis of web server logs based on Hypertext Transfer Protocol (HTTP) POST and HTTP GET method approaches that are characteristic of SQL injection attacks. In addition, we also propose structured analysis method between the web server application log file, database application, and other additional logs that exist on the webserver. This method makes the investigator more structured to analyze the log file so as to produce evidence of attack with acceptable time. There is also the possibility that other attack techniques can be detected with this method. On the other side, it can help web administrators to prepare their systems for the forensic readiness.

Keywords: web forensic, SQL injection, investigation, web shell

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Authors: Matthew Cardeiro, Amalia D. Ardeljan, Lexi Frankel, Dianela Prado Escobar, Catalina Molnar, Omar M. Rashid

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Introduction: Enterococci comprise the natural flora of nearly all animals and are ubiquitous in food manufacturing and probiotics. However, its role in the microbiome remains controversial. The gut microbiome has shown to play an important role in immunology and cancer. Further, recent data has suggested a relationship between gut microbiota and breast cancer. These studies have shown that the gut microbiome of patients with breast cancer differs from that of healthy patients. Research regarding enterococcus infection and its sequala is limited, and further research is needed in order to understand the relationship between infection and cancer. Enterococcus may prevent the development of breast cancer (BC) through complex immunologic and microbiotic adaptations following an enterococcus infection. This study investigated the effect of enterococcus infection and the incidence of BC. Methods: A retrospective study (January 2010- December 2019) was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using a Humans Health Insurance Database. International Classification of Disease (ICD) 9th and 10th codes, Current Procedural Terminology (CPT), and National Drug Codes were used to identify BC diagnosis and enterococcus infection. Patients were matched for age, sex, Charlson Comorbidity Index (CCI), antibiotic treatment, and region of residence. Chi-squared, logistic regression, and odds ratio were implemented to assess the significance and estimate relative risk. Results: 671 out of 28,518 (2.35%) patients with a prior enterococcus infection and 1,459 out of 28,518 (5.12%) patients without enterococcus infection subsequently developed BC, and the difference was statistically significant (p<2.2x10⁻¹⁶). Logistic regression also indicated enterococcus infection was associated with a decreased incidence of BC (RR=0.60, 95% CI [0.57, 0.63]). Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 398 out of 11,523 (3.34%) patients with a prior enterococcus infection and treated with antibiotics were compared to 624 out of 11,523 (5.41%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed BC. Results remained statistically significant (p<2.2x10-16) with a relative risk of 0.57 (95% CI [0.54, 0.60]). Conclusion & Discussion: This study shows a statistically significant correlation between enterococcus infection and a decrease incidence of breast cancer. Further exploration is needed to identify and understand not only the role of enterococcus in the microbiome but also the protective mechanism(s) and impact enterococcus infection may have on breast cancer development. Ultimately, further research is needed in order to understand the complex and intricate relationship between the microbiome, immunology, bacterial infections, and carcinogenesis.

Keywords: breast cancer, enterococcus, immunology, infection, microbiome

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Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Majid A. AlSayari

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The study reported here investigated social cognitive theory (SCT) in the context of Vocational Rehab (VR) for people with disabilities. The prime purpose was to increase knowledge of VR phenomena and make recommendations for improving VR services. The sample consisted of 242 persons with Spinal Cord Injuries (SCI) who completed questionnaires. A further 32 participants were Trainers. Analysis of questionnaire data was carried out using factor analysis, multiple regression analysis, and thematic analysis. The analysis suggested that, in motivational terms, and consistent with research carried out in other academic contexts, self-efficacy was the best predictor of VR performance. The author concludes that that VR self-efficacy predicted VR training performance.

Keywords: people with physical disabilities, social cognitive theory, self-efficacy, vocational training

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Authors: Min Woo Lee, Kyoung Seok Kim

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We made an effort to resolve a research question, which is about the relationship between employees’ corporate social responsibility (CSR) participation and their organizational citizenship behavior (OCB), and an effect of profiles of job characteristics. To test the question, we divided sample into two groups that have the profiles of each job characteristic. One group had high level on the five dimensions of job characteristic (D group), whereas another group had low level on the dimensions (R group). As a result, regression analyses showed that the relationship between CSR participation and OCB is positive in the D group, but the relationship is not significant in the R group. The results raise a question to the argument of recent studies showing that there is positive relationship between the CSR and the OCB. Implications and limitations are demonstrated in the conclusion.

Keywords: CSR, OCB, job characteristics, cluster analysis

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Authors: Alper Serdar Anli

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Analysis of temporal variation of reference evapotranspiration (ET0) is important in arid and semi-arid regions where water resources are limited. In this study, temporal variation of reference evapotranspiration (ET0) and meteorological drought analysis through SPEI (Standardized Precipitation Evapotranspiration Index) method have been carried out in provinces of Central Anatolia Region, Turkey. Reference evapotranspiration of concerning provinces in the region has been estimated using Penman-Monteith method and one calendar year has been split up four periods as r1, r2, r3 and r4. Temporal variation of reference evapotranspiration according to four periods has been analyzed through parametric Dickey-Fuller test and non-parametric Mann-Whitney U test. As a result, significant increasing trends for reference evapotranspiration have been detected and according to SPEI method used for estimating meteorological drought in provinces, mild drought has been experienced in general, and however there have been also a significant amount of events where moderate and severely droughts occurred.

Keywords: central Anatolia region, drought index, Penman-Monteith, reference evapotranspiration, temporal variation

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Authors: Liubov Evstigneeva

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In this paper an attempt is made to establish causal nexuses between innovation and international trade in Russia. The topicality of this issue is determined by the necessity of choosing policy instruments for economic modernization and transition to innovative development. The vector auto regression (VAR) model and Granger test are applied for the Russian monthly data from 2005 until the second quartile of 2015. Both lagged import and export at the national level cause innovation, the latter starts to stimulate foreign trade since it is a remote lag. In comparison to aggregate data, the results by patent’s categories are more diverse. Importing technologies from foreign countries stimulates patent activity, while innovations created in Russia are only Granger causality for import to Commonwealth of Independent States.

Keywords: export, import, innovation, patents

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Authors: Nosakhare Enoma, Alphose Zingoni

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The requirements for various toroidal shell forms are increasing due to new applications, available storage space and the consideration of appearance. Because of the complexity of some of these structural forms, the finite element method is nowadays mainly used for their analysis, even for simple static studies. This paper presents an easy-to-use analytical algorithm for pressurized multi-segmented toroidal shells of revolution. The membrane solution, which acts as a particular solution of the bending-theory equations, is developed based on membrane theory of shells, and a general approach is formulated for quantifying discontinuity effects at the shell junctions using the well-known Geckeler’s approximation. On superimposing these effects, and applying the ensuing solution to the problem of the pressurized toroid with four segments, closed-form stress results are obtained for the entire toroid. A numerical example is carried out using the developed method. The analytical results obtained show excellent agreement with those from the finite element method, indicating that the proposed method can be also used for complementing and verifying FEM results, and providing insights on other related problems.

Keywords: bending theory of shells, membrane hypothesis, pressurized toroid, segmented toroidal vessel, shell analysis

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Authors: Christian Rathgeber, Franz Winkler, Xiaoyu Kang, Steffen Müller

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In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results.

Keywords: trajectory planning, direct method, indirect method, highly automated driving

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Authors: Ho-Nyeon Lee

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We propose to use a gradual-refractive-index dielectric (GRID) as a simple and efficient light-outcoupling method for organic light-emitting diodes (OLEDs). Using the simple GRIDs, we could improve the light outcoupling efficiency of OLEDs rather than relying on difficult nano-patterning processes. Through numerical simulations using a finite-difference time-domain (FDTD) method, the feasibility of the GRID structure was examined and the design parameters were extracted. The outcoupling enhancement effects due to the GRIDs were proved through severe experimental works. The GRIDs were adapted to bottom-emission OLEDs and top-emission OLEDs. For bottom-emission OLEDs, the efficiency was improved more than 20%, and for top-emission OLEDs, more than 40%. The detailed numerical and experimental results will be presented at the conference site.

Keywords: efficiency, GRID, light outcoupling, OLED

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Authors: Ewedafe Simon Uzezi

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In this paper we presented a method based on Domain Decomposition (DD) for parallelization of 1-D Sugarcane Equation on parallel platform with parallel paradigms on Master-Slave platform using Message Passing Interface (MPI). The 1-D Sugarcane Equation was discretized using explicit method of discretization requiring evaluation nof temporal and spatial distribution of temperature. This platform gives better predictions of the effects of temperature distribution of the sugarcane problem. This work presented parallel overheads with overlapping communication and communication across parallel computers with numerical results across different block sizes with scalability. However, performance improvement strategies from the DD on various mesh sizes were compared experimentally and parallel results show speedup and efficiency for the parallel algorithms design.

Keywords: sugarcane, parallelization, explicit method, domain decomposition, MPI

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Authors: Chao-Qing Dai

Abstract:

In modern nonlinear science and textile engineering, nonlinear differential-difference equations are often used to describe some nonlinear phenomena. In this paper, we extend the variable coefficient Jacobian elliptic function method, which was used to find new exact travelling wave solutions of nonlinear partial differential equations, to nonlinear differential-difference equations. As illustration, we derive two series of Jacobian elliptic function solutions of the discrete sine-Gordon equation.

Keywords: discrete sine-Gordon equation, variable coefficient Jacobian elliptic function method, exact solutions, equation

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Authors: Maryam Eskafi

Abstract:

Purpose: Frequent referrals of the martyr offspring to The Martyr Foundation and studying divorce documents revealed the depth of family quarrels among the martyr families. For this reason, conducting the research of this type can be effective. Method: Research method is survey. Statistical population is the total of married offspring of the martyr living in Mashhad City of Iran. Data were gathered by using questionnaire administered with a sample of 250 selected by using cluster sampling method. Results: Family order may lead to the ground actions for divorce through life satisfaction. Conclusion: life satisfaction with -0.62 beta value has a strong negative effect on the ground actions for divorce.

Keywords: ground actions for divorce, life satisfaction, family order, satisfaction

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