nils-herrmann/clean_scirepeval huggingface dataset:
Los roles de genero y su papel en las actitudes y comportamientos afectivo sexuales: un estudio sobre adolescentes salmantinos
Year: 2016

En el presente estudio centramos nuestro interes en evaluar las actitudes, conocimientos y comportamientos de los adolescentes respecto a la sexualidad y sus practicas, asi como el impacto de variables como el genero en estas valoraciones. Metodologia. El estudio se ha llevado a cabo con una muestra de conveniencia de 141 estudiantes de Bachillerato o de modulos profesionales residentes en Salamanca, Espana. Dichos alumnos fueron evaluados mediante el Cuestionario para adolescentes sobre educacion sexual. Resultados. Los datos indican que existe un amplio desconocimiento sobre temas basicos relacionados con el uso del preservativo o el embarazo. Se encuentran ademas claras relaciones entre el genero y actitudes hacia la homosexualidad, la prostitucion, la consideracion de la sexualidad o la propia actividad sexual. Discusion. Es necesario llevar a cabo programas formativos que mejoren los conocimientos y fomenten actitudes y conductas positivas y saludables y respetuosas hacia la sexualidad propia y ajena.
Green synthesis of hydrophilic activated carbon supported sulfide nZVI for enhanced Pb(II) scavenging from water: Characterization, kinetics, isotherms and mechanisms.
Venue: Journal of hazardous materials
Year: 2020

For green synthesis of nZVI with low aggregation and high antioxidation, green tea extracts were explored as reductant during the synthesis with modification by hydrophilic porous activated carbon (HPAC) and sulfidation technology. Characterization results identified the effective preparation of porous activated carbon (PAC) with microporous and mesoporous characteristics, and the successful loading of S nZVI nanoparticles on S nZVI@HPAC. Moreover, HPAC was identified to have a higher degree of hydrophilicity surface compared to PAC, while the S nZVI with an atomic ratio of S/Fe (0.16) further improved the hydrophilic performance of S nZVI@HPAC. Batch adsorption revealed that the S nZVI@HPAC possessed a pH dependent adsorption performance with a fast kinetic equilibrium within 120 min and an outstanding Pb(II) binding of 295.30 mg/g at pH 5.0 and 50 degC. Thermodynamic results exhibited positive DHdeg and DSdeg, clearly indicative of the endothermic property of Pb(II) uptake onto S nZVI@HPAC with an increase in randomness, while the negative DGdeg uncovered a favorable and spontaneous process. Furthermore, the S nZVI@HPAC was believed to enhance the Pb(II) uptake via the synergistic effects of electrostatic attraction, chemical precipitation, complexation and reduction. The results of this work highlighted the hydrophilic porous activated carbon supported sulfide nZVI for efficient remediation of Pb(II) contaminated water.
Flipping an English writing class with technology enhanced just in time teaching and peer instruction
Venue: Interact. Learn. Environ.
Year: 2019

Just in time teaching and peer instruction are two student centred approaches that have been widely employed in various science subjects but seldom in language classrooms. This research proposed a flipped learning model through technology enhanced just in time teaching and peer instruction and investigated the effectiveness of this model in promoting English learning. Two groups of upper intermediate EFL learners participated in the study and learned in two different flipped learning modes, one with the newly proposed approach and the other with the conventional flipped learning approach. The results showed that the proposed model outperformed the conventional model in promoting the development of students' writing skills, motivation, and tendency of critical thinking. The use of an assessment centred tool (e.g. EDpuzzle) for interactive videos and cloud based tools for real time collaboration (e.g. Padlet and Google Docs) assisted in creating scaffolded learning experience, sharing culture, and opportunities of peer instruction for students in the flipped classroom with Just in time teaching and peer instruction. Such results implied that our flipped learning model is very conducive to language learning, and it is advised to be employed more widely in various language learning classes.
A Level Set Immersed Boundary Method for Reactive Transport in Complex Topologies with Moving Interfaces.
Year: 2020

A simulation framework based on the level set and the immersed boundary methods (LS IBM) has been developed for reactive transport problems in porous media involving a moving solid fluid interface. The interface movement due to surface reactions is tracked by the level set method, while the immersed boundary method captures the momentum and mass transport at the interface. The proposed method is capable of accurately modeling transport near evolving boundaries in Cartesian grids. The framework formulation guarantees second order of accuracy. Since the interface velocity is only defined at the moving boundary, a physics based interface velocity propagation method is also proposed. The method can be applied to other moving interface problems of the "Stefan" type. Here, we validate the proposed LS IBM both for flow and transport close to an immersed object with reactive boundaries as well as for crystal growth. The proposed method provides a powerful tool to model more realistic problems involving moving reactive interfaces in complex domains.
Monte Carlo SURE Based Parameter Selection for Parallel Magnetic Resonance Imaging Reconstruction
Year: 2013

Regularizing parallel MRI reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein's unbiased risk estimate (SURE) that minimizes the multi channel k space mean squared error (MSE) We automatically tune parameters for image reconstruction methods that preserve the undersampled acquired data, which cannot be accomplished using existing techniques.  We derive a weighted MSE criterion appropriate for data preserving regularized parallel imaging reconstruction and the corresponding weighted SURE. We describe a Monte Carlo approximation of the weighted SURE that uses two evaluations of the reconstruction method per candidate parameter value.  We reconstruct images using the sparsity promoting methods DESIGN and L1 SPIRiT. We validate Monte Carlo SURE against the weighted MSE. We select the regularization parameter using these methods for various noise levels and undersampling factors and compare the results to those using MSE optimal parameters.  Our method selects nearly MSE optimal regularization parameters for both DESIGN and L1SPIRiT over a range of noise levels and undersampling factors.  The proposed method automatically provides nearly MSE optimal choices of regularization parameters for data preserving nonlinear parallel MRI reconstruction methods.
Pattern Division Multiple Access (PDMA)
Year: 2019

Pattern division multiple access (PDMA) is a kind of non orthogonal multiple access technology based on the principle of the introduced reasonable diversity between multi user and joint design between transmitter and receiver to promote the capacity. PDMA can be used in 5G typical scenarios like eMBB, URLLC and mMTC, enhancing spectrum efficiency, increasing connections and decreasing latency. Followed by research work on key technologies of PDMA, PDMA was formerly included in the new technology trend report of ITU R and now is being hotly discussed in 5G new radio standardization in 3GPP, also PDMA has passed the MIIT of China 5G trial. Further, more and more PDMA based extension technologies are being proposed by academics, pushing forward PDMA development.
Dissecting the pathophysiology of immune thrombotic thrombocytopenic purpura: interplay between genes and environmental triggers
Venue: Haematologica
Year: 2021

"Activation of ADAMTS13 specific CD4+ T cells requires uptake of ADAMTS13 by antigen presenting cells (APCs) and presentation of ADAMTS13 derived peptides on HLA molecules. As the HLA DRB1*11 was identified as a risk factor for the development of iTTP, investigation of ADAMTS13 derived peptides that are preferentially presented on MHC class II of healthy individuals positive for this allele was performed."
Support Vector Regression for the Modeling and Synthesis of Near Field Focused Antenna Arrays
Year: 2019

The powerful support vector regression framework is proposed in a novel method for near field focusing using antenna arrays. By using this machine learning method, the set of weights required in the elements of an array can be calculated to achieve an assigned near field distribution focused on one or more positions. The computational cost is concentrated in an initial training process so that the trained system is fast enough for applications where moving devices are involved. The increased learning capabilities of support vector machines allow using a reduced number of training samples. Thus, these training samples may be generated with a prototype or a convenient electromagnetic analysis tool, and hence realistic effects, such as coupling or the individual radiation patterns of the elements of the arrays, are accounted for. Illustrative examples are presented.
Dynamic Modeling and Optimal Control of a Wind Turbine with Doubly Fed Induction Generator Using Imperialist Competitive and Artificial Bee Colony Algorithms
Venue: J. Circuits Syst. Comput.
Year: 2019

This paper addresses modeling, stability analysis and control of the doubly fed induction generator (DFIG) for wind turbines (WTs) In the present work, imperialist competitive and artificial bee colony algorithms are used for optimizing parameters of controllers of a WT with DFIG. Algorithms for optimizing the controllers' parameters are described. Based on this, an eigenvalue based objective function is utilized to optimize the parameters. To evaluate the optimized gains, simulations are performed on a single machine infinite bus system, and the dynamic responses of system with parameters obtained from two optimization techniques are compared.
Solar photovoltaics demand for the global energy transition in the power sector
Year: 2018

The power sector is faced with strict requirements in reducing harmful emissions and substantially increasing the level of sustainability. Renewable energy (RE) in general and solar photovoltaic (PV) in particular can offer societally beneficial solutions. The LUT energy system transition model is used to simulate a cost optimised transition pathway towards 100% RE in the power sector by 2050. The model is based on hourly resolution for an entire year, the world structured in 145 regions, high spatial resolution of the input RE resource data, and transition steps of 5 year periods. The global average solar PV electricity generation contribution is found to be about 69% in 2050, the highest ever reported. Detailed energy transition results are presented for representative countries in the world, namely, Poland, Britain and Ireland, Turkey, Saudi Arabia, Brazil, Ethiopia, and Indonesia. The global average energy system levelised cost of electricity gradually declines from 70 EUR/MWh in 2015 to 52 EUR/MWh in 2050 throughout the transition period, while deep decarbonisation of more than 95% around 2040, referenced to 2015, would be possible. The targets of the Paris Agreement can be well achieved in the power sector, while increasing societal welfare, given strong policy leadership.
Lifetime prevalence and age of onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative.
Venue: World psychiatry official journal of the World Psychiatric Association
Year: 2007

Data are presented on the lifetime prevalence, projected lifetime risk, and age of onset distributions of mental disorders in the World Health Organization (WHO)'s World Mental Health (WMH) Surveys. Face to face community surveys were conducted in seventeen countries in Africa, Asia, the Americas, Europe, and the Middle East. The combined numbers of respondents were 85,052. Lifetime prevalence, projected lifetime risk, and age of onset of DSM IV disorders were assessed with the WHO Composite International Diagnostic Interview (CIDI) a fully structured lay administered diagnostic interview. Survival analysis was used to estimate lifetime risk. Median and inter quartile range (IQR) of age of onset is very early for some anxiety disorders (7 14, IQR: 8 11) and impulse control disorders (7 15, IQR: 11 12) The age of onset distribution is later for mood disorders (29 43, IQR: 35 40) other anxiety disorders (24 50, IQR: 31 41) and substance use disorders (18 29, IQR: 21 26) Median and IQR lifetime prevalence estimates are: anxiety disorders 4.8 31.0% (IQR: 9.9 16.7% mood disorders 3.3 21.4% (IQR: 9.8 15.8% impulse control disorders 0.3 25.0% (IQR: 3.1 5.7% substance use disorders 1.3 15.0% (IQR: 4.8 9.6% and any disorder 12.0 47.4% (IQR: 18.1 36.1% Projected lifetime risk is proportionally between 17% and 69% higher than estimated lifetime prevalence (IQR: 28 44% with the highest ratios in countries exposed to sectarian violence (Israel, Nigeria, and South Africa) and a general tendency for projected risk to be highest in recent cohorts in all countries. These results document clearly that mental disorders are commonly occurring. As many mental disorders begin in childhood or adolescents, interventions aimed at early detection and treatment might help reduce the persistence or severity of primary disorders and prevent the subsequent onset of secondary disorders.
Organisation de log de requetes OLAP sous forme de site web
Venue: EDA
Year: 2010

Vu comme une simple collection de requetes, un log de requetes d'un serveur OLAP est une structure peu exploitable. Dans cet article, nous proposons d'organiser un log de requetes d'un serveur OLAP sous la forme d'un site web. Cela a plusieurs avantages, comme la comprehension rapide de ce qui a ete fait lors des sessions d'analyse precedentes ou comme l'aide aux futures sessions d'ana lyse. La technique utilisee a fait ses preuves pour la reorganisation de sites web. Le log est transforme en un graphe pondere de requetes, les poids refletant une similarite entre requetes. Cette similarite est calculee en tenant compte a la fois des faits interroges et de la presence ou non des deux requetes au sein de la meme session. Ces poids sont ensuite ajustes par une heuristique utilisant des fourmis artificielles pour trouver un equilibre entre ces deux facteurs. Enfin le log est presente sous la forme d'un site web dont la structure est l'arbre couvrant minimal de ce graphe. Cette technique est implementee en java pour le traitement de logs de requetes MDX. Des experiences ont ete conduites sur des logs synthetiques pour tester la qualite des solutions obtenues selon des criteres utilises dans le domaine du web et des interfaces homme machine.
pyBathySfM v4.0
Year: 2019

Initial release for DOI Updates are available through the GitHub repository https:/github.com/geojames/pyBathySfM A tutorial/walk through is also available https:/geojames.github.io/pyBathySfM/ Please also cite the original paper that this software was used in: Dietrich JT. 2017.  Structure from Motion: extracting shallow stream bathymetry from multi view stereo photogrammetry. Earth Surface Processes and Landforms 42 355 364.
Pain in a chromium allergic patient with total knee arthroplasty: disappearance of symptoms after revision with a special surface coated TKA a case report
Venue: Acta orthopaedica
Year: 2011

In 2005, a 60 year old woman suffering from osteoarthritis received a total knee replacement (TKA) (e.motion, BBraun Aesculap, Tuttlingen, Germany) in another hospital. The prosthesis was implanted using antibiotic loaded cement. Postoperatively, she suffered reduced mobility (E/F 0/10/60deg) and her knee pain did not get better. In 2006, since the pain continued, a cemented retropatellar replacement was implanted. Radiological examination did not reveal any sign of a mechanical complication, but the pain still persisted and the patient was admitted to our hospital. Now, she complained of partly eczematous reactions (local itching, partial oozing, eczematous rashes) which appeared about half a year after the primary surgery  Blood counts including C reactive protein test and bacteriological tests after joint aspiration virtually excluded a low grade infection. A lymphocyte transformation test showed no increased values for metal ions (chromium, cobalt, nickel)
Mid Wave and Long Wave Single Uni polar Barrier Infrared Detectors Based on Antimonide Material Systems
Year: 2013

Infrared detectors are very important technological tools for many different applications. Infrared detectors have existed as far back as the late 1700s but received a tremendous push 200 years later during World War II. Both thermal and photon based infrared detectors have had significant advancements with many different varieties becoming available with varying degrees of sensitivity, speed, and wavelength sensitivity. One of the best performing technologies is based on Mercury Cadmium Telluride. However, it still has limitations with regard to low operating temperature, material yield and processing difficulties. A newer material technology known as type II indium arsenide/gallium antimonide strain layered superlattice has received much attention for its potential superior performance from lower dark current, mature III V material fabrication techniques, and design versatility. However, superior
A Weighted Graph Attention Network Based Method for Multi label Classification of Electrocardiogram Abnormalities
Venue: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine Biology Society (EMBC)
Year: 2020

The multi label electrocardiogram (ECG) classification is to automatically predict a set of concurrent cardiac abnormalities in an ECG record, which is significant for clinical diagnosis. Modeling the cardiac abnormality dependencies is the key to improving classification performance. To capture the dependencies, we proposed a multi label classification method based on the weighted graph attention networks. In the study, a graph taking each class as a node was mapped and the class dependencies were represented by the weights of graph edges. A novel weights generation method was proposed by combining the self attentional weights and the prior learned co occurrence knowledge of classes. The algorithm was evaluated on the dataset of the Hefei Hi tech Cup ECG Intelligent Competition for 34 kinds of ECG abnormalities classification. And the micro f 1 and the macro f 1 of cross validation respectively were 91.45% and 44.48% The experiment results show that the proposed method can model class dependencies and improve classification performance.
Los roles y estereotipos de genero en los comportamientos sexuales de jovenes de Coahuila, Mexico: aproximacion desde la Teoria Fundamentada
Year: 2016

This research is a qualitative approach whose objective was to identify the roles and stereotypes of gender and the sexual behaviors of college students. The method of analysis used for this work, was the grounded theory, in particular, the open and axial coding processes. The gathering of the information was through a structured interview, using certain questions such as: What are the men and women's behaviors expected in their sexual encounters? And how much do they agree with these behaviors? We conclude that sexual behavior between men and women keep differences concerning the socialization of gender, based on the traditions of the characters' roles and the stereotypes as well as their transgression.
Revisiting where are the hard knapsack problems? via Instance Space Analysis
Venue: Comput. Oper. Res.
Year: 2021

In 2005, David Pisinger asked the question "where are the hard knapsack problems?" Noting that the classical benchmark test instances were limited in difficulty due to their selected structure, he proposed a set of new test instances for the 0 1 knapsack problem with characteristics that made them more challenging for dynamic programming and branch and bound algorithms. This important work highlighted the influence of diversity in test instances to draw reliable conclusions about algorithm performance. In this paper, we revisit the question in light of recent methodological advances in the form of Instance Space Analysis enabling the strengths and weaknesses of algorithms to be visualised and assessed across the broadest possible space of test instances. We show where the hard instances lie, and objectively assess algorithm performance across the instance space to articulate the strengths and weaknesses of algorithms. Furthermore, we propose a method to fill the instance space with diverse and challenging new test instances with controllable properties to support greater insights into algorithm selection, and drive future algorithmic innovations.
SOFTCBIR: Object Searching in Videos Combining Keypoint Matching and Graduated Assignment
Year: 2006

This paper proposes a new approach to object searching in video databases, SoftCBIR, which combines a keypoint matching algorithm and a graduated assignment algorithm based on softassign. Compared with previous approaches, SoftCBIR is an innovative combination of two powerful techniques: 1) An energy minimization algorithm is applied to match two groups of keypoints while accounting for both their similarity in descriptor space and the consistency of their geometric configuration. The algorithm computes correspondence and pose transformation between two groups of keypoints iteratively and alternately toward an optimal result. The objective energy function combines normalized distance errors in descriptor space and in the spatial domain. 2) Initial individual keypoint matching relies on Approximate K Nearest Neighbor (ANN) search. ANN achieves much more accurate initial keypoint matching results in the descriptor space than K means labeling. Experiments prove the e! ectiveness of our approach, and demonstrate the performance improvements rising from the combination of the two proposed techniques in the SoftCBIR algorithm.
Semi supervised learning using multiple one dimensional embedding based adaptive interpolation
Venue: Int. J. Wavelets Multiresolution Inf. Process.
Year: 2016

We propose a novel semi supervised learning (SSL) scheme using adaptive interpolation on multiple one dimensional (1D) embedded data. For a given high dimensional dataset, we smoothly map it onto several different 1D sequences, so that the labeled subset is converted to a 1D subset for each of these sequences. Applying the cubic interpolation of the labeled subset, we obtain a subset of unlabeled points, which are assigned to the same label in all interpolations. Selecting a proportion of these points at random and adding them to the current labeled subset, we build a larger labeled subset for the next interpolation. Repeating the embedding and interpolation, we enlarge the labeled subset gradually, and finally reach a labeled set with a reasonable large size, based on which the final classifier is constructed. We explore the use of the proposed scheme in the classification of handwritten digits and show promising results.