Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of magnet grouping in reduction of cogging torque for a slotted double-rotor axial-flux PM motor

This study is about minimization of cogging torque in an axial flux permanent magnet (AFPM) motor with integer number of slots per pole per phase with the focus on pole shifting or grouping. The analyses of cogging torque component are presented and compared with other cogging torque minimization methods and a reference AFPM motor with standard fan-shaped magnets. It is shown that magnet grouping is an effective method to eliminate cogging torque component in AFPM motors.
New Spatial FCM Approach with Application to SAR Target Clustering

This paper develops a new fuzzy clustering approach that is suitable for image processing applications. The developed approach is based upon the classical fuzzy c-means (FCM) and referred to as the spatial FCM (SFCM). Its effectiveness is due to two mechanisms. The first is the replacement of the Euclidean distance traditionally used to measure similarity between input images and clusters prototypes by a novel similarity measure that considers spatial relationships between image pixels and thus becomes less sensitive to image perturbations. The second SFCM mechanism for effectiveness is the addition of a similarity penalty term to FCM's objective function. The aim is to encourage clustering similar images into same clusters. The SFCM is compared to the FCM and some of its variants in the difficult application of synthetic aperture radar (SAR) target clustering. It is shown that the SFCM consistently yields better performance
Universität Des Saarlandes Fachrichtung 6.1 – Mathematik a Posteriori Error Estimates of Functional Type for Variational Problems Related to Generalized Newtonian Fluids a Posteriori Error Estimates of Functional Type for Variational Problems Related to Generalized Newtonian Fluids

The paper is focused on functional type a posteriori estimates of the difference between the exact solution of a variational problem modeling certain types of generalized Newtonian fluids and any function from the admissible energy class. In contrast to the a posteriori estimates obtained for example by the finite element method our estimates do not contain any local (mesh dependent) constants, and therefore they can be used regardless of the way in which an approximation has been constructed.
Improved Efficacy and Reduced Toxicity of Doxorubicin Encapsulated in Sulfatide-Containing Nanoliposome in a Glioma Model

As a glycosphingolipid that can bind to several extracellular matrix proteins, sulfatide has the potential to become an effective targeting agent for tumors overexpressing tenasin-C in their microenvironment. To overcome the dose-limiting toxicity of doxorubicin (DOX), a sulfatide-containing nanoliposome (SCN) encapsulation approach was employed to improve treatment efficacy and reduce side effects of free DOX. This study analysed in vitro characteristics of sulfatide-containing nanoliposomal DOX (SCN-DOX) and assessed its cytotoxicity in vitro, as well as biodistribution, therapeutic efficacy, and systemic toxicity in a human glioblastoma U-118MG xenograft model. SCN-DOX was shown to achieve highest drug to lipid ratio (0.5∶1) and a remarkable in vitro stability. Moreover, DOX encapsulated in SCN was shown to be delivered into the nuclei and displayed prolonged retention over free DOX in U-118MG cells. This simple two-lipid SCN-DOX nanodrug has favourable pharmacokinetic attributes in terms of prolonged circulation time, reduced volume of distribution and enhanced bioavailability in healthy rats. As a result of the improved biodistribution, an enhanced treatment efficacy of SCN-DOX was found in glioma-bearing mice compared to the free drug. Finally, a reduction in the accumulation of DOX in the drug's principal toxicity organs achieved by SCN-DOX led to the diminished systemic toxicity as evident from the plasma biochemical analyses. Thus, SCN has the potential to be an effective and safer nano-carrier for targeted delivery of therapeutic agents to tumors with elevated expression of tenascin-C in their microenvironment.
Particle Swarm Full Model Selection

In this paper we propose the application of particle swarm optimization (PSO) to the problem of full model selection (FMS) for classication tasks. We dene FMS as follows: given a pool of preprocessing methods, feature selection and learning algorithms, select the combination of these that obtains the lowest classication error for a given data set; the task also includes the selection of hyperparameters for the considered methods. This problem generates a vast search space to be explored, well suited for stochastic optimization techniques. FMS can be applied to any classication domain as it does not require domain knowledge. Dierent model types and a variety of algorithms can be considered under this formulation. Furthermore, competitive yet simple models can be obtained with FMS. We adopted PSO for the search because of its proved performance in dierent problems and because of its simplicity, since neither expensive computations nor specialized methods are needed. We compared PSO against random search in FMS using cross validation for assessing models. Experimental results in benchmark data give evidence that PSO outperforms random search at the end and through the search process. Also, PSO exhibited better convergence behavior and it is less prone to overtting than random search. Results obtained in a model selection competition show the competitiveness of models selected with PSO compared to models selected with more sophisticated techniques and with methods that use domain knowledge.
Probing into the sources of ignorance: science teachers’ practices of constructing arguments or rebuttals to denialism of climate change

Abstract This study focuses on the nature of teachers’ arguments for and rebuttals to 10 denial theories about anthropogenic climate change that are most commonly encountered in the media and public debates. Through a semi-structured survey, the study collected data from 24 participants who are K-12 teachers in Maryland and Delaware. The deductive coding and frequency analysis of data shows that although all participants of our study agree with the importance of teaching anthropogenic climate change, some teachers agree with the denial theories of climate change. The arguments for the denial theories show less epistemic quality than the rebuttals against denial theories. Moreover, teachers went beyond the textbooks and searched for other varied sources of information. However, we noticed that teachers might still doubt the anthropogenic causes of climate change. The study further uses intertextual discourse analysis to explore the reasons why use of sources might still leave teachers confused.
Interactive Non-Photorealistic Technical Illustration

Current interactive modeling systems allow users to view models in wireframe or Phong-shaded images. However, the wireframe is based on the model's parameterization, and a model's features may get lost in a nest of lines. Alone, a fully rendered image may not provide enough useful information about the structure or model features. Human technical illustrators follow certain visual conventions that are unlike Phong-shaded or wireframe renderings, and the drawings they produce are subjectively superior to conventional computer renderings. This thesis explores lighting, shading, and line illustration conventions used by technical illustrators. These conventions are implemented in a modeling system to create a new method of displaying and viewing complex NURBS models. In particular, silhouettes and edge lines are drawn in a manner similar to pen-and-ink drawings, and a shading algorithm is used that is similar to ink-wash or air-brush renderings for areas inside the silhouettes. This shading has a low intensity variation so that the black silhouettes remain visually distinct, and it has a cool-to-warm hue transition to help accent surface orientation. Applying these illustration methods produces images that are closer to human-drawn illustrations than is provided by traditional computer graphics approaches. To Bruce, for all of the love and support. ACKNOWLEDGEMENTS Thanks to Bruce Gooch, Peter Shirley, Elaine Cohen, Rich Riesenfeld, Susan and Tice Ashurst, Georgette Zubeck, David Johnson, Bill Martin, Richard Co ey, Colette Mullenho , Brian Loss, Matt Kaplan, Tom Thompson, Russ Fish, Mark Bloomenthal, and the rest of the Alpha1 and SCI research groups, past and present. Thanks to Lee Markosian, Loring Holden, Robert Zeleznik, and Andrew Forsberg, from Brown University, for letting me collaborate on the JOT Project. Also, thanks to Jason Herschaft for the dinosaur claw model. This work was supported in part by DARPA (F33615-96-C-5621) and/or the NSF Science and Technology Center for Computer Graphics and Scienti c Visualization (ASC-89-20219). All opinions, ndings, conclusions, or recommendations expressed in this document are mine and do not necessarily re ect the views of the sponsoring agencies. CHAPTER
Deep Infrared Imaging of the Microquasars 1E 1740–2942 and GRS 1758–258

We present deep infrared (2.2 μm) imaging of the Galactic microquasars 1E 1740-2942 and GRS 1758-258 using the Keck I 10 m telescope in 1998 June. The observations were taken under excellent seeing conditions (~0.″45 full width at half-maximum), making them exceptionally deep for these crowded fields. We used the USNO-A2.0 catalog to astrometrically calibrate the infrared images (along with an optical CCD image in the case of GRS 1758-258), providing independent frame ties to the known radio positions of the objects. For 1E 1740-2942, we confirm potential candidates for the microquasar previously identified by Martí et al. and show that none of the objects near the microquasar have varied significantly from 1998 to 1999. For GRS 1758-258, our astrometry indicates a position shifted from previous reports of candidates for the microquasar. We find no candidates inside our 90% confidence radius to a 2 σ limiting magnitude of Ks = 20.3 mag. We discuss the implications of these results for the nature of the microquasar binary systems.
HandiViz project: Clinical validation of a driving assistance for electrical wheelchair

Autonomy and independence in daily life, whatever the impairment of mobility, constitute fundamental needs that participate to the self-esteem and the well-being of disabled people. In this context, assistive technologies are a relevant answer. To address the driving assistance issue, we propose in this paper a unified shared control framework able to smoothly correct the trajectory of the electrical wheelchair. The system integrates the manual control with sensor-based constraints by means of a dedicated optimization strategy. The resulting low-complex and low-cost embedded system is easily plugged onto on-the-shelf wheelchairs. The robotic solution has been then validated through clinical trials that have been conducted within the Rehabilitation Center of Pôle Saint Hélier (France) with 25 volunteering patients presenting different disabling neuro-pathologies. This assistive tool is shown to be intuitive and robust as it respects the user intention, it does not alter perception while reducing the number of collisions in case of hazardous maneuvers or in crowded environment.
Adult Neurogenesis Is Associated with the Maintenance of a Stereotyped, Learned Motor Behavior

Adult neurogenesis is thought to provide neural plasticity used in forming and storing new memories. Here we show a novel relationship between numbers of new neurons and the stability of a previously learned motor pattern. In the adult zebra finch, new projection neurons are added to the nucleus HVC and become part of the motor pathway for producing learned song. However, new song learning occurs only in juveniles and the behavioral impact of adding new neurons to HVC throughout life is unclear. We report that song changes after deafening are inversely correlated with the number of new neurons added to HVC, suggesting that adult neurogenesis in this context may contribute to behavioral stability. More broadly, we propose that new neuron function may depend on the site of integration and can vary as widely as promoting, or restricting, behavioral plasticity.
The Relationship between subjective-well-being and job satisfaction of Health insurance organization staff in Tehran

Job satisfaction plays an important role in human behavior and resources management studies and may have a great effect on labor efficiency. Subjective-well-being is one of the factors affecting on job satisfaction. Subjective well-being is the consent of the person of their quality of life, based on criteria selected by their. The present study examined the relationship between subjective well-being and job satisfaction. In the present study, 114 employees of Health insurance organization were analyzed by job satisfaction questionnaires and subjective well-being questionnaires. This descriptive study was a correlational study and the data were analyzed using Pearson correlation and stepwise regression. The results showed that a strong relationship between subjective well-being and job satisfaction (0.639). It also includes the following components of subjective well-being: emotional (0.404), psychological (0.46) and social well-being (0.557) that shows a significant relationship. It can be concluded that subjective-well-being can be a predictive variable in job satisfaction. The predictability of subjective-well-being components is respectively social Well-being, psychological well-being and emotional well-being.
Constraints and opportunities facing women entrepreneurs in developing countries: A relational perspective

Purpose: this purpose of the paper to examine the interplay of constraints and opportunities affecting female entrepreneurship in developing countries. The paper integrates salient micro- and macro-level perspectives and provides a rounded account of opportunities and constraints as part of a holistic interdependent system. Design/methodology/approach: the paper adopts an integrative multi-level research design and an interpretive research methodology, capitalizing on in-depth interviews with ten women entrepreneurs to explore their perceptions and interpretations of constraints and opportunities facing female entrepreneurship in the Lebanese context. Findings: the findings presented in this paper clearly illustrate the relevance of micro-, meso-, and macro-level factors in entrepreneurship research and the usefulness of integrating multiple lens and units of analysis to capture the complexity of the women entrepreneurship experience in any particular context. Originality/value: the value added of this research lies in adapting a framework recently popularized in the context of diversity management for use in entrepreneurship research, helping to capture in turn the dynamic interplay of multiple levels of analysis and objective/subjective factors influencing female entrepreneurship
Rig ht or Wrong , Fa mil ia r or Novel in Pictorial List Discri m i nation Lea • rnlng

The interaction between nonassociative learning (presentation frequencies) and associative learning (reinforcement rates) in stimulus discrimination performance was investigated. Subjects were taught to discriminate lists of visual pattern pairs. When they chose the stimulus designated as right they were symbolically rewarded and when they chose the stimulus designated as wrong they were symbolically penalised. Subjects first learned one list and then another list. For a 'tight" group the pairs of the second list consisted of right stimuli from the first list and of novel wrong stimuli. For a 'wrong" group it was the other way round. The right group transferred some discriminatory performance from the first to the second list while the control and wrong groups initially only performed near chance with the second list. When the first list involved wrong stimuli presented twice as frequently as right stimuli, the wrong group exhibited a better transfer than the right group. In a final experiment subjects learned lists which consisted of frequent right stimuli paired with scarce wrong stimuli and frequent wrong stimuli paired with scarce right stimuli. In later test trials these stimuli were shown in new combinations and additionally combined with novel stimuli. Spbjects preferred to choose the most rewarded stimuli and to avoid the most penalised stimuli when the test pairs included at least one frequent stimulus. With scarce/scarce or scarce/novel stimulus combinations they performed less well or even chose randomly. A simple mathematical model that ascribes stimulus choices to a Cartesian combination of stimulus frequency and stimulus value succeeds in matching all these results with satisfactory precision.
Methodology for Reusing Human Resources Management Standards

Employment Services (ESs), Public ones (PESs) and Private ones (PrEAs), are becoming more and more important for Public Administrations where their social implications on sustainability, workforce mobility and equal opportunities play a fundamental strategic importance for any central or local Government. The EU SEEMP (Single European Employment Market-Place) project aims at improving facilitate workers mobility in Europe. Ontologies are used to model descriptions of job offers and curricula; and for facilitating the process of exchanging job offer data and CV data between ES. In this paper we present the methodological approach we followed for reusing existing human resources management standards like NACE, ISCO-88 (COM) and FOET, among others, in the SEEMP project, in order to build a common “language” called Reference Ontology.
NoteLook: taking notes in meetings with digital video and ink

NoteLook is a client-server system designed and built to support multimedia note taking in meetings with digital video and ink. It is integrated into a conference room equipped with computer controllable video cameras, video conference camera, and a large display rear video projector. The NoteLook client application runs on wireless pen-based notebook computers. Video channels containing images of the room activity and presentation material are transmitted by the NoteLook servers to the clients, and the images can be interactively and automatically incorporated into the note pages. Users can select channels, snap in large background images and sequences of thumbnails, and write freeform ink notes. A smart video source management component enables the capture of high quality images of the presentation material from a variety of sources. For accessing and browsing the notes and recorded video, NoteLook generates Web pages with links from the images and ink strokes correlated to the video.
Implementation of Fuzzy Cognitive Maps based on Fuzzy Neural Network and Application in Numerical Prediction of Time Series

Fuzzy Cognitive Map (FCM) has gradually emerged as a powerful paradigm for knowledge representation and a simulation mechanism applicable to numerous research and application fields. However since efficient methods to determine the states of investigated system and to quantify causalities which are the very foundation of FCM theory are lacking, constructing FCMs for complex causal systems greatly depends on expert knowledge. The manually developed models have a substantial shortcoming due to the model subjectivity and difficulties with accessing its reliability. In this paper, we proposed a fuzzy neural network to enhance the learning ability of FCMs. Our approach incorporates the inference mechanism of conventional FCMs with the determination of membership functions, as well as the quantification of causalities. In this manner, FCM models of investigated systems can be automatically constructed from data, and therefore are independent of the experts. In the employed fuzzy neural network, the concept of mutual subsethood is used to describe the causalities, which provides more transparent interpretation for causalities in FCMs. To demonstrate the capability of our approach, simulations for many benchmarks in numerical predication of time series problem are conducted. The simulation studies confirm the effectiveness of the proposed approach. Index Terms Fuzzy neural network, Fuzzy Cognitive Maps (FCMs), mutual subsethood, fuzzy rule identification
Force-presentation method for active polyhedron for realizing physical human-machine interaction

The goal of this research is to develop a new type of haptic interface termed "active polyhedron", which realizes a physical human-machine interaction with virtual continuum objects in PCs. Active polyhedrons are polyhedron-shaped linkage mechanisms. In this paper, we deal with an active icosahedron consisting of 30 intelligent cylinders, which were specially developed for this purpose. In previous reports, the mechanism and kinematics of an active icosahedron and a simple force-presentation method using on/off pneumatic valves were given. In this report, a new force-presentation pneumatic-control system using pressure-control valves, which allows a highly accurate force presentation capable of handling complex continuum objects, and a new force-presentation algorithm, which applies to an apex of the polyhedron are described. These were applied to the active icosahedron. The experimental results showed that the active icosahedron was successful in realizing physical human-machine interaction, with which operators could change the shape, feel and compliance of virtual objects in a PC as if they actually touched them
Being mindful at work and at home: Buffering effects in the stressor–detachment model

In this daily diary study, we examined the moderating role of employee domain‐specific mindfulness within the stressor–detachment model (Sonnentag & Fritz, 2015, Journal of Organizational Behavior, 36, 72). According to the stressor–detachment model, emotional and quantitative demands should be associated with decreased psychological detachment after work, which in turn is associated with decreased well‐being (i.e., low positive affect and high negative affect) at bedtime. Moreover, we proposed that both mindfulness at work and home should buffer the relations between job demands and psychological detachment and between psychological detachment and well‐being. Sixty‐five employees completed two daily surveys (i.e., after work and before going to bed) over five workdays. Results of multilevel analyses revealed that job demands did not predict psychological detachment, which in turn did not predict well‐being at bedtime. However, the relation between emotional demands and psychological detachment was buffered by both mindfulness at work and at home while the relation between quantitative demands and psychological detachment was moderated by mindfulness at home only. Moreover, we found that mindfulness at home moderated the relation between psychological detachment and positive affect at bedtime. Our study demonstrates the buffering role of daily mindfulness within the stressor–detachment model and highlights the value of considering domain‐specific mindfulness.
Using fault slippage measurement for monitoring software process quality during development

In a competitive environment where time-to-market is crucial for success, software development companies initiate process improvement programs that can shorten the development time. They especially seek improvements in the verification activities since rework commonly constitutes a significant part of the development cost. However, the success of process improvement initiatives is dependent on early and observable results since a lack of feedback on the effect of improvements is a common cause of failure. This paper investigates how to monitor the verification process as input to decisions such as improvement actions. The suggested approach was applied on three industrial software products at Ericsson and the results determined that the approach can be used for quantitative monitoring of process quality and as decision support to do rapid improvement actions.