Miracle-dz/UniFAR-FTUs huggingface dataset:
Hands on What? The Relative Effectiveness of Physical versus Virtual Materials in an Engineering Design Project by Middle School Children

Hands-on'' activities play an important, but controversial, role in early science education. In this study we attempt to clarify some of the issues surrounding the controversy by calling attention to distinctions between: (a) type of instruction (direct or discovery); (b) type of knowledge to be acquired (domain-general or domain-specific); and (c) type of materials that are used (physical or virtual). We then describe an empirical study that investigates the relative effectiveness of the physical-virtual dimension. In the present study, seventh and eighth grade students assembled and tested mousetrap cars with the goal of designing a car that would go the farthest. Children were assigned to four different conditions, depending on whether they manipulated physical or virtual materials, and whether they had a fixed number of cars they could construct or a fixed amount of time in which to construct them. All four conditions were equally effective in producing significant gains in learners' knowledge about causal factors, in their ability to design optimal cars, and in their confidence in their knowledge. Girls' performance, knowledge, and effort were equal to boys' in all conditions, but girls' confidence remained below boys' throughout. Given the fact that, on several different measures, children were able to learn as well with virtual as with physical materials, the inherent pragmatic advantages of virtual materials in science may make them the preferred instructional medium in many hands-on contexts. 2006 Wiley Periodicals, Inc. J Res Sci Teach 44: 183-203, 2007 The merits and definitions of ''hands-on'' activities in early science education have been debated for over a century (Deboer, 1991; Huxley, 1899). Advocates for hands-on science argue that it promotes learning because it is consistent with the concrete-to-abstract nature of cognitive development, because it provides additional sources of brain activation via kinesthetic involvement, and because its intrinsic interest increases motivation and engagement (Flick, 1993; Haury & Rillero, 1994). Such arguments have led the National Science Teachers Asso- ciation to recommend that the minimal amount of science instruction time devoted to hands-on
Self-refining targeted readings recommender system

Huge volume of content is produced on multiple online sources every day. It is not possible for a user to go through these articles and read about topics of interest. Secondly professional articles, blog and forum have many topics discussed in a single discussion. Automatic knowledge-based topic models is a recent approach in Natural Language Processing that extract high quality topics from a large collection of documents. The quality of topics is improved through the model's auto-learning mechanism. In this paper, targeted reading content problem is addressed through automatic knowledge-based topic models, as a readings recommender system. The application recommends text documents based on contextual relevance. The learning module helps the model to learn certain rules from each recommendation, in order to recommend more relevant content in future. The contribution of this research work is to augment knowledge based models with contextual recommender systems. An application is developed that recommends targeted readings to the audience while the knowledge-based learning module grows in experience to serve the future users better.
Development of Phonetic Categories of Stop Consonants in Spanish-English Bilingual Children

The U.S. Census Bureau [1] indicated that Spanish ranks as the #1 non-English language spoken in the United States. Over 37 million Spanish speakers including 6 million Spanish-speaking children reside in the United States, a number that has more than doubled over the last 30 years. In spite of the significant number of Spanish-English bilingual children, literature on the developmental norms of these children is limited and has revealed a paucity of information on developmental patterns. Investigating the typical development of Spanish-English bilingual children is necessary in order to establish typical developmental patterns and milestones. Differences in onset of second language (L2) exposure divide bilingual speakers into simultaneous and sequential speakers. Researchers [2-4] proposed arbitrary age cutoffs point for categorizing these two categories. Generally speaking, simultaneous bilingual speakers are those who have been exposed to the L2 within the first few years of life and continue to acquire the L2 along with L1. Sequential bilingual speakers differ from simultaneous bilinguals in that significant progress or almost complete acquisition of the L1 has been made before exposure to the L2. The purpose of this study was to provide the development characteristics of phonetic Purpose: The present study examined stops produced by Spanish-English bilingual (SEB) children in order to determine whether the bilingual children possess distinct phonetic categories across their two languages at 5 to 6 and 10 years of age.
Systematic Analyses of P-Loop Containing Nucleotide Triphosphate Hydrolase Superfamily Based on Sequence, Structure and Function

1 Graduate School of Information Science, Nara Institute of Science and Technology, 8926-1 Takayama, Ikoma, Nara 630-0101, Japan 2 Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashinoha, Kashiwa, Tokyo 277-8562, Japan 3 Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 17F Aomi Frontier Building, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan 4 PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan
Loughborough University Institutional Repository A self-determination theory approach to understanding antecedents of teachers ' motivational strategies in physical education

Physical Education (PE) teachers can influence students’ self-determination through the motivational strategies that they use. The present study examined how teachers’ reported use of three motivational strategies (providing a meaningful rationale, providing instrumental help and support, and gaining an understanding of the students) were predicted by perceived job pressure, perceptions of student self-determination, and their autonomous orientation, psychological need satisfaction, and self-determination to teach. Structural equation modeling supported a model in which perceived job pressure, perceptions of student selfdetermination and teacher autonomous orientation predicted teacher psychological need satisfaction, which, in turn positively influenced teacher self-determination. The latter positively predicted the use of all three strategies. Direct positive effects of teachers’ psychological need satisfaction on the strategies of gaining an understanding of students and instrumental help and support were also found. In summary, factors that influence teacher motivation may also indirectly affect their motivational strategies towards students.
Chapter 13 On Exploring Soft Discretization of Continuous Attributes

Searching for a binary partition of attribute domains is an i mportant task in data mining. It is present in both decision tree construction and discretization. The most important advantages of decision tree methods are compactness and cle rness of knowledge representation as well as high accuracy of classification. Decision t ree algorithms also have some drawbacks. In cases of large data tables, existing decision tree induction methods are often inefficient in both computation and description aspects. An other disadvantage of standard decision tree methods is their instability, i.e., small dat a deviations may require a significant reconstruction of the decision tree. We present novel soft discretizationmethods usingsoft cuts instead of traditional crisp (or sharp) cuts. This new concept makes it possible to generate more compact and stable decision trees with high accur y of classification. We also present an efficient method for soft cut generation from larg e databases.
Planning Wrench-Feasible Motions for Cable-Driven Hexapods

Motion paths of cable-driven hexapods must carefully be planned to ensure that the lengths and tensions of all cables remain within acceptable limits, for a given wrench applied to the platform. The cables cannot go slack-to keep the control of the robot-nor excessively tight-to prevent cable breakage-even in the presence of bounded perturbations of the wrench. This paper proposes a path-planning method that accommodates such constraints simultaneously. Given two configurations of the robot, the method attempts to connect them through a path that, at any point, allows the cables to counteract any wrench lying in a predefined uncertainty region. The configuration space, or C-space for short, is placed in correspondence with a smooth manifold, which facilitates the definition of a continuation strategy to search this space systematically from one configuration, until the second configuration is found, or path nonexistence is proved by exhaustion of the search. The force Jacobian is full rank everywhere on the C-space, which implies that the computed paths will naturally avoid crossing the forward singularity locus of the robot. The adjustment of tension limits, moreover, allows to maintain a meaningful clearance relative to such locus. The approach is applicable to compute paths subject to geometric constraints on the platform pose or to synthesize free-flying motions in the full 6-D C-space. Experiments illustrate the performance of the method in a real prototype.
Measuring performance limits of subband adaptive systems

We discuss a method to measure the convergence limits of general subband adaptive systems due to non-ideal filter banks. Aliasing caused in such filter bank presents a distortion to the subband adaptive system which forms a lower limit for the minimum mean squared error. The accuracy of the achievable model is given by the transfer function of the filter bank. To measure both aliasing and filter bank distortions, we employ the measurement technique by Heinle and Schussler (see Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, Atlanta, GA, p.2754-57, 1996). The presented approach is applicable to a wide range of subband adaptive filter systems. Examples for the measured limits are presented.
Sensitivity analysis of passive CAN bus components to investigate signal integrity of CAN network physical layer

This paper shows the application of sensitivity analysis to identify the most important network parameters impacting overshoot, undershoot and ringing of signals in CAN networks. Checking all worst case combinations of n network parameters would require 2n simulations or measurements which is not feasible for realistic CAN networks. Using results from sensitivity analysis, not only the number of simulations or measurements can be reduced thus saving time and cost, but also the ringing in CAN networks can be minimized to improve signal integrity. Simulation results have been validated using measurements and there is good agreement between simulation and measurement.
Flame detection based on spatio-temporal covariance matrix

Automatic fire flame detection is important for intelligent video surveillance. The background model and various color features are usually adopted for flame detection. In this paper, a fire flame detection method is developed by combining both background subtraction and region covariance. The color distribution method and background model with an adaptive background learning model are used to preprocess the image firstly. We then extract the space-temporal covariance matrix, which is used to fuse all the discriminative cues together. Finally we use support vector machine to classify fire scene. The proposed system is effective in detecting uncontrolled fire in complicated environment. Experiments based on several public fire video data sets are utilized to justify the effectiveness of our method.
Expression, Purification, and Evaluation of Diagnostic Potential and Immunogenicity of a Recombinant NS3 Protein from All Serotypes of Dengue Virus

Dengue is one of the major public health concerns in the world. Since all the four serotypes are actively circulating in Mexico, there is a need to develop an efficient diagnosis system to improve case management of the patients. There exist few studies evaluating the use of the NS3 protein as a protective antigen against dengue virus (DENV). In this paper we show the expression of a recombinant NS3 protein from all serotypes of dengue virus (GST-DVNS3-1-4) and report a reliable “in-house detection system” for the diagnosis of dengue infection which was field-tested in a small village (Tezonapa) in the state of Veracruz, Mexico. The fusion proteins were immunogenic, inducing antibodies to be able to recognize to antigens up to a 1 : 3200 dilution. The purified proteins were used to develop an in-house detection system (ELISA) and were further tested with a panel of 239 serum samples. The in-house results were in excellent agreement with the commercial kits with κ = 0.934 ± 0.064 (95% CI = 0.808–1.061), and κ = 0.872 ± 0.048 (95% CI = 0.779–0.965) for IgM and IgG, respectively. The agreement between the NS1 antigen detection versus the rNS3 ELISA, κ = 0.837 ± 0.066 (95% CI = 0.708–0.966), was very good. Thus, these results demonstrate that recombinant NS3 proteins have potential in early diagnosis of dengue infections.
Mental and physical movements of hands: kinesthetic information preserved in representational systems

pared with the previous data; reaction time (RT) in the identification of the left-right version of the same stimuli (Sekiyama, 1982). Both difficulty and RT showed similar trends, as a function of angular departure of the stimuli from upright, suggesting that the left-right identification is based on mental movements of representations of subjects' own hands. It was argued in terms of kinesthetic information preserved in representations.
2 Appropriating the Commons : Firms in Open Source Software

Firms in open source software (OSS) are active in a field encompassing all the characteristics of a public good, given the non-excludability and non-rivalry nature of OSS. As the case of OSS demonstrates, the fact that many important inputs to the innovative process are public should not be taken to mean that innovators are prevented from capturing private returns. The objective of this paper is to explore how firms appropriate returns from innovations that are created outside the boundaries of firms and in the public domain using the case of OSS. To do so, t he paper draws upon an explorative multiple case study of six small firms that attempt to appropriate returns from OSS, with rich empirical evidence from various data sources. The cases illustrate how firms try a variety of approaches to appropriate adequate returns and that selling services seem to be the dominant trend. Firm also balance the relative inefficiency of traditional means of intellectual property right such as patents by putting greater emphasis on first mover advantages and creating network externalities.
Preoperative Physical Activity Level Has No Relationship to the Degree of Recovery One Year after Primary Total Hip or Knee Arthroplasty: A Cohort Study

Background When it comes to prevalidation, it is assumed that a higher preoperative level of physical activity leads to better postoperative recovery. However current literature is inconclusive about the effect of prevalidation on functional recovery of patients with primary osteoarthritis (OA) who underwent a THA or TKA. Therefore the aim of this study is to analyse one of the major assumptions underlying the potential effectiveness of prevalidation namely the relationship between preoperative physical activity level and postoperative recovery one year after THA or TKA in a group of 658 OA patients. Methods and Results From 2006 to 2012, 1061 patients underwent a primary THA or TKA at University Medical Center Groningen. Preoperative and one-year postoperative patients filled in the SQUASH questionnaire to get an impression of their physical activity level, and the WOMAC questionnaire to obtain insight into degree of recovery. Missing data were multiply imputed. No relationship was found between the preoperative total (B-coefficient = 0.03, CI95% = −0.033–0.093) and leisure-time physical activity level (B-coefficient = 0.042, CI95% = −0.009–0.093) neither for preoperative compliance with the Dutch Recommendation for Health-Enhancing Physical Activity (B-coefficient = 0.002, CI95% = −0.053–0.057), and the degree of recovery one year after surgery. Conclusion The preoperative physical activity level had no relation with the degree of recovery one year after THA or TKA. The results do not support one of the major assumptions behind prevalidation, which assumes that a higher preoperative physical activity level will lead to a better recovery after THA or TKA.
Ranking importance based information on the world wide web

Identifying useful features for classification and forecast tasks from a ranked data is highly difficult and challenging. By ranking user popularity ratings from normalised area histograms, a method of feature selection for ranked data inspired from the law of vital few is proposed. We propose that the attributes that are most stable against the variations in classes have their usefulness in a forecasting task, while the attributes that are most unstable between inter-class samples but most stable within intra-class samples have their usefulness in classification tasks. The performance of the proposed method is demonstrated through a realistic example of web-content data from Yahoo! research repository: the user rating of web pages. The attributes in the data when ranked based on their importance in a year show distinct characteristics of performance in the tasks of popularity forecast and classification.
Project on Human Development in Chicago Neighborhoods: Community Survey, 1994-1995

The Project on Human Development in Chicago Neighborhoods is an interdisciplinary study aimed at deepening society's understanding of the causes and pathways of juvenile delinquency, adult crime, substance abuse, and violence. In particular, it is a study of children's social and psychological development from birth to young adulthood in urban neighborhoods. This collection contains data from a cross-sectional survey of Chicago residents in 1994 and is the first product of an eight-year project. The survey gathered information from adult residents of Chicago on their perceptions of the neighborhoods in which they live. The survey questionnaire was a multidimensional assessment of the structural conditions and organization of the neighborhoods. Data collection consisted of a household interview of residents aged 18 and older to assess key neighborhood dimensions, including the dynamic structure of the local community, organizational and political structure, cultural values, informal social control, formal social control, and social cohesion. Variables include measures of the best and worst aspects of living in Chicago, how long residents had lived in a particular neighborhood, characteristics of their neighborhood, including types of social service agencies available, and if they would consider moving to a different neighborhood and why. Other community variables measure the relationships among neighbors, including how many neighbors a respondent would recognize, how often neighbors socialized, and how often neighbors participated in other activities together. Variables that capture neighborhood social order include respondents' perceptions of neighborhood problems such as litter, graffiti, drinking, drugs, and excessive use of force by police. Respondents were also asked about their normative beliefs regarding violence, money, and various children's behaviors. Victimization variables cover how often the respondent was the victim of a fight with a weapon, a violent argument, a gang fight, sexual assault, robbery, theft, or vandalism. Other variables measure fear of crime and attitudes toward the police. Demographic variables include age, gender, education, living arrangement, national origin, and employment status. In addition, a number of scales created by the study's scientific directors are included such as social disorder, perceived neighborhood danger, and neighborhood activism. Part 1 of this study contains individual responses to survey questions. Part 2 contains data aggregated to the neighborhood cluster (NC) level (see Study Design for explanation of NC). Pertinent census data can be found in CHICAGO NEIGHBORHOOD CLUSTER CENSUS DATA FOR THE PROJECT ON HUMAN DEVELOPMENT IN CHICAGO NEIGHBORHOODS (PHDCN), 1990 AND 2000 [ICPSR 13757].
Reinforcement, Rationality, and Intentions: How Robust Is Automatic Reinforcement Learning in Economic Decision Making?

Reinforcement learning is often observed in economic decision making and may lead to detrimental decisions. Because of its automaticity, it is difficult to avoid. In three experimental studies, we investigated whether this process could be controlled by goal intentions and implementation intentions. Participants' decisions were investigated in a probability-updating task in which the normative rule to maximize expected payoff (Bayes' rule) conflicted with the reinforcement heuristic as a simple decision rule. Some participants were asked to set goal intentions designated to foster the optimization of rational decision making, while other participants were asked to furnish these goal intentions with implementation intentions. Results showed that controlling automatic processes of reinforcement learning is possible by means of goal intentions or implementation intentions that focus decision makers on the analysis of decision feedback. Importantly, such beneficial effects were not achieved by simply instructing participants to analyze the feedback, without defining a goal as the desired end state from a first-person perspective. Regarding intentions supposed to shut down reinforcement processes by controlling negative affect, effects were more complex and depended on the specified goal-directed behavior. The goal intention to suppress the disappointment elicited by negative feedback was not effective in controlling reinforcement processes. Furnishing this goal with an implementation intention even backfired and strengthened unwanted reinforcement processes. In contrast, asking participants to keep cool in response to negative decision outcomes through the use of goal intentions or implementation intentions increased decisions in line with Bayes' rule. Copyright © 2017 John Wiley & Sons, Ltd.
Wall Street and the Housing Bubble

We analyze whether mid-level managers in securitized finance were aware of a large-scale housing bubble and a looming crisis in 2004-2006 using their personal home transaction data. We find that the average person in our sample neither timed the market nor were cautious in their home transactions, and did not exhibit awareness of problems in overall housing markets. Certain groups of securitization agents were particularly aggressive in increasing their exposure to housing during this period, suggesting the need to expand the incentives-based view of the crisis to incorporate a role for beliefs.