Miracle-dz/UniFAR-FTUs huggingface dataset:
Individual Differences in Early Scientific Thinking: Assessment, Cognitive Influences, and Their Relevance for Science Learning

ABSTRACT Early scientific thinking in kindergarten (6-year-olds) was investigated in a large study involving 227 participants. We investigated (1) whether individual differences across 3 scientific-thinking components (experimentation, data interpretation, and understanding the nature of science) are stable across children, (2) whether children’s increased information-processing skills (intelligence, language abilities) and their development of an advanced theory of mind (AToM) are potential mechanisms that bring about individual differences in scientific thinking, and (3) whether individual differences in scientific thinking predict individual differences in science content knowledge. Using a newly developed instrument with 30 items (the Science-K inventory), we found that a one-dimensional Rasch model provides a good fit to the data, showing that kindergarteners’ scientific thinking goes beyond competencies in single tasks. Individual differences across the diverse scientific-thinking tasks were stable, and children’s scientific thinking was correlated with their intelligence and their language abilities. AToM was an important precursor for scientific thinking, predicting it independently from the influences of information-processing skills. Children’s science content knowledge was predicted by their score on the Science-K inventory. This finding points to a specific relation between these 2 components of scientific literacy, and it supports the view that scientific-thinking skills help to better test and revise (wrong) beliefs and misconceptions about science. Our study is the first to reveal substantial individual differences in scientific thinking in children as young as kindergarteners, and it shows that scientific thinking is important for a successful learning of science concepts, even before children enter formal schooling and begin science education.
DYNAMIC ROUTING OF IP TRAFFIC BASED ON QOS PARAMETERS

The article looks into the current state of the art of dynamic routing protocols with respect to their possibilities to react to changes in the Quality of Service when selecting the best route towards a destination network. New options that could leverage information about the ever changing QoS parameters for data communication are analysed and a Cisco Performance Routing solution is described more in detail. The practical part of this work focuses on a design and implementation of a test bed that provides a scalable laboratory architecture to manipulate QoS parameters of different data communications flowing through it. The test bed is used in various use cases that were used to evaluate Cisco Performance Routing optimization capabilities in different scenarios.
AN EXPLORATORY STUDY OF MEXICAN AMERICAN PERCEPTIONS OF THE AMERICAN AUTOMOBILE ASSOCIATION

by Manon Prévost-Mullane University of the Pacific 2018 The goal of this study was to better understand the needs of the Mexican American community in relation to the services offered and what their perception was of the American Automobile Association (AAA). At the time of the study, the AAA membership rate for the Hispanic/Latino community was 5% (American Automobile Association, 2014) while this same population in the United States was approximately 17.8% (U.S. Census Bureau, 2016). White/Caucasian members in the AAA accounted for 87% of total memberships yet was estimated at 77% of the U.S. population. With a steady population growth of the Latino community, the AAA seeks to increase membership from this population to better reflect the corresponding makeup of the United States. For the purposes of this study I focused on the Mexican American community, knowing that it was exclusive of other Latin American populations. The 2010 U.S. Census (2011) revealed 59.87% of Hispanic/Latinos identified as Mexican American. Historically, new immigrants immersed themselves in their new country and stepped away from not only their culture, but also their language. Ensuing generations of
Influencing Factors of Organizational Socialization of nurses : Resilience and Mentoring

The purpose of this study was to investigate the resilience, mentoring, and organizational socialization and to identify the related factors organizational socialization of nurses. The data collected from 129 nurses in B city and Y city. Resilience of nurses was measured by a tool which was developed by Connor and Davidson(2003) and adapted by Baek(2010), and mentoring was measured by a tool which was developed by Noe(1988) and adapted by Kwak(2006), and organizational socialization was measured by a tool from Sohn(2008). The data collected from 29th August to 22th September, 2016. The collected data were analyzed by descriptive statistics, t-test, ANOVA, Pearson’s correlation coefficients and multiple regression using SPSS 22.0 version. Factors influencing organizational socialization were resilience. Based on the result of this study, it is necessary to have different programs which enhance resilience of nurses, and organizational culture to encourage having mentoring programs to improve organizational socialization of Received (November 5, 2017), Review Result (November 24, 2017) Accepted (December 8, 2017), Published (January 31, 2018) Pusan National University Hospital, 179 Gudeok-ro, Seo-gu, Busan, Korea email: shinhwa840@naver.com (Corresponding Author) 50612 College of Nursing, Pusan National University, Beomeo-ri, Mulgeum-up, Yangsan-si, Gyeongsangnam-do, Korea email: jyha1028@pusan.ac. kr Influencing Factors of Organizational Socialization of nurses : Resilience and Mentoring Copyright c 2018 HSST 560 nurses.
ANALYSIS OF FACTORS INFLUENCE SMOKING BEHAVIOR IN POOR HOUSEHOLDS IN WEST SUMATERA PROVINCE

This research is purposed to learn the behaviors of poor households in managing their income for buying cigarettes using data from the National Social Economic Survey of West Sumatera Province in 2013 using OLS method as a tool of analysis. Results of the analysis show that the cigarette spending in percentage of income in smoker households in West Sumatera Province is very large, far larger than the percentage of spending for education and health. Household cigarette spending is influenced by income factors, cigarette prices, number of adult male household members, area of residence, age category of the household head, and education of the household head. JEL Classification: D10, D31, P46 Keywords: Cigarette Spending, OLS Regression, Smoking Household, Taste Intervention
Brain Tumor Classification Using PCA &PNN

The conventional method of detection and classification of brain tumor is by human inspection with the use of medical resonant brain images. But it is impractical when large amounts of data is to be diagnosed and to be reproducible. And also the operatorassisted classification leads to false predictions and may also lead to false diagnose. Medical Resonance images contain a noise caused by operator performance which can lead to serious inaccuracies classification. The use of artificial intelligent techniques for instant, neural networks, and fuzzy logic shown great potential in this field. Probabilistic Neural Network gives fast and accurate classification and is a best tool for classification of the tumors. Probabilistic Neural Network with image and data processing techniques is implemented for automated brain tumor classification. Decision making was performed in two stages: feature extraction using the principal component analysis and the Probabilistic Neural Network (PNN). The performance of the PNN classifier was evaluated in terms of training performance and classification accuracies. Probabilistic Neural Network gives fast and accurate classification and is a promising tool for classification of the tumors
Intra-Ethnic Business Networks in the Gurage Footwear Industry in Ethiopia

Drawing on insights from social network theory, the socio-economic and cultural dimensions of intraethnic business networks are examined for the Gurage, an ethnic group in Ethiopia. This study also examines the extent of Chinese impacts on the footwear industry of Ethiopia. A qualitative approach based on in-depth interviews was utilized in order to assess intra-ethnic business networks, while a quantitative approach, based on a cross-sectional survey, was employed to collect background data, to assess the impact of Chinese imports on local footwear producers and to identify potential cases for in-depth interviews. Gurage use ethnic networks to mobilize resources and opportunities, which in turn contributes to their success in the business. In response to the threats of Chinese imports on production activities and social capital of local footwear enterprises, firms downsized or stopped business, or resorted to other alternatives.
Carbon Monoxide Sensor Based on Non-Dispersive Infrared Principle

Carbon monoxide (CO) is one of the toxic air pollution produced in incomplete combustion of carbon-containing fuels. At a certain threshold of concentration, this gas can harm the environments and affect the human health. Unfortunately, it cannot be detected by humans. In this study, CO gas detection has been designed and constructed using the principle of Non-Dispersive Infrared (NDIR). An incandescent light bulb is used to provide infrared source. An optical filter based on interferometry with a bandpass of about 4.63 μm is used to pass the light which corresponds to the CO gas absorption. The TPS 334 thermopile sensor is used to measure light intensity after gas absorption. The built-in RTD in the thermopile is involved to compensate the results of the gas concentration measurement. The experimental result shows that this NDIR sensor can measure CO gas concentration with a sensitivity of about 7 mV / ppm.
A novel centrifuge-based approach for tunable 2D layering of plasmonic nanoparticles

Herein we present a proof-of concept study of 2-D plasmonic nanoparticles layering strategy. Our approach is based on polyvinylpyridine activation of the substrate surfaces followed by centrifuge-based sedimentation of nanoparticles. The developed platform is rather simple, reusable, and non-toxic for adherent cells, which can be realized for multiple-types plasmonic particles of tunable surface density and used for various biomedical applications, such as cell optoporation, bioimaging, SERS etc.
Identifying Roadway Physical Characteristics That Contribute to Emissions Differences between Hybrid and Conventional Vehicles

Conventional vehicles and hybrid electric vehicles (HEVs) will be the dominant vehicle types in the U.S. private passenger vehicle fleet for the foreseeable future. This study used a real-time data set obtained from monitoring vehicle performance and emissions from a series of test runs from a conventional vehicle and a HEV over an 18-month period. An innovative new method of analysis allowed the assessment of different emissions rates between the two propulsion systems and the attribution of these differences to physical roadway/infrastructure characteristics. Regression and cross-classification results identify specific roadway characteristics that contribute to emissions differences between the vehicle types. Overall, the models that included maximum grade and intersection control type performed best, however, speed limit and horizontal curvature were also shown to be important. The performance differences identified in this project confirm that engine controls that are responsive to roadway characteristics are necessary.
Real-Time Beamformer Development and Analysis of Weak Signal Detection with Interference Mitigation for Phased-Array Feed Radio Astronomy

Real-Time Beamformer Development and Analysis of Weak Signal Detection with Interference Mitigation for Phased-Array Feed Radio Astronomy James Michael Brady Department of Electrical and Computer Engineering, BYU Master of Science In recent years, the Brigham Young University (BYU) Radio Astronomy Systems group has developed phased-array feeds and the data acquisition processing systems necessary to perform radio astronomy observations. This thesis describes the development and testing of a real-time digital beamforming system that reduces both the time required to process phased-array feed data and the disk space used to record this data compared to post-processing beamforming systems. A real-data experiment is also discussed in this thesis, which focuses on some of the data post-processing required for one of BYU’s data acquisition systems. Radio-frequency interference mitigation techniques for phased-array feed radio astronomy have been studied for several years, but the effect that these techniques have on weak-signal detection is not well understood. This thesis provides analysis of a simulated weak-source observation for the Green Bank 20-meter telescope and BYU 19 element phasedarray feed with radio-frequency interference present. Interference mitigation techniques are shown to reduce the detectability of weak sources compared with the no interference case, but it is also shown that a weak source can be detected that would otherwise be masked by interference.
Observation of dark and bright pulses in q-switched erbium doped fiber laser using graphene nano-platelets as saturable absorber

In this paper, a passively Q-switched Erbium doped fiber laser (EDFL) by residing Graphene nanoplatelets (GnPs) embedded in polyvinyl alcohol (PVA) based saturable absorber (SA) is demonstrated. To aid the dispersion of GNPs, a surfactant is used and then it is mixed with polyvinyl alcohol (PVA) as host polymer to develop GnPs-PVA film based passive SA. The GnPs-PVA based film then integrated in laser cavity in ring cavity configuration for pulse laser generation. The experimental works show that the proposed passive SA operates at input pump power range from 77 mW to 128 mW with a tunable repetition rate from 78.4 kHz to 114.8 kHz and a shortest pulse width of 3.69 µs. The laser produces maximum instantaneous output peak power and pulse energy of 7.3 mW and 30.46 nJ, respectively and accompanied by signal to noise ratio (SNR) of 64 dB.
Meta-Analysis of Gene Expression and Identification of Biological Regulatory Mechanisms in Alzheimer's Disease

Alzheimer's disease (AD), also known as senile dementia, is a progressive neurodegenerative disease. The etiology and pathogenesis of AD have not yet been elucidated. We examined common differentially expressed genes (DEGs) from different AD tissue microarray datasets by meta-analysis and screened the AD-associated genes from the common DEGs using GCBI. Then we studied the gene expression network using the STRING database and identified the hub genes using Cytoscape. Furthermore, we analyzed the microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and single nucleotide polymorphisms (SNPs) associated with the AD-associated genes, and then identified feed-forward loops. Finally, we performed SNP analysis of the AD-associated genes. Our results identified 207 common DEGs, of which 57 have previously been reported to be associated with AD. The common DEG expression network identified eight hub genes, all of which were previously known to be associated with AD. Further study of the regulatory miRNAs associated with the AD-associated genes and other genes specific to neurodegenerative diseases revealed 65 AD-associated miRNAs. Analysis of the miRNA associated transcription factor-miRNA-gene-gene associated TF (mTF-miRNA-gene-gTF) network around the AD-associated genes revealed 131 feed-forward loops (FFLs). Among them, one important FFL was found between the gene SERPINA3, hsa-miR-27a, and the transcription factor MYC. Furthermore, SNP analysis of the AD-associated genes identified 173 SNPs, and also found a role in AD for miRNAs specific to other neurodegenerative diseases, including hsa-miR-34c, hsa-miR-212, hsa-miR-34a, and hsa-miR-7. The regulatory network constructed in this study describes the mechanism of cell regulation in AD, in which miRNAs and lncRNAs can be considered AD regulatory factors.
Multi-Document Summarization and Semantic Relatedness

Automatic summarization is the process of presenting the contents of written documents in a short, comprehensive fashion. Many approaches have been proposed for this problem, some of which extract content from the input documents (extractive methods), and others that generate the language in the summary based on some representation of the document contents (abstractive methods). This thesis is concerned with extractive summarization in the multi-document setting, and we define the problem as choosing the most informative sentences from the input documents, while minimizing the redundancy in the summary. This definition calls for a way of measuring the similarity between sentences that captures as much as possible of the meaning. We present novel ways of measuring the similarity between sentences, based on neural word embeddings and sentiment analysis. We also show that combining multiple sentence similarity scores, by multiplicative aggregation, helps in the process of creating better extractive summaries. We also discuss the use of information extraction for improving the quality of automatic summarization by providing ways of assessing the salience of information elements, as well as helping with the fluency of the output and providing the temporal dimension. Furthermore, we present graph-based algorithms for clustering words by co-occurrence, and for summarizing short online user-reviews by computing bicliques. The biclique algorithm provides a fast, simple algorithm for summarization in many e-commerce settings.
The Inside-Out Binding Problem

In Gareth Evans’s terms, the fundamental ground of difference that individuates our bodies is the very same fundamental ground of difference that individuates any other concrete object: namely, its position in space and time. An intuition-friendly way of thinking of this is as a division between ways of perceiving our bodies “from the inside” and “from the outside. ” Even heavily edited to deal with the glitches, a purely spatial criterion seems unpromising: given that our bodies are by and large topological donut-shaped figures, any way of drawing the boundaries between inside and outside is bound to seem a little arbitrary. Personal-level recognition of identity of body(-part) perceived both interoceptively and exteroceptively is made possible by subpersonal binding of cues from both forms of perception grounded on recognised co-location at a time of body(-part) perceived both ways at once.
Attitude Exponential Stabilization Control of Rigid Bodies via Disturbance Observer

The attitude stabilization problem of rigid bodies with external disturbance is studied. A novel disturbance observer-based control scheme is presented. Comparing with the existing observers for external disturbance, the proposed observer releases the assumption that the external disturbance should be constant or with the minor rate of change. The closed-loop attitude stabilization system is governed by the controller to be exponentially stable with disturbance rejected. The observer error of disturbance, the attitude, and the angular velocity are exponentially stabilized to be zero or within a small set with an arbitrary radius. The key feature of this scheme is that it ensures the control performance to be more robust to any external disturbance. The controller has a simple structure and does not involve complicated computation. The effectiveness of the presented solution is validated by a rigid satellite example.
To participate or not to participate in a brand micro-blog

Customers’ participation is crucial to the brand micro-blog. However, many brand micro-blogs still face the challenge of low interactive or non-interactive participation. In this paper, we propose a conceptual model that specifies four facilitators (information quality, entertainment value, service quality, and social interaction) and two inhibitors (information overload and advertising reactance) as the key determinants of brand micro-blog participation intention, and we propose that these facilitators and inhibitors in combination determine followers’ identification with the brand micro-blog, and identification eventually determines whether the followers will participate in the brand micro-blog. The data of this study was collected through a quasi-experiment conducted within the Sina micro-blog. The findings confirm that information quality, entertainment value, service quality, and social interaction are four significant facilitators of brand micro-blog participation intention. The findings also show that information overload is a significant inhibitor of brand micro-blog participation intention.
Reliability Assessment of Cable-Stayed Bridges

The paper deals with the reliability assessment of P.C. cable-stayed bridges, but it is thought that the presented methodology is generally applicable. Due to several sources of uncertainties, the geometrical and mechanical properties which define the structural problem cannot be considered as deterministic quantities. In this work, such uncertainties are modelled by using a fuzzy criterion which considers the model parameters bounded between minimum and maximum suitable values. The reliability problem is formulated in terms of safety factor and the membership function over the failure interval is derived for several limit states by using a simulation technique. In particular, the strategic planning of the simulation is found by means of a genetic optimisation algorithm and the structural analyses are carried out by taking both material and geometrical non-linearity into account. An application to a cable-stayed bridge shows the effectiveness of the proposed procedure.
Managing Evolution of Service Centric Systems by Test Models

For various reasons, service centric systems are subject to continuous evolution. Therefore, regular adaptations to their tests are essential to keep, or even improve, their quality of service. In this paper, we present a model–based approach to manage tests for evolving service centric systems. We do so by attaching state machines to all model elements of our system model and test model to manage the consistent evolution of the system and its tests. In our approach, a modification to an arbitrary model element is propagated to related model elements. As a consequence, also these model elements may change their state. Based on test requirements, our approach enables the selective generation and automatic execution of a minimal regression test suite. We demonstrate our approach by a real–world industrial example.
Multiple Optimal Path Identification using Ant Colony Optimisation in Wireless Sensor Network

Wireless Sensor Network WSN is tightly constrained for resources like energy, computational power and memory. Many applications of WSN require to communicate sensitive information at sensor nodes SN to Base station BS. The basic performance of WSN depends upon the path length and numbers of nodes in the path by which data is forwarded to BS. In this paper we present bio-inspired Ant Colony Optimisation ACO algorithm for Optimal Path Identification OPI for packet transmission to communicate between SN to BS. Our modified algorithm OPI using ACO is base-station driven which considers the path length and the number of hops in path for data packet transmission. This modified algorithm finds optimal path OP as well as several suboptimal paths between SN & BS which are useful for effective communication.
A network simplex algorithm for simple manufacturing network model

In this paper, we propose a network model called simple manufacturing network. Our model is a combined version of the ordinary multicommodity network and the manufacturing network flow model. It can be used to characterize the complicated manufacturing scenarios. By formulating the model as a minimum cost flow problem plus several bounded variables, we present a modified network simplex method, which exploits the special structure of the model and can perform the computation on the network. A numerical example is provided for illustrating our method.