Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Structures of Elementary School Students: What Is Science?.

The aim of this study is to examine the change in the cognitive structures of elementary school students in respect to the concept of science through word association test in a constructivist approach based project. The study was conducted with 50 students attending to 6 th and 7 th grades who participated in a project supported by The Scientific and Technologic Research Council of Turkey in 2014-2015 academic year. Students were applied a 90-minute activity in scope of the training on science, scientist and scientific knowledge under the project that lasted for 5 days. A word association test that included the concepts of science, scientific knowledge, scientific method, scientist, research, project, experiment and laboratory was applied at the beginning (pre-test) and at the end (post-test) of the project. While word association test was applied, the students were asked to write down the words which were constructed in their minds by the given concepts. A frequency table which consists of concepts of word association test and response words were prepared in data analysis. According to the obtained frequency table, concept networks that revealed the cognitive structures of students were drawn. Upon reviewing the frequency table of the pre-test and post-test of students, and the concept networks, it was observed that the cognitive structures in the relevant concepts of students changed positively. Accordingly, it was concluded that word association tests prove an effective method for revealing the cognitive structures of students. Study findings were discussed in comparison with the studies in the literature, and recommendations were given.
PCR-based identification of Adriatic specimen of three scorpionfish species (Scorpaenidae, Teleostei)

The identification of three scorpionfish species, the black scorpionfish ( Scorpaena porcus Linnaeus, 1758), the large-scaled scorpionfish ( S. scrofa Linnaeus, 1758) and the small red scorpionfish ( S. notata Rafinesque, 1810) is possible in adults by morphometry, but often problematic in juveniles due to their similar phenotypes. To develop a molecular species identification tool, first, we have analyzed the genetic similarity of the three species by a PCR-based ‘blind method’ that amplified bands from various locations of the genome. We found high levels of nucleotide similarity between S. porcus and S. scrofa, whereas S. notata showed a higher level of divergence from the other two species. Then, we have searched these patterns for differences between the genomes of Adriatic specimen of these three species and identified several species-specific products in two of them. For the third one a species-specific primer pair amplifying from the 16S ribosomal DNA was designed. One marker for each species was cloned, sequenced and converted into Sequence Characterized Amplified Region (SCAR) markers amplified by specific primer pairs. The SCAR markers amplified robust bands of limited variability from the target species, while no or only occasional weak products were obtained from the other two, proving that they can be used for molecular identification of these three species. These markers can help the conservation and future analysis of these three species as well as their possible selection programs for aquaculture purposes.
Diagnosis of sibling species of Drosophila involved in the colonization of North America by D. subobscura

To determine the effects of the recent colonization of the west coast of North America by the Palaearctic species Drosophila subobscura on the dynamics of the Drosophila populations, the sibling species D. athabasca and D. azteca must be classified unambiguously. We have characterized these two species using three molecular techniques: allozymes, mtDNA and RAPDs. All three techniques allow the classification of any individual as belonging to either species. The study of five localities in northern California and southern Oregon show that the area of overlap is larger than previously described.
An Approach for Controlling Faults in Wireless Sensor Networks Using Clustering

Fault control and tolerance in wireless sensor network is a challenging problem because of limited energy, bandwidth, and computational complexity. While facing numerous threats these severely resource constrained nodes are responsible for data collection, data processing, localization, time synchronization aggregation and data forwarding. One of the effective approaches to control and tolerate these threats is through clustering. In this paper we present a new method called Efficient Fault Control Mechanism for fault controlling in wireless sensor networks based on clustering and cluster-head selection. Simulation results show Efficient Fault Control Mechanism has better performance over state of art methods.
APPARATUS, TEST PROCEDURES, AND ANALYTICAL METHODS TO MEASURE SOIL ERODIBILITY IN SITU

The assessment of the erodibility of soil materials is essential for analyzing and modeling rill, gully, streambed, streambank, spillway, and embankment erosion. A submerged jet-testing apparatus has been developed and used for characterizing soil erodibility in several applications as cited in the literature. The apparatus has been developed based on knowledge of the hydraulic characteristics of a submerged jet and the characteristics of soil erodibility. The test is simple, quick, and relatively inexpensive to perform. The test is repeatable and gives consistent results. The coefficients obtained from the test results can be used in current equations to predict erosion. This article provides a description of the apparatus, methodology, and procedures for conducting jet tests in the field. An example case is also presented to illustrate the use of test results to predict erosion in an earthen channel. The estimated average erosion, for the example case of an open channel test based on jet test results, was 15.7 cm (6.2 in.) and the measured average centerline erosion in the open channel flow test was 14.5 cm (5.7 in.).
Lipase-catalyzed kinetic resolution of (±)-mandelonitrile under conventional condition and microwave irradiation

The kinetic resolution of (±)-mandelonitrile was carried out using lipase from Candida antarctica under conventional condition (orbital shaker) and microwave irradiation in toluene, producing the (S)-mandelonitrile acetate with high selectivity (up to > 98% ee, enantiomeric excess). The unreacted (R)-mandelonitrile under microwave irradiation and conventional condition was partially converted into benzaldehyde by spontaneous chemical equilibrium. The (S)-mandelonitrile acetate under microwave irradiation was produced with 92% ee and 35% yield for 8 h of reaction. Conventional transesterification of (±)-mandelonitrile in an orbital shaker produced unreacted (R)-mandelonitrile (51% ee) and (S)-mandelonitrile acetate (98% ee) in accordance with Kazlauskas rule for 184 h of reaction.
The Role of −786T/C Polymorphism in the Endothelial Nitric Oxide Synthase Gene in Males with Clinical and Biochemical Features of the Metabolic Syndrome

Background. Extensive evidence, arising from models of endothelial nitric oxide synthase gene (NOS3)-knockout mice supports the role of endothelial malfunction in the pathogenesis of the metabolic syndrome (MS). Aims. The aim of this study was to evaluate the role of −786T/C polymorphism in the etiology of MS and assess previously reported interaction with cigarette smoking. Methods. Based on International Diabetes Federation 2005 criteria, we recruited randomly 152 subjects with MS and 75 subjects without MS. Results. Allelic and genotype frequencies did not differ significantly between both groups. Total cholesterol level (CHOLT) and intima-media thickness of carotid arteries were significantly higher in −786CC homozygotes, in comparison with −786TC and −786TT patients. Regarding current smoking status, −786C allele was associated with higher CHOLT than −786T allele. Conclusion. Our study indicates the putative role of −786T/C polymorphism in the development of hypercholesterolemia, in patients with MS, which might be enhanced by cigarette smoking.
An Uncertainty Visualization Technique Using Possibility Theory: Possibilistic Marching Cubes

This paper opens the discussion about using fuzzy measure theory for isocontour/isosurface extraction in the field of uncertainty visualization. Specifically, we propose an uncertain marching cubes algorithm in the framework of possibility theory, called possibilistic marching cubes. The proposed algorithm uses the dual measures—possibility and necessity—to represent the uncertainty in the spatial location of isocontour/isosurface, which is propagated from the uncertainty in ensemble data. In addition, a novel parametric way of constructing marginal possibility distribution is proposed so that the epistemic uncertainty due to the limited size of the ensemble is considered. The effectiveness of the proposed possibilistic marching cubes algorithm is demonstrated using 2D and 3D examples.
A Criterion Validity Study of the MMPI-2 and PAI Spanish Versions with DIS Diagnosis: Implications for Clinical Practice

New Spanish versions of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) and the Personality Assessment Inventory (PAI) were assessed with the Spanish translation of the Diagnostic Interview Schedule (DIS) as the gold standard. Findings from categorical and dimensional analyses suggest that, although the degree of diagnostic concordance of both measures with the DIS was found to be moderately high, the MMPI-2 clinical scales yielded greater specificity but lower sensitivity than the PAI scales on two of four diagnostic categories (i.e., Major Depression, and Schizophrenia). Both measures failed to correctly diagnose Anxiety Disorders, while the MMPI-2 also showed poor diagnostic accuracy with Alcohol Dependence.
Detecting Periods of Eating During Free-Living by Tracking Wrist Motion

This paper is motivated by the growing prevalence of obesity, a health problem affecting over 500 million people. Measurements of energy intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require a considerable manual effort, leading to under reporting of consumption, noncompliance, and discontinued use over the long term. The purpose of this paper is to describe a new method that uses a watch-like configuration of sensors to continuously track wrist motion throughout the day and automatically detect periods of eating. Our method uses the novel idea that meals tend to be preceded and succeeded by the periods of vigorous wrist motion. We describe an algorithm that segments and classifies such periods as eating or noneating activities. We also evaluate our method on a large dataset (43 subjects, 449 total h of data, containing 116 periods of eating) collected during free-living. Our results show an accuracy of 81% for detecting eating at 1-s resolution in comparison to manually marked event logs of periods eating. These results indicate that vigorous wrist motion is a useful indicator for identifying the boundaries of eating activities, and that our method should prove useful in the continued development of body-worn sensor tools for monitoring energy intake.
Consensus and Volatility in Presidential Approval

One of the central themes in research, teaching, and popular commentary about American politics is the power of the Presidency. This is no surprise, since American domestic politics and policymaking, and even many decisions on the world stage, rotate about the axis of the U.S. president. Presidential approval plays a particularly critical role in presidential power, as ample studies have demonstrated over the past twenty years. We must be concerned, then, over recent evidence of an increasingly fickle American public. Presidents have enjoyed new peaks but also suffered new lows in popular approval. Changes in approval seem to be more rapid and the diversity of opinions at any one time seems to be growing. If the American public has become more volatile and less consensual in their evaluations of the president, it will be difficult for presidents to build and maintain legislative coalitions, unify domestic actors behind foreign policy initiatives, and ultimately maintain their electoral coalitions. The president’s success in swaying public opinion and the president’s ability to use public support as a leadership tool may depend as much on the amount of agreement (consensus) and the lability of public support (volatility) as it does on the average level of approval. This paper takes an opening look at measuring and modeling volatility and consensus in presidential approval. Drawing on data from the New York Times/CBS polls from 1976–1993, the paper shows, via descriptive analysis, how mean approval, over time volatility, and cross sectional variability, are distinct processes. The paper then proposes some alternative ways to examine volatility and consensus. Paper prepared for the annual meeting of the Southern Political Science Association, Atlanta, GA, November 1996. The author would like to thank John Aldrich, John Brehm, Lyle Scruggs, Renée Smith, Janet Box–Steffensmeier, and Jim Stimson for encouragement and help, and the ICPSR (and Suzanne DeBoef) for access to the NYT data. All remaining errors are certainly the fault of the author. Draft Copy: Comments and criticism highly encouraged
Learning to Rank Comments Within Subreddit Submissions

Naïve Bayes Naive Bayes Classification was our first stab at the problem. We saw the model had a very poor performance as the number of training examples increased. This is because for a small data set, certain words can be used as distinct identifiers for a particular post. But this nice property disappears as more and more posts have the same words. This motivated us to move on to linear regression. Linear Regression Our regression model takes a post with varying number of comments, and outputs the predicted ranking of all of the comments. This prediction is made by extracting features (listed bottom right) from the comments, normalizing them with respect to all comments in a post, and then training a regression model of linear regression or an SVR (pictorially shown above). To calculate the effectiveness of our ranking, we used a normalized Spearman’s Footrule, which is the sum of the absolute difference of rankings for each post, divided by the maximum Spearman’s Footrule error (shown below right). We tested our model on different subreddits, but show only data from /r/murica. The learning curve of /r/murica shows that our model has high bias and underfits the data, as expected since we don’t not have an enormous number of features (shown below). However, despite this lack of features, we still find that the average error decreases from 0.616 to 0.354 for /r/murica, as well as shift most errors below 0.5 (shown bottom left). The feature effectiveness varied across subreddits, including the most significant feature time; adding feature categories one at a time shows the effect of each for /r/murica (shown below right). Clustering The Meme-Clustering algorithm is our attempt to use machine learning tools to provide intelligent features that are difficult to generate using a single formula. The algorithm can be described in the following four steps: 1. generate prior frequencies for $words 2. identify (word, time) pairs of significant importance 3. run k-means on results from step 2 4. run a filter to remove undesired outputs The output of this algorithm is a collection of centroids representing phrases that had a significant impact during a time period. Below are some human readable sample output:
Propagation of Electromagnetic Waves in a Sinusoidally Modulated Dielectric Substrate

A single-layer microstrip structure with variable line width is considered in order to create, by periodic repetition, an electromagnetic bandgap structure. The width of the line is varied in such a way as to guarantee a sinusoidally modulated value of the effective dielectric constant along the longitudinal direction. By repeating periodically the structure in the orthogonal direction, a high-impedance surface is obtained. Continuous and discrete line configurations are considered, and the performances of the two-dimensional structure with respect to the uniform line case are compared
Inhalation of Silver Nanomaterials—Seeing the Risks

Demand for silver engineered nanomaterials (ENMs) is increasing rapidly in optoelectronic and in health and medical applications due to their antibacterial, thermal, electrical conductive, and other properties. The continued commercial up-scaling of ENM production and application needs to be accompanied by an understanding of the occupational health, public safety and environmental implications of these materials. There have been numerous in vitro studies and some in vivo studies of ENM toxicity but their results are frequently inconclusive. Some of the variability between studies has arisen due to a lack of consistency between experimental models, since small differences between test materials can markedly alter their behaviour. In addition, the propensity for the physicochemistry of silver ENMs to alter, sometimes quite radically, depending on the environment they encounter, can profoundly alter their bioreactivity. Consequently, it is important to accurately characterise the materials before use, at the point of exposure and at the nanomaterial-tissue, or “nanobio”, interface, to be able to appreciate their environmental impact. This paper reviews current literature on the pulmonary effects of silver nanomaterials. We focus our review on describing whether, and by which mechanisms, the chemistry and structure of these materials can be linked to their bioreactivity in the respiratory system. In particular, the mechanisms by which the physicochemical properties (e.g., aggregation state, morphology and chemistry) of silver nanomaterials change in various biological milieu (i.e., relevant proteins, lipids and other molecules, and biofluids, such as lung surfactant) and affect subsequent interactions with and within cells will be discussed, in the context not only of what is measured but also of what can be visualized.
Integrating Configuration Management and Software Deployment

As the development and use of component-based software becomes increasingly pervasive, the need arises for tools that support the controlled evolution of independently developed components—both at development and at deployment time. Traditionally, such tools have been separate: configuration management tools are used during the development of a software product and deployment tools are used to install, update, and reconfigure a software product once it is out in the field. This position paper first presents an argument why this separation is inadequate for component-based software. Then, it presents a set of requirements for an integrated system that intimately combines configuration management and software deployment functionality to support the evolution of component-based software in a unified manner.
Art or Science? Synthesising Lessons from Public Interest Litigation and the Dangers of Legal Determinism

Abstract In 2008, one of the largest funders of human rights organisations in South Africa, the Atlantic Philanthropies, published a report that identified several factors for optimal public interest litigation. Despite the relative density of organisations that conduct public interest litigation in South Africa, there has been little critical engagement with its findings. Yet this exercise is pertinent given the growing reliance by South African civil society organisations on litigation to resolve systemic failures by the state, together with the ever more pressing requirement from donors to prove the strategic value of the turn (or return) to the courts. This article aims to contribute to the discussion about the uptake and value of public interest litigation by problematising the premises and recommendations of the Atlantic Philanthropies Report (APR). The report’s analysis is tested, partly through the lens of two recent cases concerning the disconnection of municipal services – Mazibuko (water) and Joseph (electricity) – revealing another type of disconnection: that the public impact litigation process is generally too unpredictable and diffuse for it to be adequately assessed through a formulaic or scientific approach. At the same time, it has more potential for social change than covered in the APR. The article therefore advances a more expansive, contextualised and responsive framework for conceptualising the role of public impact litigation and assessing its impact. The proposed framework takes into account structural conditions of power, agency in the form of social mobilisation and the role of public interest litigation in constituting ‘politics by other means’. 1
A frequency warping approach to speaker normalization

In an effort to reduce the degradation in speech recognition performance caused by variation in vocal tract shape among speakers, a frequency warping approach to speaker normalization is investigated. A set of low complexity, maximum likelihood based frequency warping procedures have been applied to speaker normalization for a telephone based connected digit recognition task. This paper presents an efficient means for estimating a linear frequency warping factor and a simple mechanism for implementing frequency warping by modifying the filterbank in mel-frequency cepstrum feature analysis. An experimental study comparing these techniques to other well-known techniques for reducing variability is described. The results have shown that frequency warping is consistently able to reduce word error rate by 20% even for very short utterances.
Finite Element Analysis based Optimization of Magnetic Adhesion Module for Concrete Wall Climbing Robot

Wall climbing robot can provide easier accessibility to tall structures for Non Destructive Testing (NDT) and improve working environments of human operators. However, existing adhesion mechanism for climbing robots such as vortex, electromagnet etc. are still at development stage and offer no feasible adhesion mechanism. As a result, few practical products have been developed for reinforced concrete surfaces, though wall-climbing robots have been researched for many years. This paper proposes a novel magnetic adhesion mechanism for wall-climbing robot for reinforced concrete surface. Mechanical design parameters such as distance between magnets, the yoke thickness, and magnet arrangements have been investigated by Finite Element Analysis (FEA). The adhesion module can be attached under the chassis of a prototype robot. The magnetic flux can penetrate maximum concrete cover of 30 mm and attain adhesion force of 121.26 N. The prototype provides high Force-to-Weight ratio compared to other reported permanent magnet based robotic systems. Both experiment and simulation results prove that the magnetic adhesion mechanism can generate efficient adhesion force for the climbing robot to operate on vertical reinforced concrete structures.