Miracle-dz/UniFAR-FTUs huggingface dataset:
A reversible transform for seismic data processing

We use the nonstationary equivalent of the Fourier shift theorem to derive a general one-dimensional integral transform for the application and removal of certain seismic data processing steps. This transform comes from the observation that many seismic data processing steps can be viewed as nonstationary shifts. The continuous form of the transform is exactly reversible, and the discrete form provides a general framework for unitary and pseudounitary imaging operators. Any processing step which can be viewed as a nonstationary shift in any domain is a special case of this transform. Nonstationary shifts generally produce coordinate distortions between input and output domains, and those that preserve amplitudes do not conserve the energy of the input signal. The nonstationary frequency and time distortions and nonphysical energy changes inherent to such operations are predicted and quantied by this transform. Processing steps of this type are conventionally implemented using interpolation operators to map discrete data values between input and output coordinate frames. Although not explicitly derived to perform interpolation, the transform here assumes the Fourier basis to predict values of the input signal between sampling locations. We demonstrate how interpolants commonly used in seismic data processing and imaging approximate the proposed method. We nd that our transform is equivalent to the conventional sinc-interpolant with no truncation. Once the transform is developed, we demonstrate its numerical implementation by matrix-vector multiplication. As an example, we use our transform to apply and remove normal moveout.
“Dirty Politics”: The Role of Disgust Sensitivity in Voting

A growing body of research indicates that disgust sensitivity plays an important role in politics. Indeed, preliminary evidence indicates that disgust sensitivity predicts voting behavior. However, the processes that explain this association are unknown. The purpose of this study was to determine whether disgust sensitivity predicted voting intentions and behavior in the 2012 U.S. presidential election and to test whether these associations were mediated by sociopolitical values, party affiliation, and attitudes toward political candidates. Prior to the 2012 election, participants completed measures of disgust sensitivity, right-wing authoritarianism, party affiliation, attitudes toward the political candidates (i.e., Barack Obama and Mitt Romney), and voting intentions. After the 2012 election, participants reported their voting behavior. After accounting for prejudice toward African Americans, greater disgust sensitivity was significantly associated with lower intention to vote for Obama versus Romney and lower likelihood of actually voting for Obama. Disgust sensitivity was also associated with more conservative sociopolitical values, a greater likelihood of Republican Party affiliation, a lower likelihood of Democratic Party affiliation, more negative attitudes toward Obama, and more positive attitudes toward Romney. Conservative sociopolitical values, party affiliation, and attitudes toward political candidates independently mediated the association between disgust sensitivity and voting intentions. Conservative sociopolitical values and political candidate attitudes mediated the association between disgust sensitivity and voting behavior. These findings demonstrate the importance of disgust sensitivity for political attitudes and behavior. Further, mechanisms through which disgust sensitivity is implicated within voting tendencies are identified.
Where does the hard X-ray diffuse emission in clusters of galaxies come from?

The surface brightness produced by synchrotron radiation in clusters of galaxies with a radio-halo sets a degenerate constraint on the magnetic field strength, the relativistic electron density and their spatial distributions, B(r )a ndnrel(r), in the intracluster medium. Using the radio-halo in the Coma Cluster as a case study, with the radio brightness profile and the spectral index as the only constraints, predictions are made for the brightness profiles expected in the 20–80 keV band due to Inverse Compton Scattering (ICS) by the relativistic electrons on the Cosmic Microwave Background. This is done for a range of central values of the magnetic field, B, and models of its radial dependence, B(r )( of which two represent extreme situations, namely a constant value either of B or of nrel(r), the third a more realistic intermediate case). It is shown that the possible presence of scalar fluctuations on small scales in the strength of B tends to systematically depress the electron density required by the radio data, hence to decrease the ICS brightness expected. These predictions should be useful to evaluate the sensitivity required in future imaging HXR instruments, in order to obtain direct information on the spatial distribution and content of relativistic electrons, hence on the magnetic field properties. If compared with the flux in the HXR tail, whose detection has been claimed in the Coma cluster (Fusco-Femiano et al. 2004, ApJ, 602, L73), when interpreted as ICS from within the radius Rh of the radio-halo, as measured so far, the predictions lead to central values B0 that are significantly lower than those which have been obtained (albeit still controversial) from Faraday Rotation measurements. The discrepancy is somewhat reduced if the radio-halo profile is hypothetically extrapolated out to Rvir, that is about three times Rh, or, as suggested by hydrodynamical simulations (Dolag et al. 2002, A&A, 387, 383), if it is assumed that B(r) ∝ nth(r). In the latter case nrel(r) has its minimum value at the center of the cluster. If real and from ICS, the bulk of the HXR tail should then be contributed by electrons other than those responsible for the bulk of the radio-halo emission. This case illustrates the need for spatially resolved spectroscopy in the HXR, in order to obtain solid information on the non-thermal content of clusters of galaxies.
Popular science writing bringing new perspectives into science students' theses

ABSTRACT This study analyses which perspectives occur in science students’ texts at different points in time during the process of writing a popular science article. The intention is, thus, to explore how popular science writing can help students discover and discuss different perspectives on science matter. For this purpose, texts written by 12 bachelor students in biology were analysed in a case study. For each of the students, four texts were studied using content analysis: two versions of a popular science article on the student's bachelor project, and two texts reflecting on why the project is interesting. Throughout the writing process an increased number of perspectives was observed; the character of the perspectives also changed, from a narrow research perspective to a wider societal perspective. For example, environmental, medical, economical or ethical perspectives were added during the writing process. There was also a change concerning the level on which science matter was discussed, from specific to more general. A second aim was to explore how popular science writing may facilitate students’ scientific writing. In this part of the study, content analysis was conducted on 23 students’ written reflections. A vast majority described how the popular writing facilitated, in particular, the choice of content and perspectives also in their scientific writing. Altogether, the study concludes that popular science writing offers a cognitive tool to widen science students’ perspectives, and hence, to promote their development of scientific literacy and achievement of scientific writing skills.
The two-dimensional Gabor function adapted to natural image statistics: An analytical model of simple-cell responses in the early visual system

The two-dimensional Gabor function is adapted to natural image statistics by learning the joint distribution of the Gabor function parameters. The joint distribution is then approximated to yield an analytical model of simple-cell receptive fields. Adapting a basis of Gabor functions is found to take an order of magnitude less computation than learning an equivalent non-parameterized basis. Derived learning rules are shown to be capable of adapting Gabor parameters to the statistics of images of man-made and natural environments. Learning is found to be most pronounced in three Gabor parameters that represent the size, aspect-ratio, and spatial frequency of the two-dimensional Gabor function. These three parameters are characterized by non-uniform marginal distributions with heavy tails -- most likely due to scale invariance in natural images -- and all three parameters are strongly correlated: resulting in a basis of multiscale Gabor functions with similar aspect-ratios, and size-dependent spatial frequencies. The Gabor orientation and phase parameters do not appear to gain anything from learning over natural images. Different tuning strategies are found by controlling learning through the Gabor parameter learning rates. Two opposing strategies include well-resolved orientation and well-resolved spatial frequency. On image reconstruction, a basis of Gabor functions with fitted marginal distributions is shown to significantly outperform a basis of Gabor functions generated from uniformly sampled parameters. An additional increase in performance results when the strong correlations are included. However, the best analytical model does not yet achieve the performance of the learned model. A comparison with estimates for biological simple cells shows that the Gabor function adapted to natural image statistics correctly predicts some key receptive field properties.
The Effects of Motivation and Goal Setting on Response Latency and Mental Effort

Researchers have found that performance is enhanced when participants set goals that are specific, difficult, and perceived as attainable. Also, motivation contributes to performance; specifically, intrinsic motivation, approach motivation, and avoidance motivation. Ninety participants were assigned randomly to one of two motivation groups; a goal setting or a control and assessed over a series of memory problems; solvable and unsolvable. Participant’s response latencies (RL) following an unsolvable problem was examined as a function of motivation type. Based upon the results from a 2 (Group; goal setting vs. control) X 2 (test order) X 2 (memory problem difference scores) mixed ANOVA, a significant Group difference was found. The goal setting group had significantly faster RL’s compared to the control group. Secondary analyses of motivation type by goal setting group revealed no significant differences between the goal group and control group on the BAS, BIS, and Intrinsic Scales. It was hypothesized that the magnitude and type of motivation would be predictive of memory problem performance. However, no consistent relationships between motivation and RL were evident, an unexpected result.
Real time compression of triangle mesh connectivity

In this paper we introduce a new compressed representation for the connectivity of a triangle mesh. We present local compression and decompression algorithms which are fast enough for real time applications. The achieved space compression rates keep pace with the best rates reported for any known global compression algorithm. These nice properties have great benefits for several important applications. Naturally, the technique can be used to compress triangle meshes without significant delay before they are stored on external devices or transmitted over a network. The presented decompression algorithm is very simple allowing a possible hardware realization of the decompression algorithm which could significantly increase the rendering speed of pipelined graphics hardware. CR Categories: I.3. 1 [Computer Graphics]: Hardware Architecture; I.3. 3 [Computer Graphics]: Picture/Image Generation— Display algorithms
Older Adults’ Perception of Chronic Illness Management in South Korea

Objectives: Despite the recent emphasis on a patient-centered chronic care model, few studies have investigated its use in older adults in South Korea. We explored how older Korean adults perceive and cope with their chronic illness. Methods: We conducted focus group interviews in Seoul, Korea in January 2010. Focus groups were formed by disease type (hypertension and type 2 diabetes) and gender using purposive sampling. Inclusion criteria were patients aged 60 and over who had been diagnosed with diabetes or hypertension and received care at a community health center for at least six months prior to participation. Interview data were analyzed through descriptive content analysis. Results: Among personal factors, most participants felt overwhelmed when they received their diagnosis. However, with time and control of their acute symptoms using medication, their worry diminished and participants tended to denying being identified as a patient or sick person. Among socio-familial factors, participants reported experiencing stigma with their chronic illness and feeling it was a symbol of weakness. Instead of modifying their lifestyles, which might interfere with their social relationships, they resorted to only following their medicine regime prescribed by their doctor. Participants also reported feeling that their doctor only prescribed medications and acted in an authoritative and threatening manner to induce and reinforce participants’ compliance with treatment. Conclusions: For successful patient-centered management of chronic illnesses, supportive environments that include family, friends, and healthcare providers should be established.
HeNLM-LA: A LOCALLY ADAPTIVE HERMITE FUNCTIONS EXPANSION BASED NON-LOCAL MEANS DENOISING

A new noise reduction algorithm HeNLM-LA is proposed. It is a modi(cid:28)cation of the non-local means algorithm using Hermite functions expansion of pixel neighborhoods. The (cid:28)ltering strength parameter is automatically adjusted proportionally to the local noise level. An algorithm for local noise level estimation is based on edge modeling; it suppresses high-amplitude edges in the map of local image variance.
Department of Economics Econometrics Working Paper Ewp1001 Hermite Regression Analysis of Multi-modal Count Data

We discuss the modeling of count data whose empirical distribution is both multi-modal and over-dispersed, and propose the Hermite distribution with covariates introduced through the conditional mean. The model is readily estimated by maximum likelihood, and nests the Poisson model as a special case. The Hermite regression model is applied to data for the number of banking and currency crises in IMF-member countries, and is found to out-perform the Poisson and negative binomial models.
Prediction of Phenotype Information from Genotype Data

The dissection of complex diseases is one of the greatest challenges of human genetics with important clinical and scientific applications. Traditionally, associations were sought between single genetic markers and disease. The availability of large scale SNP data makes it possible, for the first time, to study the predictive power of genotypes and haplotypes with respect to phenotype data. Here we present a novel method for predicting phenotype information from genotype data. The method is based on a support vector machine that employs new kernel functions for the similarity between genotypes or their underlying haplotypes. We demonstrate our approach on SNP data for the apolipoprotein gene cluster in baboons, predicting plasma lipid levels with significant success rates, and identifying associations that were not detected using extant approaches.
ANALYSIS OF BIFURCATION AND CHAOS IN A COUPLED RAYLEIGH OSCILLATORS SYSTEM APPLIED IN THE LOCOMOTION OF A BIPEDAL ROBOT

Coupled oscillators can be used in control systems of locomotion as pattern generators similar to the pattern of human gait, providing approached trajectories of the legs. In this work, the central pattern generator (CPG), responsible for the production of rhythmic movements, is formed by a set of mutually coupled Rayleigh oscillators. From a model of two-dimensional robot, oscillators were used for simulating the behavior of the hip and knees. Each oscillator has its own parameters and the link to the other oscillators is made through coupling terms. The objective of this work is to analyze the nonlinear dynamics of this system using bifurcation diagrams and Poincaré maps. By means of the analysis and graphs generated in MATLAB, it was possible to evaluate some characteristics of the system, such as: sensitivity to the initial conditions and presence of strange attractors. Based on the results of this study, we conclude that although the use of Rayleigh oscillators represents an excellent way for generating pattern signals of locomotion, its application in the control of a bipedal robot will only be possible with the correct choice of parameters, which must be done from the data provided by the analysis of bifurcation and chaos.
Crowdsourcing for closed-loop control

We present a system for large scale robotic learning from demonstration. We describe a set of software tools for enabling human-robot interaction over the internet and gathering the large datasets that such crowdsourcing makes possible. We show results in which humans teach a robot to navigate a maze over the Internet. Robots occupy a peculiar place in our culture. We have been building robots in our imaginations for decades, robots that are alternately wondrous or terrifying, always brilliant and consummately skilled. In contrast, real robots are typically brittle and capable of only a few simple constrained tasks. Additionally, only expert programmers, intimately familiar with the particulars of a low-level robotic system, can hope to achieve any kind of complex robot behavior. This paper describes our efforts to apply the lessons of crowdsourcing to robotics to leverage the power and knowledge of a truly large number of end users to create more skilled and robust robot controllers. We focus on learning from demonstration (LfD), [2, 1] an approach to robot programming in which users demonstrate desired skills to a robot. Nothing is required of the user beyond the ability to complete the task in a way that the robot can interpret. Traditionally, LfD research has been constrained by the number of demonstrations that can be performed; unless a large number of users can interact with the robot only a limited amount of data can easily be gathered. Since users do not usually need specialized skills to demonstrate robot skills, a web-enabled system could be used to collect data from a large number of users. An online system also lifts the burden of training the robot from a single user who may only want to contribute a few demonstrations. Collecting data for closed-loop control is different from many crowdsourcing applications examined in the Machine Learning community, which has typically focused on annotation of text and labeling of images. Task demonstration often requires a significant interaction both in terms of time and information provided to the user. Users not only give the robot instructions, but also evaluate the results and provide new instructions given the outcome. We describe a recently developed system that allows a large number of users to train a robot to solve a task (in this case maze-navigation) through a video-game style interface. While a single demonstration may contain errors and provides only limited data, the demonstrations from multiple users provide enough data to create a robust policy. There have been a few initial efforts in putting robots on the Internet [4, 9]. These approaches generally allowed people to interact with robots but were not aimed at task learning. Other work examined using crowdsourcing approaches to train robots through game playing environments. Chernova et al examined using a multi-player video game where users collaborate to provide user demonstrations [3]. This work differs from ours in that
The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics

Economists have lately been called upon not only to analyze markets, but to design them. Market design involves a responsibility for detail, a need to deal with all of a market's complications, not just its principle features. Designers therefore cannot work only with the simple conceptual models used for theoretical insights into the general working of markets. Instead, market design calls for an engineering approach. Drawing primarily on the design of the entry level labor market for American doctors (the National Resident Matching Program), and of the auctions of radio spectrum conducted by the Federal Communications Commission, this paper makes the case that experimental and computational economics are natural complements to game theory in the work of design. The paper also argues that some of the challenges facing both markets involve dealing with related kinds of complementarities, and that this suggests an agenda for future theoretical research. Copyright The Econometric Society 2002.
Semi-Automated Resolution of Inconsistency for a Harmonized Multiword Expression and Dependency Parse Annotation

This paper presents a methodology for identifying and resolving various kinds of inconsistency in the context of merging dependency and multiword expression (MWE) annotations, to generate a dependency treebank with comprehensive MWE annotations. Candidates for correction are identified using a variety of heuristics, including an entirely novel one which identifies violations of MWE constituency in the dependency tree, and resolved by arbitration with minimal human intervention. Using this technique, we identified and corrected several hundred errors across both parse and MWE annotations, representing changes to a significant percentage (well over 10%) of the MWE instances in the joint corpus.
Somatic Embryogenesis Proliferation, Maturation and Germination in Cajanus cajan

Somatic embryogenesis was induced from mature cotyledon explants of two pigeon pea genotypes cultured on MS medium supplemented with different concentrations of 2,4-D and Thiadizuron (TDZ). The greatest response was obtained with 2.0 mg/l (2,4-D) or (TDZ). Type and concentrations of growth regulators along with genotypes influenced the frequency of somatic embryogenesis. TDZ was more superior than 2,4-D at 2.0 mg/l increasing number of somatic embryos/explant with ICPL 87-118 genotype and produced the highest number (29.40), while no significant deference between 2.0 mg/l of either TDZ or 2,4-D in increasing this parameter with ICPL 151 (20.0 and 21.20) respectively. Maturation treatment increased normal germinated somatic embryos significantly (1.95) compared with somatic embryos that had no maturation treatment (0.40). Half MS salts basal medium was better than full MS medium in germinating of pigeon pea somatic embryos. The number of converted embryos increased significantly from 0.75 to 1.60 when 0.1 mg/l BA was supplemented to the media. No secondary embryogenesis was induced on somatic embryos that cultured on maturation medium. However, without maturation treatment, more than 70% of secondary embryogenesis was obtained with full strength basal medium MS supplemented with 0.1mg/l BA. After one month from acclimatization the plantlets grew vigorously and a percentage of plant survival (32%) was achieved during this phase of culture. The present study aimed to produce embryos with high frequency and their subsequent conversion to plants offers potential to use in plant transformation and regeneration and to produce synthetic seeds.