Miracle-dz/UniFAR-FTUs huggingface dataset:
Auto-correlation Dependent Bounds for Relational Data

A large portion of the data that is collected in various application domains such as online social networking, nance, biomedicine, etc. is relational in nature. A subeld of Machine Learning namely; Statistical Relational Learning (SRL) is concerned with performing statistical inference on relational data. A dening property of relational data that separates it from independently and identically distributed data (i.i.d.) is the existence of correlations between individual datapoints. A major portion of the theory developed in machine learning assumes the data is i.i. d. In this paper we develop theory for the relational setting. In particular, we derive distribution free bounds for the relational setting where the class of data generation models we consider are inspired from the type joint distributions that are represented by relational classication models developed by the SRL community. A key aspect of the bound we derive is that the tightness of the bound is a function of the strength of dependence between related datapoints, with the bound reducing to the standard Hoeding’s or McDiarmid’s
The Use of a Two-Tiered Testing Strategy for the Simultaneous Detection of Small EGFR Mutations and EGFR Amplification in Lung Cancer

Lung cancer is the leading cause of cancer-related death worldwide. Recent progress in lung cancer diagnosis and treatment has been achieved due to a better understanding the molecular mechanisms of the disease and the identification of biomarkers that allow more specific cancer treatments. One of the best known examples of personalized therapy is the use of tyrosine kinase inhibitors, such as gefitinib and erlotinib, for the successful treatment of non-small-cell lung cancer patients selected based on the specific EGFR mutations. Therefore, the reliable detection of mutations is critical for the application of appropriate therapy. In this study, we tested a two-tiered mutation detection strategy using real-time PCR assays as a well-validated high-sensitivity method and multiplex ligation-dependent probe amplification (MLPA)-based EGFRmut+ assay as a second-tier standard-sensitivity method. One additional advantage of the applied MLPA method is that it allows the simultaneous detection of EGFR mutations and copy-number alterations (i.e., amplifications) in EGFR, MET and ERBB2. Our analysis showed high concordance between these two methods. With the use of this two-tier strategy, we reliably determined the frequency of EGFR mutations and EGFR, MET and ERBB2 amplifications in over 200 lung cancer samples. Additionally, taking advantage of simultaneous copy number and small mutation analyses, we showed a very strong correlation between EGFR mutations and EGFR amplifications and a mutual exclusiveness of EGFR mutations/amplifications with MET and ERBB2 amplifications. Our results proved the reliability and usefulness of the two-tiered EGFR testing strategy.
Accurate Assessment of the Oxygen Reduction Electrocatalytic Activity of Mn/Polypyrrole Nanocomposites Based on Rotating Disk Electrode Measurements, Complemented with Multitechnique Structural Characterizations

This paper reports on the quantitative assessment of the oxygen reduction reaction (ORR) electrocatalytic activity of electrodeposited Mn/polypyrrole (PPy) nanocomposites for alkaline aqueous solutions, based on the Rotating Disk Electrode (RDE) method and accompanied by structural characterizations relevant to the establishment of structure-function relationships. The characterization of Mn/PPy films is addressed to the following: (i) morphology, as assessed by Field-Emission Scanning Electron Microscopy (FE-SEM) and Atomic Force Microscope (AFM); (ii) local electrical conductivity, as measured by Scanning Probe Microscopy (SPM); and (iii) molecular structure, accessed by Raman Spectroscopy; these data provide the background against which the electrocatalytic activity can be rationalised. For comparison, the properties of Mn/PPy are gauged against those of graphite, PPy, and polycrystalline-Pt (poly-Pt). Due to the literature lack of accepted protocols for precise catalytic activity measurement at poly-Pt electrode in alkaline solution using the RDE methodology, we have also worked on the obtainment of an intralaboratory benchmark by evidencing some of the time-consuming parameters which drastically affect the reliability and repeatability of the measurement.
Taking Stock: Renewing Our Research Agenda on the Causes and Consequences of Dropping Out

Gary Natriello, Aaron M. Pallas, and Edward L. McDill provide an assessment of the findings and suggestions presented in this special issue on school dropouts and outline an agenda for the next steps in research on the problem. They argue that a comprehensive program of research should include data on student characteristics, school processes, the act of dropping out, and the economic and cognitive consequences of the failure of large numbers of students to complete high school.
Natural Resource Abundance and Economic Growth

One of the surprising features of modern economic growth is that economies with abundant natural resources have tended to grow less rapidly than natural-resource-scarce economies. In this paper we show that economies with a high ratio of natural resource exports to GDP in 1971 (the base year) tended to have low growth rates during the subsequent period 1971-89. This negative relationship holds true even after controlling for variables found to be important for economic growth, such as initial per capita income, trade policy, government efficiency, investment rates, and other variables. We explore the possible pathways for this negative relationship by studying the cross-country effects of resource endowments on trade policy, bureaucratic efficiency, and other determinants of growth. We also provide a simple theoretical model of endogenous growth that might help to explain the observed negative relationship.
On the Impact of Intensive/ Reactive Performance on EFL Learners’ Listening Comprehension Ability

Listening comprehension plays a significant role in developing foreign language learning and it can be considered as a useful skill to gain sufficient comprehensible input. The current research sought to explore the effectiveness of using reactive/performance versus intensive one on Iranian intermediate English learners’ listening comprehension ability. It was carried out at Kish English Language Institute in Tehran among 60 intermediate female learners with the age range of 10-19 through a quasi-experimental research design. The participants were assigned into two groups. First, the pretest was administered to each group. The test was taken from the book ‘Four Corners’. Then, one group was exposed to intensive performance and the other group received reactive performance. After ten sessions, a post-test that was the parallel form of the pretest, was administrated to the both groups. Finally, the data were analyzed using an independent and paired samplest-tests. Results showed that teaching listening based on intensive performance had a significant effect on learners’ listening comprehension. The findings may have some useful implications for language teachers.
The unity of moral attitudes: recipe semantics and credal exaptation*

Abstract This paper offers a noncognitivist characterization of moral attitudes, according to which moral attitudes count as such because of their inclusion of moral concepts. Moral concepts are distinguished by their contribution to the functional roles of some of the attitudes in which they can occur. They have no particular functional role in other attitudes, and should instead be viewed as evolutionary spandrels. In order to make the counter-intuitive implications of the view more palatable, the paper ends with an account of the evolution of normative judgments as exaptations of the cognitive structures that underlie beliefs.
Benefits of Incubation on Divergent Thinking

Studies on whether fixation cues provided in the first episode of divergent thinking tasks influence creative outcomes after incubation, as they do for convergent problem-solving tasks, remain limited. This research examined the beneficial effects of incubation using the delayed- and immediate-incubation paradigms. Participants in Experiment 1 were either provided or not provided fixation cues during the first episode of a new type of divergent-thinking task, similar to creating titles in plot stories. The results indicated that fixation cues moderated people’s creative outcomes after incubation. Going through incubation did not improve the participants’ creativity in the second episode for strong fixation cues. By contrast, an incubation period led to the generation of more divergent items in the second episode compared to the first episode for less strong fixation cues, and this led to the performance matching the condition without fixation cues. The results from Experiment 2 suggested that immediate incubation downsized the influence of fixation cues. Therefore, if people want to promote their creativity through a period of incubation, the outcomes may still depend on the conditions of environments in which the creative works are executed.
Numerical Analysis of High Speed Droplet Impact

When a droplet impacts a solid surface at high speed, the contact periphery expands very quickly and liquid compressibility plays an important role in the initial dynamics and the formation of lateral jets. The high speed impact results in high pressures that can account for the surface erosion. In this study, we numerically investigated a high speed droplet impacts on a solid wall. The multicomponent Euler equations with the stiffened equation of state are computed using a FV-WENO scheme with an HLLC Riemann solver (Johnsen & Colonius 2006) that accurately captures shocks and interfaces. In order to compare the available theories and experiments, 1D, 2D and axisymmetric solutions are obtained. The generated pressures, shock speeds, and the lateral jetting generation are investigated. In addition, the effect of target compliance is evaluated.
Bilingualism and Creativity: Towards a Situated Cognition Approach.

In this paper, the association between bilingualism and creativity is investigated. In the first part, the results of a literature review are reported. Previous research predominantly found that bilinguals outperform monolinguals on creativity tasks, which was explained by bilinguals' enhanced executive functioning compared to monolinguals, and their experience with multiple cultures. Most previous research has examined the relationship between bilingualism and creativity within a psychological trait framework, which does not take into account that cognitive processes are regarded to be situated‐embodied, meaning that they are influenced by environmental factors, and by a person's perceptions of and actions towards these environmental factors. In the second part, we discuss an alternative approach, in which creativity can be defined as the emerging skill of an individual to discover affordances, to come up with creative ideas and products. Recommendations for future research are discussed as well.
An Evaluation of Amazon's Grid Computing Services: EC2, S3, and SQS

Amazon.com’s Elastic Compute Cloud (EC2), Simple Storage Service (S3) and Simple Queue Service (SQS) offer enterprise-class computing, storage and coordination facilities to any organization or individual in the world with a valid credit card. This paper details our experience working with these commodity grid computing services between November 2006 and May 2007, including an analysis of the overall system’s API and ease-of-use; an analysis of EC2’s management and security facilities; an end-to-end performance analysis of S3’s throughput and latency as observed from Amazon’s EC2 cluster and other locations on the Internet; and an analysis of the SQS operation and performance. We conclude with a report of our experience moving a large-scale research application from dedicated hardware to the Amazon offering. We find that this collection of AmazonWeb Services (AWS) has great promise but are hobbled by service consistency problems, the lack of a Service Level Agreement (SLA), and a problematic Web Services Licensing Agreement (WSLA).
Analyzing the download time of availability codes

In distributed storage systems, a special sub-class of locally repairable codes, referred to as availability codes, has been proposed to enable recovery of each data block from one of its repair groups. A repair group typically contains a small number of nodes and does not overlap with any other repair group of the same data block. Availability codes have several important benefits, including high degree of fault tolerance, efficient recovery from failures, and efficient access to data by multiple users. In this paper, we study the availability codes from a queuing-theoretical perspective. Specifically, we analyze the average time necessary to download a block of data under the Poisson request arrival model in two service/scheduling scenarios. We compare the availability codes with several alternatives such as MDS codes and replication schemes. Our results indicate that availability codes can minimize the download time in some settings, but are not always optimal.
Adaptive rendering with linear predictions

We propose a new adaptive rendering algorithm that enhances the performance of Monte Carlo ray tracing by reducing the noise, i.e., variance, while preserving a variety of high-frequency edges in rendered images through a novel prediction based reconstruction. To achieve our goal, we iteratively build multiple, but sparse linear models. Each linear model has its prediction window, where the linear model predicts the unknown ground truth image that can be generated with an infinite number of samples. Our method recursively estimates prediction errors introduced by linear predictions performed with different prediction windows, and selects an optimal prediction window minimizing the error for each linear model. Since each linear model predicts multiple pixels within its optimal prediction interval, we can construct our linear models only at a sparse set of pixels in the image screen. Predicting multiple pixels with a single linear model poses technical challenges, related to deriving error analysis for regions rather than pixels, and has not been addressed in the field. We address these technical challenges, and our method with robust error analysis leads to a drastically reduced reconstruction time even with higher rendering quality, compared to state-of-the-art adaptive methods. We have demonstrated that our method outperforms previous methods numerically and visually with high performance ray tracing kernels such as OptiX and Embree.
Average Stopping Set Weight Distributions of Redundant Random Ensembles

In this paper, redundant random ensembles are defined and their average stopping set (SS) weight distributions are analyzed. A redundant random ensemble consists of a set of binary matrices with linearly dependent rows. These linearly dependent rows significantly reduce the number of stopping sets (SS) of small size. Upper and lower bounds on the average SS weight distribution of the redundant random ensembles are proved based on a combinatorial argument. Asymptotic forms of these bounds reveal asymptotic behavior of the average SS weight distributions. From these bounds, a tradeoff between the number of redundant rows (corresponding to decoding complexity of belief propagation on binary erasure channel) and the average SS weight distribution (corresponding to decoding performance) can be derived.
Predicting Recessions with Leading Indicators: Model Averaging and Selection Over the Business Cycle

This paper evaluates the ability of several commonly followed economic indicators to predict business cycle turning points. As a baseline, forecasts from univariate models are combined by taking averages or by weighting forecasts with model-implied posterior probabilities. These combined forecasts are compared to those from a sophisticated model selection algorithm that allows for nonlinear model speci_cations. The preferred forecasting model is one that allows for nonlinear behavior across the business cycle and combines information from the yield curve with other indicators, especially at very short and very long horizons.
Time-Reversal Superresolution in Random Waveguides

In this paper we analyze a time-reversal experiment in a random waveguide. We use asymptotic analysis based on a separation of scales technique. We derive an infinite-dimensional coupled power equation that we analyze in the high-frequency regime. We use this approximation to compute the transverse profile of the refocused field and show that randomness enhances spatial refocusing beyond the diffraction limit; that is, the focal spot is smaller than the carrier wavelength over two. In this experiment the random heterogeneities, in the near-field region of the source, play a primary role.
The Impact of User Biases Toward a Virtual Human’s Skin Tone on Triage Errors Within a Virtual World for Emergency Management Training

Biases influence the decisions people make in everyday life, even if they are unaware of it. This behavior transfers into social interactions in virtual environments. These systems are becoming an increasingly common platform for training, so it is critical to understand how biases will impact them. The present study investigates the effect of the ethnicity bias on error behaviors within a virtual world for medical triage training. Two between subjects variables, participant skin tone (light, dark) and avatar skin tone (light, dark), and one within subjects variable, agent/patient skin tone (light, dark), were manipulated to create a 2 X 2 X 2 mixed design with four conditions. Effects on errors were observed on errors made while helping patient (agents). Participants made considerably more errors while triaging dark-skinned agents which increased the amount of time spent on them, in comparison to light-skinned agents. Within a virtual world for training, people apply general ethnic biases against dark-skinned individuals, which is important to consider when designing such systems because the biases could impact the effectiveness of the training.
Interfacing assessment using facial expression recognition

One of the most important issues in gaming is deciding about the employed interfacing technology. Gamepad has traditionally been a popular interfacing technology for the gaming industry, but, recently motion controlled interfacing has been used widely in this industry. This is exactly the purpose of this paper to study whether the motion controlled interface is a feasible alternative to the gamepad, when evaluated from a user experience point of view. To do so, a custom game has been developed and 25 test subjects have been asked to play the game using both types of interfaces. To evaluate the users experiences during the game, their hedonic and pragmatic quality are assessed using both subjective and objective evaluation methods in order to crossvalidate the obtained results. An application of computer vision, facial expression recognition, has been used as a non-obtrusive objective and hedonic measure. While, the score obtained by the user during the game has been used as a pragmatic quality measure. The use of facial expression recognition has, to the best of our knowledge, not been used before to assess the hedonic quality of interfaces for games. The thorough experimental results show that the user experience of the motion controlled interface is significantly better than the gamepad interface, both in terms of hedonic and pragmatic quality. The facial expression recognition system proved to be a useful non-obtrusive way to objectively evaluate the hedonic quality of the interfacing technologies.
Empirical Models for Dark Matter Halos. I. Nonparametric Construction of Density Profiles and Comparison with Parametric Models

We use techniques from nonparametric function estimation theory to extract the density profiles, and their derivatives, from a set of N-body dark matter halos. We consider halos generated from ΛCDM simulations of gravitational clustering, as well as isolated spherical collapses. The logarithmic density slopes γ ≡ d log ρ/d log r of the ΛCDM halos are found to vary as power laws in radius, reaching values of γ ≈ -1 at the innermost resolved radii, ∼10-2rvir. This behavior is significantly different from that of broken-power-law models like the Navarro-Frenk-White (NFW) profile but similar to that of models like de Vaucouleurs's. Accordingly, we compare the N-body density profiles with various parametric models to find which provide the best fit. We consider an NFW-like model with arbitrary inner slope; Dehnen & McLaughlin's anisotropic model; Einasto's model (identical in functional form to Sérsic's model but fitted to the space density); and the density model of Prugniel & Simien that was designed to match the deprojected form of Sérsic's R1/n law. Overall, the best-fitting model to the ΛCDM halos is Einasto's, although the Prugniel-Simien and Dehnen-McLaughlin models also perform well. With regard to the spherical-collapse halos, both the Prugniel-Simien and Einasto models describe the density profiles well, with an rms scatter some 4 times smaller than that obtained with either the NFW-like model or the three-parameter Dehnen-McLaughlin model. Finally, we confirm recent claims of a systematic variation in profile shape with halo mass.
On Generalized Schur Numbers

ABSTRACT Let represent the equation x1 + x2 + ⋅⋅⋅ + xt − 1 = xt. For k ≥ 1, 0 ≤ i ≤ k − 1, and ti ≥ 3, the generalized Schur number S(k; t0, t1, …, tk − 1) is the least positive integer m such that for every k-coloring of {1, 2, …, m}, there exists an i ∈ {0, 1, …, k − 1} such that there exists a solution to that is monochromatic in color i. In this article, we report 26 previously unknown values of S(k; t0, t1, …, tk − 1) and conjecture that for 4 ≤ t0 ≤ t1 ≤ t2, S(3; t0, t1, t2) = t2t1t0 − t2t1 − t2 − 1.
The effects of the 1996–2012 summer heat events on human mortality in Slovakia

Abstract The impacts of summer heat events on the mortality of the Slovak population, both in total and for selected population sub-groups, are the foci of this study. This research is the first of its kind, focusing on a given population, and therefore one priority was to create a knowledge base for the issue and to basically evaluate existing conditions for the heat-mortality relationship in Slovakia. This article also aims to fill a void in current research on these issues in Europe. In addition to overall effects, we focused individually on the major historical heat events which occurred in the summers of 2007, 2010 and 2012. During the heat events, a non-negligible negative response in mortality was recorded and fatal effects were more pronounced during particularly strong heat events and periods which lasted for two or more days. In general, females and the elderly were the most sensitive groups in the population and mortality was characterized by several specific effects in individual population groups. The most extreme heat periods were commonly followed by a deficit in mortality, corresponding to a short-term mortality displacement, the pattern of which varied in specific cases. In general, displaced mortality appeared to compensate for a large part of heat-induced excess deaths.