Miracle-dz/UniFAR-FTUs huggingface dataset:
ELASTIC-WAVE INVERSE SCATTERING WITH ACTIVE AND PASSIVE SOURCE REFLECTION DATA

We develop a comprehensive theory and microlocal analysis of reverse-time imaging – also referred to as reverse-time migration or RTM – for the anisotropic elastic wave equation based on the single scattering approximation. We consider a configuration reminiscent of the seismic inverse scattering problem. In this configuration, we have an interior (point) body-force source which generates elastic waves, which scatter off discontinuities in the properties of earth’s materials (anisotropic stiffness, density), and are observed at receivers on the earth’s surface. The receivers detect all the components of displacement. We introduce (i) an anisotropic elastic-wave RTM inverse scattering transform, and for the case of mode conversions (ii) a microlocally equivalent formulation avoiding knowledge of the source via the introduction of so-called array receiver functions. These allow a seamless integration of passive source and active source approaches to inverse scattering.
AN OVERVIEW OF DATA MINING FOR COMBATING CRIME

Artificial Intelligence (AI) and Law has been a burgeoning domain since the 1980s, but it was not until the 2000s that models of reasoning about legal evidence started to feature prominently. With regard to data mining, it has been applied to legal databases, as well as to law enforcement. We survey forensic applications of data mining to fraud and otherwise to crime intelligence or investigation. Traditionally a field separate from AI and Law, the two are now coming together. Success has been achieved especially in unravelling networks and in detecting fraud.
Inference of structure in subdivided populations at low levels of genetic differentiation - the correlated allele frequencies model revisited

MOTIVATION This article considers the problem of estimating population genetic subdivision from multilocus genotype data. A model is considered to make use of genotypes and possibly of spatial coordinates of sampled individuals. A particular attention is paid to the case of low genetic differentiation with the help of a previously described Bayesian clustering model where allele frequencies are assumed to be a priori correlated. Under this model, various problems of inference are considered, in particular the common and difficult, but still unaddressed, situation where the number of populations is unknown. RESULTS A Markov chain Monte Carlo algorithm and a new post-processing scheme are proposed. It is shown that they significantly improve the accuracy of previously existing algorithms in terms of estimated number of populations and estimated population membership. This is illustrated numerically with data simulated from the prior-likelihood model used in inference and also with data simulated from a Wright-Fisher model. Improvements are also illustrated on a real dataset of eighty-eight wolverines (Gulo gulo) genotyped at 10 microsatellites loci. The interest of the solutions presented here are not specific to any clustering model and are hence relevant to many settings in populations genetics where weakly differentiated populations are assumed or sought. AVAILABILITY The improvements implemented will be made available in version 3.0. 0 of the R package Geneland. Informations on how to get and use the software are available from http://folk.uio. no/gillesg/Geneland.html. SUPPLEMENTARY INFORMATION http://folk.uio. no/gillesg/CFM/SuppMat.pdf.
Weighted Feature Gaussian Kernel SVM for Emotion Recognition

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.
Adorno, Habermas and the Search for a Rational Society

Introduction Chapter One: Society 1. State Capitalist or Late Capitalist Society? 2. Habermas on Late Capitalist Society 3. Preliminary Remarks on Domination 4. Concluding Reflections on Habermas' Concept of the Lifeworld Chapter Two: Reification 1. Damaged Life 2. Colonized Lifeworld 3. The Problem of Mediation 4. Reification and the Global Economy Chapter Three: Reason 1. The Evolution of Reason 2. The Rational Animal 3. Nature, Reason, and History 4. The Partiality for Reason Chapter Four: Critique 1. Ideology: End or Transformation? 2. The Critical Power of Critical Theory 3. Habermas Against Himself Chapter Five: Emancipation 1. Obstacles to Emancipation 2. Adorno, and the Idea of a Rational Society 3. Habermas, and the Idea of a Rational Society 4. The Utopian Gambit Conclusion
US Presidential Election 2012 Prediction using Census Corrected Twitter Model

Abstract US Presidential Election 2012 has been a very tight race between the two key candidates. There were intense battle between the two key candidates. The election reflects the sentiment of the electorate towards the achievements of the incumbent President Obama. The campaign lasted several months and the effects can be felt in the internet and twitter. The presidential debates injected new vigor in the challenger's campaign and successfully captured the electorate of several states posing a threat to the incumbent's position. Much of the sentiment in the election has been captured in the online discussions. In this paper, we will be using the original model described in Choy et. al. (2011) using twitter data to forecast the next US president. Introduction Social media has been widely used by politicians to increase the reach of their campaigns. The campaign of President Obama in 2008 demonstrated the power and reach of social media and how it can be used to change the political landscape. Social media platforms have been touted as the leading platform to engage voters. Political analysts (Stirland, 2008; Pasek, 2006; Xenos, 2007) attributed the success to the active and effective use of social media platforms to engage voters notably the younger generations usually ignored or given less importance (Pasek, 2006) by veteran politicians. The use of social media also helped to reach small population such as the Hispanics and activate support for the candidates. The poor management of social media platforms and absymal out reaches by McCain and Palin improved Obama's overall advantage in attracting voters (Stirland, 2008) and encouraging their turnout. Twitter has become a popular tool of choice for politicians to spread influence. Twitter was developed as a micro-blogging tool where all the status updates as well as the opinions written can be searched and extracted using the twitter search API (Twitter, 2011). Search capabilities allow almost real life time viewing of information posted online by various users. Political associations as well as various activitist groups have successfully used it to voice their opinions, political positions as well as gathering supports from the online audiences. Every campaign has an online presence and the research focus on the formulation of these successful online campaigns. Campaigners are on a constant lookout for new social media channels to garner supporters and drive voter shares. There are many analysts and skeptics who believe that twitter is not very useful (Pearanalytics, 2009; Gayo-Avello, 2012), others have lauded the immense potential of twitter (Skemp ,2009). There are three major objectives to be achieved using twitter information. The first aim is to assess the validity of the framework proposed in Choy et. al. (2011) to predict the new President. The second aim is to assess the methodology's power to calculate and predict state level electorate results. Finally, we will also like to evaluate the impact of twitter on the greater internet as a whole.
Educational Psychology: Learning, Instruction, Assessment

1. An Introduction to Good Thinking and Good Teaching. I. FOUNDATIONS OF THINKING. 2. Motivation. 3. Representation of Knowledge. 4. Strategies and Metacognitive Regulation of Strategies. 5. The Role of Knowledge in Thinking. II. THE CONSTRUCTION OF KNOWLEDGE. 6. Biological Factors Affecting Learning and Development. 7. Psychological Theories of Learning and Development. 8. Social Interactional Theories of Learning and Development. III. THE CLASSROOM CONTEXT. 9. Social Influences in the Classroom. 10. Schooling Practices. 11. Reading and Writing Instruction. 12. Mathematics and Science Instruction. IV. CHARACTERISTICS OF STUDENTS. 13. Traditional Perspectives on Intelligence and Academic Competence. 14. Alternative Assessments of Academic Competence. 15. Teacher-Designed Assessments: Traditional and Alternative. 16. Diversity of Learners.
New Technologies, New Identities, and the Growth of Mass Opposition in the Arab Spring

The recent revolutions known as the Arab Spring have been characterized as the products of social media. However, there is an alternative view that revolution takes place on the street or the battlefield and that the role of social media has been overstated. We argue that some new technologies can serve to facilitate rapid social change when they provide ways to overcome restrictions on the freedoms of expression and association. In doing so, communication technologies enable the formation of new social identities that can challenge existing social orders by promoting the growth of a social movement that is positioned as loyal to the nation and its people but opposed to the government. Our analyses focus on the role of social media in spreading video images of dissent and the links between this video material, satellite television, and mobile telephones in Tunisia and Egypt.
Impact of family language and testing language on reading performance in a bilingual educational context.

BACKGROUND When different languages co-exist in one area, or when one person speaks more than one language, the impact of language on psychological and educational assessment processes can be considerable. The aim of this work was to study the impact of testing language in a community with two official languages: Spanish and Basque. METHOD By taking the PISA 2009 Reading Comprehension Test as a basis for analysis, four linguistic groups were defined according to the language spoken at home and the test language. Psychometric equivalence between test forms and differences in results among the four language groups were analyzed. The comparison of competence means took into account the effects of the index of socioeconomic and cultural status (ISEC) and gender. RESULTS One reading unit with differential item functioning was detected. The reading competence means were considerably higher in the monolingual Spanish-Spanish group. No differences were found between the language groups based on family language when the test was conducted in Basque. CONCLUSIONS The study illustrates the importance of taking into account psychometric, linguistic and sociolinguistic factors in linguistically diverse assessment contexts.
Deep convolutional player modeling on log and level data

We present a novel approach to player modeling based on a convolutional neural net trained on game event logs. We test our approach and a hybrid extension over two distinct games, a clone of Super Mario Bros. and Gwario, a human computation version of Super Mario Bros. : The Lost Levels. We demonstrate high accuracy in predicting a variety of measures of player experience across these two games. Further we present evidence that our technique derives quality design knowledge and demonstrate the ability to build a more general model.
Healthcare Assessment Questions Non-invasive Ambient Sensors

In Ambient Assisted Living, care assessment instruments help to guarantee the quality of home-care treatments. Different standards and respective questionnaires are available. Because mostly the questions are individually filled out by the patients or their caregivers, this process is fault-sensitive. In this research, we propose an as automated as possible answering of most of the questions using cost-efficient non-invasive, ambient sensors. We define an approach to filter out and argue which questions of the Minimum Data Set for Home-Care (MDS-HC) of the comprehensive Resident Assessment Instrument for Home-Care (RAI-HC) can be automatically answered by such sensors. Therefore, we identify and definitely exclude the questions which cannot be answered by such sensors. Then, we map the remaining questions to possible sensors whose technology allows to answers these questions. The majority of these questions mapped to sensors can be found in published research literature. However, 22 percent of the questions are unacknowledged.
Using custom hardware and simulation to support computer systems teaching

Teaching computer systems, including computer architecture, assembly language programming and operating systems implementation, is a challenging occupation. At the University of Waikato we require all computer science and information systems students study this material at second year. The challenges of teaching difficult material to a wide range of students have driven us to find ways of making the material more accessible. The corner-stone of our strategy for delivering this material is the design and implementation of a custom CPU that meets the needs of teaching. In addition to the custom CPU we have developed several simulators that allow specific topics to be studied in detail. This paper describes our motivation for devloping a custom CPU and supporting tools. We present our CPU and the teaching board and describe the implementation of the CPU in an FPGA. The simulators that that have been developed to support the teaching of the course are then described. The paper concludes with a description of the current status of the project.
Foliar respiration acclimation to temperature and temperature variable Q10 alter ecosystem carbon balance

The response of respiration to temperature in plants can be considered at both short‐ and long‐term temporal scales. Short‐term temperature responses are not well described by a constant Q10 of respiration, and longer‐term responses often include acclimation. Despite this, many carbon balance models use a static Q10 of respiration to describe the short‐term temperature response and ignore temperature acclimation.
Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning

The cloud represents a computing paradigm where shared configurable resources are provided as a service over the Internet. Adding intra- or intercloud communication resources to the resource mix leads to a networked cloud computing environment. Following the cloud infrastructure as a Service paradigm and in order to create a flexible management framework, it is of paramount importance to address efficiently the resource mapping problem within this context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different administrative domains, in this paper a hierarchical framework is described. First, a novel request partitioning approach based on Iterated Local Search is introduced that facilitates the cost-efficient and online splitting of user requests among eligible cloud service providers (CPs) within a networked cloud environment. Following and capitalizing on the outcome of the request partitioning phase, the embedding phase&#x2014;where the actual mapping of requested virtual to physical resources is performed can be realized through the use of a distributed intracloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a thorough evaluation of the proposed overall framework on a simulated networked cloud environment is provided and critically compared against an exact request partitioning solution as well as another common intradomain virtual resource embedding solution.
Histone deacetylase inhibitor enhances 5-fluorouracil cytotoxicity by down-regulating thymidylate synthase in human cancer cells

Thymidylate synthase (TS) overexpression is a key determinant of 5-fluorouracil (5-FU) resistance in human cancer cells. TS is also acutely up-regulated with 5-FU treatment, and, thus, novel strategies targeting TS down-regulation seem to be promising in terms of modulating 5-FU resistance. Here, we report that histone deacetylase inhibitors can reverse 5-FU resistance by down-regulating TS. By using cDNA microarrays and validation experiments, we found that trichostatin A reduced the expression of both TS mRNA and TS protein. Cotreatment with trichostatin A and cycloheximide restored TS mRNA expression, suggesting that TS mRNA is repressed through new protein synthesis. On the other hand, TS protein expression was significantly reduced by lower doses of trichostatin A (50 nmol/L). Mechanistically, TS protein was found to interact with heat shock protein (Hsp) complex, and trichostatin A treatment induced chaperonic Hsp90 acetylation and subsequently enhanced Hsp70 binding to TS, which led to the proteasomal degradation of TS protein. Of note, combined treatment with low-dose trichostatin A and 5-FU enhanced 5-FU–mediated cytotoxicity in 5-FU–resistant cancer cells in accordance with TS protein down-regulation. We conclude that a combinatorial approach using histone deacetylase inhibitors may be useful at overcoming 5-FU resistance. [Mol Cancer Ther 2006;5(12):3085–95]
Connectivity calculation in mobile ad hoc networks: Realistic performance simulation

The subject of this paper is the accurate connectivity calculation in a realistic mobile ad hoc network taking into account two different mobility models and the shadowing effects. In mobile ad hoc networks mobility leads to changes in network's topology, while shadowing phenomena are the dominant propagation mechanism and have great impact on network's nodes coverage. Both affect dramatically networks connectivity. The random waypoint model and the random direction model have been employed for the simulation results while the impact of lognormal shadowing has been also considered for connectivity evaluation. It is shown that the increase of shadowing increases the network's connectivity and moreover the influence of the choice of the mobility model on network's connectivity for different operational parameters is studied. The sensitivity of connectivity on transmission power, nodes velocity, shadowing deviation and network's scalability is also investigated. Some useful conclusions about connectivity are finally drawn.
Road detection with thermal cameras through 3D information

Ground detection algorithms are important for locating the area where a vehicle can travel during autonomous navigation or for collision avoidance Advanced Driver Assistance Systems (ADAS). Although many algorithms rely on a single camera to detect the ground, they don't consider the possibility of combining transformation approaches with additional information that could be obtained from another camera mounted on the vehicle. In this paper, we propose an algorithm for ground detection that allows the use of disparity maps and the combination of infrared information to enhance road detection. To this end we propose an original approach based on a thermal stereo system to analyze the thermal features of the road that are then complemented by the depth information obtained from the disparity map. We tested the algorithm with a variety of complex scenarios and results showed that the 2D and 3D data enabled accurate detection of the road independent of the weather conditions.
Atmospheric Turbulence Measurements with the Palomar Testbed

Data from the Palomar Testbed Interferometer, with a baseline length of 110 m and an observing wavelength of 2.2 µm, were used to derive information on atmospheric turbulence on 64 nights in 1999. The measured two-aperture variance coherence times at 2.2 µm ranged from 25 msec to 415 msec (the lower value was set by instrumental limitations—the interferometer could not operate when the coherence time was lower than this). On all nights, the spectrum of the short time scale (< 600 msec) delay fluctuations had a shallower spectrum than the theoretical Kolmogorov value of 5/3. On most nights, the mean value of the power law slope was between 1.40 and 1.50. Such a sub-Kolmogorov slope will result in the seeing improving as the ≈ 0.4 power of wavelength, rather than the slower 0.2 power predicted by Kolmogorov theory. On four nights, the combination of delay and angle tracking measurements allowed a derivation of the (multiple) wind velocities of the turbulent layers, for a frozen-flow model. The derived wind velocities were all ≤ 4 m s −1 , except for a small 10 m s −1 component on one night. The combination of measured coherence time, turbulence spectral slope, and wind velocity for the turbulent layer(s) allowed a robust solution for the outer scale size (beyond which the fluctuations do not increase). On the four nights with angle tracking – 2 – data, the outer scale varied from 6 to 54 m, with most values in the 10–25 m range. Such small outer scale values cause some components of visibility and astrometric errors to average down rapidly.
An examination of humor and endorser effects on consumers' responses to direct‐to‐consumer advertising

Purpose – This study aims to examine how product involvement moderates the effects of emotional appeals namely humor and endorsers on consumers' responses to direct‐to‐consumer advertising (DTCA). Design/methodology/approach – This study employed a 2 (Humor: humor vs. non‐humor)×2 (Endorser: celebrity vs expert)×2 (Involvement: high vs low) factorial experimental design. Subjects were 420 allergy/asthma sufferers or non‐sufferers attending a large Southwestern US university as undergraduate and graduate students.Findings – Results confirm that low involvement consumers demonstrate more positive responses than high involvement consumers toward prescription drug ads with emotional appeals. Humor or a celebrity endorser enhances ad and brand attitudes, brand recall, and copy point recall of consumers without medical conditions. However, an expert endorser is found to be more effective in improving ad credibility. A three‐way interaction between humor, endorser, and involvement was evident indicating that the .