Miracle-dz/UniFAR-FTUs huggingface dataset:
States' support of higher education: A theoretical and empirical analysis

This dissertation uses public finance theory and econometrics to examine the variation of expenditures on public higher education among states. The basic theory of public goods and externalities combined with comparative static analysis provides the theoretical framework to examine the effect of possible explanatory variables on optimal subsidy levels for public higher education. Two theoretical models are developed, a one sector model of the higher education market that treats private education as independent of the public market, and a two sector model that recognizes the interdependence of the public and private markets for higher education. Cross-sectional regression techniques are then used to determine the relative importance of differences in the explanatory variables on the optimal subsidy levels and to test the usefulness of separating the two higher education markets. One of the most significant findings is that states react to the vested interest they have in educating their citizens. Variables that influence future state government income are consistently significant in determining the optimal per-student public subsidy. This supports the argument that governments' behavior is affected by their equity interest in the educational investment of their citizens. Another significant finding is that state support of private higher education appears to decrease allocations to public higher education.
Recognition and classification of P300s in EEG signals by means of feature extraction using wavelet decomposition

In the last twenty years the understanding of the brain function and the advent of powerful low-cost computer equipment allowed the birth and the development of the BCI (Brain-Computer Interface), a device that interprets brain activity to issue commands. P300 is a positive peak at about 300 ms from a stimulus, and has been used as a base for a BCI in many studies. The aim of this research consists in recognizing and classifying P300 signals by using wavelet transforms. This study analyzes both the kind of wavelets and which coefficients are more suited for a 100% correct decisions using as few repetitions of stimuli as possible. The classifier performs a quadratic discriminant analysis. The method is tested on the “BCI Competition 2003” data set IIb with excellent results.
Historical superprocess limits for population models with past dependence and competition

We consider a population structured in trait. When a birth occurs, the trait of the parent is hereditarily transmitted to the offspring unless a mutation occurs. We associate with each individual its lineage consisting of all the traits of his ancestors. The evolution of the population results from the aging, births and deaths of individuals, with a dynamics that may depend on the past history of the lineage and that allows interactions between individuals. We introduce the stochastic process that describes the system and consider its diffusion limit under the assumptions of large populations, individuals of small masses and allometric demographies.
Visibility Equalizer Cutaway Visualization of Mesoscopic Biological Models

In scientific illustrations and visualization, cutaway views are often employed as an effective technique for occlusion management in densely packed scenes. We propose a novel method for authoring cutaway illustrations of mesoscopic biological models. In contrast to the existing cutaway algorithms, we take advantage of the specific nature of the biological models. These models consist of thousands of instances with a comparably smaller number of different types. Our method constitutes a two stage process. In the first step, clipping objects are placed in the scene, creating a cutaway visualization of the model. During this process, a hierarchical list of stacked bars inform the user about the instance visibility distribution of each individual molecular type in the scene. In the second step, the visibility of each molecular type is fine‐tuned through these bars, which at this point act as interactive visibility equalizers. An evaluation of our technique with domain experts confirmed that our equalizer‐based approach for visibility specification is valuable and effective for both, scientific and educational purposes.
Policy without politicians : bureaucratic influence in comparative perspective

Have bureaucrats taken over the decision making role of politicians? This book offers a direct assessment of the role of bureaucrats in policy making by analysing how they shape policy in making decrees - laws that generally do not pass through full legislative scrutiny. These are often described as "secondary legislation" and are known by a variety of names (including decrets, arretes, administrative regulations, Verordnungen, statutory instruments). Such decrees offer an important vantage point for understanding bureaucratic power not only because they account for a large proportion of policy making activity within the executive, but also because they are made largely away from the glare of publicity. If bureaucrats have strong policy making powers and use them in a way that minimises political involvement in policy making, we would expect to find these powers especially evident in this "everyday" decision making. The book is based on research examining 52 decrees produced between 2005 and 2008 in six jurisdictions: France, the UK, Germany, Sweden, the United States and the European Union. The comparative perspective allows one to see how far different patterns of bureaucratic involvement in policy making are characteristic of particular political systems and how far they are a general feature of modern bureaucracies. The book asks three main questions about how these decrees are produced: when do politicians become involved in making them? What happens when politicians become involved? And what happens when they are not involved? The answers to these questions are provided by examination of primary source material as well as interviews with over 90 officials.
A Monthly Double-blind Peer Reviewed Refereed Open Access International E-journal -included in the International Serial Directories Export -led Growth in India: an Empirical Investigation Ijmt __________________________________________________________ a Monthly Double-blind Peer Reviewed Refereed Op

The present study attempts to test the mechanisms of Export-Led Growth in India by taking a time-series data from 1980-81 to 2008-09. It applies Ordinary Least square (OLS) method to investigate the relationship between The results of the stu dy supports the Export-Led growth Hypothesis (ELGH) in India.
DBTG: Demand-Driven Backtracking Test Generation

Test generation techniques are still weak, especially to large or complex programs. This paper presents a new test generation method, which can automatically generate inputs triggering bugs with greatly mitigating the path explosion problem. The method performs intraprocedural analysis to find potential bugs using a combined symbolic and concrete execution with simplifying callee functions; then backtracks from the bug statement to program entry to find interprocedural paths with pruning infeasible paths in due course; finally expands callee functions of these paths to prune infeasible paths again. Demand-driven means that as few paths as possible are explored in order to find feasible paths triggering bugs. We have implemented a tool based on Phoenix framework and Z3 solver. To the best of our knowledge, it is the first security analysis tool working on intermediate representation between source and binary using a combined symbolic and concrete execution. Preliminary experiments on real code of nbsmtp SMTP client are promising.
Hybrid MPI/OpenMP Strategy for Biological Multiple Sequence Alignment with DIALIGN-TX in Heterogeneous Multicore Clusters

Multiple Sequence Alignment (MSA) is a fundamental problem in Bioinformatics that aims to align more than two biological sequences in order to emphasize similarity regions. This problem is known to be NP-Complete, so heuristic methods are used to solve it. DIALIGN-TX is an iterative heuristic method for MSA that is based on dynamic programming and generates alignments by concatenating ungapped regions with high similarity. This paper proposes an MPI/OpenMP master/slave parallel strategy to run DIALIGN-TX in heterogeneous multicore clusters, with multiple allocation policies. The results obtained in a 28-core heterogeneous cluster with real sequence sets show that the execution time can be drastically reduced. Also, we show that an appropriate choice of the allocation policy and the master node has great impact on the overall system performance.
Structural Differences among Hemagglutinins of Influenza A Virus Subtypes Are Reflected in Their Antigenic Architecture: Analysis of H9 Escape Mutants

ABSTRACT We used a panel of monoclonal antibodies to H9 hemagglutinin to select 18 escape mutants of mouse-adapted influenza A/Swine/Hong Kong/9/98 (H9N2) virus. Cross-reactions of the mutants with the antibodies and the sequencing of hemagglutinin genes revealed two minimally overlapping epitopes. We mapped the amino acid changes to two areas of the recently reported three-dimensional structure of A/Swine/Hong Kong/9/98 hemagglutinin. The grouping of the antigenically relevant amino acid positions in H9 hemagglutinin differs from the pattern observed in H3 and H5 hemagglutinins. Several positions in site B of H3 hemagglutinin are distributed in two sites of H9 hemagglutinin. Unlike any subtype analyzed so far, H9 hemagglutinin does not contain an antigenic site corresponding to site A in H3 hemagglutinin. Positions 145 and 193 (H3 numbering), which in H3 hemagglutinin belong to sites A and B, respectively, are within one site in H9 hemagglutinin. This finding is consistent with the peculiarity of the three-dimensional structure of the H9 molecule, that is, the absence from H9 hemagglutinin of the lateral loop that forms site A in H3 and the equivalent site in H5 hemagglutinins. The escape mutants analyzed displayed phenotypic variations, including decreased virulence for mice and changes in affinity for sialyl substrates. Our results demonstrate a correlation between intersubtype differences in three-dimensional structure and variations among subtypes in the distribution of antigenic areas. Our findings also suggest that covariation and pleiotropic effects of antibody-selected mutations may be important in the evolution of H9 influenza virus, a possible causative agent of a future pandemic.
The New Palgrave Dictionary of Economics Online extreme poverty

Households living in extreme poverty face deprivations that cost millions of lives annually. Ending extreme poverty requires an understanding of poverty traps, including the effects of adverse biophysical and geographical factors, a lack of resources required for the investments needed to escape poverty, and poor governance. Policies must focus both on promoting market-oriented economic growth and on directly addressing the needs of the poor. Foreign aid will be required to finance interventions that poor countries cannot finance themselves, and aid to well-governed poor countries should be increased, consistent with the rich-country promise of 0.7 per cent of GNP as official development assistance.
An Expert Consensus Statement on Use of Adrenal Vein Sampling for the Subtyping of Primary Aldosteronism

Adrenal venous sampling is recommended by current guidelines to identify surgically curable causes of hyperaldosteronism but remains markedly underused. Key factors contributing to the poor use of adrenal venous sampling include the prevailing perceptions that it is a technically challenging procedure, difficult to interpret, and can be complicated by adrenal vein rupture. In addition, the lack of uniformly accepted standards for the performance of adrenal venous sampling contributes to its limited use. Hence, an international panel of experts working at major referral centers was assembled to provide updated advice on how to perform and interpret adrenal venous sampling. To this end, they were asked to use the PICO (Patient or Problem, Intervention, Control or comparison, Outcome) strategy to gather relevant information from the literature and to rely on their own experience. The level of evidence/recommendation was provided according to American Heart Association gradings whenever possible. A consensus was reached on several key issues, including the selection and preparation of the patients for adrenal venous sampling, the procedure for its optimal performance, and the interpretation of its results for diagnostic purposes even in the most challenging cases.
Uncertainty Driven Multi-scale Energy Minimization

This paper proposes a new multi-scale energy minimization algorithm which can be used to efficiently solve large scale labelling problems in computer vision. The basic modus operandi of any multi-scale method involves the construction of a smaller problem which can be solved efficiently. The solution of this problem is used to obtain a partial labelling of the original energy function, which in turn allows us to minimize it by solving its (much smaller) projection. We propose the use of new techniques for both the construction of the smaller problem, and the extraction of a partial solution. We demonstrate our method on the problem of interactive image segmentation. Traditional multi-scale approaches for segmentation extract a partial solution using an image band around the boundaries of the object segmentation obtained by minimizing the smaller problem. This strategy fails on objects with fine structures and complex topologies. In contrast, our novel approach uses a min-marginal based uncertainty measure which allows us to handle such objects. Experiments show that our techniques result in solutions with low pixel labelling error. Furthermore, they take the same or less amount of computation compared to traditional multi-scale techniques.
A comprehensive survey on shadow detection techniques

Shadow cause some unwanted change in computer vision and image analysis. Shadow leads to problems in extraction, segmentation of object and recognition due to the misclassification of shadow points as foreground or object points. So, the detection of shadow is of broad interest in computer vision. Due to the alteration in illumination of the background and similarity between appearance of the objects and background, accurate detection of shadow is difficult. Lots of researches have been done on shadow detection to address these challenges. For different environmental conditions many algorithms and techniques have been developed to detect shadow from the images. This paper aims to provide comprehensive survey of various shadow detection techniques and also includes comparative analysis of these techniques.
Exploring Resistance from a Rhetorical Perspective

Contemporary accounts of resistance at work have emphasized processes of identity construction and regulation (e.g. Alvesson and Willmott 2002). Case study examinations (e.g. Knights and McCabe 2000; Ezzamel et al. 2001) have been recently extended by detailed studies of the operation of discourse at the level of talk (e.g. Dick and Cassell 2002). This paper adds to these recent accounts by providing an analysis of arguments for and against a technological change project in a UK public sector organization. The objective is to demonstrate how such arguments are constructed to achieve particular interpretations of reality while resisting others (i.e. the use of persuasive rhetoric). In the examples analysed here, rhetorical strategies included: producing a range of identities for 'the resistant', IT support staff and others; disputing the 'realness' of people, things and processes (e.g. information, participation); producing and negotiating various boundaries (e.g. we/other, production worker/support staff); and drawing on local and broader cultural discourse. In this example, we also see how 'subjectivity', 'agency' and (political) 'structures' may serve as rhetorical resources. This paper argues that the focus on counter-argument (as resistance) demonstrates the disputative, politically oriented and dialogical nature of identity construction.
ESTIMATING SYSTEMATIC RISK: THE CHOICE OF RETURN INTERVAL AND ESTIMATION PERIOD

Capital budgeting is one of the most important strategic decisions that face financial managers. It is the process where the firm identifies, analyzes, and selects long-term projects. One popular technique to evaluate whether the project should be undertaken is the net present value method. A key ingredient of net present value is an accurately estimated weighted-average-cost-of-capital that is used to discount the future cash flows. The most difficult component of the weighted-average-cost-of-capital to calculate is the cost of equity. One approach to estimate the cost of equity is the Capital Asset Pricing Model approach where the financial manager estimates the firm’s beta. A time-series regression is often used to estimate the beta and requires the financial manager to select both a return interval and an estimation period. This study examines the return interval and estimation period the financial manager should select when estimating beta. The results show that the financial manager should select the daily return interval and an estimation period of three years or less.
Fusing Structured Light Consistency and Helmholtz Normals for 3D Reconstruction

In this paper, we propose a 3D reconstruction approach which combines a structured light based consistency measure with dense normal information obtained by exploiting the Helmholtz reciprocity principle. This combination compensates for the individual limitations of techniques providing normal information, which are mainly affected by low-frequency drift, and those providing positional information, which are often not well-suited to recover fine details. To obtain Helmholtz reciprocal samples, we employ a turntable-based setup. Due to the reciprocity, the structured light directly provides the occlusion information needed during the normal estimation for both the cameras and light sources. We perform the reconstruction by solving one global variational problem which integrates all available measurements simultaneously, over all cameras, light source positions and turntable rotations. For this, we employ an octree-based continuous min-cut framework in order to alleviate metrification errors while maintaining memory efficiency. We evaluate the performance of our algorithm both on synthetic and real-world data.
A KLD Based Method for Initial Set Selection in Active Learning

Speech recognition systems are usually trained using tremendous transcribed samples, and training data preparation is intensively time-consuming and costly. Aiming at achieving better performance of acoustic model with less transcribed samples, active learning is used in acoustic model training. This learning scheme firstly selects and transcribes a small initial training set, then iteratively selects the most informative samples corresponding to a certain criterion from the unlabeled samples, then annotates them and adds the newly transcribed samples to the training set to update the acoustic model. Concerning that the initial set influences the performance and convergence rate of active learning a lot, we proposed a method for initial set selection based on Kullback-Leibler Divergence (KLD). Our experiments show that active learning using initial set selected by our proposed method can achieve better performance.
AdVisual: a visual-based advertising system

In this work, we present a visual-based contextual advertising system, AdVisual. It is designed for content service providers to effectively select relevant ads for online videos. First, it will analyze each video and extract high level semantic visual information including specific objects, people, and significant scenes. Then ads highly related to the visual concepts are associated with the corresponding shots. As AdVisual is a user interaction system, it allows users to select favorite ads relevant to the video. By saliency detection, selected ads will be displayed as an overlay window embedded at the non-intrusive part of the shot.
Intra-Household Resource Allocation: Do Parents Reduce or Reinforce Child Cognitive Ability Gaps?

Do parents invest more or less in their high ability children? We provide new evidence on this question by comparing observed ability differences and observed investment differences between siblings in the NLSY. To overcome endogeneity issues we use sibling differences in handedness as an instrument for cognitive ability differences, since handedness is a strong determinant of cognitive ability. We find that parents invest more in high ability children, with a one standard deviation increase in child cognitive ability increasing parental investments by approximately one-third of a standard deviation. Consequently, differences in child cognitive ability are enhanced by differential parental investments. This finding has important implications for education policy.
Synchronization of fast (30-40 Hz) spontaneous oscillations in intrathalamic and thalamocortical networks

The synchronization of fast (mainly 30 to 40 Hz) oscillations in intrathalamic and thalamocortical (TC) networks of cat was studied under ketamine-xylazine anesthesia and in behaving animals by means of field potential, extra- and intracellular recordings from multiple sites in the thalamic reticular (RE) nucleus, dorsal (sensory, motor, and intralaminar) thalamic nuclei, and related neocortical areas. Far from being restricted to tonically activated behavioral states, the fast oscillations also appeared during resting sleep and deep anesthesia, when they occurred over the depolarizing component of the slow (<1 Hz) oscillation and were suppressed during the prolonged hyper- polarizations of RE, TC, and cortical neurons. The synchronization of fast rhythms among different thalamic foci was robust. Fast rhythmic cortical waves and subthreshold depolarizing potentials in TC neurons were highly coherent; however, the synchronization of the fast oscillation required recordings from reciprocally related neocortical and thalamic foci, as identified by monosynaptic responses in both directions. The short-range spatial confinement of coherent fast rhythms contrasted with the large-scale synchronization of low- frequency sleep rhythms. Transient fast rhythms, appearing over the depolarizing envelope of the slow sleep oscillation, became sustained when brain activation was elicited by stimulation of mesopontine cholinergic nuclei or during brain-active behavioral states in chronic experiments. These data demonstrate that fast rhythms are part of the background electrical activity of the brain and that desynchronization, used to designate brain-active states, is an erroneous term inasmuch as the fast oscillations are synchronized not only in intracortical but also in intrathalamic and TC networks.
Heterotic String Theory on Anti-de-Sitter Spaces

We suggest that compactifications on Anti-de-Sitter (AdS) spaces of type IIA, IIB, heterotic strings and eleven dimensional vacuua of M-theory are related by a combination of $T$ and strong/weak dualities. Maldacena conjecture relates then all these vacuua to a conformal theory on the boundaries. Furthermore acting with discrete groups on part of the internal spaces of these theories will lead to further dual theories with less or no supersymmetry.