Miracle-dz/UniFAR-FTUs huggingface dataset:
The Incremental Predictive Information Associated with Using Theoretical New Keynesian DSGE Models vs. Simple Linear Econometric Models

In this paper we construct output gap and inflation predictions using a variety of dynamic stochastic general equilibrium (DSGE) sticky price models. Predictive density accuracy tests related to the test discussed in Corradi and Swanson ["Journal of Econometrics" (2005a), forthcoming] as well as predictive accuracy tests due to Diebold and Mariano ["Journal of Business and Economic Statistics" (1995), Vol. 13, pp. 253-263]; and West ["Econometrica" (1996), Vol. 64, pp. 1067-1084] are used to compare the alternative models. A number of simple time-series prediction models (such as autoregressive and vector autoregressive (VAR) models) are additionally used as strawman models. Given that DSGE model restrictions are routinely nested within VAR models, the addition of our strawman models allows us to indirectly assess the usefulness of imposing theoretical restrictions implied by DSGE models on unrestricted econometric models. With respect to predictive density evaluation, our results suggest that the standard sticky price model discussed in Calvo ["Journal of Monetary Economics" (1983), Vol. XII, pp. 383-398] is not outperformed by the same model augmented either with information or indexation, when used to predict the output gap. On the other hand, there are clear gains to using the more recent models when predicting inflation. Results based on mean square forecast error analysis are less clear-cut, although the standard sticky price model fares best at our longest forecast horizon of 3 years, it performs relatively poorly at shorter horizons. When the strawman time-series models are added to the picture, we find that the DSGE models still fare very well, often outperforming our forecast competitions, suggesting that theoretical macroeconomic restrictions yield useful additional information for forming macroeconomic forecasts. Copyright 2005 Blackwell Publishing Ltd.
Proximate determinants of bite force in Anolis lizards

Performance measures associated with the vertebrate jaw system may provide important insights into vertebrate ecology and evolution because of their importance in many ecologically relevant tasks. Previous studies have shown that in many taxa, evolution toward higher bite force has gone hand in hand with the evolution of larger body size. However, independent of differences in overall body size, bite force may vary depending on head size and shape as well. Moreover, the underlying musculature may also drive variation in bite force. Here, we investigate the proximate determinants of bite force in lizards of the genus Anolis. We dissected the jaw muscles and quantified muscle mass, fibre length, and cross‐sectional area. Data were analysed for both sexes independently given the sexual dimorphism detected in the dataset. Our results show that the traits that explain bite force are similar in both males and females with overall body size and muscle mass being the principal determinants. Among the different muscles examined, the adductor externus and the pseudotemporalis groups were the best determinants of bite force. However, models run for males predicted the variation in bite force better than models for females, suggesting that selection on morphology improving bite force may be stronger in males.
Morphing Planar Graph Drawings with a Polynomial Number of Steps

In 1944, Cairns proved the following theorem: given any two straight-line planar drawings of a triangulation with the same outer face, there exists a morph (i.e., a continuous transformation) between the two drawings so that the drawing remains straight-line planar at all times. Cairns's original proof required exponentially many morphing steps. We prove that there is a morph that consists of O(n2) steps, where each step is a linear morph that moves each vertex at constant speed along a straight line. Using a known result on compatible triangulations this implies that for a general planar graph G and any two straight-line planar drawings of G with the same embedding, there is a morph between the two drawings that preserves straight-line planarity and consists of O(n4) steps.
Epidemiological investigation of a human leptospirosis case reported in a suburban area near Marseille

Leptospirosis has been re-emerging in both developed and developing countries, including in Europe, where the phenomenon has notably been associated with urban transmission. In this work, we describe an epidemiological investigation that demonstrated a case of human infection due to peri-urban transmission of Leptospira interrogans serovar icterohaemorrhagiae in southeastern France.
A disorder induced field effect transistor in bilayer and trilayer graphene

We propose using disorder to produce a field effect transistor (FET) in biased bilayer and trilayer graphene. Modulation of the bias voltage can produce large variations in the conductance when the effects of disorder are confined to only one of the graphene layers. This effect is based on the ability of the bias voltage to select which of the graphene layers carries current, and is not tied to the presence of a gap in the density of states. In particular, we demonstrate this effect in models of gapless ABA-stacked trilayer graphene, gapped ABC-stacked trilayer graphene and gapped bilayer graphene.
The Economic Impact of Environmental Regulation

Of course environmental deregulation will not be cost-free. Steady progress toward cleaner air, water, and land will be slowed significantly, if not reversed. While this may be of small concern in still pristine states such as Wyoming, the implications for public health, ecology, and the quality of life in states such as New Jersey are more dire. Protection and preservation of rapidly vanishing wildlife, plants, habitats, and ecosystems will be weakened nationwide. Undoubtedly we will lose parts of America’s natural heritage that might otherwise have endured. Nevertheless the economic gains forthcoming from environmental deregulation might well be worth the price.
Promoter Attenuation in Gene Therapy: Interferon-γ and Tumor Necrosis Factor-α Inhibit Transgene Expression

ABSTRACT One of the major limitations to current gene therapy is the low-level and transient vector gene expression due to poorly defined mechanisms, possibly including promoter attenuation or extinction. Because the application of gene therapy vectors in vivo induces cytokine production through specific or nonspecific immune responses, we hypothesized that cytokine-mediated signals may alter vector gene expression. Our data indicate that the cytokines interferon-γ (IFN-γ) and tumor necrosis factor-α (TNF-α) inhibit transgene expression from certain widely used viral promoters/enhancers (cytomegalovirus, Rous sarcoma virus, simian virus 40, Moloney murine leukemia virus long terminal repeat) delivered by adenoviral, retroviral or plasmid vectors in vitro. A constitutive cellular promoter (β-actin) is less sensitive to these cytokine effects. Inhibition is at the mRNA level and cytokines do not cause vector DNA degradation, inhibit total cellular protein synthesis, or kill infected/transfected cells. Admin.
Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum - Part 1: experiments and large-scale features

Abstract. A set of coupled ocean-atmosphere simulations using state of the art climate models is now available for the Last Glacial Maximum and the Mid-Holocene through the second phase of the Paleoclimate Modeling Intercomparison Project (PMIP2). This study presents the large-scale features of the simulated climates and compares the new model results to those of the atmospheric models from the first phase of the PMIP, for which sea surface temperature was prescribed or computed using simple slab ocean formulations. We consider the large-scale features of the climate change, pointing out some of the major differences between the different sets of experiments. We show in particular that systematic differences between PMIP1 and PMIP2 simulations are due to the interactive ocean, such as the amplification of the African monsoon at the Mid-Holocene or the change in precipitation in mid-latitudes at the LGM. Also the PMIP2 simulations are in general in better agreement with data than PMIP1 simulations.
DIETARY SURVEYS AND NUTRITIONAL EPIDEMIOLOGY The Dutch Healthy Diet index as assessed by 24 h recalls and FFQ: associations with biomarkers from a cross-sectional study

The Dutch Healthy Diet index (DHD-index) was developed using data from two 24 h recalls (24hR) and appeared useful to evaluate diet quality in Dutch adults. As many epidemiologic studies use FFQ, we now estimated the DHD-index score using FFQ data. We compared whether this score showed similar associations with participants ’ characteristics, micronutrient intakes, and biomarkers of intake and metabolism compared with the DHD-index using 24hR data. Data of 121 Dutch participants of the European Food Consumption Validation study were used. Dietary intake was assessed by two 24hR and a 180-item FFQ. Biomarkers measured were serum total cholesterol and carotenoids, EPA + DHA in plasma phospholipids and 24 h urinary Na. A correlation of 0 · 48 (95 % CI 0 · 33, 0 · 61) was observed between the DHD-index score based on 24hR data and on FFQ data. Classi ﬁ cation of participants into the same tertiles of the DHD-index was achieved for 57 %. Women showed higher DHD-index scores. Energy intake was inversely associated with both DHD-index scores. Furthermore, age and intakes of folate, Fe, Mg, K, vitamin B 6 and vitamin C were positively associated with both DHD-index scores. DHD-index scores showed acceptable correlations with the four combined biomarkers taking energy intake into account ( r 24hR 0.55; r FFQ 0.51). In conclusion, the DHD-index score based on FFQ data shows similar associations with participants ’ characteristics, energy intake, micronutrient intake and biomarkers compared with the score based on 24hR data. Furthermore, ranking of participants was acceptable for both methods. FFQ data may therefore be used to assess diet quality using the DHD-index in Dutch populations.
ICA-based segmentation of the brain on perfusion data

An Independent Component Analysis (ICA) based segmentation technique is presented allowing the quantitative assessment of cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT) from dynamic susceptibility contrast magnetic resonance (MR) images of the brain. Tissue types such as gray matter (GM), white matter (WM), and pathology appear as different ICA components as a result of their distinct temporal response to the first passage of contrast agent through the brain. The average CBV, CBF, and MTT values calculated for each component/tissue type could help evaluate the evolution of pathology and provide the opportunity for intersubject comparisons.
Darwinian Evolution in Parallel Universes

The genetic algorithm, also known as the evolutionary algorithm, is a useful tool for combinatorial optimization, but a successful implementation of the algorithm requires a great deal of expertise, especially in terms of the ability to select the proper tuning parameters, a delicate and difficult issue faced by most stochastic search algorithms. In this paper, we present a simple but powerful technique of running the genetic algorithm in parallel and averaging the solutions. We present theoretical explanations as well as empirical illustrations using the variable selection problem as an example.
Depression, anxiety and obsessive-compulsive symptoms and quality of life in children with attention-deficit hyperactivity disorder (ADHD) during three-month methylphenidate treatment

The current study was designed to investigate the changes that occur in depression, anxiety, obsessive—compulsive symptoms and health-related quality of life during methylphenidate (MPH) treatment in children with attention-deficit hyperactivity disorder (ADHD). Forty-five treatment naive children with ADHD, aged 8—14, were assessed based on self, parent and teacher reports at the baseline and at the end of the first and third month of MPH treatment regarding changes in inattention, hyperactivity, impulsivity, depression, anxiety and obsessive—compulsive symptoms. Changes in the quality of life were also noted. Repeated measures of analysis of variance (ANOVA) tests with Bonferroni corrections were conducted in order to evaluate the data. Symptoms of inattention, hyperactivity and impulsivity were significantly reduced (p < 0.017) following a three-month MPH treatment. There were significant decreases in depression (p = 0.004), trait anxiety (p = 0.000) and checking compulsion symptom scores (p = 0.001). Moreover, parents reported significant improvements in psychosocial (p = 0.001) and total scores (p = 0.009) of quality of life, despite no change in physical health scores (p > 0.05). Children’s ratings of quality of life measures showed no significant changes in physical health and psychosocial scores (p > 0.05), while total scores significantly improved (p = 0.001) after the treatment. Over a three-month MPH treatment, depression, trait anxiety and checking compulsion symptoms decreased and quality of life seemed to improve along with those of inattention, hyperactivity and impulsivity.
Frequent SMILES

Predictive graph mining approaches in chemical databases are extremely popular and effective. Most of these approaches first extract frequent sub-graphs and then use them as features to build predictive models. In the work presented here, the approach taken is similar. However, instead of frequent sub-graphs, frequent trees, based on SMILES strings are derived. For this, the SMILES strings of chemical compounds are decomposed into fragment trees, which in turn are mined for interesting sub-trees. These tree based patterns are then used as features by a classifier to build predictive models. The approach is experimentally evaluated on a real world chemical data set.
One-loop supergravity amplitudes from MHV diagrams

We discuss the calculation of one-loop amplitudes in supergravity using MHV diagrams. In this approach, one-loop amplitudes are expressed as sums of MHV diagrams, which incorporate large numbers of Feynman diagrams. In contrast to MHV amplitudes of gluons in Yang–Mills, tree-level MHV amplitudes of gravitons are not holomorphic in the spinor variables. In order to extend these amplitudes off shell, and use them as vertices to build loops, we introduce certain shifts for the spinor variables associated with the loop momenta. Using this off-shell prescription, we rederive in a compact way the four- and five-point MHV amplitudes of gravitons at one loop, in complete agreement with known results. We also discuss the case of one-loop MHV amplitudes with an arbitrary number of gravitons.
An Evolutionary Approach towards Clustering Airborne Laser Scanning Data

In land surveying, the generation of maps was greatly simplified with the introduction of orthophotos and at a later stage with airborne LiDAR laser scanning systems. While the original purpose of LiDAR systems was to determine the altitude of ground elevations, newer full wave systems provide additional information that can be used on classifying the type of ground cover and the generation of maps. The LiDAR resulting point clouds are huge, multidimensional data sets that need to be grouped in classes of ground cover. We propose a genetic algorithm that aids in classifying these data sets and thus make them usable for map generation. A key feature are tailor-made genetic operators and fitness functions for the subject. The algorithm is compared to a traditional k-means clustering.
Geospatial Patterns in Human Papillomavirus Vaccination Uptake: Evidence from Uninsured and Publicly Insured Children in North Carolina

Background: Human papillomavirus (HPV) vaccination coverage is far below the national objective set by Healthy People 2020. This paper explores spatial patterns in HPV vaccination uptake. Methods: Secondary data for publicly funded HPV vaccinations among age-eligible children from 2008 through 2013 from the North Carolina Immunization Registry (NCIR) were used in 2014 in an ecological analysis at the ZIP code tabulation area (ZCTA) level. We tested for spatial autocorrelation in unadjusted HPV vaccination rates using choropleth maps and Moran's I. We estimated nonspatial and spatial negative binomial models with spatially correlated random effects adjusted for demographic, economic, and healthcare variables drawn from the 2010 U.S. Census Bureau, 2008–2012 American Community Survey, 2010 ZIP Business Patterns, and the 2012–2013 Area Resource File. Results: The NCIR revealed areas of especially low rates in publicly funded HPV vaccinations among uninsured and means-tested, publicly insured children. For boys, but not girls, ZCTAs tended to have HPV vaccination rates that were similar to their neighbors. This result was partially explained by included ZCTA characteristics, but not wholly. Conclusions: To the extent that the geospatial clustering of vaccination rates is due to causal influences from one ZCTA to another (e.g., through information networks), targeting interventions to increase HPV vaccination in one area could also lead to increases in neighboring areas. Impact: Spatial targeting of HPV vaccination, especially in clusters of low vaccination areas, could be an effective strategy to reduce the spread of HPV and related cancers. Cancer Epidemiol Biomarkers Prev; 24(3); 595–602. ©2015 AACR.
A New Method of Modeling Magnetic Saturation in Electrical Machines

Performance of any electrical machine is greatly influenced by the saturation in its ferromagnetic core. Significant reductions in the values of the magnetizing reactances in both direct and quadrature axes from their corresponding unsaturated values have been observed as a result of nonlinearities introduced by saturation. Thus, in the modeling of electrical machines, proper representation of saturation in both direct and quadrature axes is of great importance for an accurate performance analysis. In this paper, a new method of modelling magnetic saturation in electrical machines has been proposed. A single equation, based on the measured parameters, has been used in this model to fit the saturation characteristics. The proposed method has been applied to model both d- and q-axis saturation characteristics of electrical machines of varying types and designs
Amphetamine and Dopamine-Induced Immediate Early Gene Expression in Striatal Neurons Depends on Postsynaptic NMDA Receptors and Calcium

Amphetamine and cocaine induce the expression of both immediate early genes (IEGs) and neuropeptide genes in rat striatum. Despite the demonstrated dependence of these effects on D1dopamine receptors, which activate the cyclic AMP pathway, there are several reports that amphetamine and cocaine-induced IEG expression can be inhibited in striatum in vivo by NMDA receptor antagonists. We find that in vivo, the NMDA receptor antagonist MK-801 inhibits amphetamine induction of c-fosacutely and also prevents downregulation of IEG expression with chronic amphetamine administration. Such observations raise the question of whether dopamine/glutamate interactions occur at the level of corticostriatal and mesostriatal circuitry or within striatal neurons. Therefore, we studied dissociated striatal cultures in which midbrain and cortical presynaptic inputs are removed. In these cultures, we find that dopamine- or forskolin-mediated IEG induction requires Ca2+ entry via NMDA receptors but not via L-type Ca2+ channels. Moreover, blockade of NMDA receptors diminishes the ability of dopamine to induce phosphorylation of the cyclic AMP responsive element binding protein CREB. Although these results do not rule out a role for circuit-level dopamine/glutamate interactions, they demonstrate a requirement at the cellular level for interactions between the cyclic AMP and NMDA receptor pathways in dopamine-regulated gene expression in striatal neurons.
Tropes in the Rhetoric of Gun Rights: A Pragma-Dialectic Analysis

This essay offers a pragma-dialectic analysis of recurring arguments proffered in response to gun control legislation. While these arguments do not appear to be persuasive enough to win many new adherents for the gun lobby, their continual circulation in the public sphere and the lack of legislative progress in any direction invites inquiry. Our analysis suggests that these prominent arguments are deeply fallacious—violating several of the implicit norms of rational discourse that structure public arguments. We conclude that such arguments short-circuit rational public debate and forestall any real resolution of public concerns about gun violence. While stalemate benefits some interlocutors, we argue that the public (and even the gun lobby) stands to benefit from resolution. We conclude by suggesting several interventions to reinvigorate public debate and nominating tougher issues in this important controversy.
Ju n 20 09 Supersymmetry , Localization and Quantum Entropy Function

AdS2/CFT1 correspondence leads to a prescription for computing the degeneracy of black hole states in terms of path integral over string fields living on the near horizon geometry of the black hole. In this paper we make use of the enhanced supersymmetries of the near horizon geometry and localization techniques to argue that the path integral receives contribution only from a special class of string field configurations which are invariant under a subgroup of the supersymmetry transformations. We identify saddle points which are invariant under this subgroup. We also use our analysis to show that the integration over infinite number of zero modes generated by the asymptotic symmetries of AdS2 generate a finite contribution to the path integral.
Probabilistic Part Of Speech Tagging for Bahasa Indonesia

In this paper we report our work in developing Part of Speech Tagging for Bahasa Indonesia using probabilistic approaches. We use Condtional Random Fields (CRF) and Maximum Entropy methods in assigning the tag to a word. We use two tagsets containing 37 and 25 part-of-speech tags for Bahasa Indonesia. In this work we compared both methods using using two different corpora. The results of the experiments show that the Maximum Entropy method gives the best result.
Modeling browsing behavior for click analysis in sponsored search

Clickthrough rate provides a fundamental measure of advertising quality, which is widely used in ad selection strategies. However, ads placed in contexts where they are rarely viewed, or where users are unlikely to be interested in commercial results, may receive few clicks regardless of their quality. In this paper, we gain insight into user browsing and click behavior for the purpose of click analysis in sponsored search domain. The list of ads displayed on a page, the user's initial motivation to browse this list, and the persistence of the user are among the contextual factors considered in this paper. We propose a probabilistic model for user's browsing and click behavior using these contextual factors. To evaluate the performance of the model, we compare it with state-of-the-art methods. The experimental results confirm that these contextual factors can better reflect user browsing and click behavior in sponsored search.