Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Density Forecasts and Value-at- Risk Estimates by Combining Densities

We investigate the added value of combining density forecasts for asset return prediction in a specific region of support. We develop a new technique that takes into account model uncertainty by assigning weights to individual predictive densities using a scoring rule based on the censored likelihood. We apply this approach in the context of recently developed univariate volatility models (including HEAVY and Realized GARCH models), using daily returns from the S&P 500, DJIA, FTSE and Nikkei stock market indexes from 2000 until 2013. The results show that combined density forecasts based on the censored likelihood scoring rule significantly outperform pooling based on the log scoring rule and individual density forecasts. The same result, albeit less strong, holds when compared to combined density forecasts based on equal weights. In addition, VaR estimates improve a t the short horizon, in particular when compared to estimates based on equal weights or to the VaR estimates of the individual models.
Genetically Determined Susceptibility to Tuberculosis in Mice Causally Involves Accelerated and Enhanced Recruitment of Granulocytes

ABSTRACT Classical twin studies and recent linkage analyses of African populations have revealed a potential involvement of host genetic factors in susceptibility or resistance to Mycobacterium tuberculosis infection. In order to identify the candidate genes involved and test their causal implication, we capitalized on the mouse model of tuberculosis, since inbred mouse strains also differ substantially in their susceptibility to infection. Two susceptible and two resistant mouse strains were aerogenically infected with 1,000 CFU of M. tuberculosis, and the regulation of gene expression was examined by Affymetrix GeneChip U74A array with total lung RNA 2 and 4 weeks postinfection. Four weeks after infection, 96 genes, many of which are involved in inflammatory cell recruitment and activation, were regulated in common. One hundred seven genes were differentially regulated in susceptible mouse strains, whereas 43 genes were differentially expressed only in resistant mice. Data mining revealed a bias towards the expression of genes involved in granulocyte pathophysiology in susceptible mice, such as an upregulation of those for the neutrophil chemoattractant LIX (CXCL5), interleukin 17 receptor, phosphoinositide kinase 3 delta, or gamma interferon-inducible protein 10. Following M. tuberculosis challenge in both airways or peritoneum, granulocytes were recruited significantly faster and at higher numbers in susceptible than in resistant mice. When granulocytes were efficiently depleted by either of two regimens at the onset of infection, only susceptible mice survived aerosol challenge with M. tuberculosis significantly longer than control mice. We conclude that initially enhanced recruitment of granulocytes contributes to susceptibility to tuberculosis.
Regularized and Adaptive Nonlinear Moving Horizon Estimation of Bottomhole Pressure During Oil Well Drilling

Abstract With the restrictions on online downhole measuring during petroleum drilling, mathematical reconstruction of the bottomhole pressure (BHP) is desired to improve control of the pressure profile throughout the well. With sufficient pressure management, increasingly tight pressure margins, that are imposed by the worsening accessibility of the remaining oil reservoirs, might be met. A regularized and adaptive Moving Horizon Estimation (MHE) approach is proposed to estimate the BHP. The observer comes with abilities to adapt to the degree of excitation via thresholded singular value decomposition, and means for filtering using an a priori estimate in the cost function. The employed observer model is nonlinear, as required by the process, and chosen to be third order to mitigate computational load. The algebraic BHP equation includes two unknown parameters and an unmeasured state. Accuracy of the model is enhanced by estimation of selected parameters. Testing on a data set from a North Sea well, conducted to investigate the suitability of the approach, has delivered promising results.
IL-25 augments type 2 immune responses by enhancing the expansion and functions of TSLP-DC–activated Th2 memory cells

Interleukin (IL) 25 (IL-17E), a distinct member of the IL-17 cytokine family, plays important roles in evoking T helper type 2 (Th2) cell–mediated inflammation that features the infiltrations of eosinophils and Th2 memory cells. However, the cellular sources, target cells, and underlying mechanisms remain elusive in humans. We demonstrate that human Th2 memory cells expressing distinctive levels of IL-25 receptor (R) are one of the responding cell types. IL-25 promotes cell expansion and Th2 cytokine production when Th2 central memory cells are stimulated with thymic stromal lymphopoietin (TSLP)–activated dendritic cells (DCs), homeostatic cytokines, or T cell receptor for antigen triggering. The enhanced functions of Th2 memory cells induced by IL-25 are associated with sustained expression of GATA-3, c-MAF, and JunB in an IL-4–independent manner. Although keratinocytes, mast cells, eosinophils, and basophils express IL-25 transcripts, activated eosinophils and basophils from normal and atopic subjects were found to secrete bioactive IL-25 protein, which augments the functions of Th2 memory cells. Elevated expression of IL-25 and IL-25R transcripts was observed in asthmatic lung tissues and atopic dermatitis skin lesions, linking their possible roles with exacerbated allergic disorders. Our results provide a plausible explanation that IL-25 produced by innate effector eosinophils and basophils may augment the allergic inflammation by enhancing the maintenance and functions of adaptive Th2 memory cells.
Channel Uncertainty Effects on Multihop AF and DF Wireless Mobile Networks

The main purpose of this paper is studying both the regenerative decode-and-forward (DF) and nonregenerative amplify-and-forward (AF) schemes for mobile wireless relay network under channel uncertainty. A wireless system consisting of one-source-one-destination mobile pair and N multihop mobile relay nodes is under investigation. The scenario being studied is appropriate for low power or widely spread network of mobile nodes, such as vehiculars, where transmitted signal can reach its first tier nodes only and degrades before reaching its second tier neighbors. Therefore, unlike previous work in the literature, this paper studies a system where no direct link exists between any node and its second tier neighbors. New proposed detection schemes, utilizing the maximum ratio combiner (MRC) principle, are proposed and designed for such a network with uncertain mobile channels. It is applied at both relays and the destination to optimally detect the received signals. Using the new proposed detection scheme, Monte-Carlo simulations are employed, and bit error rate (BER) simulation results are presented to evaluate the system performance under study. Performance comparisons for only source-relay links and for only relay-destination links under channel uncertainties were incorporated as well.
Application of Fractional-Slot Concentrated Windings to Synchronous Reluctance Motors

This paper presents an investigation into the application of fractional-slot concentrated windings to synchronous reluctance motors. The advantages and disadvantages of the synthesis of such a machine are explored with thermal aspects included, and a comparison with a similar topology, i.e., the switched reluctance motor, is also presented where appropriate. The differences in electric drive between the two reluctance motors are briefly explored. Finite element studies show that the fractional-slot concentrated wound machine can exhibit higher efficiency and torque density when compared with conventional synchronous reluctance and induction motors, and the electromagnetic model is validated through testing of a prototype machine, with thermal results also reported. Despite the many benefits, high torque ripple and low power factor reduce the topologies' desirability and are identified as an area of further research.
A visual graph-based query interface for video databases

The rapid increase of digital video data makes video query increasingly important. To better satisfy users' video query requirements, developing a user-friendly functional video query interface has become an interesting task. In this paper, we design and implement a visual query interface for video databases. In the interface, we combine the advantages of graph and text, making the interface not only easy to learn and easy to use, but also with powerful query expressiveness. In this paper, we first present a set of interface elements, using which users can specify various kinds of video content information. Next, we define a set of graphical icons to visualize these elements, thereby, supplying a visual friendly interface for users. Finally, we discuss the overall implementation framework of the interface, as well as some key implementation techniques.
Mode manipulation in small microsphere systems

In this work we demonstrate the possibility of mode manipulation in systems of symmetric photonic molecules formed by placing several microspheres in contact. We observe photonic nanojets that reflect the symmetry of the photonic molecule, with 3 jets located at 120 degrees with respect to each other for the triangular molecule. We also present some results showing the coexistence of whispering gallery modes and nanojets in the same structure.
A holographic interpretation of asymptotically de Sitter spacetimes

One of the remarkable outcomes of the AdS/CFT correspondence has been the generalization of Cardy's entropy formula for arbitrary dimensionality, as well as a variety of anti-de Sitter scenarios. More recently, related work has been done in the realm of asymptotically de Sitter backgrounds. Such studies presume a well-defined dS/CFT duality, which has not yet attained the credibility of its AdS analogue. In this paper, we derive and interpret generalized forms of the Cardy entropy for a selection of asymptotically de Sitter spacetimes. These include the Schwarzschild–de Sitter black hole (as a review of Preprint hep-th/0112093), the Reissner–Nordstrom–de Sitter black hole and a special class of topological de Sitter solutions. Each of these cases is found to have interesting implications in the context of the proposed correspondence.
Metabolisable Energy, In situ Rumen Degradation and In vitro Fermentation Characteristics of Linted Cottonseed Hulls, Delinted Cottonseed Hulls and Cottonseed Linter Residue

Dietary supplementation with conventional linted cottonseed hulls (LCSH) is a common practice in livestock production all over the world. However, supplementation with mechanically delinted cottonseed hulls (DCSH) and cottonseed linter residue (CLR) is uncommon. Cottonseed by-products, including LCSH, DCSH and CLR, were assessed by chemical analysis, an in situ nylon bag technique, an in vitro cumulative gas production technique and in vitro enzyme procedure. The crude protein (CP) content of CLR (302 g/kg dry matter (DM)) was approximately 3 times that of LCSH and 5 times that of DCSH. The crude fat content was approximately 3 times higher in CLR (269 g/kg DM) than in LCSH and 4 times higher than in DCSH. Neutral detergent fibre (311 g/kg DM) and acid detergent fibre (243 g/kg DM) contents of CLR were less than half those of DCSH or LCSH. Metabolisable energy, estimated by in vitro gas production and chemical analyses, ranked as follows: CLR (12.69 kJ/kg DM)>LCSH (7.32 kJ/kg DM)>DCSH (5.82 kJ/kg DM). The in situ degradation trial showed that the highest values of effective degradability of DM and CP were obtained for CLR (p<0.05). The in vitro disappearance of ruminal DM ranked as follows: CLR>LCSH>DCSH (p<0.05). The lowest digestibility was observed for DCSH with a two-step in vitro digestion procedure (p<0.05). The potential gas production in the batch cultures did not differ for any of the three cottonseed by-product feeds. The highest concentration of total volatile fatty acids was observed in CLR after a 72 h incubation (p<0.05). The molar portions of methane were similar between all three treatments, with an average gas production of 22% (molar). The CLR contained a higher level of CP than did LCSH and DCSH, and CLR fermentation produced more propionate. The DCSH and LCSH had more NDF and ADF, which fermented into greater amounts of acetate.
Theory of Mind Development in Adolescence and Early Adulthood: The Growing Complexity of Recursive Thinking Ability

This study explores the development of theory of mind, operationalized as recursive thinking ability, from adolescence to early adulthood (N = 110; young adolescents = 47; adolescents = 43; young adults = 20). The construct of theory of mind has been operationalized in two different ways: as the ability to recognize the correct mental state of a character, and as the ability to attribute the correct mental state in order to predict the character’s behaviour. The Imposing Memory Task, with five recursive thinking levels, and a third-order false-belief task with three recursive thinking levels (devised for this study) have been used. The relationship among working memory, executive functions, and linguistic skills are also analysed. Results show that subjects exhibit less understanding of elevated recursive thinking levels (third, fourth, and fifth) compared to the first and second levels. Working memory is correlated with total recursive thinking, whereas performance on the linguistic comprehension task is related to third level recursive thinking in both theory of mind tasks. An effect of age on third-order false-belief task performance was also found. A key finding of the present study is that the third-order false-belief task shows significant age differences in the application of recursive thinking that involves the prediction of others’ behaviour. In contrast, such an age effect is not observed in the Imposing Memory Task. These results may support the extension of the investigation of the third order false belief after childhood.
A new computer vision algorithm for classification of POLSAR images

Extracting good representations from POLSAR images is essential for many computer vision tasks. In this paper, we propose hierarchical matching pursuit (HMP), which builds a feature hierarchy layer-by-layer using an efficient matching pursuit encoder. The algorithm proposed in this paper, was applied on a POLSAR image and the result demonstrates that the extracted features using the proposed computer vision algorithm is an effective and useful method for classification of POLSAR images.
AN IMPROVED OF SPAM E-MAIL CLASSIFICATION MECHANISM USING K-MEANS CLUSTERING

Spam e-mails are considered as a serious violation of privacy. In addition, it has become costly and unwanted communication. Although, Support Vector Machine (SVM) has been widely used in e-mail spam detection, yet the problem of dealing with huge dat a is time and memory consuming and low accuracy. This study speeds up the computational time of SVM classifiers by reducing the number of support vectors. This is done by the K-means SVM (KSVM) algorithm proposed in this work. Furthermore, this paper proposes a mechanism for e-mail spam detection based on hybrid of SVM and K-means clustering and requires one more input parameter to be determined: the number of clusters. The experiment of the proposed mechanism was carried out using spambase standard dataset to evaluate the feasibility of the proposed method. The result of this hybrid method l ed to improved SVM classifier by reducing support vectors, increasing the accuracy and decreasing the time of e-mail spam detection. Experimental result s on spambase datasets showed that the improved SVM (KSVM) significantly outperforms SVM and many other recent spam detection methods in terms of cla ssification accuracy (effectiveness) and time consu ming (efficiency).
Identifying challenging CS1 concepts in a large problem dataset

We examine student difficulties with CS1 concepts by analyzing a dataset containing 266,852 student responses to weekly code-writing problems. We find that conditionals and loops prove particularly problematic, even when considering 'second chance' data; and that, while we observe some evidence of improvement, certain straightforward applications of loops continue to be problematic at the end of the term. Our contribution is the corroboration of earlier findings, and a call to use online repositories of student submissions as rich sources of data on the student learning experience.
0 . 2 Elliptic invariants

Gromov-Witten theory is used to define an enumerative geometry of curves in Calabi-Yau 5-folds. We find recursions for meeting numbers of genus 0 curves, and we determine the contributions of moving multiple covers of genus 0 curves to the genus 1 Gromov-Witten invariants. The resulting invariants, conjectured to be integral, are analogous to the previously defined BPS counts for Calabi-Yau 3 and 4-folds. We comment on the situation in higher dimensions where new issues arise. Two main examples are considered: the local Calabi-Yau P with normal bundle ⊕i=1O(−1) and the compact Calabi-Yau hypersurface X7 ⊂ P. In the former case, a closed form for our integer invariants has been conjectured by G. Martin. In the latter case, we recover in low degrees the classical enumeration of elliptic curves by Ellingsrud and Strömme.
Dispersal depends on body condition and predation risk in the semi-aquatic insect, Notonecta undulata

Dispersal is the movement of organisms across space, which has important implications for ecological and evolutionary processes, including community composition and gene flow. Previous studies have demonstrated that dispersal is influenced by body condition; however, few studies have been able to separate the effects of body condition from correlated variables such as body size. Moreover, the results of these studies have been inconsistent with respect to the direction of the relationship between condition and dispersal. We examined whether body condition influences dispersal in backswimmers (Notonecta undulata). We also tested whether an interaction between body condition and predation risk (another proximate factor that influences dispersal) could contribute to the previously observed inconsistent relationship between condition and dispersal. We imposed diet treatments on backswimmers in the laboratory, and measured the effects of food availability on body condition and dispersal in the field. We found that dispersal was a positive function of body condition, which may have important consequences for population characteristics such as the rate of gene flow and population growth. However, the effects of body condition and predation risk were additive, not interactive, and therefore, our data do not support the hypothesis that the interaction between condition and predation risk contributes to the inconsistency in the results of previous condition-dependent dispersal studies.
Lyapunov-based nonlinear estimation methods with applications to machine vision

Recent advances in image-based information estimation has enabled the use of vision sensor in many robotics and surveillance applications. The work in this dissertation, is focused on developing online techniques for image-based structure and motion (SaM) estimation. Since traditional batch methods are not useful for the online vision-based control tasks, observer-based approaches to the problem have been developed. Starting from the Kalman-filter for SaM problem by L. Matthies, many contributions to the observer approach for the SaM problem exist in literature. Various models are introduced in literature for SaM estimation but two models are prevalent, viz; a kinematic relative motion affine model with implicit outputs and a transformed nonlinear state model with the linear output equation. The existing SaM observers are designed for the case of a stationary object, requires full camera velocity information and cannot be used for certain camera motions. In this dissertation, new solutions to the SaM are presented using the transformed nonlinear state model which can be used for larger set of camera motions, does not require full camera velocity information, and are reduced-order. Solutions for the stationary as well as moving objects viewed by a moving camera are presented. In Chapter 3, a reduced order observer is developed to estimate the structure of a static object using a moving camera, where full camera velocity and linear acceleration are known. Chapter 4 focuses on the development of a reduced order observer for the SaM estimation of a stationary object when only a single camera linear velocity is known. In Chapter 5, an observer design is presented for a specific class of nonlinear systems where the output dynamics are affine in the unmeasurable state and the dynamics of the unmeasurable state are nonlinear. The method is applied to simultaneously estimate the structure and motion of a moving object seen by a moving camera. Another strategy to the observer design in the presence of an unmeasurable disturbance is an unknown input observer (UIO). Chapter 6 provides a solution to an UIO design for a general class of nonlinear systems and it’s application to structure estimation of a moving object is shown in Chapter 7.
Direct Training Method for Continuous-time Nonlinear Optimal Feedback Controller 1 2

The solutions of most nonlinear optimal control problems are given in the form of open-loop optimal control which is computed from a given xed initial condition. Optimal feedback control can in principle be obtained by solving the corresponding Hamilton-Jacobi-Bellman (HJB) dynamic programming equation, though in general this is a di cult task. We propose a practical and e ective alternative for constructing an approximate optimal feedback controller in the form of a feedforward neural network, and we justify this choice by several reasons. The controller is capable of approximately minimizing an arbitrary performance index for a nonlinear dynamical system for initial conditions arising from a nontrivial bounded subset of the state-space. A direct training algorithm is proposed and several illustrative examples are given.