Miracle-dz/UniFAR-FTUs huggingface dataset:
Sublinearity of the travel-time variance for dependent first-passage percolation

Let E be the set of edges of the d-dimensional cubic lattice ℤd, with d ≥ 2, and let t(e), e ∈ E, be nonnegative values. The passage time from a vertex v to a vertex w is defined as infπ : v→w ∑e∈π t(e), where the infimum is over all paths π from v to w, and the sum is over all edges e of π. Benjamini, Kalai and Schramm [2] proved that if the t(e)’s are i.i. d. two-valued positive random variables, the variance of the passage time from the vertex 0 to a vertex v is sublinear in the distance from 0 to v. This result was extended to a large class of independent, continuously distributed t-variables by Benaim and Rossignol [1]. We extend the result by Benjamini, Kalai and Schramm in a very different direction, namely to a large class of models where the t(e)’s are dependent. This class includes, among other interesting cases, a model studied by Higuchi and Zhang [9], where the passage time corresponds with the minimal number of sign changes in a subcritical “Ising landscape. ”
[Association between depression and chronic diseases: results from a population-based study].

OBJECTIVE To assess the association between depression and chronic diseases in adults. METHODS Population-based cross-sectional study with a sample of 1,720 adults aged 20 to 59 years conducted in the city of Florianópolis, southern Brazil, in 2009. Multistage sampling was used and census tracts were the primary sample unit. Subjects were interviewed at home, and reported being diagnosed with depression (outcome) and 11 other chronic diseases (exploratory variable) by a health provider. They were grouped into those with no chronic disease, one, and two or more diseases. Gender, age, marital status, income, physical activity, hospitalization and medical visits were confounders. Poisson regression analysis was used to estimate prevalence ratios and related 95% confidence intervals. RESULTS The prevalence of depression was 16.2% (95%CI 14.3;18.2). It was higher in women, older individuals, widowed or divorced, and poor ones. Those who reported no leisure-time physical activity and medical visits in the last two weeks, and who were hospitalized in the last year also showed higher prevalence of depression and chronic diseases. Even after adjustment for confounders the prevalence of depression was 1.44 (95%CI 1.09;1.92) times higher among those reporting one chronic disease and 2.25 times higher among those reporting two or more diseases than among those with no diseases. CONCLUSIONS The prevalence of depression is much higher among people with higher burden of chronic diseases. Health professionals, health services, and policy makers must target specific strategies to this group.
Anti-Metastatic and Anti-Tumor Growth Effects of Origanum majorana on Highly Metastatic Human Breast Cancer Cells: Inhibition of NFκB Signaling and Reduction of Nitric Oxide Production

Background We have recently reported that Origanum majorana exhibits anticancer activity by promoting cell cycle arrest and apoptosis of the metastatic MDA-MB-231 breast cancer cell line. Here, we extended our study by investigating the effect of O . majorana on the migration, invasion and tumor growth of these cells. Results We demonstrate that non-cytotoxic concentrations of O . majorana significantly inhibited the migration and invasion of the MDA-MB-231 cells as shown by wound-healing and matrigel invasion assays. We also show that O . majorana induce homotypic aggregation of MDA-MB-231 associated with an upregulation of E-cadherin protein and promoter activity. Furthermore, we show that O . majorana decrease the adhesion of MDA-MB-231 to HUVECs and inhibits transendothelial migration of MDA-MB-231 through TNF-α-activated HUVECs. Gelatin zymography assay shows that O . majorana suppresses the activities of matrix metalloproteinase-2 and -9 (MMP-2 and MMP-9). ELISA, RT-PCR and Western blot results revealed that O . majorana decreases the expression of MMP-2, MMP-9, urokinase plasminogen activator receptor (uPAR), ICAM-1 and VEGF. Further investigation revealed that O . majorana suppresses the phosphorylation of IκB, downregulates the nuclear level of NFκB and reduces Nitric Oxide (NO) production in MDA-MB-231 cells. Most importantly, by using chick embryo tumor growth assay, we also show that O . majorana promotes inhibition of tumor growth and metastasis in vivo. Conclusion Our findings identify Origanum majorana as a promising chemopreventive and therapeutic candidate that modulate breast cancer growth and metastasis.
Sustainable Intensification of Pineapple Farming in Ghana: Training and Complexity

Sustainable intensification of Ghana's smallholder farming is critical to mitigate rural poverty. Innovations for sustainable intensification include agro-ecological practices, which build up soil fertility, and mulching, which conserves soil moisture. To stimulate the adoption of these innovations, development organizations and business stakeholders provide training for farmers, to demonstrate proper usage and convince the farmers of their profitability. Using unique panel data, we analyze whether the provided training increases adoption-rates. We find effect of training is significant for the adoption of agro-ecological practices but not for mulching. The explanation is that agro-ecological practices are complex but inexpensive, so that information is the main constraint. Mulching in contrast is already a little more diffused, easier to understand but more expensive. Therefore, mulching is less constrained by lacking information and mostly by finance, which includes restricted credit access and uninsured risk.
Spectrum analysis of parabolic range gate pull-off (RGPO) signals

Digital Radio Frequency Memory (DRFM) is a method that is used to capture radar threat signals, and retransmit them by changing their parameters in order to deceive or manipulate radar threats. Range gate pull-off (RGPO) technique is widely used in DRFM methods. RGPO can be either linear or parabolic RGPO according to the applied pull-off function. In this study, firstly, analytical derivations for temporal and spectral analysis of discrete form of linear and parabolic RGPO signals are presented. Then, various scenarios dependent on the parameters of pull-off function are created. Finally, simulation results regarding the scenarios are presented.
Resource-Bounded Reasoning and Paraconsistency

Paraconsistent logic formalizes reasoning from inconsistent information. The preservationist variety of this logic concerns itself with forms of reasoning that preserve properties of information other than those, like overall satisfy and consistency, preserved by classical forms. The study of computation and information processing in the presence of inconsistency has utilized paraconsistent logics, although not generally of the preservationist kind. We argue that situations involving bounded resources for computation can give rise to situations that naturally call for preservationist paraconsistent reasoning. The point is illustrated with reference to memoryand time-limited systems, yielding approximate answers to
Query-by-conducting: An Interface to Retrieve Classical-music Interpretations by Real-time Tempo Input

This paper presents an interface for finding interpretations of a user-specified music, Query-by-Conducting. In classical music, there are many interpretations to a particular piece, and finding “the” interpretation that matches the listener’staste allowsa listener to further enjoythe piece. The critical issue in finding such an interpretation is the way or interface to allow the listener to listen through different interpretations. Our interface allows a user, by swinging a conducting hardware interface, to conduct the desired global tempo along the playback of a piece, at any time in the piece. The real-time conducting input by the user dynamically switches the interpretation being played back to the one closest to how the user is currently conducting. At the end of the piece, our interface ranks each interpretation according to how close the tempo of each interpretation was to the user input. At the core of our interface is an automated tempo estimation method based on audio-score alignment. We improve tempo estimation by requiring the audio-score alignment of different interpretations to be consistent with each other. We evaluate the tempo estimation method using a solo, chamber, and orchestral repertoire. The proposed tempo estimation decreases the error by as much as 0.94 times the original error.
An Algorithm for Online Tensor Prediction: DRAFT Do Not Distribute

We present a new method for online prediction and learning of tensors (N -way arrays N > 2) from sequential measurements. We focus on the specific case of 3-D tensors and exploit a recently developed framework of structured tensor decompositions proposed in (1). In this framework it is possible to treat 3-D tensors as linear operators and appropriately generalize notions of rank and positive definiteness to tensors in a natural way. Using these notions we propose a generalization of the matrix exponentiated gradient descent algorithm (2) to a tensor exponentiated gradient descent algorithm using an extension of the notion of von-Neumann divergence to tensors. Then following a similar construction as in (3), we exploit this algorithm to propose an online algorithm for learning and prediction of tensors with provable regret guarantees. Simulations results are presented on semi-synthetic data sets of ratings evolving in time under local influence over a social network. The result indicate superior performance compared to other (online) convex tensor completion methods. Index Terms—Tensor factorization, Online prediction and Learning, Convex Optimization
Linear Transceiver Design for Downlink Multiuser MIMO Systems: Downlink-Interference Duality Approach

This paper considers linear transceiver design for downlink multiuser multiple-input multiple-output (MIMO) systems. We examine different transceiver design problems. We focus on two groups of design problems. The first group is the weighted sum mean-square-error (WSMSE) (i.e., symbol-wise or user-wise WSMSE) minimization problems and the second group is the minimization of the maximum weighted mean-square-error (WMSE) (symbol-wise or user-wise WMSE) problems. The problems are examined for the practically relevant scenario where the power constraint is a combination of per base station (BS) antenna and per symbol (user), and the noise vector of each mobile station is a zero-mean circularly symmetric complex Gaussian random variable with arbitrary covariance matrix. For each of these problems, we propose a novel downlink-interference duality based iterative solution. Each of these problems is solved as follows. First, we establish a new mean-square-error (MSE) downlink-interference duality. Second, we formulate the power allocation part of the problem in the downlink channel as a Geometric Program (GP). Third, using the duality result and the solution of GP, we utilize alternating optimization technique to solve the original downlink problem. For the first group of problems, we have established symbol-wise and user-wise WSMSE downlink-interference duality. These duality are established by formulating the noise covariance matrices of the interference channels as fixed point functions. On the other hand, for the second group of problems, we have established symbol-wise and user-wise MSE downlink-interference duality. These duality are established by formulating the noise covariance matrices of the interference channels as marginally stable (convergent) discrete-time-switched systems. The proposed duality based iterative solutions can be extended straightforwardly to solve many other linear transceiver design problems. We also show that our MSE downlink-interference duality unify all existing MSE duality. In our simulation results, we have observed that the proposed duality based iterative algorithms utilize less total BS power than that of the existing algorithms.
Cross-cultural Music Mood Classification: A Comparison on English and Chinese Songs

Most existing studies on music mood classification have been focusing on Western music while little research has investigated whether mood categories, audio features, and classification models developed from Western music are applicable to non-Western music. This paper attempts to answer this question through a comparative study on English and Chinese songs. Specifically, a set of Chinese pop songs were annotated using an existing mood taxonomy developed for English songs. Six sets of audio features commonly used on Western music (e.g., timbre, rhythm) were extracted from both Chinese and English songs, and mood classification performances based on these feature sets were compared. In addition, experiments were conducted to test the generalizability of classification models across English and Chinese songs. Results of this study shed light on cross-cultural applicability of research results on music mood classification.
A comparative analysis of the effect of pregnancy in cohabiting unions on formal marriage in Canada, the Netherlands and Latvia: a causal event history approach to interdependent processes

Recently, the western world has witnessed among young cohorts a significant rise in both cohabitation and out of wedlock births as well as an increasingly complex relationship between marriage and childbirth. This study follows previous investigations conducted by Blossfeld and colleagues (1999) on the experience of pregnancy within cohabiting unions and how it conditions the likelihood of transition to formal marriage with the same partners. A hazard model with time-varying covariates is specified explicitly as time-dependent, with entry into first marriage as the dependent process and first pregnancy/birth as the explaining process. Our conceptual framework relies on the rational actor theory, which proposes that normguided and rational self-centred behaviour co-exist in the case when a pregnancy occurs in a consensual union and a decision is to be made by the couple with respect to marriage or non-marriage. Our test of this interrelated process is based on the experiences of Canada, Latvia, and the Netherlands. Findings suggest that the interdependencies of cohabitation, pregnancy, and marriage fit the model and are generally uniform processes across these societies. Slight country differences are attributed to attitudes and policies regarding cohabitation versus marriage and the acceptability of out of wedlock births. Paper prepared for FFS Flagship Conference Partnership and Fertility – A Revolution? 29-31 May 2000, Brussels, Belgium. Session: Partnership & fertility behaviour as interdependent processes Acknowledgements. The authors wish to thank the Advisory Group of the FFS programme of comparative research for its permission, granted under identification number 7, to use the FFS data on which this study is based. Melinda Mills’ research is supported by a Doctoral Fellowship from the Social Sciences and Humanities Research Council of Canada (752-980090). The authors particularly wish thank Pierre Turcotte from Statistics Canada, and Frans Willekens, Erik Klijzing and G`tz Rohwer for their helpful suggestions during data analysis.
Characterization of layered media using full-waveform inversion of proximal GPR data

Full-waveform inversion of proximal ground penetrating radar (GPR) data is used to determine the electromagnetic properties of layered media. The radar system consists of a vector network analyzer combined with an off-ground horn antenna operating at ultra wideband. The GPR wave propagation is modeled for a multilayered medium using a recursive Green's function computed in the frequency domain. The antenna and its interactions with the layered medium are modeled using a linear system of complex transfer functions. GPR signals were acquired in laboratory above a two-layered sand medium and two concrete slabs separated by a thin air layer (simulating a fracture). Subsequent inversions permit to retrieve the electromagnetic properties and the dimensions of these thin-layered media. For humid sand, GPR-derived dielectric permittivities showed a good agreement (RMSE = 1.65) with measured volumetric water contents. Dimensions of the three-layered concrete medium could be retrieved with a millimetric accuracy. The method is promising for the non-destructive characterization of multilayered media, including thin layers, owing to the full-waveform inversion of the radar data in a large frequency bandwidth.
Evaluating the Stresses from ECB Monetary Policy in the Euro Area

This paper investigates the extent to which euro area monetary policy has responded to evolving economic conditions in individual member states as opposed to the euro area as a whole. Based on a forward-looking Taylor rule-type policy reaction function, we conduct counterfactual exercises that compare the monetary policy behaviour of the ECB under alternative hypothetical scenarios: (1) the euro member states make individual policy decisions, and (2) the ECB responds to the economic conditions of individual members. Stress measures are then constructed to evaluate the degree of divergence of member state economies under these two hypothetical scenarios. The results we obtain reflect the extent of heterogeneity among the national economies in the monetary union, indicating that euro area policy rates have been particularly close to the ‘counterfactual’ interest rates of the largest euro members and countries with similar economic conditions, namely Germany, Austria, Belgium and France.
Forecasting Volatility under Multivariate Stochastic Volatility Model via Reprojection

This paper evaluates the performance of volatility forecasting based on stochastic volatility (SV) models. We show that the choice of squared asset-return residuals as a proxy for ex-post volatility directly leads to extremely low explanatory power in the common regression analysis of volatility forecasting. We argue that, since the measure of volatility is always model dependent, the performance of volatility forecasting should be evaluated in a consistent modeling framework. This paper provides several main contributions. First, we apply the EMM estimation method proposed by Gallant and Tauchen (1996) to estimate the multivariate SV model of asset returns. Second, we extend implementation of the underlying volatility reprojection technique proposed by Gallant and Tauchen (1998) to the estimated multivariate SV model. Finally, we illustrate that the performance of volatility forecasting based on the reprojected volatility series can be substantially improved. Furthermore, we show that the volatility forecasting performance based on the multivariate SV model is an improvement over that of univariate SV models due to the correlated movements of asset return volatility.
Well Matched Electromagnetic Boundary in FDTD-PIC for Charged Particle Penetration~!2009-08-31~!2009-12-07~!2010-04-13~!

The authors address the Matched Phase Velocity method for bounding an electromagnetic (EM) domain in the MAGIC finite difference-time domain (FDTD) particle-in-cell (PIC) EM code. Reflected power is shown to be reduced 18 dB compared to the conventional port treatment. Boundary quality is preserved under penetration by charged particles.
Hyperbolic Geometry on the Figure-Eight Knot Complement

The exact relationship between knot theory and non-euclidean geometry was a puzzle that survived more than 100 years. The histories of the two subjects were clearly intertwined; Carl Friedrich Gauss was a pioneer and did much to popularize both fields. After Gauss their two histories diverge a little, although taken together the list of luminaries in the two fields reads like a mathematical and scientific “Who’s Who? ” of the 19th and early 20th century. Nikolai Lobachevsky, Felix Klein, and Henri Poincare were three of the main developers of non-euclidean geometry while William Thomson (Lord Kelvin), James Clerk Maxwell, and Emil Artin were instrumental in fleshing out knot theory[4]. Although both subjects came to be recognized as following under the umbrella term “topology” and although giants such as Bernhard Riemann and Max Dehn [4, 7] worked in both areas the two fields remained disjoint until they were finally reunited in the 1970’s. In 1973 Robert Riley, then a graduate student at the University of Southampton in England, succeeded in showing that the figure-eight knot complement had a hyperbolic structure [4]. He did this by first showing that since fundamental group of the figure-eight knot complement is isomorphic to a subgroup of PSL2C, and then using the theory of Haken (of four color theorem fame) manifolds to show that the figure-eight knot complement is homeomorphic to H mod a discrete group of isometries [6]. Riley later showed that several other knot complements admit a hyperbolic structure and conjectured that indeed all knot complements except for torus and satellite knots admit a hyperbolic structure. It seems to often be the case in mathematics that the best way to make progress on a subject is to interest someone else in it. In 1977 Riley did exactly this when he met William Thurston at Princeton and motivated him to start investigating hyperbolic structures on knot complements [4]. Thurston soon came up with a more explicit way of showing that the figure-eight knot complement is hyperbolic. It is Thurston’s construction, which starts by gluing two tetrahedra together, that we will follow in Section 2. Relying in part on his experiences with knot complements [9] in 1978 Thurston completed his “hyperbolization theorem” or “geometrization theorem” (note that this is is a special case of the “geometrization
Sparsifying Dense Features for Action Classification

We propose an approach for sparse representation of dense features for action classification. Sparse representation has already been shown in literature as a good approximation for signals for various computer vision applications. This property is leveraged to represent a dense feature like action bank in the form of sparse dictionaries. These dictionaries are learnt using on-line dictionary learning (ODL) which further facilitates incorporating new training examples into existing dictionaries for more robust representation of various categories of action as and when required. Evaluation of the proposed method on realistic action datasets like UCF50 and HMDB51 shows that considering sparse representation of a dense feature is more suitable for classification than the feature itself.
A new approach for long-term person tracking

This paper investigates long-term visual person tracking using particle filter as the underlying framework and online boosting as the detection strategy. In the case of the being tracked person with abrupt motion, under occlusion or in low sample rate of video source, two main issues rise inevitably. One is the poor constraint of person motion model, and the other is the drastic variation of pose or incomplete appearance when the person reappears. We address the problems with an integrated framework of multiple observers, and online boosting algorithm with independent features and its static and dynamic combination aiming to balance the tradeoff of adaption and drift.