Miracle-dz/UniFAR-FTUs huggingface dataset:
Trans-Planckian problem in the healthy extension of Horava-Lifshitz gravity

Planck scale physics may influence the evolution of cosmological fluctuations in the early stages of cosmological evolution. Because of the quasi-exponential redshifting, which occurs during an inflationary period, the physical wavelengths of comoving scales that correspond to the present large-scale structure of the Universe were smaller than the Planck length in the early stages of the inflationary period. This trans-Planckian effect was studied before using toy models. The Horava-Lifshitz (HL) theory offers the chance to study this problem in a candidate UV complete theory of gravity. In this paper we study the evolution of cosmological perturbations according to HL gravity assuming that matter gives rise to an inflationary background. As is usually done in inflationary cosmology, we assume that the fluctuations originate in their minimum energy state. In the trans-Planckian region the fluctuations obey a non-linear dispersion relation of Corley-Jacobson type. In the "healthy extension" of HL gravity there is an extra degree of freedom which plays an important role in the UV region but decouples in the IR, and which influences the cosmological perturbations. We find that in spite of these important changes compared to the usual description, the overall scale-invariance of the power spectrum of cosmological perturbations is recovered. However, we obtain oscillations in the spectrum as a function of wavenumber with a relative amplitude of order unity and with an effective frequency which scales nonlinearly with wavenumber. Taking the usual inflationary parameters we find that the frequency of the oscillations is so large as to render the effect difficult to observe.
Evaluation of Some Biochemical Responses in Resistance of Fifteen Bread Wheat (Triticum aestivum L.) Genotypes to Wheat streak mosaic virus

Two greenhouse experiments were conducted in 2008-2010 at College of Agriculture, Shiraz University, Iran to evaluate the effectiveness of changes in protein content, peroxidase activity, phenolic compounds, free amino acids content and proline in response to wheat streak mosaic virus (WSMV) infection, in screening resistant bread wheat ( Triticum aestivum L.) genotypes. Fifteen wheat genotypes consisting of WSMV tolerant, intermediate and susceptible genotypes were grown in two randomized complete designs with three replications. The experiments only differed with respect to their inoculation (either infected or non-infected). The results indicated that viral infection increased the total protein and peroxidase activity of leaves in tolerant genotypes but viral infection decreased them in susceptible genotypes. Phenolic compounds increased in all infected genotypes but these increases are the highest in tolerant genotypes as compared to intermediate and susceptible ones. Viral infection reduced free amino acids in genotypes in general. The changes in proline content did not show a typical trend in tolerant, intermediate or susceptible genotypes. The analysis of variance indicated that the linear regression of leaf damage rating on the changes in total protein, peroxidase activity and phenols in the leaf was significant but the linear regression of leaf damage rating on the changes in free amino acids and proline in the leaf was not significant. Our results demonstrate the changes in total protein, peroxidase activity and phenolic compounds in a genotype could be used as suitable biochemical markers for assessing the WSMV tolerant wheat plants when grown under infected condition.
A Study on Spatial Analysis Using R-Based Deep Learning

Deep learning is a rapidly growing technology repeating epoch-making development in the field of voice/text/image cognition. Its basic principle is to systematize information and let users find the pattern for themselves through the neural network using lots of layers. Technological core is anticipation by classification. This thesis uses SNS and webpage scrapping data and GIS data for consumer needs. Data will then be extracted by accurate classification for the purpose of spatial information data with deep learning algorithm. It is necessary to call shapefiles to R, improve the accessibility to data, and cross one data set to other data set areas. This thesis intends to analyze data of various environments with data analysis tool, R, and design the process combining data of spatial information and visualizing it based on deep learning algorithm
Monitoring and Corporate Risk Management : Evidence from Insurance Use 1

Corporate governance and risk management issues have received prominent publicity in recent years following several major company failures such as Bear Stearns and Lehman Brothers. While prior studies have examined this issue within the context of derivatives’ trading, little is known regarding the linkage between corporate governance and alternative corporate risk management activities such as insurance. Using a detailed firm survey conducted by the World Bank (2004), we examine the impacts of various governance monitoring mechanisms and CEO characteristics on the corporate insurance decision. Overall, our results suggest that both monitoring mechanisms and managerial incentives induce the corporate purchase of property insurance. However, the purchase of property insurance for managerial self-interest is only prevalent in firms subject to lax monitoring and the determinants of insurance purchases are more in line with the prediction of the economic theory in firms with strong monitoring. In addition, our study contributes a number of new insights into the determinants of corporate purchase of property insurance. JEL classification: G22, G30, G32
Biomass distribution and allocation in diploid potato varieties ( Solanum phureja Juz. et Buk.)

It is necessary to study the photosynthate distribution pattern and allocation in Guanena and Latina potato varieties, which come from the Colombia variety and are relatively new in agriculture, for potato crops in Colombia. The aim of this study was to determine the distribution behavior of dry matter among the organs that make up the potato plant in order to determine the key moments in the crop cycle, where the filling of the tubers takes place, and to establish the pattern of biomass distribution in these varieties. Three consecutive experiments were performed at the “Estacion Agraria Paysandu” in Santa Elena (Medellin- Antioquia), at 2,538 m a.s. l. with average temperatures of 13.6, 14.6 and 13.81oC. The field trials were established under a random complete blocks design with a 3x2 factorial layout and five replications. The first factor corresponded to the potato varieties and the second factor corresponded to the two fertilization levels: 7 and 21 g of fertilizer per planting site, representing 259.25 and 777.77 kg of fertilizer per ha. The higher fertilizer dose is the one normally used by farmers. An NPK fertilizer compound (10 - 20 - 20 - 5(S)) was used. There were 30 experiment units with an area of 18.27 m 2 (seven 2.7 m furrows separated by 0.90 m); the distance between the plants was 0.30 m, for a density of 37,037 planting sites per ha. Weekly samplings were taken, a whole plant per experiment unit. The direct measuring evaluated variables for the dry weights of each organ, which were used to obtain curves and the distribution pattern. The development time was evaluated in accumulated growing degree-days and threshold temperatures of 2 and 29°C were used. In all of the varieties and the two fertilization treatments, most of the assimilates in the early stages of the cycle were concentrated in the roots, leaves and stems; once the tuber formation started, the leaves and stems started to allocate dry matter towards the filling of the accumulation organs.
Brain-actuated Control of Robot Navigation

Brain-driven robot navigation control is a new field stemming from recent successes in brain interfaces. Broadly speaking, brain interfaces comprise any system that aims to enable user control of a device based on brain activity-related signals, be them conscious or unconscious, voluntary or evoked, invasive or non-invasive. Strictly speaking, the term should also include technology that directly affects brains states (e.g., transcranial magnetic stimulation), but these are not usually included in the terminology. Two main families of brain interfaces exist according to the usual terminology, although the terms are often used interchangeably as well: i) Brain-computer interfaces (or BCIs) usually refers to brain-tocomputer interfaces that use non-invasive technology; ii) Brain-machine interfaces (or BMIs) often refers to implanted brain-interfaces. This chapter shall use these terms (BCI and BMI) as defined in this paragraph. Other sub-categories of BCIs are discussed below. The idea of BCIs is credited to Jaques Vidal (1973) who first proposed the idea in concrete scientific and technological terms. Until the late 1990’s the area progressed slowly as a result of work in but a handful of laboratories in Europe and North America, most notably the groups at the Wadsworth Centre (Albany, NY) and the Graz (Austria) group led by G. Pfurtscheller. Aside from the few researchers working on BCIs in the ‘70s and ’80s, slow progress then was largely due to limitations in: i) our understanding of brain electrophysiology, ii) quality and cost of recording equipment, iii) computer memory and processing speed, and iv) the performance of pattern recognition algorithms. The state-ofthe-art in these areas and the number of BCI researchers have dramatically increased in the last ten years or so. Yet, there is still an enormous amount of work do be done before BCIs can be used reliably outside controlled laboratory conditions. In this chapter, an overview of BCIs will be given, followed by a discussion of specific approaches for BCI-based robot navigation control. The chapter then concludes with a summary of challenges for the future of this new and exciting technology.
A Two-Phase Approach of Progressive Mesh Reconstruction from Unorganized Point Clouds

This paper presents a practical approach for surface reconstruction from unoriented point clouds. Instead of estimating local surface orientation, we first generate a set of depth images from the input point clouds, and a coarse mesh is then generated based on them by space carving techniques. The resultant mesh is progressively refined by local mesh refinement and optimization according to surface distance measure. A manifold mesh approximating the input points within an given tolerance is finally obtained. Our approach is easy to implement, but has the ability to outputs high quality meshes in different resolutions. We show that the proposed approach is not sensitive to several types of data disfigurement and is able to reconstruct models robustly from variance input data.
Initial effects of woody biomass removal and intercropping of switchgrass (Panicum virgatum) on herpetofauna in eastern North Carolina.

Forests are potential sources for a wide range of alternative fuels, which could reduce dependency on fossil fuels and carbon emissions, but sustainability of producing biofuels from forests has not been well-studied. Therefore, we investigated effects of woody biomass harvest, intercropping perennial grasses, and combinations of these treatments on herpetofauna in loblolly pine (Pinus taeda) plantations in a randomized and replicated field experiment in eastern North Carolina, USA. We sampled amphibians and small reptiles with drift fence arrays from April to July during 1 and 2 years after treatment establishment. We had 425 captures of 15 species of herpetofauna across the 2 sampling seasons, but did not observe large general effects of biomass removal or planting of switchgrass (Panicum virgatum) in pine plantations on detection, diversity, or relative abundance. However, planned contrasts indicated Simpson's index of diversity was greater in plots managed for switchgrass only compared with pine plantations during year 2, and that captures of southern toads (Anaxyrus terrestris) were less common in switchgrass plots than in pine plantations intercropped with switchgrass. Neither intercropping switchgrass with pine nor removal of harvest residuals caused herpetofauna diversity or abundance of common species to differ from traditional plantation management during the first 2 years following treatment establishment. With the exception of switchgrass-only plots, which had lower herpetofauna species evenness, the potential practices we considered for biofuels production are unlikely to have short-term effects on herpetofauna relative to traditional pine management. Future research should monitor herpetofauna through succession and consider landscape-scale effects and other potential feedstock sources. © 2013 The Wildlife Society.
Lecture 20 Volatility Modeling and Calibration

Note: With the presence of high-dimensional latent volatility processes, numerical integration for computing option prices is required at every time point and every iteration of MCMC. There is an urgent need for developing approximation schemes that reduce numerical integration from a high-dimensional space (of diffusion sample paths) to a low-dimensional space (of 2D or 3D random vectors). We propose using bivariate Gaussian or gamma mixtures of Gaussian to approximate joint distributions of certain integrated volatilities and additive functionals in the lifetime of relevant options or other derivatives. When implementing those schemes to computation of various derivatives prices represented by GBS formulas, they significantly improve the efficiency (speed/accuracy) of related MCMC algorithms. This will have an impact on a wide range of problems in financial econometrics.
Unintended Media Effects in a Conflict Environment: Serbian Radio and Croatian Nationalism

Do media broadcasts matter when they reach audiences that are not their target? In a conflict, the media may have an unintended effect of increasing ethnic animosity. We consider radio signals travelling across country borders in the region that witnessed one of Europe's deadliest conflicts since WWII: the Serbo-Croatian conflict in the Yugoslavian wars. Using survey data, we find that a large fraction of Croats listen to Serbian radio (intended for Serbian listeners across the border) whenever signal is available. Then, using official election results, we document that residents of Croatian villages with good-quality signal of Serbian public radio were more likely to vote for extreme nationalist parties, even after several years of peace time. Finally, ethnically-offensive graffiti are more likely to be exposed openly in the center of villages with Serbian radio reception. The effect is identified from the variation in the availability of the signal mostly due to topography and forestation. The results of a laboratory experiment confirm that Serbian radio exposure causes an increase in anti-Serbian sentiment among Croats.
Time Series Prediction : Predicting Stock Price

Time series forecasting is widely used in a multitude of domains. In this paper, we present four models to predict the stock price using the SPX index as input time series data. The martingale and ordinary linear models require the strongest assumption in stationarity which we use as baseline models. The generalized linear model requires lesser assumptions but is unable to outperform the martingale. In empirical testing, the RNN model performs the best comparing to other two models, because it will update the input through LSTM instantaneously, but also does not beat the martingale. In addition, we introduce an online to batch algorithm and discrepancy measure to inform readers the newest research in time series predicting method, which doesn't require any stationarity or non mixing assumptions in time series data. Finally, to apply these forecasting to practice, we introduce basic trading strategies that can create Win win and Zero sum situations.
Third‐Degree Price Discrimination in the Presence of Congestion Externality

This paper analyzes third-degree price discrimination of a monopoly airline in the presence of congestion externality when all markets are served. The model features the business-passenger and leisure-passenger markets where business passengers exhibit a higher time valuation, and a less price-elastic demand, than leisure passengers. Our main result is the identification of the time-valuation effect of price discrimination, which can work in the opposite direction as the well-known output effect on welfare. This time-valuation effect clearly explains why discriminating prices can improve welfare even when this is associated with a reduction in aggregate output.
Clinical relevance of high-sensitive Troponin T in cardiovascular disease

Background and aims: Troponin T (hs-cTnT) is a cardiac damage marker used in the diagnosis of non-ST segment elevation myocardial infarction (NSTEMI) and for prognostic assessment. Clinical decision-making should ideally be based on evidence. We therefore studied the prognostic significance of small changes in the level of hs-cTnT in patients with NSTEMI, the effects of renal insufficiency on levels of cardiac biomarkers, a risk assessment model including age, cystatin C (CysC) and hs-cTnT in heart failure, and whether a lowered hs-cTnT diagnostic cutoff value, from 40 ng/L to 14 ng/L (the 99 percentile), results in mortality changes and increasing health care expenditure. Methods: Four study cohorts were used. Multiple biomarkers and clinical data were combined. The first study included 1178 patients with NSTEMI. The second study included 489 patients with different degrees of renal function who were referred for glomerular filtration rate (GFR) measurement, either by Cr51EDTA or Iohexol clearance. The third study included 124 patients with heart failure and reduced left ventricular ejection fraction (HFREF). The fourth study included 39001 visits to the emergency department (ED) by patients with chest pain or dyspnea with at least one hs-cTnT measurement at the local hospital, before and after lowering the hs-cTnT diagnostic cutoff from 40 ng/L to 14 ng/L. Results: In NSTEMI, a six-hour relative hs-cTnT change <20% was observed in 25 % of NSTEMI patients and was linked to increased mortality. Compared with patients with normal kidney function, the estimated increase in the cardiac biomarkers at a GFR
Alleviation of waterlogging damage by foliar application of nitrogen compounds and tricyclazole in canola

Waterlogging stress induces harmful physiological changes which restrict canola growth. The aim of this investigation was to evaluate the effects of foliar applications of nitrogen compounds (urea, calcium nitrate and potassium nitrate) and tricyclazole at different growth times on physiological responses in canola plants (Brassica napus L. cv. Hayola 401) subjected to waterlogging stress. Plants in the 5-leaf growth stage were exposed to waterlogging conditions for two weeks. Results of waterlogged control compared to non-waterlogged control demonstrated that waterlogging stress significantly decreased the activity of superoxide dismutase (SOD; EC 1.15.1.1), catalase (CAT; EC 1.11.1.6) and peroxidase (POX; EC 1.11.1.7), while lipid peroxidation and ethylene production in the leaves were increased by the waterlogging stress. Furthermore, dry weight and length of shoots and roots were reduced by waterlogging stress. These adverse effects of waterlogging stress were alleviated by foliar application of all tested compounds; once (before the stress) or twice (before and after the stress). Twice foliar applications did not have any significant superiority to once foliar spray. It was concluded that, among the different treatments, the foliar spray of calcium nitrate, potassium nitrate and tricyclazole before the waterlogging stress were more beneficial and cost efficient than the twice application and is advisable to alleviate the waterlogging damage in canola.
Acceleration and deceleration of India-Asia convergence since the Cretaceous: Roles of mantle plumes and continental collision

[1] A strong 50–35 Ma decrease in India-Asia convergence is generally ascribed to continent-continent collision. However, a convergence rate increase of similar magnitude occurred between ∼65–50 Ma. An earlier increase occurred at ∼90 Ma. Both episodes of accelerated convergence followed upon arrival of a mantle plume below and emplacement of a large igneous province (LIP) on the Indian plate. We here first confirm these convergence rate trends, reassessing the Indo-Atlantic plate circuits. Then, using two different numerical models, we assess whether plume head arrival and its lateral asthenospheric flow may explain the plate velocity increases and whether decreased plume flux and increasing continent-plume distance may explain deceleration, even without continental collision. The results show that plume head arrival can indeed lead to absolute Indian plate motion accelerations on the order of several cm/yr, followed by decelerations on timescales similar to the reconstructed fluctuations. The 90 Ma increase could potentially be explained as response to the Morondova mantle plume alone. The 65–50 Ma convergence rate increase, however, is larger than can be explained by plume head spreading alone. We concur with previous hypotheses that plume-induced weakening of the Indian continental lithosphere-asthenosphere coupling and an increased slab pull and ridge push efficiency are the most likely explanations for the large convergence rate increase. The post-50 Ma decrease is best explained by orogeny-related increased trench resistivity, decreased slab pull due to continental subduction, and possibly restrengthening of lithosphere-asthenosphere coupling upon plume demise.
Probabilistic Approach to Robust Wearable Gaze Tracking

This paper presents a method for computing the gaze point using camera data captured with a wearable gaze tracking device. The method utilizes a physical model of the human eye, advanced Bayesian computer vision algorithms, and Kalman filtering, resulting in high accuracy and low noise. Our C++ implementation can process camera streams with 30 frames per second in realtime. The performance of the system is validated in an exhaustive experimental setup with 19 participants, using a self-made device. Due to the used eye model and binocular cameras, the system is accurate for all distances and invariant to device movement. We also test our system against a best-in-class commercial device which is outperformed for spatial accuracy and precision. The software and hardware instructions as well as the experimental data are published as open source.
Apprentissage implicite du contexte visuel et guidage de la perception

Cette these de doctorat a ete conduite entre septembre 2004 et juin 2008 a l''Universite Pierre et Marie Curie. Maximilien Chaumon y rapporte les resultats d''une experience de magnetoencephalographie (MEG) et une experience d''electroencephalographie intracrânienne (EEGi). L''introduction presente les concepts de contexte visuel, de guidage de l''attention et d''apprentissage implicite. Puis est presentee la tâche de recherche visuelle utilisee pour les experiences suivie de trois articles publies en anglais rapportant les resultats des experiences. Suit une discussion integrant l''ensemble des resultats pour proposer un scenario neurophysiologique de l''apprentissage implicite du contexte visuel. Le travail presente est parmi les premiers a caracteriser des activites distinctes dans la bande de frequence gamma au sein d''une meme experience.