Miracle-dz/UniFAR-FTUs huggingface dataset:
Response of Cowpea (Vigna unguiculata L. Walp.) Seeds in Culture to Different Rates of Seed-Treatment with Phytochemicals from Piper guineense L

Seed-borne mycoflora can severely affect seed viability and germination, seedling vigour, crop performance, quality and yield. Seed treatments present a cheap and veritable means for their control. However, owing to ecological and mammalian toxicities, alternatives to synthetic pesticides are being sought. The aim of this study was to assess in vitro the effects of 7 rates (0, 5, 10, 15 20 25 and 30%) of Piper guineense L. as seed-dressing phytochemicals on the germination of the treated cowpea seeds and the incidence of the seed-borne fungi and to determine the rate(s) that is most fungitoxic to the seed-borne mycobiota, and least phytotoxic to the cowpea seed. The experiment was laid out in completely randomized design (CRD), with 4 replicates; and was repeated twice. The results showed that the germination profile of the treated seeds deceased with increasing dose of application of the phytochemicals; with best germination of 80% obtained at 5% concentration. This study also affirmed that the mycobiota Fusarium oxysporium, F. verticilloides, Colletotrichum destructivum, C. truncatum, Aspergillus fumigatus, A. flavus, A. niger and Rhizopus spp. were associated with seeds of cowpea variety IAR-48. It indicated that though 30% of the phytochemicals significantly (P≤0.05) gave a better reduction of these seed-borne fungi; however, germination was better at 5% dose of application. This was followed by 10%, 15% etc. Hence, 5-15% aqueous root extracts of Piper guineense L. could be used as effective seed-dressing phytochemical in Integrated Disease Management (IDM) Programmes for the control of seed-borne fungi of cowpea, for improved productivity. However, P. guineense seed extract treatments should be tried out in further studies to determine the best length of exposure (soaking period) to the treament.
Capital Structure, Profitability and Firm Value: An Empirical Analysis

This study is aimed to determine the effect of Corporate Structure on Firm Value with profitability as a moderating variable. The sample used in this research was companies listed in LQ 45 on the Indonesia Stock Exchange in 2012-2016, which were 38 companies using a purposive sampling method. The independent variable was the capital structure measured by Debt to Equity Ratio (DER), and Profitability was proxied by the Return On Asset (ROA). The dependent variable was the Firm Value as measured by the ratio of Price Book Value (PBV). The results show that Capital Structure and Profitability have a significant effect on Firm Value.
ENSO impacts on ecosystem indicators in the California Current System

El Niño-Southern Oscillation (ENSO) events activate long-distance teleconnections through the atmosphere and ocean that can dramatically impact marine ecosystems along the West Coast of North America, affecting diverse organisms ranging from plankton to exploitable and protected species. Such ENSOrelated changes to marine ecosystems can ultimately affect humans in many ways, including via depressed plankton and fish production, dramatic range shifts for many protected and exploited species, inaccessibility of traditionally fished resources, more prevalent harmful algal blooms, altered oxygen and pH of waters used in mariculture, and proliferation of pathogens. The principal objective of the Forecasting ENSO Impacts on Marine Ecosystems of the US West Coast workshop was to develop a scientific framework for building an ENSOrelated forecast system of ecosystem indicators along the West Coast of North America, including major biological and biogeochemical responses. Attendees realized that a quantitative, biologically-focused forecast system is a much more challenging objective than forecasting the physical system alone; it requires an understanding of the ocean-atmospheric physical system and of diverse organism-level, population-level, and geochemical responses that, in aggregate, lead to altered ecosystem states.
Economic uncertainty and the effectiveness of montary policy. By Knut Are Aastveit, Gisle James Natvik and Sergio Sola (Norges Bank Working Paper 2013/17)

This paper explores if economic uncertainty alters the macroeconomic influence of monetary policy. We consider several measures of U.S. economic uncertainty, and estimate their interaction effects with monetary policy shocks as identified through structural vector autoregressions. We find that monetary policy shocks affect economic activity considerably weaker when uncertainty is high, consistently with “real-options” effects suggested by models with non-convex adjustment costs. Investment responds two to five times weaker when uncertainty is in its upper instead of its lower decile. High U.S. uncertainty is associated with lower policy influence not only domestically, but in Canada too. JEL-codes: E30, E32, E37
Parabolic problems for direction-dependent local-nonlocal operators

We study parabolic equations governed by integro-differential operators with nonlocal components in some directions and local components in the remaining directions. The setting contains the purely nonlocal, as well as the purely local case. Our approach is based on an energy method allowing for jumping measures that are singular or supported on cusps. In addition, the jumping measure may depend on the direction. The emphasis of our study is on the weak Harnack inequality and H\"older regularity estimates for solutions of such equations. The main regularity estimates are robust in the sense that the constants can be chosen independently of the order of differentiability of the operators.
Line Drawings of Natural Scenes Guide Visual Attention

Visual search is an important strategy of the human visual system for fast scene perception. The guided search theory suggests that the global layout or other top-down sources of scenes play a crucial role in guiding object searching. In order to verify the specific roles of scene layout and regional cues in guiding visual attention, we executed a psychophysical experiment to record the human fixations on line drawings of natural scenes with an eye-tracking system in this work. We collected the human fixations of ten subjects from 498 natural images and of another ten subjects from the corresponding 996 human-marked line drawings of boundaries (two boundary maps per image) under free-viewing condition. The experimental results show that with the absence of some basic features like color and luminance, the distribution of the fixations on the line drawings has a high correlation with that on the natural images. Moreover, compared to the basic cues of regions, subjects pay more attention to the closed regions of line drawings which are usually related to the dominant objects of the scenes. Finally, we built a computational model to demonstrate that the fixation information on the line drawings can be used to significantly improve the performances of classical bottom-up models for fixation prediction in natural scenes. These results support that Gestalt features and scene layout are important cues for guiding fast visual object searching.
IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation

Indoor robotics localization, navigation and interaction heavily rely on scene understanding and reconstruction. Compared to monocular vision which usually does not explicitly introduce any geometrical constraint, stereo vision based schemes are more promising and robust to produce accurate geometrical information, such as surface normal and depth/disparity. Besides, deep learning models trained with large-scale datasets have shown their superior performance in many stereo vision tasks. However, existing stereo datasets rarely contain the high-quality surface normal and disparity ground truth, which hardly satisfy the demand of training a prospective deep model for indoor scenes. To this end, we introduce a large-scale synthetic indoor robotics stereo (IRS) dataset with over 100K stereo RGB images and high-quality surface normal and disparity maps. Leveraging the advanced rendering techniques of our customized rendering engine, the dataset is considerably close to the real-world captured images and covers several visual effects, such as brightness changes, light reflection/transmission, lens flare, vivid shadow, etc. We compare the data distribution of IRS with existing stereo datasets to illustrate the typical visual attributes of indoor scenes. In addition, we present a new deep model DispNormNet to simultaneously infer surface normal and disparity from stereo images. Compared to existing models trained on other datasets, DispNormNet trained with IRS produces much better estimation of surface normal and disparity for indoor scenes.
X-ray spectral and flux variability of the microquasar GRS 1758−258 on timescales from weeks to years

We present the spectral and timing evolution of the persistent black hole X-ray binary GRS 1758−258 based on almost 12 years of observations using the Rossi X-ray Timing Explorer Proportional Counter Array. While the source was predominantly found in the hard state during this time, it entered the thermally dominated soft state seven times. In the soft state GRS 1758−258 shows a strong decline in flux above 3 keV rather than the pivoting flux around 10 keV more commonly shown by black hole transients. In its 3–20 keV hardness intensity diagram, GRS 1758−258 shows a hysteresis of hard and soft state fluxes typical for transient sources in outburst. The RXTE-PCA and RXTE-ASM long-term light curves do not show any orbital modulations in the range of 2–30 d. However, in the dynamic power spectra significant peaks drift between 18.47 and 18.04 d for the PCA data, while less significant signatures between 19 d and 20 d are seen for the ASM data as well as for the Swift/BAT data. We discuss different models for the hysteresis behavior during state transitions as well as possibilities for the origin of the long term variation in the context of a warped accretion disk.
A single spark model for PSR J2144−3933

The partially screened vacuum gap model (PSG) for the inner acceleration region in normal radio pulsars, a variant of the pure vacuum gap model, attempts to account for the observed thermal X-ray emission from polar caps and the subpulse drifting timescales. We have used this model to explain the presence of death lines, and extreme location of PSR J2144$-$3933 in the $P-\dot{P}$ diagram. This model requires maintaining the polar cap near a critical temperature and the presence of non-dipolar surface magnetic field to form the inner acceleration region. In the PSG model, thermostatic regulation is achieved by sparking discharges which are a feature of all vacuum gap models. We demonstrate that non-dipolar surface magnetic field reduces polar cap area in PSR J2144$-$3933 such that only one spark can be produced and is sufficient to sustain the critical temperature. This pulsar has a single component profile over a wide frequency range. Single-pulse polarimetric observations and the rotating vector model confirm that the observer's line-of-sight traverses the emission beam centrally. These observations are consistent with a single spark operating within framework of the PSG model leading to single-component emission. Additionally, single-pulse modulations of this pulsar, including lack of subpulse drifting, presence of single-period nulls and microstructure, are compatible with a single spark either in PSG or in general vacuum gap models.
Ab initio simulation of warm dense matter

Warm dense matter (WDM) -- an exotic state of highly compressed matter -- has attracted high interest in recent years in astrophysics and for dense laboratory systems. At the same time, this state is extremely difficult to treat theoretically. This is due to the simultaneous appearance of quantum degeneracy, Coulomb correlations and thermal effects, as well as the overlap of plasma and condensed phases. Recent breakthroughs are due to the successful application of density functional theory (DFT) methods which, however, often lack the necessary accuracy and predictive capability for WDM applications. The situation has changed with the availability of the first \textit{ab initio} data for the exchange-correlation free energy of the warm dense uniform electron gas (UEG) that were obtained by quantum Monte Carlo (QMC) simulations, for recent reviews, see Dornheim \textit{et al.}, Phys. Plasmas \textbf{24}, 056303 (2017) and Phys. Rep. \textbf{744}, 1-86 (2018). In the present article we review recent further progress in QMC simulations of the warm dense UEG: namely, \textit{ab initio} results for the static local field correction $G(q)$ and for the dynamic structure factor $S(q,\omega)$. These data are of key relevance for the comparison with x-ray scattering experiments at free electron laser facilities and for the improvement of theoretical models. In the second part of this paper we discuss simulations of WDM out of equilibrium. The theoretical approaches include Born-Oppenheimer molecular dynamics, quantum kinetic theory, time-dependent DFT and hydrodynamics. Here we analyze strengths and limitations of these methods and argue that progress in WDM simulations will require a suitable combination of all methods. A particular role might be played by quantum hydrodynamics, and we concentrate on problems, recent progress, and possible improvements of this method.
Convergence of Opinion Diffusion is PSPACE-complete

We analyse opinion diffusion in social networks, where a finite set of individuals is connected in a directed graph and each simultaneously changes their opinion to that of the majority of their influencers. We study the algorithmic properties of the fixed-point behaviour of such networks, showing that the problem of establishing whether individuals converge to stable opinions is PSPACE-complete.
Monetary Policy and Wealth Inequalities in Great Britain: Assessing the role of unconventional policies for a decade of household data

This paper explores whether unconventional monetary policy operations have redistributive effects on household wealth. Drawing on household balance sheet data from the Wealth and Asset Survey, we construct monthly time series indicators on the distribution of different asset types held by British households for the period that the monetary policy switched as the policy rate reached the zero lower bound (2006-2016). Using this series, we estimate the response of wealth inequalities on monetary policy, taking into account the effect of unconventional policies conducted by the Bank of England in response to the Global Financial Crisis. Our evidence reveals that unconventional monetary policy shocks have significant long-lasting effects on wealth inequality: an expansionary monetary policy in the form of asset purchases raises wealth inequality across households, as measured by their Gini coefficients of net wealth, housing wealth, and financial wealth. The evidence of our analysis helps to raise awareness of central bankers about the redistributive effects of their monetary policy decisions.
Grouping of contracts in insurance using neural networks

ABSTRACT Despite the high importance of grouping in practice, there exists little research on the respective topic. The present work presents a framework for grouping and a novel method to optimize model points in life insurance. We introduce a supervised clustering algorithm using neural networks to form a less complex portfolio, alias grouping. In a two-step approach, we first approximate selected characteristics of a portfolio. Next, we nest this estimator in a neural network, such that cluster representatives, alias model points, are calibrated in accordance with their effect on the characteristics of the portfolio. This approach is similar to the work by Horvath, B. , Muguruza, A. & Tomas, M. [(2019). Deep learning volatility. Available on arXiv 1901.09647. ], who focus on the calibration of implied volatility models. Our numerical experiments for term life insurance and defined contribution pension plans show significant improvements, in terms of capturing the characteristics of a portfolio, of the neural network approach over K-means clustering, a common baseline algorithm for grouping. These results are further confirmed by a sensitivity analysis of the investment surplus, where we additionally show the flexibility of the model to include common industry practice.
Chemical vapour deposition diamond single crystals with nitrogen-vacancy centres: a review of material synthesis and technology for quantum sensing applications

Diamond hosts a wide variety of colour centres that have demonstrated outstanding optical and spin properties. Among them, the nitrogen-vacancy (NV) centre is by far the most investigated owing to its superior characteristics, which promise the development of highly sophisticated quantum devices, in particular for sensing applications. Nevertheless, harnessing the potential of these centres mainly relies on the availability of high quality and purity diamond single crystals that need to be specially designed and engineered for this purpose. Plasma assisted chemical vapour deposition (CVD) has become a key enabling technology in this field of research. Nitrogen can indeed be directly doped in situ into a high crystalline quality diamond matrix in a controlled way, allowing the production of single isolated centres or ensembles that can potentially be integrated into a device. In this paper we will provide an overview of the requirements for synthesizing ‘quantum-grade’ diamond films using CVD. These include the reduction of impurities and surrounding spins that limit coherence times, the control of NV density in a wide range of concentrations as well as their spatial localization within the diamond. Enhancing the charge state and preferential orientation of the colour centres is also discussed. These improvements in material fabrication have contributed to positioning diamond as one of the most promising solid-state quantum systems and the first industrial applications in sensing are just starting to emerge.
Neutron lifetime beam anomaly and possible explanation

The review of experimental measurements of neutron lifetime is presented. Latest measurements with gravitational trap (PNPI NRC KI) and magnetic trap (LANL, USA) confirmed the result obtained by PNPI group in 2005. The results of measurements performed using UCN storing method are in good agreement; however, there is a significant discrepancy at 3.6{\sigma} (1% of decay probability) level with beam method experiment. The latest most accurate measurements of the neutron decay asymmetry and neutron lifetime measurements by storage method are in agreement within the Standard Model. This article discusses the possible causes of discrepancy in the measurements of the neutron lifetime. The most probable cause, apparently, is the loss of protons in beam method experiment during storage in a magnetic trap due to charge exchange collisions of protons with the residual gas. The proton becomes neutral and leaves the trap, which leads to a decrease in the number of registered protons, i.e. to a decrease in the probability of neutron decay or to an increase in the measured neutron lifetime.
Speeding up Generalized PSR Parsers by Memoization Techniques

Predictive shift-reduce (PSR) parsing for hyperedge replacement (HR) grammars is very efficient, but restricted to a subclass of unambiguous HR grammars. To overcome this restriction, we have recently extended PSR parsing to generalized PSR (GPSR) parsing along the lines of Tomita-style generalized LR parsing. Unfortunately, GPSR parsers turned out to be too inefficient without manual tuning. This paper proposes to use memoization techniques to speed up GPSR parsers without any need of manual tuning, and which has been realized within the graph parser distiller Grappa. We present running time measurements for some example languages; they show a significant speed up by some orders of magnitude when parsing valid graphs. But memoization techniques do not help when parsing invalid graphs or if all parses of an ambiguous input graph shall be determined.
Distributed Fixed Point Methods with Compressed Iterates

We propose basic and natural assumptions under which iterative optimization methods with compressed iterates can be analyzed. This problem is motivated by the practice of federated learning, where a large model stored in the cloud is compressed before it is sent to a mobile device, which then proceeds with training based on local data. We develop standard and variance reduced methods, and establish communication complexity bounds. Our algorithms are the first distributed methods with compressed iterates, and the first fixed point methods with compressed iterates.
Validating scattering-induced (sub)millimetre disc polarization through the spectral index, wavelength-dependent polarization pattern, and polarization spectrum: the case of HD 163296

A number of young circumstellar discs show strikingly ordered (sub)millimetre polarization orientations along the minor axis, which is strong evidence for polarization due to scattering by ∼0.1 mm-sized grains. To test this mechanism further, we model the ALMA dust continuum and polarization data of HD 163296 using radmc-3d. We find that scattering by grains with a maximum size of 90 μm simultaneously reproduces the polarization observed at Band 7 and the unusually low spectral index (α ∼ 1.5) between Bands 7 and 6 in the optically thick inner disc as a result of more efficient scattering at the shorter wavelength. The low spectral index of ∼2.5 inferred for the optically thin gaps is reproduced by the same grains, as a result of telescope beam averaging of the gaps (with an intrinsic α ∼ 4) and their adjacent optically thick rings (where α ≲ 2). The tension between the grain sizes inferred from polarization and spectral index disappears because the low α values do not require large mm-sized grains. In addition, the polarization fraction has a unique azimuthal variation: higher along the major axis than the minor axis in the gaps, but vice versa in the rings. We find a rapidly declining polarization spectrum (with p ∝ λ−3 approximately) in the gaps, which becomes flattened or even inverted towards short wavelengths in the optically thick rings. These contrasting behaviours in the rings and gaps provide further tests for scattering-induced polarization via resolved multiwavelength observations.
A robust, template-free approach to precise radial velocity extraction

Doppler spectroscopy is a powerful tool for discovering and characterizing exoplanets. For decades, the standard approach to extracting radial velocities (RVs) has been to cross-correlate observed spectra with a weighted template mask. While still widely used, this approach is known to suffer numerous drawbacks, and so in recent years increasing attention has been paid to developing new and improved ways of extracting RVs. In this proof-of-concept paper, we present a simple yet powerful approach to RV extraction. We use Gaussian processes to model and align all pairs of spectra with each other; we combine the pairwise RVs thus obtained to produce accurate differential stellar RVs, without constructing any template. Doing this on a highly localized basis enables a data-driven approach to identifying and mitigating spectral contamination, even without the input of any prior astrophysical knowledge. We show that a crude implementation of this method applied to an inactive standard star yields RVs with comparable precision to and significantly lower rms variation than RVs from industry-standard pipelines. Though amenable to numerous improvements, even in its basic form presented here our method could facilitate the study of smaller planets around a wider variety of stars than has previously been possible.