Uniform Penalty inversion of two-dimensional NMR Relaxation data

The inversion of two-dimensional NMR data is an ill-posed problem related to the numerical computation of the inverse Laplace transform. In this paper we present the 2DUPEN algorithm that extends the Uniform Penalty (UPEN) algorithm [Borgia, Brown, Fantazzini, {\em Journal of Magnetic Resonance}, 1998] to two-dimensional data. The UPEN algorithm, defined for the inversion of one-dimensional NMR relaxation data, uses Tikhonov-like regularization and optionally non-negativity constraints in order to implement locally adapted regularization. In this paper, we analyze the regularization properties of this approach. Moreover, we extend the one-dimensional UPEN algorithm to the two-dimensional case and present an efficient implementation based on the Newton Projection method. Without any a-priori information on the noise norm, 2DUPEN automatically computes the locally adapted regularization parameters and the distribution of the unknown NMR parameters by using variable smoothing. Results of numerical experiments on simulated and real data are presented in order to illustrate the potential of the proposed method in reconstructing peaks and flat regions with the same accuracy

Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations

We empirically verify that the market capitalisations of coins and tokens in the cryptocurrency universe follow power-law distributions with significantly different values, with the tail exponent falling between 0.5 and 0.7 for coins, and between 1.0 and 1.3 for tokens. We provide a rationale for this, based on a simple proportional growth with birth & death model previously employed to describe the size distribution of firms, cities, webpages, etc. We empirically validate the model and its main predictions, in terms of proportional growth (Gibrat's law) of the coins and tokens. Estimating the main parameters of the model, the theoretical predictions for the power-law exponents of coin and token distributions are in remarkable agreement with the empirical estimations, given the simplicity of the model. Our results clearly characterize coins as being "entrenched incumbents" and tokens as an "explosive immature ecosystem", largely due to massive and exuberant Initial Coin Offering activity in the token space. The theory predicts that the exponent for tokens should converge to 1 in the future, reflecting a more reasonable rate of new entrants associated with genuine technological innovations

Characterization of structural bone properties through portable single-sided nmr devices: State of the art and future perspectives

Nuclear Magnetic Resonance (NMR) is a well-suited methodology to study bone composition and structural properties. This is because the NMR parameters, such as the T2 relaxation time, are sensitive to the chemical and physical environment of the1H nuclei. Although magnetic resonance imaging (MRI) allows bone structure assessment in vivo, its cost limits the suitability of conventional MRI for routine bone screening. With difficulty accessing clinically suitable exams, the diagnosis of bone diseases, such as osteoporosis, and the associated fracture risk estimation is based on the assessment of bone mineral density (BMD), obtained by the dual-energy X-ray absorptiometry (DXA). However, integrating the information about the structure of the bone with the bone mineral density has been shown to improve fracture risk estimation related to osteoporosis. Portable NMR, based on low-field single-sided NMR devices, is a promising and appealing approach to assess NMR properties of biological tissues with the aim of medical applications. Since these scanners detect the signal from a sensitive volume external to the magnet, they can be used to perform NMR measurement without the need to fit a sample inside a bore of a magnet, allowing, in principle, in vivo application. Techniques based on NMR single-sided devices have the potential to provide a high impact on the clinical routine because of low purchasing and running costs and low maintenance of such scanners. In this review, the development of new methodologies to investigate structural properties of trabecular bone exploiting single-sided NMR devices is reviewed, and current limitations and future perspectives are discussed

Propagator Resolved Transverse Relaxation Exchange Spectroscopy

We use the propagator resolved transverse relaxation exchange technique to look at the movement of fluid in three different types of rock samples. The two pore model previously used to fit molecular exchange simulations to the experimental data is expanded to accommodate the three site exchange seen in two of the samples. Estimated values for pore space characteristics from the simulations were compared to values calculated from X‐Ray CT data of the samples. While discrepancies exist between the NMR and X‐Ray CT results, the molecular exchange behavior estimated from the three samples reflects well with their morphology

Bitcoin: The road to hell is paved with good promises

In this paper, by using econometric techniques we provide evidence that bitcoin exhibited the formation of speculative bubble in 2017. To conceptually rationalize the results, we delve into the extant theoretical approaches developed by Kindleberger's (1978) speculative bubbles and Minsky's (1992) financial instability hypothesis. Certainly, bitcoin has spurred a revolution in payment technology that, if treated cautiously can facilitate financial intermediation and inclusion. Ultimately, whether or not bitcoin constitutes a bubble is a decision for investors as the road to hell is paved with good promises

Gains and losses of coral skeletal porosity changes with ocean acidification acclimation

Ocean acidification is predicted to impact ecosystems reliant on calcifying organisms, potentially reducing the socioeconomic benefits these habitats provide. Here we investigate the acclimation potential of stony corals living along a pH gradient caused by a Mediterranean CO(2) vent that serves as a natural long-term experimental setting. We show that in response to reduced skeletal mineralization at lower pH, corals increase their skeletal macroporosity (features >10 μm) in order to maintain constant linear extension rate, an important criterion for reproductive output. At the nanoscale, the coral skeleton's structural features are not altered. However, higher skeletal porosity, and reduced bulk density and stiffness may contribute to reduce population density and increase damage susceptibility under low pH conditions. Based on these observations, the almost universally employed measure of coral biomineralization, the rate of linear extension, might not be a reliable metric for assessing coral health and resilience in a warming and acidifying ocean

Applicability of the tetrazolium test to coffee seeds with different types and levels of stresses.

For sale or use of coffee seeds after harvest, the coffee grower must have information regarding their initial quality, which must meet the standards established in the Sistema Nacional de Sementes e Mudas (SNSM). However, slow germination of coffee seeds makes it difficult to obtain results from evaluation of the seed physiological quality. An alternative for quick evaluation of coffee seed viability is the tetrazolium test. However, there are still questions regarding the true potential of the test for estimating the quality of seed lots with different levels of quality. The aim of this study was to eval-uate the applicability of the tetrazolium test in estimating the viability of coffee seeds with different types of stress and levels of quality. Seeds of Coffea arabica L. were used, which were placed under the following treatments to obtain different types and levels of stresses: natural processing or fully-washed processing, different times of artificial aging, drying at high temperature, exposure to below-zero (°C) temperature, and storage under conditions without climate control. After obtaining the seed lots, the seeds were evaluated physiologically by the tetrazolium test and the germination test. The tetrazolium test overestimates the potential for production of normal seedlings of seed lots of Coffea arabica L. that have the lowest level of quality. The discrepancies between the results of viability in the tetrazolium test and the germination test vary according to the level of physiological quality and the type of stress the coffee seeds were under. We emphasize that the tetrazolium test in the SNSM as an alternative to the germination test in ascertaining the quality of coffee seeds must be reviewed since the results may significantly differ from the ability to produce normal seedlings

Forecasting robust value-at-risk estimates: Evidence from UK banks

In this paper, we present a novel approach for forecasting Value-at-Risk (VaR) by combining a Bayesian GARCH(1,1) model with Student's-t distribution for the underlying volatility models, vine copula functions to model dependence, and peaks-over-threshold (POT) method of extreme value theory (EVT) to model the tail behaviour of asset returns. We further propose a new approach for threshold selection in extreme value analysis, which we call a hybrid method. The empirical results and back-testing analysis show that the model captures VaR quite well through periods of calmness and crisis; therefore, it is suitable for use as a measure of risk. Our results also suggest that with a correct implementation of the VaR model, Basel III is not needed

Evaluating the Sustainability of a Small-Scale Low-Input Organic Vegetable Supply System in the United Kingdom

www.mdpi.com/journal/sustainabilit

Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model

In this paper, we propose a model for forecasting Value-at-Risk (VaR) using a Bayesian Markov-switching GJR-GARCH(1,1) model with skewed Student’s-t innovation, copula functions and extreme value theory. A Bayesian Markov-switching GJR-GARCH(1,1) model that identifies non-constant volatility over time and allows the GARCH parameters to vary over time following a Markov process, is combined with copula functions and EVT to formulate the Bayesian Markov-switching GJR-GARCH(1,1) copula-EVT VaR model, which is then used to forecast the level of risk on financial asset returns. We further propose a new method for threshold selection in EVT analysis, which we term the hybrid method. Empirical and back-testing results show that the proposed VaR models capture VaR reasonably well in periods of calm and in periods of crisis