Instantaneous Transformations Research Articles

Instantaneous formation of covalently bonded diamond–graphite–graphene with synergistic properties

Diamond and graphene are the most widely used carbon allotropes and offer great potential for developing mechanical, electronic, energy-storage, and sensor applications. Their combination, especially interfacial covalent bonding, can impart excellent properties. However, achieving interfacial covalent bonding with superior performance using flexible and low-power strategies remains challenging. This study developed a novel instantaneous transformation method from diamond to graphene to prepare a new covalent structure of diamond–nano-graphite–graphene (CDGG). That is, a nanosecond-pulse laser induces sp3-to-sp2 instantaneous transformations from diamond to graphite in air, and the subsequent mechanical cleavage overcomes the weak van der Waals forces to achieve the final transformation of graphite to graphene. First, the key factors influencing laser-induced graphitization and mechanical cleavage were investigated, and a covalent carbon structure with multidirectional graphene was obtained. Furthermore, the mechanisms encompassing the lattice transformation, interface relationships, transformation time, and interface bonding were elucidated. The obtained new structure synergized the excellent properties of diamond, nano-graphite, and graphene, exhibiting superior lubrication, mechanochemical wear resistance, durability, and load-capacity. Compared to polished diamond, the obtained structure exhibited a significant decrease in the stable coefficient of friction by 49–59 % and a reduction of more than one order of magnitude in the relative wear rate under high friction against ferrous metals with a normal load of 1–9 N. Even under a heavy load of 100 N, it still exhibited superior lubrication and mechanochemical wear resistance. Finally, the preparation and patterning of covalent carbon structures were achieved on various diamond surfaces with high efficiency, environmental friendliness, and low power. This study is expected to broaden the scope of developing and applying diamond, diamond films, and graphene devices.

Fourier Transform with Noisy Image

The noise is a major problem in computer vision because it affects image quality and impede the illation. In this paper, we suggest method works on instantaneous transformations that are used in the analysis of the signals representing the image and the frequencies they contain, through which the image can be retrieved or the areas containing the noise where the image is transformed within the complex range and then the original image. Result of this paper are 0.9804 in case SSIM measure and 32.9850 in case PSNR measure.

A Systematic and Comprehensive Geometric Framework for Multiphase Power Systems Analysis and Computing in Time Domain

This paper presents a new framework for a systematic and thorough generalization of the most well-known instantaneous transformations used in electrical engineering for power systems analysis and computing through geometric principles based on the language of Geometric Algebra. By introducing the concepts of Kirchhoff Vector and Kirchhoff Subspace, a new generalized transformation is presented. Thus, it is shown how the Clarke, Park or Hyper-Space vector transformations (widely used in electrical engineering) are particular cases of this unifying framework. Moreover, a generalization to an arbitrary number of phases is achieved. In order to be as close as possible to the geometrical intuition, all the underlying ideas are presented by means of spatial-like conceptualizations, substantiated by their corresponding algebraic formulation. This proposal has potential uses in a wide range of power system applications such as electrical machines, current compensation, power quality, electronic converters or transmission lines. Preliminary results show the superior efficiency of the method compared to matrix methods. Some real-world examples have been included to highlight the potential use of the method.

The entropy of chaotic transitions of EEG phase growth in bipolar disorder with lithium carbonate

The application of chaos measures the association of EEG signals which allows for differentiating pre and post-medicated epochs for bipolar patients. We propose a new approach on chaos necessary for proof of EEG metastability. Shannon entropies of concealed patterns of Schwarzian derivatives from absolute instantaneous frequency transformations of EEG signals after Hilbert transform are compared and found significantly statistically different between pre and post-medication periods when fitted to von Bertalanffy’s functions. Schwarzian dynamics measures was compared at first baseline and then at the end of the first hour of one dose 300 mg lithium carbonate intake for the same subject in depressive patients. With an application of Schwarzian derivative on the prediction of von Bertalanffy’s models, integration and segregation of phase growth orbits of neural oscillations can be understood as an influence of chaos on the mixing of frequencies. A phase growth constant parameter was performed to determine the bifurcation parameter of von Bertalanffy’s model at each given non-overlapped EEG segment. Schwarzian derivative was sometimes very close positive near the origin but stayed negative for most of the number of segments. Lithium carbonate changed the chaotic invariants of the EEG Schwarzian dynamics and removed sharp boundaries in the bipolar spectrum.

EMD: Empirical Mode Decomposition and Hilbert-Huang Spectral Analyses in Python.

The Empirical Mode Decomposition (EMD) package contains Python (>=3.5) functions for analysis of non-linear and non-stationary oscillatory time series. EMD implements a family of sifting algorithms, instantaneous frequency transformations, power spectrum construction and single-cycle feature analysis. These implementations are supported by online documentation containing a range of practical tutorials.

Author Correction: Instantaneous rock transformations in the deep crust driven by reactive fluid flow

Author Correction: Instantaneous rock transformations in the deep crust driven by reactive fluid flow

Instantaneous rock transformations in the deep crust driven by reactive fluid flow

Fluid–rock interactions are a fundamental component of geodynamic processes. They link mass and energy transfer with large-scale tectonic deformation and drive mineral deposit formation, carbon sequestration and rheological changes of the lithosphere. Spatial evidence indicates that fluid–rock interactions operate on length scales that range from the grain boundary to tectonic plates, but the timescales of regional fluid–rock interactions remain essentially unconstrained. Here we present observations from an exceptionally well-exposed fossil hydrothermal system from an ophiolite sequence in northern Norway that we use to inform a multielement advection–diffusion–reaction transport model. We calculated the velocity of the fluid-driven reaction fronts and found that they can propagate at up to 10 cm per year, equivalent to the fastest tectonic plate motion and mid-ocean-ridge spreading rates. Propagation through the low-permeability rocks of the mid-crust is facilitated by a transient, reaction-induced permeability increase. We conclude that large-scale fluid-mediated rock transformations in continental collision and subduction zones occur on timescales of tens of years when reactive fluids are present. We infer that natural carbon sequestration, ore deposit formation and transient and long-term petrophysical changes of the crust proceed instantaneously, from a geological perspective. Fluid-mediated reaction fronts in rocks can propagate up to 10 centimetres per year, according to a transport model informed by observations of an ophiolite in Norway.

Transforming Complexity to Simplicity: Protein-Like Nanotransformer for Improving Tumor Drug Delivery Programmatically.

It was difficult for nanodrugs to simultaneously meet the contradictory requirements of prolonged circulation time, augmented cellular uptake, rapid lysosome escape, precise drug release, and tumor penetration in tumor drug delivery. We prepared a nanotransformer (DTIG) through assembling doxorubicin, tannic acid, and indocyanine green to overcome this dilemma. Hydrophilic DTIG showed prolonged blood circulation time. Besides, DTIG could be efficiently internalized by tumor cells through transforming into hydrophobic particles in an acidic tumor microenvironment. Subsequently, oversized hydrophobic particles were further formed in acidic lysosomes to escape from it through rupturing the lysosome. These hydrophobic DTIGs could rapidly revert to a smaller hydrophilic nanoassembly and release the payloads in cytoplasm. Similar to denaturation and renaturation of protein, these high-efficiency instantaneous transformations were activated by proton. Besides, photothermal therapy of DTIG promoted drug penetration efficiency in tumor. This optimized drug delivery process of DTIG finally offered potent antitumor efficacy and an obvious advantage on prognosis.

Instant autovaporization as intensification way of classic distillation processes: fundamental and industrial applications

In the present work, the new extraction process of Détente Instantanée Contrôlée DIC was studied, developed, optimized and compared to the conventional hydrodistillation method for the extraction of essential oils of sandalwood. DIC was used as a thermomechanical treatment, DIC subjecting the product to a high-pressure saturated steam. The DIC cycle ends with an abrupt pressure drop towards vacuum, and this instantly leads to an autovaporization of sandalwood volatile compounds. An immediate condensation in the vacuum tank produced a micro-emulsion of water and essential oils. Thus, an ultra-rapid cooling of residual leaves occurred, precluding any thermal degradation. Response surface methodology RSM was used with a 2-parameter 5-level Design of Experiments (DoE).The structure with a slight destruction of cell walls after DIC treatment. The operating parameters (independent variables) were the treatment time t, and the number of pressure drops C, whilst the main response was the extraction of extraction efficiency EE of volatile compounds. RSM Statistical analysis allowed comparing this process with conventional hydrodistillation unit operation in terms of total yields of essential oil. The most important differences between the two essential oils were reflected in the yields, with 1.14 as against 1.23 g EO/100 g of raw matter, and in the extraction time, with 5 min as against 24 hours for respectively the DIC and the hydrodistillation operations. These differences have been previewed through the fundamental analysis based on both concept of thermodynamics of instantaneous transformations and calculation of the volatility as well as on Darcy similar transfer law was used to explain the main results.

Generalized Master Equations Leading to Completely Positive Dynamics.

We provide a general construction of quantum generalized master equations with a memory kernel leading to well-defined, that is, completely positive and trace-preserving, time evolutions. The approach builds on an operator generalization of memory kernels appearing in the description of non-Markovian classical processes and puts into evidence the nonuniqueness of the relationship arising due to the typical quantum issue of operator ordering. The approach provides a physical interpretation of the structure of the kernels, and its connection with the classical viewpoint allows for a trajectory description of the dynamics. Previous apparently unrelated results are now connected in a unified framework, which further allows us to phenomenologically construct a large class of non-Markovian evolutions taking as the starting point collections of time-dependent maps and instantaneous transformations describing the microscopic interaction dynamics.

OPTIMAL HRF AND SMOOTHING PARAMETERS FOR FMRI TIME SERIES WITHIN AN AUTOREGRESSIVE MODELING FRAMEWORK

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

An open-loop controlled active lung simulator for preterm infants

We describe the underlying theory, design and experimental evaluation of an electromechanical analogue infant lung to simulate spontaneous breathing patterns of preterm infants. The aim of this work is to test the possibility to obtain breathing patterns of preterm infants by taking into consideration the air compressibility. Respiratory volume function represents the actuation pattern, and pulmonary pressure and flow-rate waveforms are mathematically obtained through the application of the perfect gas and adiabatic laws. The mathematical model reduces the simulation interval into a step shorter than 1 ms, allowing to consider an entire respiratory act as composed of a large number of almost instantaneous adiabatic transformations. The device consists of a spherical chamber where the air is compressed by four cylinder-pistons, moved by stepper motors, and flows through a fluid-dynamic resistance, which also works as flow-rate sensor. Specifically designed software generates the actuators motion, based on the desired ventilation parameters, without controlling the gas pneumatic parameters with a closed-loop. The system is able to simulate tidal volumes from 3 to 8 ml, breathing frequencies from 60 to 120 bpm and functional residual capacities from 25 to 80 ml. The simulated waveforms appear very close to the measured ones. Percentage differences on the tidal volume waveform vary from 7% for the tidal volume of 3 ml, down to 2.2–3.5% for tidal volumes in the range of 4–7 ml, and 1.3% for the tidal volume equal to 8 ml in the whole breathing frequency and functional residual capacity ranges. The open-loop electromechanical simulator shows that gas compressibility can be theoretically assessed in the typical pneumatic variable range of preterm infant respiratory mechanics.

Uniformly accelerated observer in Moyal spacetime

In Minkowski space, an accelerated reference frame may be defined as one that is related to an inertial frame by a sequence of instantaneous Lorentz transformations. Such an accelerated observer sees a causal horizon, and the quantum vacuum of the inertial observer appears thermal to the accelerated observer, also known as the Unruh effect. We argue that an accelerating frame may be similarly defined (i.e. as a sequence of instantaneous Lorentz transformations) in noncommutative Moyal spacetime, and discuss the twisted quantum field theory appropriate for such an accelerated observer. Our analysis shows that there are several new features in the case of noncommutative spacetime: chiral massless fields in $(1+1)$ dimensions have a qualitatively different behavior compared to massive fields. In addition, the vacuum of the inertial observer is no longer an equilibrium thermal state of the accelerating observer, and the Bose-Einstein distribution acquires $\theta$-dependent corrections.

Thermal stress-focusing effect in a spherical Zirconia inclusion with dynamically transforming strains

Some composite materials, such as Zirconia-toughened ceramics, are remarkable materials which have high strength, a high elastic modulus, and an improved toughness, etc. These good qualities are made possible through the stress-induced phase transformation of composite particles, which is accompanied by an impact cooling. When a spherical inclusion in an infinite elastic domain is suddenly subjected to an instantaneous phase transformation, stress waves occur at the surface of a spherical inclusion at the moment thermal impact is applied. The wave may accumulate at the center and show stress-focusing effects, even though the initial stress may be relatively small. This paper analyzes the thermal stress-focusing effect caused by the instantaneous anisotropic phase transformations in the spherical Zirconia inclusion. By use of ray theory, the numerical results give a clear indication of the mechanism of stress-focusing in an inclusion embedded in an infinite elastic medium.

Order series method for forecasting non‐Gaussian time series

AbstractA new forecasting non‐Gaussian time series method based on order series transformation properties has been proposed. The proposed method improves Yu's method without using Hermite polynomial expansion to process nonlinear instantaneous transformations and provides acceptable forecasting accuracy. Copyright © 2007 John Wiley & Sons, Ltd.

Time refraction and the quantum properties of vacuum

We present the classical and quantum theory of time refraction in a generic nonstationary medium. The classical approach leads to expressions for the temporal refraction coefficient, and the temporal Fresnel laws are given. The quantum formulation leads to the derivation of instantaneous Bogoliubov transformations and the evaluation of the number of photon pairs created from vacuum by the temporal changes in the medium. The influence of boundary conditions, the connection of this model with the dynamical Casimir effect, and radiation from superluminal nonaccelerated optical boundaries is also discussed.

Autocovariance functions of series and of their transforms

Abstract We derive a method to link exactly the autocovariance functions of two arbitrary instantaneous transformations of a time series. For example, this is useful when one wants to derive the autocovariance of the logarithm of a series from the known autocovariance of the original series and, more generally, when one wishes to describe the time-series effects of applying a nonlinear transformation to a process whose properties are known. As an illustration, we provide two corollaries and three examples. The first corollary is on the commonly used logarithmic transformation, and is applied to a geometric auto-regressive (AR) process, as well as to a positive moving-average (MA) process. The second corollary is on the tan −1 (·) transformation which will turn possibly unstable series into stable ones. As an illustration, we obtain the autocovariance function of the tan −1 (·) of an arithmetic AR process. This filter, while always producing a bounded process, preserves the stability/instability distinction of the original series, a feature that can be turned to an advantage in the design of tests. We then present a probabilistic interpretation of the main features of the new autocovariance function. We also provide a mathematical lemma on a general integral which is of independent interest.

Further analysis of official and black market exchange rates in Brazil: data transformations and structural changes

This paper extends the previous results in Bessler and Yu (1994) on the official and black market exchange rates in Brazil. Rather than taking instantaneous data transformations to produce a stable long-run equilibrium relationship as Bessler and Yu did, the possibility of structural changes in the long-run relationship was considered. It is found that the two approaches have quite different implications on the long-run dynamics of the data series. It is claimed that to fully understand the dynamics of the exchange rate data series, it is necessary to consider the possibility of structural change and explicitly model it.

Nonlinear infinite extent interpolation of stationary processes

The problem of minimum mean-square interpolation of discrete time stationary stochastic processes using a system consisting of a finite number p of nonlinear instantaneous transformations followed by a p input-one output infinite extent linear filter is studied. The expressions of the optimal interpolator and of the approximation error are derived and generalize the corresponding relations known in linear interpolation theory. Some extensions, including the estimation problem with several missing observations, are also investigated.

Some generalizations on the algebra of I(1) processes

A number of techniques have recently appeared in the literature utilizing instantaneous nonlinear transformations of stochastic processes. As in economics most variables appear to be nonstationary, it is interesting to investigate the temporal properties of nonlinear transformations of these processes. Using a unified approach based on Hermite polynomials, this paper provides some insight for polynomial, exponential, periodic, and neural-network transformations of first-order integrated processes.