Discontinuous Variation Research Articles

FORECASTING THE REALIZED VOLATILITY OF ISLAMIC EQUITIES USING MULTIVARIATE HAR-TYPE MODELS

This study proposes nine multivariate intraday models using various realized variation measures with the aim to improve volatility forecasting in the Islamic stock market in Malaysia using a dataset from 1st April 2008 to 31st March 2018. The findings show that considering independently the jump-robust realized volatility, additional daily jump realized volatility, and continuous and discontinuous jump sample path variations improved the in-sample predictive regressions compared to using the standard realized volatility. For the out-of-sample volatility forecasts evaluation, it is observed that the volatility models that disentangled the realized volatility into its continuous and discontinuous jump components have outperformed the rest of the proposed models. This is because both the continuous and discontinuous variation of returns exhibit distinctive substantial information in yielding the final volatility dynamic and thus should be modeled disjointedly. However, the empirical results suggest that the simple autoregressive specification using the standard realized volatility is often performing better or as well as the new extension models. Lastly, this study may provide useful insight in portfolio management, risk assessment, and asset pricing, particularly in the Shariah-compliant equities.

A simple method for mechanical analysis of pressurized functionally graded material thick-walled cylinder

The complex function method is employed to establish a mechanical model for pressurized thick-wall cylinders made of functionally graded materials (FGM). This model is applicable to all radial varying modes of material properties, including both continuous and discontinuous variations in Young’s modulus and Poisson’s ratio. The main concept behind this mechanical model involves dividing the thick-walled cylinder into concentric thin cylinders, each equipped with a pair of analytical functions representing stress functions. By imposing continuity conditions between adjacent thin cylinders and considering the stress boundary conditions of the entire structure, all unknown forms of analytical functions can be determined. Subsequently, by establishing the correspondence relationship between these analytical functions and stress or displacement, it becomes possible to solve for the stress or displacement at any radial position within the thick-walled cylinder. Through comparison and verification against the numerical simulation results, it can demonstrate that as long as the differential scale is sufficiently small, high accuracy can be achieved in the final result. In other words, solutions obtained for multi-layered hollow cylinder converge toward those obtained for continuously graded thick-walled cylinder. Notably, by starting from the level of stress function and avoiding complex differential and integral equations, a linear equation system can provide information on stress and displacement distributions along the radial direction. Therefore, compared to other solving methods available, this proposed approach offers simplicity and applicability.

Role of Provenance Trials in the Study of Population Differentiation

Wide distribution of many Linnean species across climatic, edaphic and biotic barriers may be either due to a wide ecological amplitude of the species as such, or to the presence of a number of distinct local populations, well adapted to the respective ecoclimates. These populations may show continuous variation along an envirormental gradient (ecocline) or discontinuous variation (ecotypes). The morphological or physiological adaptive characters are genetically fixed. Although a number of genecological techniques have been developed in the recent past, to differentiate such ecologic populations, the provenance trial technique has gained much importance. In the present communication the technique as well as some important results obtained through its use, both within and outside India, have been briefly discussed.

Spectral Characteristics and Displacement Sensing of U-Shaped Single-Mode-Multimode-Single-Mode Fiber Structure.

The U-shaped fiber configuration represents the elementary form of micro-displacement sensing, characterized by its exceptional freedom and flexibility. The study proposes the U-shaped bent single-mode-multimode-single-mode (SMS) fiber structure that integrates the multimode interference (MMI) effect for enhanced mode dispersion and the Mach-Zönder interference (MZI) effect for spectral sensitivity improvement. The transmission spectral properties of the U-shaped SMS fiber structure with a bent radius over 1 cm are experimentally measured as the change in displacement varied within the range of 5 mm in this work. As the radius decreases, the spectrum shows redshift, which is related to the central wavelength of the peak or dips-a smaller wavelength results in a stronger redshift for the same displacement change. The average sensitivity of micro-displacement measurement within a range of 5 mm is 5.41 pm/μm, and the linearity is 99.62%. The maximum sensitivity of U-shaped SMS fiber structure is 34.46 pm/μm, with the minimum displacement change of approximately 5.804 nm. The transmission spectral properties of the U-shaped SMS fiber structure within the ranges of 50 μm, 500 μm, and 5 mm are experimentally measured in this work. This experiment observed a relatively uniform spectral drift pattern in a large range of micro-displacement sensing. The measurement range is limited by the limited spectral range of the light source and the discontinuous variation in the effective refractive index. This provides an experimental reference for further understanding the characteristics of U-shaped fiber structures and applying its application in micro-displacement sensing.

Sound absorption mechanism of underwater anechoic coating with spherical cavities

Abstract An axisymmetric theoretical model is simplified to investigate sound absorption in the underwater anechoic coating with spherical cavities. An empirical equation is put forward to predict the frequency at the first absorption peak. The sound absorption mechanism of viscoelastic solid with cavity is clarified by the power analysis method. The quantitative analysis of viscoelastic power dissipation on sound energy provides a new idea for the structural topology optimization of anechoic coatings. These formulas are given to calculate the dissipation power of viscoelastic solid. The dependence of sound absorption performance of the anechoic coating upon radius and position of single or two spherical cavities of the unit cell is analyzed in detail. The study provides guidance for the design of anechoic coatings with cavities.

Depth Map Super-Resolution Based on Semi-Couple Deformable Convolution Networks

Depth images obtained from lightweight, real-time depth estimation models and consumer-oriented sensors typically have low-resolution issues. Traditional interpolation methods for depth image up-sampling result in a significant information loss, especially in edges with discontinuous depth variations (depth discontinuities). To address this issue, this paper proposes a semi-coupled deformable convolution network (SCD-Net) based on the idea of guided depth map super-resolution (GDSR). The method employs a semi-coupled feature extraction scheme to learn unique and similar features between RGB images and depth images. We utilize a Coordinate Attention (CA) to suppress redundant information in RGB features. Finally, a deformable convolutional module is employed to restore the original resolution of the depth image. The model is tested on NYUv2, Middlebury, Lu, and a Real-Sense real-world dataset created using an Intel Real-sense D455 structured-light camera. The super-resolution accuracy of SCD-Net at multiple scales is much higher than that of traditional methods and superior to recent state-of-the-art (SOTA) models, which demonstrates the effectiveness and flexibility of our model on GDSR tasks. In particular, our method further solves the problem of an RGB texture being over-transferred in GDSR tasks.

Generalized volume-complexity for RN-AdS black hole

The connection between quantum information and quantum gravity has captured the imagination of physicists. Recently, a broad new class of gravitational observables have been proposed to provide new possibilities for holographic complexity [1], which is an extension of volume in the Complexity=Volume proposal. In this paper, we investigate generalized volume-complexity for the 4-dimensional Reissner-Nordström-AdS black hole. These new gravitational observables satisfy the characteristic of the thermofield double state, i.e., they grow linearly in time on the late stage. We find that there are multiple extremal hypersurfaces anchored at a certain boundary time. In other words, for the same boundary time, more than one gravitational observable (generalized volume-complexity) can exist in the bulk. The size relationship of the gravitational observables on the two hypersurfaces changes over time. This will result in the substitution of the maximum extreme hypersurface which is dual to the complexity of the thermofield double state. We call the time when one hypersurface replaces another to become the largest extreme hypersurface the turning time τturning. That is, a hypersurface dual to the complexity of the thermofield double state defined on the boundary jumps from one branch to another. This discontinuous jump is highly reminiscent of a phase transition, and the turning time denotes the moment at which this phase transition occurs. Our findings propose a discontinuous variation in bulk physics that is dual to the complexity of the thermofield double state defined on the boundary.

Simulation of heat conduction in complex domains of multi-material composites using a meshless method

Several engineering applications involve complex materials with significant and discontinuous variations in thermophysical properties. These include materials for thermal storage, biological tissues, etc. For such applications, numerical simulations must exercise care in not smearing the interfaces by interpolating variables across the interfaces of subdomains. In this paper, we describe a high accuracy meshless method that uses domain decomposition and cloud-based interpolation of scattered data to solve heat conduction in such situations. The method is applicable to both steady state and transient problems. However, we have considered here only steady state heat conduction in complex domains. The polyharmonic spline (PHS) function with appended polynomial of prescribed degree is used for discretization. Flux balance condition must be satisfied at the interface points and the clouds of interpolation points are restricted to be within respective domains. Compared with previously proposed meshless algorithms with domain decomposition, the cloud-based interpolations are numerically better conditioned, and achieve high accuracy through the appended polynomial. The accuracy of the algorithm is demonstrated in several two and three dimensional problems using manufactured solutions with sharp discontinuity in thermal conductivity. Subsequently, we demonstrate the applicability of the algorithm to solve heat conduction in complex domains with practical boundary conditions and internal heat generation. Systematic computations with varying conductivity ratios, interpoint spacing and polynomial degree are performed to investigate the accuracy of the algorithm.

Topographic variations of mantle transition zone discontinuities in the Java subduction zone and adjacent regions from receiver function analyses

An unprecedented number of broadband seismic data from 165 stations were utilized to constrain the topographic variations in seismic discontinuities at the top and bottom of the mantle transition zone (MTZ) in the Java subduction zone. After moveout corrections under a nonplane wavefront assumption and time-to-depth conversions based on the IASP91 Earth model, the depth undulations of two discontinuities that border the MTZ (d410 and d660) were obtained by stacking P receiver functions that were grouped into circular bins with a radius of 1°. The apparent depths exhibit systematically spatial variations that range from 385 to 427 km for the d410 and 608 to 700 km for the d660, which result in a MTZ thickness of 217–309 km. The mean values are 406 ± 12, 665 ± 19, and 258 ± 18 km, suggesting thicker than normal MTZ by an average of 8 km. The major factor that accounts for the systematic depth variations across the study area originates from the subducted slab that perturbs the entirety of the MTZ, which induces a negative thermal anomaly, high velocity zone, and abnormal water presence concentrated in the lower MTZ of western Java. In Lombok and Sumbawa Islands, after the thermal and velocity heterogeneities from the subducted slab were considered, the remnant d660 uplift is found due to a significant thermal anomaly with a magnitude of up to +200 K near the d660. In eastern Java and adjacent regions, advective thermal upwelling associated with toroidal mantle flow that traversed a slab window in central Java induces a low velocity anomaly with a magnitude that is greater than the high velocity anomaly caused by the subducted slab, which apparently depressed the d410 and d660 by the same amount.

From dissipationless to normal diffusion in the easy-axis Heisenberg spin chain

The anomalous spin diffusion of the integrable easy-axis Heisenberg chain originates in the ballistic transport of symmetry sectors with nonzero magnetization. Ballistic transport is replaced by normal dissipative transport in all magnetization sectors upon introducing the integrability-breaking perturbations, including external driving. Such behavior implies that the diffusion constant obtained for the integrable model is relevant for the spread of spin excitations but not for the spin conductivity. We present numerical results for closed systems and driven open systems, indicating that the diffusion constant shows a discontinuous variation as the function of perturbation strength.

A deep learning-based network for the simulation of airborne electromagnetic responses

SUMMARYAirborne electromagnetic (AEM) method detects the subsurface electrical resistivity structure by inverting the measured electromagnetic field. AEM data inversion is extremely time-consuming when huge volumes of observational data are involved. Forward modelling is an essential part and represents a large proportion of computational cost in the inversion process. In this study, we develop an AEM simulator using deep learning as a computationally efficient alternative to accelerate 1-D forward modelling. Inspired by Google's neural machine translation, our AEM simulator adopts the long short-term memory (LSTM) modules with an encoder–decoder structure, combining the advantages in time-series regression and feature extraction. The well-trained LSTM network describes directly the mapping relationship between resistivity models with transceiver altitudes and time-domain AEM signals. The prediction results of the test set show that 95 per cent of the relative errors at most sampling points fall in the range of ±5 per cent, with average values within the range of ±0.5 per cent, indicating an overall prediction accuracy. We investigate the effects of the distributions of both resistivity and transceiver altitude in the training set on the prediction accuracy. The LSTM-based AEM simulator can effectively handle the resistivity characteristics involved in the training set and yields great sensitivity to the variations of transceiver altitudes. We also examine the adaptability of our AEM simulator for discontinuous resistivity variations. Synthetic tests indicate that the application effect of the AEM simulator relies on the completeness of the training samples and suggest that enriching the sample diversity is necessary to ensure the prediction accuracy, in cases of observation environments dominated by extreme transceiver altitudes or under-represented geological features. Furthermore, we discuss the influence of network configuration on its accuracy and computational efficiency. Our simulator can deliver ∼13 600 1-D forward modelling calculations within 1 s, which significantly improves the simulation efficiency of AEM data.

Is there a casual relation between air pollution and dementia?

Dementia has been cited as a critical public health risk in the contemporary world, while few empirical researchers try to reveal the casual relationship between air pollutant concentrations (APCs) and dementia, especially given the increasing prevalence of air pollution on a global scale. Accordingly, this paper tries to infer the causal relationship between APCs and dementia. The 59,605 valid data was compiled through a combination of the statistic from the China Family Panel Study, China Environmental Statistics Yearbook, World Meteorological Association and China National Bureau of Statistics. The RD design of this study utilizes the discontinuous variation in APCs and dementia as one crosses the Huai River boundary, which is an arbitrary heating policy that causes the significant difference in APCs between the north and south of China. We used stata17.0 to analyze the data. The results of the RD regression indicated that a 100 μ g/m3 rise in APCs led to an increase of 42.4% in the hazard ratio of suffering dementia (Coeff=-0.58, SD= 0.23, P < 0.05). Meanwhile, heterogeneous models revealed that the hazard ratio of suffering dementia by APCs was more significant in the older compared to younger (coeff= 1.35 vs coeff= 1.55, P < 0.05), male compared to female (coeff= 1.62 vs coeff= 0.71, P < 0.05), smoking compared to non-smoke (coeff= 2.12 vs coeff= 0.93, P < 0.05), and thin groups compared to medium and obesity (coeff= 2.05 vs coeff= 1.22, coeff= 1.28, P < 0.05). In addition, the O3 and SO2 were the air pollutants with the highest (coeff= 1.54, P < 0.05) and lowest effects (coeff= 0.81, P < 0.05) on the hazard ratio of suffering dementia among the five APCs, respectively. And the robustness of the results was ensured by changing the RD bandwidth, polynomial order. The results indicated that APCs significantly induced the hazard ratio of suffering dementia of Chinese residents, which provides empirical evidence in supporting the Chinese government to invest more in combating air pollution and ensure the public health of Chinese residents.

Comparative Study of Hematological Profile Variation in Three Trimesters of Pregnancy

Pregnancy or gestation is a physiological condition in which various physiological changes occur. Although pregnancy is a normal phenomenon, several hematological parameters are varied to fulfill the needs of the developing fetus. Sometimes pregnancy becomes complicated due to these changes. Objective: To determine the changes in the hematological profile of healthy pregnant females. Methods: 180 females aged 21 to 34 participated in this study and were placed in a first, second, and third group according to their trimesters, while the fourth group was the control. Each contained 45 females. These women were examined for 12 hematological parameters. Results: When compared with control, it was observed that Hb and RBCs (p-value &lt; 0.05) were lower than control while WBCs (p-value ≤ 0.03) were increased. MCV, MCH and MCHC (p-value &lt; 0.05) showed discontinuous variations along three trimesters. Increase in platelets and neutrophils while a decrease in monocytes, eosinophils, and lymphocytes was observed (p-value &lt;0.02). Conclusions: This study reported several changes in pregnant females' hematological parameters, which helped determine the reference ranges for these parameters. Moreover, pregnant women should have a balanced diet, and their hematological profile should be regularly monitored

General analysis method for global revisit characteristics of satellite constellation with repeating ground tracks

Coverage analysis is an essential process when designing a satellite constellation, and the variations of global revisit characteristics are usually elusive in discontinuous coverage problems. In dealing with this, a general method for analyzing the global revisit characteristics of constellations with repeating ground track orbits is proposed in this paper. Firstly, a two-dimensional map based analytical model for the point coverage of constellations is introduced. Then, the variations of revisit characteristics along both the parallel and meridian are analyzed based on the presented analytical model. Finally, numerical examples are carried out. On the one hand, the proposed analytical model for point coverage is demonstrated to be of high precision. On the other hand, all possible positions where the discontinuous changes of revisit characteristics occur can be analytically obtained, which can reveal the discontinuous variations of revisit characteristics along both the parallel and meridian, and can also ensure that all possible global or regional revisit characteristics are counted for a given constellation. The proposed method can contribute to constellation design and coverage performance analysis.

Morphology and tectonic modification of the Sudbury impact crater: the North Range

The basal contact of the Sudbury Igneous Complex (SIC) on the North Range is interpreted as the outer edge of a meteorite impact crater. Yet, the base of the SIC, and contacts within the SIC, and the overlying Onaping are not circular. Their outline is elliptical. This and other details of the geology of the North Range which have not been fully explained include variations in the width of the metamorphic contact aureole, lateral discontinuous variations in the thickness of the norite and granophyre units, paleomagnetic evidence that the North Range contact of the SIC originally had a dip of around 20°, and differing magnetic fabrics in the norite/gabbro versus the granophyre. Several metrics are used to determine how much of the current outline of the North Range is the result of post-impact deformation and how much is a primary feature related to a meteorite impact. Uplift, rotation, and translation experienced by different segments of the North Range of the SIC are established using dyke azimuth and petrographic analysis of Matachewan diabase dykes, and paleomagnetic and magnetic fabric data analysis. These analyses show (a) the elliptical form of the North Range is a primary feature associated with a near-circular impact crater, (b) some of the original crater wall must have been preserved, and (c) deformation of the North Range is limited to regional scale block rotation producing a southwest dip modified by minor block rotation tilting and vertical displacement associated with north–northwest-trending faults.

Learning Variable Impedance Control for Aerial Sliding on Uneven Heterogeneous Surfaces by Proprioceptive and Tactile Sensing

The recent development of novel aerial vehicles capable of physically interacting with the environment leads to new applications such as contact-based inspection. These tasks require the robotic system to exchange forces with partially-known environments, which may contain uncertainties including unknown spatially-varying friction properties and discontinuous variations of the surface geometry. Finding a solution that senses, adapts, and remains robust against these environmental uncertainties remains an open challenge. This letter presents a learning-based adaptive control strategy for aerial sliding tasks. In particular, the gains of a standard impedance controller are adjusted in real-time by a neural network policy based on proprioceptive and tactile sensing. This policy is trained in simulation with simplified actuator dynamics in a student-teacher learning setup. The real-world performance of the proposed approach is verified using a tilt-arm omnidirectional flying vehicle. The proposed controller structure combines data-driven and model-based control methods, enabling our approach to successfully transfer directly and without adaptation from simulation to the real platform. We attribute the success of the sim-to-real transfer to the inclusion of feedback control in the training and deployment. We achieved tracking performance and disturbance rejection that cannot be achieved using fine-tuned state of the art interaction control method.

Flocculation of suspended particles during estuarine mixing in the Changjiang estuary-East China Sea

Flocculation, triggered during estuarine mixing plays an important role in land-to-sea interactions and is a fundamental topic in near-shore oceanographic studies. Identifying in situ flocculation in large-river estuaries can be challenging due to the complex seawater circulation and heterogeneous suspended particulate matter (SPM) composition in these areas. In this study, three cruises were conducted in the Changjiang (Yangtze) River Estuary and the adjacent area in March, May, and July 2016. Vertical profiles of SPM total volume, mean size, and size spectra were determined using laser in situ scattering and transmissometry (LISST) measurements at 66–89 stations during the three cruises. Stable isotopic ratios of δ 13 C were also measured in the organic carbon contents of SPM collected at the surface, middle, and bottom layers of the sampling stations. LISST data were used to successfully identify the flocculation occurring in the field as well as to trace SPM size spectrum changes before and after the flocculation process. The δ 13 C values were utilized to study the response of biogeochemical parameters to the flocculation. Phytoplankton blooms occurring in May largely resulted in discontinuous variations in LISST parameters and δ 13 C from March to July. Although the pattern of SPM size spectra involved in flocculation differed among seasons, flocculation processes were always contributed by smaller particles with sizes of several tens of μm aggregating into larger ones >300 μm. Using LISST and δ 13 C measurements combined greatly improved our understanding of SPM dynamics in estuarine and coastal areas where estuarine flocculation was a critical component. • The SPM in the Changjiang Estuary could be classified into three sources. • Three sources were terrestrial sediments, biological particles, and flocculation. • LISST and OBS data could identify flocculation occurring in large-river estuaries. • The δ 13 C variations were more controlled by seasonal or spatial factors. • A combination of LISST and δ 13 C measurements could elucidate SPM dynamics.

Do Class Size Reductions Protect Students from Infectious Diseases?

We evaluate the causal effect of class size (number of students in a classroom) on incidence of class closure due to the flu, as an outcome of an infectious disease epidemic. For identification of causal effects, we apply a regression discontinuity design using discontinuous variation of class sizes, around the class size cap set by regulation, to administrative data of public primary and middle school students in one of the largest municipalities within the Tokyo metropolitan area from 2015 to 2017. Most classrooms in Japan are constructed in accordance with a standard of classroom area, 63 square meters; class size reduction improves social distancing among students in a classroom. We find that class size reduction is effective in reducing class closures due to the flu: a one-unit reduction of class size decreases class closure by about 5 percent. Additionally, forming small classes with 27 students at most, satisfying the social distancing of 1.5 meters recommended to prevent droplet infection including influenza and COVID-19, reduces class closure by about 90 percent. Moreover, we find that the older the students, the larger the effects of class size reduction. Our findings provide evidence for the effectiveness of social distancing policy in primary and middle schools to protect students from droplet infectious disease spread, including COVID-19.

Multistability in Coupled Nonlinear Metasurfaces

Multistability, namely, the property of obtaining different outputs depending on the past values of the input, is the key effect behind memory components in a variety of electronic, chemical, biological, and quantum systems. Two electromagnetic metasurfaces, with nonlinear admittances of Kerr type, are found to manifest significant multistability regarding their transmissivity. Such a feature is owed to the discontinuous variation of the response once the nature of the material changes from dielectric to plasmonic and vice versa, occurring at different levels of incoming power. The conditions for giving sizable hysteresis loops, with respect to either the input intensity or its operational wavelength, are determined. The reported results are expected to assist the modeling of nonlinear metasurfaces and open unexplored opportunities toward the efficient design of photonic memory elements.

TCB-spline-based Image Vectorization

Vector image representation methods that can faithfully reconstruct objects and color variations in a raster image are desired in many practical applications. This article presents triangular configuration B-spline (referred to as TCB-spline)-based vector graphics for raster image vectorization. Based on this new representation, an automatic raster image vectorization paradigm is proposed. The proposed framework first detects sharp curvilinear features in the image and constructs knot meshes based on the detected feature lines. It iteratively optimizes color and position of control points and updates the knot meshes. By using collinear knots at feature lines, both smooth and discontinuous color variations can be efficiently modeled by the same set of quadratic TCB-splines. A variational knot mesh generation method is designed to adaptively introduce knots and update their connectivity to satisfy the local reconstruction quality. Experiments and comparisons show that our framework outperforms the existing state-of-the-art methods in providing more faithful reconstruction results. In particular, our method is able to model undetected features and subtle or complicated color variations in-between features, which the previous methods cannot handle efficiently. Our vectorization representation also facilitates a variety of editing operations performed directly over vector images.