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Software for a service (SaaS) brings unprecedented benefits to business applications such as cost reduction and productivity. This study aims to understand the behavioral intentions of businesses that are not considering using SaaS, are in the process of evaluating the use of SaaS, are evaluating but not adopting, and planning to evaluate and use SaaS. Data were collected by asking 18 questions from 76 businesses not adopting SaaS and analyzed with One-Way Analysis of Variance (ANOVA). Fisher’s LSD test was used as a post hoc analysis to observe the differences between the groups. The findings showed that those who do not plan to use SaaS and those who evaluate and plan to use SaaS, and those who are in the process of evaluating the use of SaaS and those who plan to use SaaS, differed significantly in their opinions about the perceived advantages and security concerns. On the other hand, it is seen that the decision makers’ support of all non-SaaS adopters and the attitudes of non-SaaS adopters located in different market regions were similar. The research will contribute to informing SaaS providers to ensure business continuity and to produce customized software and applications suitable for the challenges and barriers faced by business operations. [ABSTRACT FROM AUTHOR]

Given a symmetric diffusion process and a jump process on the same underlying space, is there a subordinator such that the jump process and the subordinated diffusion process are comparable? We address this question when the diffusion satisfies a sub-Gaussian heat kernel estimate and the jump process satisfies a polynomial-type jump kernel bounds. Under these assumptions, we obtain necessary and sufficient conditions on the jump kernel estimate for such a subordinator to exist. As an application of our results and the recent stability results of Chen, Kumagai and Wang, we obtain parabolic Harnack inequality for a large family of jump processes. In particular, we show that any jump process with polynomial-type jump kernel bounds on such a space satisfy the parabolic Harnack inequality. [ABSTRACT FROM AUTHOR]

Remote sensing (RS) dehazing is a long-standing topic, as the contrast and clarity of images are seriously reduced in the severe environment. Recent learning-based ways achieve great success in RS dehazing, while these models usually suffer from unusual artifacts, mode collapse, and size limitation. To address these problems, we propose an adaptive region-based diffusion dehazing net (ARDD-Net), which is a novel diffusion-based model toward free-form RS dehazing. To be specific, a guided diffusion process is employed to transform clear RS region parts by adding Gaussian noise repeatedly and then restore the clear ones through a reverse generative procedure. In addition, region-based model is employed to address the free-size images for diffusion model. Furthermore, a cyclic shift (CS) strategy is applied to the inference process in order to avoid the inconsistent effect of certain regions and increase the image harmony. With extensive experiments, we state that our model gets outstanding performances than the comparing methods on both synthetic and real-world RS images. [ABSTRACT FROM AUTHOR]

With the emergence of the online gig economy, computer-based jobs can be completed by gig workers around the world. This raises the question whether the labour market for online gigs is truly boundless as distance no longer matters. Based on gravity models, we investigate the effect of geographical, institutional and cultural distance on almost 30 000 platform hirings between 26 European countries. While we find that online gig platforms are used to off-shore work from high- to low-wage countries, the online gig economy is not boundless as gig workers are still preferably hired from geographically close economies. A common language furthermore facilitates hirings between countries. Interestingly, though, differences in formal and informal institutions hardly affect hiring patterns across countries, suggesting that online platforms create their own institutional framework. We conclude that the online gig economy constitutes neither a boundless nor a frictionless labour market, implying that its promise of creating equal access to job opportunities is exaggerated. [ABSTRACT FROM AUTHOR]

A two-dimensional diffusion process is controlled until it enters a given subset of $ \mathbb{R}^2 $. The aim is to find the control that minimizes the expected value of a cost function in which there are no control costs. The optimal control can be expressed in terms of the value function, which gives the smallest value that the expected cost can take. To obtain the value function, one can make use of dynamic programming to find the differential equation it satisfies. This differential equation is a non-linear second-order partial differential equation. We find explicit solutions to this non-linear equation, subject to the appropriate boundary conditions, in important particular cases. The method of similarity solutions is used.

Graph dynamics for a node-labeled graph is a set of updating rules describing how the labels of each node in the graph change in time as a function of the global set of labels. The underpopulation rule is graph dynamics derived by simplifying the set of rules constituting the Game of Life. It is known that the number of label configurations met by a graph during the dynamic process defined by such rule is bounded by a polynomial in the size of the graph if the graph is undirected. As a consequence, predicting the labels evolution is an easy problem (i.e., a problem in P) in such a case. In this paper, the generalization of the underpopulation rule to signed and directed graphs is studied. It is here proved that the number of label configurations met by a graph during the dynamic process defined by any so generalized underpopulation rule is still bounded by a polynomial in the size of the graph if the graph is undirected and structurally balanced, while it is not bounded by any polynomial in the size of the graph if the graph is directed although unsigned unless P = PSpace.

The objective of this paper is to study a class of zero-sum optimal stopping games of diffusions under a so-called Poisson constraint: the players are allowed to stop only at the arrival times of their respective Poissonian signal processes. These processes can have different intensities, which makes the game setting asymmetric. We give a weak and easily verifiable set of sufficient condition under which we derive a semi-explicit solution to the game in terms of the minimal r-excessive functions of the diffusion. We also study limiting properties of the solutions with respect to the signal intensities and illustrate our main findings with explicit examples. [ABSTRACT FROM AUTHOR]

This paper deals with a nonparametric Nadaraya–Watson (NW) estimator of the drift function computed from independent continuous observations of a diffusion process. Risk bounds on the estimator and its discrete‐time approximation are established. The paper also deals with extensions of the PCO and leave‐one‐out cross‐validation bandwidth selection methods for our NW estimator. Finally, some numerical experiments are provided. [ABSTRACT FROM AUTHOR]

We establish a novel convergent iteration framework for a weak approximation of general switching diffusion. The key theoretical basis of the proposed approach is a restriction of the maximum number of switching so as to untangle and compensate a challenging system of weakly coupled partial differential equations to a collection of independent partial differential equations, for which a variety of accurate and efficient numerical methods are available. Upper and lower bounding functions for the solutions are constructed using the iterative approximate solutions. We provide a rigorous convergence analysis for the iterative approximate solutions, as well as for the upper and lower bounding functions. Numerical results are provided to examine our theoretical findings and the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

Diffusion processes, as fundamental mechanisms for particle movement in systems with different concentrations, are used to describe many real-world physical, chemical, biological, engineering, economic and social phenomena. A diffusion process can be modelled via a fractional-order transfer function with time-delay, where its parameters may be affected by circumstance. Hereupon, this study proposes a pioneer robustness indicator to achieve the phase margin invariance regardless of concurrent uncertainty on different parameters of a diffusion process. Afterwards, an analytical procedure is suggested to tune a Fractional-Order Proportional-Integral-Derivative (FO-PID) controller for a diffusion process, to favourably regulate the values of gain crossover frequency and phase margin, such that the proposed robustness criterion is met. Moreover, the solvability of the problem is analytically investigated. Finally, a numerical simulation on robust temperature control during magnetic local hyperthermia, i.e. a common method to treat cancerous tumours, is presented to validate the efficiency of the paper achievements. [ABSTRACT FROM AUTHOR]

We consider the Dawson–Watanabe superprocess obtained from a spatial motion with sub-Gaussian transition densities on a metric measure space with finite Hausdorff dimension, and examine the dimensions of the range and the set of times when the support intersects a given set, generalising results of Serlet and Tribe. As intermediate results, we prove existence of local times for the superprocess if the spectral dimension of the spatial motion satisfies d s < 4 , and prove that (2 − d s / 2) ∧ 1 is the critical Hölder-continuity exponent in the time variable. Furthermore, we prove a bound on moments of the integrated superprocess, and give uniform upper bounds on the mass the superprocess assigns to small balls, generalising a result of Perkins. [ABSTRACT FROM AUTHOR]

We deal with the change point problem in ergodic diffusion processes based on high frequency data. Tonaki et al. [12,13] studied the change point problem for the ergodic diffusion process model. However, the change point problem for the drift parameter when the diffusion parameter changes is still open. Therefore, we consider the change detection and the change point estimation for the drift parameter taking into account that there is a change point in the diffusion parameter. Moreover, we examine the performance of the tests and the estimation with numerical simulations. [ABSTRACT FROM AUTHOR]

Keywords: political economy; knowledge-based economy; discourse; power; trade unions; co-determination; J5 labor-management relations; and collective bargaining; O330 Technological change: Choices and consequences; diffusion processes; J63 Turnover; vacancies; layoffs EN political economy knowledge-based economy discourse power trade unions co-determination J5 labor-management relations and collective bargaining O330 Technological change: Choices and consequences diffusion processes J63 Turnover vacancies layoffs 1257 1268 12 06/09/23 20230401 NES 230401 What white-collar workers and the workplace tell us about the politics of capitalism Correspondence: arianna.tassinari4@unibo.it Large-scale layoffs, restructurings and downsizings in the tech sector have been a staple item of the news cycle recently, hard to ignore for even the most distracted observers of the tech world. The core insight in Rothstein's analysis is that while worker power is based on collective action, this is grounded in a very basic way in a long and hard process of convincing workers that this action is worthwhile and will actually achieve something. In the IBM Burlington case, the union was able to mobilize workers against layoffs by pointing out contradictions with a more traditional normative discourse based on long-term, mutual commitments between managers and workers. Second, even though Rothstein deserves kudos for reintegrating the workplace into an analysis of worker power, I Recoding Power i ultimately presents us with an unhelpful duality or opposition between the national level and the workplace. [Extracted from the article]

Luminescence spectroscopy experiments were realized for single colloidal quantum dots CdSe/ZnS in a broad temperature range above room temperature in a nitrogen atmosphere. Broadening and shifts of spectra due to the temperature change as well as due to spectral diffusion processes were detected and analyzed. A linear correlation between the positions of maxima and the squared linewidths of the spectra was found. This dependence was explained by a model that takes into account the slow variation of the electron-phonon coupling strength. [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations of reactions in Al/Ni layered systems have been carried out under isothermal conditions for a wide range of temperatures and several system sizes. An embedded atom method potential, known to reasonably reproduce the phase behavior of Al/Ni, was employed. Simulations revealed reaction mechanisms involving an initial fast process and much slower more complex longer-time reactions. The initial reaction process consists of diffusion of Ni from the pure solid Ni phase into the molten Al phase, resulting in the formation of an Al-rich Al/Ni liquid. The initial reaction ends when the Al/Ni liquid becomes saturated in Ni and solid Al/Ni phases begin to form at the interfaces between the pure solid Ni phase and the Al/Ni liquid. The growth of these solid phases is intrinsically slow compared to the formation of the liquid and is further slowed by the need for Ni to diffuse through the growing interfacial Al/Ni solid phases. Analysis of the initial Al/Ni liquid forming process indicates Fickian behavior with the Ni diffusion coefficient exhibiting Arrhenius temperature dependence. The longer-time slow reaction process(es) resulting in the growth of Al/Ni solid phases do not lend themselves to detailed numerical analysis because of the complex dependence of the Ni transport on the detailed nature of the interfacial layers. [ABSTRACT FROM AUTHOR]

We use molecular dynamics simulations to study the behavior of supercooled water subject to different stimuli from a diluted azobenzene hydrophobic probe. When the molecular motor does not fold, it acts as a passive probe, modifying the structure of water around it, while when the motor is active, it induces elementary diffusion processes inside the medium acting mainly on the dynamics. We study two particular densities, the density of ambient water and a lower density around the ambient pressure ice density, chosen to favor high density liquid and low density liquid (LDL) water, respectively. We find that the passive probe induces ever an acceleration or a slowing down of the diffusion process around it depending on the density of water, while the active probe induces acceleration only. We find a crossover between the diffusion coefficients for the two densities near the passive probe, around T = 215 K. This dynamical crossover is associated with a modification of the structure of water near the probe. Structure calculations show a crossover of the proportion of LDL water around the same temperature, suggesting that it induces the observed dynamical crossover. In opposition with these results, the active stimuli increase diffusion for both densities and decrease the proportion of LDL water at low temperatures. However, we also find for the active stimuli a crossover of the LDL proportion between the two densities of study, showing remarkable similarities between active and passive stimulus results. [ABSTRACT FROM AUTHOR]

Heterogeneous diffusion processes can be well described by an overdamped Langevin equation with space-dependent diffusivity D(x). We investigate the ergodic and nonergodic behavior of these processes in an arbitrary potential well U(x) in terms of the observable—occupation time. Since our main concern is the large-x behavior for long times, the diffusivity and potential are, respectively, assumed as the power-law forms D(x) = D0|x|α and U(x) = U0|x|β for simplicity. Based on the competition roles played by D(x) and U(x), three different cases, β > α, β = α, and β < α, are discussed. The system is ergodic for the first case β > α, where the time average agrees with the ensemble average, both determined by the steady solution for long times. By contrast, the system is nonergodic for β < α, where the relation between time average and ensemble average is uncovered by infinite-ergodic theory. For the middle case β = α, the ergodic property, depending on the prefactors D0 and U0, becomes more delicate. The probability density distribution of the time averaged occupation time for three different cases is also evaluated from Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Chernoff approximations of Feller semigroups and the associated diffusion processes in Riemannian manifolds are studied. The manifolds are assumed to be of bounded geometry, thus including all compact manifolds and also a wide range of non‐compact manifolds. Sufficient conditions are established for a class of second order elliptic operators to generate a Feller semigroup on a (generally non‐compact) manifold of bounded geometry. A construction of Chernoff approximations is presented for these Feller semigroups in terms of shift operators. This provides approximations of solutions to initial value problems for parabolic equations with variable coefficients on the manifold. It also yields weak convergence of a sequence of random walks on the manifolds to the diffusion processes associated with the elliptic generator. For parallelizable manifolds this result is applied in particular to the representation of Brownian motion on the manifolds as limits of the corresponding random walks. [ABSTRACT FROM AUTHOR]

We treat the change point problem in ergodic diffusion processes from discrete observations. Tonaki et al. (2021a) proposed adaptive tests for detecting changes in the diffusion and drift parameters in ergodic diffusion process models. When any change in the diffusion or drift parameter is detected by this or any other method, the next question to consider is where the change point is located. Therefore, we propose the method to estimate the change point of the parameter for two cases: the case where there is a change in the diffusion parameter, and the case where there is no change in the diffusion parameter but a change in the drift parameter. Furthermore, we present rates of convergence and distributional results of the change point estimators. Some examples and simulation results are also given. [ABSTRACT FROM AUTHOR]

Are retail investors using uncurated disclosures in form of patents for their investment decisions? This study uses the investment decisions of retail investors and variation in the local availability of patent information to answer this question. The variation comes from changes in the locations of U.S. Patent and Trademark Depository Libraries over time. I find a strong increase in the local trading volume of stocks after the release of a patent in counties that have easier access to patent information. In addition, trades made by retail investors with easier access to this information yield higher returns, compared to trades made by other investors. These results indicate that disclosures of the U.S. Patent and Trademark Office facilitate the dissemination of patent information to retail investors. Furthermore, these results suggest that retail investors complement traditional curated disclosures with uncurated disclosures in form of patents. [ABSTRACT FROM AUTHOR]

Graph dynamics for a node-labeled graph is a set of updating rules describing how the labels of each node in the graph change in time as a function of the global set of labels. The underpopulation rule is graph dynamics derived by simplifying the set of rules constituting the Game of Life. It is known that the number of label configurations met by a graph during the dynamic process defined by such rule is bounded by a polynomial in the size of the graph if the graph is undirected. As a consequence, predicting the labels evolution is an easy problem (i.e., a problem in P) in such a case. In this paper, the generalization of the underpopulation rule to signed and directed graphs is studied. It is here proved that the number of label configurations met by a graph during the dynamic process defined by any so generalized underpopulation rule is still bounded by a polynomial in the size of the graph if the graph is undirected and structurally balanced, while it is not bounded by any polynomial in the size of the graph if the graph is directed although unsigned unless P = PSpace. [ABSTRACT FROM AUTHOR]

The paper has two major themes. The first part of the paper establishes certain general results for infinite-dimensional optimization problems on Hilbert spaces. These results cover the classical representer theorem and many of its variants as special cases and offer a wider scope of applications. The second part of the paper then develops a systematic approach for learning the drift function of a stochastic differential equation by integrating the results of the first part with Bayesian hierarchical framework. Importantly, our Bayesian approach incorporates low-cost sparse learning through proper use of shrinkage priors while allowing proper quantification of uncertainty through posterior distributions. Several examples at the end illustrate the accuracy of our learning scheme. [ABSTRACT FROM AUTHOR]

A controlled branching process (CBP) is a modification of the standard Bienaymé–Galton–Watson process in which the number of progenitors in each generation is determined by a random mechanism. We consider a CBP starting from a random number of initial individuals. The main aim of this article is to provide a Feller diffusion approximation for critical CBPs. A similar result by considering a fixed number of initial individuals by using operator semigroup convergence theorems has been previously proved by Sriram et al. (Stochastic Processes Appl. 2007;117:928–946). An alternative proof is now provided making use of limit theorems for random step processes. [ABSTRACT FROM AUTHOR]

We provide an elementary proof of the support of the law of a hypoelliptic Brownian motion on the Heisenberg group H. We consider a control norm associated to left-invariant vector fields on H, and describe the support in terms of the space of finite energy horizontal curves. [ABSTRACT FROM AUTHOR]

The purpose of this study is to extend and determine the analytical solution of a twodimensional homogeneous system of fuzzy linear fractional differential equations with the Caputo derivative of two independent fractional orders. We extract two possible solutions to the coupled system under the definition of strongly generalized H-differentiability, uncertain initial conditions and fuzzy constraint coeficients. These potential solutions are determined using the fuzzy Laplace transform. Furthermore, we extend the concept of fuzzy fractional calculus in terms of the Mittag-Leffler function involving triple series. In addition, several important concepts, facts, and relationships are derived and proved as property of boundedness. Finally, to grasp the considered approach, we solve a mathematical model of the diffusion process using proposed techniques to visualize and support theoretical results. [ABSTRACT FROM AUTHOR]

This study analyzes the determinants of the "Broadband Price Index" in Europe. The data used refers to 28 European countries between 2016 and 2021. The database used is the Digital, Economy, and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index and "Connectivity", while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills", "Above Basic Digital Skills", and "At Least Basic Software Skills". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN, with an estimated value equal to an amount of 9.21%. Doi: 10.28991/HEF-2022-03-01-03 Full Text: PDF

Extensive molecular dynamics simulations of xenon in two classes of zeolite crystal systems, one consisting of purely intra-crystalline space and the other with both intra- and inter-crystalline space are reported. The latter mimics a typical poly-crystalline sample of zeolite. Comparison of results from these two systems provides insights into the structure and dynamics in the presence of inter-crystalline space. The temperature, as well as the distance between the crystallites, has been varied. The density distribution and diffusivities calculated inside the poly-crystalline system show that the interfacial region between the crystal and the inter-crystalline region acts as a bottleneck for diffusion through the system. At lower temperatures, the particles are trapped at the interface due to the pronounced energy minima present in that region. With the increase in temperature, the particles are able to overcome this barrier frequently, and the transport across the inter-crystalline region is increased. A ballistic or superdiffusive motion is seen in the inter-crystalline region along all the axes except along the axis which has the inter-crystalline space. The transition time for ballistic to diffusive motion increases with the increase in the length of the inter-crystalline space. Velocity auto- and cross correlation functions exhibit strong oscillations and exchange of kinetic energy along directions perpendicular to the direction of the inter-crystalline space. These results explain why uptake and PFGNMRmeasurements exhibit lower values for diffusivity for the same system when compared to Quasi- Elastic Neutron Scattering. Thus, using molecular dynamics simulations, we were able to correlate the difference of diffusivity values measured using various experimental methods where these intercrystalline regions are common. [ABSTRACT FROM AUTHOR]

Motivated by entropic optimal transport, we are interested in the Feynman-Kac formula associated to the parabolic equation (L + V) g = 0 with a final nonnegative boundary condition and a Markov generator L : = ∂ t + b · ∇ + Δ a / 2 . It is well-known that when the drift b , the diffusion matrix a and the scalar potential V are regular enough and not growing too fast, the classical solution g of this PDE, is represented by the Feynman-Kac formula g t (x) = E R [ exp ∫ [ t , T ] V (s , X s) d s g (X T) ∣ X t = x ] where R is the Markov measure with generator L . We do not assume that g, b and V are regular, and only require that their growth is controlled by a finite entropy condition. These hypotheses are less restrictive than the standard assumptions of the theory of viscosity solutions, and allow for instance V to belong to some Kato class. We prove that g defined by the Feynman-Kac formula belongs to the domain of the extended generator L of the Markov measure R and satisfies the trajectorial identity: [ (L + V) g ] (t , X t) = 0 , d t d P - a. e. where the path measure P is defined by P : = f (X 0) exp ∫ [ 0 , T ] V (t , X t) d t g (X T) R , with f : R n → [ 0 , ∞) another nonnegative function. We also show that the forward drift b P of P satisfies b P (t , X t) = [ b + a ∇ ~ log g ] (t , X t) , d t d P - a. e. , where ∇ ~ is some extension of the standard derivative. Our probabilistic approach relies on stochastic derivatives, semimartingales, Girsanov's theorem and the Hamilton-Jacobi-Bellman equation satisfied by log g . [ABSTRACT FROM AUTHOR]

We study convergence to non-minimal quasi-stationary distributions for one-dimensional diffusions. We give a method for reducing the convergence to the tail behavior of the lifetime via a property we call the first hitting uniqueness. We apply the results to Kummer diffusions with negative drift and give a class of initial distributions converging to each non-minimal quasi-stationary distribution. [ABSTRACT FROM AUTHOR]

There is a vast amount of literature devoted to experimental studies on adsorption from liquids examining the adsorption potential of various adsorbents with respect to various solutes. Most of these studies contain not only equilibrium but also kinetic experimental data. The standard procedure followed in the literature is to fit the kinetic experimental adsorption data to some models. Typically empirical models are employed for this purpose and among them, the pseudo-first and pseudo-second order kinetic models are the most extensively used. In particular, the linear form of their integrated equations is extensively employed. In most cases, it is found that the pseudo-second order model is not only better than other models but also leads to high fitting quality. This is rather strange since there is no physical justification for such a model, as it is well accepted that adsorption kinetics is dominated by a diffusion process. In the present work, it will be shown through examples and discussion that the success of the linearized pseudo-second order model in fitting the data is misleading. Specific suggestions on appropriate adsorption data treatment are given. [ABSTRACT FROM AUTHOR]

This article considers a class of metastable non-reversible diffusion processes whose invariant measure is a Gibbs measure associated with a Morse potential. In a companion paper (Lee and Seo in Probab Theory Relat Fields 182:849–903, 2022), we proved the Eyring–Kramers formula for the corresponding class of metastable diffusion processes. In this article, we further develop this result by proving that a suitably time-rescaled metastable diffusion process converges to a Markov chain on the deepest metastable valleys. This article is also an extension of (Rezakhanlou and Seo in , 2018), which considered the same problem for metastable reversible diffusion processes. Our proof is based on the recently developed resolvent approach to metastability. [ABSTRACT FROM AUTHOR]

The competitive diffusion game is a game-theoretic model of information spreading on a graph proposed by Alon et al. (2010). It models the diffusion process of information in social networks where several competitive companies want to spread their information, for example. The nature of this game strongly depends on the graph topology, and the relationship is studied from several aspects. In this paper, we investigate the existence of a pure Nash equilibrium of the two-player competitive diffusion game on chordal and its related graphs. We show that a pure Nash equilibrium always exists on split graphs, block graphs, and interval graphs, all of which are well-known subclasses of chordal graphs. On the other hand, we show that a pure Nash equilibrium does not always exist on (strongly) chordal graphs; the boundary of the existence of a pure Nash equilibrium is found. [ABSTRACT FROM AUTHOR]

In this paper, we propose a two-step test for parametric specification of volatility function based on high-frequency data with microstructure noise. The latent prices are first recovered at high precision under the assumption that the noise is a parametric function of observable trading information. An asymptotically distribution-free test is then built on the estimated latent prices using Khmaladze martingale transformation. We establish asymptotic theory associated with the test under both the null and alternative hypotheses. Moreover, an extension of the proposed method to incorporate intraday pattern is also formally discussed. Simulation results corroborate our theoretical findings demonstrating clear advantage of our method over an existing distribution-free method that does not take microstructure noise into account. We finally apply the test to the high-frequency data of Standard & Poor's depository receipt (SPDR) that tracks the S&P 500 index. [ABSTRACT FROM AUTHOR]

Mine tremors and rockbursts triggered by thick-hard roof fracturing are major problems in safe production of coal mines, and the corresponding numerical simulation is also a great challenge due to complexity of rock failure and wave field characteristics radiated from sources. In this paper, based on the engineering background that strong mine tremors frequently occurred in the 7301 working face of the Baodian coal mine due to thick-hard stratum fracture, a novel method is used to successfully simulate the whole process of tremor generation caused by thick-hard roof fracturing and triggered rockburst in a roadway. Much interesting information is studied in detail, including the characteristics of the source radiation wave field, the variation of the stress field caused by seismic wave diffusion, and the changes in stress, crack and displacement throughout the process of the roadway rockburst from inoculation to explosion under the disturbance of seismic waves. The effects of tremor disturbance intensity are studied based on the relationship between the relative spatial orientation of the roadway and fault plane. The disturbance to the roadway is largest in the direction of 45° of the fault plane. The research results provide a useful reference for understanding the mechanisms of rockburst induced by mine tremors. The simulation method gives a valuable insight into the disturbance effects and focal mechanism of mine tremors. Highlights: Characteristics of source radiation wave field of mine tremors induced by shear fracture are numerically simulated. Influences of fault plane geometric properties, radiation wave field, and relative position between roadway and source on rockburst are discussed. Rupture types of thick-hard stratum in different areas are investigated by moment tensor inversion. [ABSTRACT FROM AUTHOR]

In this note we introduce a new family of entropy powers which are related to generalized entropies, called Sharma-Mittal entropies, and we prove their concavity along diffusion processes generated by $L^{2}$ -Wasserstein gradient flows of corresponding entropy functionals. This result extends the result of Savaré and Toscani (2014) on the concavity of Rényi entropy powers and reveals a connection to Rényi entropy power inequalities by Bobkov and Marsiglietti (2017). [ABSTRACT FROM AUTHOR]

Consider an information diffusion process on a graph G that starts with k > 0 burnt vertices, and at each subsequent step, burns the neighbors of the currently burnt vertices, as well as k other unburnt vertices. The k-burning number of G is the minimum number of steps b k (G) such that all the vertices can be burned within b k (G) steps. Note that the last step may have smaller than k unburnt vertices available, where all of them are burned. The 1-burning number coincides with the well-known burning number problem, which was proposed to model the spread of social contagion. The generalization to k -burning number allows us to examine different worst-case contagion scenarios by varying the spread factor k. In this paper we prove that computing k -burning number is APX-hard, for any fixed constant k. We then give an O ((n + m) log ⁡ n) -time 3-approximation algorithm for computing k -burning number, for any k ≥ 1 , where n and m are the number of vertices and edges, respectively. Finally, we show that even if the burning sources are given as an input, computing a burning sequence itself is an NP-hard problem. [ABSTRACT FROM AUTHOR]

We report on a planar long-wavelength infrared photodetector based on InAs/InAs1-xSbx type-II superlattice with zinc diffusion. The superlattice structures were grown by molecular beam epitaxy, followed by a post-growth Zinc diffusion process in a metal-organic chemical vapor deposition reactor. The planar photodetectors showed a peak responsivity of 2.18 A/W, under an applied bias of −20 mV, with a corresponding quantum efficiency of 44.5%, without any anti-reflection coating, and had a 100% cut-off wavelength of $8.5 \mu \text{m}$ at 77 K temperature. These photodetectors exhibit a specific peak detectivity of $3.0\times 10^{12}$ cm.Hz1/2/W, with a dark current density of $1.5\times 10^{-5}$ A/cm2 and the differential-resistance-area product of $\sim 8.6\times 10^{-1} \Omega $.cm2, under an applied bias of −20 mV at 77 K. A comparative study between the planar and conventional mesa-isolated photodetectors was also carried out. [ABSTRACT FROM AUTHOR]

As was found in our previous works, when Nafion swells in water, polymer fibers unwind into the bulk of the surrounding liquid. This effect is controlled by the content of deuterium in water. Here, we present the results of studying the dynamics of methylene blue (MB) adsorption on the Nafion surface for MB solutions based on natural water (deuterium content is 157 ppm, the unwinding effect occurs) and based on deuterium-depleted water (DDW; deuterium content is 3 ppm, there is no unwinding). In addition, we studied the dynamics of water desorption during drying of the Nafion polymer membrane after soaking in MB solution based on natural water and DDW. It turned out that in the case of natural water, the rate of MB adsorption and water desorption is higher than in the case of DDW. It also turned out that the amount of MB adsorbed on the membrane in the case of natural water is greater than in the case of DDW. Finally, it was found that the desorption of water during drying is accompanied by a rearrangement of the absorption spectrum of Nafion. This rearrangement occurs earlier in the case of DDW. Thus, by infinitesimal changes in the deuterium content (from 3 to 157 ppm) in an aqueous solution, in which a polymer membrane swells, we can control the dynamics of adsorption and desorption processes. A qualitative model, which connects the observed effects with the slowing down of diffusion processes inside the layer of unwound fibers, is proposed. [ABSTRACT FROM AUTHOR]

Social recommendation has emerged to leverage social connections among users for predicting users’ unknown preferences, which could alleviate the data sparsity issue in collaborative filtering based recommendation. Early approaches relied on utilizing each user’s first-order social neighbors’ interests for better user modeling, and failed to model the social influence diffusion process from the global social network structure. Recently, we propose a preliminary work of a neural influence Diffusion Network (i.e., DiffNet) for social recommendation L. Wu, P. Sun, Y. Fu, R. Hong, X. Wang, and M. Wang, “A neural influence diffusion model for social recommendation,” in Proc. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2019, pp. 235–244.. DiffNet models the recursive social diffusion process for each user, such that the influence diffusion hidden in the higher-order social network is captured in the user embedding process. Despite the superior performance of DiffNet, we argue that, as users play a central role in both user-user social network and user-item interest network, only modeling the influence diffusion process in the social network would neglect the latent collaborative interests of users hidden in the user-item interest network. To this end, in this paper, we propose DiffNet++, an improved algorithm of DiffNet that models the neural influence diffusion and interest diffusion in a unified framework. By reformulating the social recommendation as a heterogeneous graph with social network and interest network as input, DiffNet++ advances DiffNet by injecting both the higher-order user latent interest reflected in the user-item graph and higher-order user influence reflected in the user-user graph for user embedding learning. This is achieved by iteratively aggregating each user’s embedding from three aspects: the user’s previous embedding, the influence aggregation of social neighbors from the social network, and the interest aggregation of item neighbors from the user-item interest network. Furthermore, we design a multi-level attention network that learns how to attentively aggregate user embeddings from these three aspects. Finally, extensive experimental results on four real-world datasets clearly show the effectiveness of our proposed model. We release the source code at https://github.com/PeiJieSun/diffnet. [ABSTRACT FROM AUTHOR]

In social networks, individuals’ decisions are strongly influenced by recommendations from their friends, acquaintances, and favorite renowned personalities. The popularity of online social networking platforms makes them the prime venues to advertise products and promote opinions. The Influence Maximization (IM) problem entails selecting a seed set of users that maximizes the influence spread, i.e., the expected number of users positively influenced by a stochastic diffusion process triggered by the seeds. Engineering and analyzing IM algorithms remains a difficult and demanding task due to the NP-hardness of the problem and the stochastic nature of the diffusion processes. Despite several heuristics being introduced, they often fail in providing enough information on how the network topology affects the diffusion process, precious insights that could help researchers improve their seed set selection. In this paper, we present VAIM, a visual analytics system that supports users in analyzing, evaluating, and comparing information diffusion processes determined by different IM algorithms. Furthermore, VAIM provides useful insights that the analyst can use to modify the seed set of an IM algorithm, so to improve its influence spread. We assess our system by: $(i)$ (i) a qualitative evaluation based on a guided experiment with two domain experts on two different data sets; $(ii)$ (i i) a quantitative estimation of the value of the proposed visualization through the ICE-T methodology by Wall et al. (IEEE TVCG - 2018). The twofold assessment indicates that VAIM effectively supports our target users in the visual analysis of the performance of IM algorithms. [ABSTRACT FROM AUTHOR]