Dispersion Matrix Research Articles

Parsimonious mixture‐of‐experts based on mean mixture of multivariate normal distributions

The mixture‐of‐experts (MoE) paradigm attempts to learn complex models by combining several “experts” via probabilistic mixture models. Each expert in the MoE model handles a small area of the data space in which a gating function controls the data‐to‐expert assignment. The MoE framework has been used extensively in designing non‐linear models in machine learning and statistics to model the heterogeneity in data for the purpose of regression, classification and clustering. The existing MoE of multi‐target regression (MoE‐MTR) models for continuous data is based on multivariate normal distributions. However, in many practical situations, for a set of data, a group or groups of observations may exhibit asymmetric and heavy‐tailed behaviour, and inference based on symmetric distributions in such situations can unduly affect the fit of the regression model. We introduce here a novel robust multivariate non‐normal MoE model by the use of mean mixture of normal distributions. The proposed model can handle the issues of MoE‐MTR models regarding possibly skewed, heavy‐tailed and noisy data. Maximum likelihood estimates of model parameters are developed based on an expectation‐maximization (EM)‐type algorithm. Parsimony is also obtained by imposing suitable constraints on the expert dispersion matrices. The usefulness of the proposed methodology is illustrated using simulated and real data sets.

Cumulant mapping as the basis of multi-dimensional spectrometry.

Cumulant mapping employs a statistical reconstruction of the whole by sampling its parts. The theory developed in this work formalises and extends ad hoc methods of 'multi-fold' or 'multi-dimensional' covariance mapping. Explicit formulae have been derived for the expected values of up to the 6th cumulant and the variance has been calculated for up to the 4th cumulant. A method of extending these formulae to higher cumulants has been described. The formulae take into account reduced fragment detection efficiency and a background from uncorrelated events. Number of samples needed for suppressing the statistical noise to a required level can be estimated using Matlab code included in Supplemental Material. The theory can be used to assess the experimental feasibility of studying molecular fragmentations induced by femtosecond or X-ray free-electron lasers. It is also relevant for extending the conventional mass spectrometry of biomolecules to multiple dimensions.

Finite sample theory for high-dimensional functional/scalar time series with applications

Statistical analysis of high-dimensional functional times series arises in various applications. Under this scenario, in addition to the intrinsic infinite-dimensionality of functional data, the number of functional variables can grow with the number of serially dependent observations. In this paper, we focus on the theoretical analysis of relevant estimated cross-(auto)covariance terms between two multivariate functional time series or a mixture of multivariate functional and scalar time series beyond the Gaussianity assumption. We introduce a new perspective on dependence by proposing functional cross-spectral stability measure to characterize the effect of dependence on these estimated cross terms, which are essential in the estimates for additive functional linear regressions. With the proposed functional cross-spectral stability measure, we develop useful concentration inequalities for estimated cross-(auto)covariance matrix functions to accommodate more general sub-Gaussian functional linear processes and, furthermore, establish finite sample theory for relevant estimated terms under a commonly adopted functional principal component analysis framework. Using our derived non-asymptotic results, we investigate the convergence properties of the regularized estimates for two additive functional linear regression applications under sparsity assumptions including functional linear lagged regression and partially functional linear regression in the context of high-dimensional functional/scalar time series.

Studies on the curing, tensile and adhesion characteristics of cushion gum to carcass in truck retreaded tires: the effect natural rubber types

In order to improve the quality of truck retreaded tyres, the cushion gum (CG) plays an important role as an adhesion medium to bond the carcass of the new tread to the worn old tyre. This study investigates the effect of natural rubber types such as reclaimed skimmed latex (RSL), ribbed smoke sheet (RSS), chloroprene (CR) and RSS added 10 phr of carbon black (CB) towards its CG performance in cold cure systems. The CG was compounded based on ASTM D3182 with 10 phr of Cumaroun Resin, 5 phr of Calcium Silicate, and other chemicals. The 4 types of CG were tested its physical and tensile properties. To determine the curing time, the rheological was analysed. The results show that the addition of carbon black may improve physical and tensile properties, excluding the elongation at break. It is found that the curing time of cushion gum based on SL rubber has the shortest duration. Each CG was applied to retreat the same type of truck’s worn tyres (1000R20). After surface modification, 5 mm of CG was bonded new same carcass the old surface and continued by heating in the autoclave chamber for 3 hours with pressure at 2 atm. The results show that the adhesion strength of cushion gum based on RSL; RSS; CR; RSS/CB is as follows: 13.64; 8.21; 8.04; 8.01 kN/m respectively, while the adhesion strength of commercial cushion gum is 15,38 kN/m. The spectra FTIR of each cushion gum convince that the less dispersion matrix compared to commercial cushion gum. To sum up, the RSL-NR is the recommended polymer for cushion gum compounding. However, in order to improve its quality, it is suggested to do some pre-treatment and increase the number of tackifier and processing oil in the formulation

Exclusive semileptonic B-meson decays using lattice QCD and unitarity

We present the results of the application of the Dispersion Matrix approach to exclusive semileptonic B-meson decays. This method allows to determine the hadronic form factors in a non-perturbative and completely modelindependent way. Starting from lattice results available at large values of the momentum transfer, the behaviour of the form factors in their whole kinematical range is obtained without introducing any parameterization of their momentum dependence. We will focus on the determination of the Cabibbo-Kobayashi- Maskawa matrix elements |Vcb| and |Vub| through the analysis of B(s) → D(s)(*)lv and B(s) → π(K)ℓν decays. New theoretical determinations of the Lepton Flavour Universality ratios relevant for these transitions will be also presented.

Multi-View Auxiliary Diagnosis Algorithm for Lung Nodules

Lung is an important organ of human body. More and more people are suffering from lung diseases due to air pollution. These diseases are usually highly infectious. Such as lung tuberculosis, novel coronavirus COVID-19, etc. Lung nodule is a kind of high-density globular lesion in the lung. Physicians need to spend a lot of time and energy to observe the computed tomography image sequences to make a diagnosis, which is inefficient. For this reason, the use of computer-assisted diagnosis of lung nodules has become the current main trend. In the process of computer-aided diagnosis, how to reduce the false positive rate while ensuring a low missed detection rate is a difficulty and focus of current research. To solve this problem, we propose a three-dimensional optimization model to achieve the extraction of suspected regions, improve the traditional deep belief network, and to modify the dispersion matrix between classes. We construct a multi-view model, fuse local three-dimensional information into two-dimensional images, and thereby to reduce the complexity of the algorithm. And alleviate the problem of unbalanced training caused by only a small number of positive samples. Experiments show that the false positive rate of the algorithm proposed in this paper is as low as 12%, which is in line with clinical application standards.

Quasi-Binomial Regression Model for the Analysis of Data with Extra-Binomial Variation

Objectives: Developing inference procedures on the quasi-binomial distribution and the regression model. Methods: Score testing and the method of maximum likelihood for regression parameters estimation. Data: Several examples are included, based on published data. Results: A quasi-binomial model is used to model binary response data which exhibit extra-binomial variation. A partial score test on the binomial hypothesis versus the quasi-binomial alternative is developed and illustrated on three data sets. The extended logit transformation on the binomial parameter is introduced and the large sample dispersion matrix of the estimated parameters is derived. The Nonlinear Mixed Procedure (NLMIXED) in SAS is shown to be very appropriate for the estimation of nonlinear regression.

Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array.

In this paper, we investigate the problem of direction-of-arrival (DOA) estimation for massive multi-input multi-output (MIMO) radar, and propose a total array-based multiple signals classification (TA-MUSIC) algorithm for two-dimensional direction-of-arrival (DOA) estimation with a coprime cubic array (CCA). Unlike the conventional multiple signal classification (MUSIC) algorithm, the TA-MUSIC algorithm employs not only the auto-covariance matrix but also the mutual covariance matrix by stacking the received signals of two sub cubic arrays so that full degrees of freedom (DOFs) can be utilized. We verified that the phase ambiguity problem can be eliminated by employing the coprime property. Moreover, to achieve lower complexity, we explored the estimation of signal parameters via the rotational invariance technique (ESPRIT)-based multiple signal classification (E-MUSIC) algorithm, which uses a successive scheme to be computationally efficient. The Cramer–Rao bound (CRB) was taken as a theoretical benchmark for the lower boundary of the unbiased estimate. Finally, numerical simulations were conducted in order to demonstrate the effectiveness and superiority of the proposed algorithms.

Performance analysis of CIM‐STSK system

Code-index modulation (CIM) uses the index of spreading code to convey information, which can be integrated with different kinds of MIMO systems to achieve higher throughput. This paper proposes a novel CIM-integrated space time shift keying scheme called CIM-STSK. The CIM-STSK system employs three types of resources to transmit information bits, which are Hadamard codes, dispersion matrix indexes and QAM constellation symbols. The mathematical expression of the bit error rate of the CIM-STSK system is derived, and the theoretical analysis is validated with Monte Carlo simulation results. Compared with the corresponding CIM-SS, STSK, CIM-SM, and CIM-QSM systems, CIM-STSK scheme can not only improve spectrum efficiency, but also achieve a better error performance.

ПОЛЯРИЗАЦІЙНИЙ ВИБІР НАВІГАЦІЙНИХ ОБ’ЄКТІВ, РОЗМІЩЕННИХ В ЗОНІ АТМОСФЕРНИХ УТВОРЕНЬ

The possibility of polarization selection implementation of the navigation objects located in the area of atmospheric formations by the ship single-position radiolocation station (radar) is considered. The polarization selection of the navigational objects located in the area of atmospheric formations is based on their different electro-physical parameters, which from them electromagnetic waves of different polarization. The process of the polarization selection is controlled by the appropriate choice of polarization, which irradiates the objects of the electromagnetic wave, given the actual Stokes parameters. The interference performance of the objects, observed by the ship’s radar, is represented by means of the Mueller matrices (i.e., dissociation), which have 16 coefficients. The determination of the matrix coefficients of the atmospheric formation dissociation is carried out by their differentiation or integration by the method of Pikar (i.e., the successive approximation). The coefficients of the atmospheric formation matrix are shown to be variable functions of time, endpoints for all values of the analyzed interval. The division of the time interval into segments, in which the coefficients of the matrix are considered constant, allows them to be calculated using Baker's formula. The practical implementation of the polarization selection of the navigation objects located in the zone of atmospheri formations, is based on the measurement of the coefficients of the dispersion matrix by the intermittent sampling of objects by non-polarized wave, double line wave, and circular polarization.

A fabric reinforced small diameter tubular graft for rabbits’ carotid artery defect

Tissue engineering small diameter artificial blood vessel is an indispensable graft for repairing extremity arterial injury. Previous researches demonstrated that suitable porosity and matching mechanical properties are two keys for tubular tissue reconstruction. In this study, we fabricated a fabric reinforced small diameter tubular graft (PPTG) from PLGA fabric and three-dimensional porous PEEUU with a structure of the bionic extracellular matrix for transplanting in situ combined braiding and thermally induced phase separation (TIPS). The prepared PPTG presented smooth and dense inner surface, fluffy and porous grafts wall, and tubular PLGA fabric evenly dispersed PEEUU matrix, which provide mechanical support for PPTG. The mechanical tests and hemolysis results showed that PPTG possess matched mechanical properties with autologous blood vessels and stable blood compatibility. Six weeks after rabbits’ carotid artery defect replacement indicated that there were no blockage occurred for PPTG group. Histological staining exhibited positive expression of endothelial cells on the inner surface of PPTG and distinct smooth muscle in the wall of PPTG, which migrated from peripheral tissues and flowing blood. Therefore, this fabric reinforced small diameter tubular graft provides a solution for endothelialization and tissue regeneration and have a potential application in vascular trauma. A fabric reinforced small diameter tubular graft from PLGA fabric and three-dimensional porous PEEUU with a structure of the bionic extracellular matrix exhibited matched mechanical properties, especially they demonstrate excellent performance to induce the migration of host cells to the wall of tubular graft and effective anti-thrombosis properties in rabbit carotid artery defect.

Correlative Image-Based Release Prediction and 3D Microstructure Characterization for a Long Acting Parenteral Implant.

Imaging-based characterization of polymeric drug-eluting implants can be challenging due to the microstructural complexity and scale of dispersed drug domains and polymer matrix. The typical evaluation via real-time (and accelerated in vitro experiments not only can be very labor intensive since implants are designed to last for 3months or longer, but also fails to elucidate the impact of the internal microstructure on the implant release rate. A novel characterization technique, combining multi-scale high resolution three-dimensional imaging, was developed for a mechanistic understanding of the impact of formulation and manufacturing process on the implant microstructure. Artificial intelligence-based image segmentation and imaging analytics convert "visualized" structural properties into numerical models, which can be used to calculate key parameters governing drug transport in the polymer matrix, such as effective permeability. Simulations of drug transport in structures constructed on the basis of image analytics can be used to predict the release rates for the drug-eluting implant without running lengthy experiments. Multi-scale imaging approach and image-based characterization generate a large amount of quantitative structural information that are difficult to obtain experimentally. The direct-imaging based analytics and simulation is a powerful tool and has potential to advance fundamental understanding of drug release mechanism and the development of robust drug-eluting implants.

Heterogeneous Tail Generalized Common Factor Modeling

A multivariate normal mean-variance heterogeneous tails mixture distribution is proposed for the joint distribution of financial factors and asset returns (referred to as Factor-HGH). The proposed latent variable model incorporates a Cholesky decomposition of the dispersion matrix to ensure a rich dependency structure for capturing the stylized facts of the data. It generalizes several existing model structures, with or without financial factors. It is further applicable in large dimensions due to a fast ECME estimation algorithm of all the model parameters. The advantages of modelling financial factors and asset returns jointly under non-Gaussian errors are illustrated in an empirical comparison study between the proposed Factor-HGH model and classical financial factor models. While the results for the Fama-French 49 industry portfolios are in line with Gaussian-based models, in the case of highly tail heterogeneous cryptocurrencies, the portfolio based on the Factor HGH model doubles the average return while keeping the volatility, the maximum drawdown, the turnover, and the expected-shortfall at a low level.

AKF-SR: Adaptive Kalman filtering-based successor representation

To understand animals’ behavior in finding relations between similar tasks and adapting themselves to changes in the tasks, it is necessary to know how the brain generalizes the learned knowledge from a previous task to unseen tasks. Recent studies in neuroscience suggest that Successor Representation (SR)-based models provide adaptation to changes in the goal locations or reward function faster than model-free algorithms, together with lower computational cost compared to that of model-based algorithms. However, it is not known how such representation might help animals to manage uncertainty in their decision making. Existing methods for the SR learning based on standard temporal difference methods (e.g., deep neural network-based algorithms) do not capture uncertainty about the estimated SR. In order to address this issue, the paper presents a Kalman filter-based SR framework, referred to as Adaptive Kalman Filtering-based Successor Representation (AKF–SR). First, Kalman temporal difference approach, which is a combination of Kalman filter and the temporal difference method, is used within the AKF–SR framework to cast the SR learning procedure into a filtering problem to benefit from uncertainty estimation of the SR, and also decreases in memory requirement and sensitivity to model’s parameters in comparison to deep neural network-based algorithms. An adaptive Kalman filtering approach is then applied within the proposed AKF–SR framework in order to tune the measurement noise covariance and measurement mapping function of Kalman filter as the most important parameters affecting the filter’s performance. Moreover, an active learning method that exploits the estimated uncertainty of the SR to form the behaviour policy leading to more visits to less certain values is proposed to improve the overall performance of an agent in terms of received rewards while interacting with its environment. Experimental results based on three reinforcement learning environments illustrate the efficacy of the proposed AKF–SR framework over state-of-the-art frameworks in terms of cumulative reward, reliability, time and computational cost, and speed of convergence to changes in the reward function.

Low-Carbon Ti-Mo Microalloyed Hot Rolled Steels: Special Features of the Formation of the Structural State and Mechanical Properties

Low-carbon Ti-Mo microalloyed steels represent a new generation of high strength steels for automobile sheet. Excellent indicators of difficult-to-combine technological, strength, and other service properties are achieved due to the superposition of a dispersed ferrite matrix and a bulk system of nanoscale carbide precipitates. Recently, developments are underway to optimize thermo-deformation processing for the most efficient use of phase precipitates. The review summarizes and analyzes the results of studies of mechanical properties depending on the chemical composition and parameters of hot deformation of low-carbon Ti-Mo microalloyed steels. Particular attention is paid to the features of the formation and the influence of various types of phase precipitates and the dispersion of the microstructure on mechanical properties. The advantages of Ti-Mo microalloying system and the tasks requiring further solution are shown.

Fossils constrain biogeographical history in a clade of flattened spiders with transcontinental distribution

AbstractAimFossil data may be crucial to infer biogeographical history, especially in taxa with tropical trans‐Pacific distributions. Here, we use extinct and extant trochanteriid flattened spiders to test hypotheses that could explain its trans‐Pacific disjunct distribution, including a Boreotropical origin with a North Atlantic dispersal, an African origin with South Atlantic dispersal and an Eurasian origin with Bering Bridge route.LocationWorld‐wide.TaxonTrochanteriidae, Plator‐Doliomalus‐Vectius (PDV) clade.MethodsMicroCT was used to collect morphological data from an undescribed Baltic amber fossil. These data were used with additional fossils and extant species in a total‐evidence, tip‐dated phylogenetic analysis. We tested different scenarios using constrained dispersal matrices in a Bayesian approach. An analysis with fossils pruned was also performed to explore how lack of fossil data might impact inferences of biogeographical process.ResultsThe phylogenetic analyses allowed us to place the new fossil in the genus Plator. Analyses without fossils suggest an African origin with a dispersal to Asia from India and a South Atlantic dispersal to South America. When fossils are included, hypothesis‐testing rejects this scenario and equally supports a Boreotropical and an Afro‐European origin with a South Atlantic route and a dispersal to Asia from Europe.Main conclusionsBiogeographical inferences of disjunctly distributed taxa should be interpreted with caution when fossils are not included. Although one alternative hypothesis was not completely rejected, results show that the Boreotropical hypothesis for the PDV clade could be a robust explanation for its actual distribution. This hypothesis is mostly overlooked in animal taxa and rigorous tests with other taxa with similar distributions may reveal that a Boreotropical origin is common. We discuss methodological approaches that could improve biogeographical tests using fossils as terminals.

Contribution of surfactants and micelles to contamination and treatability of crude oil-contaminated surface water

Subsequent to an oil spill in surface water, impacts of dispersant application on water treatability and residual contamination in distributed potable water remain largely unknown. The desired outcome of dispersant application is attributable to both nonionic and anionic surfactants which reduce interfacial tension. This study evaluated the contribution of surfactants and their agglomerates, micelles, to contamination and treatability of drinking water. Both a commercial oil-spill dispersant and a formulated dispersant solution were applied in surface water, with and without crude oil, and treated by ballasted flocculation. In crude oil-contaminated surface water, the formulated dispersant was applied at two concentrations to generate surfactant monomers and surfactant micelles. Water quality degradation in the absence of crude oil was attributable to surfactants but more importantly to other organic contaminants present in the dispersant matrix. Ballasted flocculation could only handle low dispersant concentrations judging from the generated settled water quality. In the presence of crude oil, dispersant application hindered water quality and treatability due to the introduction of surfactants that were absent in surface water and whose removal was unachievable with an optimized coagulant dose for turbidity and natural organic matter removal prior to contamination. This phenomenon was of greater significance in the presence of micelles. These findings are of relevance to regulators, petrochemical and water industry professionals in their efforts to best design contingency plans for oil-spill remediation of surface water used as drinking water supply.

Solvent-free synthesis, plasticization and compatibilization of cardanol grafted onto liquid isoprene rubber

Liquid isoprene rubber (LIR) is commonly used as plasticizer in rubber processing industry. It shows poor compatibility with inorganic fillers. Herein, cardanol grafted onto LIR (CA-g-LIR) was synthesized by solvent-free method and used as the dispersed matrix of silica particles. Results show that the optimum reactive condition is that 7 phr of cardanol monomer and 0.2 wt % of 2, 2-Azobisisobutyronitrile (AIBN) initiator per 100 g LIR react for 12 h at 70 °C. At these conditions, grafting ratio is 6.01%. CA-g-LIR shows obvious plasticizing effect, as is certified by its far high elongation at break (increase of 800%), decreased viscosity (reduction of 62%) and glass transition temperature (Tg, decline of 5.0 °C) compared with LIR. Moreover, CA-g-LIR shows good interfacial performance. The dispersion of silica particles in CA-g-LIR is better than that in LIR. CA-g-LIR is obtained by a simple and green way, low-cost, easy for industrial production. It is expected to be acted as plasticizer and compatibilizer at the same time in rubber industry.

Generalized Quadrature Space-Frequency Index Modulation for MIMO-OFDM Systems

In this paper, motivated by the framework of diversity-achieving quadrature spatial modulation (DA-QSM), we propose a generalized quadrature space-frequency index modulation (GQSF-IM) transmission scheme for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The dispersion matrices potentially transmit some combination of each symbol from each antenna at every subcarrier, and their structures lead to desirable coding properties. By setting two well-designed dispersion-matrix sets for both the in-phase (I-) and quadrature (Q-) dimensions, each resource block (RB) of MIMO-OFDM independently selects part of dispersion matrices from each set to modulate the real and imaginary parts of complex symbols, respectively. Thus a simple and systematic method which easily generates dispersion-matrix set with large size is presented. It can be verified that the proposed GQSF-IM scheme subsumes the existing QSF-IM scheme as its special case. Moreover, it can be proved that the GQSF-IM scheme automatically achieves the second order transmit diversity without requiring any parameter or matrix optimization. Owing to obtaining higher transmit diversity order, simulation results of bit error rate (BER) performance show that GQSF-IM outperforms QSF-IM in different channels such as independent and identically distributed (i.i.d.), correlated Rayleigh fading, and Rician channels. Furthermore, GQSF-IM can achieve obvious better BER performance when it combines with interleaving for more diversity gains.

Hopf Bifurcation in a Delayed Population Model Over Patches with General Dispersion Matrix and Nonlocal Interactions

Hopf Bifurcation in a Delayed Population Model Over Patches with General Dispersion Matrix and Nonlocal Interactions