scholarly journals Complex roots of real characteristic functions

1970 ◽  
Vol 25 (2) ◽  
pp. 238-238 ◽  
Author(s):  
Robert G. Staudte ◽  
Mahabanoo N. Tata
Keyword(s):  
Characteristic Functions ◽  
Complex Roots ◽  
Real Characteristic

The characteristic functions of functions

1968 ◽  
Vol 307 (1490) ◽  
pp. 317-334 ◽  
Keyword(s):  
Multivariate Analysis ◽  
Characteristic Function ◽  
Gaussian Model ◽  
Random Variable ◽  
Stable Distributions ◽  
Characteristic Functions ◽  
Real Characteristic ◽  
Vector Random Variable

The characteristic functions of various functions of a real or vector random variable are expressed in terms of the characteristic function of that variable. In the examples there is special emphasis on the stable distributions that have real characteristic functions. Some of the results suggest the practicability of generalizing traditional multivariate analysis beyond the multi-Gaussian model.

scholarly journals Micro-CT and Microscopy Study of Internal and Marginal Gap to Tooth Surface of Crenelated versus Conventional Dental Indirect Veneers

Medicina ◽  
2021 ◽  
Vol 57 (8) ◽  
pp. 772
Author(s):  
Alexandra-Cristina Măroiu ◽  
Cosmin Sinescu ◽  
Virgil-Florin Duma ◽  
Florin Topală ◽  
Anca Jivănescu ◽  
...  
Keyword(s):  
Computer Aided Design ◽  
Tooth Surface ◽  
Characteristic Functions ◽  
The Novel ◽  
Micro Ct ◽  
Marginal Gap ◽  
Luting Cement ◽  
Computer Aided ◽  
Internal Adaptation ◽  
Internal Gap

1. Background and Objectives: Ceramic veneers represent the most appropriate treatment option for minimally invasive aesthetic rehabilitation. For long-term clinical success, the accurate marginal and internal adaptation of dental restorations are of paramount importance. The aim of this in vitro study is to assess the effect of a novel (patented) design of veneers compared to conventional ones on their marginal and internal gap to the prepared tooth surface. 2. Materials and Methods: Twenty-four lithium disilicate ceramic veneers are obtained using Computer-Aided-Design (CAD) and then milled using Computer-Aided-Manufacturing (CAM). The samples are divided into two groups: 12 conventional (CO) veneers (i.e., with a linear marginal contour) and 12 crenelated (CR) veneers, the latter with the novel sinusoidal marginal design. All samples are bonded to frontal teeth, and the adhesive interfaces are analyzed using two methods, optical microscopy and micro-Computed Tomography (CT): the former for the accuracy of the marginal gap and the latter for the internal gap (as well as for the homogeneity of the luting cement) of ceramic veneers. 3. Results: STATA and one-way ANOVA tests reveal significant differences between CO and CR veneers: (i) the marginal gap is smaller for CR (64 μm) than for CO veneers (236 μm); (ii) the internal adaptation is better for CR veneers: for a cement width of up to 120 μm, the covered surface for the CR group is 81.5%, while for the CO group it is 64.5%; (iii) the mean of the porosities within the cement is not significantly different (3.4 × 106 μm3 for CO and 3.9 × 106 μm3 for CR veneers), with a higher standard deviation for the CO group. Analytical modeling is achieved for internal gaps using the micro-CT results. The characteristic functions obtained allow us to compare the volume of luting cement for the two types of veneers. 4. Conclusion: The novel veneers design produces an improvement in the marginal and internal adaptation of the restorations to the prepared tooth surface. Thus, it provides favorable premises for better clinical performances.

scholarly journals The Role of Neuropeptide Y in the Nucleus Accumbens

2021 ◽  
Vol 22 (14) ◽  
pp. 7287
Author(s):  
Masaki Tanaka ◽  
Shunji Yamada ◽  
Yoshihisa Watanabe
Keyword(s):  
Nervous System ◽  
Nucleus Accumbens ◽  
Neuropeptide Y ◽  
Emotional Behavior ◽  
Characteristic Functions ◽  
Receptor Subtypes ◽  
Neuroendocrine Mechanisms ◽  
Fear And Anxiety ◽  
The Brain

Neuropeptide Y (NPY), an abundant peptide in the central nervous system, is expressed in neurons of various regions throughout the brain. The physiological and behavioral effects of NPY are mainly mediated through Y1, Y2, and Y5 receptor subtypes, which are expressed in regions regulating food intake, fear and anxiety, learning and memory, depression, and posttraumatic stress. In particular, the nucleus accumbens (NAc) has one of the highest NPY concentrations in the brain. In this review, we summarize the role of NPY in the NAc. NPY is expressed principally in medium-sized aspiny neurons, and numerous NPY immunoreactive fibers are observed in the NAc. Alterations in NPY expression under certain conditions through intra-NAc injections of NPY or receptor agonists/antagonists revealed NPY to be involved in the characteristic functions of the NAc, such as alcohol intake and drug addiction. In addition, control of mesolimbic dopaminergic release via NPY receptors may take part in these functions. NPY in the NAc also participates in fat intake and emotional behavior. Accumbal NPY neurons and fibers may exert physiological and pathophysiological actions partly through neuroendocrine mechanisms and the autonomic nervous system.

PRICING VARIANCE SWAPS UNDER DOUBLE HESTON STOCHASTIC VOLATILITY MODEL WITH STOCHASTIC INTEREST RATE

2021 ◽  
pp. 1-17
Author(s):  
Huojun Wu ◽  
Zhaoli Jia ◽  
Shuquan Yang ◽  
Ce Liu
Keyword(s):  
Interest Rate ◽  
Closed Form ◽  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Characteristic Functions ◽  
Stochastic Interest Rate ◽  
Modeling Framework ◽  
Variance Swaps ◽  
Volatility Model ◽  
Stochastic Interest

In this paper, we discuss the problem of pricing discretely sampled variance swaps under a hybrid stochastic model. Our modeling framework is a combination with a double Heston stochastic volatility model and a Cox–Ingersoll–Ross stochastic interest rate process. Due to the application of the T-forward measure with the stochastic interest process, we can only obtain an efficient semi-closed form of pricing formula for variance swaps instead of a closed-form solution based on the derivation of characteristic functions. The practicality of this hybrid model is demonstrated by numerical simulations.

scholarly journals Development of a New Sensor Module for an Enhanced Fuel Flexible Operation of Biomass Boilers

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 661
Author(s):  
Martin Meiller ◽  
Jürgen Oischinger ◽  
Robert Daschner ◽  
Andreas Hornung
Keyword(s):  
Particle Size ◽  
Bulk Material ◽  
Detection System ◽  
Wood Chips ◽  
Convective Drying ◽  
Characteristic Functions ◽  
Biomass Combustion ◽  
Fuel Flexibility ◽  
Sensor Module ◽  
Over Time

The heterogeneity of biogenic fuels, and especially biogenic residues with regard to water and ash content, particle size and particle size distribution is challenging for biomass combustion, and limits fuel flexibility. Online fuel characterization as a part of process control could help to optimize combustion processes, increase fuel flexibility and reduce emissions. In this research article, a concept for a new sensor module is presented and first tests are displayed to show its feasibility. The concept is based on the principle of hot air convective drying. The idea is to pass warm air with 90 °C through a bulk of fuel like wood chips and measure different characteristics such as moisture, temperatures and pressure drop over the bulk material as a function over time. These functions are the basis to draw conclusions and estimate relevant fuel properties. To achieve this goal, a test rig with a volume of 0.038 m3 was set up in the laboratory and a series of tests was performed with different fuels (wood chips, saw dust, wood pellets, residues from forestry, corn cobs and biochar). Further tests were carried out with conditioned fuels with defined water and fines contents. The experiments show that characteristic functions arise over time. The central task for the future will be to assign these functions to specific fuel characteristics. Based on the data, the concept for a software for an automated, data-based fuel detection system was designed.

scholarly journals A Neural Network-Based Approach for Approximating Arbitrary Roots of Polynomials

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 317
Author(s):  
Diogo Freitas ◽  
Luiz Guerreiro Lopes ◽  
Fernando Morgado-Dias
Keyword(s):  
Iterative Methods ◽  
Fundamental Problem ◽  
Iterative Algorithms ◽  
Rounding Errors ◽  
Suggested Approach ◽  
Simultaneous Iterative Methods ◽  
Complex Roots ◽  
Roots Of Polynomials ◽  
Comparative Results ◽  
The One

Finding arbitrary roots of polynomials is a fundamental problem in various areas of science and engineering. A myriad of methods was suggested to address this problem, such as the sequential Newton’s method and the Durand–Kerner (D–K) simultaneous iterative method. The sequential iterative methods, on the one hand, need to use a deflation procedure in order to compute approximations to all the roots of a given polynomial, which can produce inaccurate results due to the accumulation of rounding errors. On the other hand, the simultaneous iterative methods require good initial guesses to converge. However, Artificial Neural Networks (ANNs) are widely known by their capacity to find complex mappings between the dependent and independent variables. In view of this, this paper aims to determine, based on comparative results, whether ANNs can be used to compute approximations to the real and complex roots of a given polynomial, as an alternative to simultaneous iterative algorithms like the D–K method. Although the results are very encouraging and demonstrate the viability and potentiality of the suggested approach, the ANNs were not able to surpass the accuracy of the D–K method. The results indicated, however, that the use of the approximations computed by the ANNs as the initial guesses for the D–K method can be beneficial to the accuracy of this method.

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