Nodal Parameters Research Articles

A Multigroup Homogeneous Flux Reconstruction Method Based on the ANOVA-HDMR Decomposition

In this paper, we formulate a new flux reconstruction method based on the High Dimensional Model Representation (HDMR) of the nodal flux shape. The method requires the conventional nodal parameters obtained as a result of the transverse-integration nodal solution procedure as well as corner values calculated by a combination of finite-volume and finite-difference approximations. The proposed flux reconstruction procedure is applicable to rectangular nodes and more than two energy groups. The flux reconstruction method is applied to a number of homogeneous and heterogeneous test problems in order to evaluate its accuracy.

Potential biomarkers for distinguishing primary from acquired premature ejaculation: A diffusion tensor imaging based network study.

Premature ejaculation (PE) is classified as primary and acquired and may be facilitated by different pathophysiology. Brain plays an important role in PE, however, differences in the central neuropathological mechanisms among subtypes of PE are unknown. We acquired diffusion tensor imaging (DTI) data from 44 healthy controls (HC) and 47 PE patients (24 primary PE and 23 acquired PE). Then, the whole-brain white matter (WM) structural networks were constructed and between-group differences of nodal segregative parameters were identified by the method of graph theoretical analysis. Moreover, receiver operating characteristic (ROC) curves were performed to determine the suitability of the altered parameters as potential neuroimaging biomarkers for distinguishing primary PE from acquired PE. PE patients showed significantly increased clustering coefficient C(i) in the left inferior frontal gyrus (triangular part) (IFGtriang.L) and increased local efficiency E loc (i) in the left precental gyrus (PreCG.L) and IFGtriang.L when compared with HC. Compared to HC, primary PE patients had increased C(i) and E loc (i) in IFGtriang.L and the left amygdala (AMYG.L) while acquired PE patients had increased C(i) and E loc (i) in IFGtriang.L, and decreased C(i) and E loc (i) in AMYG.L. Compared to acquired PE, primary PE patients had increased C(i) and E loc (i) in AMYG.L. Moreover, ROC analysis revealed that PreCG.L, IFGtriang.L and AMYG.L might be helpful for distinguishing different subtypes of PE from HC (PE from HC: sensitivity, 61.70-78.72%; specificity, 56.82-77.27%; primary PE from HC: sensitivity, 66.67-87.50%; specificity, 52.27-77.27%; acquired PE from HC: sensitivity, 34.78-86.96%; specificity, 54.55-100%) while AMYG.L might be helpful for distinguishing primary PE from acquired PE (sensitivity, 83.33-91.70%; specificity, 69.57-73.90%). These findings improved our understanding of the pathophysiological processes that occurred in patients with ejaculatory dysfunction and suggested that the abnormal segregation of left amygdala might serve as a useful marker to help clinicians distinguish patients with primary PE from those with acquired PE.

Inverse Nodal Problem for p-Laplacian String Equation with Prüfer Substitution

We consider an inverse nodal problem for p-Laplacian string equation under some boundary conditions. Asymptotic formulas for eigenvalues and nodal parameters are constructed by modified Pr¨ufer substitution. The most important process is to apply modified Pr¨ufer substitution to get an exhaustive asymptotic estimate for eigenvalues. Moreover, a reconstruction formula for density function of p-aplacian string equation is obtained by nodal parameters. Generated outcomes are the generalization of the known string problem.

Design of active network filters as hysteretic sensors

This work aims to propose and design a class of networks of coupled linear and nonlinear oscillators, in which short bursts of exogenous excitation result in sustained endogenous network activity that returns to a quiescent state only after a characteristic time and along a different path than when originally excited. The desired hysteretic behavior is obtained through the coupling of self-excited oscillations with purposely designed rate laws for slowly varying nodal parameters, governed only by local interactions in the network. The proposed architecture and the sought dynamics take inspiration from complex biological systems that combine endogenous energy sources with a paradigm for distributed sensing and information processing. In this paper, the network design problem considers arbitrary topologies and investigates the dependence of the desired response on model parameters, as well as on the placement of a single nonlinear node in an otherwise linear network. Perturbation analysis in various asymptotic parameter limits is used to define the proposed internal dynamics. Parameter continuation techniques validate the asymptotic results numerically and demonstrate their robustness over finite ranges of parameter values. Both approaches suggest a nontrivial dependence of the optimal distribution of nonlinearity on the network topology.

Innovative Timoshenko soil-pile integrated element for lager diameter laterally-loaded piles considering soil-pile interactions

The large diameter piles (LDP) are designed to provide strong bearing capacity, which should be carefully analysed to ensure the superstructures’ reliability. The conventional discrete spring element (DSE) method with the Euler-Bernoulli beam element is inappropriate for LDPs as the pile’s shear deformations may be considerable. Besides, the nonlinear soil-pile interactions (SPI) cannot be conveniently simulated with the DSE method. To accurately and effectively evaluate the lateral performance of LDP under extreme load, this paper develops an innovative soil-pile integrated element based on the Timoshenko beam theory. The Green-Lagrange strain is used to formulate the potential energy function with the SPI considered. The Gauss integration method is adopted to simplify the element formulation and evaluate the SPI within the element end nodes. The secant and tangent matrixes are derived for calculating the element deformations and internal forces. The transformation matrix describing the nodal parameters’ relation between element local and global coordinate is presented for practical numerical analysis. The soil-pile integrated element avoids using discrete soil spring elements, significantly reducing the modelling and computing efforts. The verification examples demonstrate that the proposed soil-pile integrated element has high accuracy and efficiency in geometrically nonlinear analysis.

Distinguishing major depressive disorder from bipolar disorder in remission: A brain structural network analysis

BackgroundIt is challenging to differentiate major depressive disorder (MDD) from bipolar disorder (BD) in depression and remission. To exclude the potential influence of depressive episodes, we compared the white matter (WM) network between MDD and BD patients in remission to find disease-specific alterations in MDD and BD, and then distinguish these two affective disorders. MethodsWe recruited 33 patients with remitted MDD (rMDD), 54 patients with remitted BD (rBD), and 60 healthy controls (HCs). Diffusion tensor imaging and high-resolution 3D T1-weighted image were acquired. Global and nodal topological parameters were used to depict the alterations of the whole-brain WM network. ResultsWe found that rMDD displayed increased global network efficiency (Eglob) and local network efficiency (Eloc) compared with HCs, whereas we found no significance between rBD and HCs. Compared with rBD and HCs, patients in the rMDD group showed increased nodal degree and nodal efficiency, and decreased nodal shortest path length in the four cerebral regions, including the right calcarine fissure (CAL.R), right cuneus (CUN.R), left lingual gyrus (LING.L), and left middle occipital gyrus (MOG.L). We did not find any rBD specific changes of nodal topological metrics. LimitationsThe main limitation is the possible effects of medication and BD subtypes on the results. ConclusionsOur findings indicate that rMDD exhibited elevated global properties compared with HCs group, and increased nodal properties in the CAL.R, CUN.R, LING.L, and MOG.L specifically compared with rBD and HCs, which may underlie the distinction of the two affective disorders in remission.

Discrimination of Microseismic Events in Coal Mine Using Multifractal Method and Moment Tensor Inversion

Discrimination of various microseismic (MS) events induced by blasting and mining in coal mines is significant for the evaluation and forecasting of rock bursts. In this paper, multifractal and moment tensor inversion methods were used to investigate the waveform characteristics and focal mechanisms of different MS events in a more quantitative way. The multifractal spectrum calculation results indicate that the three types of MS waveform have different distribution ranges in the multifractal parameters of ∆α and Δf(α). The results show that the blasting schemes also have a great influence on MS waveform characteristics. Consequently, the multifractal parameters of ∆α and Δf(α) can be used to discriminate different MS events. Further, the focal mechanisms of MS events were calculated by seismic moment tensor inversion. The results show that an explosion is not the dominant mechanism of deep-hole blasting MS events, and the CLVD and DC components account for an important proportion, indicating that some additional processes occur during blasting. Moreover, the coal-rock fracture MS events are characterized by compression implosion or compression/shear implosion mixed focal mechanisms, while the overburden movement MS events are tensile explosion or tensile/shear explosion mixed focal mechanisms. The focal mechanisms and nodal plane parameters have close relationships with the inducing factors and occurrence processes of MS events.

Towards an Improved Pathological Node Classification for Prognostic Stratification of Patients With Oral Cavity Squamous Cell Carcinoma: Results From a Nationwide Registry Study.

BackgroundTo assess the prognostic significance of different nodal parameters [i.e., number of pathologically positive nodes, log odds of positive lymph nodes, lymph node ratio (LNR), and extra-nodal extension (ENE)] in Taiwanese patients with oral cavity squamous cell carcinoma (OCSCC), and to devise an optimized pN classification system for predicting survival in OCSCC.MethodsA total of 4287 Taiwanese patients with first primary OCSCC and nodal metastases were enrolled. Cox proportional hazards regression analysis with the spline method was applied to identify the optimal cut-off values for LNR, log odds of positive lymph nodes, and number of pathologically positive nodes.ResultsOn multivariable analysis, we identified a LNR ≥0.078/0.079, the presence of at least three pathologically positive nodes, and ENE as independent prognosticators for 5-year disease-specific survival (DSS) and overall survival (OS) rates. We therefore devised a four-point prognostic scoring system according to the presence or absence of each variable. The 5-year DSS and OS rates of patients with scores of 0−3 were 70%/62%/50%/36% (p <0.0001) and 61%/52%/40%25%, respectively (p <0.0001). On analyzing the AJCC 2017 pN classification, patients with pN3a displayed better survival rates than those with pN2 disease. The 5-year DSS and OS rates of patients with pN1/pN2/pN3a/pN3b disease were 72%/60%/67%/43% (p <0.0001) and 63%/51%/67%/33%, respectively (p <0.0001).ConclusionsThree nodal parameters (i.e., a LNR ≥0.078/0.079, the presence of at least three pathologically positive nodes, and ENE) assessed in combination provided a better prognostic stratification than the traditional AJCC pN classification.

White matter structural network alterations in congenital bilateral profound sensorineural hearing loss children: A graph theory analysis

Functional magnetic resonance imaging (fMRI) studies have revealed a functional reorganization in patients with sensorineural hearing loss (SNHL). The structural basement of functional changes has also been investigated recently. Graph theory analysis brings a new understanding of the structural connectome and topological features in central neural system diseases. However, little is known about the structural network connectome changes in SNHL patients, especially in children. We explored the differences in topologic organization, rich-club organization, and structural connection between children with congenital bilateral profound SNHL and normal hearing under the age of three using graph theory analysis and probabilistic tractography. Compared with the normal-hearing (NH) group, the SNHL group showed no difference in global and nodal topological parameters. Increased structural connection strength were found in the right cortico-striatal-thalamus-cortical circuity. Decreased cross-hemisphere connections were found between the right precuneus and the left auditory cortex as well as the left subcortical regions. Rich-club organization analysis found increased local connection in the SNHL group. These results revealed structural organizations after hearing deprivation in congenital bilateral profound SNHL children.

Inverse nodal problem for conformable Sturm-Liouville operator with jump conditions

We consider a conformable fractional Sturm-Liouville problem with the discontinuous(or jump) condition inside the interval. The asymptotic formulas for the eigenvalues, nodal parameters (nodal points and nodal lengths) of this problem are calculated by the modified Pr?fer substitutions. Also, using these asymptotic formulas, an explicit formula for the potential functions is given. After all, we discuss Lipschitz stability for the considered problem.

The use of thin-walled structures for the sustainable development of agro-industrial systems and facilities

The issues of optimal use of strength resources of materials from which elements of thin-walled objects of the agro-industrial complex are made for the purpose of sustainable development of agricultural production are currently coming to the fore. In this regard, the development of modern algorithms for the numerical analysis of the processes of physically nonlinear deformation of thin-walled objects of agro-industrial complex of various sizes and shapes is becoming a rather urgent topic. The article proposes an algorithm for the finite element analysis of physically nonlinear deformation of thin-walled objects of the agro-industrial complex, taking into account the transverse shear, based on the hypotheses of the theory of plastic flow The element of discretization of the thin-walled object of the agricultural and industrial complex was a four-node fragment of its middle surface. The stiffness matrix of this sampling unit was obtained in the process of minimizing the Lagrange functional with respect to the sought nodal parameters, which were the components of the step vector of displacement and their first-order partial derivatives, as well as the components of the step vector of the angles of rotation of the normal.

Network flow calculation based on the directional nodal potential method for meshed heating networks

Heating flow calculation method can determine the temperature and pressure of each node and the mass flow of each branch in the energy network. Since the heating network flow is coupling network flow, it is difficult to deal with discontinuous nodal parameters at the mixing node. The objective of this paper is to obtain characteristics in meshed heating networks based on the physical mechanism analysis and develop a decoupling calculation method for network flow. First, pressure and temperature are proved as two types of physical potentials, for thermal potential energy flow and pressure potential energy flow, respectively. Then, nodal potential energy flow conservation is obtained as the basic rule for the potential energy flow. Due to the transmission speed differences between pressure and thermal potential energy flow, the inflow temperature is different. Using the nodal pressure differences to describe the flow direction of the coupling network flow, temperatures of inflows and outflows at the mixing node are determined. Finally, the directional nodal potential method (DNPM) is developed. The results show that the proposed DNPM can deal with the complex networks containing several potential energy flows with higher convergence speed and more concise modeling formulation.

Strength calculation algorithm for shell structures based on a four-node discretization element

The article describes a method for calculating shell structures taking into account transverse shear deformations during elastoplastic deformation. The geometric relationships between the increments of deformations in an arbitrary layer of the shell and the increments of the components of the displacement vector, the components of the vector of inclination angles of the normal are obtained on the basis of the hypothesis of S.P. Tymoshenko. The slope of the normal and the increment of the slope are performed from the original position of the normal. The physical relationships between the increments of the stress tensor components and the increments of the components of the deformation tensor at the loading step were obtained on the basis of the hypothesis that they were proportional, based on the deformation theory of plasticity. In the finite element implementation of the developed algorithm, a four-node fragment of the middle surface of the shell structure with nodes located at the vertices of the quadrangular fragment was used. The increments of the displacement vector components, their first derivatives with respect to curvilinear coordinates, as well as the increments of the components of the normal rotation angle vector were selected as the nodal variable parameters of the four-node finite element at the loading step. The size of the stiffness matrix of the four-node finite element was 44x44. The developed algorithm was tested on test problems for calculating a cylindrical shell using a duralumin alloy with a deformation diagram in the form of a two-link broken line as a material.

High-resolution at 3T for in vivo derivative NMR spectroscopy in medical diagnostics of ovarian tumor: exact quantification by shape estimations

High-resolution at 3T for in vivo derivative NMR spectroscopy in medical diagnostics of ovarian tumor: exact quantification by shape estimations

A novel framework for high-speed cam curve synthesis: piecewise high-order interpolation, pointwise scaling and piecewise modulation

This study proposes a novel mathematical framework for optimal synthesis of high-speed cam curves, comprising three key aspects: piecewise high-order interpolation (PHOI), pointwise scaling and piecewise modulation. In this framework, PHOI is responsible for constructing a smooth and faithful cam curve under multiorder motion constraints (including displacement, velocity, acceleration and jerk), and pointwise scaling and piecewise modulation are further introduced for optimal tuning of nodal and internodal motion parameters. Mathematically, the combination of PHOI, pointwise scaling and/or piecewise modulation will enable a full and direct control of local/global motion parameters for enhanced high-speed performance of the synthesized cam curve. Concerning the validation of this framework, three detailed numerical examples (curve reconstruction, kinematic and dynamic optimizations) are performed. The excellent interpolation accuracy of PHOI, improved motion continuity by pointwise scaling, lowered motion peaks by pointwise scaling and piecewise modulation, and reduced dynamic error of the optimized cam curve collectively demonstrate the effectiveness and versatility of the proposed framework in data-driven reconstruction and application-oriented optimization of high-speed precision cam profiles.

Whole-body diffusion-weighted MRI in lymphoma-comparison of global apparent diffusion coefficient histogram parameters for differentiation of diseased nodes of lymphoma patients from normal lymph nodes of healthy individuals.

Morphologic features yield low diagnostic accuracy to distinguish between diseased and normal lymph nodes. The purpose of this study was to compare diseased lymphomatous and normal lymph nodes using global apparent diffusion coefficient (gADC) histogram parameters derived from whole-body diffusion-weighted MRI (WB-DWI). 1.5 Tesla WB-DWI of 23 lymphoma patients and 20 healthy volunteers performed between 09/2010 and 07/2015 were retrospectively reviewed. All diseased nodal groups in the lymphoma cohort and all nodes visible on b900 images in healthy volunteers were segmented from neck to groin to generate a total diffusion volume (tDV). A connected component-labelling algorithm separated spatially distinct nodes. Mean, median, skewness, kurtosis, minimum, maximum, interquartile range (IQR), standard deviation (SD), 10th and 90th centile of the gADC distribution were derived from the tDV of each patient/volunteer and from spatially distinct nodes. gADC and regional nodal ADC parameters were compared between malignant and normal nodes using t-tests and ROC curve analyses. A P value ≤0.05 was deemed statistically significant. Mean, median, IQR, 10th and 90th centiles of gADC and regional nodal ADC values were significantly lower in diseased compared with normal lymph nodes. Skewness, kurtosis and tDV were significantly higher in lymphoma. The SD, min and max gADC showed no significant difference between the two groups (P>0.128). The diagnostic accuracies of gADC parameters by AUC from highest to lowest were: 10th centile, mean, median, 90th centile, skewness, kurtosis and IQR. A 10th centile gADC threshold of 0.68×10-3 mm2/s identified diseased lymphomatous nodes with 91% sensitivity and 95% specificity. WB-DWI derived gADC histogram parameters can distinguish between malignant lymph nodes of lymphoma patients and normal lymph nodes of healthy individuals.

Disrupted Topological Organization in White Matter Networks in Unilateral Sudden Sensorineural Hearing Loss.

Sudden sensorineural hearing loss (SSNHL) is a sudden-onset hearing impairment that rapidly develops within 72 h and is mostly unilateral. Only a few patients can be identified with a defined cause by routine clinical examinations. Recently, some studies have shown that unilateral SSNHL is associated with alterations in the central nervous system. However, little is known about the topological organization of white matter (WM) networks in unilateral SSNHL patients in the acute phase. In this study, 145 patients with SSNHL and 91 age-, gender-, and education-matched healthy controls were evaluated using diffusion tensor imaging (DTI) and graph theoretical approaches. The topological properties of WM networks, including global and nodal parameters, were investigated. At the global level, SSNHL patients displayed decreased clustering coefficient, local efficiency, global efficiency, normalized clustering coefficient, normalized characteristic path length, and small-worldness and increased characteristic path length (p < 0.05) compared with healthy controls. At the nodal level, altered nodal centralities in brain regions involved the auditory network, visual network, attention network, default mode network (DMN), sensorimotor network, and subcortical network (p < 0.05, Bonferroni corrected). These findings indicate a shift of the WM network topology in SSNHL patients toward randomization, which is characterized by decreased global network integration and segregation and is reflected by decreased global connectivity and altered nodal centralities. This study could help us understand the potential pathophysiology of unilateral SSNHL.

On the Lipschitz stability of inverse nodal problem for Dirac system

Inverse nodal problem on Dirac operator is determination problem of the parameters in the boundary conditions, number m and potential function V by using a set of nodal points of a component of two component vector eigenfunctions as the given spectral data. In this study, we solve a stability problem using nodal set of vector eigenfunctions and show that the space of all V functions is homeomorphic to the partition set of all space of asymptotically equivalent nodal sequences induced by an equivalence relation. Moreover, we give a reconstruction formula for the potential function as a limit of a sequence of functions and associated nodal data of one component of vector eigenfunction. Our technique depends on the explicit asymptotic expressions of the nodal parameters and, it is basically similar to [1, 2] which is given for Sturm-Liouville and Hill's operators, respectively.

White Matter Structural Network Analysis to Differentiate Alzheimer's Disease and Subcortical Ischemic Vascular Dementia.

To explore the evaluation of white matter structural network analysis in the differentiation of Alzheimer’s disease (AD) and subcortical ischemic vascular dementia (SIVD), 67 participants [31 AD patients, 19 SIVD patients, and 19 normal control (NC)] were enrolled in this study. Each participant underwent 3.0T MRI scanning. Diffusion tensor imaging (DTI) data were analyzed by graph theory (GRETNA toolbox). Statistical analyses of global parameters [gamma, sigma, lambda, global shortest path length (Lp), global efficiency (Eg), and local efficiency (Eloc)] and nodal parameters [betweenness centrality (BC)] were obtained. Network-based statistical analysis (NBS) was employed to analyze the group differences of structural connections. The diagnosis efficiency of nodal BC in identifying different types of dementia was assessed by receiver operating characteristic (ROC) analysis. There were no significant differences of gender and years of education among the groups. There were no significant differences of sigma and gamma in AD vs. NC and SIVD vs. NC, whereas the Eg values of AD and SIVD were statistically decreased, and the lambda values were increased. The BC of the frontal cortex, left superior parietal gyrus, and left precuneus in AD patients were obviously reduced, while the BC of the prefrontal and subcortical regions were decreased in SIVD patients, compared with NC. SIVD patients had decreased structural connections in the frontal, prefrontal, and subcortical regions, while AD patients had decreased structural connections in the temporal and occipital regions and increased structural connections in the frontal and prefrontal regions. The highest area under curve (AUC) of BC was 0.946 in the right putamen for AD vs. SIVD. White matter structural network analysis may be a potential and promising method, and the topological changes of the network, especially the BC change in the right putamen, were valuable in differentiating AD and SIVD patients.

Galerkin approximation with quintic B-spline as basis and weight functions for solving second order coupled nonlinear Schrödinger equations

In this article, the Galerkin method, based on quintic B-spline function as the shape and weight functions is described for the numerical solution of the second order coupled nonlinear Schrödinger equations. Finite difference and Crank–Nicolson schemes are used to discretize the time derivative and nodal parameters respectively. Three numerical problems are presented to assess the accuracy and capability of the proposed method. The maximum errors, norms and conserved quantities are calculated. The obtained numerical results show that the present scheme with higher order B-spline as basis and weight functions performs well and accurately. The numerical results are compared with analytical and published results.