First-order Components Research Articles

A nonmode-shape-based model updating method for offshore structures using extracted components from measured accelerations

As the precision of model updating based on modal parameters usually depends on the accuracy of mode shapes, which are frequently affected by measurement noise and spatial incompleteness, there has been paid much attention to the research on this topic arising from the practical marine engineering. To overcome this challenging issue, a novel nonmode-shape-based model updating method has been proposed in this paper for reliable and effective identification of complex engineering structures. Based on the measured signals from accelerometers, the acceleration components corresponding to the first several natural frequencies of the structure have been extracted. Following that, a series of linear equations containing the updating coefficients have been established with the fuse of modal information from the baseline model to determinate the change in structural parameters. The major contributions of this research include: (1) The underlying principle of the proposed method is based on the time-dependent acceleration components instead of mode shapes in traditional methods to construct more equations, which represents more structural parameters such as the mass, stiffness and damping properties under considerations and (2) The isolation of noise and acceleration components has been achieved by the developed complex exponential decomposition technique, leading to the proposed method with the capability of denoising suitable for marine engineering applications. Moreover, the analytical signal can also be obtained to construct equations for the calculation of structural damping property using Hilbert transform. To verify the effectiveness of the proposed method, a numerical example of the cantilever beam has been examined under the consideration of spatial completeness, spatial incompleteness and measurement noise. Results have shown that the updating coefficients of the model can be accurately calculated using more equations constructed purely by the first-order acceleration components in the proposed method. Meanwhile, the absolute maximum error of the natural frequency has been reduced from 4.711% to 0.785% for the acceleration containing 5% measurement noise. Next, a jacket platform model has been established to verify the performance of the proposed method applicable to complex engineering structures. It has been noted that the maximum error (0.957%) of the first three natural frequencies of the updated model has been evaluated. Finally, a set of experiments of cantilever beams have been carried out. These tests have been designed according to the number and location of the cracks. The maximum error (1.559%) of the natural frequencies has been observed as compared with the real results, which have further demonstrated the effectiveness of the proposed method.

Systemic Inflammation Contributes to the Association Between Childhood Socioeconomic Disadvantage and Midlife Cardiometabolic Risk.

Childhood socioeconomic disadvantage is associated with increased risk for chronic inflammation and cardiometabolic disease at midlife. As it is presently unknown whether inflammation mediates the relationship between childhood socioeconomic status (SES) and adulthood cardiometabolic risk, we investigated associations between retrospectively reported childhood SES, circulating levels of inflammatory markers, and a latent construct of cardiometabolic risk in midlife adults. Participants were 1,359 healthy adults aged 30-54 (Adult Health and Behavior Iⅈ 52% women, 17% Black) who retrospectively reported childhood SES (parental education, occupational grade). Measures included plasma interleukin (IL)-6, C-reactive protein (CRP), and cardiometabolic risk factors. Structural equation modeling was conducted, with cardiometabolic risk modeled as a second-order latent variable with adiposity, blood lipids, glucose control, and blood pressure as first-order components. Lower childhood SES was associated with greater risk for cardiometabolic disease at midlife (β = -0.08, CI[-0.04, -0.01], p = .01) in models adjusted for demographics, but this association was attenuated in models that adjusted for adulthood SES and health behaviors. In fully-adjusted models, the relationship between lower childhood SES and adult cardiometabolic risk was partially explained by higher circulating levels of CRP (β = -0.05, CI[-0.02, -0.01], p = .001), but not by IL-6. In an exploratory model, lower adulthood SES was also found to independently contribute to the association between childhood SES and adult cardiometabolic risk (β = -0.02, CI[-0.01, -0.001], p = .02). The current study provides initial evidence that systemic inflammation may contribute to childhood socioeconomic disparities in cardiometabolic risk in midlife. Future work would benefit from prospective investigation of these relationships.

A novel inductive angular displacement sensor based on time-grating

The paper proposes a novel inductive angular displacement sensor to measure large-diameter hollow rotating mechanical components in large science facilities. The sensor design includes a stator, a rotor with two layers of windings. The stator is fabricated according to the dimension of the rotor, which is the large-diameter hollow rotary mechanical components. Based on the principle of electromagnetic induction, the theoretical model of the proposed sensor is acquired by mathematical equations in detail. The proposed sensor design ensures integration of the large-diameter hollow rotating mechanical components with the stator, and solves the problem that the sensors cannot be coaxially installed in the closed-loop control process of large mechanical rotating parts. The performance of the sensor is evaluated by tests of the prototype sensor fabricated by printed circuit board technology, which manifests the effectiveness of the proposed sensor. The results demonstrate the value of original dynamic relative error is ±97.6″ over 0°–360° range, and the measurement error mainly includes first-order and second-order harmonic components. Therefore, the original errors are reduced by optimizing the angular displacement algorithm of the sensor, optimized results demonstrate the final relative accuracy of the sensor is ±3.5″ over the 0°–360° measurement range.

On the design of scalable networks rejecting first order disturbances

This paper is concerned with the problem of designing distributed control protocols for network systems affected by delays and disturbances consisting of a first-order polynomial component and a residual signal. Specifically, we propose the use of a multiplex architecture to design distributed control protocols to reject polynomial disturbances up to ramps and guarantee a scalability property that prohibits the amplification of residual disturbances. For this architecture, we give a sufficient condition on the control protocols to guarantee scalability and ramps rejection. The effectiveness of the result, which can be used to study networks of nonlinearly coupled nonlinear agents, is illustrated via a robot formation control problem.

Prediction for Various Drought Classes Using Spatiotemporal Categorical Sequences

Drought frequently spreads across large spatial and time scales and is more complicated than other natural disasters that can damage economic and other natural resources worldwide. However, improved drought monitoring and forecasting techniques can help to minimize the vulnerability of society to drought and its consequent influences. This emphasizes the need for improved drought monitoring tools and assessment techniques that provide information more precisely about drought occurrences. Therefore, this study developed a new method, Model-Based Clustering for Spatio-Temporal Categorical Sequences (MBCSTCS), that uses state selection procedures through finite mixture modeling and model-based clustering. The MBCSTCS uses the functional structure of first-order Markov model components for modeling each data group. In MBCSTCS, the suitable order K of the components is selected by Bayesian information criterion (BIC). In MBCSTCS, the estimated mixing proportions and the posterior probabilities are used to compute probability distribution associated with the future steps of transitions. Furthermore, MBCSTCS predicts drought occurrences in future time using spatiotemporal categorical sequences of various drought classes. The MBCSTCS is applied to the six meteorological stations in the northern area of Pakistan. Moreover, it is found that MBCSTCS provides expeditious information for the long-term spatiotemporal categorical sequences. These findings may be helpful to make plans for early warning systems, water resource management, and drought mitigation policies to decrease the severe effects of drought.

Higher-order harmonic induced wave resonance for two side-by-side boxes in close proximity

Wave resonance in a narrow gap formed by two boxes in the side-by-side arrangement is investigated by employing a numerical wave flume based on the OpenFOAM® package. In the present study, the main focus lies in the exploration of the nonlinear resonant behavior induced by the second- and third-order harmonic components which occur around half and one third of the resonant frequencies. A wide range of incident wave frequencies is considered, by which the higher-order harmonic induced wave resonance at lower wave frequencies is discussed. By the harmonic analysis, it is revealed that at the resonant frequency the first-order harmonic component dominates the wave resonance and the second-order effect is minor, which coincides with the conclusion drawn in the previous study. However, around half or one third of the resonant frequencies, the first-order harmonic component is in good agreement with the linear potential flow solutions, but the second- or third-order harmonic component is significant, causing the corresponding higher-order harmonic induced wave resonance. In addition, the numerical results show that the second- and third-order harmonic induced wave resonances only influence the wave properties inside the narrow gap, such as the wave response in the narrow gap and the horizontal wave forces on the boxes. The wave responses around the two-box system, the vertical wave forces on the boxes and the reflection and transmission coefficients are hardly affected by the wave resonance around the corresponding half and one third of the resonant frequencies. The higher-order harmonic induced normalized wave elevation in the narrow gap increases with the increase in incident wave height, implying the increased influence of the free surface nonlinearity.

Shaft system profile reconstruction method based on L-shaped axial four-probe method

The inability to extract spatial axis and radial multi-error coupling phenomenon exists in the process of axial profile reconstruction, which is essentially a first harmonic suppression problem as well as a multi-error decoupling problem. In this paper, a four-probe system is constructed based on an L-shaped arrangement in two adjacent planes. First, the mathematical model of the first harmonic suppression problem of the shaft system is established in the first plane, and the first harmonic component of roundness error is used as the axial reference for reconstructing the profile, and the value of the first-order harmonic component is solved by theoretical derivation, and the spatial axis of the reconstructed shaft system profile is fitted with it, which proves the correctness of the established mathematical model by the data simulation. Then, the radial mixed error detection is carried out in two adjacent planes in the axial direction, and the results measured at the two measurement positions are analyzed theoretically to obtain the tilt error decoupling formula. It breaks through the limitation that the error separation online detection cannot be performed in the standard ball measurement method. The experiment verifies that the accuracy of the spatial axis is improved by up to 0.5 μm after decoupling the tilt error, and the accuracy of the reconstructed circularity profile of a single section is improved by up to 2.657 mm. In the comparison experiment with the standard ball measurement method, the difference of the measured roundness error between the two methods does not exceed 1.2 μm, which proves that the online inspection method proposed in this paper can guarantee the accuracy of the reconstructing circularity profile.

Prediction of Drought Severity Using Model-Based Clustering

Drought is a common climatic extreme that frequently spreads across large spatial and time scales. It affects living standard of people throughout the globe more than any other climate extreme. Therefore, the present study proposed a new technique, known as model-based clustering of categorical drought states sequences (MBCCDSS), for monthly prediction of drought severity to timely inform decision-makers to anticipate reliable actions and plans to minimize the negative impacts of drought. The potential of the proposed technique is based on the expectation-maximization (EM) algorithm for finite mixtures with first-order Markov model components. Moreover, the proposed approach is validated on six meteorological stations in the northern area of Pakistan. The study outcomes provide the basis to explore and frame more essential assessments to mitigate drought impacts for the selected stations.

New slant range model and azimuth perturbation resampling based high-squint maneuvering platform SAR imaging

Strong spatial variance of the imaging parameters and serious geometric distortion of the image are induced by the acceleration and vertical velocity in a high-squint synthetic aperture radar (SAR) mounted on maneuvering platforms. In this paper, a frequency-domain imaging algorithm is proposed based on a novel slant range model and azimuth perturbation resampling. First, a novel slant range model is presented for mitigating the geometric distortion according to the equal squint angle curve on the ground surface. Second, the correction of azimuth-dependent range cell migration (RCM) is achieved by introducing a high-order time-domain perturbation function. Third, an azimuth perturbation resampling method is proposed for azimuth compression. The azimuth resampling and the time-domain perturbation are used for correcting first-order and high-order azimuthal spatial-variant components, respectively. Experimental results illustrate that the proposed algorithm can improve the focusing quality and the geometric distortion correction accuracy of the imaging scene effectively.

Relevance of longitudinal fields of paraxial optical vortices

Longitudinal electromagnetic fields generally become comparable with the usually dominant transverse components in strongly focused, non-paraxial beams. For paraxial optical vortex modes it is highlighted here how their angular momentum properties produce longitudinal fields that in general must be accounted for. First-order longitudinal components of quantized Laguerre–Gaussian modes are derived and numerically studied with respect to the paraxial parameter, highlighting light-matter and spin-orbit interactions that stem from the longitudinal fields of paraxial beams in free space. New restrictions are cast on the validity of neglecting longitudinal fields for paraxial optical vortices interacting with atoms, molecules and other nanostructures.

Population Pharmacokinetic Modelling and Simulation to Determine the Optimal Dose of Nanoparticulated Sorafenib to the Reference Sorafenib.

Sorafenib, an oral multikinase inhibitor, exhibits a highly variable absorption profile due to enterohepatic reabsorption and poor solubility. SYO-1644 improved the solubility of sorafenib by nanoparticulation technology leading to enhanced bioavailability. To evaluate the pharmacokinetically equivalent dose of SYO-1644 to the reference Nexavar® 200 mg, a randomized, open-label, replicated two-period study was conducted in healthy volunteers. A total of 32 subjects orally received a single dose of the following assigned treatment under a fasted state in the first period and repeated once more in the second period with a two-week washout: SYO-1644 100, 150 and 200 mg and Nexavar® 200 mg. Pharmacokinetic (PK) samples were collected up to 168 h post-dose. The PK profile was evaluated by both non-compartmental analysis and population PK method. With the final model, 2 × 2 crossover trial scenarios with Nexavar® 200 mg and each dose of SYO-1644 ranging from 100 to 150 mg were repeated 500 times by Monte Carlo simulation, and the proportion of bioequivalence achievement was assessed. Transit absorption compartments, followed by a one-compartment model with first-order elimination and enterohepatic reabsorption components were selected as the final model. The simulation results demonstrated that the SYO-1644 dose between 120 and 125 mg could yielded the highest proportion of bioequivalence.

Anti-Resonance Frequency Control by Span-Tuning Dynamic Vibration Absorber for Brush Cutter Vibration Reduction

Abstract Significant handle vibrations often occur during mowing operation even with anti-vibration type brush cutters. This is often caused by combined-bending natural mode of the main pipe and driveshaft which is mainly excited by cutting head rotational force. In this study, we focused on the placement span of the rubber bushings that support the driveshaft to suppress this kind of resonance. More specifically, we have designed a new component, called a span-tuning dynamic vibration absorber (ST-DVA), which utilizes the bending mode of the driveshaft that is determined by the placement span of rubber bushings. Analysis results of the finite element method (FEM) showed that the ST-DVA generated anti-resonance at a specific point on the main pipe under the first-order inertial force of the cutting head. We also succeeded in controlling anti-resonance frequency under the excitation. In actual measurements at the target frequency, handle vibration of the first-order component of the cutting head could be reduced by 51% and overall handle vibration could be reduced by 49% compared with those produced via equal-span rubber bushing placement. Hence, our study provides a design method that makes it possible to utilize the driveshaft, which a primary brush cutter component, as a dynamic vibration absorber by altering the placement span of the rubber bushings.

Testing measurement model of consumption value in relation to consumers’ new electronics products adoption behavior in Ho Chi Minh City

The aim of this study is to examine the measurement model for new products’ consumption value and investigate the relationship between consumption value, adoption intention of new products and adoption behaviour of new products. Based on preceding theories, the consumption value concept is proposed as a multidimensional formative construct in this work. This study adopts partial least squares structural equation modeling (PLS-SEM) technique to test both the measurement model and hypotheses based on a data set of 915 consumers who bought and owned at least one new personal electronic device within 6 months before the survey was conducted in Ho Chi Minh city. The results show that the overall consumption value of new products is a second – order multidimensional formative construct with five first-order components which were also shown to have significant weights in the overall consumption value in the context of new personal electronic products, consisting of functional value, epistemic value, unique value, economical value and emotional value. The nomological validity is confirmed when the consumption value construct is shown to have a positive impact on both new products adoption intention and adoption behavior.

Generation of nanosecond cylindrical vector beams in two-mode fiber and its applications of stimulated Raman scattering

We present the generation of the nanosecond cylindrical vector beams (CVBs) in a two-mode fiber (TMF) and its applications of stimulated Raman scattering. The nanosecond (1064 nm, 10 ns, 10 Hz) CVBs have been directly produced with mode conversion efficiency of ∼18 dB (98.4%) via an acoustically induced fiber grating, and then the stimulated Raman scattering signal is generated based on the transmission of the nanosecond CVBs in a 100-m-long TMF. The transverse mode intensity and polarization distributions of the first-order Stokes shift component (1116.8 nm) are consistent with the nanosecond CVBs pump pulse.

On Distance Statistics of First Arriving Multi-Paths in Indoor mm-Wave Communications

This paper presents a mathematical framework to evaluate distance statistics of first arriving multi-path components at millimeter wave (mm-Wave) frequencies in a typical indoor environment. The proposed modeling approach is based on a numerically tractable channel model that accounts for the line-of-sight (LoS) component and first-order reflection components from surrounding walls. Based on the derived statistics, an approximation for coverage probability of mm-Wave indoor wireless local area networks (WLAN)s is obtained. Further, the coverage probability for an access point (AP) to user node link is determined after accounting for blockage of LoS component and optimal antenna beamforming in the modeling framework. The analysis of coverage probability provides useful insights which can be applied to plan optimum AP location layout in a typical mm-Wave indoor WLAN.

On Goodness of WiFi Based Monitoring of Sleep Vital Signs in the Wild

WiFi channel state information (CSI) has emerged as a plausible modality for sensing different human vital signs, i.e., respiration and body motion, as a function of modulated wireless signals that travel between WiFi devices. Although a remarkable proposition, most of the existing research in this space struggles to withstand robust performance beyond experimental conditions. To this end, we take a careful look at the dynamics of WiFi signals under human respiration and body motions in the wild. We first characterize the WiFi signal components—multipath and signal subspace—that are modulated by human respiration and body motions. We extrapolate on a set of transformations, including first-order differentiation, max-min normalization and component projections, that faithfully explains and quantifies the dynamics of respiration and body motions on WiFi signals. Grounded in this characterization, we propose two methods: 1) a respiration tracking technique that models the peak dynamics observed in the time-varying signal subspace and 2) a body-motion tracking technique built with a multi-dimensional clustering of evolving signal subspace. Finally, we reflect on the manifestation of these techniques in a practical sleep monitoring application. Our systematic evaluation with over 550 hours of data from 5 users covering both line-of-sight (LOS) and non-line-of-sight (NLOS) settings shows that the proposed techniques can achieve comparable performance to purpose-built pulse-Doppler radar.

Distributions of Hyper-Local Configuration Elements to Characterize, Compare, and Assess Landscape-Level Spatial Patterns.

Even with considerable attention in recent decades, measuring and working with patterns remains a complex task due to the underlying dynamic processes that form these patterns, the influence of scales, and the many further implications stemming from their representation. This work scrutinizes binary classes mapped onto regular grids and counts the relative frequencies of all first-order configuration components and then converts these measurements into empirical probabilities of occurrence for either of the two landscape classes. The approach takes into consideration configuration explicitly and composition implicitly (in a common framework), while the construction of a frequency distribution provides a generic model of landscape structure that can be used to simulate structurally similar landscapes or to compare divergence from other landscapes. The technique is first tested on simulated data to characterize a continuum of landscapes across a range of spatial autocorrelations and relative compositions. Subsequent assessments of boundary prominence are explored, where outcomes are known a priori, to demonstrate the utility of this novel method. For a binary map on a regular grid, there are 32 possible configurations of first-order orthogonal neighbours. The goal is to develop a workflow that permits patterns to be characterized in this way and to offer an approach that identifies how relatively divergent observed patterns are, using the well-known Kullback–Leibler divergence.

Automatic wavefront reconstruction on single interferogram with spatial carrier frequency using Fourier transform

Optical interferometry can be applied to obtain the wavefront phase and reconstruct the three-dimensional wavefront by analyzing interference fringes. Single interferogram analysis based on two-dimensional Fourier transform is proposed. This method just needs to acquire and analyze single interferogram to solve the wavefront phase. Compared with phase-shift method, Single interferogram analysis can reduce experiment cost and the limitation of measuring environment like vibration, airflow and noise, and meet the requirement of real-time and dynamic interferometry. Because the wavefront phase information is included in the carrier frequency components of single interferogram, an image edge detection method is used to automatically extract the center and boundary of the first-order carrier component of the spatial spectrum of the interferogram in the frequency domain.

The trigonometric orthogonality of phase-stepping curves in grating-based x-ray phase-contrast imaging: Integral property and its implications for noise optimization.

Grating-based x-ray phase-contrast imaging (GPCI) is a promising technique for clinical applications as it can provide two newly emerging imaging modalities (differential phase-contrast and dark-field contrast) in addition to the conventional absorption contrast. As far, phase-stepping strategy is the most commonly used approach in GPCI to indirectly acquire differential phase-contrast and dark-field contrast. It is known that the obtained phase-stepping curves (PSCs) have the cosine property and the convolution property, leading to two types of information retrieval approaches in literature: the Fourier component analysis and the multi-order moment analysis. The purpose of this paper is to derive a new property of PSCs and apply the property to noise optimization for information retrieval. Based on the cosine expression of the flat PSC without the sample and the well-established convolution relationship between the flat PSC and the sample PSC, we reveal an important integral property of PSCs: the inner product of PSCs and an arbitrary function contains only zero-order and first-order components in the Fourier series. Furthermore, we apply the property to the direct multi-order moment analysis and propose a set of generalized forms including an optimal one in the presence of noise. To validate the effectiveness of our analysis, we compared the simulated and real experiment results retrieved by the original direct multi-order moment analysis with the ones retrieved by our proposed noise-optimal form. A significant improvement of noise performance by our method is observed and the improvement ratio in differential phase-contrast is consistent with our theoretical calculation (39.2%). In this paper, we reveal a new integral property of the acquired PSCs with and without samples in GPCI, which can be applied to information retrieval approaches like the direct multi-order moment analysis. Then we optimize these approaches to improve the noise performance, offering great potentials of dose reduction in practical applications.

Analysis of differences in vegetation phenology cycle of abandoned farmland, using harmonic analysis of time-series vegetation indices data: the case of Gwangyang City, South Korea

ABSTRACT Globally, countries have experienced substantial increases in farmland abandonment. Although vegetation phenology is a key factor for the classification of land use, understanding of the phenological change of abandoned farmland is lacking. Using harmonic analysis of NDVI and NDWI extracted from Landsat imagery, this study investigates the distinctive phenological characteristics of abandoned farmland, which contrasts with that of three other agricultural types (paddy, agricultural field, orchard) in the study site of Gwangyang City in Jeollanam Province, South Korea. The results suggest that abandoned farmland has higher overall greenness coverage and overall water content in vegetation than the other uses. In terms of both indices, abandoned farmlands changed with relatively less fluctuation than those of other uses, suggesting the existence of constant and unmanaged vegetation from ecological succession, which differs from crop fields that undergo cultivation procedures. The significant harmonic components differed among agricultural types and vegetation indices. In paddy, NDVI was explained with multiple, higher-order harmonic components, while in other types only first-order components met the 5% statistical significance level. With NDWI, land types were more clearly discernible, because of the different cultivation procedures involving water: wet-field method (paddy), dryland farming (orchard, agricultural field), and no cultivation (abandoned farmland). The analysis confirms that harmonic analysis could be useful in discerning abandoned farmland among areas of active agricultural use and shows that the statistical significance of harmonic terms can be employed as indicators of different agricultural types. The observed pattern of the geographic distribution of abandoned farmland has policy implications for the promotion of sustainable reuse of marginal farmland.