Quadratic Coefficients Research Articles

A generalisation of the method of regression calibration and comparison with Bayesian and frequentist model averaging methods

For many cancer sites low-dose risks are not known and must be extrapolated from those observed in groups exposed at much higher levels of dose. Measurement error can substantially alter the dose–response shape and hence the extrapolated risk. Even in studies with direct measurement of low-dose exposures measurement error could be substantial in relation to the size of the dose estimates and thereby distort population risk estimates. Recently, there has been considerable attention paid to methods of dealing with shared errors, which are common in many datasets, and particularly important in occupational and environmental settings. In this paper we test Bayesian model averaging (BMA) and frequentist model averaging (FMA) methods, the first of these similar to the so-called Bayesian two-dimensional Monte Carlo (2DMC) method, and both fairly recently proposed, against a very newly proposed modification of the regression calibration method, the extended regression calibration (ERC) method, which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. The quasi-2DMC with BMA method performs well when a linear model is assumed, but very poorly when a linear-quadratic model is assumed, with coverage probabilities both for the linear and quadratic dose coefficients that are under 5% when the magnitude of shared Berkson error is large (50%). For the linear model the bias is generally under 10%. However, using a linear-quadratic model it produces substantially biased (by a factor of 10) estimates of both the linear and quadratic coefficients, with the linear coefficient overestimated and the quadratic coefficient underestimated. FMA performs as well as quasi-2DMC with BMA when a linear model is assumed, and generally much better with a linear-quadratic model, although the coverage probability for the quadratic coefficient is uniformly too high. However both linear and quadratic coefficients have pronounced upward bias, particularly when Berkson error is large. By comparison ERC yields coverage probabilities that are too low when shared and unshared Berkson errors are both large (50%), although otherwise it performs well, and coverage is generally better than the quasi-2DMC with BMA or FMA methods, particularly for the linear-quadratic model. The bias of the predicted relative risk at a variety of doses is generally smallest for ERC, and largest for the quasi-2DMC with BMA and FMA methods (apart from unadjusted regression), with standard regression calibration and Monte Carlo maximum likelihood exhibiting bias in predicted relative risk generally somewhat intermediate between ERC and the other two methods. In general ERC performs best in the scenarios presented, and should be the method of choice in situations where there may be substantial shared error, or suspected curvature in the dose response.

The impact of modulational instability on coastal wave forecasting using quadratic models

Coastal wave forecasting over large spatial scales is essential for many applications (e.g., coastal safety assessments, coastal management and developments, etc.). This demand explains the necessity for accurate yet effective models. A well-known efficient modelling approach is the quadratic approach (often referred to as frequency-domain models, nonlinear mild-slope models, amplitude models, etc.). The efficiency of this approach stems from a significant modelling reduction of the original governing equations (e.g., Euler equations). Most significantly, the description of wave nonlinearity essentially collapses into a single mode coupling term determined by the quadratic interaction coefficients. As a result, it is expected that the efficiency achieved by the quadratic approach is accompanied by a decrease in prediction accuracy. In order to gain further insight into the predictive capabilities of this modelling approach, this study examines six different quadratic formulations, three of which are of the Boussinesq type and the other three are referred to as fully dispersive. It is found that while the Boussinesq formulations reliably predict the evolution of coastal waves, the predictions by the fully dispersive formulations tend to be affected by false developments of modulational instability. Consequently, the predicted wave fields by the fully dispersive formulations are characterized by unexpectedly strong modulations of the sea-swell part and associated unexpected infragravity response. The impact of the modulational instability on wave prediction based on the quadratic approach is further demonstrated using existing laboratory results of bichromatic and irregular wave conditions.

145 The effect of a plant secondary metabolite blend on energy metabolism and nutrient balance of beef cattle consuming low-quality warm season grass hay

Abstract Plant secondary metabolites (PSM) such as condensed tannins, hydrolysable tannins, saponins and essential oils purportedly impact rumen fermentation at low inclusion rates in beef cattle diets. Twelve steers (347 ± 23 kg BW) of British and continental influence were allocated to 1 of 4 replicated 3 x 3 Latin squares. Latin squares each had 14 d periods (10 d adaptation and 4 d for sample collection). All cattle were fed ground warm-season hay (89.5% DM, 92.8% OM, 65.9% NDF, 43.6% ADF, 6.70% CP) at 1.5% of BW (DM-basis) and supplemented with soybean meal at 0.18% of BW (DM-basis) once daily. Treatments consisted of a blend of tannins, saponins and essential oils provided at 0% (Control), 0.1% (Low) and 0.3% (High) of hay offering. Treatments were mixed with daily soybean meal allotment and provided before feeding of hay. Urine and feces were completely collected from d 11 through 14 at 0730 h and daily amounts of urine and feces produced were measured gravimetrically. Measures of gaseous exchange were determined via indirect calorimetry on d 13 and 14. Open-circuit respiration calorimeters (91.4 × 91.4 × 191.2 cm) were used to collect respired gas and ruminal methane production. Total oxygen consumption and production of carbon dioxide and methane were calculated from the difference in concentration of oxygen, carbon dioxide, and methane from air exhausted from each calorimeter and concentration of oxygen, carbon dioxide, and methane in ambient air and multiplied by amounts of air flowing from each calorimeter standardized for temperature, pressure, and humidity. Data were analyzed for a Latin square using the MIXED procedure of SAS with fixed effect of treatment, period and square and random effect of steer. Linear and quadratic contrast coefficients were assigned using PROC IML for uneven spacing of treatments. Significance was declared when P ≤ 0.05. Per experimental design, forage N and OM intake did not differ (P ≥ 0.77). Apparent total tract digestion of OM, NDF and ADF did not differ (P ≥ 0.66) among treatments. Fecal nitrogen excretion, and the percentage of N excreted in feces increased linearly (P = 0.01). N balance tended (P = 0.08) to decrease linearly with increasing PSM supplemented. Methane (L/kg DMI) was not affected (P = 0.28) by treatments. Methane, GE, DE, and ME (mcal/kg DMI) was unaffected (P = 0.19) by treatment. Under the conditions of this experiment, a blend of PSM had little effect on rumen fermentation or energy metabolism in beef steers.

Inflation in symmergent metric-Palatini gravity

In this paper, we study the cosmological inflation phenomenon in symmergent gravity theory. Symmergent gravity is a novel framework which merges gravity and the standard model (SM) so that the gravity emerges from the matter loops and restores the broken gauge symmetries along the way. Symmergent gravity is capable of inducing the gravitational constant G and the quadratic curvature coefficient cO from the loop corrections of the matter sector in a flat space-time. In the event that all the matter fields, including the beyond the standard model (BSM) sector, are mass degenerate, the vacuum energy can be expressed in terms of G and cO . The parameter which measures the deviation from the mass degeneracy is dubbed α̂. The parameters, cO and α̂, of symmergent gravity convey the information about the fermion and boson balance in the matter (SM+BSM) sector in number and in mass, respectively. In our analysis, we have investigated the space of the symmergent parameters cO and α̂ wherein they produce results that comply with the inflationary observables ns , r, and dns /d ln k.We have shown that the vacuum energy together with the quadratic curvature term arising in the symmergent gravity prescription are capable of inflating the universe provided that the quadratic curvature coefficient cO is negative (which corresponds to fermion dominance in number in the matter sector) and the deviation from the mass degeneracy in the matter sector is minute for both boson mass dominance and fermion mass dominance cases.

To Evaluate the Age–Happiness Relationship, Look Beyond Statistical Significance

The persistent contentiousness of research on the age–happiness relationship is puzzling; it should be possible to gain clarity and consensus about how to address the question effectively. In this paper I show that a key reason for the lack of clarity consists of overreliance on statistical significance as a means of evaluating empirical results. The statistical significance of a quadratic specification (age plus age-squared) is often taken as evidence in support of a ‘u-shaped’ relationship between age and happiness. But statistical significance on its own cannot tell us whether the age–happiness relationship is ‘u-shaped’ (nor indeed whether it takes any other shape). On the contrary, statistical significance can mislead us about it: a set of quadratic age coefficients can be ‘significant’ even when the relationship is obviously characterised by a different shape. When we have clarity on how to construct the analysis so that we can ‘see’ the underlying patterns in the data, it becomes obvious that the age–happiness relationship in European countries commonly shows other patterns; a u-shape is evident only in a minority of countries.

Developing crown width model for mixed forests using soil, climate and stand factors

Abstract The tree crown is a useful measure of tree vigour and is highly relevant to a tree's environmental adaptability. Crown allometry depends on environmental and stand conditions. Several studies have focussed on the effects of climate change and competitive intensity on the crown, but the regulatory role of soil resources and diversity on crown allometry and carbon allocation has been neglected. Data from 20,994 trees in 232 mixed forests collected between 2011 and 2019 were located near four major mountain ranges in northeast China. The proposed crown width model includes the stand developmental stage, soil, climate, competition intensity, species mixture, species diversity, structural diversity and their interactions. We observed that the cross‐species allometric scaling exponent does not conform to the universal scaling law. Our results showed that crown width increased with increasing soil bulk density, quadratic mean diameter and coefficient of diameter variation but decreased with increasing de Martonne aridity index, basal area, Simpson index and species mixture. The interaction between quadratic mean diameter and soil bulk density had a significant negative effect on crown width. The influence of a particular factor within the interaction term on crown width was modulated by the gradients of other factors. Furthermore, soil bulk density contributed more to crown width modelling than the aridity index, and structural diversity had a greater effect on crown width than species diversity. Synthesis. Our results provide new insights into the environmental variability of crown allometry in mixed forests under global change, which is critical for improving regional and global estimates of forest biomass and carbon stocks.

Castor-oil biobased foam: the effect of the composition on the physical and mechanical properties via a statistical mixture design.

PU foams are versatile materials that find applications in a wide range of products, from upholstery to packaging and construction. These foams consist primarily of two components, polyol and prepolymer, and their concentrations play a crucial role in determining their physical and mechanical properties. A second-order mixture design approach is used in this work to identify the significant components and their contributions on the physical-mechanical properties of biodegradable castor oil-based foams. The experimental design includes three components: two types of polyols and one prepolymer. These components are varied in nine distinct conditions to evaluate their effects on properties such as expansion rate, bulk density, compressive strength, and tensile strength. The Scheffé's quadratic model coefficients exhibit R-squared values higher than 0.84 in most cases. Chemical analysis using infrared spectroscopy confirms the successful formation of the urethane bond during the manufacturing process. The biobased foams developed in this work have densities ranging between 61 and 100 kg m-3, compressive modulus of 11-15 MPa and compressive strength between 273 and 429 kPa. The tensile modulus varies between 3.2 and 4.9 MPa, with a tensile strength in the range of 370-500 kPa. These results highlight the potential of biodegradable castor oil-based foams as promising alternative materials to traditional synthetic foams.

МЕТОДИЧЕСКИЙ ПОДХОД К ОЦЕНКЕ И РЕГУЛИРОВАНИЮ ДИСБАЛАНСА СПРОСА И ПРЕДЛОЖЕНИЯ ПРОФЕССИОНАЛЬНЫХ КАДРОВ НА РЕГИОНАЛЬНЫХ РЫНКАХ ТРУДА

The article presents a methodological approach to assessing and regulating the imbalance of demand and supply of professional personnel in regional labor markets. The author's methodology for assessing imbalances in professional personnel consists of four stages. In the first stage, the degree of regional differentiation is assessed according to the criteria of sectoral structural changes in employment and production based on indicators of regional asymmetry of structural changes, the quadratic coefficient of absolute structural changes, the integral coefficients of structural differences by K. Gatev, A. Salai, the V.M. Ryabtseva. In addition, the paper determines the dominant type of imbalance in the supply and demand of professional personnel (in the context of higher vocational training, secondary vocational training, nongovernmental education) in regional labor markets, it also classifies the subjects of the Russian Federation according to this criterion and identifies the differences in regional situations. The second stage is to assess the dynamic characteristics of the imbalance of professional personnel based on indicators of demand and supply volatility. The volatility of the types of imbalances in demand and supply of professional personnel is determined (in the context of higher vocational education, secondary vocational education, nongovernmental education), and an assessment and differentiation of regional situations is made based on the variability of imbalances. The third stage consists of assessing the determinants of the imbalance of professional personnel in regional labor markets. Based on groups of indicators that induce spatial differences in situations of imbalance in demand and supply of professional personnel in the constituent entities of the Russian Federation, these differences are identified, grouped by the dominant type of imbalance, according to the most significant factors (based on the tools of regression models). The contribution of each factor is determined. The fourth stage is to develop monitoring and tools for regulating regional labor markets in accordance with the type, dynamic characteristics and determinants of the imbalance of professional personnel.

The planar anodic Al2O3-ZrO2 nanocomposite capacitor dielectrics for advanced passive device integration

ABSTRACT The need for integrated passive devices (IPDs) emerges from the increasing consumer demand for electronic product miniaturization. Metal-insulator-metal (MIM) capacitors are vital components of IPD systems. Developing new materials and technologies is essential for advancing capacitor characteristics and co-integrating with other electronic passives. Here we present an innovative electrochemical technology joined with the sputter-deposition of Al and Zr layers to synthesize novel planar nanocomposite metal-oxide dielectrics consisting of ZrO2 nanorods self-embedded into the nanoporous Al2O3 matrix such that its pores are entirely filled with zirconium oxide. The technology is utilized in MIM capacitors characterized by modern surface and interface analysis techniques and electrical measurements. In the 95–480 nm thickness range, the best-achieved MIM device characteristics are the one-layer capacitance density of 112 nF·cm−2, the loss tangent of 4·10−3 at frequencies up to 1 MHz, the leakage current density of 40 pA·cm−2, the breakdown field strength of up to 10 MV·cm−1, the energy density of 100 J·cm−3, the quadratic voltage coefficient of capacitance of 4 ppm·V−2, and the temperature coefficient of capacitance of 480 ppm·K−1 at 293–423 K at 1 MHz. The outstanding performance, stability, and tunable capacitors’ characteristics allow for their application in low-pass filters, coupling/decoupling/bypass circuits, RC oscillators, energy-storage devices, ultrafast charge/discharge units, or high-precision analog-to-digital converters. The capacitor technology based on the non-porous planar anodic-oxide dielectrics complements the electrochemical conception of IPDs that combined, until now, the anodized aluminum interconnection, microresistors, and microinductors, all co-related in one system for use in portable electronic devices.

Influence of Increasing Deposition Temperature during Atomic Layer Deposition on Electrical Properties and Reliability in Al2O3 - Doped ZrO2 Based Two-Dimensional and Three-Dimensional Metal-Insulator-Metal Decoupling Capacitors

The influence of deposition temperature (TD) on thin film layers of high-k dielectrics used as insulators in embedded Metal-Insulator-Metal (MIM) decoupling capacitors is critical to their future behavior in terms of electrical properties and reliability. These layers are deposited via atomic layer deposition (ALD), which is known for its high uniformity in any type of structural topology. High-k dielectrics, such as Zr, inside high aspect ratio three-dimensional (3-D) structures are a challenging task even in the case of ALD processing. Al2O3 doping is often used within the high-k layer stack during ALD to optimize electrical performance of MIM structures with respect to leakage currents and reliability. In this context, appropriate atomic layer deposition temperature (TD) of the Al2O3-doped ZrO2 high-dielectric stack must be established to enable optimum electrical properties. Electrical data of decoupling capacitors must fulfill the industrial requirements, which demand that, for example, the leakage current density (J) must not exceed a certain level (<1µA/cm²) and that long-term lifetimes under different operating temperatures of a minimum of 10 years at accumulated fail rate of 10 ppm must be achieved.In this work, we report on a study of the influence of ALD TD on Al2O3-doped ZrO2 thin films fabricated on 300mm wafers. We evaluate the impact of TD on high aspect ratio substrates based on electrical properties and reliability parameters. To achieve this, we use 3 different deposition temperatures (293°C, 313°C, and 333°C) and two physical topologies (planar and 3-D capacitors with cavities-trenches) without compromising the chemical stability of the ALD precursors. For metal precursors, TEMAZ (Tetrakis-ethylmethylamino-zirconium) and TMA (Tri-methyl-aluminum) are used for Zr and Al, respectively. Ozone is used as reactant agent and argon as carrier/purge gas. The ZrO2 cycle consists of pulsing with TEMAZ, purging with Ar gas, oxidizing with O3, and purging with Ar gas. In a similar way, the dopant (TMA) is added, followed by purging steps with Ar, O3 and Ar again. After a few ZrO2 cycles, an Al2O3 cycle is followed, so that nano-laminate films of Al2O3 are formed on top of ZrO2 films. By repeating the ZrO2 and the Al2O3 cycles several times, the desired film thickness is achieved. For the MIM stacks, TiN is used as an electrode material on both sides. There was no post deposition anneal to maintain the amorphous state of the insulator with low defect density and high structural uniformity.The planar capacitors show minimal changes in terms of capacitance density with increasing TD. On the other hand, the 3-D samples show a 17% increase in capacitance density with a TD increase of 20°C from 293°C to 313°C. This increase becomes much smaller (2.3%) for a further TD increase of 20°C at 333°C. However, with increasing TD, the E-field linearity of 3-D samples, expressed by the quadratic E-field capacitor coefficient α, increases by 2% and 17% for TD=313°C and TD=333°C, respectively. The significant improvement in field linearity indicates the highest TD provides the best and most stable capacitance behavior. The J(E)-curves of planar and 3-D devices exhibit different behavior with respect to current density and dielectric breakdown. Specifically, planar devices show greater variation in J(E)-curves over temperature, with decreasing breakdown field (EBD) as TD increases. On the other hand, 3-D samples show little variation in EBD with temperature. Furthermore, planar devices show lower symmetry in their J(E)-curves over the field polarity compared to 3-D capacitors, which could be attributed to differences in conduction mechanisms. Despite having a lower EBD, planar devices reveal improved lifetime and reliability with increasing TD, possibly due to reduced carbon impurities during the insulator deposition. For instance, increasing TD from 293°C to 313°C leads to a 47% improvement in extrapolated lifetime, while a further increase in TD, improves lifetime by an additional 14%. A 10-year lifetime goal can only be achieved at 1MV/cm with TD=333°C and for samples exposed to any temperature conditions (25-150°C). In contrast, 3-D capacitors exhibit a better degradation slope at lower deposition temperatures but require the highest TD to achieve an 18% improvement in lifetime. However, due to their lower EBD, they cannot reach the 10-year lifetime goal at 1MV/cm, except at low applied temperatures (25°C-50°C).In conclusion, the highest TD of 333°C without any chemical decomposition of the metal precursor (TEMAZ) is the optimal deposition temperature for both planar and 3-D Al2O3-doped ZrO2 based MIM decoupling capacitors, providing auspicious results in terms of all relevant parameters. Figure 1

Survey of second harmonic generation in commercial germanium-doped fibers

Seeded optical poling is a promising and simple method to write an effective quadratic coefficient in silica optical fibers doped with germanium. We considered commercial solid core fibers since these fibers could allow for a wide adoption of optical poling. For each fiber, we optimized the poling process and analyzed the second harmonic conversion efficiencies in relation with the fiber chemical composition as obtained resorting to energy-dispersive X-ray spectroscopy. Our comprehensive investigation shows that segments of fibers spanning 20 cm, featuring a germanium content of around 6%, can effectively convert 30 mW of 1064 nm light with efficiencies hovering around 1%.

Research on the Synergistic Development and Operation Mechanism of Vocational Education and Innovative Development Concepts in the Context of Deep Learning

Abstract This paper proposes that the synergistic mechanism promotes the vocational education innovation system to transition from the primitive low-level, ordered and relatively balanced stage to the high-level, ordered and fully synergistic stage. By analyzing the dynamic evolution process of the order parameter, a complex system with self-evolution capability is built, and the vocational education collaborative innovation model is constructed at three levels: macro, meso and micro. Finally, in carrying out the benefit distribution and arithmetic example analysis, the spillover effect of the synergistic subject is explored, and the optimal value is taken using the optimization model of synergistic development of higher vocational colleges and universities. The results show that when the quadratic term coefficient of innovation output is 0.086, the stabilization strategy is (0,1) or (1,0), and the multi-body innovation resources realize interaction stabilization without spillover or feedback effects. This study proposes the optimal path of innovation integration mechanism from the aspects of mechanism, mode and content, which can provide new ideas for the collaborative development of vocational education and enterprises.

Assessment of green technology innovation on energy-environmental efficiency in China under the influence of environmental regulation considering spatial effects

Enhancing energy-environmental efficiency (EEE) is crucial for achieving energy conservation and emission reduction goals. Investigating the mechanism through which green technology innovation (GTI) affects EEE and understanding the role of environmental regulation (ER) in this process provides a theoretical basis for efficient utilization of GTI and ER. This study employs a Dynamic Spatial Durbin Model and utilizes panel data from 2003 to 2017 for 30 Chinese provinces to examine the impact of GTI on EEE in the presence of ER. The empirical results reveal: (1) GTI has a U-shaped impact on EEE, primarily driven by SubGI. (2) GTI’s influence on EEE is predominantly reflected in PTE, also stemming from SubGI. (3) The interaction term between ER and GTI is 0.0022, while the GTI coefficient is − 0.0741, and the GTI quadratic term coefficient is 0.0007, all statistically significant. This implies that ER mitigates the negative impact of GTI on EEE while strengthening its positive effect. These findings provide empirical evidence and policy insights for more effectively utilizing GTI and ER to enhance EEE and achieve energy conservation and emissions reduction goals.

Matter accretion onto charged black holes in symmergent gravity

In astrophysics, accretion is a process where the black hole acquires matter. The gravitational energy is released as a result of the accretion and converted into radiation. Accretion onto dark compact objects, for example, neutron stars, white dwarfs, and black holes is a significant process in the astrophysical phenomenon. It is a fruitful way to examine the features of modified gravity theories by testing the analysis of their results related to dark compact objects. Here, we study the motion of a charged particle moving in near a charged symmergent black hole with Maxwell field. The symmergent gravity is a newly developed modified theory gravity within the framework of the vacuum energy VO, gravitational constant G, and quadratic curvature coefficient cO. The vacuum energy VO can be defined in terms of G and cO in the case where all the fields are degenerate in the form of mass. Further, two different choices of the parameter α provide us two different black hole spacetimes, like de Sitter for α<1 and anti-de Sitter for α>1. For this, we explore the accretion of perfect fluid onto the spherically symmetric charged symmergent black hole. Then, we get analytical results among the four-velocity and energy densities of the accreting matter. Further, we investigate it for well-known fluids flowing onto a charged symmergent black hole. Applying the Hamiltonian approach, we are able to explore the nature of accretion for these fluids such as ultra-stiff fluid, ultra-relativistic fluid, radiation fluid, and sub-relativistic fluid onto the source mass. For this study, we classified isothermal types of fluid in the context of equations of state. In addition, we introduced the application of polytropic test fluid associated with accretion disks. The accretion rate is analyzed near a charged symmergent black hole, which produced a typical behavior presented graphically by the significant parameters α and Q.

Finding the Best Model in Nonlinear Regression: Using the Coefficient of Determination

In Indonesia, inflation plays a significant role in shaping economic growth. Therefore, it is essential toexamine the impact of inflation on economic growth through a comprehensive analysis. This analysisaims to identify the factors influencing economic growth in Indonesia by utilizing nonlinear regressionanalysis. The study focuses specifically on modeling economic growth in Batam City and its correlation with inflation. The primary goal is to identify the most effective nonlinear regression model thataccurately represents the relationship between economic growth and inflation, as determined by the coefficient of determination. The method used in this research is nonlinear regression methods providea more accurate and comprehensive analysis when dealing with complex relationships and can helpuncover valuable insights that may be missed by simpler linear models. The results of the analysisfinding the model that is suitable for modeling inflation on economic growth is a quadratic model witha coefficient of determination of 73.4%. The research has found that the best model for explaining theimpact of inflation on economic growth is the Quadratic model with an R-value of 0.734 or 75%. Theseresults indicate that the Quadratic model can account for 75% of the influence of inflation on economicgrowth.

Identification of cable tension through physical models and non-contact measurements

Determining the static and dynamic response of structural cables is a mechanical problem of theoretical and practical interest in many aspects of civil engineering. In particular, the cable tension is a fundamental variable to be assigned in direct design problems, as well as a fundamental unknown to be assessed in inverse identification problems. The present paper outlines an original analytical strategy for identifying the axial tension of inclined sagged cables in cable-stayed structures, based on static measurements. Starting from the classic formulation of an inextensible, perfectly flexible model of catenary suspended cables, a perturbation-based low-order polynomial approximation of the static configuration under self-weight is achieved (direct problem). The quadratic and cubic coefficients of the configurational function are tension-dependent quantities, whose analytical expressions can be mathematically inverted to define consistent parametric formulas for tension identification (inverse problem). The experimental assessment of the static cable configuration, which serves as input for the inverse problem, is provided by the geometric data acquired by modern and noninvasive techniques of non-contact measurement. The methodological advantage is that the laser scanner acquisition of point cloud models can efficiently and economically provide precise and redundant three-dimensional geometric descriptions of the cable configuration, which is suitable for a highly accurate and statistically robust data treatment. Lastly, the identification strategy is successfully applied to a real-scale structure, for tension identification in the stays of a cable-stayed footbridge. The results are discussed from a qualitative and quantitative viewpoint, and finally validated through a comparison with the outcomes of a dynamic identification procedure based on high-speed camera acquisitions.

Dual-Matrix Domain Wall: A Novel Technique for Generating Permutations by QUBO and Ising Models with Quadratic Sizes

The Ising model is defined by an objective function using a quadratic formula of qubit variables. The problem of an Ising model aims to determine the qubit values of the variables that minimize the objective function, and many optimization problems can be reduced to this problem. In this paper, we focus on optimization problems related to permutations, where the goal is to find the optimal permutation out of the n! possible permutations of n elements. To represent these problems as Ising models, a commonly employed approach is to use a kernel that applies one-hot encoding to find any one of the n! permutations as the optimal solution. However, this kernel contains a large number of quadratic terms and high absolute coefficient values. The main contribution of this paper is the introduction of a novel permutation encoding technique called the dual-matrix domain wall, which significantly reduces the number of quadratic terms and the maximum absolute coefficient values in the kernel. Surprisingly, our dual-matrix domain-wall encoding reduces the quadratic term count and maximum absolute coefficient values from n3−n2 and 2n−4 to 6n2−12n+4 and 2, respectively. We also demonstrate the applicability of our encoding technique to partial permutations and Quadratic Unconstrained Binary Optimization (QUBO) models. Furthermore, we discuss a family of permutation problems that can be efficiently implemented using Ising/QUBO models with our dual-matrix domain-wall encoding.

A Unified General Resistance Formula for Uniform Coarse Porous Media

Many authors studied the nonlinear relationship between seepage velocity and hydraulic gradient in coarse granular materials. They managed different approaches and variables to define the resistance formula applicable to that type of granular media. Based on the analysis of the different approaches and experimental data obtained by the corresponding authors, we propose a unified general seepage equation applicable to large-sized granular materials. Such an equation gives unity to the main nonlinear resistance formulas developed to date. Particularly relevant are the conclusions regarding the relationship of the linear (α*) and quadratic (β*) dimensionless coefficients of the resistance formula with the representative size of the particle and the geometrical features of the porous materials.

Minimal chaotic models from the Volterra gyrostat

Low-order models obtained through Galerkin projection of several physically important systems (e.g., Rayleigh–Bénard convection, mid-latitude quasi-geostrophic dynamics, and vorticity dynamics) appear in the form of coupled gyrostats. Forced dissipative chaos is an important phenomenon in these models, and this paper introduces and identifies “minimal chaotic models” (MCMs), in the sense of having the fewest external forcing and linear dissipation terms, for the class of models arising from an underlying gyrostat core. The identification of MCMs reveals common conditions for chaos across a wide variety of physical systems. It is shown here that a critical distinction is whether the gyrostat core (without forcing or dissipation) conserves energy, depending on whether the sum of the quadratic coefficients is zero. The paper demonstrates that, for the energy-conserving condition of the gyrostat core, the requirement of a characteristic pair of fixed points that repel the chaotic flow dictates placement of forcing and dissipation in the minimal chaotic models. In contrast if the core does not conserve energy, the forcing can be arranged in additional ways for chaos to appear in the subclasses where linear feedbacks render fewer invariants in the gyrostat core. In all cases, the linear mode must experience dissipation for chaos to arise. The Volterra gyrostat presents a clear example where the arrangement of fixed points circumscribes more complex dynamics.

Two large-exposure-ratio image fusion by improved morphological segmentation.

The fusion of two large-exposure-ratio images, especially in the rocket launch field, is a challenging task because of fast-moving objects and differential features from daily scenes. Based on the large-exposure-ratio images, we propose a principle of halo formation at the boundaries of over-exposed areas. To avoid the halos in the fusion images, an improved morphological segmentation (IMS) method is developed to segment the over-exposed regions and boundaries. The IMS method is inspired by the mountain topography and builds a bridge between the 3D patches and quadratic polynomial coefficients. An improved multiscale method with segmentation in high-exposed images is proposed. In the rocket launch observation experiment, we constructed a two-camera simultaneous imaging system to avoid the dynamic scenes. The result of our proposed fusion method could best preserve the details and colors of the flames in low-exposed images and has the best subjective observation. The objective matrices also demonstrate superior edge and contrast performances over mainstream methods.