Exact Fit Research Articles

Microscopic Bardeen-Cooper-Schrieffer formulation of the critical temperature of multilayer copper-oxide superconductors

We study superconductivity in multilayer copper oxides, in the frame of a realistic microscopic formulation. Solving the full temperature dependent BCS gap equations, we obtain a maximum in the transition temperature Tc for M=3 or 4 CuO2 layers in the unit cell for appropriate values of the interlayer tunneling (negative pair tunneling), and via the consideration of the doping imbalance between the inner and outer layers. This is the ubiquitous experimental result for Ca intercalated copper oxides, as opposed to other intercalating elements. Further, using a restricted set of parameters, we obtain an exact fit of Tc(M=1-4) for five different Ca intercalated homologuous copper oxide families.

Kinetic parameters from temperature programmed desorption spectra combined with energy relations: top and bridge CO on Rh(100)

A Monte Carlo model of CO on Rh(100) is presented that can correctly describe CO adsorption and desorption over the entire coverage region: from 0 ML to saturation coverage (0.83 ML). Experimental temperature-programmed desorption traces are fitted with simulated traces by differential evolution to obtain numerical values of kinetic parameters. Energy relations are used to limit the amount of fitted parameter sets to only include sets which can reproduce the experimentally observed adlayer structures. The fit that best approaches the actual kinetic parameters uses additional relations to improve the position of the desorption features. In both cases, an exact fit between the experimental and simulated desorption traces is not obtained. Because of this, the magnitude of the obtained kinetic parameters is determined only qualitatively.

A COSMO-RS based guide to analyze/quantify the polarity of ionic liquids and their mixtures with organic cosolvents

A COSMO-RS descriptor (S(sigma-profile)) has been used in quantitative structure-property relationship (QSPR) studies by a neural network (NN) for the prediction of empirical solvent polarity E(T)(N) scale of neat ionic liquids (ILs) and their mixtures with organic solvents. S(sigma-profile) is a two-dimensional quantum chemical parameter which quantifies the polar electronic charge of chemical structures on the polarity (sigma) scale. Firstly, a radial basis neural network exact fit (RBNN) is successfully optimized for the prediction of E(T)(N), the solvatochromic parameter of a wide variety of neat organic solvents and ILs, including imidazolium, pyridinium, ammonium, phosphonium and pyrrolidinium families, solely using the S(sigma-profile) of individual molecules and ions. Subsequently, a quantitative structure-activity map (QSAM), a new concept recently developed, is proposed as a valuable tool for the molecular understanding of IL polarity, by relating the E(T)(N) polarity parameter to the electronic structure of cations and anions given by quantum-chemical COSMO-RS calculations. Finally, based on the additive character of the S(sigma-profile) descriptor, we propose to simulate the mixture of IL-organic solvents by the estimation of the S(sigma-profile)(Mixture) descriptor, defined as the weighted mean of the S(sigma-profile) values of the components. Then, the E(T)(N) parameters for binary solvent mixtures, including ILs, are accurately predicted using the S(sigma-profile)(Mixture) values from the RBNN model previously developed for pure solvents. As result, we obtain a unique neural network tool to simulate, with similar reliability, the E(T)(N) polarity of a wide variety of pure ILs as well as their mixtures with organic solvents, which exhibit significant positive and negative deviations from ideality.

Minimal perfect hashing: A competitive method for indexing internal memory

A perfect hash function (PHF) is an injective function that maps keys from a set S to unique values. Since no collisions occur, each key can be retrieved from a hash table with a single probe. A minimal perfect hash function (MPHF) is a PHF with the smallest possible range, that is, the hash table size is exactly the number of keys in S. MPHFs are widely used for memory efficient storage and fast retrieval of items from static sets. Differently from other hashing schemes, MPHFs completely avoid the problem of wasted space and wasted time to deal with collisions. Until recently, the amount of space to store an MPHF description for practical implementations found in the literature was O ( log n ) bits per key and therefore similar to the overhead of space of other hashing schemes. Recent results on MPHFs presented in the literature changed this scenario: an MPHF can now be described by approximately 2.6 bits per key. The objective of this paper is to show that MPHFs are, after the new recent results, a good option to index internal memory when static key sets are involved and both successful and unsuccessful searches are allowed. We have shown that MPHFs provide the best tradeoff between space usage and lookup time when compared with other open addressing and chaining hash schemes such as linear hashing, quadratic hashing, double hashing, dense hashing, cuckoo hashing, sparse hashing, hopscotch hashing, chaining with move to front heuristic and exact fit. We considered lookup time for successful and unsuccessful searches in two scenarios: (i) the MPHF description fits in the CPU cache and (ii) the MPHF description does not fit entirely in the CPU cache. Considering lookup time, the minimal perfect hashing outperforms the other hashing schemes in the two scenarios and, in the first scenario, the performance is better even when the compared methods leave more than 80% of the hash table entries free. Considering space overhead (the amount of used space other than the key-value pairs), the minimal perfect hashing is within a factor of O ( log n ) bits lower than the other hashing schemes for both scenarios.

The relation between intrapersonal and interpersonal staff behaviour towards clients with ID and challenging behaviour: a validation study of the Staff–Client Interactive Behaviour Inventory

Interpersonal staff behaviour is one of the instigating factors associated with challenging behaviour in clients with intellectual disabilities (ID). There are several studies focusing on the influence of intrapersonal staff characteristics - such as beliefs, attributions and emotional reactions - on staff behaviour. Little is known, however, about interpersonal staff behaviour itself. This study describes the development and validation of the Staff-Client Interactive Behaviour Inventory (SCIBI), measuring both intrapersonal and interpersonal staff behaviour in response to challenging behaviour in clients with ID. A total of 292 staff members, employed in residential and community services, completed the SCIBI for 34 clients with ID and challenging behaviour. Confirmatory factor analysis of a seven-factor model - with assertive control, hostile, friendly and support-seeking interpersonal behaviour; proactive thinking; self-reflection; and critical expressed emotion as reliable factors - showed an exact fit to the data, indicating construct validity and reliability of the SCIBI. A series of multilevel regression analyses showed higher age of the client to be negatively associated with assertive control. Job experience, level of education, type and sex of staff predicted interpersonal behaviour. Also, intrapersonal staff behaviour, including critical expressed emotion, proactive thinking and self-reflection, predicted interpersonal behaviour. The SCIBI can be used to identify staff intrapersonal and interpersonal behaviour towards clients with ID and challenging behaviour. Results obtained with the SCIBI can provide new directions for individual client treatment plans and staff training programmes.

Data depth for simple orthogonal regression with application to crack orientation

This paper studies tangential and simplicial data depth for simple orthogonal regression. Given N points in the plane, simple orthogonal regression means that we wish to determine the line through the origin that has smallest distance to the points measured in the direction orthogonal to the line. For both depth notions, it is proved that two lines which are orthogonal to each other, i.e. two lines forming a cross, have the same depth. Depth-based orthogonal regression can thus merely fit crosses, not lines. We investigated the robustness properties of maximum depth estimators using the notion of exact fit. Another topic the paper covers is the testing of the hypothesis that the data points form a cross-like pattern. After a simple transformation, such a test can be based on the biggest data depth. The paper discusses an application of this test for the investigation of stress fractures in materials.

On the Model-Based Bootstrap With Missing Data: Obtaining a P-Value for a Test of Exact Fit

Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine (1992). An extension of this transformation to missing data was presented by Enders (2002), but it is an approximate and not an exact solution, with the degree of approximation unknown. In this article, we provide several approaches to obtaining an exact solution. First, an explicit solution for the special case when the sample covariance matrix within each missing data pattern is invertible is given. Second, 2 iterative algorithms are described for obtaining an exact solution in the general case. We evaluate the rejection rates of the bootstrapped likelihood ratio statistic obtained via the new procedures in a Monte Carlo study. Our main finding is that model-based bootstrap with incomplete data performs quite well across a variety of distributional conditions, missing data mechanisms, and proportions of missing data. We illustrate our new procedures using empirical data on 26 cognitive ability measures in junior high students, published in Holzinger and Swineford (1939).

An empirical correlation of gas permeability and permselectivity in polymers and its theoretical basis

A large database of permeability values for common gases (He, H 2, O 2, N 2, CO 2 and CH 4) has been employed in the following correlation: P j = k P i n where P i and P j are the permeabilities of gases i and j; the indices are chosen such that the value of n is >1.0. The plots of log P i versus log P j show linear behavior over nine orders of magnitude implying solution–diffusion behavior persists over the entire range of permeabilities existing in known dense polymeric materials. The scatter of data around the linear correlation for each gas pair was modest over the entire range of permeability. It was found that n correlates with the kinetic diameter of the specific gases of the pair by a relationship: n − 1∼( d j / d i ) 2 − 1 in agreement with theory. Correlations exist between n and k for the noted relationship and n u and k u of the upper bound relationship of P i = k u α i j n u where α ij = P i/ P j . The experimental values of n − 1 enable the determination of a new set of kinetic diameters showing excellent agreement between theory and experimental results. The value of 1/ k was found to be virtually an exact fit with the relationship developed by Freeman in predicting the value of k u for the upper bound relationship using the new set of kinetic diameters where the calculations were constrained to minimize the error in ( n − 1) = ( d j / d i ) 2 − 1. The significance of these results includes a new set of kinetic diameters predicted by theory and agreeing with experimental data with accuracy significantly improved over the zeolite determined diameters previously employed to correlate diffusion selectivity in polymers. One consequence of this analysis is that the kinetic diameter of CO 2 is virtually identical to that of O 2. Additionally, the theoretical relationship developed by Freeman for the upper bound prediction is further verified by this analysis which correlates the average permeability for polymeric materials as compared to the few optimized polymer structures offering upper bound performance.

Modeling transformation paths of multiphase materials: The triple point of zirconia

We propose a general method for modeling transformation paths of multiphase materials such that elastic moduli can be fitted exactly. The energy landscape obtained in this way is global and automatically enjoys the correct symmetries. The method is applied to the triple point of zirconia, where tetragonal, orthorhombic (orthoI), and monoclinic phases meet. An explicit and relatively simple expression yields a phenomenological model in the two-dimensional space spanned by a set of order parameters. We also show how to extend this energy to a fully three-dimensional model with an exact fit of all given elastic moduli.

Mosaicking of the 1:75 000 sheets of the Third Military Survey of the Habsburg Empire

The original map sheets of the Third Military Survey of the Austro-Hungarian Monarchy cannot be mosaicked in their original, printed form because of their uneven trapezoid format. To make a digitized raster mosaic of the individual sheets, they all should be georeferenced. Instead of the original projections, which vary from sheet to sheet, a series of sinusoid projections was defined, one unique projection for each sheet columns. The sinusoid projection provides an appropriate approximation of the original trapezoid forms and size of the sheets. Each sheet were rectified in the respective projection then reprojected to a general conic projection, defined for the final mosaic. After all of those transformations, the transformed digital content of the sheets fits to each other well enough to make a geo-referred mosaic. The location parameters of the geodetic datum used for transformation to modern projection systems are the followings: dX = +600 m; dY = +205 m; dZ = +437 m. These figures gives exact fit at the fundamental point of Hermannskogel. Because of the not unified geodetic adjustment of the original base point system, using one unified datum causes a maximum error of 220 meters throughout the whole territory of the Monarchy and the adjacent area on the maps.

Model Error in Covariance Structure Models

The present study investigated the degree to which violation of the parameter drift assumption affects the Type I error rate for the test of close fit and power analysis procedures proposed by MacCallum, Browne, and Sugawara (1996) for both the test of close fit and the test of exact fit. The parameter drift assumption states that as sample size increases both sampling error and model error (i.e. the degree to which the model is an approximation in the population) decrease. Model error was introduced using a procedure proposed by Cudeck and Browne (1992). The empirical power for both the test of close fit, in which the null hypothesis specifies that the Root Mean Square Error of Approximation (RMSEA) ≤ .05, and the test of exact fit, in which the null hypothesis specifies that RMSEA = 0, is compared with the theoretical power computed using the MacCallum et al. (1996) procedure. The empirical power and theoretical power for both the test of close fit and the test of exact fit are nearly identical under violations of the assumption. The results also indicated that the test of close fit maintains the nominal Type I error rate under violations of the assumption.

An allometric function to fit leg‐loop harnesses to terrestrial birds

Harnesses are indispensable for a long‐term attachment of instruments to animals, particularly birds. The exact fit is crucial for both the reliability of the tags and the animals’ health and natural behaviour. Using data from 19 bird species ranging from 8–400 g, I present an allometric function to calculate the dimension of leg‐loop harnesses for birds on the basis of body mass data. The model greatly facilitates determining the correct loop span for new species without time‐consuming experiments. More importantly, the equation permits calculation of the excess span that is required for tagging juvenile, still growing birds.

Deriving tree diameter distributions using Bayesian model averaging

Diameter distributions of loblolly pine trees ( Pinus taeda L.) were derived using Bayesian methods. The Bayesian derived distributions were compared to traditional maximum likelihood techniques for estimating diameter distributions. The data for this study come from a planting density study established in 1983 at four locations in Virginia and North Carolina. Results of the Bayesian analysis show that different distributional forms had the highest posterior probability at different ages for the diameter distributions. Standard goodness-of-fit statistics for the maximum likelihood estimates did not consistently recommend a distribution for the empirical data. Further, there were cases where no distribution was chosen from the candidate distributions based on the goodness-of-fit statistics. The lack of a clear distribution that fits over the range of ages for the diameter data suggests that a Bayesian model averaging technique would be beneficial for deriving tree diameter distributions with probability proportional to the posterior distribution. A simulation study was conducted to compare the goodness-of-fit statistics from the averaged distributional model and other candidate distributions. Results indicated that the averaged distribution had superior goodness-of-fit values over the candidate models; the exception being when the candidate distribution was an exact fit to the data.

Orthopädieschuhtechnische Versorgungsmöglichkeiten nach Trauma

Orthopedic shoe-makers are important partners for the physicians, to protect the results of operations and to offer an alternative, conservative method to an operation. Basic for each orthopedic shoe is a prescription that is as detailed as possible. A precondition for successful therapy is not only the exact fit and function but also an immediate delivery including acceptance by the patient. Variety and quality of the industrial manufactured supplies have increased significantly during recent years and is becoming even more important. Nevertheless, not every foot will fit the industrial norms. Thus, there will always be a need for custom-made shoes. Here we would like to introduce a few examples as ideas and for discussion.

Structural equation modeling made difficult

In his target article ( Barrett, 2007), Paul Barrett argues persuasively against continued use of approximate fit indices in SEM in relation to current thresholds for acceptable fit, given recent research that has cast doubt on the generality of these thresholds. He proposes greater use of the chi-square test of exact fit as an alternative, except in special circumstances. Apart from the problems with current fit thresholds, a further problem with fit indices is the lack of any direct relationship between the value of an index and the degree of misspecification in the model. In response to these problems, a procedure for using fit indices in the absence of thresholds is outlined here. The approach requires the investigator to specify acceptable levels of misspecification a priori, and then uses this information in a simulation procedure to develop a decision for retaining versus rejecting the model. It is argued that this approach is preferable to exclusive reliance on the chi-square test of exact fit. Comments on other points made in the target article are given.

Parameter evaluation for lightning impulse with oscillation and overshoot using the Eigensystem Realization Algorithm

This paper presents a novel approach for the evaluation of impulse parameters. The approach is based on the eigensystem realization algorithm (ERA) which produces a state space model to fit the impulse waveform. Instead of the conventional static mathematical curve model, the dynamic state space model gives a more exact fit for all types of impulse waveforms. This paper demonstrates the feasibility of decomposing the impulse waveform into various components such as smooth, overshoot, oscillations, and high frequency noise etc. Using the presented method it is possible to accurately extract the individual component, even for the overshoot or low frequency oscillation, in analytic functions without significant distortion of the original waveform. Depending on the identified oscillation frequency or overshoot duration, the unwanted components can be removed for the construction of the mean curve. Once the mean curve is obtained and described by analytic functions, the Newton-Raphson method can be performed to the computation of the impulse parameters with high accuracy. Results obtained with analytic and measured impulses show its applicability

Rethinking fit assessment in structural equation modelling: A commentary and elaboration on Barrett (2007)

With seemingly few exceptions, current practice in structural equation modelling (SEM) aims at establishing close rather than exact fit between hypothetical models and observed data. This orientation has gone without serious challenge until the appearance of a sharp critique by Barrett (2007), who suggests discontinuing the use of approximate fit indices (AFIs) in SEM. The present article provides a commentary and elaboration on the key aspects of Barrett’s position, and also supplies further practical guidance and methodological references to applied researchers, who may be motivated to significantly alter their modelling practices in order to address the issues he raises. I strongly support his calls for performing more detailed diagnostic examinations of model misfit when confronted with a significant chi-square ( χ 2) test statistic, rather than simply deferring to AFIs. However, I do not second the recommendation that assessments of a model’s predictive accuracy (e.g., R 2 values) can supplant a focused search for the reasons underlying significant global misfit. Accordingly, some misconceptions about the relationship between global model fit and predictive accuracy are pointed out, and modified advice is given to practitioners. Issues surrounding how to properly appraise a model yielding a non-significant χ 2 are also discussed, as are concerns raised by Barrett about small sample size and power in SEM. It is concluded that AFIs offer little value-added in SEM practice, given the wide variety of available methods for performing detailed model assessments. However, I leave the issue of whether AFIs should be completely abandoned to future research.

Unique Pore Selectivity for Cs+ and Exceptionally High NH4+ Exchange Capacity of the Chalcogenide Material K6Sn[Zn4Sn4S17

Highly selective ion-exchange properties and -exchange capacities of the open framework chalcogenide material K(6)Sn[Zn(4)Sn(4)S(17)] (1) with Cs(+) and NH(4)(+) are reported. Because the structure of this framework is known in great detail, these studies are a rare example where structure/property relationships can be directly drawn. 1 possesses three types of micropore cavities. The largest pore of 1 presents an exact fit for Cs(+) and exhibits high selectivity for this ion, as demonstrated by competitive ion-exchange experiments. The next largest pore has a greater capacity (up to four cations) and is well suited for NH(4)(+) ions. This leads to a high ammonium-exchange capacity for 1 of 3.06 mequiv/gr, which is close to the NH(4)(+)-exchange capacities of natural zeolites. The single-crystal structures of ammonium-exchanged products at various stages reveal an unusual mechanism for the exchange process of 1 which involves diffusion of ammonium cations from the large cavity to the small ones of the framework. Thermal analysis of one of these ammonium-exchanged products, in combination with mass spectroscopy, showed the decomposition of NH(4)(+) cations to NH(3) and H(2)S with the parallel transformation of the exchanged product to a mixture of crystalline phases. Since K(6)Sn[Zn(4)Sn(4)S(17)] can be grown in suitably large crystals (much larger than most zeolites), it defines an excellent model system in which ion-exchange processes and products can be characterized and studied in detail in various reaction stages.

Kinematic development and paleostress analysis of the Denizli Basin (Western Turkey): implications of spatial variation of relative paleostress magnitudes and orientations

Paleostress orientations and relative paleostress magnitudes (stress ratios), determined by using the reduced stress concept, are used to improve the understanding of the kinematic characteristics of the Denizli Basin. Two different dominant extension directions were determined using fault-slip data and travertine fissure orientations. In addition to their stratigraphically coeval occurrence, the almost exact fit of the σ 2 and σ 3 orientations for the NE–SW and NW–SE extension directions in the Late Miocene to Recent units indicate that these two extension directions are a manifestation of stress permutations in the region and are contemporaneous. This relationship is also demonstrated by the presence of actively developing NE–SW and NW–SE elongated grabens developed as the result of NE–SW and NW–SE directed extension in the region. Moreover, stress ratios plots indicate the presence of a zone of major stress ratio changes that are attributed to the interference of graben systems in the region. It is concluded that the plotting of stress orientations and distribution of stress ratios is a useful tool for detecting major differences in stress magnitudes over an area, the boundaries of which may indicate important subsurface structures that cannot be observed on the surface.

Particle migration and gap healing around trabecular metal implants

Bone on-growth and peri-implant migration of polyethylene particles were studied in an experimental setting using trabecular metal and solid metal implants. Cylindrical implants of trabecular tantalum metal and solid titanium alloy implants with a glass bead blasted surface were inserted either in an exact surgical fit or with a peri-implant gap into a canine knee joint. We used a randomised paired design. Polyethylene particles were injected into the knee joint. In both types of surgical fit we found that the trabecular metal implants had superior bone ongrowth in comparison with solid metal implants (exact fit: 23% vs. 7% [p=0.02], peri-implant gap: 13% vs. 0% [p=0.02]. The number of peri-implant polyethylene particles was significantly reduced around the trabecular metal implants with a peri-implant gap compared with solid implants.