Unity Weight Research Articles

Constructing composite scores for contemporaneous behaviors: A comparison of four approaches

AbstractComposite scores, where the results of two or more measures are combined, are commonly used in many fields, including ethology. Composite scores can simplify the analysis and interpretation of data while capturing the salient features of the underlying latent variable(s) approximated by the score. Here we outline four approaches for constructing composite scores in ethological studies: ad hoc (AH) assignment, discriminant analysis (DA), principal components analysis (PCA), and partial least squares (PLS). We give examples of each using previously published data from a study of responses of lone star ticks (Amblyomma americanum) to several deterrent phytochemicals. In most cases, researchers construct AH composite scores by subjectively assigning weights and signs to the behavioral components; unity weighting constrains weights to −1 or 1 on standardized variables. Because the weights and signs of the coefficients are subjectively assigned, AH scores may generate a spurious result. DA can be used to construct composite behavioral scores when there are clearly defined treatments or preference tests using distinct stimuli. The DA score created consists of orthogonal variables that capture the variability in the behavioral measures most closely aligned with the differences among treatment or stimuli variables. This approach assumes that subjects discriminate treatment or stimuli differences, but may not manifest clear overt behavior that they are able to do so; it reduces dimensionality, usually to a single axis, representing the underlying latent variable of interest. The PCA approach is similar to DA except that the composite score is created independently of treatment or stimuli variables. Thus, this method can be used to investigate possible relationships between a composite score and any relevant independent variable, perhaps measured asynchronously with the behaviors. PLS is a multivariate method related to DA and PCA and is also used to create latent orthogonal variables. However, these new variables are constructed to maximize correlation with one or more continuous independent variables. Creation of a composite score requires the researcher to consider not only the method used to create it, but, at an earlier stage in the research, which behaviors should be components and how best to measure them.

Analysis of combined probability and nonprobability samples: a simulation evaluation and application to a teen smoking behavior survey

In scientific studies with low-prevalence outcomes, probability sampling may be supplemented by nonprobability sampling to boost the sample size of desired subpopulation while remaining representative to the entire study population. To utilize both probability and nonprobability samples appropriately, several methods have been proposed in the literature to generate pseudo-weights, including ad-hoc weights, inclusion probability adjusted weights, and propensity score adjusted weights. We empirically compare various weighting strategies via an extensive simulation study, where probability and nonprobability samples are combined. Weight normalization and raking adjustment are also considered. Our simulation results suggest that the unity weight method (with weight normalization) and the inclusion probability adjusted weight method yield very good overall performance. This work is motivated by the Buckeye Teen Health Study, which examines risk factors for the initiation of smoking among teenage males in Ohio. To address the low response rate in the initial probability sample and low prevalence of smokers in the target population, a small convenience sample was collected as a supplement. Our proposed method yields estimates very close to the ones from the analysis using only the probability sample and enjoys the additional benefit of being able to track more teens with risky behaviors through follow-ups.

A methodology for unstructured damped stress inversion of microseismic focal mechanisms: Application to the Vaca Muerta Formation, Argentina

Current methodologies for stress inversion from microseismic focal mechanisms require the assignment of events to a regular grid and then solving for the stress state at each grid node. This approach can lead to irregularities in the solution because some nodes may contain few or even no events. To address this issue, we modified the algorithm to solve for stresses on an irregular (unstructured) grid. We first use the [Formula: see text]-means algorithm to split the data into suitably sized groups. The centroids of these groups are then considered as the nodes of an unstructured grid, and we simultaneously solve for the stress state in each group using damped inversion. To account for the irregularity of the unstructured grid, we use the reciprocal square distance between nodes as weights, as opposed to the existing method in which a weight of unity is assigned between adjacent nodes on a regular grid. Focal planes are selected from the auxiliary plane using the fault instability criterion. The method is first applied to synthetic data sets in which we simulate and subsequently invert for the stress field around a mode-I fracture at depth, in a strike-slip and in a normal faulting stress regime. Results indicate a stress orientation error of 10° and a stress ratio error between 1% and 10%. We then consider focal mechanism data from an unconventional shale play in the Vaca Muerta Formation in Argentina, and our results suggest the presence of a preexisting strike-slip faulting stress regime. We also find that the unambiguous focal plane picks suggest that the apparent dip-slip focal mechanisms are indeed dip-slip movement along subvertical natural fractures, which correlate well with image log data. We suggest that these dip-slip events are caused by stress changes induced by the opening of the hydraulic fractures.

A new real-time flood forecasting model based on robust kalman filter method

The telemetry inevitably brings some outliers in observation data. The real-time flood forecasting based on conventional Kalman filter is sensitive to the outliers, that cannot guarantee the reliable forecasting results. In this paper a new real-time flood forecasting model based on a robust Kalman filter is described. The proposed robust filter assigns the less weight to the outliers by inserting the weight factors, and the unity weight to the normal data. That makes the robust Kalman filter method is insensitive the outliers, meanwhile keeps the properties of the conventional Kalman filer. The feasibility of the robust approach is demonstrated with unbiased and biased data.

Flexural rotation capacity models fitted to test results using different statistical approaches

Practical models for the ultimate deformations of flexure‐controlled members were fitted to a database of thousands of tests. They cover beams, rectangular columns or walls, members with T‐, H‐, C‐, or box section, conforming or not to seismic design codes, with or without fiber reinforced polymer jackets, in monotonic or cyclic uniaxial flexure with axial force. Model parameters were statistically derived assigning to each test (a) a weight of unity; (b) weight inversely proportional to the number of tests in a testing campaign, or (c) weight inversely proportional to the root‐mean‐square error of tests in a campaign. Predictions correlate well to those of a physical model based on curvatures and a plastic hinge length. Analysis of variance suggests that the scatter of model predictions with respect to test results comes more from the testing itself than from the model. Intralab and interlab variabilities are quantified and pure error is estimated from tests of nominally identical specimens.

Monitoring tool wear using classifier fusion

Real time monitoring of manufacturing processes using a single sensor often poses significant challenge. Sensor fusion has thus been extensively investigated in recent years for process monitoring with significant improvement in performance. This paper presents the results for a monitoring system based on the concept of classifier fusion, and class-weighted voting is investigated to further enhance the system performance. Classifier weights are based on the overall performances of individual classifiers, and majority voting is used in decision making. Acoustic emission monitoring of tool wear during the coroning process is used to illustrate the concept. A classification rate of 87.7% was obtained for classifier fusion with unity weighting. When weighting was based on overall performance of the respective classifiers, the classification rate improved to 95.6%. Further using state performance weighting resulted in a 98.5% classification. Finally, the classifier fusion performance further increased to 99.7% when a penalty vote was applied on the weighting factor.

Design Aid for the Verification of Resistance to Failure by Hydraulic Heave

For the determination of the required embedded length for the safety against hydraulic heave several approximate solutions exist. However, most of these solutions do not take into account the geometrical boundary conditions such as width B and length L of the excavation as well as the thickness of the aquifer S. Thus, values obtained by such simplified approximate solutions can easily lead to an unsafe design. For this reason investigations on the safety against hydraulic heave have been carried out at the Chair of Geotechnical Engineering at RWTH Aachen University. From the results of numerous calculations dimensionless design charts have been generated. With the help of these design charts the required embedded length T can be determined quite easily taking into account the difference of the ground water level H, the geometrical boundary conditions of the excavation and the unity weight of submerged soil γ’.

Buoyancy-driven fluid flow and heat transfer in a square cavity with a wavy baffle—Meshless numerical analysis

Abstract The meshless local Petrov–Galerkin method is implemented to simulate the buoyancy-driven flow and heat transfer in a differentially-heated enclosure having a baffle attached to its higher temperature side wall. To execute the proposed numerical treatment, the stream function–vorticity formulation is employed and a unity weighting function is applied for the weak form of the governing equations. In this meshless numerical approach, the field variables are approximated using the MLS interpolation technique. Being attested through comparing the results of two test case simulations with the results of either an analytical or a conventional numerical approach, the MLPG method is applied to investigate the buoyancy-driven flow and heat transfer in the baffled cavity. The present analyses involve a parametric study to implicate the effects of the baffle undulation number, amplitude, location on the wall, and the system Rayleigh number. The investigation reveals the eminent participation of the baffle in transferring heat from the hot wall. The analyses disclose an increase of the hot wall average Nusselt number by elevating the location of the baffle on the hot wall. This average Nusselt number descends with increasing the baffle amplitude. The cold wall average Nusselt number increases as the baffle number of undulation augments.

Multi-model inference of adult and childhood leukaemia excess relative risks based on the Japanese A-bomb survivors mortality data (1950–2000)

Some relatively new issues that augment the usual practice of ignoring model uncertainty, when making inference about parameters of a specific model, are brought to the attention of the radiation protection community here. Nine recently published leukaemia risk models, developed with the Japanese A-bomb epidemiological mortality data, have been included in a model-averaging procedure so that the main conclusions do not depend on just one type of model or statistical test. The models have been centred here at various adult and young ages at exposure, for some short times since exposure, in order to obtain specially computed childhood Excess Relative Risks (ERR) with uncertainties that account for correlations in the fitted parameters associated with the ERR dose-response. The model-averaged ERR at 1 Sv was not found to be statistically significant for attained ages of 7 and 12 years but was statistically significant for attained ages of 17, 22 and 55 years. Consequently, such risks when applied to other situations, such as children in the vicinity of nuclear installations or in estimates of the proportion of childhood leukaemia incidence attributable to background radiation (i.e. low doses for young ages and short times since exposure), are only of very limited value, with uncertainty ranges that include zero risk. For example, assuming a total radiation dose to a 5-year-old child of 10 mSv and applying the model-averaged risk at 10 mSv for a 7-year-old exposed at 2 years of age would result in an ERR=0.33, 95% CI: -0.51 to 1.22. One model (United Nations scientific committee on the effects of atomic radiation report. Volume 1. Annex A: epidemiological studies of radiation and cancer, United Nations, New York, 2006) weighted model-averaged risks of leukaemia most strongly by half of the total unity weighting and is recommended for application in future leukaemia risk assessments that continue to ignore model uncertainty. However, on the basis of the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

Images of History and the Nation: Namibia and Zimbabwe Compared

ABSTRACT The article contrasts the historical trajectories of Namibia and Zimbabwe with a specific focus on the dynamics of the broad liberation movements in both countries, the stages of their development and the social settings in which they operated and still operate in their capacities of ruling parties after independence. The differences of both historical processes are mapped and pinpointed in particular with respect to the role of settlers and to trajectories of violence. There are also clear divergences in their conceptualisation, discursive adaptation and debate of historical issues. These are linked to an array of features that differentiate both countries, ranging from the diverse weight of political unity through the contrasting role of settler communities to the differential weight of class analysis in existing literature. In these very diverse ways, history emerges, in both countries, as a rather hotly contested terrain.

Unity hard red spring wheat

Unity is a hard red spring wheat that meets the end-use quality specifications of the Canada Western Red Spring class. Unity is the first spring wheat cultivar registered in Canada that contains the antibiosis resistance gene Sm1, which produces a product that reduces the palatability of developing seeds to wheat midge larvae (Sitodiplosis mosellana Géhin). Unity is a partial backcross derivative of McKenzie, using Clark as the donor of the Sm1 gene for midge resistance. Unity was found to be adapted to the eastern wheat growing regions of the Canadian prairies as represented in the Central Bread Wheat Cooperative Registration Test in 2004, 2005 and 2006. For registration testing, the performance of Unity was estimated using the varietal blend Unity VB, which consisted of 90% Unity and 10% Waskada. In comparison to the check cultivars (Katepwa, McKenzie, CDC Teal, AC Barrie, and Superb), Unity was the highest yielding cultivar overall; although not significant, Unity was 5% higher yielding than McKenzie. Unity matured significantly later than Katepwa and significantly earlier than Superb. Unity had significantly shorter plant stature than Katepwa and significantly taller stature than Superb. Unity had significantly greater lodging scores than AC Barrie and Superb. The test weight of Unity was significantly higher than the best check: 0.9 kg hL-1 higher than McKenzie. Unity expressed resistance to leaf rust, stem rust and common bunt, intermediate resistance to loose smut, and susceptibility to fusarium head blight. Unity had preharvest sprouting resistance with an overall sprouting score similar to the best checks McKenzie and Superb. Unity also maintained its falling numbers following natural or artificial weathering of spikes. The end-use suitability attributes of Unity were similar to the recurrent parent McKenzie for all traits except amylograph viscosity which was significantly higher than all checks except Superb. Key words: Triticum aestivum L., cultivar description, red spring wheat, test weight, preharvest sprouting, wheat midge antibiosis

Níveis nutricionais de metionina + cistina digestível para poedeiras semipesadas no segundo ciclo de produção

Um experimento foi conduzido com o objetivo de estabelecer a exigência nutricional de metionina + cistina (met + cist) para poedeiras semipesadas no segundo ciclo de produção. Utilizaram-se 180 poedeiras semipesadas no período de 79 a 95 semanas de idade alimentadas com uma ração basal deficiente em met + cist (0,490%) suplementada com 0,00; 0,053; 0,108; 0,161; e 0,214% de DL-metionina (98%), de forma a proporcionar 0,490; 0,542; 0,594; 0,648; e 0,698% de met + cist digestível. Os níveis de suplementação de met + cist obedeceram, respectivamente, às relações de 75, 83, 91, 99 e 107 com lisina. O delineamento experimental foi o inteiramente casualizado com cinco níveis de met + cist, seis repetições e seis aves por unidade experimental. Avaliaram-se os consumos de ração e de met + cist, a conversão alimentar por dúzia e por massa de ovos, o ganho de peso, a taxa de postura, o peso e a massa de ovos, a porcentagem dos componentes dos ovos e a qualidade interna dos ovos. Os níveis de met + cist tiveram efeito linear positivo sobre a conversão alimentar por dúzia de ovos, efeito quadrático sobre o consumo de ração, o ganho de peso e a conversão alimentar. Os níveis de met + cist tiveram efeito linear positivo sobre a taxa de postura e efeito quadrático sobre o peso e a massa de ovos. Observaram-se ainda efeito quadrático sobre a unidade Haugh e efeito linear sobre o índice de gema. A exigência de met + cist é igual ou superior a 0,698%, que corresponde a consumo mínimo de 786 mg de met + cist digestível/ave.dia.

Enhanced imaging in low dose electron microscopy using electron counting

We compare the direct electron imaging performance at 120keV of a monolithic active pixel sensor (MAPS) operated in a conventional integrating mode with the performance obtained when operated in a single event counting mode. For the combination of sensor and incident electron energy used here, we propose a heuristic approach with which to process the single event images in which each event is renormalised to have an integrated weight of unity. Using this approach we find enhancements in the Nyquist frequency modulation transfer function (MTF) and detective quantum efficiency (DQE) over the corresponding integrating mode values by factors of 8 and 3, respectively.

Hermite-Legendre-Gauss-Lobatto Direct Transcription in Trajectory Optimization

D IRECT methods have been widely applied for solving trajectory optimization problems [1–5]. Among the popular methods are the Hermite–Simpson method [6] and the Legendre pseudospectral (PS)method [7,8]. There has been some considerable interest in developing theory related to the Legendre PS method due to its high accuracy, although the Hermite–Simpson method continues to be applied to large-scale practical problems [9]. The main characteristic of the Hermite–Simpson method is the combination of reasonable accuracy with a highly sparse constraint Jacobian and Hessian matrix [10]. The PS method offers impressive accuracy (spectral accuracy) for smooth problems, but the constraint Jacobians are much denser than other methods. The sparsity of the constraint Jacobians can be increased in the PS method by using knots [11]. In addition to the Hermite–Simpson method, additional highorder methods have been proposed by Herman and Conway [2]. These methods are attractive from the point of view of accuracy, but in the framework proposed by Herman and Conway, they require detailed derivation when extended to arbitrary higher orders. For instance, in [2], the form of the constraints was derived via the symbolic manipulation software MAPLE. The purpose of this Note is to provide an alternative framework for arbitrary higher-order methods suitable for implementation on digital computers and in a reusable form. The optimal control problem is approximated by a discrete nonlinear programming problem (NLP) by expanding the state trajectories using local Hermite interpolating polynomials. For high accuracy, the collocation points are selected from the family of Gauss–Lobatto points. This also allows the integral performance index to be approximated viaGauss– Lobatto quadrature rules. For optimal control problems of the Bolza form, the natural choice of quadrature points are the Legendre– Gauss–Lobatto (LGL) points, because they are derived on the basis of a unity weight function, giving the highest accuracy for polynomial integrands. The generalization of the approach is referred to as the Hermite–Legendre–Gauss–Lobatto (HLGL) approach throughout the remainder of this Note.

Powder perturbation functions in angular correlations for distributions of electric field gradient tensor components: analytical expressions for I=1

Analytical expressions for powder perturbation functions in angular correlations for the following distributions of electric field gradient tensor components are derived for I=1: (i) straight line distributions (one-dimensional (1D) trajectories) applicable for cases where tensor components depend linearly on each other and (ii) 2D distributions (areas) in the Czjzek-plot, a variant of a Cartesian Vxx versus Vzz-plot. For the sake of simplicity, a weight of unity was used for the trajectories and areas, respectively. The results contain the 1D or 2D Fourier transform (eventually in a rotated coordinate system) of the distribution function and can easily be extended for other weights and/or shapes. A new set of parameters to describe the distributions is given. These results have implications for the analysis of 2H-NMR data.

Process Variation Aware Transistor Sizing for Load Balance of Multiple Paths in Dynamic CMOS for Timing Optimization

The complexity in timing optimization of high performance microprocessors has been increasing with the number of channel-connected transistors in various paths of dynamic CMOS circuits and the rising magnitude of process variations in nanometer CMOS process. In this paper, a process variation aware transistor sizing algorithm for dynamic CMOS circuits while considering the Load Balance of Multiple Paths (LBMP) is proposed. The proposed iterative optimization algorithm is a deterministic approach and is illustrated first by a 2-b weighted binary-to-thermometric converter (WBTC) and of which the critical path was optimized from an initial delay of 355 ps to an optimal delay of 157 ps, which accounts for a 55.77% delay improvement. A 4-b unity weight binary-to-thermometric converter (UWBTC) was also designed and of which the critical path was optimized from an initial delay of 152 ps to an optimal delay of 103 ps, which accounts for a 32.23% delay improvement. Finally, a 64-b parallel binary adder was partitioned to a mixed dynamic-static CMOS style and the critical path and the power delay product were optimized to 632 ps and 84.17 pJ respectively.

Frequency Modulation and First-Order Delta Sigma Modulation: Signal Representation With Unity Weight Dirac Impulses

Signal representation by means of unity weight and continuous-time aperiodic Dirac impulses is discussed, where the Dirac impulses are triggered at the zero crossings of frequency-modulated (FM) sinusoids. Analysis is based on generalized FM. The Fourier spectrum Psi(f) of such a Dirac impulse sequence psi(t) is composed of the signal spectrum plus a superposition of weighted FM spectra around integer multiples of the carrier frequency. It is demonstrated that FM-related sequences Psi(t) are generated by asynchronous DeltaSigmamodulators of first order. Practically relevant clock-synchronous versions psid(t) of Psid(t) are obtained, when the clock rate is twice the FM carrier frequency. A DeltaSigma-spectrum psid(f) can be regarded as a superposition of weighted and shifted versions of psi(f), whereby the first partial FM spectrum in psi(f) around the FM carrier frequency plays a dominant role.

Robust recursive estimation of auto-regressive updating model parameters for real-time flood forecasting

In this paper, a new robust recursive method of estimating auto-regressive updating model parameters for real-time flood forecasting using weighted least squares with a forgetting factor is described. The proposed robust recursive least squares (RRLS) method differs from the conventional recursive least squares method by the insertion of a non-linear transformation of the residuals. The RRLS algorithm takes into account the contaminated Gaussian nature of the gross errors for the observed discharge, and assigns less weight to a small portion of large residuals, and gives unity weight to the bulk of moderate residuals generated by the nominal Gaussian distribution. It is the reason why the RRLS method is insensitive to outliers. The proposed method has the potential to give less biased estimates in the presence of outliers. The feasibility of the robust approach is demonstrated with synthetic and real data.

The discomfort behavior scale: A measure of discomfort in the cognitively impaired based on the minimum data set 2.0

Because persons with cognitive impairment often cannot self-report pain, it is imperative to develop instruments that use observable indicators. The purpose of this study was to develop and test the psychometric properties of the Discomfort Behavior Scale (DBS), which is comprised of 17 items from the Minimum Data Set (MDS). MDS data from 29,120 cognitively impaired nursing home residents were used for psychometric testing. Factor analyses of the DBS indicated that it reflects a single discomfort dimension. The items are tau equivalent, allowing unity weighting and simple summation to create scale scores, and the internal consistency was good. The DBS has potential to be useful in studies of efforts to improve pain management in cognitively impaired residents of nursing homes.

Robust recursive AR speech analysis

In this paper a new robust recursive method of estimating the linear prediction parameters of an auto-regressive speech signal model using weighted least squares with variable forgetting factors (VVFs) is described. The proposed robust recursive least-squares (RRLS) method differs from the conventional recursive least-squares (RLS) method by the insertion of a suitably chosen nonlinear transformation of the prediction residuals. The RRLS algorithm takes into account the contaminated Gaussian nature of the excitation for voiced speech, and the effect of nonlinearity is to assign less weight to the small portions of large residuals so that the spiky excitation will not greatly influence the final AR parameter estimates, while giving unity weight to the bulk of small to moderate residuals generated by the nominal Gaussian distribution. In addition, the VFF is adapted to a nonstationary speech signal by a generalized likelihood ratio algorithm, which accounts for the nonstationarity of a speech signal. The proposed method has a good adaptability to the nonstationary parts of a speech signal, and gives low bias and low variance at the stationary signal segments. The feasibility of the robust approach is demonstrated with both synthesized and natural speech.