Linear Aggregation In The Social Accounting Matrix Framework

In economic literature, information deficiencies and computational complexities have traditionally been solved through the aggregation of agents and institutions. In inputoutput modelling, researchers have been interested in the aggregation problem since the beginning of 1950s. Extending the conventional input-output aggregation approach to the social accounting matrix (SAM) models may help to identify the effects caused by the information problems and data deficiencies that usually appear in the SAM framework. This paper develops the theory of aggregation and applies it to the social accounting matrix model of multipliers. First, we define the concept of linear aggregation in a SAM database context. Second, we define the aggregated partitioned matrices of multipliers which are characteristic of the SAM approach. Third, we extend the analysis to other related concepts, such as aggregation bias and consistency in aggregation. Finally, we provide an illustrative example that shows the effects of aggregating a social accounting matrix model.

A linear optimization technique for graph pebbling

Graph pebbling is a network model for studying whether or not a given supply of discrete pebbles can satisfy a given demand via pebbling moves. A pebbling move across an edge of a graph takes two pebbles from one endpoint and places one pebble at the other endpoint; the other pebble is lost in transit as a toll. It has been shown that deciding whether a supply can meet a demand on a graph is NP-complete. The pebbling number of a graph is the smallest t such that every supply of t pebbles can satisfy every demand of one pebble. Deciding if the pebbling number is at most k is NP 2 -complete. In this paper we develop a tool, called theWeight Function Lemma, for computing upper bounds and sometimes exact values for pebbling numbers with the assistance of linear optimization. With this tool we are able to calculate the pebbling numbers of much larger graphs than in previous algorithms, and much more quickly as well. We also obtain results for many families of graphs, in many cases by hand, with much simpler and remarkably shorter proofs than given in previously existing arguments (certificates typically of size at most the number of vertices times the maximum degree), especially for highly symmetric graphs. Here we apply theWeight Function Lemma to several specific graphs, including the Petersen, Lemke, 4th weak Bruhat, Lemke squared, and two random graphs, as well as to a number of infinite families of graphs, such as trees, cycles, graph powers of cycles, cubes, and some generalized Petersen and Coxeter graphs. This partly answers a question of Pachter, et al., by computing the pebbling exponent of cycles to within an asymptotically small range. It is conceivable that this method yields an approximation algorithm for graph pebbling.

Relaxation methods for solving linear inequality systems: Converging results

The problem of finding a feasible solution to a linear inequality system arises in numerous contexts. In [12] an algorithm, called extended relaxation method, that solves the feasibility problem, has been proposed by the authors. Convergence of the algorithm has been proven. In this paper, we onsider a class of extended relaxation methods depending on a parameter and prove their convergence. Numerical experiments have been provided, as well.

A subspace correction method for discontinuous Galerkin discretizations of linear elasticity equations

We study preconditioning techniques for discontinuous Galerkin discretizations of isotropic linear elasticity problems in primal (displacement) formulation. We propose subspace correction methods based on a splitting of the vector valued piecewise linear discontinuous finite element space, that are optimal with respect to the mesh size and the Lamé parameters. The pure displacement, the mixed and the traction free problems are discussed in detail. We present a convergence analysis of the proposed preconditioners and include numerical examples that validate the theory and assess the performance of the preconditioners.

Preliminary Experience in Treatment of Papillary and Macular Retinoblastoma: Evaluation of Local Control and Local Complications After Treatment with Linear Accelerator-Based Stereotactic Radiotherapy with Micromultileaf Collimator as Second-Line or Salvage Treatment after chemotherapy.

PURPOSE: To determine the local control and complication rates for children with papillary and/or macular retinoblastoma progressing after chemotherapy and undergoing stereotactic radiotherapy (SRT) with a micromultileaf collimator. METHODS AND MATERIALS: Between 2004 and 2008, 11 children (15 eyes) with macular and/or papillary retinoblastoma were treated with SRT. The mean age was 19 months (range, 2-111). Of the 15 eyes, 7, 6, and 2 were classified as International Classification of Intraocular Retinoblastoma Group B, C, and E, respectively. The delivered dose of SRT was 50.4 Gy in 28 fractions using a dedicated micromultileaf collimator linear accelerator. RESULTS: The median follow-up was 20 months (range, 13-39). Local control was achieved in 13 eyes (87%). The actuarial 1- and 2-year local control rates were both 82%. SRT was well tolerated. Late adverse events were reported in 4 patients. Of the 4 patients, 2 had developed focal microangiopathy 20 months after SRT; 1 had developed a transient recurrence of retinal detachment; and 1 had developed bilateral cataracts. No optic neuropathy was observed. CONCLUSIONS: Linear accelerator-based SRT for papillary and/or macular retinoblastoma in children resulted in excellent tumor control rates with acceptable toxicity. Additional research regarding SRT and its intrinsic organ-at-risk sparing capability is justified in the framework of prospective trials.

Multiple-scale hydrological and geophysical data integration through non-linear Bayesian sequential simulation

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Local Distance-Based Generalized Linear Models using the dbstats package for R

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

Immunocompetence and nestling survival in the house martin: the tasty chick hypothesis

In altricial birds post-fledging survival is usually positively related to nestling body mass. A large number of studies have shown that the latest hatched chick is the more likely to die, even if food is abundant. Here we suggest that ectoparasites may be a key factor in the evolution and the maintenance of the establishment of weight hierarchies within broods. We prepose the hypothesis that weight hierarchies within broods may be adaptive if the chick in poor condition is the one with the least efficient immune system within a nest. In this case parasites would preferentially feed on such a "tasty chick", because it would allow high reproductive rates for the parasites, without negatively affecting the survival of the other nestlings. This could prevent entire nest failure of the brood or allow the other chicks to grow more efficiently. This hypothesis was investigated in a colony of house martins Delichon urbica. We predicted that immunocompetence was positively correlated with body condition, and that nestlings dying before hedging should have lower immune responses when challenged with an antigen. T-cell immune response to an experimentally injected antigen was strongly positively related to body condition. Non-surviving chicks had low body condition and a weak immune response. The implications of these results are discussed in the context of the adaptive significance of hatching asynchrony.

Impact of reduced cerebral perfusion pressure on outcome after severe traumatic brain injury is dependent on brain tissue oxygen pressure

INTRODUCTION. Reduced cerebral perfusion pressure (CPP) may worsen secondary damage and outcome after severe traumatic brain injury (TBI), however the optimal management of CPP is still debated. STUDY HYPOTHESIS: We hypothesized that the impact of CPP on outcome is related to brain tissue oxygen tension (PbtO2) level and that reduced CPP may worsen TBI prognosis when it is associated with brain hypoxia. DESIGN. Retrospective analysis of prospective database. METHODS. We analyzed 103 patients with severe TBI who underwent continuous PbtO2 and CPP monitoring for an average of 5 days. For each patient, duration of reduced CPP (\60 mm Hg) and brain hypoxia (PbtO2\15 mm Hg for[30 min [1]) was calculated with linear interpolation method and the relationship between CPP and PbtO2 was analyzed with Pearson's linear correlation coefficient. Outcome at 30 days was assessed with the Glasgow Outcome Score (GOS), dichotomized as good (GOS 4-5) versus poor (GOS 1-3). Multivariable associations with outcome were analyzed with stepwise forward logistic regression. RESULTS. Reduced CPP (n=790 episodes; mean duration 10.2 ± 12.3 h) was observed in 75 (74%) patients and was frequently associated with brain hypoxia (46/75; 61%). Episodes where reduced CPP were associated with normal brain oxygen did not differ significantly between patients with poor versus those with good outcome (8.2 ± 8.3 vs. 6.5 ± 9.7 h; P=0.35). In contrast, time where reduced CPP occurred simultaneously with brain hypoxia was longer in patients with poor than in those with good outcome (3.3±7.4 vs. 0.8±2.3 h; P=0.02). Outcome was significantly worse in patients who had both reduced CPP and brain hypoxia (61% had GOS 1-3 vs. 17% in those with reduced CPP but no brain hypoxia; P\0.01). Patients in whom a positive CPP-PbtO2 correlation (r[0.3) was found also were more likely to have poor outcome (69 vs. 31% in patients with no CPP-PbtO2 correlation; P\0.01). Brain hypoxia was an independent risk factor of poor prognosis (odds ratio for favorable outcome of 0.89 [95% CI 0.79-1.00] per hour spent with a PbtO2\15 mm Hg; P=0.05, adjusted for CPP, age, GCS, Marshall CT and APACHE II). CONCLUSIONS. Low CPP may significantly worsen outcome after severe TBI when it is associated with brain tissue hypoxia. PbtO2-targeted management of CPP may optimize TBI therapy and improve outcome of head-injured patients.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

Pre-hatching maternal effects and the tasty chick hypothesis

Question: Are maternal effects (i.e. maternal transfer of immune components to their offspring via the placenta or the egg) specifically directed to the offspring on which ectoparasites predictably aggregate? Organisms: The barn owl (Tyto alba) because late-hatched offspring are the main target of the ectoparasitic fly Carnus hemapterus. Hypothesis: Pre-hatching maternal effects enhance parasite resistance of late- compared with early-hatched nestlings. Search method: To disentangle the effect of natal from rearing ranks on parasite intensity, we exchanged hatchlings between nests to allocate early- and late-hatched hatchlings randomly in the within-brood age hierarchy. Result: After controlling for rearing ranks, cross-fostered late-hatched nestlings were less parasitized but lighter than cross-fostered early-hatched nestlings. Conclusion: Pre-hatching maternal effects increase parasite resistance of late-hatched offspring at a growth cost.