Analysis of linear networks with inconsistent initial conditions

This paper presents a new method to analyze timeinvariant linear networks allowing the existence of inconsistent initial conditions. This method is based on the use of distributions and state equations. Any time-invariant linear network can be analyzed. The network can involve any kind of pure or controlled sources. Also, the transferences of energy that occur at t=O are determined, and the concept of connection energy is introduced. The algorithms are easily implemented in a computer program.

Biodiversity: predictive traits to the rescue

Climate change poses new challenges to the conservation of species, which at present requires data-hungry models to meaningfully anticipate future threats. Now a study suggests that species traits may offer a simpler way to help predict future extinction risks.

Linear least squares estimation of the first order moving average parameter

We propose an iterative procedure to minimize the sum of squares function which avoids the nonlinear nature of estimating the first order moving average parameter and provides a closed form of the estimator. The asymptotic properties of the method are discussed and the consistency of the linear least squares estimator is proved for the invertible case. We perform various Monte Carlo experiments in order to compare the sample properties of the linear least squares estimator with its nonlinear counterpart for the conditional and unconditional cases. Some examples are also discussed

A theoretical and practical study on linear reforms of dual taxes

[cat] En aquest treball extenem les reformes lineals introduïdes per Pfähler (1984) al cas d’impostos duals. Estudiem l’efecte relatiu que els retalls lineals duals d’un impost dual tenen sobre la distribució de la desigualtat -es pot fer un estudi simètric per al cas d’augments d’impostos-. Tambe introduïm mesures del grau de progressivitat d’impostos duals i mostrem que estan connectades amb el criteri de dominació de Lorenz. Addicionalment, estudiem l’elasticitat de la càrrega fiscal de cadascuna de les reformes proposades. Finalment, gràcies a un model de microsimulació i una gran base de dades que conté informació sobre l’IRPF espanyol de l’any 2004, 1) comparem l’efecte que diferents reformes tindrien sobre l’impost dual espanyol i 2) estudiem quina redistribució de la riquesa va suposar la reforma dual de l’IRPF (Llei ’35/2006’) respecte l’anterior impost.

Predictive factors in the long term outcome in gastro-oesophageal reflux disease: six years follow up of 107 patients

There is little information concerning the long term outcome of patients with gastro-oesophageal reflux disease (GORD). Thus 109 patients with reflux symptoms (33 with erosive oesophagitis) with a diagnosis of GORD after clinical evaluation and oesophageal testing were studied. All patients were treated with a stepwise approach: (a) lifestyle changes were suggested aimed at reducing reflux and antacids and the prokinetic agent domperidone were prescribed; (b) H2 blockers were added after two months when symptoms persisted; (c) anti-reflux surgery was indicated when there was no response to (b). Treatment was adjusted to maintain clinical remission during follow up. Long term treatment need was defined as minor when conservative measures sufficed for proper control, and as major if daily H2 blockers or surgery were required. The results showed that one third of the patients each had initial therapeutic need (a), (b), and (c). Of 103 patients available for follow up at three years and 89 at six years, respective therapeutic needs were minor in 52% and 55% and major in 48% and 45%. Eighty per cent of patients in (a), 67% in (b), and 17% in (c) required only conservative measures at six years. A decreasing lower oesophageal sphincter pressure (p < 0.001), radiological reflux (p = 0.028), and erosive oesophagitis (p = 0.031), but not initial clinical scores, were independent predictors of major therapeutic need as shown by multivariate analysis. The long term outcome of GORD is better than previously perceived.

Drug-induced linear IgA bullous dermatosis probably induced by furosemide.

Linear IgA bullous dermatosis (LABD) is an autoimmune disease, characterized by linear deposition of IgA along the basement membrane zone. Drug-induced LABD is rare but increasing in frequency. A new case of drug-induced LABD associated with the administration of furosemide is described.

Low predictive value of elevated blood pressure during childhood and adolescence

Background: Screening of elevated blood pressure (BP) in children has been advocated to early identify hypertension. However, identification of children with sustained elevated BP is challenging due to the high BP variability. The value of an elevated BP measure during childhood and adolescence for the prediction of future elevated BP is not well described. Objectives: We assessed the positive (PPV) and negative (NPV) predictive value of high BP for sustained elevated BP in cohorts of children of the Seychelles, a rapidly developing island state in the African region. Methods: Serial school-based surveys of weight, height, and BP were conducted yearly between 1998-2006 among all students of the country in four school grades (kindergarten [G0, mean age (SD): 5.5 (0.4) yr], G4 [9.2 (0.4) yr], G7 [12.5 (0.4) yr] and G10 (15.6 (0.5) yr]. We constituted three cohorts of children examined twice at 3-4 years interval: 4,557 children examined at G0 and G4, 6,198 at G4 and G7, and 6,094 at G7 and G10. The same automated BP measurement devices were used throughout the study. BP was measured twice at each exam and averaged. Obesity and elevated BP were defined using the CDC (BMI_95th sex-, and age-specific percentile) and the NHBPEP criteria (BP_95th sex-, age-, and height specific percentile), respectively. Results: Prevalence of obesity was 6.1% at G0, 7.1% at G4, 7.5% at G7, and 6.5% at G10. Prevalence of elevated BP was 10.2% at G0, 9.9% at G4, 7.1% at G7, and 8.7% at G10. Among children with elevated BP at initial exam, the PPV of keeping elevated BP was low but increased with age: 13% between G0 and G4, 19% between G4 and G7, and 27% between G7 and G10. Among obese children with elevated BP, the PPV was higher: 33%, 35% and 39% respectively. Overall, the probability for children with normal BP to remain in that category 3-4 years later (NPV) was 92%, 95%, and 93%, respectively. By comparison, the PPV for children initially obese to remain obese was much higher at 71%, 71%, and 62% (G7-G10), respectively. The NPV (i.e. the probability of remaining at normal weight) was 94%, 96%, and 98%, respectively. Conclusion: During childhood and adolescence, having an elevated BP at one occasion is a weak predictor of sustained elevated BP 3-4 years later. In obese children, it is a better predictor.

Enhanced pulse propagation in non-linear arrays of oscillators

The propagation of a pulse in a nonlinear array of oscillators is influenced by the nature of the array and by its coupling to a thermal environment. For example, in some arrays a pulse can be speeded up while in others a pulse can be slowed down by raising the temperature. We begin by showing that an energy pulse (one dimension) or energy front (two dimensions) travels more rapidly and remains more localized over greater distances in an isolated array (microcanonical) of hard springs than in a harmonic array or in a soft-springed array. Increasing the pulse amplitude causes it to speed up in a hard chain, leaves the pulse speed unchanged in a harmonic system, and slows down the pulse in a soft chain. Connection of each site to a thermal environment (canonical) affects these results very differently in each type of array. In a hard chain the dissipative forces slow down the pulse while raising the temperature speeds it up. In a soft chain the opposite occurs: the dissipative forces actually speed up the pulse, while raising the temperature slows it down. In a harmonic chain neither dissipation nor temperature changes affect the pulse speed. These and other results are explained on the basis of the frequency vs energy relations in the various arrays

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations.

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Molecular clock is involved in predictive circadian adjustment of renal function.

Renal excretion of water and major electrolytes exhibits a significant circadian rhythm. This functional periodicity is believed to result, at least in part, from circadian changes in secretion/reabsorption capacities of the distal nephron and collecting ducts. Here, we studied the molecular mechanisms underlying circadian rhythms in the distal nephron segments, i.e., distal convoluted tubule (DCT) and connecting tubule (CNT) and the cortical collecting duct (CCD). Temporal expression analysis performed on microdissected mouse DCT/CNT or CCD revealed a marked circadian rhythmicity in the expression of a large number of genes crucially involved in various homeostatic functions of the kidney. This analysis also revealed that both DCT/CNT and CCD possess an intrinsic circadian timing system characterized by robust oscillations in the expression of circadian core clock genes (clock, bma11, npas2, per, cry, nr1d1) and clock-controlled Par bZip transcriptional factors dbp, hlf, and tef. The clock knockout mice or mice devoid of dbp/hlf/tef (triple knockout) exhibit significant changes in renal expression of several key regulators of water or sodium balance (vasopressin V2 receptor, aquaporin-2, aquaporin-4, alphaENaC). Functionally, the loss of clock leads to a complex phenotype characterized by partial diabetes insipidus, dysregulation of sodium excretion rhythms, and a significant decrease in blood pressure. Collectively, this study uncovers a major role of molecular clock in renal function.

Linear relations between writhe and minimal crossing number in Conway families of ideal knots and links

We showed earlier how to predict the writhe of any rational knot or link in its ideal geometric configuration, or equivalently the average of the 3D writhe over statistical ensembles of random configurations of a given knot or link (Cerf and Stasiak 2000 Proc. Natl Acad. Sci. USA 97 3795). There is no general relation between the minimal crossing number of a knot and the writhe of its ideal geometric configuration. However, within individual families of knots linear relations between minimal crossing number and writhe were observed (Katritch et al 1996 Nature 384 142). Here we present a method that allows us to express the writhe as a linear function of the minimal crossing number within Conway families of knots and links in their ideal configuration. The slope of the lines and the shift between any two lines with the same