Metabolic and Endocrine correlates of cognitive function in healthy young women

Obesity has been associated with cognitive decline in longitudinal studies of older individuals. We hypothesized that the cognitive sequelae of obesity may be detectable in the reproductive years. In addition, we explored the hypothesis that these associations may be mediated by the hormonal milieu. In this study of 49 young healthy lean and overweight women aged 20–45, we investigated the association between performance on a battery of cognitive tests, body composition parameters (BMI, total fat, abdominal (visceral, subcutaneous and total) adipose tissue, and muscle), and hormone levels (insulin, adiponectin, leptin, IGF-1, estrogen, testosterone, and vitamin D). We found a significant negative association between both visceral adiposity and muscle, and performance in the domain of verbal learning and memory, after controlling for age and education. Other body composition parameters showed similar trends (0.05<p<0.10). Additionally, the degree of insulin resistance was negatively associated with executive function domain. None of the associations between the other hormones examined (adipokines, IGF-1, gonadal hormones and vitamin D) and cognitive function were significant. These preliminary findings suggest a possible association between obesity and cognitive function in healthy young women of reproductive age. More research is warranted into the potential modulatory effect of insulin resistance on this association

A numerical study of the development of bulk scale-free structures upon growth of self-affine aggregates

During the last decade, self-affine geometrical properties of many growing aggregates, originated in a wide variety of processes, have been well characterized. However, little progress has been achieved in the search of a unified description of the underlying dynamics. Extensive numerical evidence has been given showing that the bulk of aggregates formed upon ballistic aggregation and random deposition with surface relaxation processes can be broken down into a set of infinite scale invariant structures called "trees". These two types of aggregates have been selected because it has been established that they belong to different universality classes: those of Kardar-Parisi-Zhang and Edward-Wilkinson, respectively. Exponents describing the spatial and temporal scale invariance of the trees can be related to the classical exponents describing the self-affine nature of the growing interface. Furthermore, those exponents allows us to distinguish either the compact or non-compact nature of the growing trees. Therefore, the measurement of the statistic of the process of growing trees may become a useful experimental technique for the evaluation of the self-affine properties of some aggregates.Comment: 19 pages, 5 figures, accepted for publication in Phys.Rev.

Interface roughening with nonlinear surface tension

Using stability arguments, this Brief Report suggests that a term that enhances the surface tension in the presence of large height fluctuations should be included in the Kardar-Parisi-Zhang equation. A one-loop renormalization group analysis then shows for interface dimensions larger than $\simeq 3.3$ an unstable strong-coupling fixed point that enters the system from infinity. The relevance of these results to the roughening transition is discussed.Comment: 4 pages RevTeX, 1 figur

High dimensional behavior of the Kardar-Parisi-Zhang growth dynamics

We investigate analytically the large dimensional behavior of the Kardar-Parisi-Zhang (KPZ) dynamics of surface growth using a recently proposed non-perturbative renormalization for self-affine surface dynamics. Within this framework, we show that the roughness exponent $\alpha$ decays not faster than $\alpha\sim 1/d$ for large $d$. This implies the absence of a finite upper critical dimension.Comment: RevTeX, 4 pages, 2 figures. To appear in Phys. Rev.

Directed polymers in high dimensions

We study directed polymers subject to a quenched random potential in d transversal dimensions. This system is closely related to the Kardar-Parisi-Zhang equation of nonlinear stochastic growth. By a careful analysis of the perturbation theory we show that physical quantities develop singular behavior for d to 4. For example, the universal finite size amplitude of the free energy at the roughening transition is proportional to (4-d)^(1/2). This shows that the dimension d=4 plays a special role for this system and points towards d=4 as the upper critical dimension of the Kardar-Parisi-Zhang problem.Comment: 37 pages REVTEX including 4 PostScript figure

Recent results on multiplicative noise

Recent developments in the analysis of Langevin equations with multiplicative noise (MN) are reported. In particular, we: (i) present numerical simulations in three dimensions showing that the MN equation exhibits, like the Kardar-Parisi-Zhang (KPZ) equation both a weak coupling fixed point and a strong coupling phase, supporting the proposed relation between MN and KPZ; (ii) present dimensional, and mean field analysis of the MN equation to compute critical exponents; (iii) show that the phenomenon of the noise induced ordering transition associated with the MN equation appears only in the Stratonovich representation and not in the Ito one, and (iv) report the presence of a new first-order like phase transition at zero spatial coupling, supporting the fact that this is the minimum model for noise induced ordering transitions.Comment: Some improvements respect to the first versio

Renormalization group study of one-dimensional systems with roughening transitions

A recently introduced real space renormalization group technique, developed for the analysis of processes in the Kardar-Parisi-Zhang universality class, is generalized and tested by applying it to a different family of surface growth processes. In particular, we consider a growth model exhibiting a rich phenomenology even in one dimension. It has four different phases and a directed percolation related roughening transition. The renormalization method reproduces extremely well all the phase diagram, the roughness exponents in all the phases and the separatrix among them. This proves the versatility of the method and elucidates interesting physical mechanisms.Comment: Submitted to Phys. Rev.

Critical behavior of a one-dimensional fixed-energy stochastic sandpile

We study a one-dimensional fixed-energy version (that is, with no input or loss of particles), of Manna's stochastic sandpile model. The system has a continuous transition to an absorbing state at a critical value $\zeta_c$ of the particle density. Critical exponents are obtained from extensive simulations, which treat both stationary and transient properties. In contrast with other one-dimensional sandpiles, the model appears to exhibit finite-size scaling, though anomalies exist in the scaling of relaxation times and in the approach to the stationary state. The latter appear to depend strongly on the nature of the initial configuration. The critical exponents differ from those expected at a linear interface depinning transition in a medium with point disorder, and from those of directed percolation.Comment: 15 pages, 11 figure

Ecological Invasion, Roughened Fronts, and a Competitor's Extreme Advance: Integrating Stochastic Spatial-Growth Models

Both community ecology and conservation biology seek further understanding of factors governing the advance of an invasive species. We model biological invasion as an individual-based, stochastic process on a two-dimensional landscape. An ecologically superior invader and a resident species compete for space preemptively. Our general model includes the basic contact process and a variant of the Eden model as special cases. We employ the concept of a "roughened" front to quantify effects of discreteness and stochasticity on invasion; we emphasize the probability distribution of the front-runner's relative position. That is, we analyze the location of the most advanced invader as the extreme deviation about the front's mean position. We find that a class of models with different assumptions about neighborhood interactions exhibit universal characteristics. That is, key features of the invasion dynamics span a class of models, independently of locally detailed demographic rules. Our results integrate theories of invasive spatial growth and generate novel hypotheses linking habitat or landscape size (length of the invading front) to invasion velocity, and to the relative position of the most advanced invader.Comment: The original publication is available at www.springerlink.com/content/8528v8563r7u2742

Accounting for assay performance when estimating the temporal dynamics in SARS-CoV-2 seroprevalence in the U.S.

Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection