Free inertial processes driven by Gaussian noise: Probability distributions, anomalous diffusion and fractal behavior

We study the motion of an unbound particle under the influence of a random force modeled as Gaussian colored noise with an arbitrary correlation function. We derive exact equations for the joint and marginal probability density functions and find the associated solutions. We analyze in detail anomalous diffusion behaviors along with the fractal structure of the trajectories of the particle and explore possible connections between dynamical exponents of the variance and the fractal dimension of the trajectories.

Modelling diffusion of innovations in a social network

A simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information, agents decide whether to upgrade their level or not, balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.

Self-organized evolution in a socio-economic environment

We propose a general scenario to analyze technological changes in socio-economic environments. We illustrate the ideas with a model that incorporating the main trends is simple enough to extract analytical results and, at the same time, sufficiently complex to display a rich dynamic behavior. Our study shows that there exists a macroscopic observable that is maximized in a regime where the system is critical, in the sense that the distribution of events follow power laws. Computer simulations show that, in addition, the system always self-organizes to achieve the optimal performance in the stationary state.

Self-dynamic structure factor of dense liquids: Theory and simulation

The self-intermediate dynamic structure factor Fs(k,t) of liquid lithium near the melting temperature is calculated by molecular dynamics. The results are compared with the predictions of several theoretical approaches, paying special attention to the Lovesey model and the Wahnstrm and Sjgren mode-coupling theory. To this end the results for the Fs(k,t) second memory function predicted by both models are compared with the ones calculated from the simulations.

Random diffusion and leverage effect in financial markets

We prove that Brownian market models with random diffusion coefficients provide an exact measure of the leverage effect [J-P. Bouchaud et al., Phys. Rev. Lett. 87, 228701 (2001)]. This empirical fact asserts that past returns are anticorrelated with future diffusion coefficient. Several models with random diffusion have been suggested but without a quantitative study of the leverage effect. Our analysis lets us to fully estimate all parameters involved and allows a deeper study of correlated random diffusion models that may have practical implications for many aspects of financial markets.

Dynamical properties of the Zhang model of self-organized criticality

Critical exponents of the infinitely slowly driven Zhang model of self-organized criticality are computed for d=2 and 3, with particular emphasis devoted to the various roughening exponents. Besides confirming recent estimates of some exponents, new quantities are monitored, and their critical exponents computed. Among other results, it is shown that the three-dimensional exponents do not coincide with the Bak-Tang-Wiesenfeld [Phys. Rev. Lett. 59, 381 (1987); Phys. Rev. A 38, 364 (1988)] (Abelian) model, and that the dynamical exponent as computed from the correlation length and from the roughness of the energy profile do not necessarily coincide, as is usually implicitly assumed. An explanation for this is provided. The possibility of comparing these results with those obtained from renormalization group arguments is also briefly addressed.

Generalized Langevin equations: Anomalous diffusion and probability distributions

We study the motion of a particle governed by a generalized Langevin equation. We show that, when no fluctuation-dissipation relation holds, the long-time behavior of the particle may be from stationary to superdiffusive, along with subdiffusive and diffusive. When the random force is Gaussian, we derive the exact equations for the joint and marginal probability density functions for the position and velocity of the particle and find their solutions.

Exact temporal evolution for some non-linear diffusion process

Exact solutions to FokkerPlanck equations with nonlinear drift are considered. Applications of these exact solutions for concrete models are studied. We arrive at the conclusion that for certain drifts we obtain divergent moments (and infinite relaxation time) if the diffusion process can be extended without any obstacle to the whole space. But if we introduce a potential barrier that limits the diffusion process, moments converge with a finite relaxation time.

Diffusion Spectrum Imaging after stroke shows structural changes in the contra-lateral motor network correlating with functional recovery

There is growing interest in understanding the role of the non-injured contra-lateral hemisphere in stroke recovery. In the experimental field, histological evidence has been reported that structural changes occur in the contra-lateral connectivity and circuits during stroke recovery. In humans, some recent imaging studies indicated that contra-lateral sub-cortical pathways and functional and structural cortical networks are remodeling, after stroke. Structural changes in the contra-lateral networks, however, have never been correlated to clinical recovery in patients. To determine the importance of the contra-lateral structural changes in post-stroke recovery, we selected a population of patients with motor deficits after stroke affecting the motor cortex and/or sub-cortical motor white matter. We explored i) the presence of Generalized Fractional Anisotropy (GFA) changes indicating structural alterations in the motor network of patientsâeuro? contra-lateral hemisphere as well as their longitudinal evolution ii) the correlation of GFA changes with patientsâeuro? clinical scores, stroke size and demographics data iii) and a predictive model.

Self-Consolidating Concrete—Applications for Slip-Form Paving: Phase II, May 2011

The goal of the project was to develop a new type of self-consolidating concrete (SCC) for slip-form paving to simplify construction an make smoother pavements. Developing the new SCC involved two phases: a feasibility study (Phase I sponsored by TPF-5[098] and concrete admixtures industry) and an in-depth mix proportioning and performance study and field applications (Phase II). The phase I study demonstrated that the new type of SCC needs to possess not only excellent self-consolidating ability before a pavement slab is extruded, but also sufficient “green” strength (the strength of the concrete in a plastic state) after the extrusion. To meet these performance criteria, the new type of SCC mixtures should not be as fluid as conventional SCC but just flowable enough to be self-consolidating. That is, this new type of SCC should be semi-flowable self-consolidating concrete (SFSCC). In the phase II study, effects of different materials and admixtures on rheology, especially the thixotropy, and green strength of fresh SFSCC have been further investigated. The results indicate that SFSCC can be designed to (1) be workable enough for machine placement, (2) be self-consolidating without segregation, (3) hold its shape after extrusion from a paver, and (4) have performance properties (strength and durability) comparable with current pavement concrete. Due to the combined flowability (for self-consolidation) and shape-holding ability (for slip-forming) requirements, SFSCC demands higher cementitious content than conventional pavement concrete. Generally, high cementitious content is associated with high drying shrinkage potential of the concrete. However, well-proportioned and well-constructed SFSCC in a bike path constructed at Ames, IA, has not shown any shrinkage cracks after approximately 3 years of field service. On the other hand, another SFSCC pavement with different mix proportions and construction conditions showed random cracking. The results from the field SFSCC performance monitoring implied that not only the mix proportioning method but also the construction practice is important for producing durable SFSCC pavements. A carbon footprint, energy consumption, and cost analysis conducted in this study have suggested that SFSCC is economically comparable to conventional pavement concrete in fixed-form paving construction, with the benefit of faster, quieter, and easier construction.

Autoreactive T cells bypass negative selection and respond to self-antigen stimulation during infection.

Central and peripheral tolerance prevent autoimmunity by deleting the most aggressive CD8(+) T cells but they spare cells that react weakly to tissue-restricted antigen (TRA). To reveal the functional characteristics of these spared cells, we generated a transgenic mouse expressing the TCR of a TRA-specific T cell that had escaped negative selection. Interestingly, the isolated TCR matches the affinity/avidity threshold for negatively selecting T cells, and when developing transgenic cells are exposed to their TRA in the thymus, only a fraction of them are eliminated but significant numbers enter the periphery. In contrast to high avidity cells, low avidity T cells persist in the antigen-positive periphery with no signs of anergy, unresponsiveness, or prior activation. Upon activation during an infection they cause autoimmunity and form memory cells. Unexpectedly, peptide ligands that are weaker in stimulating the transgenic T cells than the thymic threshold ligand also induce profound activation in the periphery. Thus, the peripheral T cell activation threshold during an infection is below that of negative selection for TRA. These results demonstrate the existence of a level of self-reactivity to TRA to which the thymus confers no protection and illustrate that organ damage can occur without genetic predisposition to autoimmunity.

Stem cell-related "self-renewal" signature and high epidermal growth factor receptor expression associated with resistance to concomitant chemoradiotherapy in glioblastoma.

PURPOSE: Glioblastomas are notorious for resistance to therapy, which has been attributed to DNA-repair proficiency, a multitude of deregulated molecular pathways, and, more recently, to the particular biologic behavior of tumor stem-like cells. Here, we aimed to identify molecular profiles specific for treatment resistance to the current standard of care of concomitant chemoradiotherapy with the alkylating agent temozolomide. PATIENTS AND METHODS: Gene expression profiles of 80 glioblastomas were interrogated for associations with resistance to therapy. Patients were treated within clinical trials testing the addition of concomitant and adjuvant temozolomide to radiotherapy. RESULTS: An expression signature dominated by HOX genes, which comprises Prominin-1 (CD133), emerged as a predictor for poor survival in patients treated with concomitant chemoradiotherapy (n = 42; hazard ratio = 2.69; 95% CI, 1.38 to 5.26; P = .004). This association could be validated in an independent data set. Provocatively, the HOX cluster was reminiscent of a "self-renewal" signature (P = .008; Gene Set Enrichment Analysis) recently characterized in a mouse leukemia model. The HOX signature and EGFR expression were independent prognostic factors in multivariate analysis, adjusted for the O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, a known predictive factor for benefit from temozolomide, and age. Better outcome was associated with gene clusters characterizing features of tumor-host interaction including tumor vascularization and cell adhesion, and innate immune response. CONCLUSION: This study provides first clinical evidence for the implication of a "glioma stem cell" or "self-renewal" phenotype in treatment resistance of glioblastoma. Biologic mechanisms identified here to be relevant for resistance will guide future targeted therapies and respective marker development for individualized treatment and patient selection.