Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Animal models of prenatal immune challenge and their contribution to the study of schizophrenia: a systematic review

Prenatal immune challenge (PIC) in pregnant rodents produces offspring with abnormalities in behavior, histology, and gene expression that are reminiscent of schizophrenia and autism. Based on this, the goal of this article was to review the main contributions of PIC models, especially the one using the viral-mimetic particle polyriboinosinic-polyribocytidylic acid (poly-I:C), to the understanding of the etiology, biological basis and treatment of schizophrenia. This systematic review consisted of a search of available web databases (PubMed, SciELO, LILACS, PsycINFO, and ISI Web of Knowledge) for original studies published in the last 10 years (May 2001 to October 2011) concerning animal models of PIC, focusing on those using poly-I:C. The results showed that the PIC model with poly-I:C is able to mimic the prodrome and both the positive and negative/cognitive dimensions of schizophrenia, depending on the specific gestation time window of the immune challenge. The model resembles the neurobiology and etiology of schizophrenia and has good predictive value. In conclusion, this model is a robust tool for the identification of novel molecular targets during prenatal life, adolescence and adulthood that might contribute to the development of preventive and/or treatment strategies (targeting specific symptoms, i.e., positive or negative/cognitive) for this devastating mental disorder, also presenting biosafety as compared to viral infection models. One limitation of this model is the incapacity to model the full spectrum of immune responses normally induced by viral exposure.

On Disruption of Fear Memory by Reconsolidation Blockade: Evidence from Cannabidiol Treatment

The search for reconsolidation blockers may uncover clinically relevant drugs for disrupting memories of significant stressful life experiences, such as those underlying the posttraumatic stress disorder. Considering the safety of systemically administered cannabidiol (CBD), the major non-psychotomimetic component of Cannabis sativa, to animals and humans, the present study sought to investigate whether and how this phytocannabinoid (3-30 mg/kg intraperitoneally; i.p.) could mitigate an established memory, by blockade of its reconsolidation, evaluated in a contextual fear-conditioning paradigm in rats. We report that CBD is able to disrupt 1- and 7-days-old memories when administered immediately, but not 6 h, after their retrieval for 3 min, with the dose of 10 mg/kg being the most effective. This effect persists in either case for at least 1 week, but is prevented when memory reactivation was omitted, or when the cannabinoid type-1 receptors were antagonized selectively with AM251 (1.0 mg/kg). Pretreatment with the serotonin type-1A receptor antagonist WAY100635, however, failed to block CBD effects. These results highlight that recent and older fear memories are equally vulnerable to disruption induced by CBD through reconsolidation blockade, with a consequent long-lasting relief in contextual fear-induced freezing. Importantly, this CBD effect is dependent on memory reactivation, restricted to time window of <6h, and is possibly dependent on cannabinoid type-1 receptor-mediated signaling mechanisms. We also observed that the fear memories disrupted by CBD treatment do not show reinstatement or spontaneous recovery over 22 days. These findings support the view that reconsolidation blockade, rather than facilitated extinction, accounts for the aforementioned CBD results in our experimental conditions. Neuropsychopharmacology (2012) 37, 2132-2142; doi:10.1038/npp.2012.63; published online 2 May 2012

Arbitrage-Free Conditions and Hedging Strategies for Markets with Penalty Costs on Short Positions

We consider a discrete-time financial model in a general sample space with penalty costs on short positions. We consider a friction market closely related to the standard one except that withdrawals from the portfolio value proportional to short positions are made. We provide necessary and sufficient conditions for the nonexistence of arbitrages in this situation and for a self-financing strategy to replicate a contingent claim. For the finite-sample space case, this result leads to an explicit and constructive procedure for obtaining perfect hedging strategies.

Successful Strategy for Targeting the Central Nervous System Using Magnetic Albumin Nanospheres

This study reports on the successful use of magnetic albumin nanosphere (MAN), consisting of maghemite nanoparticles hosted by albumin-based nanosphere, to target different sites within the central nervous system (CNS). Ultrastructural analysis by transmission electron microscopy (TEM) of the material collected from the mice was performed in the time window of 30 minutes up to 30 days after administration. Evidence found that the administered MAN was initially internalized and transported by erythrocytes across the blood-brain-barrier and transferred to glial cells and neuropils before internalization by neurons, mainly in the cerebellum. We hypothesize that the efficiency of MAN in crossing the BBB with no pathological alterations is due to the synergistic effect of its two main components, the iron-based nanosized particles and the hosting albumin-based nanospheres. We found that the MAN in targeting the CNS represents an important step towards the design of nanosized materials for clinical and diagnostic applications.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

Skin Penetration Time-Profiles for Continuous 810nm and Superpulsed 904nm Lasers in a Rat Model

Objective: The purpose of this study was to investigate the rat skin penetration abilities of two commercially available low-level laser therapy (LLLT) devices during 150 sec of irradiation. Background data: Effective LLLT irradiation typically lasts from 20 sec up to a few minutes, but the LLLT time-profiles for skin penetration of light energy have not yet been investigated. Materials and methods: Sixty-two skin flaps overlaying rat's gastrocnemius muscles were harvested and immediately irradiated with LLLT devices. Irradiation was performed either with a 810 nm, 200mW continuous wave laser, or with a 904 nm, 60mW superpulsed laser, and the amount of penetrating light energy was measured by an optical power meter and registered at seven time points (range, 1-150 sec). Results: With the continuous wave 810nm laser probe in skin contact, the amount of penetrating light energy was stable at similar to 20% (SEM +/- 0.6) of the initial optical output during 150 sec irradiation. However, irradiation with the superpulsed 904 nm, 60mW laser showed a linear increase in penetrating energy from 38% (SEM +/- 1.4) to 58% (SEM +/- 3.5) during 150 sec of exposure. The skin penetration abilities were significantly different (p < 0.01) between the two lasers at all measured time points. Conclusions: LLLT irradiation through rat skin leaves sufficient subdermal light energy to influence pathological processes and tissue repair. The finding that superpulsed 904nm LLLT light energy penetrates 2-3 easier through the rat skin barrier than 810nm continuous wave LLLT, corresponds well with results of LLLT dose analyses in systematic reviews of LLLT in musculoskeletal disorders. This may explain why the differentiation between these laser types has been needed in the clinical dosage recommendations of World Association for Laser Therapy.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.