Forecasting Exchange-Rates via Local Approximation Methods and Neural Networks

There has been an increased number of papers in the literature in recent years, applying several methods and techniques for exchange - rate prediction. This paper focuses on the Greek drachma using daily observations of the drachma rates against four major currencies, namely the U.S. Dollar (USD), the Deutsche Mark (DM), the French Franc (FF) and the British Pound (GBP) for a period of 11 years, aiming at forecasting their short-term course by applying local approximation methods based on both chaotic analysis and neural networks.Key Words: Exchange Rates, Forecasting, Neural Networks

SPATIAL DISTRIBUTION REQUIREMENTS OF REFERENCE GROUND CONTROL FOR ESTIMATING LIDAR/INS BORESIGHT MISALIGNMENT

LiDAR (Light Detection and Ranging, also known as Airborne Laser Scanning – ALS) is a powerful technology for obtaining detailed and accurate terrain models as well as precise description of natural and man-made objects from airborne platforms, with excellent vertical accuracy. High performance integrated GPS/INS systems provide the necessary navigation information for the LiDAR data acquisition platform, and therefore, the proper calibration of the entire Mobile Mapping System (MMS) including individual and inter-sensor calibration, is essential to determine the accurate spatial  relationship of the involved sensors. In particular, the spatial relationship between the INS body frame and the LiDAR body frame is of high importance as it could be the largest source of systematic errors in airborne MMS. The feasibility of using urban areas, especially buildings, for boresight misalignment is still investigated. In this research, regularly or randomly distributed, photogrammetrically restituted buildings are used as reference surfaces, to investigate the impact of  the spatial distribution and the distance between the necessary ‘building-positions’ on boresight’s misalignment parameter estimation. The data used for performance evaluation included LiDAR point clouds Pothou, A. et al  777 and aerial images captured in a test area in London, Ohio, USA. The city includes mainly residential houses and a few bigger buildings

A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals

<p>Abstract</p> <p>Background</p> <p>Humans are routinely and concurrently exposed to multiple toxic chemicals, including various metals and organics, often at levels that can cause adverse and potentially synergistic effects. However, toxicokinetic modeling studies of exposures to these chemicals are typically performed on a single chemical basis. Furthermore, the attributes of available models for individual chemicals are commonly estimated specifically for the compound studied. As a result, the available models usually have parameters and even structures that are not consistent or compatible across the range of chemicals of concern. This fact precludes the systematic consideration of synergistic effects, and may also lead to inconsistencies in calculations of co-occurring exposures and corresponding risks. There is a need, therefore, for a consistent modeling framework that would allow the systematic study of cumulative risks from complex mixtures of contaminants.</p> <p>Methods</p> <p>A Generalized Toxicokinetic Modeling system for Mixtures (GTMM) was developed and evaluated with case studies. The GTMM is physiologically-based and uses a consistent, chemical-independent physiological description for integrating widely varying toxicokinetic models. It is modular and can be directly "mapped" to individual toxicokinetic models, while maintaining physiological consistency across different chemicals. Interaction effects of complex mixtures can be directly incorporated into the GTMM.</p> <p>Conclusions</p> <p>The application of GTMM to different individual metals and metal compounds showed that it explains available observational data as well as replicates the results from models that have been optimized for individual chemicals. The GTMM also made it feasible to model toxicokinetics of complex, interacting mixtures of multiple metals and nonmetals in humans, based on available literature information. The GTMM provides a central component in the development of a "source-to-dose-to-effect" framework for modeling population health risks from environmental contaminants. As new data become available on interactions of multiple chemicals, the GTMM can be iteratively parameterized to improve mechanistic understanding of human health risks from exposures to complex mixtures of chemicals.</p

Mathematical model of uptake and metabolism of arsenic(III) in human hepatocytes - Incorporation of cellular antioxidant response and threshold-dependent behavior

<p>Abstract</p> <p>Background</p> <p>Arsenic is an environmental pollutant, potent human toxicant, and oxidative stress agent with a multiplicity of health effects associated with both acute and chronic exposures. A semi-mechanistic cellular-level toxicokinetic (TK) model was developed in order to describe the uptake, biotransformation and clearance of arsenical species in human hepatocytes. Notable features of this model are the incorporation of arsenic-glutathione complex formation and a "switch-like" formulation to describe the antioxidant response of hepatocytes to arsenic exposure.</p> <p>Results</p> <p>The cellular-level TK model applies mass action kinetics in order to predict the concentrations of trivalent and pentavalent arsenicals in hepatocytes. The model simulates uptake of arsenite (iAs^III) via aquaporin isozymes 9 (AQP9s), glutathione (GSH) conjugation, methylation by arsenic methyltransferase (AS3MT), efflux through multidrug resistant proteins (MRPs) and the induced antioxidant response via thioredoxin reductase (TR) activity. The model was parameterized by optimization of model estimates for arsenite (iAs^III), monomethylated (MMA) and dimethylated (DMA) arsenicals concentrations with time-course experimental data in human hepatocytes for a time span of 48 hours, and dose-response data at 24 hours for a range of arsenite concentrations from 0.1 to 10 μM. Global sensitivity analysis of the model showed that at low doses the transport parameters had a dominant role, whereas at higher doses the biotransformation parameters were the most significant. A parametric comparison of the TK model with an analogous model developed for rat hepatocytes from the literature demonstrated that the biotransformation of arsenite (e.g. GSH conjugation) has a large role in explaining the variation in methylation between rats and humans.</p> <p>Conclusions</p> <p>The cellular-level TK model captures the temporal modes of arsenical accumulation in human hepatocytes. It highlighted the key biological processes that influence arsenic metabolism by explicitly modelling the metabolic network of GSH-adducts formation. The parametric comparison with the TK model developed for rats suggests that the variability in GSH conjugation could have an important role in inter-species variability of arsenical methylation. The TK model can be incorporated into larger-scale physiologically based toxicokinetic (PBTK) models of arsenic for improving the estimates of PBTK model parameters.</p

Lack of LDL Receptor Enhances Amyloid Deposition and Decreases Glial Response in an Alzheimer's Disease Mouse Model

BACKGROUND: Apolipoprotein E (ApoE), a cholesterol carrier associated with atherosclerosis, is a major risk factor for Alzheimer's disease (AD). The low-density lipoprotein receptor (LDLR) regulates ApoE levels in the periphery and in the central nervous system. LDLR has been identified on astrocytes and a number of studies show that it modulates amyloid deposition in AD transgenic mice. However these findings are controversial on whether LDLR deletion is beneficial or detrimental on the AD-like phenotype of the transgenic mice. METHODOLOGY/PRINCIPAL FINDINGS: To investigate the role of LDLR in the development of the amyloid related phenotype we used an APP/PS1 transgenic mouse (5XFAD) that develops an AD-like pathology with amyloid plaques, astrocytosis and microgliosis. We found that 4 months old 5XFAD transgenic mice on the LDLR deficient background (LDLR-/-) have increased amyloid plaque deposition. This increase is associated with a significant decrease in astrocytosis and microgliosis in the 5XFAD/LDLR-/- mice. To further elucidate the role of LDLR in relation with ApoE we have generated 5XFAD transgenic mice on the ApoE deficient (ApoE-/-) or the ApoE/LDLR double deficient background (ApoE-/-/LDLR -/-). We have found that ApoE deletion in the 4 months old 5XFAD/ApoE-/- mice decreases amyloid plaque formation as expected, but has no effect on astrocytosis or microgliosis. By comparison 5XFAD/ApoE-/-LDLR -/- double deficient mice of the same age have increased amyloid deposition with decreased astrocytosis and microgliosis. CONCLUSIONS: Our analysis shows that LDL deficiency regulates astrocytosis and microgliosis in an AD mouse model. This effect is independent of ApoE, as both 5XFAD/LDLR -/- and 5XFAD/ApoE-/- LDLR -/- mice show reduction in inflammatory response and increase in amyloid deposition compared to control mice. These results demonstrate that LDLR regulates glial response in this mouse model independently of ApoE and modifies amyloid deposition

Attentive Learning of Sequential Handwriting Movements: A Neural Network Model

Defense Advanced research Projects Agency and the Office of Naval Research (N00014-95-1-0409, N00014-92-J-1309); National Science Foundation (IRI-97-20333); National Institutes of Health (I-R29-DC02952-01)

Mesoscale modeling of combined aerosol and photo-oxidant processes in the Eastern Mediterranean

International audienceParticulate matter and photo-oxidant processes in the Eastern Mediterranean have been studied using the UAM-AERO mesoscale air quality model in conjunction with the NILU-CTM regional model. Meteorological data were obtained from the RAMS prognostic meteorological model. The modeling domain includes the eastern Mediterranean area between the Greek mainland and the island of Crete. The modeling system is applied to study the atmospheric processes in three periods, i.e. 13?16 July 2000, 26?30 July 2000 and 7?14 January 2001. The spatial and temporal distributions of both gaseous and particulate matter pollutants have been extensively studied together with the identification of major emission sources in the area. The modeling results were compared with field data obtained in the same period. The objective of the current modeling work was mainly to apply the UAM-AERO mesoscale model in the eastern Mediterranean in order to assess the performed field campaigns and determine that the applied mesoscale model is fit for this purpose. Comparison of the modeling results with measured data was performed for a number of gaseous and aerosol species. The UAM-AERO model underestimates the PM10 measured concentrations during summer and winter campaigns. Discrepancies between modeled and measured data are attributed to unresolved particulate matter emissions. Particulate matter in the area is mainly composed by sulphate, sea salt and crustal materials, and with significant amounts of nitrate, ammonium and organics. During winter the particulate matter and oxidant concentrations were lower than the summer values

The role of carotid plaque echogenicity in baroreflex sensitivity

ObjectiveThe baroreflex sensitivity is impaired in patients with carotid atherosclerosis. The purpose of our study was to assess the impact of carotid plaque echogenicity on the baroreflex function in patients with significant carotid atherosclerosis, who have not undergone carotid surgery.MethodSpontaneous baroreflex sensitivity (sBRS) was estimated in 45 patients with at least a severe carotid stenosis (70%-99%). sBRS calculation was performed noninvasively, with the spontaneous sequence method, based on indirectly estimated central blood pressures from radial recordings. This method failed in three patients due to poor-quality recordings, and eventually 42 patients were evaluated. After carotid duplex examination, carotid plaque echogenicity was graded from 1 to 4 according to Gray-Weale classification and the patients were divided into two groups: the echolucent group (grades 1 and 2) and the echogenic group (grades 3 and 4).ResultsSixteen patients (38%) and 26 patients (62%) were included in the echolucent and echogenic group, respectively. Diabetes mellitus was observed more frequently among echolucent plaques (χ2 = 8.0; P < .004), while those plaques were also more commonly symptomatic compared with echogenic atheromas (χ2 = 8.5; P < .003). Systolic arterial pressure, diastolic arterial pressure, and heart rate were similar in the two groups. Nevertheless, the mean value of baroreflex sensitivity was found to be significantly lower in the echogenic group (2.96 ms/mm Hg) compared with the echolucent one (5.0 ms/mm Hg), (F [1, 42] = 10.1; P < .003).ConclusionsThese findings suggest that echogenic plaques are associated with reduced baroreflex function compared with echolucent ones. Further investigation is warranted to define whether such an sBRS impairment could be responsible for cardiovascular morbidity associated with echogenic plaques

ACCURATE 3D SCANNING OF DAMAGED ANCIENT GREEK INSCRIPTIONS FOR REVEALING WEATHERED LETTERS

In this paper two non-invasive non-destructive alternative techniques to the traditional and invasive technique of squeezes are presented alongside with specialized developed processing methods, aiming to help the epigraphists to reveal and analyse weathered letters in ancient Greek inscriptions carved in masonry or marble. The resulting 3D model would serve as a detailed basis for the epigraphists to try to decipher the inscription. The data were collected by using a Structured Light scanner. The creation of the final accurate three dimensional model is a complicated procedure requiring large computation cost and human effort. It includes the collection of geometric data in limited space and time, the creation of the surface, the noise filtering and the merging of individual surfaces. The use of structured light scanners is time consuming and requires costly hardware and software. Therefore an alternative methodology for collecting 3D data of the inscriptions was also implemented for reasons of comparison. Hence, image sequences from varying distances were collected using a calibrated DSLR camera aiming to reconstruct the 3D scene through SfM techniques in order to evaluate the efficiency and the level of precision and detail of the obtained reconstructed inscriptions. Problems in the acquisition processes as well as difficulties in the alignment step and mesh optimization are also encountered. A meta-processing framework is proposed and analysed. Finally, the results of processing and analysis and the different 3D models are critically inspected and then evaluated by a specialist in terms of accuracy, quality and detail of the model and the capability of revealing damaged and ”hidden” letters

Modulation of human macrophage responses to mycobacterium tuberculosis by silver nanoparticles of different size and surface modification

Exposure to silver nanoparticles (AgNP) used in consumer products carries potential health risks including increased susceptibility to infectious pathogens. Systematic assessments of antimicrobial macrophage immune responses in the context of AgNP exposure are important because uptake of AgNP by macrophages may lead to alterations of innate immune cell functions. In this study we examined the effects of exposure to AgNP with different particle sizes (20 and 110 nm diameters) and surface chemistry (citrate or polyvinlypyrrolidone capping) on cellular toxicity and innate immune responses against Mycobacterium tuberculosis (M.tb) by human monocyte-derived macrophages (MDM). Exposures of MDM to AgNP significantly reduced cellular viability, increased IL8 and decreased IL10 mRNA expression. Exposure of M.tb-infected MDM to AgNP suppressed M.tb-induced expression of IL1B, IL10, and TNFA mRNA. Furthermore, M.tb-induced IL-1β, a cytokine critical for host resistance to M.tb, was inhibited by AgNP but not by carbon black particles indicating that the observed immunosuppressive effects of AgNP are particle specific. Suppressive effects of AgNP on the M.tb-induced host immune responses were in part due to AgNP-mediated interferences with the TLR signaling pathways that culminate in the activation of the transcription factor NF-κB. AgNP exposure suppressed M.tb-induced expression of a subset of NF-κB mediated genes (CSF2, CSF3, IFNG, IL1A, IL1B, IL6, IL10, TNFA, NFKB1A). In addition, AgNP exposure increased the expression of HSPA1A mRNA and the corresponding stress-induced Hsp72 protein. Up-regulation of Hsp72 by AgNP can suppress M.tb-induced NF-κB activation and host immune responses. The observed ability of AgNP to modulate infectious pathogen-induced immune responses has important public health implications