CDM accelerating cosmology as an alternative to Lambda CDM model

A new accelerating cosmology driven only by baryons plus cold dark matter (CDM) is proposed in the framework of general relativity. In this scenario the present accelerating stage of the Universe is powered by the negative pressure describing the gravitationally-induced particle production of cold dark matter particles. This kind of scenario has only one free parameter and the differential equation governing the evolution of the scale factor is exactly the same of the Lambda CDM model. For a spatially flat Universe, as predicted by inflation (Omega(dm) + Omega(baryon) = 1), it is found that the effectively observed matter density parameter is Omega(meff) = 1 - alpha, where alpha is the constant parameter specifying the CDM particle creation rate. The supernovae test based on the Union data (2008) requires alpha similar to 0.71 so that Omega(meff) similar to 0.29 as independently derived from weak gravitational lensing, the large scale structure and other complementary observations.

Preventive and curative glycoside kaempferol treatments attenuate the TH2-driven allergic airway disease

Asthma is a chronic respiratory disease characterized by airway inflammation and airway hyperresponsiveness (AHR). One strategy to treat allergic diseases is the development of new drugs. Flavonoids are compounds derived from plants and are known to have antiallergic, anti-inflammatory, and antioxidant properties. To investigate whether the flavonoid kaempferol glycoside 3-O-[beta-D-glycopiranosil-(1 -> 6)-alpha-L-ramnopiranosil]-7-O-alpha-L-ramnopiranosil-kaempferol (GRRK) would be capable of modulating allergic airway disease (AAD) either as a preventive (GRRK P) or curative (GRRK C) treatment in an experimental model of asthma. At weekly intervals, BALB/c mice were subcutaneously (sc) sensitized twice with ovalbumin (OVA)/alum and challenged twice with OVA administered intranasally. To evaluate any preventive effects GRRK was administered 1 h (hour) before each OVA-sensitization and challenge, while to analyze the curative effects mice were first sensitized with OVA, followed by GRRK given at day 18 through 21. The onset: of AAD was evaluated 24 h after the last OVA challenge. Both treatments resulted in a dose-dependent reduction in total leukocyte and eosinophil counts in the bronchoalveolar lavage fluid (BAL). GRRK also decreased CD4(+), B220(+), MHC class II and CD40 molecule expressions in BAL cells. Histology and lung mechanic showed that GRRK suppressed mucus production and ameliorated the AHR induced by OVA challenge. Furthermore, GRRK impaired Th2 cytokine production (IL-5 and IL-13) and did not induce a Th1 pattern of inflammation. These findings demonstrate that GRRK treatment before or after established allergic lung disease down-regulates key asthmatic features. Therefore. GRRK has a potential clinical use for the treatment of allergic asthma. (C) 2009 Elsevier B.V. All rights reserved.

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

An approach for solving the lot-sizing problem of a market-driven foundry

Foundries can be found all over Brazil and they are very important to its economy. In 2008, a mixed integer-programming model for small market-driven foundries was published, attempting to minimize delivery delays. We undertook a study of that model. Here, we present a new approach based on the decomposition of the problem into two sub-problems: production planning of alloys and production planning of items. Both sub-problems are solved using a Lagrangian heuristic based on transferences. An important aspect of the proposed heuristic is its ability to take into account a secondary practice objective solution: the furnace waste. Computational tests show that the approach proposed here is able to generate good quality solutions that outperform prior results. Journal of the Operational Research Society (2010) 61, 108-114. doi:10.1057/jors.2008.151

Fault Coverage-Driven Incremental Test Generation

In this paper, we consider a classical problem of complete test generation for deterministic finite-state machines (FSMs) in a more general setting. The first generalization is that the number of states in implementation FSMs can even be smaller than that of the specification FSM. Previous work deals only with the case when the implementation FSMs are allowed to have the same number of states as the specification FSM. This generalization provides more options to the test designer: when traditional methods trigger a test explosion for large specification machines, tests with a lower, but yet guaranteed, fault coverage can still be generated. The second generalization is that tests can be generated starting with a user-defined test suite, by incrementally extending it until the desired fault coverage is achieved. Solving the generalized test derivation problem, we formulate sufficient conditions for test suite completeness weaker than the existing ones and use them to elaborate an algorithm that can be used both for extending user-defined test suites to achieve the desired fault coverage and for test generation. We present the experimental results that indicate that the proposed algorithm allows obtaining a trade-off between the length and fault coverage of test suites.

Spallation product distributions and neutron multiplicities for accelerator-driven system using the CRISP code

Neutron multiplicities for several targets and spallation products of proton-induced reactions in thin targets of interest to an accelerator-driven system obtained with the CRISP code have been reported. This code is a Monte Carlo calculation that simulates the intranuclear cascade and evaporationl fission competition processes. Results are compared with experimental data, and agreement between each other can be considered quite satisfactory in a very broad energy range of incitant particles and different targets.

The dynamics of cargo driven by molecular motors in the context of asymmetric simple exclusion processes

We consider the dynamics of cargo driven by a collection of interacting molecular motors in the context of ail asymmetric simple exclusion process (ASEP). The model is formulated to account for (i) excluded-volume interactions, (ii) the observed asymmetry of the stochastic movement of individual motors and (iii) interactions between motors and cargo. Items (i) and (ii) form the basis of ASEP models and have already been considered to study the behavior of motor density profile [A. Parmeggiani. T. Franosch, E. Frey, Phase Coexistence in driven one-dimensional transport, Phys. Rev. Lett. 90 (2003) 086601-1-086601-4]. Item (iii) is new. It is introduced here as an attempt to describe explicitly the dependence of cargo movement on the dynamics of motors in this context. The steady-state Solutions Of the model indicate that the system undergoes a phase transition of condensation type as the motor density varies. We study the consequences of this transition to the behavior of the average cargo velocity. (C) 2009 Elsevier B.V. All rights reserved.

Orbitally driven east-west antiphasing of South American precipitation

The variations of tropical precipitation are antiphased between the hemispheres on orbital timescales. This antiphasing arises through the alternating strength of incoming solar radiation in the two hemispheres, which affects monsoon intensity and hence the position of the meridional atmospheric circulation of the Hadley cells(1-4). Here we compare an oxygen isotopic record recovered from a speleothem from northeast Brazil for the past 26,000 years with existing reconstructions of precipitation in tropical South America(5-8). During the Holocene, we identify a similar, but zonally oriented, antiphasing of precipitation within the same hemisphere: northeast Brazil experiences humid conditions during low summer insolation and aridity when summer insolation is high, whereas the rest of southern tropical South America shows opposite characteristics. Simulations with a general circulation model that incorporates isotopic variations support this pattern as well as the link to insolation-driven monsoon activity. Our results suggest that convective heating over tropical South America and associated adjustments in large-scale subsidence over northeast Brazil lead to a remote forcing of the South American monsoon, which determines most of the precipitation changes in the region on orbital timescales.

Formalization of an architectural model for exception handling coordination based on CA action concepts

Architectures based on Coordinated Atomic action (CA action) concepts have been used to build concurrent fault-tolerant systems. This conceptual model combines concurrent exception handling with action nesting to provide a general mechanism for both enclosing interactions among system components and coordinating forward error recovery measures. This article presents an architectural model to guide the formal specification of concurrent fault-tolerant systems. This architecture provides built-in Communicating Sequential Processes (CSPs) and predefined channels to coordinate exception handling of the user-defined components. Hence some safety properties concerning action scoping and concurrent exception handling can be proved by using the FDR (Failure Divergence Refinement) verification tool. As a result, a formal and general architecture supporting software fault tolerance is ready to be used and proved as users define components with normal and exceptional behaviors. (C) 2010 Elsevier B.V. All rights reserved.

Cellular automaton model for molecular traffic jams

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Equipping Simulation Model (BIOSIM)’s Actors With Multi-agent Intelligence on Cross platforms

Thesis is to Introduce an Intelligent cross platform architecture with Multi-agent system in order to equip the simulation Models with agents, having intelligent behavior, reactive and pro-active nature and rational in decision making.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study was applied to the Bacchiglione catchment, located in Italy. The first methodological step was to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model were implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge were generated, as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location were assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that, overall, the assimilation of uncertain observations can improve the hydrologic model performance. In particular, it was found that the model structure is an important factor, of difficult characterization, since can induce different forecasts in terms of outflow discharge. This study is partly supported by the FP7 EU Project WeSenseIt.

Hydrodynamic Simulations Of Vacuum-Driven Storage Tanks

As a result of urbanization, stormwater runoff flow rates and volumes are significantly increased due to increasing impervious land cover and the decreased availability of depression storage. Storage tanks are the basic devices to efficiently control the flow rate in drainage systems during wet weather. Presented in the paper conception of vacuum-driven detention tanks allows to increase the storage capacity by usage of space above the free surface water elevation at the inlet channel. Partial vacuum storage makes possible to gain cost savings by reduction of both the horizontal area of the detention tank and necessary depth of foundations. Simulation model of vacuum-driven storage tank has been developed to estimate potential profits of its application in urban drainage system. Although SWMM5 has no direct options for vacuum tanks an existing functions (i.e. control rules) have been used to reflect its operation phases. Rainfall data used in simulations were recorded at raingage in Czestochowa during years 2010÷2012 with time interval of 10minutes. Simulation results gives overview to practical operation and maintenance cost (energy demand) of vacuum driven storage tanks depending of the ratio: vacuum-driven volume to total storage capacity. The following conclusion can be drawn from this investigations: vacuum-driven storage tanks are characterized by uncomplicated construction and control systems, thus can be applied in newly developed as well as in the existing urban drainage systems. the application of vacuum in underground detention facilities makes possible to increase of the storage capacity of existing reservoirs by usage the space above the maximum depth. Possible increase of storage capacity can achieve even a few dozen percent at relatively low investment costs. vacuum driven storage tanks can be included in existing simulation software (i.e. SWMM) using options intended for pumping stations (including control and action rules ).