Dynamic regulation of the tryptophan operon: A modeling study and comparison with experimental data

A mathematical model for regulation of the tryptophan operon is presented. This model takes into account repression, feedback enzyme inhibition, and transcriptional attenuation. Special attention is given to model parameter estimation based on experimental data. The model's system of delay differential equations is numerically solved, and the results are compared with experimental data on the temporal evolution of enzyme activity in cultures of Escherichia coli after a nutritional shift (minimal + tryptophan medium to minimal medium). Good agreement is obtained between the numeric simulations and the experimental results for wild-type E. coli, as well as for two different mutant strains.

Statistical modeling of large microarray data sets to identify stimulus-response profiles

A statistical modeling approach is proposed for use in searching large microarray data sets for genes that have a transcriptional response to a stimulus. The approach is unrestricted with respect to the timing, magnitude or duration of the response, or the overall abundance of the transcript. The statistical model makes an accommodation for systematic heterogeneity in expression levels. Corresponding data analyses provide gene-specific information, and the approach provides a means for evaluating the statistical significance of such information. To illustrate this strategy we have derived a model to depict the profile expected for a periodically transcribed gene and used it to look for budding yeast transcripts that adhere to this profile. Using objective criteria, this method identifies 81% of the known periodic transcripts and 1,088 genes, which show significant periodicity in at least one of the three data sets analyzed. However, only one-quarter of these genes show significant oscillations in at least two data sets and can be classified as periodic with high confidence. The method provides estimates of the mean activation and deactivation times, induced and basal expression levels, and statistical measures of the precision of these estimates for each periodic transcript.

Blood flow and oxygen delivery to human brain during functional activity: Theoretical modeling and experimental data

Coupling of cerebral blood flow (CBF) and cerebral metabolic rate for oxygen (CMRO2) in physiologically activated brain states remains the subject of debates. Recently it was suggested that CBF is tightly coupled to oxidative metabolism in a nonlinear fashion. As part of this hypothesis, mathematical models of oxygen delivery to the brain have been described in which disproportionately large increases in CBF are necessary to sustain even small increases in CMRO2 during activation. We have explored the coupling of CBF and oxygen delivery by using two complementary methods. First, a more complex mathematical model was tested that differs from those recently described in that no assumptions were made regarding tissue oxygen level. Second, [15O] water CBF positron emission tomography (PET) studies in nine healthy subjects were conducted during states of visual activation and hypoxia to examine the relationship of CBF and oxygen delivery. In contrast to previous reports, our model showed adequate tissue levels of oxygen could be maintained without the need for increased CBF or oxygen delivery. Similarly, the PET studies demonstrated that the regional increase in CBF during visual activation was not affected by hypoxia. These findings strongly indicate that the increase in CBF associated with physiological activation is regulated by factors other than local requirements in oxygen.

Temperature chaos in 3D Ising spin glasses is driven by rare events

Temperature chaos has often been reported in the literature as a rare-event–driven phenomenon. However, this fact has always been ignored in the data analysis, thus erasing the signal of the chaotic behavior (still rare in the sizes achieved) and leading to an overall picture of a weak and gradual phenomenon. On the contrary, our analysis relies on a largedeviations functional that allows to discuss the size dependences. In addition, we had at our disposal unprecedentedly large configurations equilibrated at low temperatures, thanks to the Janus computer. According to our results, when temperature chaos occurs its effects are strong and can be felt even at short distances.

Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.

Mathematical modeling of drying process of unripe banana slices

Unripe banana flour (UBF) production employs bananas not submitted to maturation process, is an interesting alternative to minimize the fruit loss reduction related to inappropriate handling or fast ripening. The UBF is considered as a functional ingredient improving glycemic and plasma insulin levels in blood, have also shown efficacy on the control of satiety, insulin resistance. The aim of this work was to study the drying process of unripe banana slabs (Musa cavendishii, Nanicão) developing a transient drying model through mathematical modeling with simultaneous moisture and heat transfer. The raw material characterization was performed and afterwards the drying process was conducted at 40 ºC, 50 ºC e 60 ºC, the product temperature was recorded using thermocouples, the air velocity inside the chamber was 4 m·s-1. With the experimental data was possible to validate the diffusion model based on the Fick\'s second law and Fourier. For this purpose, the sorption isotherms were measured and fitted to the GAB model estimating the equilibrium moisture content (Xe), 1.76 [g H2O/100g d.b.] at 60 ºC and 10 % of relative humidity (RH), the thermophysical properties (k, Cp, ?) were also measured to be used in the model. Five cases were contemplated: i) Constant thermophysical properties; ii) Variable properties; iii) Mass (hm), heat transfer (h) coefficient and effective diffusivity (De) estimation 134 W·m-2·K-1, 4.91x10-5 m-2·s-1 and 3.278?10-10 m·s-2 at 60 ºC, respectively; iv) Variable De, it presented a third order polynomial behavior as function of moisture content; v) The shrinkage had an effect on the mathematical model, especially in the 3 first hours of process, the thickness experienced a contraction of about (30.34 ± 1.29) % out of the initial thickness, finding two decreasing drying rate periods (DDR I and DDR II), 3.28x10-10 m·s-2 and 1.77x10-10 m·s-2, respectively. COMSOL Multiphysics simulations were possible to perform through the heat and mass transfer coefficient estimated by the mathematical modeling.

Towards a model-driven engineering approach of data mining

Nowadays, data mining is based on low-level specications of the employed techniques typically bounded to a specic analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Here, we propose a model-driven approach based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (via data-warehousing technology) and the analysis models for data mining (tailored to a specic platform). Thus, analysts can concentrate on the analysis problem via conceptual data-mining models instead of low-level programming tasks related to the underlying-platform technical details. These tasks are now entrusted to the model-transformations scaffolding.

Integrating the development of data mining and data warehouses via model-driven engineering

Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.

A model driven framework for geographic knowledge discovery

Geographic knowledge discovery (GKD) is the process of extracting information and knowledge from massive georeferenced databases. Usually the process is accomplished by two different systems, the Geographic Information Systems (GIS) and the data mining engines. However, the development of those systems is a complex task due to it does not follow a systematic, integrated and standard methodology. To overcome these pitfalls, in this paper, we propose a modeling framework that addresses the development of the different parts of a multilayer GKD process. The main advantages of our framework are that: (i) it reduces the design effort, (ii) it improves quality systems obtained, (iii) it is independent of platforms, (iv) it facilitates the use of data mining techniques on geo-referenced data, and finally, (v) it ameliorates the communication between different users.

A Hardware-Software Approach for On-Line Soft Error Mitigation in Interrupt-Driven Applications

Integrity assurance of configuration data has a significant impact on microcontroller-based systems reliability. This is especially true when running applications driven by events which behavior is tightly coupled to this kind of data. This work proposes a new hybrid technique that combines hardware and software resources for detecting and recovering soft-errors in system configuration data. Our approach is based on the utilization of a common built-in microcontroller resource (timer) that works jointly with a software-based technique, which is responsible to periodically refresh the configuration data. The experiments demonstrate that non-destructive single event effects can be effectively mitigated with reduced overheads. Results show an important increase in fault coverage for SEUs and SETs, about one order of magnitude.

Modeling and validation of the thermal behavior of buildings for the development of demand response methods

The representation of the thermal behaviour of the building is achieved through a relatively simple dynamic model that takes into account the effects due to the thermal mass of the building components. The model of a intra-floor apartment has been built in the Matlab-Simulink environment and considers the heat transmission through the external envelope, wall and windows, the internal thermal masses, (i.e. furniture, internal wall and floor slabs) and the sun gain due to opaque and see-through surfaces of the external envelope. The simulations results for the entire year have been compared and the model validated, with the one obtained with the dynamic building simulation software Energyplus.

Finite element modeling of motor vehicles. Protocol for developing INGRID data input desks for DYNA3D computer code. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research Development, McLean, Va.

Intercity travel data search. Final report.

Transportation Department, Office of Transportation Policy Development, Washington, D.C.

An analysis of mopeds as a potential safety problem in the United States. Volume II: data analysis and usage and accident projections. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Feasibility planning study for a behavior data base. Volume 1 - summary. Volume 2 - appendix A: summary information on the drinking and driving and occupant restraint surveys. Volume 3 - appendix B: compendium of survey questions on drinking and driving and occupant restraints. Final report.

National Highway Traffic Safety Administration, Washington, D.C.