Modelling the air-gap field strength of electric machines to improve performance of haptic mechanisms

The air-gap of electro-magnetic (EM) actuators determines key operating parameters such as their ability to generate force. In haptic devices these parameters are not optimised for the conditions typically seen in operation and include the heat produced in the air-gap, the volume of the air-gap, and the intensity and direction of the magnetic field. The relationship between these parameters is complex thus design decisions are difficult to make. This paper considers the role of the radial magnetic field in cylindrical electric motors, a type often used in haptic devices. Two models are derived and compared with experimental measurements. The first model is a closed form solution, the second is a classic Poisson solution to Ampere's equation. These models are shown to be valid for making more general design decisions in relation to haptic actuators, and in particular allow an evaluation of the trade off between the volume of the air-gap, the resulting radial magnetic field and hence heat generated and the resulting forces

Structural Insights of Non-canonical U*U Pair and Hoogsteen Interaction Probed with Se Atom

Unlike DNA, in addition to the 20 -OH group, uracil nucleobase and its modifications play essential roles in structure and function diversities of non- coding RNAs. Non-canonical U.U base pair is ubiquitous in non-coding RNAs, which are highly diversified. However, it is not completely clear how uracil plays the diversifing roles. To investigate and compare the uracil in U-A and U.U base pairs, we have decided to probe them with a selenium atom by synthesizing the novel 4-Se-uridine (SeU) phosphoramidite and Se-nucleobase-modified RNAs (SeU-RNAs), where the exo-4-oxygen of uracil is replaced by selenium. Our crystal structure studies of U-A and U.U pairs reveal that the native and Se-derivatized structures are virtually identical, and both U-A and U.U pairs can accommodate large Se atoms. Our thermostability and crystal structure studies indicate that the weakened H-bonding in U-A pair may be compensated by the base stacking, and that the stacking of the trans- Hoogsteen U.U pairs may stabilize RNA duplex and its junction. Our result confirms that the hydrogen bond (O4.. .H-C5) of the Hoogsteen pair is weak. Using the Se atom probe, our Se- functionalization studies reveal more insights into the U.U interaction and U-participation in structure and function diversification of nucleic acids

Passive ocean acoustic tomography: theory and experiment

In this paper the Passive Ocean Acoustic Tomography (P-OAT) methodology is presented. This technique, avoiding the use of a dedicated active sound source, estimates the sea water temperature spatial distribution from the received noise emitted from ships of opportunity. The feasibility of the proposed methodology has been confirmed both by test-runs on semi-synthetic data and by the use of real acoustic and environmental data collected during INTIMATE00 experiment performed on October 2000 in the Atlantic Ocean off the Portuguese coasts

Pre-operational short-term forecasts for Mediterranean Sea biogeochemistry

Operational prediction of the marine environment is recognised as a fundamental research issue in Europe. We present a pre-operational implementation of a biogeochem- ical model for the pelagic waters of the Mediterranean Sea, developed within the framework of the MERSEA-IP Euro- pean project. The OPATM-BFM coupled model is the core of a fully automatic system that delivers weekly analyses and forecast maps for the Mediterranean Sea biogeochem- istry. The system has been working in its current configura- tion since April 2007 with successful execution of the fully automatic operational chain in 87% of the cases while in the remaining cases the runs were successfully accomplished af- ter operator intervention. A description of the system devel- oped and also a comparison of the model results with satel- lite data are presented, together with a measure of the model skill evaluated by means of seasonal target diagrams. Future studies will address the implementation of a data assimila- tion scheme for the biogeochemical compartment in order to increase the skill of the model’s performance

Preliminary deployment of Grid-assisted oceanographic applications

Abstract. Grid integration of OGS oceanographic remote instruments and coupled physical-biogeochemical model has been explored in the framework of the EC-FP7 DORII project. We discuss here the first preliminary results achieved, describing the different tools developed with the support of the project consortium. A general background of the Grid technology for the e-Science is also provided.</p

Grouped graphical Granger modeling for gene expression regulatory networks discovery

We consider the problem of discovering gene regulatory networks from time-series microarray data. Recently, graphical Granger modeling has gained considerable attention as a promising direction for addressing this problem. These methods apply graphical modeling methods on time-series data and invoke the notion of ‘Granger causality’ to make assertions on causality through inference on time-lagged effects. Existing algorithms, however, have neglected an important aspect of the problem—the group structure among the lagged temporal variables naturally imposed by the time series they belong to. Specifically, existing methods in computational biology share this shortcoming, as well as additional computational limitations, prohibiting their effective applications to the large datasets including a large number of genes and many data points. In the present article, we propose a novel methodology which we term ‘grouped graphical Granger modeling method’, which overcomes the limitations mentioned above by applying a regression method suited for high-dimensional and large data, and by leveraging the group structure among the lagged temporal variables according to the time series they belong to. We demonstrate the effectiveness of the proposed methodology on both simulated and actual gene expression data, specifically the human cancer cell (HeLa S3) cycle data. The simulation results show that the proposed methodology generally exhibits higher accuracy in recovering the underlying causal structure. Those on the gene expression data demonstrate that it leads to improved accuracy with respect to prediction of known links, and also uncovers additional causal relationships uncaptured by earlier works

Modeling Carbon Budgets and Acidification in the Mediterranean Sea Ecosystem Under Contemporary and Future Climate

We simulate and analyze the effects of a high CO2 emission scenario on the Mediterranean Sea biogeochemical state at the end of the XXI century, with a focus on carbon cycling, budgets and fluxes, within and between the Mediterranean subbasins, and on ocean acidification. As a result of the overall warming of surface water and exchanges at the boundaries, the model results project an increment in both the plankton primary production and the system total respiration. However, productivity increases less than respiration, so these changes yield to a decreament in the concentrations of total living carbon, chlorophyll, particulate organic carbon and oxygen in the epipelagic layer, and to an increment in the DIC pool all over the basin. In terms of mass budgets, the large increment in the dissolution of atmospheric CO2 results in an increment of most carbon fluxes, including the horizontal exchanges between eastern and western sub-basins, in a reduction of the organic carbon component, and in an increament of the inorganic one. The eastern sub-basin accumulates more than 85% of the absorbed atmospheric CO2. A clear ocean acidification signal is observed all over the basin, quantitatively similar to those projected in most oceans, and well detectable also down to the mesopelagic and bathypelagic layers

Model Order Reduction for Rotating Electrical Machines

The simulation of electric rotating machines is both computationally expensive and memory intensive. To overcome these costs, model order reduction techniques can be applied. The focus of this contribution is especially on machines that contain non-symmetric components. These are usually introduced during the mass production process and are modeled by small perturbations in the geometry (e.g., eccentricity) or the material parameters. While model order reduction for symmetric machines is clear and does not need special treatment, the non-symmetric setting adds additional challenges. An adaptive strategy based on proper orthogonal decomposition is developed to overcome these difficulties. Equipped with an a posteriori error estimator the obtained solution is certified. Numerical examples are presented to demonstrate the effectiveness of the proposed method

Effects of stator and rotor core ovality on induction machine behavior

Asymmetries in the air gap of induction motors produce additional harmonics in the flux density and force waves. A complete transient finite element model analyzes the harmonics produced from two possible asymmetries, a stator core ovality and a rotor ovality. The analysis of the air gap flux density and magnetic force waves determined by the finite element model shows unique harmonic frequencies due to the ovality of the air gap