Digitales stochastisches Magnetfeld-Sensorarray

Digitales stochastisches Magnetfeld-Sensorarray Stefan Rohrer Im Rahmen eines mehrjährigen Forschungsprojektes, gefördert von der Deutschen Forschungsgesellschaft (DFG), wurden am Institut für Mikroelektronik (IPM) der Universität Kassel digitale Magnetfeldsensoren mit einer Breite bis zu 1 µm entwickelt. Die vorliegende Dissertation stellt ein aus diesem Forschungsprojekt entstandenes Magnetfeld-Sensorarray vor, das speziell dazu entworfen wurde, um digitale Magnetfelder schnell und auf minimaler Fläche mit einer guten räumlichen und zeitlichen Auflösung zu detektieren. Der noch in einem 1,0µm-CMOS-Prozess gefertigte Test-Chip arbeitet bis zu einer Taktfrequenz von 27 MHz bei einem Sensorabstand von 6,75 µm. Damit ist er das derzeit kleinste und schnellste digitale Magnetfeld-Sensorarray in einem Standard-CMOS-Prozess. Konvertiert auf eine 0,09µm-Technologie können Frequenzen bis 1 GHz erreicht werden bei einem Sensorabstand von unter 1 µm. In der Dissertation werden die wichtigsten Ergebnisse des Projekts detailliert beschrieben. Basis des Sensors ist eine rückgekoppelte Inverter-Anordnung. Als magnetfeldsensitives Element dient ein auf dem Hall-Effekt basierender Doppel-Drain-MAGFET, der das Verhalten der Kippschaltung beeinflusst. Aus den digitalen Ausgangsdaten kann die Stärke und die Polarität des Magnetfelds bestimmt werden. Die Gesamtanordnung bildet einen stochastischen Magnetfeld-Sensor. In der Arbeit wird ein Modell für das Kippverhalten der rückgekoppelten Inverter präsentiert. Die Rauscheinflüsse des Sensors werden analysiert und in einem stochastischen Differentialgleichungssystem modelliert. Die Lösung der stochastischen Differentialgleichung zeigt die Entwicklung der Wahrscheinlichkeitsverteilung des Ausgangssignals über die Zeit und welche Einflussfaktoren die Fehlerwahrscheinlichkeit des Sensors beeinflussen. Sie gibt Hinweise darauf, welche Parameter für das Design und Layout eines stochastischen Sensors zu einem optimalen Ergebnis führen. Die auf den theoretischen Berechnungen basierenden Schaltungen und Layout-Komponenten eines digitalen stochastischen Sensors werden in der Arbeit vorgestellt. Aufgrund der technologisch bedingten Prozesstoleranzen ist für jeden Detektor eine eigene kompensierende Kalibrierung erforderlich. Unterschiedliche Realisierungen dafür werden präsentiert und bewertet. Zur genaueren Modellierung wird ein SPICE-Modell aufgestellt und damit für das Kippverhalten des Sensors eine stochastische Differentialgleichung mit SPICE-bestimmten Koeffizienten hergeleitet. Gegenüber den Standard-Magnetfeldsensoren bietet die stochastische digitale Auswertung den Vorteil einer flexiblen Messung. Man kann wählen zwischen schnellen Messungen bei reduzierter Genauigkeit und einer hohen lokalen Auflösung oder einer hohen Genauigkeit bei der Auswertung langsam veränderlicher Magnetfelder im Bereich von unter 1 mT. Die Arbeit präsentiert die Messergebnisse des Testchips. Die gemessene Empfindlichkeit und die Fehlerwahrscheinlichkeit sowie die optimalen Arbeitspunkte und die Kennliniencharakteristik werden dargestellt. Die relative Empfindlichkeit der MAGFETs beträgt 0,0075/T. Die damit erzielbaren Fehlerwahrscheinlichkeiten werden in der Arbeit aufgelistet. Verglichen mit dem theoretischen Modell zeigt das gemessene Kippverhalten der stochastischen Sensoren eine gute Übereinstimmung. Verschiedene Messungen von analogen und digitalen Magnetfeldern bestätigen die Anwendbarkeit des Sensors für schnelle Magnetfeldmessungen bis 27 MHz auch bei kleinen Magnetfeldern unter 1 mT. Die Messungen der Sensorcharakteristik in Abhängigkeit von der Temperatur zeigen, dass die Empfindlichkeit bei sehr tiefen Temperaturen deutlich steigt aufgrund der Abnahme des Rauschens. Eine Zusammenfassung und ein ausführliches Literaturverzeichnis geben einen Überblick über den Stand der Technik.

Certified Rapid Solution of Parametrized Linear Elliptic Equations: Application to Parameter Estimation

We present a technique for the rapid and reliable evaluation of linear-functional output of elliptic partial differential equations with affine parameter dependence. The essential components are (i) rapidly uniformly convergent reduced-basis approximations — Galerkin projection onto a space WN spanned by solutions of the governing partial differential equation at N (optimally) selected points in parameter space; (ii) a posteriori error estimation — relaxations of the residual equation that provide inexpensive yet sharp and rigorous bounds for the error in the outputs; and (iii) offline/online computational procedures — stratagems that exploit affine parameter dependence to de-couple the generation and projection stages of the approximation process. The operation count for the online stage — in which, given a new parameter value, we calculate the output and associated error bound — depends only on N (typically small) and the parametric complexity of the problem. The method is thus ideally suited to the many-query and real-time contexts. In this paper, based on the technique we develop a robust inverse computational method for very fast solution of inverse problems characterized by parametrized partial differential equations. The essential ideas are in three-fold: first, we apply the technique to the forward problem for the rapid certified evaluation of PDE input-output relations and associated rigorous error bounds; second, we incorporate the reduced-basis approximation and error bounds into the inverse problem formulation; and third, rather than regularize the goodness-of-fit objective, we may instead identify all (or almost all, in the probabilistic sense) system configurations consistent with the available experimental data — well-posedness is reflected in a bounded "possibility region" that furthermore shrinks as the experimental error is decreased.

Benchmarking de implementaciones WMS-C de software libre

La propuesta WMS Cached (WMS-C) surge ante la necesidad de disponer de una solución más escalable al actual servicio web de mapas (WMS). Mediante la limitación de los parámetros de las peticiones a un conjunto discreto de valores, el servidor de mapas puede servir imágenes pregeneradas (teselas) a gran velocidad. En este documento se recogen las medidas de rendimiento realizadas sobre las implementaciones WMS-C: Tilecache, GeoWebcache y WMSCWrapper, todas ellas basadas en software libre. Los resultados de los benchmarks reflejan que, con todas las peticiones cacheadas y bajo las mismas condiciones, la caché WMSCWrapper ofrece un mejor rendimiento que las otras implementaciones. La difusión de estos resultados será de utilidad para ayudar a diversas entidades en la elección de una de estas soluciones libres en función de su objetivo de optimización

Distinct Unfolding and Refolding Pathways of Ribonuclease A Revealed by Heating and Cooling Temperature Jumps

Heating and cooling temperature jumps (T-jumps) were performed using a newly developed technique to trigger unfolding and refolding of wild-type ribonuclease A and a tryptophan-containing variant (Y115W). From the linear Arrhenius plots of the microscopic folding and unfolding rate constants, activation enthalpy (ΔH#), and activation entropy (ΔS#) were determined to characterize the kinetic transition states (TS) for the unfolding and refolding reactions. The single TS of the wild-type protein was split into three for the Y115W variant. Two of these transition states, TS1 and TS2, characterize a slow kinetic phase, and one, TS3, a fast phase. Heating T-jumps induced protein unfolding via TS2 and TS3; cooling T-jumps induced refolding via TS1 and TS3. The observed speed of the fast phase increased at lower temperature, due to a strongly negative ΔH# of the folding-rate constant. The results are consistent with a path-dependent protein folding/unfolding mechanism. TS1 and TS2 are likely to reflect X-Pro114 isomerization in the folded and unfolded protein, respectively, and TS3 the local conformational change of the β-hairpin comprising Trp115. A very fast protein folding/unfolding phase appears to precede both processes. The path dependence of the observed kinetics is suggestive of a rugged energy protein folding funne

A Newton method for pose refinement of 3D models

Different optimization methods can be employed to optimize a numerical estimate for the match between an instantiated object model and an image. In order to take advantage of gradient-based optimization methods, perspective inversion must be used in this context. We show that convergence can be very fast by extrapolating to maximum goodness-of-fit with Newton's method. This approach is related to methods which either maximize a similar goodness-of-fit measure without use of gradient information, or else minimize distances between projected model lines and image features. Newton's method combines the accuracy of the former approach with the speed of convergence of the latter.

Equatorial waves in the lower stratosphere. II: Annual and interannual variability

The annual and interannual variability of idealized, linear, equatorial waves in the lower stratosphere is investigated using the temperature and velocity fields from the ECMWF 15-year re-analysis dataset. Peak Kelvin wave activity occurs during solstice seasons at 100 hPa, during December-February at 70 hPa and in the easterly to westerly quasi-biennial oscillation (QBO) phase transition at 50 hPa. Peak Rossby-gravity wave activity occurs during equinox seasons at 100 hPa, during June-August/September-November at 70 hPa and in the westerly to easterly QBO phase transition at 50 hPa. Although neglect of wind shear means that the results for inertio-gravity waves are likely to be less accurate, they are still qualitatively reasonable and an annual cycle is observed in these waves at 100 hPa and 70 hPa. Inertio-gravity waves with n = 1 are correlated with the QBO at 50 hPa, but the eastward inertio-gravity n = 0 wave is not, due to its very fast vertical group velocity in all background winds. The relative importance of different wave types in driving the QBO at 50 hPa is also discussed. The strongest acceleration appears to be provided by the Kelvin wave while the acceleration provided by the Rossby-gravity wave is negligible. Of the higher-frequency waves, the westward inertio-gravity n = 1 wave appears able to contribute more to the acceleration of the 50 hPa mean zonal wind than the eastward inertio-gravity n = 1 wave.

Molecular methods for the analysis of gut microbiota

This review focuses on methodological approaches used to study the composition of human faecal microbiota. Gene sequencing is the most accurate tool for revealing the phylogenetic relationships between bacteria. The main application of fluorescence in situ hybridization (FISH) in both microscopy and flow cytometry is to enumerate faecal bacteria. While flow cytometry is a very fast method, FISH microscopy still has a considerably lower detection limit.

Speed sensorless vector control of induction machines

A novel rotor velocity estimation scheme applicable to vector controlled induction motors has been described. The proposed method will evaluate rotor velocity, ωr, on-line, does not require any extra transducers or injection of any signals, nor does it employ complicated algorithms such as MRAS or Kalman filters. Furthermore, the new scheme will operate at all velocities including zero with very little error. The procedure employs motor model equations, however all differential and integral terms have been eliminated giving a very fast, low-cost, effective and practical alternative to the current available methods. Simulation results verify the operation of the scheme under ideal and PWM conditions.

Heterosite effects in novel heteronuclear clusters [OS2Ru(CO)(11)(PPh3)] and Os2Ru(CO)(10)(2-acetylpyridine-N-isopropylimine)]

A new synthetic route towards the mixed-metal cluster [OS2Ru(CO)(12)] is described together with the syntheses of its PPh3 and iPr-AcPy (iPr-AcPy = 2-acetylpyridine-N-isopropylimine) derivatives. The molecular structures of the novel clusters [Os2Ru(CO)(11)(PPh3)] and [Os2Ru(CO)(10)(iPr-AcPy)] were determined on the basis of crystalline solid solutions of the Os2Ru and corresponding Os-3 species. The structures reveal that coordination of the Lewis bases occurs exclusively at the ruthenium site of [Os2Ru(CO)(12)], which is in agreement with density functional theory (DFT) calculations on several structural isomers of these compounds. According to the time-dependent DFT results, the lowest optically accessible excited state of [Os2Ru(CO)(10)(iPr-AcPy)] has a prevailing sigma(Ru-Os-2)pi*(iPr-AcPy) character, with a partial sigma sigma*(Ru-Os-2) contribution. In weakly coordinating 2-chlorobutane, the excited state has a lifetime tau = 10.4 +/- 1.2 ps and produces biradicals considerably faster than observed for [Os-3(CO)10(iPr-AcPy) (tau = 25.3 +/- 0.7ps)]. In coordinating acetonitrile, the excited state of [Os2Ru(CO)(10)(iPr-AcPy)] decays mono-exponentially with a lifetime tau = 2.1 +/- 0.2 ps. In contrast to [Os-3(CO)(10)(iPr-AcPy)] that forms biradicals as the main primary photoproduct even in strongly coordinating solvents, zwitterion formation from the solvated lowest excited state is observed for the heterometallic cluster. This is concluded from time-resolved absorption studies in the microsecond time domain. Due to the lower tendency of the coordinatively unsaturated Ru+(CO)(2)(iPr-AcPy-/0) moiety to bind a Lewis base, the heteronuclear biradical and zwitterionic photoproducts live significantly shorter than their triosmium counterparts. The influence of the weaker Os-2-Ru(iPr-AcPy) bond on the redox reactivity is clearly reflected in very reactive radical anions formed upon electrochemical reduction of [Os2Ru(CO)(10)(iPr-AcPy)]. The dimer [-OS(CO)(4)-Os(CO)(4)-Ru(CO)(2)(iPr-AcPy)](2)(2-) is the only IR-detectable intermediate reduction product. The dinuclear complex [Os-2(CO)(8)](2-) and insoluble [Ru(CO)(2)(iPr-AcPy)](n), are the ultimate reduction products, proving fragmentation of the OS2Ru core.

Optimal piecewise locally linear modeling

Associative memory networks such as Radial Basis Functions, Neurofuzzy and Fuzzy Logic used for modelling nonlinear processes suffer from the curse of dimensionality (COD), in that as the input dimension increases the parameterization, computation cost, training data requirements, etc. increase exponentially. Here a new algorithm is introduced for the construction of a Delaunay input space partitioned optimal piecewise locally linear models to overcome the COD as well as generate locally linear models directly amenable to linear control and estimation algorithms. The training of the model is configured as a new mixture of experts network with a new fast decision rule derived using convex set theory. A very fast simulated reannealing (VFSR) algorithm is utilized to search a global optimal solution of the Delaunay input space partition. A benchmark non-linear time series is used to demonstrate the new approach.

On the entrainment assumption in Schatzmann's integral plume model

The behaviour of stationary, non-passive plumes can be simulated in a reasonably simple and accurate way by integral models. One of the key requirements of these models, but also one of their less well-founded aspects, is the entrainment assumption, which parameterizes turbulent mixing between the plume and the environment. The entrainment assumption developed by Schatzmann and adjusted to a set of experimental results requires four constants and an ad hoc hypothesis to eliminate undesirable terms. With this assumption, Schatzmann’s model exhibits numerical instability for certain cases of plumes with small velocity excesses, due to very fast radius growth. The purpose of this paper is to present an alternative entrainment assumption based on a first-order turbulence closure, which only requires two adjustable constants and seems to solve this problem. The asymptotic behaviour of the new formulation is studied and compared to previous ones. The validation tests presented by Schatzmann are repeated and it is found that the new formulation not only eliminates numerical instability but also predicts more plausible growth rates for jets in co-flowing streams.

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

A radial basis function network classifier to maximise leave-one-out mutual information

tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.

Nuclear Factor-kappaB controls the reaggregation of 3D neurosphere cultures in vitro

The approach of reaggregation involves the regeneration and self-renewal of histotypical 3D spheres from isolated tissue kept in suspension culture. Reaggregated spheres can be used as tumour, genetic, biohybrid and neurosphere models. In addition the functional superiority of 3D aggregates over conventional 2D cultures developed the use of neurospheres for brain engineering of CNS diseases. Thus 3D aggregate cultures created enormous interest in mechanisms that regulate the formation of multicellular aggregates in vitro. Here we analyzed mechanisms guiding the development of 3D neurosphere cultures. Adult neural stem cells can be cultured as self-adherent clusters, called neurospheres. Neurospheres are characterised as heterogeneous clusters containing unequal stem cell sub-types. Tumour necrosis factor-alpha (TNF-alpha is one of the crucial inflammatory cytokines with multiple actions on several cell types. TNF-alpha strongly activates the canonical Nuclear Factor Kappa-B (NF- kappaB) pathway. In order to investigate further functions of TNF in neural stem cells (NSCs) we tested the hypothesis that TNF is able to modulate the motility and/or migratory behaviour of SVZ derived adult neural stem cells. We observed a significantly faster sphere formation in TNF treated cultures than in untreated controls. The very fast aggregation of isolated NSCs (<2h) is a commonly observed phenomenon, though the mechanisms of 3D neurosphere formation remain largely unclear. Here we demonstrate for the first time, increased aggregation and enhanced motility of isolated NSCs in response to the TNF-stimulus. Moreover, this phenomenon is largely dependent on activated transcription factor NF-kappaB. Both, the pharmacological blockade of NF-kappaB pathway by pyrrolidine dithiocarbamate (PDTC) or Bay11-7082 and genetic blockade by expression of a transdominant-negative super-repressor IkappaB-AA1 led to decreased aggregation.

Strong quenching of chlorophyll fluorescence in the desiccated state in three poikilohydric and homoiochlorophyllous moss species indicates photo-oxidative protection on highly light-exposed rocks of a tropical inselberg

The three poikilophydric and homoiochlorophyllous moss species Campylopus savannarum (C. Muell.) Mitt., Racocarpus fontinaloides (C. Muell.) Par. and Ptychomitrium vaginatum Besch. grow on sun-exposed rocks of a tropical inselberg in Brazil subject to regular drying and wetting cycles. Effective photo-oxidative protection in the light-adapted desiccated state in all three species is achieved by a reduction of ground chlorophyll fluorescence, F, to almost zero. Upon rewatering, the kinetics of the recovery of F in air dry cushions to higher values is very fast in the first 5min, but more than 80min are needed until an equilibrium is reached gradually. The kinetics were not different between the three species. The three moss species, have a distinct niche occupation and form a characteristic zonation around soil vegetation islands on the rock outcrops, where C. savannarum and R. fontinaloides form an inner and outer belt, respectively, around vegetation islands and P vaginatum occurs as small isolated cushions on bare rock. However, they were not distinguished by the reduction of F in the dry state and the rewetting recovery kinetics and only slightly different in their photosynthetic capacity. Stable isotope ratios (delta C-13, delta N-15) indicate that liquid films of water limiting diffusion of CO2 are important in determining carbon acquisition and suggest that limitation of CO2 fixation by water films must be more pronounced over time in P vaginatum than in the latter species. This is determined by both the micro site occupied and the form of the moss cushions. (c) 2007 Elsevier GmbH. All rights reserved.