A new method to extract gate coupling ratio and oxide trapped charge in flash memory cell

A new method to obtain the gate coupling ratio (α_g) and oxide trapped charge (Q_ox) as a result of cycling in flash memory cells is described here. Three cells with an equivalent physical structure but different erase characteristics are measured. The threshold changes versus erase times are fitted to the charge removal rate calculated based on Fowler-Nordheim (FN) tunneling and the capacitive relations among all nodes. The extracted α_g is independent of technologies and this method is particular useful when the profile of the floating gate is not traditionally rectangular owing to advanced processes such as trapezoidal poly etch or a poly-spacer addition on the floating gate sidewall. The Q_ox can also be determined once α_g is extracted.     

Validated design of dynamic membership services and protocols for cooperative groups

This paper first presents a groupware service and an associated protocol that manage the dynamic membership of agents inside cooperative groups and second gives the design methodology that has been used for defining the service and the protocol. The model used to represent cooperative groups is based on graphs that give the knowledge relationships between agents and define the dynamics of the group. The protocol providing the membership service is specified using the VAL formal specification environment based on a Petri net formalism. The VAL specification is verified using observational and safety projections derived from the reachability graph. Then the VAL specification is translated and adapted to an Estelle specification. The Estelle specification has been used for a final implementation of the protocol on top of a distributed platform.     

Optimal control law for classical and multiconjugate adaptive optics

Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems.     

Sliding mode closed-loop control of FES: controlling the shank movement

Functional electrical stimulation (FES) enables restoration of movement in individuals with spinal cord injury. FES-based devices use electric current pulses to stimulate and excite the intact peripheral nerves. They produce muscle contractions, generate joint torques, and thus, joint movements. Since the underlying neuromuscular-skeletal system is highly nonlinear and time-varying, feedback control is necessary for accurate control of the generated movement. However, classical feedback/closed-loop control algorithms have so far failed to provide satisfactory performance and were not able to guarantee stability of the closed-loop system. Because of this, only open-loop controlled FES devices are in clinical use in spite of their limitations. The purpose of the reported research was to design a novel closed-loop FES controller that achieves good tracking performance and guarantees closed-loop stability. Such a controller was designed based on a mathematical neuromuscular-skeletal model and is founded on a sliding mode control theory. The controller was used to control shank movement and was tested in computer simulations as well as in actual experiments on healthy and spinal cord injured subjects. It demonstrated good robustness, stability, and tracking performance properties.     

Analysis of direct solar ultraviolet irradiance measurements in the French Alps. Retrieval of turbidity and ozone column amount

Direct ultraviolet spectral solar irradiance is regularly obtained by the difference between global and diffuse irradiances at the French Alpine station of Brian?on; the data of years 2001 and 2002 are analyzed in this paper. Comparison with modeled values is used for cloud screening, and an average UV-A aerosol optical depth is used as an index of turbidity; it is found to be around 0.05 for the clear winter days and around 0.2 in summer. Langley plots are used to verify the instrument calibration; they confirm the expected uncertainty smaller than 5%. The ozone total column amount is estimated with an uncertainty between -3 and Dobson units; comparisons with TOMS (Total Ozone Mapping Spectrometer) overpass values shows agreement within the expected uncertainties of both instruments.     

Putative dynamics of vasopressin in its V1a receptor binding site

The molecular architecture of the GPCRs, including the dynamic set of interactions between the receptor and the ligand, is one of the key structural questions of biophysical approaches. In the present study, molecular dynamics (MD) simulations were performed on the well-validated molecular model of the vasopressin V1a receptor applying different parameters (i.e., force fields, time variation, use of constraints) in order to sample the conformational space of the endogenous ligand arginine vasopressin (AVP), to explore different putative binding modes, and to analyze the simulation results with respect to experimental data. Noteworthy, it is to mention that for the first time a model of the vasopressin receptor remained stable in a 500 ps MD simulation run under vacuo boundary conditions using the Kollman all-atom FF even though no constraints were imposed. Conclusively, we determined an optimized experimental procedure for studying the dynamics and structure-functionship of this highly important family of GPCRs: the use of MD simulations with the Kollman all-atom force-field parameters on a constrained receptor. Our simplified model may be used as a basis for structure based design of new GPCR ligands and for in silico screening of virtual combinatorial chemistry libraries.     

Effects of 1,4-Benzoxazin-3-One Derivatives from Maize on Survival and Fecundity of Metopolophium dirhodum (Walker) on Artificial Diet

Effects of 2--D-glucopyranosyloxy-4-hydroxy-7-methoxy-1,4benzoxazin-3-one (DIMBOA-Glc) and DIMBOA-Glc N-O-methylated (HDMBOA-Glc), two compounds present in high concentration in maize, were tested on the aphid Metopolophium dirhodum reared on artificial diet. HDMBOA-Glc and DIMBOA-Glc decrease survival of adults with an LD₅₀ of 1 mM and 5.6 mM, respectively, after 72 hr of feeding. These compounds also decrease the fecundity of the aphids at concentrations of 2 mM and 1 mM, respectively. At concentrations of 2 mM HDMBOA-Glc and 8 mM DIMBOA-Glc in the diet, the average lifetime fecundity of 10 females is near zero. Offspring mortality on diet with 2 mM DIMBOA-Glc is significantly higher than with the control diet. In contrast, HDMBOA-Glc has no effect on the survival of offspring. The possibility that these compounds protect Poaceae against aphids is discussed.     

Embedded holonic fault diagnosis of complex transportation systems

The use of electronic equipment and embedded computing technologies in modern complex transportation systems continues to grow in a highly competitive market, in which product maintainability and availability is vital. These technological advances also make fault diagnosis and maintenance interventions much more challenging, since these operations require a deep understanding of the entire system. This paper proposes a holonic cooperative fault diagnosis approach, along with a generic architecture, to increase the embedded diagnosis capabilities of complex transportation systems. This concept is applied to the fault diagnosis of door systems of a railway transportation system.     

Time series classification for the prediction of dialysis in critically ill patients using echo statenetworks

Objective: Time series often appear in medical databases, but only few machine learning methods exist that process this kind of data properly. Most modeling techniques have been designed with a static data model in mind and are not suitable for coping with the dynamic nature of time series. Recurrent neural networks (RNNs) are often used to process time series, but only a few training algorithms exist for RNNs which are complex and often yield poor results. Therefore, researchers often turn to traditional machine learning approaches, such as support vector machines (SVMs), which can easily be set up and trained and combine them with feature extraction (FE) and selection (FS) to process the high-dimensional temporal data. Recently, a new approach, called echo state networks (ESNs), has been developed to simplify the training process of RNNs. This approach allows modeling the dynamics of a system based on time series data in a straightforwardway.The objective of this study is to explore the advantages of using ESN instead of other traditional classifiers combined with FE and FS in classification problems in the intensive care unit (ICU) when the input data consists of time series. While ESNs have mostly been used to predict the future course of a time series, we use the ESN model for classification instead. Although time series often appear in medical data, little medical applications of ESNs have been studiedyet.Methods and material: ESN is used to predict the need for dialysis between the fifth and tenth day after admission in the ICU. The input time series consist of measured diuresis and creatinine values during the first 3days after admission. Data about 830 patients was used for the study, of which 82 needed dialysis between the fifth and tenth day after admission. ESN is compared to traditional classifiers, a sophisticated and a simple one, namely support vector machines and the naive Bayes (NB) classifier. Prior to the use of the SVM and NB classifier, FE and FS is required to reduce the number of input features and thus alleviate the curse dimensionality. Extensive feature extraction was applied to capture both the overall properties of the time series and the correlation between the different measurements in the time series. The feature selection method consists of a greedy hybrid filter-wrapper method using a NB classifier, which selects in each iteration the feature that improves prediction the best and shows little multicollinearity with the already selected set. Least squares regression with noise was used to train the linear readout function of the ESN to mitigate sensitivity to noise and overfitting. Fisher labeling was used to deal with the unbalanced data set. Parameter sweeps were performed to determine the optimal parameter values for the different classifiers. The area under the curve (AUC) and maximum balanced accuracy are used as performance measures. The required execution time was also measured.Results: The classification performance of the ESN shows significant difference at the 5% level compared to the performance of the SVM or the NB classifier combined with FE and FS. The NB+FE+FS, with an average AUC of 0.874, has the best classification performance. This classifier is followed by the ESN, which has an average AUC of 0.849. The SVM+FE+FS has the worst performance with an average AUC of 0.838. The computation time needed to pre-process the data and to train and test the classifier is significantly less for the ESN compared to the SVM andNB.Conclusion: It can be concluded that the use of ESN has an added value in predicting the need for dialysis through the analysis of time series data. The ESN requires significantly less processing time, needs no domain knowledge, is easy to implement, and can be configured using rules ofthumb.